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Hum GenetDOI 10.1007/s00439-014-1423-7

OrIGInal InvestIGatIOn

Clinical and genomic evaluation of 201 patients with Phelan–McDermid syndrome

Sara M. Sarasua · Luigi Boccuto · Julia L. Sharp · Alka Dwivedi · Chin‑Fu Chen · Jonathan D. Rollins · R. Curtis Rogers · Katy Phelan · Barbara R. DuPont

received: 13 september 2013 / accepted: 19 January 2014 © springer-verlag Berlin Heidelberg 2014

as speech and developmental delay and macrocephaly cor-related with deletion size. Deletion sizes in more recently diagnosed patients tend to be smaller than those diagnosed a decade earlier. seventy-three percent of de novo deletions were of paternal origin. seizures were reported three times more often among patients with a de novo deletion of the maternal rather than paternal chromosome 22. this analy-sis improves the understanding of the clinical presentation and natural history of PMs and can serve as a reference for the prevalence of clinical features in the syndrome.

Introduction

a substantial body of work is accumulating to better under-stand the clinical features of Phelan–McDermid syndrome (PMs), which has a wide spectrum of clinical presenta-tion. this includes developmental delay and significant speech delay, intellectual disability, hypotonia, and minor dysmorphic features (Bonaglia et al. 2010; Phelan and McDermid 2012; Phelan et al. 2001; soorya et al. 2013). PMs is associated with deletions, and occasionally dupli-cations, of up to 9 Mb in size in the 22q13 region. Chro-mosomal abnormalities include simple terminal deletions, ring chromosomes, translocations, interstitial deletions, as well as duplications. In almost all cases, the SHANK3 gene, mapping to the distal end of 22q13.33, is affected (Bonaglia et al. 2010; Phelan and McDermid 2012; Wil-son et al. 2003) or in rare cases, disrupted (anderlid et al. 2002; Bonaglia et al. 2001, 2006; Delahaye et al. 2009; Misceo et al. 2011). SHANK3 is a candidate gene for many of the neurologic features of the syndrome (Bonaglia et al. 2001, 2006; Phelan and McDermid 2012) and deletions or point mutations have also been reported in isolated cases of autism spectrum disorders (asDs) (Betancur et al. 2009;

Abstract this study is the first to describe age-related changes in a large cohort of patients with Phelan–McDer-mid syndrome (PMs), also known as 22q13 deletion syn-drome. Over a follow-up period of up to 12 years, physi-cal examinations and structured interviews were conducted for 201 individuals diagnosed with PMs, 120 patients had a focused, high-resolution 22q12q13 array CGH, and 92 patients’ deletions were assessed for parent-of-origin. 22q13 genomic anomalies include terminal deletions of 22q13 (89 %), terminal deletions and interstitial duplica-tions (9 %), and interstitial deletions (2 %). Considering different age groups, in older patients, behavioral problems tended to subside, developmental abilities improved, and some features such as large or fleshy hands, full or puffy eyelids, hypotonia, lax ligaments, and hyperextensible joints were less frequent. However, the proportion reporting an autism spectrum disorder, seizures, and cellulitis, or pre-senting with lymphedema or abnormal reflexes increased with age. some neurologic and dysmorphic features such

Electronic supplementary material the online version of this article (doi:10.1007/s00439-014-1423-7) contains supplementary material, which is available to authorized users.

s. M. sarasua (*) · l. Boccuto · a. Dwivedi · C.-F. Chen · J. D. rollins · r. C. rogers · B. r. DuPont Office of Bioinformatics and epidemiology, Greenwood Genetic Center, 101 Gregor Mendel Circle, Greenwood, sC 29646, Usae-mail: ssarasua@ggc.org

J. l. sharp Department of Mathematical sciences, Clemson University, Clemson, sC 29634, Usa

K. Phelan Hayward Genetics Center and Department of Pediatrics, tulane University school of Medicine, new Orleans, la 70112, Usa

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Boccuto et al. 2013; Durand et al. 2007; Gauthier et al. 2009; Grabrucker et al. 2011; Moessner et al. 2007). asDs are frequently a co-morbid condition of PMs (Dhar et al. 2010; Jeffries et al. 2005; lindquist et al. 2005; Manning et al. 2004; Phelan et al. 2001; Philippe et al. 2008; sarasua et al. 2011; soorya et al. 2013). several lines of evidence suggest that deletion size is predictive of phenotypic sever-ity (Jeffries et al. 2005; sarasua et al. 2011, 2013; Wilson et al. 2003; Wilson et al. 2008; soorya et al. 2013), sug-gesting that genes other than SHANK3 may play a role in defining the highly variable PMs phenotype. We have pre-viously published analyses that looked specifically at size (sarasua et al. 2011) and location (sarasua et al. 2013) of the deletion in relation to phenotypes in a subset of 70 PMs patients and at growth in a subset of 55 PMs patients (rol-lins et al. 2011a).

One area of research that has not been adequately explored is an assessment of age-related changes in PMs phenotypes. Because the syndrome is rare and published studies have analyzed small cohorts, clinical features tend to have been examined in aggregate without looking at age-specific differences. However, understanding age-related changes is important for clinical management, and geno-type–phenotype assessments may need to account for age if clinical features change with age. two reports that do assess longitudinal changes include a case series of seven patients where a progressive loss of skills was observed (Denayer et al. 2012). these losses tended to follow acute health events, but were noted even in those without such events. another report of three individuals also report neu-rological deterioration with age (Bonaglia et al. 2011). Beyond these reports, little information is available on age-related changes in the syndrome.

In this study, we examine the prevalence of 64 clinical features across ages, deletion sizes, and parental origin to better inform patients, researchers, and clinicians on the clinical profile of PMs.

Subjects and methods

Patient recruitment

a total of 201 individuals with a PMs diagnosis partici-pated in the study at least once from 2004 to 2010, primar-ily during four biannual meetings of the Phelan–McDermid syndrome Family support Conferences. Of these, 55 par-ticipated two or more times, including the earliest confer-ences in 1998 and 2000. Parents or guardians answered a standardized medical history questionnaire (n = 186). at the conferences, patients were offered a standardized phys-ical examination by a trained clinical geneticist and 116 patients participated. Height and head circumference of

the patients were measured and were converted to age- and gender-specific percentiles using growth charts (rollins et al. 2010, 2011b; Kuczmarski et al. 2002; WHO 2006). In addition, blood samples for array comparative genomic hybridization (CGH) were collected between 2006 and 2010. In a subset of 92 patients and their parents, Dna was extracted from peripheral blood to perform a parent-of-origin analysis. Informed consent was provided and the study was approved by the Institutional review Board of the self regional Health system (Greenwood, south Caro-lina, Usa).

