Literature DB >> 31695380

Rare compound heterozygous missense SPATA7 variations and risk of schizophrenia; whole-exome sequencing in a consanguineous family with affected siblings, follow-up sequencing and a case-control study.

Hirofumi Igeta1, Yuichiro Watanabe1, Ryo Morikawa1, Masashi Ikeda2, Ikuo Otsuka3, Satoshi Hoya1, Masataka Koizumi1, Jun Egawa1, Akitoyo Hishimoto3, Nakao Iwata2, Toshiyuki Someya1.   

Abstract

PURPOSE: Whole-exome sequencing (WES) of multiplex families is a promising strategy for identifying causative variations for common diseases. To identify rare recessive risk variations for schizophrenia, we performed a WES study in a consanguineous family with affected siblings. We then performed follow-up sequencing of SPATA7 in schizophrenia-affected families. In addition, we performed a case-control study to investigate association between SPATA7 variations and schizophrenia. PATIENTS AND METHODS: WES was performed on two affected siblings and their unaffected parents, who were second cousins, of a multiplex schizophrenia family. Subsequently, we sequenced the coding region of SPATA7, a potential risk gene identified by the WES analysis, in 142 affected offspring from 137 families for whom parental DNA samples were available. We further tested rare recessive SPATA7 variations, identified by WES and sequencing, for associations with schizophrenia in 2,756 patients and 2,646 controls.
RESULTS: Our WES analysis identified rare compound heterozygous missense SPATA7 variations, p.Asp134Gly and p.Ile332Thr, in both affected siblings. Sequencing SPATA7 coding regions from 137 families identified no rare recessive variations in affected offspring. In the case-control study, we did not detect the rare compound heterozygous SPATA7 missense variations in patients or controls.
CONCLUSION: Our data does not support the role of the rare compound heterozygous SPATA7 missense variations p.Asp134Gly and p.Ile332Thr in conferring a substantial risk of schizophrenia.
© 2019 Igeta et al.

Entities:  

Keywords:  Japanese; multiplex schizophrenia family; next-generation sequencing; recessive variations

Year:  2019        PMID: 31695380      PMCID: PMC6707433          DOI: 10.2147/NDT.S218773

Source DB:  PubMed          Journal:  Neuropsychiatr Dis Treat        ISSN: 1176-6328            Impact factor:   2.570


Introduction

Schizophrenia is a complex disorder with heritability of approximately 80%.1 Understanding the genetic architecture of schizophrenia has progressed steadily.2–4 Genome-wide association studies (GWASs) have discovered common loci associated with schizophrenia.5–7 Intriguingly, association of the major histocompatibility complex locus with schizophrenia involves structurally distinct alleles of C4 that affect the expression of C4A and C4B in the brain.8 However, the heritability of schizophrenia is not fully explained by common variations, suggesting that rare variations also contribute to schizophrenia liability.9 Indeed, rare copy number variations are associated with schizophrenia.10–12 Whole-exome sequencing (WES) studies have demonstrated that rare sequence variations play a substantial role in the genetic etiology of schizophrenia.13–15 Of note, SETD1A was identified as a risk gene for schizophrenia with a large effect.16,17 WES and whole-genome sequencing (WGS) of multiplex families is a promising strategy for identifying causative variations for common diseases.18,19 The number of WES and WGS studies that have examined multiplex schizophrenia families is still limited, but they have detected highly penetrant variations in GRM5,20 UNC13B,21 SHANK2 and SMARCA1,22 RELN,23 TAAR1,24 RBM12,25 CSPG4,26 PTPRA,27 ITGΒ4,28 TIMP2,29 and TENM4.30 Two recent studies suggested that a combined strategy including identity-by-descent (IBD) mapping and WES may be useful in identifying rare risk variations for schizophrenia inherited from common ancestors31,32 Harold et al performed IBD mapping using Irish schizophrenia GWAS data and identified potential risk haplotypes.31 Subsequently, they conducted WES and identified PCNT p.Gly1452Arg as a potential risk haplotype, although this missense variation was not associated with schizophrenia in replication samples. In the other study, Salvoro et al performed IBD mapping and WES in multiplex families with schizophrenia, bipolar disorder, and schizoaffective disorder from Chioggia, Italy.32 Among potential risk haplotypes, they found significant enrichment of non-synonymous variations of genes involved in extracellular matrix biology and axon guidance processes. Here, we performed a three-stage study to identify rare recessive variations that play a substantial role in conferring schizophrenia risk. First, we undertook a WES study in a multiplex family with two siblings with schizophrenia whose unaffected parents were second cousins. Second, we sequenced the coding region of SPATA7, a potential risk gene identified by the WES study, in 142 affected offspring from 137 families for whom parental DNA samples were available. Third, we conducted a case-control study to examine association of rare recessive SPATA7 variations, identified by WES and sequencing, with schizophrenia in 2,756 patients and 2,646 controls.

