The Genomics of Arthrogryposis, a Complex Trait: Candidate Genes and Further Evidence for Oligogenic Inheritance

Davut Pehlivan; Yavuz Bayram; Nilay Gunes; Zeynep Coban Akdemir; Anju Shukla; Tatjana Bierhals; Burcu Tabakci; Yavuz Sahin; Alper Gezdirici; Jawid M Fatih; Elif Yilmaz Gulec; Gozde Yesil; Jaya Punetha; Zeynep Ocak; Christopher M Grochowski; Ender Karaca; Hatice Mutlu Albayrak; Periyasamy Radhakrishnan; Haktan Bagis Erdem; Ibrahim Sahin; Timur Yildirim; Ilhan A Bayhan; Aysegul Bursali; Muhsin Elmas; Zafer Yuksel; Ozturk Ozdemir; Fatma Silan; Onur Yildiz; Osman Yesilbas; Sedat Isikay; Burhan Balta; Shen Gu; Shalini N Jhangiani; Harsha Doddapaneni; Jianhong Hu; Donna M Muzny; Baylor-Hopkins Center for Mendelian Genomics; Eric Boerwinkle; Richard A Gibbs; Konstantinos Tsiakas; Maja Hempel; Katta Mohan Girisha; Davut Gul; Jennifer E Posey; Nursel H Elcioglu; Beyhan Tuysuz; James R Lupski

doi:10.1016/j.ajhg.2019.05.015

. 2019 Jun 20;105(1):132–150. doi: 10.1016/j.ajhg.2019.05.015

The Genomics of Arthrogryposis, a Complex Trait: Candidate Genes and Further Evidence for Oligogenic Inheritance

Davut Pehlivan ^1,^2,²⁸, Yavuz Bayram ^1,^3,²⁸, Nilay Gunes ⁴, Zeynep Coban Akdemir ¹, Anju Shukla ⁵, Tatjana Bierhals ⁶, Burcu Tabakci ⁷, Yavuz Sahin ⁸, Alper Gezdirici ⁹, Jawid M Fatih ¹, Elif Yilmaz Gulec ⁹, Gozde Yesil ¹⁰, Jaya Punetha ¹, Zeynep Ocak ⁹, Christopher M Grochowski ¹, Ender Karaca ¹, Hatice Mutlu Albayrak ¹¹, Periyasamy Radhakrishnan ⁵, Haktan Bagis Erdem ¹², Ibrahim Sahin ¹³, Timur Yildirim ¹⁴, Ilhan A Bayhan ¹⁴, Aysegul Bursali ¹⁴, Muhsin Elmas ¹⁵, Zafer Yuksel ¹⁶, Ozturk Ozdemir ¹⁷, Fatma Silan ¹⁷, Onur Yildiz ¹⁷, Osman Yesilbas ¹⁸, Sedat Isikay ¹⁹, Burhan Balta ²⁰, Shen Gu ¹, Shalini N Jhangiani ²¹, Harsha Doddapaneni ²¹, Jianhong Hu ²¹, Donna M Muzny ²¹; Baylor-Hopkins Center for Mendelian Genomics, Eric Boerwinkle ^21,²², Richard A Gibbs ^1,²¹, Konstantinos Tsiakas ²³, Maja Hempel ⁶, Katta Mohan Girisha ⁵, Davut Gul ²⁴, Jennifer E Posey ¹, Nursel H Elcioglu ^7,²⁵, Beyhan Tuysuz ⁴, James R Lupski ^1,^21,^26,^27,^∗

¹Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA

²Section of Pediatric Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA

³Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA

⁴Department of Pediatric Genetics, Istanbul University-Cerrahpasa Medical Faculty, Istanbul 34096, Turkey

⁵Department of Medical Genetics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal 576104, India

⁶Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, Martinistraße 52, Hamburg 20246, Germany

⁷Department of Pediatric Genetics, Marmara University Medical School, Istanbul 34854, Turkey

⁸Department of Medical Genetics, Necip Fazıl City Hospital, Kahramanmaras 46050, Turkey

⁹Department of Medical Genetics, Kanuni Sultan Suleyman Training and Research Hospital, Istanbul 34303, Turkey

¹⁰Department of Medical Genetics, Bezmi Alem Vakif University Faculty of Medicine, Istanbul 34093, Turkey

¹¹Department of Pediatrics, Division of Pediatric Genetics, Faculty of Medicine, Ondokuz Mayıs University, Samsun 55270, Turkey

¹²Department of Medical Genetics, University of Health Sciences, Diskapi Yildirim Beyazit Training and Research Hospital, Ankara 06110, Turkey

¹³Department of Medical Genetics, University of Erzurum, School of Medicine, Erzurum 25240, Turkey

¹⁴Department of Orthopedics and Traumatology, Baltalimani Bone Diseases Training and Research Hospital, Istanbul 34470, Turkey

¹⁵Department of Medical Genetics, Afyon Kocatepe University, School of Medicine, Afyon 03218, Turkey

¹⁶Medical Genetics Clinic, Mersin Women and Children Hospital, Mersin 33330, Turkey

¹⁷Department of Medical Genetics, Faculty of Medicine, Onsekiz Mart University, Canakkale 17000, Turkey

¹⁸Division of Critical Care Medicine, Department of Pediatrics, University of Health Sciences, Van Training and Research Hospital, Van 65130, Turkey

¹⁹Department of Physiotherapy and Rehabilitation, Hasan Kalyoncu University, School of Health Sciences, Gaziantep 27000, Turkey

²⁰Department of Medical Genetics, Kayseri Training and Research Hospital, Kayseri 38080, Turkey

²¹Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA

²²Human Genetics Center, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA

²³Department of Pediatrics, University Medical Center Hamburg-Eppendorf, Hamburg, 20246, Germany

²⁴Department of Medical Genetics, Gulhane Military Medical School, Ankara 06010, Turkey

²⁵Eastern Mediterranean University School of Medicine, Cyprus, Mersin 10, Turkey

²⁶Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA

²⁷Texas Children’s Hospital, Houston, TX 77030, USA

^∗

Corresponding author jlupski@bcm.edu

²⁸

These authors contributed equally to this work

PMCID: PMC6612529 PMID: 31230720

Abstract

Arthrogryposis is a clinical finding that is present either as a feature of a neuromuscular condition or as part of a systemic disease in over 400 Mendelian conditions. The underlying molecular etiology remains largely unknown because of genetic and phenotypic heterogeneity. We applied exome sequencing (ES) in a cohort of 89 families with the clinical sign of arthrogryposis. Additional molecular techniques including array comparative genomic hybridization (aCGH) and Droplet Digital PCR (ddPCR) were performed on individuals who were found to have pathogenic copy number variants (CNVs) and mosaicism, respectively. A molecular diagnosis was established in 65.2% (58/89) of families. Eleven out of 58 families (19.0%) showed evidence for potential involvement of pathogenic variation at more than one locus, probably driven by absence of heterozygosity (AOH) burden due to identity-by-descent (IBD). RYR3, MYOM2, ERGIC1, SPTBN4, and ABCA7 represent genes, identified in two or more families, for which mutations are probably causative for arthrogryposis. We also provide evidence for the involvement of CNVs in the etiology of arthrogryposis and for the idea that both mono-allelic and bi-allelic variants in the same gene cause either similar or distinct syndromes. We were able to identify the molecular etiology in nine out of 20 families who underwent reanalysis. In summary, our data from family-based ES further delineate the molecular etiology of arthrogryposis, yielded several candidate disease-associated genes, and provide evidence for mutational burden in a biological pathway or network. Our study also highlights the importance of reanalysis of individuals with unsolved diagnoses in conjunction with sequencing extended family members.

Keywords: arthrogryposis, multilocus pathogenic variation, trio-exome, ES reanalysis, identity-by-descent, absence of heterozygosity, joint contracture, neuromuscular disease

Introduction

Arthrogryposis is a term that describes the clinical observation of joint contractures in more than one segment of the body. It does not describe a specific disease entity, but rather represents a descriptive clinical neuromuscular sign for multiple contractures associated with different medical conditions. The primary underlying cause of arthrogryposis is postulated to be decreased fetal joint mobility during intrauterine development. Lack of fetal joint mobility might result from multiple etiologies for perturbed neuromuscular function; these etiologies include intrinsic causes such as neurological disorders, muscle diseases, skeletal conditions, and abnormalities in connective and cartilage tissue and extrinsic factors such as maternal diseases, intrauterine space limitations, maternal exposures to drugs or chemicals, and decreased blood supply to the fetus.¹ Thus, arthrogryposis can be thought of as a birth defect due to a malformation in some individuals and as a deformation in others or, also, as a complex trait with both genetic and environmental influences.

