adverse effects of asparaginase in pediatric patients with

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Theses and Dissertations (ETD) College of Graduate Health Sciences

8-2015

Adverse Effects of Asparaginase in Pediatric Patients with Acute Adverse Effects of Asparaginase in Pediatric Patients with Acute

Lymphoblastic Leukemia Lymphoblastic Leukemia

Chengcheng Liu University of Tennessee Health Science Center

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Recommended Citation Recommended Citation Liu, Chengcheng , "Adverse Effects of Asparaginase in Pediatric Patients with Acute Lymphoblastic Leukemia" (2015). Theses and Dissertations (ETD). Paper 157. http://dx.doi.org/10.21007/etd.cghs.2015.0185.

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Adverse Effects of Asparaginase in Pediatric Patients with Acute Lymphoblastic Adverse Effects of Asparaginase in Pediatric Patients with Acute Lymphoblastic Leukemia Leukemia

Abstract Abstract Acute lymphoblastic leukemia (ALL) is the most common type of childhood cancer. Asparaginase is a critical treatment component for ALL. However, its use is complicated by adverse effects, such as hypersensitivity, osteonecrosis and pancreatitis.

Hypersensitivity to asparaginase typically requires discontinuation of current formulation and substitution with other formulations, but the differential diagnosis can be challenging, and the diagnostic utility of antibody tests is unclear. We comprehensively analyzed anti-Elspar (native E.coli asparaginase) IgG antibodies in 410 pediatric patients treated on an asparaginaseintensive front-line clinical trial. Of 169 patients (41.2%) who exhibited clinical allergy, 147 (87.0%) were positive for anti-Elspar antibody. Of 241 patients without clinical allergy, 89 (36.9%) had detectable antibody. Among those positive for antibody, the antibody titers were higher in those who developed allergy than in those who did not (P < 1.0 × 10-15). Antibody measures at week 7 of continuation therapy had a sensitivity of 87%-88% and a specificity of 68%-69% for predicting or confirming clinical reactions. Antibodies were inversely associated with serum asparaginase activity (P = 7.0 × 10-6 ). Interestingly, high antibodies were associated with a lower risk of osteonecrosis (odds ratio = 0.83; 95% confidence interval, 0.78-0.89; P = 0.007), which is a dose-limiting adverse effect of glucocorticoids but has also been linked to asparaginase treatment. We conclude that antibodies were related to clinical allergy and to low systemic exposure to asparaginase, leading to lower risk of other adverse effects of therapy. Measures of serum antibodies to asparaginase can be useful in patients with ALL.

Osteonecrosis is a common dose-limiting toxicity of glucocorticoids. Data from clinical trials suggest that other medications can increase the risk of glucocorticoid-induced osteonecrosis. Here we utilized a mouse model to study the effect of asparaginase treatment on dexamethasone-induced osteonecrosis. After 6 weeks of treatment, mice receiving asparaginase along with dexamethasone had a higher rate of osteonecrosis than those receiving only dexamethasone (44% vs. 10%, P = 0.006). Primary epiphyseal arteriopathy, an initiating event for osteonecrosis, was observed in 58% of mice receiving asparaginase and dexamethasone compared to 17% of mice receiving dexamethasone only (P = 0.007). As in the clinic, greater exposure to asparaginase was associated with greater plasma exposure to dexamethasone (P = 0.0001). This model also recapitulated other clinical risk factors for osteonecrosis, including age at start of treatment, and association with the systemic exposure to dexamethasone (P = 0.027) and asparaginase (P = 0.036). We conclude that asparaginase can potentiate the osteonecrotic effect of glucocorticoids.