Materials and methods

Participants

This study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of each participating institute. All participants gave written informed consent, and all were of Japanese descent. We included two siblings with schizophrenia (#4 and #5) and their unaffected parents (#1 and #2) in a WES study (Figure 1). In this family, the female proband (#4) and her younger sister (#5) were diagnosed with schizophrenia. Their older sister (#3) was suspected of having postpartum depression. Their younger brother (#6) died one day after a Caesarean section delivery. Their younger brother (#7) was not diagnosed with any psychiatric disorder. Their unaffected father (#1) and mother (#2) were second cousins. Diagnoses of each family member were made using Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) criteria, as previously described.33
Figure 1

Pedigree of a consanguineous family with two schizophrenia siblings. The female proband (#4), indicated by an arrow, and her younger sister (#5) were diagnosed with schizophrenia, indicated by black shaded symbols. Their older sister (#3) was suspected of having postpartum depression, indicated by a gray shaded symbol. Their parents (#1 and #2) and younger brothers (#6 and #7) were not diagnosed with any psychiatric disorder, indicated by unshaded symbols. Their younger brother (#6) died one day after a Caesarean section delivery, indicated by a diagonal line through the symbol. Their parents (#1 and #2) were second cousins, indicated by a double line between individuals. Squares and circles represent males and females, respectively. Crosses represent individuals from whom genomic DNA samples were available.

Pedigree of a consanguineous family with two schizophrenia siblings. The female proband (#4), indicated by an arrow, and her younger sister (#5) were diagnosed with schizophrenia, indicated by black shaded symbols. Their older sister (#3) was suspected of having postpartum depression, indicated by a gray shaded symbol. Their parents (#1 and #2) and younger brothers (#6 and #7) were not diagnosed with any psychiatric disorder, indicated by unshaded symbols. Their younger brother (#6) died one day after a Caesarean section delivery, indicated by a diagonal line through the symbol. Their parents (#1 and #2) were second cousins, indicated by a double line between individuals. Squares and circles represent males and females, respectively. Crosses represent individuals from whom genomic DNA samples were available. For sequencing SPATA7 coding regions, we included 142 affected offspring (79 men and 63 women; mean age, 29.4±9.0 years) from 137 families for whom parental DNA samples were available for genotyping. These affected offspring were diagnosed with schizophrenia according to DSM-IV or DSM-5 criteria and were not included in the case-control study. The case-control study population comprised 2,756 patients with schizophrenia and 2,646 controls, who were recruited from Fujita Health University,6 Kobe University,34 and Niigata University35 (Table 1). The patients were diagnosed according to DSM-IV or DSM-5 criteria. Controls had no personal or family history (first-degree relatives) of psychiatric disorders.
Table 1

Characteristics of case-control study participants

InstitutePatientsControls
nMen (%)Mean age ± SDnMen (%)Mean age ± SD
Fujita Health University1,111569 (51.2%)46.2±14.81,124486 (43.2%)40.5±12.8
Kobe University939489 (52.1%)54.3±15.0851400 (47.0%)52.3±18.6
Niigata University706377 (53.2%)43.1±13.5671341 (50.8%)38.3±10.9
Total2,7561,435 (52.1%)48.1±15.22,6461,227 (46.4%)43.8±15.8
Characteristics of case-control study participants

Wes

From the family, we obtained genomic DNA samples from the proband (#4), her affected younger sister (#5), and their unaffected father (#1) and mother (#2; Figure 1). WES was performed at Takara Bio Inc. (Shiga, Japan), using the HiSeq2500 system (Illumina, San Diego, CA, USA). We prepared exome libraries using the SureSelect Human All Exon V6 Kit (Agilent, Santa Clara, CA, USA). WES data were processed using GeneData Expressionist for Genomic Profiling v9.1.4a (Genedata, Basel, Switzerland). Adaptor sequences and low-quality reads were removed from raw sequence reads using Trimmomatic v0.1.9 (http://www.usadellab.org/cms/?page=trimmomatic).36 Cleaned sequence reads were mapped against the reference human genome (UCSC hg19) using the Burrows–Wheeler Aligner-MEM v0.7.12 (http://bio-bwa.sourceforge.net/).37 Variations were annotated using SnpEff v3.6c (http://snpeff.sourceforge.net/)38 and VCFtools v0.1.9 (https://vcftools.github.io/index.html).39 We calculated the coefficient of relationship from the WES data for each pair of individuals using peddy (https://github.com/brentp/peddy).40 To prioritize variations, we applied the following filtering steps (Table 2). First, we included variations on autosomes. Second, we included variations covered by ≥10 reads. Third, we included “HIGH” or “MODERATE” Effect_Impact variations predicted using SnpEff v3.6c. Fourth, we included recessive homozygous and compound heterozygous variations identified in both affected siblings. Fifth, we included rare variations with mutant allele frequency <0.01 in the Japanese Multi Omics Reference Panel (jMorp) 3.5KJPNv2 (https://jmorp.megabank.tohoku.ac.jp/201808/),41 the Human Genetic Variation Database (HGVD) v1.42 (http://www.genome.med.kyoto-u.ac.jp/SnpDB/),42 the BioBank Japan Whole-Genome Sequencing (BBJWGS) database (http://jenger.riken.jp/),43 Japanese data from the 1000 Genomes Project (1KGP) phase 3 (https://www.ncbi.nlm.nih.gov/variation/tools/1000genomes/),44 and East Asian data from the Genome Aggregation Database (gnomAD) v2.1 (non-neuro) (http://gnomad.broadinstitute.org/).45
Table 2