The prevalence of arthrogryposis ranges from ∼1/3000–5000, and it has a high (∼50%) mortality rate.² The etiology is thought to be mostly genetic, and variants in more than 300 genes associated with over 400 Mendelian conditions have been identified.³ Copy number variants (CNVs) including microdeletions and duplications have also been implicated in individuals with arthrogryposis.⁴^,⁵^,⁶^,⁷ The molecular etiology of arthrogryposis and the potential biological pathways involved remain unknown in many individuals; molecular diagnostic rates of 47% in an Australian cohort of 38 families and 58% in a Turkish cohort of 48 families (phase I of this study) have been reported.⁸^,⁹ One of the insights into the potential genetic architecture and underlying genetic etiology of some individuals with arthrogryposis, recognized only through genome-wide screening of coding regions, is the contribution of rare variants in multiple loci of a single personal genome to the observed phenotype (i.e., multiple molecular diagnoses leading to a blended phenotype).¹⁰^,¹¹^,¹²^,¹³^,¹⁴ Additionally, both mono- and bi-allelic variants of several genes, responsible respectively for autosomal-dominant (AD) and autosomal-recessive (AR) disease traits, are known to cause either the same or a different syndrome and are being reported more frequently with genome-wide analysis techniques such as exome sequencing (ES).⁸^,¹⁵^,¹⁶^,¹⁷^,¹⁸^,¹⁹

We previously reported molecular findings from 28 out of 48 arthrogryposis-affected families (a molecular diagnostic yield of 58.3%).⁸ In the current study, we enrolled an additional 71 families (including two families found through GeneMatcher) and performed a reanalysis of 20 undiagnosed families, including ten families for which the initial proband-exome was extended to trio exome with parental samples, from the previously reported cohort. We provide clinical and genomic evidence for 15 candidate arthrogryposis-associated genes and four candidate developmental delay and intellectual disability (DD and ID)-associated genes. Our findings suggest mutational burden might contribute to the molecular diagnosis of some individuals with arthrogryposis through the aggregation of multilocus pathogenic variation in a personal genome.

Material and Methods

Study Participants

We recruited 103 individuals and fetuses from 91 mostly Turkish families (only two families of different ethnicity were found through GeneMatcher) with the presenting clinical feature of arthrogryposis (Figure 1A). Of the 103 participants, 53 were female (51.5%), 47 were male (45.6%), and three (2.9%) had a gender that was not reported (fetus). Ages ranged from 19 gestational weeks to 42 years old. Thirty-four of the participant families were characterized as having syndromic arthrogryposis, whereas 57 had an apparent isolated neuromuscular disorder. Parental consanguinity was reported in 46 families (50.5%), and 45 families (49.5%) had no historical evidence for parental consanguinity. After all relevant family members provided written informed consent, peripheral blood was collected from affected individuals, parents, and unaffected relatives if available. Genomic DNA was extracted from blood leukocytes according to standard procedures. All genomic studies were performed on DNA samples isolated from blood. This study was approved by the institutional review board at Baylor College of Medicine (IRB protocol # H-29697).

Distribution and Molecular Results of Enrolled Individuals in the Arthrogryposis Cohort and Families with Multilocus Pathogenic Variation

(A) Distribution of individuals enrolled in arthrogryposis cohort.

(B) A pie chart displaying the distribution of molecular findings for each individual in this study (i.e., phase II) of the arthrogryposis cohort (89 families). Multilocus pathogenic variant model families were classified according to muscle gene status. A corresponding explanation for the colors in the pie chart is below the chart. The abbreviation CNV = copy number variation.

(C) Families affected with multilocus pathogenic variation (19 families) from phase I + II. Abbreviations are as follows: HMZ = homozygous, HTZ = heterozygous, Comp HTZ = compound heterozygous, and XL = hemizygous male.

Exome Sequencing

We applied ES to selected family members through the Baylor-Hopkins Center for Mendelian Genomics (BHCMG) research initiative.²⁰ All experimental procedures were performed according to previously described methods.²¹ Briefly, genomic DNA samples underwent exome capture with Baylor College of Medicine Human Genome Sequencing Center core design (52 Mb, Roche NimbleGen, RRID: nif-0000-31466), and were then sequenced on the HiSeq platform (Illumina) with ∼100× depth of coverage. Sequence data were aligned and mapped to the human genome reference sequence (hg19) with the Mercury in-house bioinformatics pipeline.²² Variants were called with ATLAS2 (an integrative variant analysis pipeline optimized for variant discovery) and SAMTOOLS (RRID: nlx_154607; the Sequence Alignment/Map) suites, and they were annotated with an in-house-developed annotation pipeline that uses annotation of genetic variants and additional tools and databases.²³^,²⁴^,²⁵ Variant filtering parsed nonsynonymous variants by population frequency data. The minor allele frequency of candidate variants was obtained from publicly available databases such as the 1000 Genomes Project and other large-scale exome-sequencing projects, including the Exome Variant Server; the National Heart, Lung, and Blood Institute (NHLBI) Grand Opportunity Exome Sequencing Project (ESP); the Atherosclerosis Risk in Communities Study Database (ARIC); the Genome Aggregation Database (gnomAD); the Exome Aggregation Consortium (ExAC); and our in-house-generated exome database (∼13,000 individuals) at the Baylor College of Medicine Human Genome Sequencing Center.

In order to detect disease-causing single nucleotide variants (SNVs), a stepwise analysis workflow was implemented.²⁶ To be able to identify CNVs, we used publicly available bioinformatics tools, including XHMM (eXome-Hidden Markov Model), CoNIFER, and CoNVex programs, for larger CNVs (≥3 exon deletion and duplication), and we used an in-house-developed software, HMZDelFinder, for smaller homozygous and hemizygous intragenic CNVs.²⁷^,²⁸ In order to capture de novo disease-causing variants, we used another in-house-developed program called DNM (de novo mutation)-Finder.²⁶ All candidate genes were submitted to GeneMatcher to identify additional individuals with variants likely to be damaging in the same gene.²⁹^,³⁰ To examine absence of heterozygosity (AOH) regions, which might represent identity-by-descent (IBD), surrounding candidate variants, we calculated B-allele frequency by using exome variant data as a ratio of variant reads to total reads.³¹ These data were then processed with the circular binary segmentation (CBS) algorithm³² in order to identify AOH regions. The calculated AOH intervals from BafCalculator could represent “apparent genetic transmission distortion” of individual genomic loci, resulting in runs-of-homozygosity (ROHs) for diploid alleles that can occur by: (1) IBD, (2) uniparental disomy,³³ or (3) a large deletion CNV.

Sanger Sequencing

To validate exome-identified candidate variants by an orthogonal, experimental DNA-sequencing method and segregate these variants in the families, we amplified target exons from genomic DNA by using conventional PCR (HotStar TaqDNA polymerase, QIAGEN) and high-GC-content long-range PCR (TaKaRa LA Taq, Clontech), and we analyzed PCR amplification products by Sanger sequencing (DNA Sequencing Core Facility at Baylor College of Medicine). If the exome-identified variant was not confirmed by Sanger sequencing or if segregation analysis showed inconsistency with Mendelian expectations under the hypothesized genetic model, then the variant was considered to be unlikely to contribute to the arthrogryposis trait.

Chromosomal Microarray Analysis for Genome-Wide CNV Detection

For individuals in whom we detected a CNV (individual BAB7128) through genome-wide sequencing data and bioinformatic CNV-detection tools,³⁴ or as part of the preliminary, low-resolution clinical genomics diagnostic studies such as karyotyping and low-resolution array comparative genomic hybridization (aCGH; individual BAB8145 and individual BAB9312), we performed Agilent’s custom-designed whole-genome array (Baylor Genetics Laboratory, CMA version 11, design#079906) to confirm the CNV. All array procedures, including DNA fragmentation and labeling, array hybridization, washing, and scanning, were performed according to the manufacturer’s instructions and previously described protocols³⁵ with minor modifications. Gender-matched female control (NA15510) DNA and male control (NA10851) DNA were obtained from Coriell cell repositories (Coriell Institute for Medical Research). Data processing and analyses were done with Agilent Feature Extraction Software (version 11.5, Agilent Technologies) and Agilent Genomic Workbench (edition 7.0.4.0, Agilent Technologies).

Droplet Digital PCR Mosaicism Analysis

Variants suspected to be in a mosaic state on the basis of exome read-depth ratios (vR/tR, variant reads/total reads) were further validated via an orthogonal experimental system on a BioRad QX200 ddPCR platform. Custom-designed fluorescent TaqMan probes targeting the mutant variant (FAM fluorescence) and the reference (HEX fluorescence) were multiplexed with common forward and reverse primers and run under standard ddPCR conditions.³⁶ The fractional abundances for the amplified mutant and reference allele were calculated to determine the percent of the mosaicism.

Human and Fruit Fly Cross-Database Mining for Candidate Gene Analyses

We evaluated orthologs and paralogs in fruit flies and humans for identified candidate disease genes. In order to determine the human paralogs for fruit fly genes, we used DRSC Integrative Ortholog Prediction Tool (DIOPT).³⁷ We first forward checked the human gene in the fruit fly, and fly genes with the highest DIOPT scores were reverse checked to detect the number of human homologs. A DIOPT score of 3 is set as the threshold to determine the presence of paralogs or orthologs in the human or fly, respectively.