Genetic analysis

Array CGH

22q13 deletions and duplications were delineated from Dna isolated from whole blood specimens using a tar-geted, custom 4 × 44 K 60-mer oligo array designed to cover 22q12.3-terminus by Oxford Gene technology (Oxford, UK) as described previously (sarasua et al. 2011). the focused array was designed to both confirm the dele-tions in previously diagnosed patients as well as to identify breakpoints with high resolution. the arrays were offered to all interested attendees of the 2006 and 2008 family support conferences. Blood specimens were either drawn at the conferences or were drawn by personal physicians and mailed to the investigators. the 2006 human genome build (nCBI 36/HG 18) was used to establish array CGH genomic breakpoint coordinates (International Human Genome sequencing Consortium 2004).

Parent‑of‑origin analysis

to determine parental origin of the affected chromosome, genomic Dna was isolated by high salt precipitation from peripheral blood from 92 patients and their parents. Because SHANK3 is deleted in all cases tested, this gene was selected for parent-of-origin testing. the amplified target region of SHANK3 covers a 491-bp region includ-ing part of intron 9, exon 10 and part of intron 10. the region was selected for the presence of two highly varia-ble snPs: c.1304+42 G>a (nG_008607.1:g.25449 G>a, rs13055562) and c.1304+103 C>a (nG_008607.1:g.25511 C>a, rs2341009). the rs13055562 allele frequencies, according to the 1000 genome database (http://www.1000genomes.org/home), are 62.4 % G and 37.6 % a; while the rs2341009 allele frequencies are 73.7 % a and 26.3 % C. the region also includes a third snP, c.1304+48 C>t (nG_008607.1:g.25455 C>t, rs76224556), which is rarer in the normal population (96.2 % C and 3.8 % t) and has been reported in association with autism spectrum disor-ders (Boccuto et al. 2013). each sample was amplified by

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PCr, purified and then sequenced using the DYenamiv et Dye terminator Cycle sequencing Kit on the MegaBaCe 1000 analysis system (amersham Biosciences, sunny-vale, Ca, Usa). sequencing was performed in both for-ward and reverse directions. the highly polymorphic tan-dem ta repeats of the microsatellite D22S1169, mapping within SHANK3, were also analyzed. the polymorphisms were detected by CeQ™ 8800 Genetic analysis system (Beckman Coulter, Brea, Ca, Usa). an expanded descrip-tion of the methods used is provided in the supplemental Materials.

statistical analysis

a total of 201 individuals participated at least once in the study and 55 of these individuals participated more than once. Most of the analyses in this study are cross-sectional and include only the data from the most recent visit (during 2004–2010) such that each observation is independent. In a subset of analyses designed to specifically look longitudi-nally, only those individuals who attended multiple times were included in a repeated-measures analysis as explained below. sas software was used for all statistical analyses (sas Institute 2009). When available, currently having a condition was assessed rather than ever having a condi-tion. results were judged to be statistically significant at P < 0.05 and of borderline significance at 0.05 < P < 0.10.

Cross‑sectional analysis

Differences in age and deletion size distributions were examined by gender, age group, type of microarray result, year of diagnosis, and parent-of-origin using Wilcoxon rank sum or Kruskal–Wallis P values. the prevalence of 62 features was compared across four age groups: 0.4–4.9, 5–9.9 years, 10–17.9, and 18–64 years. the age categories were selected to represent the pre-school, school age, ado-lescent, and adult phases of life. statistical significance was assessed with the Cochran–Mantel–Haenszel Chi-square test using rank scores or Fisher’s exact test when sample sizes were small. the effect of deletion size (independent variable) on phenotypes (dependent variable) was assessed in regression models and included age and gender covari-ates. For continuous phenotypes (age at learning to walk, level of developmental delay, and head circumference and height percentile), linear regression models were used. For dichotomous phenotypes, logistic regression was used. For the models assessing the effect of deletion size, cases were excluded if they had a duplication (n = 11), intersti-tial deletion (n = 2) or a reported translocation (n = 9). the analyses were not conducted if there were fewer than five cases. the association between parent-of-origin of

the affected chromosome and dichotomous outcomes was assessed by Fisher’s exact test.

Longitudinal analysis

For those individuals who attended two or more times (n = 55), a longitudinal analysis was conducted to examine changes within the same group of individuals. the longitu-dinal analysis was conducted for those features that showed statistically significant (P < 0.05) age-related differences in prevalence in the cross-sectional analysis. a repeated-measures logistic regression procedure was used to model the log odds of medical/behavioral features. a longitudinal analysis was not conducted of physical examination fea-tures because too few individuals had multiple visits for these conditions (n ≤ 12).

Results

Cytogenetic findings

Of the 120 individuals with a custom 22q13 microarray, the majority (89 %) were 22q13 terminal deletions; however, terminal deletions accompanied by proximal duplications (9 %), and interstitial deletions (2 %) were also observed (table 1; Fig. 1). Deletion breakpoints were highly varied across the 9-Mb terminal region of 22q13 (Fig. 1). the interstitial deletions did not include SHANK3. Genome-wide array CGH was not performed and some of these patients also had cytogenetic findings of translocations or ring chromosome 22. Medical history information and prior laboratory testing identified 14 patients with ring 22 and 9 patients with deletions associated with unbalanced translocations. there was no significant difference in dele-tion sizes among those with ring 22 (mean 4.7 Mb, range 2.2–7.7), unbalanced translocations affecting 22q13 (mean 5.6 Mb, range 1.3–8.9), or simple terminal deletions (mean 5.3 Mb, range 0.2–9.2) (Kruskal–Wallis P = 0.5833). among the cases in which deletion size was assessed, there was no difference in median deletion size between those with terminal deletions, terminal deletions and dupli-cations, or interstitial deletions (P = 0.3765) (table 1). eleven patients were found to have terminal deletions with a duplication immediately preceding the deletion break-point (Fig. 1). For the patients with both a duplication and terminal 22q13 deletion, duplication sizes ranged from 0.02 to 6.84 Mb with a median duplication size of 1.3 Mb. Physical examination and medical history features were similar for those with both a duplication and deletion of 22q13 and age- and deletion size-matched patients with ter-minal 22q13 deletions (supplemental Materials table s1).

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age, gender, and year of diagnosis correlation with genetic features

Of 201 individuals with at least one physical exam or health record, the mean age at most recent study participation was 8.4 years, median age was 6.2 years with a range of 0.4–64.2 years (table 1). age and deletion size did not vary by gender. no age difference was observed between partici-pants who did and did not have a microarray test performed (P = 0.9911) or by the type of 22q13 chromosomal anomaly (P = 0.1113). Individuals diagnosed prior to the year 2000 tended to be older at the time of most recent study participa-tion (P < 0.0001) and tended to have larger deletion sizes (P = 0.0040); likewise, year of diagnosis was inversely correlated with deletion size (spearman r = −0.281, P = 0.0075, n = 89). However, age at study participation

and deletion size were not correlated (spearman r = 0.020, P = 0.8249, n = 120). there was no difference in deletion size (P = 0.6616) or age of participant (P = 0.9552) for those with missing or known year of diagnosis.

Overall prevalence of clinical features

some of the most common features observed in our cohort (tables 2, 3) were speech delay (100 %), hypotonia (75 %), distinctive neurological abnormalities such as overheating (68 %) and high pain threshold (77 %), and minor dysmor-phic traits like long eyelashes (93 %), dysplastic toenails (73 %), and large or fleshy hands (63 %). Other common problems included seizures (27 %), asDs (31 %), gas-troesophageal reflux (42 %), kidney problems (26 %), fre-quent constipation (41 %), and skin rashes (39 %). low

Table 1 age and size of deletions by gender, age group, type of chromosomal anomaly, year of diagnosis, and parent-of-origin

NA not applicable

Bold values indicate significance at alpha = 0.05a Wilcoxon rank sum 2-sided P value for two-level analysis, Kruskal–Wallis P value for multilevel analysisb the size of duplications accompanying deletions ranged from 0.02 to 6.84 Mb with a median duplication size of 1.33 Mb

Patient information sample size Median age at most recent visit, years (min–max)

P valuea 22q13.3 deletion size (Mb) (n = 120)

P valuea

at least one health history interview or physical examination

From 2004 to 2010

201 6.2 (0.4–64.2) 5.16 (0.22–9.22)

Gender

Male 81 (40 %) 6.5 (0.4–44.6) 0.1481 6.03 (0.22–9.22) 0.1855

Female 120 (60 %) 6.2 (1.1–64.2) 5.03 (0.37–9.22)

age at most recent visit <0.0001 0.1507

0.4–4.9 years 77 (38 %) 3.2 (0.4–4.9) 5.89 (0.34–9.22)

5–9.9 years 67 (33 %) 6.9 (5.0–9.8) 4.41 (0.22–9.22)

10–17.9 years 36 (18 %) 12.3 (10.0–17.7) 5.23 (1.04–8.94)

18–64 years 21 (10 %) 21.3 (18.3–64.2) 6.63 (2.75–8.96)

Microarray result

none available 81 (40 %) 6.2 (0.4–64.2) 0.9911 na na

available 120 (60 %) 6.5 (0.9–44.6) 5.2 (0.22–9.22)

type of result

terminal deletion 107 (89 %) 6.3 (0.9–44.6) 0.1113 5.2 (0.22–9.22) 0.3765

Interstitial deletion 2 (2 %) 18.5 (15.7–21.2) 4.4 (2.72–6.04)

Deletion and duplicationb 11 (9 %) 6.7 (2.3–12.2) 4.8 (0.41–7.18)

Year of diagnosis

Unavailable 43 (21 %) 5.6 (0.9–36.6) 0.9552 5.0 (0.34–9.22) 0.6616

available 158 (79 %) 6.3 (0.4–64.2) 5.2 (0.22–9.22)

Before 2000 22 (14 %) 13.7 (7.9–23.5) <0.0001 8.5 (1.58–9.22) 0.0040

2000–2004 62 (39 %) 7.0 (2.6–44.6) 5.8 (0.41–8.78)

2005–2010 74 (47 %) 4.2 (0.4–64.2) 3.9 (0.22–8.94)

Parent-of-origin of deleted chromosome 0.6759 0.2978

Mother 17 (27 %) 6.9 (0.9–21.3) 5.2 (1.78–9.22)

Father 47 (73 %) 5.3 (1.1–36.6) 5.1 (0.34–8.94)

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birthweight (<2,500 g) occurred in 18 % of patients (32 out of 174) with a median reported birthweight of 3,178 g, ranging from 964 to 4,309 g. Preterm births (<37-week gestation) were reported for 22 % of patients with a median gestational age of 39 weeks, ranging from 28 to 43 weeks.

Cross-sectional analysis of development, health, and physical features

Developmental, speech, and neurological features

By 3 years of age, the majority of patients (88 %) could walk independently (table 2). the median age when this

skill was acquired was 22 months, ranging from 10 to 98 months of age. Few patients were reported to be toi-let trained (24 %); the age when this skill was acquired ranged from 36 months to 20 years (median age 6.5 years). speech abilities, among those over age 3 years, did not improve significantly with age (P = 0.6179), except that the strongest verbal abilities were more prevalent in those over 5 years of age (table 2). In total, 50 % of the patient group (72/144) had no speech, 27 % (39/144) reportedly had a vocabulary of 40 words or less, 10 % (15/144) were reported to have 50 or more words or the ability to use phrases, and 13 % (18/144) reportedly had large vocabu-laries, used full sentences, or used speech as a primary

Fig. 1 Deletions (red bars) and duplications (blue bars) observed in unrelated individuals with Phelan–McDermid syndrome. Deletions include interstitial deletions (top group), terminal deletions (middle group), and deletions with duplications (lower group). the location of

22q13 cytogenetic bands and known genes are also presented in this figure produced using the UCsC genome browser (Kent et al. 2002) using the 2006 (hg18) genome build (International Human Genome sequencing Consortium 2004) (color figure online)

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Table 2 Current health, developmental, and behavioral features of individuals with Phelan–McDermid syndrome, by age

Bold values indicate significance at alpha = 0.05a P value from Cochran–Mantel–Haenszel Chi-square (row mean scores differ) statistic, rank scoresb Fisher’s exact 2-sided P-value

Feature all ages age (0.4–4.9 years) age (5–9.9 years) age (10–17.9 years) age (18–64 years) P valuea

Yes/total (%) Yes/total (%) Yes/total (%) Yes/total (%) Yes/total (%)

Developmental/neurological

speech (age ≥3 years) 0.6179

none 72/144 (50 %) 20/37 (54 %) 29/59 (49 %) 16/29 (55 %) 7/19 (37 %)

1–40 words 39/144 (27 %) 13/37 (35 %) 13/59 (22 %) 5/29 (17 %) 8/19 (42 %)

50+ words or phrases 15/144 (10 %) 4/37 (11 %) 5/59 (8 %) 3/29 (10 %) 3/19 (16 %)

verbal communication 18/144 (13 %) 0/37 (0 %) 12/59 (20 %) 5/29 (17 %) 1/19 (5 %)

Walking unassisted (age ≥3 years) 128/146 (88 %) 32/40 (80 %) 51/58 (88 %) 27/30 (90 %) 18/18 (100 %) <0.0379

toilet trained (age ≥3 years) 33/140 (24 %) 3/39 (8 %) 10/55 (18 %) 9/28 (32 %) 11/18 (60 %) <0.0001

any type of seizures 41/151 (27 %) 6/55 (11 %) 14/53 (26 %) 10/23 (43 %) 12/20 (60 %) <0.0001

sleep problems (other than sleep apnea)

12/26 (46 %) 5/11 (45 %) 3/6 (50 %) 1/1 (100 %) 3/7 (43 %) 1.0000b

Overheats or turns red easily 105/155 (68 %) 33/58 (57 %) 41/55 (75 %) 20/24 (83 %) 11/18 (61 %) 0.0816

Decreased perspiration 89/149 (60 %) 33/61 (54 %) 35/58 (60 %) 17/25 (68 %) 11/18 (61 %) 0.3655

Overly sensitive to touch 80/175 (46 %) 33/67 (49 %) 24/58 (41 %) 14/32 (44 %) 9/18 (50 %) 0.6990

High pain threshold 131/170 (77 %) 44/64 (69 %) 44/56 (79 %) 26/31 (84 %) 17/19 (89 %) 0.0256

arachnoid cyst 24/129 (19 %) 6/46 (13 %) 11/44 (25 %) 5/21 (24 %) 2/18 (11 %) 0.6091

Gastroesophageal reflux 62/149 (42 %) 24/56 (43 %) 22/52 (42 %) 7/23 (30 %) 9/18 (50 %) 0.8502

Behavioral features

asD (age ≥3 years) 39/127 (31 %) 7/36 (19 %) 15/50 (30 %) 9/25 (36 %) 8/16 (50 %) 0.0270

asD + autistic-like features (age ≥3 years)

44/127 (35 %) 7/36 (19 %) 17/50 (34 %) 9/25 (36 %) 11/16 (69 %) 0.0027

Chewing non-food items 153/181 (85 %) 67/76 (88 %) 58/64 (91 %) 27/34 (79 %) 12/20 (60 %) 0.0121

Impulsiveness 78/166 (47 %) 26/61 (43 %) 29/55 (53 %) 15/31 (48 %) 8/19 (42 %) 0.7085

Biting (self or others) 82/179 (46 %) 41/70 (58 %) 26/58 (45 %) 13/32 (41 %) 2/19 (11 %) 0.0006

Hair pulling 48/118 (41 %) 23/43 (53 %) 15/38 (39 %) 6/21 (29 %) 4/16 (25 %) 0.0163

excessive screaming 54/174 (31 %) 24/68 (35 %) 17/56 (30 %) 10/32 (31 %) 3/18 (17 %) 0.2231

aggressive behavior 49/127 (28 %) 18/74 (24 %) 15/61 (25 %) 11/33 (33 %) 5/20 (25 %) 0.5534

nonstop crying 38/178 (21 %) 20/69 (29 %) 14/58 (24 %) 4/32 (13 %) 0/19 (0 %) 0.0051

Other clinical features

Genital anomalies 8/146 (5 %) 3/56 (5 %) 1/51 (2 %) 2/23 (9 %) 2/16 (13 %) 0.2302

Precocious puberty 15/121 (12 %) 0/48 (0 %) 5/35 (14 %) 9/22 (41 %) 1/16 (6 %) 0.0017

Frequent urinary tract infections 12/158 (8 %) 4/59 (7 %) 3/54 (6 %) 2/26 (8 %) 3/19 (16 %) 0.5182b

vesicouretal reflux 18/133 (14 %) 9/46 (20 %) 7/50 (14 %) 2/21 (10 %) 0/16 (0 %) 0.2593b

Polycystic kidneys 6/132 (5 %) 1/51 (2 %) 5/46 (11 %) 0/19 (0 %) 0/16 (0 %) 0.1650b

Duplicate kidney 1/135 (1 %) 0/51 (0 %) 1/47 (2 %) 0/21 (0 %) 0/16 (0 %) 0.6222b

Dilated renal pelvis 7/129 (5 %) 5/51 (10 %) 1/43 (2 %) 1/19 (5 %) 0/16 (0 %) 0.3760b

Increased kidney size 11/126 (9 %) 3/50 (6 %) 6/42 (14 %) 2/18 (11 %) 0/16 (0 %) 0.3176b

Other kidney trouble 25/133 (19 %) 12/49 (24 %) 9/50 (18 %) 1/18 (6 %) 3/16 (19 %) 0.3752b

any kidney problem 39/148 (26 %) 18/56 (32 %) 14/53 (26 %) 5/22 (23 %) 2/17 (12 %) 0.1094

Frequent constipation 11/27 (41 %) 4/10 (40 %) 1/8 (13 %) 2/2 (100 %) 4/7 (57 %) 0.1023b

skin rashes 60/152 (39 %) 15/58 (26 %) 22/50 (44 %) 15/26 (58 %) 8/18 (44 %) 0.0088

Cellulitis 9/137 (7 %) 2/54 (4 %) 1/48 (2 %) 1/19 (5 %) 5/16 (31 %) 0.0027b

Diabetes 2/129 (2 %) 1/48 (2 %) 0/42 (0 %) 0/22 (0 %) 1/17 (6 %) 0.2751b

Hypothyroid 7/121 (6 %) 0/44 (0 %) 3/42 (7 %) 2/19 (11 %) 2/16 (13 %) 0.0707b

Hyperthyroid 1/122 (1 %) 0/44 (0 %) 0/42 (0 %) 0/19 (0 %) 1/17 (6 %) 0.1393b

enzyme deficiency 4/107 (4 %) 0/37 (0 %) 1/37 (3 %) 1/17 (6 %) 2/16 (13 %) 0.0806b

Immune deficiency 14/113 (12 %) 7/44 (16 %) 4/39 (10 %) 0/15 (0 %) 3/15 (20 %) 0.2910b

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means of communication. speech ability (categorized into four levels) was inversely correlated with other measures of development including age at learning to walk (spearman r = −0.319, P = 0.0015) and level of developmental delay (based upon a rank score of 1 = “mild” to 7 = “profound”) (r = −0.502, P < 0.0001).

the prevalence of any type of reported seizures increased with age from 11 % among those under age 5 years to 60 % among adults, and the prevalence of a

high pain threshold increased from 69 to 89 % between the youngest and oldest age groups (table 2).

Behavioral features and major systems

the number of PMs patients reported to have asD or to exhibit autistic-like features increased with age ranging from 19 % in the 3- to 4.9-year-old age group to 60 % among those over 18 years. as seen in table 2, many adverse behaviors

Table 3 Physical exam features by age of individuals with Phelan–McDermid syndrome

Bold values indicate significance at alpha = 0.05a Fisher’s exact 2-sided P-valueb P value from Cochran–Mantel–Haenzel Chi-square (row mean scores differ) statistic, rank scoresc the presence of both hyperreflexia an hyporeflexia at different locations in the same individual

Feature all ages age (0.4–4.9 years) age (5–9.9 years) age (10–17.9 years) age (18–45 years) P valuea

Yes/total (%) Yes/total (%) Yes/total (%) Yes/total (%) Yes/total (%)

Height 0.0133b

<5th percentile 11/96 (11 %) 3/42 (7 %) 3/29 (10 %) 5/18 (28 %) 0/7 (0 %)

5th–95th percentile 76/96 (79 %) 31/42 (74 %) 25/29 (86 %) 13/18 (72 %) 7/7 (100 %)

>95th percentile 9/96 (9 %) 8/42 (19 %) 1/29 (3 %) 0/18 (0 %) 0/7 (0 %)

Head circumference 0.5449b

<3rd percentile 12/110 (11 %) 4/52 (8 %) 5/33 (15 %) 3/20 (15 %) 0/5 (0 %)

3–97th percentile 78/110 (71 %) 38/52 (73 %) 26/33 (79 %) 11/20 (55 %) 3/5 (60 %)

>97th percentile 20/110 (18 %) 10/52 (19 %) 2/33 (6 %) 6/20 (30 %) 2/5 (40 %)

long eyelashes 105/113 (93 %) 45/49 (92 %) 35/35 (100 %) 19/22 (86 %) 6/7 (86 %) 0.0790

Dolichocephaly 36/113 (32 %) 19/50 (38 %) 7/35 (20 %) 7/21 (33 %) 3/7 (42 %) 0.2923

Pointed chin 58/111 (52 %) 31/51 (61 %) 15/32 (47 %) 9/21 (43 %) 3/7 (43 %) 0.4003

Facial asymmetry 9/110 (8 %) 2/48 (4 %) 2/34 (6 %) 3/21 (14 %) 2/7 (29 %) 0.0948

High or arched palate 49/104 (47 %) 20/44 (45 %) 13/34 (38 %) 11/21 (52 %) 5/5 (100 %) 0.0739

Full or puffy eyelids 60/109 (55 %) 33/49 (67 %) 15/33 (45 %) 11/20 (55 %) 1/7 (14 %) 0.0297

epicanthal folds 52/111 (47 %) 28/49 (57 %) 16/34 (47 %) 6/21 (29 %) 2/7 (29 %) 0.1204

Deep set eyes 34/111 (31 %) 18/49 (37 %) 9/34 (26 %) 6/21 (29 %) 1/7 (14 %) 0.6113

large or fleshy hands 71/112 (63 %) 39/49 (80 %) 14/35 (40 %) 14/21 (67 %) 4/7 (57 %) 0.0023

2/3 toe syndactyly 53/110 (48 %) 23/48 (48 %) 17/35 (49 %) 10/21 (48 %) 3/6 (50 %) 1.0000

Dysplastic toenails 81/111 (73 %) 39/48 (81 %) 24/36 (67 %) 15/21 (71 %) 3/6 (50 %) 0.2268

Dysplastic fingernails 26/111 (23 %) 15/48 (31 %) 7/35 (20 %) 3/21 (14 %) 1/7 (14 %) 0.4368

single palmar crease 12/109 (11 %) 4/47 (9 %) 2/34 (6 %) 4/21 (19 %) 2/7 (29 %) 0.1374

strabismus 28/109 (26 %) 11/47 (23 %) 9/34 (26 %) 7/21 (33 %) 1/7 (14 %) 0.6874

Hypotonia 82/110 (75 %) 41/48 (85 %) 25/34 (74 %) 12/21 (57 %) 4/7 (57 %) 0.0428

lax ligaments 72/110 (65 %) 34/48 (71 %) 25/34 (74 %) 12/21 (57 %) 1/7 (14 %) 0.0185

Hyperextensible joints 68/111 (61 %) 32/49 (65 %) 24/34 (71 %) 11/21 (52 %) 1/7 (14 %) 0.0338

lymphedema 26/108 (24 %) 8/47 (17 %) 6/34 (18 %) 7/20 (35 %) 5/7 (71 %) 0.0122

abnormal reflexes 44/91 (48 %) 15/41 (37 %) 12/27 (44 %) 14/18 (78 %) 3/5 (60 %) 0.0230

reflexes 0.0119

Hyporeflexia 28/91 (31 %) 12/41 (29 %) 8/27 (30 %) 7/18 (39 %) 1/5 (20 %)

normal 47/91 (52 %) 26/41 (63 %) 15/27 (56 %) 4/18 (22 %) 2/5 (40 %)

Hypo- and hyperreflexiac 2/91 (2 %) 0/41 (0 %) 1/27 (4 %) 0/18 (0 %) 1/5 (20 %)

Hyperreflexia 14/91 (15 %) 3/41 (7 %) 3/27 (11 %) 7/18 (39 %) 1/5 (20 %)

Ptosis 53/112 (47 %) 25/50 (50 %) 10/33 (30 %) 13/22 (59 %) 5/7 (71 %) 0.0722

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including chewing behaviors, nonstop crying, biting, and hair pulling showed decreased prevalence with age. some condi-tions remained problematic such as gastroesophageal reflux which was reported for 30–50 % of individuals regardless of age. a history of precocious puberty was reported for 14 % of patients from age 5 to 9 and for 41 % among those from 10 to 17 years of age. a history of precocious puberty was more frequent among females, being reported in 0/35 females under age 5, 5/26 (19 %) girls ages 5–9 years, 6/12 (50 %) girls ages 10–17 years, and 1/8 (13 %) women over age 18 years. the prevalence of kidney problems did not change with age, while the prevalence of skin rashes and celluli-tis increased with age. Diabetes, thyroid abnormalities, and enzyme deficiencies were rare (≤6 %) (table 2).

Physical examination features

Commonly observed features included long eyelashes, dys-plastic toenails, pointed chin, full or puffy eyelids, and large or fleshy hands (table 3). Most physical features remained unchanged by age of the patient other than height and hand size. While the majority of patients were of typical stature (5th–95th percentile, mean height percentile = 53), there was a trend of decreasing height percentile with age (spear-man r = −0.3373, P = 0.0008, n = 96). among those under age 5 years, 19 % were tall for age (>95th percentile) and 7 % were short for age (<5th percentile), but among those 10–17 years of age, none had tall stature and 28 % had short stature. the mean height percentile was 68th for those ages less than 5 years, 42nd for those ages 5–9, 35th for those ages 10–17, and 61st for those over age 18 years. the proportion with atypical head circumference did not vary by age, but 18 % had macrocephaly (>97th percentile) and 11 % had microcephaly (<3rd percentile). the mean head circumference was 54th percentile, range of 0.5th to 99.5th percentile. Height and head circumference were correlated (spearman r = 0.3508, P = 0.0006, n = 93), although the correlation was strongest for the older age groups. For those under age 5 years, the correlation was r = 0.263, P = 0.0928, n = 42. For those between the ages of 5 and 9.9 years, the correlation was r = 0.381, P = 0.0416, n = 29. For those between 10 and 17.9 years of age the cor-relation was r = 0.5302, P = 0.0286, n = 17. and for those over age 18 years of age, the correlation was r = 0.205, P = 0.7406, n = 5. Microcephaly (<3rd percentile) was more common among those with short stature (<5th percen-tile) than among those with normal stature (risk ratio 5.0, 95 % CI 1.67–34.40). Macrocephaly (>97th percentile) was more common among those with tall stature (>95th percen-tile) than among those with normal stature (rr = 1.8, 95 % CI 0.62–4.97). adjusting for age did not change these asso-ciations. the proportion with large or fleshy hands and full or puffy eyelids also decreased with age.

regarding neuromuscular findings, fewer individuals exhibited hypotonia, lax ligaments, hyperextensible joints, or hyporeflexia as age increased (table 3). the prevalence of cases having hyperreflexia increased with age.

Parent-of-origin effects

Of the 92 trios with de novo 22q13 deletions assessed, 64 (70 %) were informative for parental origin of the affected chromosome. the deletions originated from the paternally inherited chromosome in 73 % of cases (47/64) and from the maternally inherited chromosome in 27 % of cases (17/64) (table 1). Parental origin of the affected chromosome was not associated with patients’ age at assessment or deletion size. Parental age at con-ception of the affected child did not differ between those transmitting and not transmitting an affected chromo-some. the mean age of mothers at conception of the affected child was 31.4 years (range of 19–42) and for fathers was 33.4 years (range 20–46). Of the 60 features examined, only the proportion reporting seizures differed significantly by parent-of-origin. Having seizures was more common among offspring inheriting a maternally derived deletion (7/13, 54 %) than a paternally derived deletion (5/30, 17 %; P = 0.0241, Fisher’s exact test). the association remained after adjustment for age and gender. none of the other 60 features assessed were sta-tistically significant (P < 0.05).

longitudinal analysis

among the 55 patients who had two or more visits and could be assessed longitudinally, the mean time between assessments was 3.7 years and the median was 3.0 years (range 0.3–12.1 years). the youngest patient was 9-months old while the oldest was 40 years of age. Of these, 41 came for two visits, 13 came for 3 visits, and 1 came for 4 visits. the direction of effect in the longitudinal analysis (table 4) was in agreement with the cross-sectional analysis, although the level of statistical significance was typically poor. In general, however, there was little observed change in features between assessments in this cohort. the ability to walk and use the toilet independently and high pain tol-erance all were observed to increase significantly between assessments.

22q13 deletion size effects

Deletion size was significantly (P < 0.05) associated with 15 out of 54 features assessed (tables 5, supplemental table s2 and supplemental Figure s1). Features related to developmental delay (severity of developmental delay, speech ability, walking ability), growth (macrocephaly,

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large/fleshy hand size), dysmorphic features (facial asymmetry, 2/3 toe syndactyly, dolichocephaly), and neurological features (abnormal reflexes, strabismus) were associated with larger deletion sizes. all macroce-phalic patients with terminal deletions had a deletion size >5.02 Mb (supplemental Figure s1). the association of stature and deletion size was complicated by small sam-ple size and potential interaction with age. Deletion size was not predictive of tall stature in the logistic regression model adjusting for age and gender (P = 0.1633). For the 7 individuals with tall stature who had microarray results, all were under 5 years of age (median 3.4, range 1.3–4.9 years) and all had deletion sizes larger than 4.6 Mb (median 6.2, range 4.6–9.2 Mb). In comparison, for those with typical stature, the median age was 6.1 years (range 0.8–21) and the median deletion size was 4.7 Mb (range 0.2–8.8 Mb). those with short stature had a similar age distribution (median age 5.2 years, range 1.8–17.2 years), but typically larger deletions (median deletion size 8.1 Mb, range 2.2–9.2 Mb). larger deletion size was of borderline statistical significance as a predictor of short stature (P = 0.0971). However, when modeled with inter-action terms, age, deletion size, and an age–deletion size

interaction term were all significant. While deletion sizes were not significantly different for females reported to have precocious puberty (median 5.25 Mb, range of 4.07–9.22 (n = 7), or not to have precocious puberty (median 5.77 Mb, range of 0.37–8.94, n = 33, P = 0.4383), we noted qualitative differences in the minimum deletion sizes between the two groups. also, since the smallest deletion size of an individual with precocious puberty is 4 Mb, many genes in addition to SHANK3 are co-deleted. therefore, we cannot conclude whether it is most likely associated with SHANK3 or other 22q13.3 genes. aggressive behavior and impulsiveness were inversely associated with deletion size. asDs were of borderline statistical significance (0.05 < P < 0.10). seizures, hypo-tonia, birth weight, and gestational age at birth were not found associated with deletion size. speech ability varied markedly by deletion size (table 5, supplemental Figure s1). speech ability was inversely correlated with size of terminal deletion (r = −0.428, P = 0.0002). While the largest deletion among patients with absent speech was 9.22 Mb, the largest deletion for those with full sentences and functional language was 4.53 Mb (table 5, supple-mental Figure s1).

Table 4 Features associated with increased age as assessed in a repeated-measures logistic regression model

Bold values indicate significance at alpha = 0.05a Only features with P < 0.10 are reportedb the beta coefficient represents the change in log odds between a 1-year increase in follow-up agec the odds ratio (with 95 % confidence interval) represents the increased odds of having the feature between a 1-year increase in follow-up age

Feature sample size, n Beta coefficientb P value Odds ratio (95 % CI)c

Features becoming more common with increased age

Use toilet alone 45 0.4363 0.0037 1.5 (1.16–2.06)

High pain tolerance 46 0.3348 0.0062 1.4 (1.10–1.77)

Walk alone 47 0.6623 0.0459 1.9 (1.01–3.71)

Cellulitis 20 0.1983 0.0789 1.2 (0.93–1.52)

Features becoming less common with increased age

Biting 48 −0.0880 0.0801 0.9 (0.83–1.01)

Hair pulling 12 −0.7665 0.0920 0.5 (0.19–1.16)

Table 5 terminal 22q13 deletion size by level of speech ability among patients age 3 years and older

Bold values indicate significance at alpha = 0.05a the odds ratio (with 95 % confidence interval) represents the decreased odds of having a given speech ability compared to absent speech with a 1 Mb increase in terminal deletion size, adjusting for age and gender in a logistic regression model

speech level sample size Median deletion size (Mb)

Minimum (Mb)

Maximum (Mb)

Kruskal–Wallis P-value

Odds ratio (95 % CI)a

absent 38 6.55 0.34 9.22 0.0025 reference

1–49 words 18 5.81 1.62 7.45 0.79 (0.60–1.03)

50+ words or phrases 7 4.19 0.37 5.25 0.57 (0.35–0.93)

Full sentences, verbal communication 8 2.42 0.22 4.53 0.35 (0.16–0.75)

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Discussion

With 201 participants, this study is the largest to date to describe the prevalence of 64 important features of PMs. We note that many features of the syndrome are not static, but change in frequency with age of patient.

longitudinal vs. cross-sectional analysis

Both the cross-sectional and longitudinal analyses found age-related changes in the prevalence of various health history and developmental milestones. the longitudinal analysis was performed on a much smaller sample size and patients had widely ranging ages at assessment, but this analysis generally agreed with the results derived from the larger cross-sectional analysis. the agreement between age effects noted in the cross-sectional and longitudinal analy-ses of health history features supports the use of cross-sec-tional data as a good proxy for longitudinal health history follow-up of individuals.

sample size was insufficient to perform a longitudinal analysis of growth or other features obtained from physi-cal exam. While most patients were of typical height, in the cross-sectional data we did observe a trend of decreasing stature-for-age with increased age, although all adults were within the 5th–95th gender-specific percentile for height. this observation is consistent with a decrease in rate of growth during childhood and should be investigated in future studies.

the explanation for phenotypic changes with age may be related to expected changes observed with development, albeit at a delayed rate. For instance, independent walk-ing and toileting abilities improved with age and adverse behaviors such as chewing non-food items, biting, hair pulling, and excessive crying were less prevalent with age. adverse features that increased with age, such as the pro-portion of patients reporting ever having seizures or asD, could be related to having had more opportunity to have these features, more time to acquire a diagnosis, longer exposure to environmental factors (i.e., drugs, trauma, infection), or neurological deterioration leading to these features.

Parent-of-origin effects

this study reports the largest cohort for parent-of-origin analysis of the 22q13 deletion. Our finding of a prepon-derance of deletions occurring on the paternally inherited chromosome agrees with previous reports (Bonaglia et al. 2011; Jeffries et al. 2005; luciani et al. 2003; Wilson et al. 2003). also, in agreement with previous findings were the lack of age difference between the parents transmit-ting the affected chromosome and the parents transmitting

the normal one (Bonaglia et al. 2011) and no difference in sizes of deletions by parent-of-origin (Bonaglia et al. 2011; luciani et al. 2003). We observed only one feature, seizures, associated with parent-of-origin. Other studies report lack of association with parent-of-origin and phe-notypes (luciani et al. 2003; Jeffries et al. 2005). Wilson et al. (2003) found two features (measures of community living and a high palate) to be associated with paternal ori-gin, and found seizures to be unassociated with parent-of-origin. While no 22q13.3 genes are known to be imprinted according to the Catalog of Parent-of-Origin effects (Mori-son et al. 2001), prediction algorithms suggest the potential for several 22q13.31q13.33 genes to be imprinted including CELSR1 in 22q13.31 and ALG12, TUBGCP6, MAPK12, PPP6R2, NCAPH2, and SHANK3 in 22q13.33 (luedi et al. 2007). thus, further investigation is needed to explore potential epigenetic effects as contributing to the variability of clinical features in PMs.

effect of deletion size

Our current study, our prior analyses on a subset of this cohort (sarasua et al. 2011, 2013), and other investigators (soorya et al. 2013; Wilson et al. 2003; Dhar et al. 2010; Jeffries et al. 2005; aldinger et al. 2013; Hannachi et al. 2013) have found associations between deletion size and phenotypes which may indicate additional genes, regula-tory elements, or position effects contributing to PMs. Our finding that the risks of aggressive behavior and impulsiveness decrease with larger deletion sizes may indicate that greater physical or cognitive impairments reduce the ability of patients to display these behaviors. Our current analysis, based on larger sample size and adjusting for age and gender, resulted in similar find-ings from our prior analyses (sarasua et al. 2011, 2013). two of the strongest associations with deletion size, found both in the smaller cohorts published earlier (sar-asua et al. 2011, 2013) and in our expanded cohort, are for macrocephaly and speech ability. While many patients had absent speech regardless of deletion size, a correlation was observed between deletion size and speech ability (table 5, supplemental Figure s1). this correlation may indicate a cumulative effect of loss of multiple genes or regulatory elements. Genes of particular interest include MPPED1 and CYB5R3 in 22q13.2, and FBLN1, NUP50, C22orf9, KIAA1644, PARVB, TRMU, WNT7B, ATXN10, and micro rnas hsa-mir-1249, hsa-let-7a-3 and hsa-let7 in 22q13.31. regarding head circumference, all patients with macrocephaly have a deletion size >5 Mb and all cases are missing one copy of WNT7B, which interacts with GPC3 (Capurro et al. 2005), the protein involved in the macrocephaly syndrome simpson–Golabi–Behmel syndrome (Pilia et al. 1996).

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similar to our study, a recent study of 32 PMs patients found deletion size positively associated with number of dysmorphic features, number of medical comorbidities, gross motor skills, qualitative abnormalities in recipro-cal social interactions, and qualitative abnormalities in communication (soorya et al. 2013). Unlike our findings, expressive and receptive language skills were not signifi-cantly associated with deletion size in that study. Our study found deletion size to be of borderline statistical signifi-cance and to be inversely associated with asDs while their study found asDs to be positively associated with deletion size. Our assessment of asDs relied upon parent report of an asD diagnosis while their study included assessments using standard diagnostic scales (e.g., vineland and aDI-r). In their study, any type of seizure was reported in 41 % of patients, in line with our observations. they further determined that 22 % had only febrile seizures and 19 % had non-febrile seizures. Of those with non-febrile sei-zures, all had confirmatory abnormal eeG findings. Our study did not have access to eeG or imaging studies.

We did not conduct sequencing analysis of breakpoints to investigate molecular mechanisms generating the 22q13 rearrangements in our patients. However, molecular mecha-nisms generating and stabilizing terminal deletions, includ-ing ring 22 and translocations, have been studied in detail by Bonaglia et al. (2011) and include telomere healing and cap-ture for terminal deletions and non-homologous end-joining for ring chromosomes and translocations. the mechanisms generating and stabilizing 22q13 deletions with proximal duplications have not been studied. However, these types of duplication–deletion terminal deletions have been described for most chromosome arms, with the most likely mechanism being due to a U-type exchange between sister chromatids after a pre-meiotic double-strand break (rowe et al. 2009; Ballif et al. 2003; Chen et al. 2005; Wang et al. 2008).

Changes in diagnostic sensitivity: changing picture of PMs

Diagnostic sensitivity has increased dramatically in the past 10 or more years. now that chromosome array CGH is a first-tier test for children with developmental disabilities as well as congenital anomalies (Miller et al. 2010), not only will more individuals be tested, but also a higher number of small deletions will be detected with this technique. these two factors may affect the severity and types of disabilities present in individuals diagnosed with PMs, likely identi-fying individuals with smaller deletions and possibly more mild or different features. Because deletion size affects the constellation and severity of phenotypes found in patients and because age of evaluation affects the degree to which certain phenotypes are manifested, both of these factors will need to be addressed in future genotype–phenotype studies and clinical therapeutic trials.

limitations

there were several limitations to this analysis. a large number of statistical tests were performed and some find-ings may be due to chance. While a focused, high-density oligo array CGH was used to delineate 22q13 deletion breakpoints, a genome-wide array CGH was not performed and some patients have additional chromosomal rearrange-ments such as translocations or ring chromosome. Medical history was obtained by questionnaires completed by par-ents and, although most of such questionnaires were filled under the supervision of clinical geneticists, the collected data may be subject to recall or information bias. In par-ticular, the results of eeG, imaging studies, or medical charts were generally unavailable to investigators. How-ever, growth and physical features were obtained by stand-ardized physical assessment by trained clinical geneticists providing robust analysis of physical features.

Conclusion

Patients with PMs present with a diversity of speech, developmental, behavioral, neurologic, and other clini-cal features. the manifestation of these features varies by age at evaluation and deletion size, but generally not by parent-of-origin of the affected chromosome. Patients with PMs carry widely varying deletions with no apparent com-mon breakpoints and structural variations include terminal and interstitial deletions as well as duplications of 22q13. Patients diagnosed more recently tend to have smaller dele-tions, likely reflecting the improved diagnostic sensitivity as well as increased testing, and thus may present with less severe or different phenotypes than reported in the earlier literature on PMs. additional longitudinal follow-up, par-ticularly among adults, is needed to determine progression of the syndrome with age. this is the largest and most com-prehensive assessment of Phelan–McDermid syndrome to date and can serve as a baseline for future comparisons.

Acknowledgments We thank the patients and families who par-ticipated in this study and made this work possible and the Phelan–McDermid syndrome Foundation who organized the biannual family conferences where much of the data collection took place. We thank Gail stapleton and Cindy skinner who managed data collection at the family conferences. We thank Dr. amy lawton-rauh and Dr. Charles schwartz for helpful comments on the manuscript. We dedicate this paper to the memory of Julianne s. Collins.

This work was supported, in part, by a fellowship to SMS from the Phelan–McDermid Syndrome Foundation; the Genetics Endowment of South Carolina; and the South Carolina Depart‑ment of Disabilities and Special Needs.

Conflict of interest the authors declare no conflict of interest.

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