Acute pancreatitis is a serious complication of asparaginase with no definitive treatment. Risk factors for asparaginase-induced pancreatitis, especially the genetic predisposition, have not been clearly identified. We studied 5398 pediatric patients with ALL and showed that older age, higher exposure to asparaginase, higher Native American ancestry or African ancestry were independent clinical risk factors for pancreatitis. To determine genetic risk factors, we performed a genome-wide association study. A rare nonsense variant rs199695765 in CPA2, a pancreatic enzyme, was highly associated with pancreatitis (odds ratio = 588, 95% confidence interval 66.8- 5166, P = 9.0 ×10-9 ). A gene-level analysis showed an excess of additional CPA2 variants in those who did versus did not develop pancreatitis (P = 0.018). Furthermore, common variants in genes critical to purine metabolism and cytoskeleton function were also associated with development of pancreatitis. Our findings are consistent with a mixed genetic architecture underlying serious adverse drug effects, wherein a combination of rare but highly penetrant and common but weakly penetrant genetic risk factors contribute to genetic risk. For the patients carrying the highly penetrant variants, consideration should be given to treatment with a nonasparaginase

containing ALL chemotherapy regimens.

Overall, we studied the major adverse effects of asparaginase in patients treated for ALL. These findings will provide important guidance for precision medicine.

Document Type Document Type Dissertation

Degree Name Degree Name Doctor of Philosophy (PhD)

Program Program Biomedical Sciences

Research Advisor Research Advisor Mary V. Relling, Pharm.D.

Keywords Keywords Acute lymphoblastic leukemia Asparaginase, GWAS, Hypersensitivity, Osteonecrosis, Pancreatitis

Subject Categories Subject Categories Diseases | Medical Sciences | Medicine and Health Sciences | Therapeutics

This dissertation is available at UTHSC Digital Commons: https://dc.uthsc.edu/dissertations/157

https://dc.uthsc.edu/dissertations/157

ADVERSE EFFECTS OF ASPARAGINASE IN PEDIATRIC PATIENTS WITH ACUTE LYMPHOBLASTIC LEUKEMIA

DEDICATION

This work is dedicated to my parents Haiying Liu Hua Cheng

and my husband Hao Wu

Thank you for all of your love and support along the way.

ACKNOWLEDGEMENTS

ABSTRACT

E.coli

P

PP

P

PP

P P

CPA2P

CPA2P

TABLE OF CONTENTS

CHAPTER 1. BACKGROUND ........................................................................................1

E.coli

Erwinia

CHAPTER 2. ASPARAGINASE HYPERSENSITIVITY ...........................................10

Ex vivo

CHAPTER 3. POTENTIATING EFFECT OF ASPARAGINASE ONGLUCOCORTICOID-INDUCED OSTEONECROSIS ..............................................38

CHAPTER 4. ASPARAGINASE-INDUCED ACUTE PANCREATITIS .................51

CPA2

CPA2

CHAPTER 5. SUMMARY ..............................................................................................82

LIST OF REFERENCES ................................................................................................83

APPENDIX A. SUPPLEMENTARY INFORMATION FOR CHAPTER 2 .............97

APPENDIX B. SUPPLEMENTARY INFORMATION FOR CHAPTER 3 ...........111

APPENDIX C. SUPPLEMENTARY INFORMATION FOR CHAPTER 4 ...........139

VITA................................................................................................................................171

LIST OF TABLES

CPA2

P

P

LIST OF FIGURES

Ex vivo

LIST OF ABBREVIATIONS

CHAPTER 1. BACKGROUND

Acute Lymphoblastic Leukemia (ALL)

BCR ABL1

Asparaginase

Introduction

Escherichia coli

E.coli

E.coli- Erwinia chrysanthemi

Formulations

E.coli E.coli Erwinia

chrysanthemi

Native E.coli asparaginase

E.coli

E.coli

E.coli

E.coli

PEG-asparaginase

E.coli

E.coli E.coli

E.coli

Erwinia asparaginase

ErwiniaE.coli

Erwinia

E.coli Erwinia E.coli

ErwiniaErwinia

Erwinia

Adverse effects

Hypersensitivity

E.coli

E. coli Erwinia

E.coli

E.coli

Acute pancreatitis

PRSS1 and PRSS2SPINK1

CFTR

CTRC CASR CLDN2CPA1 HLA-DRB1

Drug interaction with glucocorticoids

Effect on glucocorticoid-induced osteonecrosis

Figure 1-1

Figure 1-1. Proposed mechanisms of glucocorticoid-induced osteonecrosis

Pharmacogenomics: A Brief Introduction

Cohort study

Case-control study

Candidate-gene approach

TPMTTPMT

TPMTa priori

GWAS

CHAPTER 2. ASPARAGINASE HYPERSENSITIVITY*

Introduction

Methods

Patients

Table 2 1

Asparaginase regimen and sample collection

Leukemia.