Results

Exome Sequencing and Family-Based Genomics in Arthrogryposis

We applied ES in a large cohort (Figure 1A, phase II) of 69 newly recruited families, a clinically heterogeneous group of individuals in whom the arthrogryposis phenotype is an apparent, isolated clinical feature (nonsyndromic arthrogryposis) or is part of the disease spectrum (syndromic arthrogryposis). Molecular findings from the analysis of phase I of this cohort had revealed a 58.3% (28 of 48 families studied) molecular diagnostic rate.⁸ In phase II of this family-based genomics study, we analyzed 91 families, including 69 newly ascertained and recruited families, 20 families who remained “molecularly undiagnosed” from phase I, and two families identified through GeneMatcher (Figure 1A).

The results were divided into the five categories presented below: (1) known disease-associated genes that have an established association with the arthrogryposis phenotype; (2) “probably causative” arthrogryposis-associated genes: rare variant, likely to be damaging, pathogenic alleles present in at least two different families; (3) “possibly causative” arthrogryposis-associated genes: pathogenic variants discovered in only one family in this study; (4) oligogenic inheritance and blended phenotypes: multilocus pathogenic variation, i.e., variants present in at least two disease-associated genes, that explains the observed set of phenotypic features including arthrogryposis; (5) CNVs causing the arthrogryposis phenotype. The molecular findings of the individuals for the entire cohort are described in Tables 1, 2, S1, and S2, and Figures S1 and S2.

Table 1.

Molecular Summary of the Known, Probably, and Possibly Causative Arthrogryposis Genes in the Cohort

Gene	Proband	Nucleotide (Protein)	Zygosity	AOH Block Around the Gene (Mb)	Total AOH (Mb)
Known Causative Genes

CHRNG	BAB8511	c.753_754del (p.Val253Alafs^∗44)	Hmz	20.8	162.1
	BAB8571	c.256C>T (p.Arg86Cys)	Hmz	25.8	251.1
	BAB8603	c.256C>T (p.Arg86Cys)	Hmz	6.7	154.5
	BAB8685	c.753_754del (p.Val253Alafs^∗44)	Hmz	19.0	248.8
	BAB9851	c.753_754del (p.Val253Alafs^∗44)	Hmz	22.3	123.3
	BAB9942	c.256C>T (p.Arg86Cys)	Hmz	3.5	557.7
ECEL1	BAB8223	c.1630C>T (p.Arg544Cys)	Hmz	3.3	199.2
	BAB9537	c.1581+1G>A	Hmz	14.2	164.4
	BAB10711	c.1916C>T (p.Ser639Phe)	Hmz	14.7	238
NEB	BAB8518	c.24988C>T (p.Arg8330^∗)	Hmz	73.4	151.2
COL12A1	BAB8843	c.1488dup (p.Phe497Ilefs^∗5)	Hmz	20.8	297.9
KLHL7	BAB8095	c.1051C>T (p.Arg351^∗)	Hmz	14.1	36.2
	BAB8098	c.1051C>T (p.Arg351^∗)	Hmz	21.7	96.5
	BAB8652	c.1022del (p.Leu341Trpfs^∗9)	Hmz	15.5	248.5
	BAB10699	c.565C>T (p.Arg189^∗)	Hmz	26.0	354.3
	BAB10705	c.565C>T (p.Arg189^∗)	Hmz	22.9	238.2
MYBPC1	BAB8515	c.32A>G (p.Glu11Gly)	Hmz	25.8	351.9
MYBPC2	BAB9540	c.920T>C (p.Val307Ala)	Comp Htz	–	156.1
MYBPC2	BAB9540	c.3194C>T (p.Ala1065Val)	Comp Htz	–	156.1
MFN2	BAB3941	c.526G>A (p.Gly176Ser)	Hmz	0.8	99.6
SYNE1	BAB7084	c.2839G>A (p.Glu947Lys)	Comp Htz	–	17.7
SYNE1	BAB7084	c.21164A>G (p.Lys7055Arg)	Comp Htz	–	17.7
PLEC	BAB7079	c.6523A>G (p.Lys2175Glu)	Comp Htz	–	8.2
PLEC	BAB7079	c.8813C>T (p.Thr2938Met)	Comp Htz	–	8.2
POR	BAB8694	c.859G>C (p.Ala287Pro)	Hmz	13.5	102.8
HSD17B4	BAB8832	c.1417C>T (p.Arg473Trp)	Hmz	49.0	202.9
HSD17B4	BAB8835	c.1417C>T (p.Arg473Trp)	Hmz	60.7	165.3
POMGNT1	BAB8986	c.461C>A (p.Pro154His)	Hmz / Hmz	29.3	168.4
POMGNT1	BAB8986	c.550C>T (p.His184Tyr)	Hmz / Hmz	29.3	168.4
FKBP10	BAB9244	c.890_897dup (p.Gly300^∗)	Hmz	4.3	154.5
TGFB3	BAB9703	c.171del (p.Glu58Serfs^∗4)	Hmz	48.5	183.4
TGFB3	BAB9704	c.171del (p.Glu58Serfs^∗4)	Hmz	30.1	480.7
TTN	BAB7779	c.2370+2T>C	Comp Htz	–	34.2
TTN	BAB7779	c.67279C>T (p.Arg22427^∗)	Comp Htz	–	34.2
IGF1	BAB9740	c.156dup (p.Leu53Alafs^∗5)	Hmz	15.7	289.3
IGF1	BAB9741	c.156dup (p.Leu53Alafs^∗5)	Hmz	6.6	208.3
TOR1A	BAB10702	c.506T>C (p.Phe169Ser)	Hmz	11.8	196.4
MYH3	BAB3964	c.2015G>A (p.Arg672His)	Htz	–	30.4
MYH3	BAB9848	c.2015G>A (p.Arg672His)	Htz	–	26.1
TNNT3	BAB3928	c.163C>T (p.Arg55Cys)	Htz	–	10.4
SYT2	BAB7308	c.1081G>C (p.Asp361His)	Htz	–	65.5
PIEZO2	BAB8789	c.8181_8183del (p.Glu2727del)	Htz	–	208.2
TRPV4	BAB8991	c.806G>A (p.Arg269His)	Htz	–	39.5
PQBP1	BAB8090	c.463C>T (p.Arg155^∗)	Hemi	–	24.2

Probably Causative Genes

RYR3	BAB7845	c.2486G>A (p.Arg829His)	Hmz	1.8	247.5
	PAED187	c.2000A>G (p.Asp667Gly)	Comp Htz	–	5.5
	PAED187	c.11164+1G>A	Comp Htz	–	5.5
	BAB8988	c.8939G>T (p.Arg2980Leu)	Hmz	12.0	149.6
MYOM2	BAB8905	c.621C>G (p.Ser207Arg)	Hmz	7.2	312.9
MYOM2	IN076	c.2797C>T (p.Gln933^∗)	Hmz	7.2	369.1
ABCA7	BAB6807	c.5092C>T (p.Arg1698Trp)	Hmz	3.8	153.9
	BAB6808	c.5092C>T (p.Arg1698Trp)	Hmz	3.0	180.2
	BAB10708	c.3076C>T (p.Arg1026Cys)	Comp Htz	–	233.8
	BAB10708	c.4045C>T (p.Arg1349Trp)	Comp Htz	–	233.8
ERGIC1	BAB8802	c.782G>A (p.Gly261Asp)	Hmz	30.8	274.6
SPTBN4	BAB8691	c.6433G>A (p.Ala2145Thr)	Hmz	3.4	183.9

Possibly Causative Genes

MID1IP1	BAB8397	c.297C>G (p.Asn99Lys)	Hemi	–	374.7
DRG1	BAB8807	c.118C>T (p.Arg40^∗)	Hmz	7.6	251.6
TANC1	BAB8807	c.2830C>T (p.His944Tyr)	Hmz	10.3	251.6
MYOM3	BAB8532	c.3534+56C>T	Comp Htz	–	107.2
MYOM3	BAB8532	c.1684G>A (p.Val562Ile)	Comp Htz	–	107.2
TNRC6C	BAB8688	c.1022G>A (p.Gly341Glu)	Hmz	7.0	132.0
FLII	BAB7710	c.2590C>T (p.Arg864Trp)	Hmz	2.2	257.4
TAF9B	BAB8400	c.133C>A (p.Arg45Ser)	Hemi	–	110.6
MED27	BAB8606	c.770C>T (p.Pro257Leu)	Hmz	11.8	195.2
MED27	BAB8609	c.770C>T (p.Pro257Leu)	Hmz	2.0	233.7
CACUL1	BAB9729	c.910_911del (p.Leu304Ilefs^∗3)	Hmz	10.0	158.9
FGFRL1	BAB3944	c.124C>T (p.Arg42Trp)	Hmz	3.4	290.2
TMEM214	BAB5192	c.764G>A (p.Arg255Gln)	Hmz	15.9	220.3
NR2C1	BAB8086	c.544+1G>C	Hmz	4.3	231.7
NR2C1	BAB8087	c.544+1G>C	Hmz	6.7	126.3
PRDM2	BAB9309	c.4283_4295del (p.Leu1428Glnfs^∗15)	Htz	–	284.5
FAT1	BAB8356	c.6026A>G (p.Asn2009Ser)	Hmz	2.0	142.9

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Abbreviations are as follows: Mb = megabase, AOH = absence of heterozygosity, Hmz = homozygous, Hemi = hemizygous, Htz = heterozygous, and Comp Htz = compound heterozygous.