Filtering steps applied to variations identified by WES

Filtering stepNumber of remaining variations
Called213,038
On autosomes209,389
Covered with 10 or more reads102,293
HIGH or MODERATE Effect_Impact11,210
Recessive156
Homozygous60
Compound heterozygous96
With mutant allele frequency <0.012

Abbreviation: WES, whole-exome sequencing.

Filtering steps applied to variations identified by WES Abbreviation: WES, whole-exome sequencing. To validate prioritized variations, we performed Sanger sequencing using a 3130xl Genetic Analyzer (Applied Biosystems, Foster City, CA, USA), as previously described.46

Sequencing the SPATA7 coding region

The SPATA7 coding region (RefSeq accession number, NM_018418) was sequenced in 142 affected offspring from 137 families. In 32 offspring, we screened for rare recessive SPATA7 variations using our published35,47 and unpublished WES data. In the remaining 110 offspring, we performed Sanger sequencing. Primer sequences for amplification are listed in Table S1.48
Table S1

Primer sequences for sequencing SPATA7 coding regions

ExonForwardReverse
15ʹ-CGCAACTGTCCTCCTAGTACC-3’5ʹ-ACAAATTCAGGGCAAAGAAGC-3’
25ʹ-TTTAATGCTGTAACTCAGACTTCCT-3’5ʹ-TGAAGTTCAAATATTCGTCAAATG-3’
35ʹ-AAGGTTTGAACCCAAATGGTC-3’5ʹ-CAAAAATGGGTATGAATTTGCT-3’
45ʹ-CAAGGTCTGGAACATTTTGTGA-3’5ʹ-TGTTTATGTGGCACAGGAATTT-3’
55ʹ-ATCTAGAGGCACATGTGAAATAAA-3’5ʹ-CAAAGTCAGATTGTACCACTAAAGAA-3’
6.1a5ʹ-TTTTGTAAACCCTTGAGGCTATC-3’5ʹ-GGAGTGAATGGCAATTGTTTGT-3’
6.2a5ʹ-AGTCATCACAAATGGTCCTGAG-3’5ʹ-TTCCAATCAAAAGGGCACTATC-3’
75ʹ-TCTGGCAGTAGGTTTTAGTTGTTTT-3’5ʹ-TGTATGATAAGTGCCACCAACAG-3’
85ʹ-TGCTGTGTTATATTCTGCTTTCG-3’5ʹ-TAGATTGGAGCATGCAATTAAA-3’
95ʹ-CATTAACCTTAGTCAAATTGTCATTG-3’5ʹ-TGGTTTCTTTGATTCTTAATCCTTG-3’
105ʹ-CCCAGTGGATTGCATTTGA-3’5ʹ-GGTGAACTTCCCCTAGAGTATGA-3’
115ʹ-TTTTCAACCTTTGTAGTTTCAGTG-3’5ʹ-TTCCTTTCACTTCTCCCACCAC-3’
12.1a5ʹ-AATCCTGTGAGATTTTCAGCAC-3’5ʹ-TCACAGAAGTTTCCCGATCTGT-3’
12.2a5ʹ-GAAGTAACAATTCAGCAGGAACG-3’5ʹ-TGAGTTACTGGCCATTTGAGGT-3’

Note: aExons 6 and 12 were amplified as two overlapping fragments.