Table 2-1. Clinical features of patients with (n = 410) and without (n = 88) samples evaluable for anti-asparaginase antibodies

Clinical features Patients with samplesn (%)

Patients without samplesn (%)

P

Figure 2 1

Erwinia

Phenotyping of clinical allergy to asparaginase

Anti-asparaginase antibodies

Antibody assay

Table 2 2

Appendix A Table A 1Figures A 1 A 3

Figure 2-1. Total XV asparaginase regimen and anti-asparaginase antibody measurements

Table 2-2. Number of patients with evaluable blood samples at each time point

Time point of antibody test Number of patients (samples)

Day 5 19 34 Week 7 Week 17

Induction Consolidation Continuation (Reinduction I) (Reinduction II)

10000 U/m2

Weeks 1 4 7 1 4 7 1 4 7 10 14 17 20 47

10000 U/m2

25000 U/m210000 U/m2

ASP (LR)

( )( )

ANTI-ASP

ASP (SHR)

Induction AUC Continuation AUCANTI-ASPAUC

Data analysis

Equation 2 1 Equation 2 2Equation 2 3

Appendix A

(Eq. 2 1)

(Eq. 2 2)

(Eq. 2 3)

Estimation of antibody area-under-the-curve (AUC)

Figure 2 1

Figure A 4

Asparaginase activity

Figure 2-2

Figure 2-2. Enzyme reactions in asparaginase activity assay

E. coli

Ex vivo asparaginase neutralization assay

ex vivo

Prognostic value of antibody tests

Sensitivity, specificity and predictive values

Receiver-operator-characteristic (ROC) curves

Asparaginase adverse effects in Total XV

Statistical analysis

rpart

Results

Asparaginase allergy

P =

P = Figure 2-3

Table 2-3

Table 2-4 Table 2-5P = P

=

P =

P = P =

P =

Antibodies and allergy

P

P = P = P

(P

Figure 2-4

P =

P =

Figure 2-3. Frequency of hypersensitivity to Elspar

PP =

Table 2-3. Timing of allergic reaction to Elspar

Phase Low-risk(n = 100)

Standard/high-risk(n = 69)

Total(n = 169)

Table 2-4. Clinical features and allergic reactions to Elspar

All patients (n = 410) Low-risk arm (n = 197) Standard/high-risk arm (n = 213)

Clinicalfeatures

n Allergyn (%)

No allergyn (%)

P n Allergyn (%)

No allergyn (%)

P n Allergyn (%)

No allergyn (%)

P

Table 2-5. Clinical features and anti-Elspar antibody status

All patients (n = 410) Low-risk arm (n = 197) Standard/high-risk arm (n = 213)

Clinicalfeatures

n Positiven (%)

Negativen (%)

P n Positiven (%)

Negativen (%)

P n Positiven (%)

Negativen (%)

P

Figure 2-4. Antibody levels in patients with and without clinical reactions

P = P =

Figure 2-5

Table 2-6

Table A-2 Figure A-5

Figure 2-6

Figure 2-6

P = P = Figure 2-7

Figure 2-4

P = Figure A-6

Figure 2-8

Figure 2-5. Anti-Elspar antibody level relative to the time of clinical reaction to Elspar

Table 2-6. Sensitivity, specificity and predictive values of three anti-Elspar antibody tests for predicting or confirming clinical reactions to Elspar

Risk arm N of patients

Time of Ab test

Time of Rxn

Time between test and rxn

(weeks)

Sensitivity(%)

Specificity(%)

PPV(%)

NPV(%)

Figure 2-6. ROC curves of the antibody tests

Figure 2-7. Association between week 7 anti-Elspar antibody level and the proportion of patients reacting to Elspar around week 7

Figure 2-8. The frequency of hypersensitivity to Oncaspar and Erwinase

Antibodies and serum asparaginase activity

in vivo

P = P = Figure 2–9

in vivo

P =

P =

exvivo Figure 2–10

= P = Figure 2–10A

= P = Figure 2–10B

Antibodies and adverse effects

P = Table 2–7

Figure 2–11

P= P = P =

P = Figure 2–11

Figure 2-9. Correlation between serum asparaginase activity and antibody level

Figure 2-10. Ex vivo neutralization of patient sera with antibodies

Table 2-7. Multivariate analysis showed that low anti-Elspar antibody area-under-curve (AUC) was a risk factor of osteonecrosis (n = 360)

Patient characteristics P Hazard ratio (95% CI)

Figure 2-11. Cumulative incidence of osteonecrosis based on anti-asparaginase antibody AUC

P PP =

P = P =

Discussion

Table 2-6

Figure A-7

Figure 2-7

Figures 2-6 and A-5

Figure 2-9ex vivo

Figure2-10

Figure 2-9

Figure2-11

Figure 2-11D

Table 2-7

P =

P = P =

Conclusion

CHAPTER 3. POTENTIATING EFFECT OF ASPARAGINASE ON GLUCOCORTICOID-INDUCED OSTEONECROSIS

Introduction

Methods

Chemicals

Animals

Appendix B Table B-1 Figure B-1

Asparaginase and dexamethasone pharmacokinetics

Figure 3-1

Figure 3-2 Appendix B

Mouse model of dexamethasone-induced osteonecrosis

Appendix B Tables B-1 B-2 Figures B-1 B-7

Figure 3-1. Dexamethasone and asparaginase treatment regimens

Effect of asparaginase on osteonecrosis

Figure 3-1

Plasma dexamethasone concentration and asparaginase activity

Appendix B

Histological evaluation of osteonecrosis and arteriopathy


Results

Plasma dexamethasone concentration was increased by asparaginase treatment

Figure 3-1

P =

P = Figure 3-2

Asparaginase treatment potentiated osteonecrosis and arteriopathy in dexamethasone-treated mice

Figure 3-1

P

P =

P = Figure 3-3

P =

P = Appendix B Figure B-8

P = P = Figure 3-4

Figure 3-2. Plasma dexamethasone concentration was positively associated with asparaginase activity in PK experiment

Figure 3-3. Asparaginase treatment potentiated osteonecrosis and arteriopathy in dexamethasone-treated mice

Figure 3-4. Osteonecrosis was associated with higher plasma dexamethasone and asparaginase levels in mice receiving both dexamethasone and asparaginasetreatment

P P

Arteriopathy was likely the initiating event of osteonecrosis

P =

Figure 3-5Figure 3-5D

Figure 3-5E

Figure 3-5F

Figure 3-5IFigure 3-5G

Discussion

Figure 3-2 Figure B-8

P = P =

P = P = Figure 3-4 P = P =

Figure 3-5. Histology of osteonecrosis and arteriopathy

E.coli

Appendix B

Figure B-9Figure B-10

Figure B-11Figure B-12

P Figure B-13

Table B-3P <

Figure B-14

Conclusion

CHAPTER 4. ASPARAGINASE-INDUCED ACUTE PANCREATITIS

Introduction

PRSS1 and PRSS2 SPINK1CFTR

CTRC CASR CLDN2CPA1 HLA-DRB1

Methods

Patients and treatment

Table 4-1 Figure 4-1

Table 4-1. Comparison of asparaginase regimens

Protocol Induction Consolidation Interim Maintenance (IM) and Delayed

Intensification (DI)

Maintenance Total ASP doseb

(U/m2)

Total ASP

weeksc

N (%) of patients

developingpancreatitis

E. coli E. coli

E. coli E. coli

E. coli

E. coli

E. coli E. coli E. coli

Table 4-1. (Continued)

Protocol Induction Consolidation Interim Maintenance (IM) and Delayed

Intensification (DI)

Maintenance Total ASP doseb

(U/m2)

TotalASP

weeksc

N (%) of patients

developing pancreatitis

E.coli

E.coli E.coli E.coli E.coli E.coli

Figure 4-1. Study design

P

Table 4-2

Diagnosis of acute pancreatitis

Genotyping

Figure 4-1

Figure 4-1

Table 4-5 Figure C-1

Figure 4-2

Table 4-2. Number of patients included in this study

Study Protocol N ofpatients

N (%) with array dataa

N (%) with deep sequencing datab

Figure 4-2. Race group assignments based on the ancestral composition of patients in the cohort (n = 5185) by treatment protocol

SNP-based analysis for pancreatitis

P

Gene-level analysis of nonsense variants using SKAT

Deep sequencing of selected genes

Table 4-2

Table 4-3Appendix C

Appendix C

Table 4-3. Putative genes associated with pancreatitis (n = 42) selected for deep sequencing based on GWAS result or literature review

Gene Official full name Function* SourceADAMTS18

AGER

ALS2CL

C11orf63

C12orf40

C9orf117

CASR

CD52CFTR

CLDN2

CPA1

Table 4 3. (Continued)

Gene Official full name Function* SourceCPA2

CTRC

DDX49

DOCK5

FHIT

GCKR

HOGA1

HSD17B2

IFNA5INMT

ITFG1

KLHDC1 HCFC2


Gene Official full name Function* SourceLRRC39 LRSAM1

MICAL2

MPZL3NMI

PHKB

PRSS1

PRSS2

RANBP10

RUFY4 FYCO1


Gene Official full name Function* SourceSCAMP3

SERPINA9

SLC6A18

SNTG2

SPAG8

SPINK1

TRAP1

ZNF233

ZNF701

ZRANB3


ctree party

Results

Pancreatitis associated with asparaginase

Figure 4-3A

Figure 4-3AFigure 4-4

P = = P = Figure

4-3B CP =

Clinical risk factors

Figure 4-5P =

P =

Table 4-1

Figure 4-3. Incidence of pancreatitis differed by protocols

E. coli

E. coli

Figure 4-4. Time of pancreatitis in the cohort (n = 5185) during the first year of therapy

Figure 4-5. The incidence of pancreatitis based on clinical characteristics *

P = Table 4-4

Figure 4-6Table 4-1

E.coli

Figure 4-7

P =

P =

Gene-level analysis of nonsense variants identified CPA2

PTable 4-5 CPA2

P = Figure 4-8A

Figure 4-8B

GWAS of common SNPs

FHIT P = P =

DOCK5 ACTN2 MICAL2 Table4-6

P

Appendix C Tables C-1, C-2 C-3

Table 4-4. Multivariate analysis for clinical risk of pancreatitis in the cohort study (n = 5185)

Patient characteristics P Odds ratio (95% CI)

§

E.coli

§ E.coli

Figure 4-6. Association between Native American ancestry and pancreatitis

Figure 4-7. CART analysis of clinical risk factors for pancreatitis in the cohort (n = 5185)

Table 4-5. Six genes associated with pancreatitis from the gene-level analysis of nonsense SNPs

Cohort (n = 3256) Case-control (n = 213)Gene Chr Nonsense

SNPs(major

allele/risk allele)

Population RAF%

(n)a

CADDscore

RAF% in

patients with AP(n = 95)

RAF% in patients without

AP(n = 3161)

Coeff-icientc

(SE)

Pc RAF% in

cases(n =71)

RAF% in

controls(n =142)

Coeff-icientd

(SE)

Pd PPV/NPVe

(n = 3256)

CPA2

SERPINA9

HSD17B2

GCKR

ZNF233

SLC6A18

Figure 4-8. Nonsense SNP rs199695765 in CPA2 associated with pancreatitis

CPA2

P =

Table 4-6. Top 20 common SNPs (cohort risk allele frequency > 1%) significantly associated with pancreatitis in the cohort

Cohort(n = 5185)

Case-control(n = 213)

Cohort RAF vs race(n = 5185)

SNP Gene Chr Location Major allele/risk

allele

RAF% in patients with AP(n = 117)

RAF% in patients

without AP(n = 5068)

Coeff-icientb

(SE)

P RAF% in cases(n = 71)

RAF% in controls(n = 142)

Coeff-icientc

(SE)

P Hispanic Black

(n = 1527)

White Asian

(n = 3168)

FHIT

DOCK5

ACTN2

ITFG1

AGPAT4

FHIT

ITFG1

MICAL2

AGPAT4

MICAL2

ACTN2

PHKB

DOCK5

MICAL2


P

Deep sequencing detected novel variants in CPA2 and other candidate genes

apriori

PRSS1 PRSS2SPINK1 CFTR CASR CTRC CPA1 CLDN2 Table 4-3

CPA2Appendix

C Table C-4 CPA2 P

CPA2CPA2

P = Figure 4-8B

P =

Table4-5

Appendix C Table C-5 P

P P =

Figure C-2Table 4-3

Figure C-3

HOGA1P =

CPA2 P = P =

P =

Table C-6P

CFTRP =

P

Discussion

CPA2

Figure 4-8AFigure 4-8B

CPA2Table C-4

CPA2CPA2

CPA2

CPA1

CPA2

HOGA1

CPA2 HOGA1Table 4-6

FHIT

DOCK5 ACTN2 MICAL2

DOCK5

ACTN2

MICAL2

Table 4-6

PRSS1 PRSS2 SPINK1 CTRC CFTR, CASR CPA1 CLDN2

Table C-6P Table C-5 HLA-

DRB1*07:01P =

Figure 4-3

E.coli E.coli

E. coli

Figure 4-4Figure 4-3B C

Table 4-4 Figures 4-6 4-7Table 4-6

PCPA2

Conclusion

CPA2

CPA2

CHAPTER 5. SUMMARY

CPA2

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APPENDIX A. SUPPLEMENTARY INFORMATION FOR CHAPTER 2

Anti-asparaginase Antibody ELISA

Positive and negative controls

Asparaginase antigens

Measurement of anti-asparaginase IgG antibodies by ELISA

o

Normalization of Antibody Readings

Table A-1 Figure A-1

Equation A-1Equation A-2

(Eq. A 1)

(Eq. A 2)

Figure A-2

Table A-1. Comparison between antibody OD readings obtained at SJCRH (n = 1539) and UTHSC (n = 665)

Antigen Facility Positivecut-offa

Median (range) Mean (SD) ofpositive readings

Pb Mean (SD) ofnegative readings

Pb

Figure A-1. Anti-Elspar OD readings obtained at SJCRH (n = 1539) and UTHSC (n = 665) relative to the time of clinical reaction

Figure A-2. Fitted curves for (A) anti-Elspar, (B) anti-Erwinase and (C) anti-Oncaspar OD readings of the samples (n = 194) measured at both SJCRH and UTHSC

Figure A-2. (Continued)

Figure A-2A

Figure A-2B

Figure A-2C

Table A-1Figure A-3

Figure A-3. UTHSC OD readings before and after normalization

Figure A-4. Determination of AUC threshold

Table A-2. Sensitivity, specificity and predictive values of anti-Elspar antibody test at week 7 for predicting or confirming clinical reactions to Elspar using current positivity cutoff and optimized cutoff by recursive partitioning

Risk arm N of patients

Time of Ab test

Time of Rxn

Time between test and rxn

(weeks)

Cutoff OD value

Sensitivity(%)

Specificity(%)

PPV(%)

NPV(%)

Figure A-5. Week-7 optimal threshold of OD value to predict or to confirm clinical reactions

Figure A-6. Elspar has stronger cross-reactivity with Oncaspar than with Erwinase

Figure A-7. Sensitivity of antibody tests within 30 days of reactions

APPENDIX B. SUPPLEMENTARY INFORMATION FOR CHAPTER 3

Mouse Model of Dexamethasone-induced Osteonecrosis

Methods

Chemicals

Animals

Mycoplasma pulmonis

Treatments

Enteric and blood cultures

Measurement of plasma concentration of dexamethasone and corticosterone

m/zm/z m/z

m/z

Results

Body weight differed by substrains

PFigure B-1

P =

P =

P

Effect of substrain, source, age and treatment regimens on survival and development of osteonecrosis

Figure B-2

Figure B-1. Body weight of mice before and after treatment

PP

Figure B-2. Incidence of osteonecrosis increased with longer treatment duration

Figure B-3

P = Table B-1 P = Figure B-4A

Table B-1 Figure B-4B

P = Figure B-4A

Enterococcus faecalis

Figure B-4A

P = Figure B-4AP = Table B-1

Table B-2E. faecalis Staphylococcus xylosus Lactococcus lactis

E. faecalis

E. faecalis

Figure B-3. Similar histologic appearance of osteonecrosis in mice of different substrain, age and treatment groups

Table B-1. Incidence of ON in male BALB/c mice from different experiments

Substrain Source Age DEX Treatmentduration(weeks)

Frequency of ONa

(n positive/n analyzed)

Figure B-4. Survival differed by substrains, sources, regimens and age of mice

Table B-2. Enteric culture isolates from BALB/cJ mice from vendor and in-house breeding colony

Vendor-derived In-house bredTime Isolate TCN

sensitivityTMP

sensitivityIsolate TCN

sensitivityTMP

sensitivityEnterococcus faecalis Enterococcus faecalis

Staphylococcus xylosus Lactococcus lactisStaphylococcus epidermidis Escherichia coli

Enterococcus faecalis Enterococcus faecalisEnterococcus gallinarum Enterococcus gallinarum

Dexamethasone pharmacokinetics and pharmacodynamics

P = P = Figure B-5A

Table B-1P = Figure B-5B

Figure B-6

Gender-dependent difference in susceptibility to osteonecrosis

P = Figure B-7A

P Figure B-7BP =

Figure B-7C

Discussion

Figure B-5. Plasma concentrations of dexamethasone

Figure B-6. Inverse association between plasma corticosterone and dexamethasone levels

Figure B-7. Gender-dependent differences in susceptibility to osteonecrosis

Table B-1

Figure B-4B

E. faecalis

Table B-1 Figure B-5B

Figure B-5A P

Table B-1

P Figure B-7B

Conclusion

Effect of Asparaginase Treatment on Dexamethasone Pharmacokinetics

Figure B-8. Plasma dexamethasone concentration was positively associated with asparaginase activity in osteonecrosis experiment

Effect of asparaginase and dexamethasone on plasma protein and lipid levels

Figure B-9. Mouse plasma amylase level after treatment with dexamethasone and asparaginase

Figure B-10. Mouse plasma lipase level after treatment with dexamethasone and asparaginase

P

Figure B-11. Mouse plasma triglyceride level after treatment with dexamethasone and asparaginase

Figure B-12. Mouse plasma albumin level after treatment with dexamethasone and asparaginase

P

P

Figure B-13. Mouse plasma cortisol level after treatment with dexamethasone and asparaginase

P

Table B-3. Inhibition of plasma protein level in human and mouse by asparaginase treatment

Protein Data source Inhibition% N of ASN/total AA

ASN% N of GLN/total AA

GLN% ASN+GLN%

Table B-3. (Continued)

Protein Data source Inhibition% N of ASN/total AA

ASN% N of GLN/total AA

GLN% ASN+GLN%

Figure 3-1

Figure B-14. Correlation between asparagine content in the protein and theextent of inhibition by asparaginase treatment

Figure 3-1Table B-3

APPENDIX C. SUPPLEMENTARY INFORMATION FOR CHAPTER 4

Deep Sequencing of Selected Genes

Table4-3

SNP-based and Gene-based Analysis of Variants Identified by Deep Sequencing

Figure C-1. CADD score in all SNPs on exome array (n = 162586) and pancreatitis-associated SNPs (P < 0.05; n = 8018)

P

Table C-1. Top 10 SNPs from genome-wide analysis of nonsense SNPs; n = 2,357 SNPs

Cohort (n = 3256) a Case/control (n = 213)SNP Gene Chr Location Major

allele/risk

allele

PopulationRAF% (n)b


RAF% in patients


Coeff-icientc

Pc RAF% in cases(n = 71)

RAF% in

controls(n = 142)

Coeff-icientd

Pd

CPA2

ZNF701

C17orf66

C9orf117

SLC26A10

SERPINA9

HEATR7B2

CCL26

ERV3-1

GCKR

Table C-2. Top 10 SNPs from genome-wide analysis of missense SNPs (excluding nonsense SNPs); n = 144,349 SNPs

Cohort (n = 3256) a Case/control (n = 213)SNP Gene Chr Location Major

allele/risk

allele

PopulationRAF% (n)b


RAF% in patients


Coeff-icientc

Pc RAF% in cases(n = 71)

RAF% in

controls(n = 142)

Coeff-icientd

Pd

ADAMTS18

CDC20

PDLIM5

C3orf20

NTF4

C8orf84

NEB

MICAL1

MYOM2

TAS2R16

Table C-3. Top 10 SNPs from genome-wide analysis of synonymous and non-coding SNPs; n = 774,238 SNPs

Cohort (n = 3256) a Case/ctrl (n = 213)SNP Gene Chr Location FunctionMajor

allele/risk

allele

Popu-lation

RAF% (n)b

RAF% in


RAF% in patients without

AP(n = 3161)

Coeff-icientc

Pc RAF% in

cases(n = 71)

RAF% in

controls(n = 142)

Coeff-icientd

Pd

HOGA1

FHIT

-

SPATA21

-

-

C9orf5

FHIT

-

MICAL2

Table C-4. All 380 CPA2 variants identified in the cohort (n = 4217) and the case-control group (n = 162)

Cohort (n = 4217) Case-control (n = 162)Chr:Loca RSID Loca-

tionFunction MAF% in


MAF% in patientswithout

AP(n = 3220)

Coeff-icientb

Pb MAF% in cases(n = 47)

MAF% in controls(n = 115)

Coeff-icientc

Pc

Table C-4. (Continued)




MAF% in patients without

AP(n = 3220)

Coeff-icientb



Coeff-icientc

Pc






AP(n = 3220)

Coef-ficientb



Coef-ficientc

Pc






AP(n = 3220)

Coeff-icientb



Coeff-icientc

Pc






AP(n = 3220)

Coeff-icientb



Coeff-icientc

Pc

CPA2

Table C-5. Top genes (P < 0.05) in the gene-level analysis of nonsense variants identified in putative pancreatitis (n = 42) and non-pancreatitis genes (n = 241) based on variants identified by deep sequencing

Ranka Gene N of SNPsb Cohort SKAT P(n = 4217)

Case-control SKAT P(n = 162)

Pancreatitis-associatedc

HOGA1CPA2

ZNF233C9orf117LRRC39

XDHXRCC1IFNA5QPCT

C11orf63ZRANB3C12orf40DDX49GCKRSNTG2RUFY4MPZL3DAPL1ALS2CLCENPQ

NMI

Figure C-2. Top pathways and functions of pancreatitis-associated genes (n = 42) Table 4-3

Figure C-3. Top pathways and functions of pancreatitis-associated genes identified by GWAS (n = 34)

Table 4-3

Table C-6. SNPs (n = 81) identified by deep sequencing in previously reported pancreatitis-associated candidate genes (n = 8) at the P < 0.05 level (highlighted) in either the cohort or the case-control group

Cohort (n = 4217) Case-control (n = 162)Gene

(n of SNPs at P < 0.05/n of

all SNPs)a

Chr:Locb RSID Function Majorallele/minor allele

MAF% in

patients with AP

(n = 95)

MAF% in

patients without

AP(n = 3161)

Coeff-icientc

Pc MAF% in cases

(n = 47)

MAF% in con-trols(n =115)

Coeff-icientd

Pd Dire-ctione

CTRC

CASR

SPINK1


Cohort (n = 4217) Case-control (n = 162)

Gene(n of SNPs at P < 0.05/n of

all SNPs)a


MAF% in


MAF% in patients

without AP(n = 3,161)

Coeff-icientc

Pc MAF% in cases(n = 47)

MAF% in con-trols(n = 115)

Coeff-icientd

Pd Dire-ctione

CFTR


Cohort (n = 4217) Case-control (n = 162)

Gene(n of SNPs at P < 0.05/n of

all SNPs)a

Chr:Locb RSID Function Majorallele/

minor allele

MAF% in


MAF% in

patients without

AP(n =

3,161)

Coeff-icientc



Coeff-icientd

Pd Dire-ctione

CPA180,81

PRSS1


Cohort (n = 4217) Case-control (n = 162)Gene

(n of SNPs at P < 0.05/n of

all SNPs)a


MAF% in


MAF% in

patients without

AP(n =

3,161)

Coeff-icientc



Coeff-icientd

Pd Dire-ctione

PRSS1

PRSS266,69

CLDN266,69


P

adverse effects of asparaginase in pediatric patients with

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