Table 2.

Molecular Summary of the Multilocus Pathogenic Variation Cohort

Family ID (HOU#)	Proband ID (BAB#)	Gene	Nucleotide (Protein)	Zygosity	AOH Block Around the Gene (Mb)	Total AOH (Mb)
HOU2523	BAB6807	COL6A3	c.619C>T (p.Gln207^∗)	Hmz	7.8	153.9
	BAB6807	ABCA7	c.5092C>T (p.Arg1698Trp)	Hmz	3.8	153.9
	BAB6808	ABCA7	c.5092C>T (p.Arg1698Trp)	Hmz	3.0	180.2
	BAB6808	ADNP	c.775A>C (p.Asn259His)	Hmz	–	180.2
HOU2790	BAB7710	ECEL1	c.505_529del (p.Gly169Serfs^∗26)	Hmz	20.1	257.4
HOU2790	BAB7710	FLII	c.2590C>T (p.Arg864Trp)	Hmz	2.2	257.4
HOU2817	BAB7845	RYR3	c.2486G>A (p.Arg829His)	Hmz	1.8	247.5
		MYO18B	c.2879C>T (p.Ala960Val)	Comp Htz	–
		MYO18B	c.3397C>T (p.Arg1133Trp)	Comp Htz	–
HOU3050	BAB8397	NEB	c.19101+5G>A	Hmz	–	374.7
HOU3050	BAB8397	MID1IP1	c.297C>G (p.Asn99Lys)	Hemi	–	374.7
HOU3051	BAB8400	GBE1	c.1864_1866del (p.Leu622del)	Hmz	37.9	110.6
		AP4M1	c.136C>G (p.Pro46Ala)	Hmz	14.2
		TAF9B	c.133C>A (p.Arg45Ser)	Hemi	–
HOU3112	BAB8532	SPEG	c.6971T>A (p.Ile2324Asn)	Hmz	22.6	107.2
		MYOM3	c.1684G>A (p.Val562Ile)	Comp Htz	–
		MYOM3	c.3534+56C>T	Comp Htz	–
		CIT	c.2651A>C:p.Gln884Pro	Htz	–
HOU3125	BAB8600	FBN2	c.4094G>C (p.Cys1365Ser)	Htz	–	–
	BAB8601	FBN2	c.4094G>C (p.Cys1365Ser)	Htz	–	31.9
	BAB8601	COL6A3	c.367G>A (p.Val123Met)	Hmz	1.5	31.9
HOU3127	BAB8606	COG6	c.726del (p.Cys242Trpfs^∗7)	Hmz	16.9	195.2
	BAB8606	MED27	c.770C>T (p.Pro257Leu)	Hmz	11.8	195.2
	BAB8609	MED27	c.770C>T (p.Pro257Leu)	Hmz	2.0	233.7
HOU3149	BAB8688	KLHL7	c.1258C>T (p.Arg420Cys)	Hmz	17.9	132.0
		HOXA11	c.304G>A (p.Val102Met)	Hmz	17.9
		TNRC6C	c.1022G>A (p.Gly341Glu)	Hmz	7.0
HOU3180	BAB8807	DRG1	c.118C>T (p.Arg40^∗)	Hmz	6.7	251.6
		TANC1	c.2830C>T (p.His944Tyr)	Hmz	10.3
		BRWD3	c.592-3T>C	Hemi	–
HOU3943	BAB10708	SPEG	c.9575C>A (p.Thr3192Asn)	Htz	–	233.8
		TPM2	c.620_631dup (p.Gln210_Ala211insValGluAlaGln)	Htz	–
		ABCA7	c.3076C>T (p.Arg1026Cys)	Comp Htz	–
		ABCA7	c.4045C>T (p.Arg1349Trp)		–

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Abbreviations are as follows: Mb = megabase, AOH = absence of heterozygosity, Hmz = homozygous, Hemi = hemizygous, Htz = heterozygous, and Comp Htz = compound heterozygous.

The overall molecular diagnostic rate in the present phase II cohort of 89 families with arthrogryposis is 65.2% (58/89); 43 of these 89 families have variants in previously described arthrogryposis-associated genes (six out of nine oligogenic families have both known and candidate genes). 18 out of 89 families, including both single locus and multilocus families, have variants in arthrogryposis-associated candidate genes. Three families were found to have CNVs that are thought to contribute to the arthrogryposis phenotype. Considering all families studied in both phase I⁸ and phase II, we achieved a molecular diagnostic rate of 73.5% (86/117) when considering both known and potential disease genes, and 58.1% (68/117) of families had a molecular diagnosis involving a known disease gene.

Of note, the rate of consanguinity, as measured by AOH, was significantly higher in the molecularly diagnosed individuals compared to undiagnosed cohort individuals (60/86 = 69.8% in diagnosed cohort versus 5/31 = 16.1% in the undiagnosed cohort, p < 0.0001 Fisher’s exact two-tailed test). However, we did not observe a significant difference in evidence for consanguinity in syndromic versus non-syndromic arthrogryposis in the diagnosed compared to undiagnosed individuals (30/86 = 34.9% in the diagnosed cohort versus 8/31 = 25.8% in the undiagnosed cohort, p = 0.3824 Fisher’s exact two-tailed test). In the current study, we propose five probably causative and ten possibly causative arthrogryposis-associated genes and four candidate DD-and-ID-associated genes contributing to the disease phenotype (Figure 1B). Potential multilocus pathogenic variation, i.e., the oligogenic model, was observed in 11 families in this phase II cohort, specifically in 19.0% (11/58) of individuals with a diagnosis. The overall potential oligogenic inheritance rate including both phase I and phase II studies is 22.1% (19/86) of diagnosed individuals (Figure 1C).

Known Arthrogryposis-Associated Genes

A total of 43 families have a pathogenic variant in a gene associated with either nonsyndromic (isolated) or syndromic arthrogryposis (Tables 1, 2, and S1, and Figures S1 and S2). The most common identified molecular diagnoses and implicated genes included CHRNG (MIM: 100730), associated with Escobar syndrome and lethal multiple pterygium syndrome (EVMPS [MIM: 265000] and LMPS [MIM: 253290], respectively), in 12 of 116 Turkish families (10.3%, excluding the individual of Arabic origin in phase I), and ECEL1 (MIM: 605896), associated with distal arthrogryposis type 5D (DA5D [MIM: 615065]) in six families. The calculated total AOH after we used BafCalculator on exome-generated variant data³¹ was on average 218.66 Mb for these 18 families, whereas the average calculated total AOH size in the entire Turkish cohort (∼700 exomes) is 91.38 Mb. Rare variants in KLHL7 (MIM: 611119), previously associated with cold-induced sweating syndrome (CISS3 [MIM: 617055]), were identified in four unrelated families with syndromic primarily distal arthrogryposis. The syndromic features were characterized by variable involvement of the genitourinary system, DD and ID, and congenital heart disease, each in at least two families; these features represent a potential expansion of the known disease phenotypes associated with KLHL7. Additional molecular diagnoses reported in more than one family involved MYH3 (MIM: 160720), associated with several forms of distal arthrogryposis (DA2A [MIM: 193700], DA2B [MIM: 601680], and DA8 [MIM: 178110]) in two families, and SPEG (MIM: 615950), linked to centronuclear myopathy 5 (CNM5 [MIM: 615959]). In total, rare variants in 45 different known genes were found within 43 families (including oligogenic families), and these findings reveal the extensive genetic heterogeneity in the arthrogryposis cohort. Additionally, we identified a second family with variants in MYBPC2 (MIM: 160793), first proposed as a candidate arthrogryposis-associated gene in the phase I study.

Probably Causative Arthrogryposis-Associated Genes

We found evidence for five candidate genes, RYR3 (MIM: 180903), MYOM2 (MIM: 603509), ERGIC1 (MIM: 617946), SPTBN4 (MIM: 606214), and ABCA7 (MIM: 605414), in which predicted deleterious variants are likely to be contributing to and probably causing the arthrogryposis phenotype; the variants likely to be pathogenic are present in at least two families, and additional families were identified either within our cohort, through GeneMatcher, or in recent publications (molecular findings in Tables 1, 2, and S1, and Figures S1 and S2; clinical findings in the Supplemental Text). For each of these genes, additional data, such as minor allele frequencies, evolutionary conservation, and CADD-phred scores of identified variants, that support their candidacy as arthrogryposis genes are provided (Tables 1, 2, and S1). These genes were not previously linked to any human disease in OMIM, or there has been only one reported individual, family, or variant; thus, we consider the variants within these genes to be probably causative for the arthrogryposis phenotype.

RYR3

RYR3 bi-allelic variants were found in three unrelated individuals (Table 1 and Figure 2): one was found as part of a potential multilocus mutational burden disease model (RYR3 + MYO18B [MIM: 607295]) (individual BAB7845), one was identified through GeneMatcher (individual PAED187), and one was found by assuming a single-gene-single-disease model (individual BAB8988). The first individual, BAB7845, is a 6-month-old female who was born to a first degree cousin marriage with 247.5 Mb of total AOH. The proband exome revealed a compound-heterozygous variant in a known gene, MYO18B (GenBank: NM_032608; c.[2879C>T]; [3397C>T]: p.[Ala960Val]; [Arg1133Trp]), and a homozygous variant in RYR3 (GenBank: NM_001243996; c.2486G>A [p.Arg829His]) (Figures 2A–2D). The c.2879C>T MYO18B variant and the RYR3 variant were each reported as homozygous in one individual in gnomAD. On the basis of the amino acid conservation and “likely damaging prediction scores” (Table S1) of the variants identified herein, we propose that all three variants are hypomorphic alleles, and each contributes to the arthrogryposis phenotype in this individual. Variants in MYO18B were recently shown to cause a neuromuscular disease spectrum ranging from nemaline myopathy with cardiomyopathy to Klippel-Feil anomaly with myopathy (KFS4 [MIM: 616549]),³⁸^,³⁹ and here we report the fourth family with MYO18B variants. Individual PAED187 has compound heterozygosity for a missense variant (GenBank: NM_001036.3; c.2000A>G [p.Asp667Gly]) and a variant affecting the splice donor (c.11164+1G>A) in RYR3 (Figures 2E and 2F). Individual BAB8988 was born to first degree cousin parents with 149.6 Mb of total AOH according to BafCalculator. Trio ES revealed a homozygous nonsynonymous change in RYR3 (GenBank: NM_001243996; c.8939G>T [p.Arg2980Leu]) (Figures 2G–2I). Recently, compound-heterozygous alleles in RYR3, c.[6208A>G]; [8939G>T]: p.[Met2070Val]; [Arg2980Leu], were reported in a 22-year-old female with myopathic facies, proximal weakness in all four limbs, mild scapular winging, and type 1 muscle fiber atrophy and predominance in muscle biopsy.⁴⁰ The c.8939G>T variant in the reported individual is the same variant observed in individual BAB8988.

The ryanodine receptors are intracellular Ca²⁺ release channels that play a key role in cell signaling via Ca²⁺. RYR1 (MIM: 180901) plays a role in the initial voltage-dependent Ca²⁺ release, and RYR3 functions during the prolonged Ca²⁺ release.⁴¹^,⁴² Further evidence that the pathogenicity of the variants in RYR3 probably contribute to the arthrogryposis phenotype comes from bioinformatics studies; Abath Neto et al. performed a computational data-mining study based on gene ontology (GO) terms, human phenotype ontology (HPO) terms, pathways, complexes, and protein motifs, and they found that RYR3 is highly ranked as one of the congenital myopathy genes.⁴³ Mutations in RYR1, a paralog of RYR3, were shown to cause several neuromuscular disorders including central core disease (CCD [MIM: 117000]), myopathies (MIM: 255320 and 117000), and the complex trait of susceptibility to malignant hyperthermia (MHS1 [MIM: 145600]), a sometimes lethal disease induced by exposure to certain anesthetics during surgical interventions; deleterious variants in RYR2 (MIM: 180902) were known to cause cardiac rhythm disorders (ARVD2 [MIM: 600996] and CPVT1 [MIM: 604772]), whereas no disease has been linked to RYR3. Taken together, we propose pathogenic variants in RYR3 are causing neuromuscular disease on the basis of the presence of deleterious variants in three unrelated families and functional evidence for its involvement in neuromuscular disease.

MYOM2

Two unrelated individuals carry variants in MYOM2 (Figure 3). Trio ES revealed a homozygous missense variant (GenBank: NM_003970; c.621C>G [p.Ser207Arg]) in Myomesin-2 (MYOM2) in individual BAB8905 (Figures 3A–C). The second individual, a fetus terminated at 20 weeks of gestation (found through GeneMatcher) (individual IN076), was found to have a homozygous nonsense variant and presumed null allele (GenBank: NM_003970; c.2797C>T [p.Gln933^∗]) in MYOM2 (Figures 3D–G). Because MYOM2 is specifically expressed in the heart and skeletal muscle, the cardiac and arthrogryposis findings can be potentially explained by loss of function (LoF) mutation of MYOM2. Further evidence for probable pathogenicity comes from functional studies that showed that MYOM2 interacts directly with dysferlin, which plays an essential role in sarcolemma repair; abnormalities of dysferlin cause a wide variety of myopathies called dysferlinopathies.⁴⁴

ABCA7

Bi-allelic ABCA7 variants were found in two unrelated families (Figure 4). In the first family, there were two affected siblings, individuals BAB6807 and BAB6808 (Figures 4A and4B). The younger female sibling was more severely affected with arthrogryposis, whereas the older male sibling, individual BAB6808, was observed to have DD and ID in addition to a neuromuscular phenotype. ES was performed on both affected siblings. Individual BAB6807 was found to have a novel homozygous stop-gain mutation (GenBank: NM_057166; c.619C>T [p.Gln207^∗]) in the known COL6A3 gene (MIM: 120250), but the affected brother and healthy parents were heterozygous for this variant. Given the relative phenotypic similarity between the two affected siblings (the female is more severely affected, and the brother had additional DD and ID phenotype), we searched for variants shared by the two affected siblings and found a homozygous missense change (GenBank: NM_019112; c.5092C>T [p.Arg1698Trp]) in ATP-binding cassette, subfamily A, member 7 (ABCA7). Individual BAB6808, who has an additional DD and ID phenotype, was found to carry a deleterious homozygous variant (GenBank: NM_015339; c.775A>C [p.Asn259His]) in ADNP (MIM: 611386), in which variants are known to cause DD and ID (HVDAS [MIM: 615873]).⁴⁵ The homozygous COL6A3 variant in individual BAB6807 probably explains the more severe phenotype in this individual. In the second family, individual BAB10708 is found to have variants in three different genes: (1) compound-heterozygous deleterious variants in ABCA7 (GenBank: NM_019112; c.[3076C>T]; [4045C>T]: p.[Arg1026Cys]; [Arg1349Trp]), (2) a de novo heterozygous variant in SPEG (MIM: 615950; GenBank: NM_005876; c.9575C>A [p.Thr3192Asn]), in which bi-allelic variants are known to cause centronuclear myopathy 5 (CNM5 [MIM: 615959]), and (3) a de novo, heterozygous, non-frameshift insertion in TPM2 (MIM: 190990; GenBank: NM_003289; c.620_631dup [p.Gln210_Ala211insValGluAlaGln]), in which mono-allelic variants are known to cause a broad spectrum of neuromuscular disorders including distal arthrogryposis multiplex congenita types 1 and 2B (DA1A [MIM: 108120] and DA2B [601680]) (Figures 4C and 4D). Heterozygous variants in ABCA7 have been linked to Alzheimer susceptibility (AD9 [MIM: 608907]); however, bi-allelic variants associated with recessive trait variants have not been reported in any diseases previously. ATP-binding cassette (ABC) proteins transport various molecules across extra- and intra-cellular membranes. Heterozygous variants in ABCA1 (MIM: 600046) are associated with type 2 HDL deficiency and protection against coronary artery disease in familial hypercholesterolemia (MIM: 604091 and 143890, respectively), and homozygous variants in ABCA1 are known to cause Tangier disease (TGD [MIM: 205400]), which has clinical features of distal muscle atrophy and peripheral neuropathy. As per the STRING database, there is distant interaction between ABCA1 and ABCA7.

ERGIC1

Trio ES of individual BAB8802 showed a homozygous change (GenBank: NM_001031711; c.782G>A [p.Gly261Asp]) in ERGIC1 (Figure 5). This gene was reported in a large family affected with arthrogryposis multiplex congenita; in this family, 40 affected individuals were found to have c.293T>A (p.Val98Glu), cosegregating with the AR disease trait.⁴⁶ However, to date, no additional families or variants in ERGIC1 have been associated with arthrogryposis. ERGIC (ER-Golgi intermediate compartment) family proteins are transmembrane proteins that are localized to the ER-Golgi intermediate compartment, but the function of ERGIC1 remains elusive.⁴⁷ The observation of a second family with rare variation in ERGIC1 in association with arthrogryposis strengthens its relevance to the arthrogryposis phenotype.

SPTBN4

Trio ES revealed a homozygous GenBank: NM_020971; c.6433G>A (p.Ala2145Thr) variant in SPTBN4 in individual BAB8691, who presented with distal contractures, hearing loss, and DD and ID (Figure 6). Recently, Knierim et al. reported a homozygous nonsense variant GenBank: NP_066022.2; p.Gln533^∗ in a male with myopathy, distal arthrogryposis, scoliosis, hearing loss, severe DD and ID, increased cerebrospinal fluid (CSF) spaces on brain MRI, and peripheral neuropathy.⁴⁸ An immunoblot and immunostaining showed the absence of SPTBN4, and a knock-out mouse model showed findings, including muscle weakness, decreased locomotion, quivering, ataxia, and hearing loss, that are similar to those in humans. Between these two individuals there is significant phenotypic overlap, including severe DD and ID, grossly normal brain MRI, hearing loss, distal contractures, and failure to thrive. Another homozygous variant (GenBank: NM_020971.2; c.3394del [p.His1132Thrfs^∗39]) of SPTBN4 was reported by Anazi et al. in an individual who had no reported arthrogryposis but did have clinical features of global developmental delay, hypotonia, dysphasia, recurrent respiratory infections, blue sclerae, hyporeflexia, and failure to thrive.⁴⁹ Although the authors did not report any electromyography or nerve conduction studies, the clinical observation of hyporeflexia and hypotonia might be features of peripheral neuropathy. SPTBN4 encodes a nonerythrocytic member of the beta-spectrin protein family that is mainly expressed in the brain, peripheral nervous system, pancreas, and skeletal muscle. Mutation of different domains might explain why each person presented with more central nervous system than neuromuscular features. Our individual has both neuromuscular and central nervous system findings and is the second individual now demonstrated to have arthrogryposis in association with a rare variant in SPTBN4; this supports that SPTBN4 is associated with both DD and ID and with the arthrogryposis phenotype.

Possibly Causative Arthrogryposis-Associated Genes

We identified ten candidate arthrogryposis-associated genes (CACUL1, DRG1 [MIM: 603952], FAT1 [MIM: 600976], FGFRL1 [MIM: 605830], FLII [MIM: 600362], MID1IP1 [MIM: 300961], MYOM3 [MIM: 616832], NR2C1 [MIM: 601529], PRDM2 [MIM: 601196], and TMEM214 [MIM: 615301]) and four candidate DD-and-ID-associated genes (MED27 [MIM: 605044], TAF9B [MIM: 300754], TANC1 [MIM: 611397], and TNRC6C [MIM: 610741]) (Tables 1, 2, and S1, Figures S1–S4, and the Supplemental Text). Rare variants in each gene were identified in a single family, leading to their classification as candidate disease genes for which additional evidence is required before they are established as disease-associated genes. Evidence supporting plausible pathogenicity of these variant alleles includes amino acid conservation among other species, the predicted probably damaging effect of the variant made on the basis of bioinformatics tools, and interactome studies. Only two of these genes are highlighted here, and clinical and molecular results of all candidate genes are detailed in the oligogenic inheritance and blended phenotype section in Tables 1, 2, and S1, and the Supplemental Text.

Trio ES in individual BAB9729 revealed a homozygous 2 bp deletion (GenBank: NM_153810; c.910_911del [p.Leu304Ilefs^∗3]) in CACUL1, encoding a cell-cycle-associated protein capable of promoting cell proliferation through the activation of CDK2 at the G1/S phase transition (Figure S5). Interacting genes, NEDD8 (MIM: 603171) and FBXW7 (MIM: 606278), have a role in muscle function. Lange et al. showed that obscurin, a binding partner of titin, contains a non-modular C terminus that interacts with muscle specific isoforms of Ankyrin-1 (small Ankyrin-1.5; sAnk1.5).⁵⁰ sAnk1.5 localization and levels of sAnk1.5 expression are downregulated in obscurin knockout tissues, probably through ubiquitylation and/or neddylation of sAnk1.5.⁵⁰ Another interacting gene, Fbxw7b, negatively regulates differentiation, proliferation, and migration of myoblasts and satellite cells on muscle fibers.⁵¹ The same group additionally showed that overexpression of Fbxw7b induces the expression of myogenin and major atrogene markers (atrogin-1 and MuRF-1) and eventually reduces myoblast differentiation.⁵²

Trio ES in individual BAB9309 revealed a de novo frameshift deletion (GenBank: NM_012231; c.4283_4295del [p.Leu1428Glnfs^∗15]) in PR domain-containing protein 2 (PRDM2 [MIM: 601196]). The fraction of variant reads (12/150, 8.0%) suggested somatic mosaicism, an experimental conclusion that was supported by an independent orthogonal experimental approach that used ddPCR (Figure 7A). PRDM2 is a member of a nuclear histone and protein methyltransferase superfamily and plays a major role in the regulation of myogenesis.⁵³^,⁵⁴

Molecular Studies in Individual BAB9309 and Copy Number Variant Families

(A) Droplet digital PCR (ddPCR) results for the family; the results show 8% mosaicism for the *PRDM2* variant in the proband, and this finding is consistent with the exome mosaicism rate (8%) and no deletion in the healthy parents.

(B) Results for aCGH analyses in three individuals are shown. Each dot indicates oligonucleotide probes: black dots represent a normal copy number, red dots represent a copy number gain, and green dots represent copy number losses as compared with a gender-matched control. The proband’s designated ID (BAB#s), the chromosomal location, and the approximate sizes of the copy number variants (CNVs) are written above each chromosome ideogram, and the chromosome number is written on the left side of ideogram. Red dashed lines determine the chromosomal region investigated by aCGH. Abbreviations are as follows: Chr = chromosome, Del = deletion, Dup = duplication, Mb = megabase, NTC = no template control, and Ter = terminal.

CNVs in Arthrogryposis

In three individuals, we found CNVs that were probably contributing to the arthrogryposis phenotype (Figure 7B and Table S2). We searched the genomic intervals defined by these CNV regions in these three individuals for possible candidate dosage-sensitive genes; however, we could not readily identify any specific potentially dosage-sensitive genes. We also examined the DECIPHER database for additional individuals with CNVs involving the identified regions and found a few individuals with overlapping features in two of these three individuals (individuals BAB7128 and BAB9312). However, the overlapping region of CNV remained substantial and had multiple annotated genes within its boundaries, precluding identification of a single, potentially etiologic gene. Individual BAB7128 was a 20-month-old male with DD and ID, hearing loss, bilateral hip dislocation, and pes equinovarus (PEV) deformity. The CNV detection tool (XHMM) showed a 6.7 Mb de novo deletion that includes 54 genes in the deletion region on chromosome 5 (hg19.g.chr5: 129673070–136365890). A DECIPHER database search revealed four individuals (DECIPHER ID#s 785, 2224, 256078, and 260667) with scoliosis, distal arthrogryposis, camptodactyly, and/or PEV. The smallest overlapping region of ∼2 Mb involving 11 genes (hg19.g.chr5: 129673070–131550089) was found in DECIPHER individual 785. This individual has camptodactyly and PEV, which partially explain our subject’s clinical features. Individual BAB8145 was a 3.5-year-old female with DD and ID, contractures in fingers and toes, and PEV. She was found to have two de novo deletions: a 9.43Mb deletion in chromosome 10 (hg19.g.chr10: 58374373–67805420) involving 29 genes and a 0.7 Mb de novo deletion in a non-coding region on chromosome 11 (hg19.g.chr11: 90798107–91499657); this was followed by an ∼1 Mb normal copy number and 7.58 Mb de novo deletion on chromosome 11 (hg19.g.chr11: 92950818–100534639) involving 39 genes in the region, and this was detected by karyotyping. Individual BAB9312 was a 7-year-old female who presented with DD and ID, hearing loss, and PEV. She was found to have a complex genomic rearrangement (CGR)⁵⁵ involving chromosome 18: a 21.8 Mb duplication (hg19.g.chr18: 21901302–43716565) and an 11.6 Mb deletion (hg19.g.chr18: 66350129–78002264) (Figure 7B). Interestingly, there were three DECIPHER individuals (# 251072, 269015, and 319532) with overlapping clinical features that included DD and ID, hearing loss, PEV, and additional clinical findings, but the overlapping region was ∼10 Mb in all three individuals (hg19.g.chr18: 67223975–77120273).

Families Potentially Affected by Multilocus Pathogenic Variation

Although many of the early cohort-based studies describing multiple molecular diagnoses involve known disease genes, there have been more recent reports of multiple molecular diagnoses for which one identified gene is a candidate gene proposed to explain the observed, expanded phenotype associated with a well-studied, known disease-associated gene.¹⁰^,¹⁴^,³¹^,⁵⁶ Given the rarity of the conditions studied, it is unlikely that two or more unrelated families will share the same combination of multiple molecular diagnoses. However, apparent phenotypic expansion in the setting of a single molecular diagnosis can, in some individuals, suggest a second, or even third, molecular diagnosis explaining the observed, expanded phenotypic features.³¹ Considering this possibility in the present cohort, we further explored 11 families for which there was evidence of multilocus pathogenic variation potentially contributing to the phenotype, i.e., mutational burden contributing to a blended phenotype (Tables 2 and S1, Figures S1 and S2, and the Supplemental Text).¹⁰ Six out of 11 families have three genes with variants that are likely to be pathogenic and that we propose have an impact on the disease phenotype. We highlight one example from “known-known” and one example from “known-candidate” gene patterns, and the remainder of individuals with proposed multilocus pathogenic variation are detailed in Tables 2 and S1, Figure S2, and the Supplemental Text.