Case-control study

We performed an association study of rare recessive SPATA7 variations, prioritized via WES and sequencing, with schizophrenia in 2,756 patients and 2,646 controls. We genotyped p.Asp134Gly and p.Ile332Thr in our case-control samples, using the TaqMan 5′-exonuclease assay (Thermo Fisher Scientific, Waltham, MA, USA; Table S2), as previously described.33
Table S2

Probes used for the TaqMan 5′-exonuclease assay

VariationForward primerReverse primerReporter 1Reporter 2
p.Asp134Gly5ʹ-CTCAGGCGAACCGCAAATT −3’5ʹ-GACCTTGCAAAGGATGAAAATCCAT −3’5ʹ-VIC-CTTTTAACATGTCATCCTC -NFQ-3’5ʹ-FAM-TTAACATGCCATCCTC -NFQ-3’
p.Ile332Thr5ʹ-CTTTAGAAGGGCATGACTCAACATG −3’5ʹ-ACCTTGGTGAGGAATGCTGAAG −3’5ʹ-VIC-AGCATCATCCTTAATCTCAT -NFQ-3’5ʹ-FAM-AGCATCATCCTTAGTCTCAT -NFQ-3’

In silico analysis

We performed in silico analysis to predict the functional effects of SPATA7 variations identified via WES and resequencing using Polymorphism Phenotyping v2 (PolyPhen-2; http://genetics.bwh.harvard.edu/pph2/),49 Protein Variation Effect Analyzer v1.1 (PROVEN; http://provean.jcvi.org/genome_submit_2.php?species=human),50 and Combined Annotation Dependent Depletion (CADD; http://cadd.gs.washington.edu/home) scores.51

Results

The mean read depth varied from 48.0× to 67.6×, and 97.1–98.1% of the target regions were covered by 10 or more reads (Table S3). We identified a total of 213,038 variations via WES (Table 2). The coefficient of relationship observed for the parents (#1 and #2) was 0.038, which was similar to 0.031, the value expected for second cousins (Table S4). The coefficients of relationship observed for the other pairs of individuals ranged from 0.430 to 0.522, which were similar to 0.5, the value expected for parent-offspring or siblings. After the filtering steps (Table 2), we prioritized rare compound heterozygous missense variations in SPATA7 (Table 3). One was previously unidentified: an A to G transition (g.88892604A>G) at codon 134 resulting in an aspartic acid to glycine substitution (p.Asp134Gly). The other, a T to C transition (g.88895774T>C) at codon 332 resulting in an isoleucine to threonine substitution (p.Ile332Thr), had been previously reported (rs534658921). Unaffected father (#1) and mother (#2) transmitted the mutant p.Ile332Thr and p.Asp134Gly alleles, respectively, to both affected siblings (#4 and #5). In silico analysis predicted these variations to be “benign” and “neutral” using PolyPhen-2 and PROVEN, respectively (Table 3). CADD scores for p.Asp134Gly and p.Ile332Thr were 3.243 and 8.805, respectively, indicating that these variations were not deleterious.
Table S3

WES quality report summary

Father (#1)Mother (#2)Proband (#4)Affected sibling (#5)
Mean depth58.455.967.648.0
Coverage at 10×98.197.997.497.1

Abbreviation: WES, whole-exome sequencing.

Table S4

Coefficient of relatedness from the WES data for each pair of individuals

Pair of individualsCoefficient of relatedness
Father (#1) and mother (#2)0.038
Father (#1) and proband (#4)0.522
Father (#1) and affected sibling (#5)0.513
Mother (#2) and proband (#4)0.494
Mother (#2) and affected sibling (#5)0.503
Proband (#4) and affected sibling (#5)0.430

Abbreviation: WES, whole-exome sequencing.

Table 3

Rare compound heterozygous missense SPATA7 variations prioritized by WES

dbSNP IDPositionaAllelebExonProteinInheritanceIn silico analysisCADDMAF
PolyPhen-2PROVENjMorpHGVDBBJWGS1KGPgnomAD
88892604A/G6Asp134GlyMaternalBenignNeutral3.243
rs53465892188895774T/C8Ile332ThrPaternalBenignNeutral8.8050.00010.00040.00097465900.0005220

Notes: aPosition according to GRCh37. bReference/mutant allele.

Abbreviations: 1KGP, 1000 Genomes Project; BBBWGS, BioBank Japan Whole-Genome Sequencing; CADD, Combined Annotation Dependent Depletion; gnomAD, the Genome Aggregation Database; HGVD, the Human Genetic Variation Database; jMorp, Japanese Multi Omics Reference Panel; MAF, mutant allele frequency; PolyPhen-2, Polymorphism Phenotyping v2; PROVEN, Protein Variation Effect Analyzer; WES, whole-exome sequencing.

Rare compound heterozygous missense SPATA7 variations prioritized by WES Notes: aPosition according to GRCh37. bReference/mutant allele. Abbreviations: 1KGP, 1000 Genomes Project; BBBWGS, BioBank Japan Whole-Genome Sequencing; CADD, Combined Annotation Dependent Depletion; gnomAD, the Genome Aggregation Database; HGVD, the Human Genetic Variation Database; jMorp, Japanese Multi Omics Reference Panel; MAF, mutant allele frequency; PolyPhen-2, Polymorphism Phenotyping v2; PROVEN, Protein Variation Effect Analyzer; WES, whole-exome sequencing. Sequencing SPATA7 coding regions identified eight variations in 142 affected offspring (Table S5). However, there were no rare recessive variations. In the case-control study, p.Asp134Gly was not found in 2,732 patients or 2,627 controls, while heterozygous p.Ile332Thr was observed in five patients and one control (Table 4). In these individuals, we did not detect other rare variations by sequencing SPATA7 coding regions. The frequency of mutant alleles (0.0002) of p.Ile332Thr in our control group was similar to that in large databases including jMorp (0.0001), HGVD (0.0004), and gnomAD (0.0005; Table 3).
Table S5

SPATA7 variations identified by sequencing

dbSNP IDPositionaAllelebExonProteinIn silico analysisMAF
PolyPhen-2PROVENjMorpHGVDBBJWGS1KGPgnomAD
rs490444888852166G/A1Asp2AsnPossibly damagingNeutral0.05560.05740.05409360.04330.03567
rs52723605088857725_88857728TCAG/delSplice Acceptor Variant0.00890.01267060.006294
rs317996988862529G/A4Val74MetBenignNeutral0.28340.27310.2807020.30290.3236
88892638C/G6Ser145SerNeutral
rs76921171388894018A/T7Asp297ValPossibly damagingDeleterious0.00380.00390.003411310.0004694
rs37537198288897520A/G9Met345ValBenignNeutral0.00460.00620.006335280.001002
rs75067689388904442C/A12Phe492LeuBenignNeutral0.00530.00540.006822610.0007465
rs1013978488904567G/A12Arg534GlnBenignNeutral0.02360.02110.02729040.00960.02946

Note: aPosition according to GRCh37. bReference/mutant allele.

Abbreviations: 1KGP, 1000 Genomes Project; BBBWGS, BioBank Japan Whole-Genome Sequencing; gnomAD, the Genome Aggregation Database; HGVD, the Human Genetic Variation Database; jMorp, Japanese Multi Omics Reference Panel; MAF, mutant allele frequency; PolyPhen-2, Polymorphism Phenotyping v2; PROVEN, Protein Variation Effect Analyzer.

Table 4

Genotyping of two missense SPATA7 variations in the case-control study

VariationSamplePatientControl
1/1a1/2a2/2a1/1a1/2a2/2a
p.Asp134GlyFujita1,108001,12000
Kobe9180083700
Niigata7060067000
Combined2,732002,62700
p.Ile332ThrFujita1,109001,12000
Kobe9134083610
Niigata7051067000
Combined2,727502,62610

Note: aGenotypes: reference and mutant alleles are denoted by 1 and 2, respectively.

Genotyping of two missense SPATA7 variations in the case-control study Note: aGenotypes: reference and mutant alleles are denoted by 1 and 2, respectively.

Discussion

In the first-stage of this study, we did not identify rare recessive homozygous variations, but rare compound heterozygous missense SPATA7 variations, p.Asp134Gly and p.Ile332Thr, via WES in a family with two affected siblings whose unaffected parents were second cousins. Even in a consanguineous pedigree, a disease trait may be caused by compound heterozygous variations.52 For example, rare compound heterozygous missense AACS variations were identified in a consanguineous Pakistani family with autosomal recessive intellectual disability.53 In the second-stage of our study, sequencing SPATA7 coding regions did not detect rare recessive variations in 142 affected offspring for whom parental DNA samples were available for genotyping. In the third-stage of the study, we did not provide statistical evidence for the associations of SPATA7 p.Asp134Gly and p.Ile332Thr with schizophrenia in 2,756 patients and 2,646 controls. There is no converging evidence that rare recessive variations play an important role in the genetic etiology of schizophrenia. In a WES study of seven Italian schizophrenia patients with a high number of large runs of homozygosity (ROH), Giacopuzzi et al identified 119 low frequency, homozygous, recessive, non-synonymous and splice-cite variations in 107 genes within ROH regions.54 These genes significantly overlapped with the composite set of 1,796 genes of a Swedish case-control sample.14 Using WES data of the Swedish case-control sample, Magri et al found that rare homozygous variations in genes of the gamma-aminobutyric acid system were more frequent in patients (6/4,225) compared with controls (0/5,834).55 However, Ruderfer et al observed no significant difference in rare recessive gene-disrupting variations between Swedish patients (229 of 2,477) and controls (233 of 2,481).56 WES of 604 Bulgarian parent-affected offspring trios did not find an increased burden of rare recessive non-synonymous variations.57 To draw any conclusion on the effect of rare recessive variations on schizophrenia, further studies should be performed using sufficiently large sample sizes. SPATA7 encodes spermatogenesis-associated protein 7 (SPATA7). Spata7 was identified in rat testis, and SPATA7 was isolated by screening a human testis library.58 SPATA7 mRNA levels are high in retina, brain and testis.59 Recessive loss-of-function SPATA7 variations cause Laber congenital amaurosis and juvenile retinitis pigmentosa.48,59,60 In mouse retina, SPATA7 plays a critical role in the proper localization of proteins at the distal connecting cilium.61,62 However, the functions of SPATA7 in the brain remain unclear. In silico analysis predicted the SPATA7 variations, p.Asp134Gly and p.Ile332Thr, to be not damaging. Nevertheless, functional analyses are required to assess the functional implications of these variations. Earlier WES studies also reported no significant association between rare SPATA7 variations and schizophrenia14 and no de novo SPATA7 variations in schizophrenia.13 SPATA7 expression in the dorsolateral prefrontal cortex was not altered in schizophrenia patients.63 There were no available data regarding the methylation of SPATA7 in the three postmortem brain studies that are registered in the schizophrenia database (SZDB) v2 (http://www.szdb.org/index.html).64 Taken together, these findings do not support the role of SPATA7 in the development of schizophrenia. There are some limitations to our study. First, our WES study had no power to statistically analyze the results and assess their significance. Therefore, we performed follow-up sequencing of SPATA7 and a case-control study. However, we did not confirm the findings from the WES study. Second, we prioritized rare recessive variations because we hypothesized that these variations play a substantial role in conferring risk for schizophrenia in the consanguineous family with affected siblings. However, the inclusion of compound heterozygous variations may partially contradict the original study design. When we included low frequency, homozygous, recessive variations with mutant allele frequency <0.05, we identified two missense variations: HEBP2 p.Arg140Gln (rs3734303) and UPK2 p.Arg152Cy (rs137900462). Even when we genotyped rs3734303 and rs137900462 in our case-control samples, we found no significant associations between these two low frequency missense variations and schizophrenia (Table S6). It is possible that we overlooked the role of other kinds of variations, eg de novo variations13,17 and copy number variations.10–12 In our family, we identified no rare de novo variations or large homozygous deletions shared by two affected siblings. Third, genomic DNA samples from three siblings (#3, #6 and #7) were not available, and thus we were unable to assess whether they had rare compound heterozygous missense SPATA7 variations (p.Asp134Gly and p.Ile332Thr). Therefore, it was difficult to distinguish whether the variations that were prioritized in the family were potential risk variations or were coincidentally shared by two affected siblings. Fourth, our results did not exclude the possibility that common variations are implicated in schizophrenia vulnerability in consanguineous families. Interestingly, a WGS study of eight families with monozygotic twin pairs discordant for schizophrenia revealed that polygenic risk scores were higher in probands than in unaffected parents.65 Because we performed WES but not WGS, we were unable to calculate the polygenic risk scores.
Table S6

Genotyping of two uncommon missense variations in the case-control study

VariationSamplePatientControl
1/1a1/2a2/2a1/1a1/2a2/2a
rs3734303Fujita1,0208821,032901
Kobe871471794413
Niigata657481629420
Combined2,54818342,4551734
rs137900462Fujita1,0654601,088350
Kobe887301794380
Niigata675310625460
Combined2,62710712,5071190

Note: aGenotypes: reference and mutant alleles are denoted by 1 and 2, respectively.

Conclusion

Our data provide no evidence for the contribution of the rare compound heterozygous SPATA7 missense variations p.Asp134Gly and p.Ile332Thr to the risk of schizophrenia.

Supplementary materials

Primer sequences for sequencing SPATA7 coding regions Note: aExons 6 and 12 were amplified as two overlapping fragments. Probes used for the TaqMan 5′-exonuclease assay WES quality report summary Abbreviation: WES, whole-exome sequencing. Coefficient of relatedness from the WES data for each pair of individuals Abbreviation: WES, whole-exome sequencing. SPATA7 variations identified by sequencing Note: aPosition according to GRCh37. bReference/mutant allele. Abbreviations: 1KGP, 1000 Genomes Project; BBBWGS, BioBank Japan Whole-Genome Sequencing; gnomAD, the Genome Aggregation Database; HGVD, the Human Genetic Variation Database; jMorp, Japanese Multi Omics Reference Panel; MAF, mutant allele frequency; PolyPhen-2, Polymorphism Phenotyping v2; PROVEN, Protein Variation Effect Analyzer. Genotyping of two uncommon missense variations in the case-control study Note: aGenotypes: reference and mutant alleles are denoted by 1 and 2, respectively.
  65 in total

1.  Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects.

Authors:  Christian R Marshall; Daniel P Howrigan; Daniele Merico; Bhooma Thiruvahindrapuram; Wenting Wu; Douglas S Greer; Danny Antaki; Aniket Shetty; Peter A Holmans; Dalila Pinto; Madhusudan Gujral; William M Brandler; Dheeraj Malhotra; Zhouzhi Wang; Karin V Fuentes Fajarado; Michelle S Maile; Stephan Ripke; Ingrid Agartz; Margot Albus; Madeline Alexander; Farooq Amin; Joshua Atkins; Silviu A Bacanu; Richard A Belliveau; Sarah E Bergen; Marcelo Bertalan; Elizabeth Bevilacqua; Tim B Bigdeli; Donald W Black; Richard Bruggeman; Nancy G Buccola; Randy L Buckner; Brendan Bulik-Sullivan; William Byerley; Wiepke Cahn; Guiqing Cai; Murray J Cairns; Dominique Campion; Rita M Cantor; Vaughan J Carr; Noa Carrera; Stanley V Catts; Kimberley D Chambert; Wei Cheng; C Robert Cloninger; David Cohen; Paul Cormican; Nick Craddock; Benedicto Crespo-Facorro; James J Crowley; David Curtis; Michael Davidson; Kenneth L Davis; Franziska Degenhardt; Jurgen Del Favero; Lynn E DeLisi; Dimitris Dikeos; Timothy Dinan; Srdjan Djurovic; Gary Donohoe; Elodie Drapeau; Jubao Duan; Frank Dudbridge; Peter Eichhammer; Johan Eriksson; Valentina Escott-Price; Laurent Essioux; Ayman H Fanous; Kai-How Farh; Martilias S Farrell; Josef Frank; Lude Franke; Robert Freedman; Nelson B Freimer; Joseph I Friedman; Andreas J Forstner; Menachem Fromer; Giulio Genovese; Lyudmila Georgieva; Elliot S Gershon; Ina Giegling; Paola Giusti-Rodríguez; Stephanie Godard; Jacqueline I Goldstein; Jacob Gratten; Lieuwe de Haan; Marian L Hamshere; Mark Hansen; Thomas Hansen; Vahram Haroutunian; Annette M Hartmann; Frans A Henskens; Stefan Herms; Joel N Hirschhorn; Per Hoffmann; Andrea Hofman; Hailiang Huang; Masashi Ikeda; Inge Joa; Anna K Kähler; René S Kahn; Luba Kalaydjieva; Juha Karjalainen; David Kavanagh; Matthew C Keller; Brian J Kelly; James L Kennedy; Yunjung Kim; James A Knowles; Bettina Konte; Claudine Laurent; Phil Lee; S Hong Lee; Sophie E Legge; Bernard Lerer; Deborah L Levy; Kung-Yee Liang; Jeffrey Lieberman; Jouko Lönnqvist; Carmel M Loughland; Patrik K E Magnusson; Brion S Maher; Wolfgang Maier; Jacques Mallet; Manuel Mattheisen; Morten Mattingsdal; Robert W McCarley; Colm McDonald; Andrew M McIntosh; Sandra Meier; Carin J Meijer; Ingrid Melle; Raquelle I Mesholam-Gately; Andres Metspalu; Patricia T Michie; Lili Milani; Vihra Milanova; Younes Mokrab; Derek W Morris; Bertram Müller-Myhsok; Kieran C Murphy; Robin M Murray; Inez Myin-Germeys; Igor Nenadic; Deborah A Nertney; Gerald Nestadt; Kristin K Nicodemus; Laura Nisenbaum; Annelie Nordin; Eadbhard O'Callaghan; Colm O'Dushlaine; Sang-Yun Oh; Ann Olincy; Line Olsen; F Anthony O'Neill; Jim Van Os; Christos Pantelis; George N Papadimitriou; Elena Parkhomenko; Michele T Pato; Tiina Paunio; Diana O Perkins; Tune H Pers; Olli Pietiläinen; Jonathan Pimm; Andrew J Pocklington; John Powell; Alkes Price; Ann E Pulver; Shaun M Purcell; Digby Quested; Henrik B Rasmussen; Abraham Reichenberg; Mark A Reimers; Alexander L Richards; Joshua L Roffman; Panos Roussos; Douglas M Ruderfer; Veikko Salomaa; Alan R Sanders; Adam Savitz; Ulrich Schall; Thomas G Schulze; Sibylle G Schwab; Edward M Scolnick; Rodney J Scott; Larry J Seidman; Jianxin Shi; Jeremy M Silverman; Jordan W Smoller; Erik Söderman; Chris C A Spencer; Eli A Stahl; Eric Strengman; Jana Strohmaier; T Scott Stroup; Jaana Suvisaari; Dragan M Svrakic; Jin P Szatkiewicz; Srinivas Thirumalai; Paul A Tooney; Juha Veijola; Peter M Visscher; John Waddington; Dermot Walsh; Bradley T Webb; Mark Weiser; Dieter B Wildenauer; Nigel M Williams; Stephanie Williams; Stephanie H Witt; Aaron R Wolen; Brandon K Wormley; Naomi R Wray; Jing Qin Wu; Clement C Zai; Rolf Adolfsson; Ole A Andreassen; Douglas H R Blackwood; Elvira Bramon; Joseph D Buxbaum; Sven Cichon; David A Collier; Aiden Corvin; Mark J Daly; Ariel Darvasi; Enrico Domenici; Tõnu Esko; Pablo V Gejman; Michael Gill; Hugh Gurling; Christina M Hultman; Nakao Iwata; Assen V Jablensky; Erik G Jönsson; Kenneth S Kendler; George Kirov; Jo Knight; Douglas F Levinson; Qingqin S Li; Steven A McCarroll; Andrew McQuillin; Jennifer L Moran; Bryan J Mowry; Markus M Nöthen; Roel A Ophoff; Michael J Owen; Aarno Palotie; Carlos N Pato; Tracey L Petryshen; Danielle Posthuma; Marcella Rietschel; Brien P Riley; Dan Rujescu; Pamela Sklar; David St Clair; James T R Walters; Thomas Werge; Patrick F Sullivan; Michael C O'Donovan; Stephen W Scherer; Benjamin M Neale; Jonathan Sebat
Journal:  Nat Genet       Date:  2016-11-21       Impact factor: 38.330

2.  Analysis of exome sequence in 604 trios for recessive genotypes in schizophrenia.

Authors:  E Rees; G Kirov; J T Walters; A L Richards; D Howrigan; D H Kavanagh; A J Pocklington; M Fromer; D M Ruderfer; L Georgieva; N Carrera; P Gormley; P Palta; H Williams; S Dwyer; J S Johnson; P Roussos; D D Barker; E Banks; V Milanova; S A Rose; K Chambert; M Mahajan; E M Scolnick; J L Moran; M T Tsuang; S J Glatt; W J Chen; H-G Hwu; B M Neale; A Palotie; P Sklar; S M Purcell; S A McCarroll; P Holmans; M J Owen; M C O'Donovan
Journal:  Transl Psychiatry       Date:  2015-07-21       Impact factor: 6.222

3.  Who's Who? Detecting and Resolving Sample Anomalies in Human DNA Sequencing Studies with Peddy.

Authors:  Brent S Pedersen; Aaron R Quinlan
Journal:  Am J Hum Genet       Date:  2017-02-09       Impact factor: 11.025

4.  Rare variant analysis in multiply affected families, association studies and functional analysis suggest a role for the ITGΒ4 gene in schizophrenia and bipolar disorder.

Authors:  N L O'Brien; A Fiorentino; D Curtis; C Rayner; C Petrosellini; M Al Eissa; N J Bass; A McQuillin; S I Sharp
Journal:  Schizophr Res       Date:  2018-03-09       Impact factor: 4.939

5.  Exome Sequencing Identifies TENM4 as a Novel Candidate Gene for Schizophrenia in the SCZD2 Locus at 11q14-21.

Authors:  Chao-Biao Xue; Zhou-Heng Xu; Jun Zhu; Yu Wu; Xi-Hang Zhuang; Qu-Liang Chen; Cai-Ru Wu; Jin-Tao Hu; Hou-Shi Zhou; Wei-Hang Xie; Xin Yi; Shan-Shan Yu; Zhi-Yu Peng; Huan-Ming Yang; Xiao-Hong Hong; Jian-Huan Chen
Journal:  Front Genet       Date:  2019-01-28       Impact factor: 4.599

6.  Candidate CSPG4 mutations and induced pluripotent stem cell modeling implicate oligodendrocyte progenitor cell dysfunction in familial schizophrenia.

Authors:  Femke M de Vrij; Christian G Bouwkamp; Nilhan Gunhanlar; Guy Shpak; Bas Lendemeijer; Maarouf Baghdadi; Shreekara Gopalakrishna; Mehrnaz Ghazvini; Tracy M Li; Marialuisa Quadri; Simone Olgiati; Guido J Breedveld; Michiel Coesmans; Edwin Mientjes; Ton de Wit; Frans W Verheijen; H Berna Beverloo; Dan Cohen; Rob M Kok; P Roberto Bakker; Aviva Nijburg; Annet T Spijker; P M Judith Haffmans; Erik Hoencamp; Veerle Bergink; Jacob A Vorstman; Timothy Wu; Loes M Olde Loohuis; Najaf Amin; