journal of blood group serology and molecular genetics...2–5 percent rbc suspension and monoclonal...

Journal of Blood Group Serology and Molecular Genetics

Vo lu m e 32, Nu m b e r 4, 2016

135 Ori g i n al rep O rt

Distribution of blood groups in the Iranian general populationE. Shahverdi, M. Moghaddam, A. Talebian, and H. Abolghasemi

140 Case rep O rt

Acute hemolytic transfusion reaction attributed to anti-Ata

J.S. Raval, S.K. Harm, B. Wagner, D.J. Triulzi, and M.H. Yazer


A detailed flow cytometric method for detection of low-level in vivo red blood cell–bound IgG, IgA, and IgMW. Beres, G.M. Meny, and S. Nance


Trends of ABO and Rh phenotypes in transfusion-dependent patients in PakistanN. Anwar, M. Borhany, S. Ansari, S. Khurram, U. Zaidi, I. Naseer, M. Nadeem, and T. Shamsi


Human platelet antigen allelic diversity in Peninsular MalaysiaW.U.W. Syafawati, Z. Zefarina, Z. Zafarina, M.N. Hassan, M.N. Norazmi, S. Panneerchelvam, G.K. Chambers, and H.A. Edinur

ImmunohematologyJournal of Blood Group Serology and Molecular Genetics

Volume 32, Number 4, 2016

CONTENTS

174an n Ou n Cem en ts

177adv ert isem en ts

181inst ruCt i O ns fO r au t h O rs

183su bsCri p t i O n in fO rm at i O n

Immunohematology is published quarterly (March, June, September, and December) by the American Red Cross, National Headquarters, Washington, DC 20006.

Immunohematology is indexed and included in Index Medicus and MEDLINE on the MEDLARS system. The contents are also cited in the EBASE/Excerpta Medica and Elsevier

BIOBASE/Current Awareness in Biological Sciences (CABS) databases.

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Web site: www.redcross.org/about-us/publications/immunohematology

Copyright 2016 by The American National Red Cross ISSN 0894-203X

ed i tO r- i n-Ch i ef

Sandra Nance, MS, MT(ASCP)SBBPhiladelphia, Pennsylvania

ma n ag i n g ed i tO r

Cynthia Flickinger, MT(ASCP)SBBWilmington, Delaware

teC h n i Ca l ed i tO rs

Christine Lomas-Francis, MScNew York City, New York

Joyce Poole, FIBMSBristol, United Kingdom

Dawn M. Rumsey, ART(CSMLT)Norcross, Georgia

sen i O r med i Ca l ed i tO r

David Moolten, MDPhiladelphia, Pennsylvania

as s O C i at e med i Ca l ed i tO rs

P. Dayand Borge, MDPhiladelphia, Pennsylvania

Corinne L. Goldberg, MDDurham, North Carolina

mO leC u l a r ed i tO r

Margaret A. Keller, PhDPhiladelphia, Pennsylvania

ed i tO r i a l as s ista n t

Linda Frazier

prO d u Ct i O n as s ista n t

Marge Manigly

CO p y ed i tO r

Frederique Courard-Houri

prO O f r e a d er

Wendy Martin-Shuma

eleCt rO n i C pu b l is h er

Paul Duquette

ed i tO r i a l bOa r d

Patricia Arndt, MT(ASCP)SBBPomona, California

Barbara J. Bryant, MDGalveston, Texas

Lilian M. Castilho, PhDCampinas, Brazil

Martha R. Combs, MT(ASCP)SBBDurham, North Carolina

Geoffrey Daniels, PhDBristol, United Kingdom

Anne F. Eder, MDBethesda, Maryland

Melissa R. George, DO, FCAPHershey, Pennsylvania

Christine Lomas-Francis, MScNew York City, New York

Geralyn M. Meny, MDSan Antonio, Texas

Paul M. Ness, MDBaltimore, Maryland

Thierry Peyrard, PharmD, PhDParis, France

S. Gerald Sandler, MDWashington, District of Columbia

Jill R. Storry, PhD Lund, Sweden

Nicole ThorntonBristol, United Kingdom

em er i t us ed i tO rs

Delores Mallory, MT(ASCP)SBBSupply, North Carolina

Marion E. Reid, PhD, FIBMSBristol, United Kingdom

On Ou r COv er

Edward Hopper, in a realist vision, saw an America still young and booming but already hardened by experience. Nighthawks (1942), one of his best-known works, reveals his simple obsession with geometry and light in its clean lines and angles and in the harsh contrast between the fluorescent lighting of the diner and the city darkness outside it. It is within this manifold darkness of dim shapes and slashing shadows that both the viewer and the painter stand. The four people pictured in the restaurant pay little attention to each other despite their proximity, evoking a mood of gritty isolation in a country already lonely, wary, and vigilant. Flow cytometry, with its methodological use of fluorescence, is the subject of an article in this issue by Beres et al.

David Moolten, MD

IMMUNOHEMATOLOGY, Volume 32, Number 4, 2016 135

Distribution of blood groups in the Iranian general populationE. Shahverdi, M. Moghaddam, A. Talebian, and H. Abolghasemi

Original repOrt

We report the first study of antigen and phenotype prevalence within various blood group systems in the Iranian general population. In this retrospective study, samples from 3475 individuals referred to the Immunohematology Reference Laboratory of the Iranian Blood Transfusion Organization, Tehran, Iran, for paternity testing from 1998 to 2008 were additionally tested for red blood cell (RBC) antigens in the Rh, Kell, Kidd, Duffy, MNS, Lutheran, P1PK, and Xg blood group systems. The antigen testing was performed by the tube method, and the phenotype prevalences were expressed as percentages. Of 3475 (1857 male and 1618 female) blood samples, 1268 samples were typed as group O (36.49%), 1115 as group A (32.09%), 823 as group B (23.68%), and 269 as group AB (7.74%). In our sample population, 3152 (90.71%) samples were D+ and 323 (9.29%) were D–. Analysis of Rh antigen typing results showed e (3359; 96.66%) to be most prevalent in the Iranian population, followed by D (3152; 90.71%), C (2677; 77.04%), c (2557; 73.58%), and E (1059; 30.47%). In the Kell blood group system, 3293 (94.76%) samples were typed as K–k+. For the Kidd and Duffy blood group systems, the following were the most common phenotypes: Jk(a+b+) (1703; 49%), Jk(a+b–) (1006; 28.95%), Fy(a+b+) (1495; 43.02%), and Fy(a+b–) (1005; 28.92%). In the MNS blood group system, the following were the most common phenotypes: M+N+ (1668; 48%), M+N– (1310; 37.70%), S+s+ (1564; 45%), and S–s+ (1392; 40.06%). In the Lutheran and P1PK blood group systems, Lu(a–b+) and P1+ phenotypes were observed in 3292 (94.73%) and 1966 (56.58%) samples, respectively. The Xg antigen was present in 1953 (56.20%) samples versus 1522 (43.80%) samples identified as Xg(a–). Knowledge of the prevalence of RBC antigen phenotypes in a population can be useful in databank creation for providing antigen-negative compatible blood to patients with multiple alloantibodies. Immunohematology 2016;32: 135–139.

Key Words: blood group systems, red blood cell antigens, phenotype prevalence, MNS, ABO, Rh, Kell, Kidd, Duffy

The nine major blood group systems include ABO, Rh, Kell, Kidd, Duffy, MNS, P1PK, Lewis, and Lutheran.1,2 Identifying blood group antigens is very important in blood transfusion and organ transplantation to minimize major transfusion reactions.3,4 Determining the prevalence of red blood cell (RBC) antigens of various blood groups in first-time voluntary blood donors would help us obtain insight into blood group distribution in a geographic population. This information can also help us lay the foundation for starting a databank of antigen-negative blood, which would aid in the prevention of

transfusion reactions in alloimmunized patients.5 There are some studies limited to ABO and Rh blood groups,6–10 but other than one older study of blood group distribution,11 no current data are available on RBC antigens and phenotype prevalence in Iran. The present study is the first comprehensive report of the prevalence of various RBC antigens and phenotypes of various blood groups in the Iranian general population.

Materials and Methods

This retrospective study was carried out using the data from 3475 individuals referred for paternity testing during a period of 10 years (from 1998 to 2008) to the Immunohematology Reference Laboratory (IRL) of the Iranian Blood Transfusion Organization (IBTO), Tehran, Iran, to derive information on the population prevalence of antigens and phenotypes in ABO, Rh, and seven other major blood group systems.

Ethical ConsiderationsThis study was approved by the ethics committee of IBTO

and its health services. Individuals were asked to sign an informed consent form before blood samples were obtained. All the terms of the Helsinki Declaration were met, and the personal information remained anonymous.

Sample SizeThe sample size included all blood samples from

individuals referred to the national forensic laboratory in Tehran, Iran, and the IRL of IBTO. During these 10 years, blood samples were collected and tested independently in two centers.

Blood SamplesTesTing for ABo And rh AnTigens

Six milliliters of peripheral blood was drawn from each person into a vial containing ethylenediaminetetraacetic acid (EDTA) anticoagulant. Blood samples were collected under aseptic conditions from an anticubital vein for determination of blood group antigens. Initial ABO blood grouping was

136 IMMUNOHEMATOLOGY, Volume 32, Number 4, 2016

determined by the tube method using commercially prepared antisera provided by Iranian Blood Research and Fractionation [IBRF], Tehran, Iran. The presence of D was determined serologically using reagents from IBRF. Weak-D testing was performed on samples initially tested as D–. Repeat ABO and D testing for blood group confirmation was performed by the conventional tube method as per our standard operating procedure using monoclonal reagents from different commercial companies: anti-A (Bio-Rad, Munich, Germany), anti-B (Bio-Rad), and anti-D (CE-Immumodiagnostika, Heidelberg, Germany). Testing for the presence of the weak-D phenotype was done on all samples typed as D– as per manufacturer’s instructions. The tube method using a 2–5 percent RBC suspension and monoclonal Rh antisera (anti-C, anti-c, anti-E, and anti-e, Diamed AG, Cressier sur Morat, Switzerland) as per the manufacturer’s instructions was performed for the common Rh antigens (C, E, c, e). A reaction range of 1+ to 4+ agglutination indicated the presence of the corresponding antigen. The absence of agglutination was confirmed macroscopically per the manufacturer’s instructions indicating the antigen’s absence.

TesTing for Kell, Kidd, duffy, Mnss, luTherAn, P1, And Xg AnTigens

Cells with either the presence or absence of the antigens to be tested were selected from an in-house screening cell panel that was validated with commercial panel cells (Diacell, Diamed AG). These cells were used as positive and negative controls to ensure expected reactivity of antisera to be used in the testing.

inTerPreTATion of TuBe TesTing resulTs: Positive: Various-sized clumps of RBCs on the bottom

of the tube, graded from 1+ to 4+, indicated the presence of the corresponding antigen.

Negative: A smooth RBC suspension after re-suspension of cells on the bottom of the tube indicated the absence of the corresponding antigen.

Statistical AnalysisRBC antigen and phenotype prevalence within the various

blood group systems was calculated by totaling the number of individuals positive for a particular antigen or phenotype divided by the total number of individuals screened. Results are expressed as a percentage.

Results

The prevalence of different blood group antigens and phenotypes in a total of 3475 (1857 male and 1618 female) individual samples was compared.

ABO and Rh Blood Group SystemsThe breakdown of results for ABO blood grouping was

1268 (36.49%) typed as group O followed by 1115 (32.09%) as group A, 823 (23.68%) as group B, and 269 (7.74%) as group AB. D phenotype prevalence analysis showed 3152 (90.71%) D+ individuals and 323 (9.27%) D– individuals. In total, among D+ individuals, group O (1148; 33.06%) was found to be most prevalent followed by groups A (1014; 29.19%), B (743; 21.41%), and AB (247; 7.11%). Among D– individuals, blood groups O (128; 3.7%) and A (107; 3.10%) were the most common, followed by groups B (75; 2.17%) and AB (13; 0.62%). Testing for Rh antigens found Rh5(e) (3359; 96.66%) to be most prevalent of the common Rh antigens in this Iranian population, followed by Rh1(D) (3152; 90.70%), Rh2(C) (2677; 77.04%), Rh4(c) (2557; 73.58%), and Rh3(E) (1059; 30.47%). Nine probable Rh phenotype combinations were found to be present in our D+ population; the most common phenotype was DCe/dce (R1r; 873; 27.70%) (Tables 1 and 2).

Other Blood Group SystemsIn the Kell blood group system, 3293 (94.76%) samples

were typed as K–k+. The Kp(a+b–) phenotype was rarely found. In the Kidd and Duffy blood group systems, Jk(a+b+) (1670; 48.06%) and Fy(a+b+) (1466; 42.19%) were the most common phenotypes observed. Jk(a–b–) and Fy(a–b–) were found as rare phenotypes in the Kidd and Duffy blood group systems, respectively. M+N+ (1660; 47.77%) and S+s+ (1569; 45.15%) were the most common phenotypes observed in the

E. Shahverdi et al.

Table 1. Prevalence of D+ phenotypes in the Iranian study population (N = 3152)

Phenotype

Antigens present Fisher-Race Modified Weiner Prevalence (%)

D Cc e DCe/dce R1r 27.70

D C e DCe/DCe R1R1 22.38

D Cc Ee DCe/DcE R1R2 14.59

D c Ee DcE/dce R2r 10.35

D c E DcE/DcE R2R2 2.30

D c e Dce/dce R0r 1.78

D C Ee DCE/DCe RzR1 0.08

D Cc E DCE/DcE RzR2 0.01

D C E DCE/DCE RzRz 0.008


Blood groups in Iran

MNS blood group system. In the Lutheran and P1PK blood group systems, Lu(a–b+) and P1+ phenotypes were observed in 3292 (94.73%) and 1966 (56.58%) samples, respectively. The rare phenotype Lu(a–b–) was observed in none (0%) of the samples. The Xg antigen was identified in 1953 samples (56.20%), versus 1522 (43.80%) samples that typed as Xg(a–) (Table 3).

Discussion

In our study, blood group O was the most prevalent, followed by groups A, B, and AB. According to some studies, in the United States, group O is the most prevalent, followed by groups A, B, and AB.12 Klein and Anstee13 showed that the most common blood groups in Australians were O and A. These results are in line with our findings. According to a previous Iranian study, blood group O was the most common.14 The prevalence is different between that study and ours (41% vs. 36%). In contrast, in some other studies of populations in other countries,3,15–18 blood group B was most prevalent. According to Tomilin et al.,19 blood group A was the most prevalent group in the Russian Federation.

In our study, the targeted population showed D– prevalence of 9 percent, as compared with 17 percent in Britain and 4.29 percent in India.20,21 This result suggests that the expected rate of Rh isoimmunization would be lower in our population than that encountered in the British population. Studies have reported that in the United States, 85 percent of the population were found to be D+.22 The prevalence of D– individuals varies from 20 percent to 40 percent in Basque populations to 0 percent to 1 percent in Japanese, Chinese, Burmese, Melanesian, Mauri, American Indian, and Eskimo populations.3

The worldwide prevalence of D differs between ethnic groups—from 85 percent in white populations to 92 percent in black populations.23,24 In the present study, we found the prevalence of D to be 91 percent.

We report for the first time the prevalence of other common antigens in the Rh system, including C, c, E, and e, in a general Iranian population. We found e to be the most prevalent Rh antigen in this population. DCe/dce (R1r) was the most common phenotype in the D+ population versus dce/dce (rr) in that of the D–. In previous studies on Thai and Chinese individuals, CDe/CDe (R1R1) has been reported to be of the highest prevalence.25 Nanu and Thapliyal also found DCe/DCe (R1R1) to be the most common phenotype in that population.26 The prevalence of cde/cde (rr) varies among different ethnic groups. It was reported in 35 percent of white individuals, 26 percent of black individuals, and in only 3 percent of individuals of Asian descent.27–30

Table 2. Prevalence of D– phenotypes in the Iranian study population (N = 323)

Phenotype

Antigens present Fisher-Race (assumed) Modified Weiner Prevalence (%)

c e dce/dce rr 9.59

Cc e dCe/dce r′r 1.95

c Ee dcE/dce r″r 0.45

Cc Ee dCe/dcE r′r″ 0.05

C e dCe/dCe r′r′ 0.04

c E dcE/dcE r″r″ 0.001

C Ee dCE/dCe ryr′ Rare

CE dCE/dCE ryry Rare

Cc E dCE/dcE ryr″ Rare

Cc Ee dCE/dce ryr Rare

Table 3. Prevalence of phenotypes in various blood group systems in the Iranian study population (N = 3475)

System Phenotype Prevalence (%)

Kell Kp(a–b+) 99

K–k+ 95

K+k+ 4.8

Kp(a+b+) 0.8

K+k– 0.2

Kp(a+b–) Rare

Kidd Jk(a+b+) 49

Jk(a+b–) 29

Jk(a–b+) 22

Jk(a–b–) Rare

Duffy Fy(a+b+) 43

Fy(a+b–) 29

Fy(a–b+) 28

Fy(a–b–) 1

MNS M+N+ 48

M+N– 38

M–N+ 14

S+s+ 45

S–s+ 40

S+s– 15

S–s– 0

Lutheran Lu(a–b+) 91

Lu(a+b+) 6

Lu(a+b–) 3

Lu(a–b–) 0

P1PK P1+ 67

P1– 33

Xg Xg(a+) 58

Xg(a–) 42


In the Kell system, the most common phenotype in our population was found to be K–k+ (95%), which is found in 100 percent of peoples from Southeast Asia.27 The prevalence of K+k– in this study was 0.2 percent. None of the individuals of the Thakral et al. study5 were found to be K+k–. The rarest phenotype in our study was Kp(a+b–), whereas Kp(a+b+) was found to be rare in the Thakral et al. study population.5 This shows that a rare phenotype in a certain population does not necessarily imply rarity of that phenotype in another population.

In the Duffy system, Fy(a+b+) and Fy(a–b–) were the most common and the rarest phenotypes, respectively. According to Agarwal et al.,15 Fy(a–b–) was rare in Indian and white populations, although it was common in a black population. In virtually all Indian studies, Fy(a+b+) was the most common phenotype in the white population.15 Plasmodium vivax is endemic to India, and therefore we expect India to have a high prevalence of the Fy(a–b–) phenotype because the Duffy antigen has been proposed to be the receptor for entry of P. vivax into red blood cells.31 Lack of this phenotype in studies from India could be attributable to fewer P. vivax infections. In Iran, thanks to preventive measures and treatment protocols, malaria has been eradicated, and this may account for the low prevalence of the Fy(a–b–) phenotype in our population.

Jk(a+b+) was the most common Kidd phenotype in our study. Nathalang et al.27 reported similar findings in Asian and Thai populations. Moreover, Jk(a–b–) has rarely been found.

In our study, the M+N+ phenotype was the most common in the MNS blood group system. In the Nanu and Thapliyal study, the M+N– phenotype was reported to be the most common.26

S+s+ was the most common phenotype in our study. In other studies, S–s+ has been reported as the most common phenotype.5,15 Further, the M+N+S+s+ phenotype was reported to be the most common by Nanu and Thapliyal, as well as in people of European descent and in African Americans.26,32,33 In our population study, M+N+S+s+ was found to be the most common phenotype. It is possible that in areas where heterozygous phenotypes are most prominent, less alloimmunization occurs. In these areas, the value of a donor database might be in question.

In the Lutheran system, Lu(a–b+) was the most common phenotype found in our study, which is true for most of the populations around the world.15 In our study, there also was no one with the Lu(a–b–) phenotype. Lu(a–b–) was reported as a very rare phenotype in the study by Thakral et al.5

In the P1PK system, P1+ was the most common phenotype in our study. Musa et al.34 demonstrated that

Malays and Chinese populations had high prevalence of the P1– phenotype, whereas the Indian population had higher prevalence of P1+. A lower prevalence of the P1– phenotype was reported among Thai individuals.35

In our study, the Xg(a+) phenotype was found as the most common phenotype in the Xg blood system. The distribution of the Xg antigen in our sample population is comparable with that reported in the Daniels study.36

Conclusions

We reported on the distribution of various blood group antigens and phenotypes among a general Iranian population. The study has a vital impact on the management of blood bank and transfusion services in this area. Knowledge of blood group antigen distribution is also important for clinical studies, for worldwide reliable geographical information, and for forensic research in various populations.

References

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2. Smart E, Armstrong B. Blood group systems. ISBT Sci Ser 2008;3:68–92.

3. Khattak ID, Khan TM, Khan P, Shah S, Khattak ST, Ali A. Frequency of ABO and Rhesus blood groups in District Swat, Pakistan. J Ayub Med Coll Abbottabad 2008;20:127–9.

4. Khurshid B, Naz M, Hassan M, Mabood S. Frequency of ABO and Rh (D) blood groups in district Swabi NWFP (Pakistan). J Sc Tech Univ Peshawar 1992;16:5–6.

5. Thakral B, Saluja K, Sharma RR, Marwaha N. Phenotype frequencies of blood group systems (Rh, Kell, Kidd, Duffy, MNS, P, Lewis, and Lutheran) in north Indian blood donors. Transfus Apher Sci 2010;43:17–22.

6. Pourfathollah A, Oody A, Honarkaran N. Geographical distribution of ABO and Rh (D) blood groups among Iranian blood donors in the year 1361 (1982) as compared with that of the year 1380 (2001). Sci J Iran Blood Transfus Organ. 2004;1:11–7.

7. Boskabady M, Shademan A, Ghamami G, Mazloom R. Distribution of blood groups among population in the city of Mashhad (North East of Iran). Pak J Med Sci 2005;21:194–8.

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14. Marzban M, Kamali M, Hosseinbasi T. Blood groups of the people of Ahwaz, Iran. Anthropologischer Anzeiger 1988;46:83–9.

15. Agarwal N, Thapliyal RM, Chatterjee K. Blood group phenotype frequencies in blood donors from a tertiary care hospital in north India. Blood Res 2013;48:51–4.

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31. Langhi DM Jr, Bordin JO. Duffy blood group and malaria. Hematology 2006;11:389–98.

32. Cleghorn T. MNSs gene frequencies in English blood donors. Nature 1960;187:701.

33. Race RR, Sanger R. Blood groups in man. Oxford: Blackwell Scientific Publications, 1965.

34. Musa RH, Ahmed SA, Hashim H, Ayob Y, Asidin NH, Choo PY, et al. Red cell phenotyping of blood from donors at the National Blood Center of Malaysia. Asian J Transfus Sci 2012;6:3.

35. Panigrahi I, Marwaha RK. Common queries in thalassemia care. Indian Pediatr 2006;43:513.

36. Daniels G. Human blood groups. Hoboken, NJ: John Wiley & Sons, 2008.

Ehsan Shahverdi, MD, member of Student Research Committee, Baqiyatallah University of Medical Sciences, Blood Transfusion Research Center, High Institute for Research and Education in Transfusion Medicine, Tehran, Iran; Mostafa Moghaddam, MSc (corresponding author), Head of Immunohematology Reference Laboratory, Iranian Blood Transfusion Organization, Blood Transfusion Research Center, High Institute for Research Center and Education in Transfusion Medicine, Iranian Blood Transfusion Organization Bldg., Hemmat Expy., Tehran, Iran, [email protected]; Ali Talebian, MD, past Deputy of Technical and Modern Technology (retired), Iranian Blood Transfusion Organization, Blood Transfusion Research Center, High Institute for Research Center and Education in Transfusion Medicine, Tehran, Iran; and Hassan Abolghasemi, MD, past Managing Director, Iranian Blood Transfusion Organization, current Head of Pediatric Hematology and Oncology Department, Baqiyatallah University of Medical Sciences, Tehran, Iran.

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Acute hemolytic transfusion reaction attributed to anti-Ata

J.S. Raval, S.K. Harm, B. Wagner, D.J. Triulzi, and M.H. Yazer

Case repOrt

Anti-Ata is a rare alloantibody that can be clinically significant. We report a case of a woman who, after emergency-released uncrossmatched red blood cell transfusion, experienced an acute hemolytic transfusion reaction attributed to anti-Ata. The case presented herein highlights the importance of recognizing that anti-Ata may indeed cause acute hemolytic reactions. Immunohematology 2016;32:140–142.

Key Words: anti-Ata, high-prevalence antigen, hemolytic transfusion reaction

Anti-Ata is directed at the Ata (Augustine) antigen, a high-prevalence red blood cell (RBC) antigen present in greater than 99 percent of people in all populations.1 Individuals lacking the Ata antigen, who can potentially make anti-Ata, often originate from the Caribbean or Southern United States.1 The Ata antigen and corresponding antibody were

first described by Applewhaite and colleagues in 1967 after a weakly positive direct antiglobulin test (DAT) was incidentally discovered in an infant of a multiparous black woman of West Indian origin named Mrs. August.2 There was no laboratory or clinical evidence of hemolytic disease of the fetus and newborn (HDFN) during any of her three pregnancies. Subsequent population analyses have demonstrated reactivity of anti-Ata with RBCs of at least 6600 random New Yorkers (including at least 2200 individuals of African ancestry),2 at least 3000 random blood donors,3 and 8551 out of 8552 people living in Detroit, Michigan, of African ancestry4—thus establishing the high prevalence of Ata.

There have been several published reports describing anti-Ata, totaling 14 patients in all, but only a subset of these patients have experienced an adverse reaction after RBC transfusion attributed to anti-Ata (Table 1). The reported adverse reactions

Table 1. Reported cases of anti-Ata

Casereference Gender Age Race ABO groupPrevious

transfusionPrevious

pregnancy Adverse reaction

12 Female Unknown Black B No Yes DAT+ in newborn

23 Female 40 Black A No Yes No

35 Male 65 Black O Yes — Chills

45 Female 26 Black O No Yes No

55 Female 34 Black AB Yes Yes No

65 Female 39 Black B No Yes Unknown

75 Female 44 Black B Unknown Yes DAT+ in newborn

85 Female 35 Black B No Yes No

96 Female Unknown Black B Unknown Yes DAT+ in newborn; decreased 24-hour RBC survival study (2 mL)

107 Female 26 Black O Yes No Fever, chills, nausea associated with decreased 3- and 19-hour RBC survival study (5 mL)

117 Female 36 Black A No Yes DAT+ in newborn

128 Female 35 Black A Unknown Yes HDFN

139 Female 60 Black Unknown No Yes DHTR

1410 Female 37 Black AB No Yes No

15* Female 40 Black O No Yes AHTR

*Patient described in the current report.DAT = direct antiglobulin test; RBC, red blood cell; HDFN = hemolytic disease of the fetus and newborn; DHTR = delayed hemolytic transfusion reaction; AHTR = acute hemolytic transfusion reaction.


Acute HTR attributed to anti-Ata

in this population include positive DAT in newborns,2,5,6 chills,5,7 fever,7 nausea,7 decreased RBC survival,6,7 a moderate case of HDFN,8 and, most recently, a case of severe delayed hemolytic transfusion reaction.9 Nonetheless, until now, no acute hemolytic transfusion reaction associated with transfusion of an At(a+) RBC unit has been described. We report a case in which a clinically significant acute hemolytic transfusion reaction was attributed to anti-Ata.


All data were retrospectively collected from the patients’ medical records. This review was approved by the Quality Council of the Institute for Transfusion Medicine (Pittsburgh, PA). ABO and D testing were performed using solid-phase technology (Galileo, Immucor, Inc., Norcross, GA). All additional immunohematology testing was performed using saline tube methods with reactions graded on a scale of 0 to 4+. Additional reagents used included low-ionic-strength saline (LISS), polyspecific (anti-IgG/anti-C3d) antihuman globulin (AHG), monospecific anti-IgG AHG, monospecific anti-C3d AHG, and acid elution kit (all obtained from Immucor, Inc.).

Case Report

A 40-year-old black woman with history of autoimmune hypothyroidism, three uneventful pregnancies, and no history of transfusion presented with fatigue and dyspnea on exertion. Her symptoms were secondary to megaloblastic anemia and severe vitamin B12 deficiency attributable to pernicious anemia that was positive for anti-intrinsic factor antibody. Her admission laboratory values included: hemoglobin 5.6 g/dL (normal 12.3–15.3 g/dL), platelet count 80,000/µL (normal 145,000–445,000/µL), lactate dehydrogenase (LDH) 4440 IU/L (normal 110–216 IU/L), total bilirubin 3.7 mg/dL (normal 0.2–1.2 mg/dL), and direct bilirubin 0.8 mg/dL (normal 0.0–0.4 mg/dL). Her ABO and D typings showed her RBCs to be group O, D+. Her antibody screen was positive, with all screening cells reacting 3+ at the AHG phase in tube testing with LISS enhancement. Because of her positive antibody screen, a DAT was performed, and it was negative with polyspecific AHG reagent; an eluate was performed and was also negative. Because of the patient’s symptomatic anemia, the decision was made to emergently transfuse the patient, and two emergency-released uncrossmatched RBC units were issued. Approximately 15 minutes after the first RBC unit had been completely transfused, the patient developed chills and had one episode of dark urine, although she remained afebrile with stable vital signs.

A transfusion reaction workup was initiated. All elements of the clerical check were confirmed normal; these elements consisted of verification of (1) the blood bank issuing the proper blood product to the proper patient, (2) the unit number on the blood unit matching the unit number on the transfusion reaction form, (3) documentation of health care personnel having double-checked patient identification and blood product information prior to transfusion of the blood unit to the proper patient, and (4) patient identification on the post-transfusion blood sample and transfusion reaction form matching the blood bank records. Both the pre-transfusion and post-transfusion plasma specimens were icteric on visual inspection with no hemolysis noted. Biochemical tests of hemolysis were positive, including increased LDH (5669 IU/L), increased total bilirubin (7.1 mg/dL), increased direct bilirubin (2.2 mg/dL), and haptoglobin less than 10 mg/dL (normal 16–200 mg/dL). Repeat hemoglobin measurement demonstrated no post-transfusion increase from her pre-transfusion concentration (5.4 mg/dL). The DAT was now found to be weakly positive with polyspecific AHG reagent, negative with anti-C3d reagent, and weakly positive with anti-IgG AHG reagent. The eluate reacted with all screening cells at AHG phase (2+) except for the autocontrol. These findings suggested an alloantibody to a high-prevalence antigen had been detected, and anti-Ata was subsequently identified by a large immunohematology reference laboratory (Immunohematology Reference Laboratory, LifeShare Blood Centers, Shreveport, LA). The patient’s RBCs were serologically typed for Ata and found to be negative. A differential adsorption using human erythrocyte stroma prepared from R1R1, R2R2, and rr cells of known phenotype was performed on the patient’s serum to rule out the presence of any other underlying alloantibodies; none were identified. Two At(a–) RBCs units were obtained (one frozen unit immediately available from internal RBC inventory and one frozen unit available from regional blood donor center within 48 hours of request via the American Rare Donor Program), crossmatched, transfused without incident, and appropriately increased her hemoglobin level (pre-transfusion value 6.9 g/dL to post-transfusion value 8.9 g/dL).

Discussion

This case report describes a rare alloantibody, anti-Ata, which was implicated as a cause of a clinically significant acute hemolytic reaction. Immunohematology data from previous reports of anti-Ata have described it to be detectable with polyspecific and/or anti-IgG AHG reagents when bound to RBCs,2,3,5,6,8–11 and in the vast majority of cases there has


been no complement bound to the RBCs as detected using routine anti-C3d monospecific AHG reagent.1,8 The in vitro immunohematologic characteristics of anti-Ata described in this current report are consistent with those previously reported. Autoimmune disease has been posited7 as having an association with development of anti-Ata—this proposed relationship is supported by the patient in the current report, who has two autoimmune diseases.

Recently, the genetic basis for the At(a–) phenotype has been discovered: a non-synonymous single nucleotide polymorphism in rs45458701 (c.1171G>A in exon 12 of SLC29A1) resulting in a non-conservative p.Glu391Lys substitution.12 This finding has the potential to identify At(a–) donors and patients via RBC genotyping studies. Based on this evidence, the Augustine blood group system was formed (symbol AUG), and the Ata antigen was named AUG2 (number 036002).13

In conclusion, although anti-Ata is a rare antibody of variable clinical significance, it has the potential to cause rapid, acute, clinically significant hemolysis. If possible, patients who develop anti-Ata and require RBCs should be transfused with units negative for the cognate antigen.

Acknowledgments

We wish to thank Dr. Donald L. Kelley and Mrs. Kimberly Gabert (Institute for Transfusion Medicine, Pittsburgh, PA) for their assistance in acquiring the clinical and laboratory data for this case report.

References

1. Reid ME, Lomas-Francis C, Olsson ML. The blood group antigen factsbook. 3rd ed. San Diego, CA: Academic Press, 2012:682.

2. Applewhaite F, Ginsberg V, Gerena J, Cunningham CA, Gavin J. A very frequent red cell antigen, Ata. Vox Sang 1967;13: 444–5.

3. Frank S, Schmidt RP, Baugh M. Three new antibodies to high-incidence antigenic determinants (anti-El, anti-Dp, and anti-So). Transfusion 1970;10:254–7.

4. Winkler MM, Hamilton JR. Previously tested donors eliminated to determine rare phenotype frequencies. International Society of Blood Transfusion/American Association of Blood Banks 1990 Joint Congress. Arlington, VA: American Association of Blood Banks, 1990:158.

J.S. Raval et al.

5. Gellerman MM, McCreary J, Yedinak E, Stroup M. Six additional examples of anti-Ata. Transfusion 1973;13:225–30.

6. Sweeney JD, Holme S, McCall L, Huett D, Storry J, Reid M. At(a–) phenotype: description of a family and reduced survival of At(a+) red cells in a proposita with anti-Ata. Transfusion 1995;35:63–7.

7. Ramsey G, Sherman LA, Zimmer AM, et al. Clinical significance of anti-Ata. Vox Sang 1995;69:135–7.

8. Culver PL, Brubaker DB, Sheldon RE, Martin M, Richter CA. Anti-Ata causing mild hemolytic disease of the newborn. Transfusion 1987;27:468–70.

9. Cash KL, Brown T, Sausais L, Uehlinger J, Reed LJ. Severe delayed hemolytic transfusion reaction secondary to anti-Ata. Transfusion 1999;39:834–7.

10. Burnette RE, Couter K. A positive antibody screen—an encounter with the Augustine antibody. J Natl Med Assoc 2002;94:166–70.

11. Ramsey G, Smietana SJ. Multiple or uncommon red cell alloantibodies in women: association with autoimmune disease. Transfusion 1995;35:582–6.

12. Daniels G, Ballif BA, Helias V, et al. Lack of the nucleoside transporter ENT1 results in the Augustine-null blood type and ectopic mineralization. Blood 2015;125:3651–4.

13. Storry JR, Castilho L, Chen Q, et al. International Society of Blood Transfusion Working Party on Red Cell Immunogenetics and Terminology: report of the Seoul and London meetings. ISBT Sci Ser 2016;11:118–22.

Jay S. Raval, MD (corresponding author), Department of Pathology, University of Pittsburgh, The Institute for Transfusion Medicine, Pittsburgh, PA 15213 [current affiliation: Department of Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill, NC 27599-7525], [email protected]; Sarah K. Harm, MD, Department of Pathology, University of Pittsburgh, The Institute for Transfusion Medicine [current affiliation: Department of Pathology and Laboratory Medicine, University of Vermont, Burlington, VT]; Bethann Wagner, MT(ASCP)SBB, Education and Technical Training Supervisor, The Institute for Transfusion Medicine; Darrell J. Triulzi, MD, Department of Pathology, University of Pittsburgh, The Institute for Transfusion Medicine; and Mark H. Yazer, MD, Department of Pathology, University of Pittsburgh, The Institute for Transfusion Medicine, Pittsburgh, PA.


Human platelet antigen allelic diversity in Peninsular MalaysiaW.U.W. Syafawati, Z. Zefarina, Z. Zafarina, M.N. Hassan, M.N. Norazmi, S. Panneerchelvam, G.K. Chambers, and H.A. Edinur

Original repOrt

Human platelet antigens (HPAs) are polymorphic and immunogenic glycoproteins encoded by biallelic genes on human chromosome 17 (HPA-1 to -4 and HPA-6 to -11), chromosome 5 (HPA-5), and chromosome 6 (HPA-15) and expressed on the surface of platelets. In the present study, we typed seven HPA loci (HPA-1 to -6 and HPA-15) by polymerase chain reaction using sequence-specific primer and sequence-based typing in 166 blood samples representing three Orang Asli groups (Semang, Senoi, and Proto-Malays) that inhabit Peninsular Malaysia. Combined with previous HPA data collected for Malay subethnic groups, Malays, Chinese, and Indians, our analyses showed high genetic diversity in Peninsular Malaysia, which is consistent with multiple settlements of the region by several founding ancestors (Semang, Senoi, and Proto-Malays) in the last 50,000 years. The gene pools of these ancient populations were then further shaped by various evolutionary pressures such as repeated founder effects, natural selection, and admixture with the relatively recent arrivals such as Chinese, Indians, and Malay subethnic groups. Medical consequences of this genetic complexity are also discussed, including the risks of platelet alloimmunization associated with random platelet transfusion and gestation. Immunohematology 2016;32:143–160.

Key Words: human platelet antigen, Orang Asli, Semang, Senoi, Proto-Malays, Peninsular Malaysia

Human platelet antigens (HPAs) are expressed on the surface of platelets. They are polymorphic and immunogenic glycoproteins encoded by the biallelic genes on human chromosomes 17 (HPA-1 to -4 and HPA-6 to -11), 5 (HPA-5), and 6 (HPA-15).1,2 HPAs are clinically relevant in transfusion and gestation, since incompatibility can cause posttransfusion purpura (PTP),3 platelet transfusion refractoriness (PTR),4 and neonatal alloimmune thrombocytopenia (NAIT).5 Collections of HPA data have been reported for many populations, including Europeans,6–8 Asians,9–13 Africans,1 and Amerindians.14 Knowledge about local distributions of HPAs is useful for population and disease studies as well as for estimating the risk of platelet alloimmunization. In Peninsular Malaysia, HPA data have been collected and reported for Malay subethnic groups,15 Malays,16 Chinese,16 and Indians,16 but not for the minority indigenous peoples collectively known as Orang Asli. They are represented by three major groups with

each one containing six subgroups (Department of Orang Asli Affairs, Malaysia: http://www.jakoa.gov.my): Semang (Batek, Jahai, Kensiu, Kintak, Lanoh, and Mendriq), Senoi (Semai, Temiar, Semoq Beri, Jahut, Che Wong, and Meh Meri), and Proto-Malays (Orang Kanaq, Kuala, Seletar, Jakun, Semelai, and Temuan).

The Semang inhabit northern parts of Peninsular Malaysia and are physically of small body size with dark skin and frizzy hair. The Semang are hunter-gatherers and numerically the smallest of all the Orang Asli groups. They arrived in Peninsular Malaysia about 50,000 years ago and together with Australian Aborigines and Papuans17 are associated with those earliest modern humans who migrated out of Africa. The Senoi, who inhabit the foothills and lowlands of northern and central regions of Peninsular Malaysia, are estimated to have arrived about 8,000 years ago and are the largest group of Orang Asli. The light-skinned and relatively tall Senoi people are linked to Austro-Asiatic agriculturists who originated from mainland Southeast Asia or South China. In contrast, Proto-Malays arrived quite recently in Peninsular Malaysia (~4,000 years ago).18 They are believed to be descendants of Neolithic Austronesian voyagers who migrated out of Taiwan to islands of Southeast Asia, and Near and Remote Oceania.19 It is from this Orang Asli group that the admixed Deutero-Malays later emerged. Their contemporary gene pool now contains recent minor admixture from other residents in Malaysia, including Chinese and Indians.20

Overall, our present study on HPA in representative OA groups/subgroups complements earlier studies on Malays,16 Chinese,16 Indians,16 and Malay subethnic groups15 and thus provides more fully extensive documentation of HPA allelic spectra in Peninsular Malaysia for the first time. These data sets can now be subjected to a small-scale meta-analysis study of ancestry and used to estimate the risks of platelet alloimmunization associated with random platelet transfusion and gestation. We present the findings from this investigation and our comments on their significance.


W.U.W. Syafawati et al.


Blood SamplesA total of 166 blood samples were obtained with informed

consent from all three Orang Asli groups: Semang (Batek: N = 27, Che Wong: N = 26, and Kensiu: N = 36), Senoi (Lanoh: N = 25 and Semai: N = 41), and Proto-Malays (Orang Kanaq: N = 11). The Orang Asli study samples were then split into smaller subsamples of unrelated (u) individuals; uBatek (N = 17), uChe Wong (N = 14), uKensiu (N = 21), uLanoh (N = 13), uSemai (N = 34), and uProto-Malays (N = 7). All volunteers were self-declared as having three generations lacking any admixture with other ethnicities. This study was reviewed and approved by the human ethics committee of the University Sains Malaysia [reference no. USM/JEPeM/1406217 and USM/PPP/ethics committee/2012(19)].

DNA ExtractionDNA from blood samples were extracted using a kit

(QIAamp DNA Mini Kit, QIAGEN, Hilden, Germany). Extractions were performed according to the manufacturer’s instructions. The eluted DNA was quantified by spectrophotometry (NanoDrop 2000c Spectrophotometer, Thermo Scientific, Waltham, MA) and stored at –20°C until further use.

Sequence-Specific Primer Genotyping of HPA-1 to -6 and HPA-15 Loci

The polymerase chain reaction using sequence-specific primer (PCR-SSP) genotyping protocols, including oligonucleotide primers and thermal cycling parameters, reported by Kupatawintu et al.11 and Feng et al.,12 were used to genotype HPA-1, -2, -4, -5, and -15, and HPA-3 and -6, respectively. The amplified products and DNA size markers were separated by using stained 2 percent agarose gels (SYBR Safe, Life Technologies Corp., Singapore) and visualized using a digital gel documentation system (Vilber Lourmat Software, VILBER, Eberhardzell, Germany). All HPA allelic scoring was made by comparing band patterns for amplified HPA allele-specific products with a DNA size standard.

Sequence-Based Typing of HPA-15Our PCR-SSP typing showed an extremely high frequency

of HPA-15b/b genotype in Orang Asli. Indeed, the HPA-15b allele is fixed in Batek. Thus, we randomly selected 20 samples and genotyped the HPA-15 locus using sequence-based typing (SBT) as part of our verification procedure. The HPA-15 locus was amplified from these selected DNA

samples using specific discriminating oligonucleotide primers (forward: 5 -́GAATATGGATCAATATGCAGTA-3 ;́ reverse: 5 -́AAAAGACAAAGCCAAGGA-3 )́ and PCR cycling condi-tions reported by Xu et al.21 The amplified PCR products were then purified (QIAquick PCR Purification, QIAGEN) and analyzed using agarose gel electrophoresis. The remaining aliquots of purified PCR amplicons were sent to the DNA sequencing service provided by 1st BASE Biochemicals, Singapore, (Applied Biosystems 3730xl DNA analyzer, Foster City, CA).

Statistical AnalysesAllele and genotype frequencies were determined using

the following formula:

genotype frequency = number of genotype observed/ number of individuals and allele frequency =

number of allele observed/2 (number of individuals)

χ2 tests were used for evaluating Hardy-Weinberg equilibrium (HWE) in Orang Asli using the formula:

χ2 = ∑ [(O – E) 2/E]

where O and E are observed and expected number of genotypes, respectively. Significant departure from HWE is considered at a p value <0.05.22 Genetic differentiation between pairs of Orang Asli subgroups and between Orang Asli and previously studied Malay subethnic groups,15 Malays,16 Chinese,16 and Indians16 were evaluated using Fischer’s exact test in a software program (SPSS, SPSS Inc., Chicago, IL). Two data sets were considered significantly different at a p value <0.05. Genetic relationships between Orang Asli subgroups, Malay subethnic groups, and other reference populations were studied using principal coordinate analysis software (Multivariate Statistical Software Package 3, Kovach Computing Services, Pentraeth, Isle of Anglesey, UK). The HPA frequency data for reference populations were obtained from published resources6–9,13,15,16,23,24 and the IPD-HPA database.1 The probability of transfusion and pregnancy alloimmunization were calculated using the formula established by De La Vega Elena et al.14

Results

The HPA genotype data for Orang Asli and their smaller subsamples of unrelated (u) individuals are shown in Tables 1 and 2, respectively. No significant departures from HWE were


HPA diversity in Peninsular Malaysia

observed, except for HPA-15 in Che Wong. The frequencies of the major (most common) HPA alleles in Orang Asli subgroups were as follows: HPA-1a (0.958–1.000), -2a (1.000), -4a (1.000), -5a (0.788–1.000), and -6a (1.000), as shown in Tables 3 and 4. There are marked differences, however, for HPA-3 and -15 allelic distributions in Orang Asli. For instance, HPA-3b is found at relatively high frequency in Batek (0.500) and Che Wong (0.577), whereas HPA-3a was recorded as the most frequent HPA-3 type in Kensiu, Lanoh, Senoi, and Orang Kanaq (0.640–0.875). For the HPA-15 locus, HPA-15b was the most frequent allele in Batek, Kensiu, and Lanoh, compared with HPA-15a in Orang Kanaq and Semai. The Che Wong showed an equal frequency of HPA-15a and -15b alleles. Exact tests for population differentiation showed no significant differences between pairs of Orang Asli subgroups and their smaller subsample of unrelated individuals (Table 5). Therefore, we used the larger combined (related and unrelated individuals) set of HPA data for Orang Asli to compare them with that reported for Malay subethnic groups,15 Malays,16 Chinese,16 and Indians16 (Table 6). Our results show significant differences between some of the HPA data sets listed in Table 6, especially for HPA-3 and -15. The Malaysia subpopulations including Orang Asli, Malays, Chinese, and Indians are

widely scattered in the top left and right parts of the principal coordinate (PCO) plot (Fig. 1). In contrast, other populations such as Taiwan aborigines and Europeans are plotted on the center and top right-hand corner of Figure 1, respectively.

Discussion

A series of immigrations have contributed to today’s highly diverse and complex genetic structure in Peninsular Malaysia. Therefore, genetic screening of medically important regions within the human genome should become a primary target of biomedical research to better promote the delivery of equitable healthcare to communities. In the present study, we screened the HPA-1 to -6 and HPA-15 loci in the following OA subgroups; Batek, Che Wong, Kensiu, Lanoh, Semai, and Orang Kanaq, who represent three larger Orang Asli groups presently living in Peninsular Malaysia.

The HPA data collected for the Orang Asli subgroups generally showed similarities in terms of their most frequently observed genotypes and alleles (Tables 1 and 3). The only exceptions are the HPA-3 and -15 systems, where significant differences were not only recorded between Orang Asli groups (Semang versus Senoi versus Proto-Malays), but also

Table 1. HPA genotype profiles and Hardy-Weinberg equilibrium estimations for Orang Asli subgroups

Batek (N = 27) Che Wong (N = 26) Kensiu (N = 36) Lanoh (N = 25) Semai (N = 40) Orang Kanaq (N = 11)

HPA O E p O E p O E p O E p O E p O E p

1a/1a 1.000 1.000 NA 1.000 1.000 NA 0.917 0.918 0.794 1.000 1.000 NA 0.976 0.976 0.937 1.000 1.000 NA

1a/1b 0.000 0.000 0.000 0.000 0.083 0.080 0.000 0.000 0.024 0.024 0.000 0.000

1b/1b 0.000 0.000 0.000 0.000 0.000 0.002 0.000 0.000 0.000 0.001 0.000 0.000

2a/2a 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA

2a/2b 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

2b/2b 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

3a/3a 0.185 0.250 0.178 0.115 0.179 0.184 0.750 0.766 0.391 0.480 0.410 0.127 0.463 0.45 0.695 0.636 0.669 0.461

3a/3b 0.630 0.500 0.615 0.488 0.250 0.219 0.320 0.461 0.415 0.442 0.364 0.298

3b/3b 0.185 0.250 0.270 0.333 0.000 0.015 0.200 0.130 0.122 0.108 0.000 0.033

4a/4a 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA

4a/4b 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

4b/4b 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

5a/5a 0.704 0.726 0.366 0.615 0.622 0.848 0.694 0.718 0.279 1.000 1.000 NA 0.781 0.793 0.430 1.000 1.000 NA

5a/5b 0.296 0.252 0.346 0.333 0.306 0.259 0.000 0.000 0.220 0.195 0.000 0.000

5b/5b 0.000 0.022 0.039 0.045 0.000 0.023 0.000 0.000 0.000 0.012 0.000 0.000

6a/6a 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA

6a/6b 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

6b/6b 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

15a/15a 0.000 0.000 NA 0.077 0.250 <0.001 0.083 0.130 0.221 0.080 0.068 0.747 0.342 0.275 0.088 0.818 0.826 0.740

15a/15b 0.000 0.000 0.846 0.500 0.556 0.461 0.360 0.385 0.366 0.499 0.182 0.165

15b/15b 1.000 1.000 0.077 0.250 0.361 0.408 0.560 0.548 0.293 0.226 0.000 0.008

HPA = human platelet antigen; O = observed frequency; E = expected frequency; NA = not applicable.



Table 2. HPA genotype profiles and Hardy-Weinberg equilibrium estimations for smaller subsamples of unrelated Orang Asli individuals

uBatek (N = 17) uChe Wong (N = 14) uKensiu (N = 21) uLanoh (N = 13) uSemai (N = 34) uOrang Kanaq (N = 7)

HPA O E p O E p O E p O E p O E p O E p

1a/1a 1.000 1.000 NA 1.000 1.000 NA 0.857 0.862 0.725 1.000 1.000 NA 0.971 0.971 0.931 1.000 1.000 NA

1a/1b 0.000 0.000 0.000 0.000 0.143 0.133 0.000 0.000 0.029 0.029 0.000 0.000

1b/1b 0.000 0.000 0.000 0.000 0.000 0.005 0.000 0.000 0.000 0.000 0.000 0.000

2a/2a 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA

2a/2b 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1.000 0.000 0.000 0.000 0.000

2b/2b 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

3a/3a 0.118 0.222 0.086 0.143 0.154 0.857 0.810 0.819 0.630 0.462 0.379 0.207 0.471 0.438 0.395 0.714 0.735 0.659

3a/3b 0.706 0.498 0.500 0.477 0.191 0.172 0.308 0.473 0.382 0.448 0.286 0.245

3b/3b 0.177 0.28 0.357 0.369 0.000 0.009 0.231 0.148 0.147 0.114 0.000 0.020

4a/4a 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA

4a/4b 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

4b/4b 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

5a/5a 0.765 0.779 0.583 0.643 0.617 0.571 0.667 0.694 0.359 1.000 1.000 NA 0.794 0.831 0.573 1.000 1.000 NA

5a/5b 0.235 0.208 0.286 0.337 0.333 0.278 0.000 0.000 0.206 0.161 0.000 0.000

5b/5b 0.000 0.014 0.071 0.046 0.000 0.030 0.000 0.000 0.000 0.080 0.000 0.000

6a/6a 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA 1.000 1.000 NA

6a/6b 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

6b/6b 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

15a/15a 0.000 0.000 NA 0.070 0.250 0.008 0.095 0.128 0.519 0.077 0.053 0.500 0.294 0.236 0.171 0.857 0.862 0.839

15a/15b 0.000 0.000 0.857 0.500 0.524 0.459 0.231 0.355 0.382 0.500 0.143 0.133

15b/15b 1.000 1.000 0.070 0.250 0.381 0.413 0.692 0.592 0.324 0.265 0.000 0.005

HPA = human platelet antigen; u = unrelated; O = observed frequency; E = expected frequency; NA = not applicable.

Fig. 1. Principal coordinate plot showing genetic relationships between the studied Orang Asli subgroups and other reference populations. The plot was constructed using HPA-1 to -5 allele frequencies from the reference populations listed in Table 3.



between Semang subgroups (Batek versus Kensiu for HPA-3 and Batek versus Che Wong for HPA-15; Table 6). A similar observation was also apparent between Proto-Malays and their Austronesian relatives, the Malay subethnic groups (Table 6). These genetic differences are all well demonstrated on the PCO plot constructed using HPA-1 to -5 allele frequencies (Fig. 1). The PCO analysis converts genetic variations between HPA data sets into several axes and the distance between populations demonstrates their genetic relationship. The two most informative axes were selected to construct the two-dimentional scatter plot shown in Figure 1. Genetic

differentiation within Orang Asli subgroups (specifically, between Semang subgroups) and between Proto-Malays and Malay subethnic groups has also been reported by others.25 In contrast, there are no obvious differences between the two Senoi subgroups (Lanoh and Semai) who are members of the largest Orang Asli group in Peninsular Malaysia (Table 6 and Fig. 1). This finding might be attributable to the relatively small sizes of the Semang and Proto-Malay populations. As such, they are expected to be much more likely affected by selective forces and bottlenecks as compared with the larger Orang Asli group, the Senoi, or with other Malaysian subpopulations,

Table 3. HPA allele frequencies in Orang Asli subgroups and other reference populations

Population 1a 1b 2a 2b 3a 3b 4a 4b 5a 5b 6a 6b 15a 15b

Batek 1.000 0.000 1.000 0.000 0.500 0.500 1.000 0.000 0.852 0.148 1.000 0.000 0.000 1.000

Che Wong 1.000 0.000 1.000 0.000 0.423 0.577 1.000 0.000 0.788 0.212 1.000 0.000 0.500 0.500

Kensiu 0.958 0.042 1.000 0.000 0.875 0.125 1.000 0.000 0.847 0.153 1.000 0.000 0.361 0.639

Lanoh 1.000 0.000 1.000 0.000 0.640 0.360 1.000 0.000 1.000 0.000 1.000 0.000 0.260 0.740

Semai 0.988 0.012 1.000 0.000 0.671 0.329 1.000 0.000 0.890 0.110 1.000 0.000 0.524 0.476

Orang Kanaq 1.000 0.000 1.000 0.000 0.818 0.182 1.000 0.000 1.000 0.000 1.000 0.000 0.909 0.091

Champa15 0.980 0.020 0.970 0.030 0.677 0.323 1.000 0.000 0.990 0.010 0.980 0.020 0.480 0.520

Kelantan15 1.000 0.000 0.940 0.060 0.571 0.429 1.000 0.000 1.000 0.000 0.990 0.010 0.490 0.510

Banjar15 1.000 0.000 0.950 0.050 0.616 0.384 0.950 0.050 0.950 0.050 0.980 0.020 0.480 0.520

Bugis15 1.000 0.000 1.000 0.000 0.554 0.446 1.000 0.000 0.950 0.050 0.910 0.090 0.620 0.380

Jawa15 1.000 0.000 1.000 0.000 0.628 0.372 1.000 0.000 0.960 0.040 1.000 0.000 0.450 0.550

Malays16 0.975 0.025 0.963 0.037 0.503 0.497 0.995 0.005 0.950 0.050 0.993 0.007 0.515 0.485

Chinese16 1.000 0.000 0.967 0.033 0.573 0.427 0.998 0.002 0.983 0.017 0.983 0.017 0.498 0.502

Indians16 0.885 0.115 0.960 0.040 0.620 0.380 0.995 0.005 0.940 0.060 0.995 0.005 0.408 0.592

Kinh Vietnam23 0.986 0.014 0.953 0.047 0.486 0.514 1.000 0.000 0.972 0.028 0.986 0.014 0.523 0.477

Australian Aboriginal7 0.997 0.003 1.000 0.000 0.932 0.068 1.000 0.000 0.754 0.246 NA NA NA NA

Chinese Han13 0.994 0.006 0.952 0.048 0.595 0.405 0.995 0.005 0.986 0.014 0.987 0.013 0.532 0.468

Minnan9 0.998 0.002 0.957 0.043 0.550 0.450 0.995 0.005 0.990 0.010 NA NA NA NA

Hakka9 1.000 0.000 0.970 0.030 0.602 0.398 0.996 0.004 0.996 0.004 NA NA NA NA

Atayal9 1.000 0.000 0.930 0.070 0.500 0.500 1.000 0.000 1.000 0.000 NA NA NA NA

Saisiat9 1.000 0.000 0.956 0.044 0.456 0.544 1.000 0.000 0.965 0.035 NA NA NA NA

Bunun9 1.000 0.000 0.989 0.011 0.417 0.583 1.000 0.000 1.000 0.000 NA NA NA NA

Tsou9 1.000 0.000 1.000 0.000 0.245 0.755 1.000 0.000 0.980 0.020 NA NA NA NA

Rukai9 1.000 0.000 0.970 0.030 0.570 0.430 1.000 0.000 1.000 0.000 NA NA NA NA

Paiwan9 1.000 0.000 1.000 0.000 0.667 0.333 1.000 0.000 1.000 0.000 NA NA NA NA

Ami9 1.000 0.000 0.995 0.005 0.495 0.505 1.000 0.000 0.975 0.026 NA NA NA NA

Yami9 1.000 0.000 1.000 0.000 0.566 0.434 1.000 0.000 0.984 0.016 NA NA NA NA

Pazeh9 1.000 0.000 0.960 0.040 0.610 0.390 0.990 0.010 0.980 0.020 NA NA NA NA

Maori24 0.968 0.032 0.947 0.053 0.564 0.436 1.000 0.000 1.000 0.000 1.000 0.000 0.362 0.638

Polynesian24 0.980 0.020 0.920 0.080 0.720 0.280 1.000 0.000 0.940 0.060 0.900 0.100 0.300 0.700

Wales8 0.825 0.175 0.902 0.098 0.607 0.393 1.000 0.000 0.903 0.097 1.000 0.000 NA NA

Italy1 0.850 0.150 0.980 0.110 0.610 0.390 1.000 0.000 0.900 0.100 1.000 0.000 NA NA

UK6 0.840 0.160 0.925 0.075 0.627 0.373 1.000 0.000 0.914 0.086 1.000 0.000 NA NA

Australian7 0.858 0.142 0.927 0.073 0.599 0.401 1.000 0.000 0.905 0.095 NA NA NA NA

HPA = human platelet antigen; NA = not available.


Table 4. HPA allele frequencies for the smaller subsamples of unrelated Orang Asli individuals

Population 1a 1b 2a 2b 3a 3b 4a 4b 5a 5b 6a 6b 15a 15b

uBatek 1.000 0.000 1.000 0.000 0.471 0.529 1.000 0.000 0.882 0.118 1.000 0.000 0.000 1.000

uChe Wong 1.000 0.000 1.000 0.000 0.393 0.607 1.000 0.000 0.786 0.214 1.000 0.000 0.500 0.500

uKensiu 0.929 0.071 1.000 0.000 0.905 0.095 1.000 0.000 0.833 0.167 1.000 0.000 0.357 0.643

uLanoh 1.000 0.000 1.000 0.000 0.615 0.385 1.000 0.000 1.000 0.000 1.000 0.000 0.231 0.769

uSemai 0.985 0.015 1.000 0.000 0.662 0.338 1.000 0.000 0.912 0.088 1.000 0.000 0.485 0.515

uOrang Kanaq 1.000 0.000 1.000 0.000 0.857 0.143 1.000 0.000 1.000 0.000 1.000 0.000 0.929 0.071

HPA = human platelet antigen; u = unrelated.


Table 5. Homogeneity tests (p values), based on HPA data, between pairs of Orang Asli subgroups and their smaller subsample of unrelated individuals

Batek uBatek Che Wong uChe Wong Kensiu uKensiu Lanoh uLanoh Semai uSemai Orang Kanaq uOrang Kanaq

HPA-1 Batek * * * * * * * * * * * *

uBatek NA * * * * * * * * * * *

Che Wong NA NA * * * * * * * * * *

uChe Wong NA NA NA * * * * * * * * *

Kensiu NA NA NA NA * * * * * * * *

uKensiu 0.533 NA 0.284 0.259 0.250 * * * * * * *

Lanoh NA NA NA NA NA 0.284 * * * * * *

uLanoh NA NA NA NA NA 0.270 NA * * * * *

Semai NA NA NA NA NA 0.551 NA NA * * * *

uSemai 1.000 1.000 1.000 1.000 1.000 0.150 1.000 1.000 1.000 * * *

Orang Kanaq NA NA NA NA NA 1.000 NA NA NA 1.000 * *

uOrang Kanaq NA NA NA NA NA 0.551 NA NA NA 1.000 NA *

HPA-3 Batek * * * * * * * * * * * *

uBatek 0.623 * * * * * * * * * * *

Che Wong 0.578 1.000 * * * * * * * * * *

uChe Wong 0.583 0.588 0.440 * * * * * * * * *

Kensiu <0.001 0.002 0.006 0.004 * * * * * * * *

uKensiu <0.001 <0.001 <0.001 <0.001 0.443 * * * * * * *

Lanoh 0.853 0.056 0.065 0.171 0.417 0.032 * * * * * *

uLanoh 0.861 0.065 0.084 0.245 0.197 0.034 1.000 * * * * *

Semai 0.633 0.044 0.011 0.159 0.376 0.024 0.533 0.324 * * * *

uSemai 0.625 0.039 0.013 0.090 0.269 0.028 1.000 0.827 0.619 * * *

Orang Kanaq 1.000 0.012 0.003 0.015 0.603 0.234 0.641 0.641 NA 1.000 * *

uOrang Kanaq 0.320 0.012 0.004 0.023 1.000 0.622 0.804 0.478 0.592 0.605 0.576 *

HPA-5 Batek * * * * * * * * * * * *

uBatek 0.415 * * * * * * * * * * *

Che Wong 1.000 0.422 * * * * * * * * * *

uChe Wong 0.816 0.544 0.832 * * * * * * * * *

Kensiu 0.667 1.000 0.448 0.833 * * * * * * * *

uKensiu 1.000 0.721 0.716 0.675 0.729 * * * * * * *

Lanoh 0.050 0.121 0.050 0.064 0.106 0.050 * * * * * *

uLanoh 0.050 0.113 0.050 0.066 0.102 0.050 NA * * * * *

Semai 1.000 1.000 0.656 1.000 1.000 1.000 0.123 0.111 * * * *

uSemai 0.199 0.714 0.124 0.157 0.702 0.208 0.317 0.167 0.606 * * *

Orang Kanaq 0.251 0.546 0.245 0.626 0.530 0.294 NA NA NA 1.000 * *

uOrang Kanaq 0.103 0.283 0.106 0.349 0.263 0.141 NA NA 0.462 0.567 NA *



Table 5. Continued.Batek uBatek Che Wong uChe Wong Kensiu uKensiu Lanoh uLanoh Semai uSemai Orang Kanaq uOrang Kanaq

HPA-15 Batek * * * * * * * * * * * *

uBatek NA * * * * * * * * * * *

Che Wong <0.001 <0.001 * * * * * * * * * *

uChe Wong <0.001 <0.001 1.000 * * * * * * * * *

Kensiu 0.001 <0.001 0.263 0.208 * * * * * * * *

uKensiu 0.003 <0.001 0.163 0.099 1.000 * * * * * * *

Lanoh 0.007 0.001 <0.001 0.004 0.225 1.000 * * * * * *

uLanoh 0.037 0.026 <0.001 0.001 0.050 0.078 0.245 * * * * *

Semai 0.001 <0.001 0.029 0.017 0.073 0.109 0.115 0.060 * * * *

uSemai 0.001 <0.001 0.034 0.011 0.180 0.215 0.398 0.086 0.456 * * *

Orang Kanaq 0.001 <0.001 0.027 0.019 0.017 0.022 0.024 0.036 0.014 0.007 * *

uOrang Kanaq <0.001 <0.001 0.002 0.001 0.001 0.001 0.005 0.003 0.034 0.019 1.000 *

Only polymorphic HPA systems were subjected to this analysis. HPA = human platelet antigen; u = unrelated; NA = not applicable.

Table 6. Homogeneity tests (p value), based on HPA data, between Orang Asli and other subpopulations in Peninsular Malaysia

Batek Che Wong Kensiu Lanoh Semai Orang Kanaq Banjar* Bugis* Champa* Jawa* Kelantan* Malays** Chinese**

HPA-1 Batek — — — — — — — — — — — — —

Che Wong NA — — — — — — — — — — — —

Kensiu NA NA — — — — — — — — — — —

Lanoh NA NA NA — — — — — — — — — —

Semai NA NA NA NA — — — — — — — — —

Orang Kanaq NA NA NA NA NA — — — — — — — —

Banjar* NA NA NA NA NA NA — — — — — — —

Bugis* NA NA NA NA NA NA NA — — — — — —

Champa* NA NA NA NA NA NA 0.528 0.507 — — — — —

Jawa* NA NA NA NA NA NA NA NA 0.503 — — — —

Kelantan* NA NA NA NA NA NA NA NA 0.512 NA — — —

Malays** NA NA NA NA NA NA NA NA NA NA NA — —

Chinese** NA NA NA NA NA NA NA NA NA NA NA NA —

Indians** 0.023 0.026 0.149 0.030 0.012 0.207 0.015 0.006 0.010 0.004 0.004 <0.001 <0.001

HPA-2 Batek — — — — — — — — — — — — —

Che Wong NA — — — — — — — — — — — —

Kensiu NA NA — — — — — — — — — — —

Lanoh NA NA NA — — — — — — — — — —

Semai NA NA NA NA — — — — — — — — —



Bugis* NA NA NA NA NA NA 0.085 — — — — — —

Champa* 0.016 0.593 0.486 0.604 0.448 0.800 0.199 1.000 — — — — —

Jawa* NA NA NA NA NA NA 0.077 NA 1.000 — — — —

Kelantan* NA NA NA NA NA NA 0.034 0.051 0.153 0.046 — — —

Malays** 0.315 0.328 0.215 0.343 0.174 0.623 NA NA 0.051 NA NA — —

Chinese** 0.425 0.439 0.321 0.453 0.274 0.705 0.481 0.343 0.278 0.347 0.362 0.544 —

Indians** 0.338 0.352 0.237 0.366 0.194 0.641 0.542 0.270 0.201 0.276 0.422 1.000 0.840



Table 6. Continued.


HPA-3 Batek — — — — — — — — — — — — —

Che Wong 0.655 — — — — — — — — — — — —

Kensiu <0.001 0.006 — — — — — — — — — — —

Lanoh 0.853 0.065 0.417 — — — — — — — — — —

Semai 0.633 0.011 0.376 0.533 — — — — — — — — —

Orang Kanaq 1.000 0.003 0.603 0.641 0.356 — — — — — — — —

Banjar* 0.195 0.055 0.004 0.690 NA 0.235 — — — — — — —

Bugis* 0.001 <0.001 0.001 0.284 0.018 0.065 0.015 — — — — — —

Champa* 0.016 0.003 0.017 0.895 0.661 0.364 0.643 0.025 — — — — —

Jawa* 0.155 0.030 0.005 0.491 0.935 0.279 1.000 0.007 0.625 — — — —

Kelantan* 0.454 0.188 <0.001 0.367 0.428 0.096 0.801 0.002 0.181 0.705 — — —

Malays** 0.534 0.333 <0.001 0.041 0.014 0.010 0.190 <0.001 0.001 0.093 0.557 — —

Chinese** 0.274 0.078 <0.001 0.251 0.241 0.075 0.758 <0.001 0.058 0.659 0.949 0.127 —

Indians** 0.114 0.018 <0.001 0.409 0.672 0.180 0.965 <0.001 0.226 0.971 0.726 0.003 0.394

HPA-4 Batek — — — — — — — — — — — — —

Che Wong NA — — — — — — — — — — — —

Kensiu NA NA — — — — — — — — — — —

Lanoh NA NA NA — — — — — — — — — —

Semai NA NA NA NA — — — — — — — — —




Champa* NA NA NA NA NA NA 0.048 NA — — — — —

Jawa* NA NA NA NA NA NA 0.077 NA NA — — — —

Kelantan* NA NA NA NA NA NA 0.093 NA NA NA — — —

Malays** NA NA NA NA NA NA <0.001 NA NA NA NA — —

Chinese** NA NA NA NA NA NA NA NA NA NA NA 0.368 —

Indians** NA NA NA NA NA NA NA NA NA NA NA 0.368 NA

HPA-5 Batek — — — — — — — — — — — — —

Che Wong 1.000 — — — — — — — — — — — —

Kensiu 0.667 0.448 — — — — — — — — — — —

Lanoh 0.050 0.050 0.106 — — — — — — — — — —

Semai 1.000 0.656 1.000 0.123 — — — — — — — — —

Orang Kanaq 0.251 0.245 0.530 NA NA — — — — — — — —

Banjar* NA 0.038 NA NA NA NA — — — — — — —

Bugis* NA 0.028 NA NA NA NA 0.684 — — — — — —

Champa* NA <0.001 NA NA NA NA 0.552 0.157 — — — — —

Jawa* NA 0.009 NA NA NA NA 0.027 0.221 0.312 — — — —

Kelantan* NA <0.001 NA NA NA NA 0.209 0.115 1.000 0.242 — — —

Malays** NA <0.001 NA NA NA NA NA NA NA NA NA — —

Chinese** NA <0.001 NA NA NA NA NA NA NA NA NA NA —

Indians** 0.026 0.001 0.007 0.202 0.296 0.492 0.914 0.910 0.117 0.745 0.107 0.571 0.009



Table 6. Continued.


HPA-6 Batek — — — — — — — — — — — — —

Che Wong NA — — — — — — — — — — — —

Kensiu NA NA — — — — — — — — — — —

Lanoh NA NA NA — — — — — — — — — —

Semai NA NA NA NA — — — — — — — — —




Champa* NA NA NA NA NA NA 1.000 0.020 — — — — —

Jawa* NA NA NA NA NA NA 0.435 0.011 1.000 — — — —

Kelantan* NA NA NA NA NA NA 1.000 0.262 0.564 0.220 — — —

Malays** NA NA NA NA NA NA NA NA NA NA NA — —

Chinese** NA NA NA NA NA NA NA NA NA NA NA NA —

Indians** NA NA NA NA NA NA NA NA NA NA NA NA NA

HPA-15 Batek — — — — — — — — — — — — —

Che Wong <0.001 — — — — — — — — — — — —

Kensiu 0.001 0.263 — — — — — — — — — — —

Lanoh 0.007 <0.001 0.225 — — — — — — — — — —

Semai 0.001 0.029 0.073 0.115 — — — — — — — — —

Orang Kanaq 0.001 0.027 0.017 0.024 0.014 — — — — — — — —

Banjar* <0.001 <0.001 0.022 0.071 0.686 0.014 — — — — — — —

Bugis* <0.001 0.001 0.003 0.002 0.445 0.064 0.264 — — — — — —

Champa* <0.001 0.001 0.081 0.058 0.625 0.003 0.602 0.022 — — — — —

Jawa* <0.001 0.084 0.476 0.049 0.739 <0.001 0.047 0.027 0.209 — — — —

Kelantan* <0.001 0.002 0.014 0.009 0.085 0.028 0.445 0.851 0.558 0.091 — — —

Malays** <0.001 0.009 0.042 0.001 0.160 <0.001 0.055 0.078 0.258 0.438 0.269 — —

Chinese** <0.001 0.011 0.078 0.003 0.130 <0.001 0.048 0.046 0.257 0.598 0.185 0.870 —

Indians** <0.001 0.001 0.304 0.168 0.067 <0.001 0.109 0.002 0.334 0.303 0.040 0.005 0.017

HPA = human platelet antigen. *Data from previous study; NA = not applicable.15 **Data from previous study.16

such as Indians and Malays. All these effects are also well demonstrated by the reduced genetic diversity in Batek and Proto-Malays. The Batek were also observed to be fixed for HPA-15b and subsequently have the highest frequency for this allele compared with all other populations that we have characterized for the HPA-15 locus (Tables 1 and 3).

There are obvious genetic similarities and differences between Orang Asli and other major subpopulations in Peninsular Malaysia (Table 6 and Fig. 1); these are expected because of the different origins of their founding ancestors.17–20 The genetic complexity in Peninsular Malaysia is medically

important, since HPAs have been implicated in pathogeneses of NAIT,26 PTP,27 and PTR.28 This complexity might create a real high-risk scenario in Malaysia, as shown by the high probability of transfusion and gestation alloimmunization, particularly between pairs of donors or parents from different ethnic backgrounds (relative risk figures are shown in Tables 7–20). Study of PTR and NAIT in Malay, Chinese, and Indian patients showed the predominance of anti-HPA-3a together with lesser contributions from anti-HPA-1a, -5b, and -15b detected in patients with NAIT, associated with mild thrombocytopenia.29 Anti-HPA-5b was also reported



Table 8. Hypothetical transfusion and gestation HPA alloimmunization risks between pairs of Che Wong and other Malaysian subpopulations

HPA Transfusion Gestation

W>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I W>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I

1a 0/0/0.001/0/0/0.001/0/0/0/0/0/0/0/0.013 0/0/0.009/0/0.009/0/0/0/0/0/0/0/0/0.012

1b 0/0/0.075/0/0.039/0/0/0/0.038/0/0/0.047/0/0.172 0/0/0.039/0/0.012/0/0/0/0.019/0/0/0.024/0/0.090

2a 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002 0/0/0/0/0/0/0.003/0/0.971/0/0.003/0.001/0.001/0.002

2b 0/0/0/0/0/0/0.090/0/0.054/0/0.099/0.068/0.061/0.072 0/0/0/0/0/0/0.045/0/0.029/0/0.051/0.034/0.031/0.037

3a 0.188/0.222/0.016/0.113/0.096/0.032/0.125/0.159/0.093/0.119/0.150/0.186/0.149/0.123 0.125/0.141/0.014/0.083/0.072/0.027/0.091/0.110/0.070/0.087/0.105/0.124/0.104/0.089

3b 0.147/0.188/0.179/0.241/0.248/0.221/0.235/0.213/0.248/0.239/0.220/0.189/0.220/0.238 0.125/0.103/0.096/0.148/0.148/0.122/0.145/0.137/0.148/0.147/0.140/0.126/0.140/0.146

4a 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0

4b 0/0/0/0/0/0/0.090/0/0/0/0/0.001/0.004/0.010 0/0/0/0/0/0/0.045/0/0/0/0/0.005/0.002/0.005

5a 0.022/0.042/0.022/0/0.012/0/0.003/0.003/0/0.001/0/0.003/0/0.004 0.019/0.035/0.019/0/0.011/0/0.003/0.003/0/0.001/0/0.003/0/0.004

5b 0.199/0.235/0.203/0/0.165/0/0.090/0.094/0.010/0.069/0/0.088/0.033/0.103 0.107/0.132/0.100/0/0.087/0/0.045/0.048/0.010/0.035/0/0.045/0.016/0.053

6a 0/0/0/0/0/0/0/0.009/0/0/0.001/0/0/0 0/0/0/0/0/0/0/0.008/0/0/0.001/0/0/0

6b 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020

15a 0/0.188/0.242/0.248/0.175/0.008/0.182/0.123/0.197/0.212/0.150/0.180/0.188/0.228 0/0.125/0.147/0.142/0.119/0.007/0.115/0.089/0.130/0.136/0.105/0.121/0.125/0.143

15b 0/0.188/0.113/0.063/0.199/0.144/0.142/0.237/0.177/0.161/0.220/0.195/0.190/0.238 0/0.125/0.083/0.050/0.131/0.075/0.196/0.054/0.120/0.111/0.140/0.129/0.127/0.098

The Che Wong subgroup was assumed as donor and father populations for transfusion and gestation, respectively. HPA data for Banjar, Bugis, Champa, Jawa, Kelantan, Malays, Chinese, and Indians were obtained from Wan Syafawati et al.15 and Tan et al.16 HPA = human platelet antigen; B = Batek; W = Che Wong; K = Kensiu; L = Lanoh; S = Semai; O = Orang Kanaq; BA = Banjar; BU = Bugis; C = Champa; J = Jawa; KE = Kelantan; M = Malays; CH = Chinese; I = Indians; > = donor to recipient and father to mother population for random platelet transfusion and gestation, respectively.

Table 7. Hypothetical transfusion and gestation HPA alloimmunization risks between pairs of Batek and other Malaysian subpopulations


B>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I B>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I

1a 0/0/0.009/0/0.009/0/0/0/0/0/0/0/0/0.013 0/0/0.001/0/0.001/0/0/0/0/0/0/0/0/0.012

1b 0/0/0.075/0/0.039/0/0/0/0.038/0/0/0.047/0/0.172 0/0/0.039/0/0.012/0/0/0/0.019/0/0/0.024/0/0.090

2a 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002 0/0/0/0/0/0/0.003/0/0.971/0/0.003/0.001/0.001/0.002

2b 0/0/0/0/0/0/0.090/0/0.054/0/0.099/0.068/0.061/0.072 0/0/0/0/0/0/0.045/0/0.029/0/0.051/0.034/0.031/0.037

3a 0.188/0.222/0.016/0.241/0.096/0.032/0.125/0.159/0.093/0.119/0.150/0.186/0.149/0.123 0.125/0.141/0.014/0.083/0.072/0.027/0.091/0.110/0.070/0.087/0.105/0.124/0.104/0.089

3b 0.188/0.147/0.179/0.241/0.248/0.221/0.235/0.213/0.248/0.239/0.220/0.189/0.220/0.238 0.125/0.103/0.096/0.148/0.148/0.122/0.145/0.137/0.148/0.147/0.140/0.126/0.140/0.146

4a 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0

4b 0/0/0/0/0/0/0.090/0/0/0/0/0.001/0.004/0.010 0/0/0/0/0/0/0.045/0/0/0/0/0.005/0.002/0.005

5a 0.022/0.042/0.022/0/0.012/0/0.003/0.003/0/0.001/0/0.003/0/0.004 0.019/0.035/0.019/0/0.011/0/0.003/0.003/0/0.001/0/0.003/0/0.004

5b 0.199/0.235/0.203/0/0.165/0/0.090/0.094/0.010/0.069/0/0.088/0.033/0.103 0.107/0.132/0.100/0/0.087/0/0.045/0.048/0.010/0.035/0/0.045/0.016/0.053

6a 0/0/0/0/0/0/0/0.009/0/0/0.001/0/0/0 0/0/0/0/0/0/0/0.008/0/0/0.001/0/0/0

6b 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020 0/0/0/0/0/0/0.0160/0.078/0.010/0/0.027/0.007/0.016/0.005

15a 0/0.188/0.242/0.248/0.175/0.008/0.182/0.123/0.197/0.212/0.150/0.180/0.188/0.228 0/0.125/0.147/0.142/0.119/0.007/0.115/0.089/0.130/0.136/0.105/0121/0.125/0.143

15b 0/0.188/0.113/0.063/0.199/0.144/0.142/0.237/0.177/0.161/0.220/0.195/0.190/0.238 0/0.125/0.083/0.050/0.131/0.075/0.196/0.054/0.120/0.111/0.140/0.129/0.127/0.098

The Batek subgroup is assumed as donor and father populations for transfusion and gestation, respectively. HPA data for Banjar, Bugis, Champa, Jawa, Kelantan, Malays, Chinese, and Indians were obtained from Wan Syafawati et al.15 and Tan et al.16 HPA = human platelet antigen; B = Batek; W = Che Wong; K = Kensiu; L = Lanoh; S = Semai; O = Orang Kanaq; BA = Banjar; BU = Bugis; C = Champa; J = Jawa; KE = Kelantan; M = Malays; CH = Chinese; I = Indians; > = donor to recipient and father to mother population for random platelet transfusion and gestation, respectively.



Table 9. Hypothetical transfusion and gestation HPA alloimmunization risks between pairs of Kensiu and other Malaysian subpopulations


K>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I K>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I

1a 0/0/0.001/0/0.001/0/0/0/0/0/0/0/0/0.013 0/0/0.009/0/0.009/0/0/0/0/0/0/0/0/0.012

1b 0/0/0.075/0/0.039/0/0/0/0.038/0/0/0.047/0/0.172 0/0/0.039/0/0.012/0/0/0/0.019/0/0/0.024/0/0.090

2a 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002 0/0/0/0/0/0/0.003/0/0.971/0/0.003/0.001/0.001/0.002

2b 0/0/0/0/0/0/0.090/0/0.054/0/0.099/0.068/0.061/0.072 0/0/0/0/0/0/0.045/0/0.029/0/0.051/0.034/0.031/0.037

3a 0.188/0.222/0.016/0.113/0.096/0.032/0.125/0159/0.093/0.119/0.150/0.186/0.149/0.123 0.125/0.141/0.014/0.083/0.072/0.027/0.091/0.110/0.070/0.087/ 0.105/0.124/0.104/0.089

3b 0.188/0.147/0.179/0.241/0.248/0.221/0.235/0.213/0.248/0.239/0.220/0.189/0.220/0.238 0.125/0.103/0.096/0.148/0.148/0.122/0.145/0.137/0.148/0.147/ 0.140/0.126/0.140/0.146

4a 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0

4b 0/0/0/0/0/0/0.090/0/0/0/0/0.001/0.004/0.010 0/0/0/0/0/0/0.045/0/0/0/0/0.005/0.002/0.005

5a 0.022/0.042/0.022/0/0.012/0/0.003/0.003/0/0.001/0/0.003/0/0.004 0.019/0.035/0.019/0/0.011/0/.003/0.003/0/0.001/0/0.003/0/0.004

5b 0.199/0.235/0.203/0/0.165/0/0.090/0.094/0.010/0.069/0/0.088/0.033/0.103 0.107/0.132/0.100/0/0.087/0/0.045/0.048/0.010/0.035/0/0.045/0.016/0.053

6a 0/0/0/0/0/0/0/0.009/0/0/0.001/0/0/0 0/0/0/0/0/0/0/0.008/0/0/0.001/0/0/0

6b 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020

15a 0/0.188/0.242/0.248/0.175/0.008/0.182/0.123/0.197/0.212/0.150/0.180/0.188/0.228 0/0.125/0.147/0.142/0.119/0.007/0.115/0.089/0.130/0.136/0.105/0121/0.125/0.143

15b 0/0.188/0.113/0.199/0.144/0.063/0.142/0.237/0.177/0.161/0.220/0.195/0.190/0.238 0/0.125/0.083/0.050/0.131/0.075/0.196/0.054/0.120/0.111/0.140/0.129/0.127/0.098

The Kensiu subgroup is assumed as donor and father populations for transfusion and gestation, respectively. HPA data for Banjar, Bugis, Champa, Jawa, Kelantan, Malays, Chinese, and Indians were obtained from Wan Syafawati et al.15 and Tan et al.16 HPA = human platelet antigen; B = Batek; W = Che Wong; K = Kensiu; L = Lanoh; S = Semai; O = Orang Kanaq; BA = Banjar; BU = Bugis; C = Champa; J = Jawa; KE = Kelantan; M = Malays; CH = Chinese; I = Indians; > = donor to recipient and father to mother population for random platelet transfusion and gestation, respectively.

Table 10. Hypothetical transfusion and gestation HPA alloimmunization risks between pairs of Lanoh and other Malaysian subpopulations


L>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I L>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I

1a 0/0/0.001/0/0.001/0/0/0/0/0/0/0/0/0.013 0/0/0.009/0/0.009/0/0/0/0/0/0/0/0/0.012

1b 0/0/0.075/0/0.039/0/0/0/0.038/0/0/0.047/0/0.172 0/0/0.039/0/0.012/0/0/0/0.019/0/0/0.024/0/0.090

2a 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002 0/0/0/0/0/0/0.003/0/0.971/0/0.003/0.001/0.001/0.002

2b 0/0/0/0/0/0/0.090/0/0.054/0/0.099/0.068/0.061/0.072 0/0/0/0/0/0/0.045/0/0.029/0/0.051/0.034/0.031/0.037

3a 0.188/0.222/0.016/0.113/0.096/0.032/0.125/0.159/0.093/0.119/0.150/0.186/0.149/0.123 0.125/0.141/0.014/0.083/0.072/0.027/0.091/0.110/0.070/0.087/0.105/0.124/0.104/0.089

3b 0.188/0.222/0.016/0.241/0.248/0.032/0.235/0.213/0.248/0.239/0.220/0.189/0.220/0.238 0.125/0.103/0.096/0.148/0.148/0.122/0.145/0.137/0.148/0.147/0.140/0.126/0.140/0.146

4a 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0

4b 0/0/0/0/0/0/0.090/0/0/0/0/0.001/0.004/0.010 0/0/0/0/0/0/0.045/0/0/0/0/0.005/0.002/0.005

5a 0.022/0.042/0.022/0/0.012/0/0.003/0.003/0/0.001/0/0.003/0/0.004 0.019/0.035/0.019/0/0.011/0/0.003/0.003/0/0.001/0/0.003/0/0.004

5b 0.199/0.235/0.203/0/0.165/0/0.090/0.094/0.010/0.069/0/0.088/0.033/0.103 0.107/0.132/0.100/0/0.087/0/0.045/0.048/0.010/0.035/0/0.045/0.016/0.053

6a 0/0/0/0/0/0/0/0.009/0/0/0.001/0/0/0 0/0/0/0/0/0/0/0.008/0/0/0.001/0/0/0

6b 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020

15a 0/0.188/0.242/0.248/0.175/0.008/0.182/0.123/0.197/0.212/0.150/0.180/0.188/0.228 0/0.125/0.147/0.050/0.119/0.007/0.115/0.089/0.130/0.136/0.105/0.121/0.125/0.143

15b 0/0.188/0.113/0.063/0.199/0.144/0.142/0.237/0.177/0.161/0.220/0.195/0.190/0.238 0/0.125/0.083/0.050/0.131/0.075/0.196/0.054/0.120/0.111/0.140/0.129/0.127/0.098

The Lanoh subgroup is assumed as donor and father populations for transfusion and gestation, respectively. HPA data for Banjar, Bugis, Champa, Jawa, Kelantan, Malays, Chinese, and Indians were obtained from Wan Syafawati et al.15 and Tan et al.16 HPA = human platelet antigen; B = Batek; W = Che Wong; K = Kensiu; L = Lanoh; S = Semai; O = Orang Kanaq; BA = Banjar; BU = Bugis; C = Champa; J = Jawa; KE = Kelantan; M = Malays; CH = Chinese; I = Indians; > = donor to recipient and father to mother population for random platelet transfusion and gestation, respectively.



Table 11. Hypothetical transfusion and gestation HPA alloimmunization risks between pairs of Semai and other Malaysian subpopulations


S>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I S>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I

1a 0/0/0.001/0/0.001/0/0/0/0/0/0/0/0/0.013 0/0/0.009/0/0.009/0/0/0/0/0/0/0/0/0.012

1b 0/0/0.075/0/0.039/0/0/0/0.038/0/0/0.047/0/0.172 0/0/0.039/0/0.012/0/0/0/0.019/0/0/0.024/0/0.09

2a 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002 0/0/0/0/0/0/0.003/0/0.971/0/0.003/0.001/0.001/0.002

2b 0/0/0/0/0/0/0.090/0/0.054/0/0.099/0.068/0.061/0.072 0/0/0/0/0/0/0.045/0/0.029/0/0.051/0.034/0.031/0.037

3a 0.188/0.222/0.016/0.113/0.096/0.032/0.125/0.159/0.093/0.119/0.150/0.186/0.149/0.123 0.125/0.141/0.014/0.083/0.072/0.027/0.091/0.110/0.070/0.087/0.105/0.124/0.104/0.089

3b 0.188/0.147/0.179/0.241/0.248/0.221/0.235/0.213/0.248/0.239/0.220/0.189/0.220/0.238 0.125/0.103/0.148/0.122/0.148/0.096/0.145/0.137/0.148/0.147/0.140/0.126/0.140/0.146

4a 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0

4b 0/0/0/0/0/0/0.090/0/0/0/0/0.001/0.004/0.010 0/0/0/0/0/0/0.045/0/0/0/0/0.005/0.002/0.005

5a 0.022/0.042/0.022/0/0.012/0/0.003/0.003/0/0.001/0/0.003/0/0.004 0.019/0.035/0.019/0/0.011/0/0.003/0/0.001/0/0.003/0/0.004

5b 0.199/0.235/0.203/0/0.165/0/0.090/0.094/0.010/0.069/0/0.088/0.033/0.103 0.107/0.132/0.100/0/0.087/0/0.045/0.048/0.010/0.035/0/0.045/0.016/0.053

6a 0/0/0/0/0/0/0/0.009/0/0/0.001/0/0/0 0/0/0/0/0/0/0/0.008/0/0/0.001/0/0/0

6b 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020

15a 0/0.188/0.242/0.248/0.175/0.008/0.182/0.123/0.197/0.212/0.150/0.180/0.188/0.228 0/0.125/0.147/0.142/0.119/0.007/0.115/0.089/0.130/0.136/0.105/0.121/0.125/0.143

15b 0/0.188/0.113/0.063/0.199/0.144/0.142/0.237/0.177/0.161/0.220/0.195/0.190/0.238 0/0.125/0.083/0.050/0.131/0.075/0.196/0.054/0.120/0.111/0.140/0.129/0.127/0.098

The Semai subgroup is assumed as donor and father populations for transfusion and gestation, respectively. HPA data for Banjar, Bugis, Champa, Jawa, Kelantan, Malays, Chinese, and Indians were obtained from Wan Syafawati et al.15 and Tan et al.16 HPA = human platelet antigen; B = Batek; W = Che Wong; K = Kensiu; L = Lanoh; S = Semai; O = Orang Kanaq; BA = Banjar; BU = Bugis; C = Champa; J = Jawa; KE = Kelantan; M = Malays; CH = Chinese; I = Indians; > = donor to recipient and father to mother population for random platelet transfusion and gestation, respectively.

Table 12. Hypothetical transfusion and gestation HPA alloimmunization risks between pairs of Orang Kanaq and other Malaysian subpopulations


O>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I O>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I

1a 0/0/0.001/0/0.001/0/0/0/0/0/0/0/0/0.013 0/0/0.009/0/0.009/0/0/0/0/0/0/0/0/0.012

1b 0/0/0.075/0/0.039/0/0/0/0.038/0/0/0.047/0/0.172 0/0/0.390/0/0.012/0/0/0/0.019/0/0/0.024/0/0.090

2a 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002 0/0/0/0/0/0/0.003/0/0.971/0/0.003/0.001/0.001/0.002

2b 0/0/0/0/0/0/0.090/0/0.054/0/0.099/0.068/0.061/0.072 0/0/0/0/0/0/0.045/0/0.029/0/0.051/0.034/0.031/0.037

3a 0.188/0.222/0.016/0.113/0.096/0.032/0.125/0.159/0.093/0.119/0.150/0.186/0.149/0.123 0.125/0.141/0.014/0.083/0.072/0.027/0.091/0.110/0.070/0.087/0.105/0.124/0.104/0.089

3b 0.188/0.147/0.179/0.241/0.248/0.221/0.235/0.213/0.248/0.239/0.220/0.189/0.220/0.238 0.125/0.103/0.096/0.148/0.148/0.122/0.145/0.137/0.148/0.147/0.140/0.126/0.140/0.146

4a 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0

4b 0/0/0/0/0/0/0.090/0/0/0/0/0.001/0.004/0.010 0/0/0/0/0/0/0.045/0/0/0/0/0.005/0.002/0.005

5a 0.022/0.042/0.022/0/0.012/0/0.003/0.003/0/0.001/0/0.003/0/0.004 0.019/0.035/0.019/0/0.011/0/0.003/0.003/0/0.001/0/0.003/0/0.004

5b 0.199/0.235/0.203/0/0.165/0/0.090/0.094/0.010/0.069/0/0.088/0.033/0.103 0.107/0.132/0.100/0/0.087/0/0.045/0.048/0.010/0.035/0/0.045/0.016/0.053

6a 0/0/0/0/0/0/0/0.009/0/0/0.001/0/0/0 0/0/0/0/0/0/0/0.008/0/0/0.001/0/0/0

6b 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020

15a 0/0.188/0.242/0.248/0.175/0.008/0.182/0.123/0.197/0.212/0.150/0.180/0.188/0.228 0/0.125/0.083/0.050/0.131/0.115/0.075/0.089/0.130/0.136/0.105/0.121/0.125/0.143

15b 0/0.188/0.113/0.063/0.199/0.144/0.142/0.237/0.177/0.161/0.220/0.195/0.190/0.238 0/0.125/0.083/0.050/0.131/0.075/0.196/0.054/0.120/0.111/0.140/0.129/0.127/0.098

The Orang Kanaq subgroup is assumed as donor and father populations for transfusion and gestation, respectively. HPA data for Banjar, Bugis, Champa, Jawa, Kelantan, Malays, Chinese, and Indians were obtained from Wan Syafawati et al.15 and Tan et al.16 HPA = human platelet antigen; B = Batek; W = Che Wong; K = Kensiu; L = Lanoh; S = Semai; O = Orang Kanaq; BA = Banjar; BU = Bugis; C = Champa; J = Jawa; KE = Kelantan; M = Malays; CH = Chinese; I = Indians; > = donor to recipient and father to mother population for random platelet transfusion and gestation, respectively.



Table 13. Hypothetical transfusion and gestation HPA alloimmunization risks between pairs of Banjar and other Malaysian subpopulations


BA>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I BA>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I

1a 0/0/0.009/0/0.009/0/0/0/0/0/0/0/0/0.013 0/0/0.001/0/0.001/0/0/0/0/0/0/0/0/0.012

1b 0/0/0.075/0/0.039/0/0/0/0.038/0/0/0.047/0/0.172 0/0/0.039/0/0.012/0/0/0/0.019/0/0/0.024/0/0.090

2a 0.002/0/0/0/0/0/0.003/0/0.001/0/0/0.003/0.001/0.001 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002

2b 0/0/0/0/0/0/0.090/0/0.054/0/0.099/0.068/0.061/0.072 0/0/0/0/0/0/0.045/0/0.027/0/0.051/0.034/0.031/0.037

3a 0.188/0.222/0.016/0.241/0.096/0.032/0.125/0.159/0.093/0.119/0.150/0.186/0.149/0.123 0.125/0.141/0.014/0.083/0.072/0.027/0.091/0.110/0.070/0.087/0.105/0.124/0.104/0.089

3b 0.188/0.147/0.179/0.241/0.248/0.221/0.235/0.213/0.248/0.239/0.220/0.189/0.220/0.238 0.125/0.103/0.096/0.148/0.148/0.122/0.145/0.137/0.148/0.147/0.140/0.126/0.140/0.146

4a 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0

4b 0/0/0/0/0/0/0.090/0/0/0/0/0.001/0.004/0.010 0/0/0/0/0/0/0.045/0/0/0/0/0.005/0.002/0.005

5a 0.022/0.042/0.022/0/0.012/0/0.003/0.003/0/0.001/0/0.003/0/0.004 0.019/0.035/0.019/0/0.011/0/0.003/0.003/0/0.001/0/0.003/0/0.004

5b 0.199/0.235/0.203/0/0.165/0/0.090/0.094/0.010/0.069/0/0.088/0.033/0.103 0.107/0.132/0.100/0/0.087/0/0.045/0.048/0.010/0.035/0/0.045/0.016/0.053

6a 0/0/0/0/0/0/0/0.009/0/0/0.001/0/0/0 0/0/0/0/0/0/0/0.008/0/0/0.001/0/0/0

6b 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020 0/0/0/0/0/0/0.016/0.078/0.010/0/0.027/0.007/0.016/0.005

15a 0/0.188/0.242/0.248/0.175/0.008/0.182/0.123/0.197/0.212/0.150/0.180/0.188/0.288 0/0.125/0.147/0.142/0.119/0.007/0.115/0.089/0.130/0.136/0.105/0.121/0.125/0.143

15b 0/0.188/0.113/0.063/0.199/0.144/0.142/0.237/0.177/0.161/0.220/0.195/0.190/0.138 0/0.125/0.083/0.050/0.131/0.075/0.096/0.054/0.120/0.111/0.140/0.129/0.127/0.098

The Banjar subgroup is assumed as donor and father populations for transfusion and gestation, respectively. HPA data for Banjar, Bugis, Champa, Jawa, Kelantan, Malays, Chinese, and Indians were obtained from Wan Syafawati et al.15 and Tan et al.16 HPA = human platelet antigen; B = Batek; W = Che Wong; K = Kensiu; L = Lanoh; S = Semai; O = Orang Kanaq; BA = Banjar; BU = Bugis; C = Champa; J = Jawa; KE = Kelantan; M = Malays; CH = Chinese; I = Indians; > = donor to recipient and father to mother population for random platelet transfusion and gestation, respectively.

Table 14. Hypothetical transfusion and gestation HPA alloimmunization risks between pairs of Bugis and other Malaysian subpopulations


BU>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I BU>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I

1a 0/0/0.009/0/0.009/0/0/0/0/0/0/0/0/0.013 0/0/0.001/0/0.001/0/0/0/0/0/0/0/0/0.012

1b 0/0/0.075/0/0.039/0/0/0/0.038/0/0/0.047/0/0.172 0/0/0.039/0/0.012/0/0/0/0.019/0/0/0.024/0/0.090

2a 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002

2b 0/0/0/0/0/0/0.090/0/0.054/0/0.099/0.068/0.061/0.072 0/0/0/0/0/0/0/0.045/0.027/0/0.051/0.034/0.031/0.037

3a 0.188/0.222/0.016/0.241/0.096/0.032/0.125/0.159/0.093/0.119/0.150/0.186/0.149/0.123 0.125/0.141/0.014/0.083/0.072/0.027/0.091/0.110/0.070/0.087/0.105/0.124/0.104/0.089

3b 0.188/0.147/0.179/0.241/0.248/0.221/0.235/0.213/0.248/0.239/0.220/0.189/0.220/0.238 0.125/0.103/0.096/0.148/0.148/0.122/0.145/0.137/0.148/0.147/0.140/0.126/0.140/0.146

4a 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0

4b 0/0/0/0/0/0/0.090/0/0/0/0/0.001/0.004/0.010 0/0/0/0/0/0/0.045/0/0/0/0/0.005/0.002/0.005

5a 0.004/0.022/0.042/0.022/0/0.012/0/0.003/0.003/0/0.001/0/0.003/0 0.019/0.035/0.019/0/0.011/0/0.003/0.003/0/0.001/0/0.003/0/0.004

5b 0.199/0.235/0.203/0/0.165/0/0.090/0.094/0.010/0.069/0/0.088/0.033/0.103 0.107/0.132/0.100/0/0.087/0/0.045/0.048/0/0.035/0/0.045/0.016/0.053

6a 0/0/0/0/0/0/0/0.009/0/0/0.001/0/0/0 0/0/0/0/0/0/0/0.008/0/0/0.001/0/0/0

6b 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020 0/0/0/0/0/0/0.016/0.078/0.010/0/0.027/0.007/0.016/0.005

15a 0/0.188/0.242/0.248/0.175/0.008/0.182/0.123/0.197/0.212/0.150/0.180/0.188/0.228 0/0.125/0.147/0.142/0.119/0.007/0.115/0.089/0.130/0.136/0.105/0.121/0.125/0.143

15b 0/0.188/0.113/0.063/0.199/0.144/0.142/0.237/0.177/0.161/0.220/0.195/0.190/0.138 0/0.125/0.083/0.050/0.131/0.075/0.096/0.054/0.120/0.111/0.140/0.129/0.127/0.098

The Bugis subgroup is assumed as donor and father populations for transfusion and gestation, respectively. HPA data for Banjar, Bugis, Champa, Jawa, Kelantan, Malays, Chinese, and Indians were obtained from Wan Syafawati et al.15 and Tan et al.16 HPA = human platelet antigen; B = Batek; W = Che Wong; K = Kensiu; L = Lanoh; S = Semai; O = Orang Kanaq; BA = Banjar; BU = Bugis; C = Champa; J = Jawa; KE = Kelantan; M = Malays; CH = Chinese; I = Indians; > = donor to recipient and father to mother population for random platelet transfusion and gestation, respectively.



Table 15. Hypothetical transfusion and gestation HPA alloimmunization risks between pairs of Champa and other Malaysian subpopulations


C>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I C>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I

1a 0/0/0.009/0/0.009/0/0/0/0/0/0/0/0/0.013 0/0/0.001/0/0.001/0/0/0/0/0/0/0/0/0.012

1b 0/0/0.075/0/0.039/0/0/0/0.038/0/0/0.047/0/0.172 0/0/0.039/0/0.012/0/0/0/0.019/0/0/0.024/0/0.090

2a 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002

2b 0/0/0/0/0/0/0.090/0/0.054/0/0.099/0.068/0.061/0.072 0/0/0/0/0/0/0.045/0/0.027/0/0.051/0.034/0.031/0.037

3a 0.188/0.222/0.016/0.241/0.096/0.032/0.125/0.159/0.093/0.119/0.150/0.186/0.149/0.123 0.125/0.141/0.014/0.083/0.072/0.027/0.091/0.110/0.070/0.087/0.105/0.124/0.104/0.089

3b 0.188/0.147/0.179/0.241/0.248/0.221/0.235/0.213/0.248/0.239/0.220/0.189/0.220/0.238 0.125/0.103/0.096/0.148/0.148/0.122/0.145/0.137/0.148/0.147/0.140/0.126/0.140/0.146

4a 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0 0/0/0/0/0/0/0/0.003/0/0/0/0/0/0

4b 0/0/0/0/0/0/0.090/0/0/0/0/0.001/0.004/0.010 0/0/0/0/0/0/0/0.045/0/0/0/0.005/0.002/0.005

5a 0.022/0.042/0.022/0/0.012/0/0.003/0.003/0/0.001/0/0.003/0/0.004 0.019/0.035/0.019/0/0.011/0/0.003/0.003/0/0.001/0/0.003/0/0.004

5b 0.199/0.235/0.203/0/0.165/0/0.090/0.094/0.010/0.069/0/0.088/0.033/0.103 0.107/0.132/0.100/0/0.087/0/0.045/0.048/0.010/0.035/0/0.045/0.016/0.053

6a 0/0/0/0/0/0/0/0.009/0/0/0.001/0/0/0 0/0/0/0/0/0/0/0.008/0/0/0.001/0/0/0

6b 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020 0/0/0/0/0/0/0.016/0.078/0.010/0/0.027/0.007/0.016/0.005

15a 0/0.188/0.242/0.248/0.175/0.008/0.182/0.123/0.197/0.212/0.150/0.180/0.188/0.228 0/0.125/0.147/0.142/0.119/0.007/0.115/0.089/0.130/0.136/0.105/0.121/0.125/0.143

15b 0/0.188/0.113/0.063/0.199/0.144/0.142/0.237/0.177/0.161/0.220/0.195/0.190/0.138 0/0.125/0.083/0.050/0.131/0.075/0.096/0.054/0.120/0.111/0.140/0.129/0.127/0.098

The Champa subgroup is assumed as donor and father populations for transfusion and gestation, respectively. HPA data for Banjar, Bugis, Champa, Jawa, Kelantan, Malays, Chinese, and Indians were obtained from Wan Syafawati et al.15 and Tan et al.16 HPA = human platelet antigen; B = Batek; W = Che Wong; K = Kensiu; L = Lanoh; S = Semai; O = Orang Kanaq; BA = Banjar; BU = Bugis; C = Champa; J = Jawa; KE = Kelantan; M = Malays; CH = Chinese; I = Indians; > = donor to recipient and father to mother population for random platelet transfusion and gestation, respectively.

Table 16. Hypothetical transfusion and gestation HPA alloimmunization risks between pairs of Jawa and other Malaysian subpopulations


J>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I J>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I

1a 0/0/0.009/0/0.009/0/0/0/0/0/0/0/0/0.013 0/0/0.001/0/0.001/0/0/0/0/0/0/0/0/0.012

1b 0/0/0.075/0/0.039/0/0/0/0.038/0/0/0.047/0/0.172 0/0/0.039/0/0.012/0/0/0/0.019/0/0/0.024/0/0.090

2a 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002

2b 0/0/0/0/0/0/0.090/0/0.054/0/0.099/0.068/0.061/0.072 0/0/0/0/0/0/0.045/0/0.027/0/0.051/0.034/0.031/0.037

3a 0.188/0.222/0.016/0.241/0.096/0.032/0.125/0.159/0.093/0.009/0.150/0.186/0.149/0.123 0.125/0.141/0.014/0.083/0.072/0.027/0.091/0.110/0.070/0.087/0.105/0.124/0.104/0.089

3b 0.188/0.147/0.179/0.241/0.248/0.221/0.235/0.213/0.248/0.239/0.220/0.189/0.220/0.238 0.125/0.103/0.096/0.148/0.148/0.122/0.145/0.137/0.148/0.147/0.140/0.126/0.140/0.146

4a 0/0/0/0/0/0/0/0.003/0/0/0/0/0/0 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0

4b 0/0/0/0/0/0/0/0.090/0/0/0/0.001/0.004/0.010 0/0/0/0/0/0/0.045/0/0/0/0/0.005/0.002/0.005

5a 0.022/0.042/0.022/0/0.012/0/0.003/0.003/0/0.001/0/0.003/0/0.004 0.019/0.035/0.019/0/0.011/0/0.003/0.003/0/0.001/0/0.003/0/0.004

5b 0.199/0.235/0.203/0/0.165/0/0.090/0.094/0.010/0.069/0/0.088/0.033/0.103 0.107/0.132/0.100/0/0.087/0/0.045/0.048/0.010/0.035/0/0.045/0.016/0.053

6a 0/0/0.009/0/0.001/0/0/0/0/0/0/0/0/0 0/0/0/0/0/0/0/0/0.008/0/0.001/0/0/0

6b 0.032/0.148/0.010/0/0.054/0.014/0.033/0.020/0/0/0/0/0/0 0/0/0/0/0/0/0.016/0.078/0.010/0/0.027/0.007/0.016/0.005

15a 0/0.188/0.242/0.248/0.175/0.008/0.182/0.123/0.197/0.212/0.150/0.180/0.188/0.228 0/0.125/0.147/0.142/0.119/0.007/0.115/0.089/0.130/0.136/0.105/0.121/0.125/0.143

15b 0/0.188/0.113/0.063/0.199/0.144/0.142/0.237/0.177/0.161/0.220/0.195/0.190/0.138 0/0.125/0.083/0.050/0.131/0.075/0.096/0.054/0.120/0.111/0.140/0.129/0.127/0.098

The Jawa subgroup is assumed as donor and father populations for transfusion and gestation, respectively. HPA data for Banjar, Bugis, Champa, Jawa, Kelantan, Malays, Chinese, and Indians were obtained from Wan Syafawati et al.15 and Tan et al.16 HPA = human platelet antigen; B = Batek; W = Che Wong; K = Kensiu; L = Lanoh; S = Semai; O = Orang Kanaq; BA = Banjar; BU = Bugis; C = Champa; J = Jawa; KE = Kelantan; M = Malays; CH = Chinese; I = Indians; > = donor to recipient and father to mother population for random platelet transfusion and gestation, respectively.



Table 17. Hypothetical transfusion and gestation HPA alloimmunization risks between pairs of Kelantan and other Malaysian subpopulations


KE>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I KE>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I

1a 0/0/0.009/0/0.009/0/0/0/0/0/0/0/0/0.013 0/0/0.001/0/0.001/0/0/0/0/0/0/0/0/0.012

1b 0/0/0.075/0/0.039/0/0/0/0.038/0/0.047/0/0/0.172 0/0/0.039/0/0.012/0/0/0/0/0.019/0/0.024/0/0.09

2a 0/0/0/0/0/0/0/0.001/0/0.003/0.003/0.001/0.001/0.002 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002

2b 0/0/0/0/0/0/0.090/0/0.054/0/0.099/0.068/0.061/0.072 0/0/0/0/0/0/0.045/0/0.027/0/0.051/0.034/0.031/0.037

3a 0.188/0.222/0.016/0.241/0.096/0.032/0.125/0.159/0.093/0.119/0.150/0.186/0.149/0.123 0.125/0.141/0.014/0.083/0.072/0.027/0.091/0.110/0.070/0.087/0.105/0.124/0.104/0.089

3b 0.188/0.147/0.179/0.241/0.248/0.221/0.235/0.213/0.248/0.239/0.220/0.189/0.220/0.238 0.125/0.103/0.096/0.148/0.148/0.122/0.145/0.137/0.148/0.147/0.140/0.126/0.140/0.146

4a 0/0/0/0/0/0/0/0.003/0/0/0/0/0/0 0/0/0/0/0/0/0/0.003/0/0/0/0/0/0

4b 0/0/0/0/0/0/0/0.090/0/0/0/0.001/0.004/0.010 0/0/0/0/0/0/0/0.045/0/0/0/0.005/0.002/0.005

5a 0.022/0.042/0.022/0/0.012/0/0.003/0.003/0/0.001/0/0.003/0/0.004 0.019/0.035/0.019/0/0.011/0/0.003/0.003/0/0.001/0/0.003/0/0.004

5b 0.199/0.235/0.203/0/0.165/0/0.090/0.094/0.010/0.069/0/0.088/0.033/0.103 0.107/0.132/0.100/0/0.087/0/0.045/0.048/0.010/0.035/0/0.045/0.016/0.053

6a 0/0/0/0/0/0/0/0.009/0/0/0.001/0/0/0 0/0/0/0/0/0/0/0.008/0/0/0.001/0/0/0

6b 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020 0/0/0/0/0/0/0.016/0.078/0.010/0/0.027/0.007/0.016/0.005

15a 0/0.188/0.242/0.248/0.175/0.008/0.182/0.123/0.197/0.212/0.150/0.180/0.188/0.288 0/0.125/0.147/0.142/0.119/0.007/0.115/0.089/0.130/0.136/0.105/0.121/0.125/0.143

15b 0/0.188/0.113/0.063/0.199/0.144/0.142/0.237/0.177/0.161/0.220/0.195/0.190/0.138 0/0.125/0.083/0.050/0.131/0.075/0.096/0.054/0.120/0.111/0.140/0.129/0.127/0.098

The Kelantan subgroup is assumed as donor and father populations for transfusion and gestation, respectively. HPA data for Banjar, Bugis, Champa, Jawa, Kelantan, Malays, Chinese, and Indians were obtained from Wan Syafawati et al.15 and Tan et al.16 HPA = human platelet antigen; B = Batek; W = Che Wong; K = Kensiu; L = Lanoh; S = Semai; O = Orang Kanaq; BA = Banjar; BU = Bugis; C = Champa; J = Jawa; KE = Kelantan; M = Malays; CH = Chinese; I = Indians; > = donor to recipient and father to mother population for random platelet transfusion and gestation, respectively.

Table 18. Hypothetical transfusion and gestation HPA alloimmunization risks between pairs of Malays and other Malaysian subpopulations


M>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I M>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I

1a 0/0/0.009/0/0.009/0/0/0/0/0/0/0/0/0.013 0/0/0.001/0/0.001/0/0/0/0/0/0/0/0/0.012

1b 0/0/0.075/0/0.039/0/0/0/0.038/0/0/0.047/0/0.172 0/0/0.039/0/0.012/0/0/0/0.019/0/0/0.024/0/0.09

2a 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002

2b 0/0/0/0/0/0/0.090/0/0.054/0/0.099/0.068/0.061/0.072 0/0/0/0/0/0/0.045/0/0.027/0/0.051/0.034/0.031/0.037

3a 0.188/0.222/0.016/0.241/0.096/0.032/0.125/0.159/0.093/0.119/0.150/0.186/0.149/0.123 0.125/0.141/0.014/0.083/0.072/0.027/0.091/0.110/0.070/0.087/0.105/0.124/0.104/0.089

3b 0.188/0.147/0.179/0.241/0.248/0.221/0.235/0.213/0.248/0.239/0.220/0.189/0.220/0.238 0.125/0.103/0.096/0.148/0.148/0.122/0.145/0.137/0.148/0.147/0.140/0.126/0.140/0.146

4a 0/0/0/0/0/0/0/0/0/0.003/0/0/0/0 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0

4b 0.001/0.004/0.010/0.090/0/0/0/0/0/0/0/0/0/0 0/0/0/0/0/0/0.045/0/0/0/0/0.005/0.002/0.005

5a 0.022/0.042/0.022/0/0.012/0/0.003/0.003/0/0.001/0/0.003/0/0.004 0.019/0.035/0.019/0/0.011/0/0.003/0.003/0/0.001/0/0.003/0/0.004

5b 0.199/0.235/0.203/0/0.165/0/0.090/0.094/0.010/0.069/0/0.088/0.033/0.103 0.107/0.132/0.100/0/0.087/0/0.045/0.048/0.010/0.035/0/0.045/0.016/0.053

6a 0/0/0/0/0/0/0/0.009/0/0/0.001/0/0/0 0/0/0/0/0/0/0/0.008/0/0/0.001/0/0/0

6b 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020 0/0/0/0/0/0/0.016/0.078/0.010/0/0.027/0.007/0.016/0.005

15a 0/0.188/0.242/0.248/0.175/0.008/0.182/0.123/0.197/0.212/0.150/0.180/0.188/0.288 0/0.125/0.147/0.142/0.119/0.007/0.115/0.089/0.130/0.136/0.105/0.121/0.125/0.143

15b 0/0.188/0.113/0.063/0.199/0.144/0.142/0.237/0.177/0.161/0.220/0.195/0.190/0.138 0/0.125/0.083/0.050/0.131/0.075/0.096/0.054/0.120/0.111/0.140/0.129/0.127/0.098

The Malays subgroup is assumed as donor and father populations for transfusion and gestation, respectively. HPA data for Banjar, Bugis, Champa, Jawa, Kelantan, Malays, Chinese, and Indians were obtained from Wan Syafawati et al.15 and Tan et al.16 HPA = human platelet antigen; B = Batek; W = Che Wong; K = Kensiu; L = Lanoh; S = Semai; O = Orang Kanaq; BA = Banjar; BU = Bugis; C = Champa; J = Jawa; KE = Kelantan; M = Malays; CH = Chinese; I = Indians; > = donor to recipient and father to mother population for random platelet transfusion and gestation, respectively.



Table 19. Hypothetical transfusion and gestation HPA alloimmunization risks between pairs of Chinese and other Malaysian subpopulations


CH>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I CH>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I

1a 0/0/0.009/0/0.009/0/0/0/0/0/0/0/0/0.013 0/0/0.001/0/0.001/0/0/0/0/0/0/0/0/0.012

1b 0/0/0.075/0/0.039/0/0/0/0.038/0/0/0.047/0/0.172 0/0/0.039/0/0.012/0/0/0/0.019/0/0/0.024/0/0.090

2a 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002 0.002/0/0/0/0/0/0.003/0/0.001/0/0.003/0/0.001/0.001

2b 0/0/0/0/0/0/0.090/0/0.054/0/0.099/0.068/0.061/0.072 0/0/0/0/0/0/0.045/0/0.027/0/0.051/0.034/0.031/0.037

3a 0.188/0.222/0.016/0.241/0.096/0.032/0.125/0.159/0.093/0.119/0.150/0.186/0.149/0.123 0.125/0.141/0.014/0.083/0.072/0.027/0.091/0.110/0.070/0.087/0.105/0.104/0.104/0.089

3b 0.188/0.147/0.179/0.241/0.248/0.221/0.235/0.213/0.248/0.239/0.220/0.189/0.220/0.238 0.125/0.103/0.096/0.148/0.148/0.122/0.145/0.137/0.148/0.147/0.140/0.126/0.140/0.146

4a 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0 0/0/0/0/0/0/0/0/0/0.003/0/0/0/0

4b 0/0/0/0/0/0/0.090/0/0/0/0/0.001/0.004/0.010 0/0/0/0/0/0/0.045/0/0/0/0/0.005/0.002/0.005

5a 0.022/0.042/0.022/0/0.012/0/0.003/0.003/0/0.001/0/0.003/0/0.004 0.019/0.035/0.019/0/0.0110/0/0.003/0.003/0/0.001/0/0.003/0/0.004

5b 0.199/0.235/0.203/0/0.165/0/0.090/0.094/0.010/0.069/0/0.088/0.033/0.103 0.107/0.132/0.100/0/0.087/0/0.045/0.048/0.010/0.035/0/0.045/0.016/0.053

6a 0/0/0/0/0/0/0/0.009/0/0/0.001/0/0/0 0/0/0/0/0/0/0/0.008/0/0/0.001/0/0/0

6b 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020 0/0/0/0/0/0/0.016/0.078/0.010/0/0.027/0.007/0.016/0.005

15a 0/0.188/0.242/0.248/0.175/0.008/0.182/0.123/0.197/0.212/0.150/0.180/0.188/0.288 0/0.125/0.147/0.142/0.119/0.007/0.115/0.089/0.130/0.136/0.105/0.121/0.125/0.143

15b 0/0.188/0.113/0.063/0.199/0.144/0.142/0.237/0.177/0.161/0.220/0.195/0.190/0.138 0/0.125/0.083/0.050/0.131/0.075/0.096/0.054/0.120/0.111/0.140/0.129/0.127/0.098

The Chinese subgroup is assumed as donor and father populations for transfusion and gestation, respectively. HPA data for Banjar, Bugis, Champa, Jawa, Kelantan, Malays, Chinese, and Indians were obtained from Wan Syafawati et al.15 and Tan et al.16 HPA = human platelet antigen; B = Batek; W = Che Wong; K = Kensiu; L = Lanoh; S = Semai; O = Orang Kanaq; BA = Banjar; BU = Bugis; C = Champa; J = Jawa; KE = Kelantan; M = Malays; CH = Chinese; I = Indians; > = donor to recipient and father to mother population for random platelet transfusion and gestation, respectively.

Table 20. Hypothetical transfusion and gestation HPA alloimmunization risks between pairs of Indians and other Malaysian subpopulations


I>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I I>B/W/K/L/S/O/BA/BU/C/J/KE/M/CH/I

1a 0/0/0.009/0/0.009/0/0/0/0/0/0/0/0/0.013 0.012/00/0.001/0/0.001/0/0/0/0/0/0/0/0

1b 0/0/0.075/0/0.039/0/0/0/0.038/0/0/0.047/0/0.172 0.090/0/0/0.039/0/0.012/0/0/0/0.019/0/0/0.024/0

2a 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002 0/0/0/0/0/0/0.003/0/0.001/0/0.003/0.001/0.001/0.002

2b 0/0/0/0/0/0/0.090/0/0.054/0/0.099/0.068/0.061/0.072 0/0/0/0/0/0/0.045/0/0.027/0/0.051/0.034/0.031/0.037

3a 0.188/0.222/0.016/0.241/0.096/0.032/0.125/0.159/0.093/0.119/0.150/0.186/0.149/0.123 0.125/0.141/0.014/0.083/0.072/0.027/0.091/0.110/0.070/0.087/0.105/0.124/0.104/0.089

3b 0.188/0.147/0.179/0.241/0.248/0.221/0.235/0.213/0.248/0.239/0.220/0.189/0.220/0.238 0.125/0.103/0.096/0.148/0.148/0.122/0.145/0.137/0.148/0.147/0.140/0.126/0.140/0.146

4a 0/0/0/0/0/0/0.003/0/0/0/0/0/0/0 0/0/0/0/0/0/0/0/0/0.003/0/0/0/0

4b 0/0/0/0/0/0/0.090/0/0/0/0/0.001/0.004/0.010 0/0/0/0/0/0/0.045/0/0/0/0/0.002/0.005/0.005

5a 0.022/0.042/0.022/0/0.012/0/0.003/0.003/0/0.001/0/0.003/0/0.004 0.019/0.035/0.019/0/0.011/0/0.003/0.003/0/0.001/0/0.003/0/0.004

5b 0.199/0.235/0.203/0/0.165/0/0.090/0.094/0.010/0.069/0/0.088/0.033/0.103 0.107/0.132/0.100/0/0.087/0/0.045/0.048/0.010/0.035/0/0.045/0.016/0.053

6a 0/0/0/0/0/0/0/0.009/0/0/0.001/0/0/0 0/0/0/0/0/0/0/0.008/0/0/0.001/0/0/0

6b 0/0/0/0/0/0/0.032/0.148/0.010/0/0.054/0.014/0.033/0.020 0/0/0/0/0/0/0.016/0.078/0.010/0/0.027/0.007/0.016/0.005

15a 0/0.188/0.242/0.248/0.175/0.008/0.182/0.123/0.197/0.212/0.150/0.180/0.188/0.288 0/0.125/0.147/0.142/0.119/0.007/0.115/0.089/0.130/0.136/0.105/0.121/0.125/0.143

15b 0/0.188/0.113/0.063/0.199/0.144/0.142/0.237/0.177/0.161/0.220/0.190/0.138/0.195 0/0.125/0.083/0.050/0.131/0.075/0.096/0.054/0.120/0.111/0.140/0.129/0.127/0.098

The Indians subgroup is assumed as donor and father populations for transfusion and gestation, respectively. HPA data for Banjar, Bugis, Champa, Jawa, Kelantan, Malays, Chinese, and Indians were obtained from Wan Syafawati et al.15 and Tan et al.16 HPA = human platelet antigen; B = Batek; W = Che Wong; K = Kensiu; L = Lanoh; S = Semai; O = Orang Kanaq; BA = Banjar; BU = Bugis; C = Champa; J = Jawa; KE = Kelantan; M = Malays; CH = Chinese; I = Indians; > = donor to recipient and father to mother population for random platelet transfusion and gestation, respectively.



as the most common HPA alloantibody in a cohort of multi-transfused thrombocytopenic patients at Universiti Sains Malaysia Hospital.30 This is the second largest hospital in northeast Peninsular Malaysia and in 2014 supplied more than 6061 units of untyped platelet concentrates/apheresis (equal to more than 23 percent of total consumption of blood/blood components) (Z. Zefarina and M.N. Hassan, unpublished data). The presence of individuals who are homozygous for less frequent HPA alleles (e.g., HPA-3b/b in Batek, Che Wong, Lanoh, Senoi, Malays, Chinese, and Indian; HPA-5b/b in Che Wong; HPA-1b/b in Indians; HPA-2b/b in Indians; HPA-5b/b in Indians) provides further support for our views on the significantly higher overall risk of HPA alloimmunization in Malaysia. Thus, HPA typing is expected to become an important screening process in the future healthcare of the country—especially for management of patients with PTR, NAIT, and PTP. An important caveat to note is that our data analysis outputs were generated from a relatively small number of samples and our ancestry and health inferences might be affected by this limitation.

In conclusion, we believe that the present study has successfully genotyped HPA-1 to -6 and HPA-15 loci in Orang Asli individuals in Peninsular Malaysia and shows high genetic diversity related to independent waves of immigrants into this region in prehistoric (i.e., Semang, Senoi, and Proto-Malays) and historic (Malay subethnic groups, Chinese, Indians) times. The gene pools of the settlers in Peninsular Malaysia were then further shaped by evolutionary processes including founder effects, bottlenecks, and natural selection.

Acknowledgments

This project was supported by a short-term grant (304/PPSK/61313062), and the MSc scholarship for W.U.W. Syafawati was supported by the long-term research grant scheme (304/PPSK/6150115/U132). G.K. Chambers thanks Victoria University of Wellington, New Zealand, for alumnus support.

References

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12. Feng ML, Liu DZ, Shen W, et al. Establishment of an HPA-1 to -16 typed donor registry in China. Transfus Med 2006;16:369–74.

13. Yan L, Zhu F, He J, et al. Human platelet antigen systems in three Chinese ethnic populations. Immunohematology 2006;22:6–10.

14. De La Vega Elena CD, Nogues N, Fernandez Montoya A, et al. Human platelet-specific antigens frequencies in the Argentinean population. Transfus Med 2008;18:83–90.

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The editorial staff of Immunohematology welcomes manuscripts pertaining to blood group serology and molecular genetics for consideration for publication. We are especially interested in review articles, case reports, papers on platelet and white cell serology, scientific articles covering original investigations or new blood group alleles, papers on molecular testing, and papers on new methods for use in the blood bank. To obtain instructions for

submitting scientific articles, case reports, and review articles, see Instructions for Authors in every issue of Immunohematology or e-mail a request to [email protected]. Include fax and phone numbers and e-mail address with all manuscripts and correspondence. E-mail all manuscripts to [email protected].

Manuscripts

22. Rodriguez S, Gaunt TR, Day INM. Hardy-Weinberg equilibrium testing of biological ascertainment for Mendelian randomization studies. Am J Epidemiol 2009;169:505–14.

23. Halle L, Bach KH, Martageix C, et al. Eleven human platelet systems studied in the Vietnamese and Ma'ohis Polynesian populations. Tissue Antigens 2004;63:34–40.

24. Edinur HA, Dunn PP, Lea RA, et al. Human platelet antigens frequencies in Maori and Polynesian populations. Transfus Med 2013;23:330–7.

25. NurWaliyuddin HZA, Norazmi MN, Edinur HA, et al. Ancient genetic signatures of Orang Asli revealed by killer immunoglobulin-like receptor gene polymorphisms. PLoS One 2015;10:e0141536.

26. Kaplan C. Foetal and neonatal alloimmune thrombocytopaenia. Orphanet J Rare Dis 2006;10:39.

27. Waters AH. Post-transfusion purpura. Blood Rev 1989;3:83–7. 28. Slichter SJ, Davis K, Enright H, et al. Factors affecting

posttransfusion platelet increments, platelet refractoriness, and platelet transfusion intervals in thrombocytopenic patients. Blood 2005;105:4106–14.

29. Armani MI, Santoso S. The relevance of platelet antigen/antibodies in multi ethnic in Malaysia. Vox Sang 2015;109:1–96.

30. Wan Mahmood WH, Mustaffa R. Platelet alloantibody in multiply transfused thrombocytopenic patients. Int Med J Malaysia 2007:6:1–10.


Wan Ubaidillah Wan Syafawati, BSc, MSc student, Biomedicine Programme, School of Health Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia; Zulkafli Zefarina, M.Path, Lecturer, Biomedicine Programme, School of Health Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia; Zafarina Zafarina, PhD, Lecturer, Human Identification Unit/DNA, Forensic Programme, School of Health Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia; Mohd Nazri Hassan, M.Path, Lecturer, Hematology Department, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia, Mohd Nor Norazmi, PhD, Lecturer, Human Identification Unit/DNA, Forensic Programme, School of Health Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia; Sundararajulu Panneerchelvam, MSc, Lecturer, Human Identification Unit/DNA, Forensic Programme, School of Health Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia; Geoffrey Keith Chambers, PhD, Lecturer, School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand; and Hisham Atan Edinur, PhD (corresponding author), Lecturer, Forensic Programme, School of Health Sciences, Universiti Sains Malaysia, Health Campus, 16150 Kubang Kerian, Kelantan, Malaysia, [email protected].


A detailed flow cytometric method for detection of low-level in vivo red blood cell–bound IgG, IgA, and IgMW. Beres, G.M. Meny, and S. Nance

Original repOrt

Flow cytometric methods are commonly used to analyze white blood cell surface antigen expression. We developed a flow cytometric method to detect red blood cell (RBC)-bound immunoglobulin (Ig)G, IgA, and IgM. RBCs were washed; incubated with fluorescein isothiocyanate (FITC)-conjugated anti-IgG, -IgA, or -IgM; washed; and analyzed on the flow cytometer. The method was optimized by determining the dilution of FITC-conjugated anti-IgG, -IgA, and -IgM providing the greatest amount of fluorescence when tested with Ig-coated RBCs and the least amount of fluorescence when tested with naive RBCs. Tannic acid was used to prepare Ig-coated RBCs. Cross-reactivity of FITC-conjugated anti-IgG, -IgA, and -IgM with Ig-coated RBCs was evaluated, and a reference range was established. Use of this method may assist in clinical evaluation of patients who present with hemolysis and a negative direct antiglobulin test. Immunohematology 2016;32:161–169.

Key Words: red blood cell, direct antiglobulin test, autoimmune hemolytic anemia, tannic acid, flow cytometry, immunoglobulins

The tube-based direct antiglobulin test (DAT) is routinely used in clinical laboratories to evaluate red blood cell (RBC)-bound immunoglobulin (Ig). Although flow cytometric methods are commonly used to analyze white blood cell (WBC) surface antigen expression,1 the flow cytometer is less frequently used by clinical laboratories to detect and analyze RBC-bound IgG, IgA, or IgM.2–5 A positive DAT can indicate the presence of autoimmune hemolytic anemia (AIHA), but 5 percent to 10 percent of patients with AIHA are DAT-negative.6 Therefore, a method that detects low levels of RBC-bound immunoglobulins may be of value in the symptomatic, DAT-negative patient who has no other reason for hemolysis.

Patient samples submitted to an immunohematology reference laboratory (IRL) for evaluation of AIHA are routinely tested by serologic assays, including the DAT. The routine DAT detects as few as 200 molecules of IgG per RBC.7 A negative DAT in the presence of clinical hemolysis may warrant further study. DAT-negative samples may be further analyzed via special serologic methods, such as washing the patient’s RBCs in cold (4°C) saline, performing the DAT using additional

antiglobulin reagents or antisera, such as anti-IgA and anti-IgM, and testing a concentrated eluate from the patient’s RBCs. These special serologic methods were reported to detect RBC-bound IgG in 3 percent to 19 percent of DAT-negative RBC samples from patients suspected to have AIHA.6

Flow cytometric methods have been described for detecting low-level RBC-bound IgG in cases of suspected AIHA with a negative DAT.5 This nonserologic assay was reported to detect IgG on RBCs in 21 percent of DAT-negative RBC samples from patients suspected to have AIHA.6

In addition to the detection of IgG, the detection of IgA and IgM may also be important in cases of suspected AIHA with a negative DAT.8–12 RBC-based flow cytometry is a rare application of flow cytometry not generally available in hospital laboratories. There are no commercially available tests to detect RBC-bound IgA and IgM. A flow cytometry–based method was developed in our facility to detect RBC-bound IgG, IgA, and IgM using reagents not manufactured or sold for this purpose. Detailed information is presented to permit implementation in a clinical laboratory of a flow cytometric method for detection of RBC-bound IgG, IgA, and IgM. Use of this method may assist in clinical evaluation of patients who present with hemolysis and a negative DAT.


Flow Cytometry Startup, Shutdown, and CalibrationTwo flow cytometers (FACSCalibur and FACScan, Becton

Dickinson, San Jose, CA) were used for RBC analysis. The manufacturer’s startup, shutdown, maintenance, and care procedures were followed. Before and after use, the flow cytometer was cleaned using a 10 percent bleach solution and deionized water, the waste container was emptied when applicable, and the sheath reservoir was maintained at the appropriate level.

Each day prior to testing, software and special beads (FACSComp with CaliBRITE beads, Becton Dickinson) were used to monitor the flow cytometer performance and provide


automated instrument setup: i.e., check laser alignment, optimally adjust instrument settings, monitor sensitivity, and set compensation. The lyse/wash assay on both flow cytometers was performed with five sets of beads: unlabeled beads, fluorescein isothiocyanate (FITC)-labeled beads, phycoerythrin (PE)-labeled beads, peridinin chlorophyll protein (PerCP)-labeled beads, and allophyscocyanin (APC)-labeled beads (only used with the FACSCalibur, Becton Dickinson). After analysis of the beads, a summary report was generated, and all results had to be reported as “pass” before the flow cytometer could be used. PE, PerCP, and APC, although not used in this assay, were evaluated as part of the standard instrument setup procedure implemented in our laboratory.

Prior to use each day, current instrument settings on the flow cytometer, namely, detectors (photodiode and photo-multiplier tubes), amplifiers, threshold, and compensation, are checked to ensure that the data plots show all captured RBCs without the use of gates (Fig. 1). The RBCs used in this check are collected in ethylenediaminetetraacetic acid (EDTA) and washed to minimize interference by agglutinated RBCs and WBCs. Using software (CellQuest, Becton Dickinson), slight adjustments to the instrument settings are made, if needed, and saved for use in that day’s testing.

Flow Cytometry Negative Control RBC PreparationBaseline settings to detect RBC autofluorescence and

instrument noise were determined by analyzing RBC samples

prepared in the following manner without the addition of FITC-labeled anti-immunoglobulin.1 Residual RBC samples from healthy group O blood donors passing screening and health history for blood donation were used as negative controls. Ten residual donor RBC samples collected on the same day were washed four times in 1× phosphate-buffered saline (Dulbecco’s phosphate-buffered saline [DPBS], Lonza, Walkersville, MD) and pooled together. An aliquot from the pooled donor sample was prepared and tested as the negative control for each test run. The RBCs were washed four times in 1× DPBS, once in 0.6 percent bovine serum albumin (BSA) (Sigma Aldrich, St. Louis, MO) prepared in the DPBS, and resuspended to a 1 percent concentration in 0.6 percent BSA. The 1 percent RBC suspension was analyzed on the flow cytometer, and integrated markers on the histogram were used to control for autofluorescence and instrument noise (Fig. 2).1

The pooled donor sample was stored in a storage solution (RBC Storage Solution, Immucor, Inc., Norcross, GA) and used as a negative control for up to 30 days after the initial

draw date.13 This expiration date was based on a stability study that analyzed five control sets during and up to 37 days after the initial draw date (Table 1).13 In a separate study, over 16 months, 24 pooled donor samples were evaluated 67 times for RBC-bound IgG, IgM, and IgA. The pooled donor samples showed low variance in the percent of RBC-bound

W. Beres et al.

Fig. 1 Example of a dot plot of pooled donor red blood cells without the addition of antibody to adjust instrument controls.

Fig. 2 Example of a histogram of pooled donor red blood cells (RBCs) without the addition of antibodies. The instrument controls were adjusted to place the RBCs below 101, and the markers were set at the RBC peak.


Detection of RBC-bound immunoglobulins

immunoglobulins detected and provided expected normal results when evaluated up to 30 days after the initial draw date (Table 2).14

Flow Cytometry Positive Control RBC PreparationSpecific Ig-coated RBCs were prepared to ensure

appropriate reactivity of the specific antisera (e.g., anti-IgG) with Ig-coated RBCs and also to ensure no cross-reactivity with the other coated RBC preparations (e.g., anti-IgG with IgA-coated RBCs and anti-IgG with IgM-coated RBCs). Neither the antisera nor the proteins used to coat the RBCs are manufactured for flow cytometric analysis of RBCs; therefore, these controls are important to include in testing.

In vitro Ig-coated (IgG, IgA, and IgM) RBCs were prepared by tannic acid treatment for use as positive controls.15 The tannic acid method was selected to minimize nonspecific aggregation of Ig-coated RBCs. The pooled donor sample that served as a negative control was used to create the positive control samples 8 to 21 days after collection. The pooled donor sample was washed three times in DPBS having a pH of 6.8. The pH of the DPBS is critical to obtain proper tanning and immunoglobulin coating of the RBCs. A total of 600 μL packed RBCs were mixed with 10 mL of 25 μg/mL acid (Tannic Acid, Sigma-Aldrich, St. Louis, MO) in DPBS. This mixture was incubated in a 37°C ±1°C dry air incubator for 15 minutes ±1 minute. The tannic acid–treated RBCs were then washed

three times in DPBS to remove any residual tannic acid, and an aliquot was set aside for flow cytometric testing. The tannic acid only–treated RBCs were stored in the storage solution (RBC Storage Solution) and used for up to 31 days beyond the donor’s collection date.

The tannic acid–treated RBC aliquots were coated with IgG, IgM, or IgA (ChromPure human IgG whole molecule, ChromPure human IgM [myeloma] whole molecule, or ChromPure human IgA whole molecule, Jackson ImmunoResearch Laboratories, West Grove, PA). Various concentrations of the coating protein were evaluated prior to use to determine the optimal coat concentration (1.9 × 10–6 mg/mL to 0.5 mg/mL), as the concentration can vary between reagent lots and with the antibody used. A 0.02 mg/mL solution of each immunoglobulin was determined to be the optimal coating concentration for the coated proteins. The immunoglobulin coating proteins were prepared in DPBS and heated in a 56°C ±1°C water bath for 1 hour ±5 minutes before mixing with the tannic acid–treated RBCs. A total of 200 μL washed packed tannic acid–treated RBCs were mixed with 500 μL heated immunoglobulin solution. This mixture was incubated in a 37°C ±1°C dry air incubator for 1 hour ±5 minutes. Passive binding of immunoglobulin to RBCs occurs immediately after adding immunoglobulin to the tannic acid–treated donor RBC aliquots.15 The Ig-coated RBCs were washed three times in DPBS and once with 0.6 percent BSA to remove any excess immunoglobulin, and resuspended to a 1 percent concentration in 0.6 percent BSA for use as a positive control. Aliquots of each positive control (IgA-, IgM-, and IgG-coated RBCs) were set aside for testing. Samples were mixed by vortexing and were inspected for agglutination prior to testing. Visual agglutination of RBCs has not been observed when viewed microscopically. The donor pooled sample (negative control), described in the previous section, and the positive control samples prepared from the donor pool were tested in parallel for each run as a complete control set.

The Ig-coated RBCs were stored in the red blood cell storage solution (RBC Storage Solution) and used for 31 days beyond the initial draw date.13 The use of the Ig-coated cells for 31 days was based on a stability study that analyzed five control sets during and up to 37 days after the initial draw date.13

Patient and Donor SamplesResidual aliquots of blood donor samples were obtained

after completion of infectious disease testing to prepare the complete control set. Ninety residual donor samples, 24 pooled donor samples, and 8 complete control sets are included in this

Table 1. Stability study analyzing five control sets during and up to 37 days after the initial draw date

PoolPool age when coated (days)

Time of study (days)

IgG IgA IgM

Max Min Max Min Max Min

A 8 37 95.4 83.4 92.4 89.6 95.9 92.5

B 13 27 69.1 41.3 78.7 60.4 91.7 54.7

C 13 31 62.6 11.2 81.5 67.1 92.2 76.7

D 17 28 99.0 65.0 99.4 77.1 98.9 56.2

E 20 35 95.9 72.8 99.2 88.3 98.9 79.9

Based on data from Beres and Nance.13

Ig = immunoglobulin; Max = maximum; Min = minimum.

Table 2. Evaluation of 24 normal donor pools for RBC-bound immunoglobulin levels

% RBC-bound IgG % RBC-bound IgA % RBC-bound IgM

Mean of 24 pools* 1.34 2.74 1.69

Standard deviation 1.33 2.79 2.16


*The normal range for these data was determined to be: RBC-bound IgG: 0–5.33 %M2, RBC-bound IgA: 0–11.11 %M2, and RBC-bound IgM: 0–8.17 %M2.RBC = red blood cell; Ig = immunoglobulin.


study. Residual aliquots of 317 patient blood samples referred to the IRL were selected for flow cytometry analysis if their DAT was negative to 3+ (4+ is strongest reaction) with anti-IgG. All blood samples were collected in EDTA and stored between 2°C and 6°C prior to use or up to 31 days past the initial draw date. The protocol was developed and approved by an institutional review board; the samples were tested according to this protocol.

Direct Antiglobulin TestRBCs were washed four times in saline and suspended

to a 4 percent suspension. Four test tubes were labeled (Poly, IgG, C3, and Saline) and prepared by adding one drop of 4 percent RBC suspension to each tube followed by one to two drops of anti-human immunoglobulin reagents (anti-IgG, -C3d; anti-IgG; anti-C3bd; Immucor, Inc.) or 0.85 percent saline (Blood Bank Saline, Thermo Scientific, Waltham, MA) to the appropriately labeled test tube. The tubes were mixed and centrifuged at 1000g. The cell buttons were gently resuspended and examined for agglutination. Negative tests were controlled by adding one drop of the appropriate control RBCs, recentrifuged, and examined again for agglutination.16

Flow Cytometry Test Sample PreparationThe patient and donor RBCs were washed four times

in DPBS, once in 0.6 percent BSA, and resuspended to a 1 percent concentration in BSA. Subsequently, 500 μL of the 1 percent RBC suspensions was aliquoted into four flow cytometry tubes (Falcon® 5 mL polystyrene round-bottom 12 × 75 mm, Corning Inc., Life Sciences, Tewksbury, MA): one tube to control for background and autofluorescence and the other three for antibody testing. A maximum of 10 patient samples, including controls, is recommended for one batch of testing when evaluating for RBC-bound IgG, IgA, and IgM. As the number of samples increases, the amount of time between steps increases, thus extending incubation periods. This limit was based on one technician performing the assay on one flow cytometer not equipped with a loader or high-throughput sampler.

Flow Cytometry Antibody LabelingThe flow cytometer detects immunoglobulins (antibodies)

on RBCs by the addition of FITC-labeled anti-immunoglobulin. The test samples and a set of the control samples were sensitized with FITC-conjugated antibodies. Samples of 500 μL of the 1 percent RBC suspensions were centrifuged for 60 seconds at 1000g, and the supernatant was removed. Then, 500 μL FITC-conjugated antibodies diluted in 0.6 percent BSA

was added to each cell button, and the tubes were vortexed. The RBC and FITC-antibody solution was incubated in the dark, at room temperature, for 45–60 minutes, washed, and resuspended in 500 μL of 0.6 percent BSA. Controls are used together as a set: the in vitro Ig-coated (IgG, IgA, and IgM) samples (positive controls) and the nontreated pooled donor sample (negative control). Therefore, with each test batch, all antisera are tested against a negative control and cells coated with IgG, IgA, and IgM (thus, one coated cell serves as a positive control and the two other coated cells are controls for cross-reactivity). This control set is tested in parallel with each test run. A reagent control sample of tannic acid–only treated RBCs was evaluated during method development, but was discontinued, since nonspecific binding caused by tannic acid treatment was not observed.

Flow Cytometry Acquisition and AnalysisFlow cytometry testing was performed on two flow

cytometers (FACSCalibur and FACScan, Becton Dickinson). Prior to use, the automated instrument setup was performed using software and special beads (FACSComp and CaliBRITE beads, Becton Dickinson). The instrument controls were optimized to display cell populations of interest on the data plots, forward and side scatter amps were set to linear mode, and the FLI and FL2 amps were set to logarithmic mode.17 Gates were established to view all RBCs. Prior to testing, all samples were mixed by vortexing and were visually inspected for agglutination. If RBC agglutination was suspected, the sample was viewed microscopically after the flow cytometry testing to determine false positives; no RBC agglutination was observed by microscopic evaluation in this study. Conse-quently, only the positive tests were viewed microscopically in the amended procedure. Fifty thousand RBCs are acquired from each sample at optimized settings.

During sample analysis, the relative fluorescence or light scatter intensity is displayed in a single parameter histogram on the x axis and the number of events on the y axis. Marker 1 (M1) is used to separate the native background autofluorescence of RBCs, and Marker 2 (M2) is used to identify the fluorescence emitted by the RBC-bound FITC-labeled antibodies bound to immunoglobulins on the target RBCs (Fig. 2). The results are calculated by subtracting the %M2 value of the washed target RBCs from the %M2 FITC-labeled antibody treated target RBCs. This calculated value is then evaluated against the established normal reference range to determine if the RBC immunoglobulin levels detected are in the normal range.

W. Beres et al.


Results

Optimal FITC-Conjugated Antibody DilutionPrior to testing, the optimal FITC-conjugated antibody

dilution was determined for staining a 500 μL volume of 1 percent RBCs. During method development, antibodies from two manufacturers were evaluated to determine the optimal antibody dilution: the first set of IgG, IgM, and IgA antibodies [FITC-conjugated goat F(ab )́2 anti-human IgG, FITC-conjugated goat F(ab )́2 anti-human IgM, FITC-conjugated goat F(ab )́2 anti-human IgA; Invitrogen, Camarillo, CA; Life Technologies, Carlsbad, CA] were all goat-sourced antibodies. The set from the second manufacturer (FITC-conjugated mouse FCγ anti-human IgG, FITC-conjugated goat Fc5μ anti-human IgM, FITC-conjugated goat anti-human serum IgA; Jackson ImmunoResearch Laboratories) included an IgG antibody that was mouse-sourced.

The optimal FITC-conjugated antibody dilution was determined by comparing the results of the RBCs from the positive and negative control set: i.e., observing results generated from testing various antibody dilutions (e.g., between 1/25 and 1/400) of the in vitro Ig-coated (IgG, IgA, and IgM) positive controls and the untreated pooled donor sample (negative control). The antibody dilution that yielded the highest percentage of RBC-bound Ig detected on the corresponding positive control sample (e.g., IgA-coated RBCs analyzed by anti-IgA) when compared with the other antibody dilutions evaluated, that had no observed cross-reactivity, and that exhibited the greatest percentage of separation between negative and positive control results was chosen as the optimal dilution. It is critical to choose an antibody dilution with a high result when selecting the positive control. The positive control result must be greater than the results of the patient samples evaluated in the test run to ensure that cross-reactivity with the other antibodies tested in this assay is excluded.

Each lot of FITC-conjugated antibody is prepared by the manufacturer and, in general, with different antibody concentrations (mg/mL) and with different ratios of FITC fluorophoros conjugated to the protein (µg/mg). The optimal dilution of each FITC-conjugated antibody is lot-specific and was determined prior to its use to optimize maximum reactivity and to minimize cross-reactivity.

As an example, the optimal dilution was identified as 1/50 for the FITC-conjugated goat F(ab )́2 anti-human IgM (lot 923278E, Invitrogen; Life Technologies). The positive control sample, IgM-coated RBCs, was evaluated with anti-IgM at dilutions of 1/25, 1/50, 1/100, and 1/200. The 1/50

dilution detected the greatest amount of RBC-bound IgM when compared with the results from the 1/25, 1/100, and 1/200 dilutions (Table 3). The optimal dilution for FITC-conjugated goat anti-human serum IgA (lot 120546, Jackson ImmunoResearch Laboratories) was identified as 1/50 (Table 4), which also had the greatest amount of RBC-bound IgA when compared with the other dilutions. The optimal dilution of the FITC-conjugated goat F(ab )́2 anti-human IgG (lot 119255, Jackson ImmunoResearch Laboratories) was identified as 1/300 (Table 5), since this dilution showed minimal cross-reactivity when compared with the other anti-IgG dilutions, and had the greatest percentage of RBC-bound IgG with IgG-coated RBCs for 1/50 and 1/100, and similar for 1/200 and 1/400, making either acceptable for use.

Cross-ReactivityWhile evaluating the optimal FITC-conjugated antibody

dilution, the antibodies were also evaluated for cross-reactivity. The control set, as described earlier, RBCs from the negative and positive control set (the in vitro Ig-coated [IgG, IgA, and IgM] control), and the untreated pooled donor sample were tested in parallel with each test run. The anti-IgG was evaluated with RBC-coated IgA whole molecule (ChromPure, Jackson ImmunoResearch Laboratories) and IgM (myeloma) whole molecule (ChromPure); the anti-IgA was evaluated with RBC-coated IgG whole molecule (ChromPure) and IgM (myeloma) whole molecule (ChromPure); and the anti-IgM was evaluated with RBC-coated IgG whole molecule (ChromPure) and RBC-bound IgA whole molecule (ChromPure). The IgG-, IgA-, and IgM-coated RBCs were prepared by tannic acid treatment, as described earlier, and were analyzed by flow cytometry by the corresponding antibody (e.g., IgA-coated RBCs analyzed by anti-IgA) to ensure adequate RBC coating. The pooled donor sample used in preparing the Ig-coated RBCs was analyzed as a negative control.

Cross-reactivity was evaluated with one of each IgG-, IgM-, and IgA-conjugated antibody: FITC-conjugated goat F(ab )́2 anti-human IgM (Invitrogen; Life Technologies) (Table 3), FITC-conjugated goat anti-human serum IgA (lot 93818, Jackson ImmunoResearch Laboratories) (Table 4), and FITC-conjugated goat F(ab )́2 anti-human IgG (Jackson ImmunoResearch Laboratories) (Table 5). Cross-reactivity was tested concurrently along with determining the optimal reagent antibody dilutions. The percent of RBC-bound antibody detected from RBCs coated with the conjugate antibody was within the established normal reference ranges (as described in the following section), and cross-reactivity was not observed. Cross-reactivity with controls was monitored with each batch



tested. This monitoring for cross-reactivity is important and, if seen, invalidated the testing using that antibody.

RBC-Bound Immunoglobulin (IgG, IgA, and IgM) Reference Range

The RBC-bound immunoglobulin reference range or normal range of RBC-bound immunoglobulin was defined to detect positive samples. The ranges were established by determining the amount of RBC-bound immunoglobulin on 30 naive washed individual allogeneic donor blood samples by flow cytometry; 10 samples were evaluated in three separate batches on different days. Following the described protocol, the blood samples were evaluated by each antibody using the lot-specific predetermined optimal dilution to give the RBC-bound immunoglobulin negative range. This step was performed for all antibodies used—anti-IgG, anti-IgA, and anti-IgM—after the optimal antibody dilution and cross-reactivity were determined. The normal range was calculated by using the mean result of the donor samples ±3 standard deviations (Tables 6–8). For the normal range to be valid, the control set (evaluated in the previous section) must be within the newly established normal range. If the control set is outside the normal range, a new optimal dilution must be chosen.

Negative and Positive Control Set Storage Parameters

The pooled donor sample, tannic acid–only treated RBCs, and Ig-coated RBCs were stored in the storage solution (RBC Storage Solution) and used for up to 31 days after the initial draw date. The use of the coated cells for 31 days was based on a stability study that analyzed five control sets during and up to 37 days after the initial draw date.13 In a separate study, over 16 months, 24 pooled naive donor samples were evaluated 67 times for RBC-bound IgG, IgM, and IgA. The pooled donor samples showed low variance in RBC-bound immunoglobulins and provided expected normal results when evaluated up to 30 days after the initial draw date (Table 2).14

Patient and Donor SamplesPreliminary results in our laboratory on 237 patient

samples and 20 autologous donor samples examined by flow cytometry (individual donations for self-use) demonstrated RBC-bound IgG on 16 percent of DAT-negative patient samples and 0 percent of autologous donor samples18 (Table 9). Results on 80 DAT-negative patient samples suspected for AIHA were collected over 4 years (July 2012 to Aug 2016). The samples were examined by flow cytometry, and 28.75 percent were found to have RBC-bound IgG, 32.50 percent had RBC-

W. Beres et al.

Table 3. Determination of IgM dilution by evaluation of optimal reactivity and cross-reactivity: percentage of RBC-bound IgM detected by anti-human IgM

Control set*

Anti-IgM dilution

1/25 1/50† 1/100 1/200 Unstained

Donor pool 2.08 0.62 0.27 0.32 0.12

IgG 3.52 1.41 1.00 0.38 0.15

IgA 3.11 1.26 0.87 0.45 0.15

IgM 77.58 77.99 75.22 74.33 0.10

Antibody: FITC-conjugated goat F(ab´)2 anti-human IgM lot: 923278E, Invitrogen; Life Technologies.*The control set consists of RBCs from the negative and positive control set: the in vitro Ig-coated (IgG, IgA, and IgM) controls and the untreated pooled donor sample.†From these data, the optimal antibody dilution was determined to be 1/50. The normal range was determined in Table 6 to be 0–6.00 %M2.Ig = immunoglobulin; RBC = red blood cell.

Table 4. Determination of IgA dilution by evaluation of optimal reactivity and cross-reactivity: percentage of RBC-bound IgA detected by anti-human IgA

Control set*

Anti-IgA dilution

1/25 1/50† 1/100 1/200 Unstained

Donor pool 1.95 0.91 0.56 0.37 0.06

IgG 6.15 2.39 2.39 1.39 0.08

IgA 61.46 61.53 53.53 50.61 0.06

IgM 6.28 2.85 2.25 1.88 0.11

Antibody: FITC-conjugated goat anti-human serum IgA lot: 120546 Jackson ImmunoResearch Laboratories.*The control set consists of RBCs from the negative and positive control set: the in vitro Ig-coated (IgG, IgA, and IgM) controls and the untreated pooled donor sample.†From these data, the optimal antibody dilution was determined to be 1/50. The normal range was determined in Table 7 to be 0–6.90 %M2.Ig = immunoglobulin; RBC = red blood cell.

Table 5. Determination of IgG dilution by evaluation of optimal reactivity and cross-reactivity: percentage of RBC-bound IgG detected by anti-human IgG

Control set*

Anti-IgG dilution

1/50 1/100 1/200 1/300† 1/400 Unstained

Donor pool 2.72 0.77 0.64 0.49 0.52 0.18

IgG 75.01 73.72 80.78 70.86 70.61 0.15

IgA 5.55 3.39 3.20 1.65 1.36 0.25

IgM 8.64 5.83 2.71 3.35 2.28 0.12

Antibody: FITC-conjugated mouse FCγ anti-human IgG lot: 119255, Jackson ImmunoResearch Laboratories.*The control set consists of RBCs from the negative and positive control set: the in vitro Ig-coated (IgG, IgA, and IgM) controls and the untreated pooled donor sample.†From these data, the optimal antibody dilution was determined to be 1/300. The normal range was determined in Table 8 to be 0–7.29 %M2.Ig = immunoglobulin; RBC = red blood cell.


bound IgA, and 40.00 percent had RBC-bound IgM (Table 10). Eleven (13.75%) of the DAT-negative samples evaluated had elevated levels of RBC-bound IgG, IgA, and IgM (Fig. 3).

Discussion

When implementing a RBC-based flow cytometry method, there are many different points to consider, because these FITC-conjugated antibodies are not standardized by the manufacturers for this method. The optimal FITC-conjugated antibody dilutions must be chosen that result in a low %M2 with negative controls, a high %M2 with positive controls, and no cross-reactivity with other Ig-coated RBCs. The positive control %M2 should be optimized or selected to be greater than the highest %M2 results anticipated to be found in positive patient samples to rule out cross-reactivity for valid tests. The negative control range %M2 should be low enough to detect RBCs coated with low levels of immunoglobulins.

Many flow cytometry operators are trained in WBC applications but are not trained in the study of RBC-based antigen–antibody reactions.19 A detailed flow cytometer procedure will be of assistance in the laboratory evaluation of patients who present clinically with hemolysis and a negative DAT. Ideally, it should be adaptable to flow cytometers of different models, from different manufacturers, or with different software—with careful validation and controls. The method described in this article is an improvement over subjective manual testing because results are obtained by an automated system and analyzed cell by cell. Our lab studies started with the evaluation of RBC-bound IgG because of its clinical importance and our desire to provide the ability to compare flow cytometry


Table 6. Evaluation of 30 randomly selected donors over 3 days (normal range): percentage of RBC-bound IgM detected by 1/50 anti-human IgM

Mean RBC-bound IgM detected

Donors(N = 30) Day 1 Day 2 Day 3 Mean

Standard deviation Range*

1–10 1.17

11–20 2.02

21–30 2.05

1–30 1.68 1.44 0–6.00

Antibody: FITC-conjugated goat F(ab´)2 anti-human IgM, lot: 923278E Invitrogen; Life Technologies.*The normal range was calculated by using the mean of the donor samples ±3 standard deviations. RBC = red blood cell; Ig = immunoglobulin.

Table 7. Evaluation of 30 randomly selected donors over 3 days (normal range): percentage of RBC-bound IgA detected by 1/50 anti-human IgA

Mean RBC-bound IgA detected



1–10 3.25

11–20 2.76

21–30 1.11

1–30 2.37 1.51 0–6.90

Antibody: FITC-conjugated goat anti-human serum IgA, lot: 120546, Jackson ImmunoResearch Laboratories.*The normal range was calculated by using the mean of the donor samples ±3 standard deviations.RBC = red blood cell; Ig = immunoglobulin.

Table 8. Evaluation of 30 randomly selected donors over 3 days (normal range): percentage of RBC-bound IgG detected by 1/300 anti-human IgG

Mean RBC-bound IgG detected



1–10 1.15

11–20 2.25

21–30 2.72

1–30 2.04 1.75 0–7.29

Antibody: FITC-conjugated mouse FCγ anti-human IgG, lot: 119255, Jackson ImmunoResearch Laboratories.*The normal range was calculated by using the mean of the donor samples ±3 standard deviations.RBC = red blood cell; Ig = immunoglobulin.

Table 9. Detection of in vivo RBC-bound IgG measured by flow cytometry

Number of samples evaluated

Number of samples with elevated levels of RBC-bound IgG

% Samples with RBC-bound IgG

DAT-negative patients

95 15 16

Autologous donors 20 0 0


RBC = red blood cell; Ig = immunoglobulin; DAT = direct antiglobulin test.

Table 10. Detection of in vivo RBC-bound IgG, IgA, and IgM by flow cytometry in DAT-negative patient samples (N = 80)

IgG* IgA* IgM* IgG and IgAIgG and

IgMIgA and

IgMIgG, IgA, and IgM Total

1 4 9 5 6 6 11 42

(1.25%) (5.00%) (11.25%) (6.25%) (7.50%) (7.50%) (13.75%) (52.50%)

The samples were examined by flow cytometry; 28.75 percent were found to have RBC-bound IgG, 32.50 percent had RBC-bound IgA, and 40.00 percent had RBC-bound IgM.*Only one RBC-bound immunoglobulin detected on the sample.RBC = red blood cell; Ig = immunoglobulin; DAT = direct antiglobulin test.


results with standard tube test results. RBC-bound IgA and IgM detection was studied after the IgG detection procedure was optimized to enable the evaluation of patients with negative DATs and hemolysis of unknown etiology that may be caused by anti-IgA or anti-IgM.

Patient samples submitted to a laboratory for evaluation of AIHA are routinely tested for the presence of cell-bound IgG (and C3) via a tube DAT. If a negative DAT is obtained, flow cytometry testing can be performed after preparing controls, establishing the appropriate dilution of FITC-conjugated antibody, and establishing a reference range. We have provided information for flow cytometry operators to allow for implementation of a flow cytometric method for detection of RBC-bound IgG, IgA, and IgM to assist in clinical evaluation of patients who present with hemolysis and a negative DAT.

Acknowledgments

We would like to thank Savita Singh, Karen Weikel, and Abraham Thomas for collecting and providing residual patient and donor samples used for this testing. This study was supported by the American Red Cross Blood Services.

References

1. Hanson CA. Reticulocyte analysis by flow cytometry. In: Keren DF, Hanson CA, Hurtubise PE, eds. Flow cytometry and clinical diagnosis. Chicago: American Society of Clinical Pathologists, 1994:368–83.

2. Fayek MH, Saad AA, Eissa DG, Tawfik LM, Kamal G. Role of gel test and flow cytometry in diagnosis of Coombs' negative autoimmune haemolytic anaemia. Int J Lab Hematol 2012;34:311–9.

3. Lin JS, Hao TC, Lyou JY, et al. Clinical application of a flow cytometric direct antiglobulin test. Transfusion 2009;49: 1335–46.

4. Chaudhary R, Das S, Gupta R, Khetan D. Application of flow cytometry in detection of red cell bound IgG in Coombs negative AIHA. Hematology 2006;11:295–300.

5. Nance SJ, Garratty G. Application of flow cytometry to immunohematology. J Immunol Methods 1987;101:127–31.

6. Garratty G. Immune hemolytic anemia associated with negative routine serology. Semin Hematol 2005;42:156–64.

7. Garratty G. Immunobiology of transfusion medicine. New York: Marcel Dekker, 1994.

8. McGann PT, McDade J, Mortier NA, Combs MR, Ware RE. IgA-mediated autoimmune hemolytic anemia in an infant. Pediatr Blood Cancer 2011;56:837–9.

9. Duarte-Rey C, Bogdanos DP, Leung PS, Anaya JM, Gershwin ME. IgM predominance in autoimmune disease: genetics and gender. Autoimmune Rev 2012;11:A404–12.

10. Stroncek DF, Njoroge JM, Procter JL, Childs RW, Miller J. A preliminary comparison of flow cytometry and tube agglutination assays in detecting red blood cell-associated C3d. Transfus Med 2003;13:35–41.

11. Fueger JT, Gottschall JL, Curtis BR, Johnson ST. DAT negative immune hemolytic anemia: the role of enhanced techniques [abstract]. Transfusion 2003;43:103A.

12. Green GA. Autologous IgM, IgA and complement binding to sickle erythrocytes in vivo: evidence or the existence of dense sickle cell subsets. Blood 1993;82:985–92.

W. Beres et al.

Fig. 3 A DAT-negative patient sample evaluated by flow cytometry for RBC-bound IgG, IgA, and IgM. The histogram results were overlaid on top of the unstained negative control. The sample had elevated levels of RBC-bound IgG (22.12%), IgA (8.00%), and IgM (17.12%). For this testing, the normal ranges of RBC-bound immunoglobulin were IgG: 0–4.91%; IgA: 0–4.20%; IgM: 0–4.01%. DAT = direct antiglobulin test, RBC = red blood cell.


13. Beres W, Nance S. Stability of in vitro red blood cell (RBC)-bound IgG, IgA and IgM by flow cytometric (FC) analysis [abstract]. Transfusion 2013;53:182A.

14. Beres W, Nance SJ. Evaluation of normal donor pools for RBC-bound immunoglobulin (Ig) levels measure by flow cytometry [abstract]. Transfusion 2014;54:179A.

15. Hunt AF, Reed MI. Tannic acid and chromic chloride-induced binding of protein to red cells: a preliminary study of possible binding sites and reaction mechanisms. Med Lab Sci 1990;47:189–94.

16. Fung ML, Grossman BJ, Hillyer CD, Westhoff CM, eds. Technical manual. 18th ed. Arlington, VA: American Association of Blood Banks, 2014:425–7.

17. The instrument controls in CellQuest. In: Operator training manual FACSCalibur. San Jose, CA: Becton Dickinson Immunocytometry Systems, 1999;5:6, 10.


18. Beres W, McGuire L, Nance S, Meny G. Detection of in vivo red blood cell (RBC) bound IgG measured by flow cytometry (FC) [abstract]. Transfusion 2010;50:166A.

19. Arndt PA, Garratty G. A critical review of published methods for analysis of red cell antigen-antibody reactions by flow cytometry, and approaches for resolving problems with red cell agglutination. Transfus Med Rev 2010;24:172–94.

Wendy Beres, BS, Immunohematology Assay Development Associate II (corresponding author), Biomedical Services, American Red Cross, 700 Spring Garden St., Philadelphia, PA 19123, [email protected]; Geralyn M. Meny, MD, MS, MT(ASCP)SBB, Physician Consultant, Grifols Diagnostic Solutions, Inc., Emeryville, CA; and Sandra Nance, MS, MT(ASCP)SBB, Senior Director, Immunohematology Reference Laboratory, Biomedical Services, American Red Cross, Philadelphia, PA.

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Trends of ABO and Rh phenotypes in transfusion-dependent patients in PakistanN. Anwar, M. Borhany, S. Ansari, S. Khurram, U. Zaidi, I. Naseer, M. Nadeem, and T. Shamsi

Original repOrt

The objective of this study was to determine the prevalence of ABO and Rh phenotypes in the general Pakistan population. This information could be used to help reduce the rate of alloimmunization in patients with blood disorders, such as thalassemia major, who require frequent blood transfusions. A total of 242 patients with blood disorders requiring frequent blood transfusions were enrolled in the study. ABO and Rh typing was performed on samples from these patients using tube and gel methods. Of these 242 patients, 146 (60.4%) were male and 96 (39.6%) were female. The prevalence of ABO and D phenotypes was as follows: group O, D+ (38.8%), group O, D– (2.5%), group B, D+ (32.2%), group A, D+ (17.4%), group A, D– (1.7%), and group AB, D+ (7.4%). Of the 242 patients, 232 (95.8%) were D+ and 10 (4.2%) were D–. The most prevalent Rh antigen was found to be e (97%), followed by D (95%), C (89.6%), c (62.8%), and lastly, E (22.6%). The prevalence of Rh phenotypes was: R1R1 (37.7%), R1r (33.4%), R1R2 (19.4%), R2r (5.2%), and rr (4.3 %). All of the D– patients were rr. In our study, the highest prevalence of ABO phenotypes was group O and the most prevalent Rh antigen was e. Rh phenotyping, along with antibody screening and identification should be performed prior to transfusion of patients requiring multiple transfusions to reduce and possibly prevent the rate of alloimmunization. Immunohematology 2016;32:170–173.

Key Words: ABO, Rh phenotype, alloimmunization

Among the blood group systems discovered to date, the ABO and Rh systems are the most clinically significant in the field of transfusion medicine.1–3 The ABO system was identified by Karl Landsteiner in 1901, and the Rh system was delineated in 1940 by Landsteiner and Weiner.3,4 The ABO blood group system is critical because it is the only blood group system in which antibodies are constantly, predictably, and naturally present in the serum of people who lack the antigen.2 Currently, more than 50 Rh antigens have been discovered in the Rh system, 5 of which are associated with commonly made clinically significant antibodies, namely, D, C, E, c, and e.3,5,6

Both systems are important because of the immuno-genicity of their antigens and the potency of their antibodies; the diverse genetic polymorphism within the Rh system is particularly immunogenic, because Rh antigens have been implicated in hemolytic disease of the newborn and delayed hemolytic transfusion reactions.3,6 Previous studies that focused on patients with thalassemia of predominantly

Asian descent emphasized that transfusion of phenotypically matched blood for the four Rh antigens, compared with blood phenotypically matched for the standard ABO and D antigens, proves to be effective in preventing alloimmunization.7,8

In Pakistan, thalassemia major constitutes the major bulk of red blood cell (RBC) transfusion-dependent disorders where alloimmunization is frequently observed—with Rh antigens being implicated as the most common cause, occurring because of incompatibilities between patients and blood donors.8 Furthermore, routine blood group typing of patients identifies ABO and D only.7,8 Typing patients and donors to match for the other four common Rh antigens would significantly reduce RBC alloimmunization and reduce the frequency of transfusion in patients with thalassemia.8,9 Moreover, it is important to know the prevalence of Rh phenotypes in the patient population receiving regular blood transfusions in order to prevent alloimmunization. ABO phenotypes have been observed and studied in various regions of the country, but limited data have been reported from Pakistan on Rh phenotype prevalence. Delineating Rh prevalence is necessary in finding compatible blood for patients with Rh alloantibodies requiring regular blood transfusion, as emphasized by a regional study done on blood donors.9 Therefore, with this objective, this study was undertaken to determine the prevalence of ABO and Rh phenotypes in patients with transfusion-dependent blood disorders.


The study was conducted at the blood bank department of the National Institute of Blood Diseases and Bone Marrow Transplantation, Karachi, Pakistan, from August 2012 to October 2014 and was approved by the institutional ethics committee. All patients who presented with blood disorders requiring frequent blood transfusions during the study period and who had not yet received their first transfusion were included in the study. Informed consent was obtained in the local language before enrolling patients in the study.

A 5.0-mL blood sample was drawn from each patient: 2.0 mL in a tube containing ethylenediaminetetraacetic acid


ABO and Rh phenotypes in Pakistan

(EDTA) and 3.0 mL in a plain vial. ABO and Rh were tested using the tube method for serologic testing.

Forward and reverse ABO grouping was performed by the tube method and by gel technology. For forward ABO grouping, commercially available monoclonal blood group antisera (anti-A; anti-B; anti-A,B; anti-H; anti-A1) were used, and for reverse grouping, 3–5 percent pooled RBC suspensions of group A, B, and O cells prepared in-house were used. Gel testing by IDcard LISS/Coombs was also used as required. D typing was done by the tube method using monoclonal/polyclonal anti-D (Rh0 and Rh1) and by using the gel method card. For detecting C, c, E, and e, specific monoclonal reagent antisera were used and testing was performed using the standard tube agglutination method. Samples showing no agglutination with anti-D were tested by the indirect antiglobulin test (IAT) for the presence of weak D.

Both Rh control and Coombs control cells were used to ensure diagnostic sensitivity and specificity for the detection of D. In addition, commercial RBCs (rr, R1R1, and R2R2) were used with negative antigenic expression of E, C, c, and e to serve as controls for the antisera testing; false-positive and false-negative results were avoided by performing quality control with each step.

All antisera, gel cards, and reagent red cells used in the ABO and Rh testing were obtained from Diamed (Cressier FR, Switzerland).

A statistical package (SPSS-17, IBM, Armonk, NY) was used to analyze the data. Prevalence percentages were computed for categorical variables, and mean and standard deviation (SD) were calculated for quantitative variables.

Results

A total of 242 patients, having known blood disorders that required frequent blood transfusions and having no prior history of transfusion, were enrolled after obtaining informed consent; 146 (60%) were male and 96 (40%) were female. The patients included 222 with known cases of beta thalassemia major, 12 with aplastic anemia, 4 with pure RBC aplasia, 2 with Diamond-Blackfan anemia, and 2 with chronic lymphocytic leukemia. Thus, the majority were patients with thalassemia major. Their ages ranged from 1 month to 40 years, and their median age was 3 years. Prevalence of ABO and D phenotypes is shown in Figure 1. The overall prevalence of Rh phenotypes is shown in Figure 2. In this group, 232 (96%) were D+ and 10 (4%) were D–. All of the D– patients were observed to be rr; weak D was not found in any of the D– patients. The

prevalence of Rh antigens in our study and their similarities with other Asian populations is shown in Table 1.10,11

Discussion

The prevalence of ABO and D phenotypes among the studied patients were as follows: group O, D+ (38.8%), group O, D– (2.5%), group B, D+ (32.2%), group A, D+ (17.4%), group A, D– (1.7%), and group AB, D+ (7.4%). Analysis from previous studies on the prevalence of ABO in the Pakistan population revealed that, in the provinces of Sindh and Baluchistan, the order of prevalence of ABO phenotypes is O > B > A > AB, which is similar to that of the present study; whereas in the regions of Punjab and Khyber Pakhtunkhwa, the order was B > O > A > AB, with B being the most prevalent

Fig. 1 Prevalence of ABO and D phenotypes in the studied Pakistan patient population.

O+ B+ A+ AB+ O– A–

38.8%32.2%

17.4%

7.4%2.5% 1.7%

Fig. 2 Prevalence of Rh phenotypes in the studied Pakistan patient population.

R1R1 R1r R1R2 R2r rr

37.7%33.4%

19.4%

5.2% 4.3%

Table 1. Comparison of prevalence of Rh antigens in the studied Pakistan patient population with that in other Asian populations

Rh antigen

Our study(n = 242)

%

UAE study10

(n = 661)%

India study11

(n = 1240)%

e 97 97.3 98.3

D 95 91.1 84.76

C 89.6 73.2 84.76

c 62.8 71 52.82

E 22.6 21 17.9

UAE = United Arab Emirates.


ABO blood group.12–16 Studies done in the United States, Britain, Bangladesh, Sudan, India, and Saudi Arabia6,17–21 also revealed that group O is the most prevalent ABO blood group. In Nepal, however, group A is the most prevalent ABO group.22 Group AB is the least prevalent blood group throughout the world, and the same was found in our study.18–22

Our results show that none of the patients whose samples typed as D– had weak D; Sharma and colleagues in India1 observed the same. The most and least prevalent Rh antigens in our study population were e (97%) and E (22.6%), respectively. This finding is in concordance with other Asian studies, as shown in Table 1.10,11 Similar findings were observed in Palestine and Europe, where e was the most prevalent and E was the least prevalent Rh antigen.6,23 In another Indian study, however, among Rh antigens, D was the most prevalent.1 According to a study done in Sudan, the prevalence of Rh antigens was D (93%), e (79.5%), c (68.5%), C, (27%), and E (18.5%).3

In our study, R1R1 was found to be the most prevalent Rh phenotype, and all of our D– patients were observed to be rr. Similar results were observed by Sharma et al.1 In another study, R1R1 was also found to be most prevalent.24

In Pakistan, limited studies are available on Rh phenotypes. A recent regional study identifying the ABO and Rh phenotypes in blood donors showed quite similar results as we found in our patients, which shows that the phenotypes of frequently transfused patients do not differ from the regional donor pool in Pakistan.9 Nonetheless, studies on a larger scale are needed for us to identify the actual RBC phenotypes of our population. Because antibodies against Rh antigens are implicated as the most common cause of alloimmunization in patients in Pakistan requiring frequent blood transfusions, transfusion of Rh antigen–matched blood, especially in this patient population, may significantly reduce the rate of alloimmunization.7–9

Once an antibody develops in a patient, the only blood that can be transfused to that patient without harm is blood that is antigen-negative for the identified antibody. In addition to patient Rh typing, donor Rh typing must also be performed. Donor typing would help us build an inventory of various Rh-phenotyped units that could be matched to a patient’s Rh phenotype in addition to providing the required antigen-negative blood if the patient has non-Rh antibodies. This inventory would save time and resources in times of need. The lack of information on the Rh phenotypes in our donor pool is one of the major limitations of our study.

In conclusion, our study showed the order of prevalence of ABO phenotypes in Pakistan patients was O > B > A > AB. In the Rh system, e was the most prevalent antigen and the least common was E. In Rh phenotypes identified in our study population, R1R1 was the most prevalent and rr was the least prevalent. Rh antigenic phenotyping, along with antibody screening and antibody identification prior to transfusion of patients requiring multiple transfusions, should be performed on all patients to reduce alloimmunization. Furthermore, complete Rh typing of blood donors and regional studies on larger donor populations are needed to help not only in finding compatible units of blood, but in building a donor database of common as well as rare phenotypes.

Acknowledgments

The authors would like to acknowledge the patients for their participation and blood bank staff for their substantial aid in coordination of the study.

References

1. Sharma DC, Singhal S, Rai S, Iyenger S, Sao S, Jain B. Incidence of Rh antigens, phenotype and probable genotype in the population of Gwalior and Chambal region, Central India. Int Blood Res Rev 2013;1:29–43.

2. Shakir M, Khan SA, Ghani E. Frequency of ABO and RH (D) blood group systems among blood donors in Rawalpindi/Islamabad area. PASFMJ 2012;62. Available at http://www.pafmj.org/.

3. Shahata WM, Khalil HB, Abass A-E, Adam I, Hussien SM. Blood group and Rhesus antigens among blood donors attending central blood bank in Sudan. Sudan JMS 2012;7:245–8.

4. Daniels G, Fletcher A, Garratty G, et al. Blood group terminology 2004: from the International Society of Blood Transfusion committee on terminology for red cell surface antigens. Vox Sang 2004;87:304–16.

5. Makroo R, Gupta R, Bhatia A, Rosamma NL. Rh phenotype, allele and haplotype frequencies among 51,857 blood donors in North India. Blood Transfus 2014;12:36–9.

6. EL-Wahhab Skaik YA. The Rh allele frequencies in Gaza city in Palestine. Asian J Transfus Sci 2011;5:150–2.

7. Singer ST, Wu V, Mignacca R, Kuypers FA, Morel P, Vichinsky EP. Alloimmunization and erythrocyte autoimmunization in transfusion-dependent thalassemia patients of predominantly Asian descent. Blood 2000;96:3369–73.

8. Zaidi U, Borhany M, Ansari S, et al. Red cell alloimmunisation in regularly transfused beta thalassemia patients in Pakistan. Transfus Med 2015;25:106–10.

9. Karim F, Moiz B, Mohammad FJ, Ausat F, Khurshid M. Rhesus and Kell phenotyping of voluntary blood donors: foundation of a donor data bank. J Coll Physicians Surg Pak 2015;25: 757–60.

N. Anwar et al.


ABO and Rh phenotypes in Pakistan

10. Taha JY. Rh antigen and phenotype frequency in Kalba region, UAE. Bahrain Med Bull 2012;34.

11. Thakral B, Saluja K, Sharma RR, Marwaha N. Phenotype frequencies of blood group system (Rh, Kell, Kidd, Duffy, MNSs, P, Lewis and Lutheran) in North Indian blood donors. Transfus Apher Sci 2010;43:17–22.

12. Khan MS, Farooq N, Qamar N, et al. Trend of blood groups and Rh factor in the twin cities of Rawalpindi and Islamabad. J Pak Med Assoc 2006;56:299.

13. Alam M. ABO and Rhesus blood groups in potential blood donors at Skardu (northern areas). Pak J Pathol 2005;16:94–7.

14. Khattak ID, Khan TM, Khan P, Shah SM, Khattak ST, Ali A. Frequency of ABO and Rhesus blood groups in District Swat, Pakistan. J Ayub Med Coll Abbottabad 2008;20:127–9.

15. Mahmood MA, Anjum AH, Train SM, Shahid R, Usman M, Khawar SH. Pattern of ABO and Rh blood groups in Multan region. Biomedica 2005;2:1–4.

16. Ali N, Anwar M, Bhatti FA, Nadeem M, Nadeem A, Ali M. Frequency of ABO and Rh blood groups in major ethnic groups and casts of Pakistan. Pak J Med Sci 2005;21:26–9.

17. Garratty G, Glynn SA, McEntire R. ABO and Rh(D) phenotype frequencies of different racial/ethnic groups in the United States. Transfusion 2004;44:703.

18. Canadian Blood Services–Société canadienne du sang. Types & Rh System, Canadian Blood Services. Retrieved 2010-11-9. https://blood.ca/en

19. Periyavan S, Sangeetha S, Marimuthu P, Manjunath B, Seema D. Distribution of ABO and Rhesus-D blood groups in and around Bangalore. Asian J Transfus Sci 2010;4:41.

20. Talukdar SI, Das RK. Distribution of ABO and Rh blood groups among blood donors of Dinajpur district of Bangladesh. Dinajpur Med Col J 2010;55:58.

21. Bashwari LA, Al-Mulhim AA, Ahmad MS, Ahmed MA. Frequency of ABO blood groups in the Eastern region of Saudi Arabia. Saudi Med J 2001;22:1008–12.

22. Pramanik T, Praminic S. Distribution of ABO and Rh blood groups in Nepalese medical students: a report. East Mediterr Health J 2000;6:156–8.

23. Daniels GL. Human blood groups. 2nd ed. Oxford, UK: Blackwell Science, 2002.

24. Furqan E, Shamsi TS, Ahmed A, Syed S. Prevalence of Rhesus phenotypes among local population in Karachi. J Pak Med Assoc 1998;48:278–9.

Nida Anwar, FCPS, Consultant Hematologist, Department of Hematology of National Institute of Blood Disease & Bone Marrow Transplantation, Karachi, Pakistan; Munira Borhany (corresponding author), FCPS, Consultant Hematologist, Head of Department of Blood Bank of National Institute of Blood Disease & Bone Marrow Transplantation, St/2 A Block 17, Gulshan-e-Iqbal KDA Scheme 24, Karachi, Pakistan, 75300, [email protected]; Saqib Ansari, PhD, Consultant Hematologist, Department of Hematology of National Institute of Blood Disease & Bone Marrow Transplantation, Karachi, Pakistan; Sana Khurram, FCPS, Consultant Hematologist, Department of Hematology of National Institute of Blood Disease & Bone Marrow Transplantation, Karachi, Pakistan; Uzma Zaidi, FCPS, Consultant Hematologist, Department of Hematology of National Institute of Blood Disease & Bone Marrow Transplantation, Karachi, Pakistan; Imran Naseer, BS, Department of Blood Bank of National Institute of Blood Disease & Bone Marrow Transplantation, Karachi, Pakistan; Muhammad Nadeem, FCPS, Consultant Hematologist, Department of Hematology of National Institute of Blood Disease & Bone Marrow Transplantation, Karachi, Pakistan; and Tahir Shamsi, FRCPath, Consultant Hematologist, Department of Hematology of National Institute of Blood Disease & Bone Marrow Transplantation, Karachi, Pakistan.

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