Trio ES in individual BAB8600 (index) and her more severely affected mother, individual BAB8601, revealed novel variants in two known genes, FBN2 (MIM: 612570) and COL6A3 (Figure S6). The variant in FBN2 was a de novo missense change (GenBank: NM_001999; c.4094G>C [p.Cys1365Ser]) in the mother that was transmitted to the less severely affected child. The COL6A3 variant (GenBank: NM_057167; c.367G>A [p.Val123Met]) was a homozygous missense change in the mother and heterozygous in the affected child and maternal grandparents. Mutations in FBN2 are known to cause autosomal-dominant contractural arachnodactyly (DA9 [MIM: 121050]), whereas deleterious variants in COL6A3 cause several neuromuscular phenotypes including dominantly and recessively inherited Bethlem myopathy 1 (BTHLM1 [MIM: 158810]). Additional features in the mother can potentially be parsimoniously explained by homozygosity for the identified variant in COL6A3.

Individual BAB8397 underwent trio ES, which showed a reported, homozygous splice-site variant (GenBank: NM_001271208; c.19101+5G>A) in NEB (MIM: 161650) and a hemizygous, i.e., X-linked in a male proband, nonsynonymous variant (GenBank: NM_001098791; c.297C>G [p.Asn99Lys]) in MID1IP1 (Figure S7). The NEB variant identified in the proband was previously reported in a compound-heterozygous state with a nonsense variant (p.Tyr1858^∗) in an arthrogryposis-affected individual who died during the neonatal period.⁵⁷ The more severe phenotype in that individual could be explained by loss of function of the second allele. The second gene, MID1IP1, was not linked to any human disease previously. However, there are studies showing that MID1IP1 probably plays a role in myogenesis.⁵⁸^,⁵⁹ Casey et al. showed that Mid1ip1 expression is increased in the skeletal muscle of rats with peroxisome proliferator-activated receptors (PPAR)-induced myopathy.⁵⁸ Additionally, Bower et al. showed upregulation of Mid1ip1 both with feeding and in vitro myogenesis in salmon fish.⁵⁹ The study further showed that Mid1ip1 is highly expressed in fast and slow twitch muscle fibers compared to other tissues in the body. Although the function of MID1IP1 is not fully delineated, taken together, these data provide evidence that the MID1IP1 variant is likely to be contributing to the myopathy and contracture phenotype in our study individual.

The median total AOH size (individual locus AOH regions ≥3 Mb) calculated from exome data with BafCalculator in the probands with arthrogryposis and without any evidence for multilocus pathogenic variation (n = 97) is significantly higher (89.7 Mb) than the median total AOH size in the non-Turkish probands present in the Baylor-CMG database (n = 2,340) (23.5 Mb) (Mann-Whitney U test, p value = 7.35 × 10⁻¹⁷). Intriguingly, the probands that were studied in this arthrogryposis cohort and had dual molecular diagnoses (n = 19) have a larger median total AOH size (159.3 Mb) than the median total AOH size of the probands without any dual molecular diagnosis (n = 97; 89.7 Mb) (Mann-Whitney U test, p value = 0.02).

Discussion

We investigated the underlying molecular etiology of a large cohort (totaling 117 families including the phase I cohort) of individuals with arthrogryposis, either as an isolated clinical entity or as part of a syndrome, by using genome-wide assays. The current phase II cohort consists of 91 families, including two families identified through GeneMatcher, and 20 families who remained undiagnosed during the phase I study: ten out of 20 families who remained undiagnosed during phase I underwent reanalysis, and we expanded the sequencing to additional family members (e.g., index ES to trio or quad ES) in the remaining ten families. Overall, the molecular diagnostic rate from the combined phase I and II families was 73.5% (86 out of 117) when including both known and candidate genes, and 58.1% (68 out of 117) when considering molecular diagnoses involving only known genes.

Some experimental analysis enhancements that were implemented in our phase II approach and that potentially contributed to the increase in the molecular diagnostic yield in the second cohort (65.1% in phase II versus 58.3% in phase I) are expanding to trio ES and reanalyzing with additional bioinformatics tools the individuals from phase I who had unsolved molecular diagnoses. Multilocus pathogenic variation, consistent with a mutational burden or a potential oligogenic inheritance model, was observed in 19.0% (11/58) of the unrelated individuals with a molecular diagnosis in the present (phase II) cohort and 22.1% (19/86) of all 86 arthrogryposis-affected individuals with a molecular diagnosis reported here and in our previous [Phase I⁸ + II] study. Although AOH is indeed predicted to increase the frequency of homozygous variants in this cohort, identified multiple molecular diagnoses involved at least one known disease-associated locus in each individual and included known pathogenic or premature truncating variants at six loci, and additional evidence for the pathogenicity of identified variants is provided (Table S1 and Figure S2). Parents who are carriers for multilocus variation are notably unaffected, and four families with intrafamilial phenotypic variation (families HOU2523, HOU2620, HOU2791, and HOU3125) provide an opportunity to further dissect the relationship between observed phenotypes and identified genotypes.

Our phase II study additionally contributed to the classification of five genes (MYOM2, RYR3, ERGIC1, SPTBN4, and ABCA7), in which variation is probably causative of the arthrogryposis phenotype because they have now been identified in more than one family with the same phenotype.

We previously studied human disease-associated genes by using the universality of biology and the bidirectional synergism between fly and human genetics; this showed that essential fly genes with multiple human paralogs are 8-fold more likely to be disease-causing genes.⁶⁰ We applied this approach to human paralogs for our proposed candidate genes in the arthrogryposis cohort and found that 14 of 19 have a fly ortholog, and 8 of 14 genes (including DD-and-ID-associated genes) have two or more human paralogs (Table S3).

Reanalysis of Exome Data and Expansion to Include Studies of Additional Family Members

We previously showed in a pilot study (N = 74 families) that reanalysis in the research setting could potentially solve the previously unsolved clinical exomes for about half of affected individuals.²⁶ Effective experimental approaches for improving molecular diagnostic “solved rates” included: expanding singleton ES to additional family members (trio ES or other affected family member[s]) and applying additional, in-house-developed bioinformatics tools to detect indels, CNVs, and de novo variants with more relaxed analysis parameters. In the phase II study, we also expanded singleton ES to trio ES in ten previously studied families to uncover the genetic etiology of arthrogryposis and evaluate the diagnostic value of trio ES over singleton ES. Four out of ten families (40%) were provided with a molecular diagnosis upon expansion to trio ES and the application of bioinformatics tools to identify de novo and compound heterozygous variants and CNVs.²⁶ For the remaining ten families for whom parental samples were not available, reanalysis revealed variants that can potentially explain the molecular etiology of the observed phenotypes in five families. The overall diagnostic rate of exome reanalysis, including expansion to trio ES, in this cohort is 45% (9/20), which is consistent with our previous findings of the diagnostic utility of reanalysis.²⁶ Crucial experimental approaches for a reanalysis cohort are detailed in Table S4.

Phenotypic Expansion

In two personal genomes from unrelated individuals, we found variants in genes previously associated with conditions that do not include arthrogryposis as a phenotype; we now propose an expansion of the known phenotypes associated with these genes. Individual BAB7308 was found to have a de novo, heterozygous SYT2 (MIM: 600104) variant (GenBank: NM_177402; c.1081G>C [p.Asp361His], Figure S8), and details of this individual are described in Tables 1 and S1 and the Supplemental Text. The second individual, BAB8356, had proband ES, which revealed a homozygous change (GenBank: NM_005245; c.6026A>G [p.Asn2009Ser]) in FAT tumor-suppressor homolog 1 - Drosophila (FAT1) (Figure S9). Clinical details of this gene are described in the Supplemental Text. Bi-allelic variants of FAT1 were shown to cause glomerulotubular nephropathy.⁶¹ Interestingly, two recent studies showed that FAT1 expression has a role in the pathogenesis of fascioscapulohumeral dystrophy (FSHD1 [MIM: 158900]).⁶²^,⁶³ Two additional studies showed heterozygous rare variants of FAT1 in individuals with FSHD.⁶⁴^,⁶⁵ FAT1 is a member of protocadherin and has a role in smooth muscle cell motility, actin accumulation, cell polarity, migrating muscle precursors, and kidney development.⁶⁶^,⁶⁷^,⁶⁸^,⁶⁹ We here propose another bi-allelic variant in this gene with a phenotype of arthrogryposis. Interestingly, there are increasing examples of Mendelian disease-gene discoveries for which bi-allelic variation associated with a recessively inherited trait is identified in a gene previously or simultaneously described in association with a dominant trait conferred by mono-allelic variation. MAB21L2 (MIM: 604357), associated with dominant and recessive forms of microphthalmia/coloboma and skeletal dysplasia syndrome (MCSKS [MIM: 615877]), and ATAD3A (MIM: 612316), associated with autosomal-dominant or recessive Harel-Yoon syndrome (HAYOS [MIM: 617183]), are examples that illustrate both de novo and homozygous variants, and they lead to dominantly and recessively inherited conditions, respectively, that are associated with a single locus,¹⁷^,¹⁸ as is now described for MFN2 (MIM: 608507), TGFB3 (MIM: 190230), CIT (MIM: 605629), SPEG, ADNP, and FAT1 in the present study.

Rare-Variant Multilocus Pathogenic Variation

In the combined phase I + phase II arthrogryposis cohort, we identified 19 families with rare variation found at more than one locus and contributing to the observed phenotype; there were 16 individuals with an AR + AR (14 individuals) or AR + AR + AR (two individuals) multilocus disease-trait pattern, representing 84.2% (16/19) of individuals with multilocus variation (Figure 1C). Of the 37 identified AR molecular loci in all 19 individuals with multiple molecular diagnoses, 31 (31/37, 83.7%) loci demonstrated homozygosity for rare variants that are private to the studied clan (the Turkish population frequency can be found in Table S1). This is in striking contrast to an analysis of multilocus variation in a cohort of North American referrals to a diagnostic laboratory; for this cohort there were 11 individuals with an AR + AR (nine individuals) or AR + AR + AR (two individuals) disease pattern, representing 10.9% (11/101) of multilocus variation individuals studied (Figure 1C).¹⁰ The relative frequency of multiple molecular diagnoses was higher (22%, 19/86) in the arthrogryposis cohort compared to a relatively outbred population (4.9%, 101/2076), and this was driven by a high rate of AR + AR diagnoses (84.2% 16/19) in the arthrogryposis cohort compared to the North American referral population (10.9%, 11/101, two-tailed p < 0.0001, Fisher’s exact test). Further evidence for IBD-driven, genome-wide accumulation of deleterious variants is shown in large cohort population studies as well.⁷⁰

In summary, we provide evidence for multiple candidate genes and further evidence for multilocus pathogenic variation that contributes to the complex trait of arthrogryposis. Moreover, we provide evidence further extending the clan genomics hypothesis⁷¹ and emboldening the rare-variant multilocus-pathogenic-variation model for a complex trait. This study also highlights: (1) the value of reanalysis and exome variant analyses on additional family members and its ability to conclude a molecular diagnosis in this era of rapid gene discovery, (2) oligogenic inheritance and blended phenotypes can be responsible for up to ∼22% of the arthrogryposis diagnoses in individuals, and the majority of this can be driven by population substructure and IBD, (3) both mono-allelic and bi-allelic variants in a single gene can contribute to human disease, causing either similar or different phenotypes, (4) paralogs of known disease-associated genes can be responsible for disease traits, and (5) genetic models for complex traits can be built from underlying Mendelian principles and explored experimentally.

Declaration of Interests

Baylor College of Medicine (BCM) and Miraca Holdings have formed a joint venture with shared ownership and governance of the Baylor Genetics (BG), which performs clinical microarray analysis and clinical exome sequencing. J.R.L. serves on the scientific advisory board of the BG. J.R.L. has stock ownership in 23andMe, is a paid consultant for Regeneron Pharmaceuticals, and is a co-inventor on multiple United States and European patents related to molecular diagnostics for inherited neuropathies, eye diseases, and bacterial genomic fingerprinting. The other authors declare no conflicts of interest.

Acknowledgments

The authors thank the families and their health care teams for participating in this project.

This work was supported in part by R35 NS105078 and MDA#512848 to J.R.L. and a jointly funded National Human Genome Research Institute (NHGRI) and National Heart, Lung, and Blood Institute (NHLBI) grant to the Baylor-Hopkins Center for Mendelian Genomics (UM1 HG006542). J.E.P. is supported by NHGRI K08 HG008986. D.P. is supported by the National Institutes of Health - Brain Disorders and Development Training Grant (T32 NS043124-17) and a Clinical Research Training Scholarship in Neuromuscular Disease partnered by the American Brain Foundation (ABF) and Muscle Study Group (MSG). This study is partly funded by Tubitak project number 217S675, Turkey to N.E. and B.T.. This study is partly funded by Indian Council of Medical Research, New Delhi, India with File no.: No.5/13/58/2015/NCD-III to A.S.

Published: June 20, 2019

Footnotes

Supplemental Data can be found online at https://doi.org/10.1016/j.ajhg.2019.05.015.

Accession Numbers

The dbGaP accession number for all exome sequences reported in this paper and for which informed consent for data sharing in controlled-access databases has been provided is dbGaP: phs000711.v5.p1.

Web Resources

1000 Genomes, http://www.1000genomes.org
ARIC Database, https://sites.cscc.unc.edu/aric/
BaFCalculator Browser, https://github.com/BCM-Lupskilab/BafCalculator
Cell Culture Repositories, https://ccr.coriell.org
CoNIFER, http://conifer.sourceforge.net
CoNVex, ftp://ftp.sanger.ac.uk/pub/users/pv1/CoNVex/Docs/CoNVex.pdf
DNM-Finder Browser, https://github.com/BCM-Lupskilab/DNM-Finder
ExAC Browser, http://exac.broadinstitute.org/
GeneMatcher Browser, https://genematcher.org/
gnomAD Browser, https://gnomad.broadinstitute.org/
Genotype-Tissue Expression - GTEx Portal, https://gtexportal.org/home/
HmzDelFinder Browser, https://github.com/BCM-Lupskilab/HMZDelFinder
Human-Fly Ortholog Comparison Browser, https://www.flyrnai.org/cgi-bin/DRSC_orthologs.pl
IGV, https://www.broadinstitute.org/igv/
Online Mendelian Inheritance in Man, https://www.omim.org/
NHLBI GO Exome Sequencing Project, https://evs.gs.washington.edu/EVS
STRING 10.5, https://string-db.org/
UCSC Genome Browser, https://genome.ucsc.edu
UniProt, https://www.uniprot.org/
DECIPHER, https://decipher.sanger.ac.uk/
XHMM, http://atgu.mgh.harvard.edu/xhmm/index.shtml

Supplemental Data

Document S1. Supplemental Text, Figures S1–S9, and Tables S2 and S4.

mmc1.pdf^{(6.5MB, pdf)}

Table S1. Molecular, Bioinformatic, and Clinical Details of the Entire Arthrogryposis Cohort.

mmc2.xlsx^{(33.1KB, xlsx)}

Table S3. Paralog/Ortholog Predictions for the Novel and Candidate Genes.

mmc3.xlsx^{(12.8KB, xlsx)}

Document S2. Article plus Supplemental Data.

mmc4.pdf^{(8.5MB, pdf)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Document S1. Supplemental Text, Figures S1–S9, and Tables S2 and S4.

mmc1.pdf^{(6.5MB, pdf)}

Table S1. Molecular, Bioinformatic, and Clinical Details of the Entire Arthrogryposis Cohort.

mmc2.xlsx^{(33.1KB, xlsx)}

Table S3. Paralog/Ortholog Predictions for the Novel and Candidate Genes.

mmc3.xlsx^{(12.8KB, xlsx)}

Document S2. Article plus Supplemental Data.

mmc4.pdf^{(8.5MB, pdf)}

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PERMALINK

The Genomics of Arthrogryposis, a Complex Trait: Candidate Genes and Further Evidence for Oligogenic Inheritance

Davut Pehlivan

Yavuz Bayram

Nilay Gunes

Zeynep Coban Akdemir

Anju Shukla

Tatjana Bierhals

Burcu Tabakci

Yavuz Sahin

Alper Gezdirici

Jawid M Fatih

Elif Yilmaz Gulec

Gozde Yesil

Jaya Punetha

Zeynep Ocak

Christopher M Grochowski

Ender Karaca

Hatice Mutlu Albayrak

Periyasamy Radhakrishnan

Haktan Bagis Erdem

Ibrahim Sahin

Timur Yildirim

Ilhan A Bayhan

Aysegul Bursali

Muhsin Elmas

Zafer Yuksel

Ozturk Ozdemir

Fatma Silan

Onur Yildiz

Osman Yesilbas

Sedat Isikay

Burhan Balta

Shen Gu

Shalini N Jhangiani

Harsha Doddapaneni

Jianhong Hu

Donna M Muzny

Eric Boerwinkle

Richard A Gibbs

Konstantinos Tsiakas

Maja Hempel

Katta Mohan Girisha

Davut Gul

Jennifer E Posey

Nursel H Elcioglu

Beyhan Tuysuz

James R Lupski

Abstract

Introduction

Material and Methods

Study Participants

Figure 1.

Exome Sequencing

Sanger Sequencing

Chromosomal Microarray Analysis for Genome-Wide CNV Detection

Droplet Digital PCR Mosaicism Analysis

Human and Fruit Fly Cross-Database Mining for Candidate Gene Analyses

Results

Exome Sequencing and Family-Based Genomics in Arthrogryposis

Table 1.

Table 2.

Known Arthrogryposis-Associated Genes

Probably Causative Arthrogryposis-Associated Genes

RYR3

Figure 2.

MYOM2

Figure 3.

ABCA7

Figure 4.

ERGIC1

Figure 5.

SPTBN4

Figure 6.

Possibly Causative Arthrogryposis-Associated Genes

Figure 7.

CNVs in Arthrogryposis

Families Potentially Affected by Multilocus Pathogenic Variation

Discussion

Reanalysis of Exome Data and Expansion to Include Studies of Additional Family Members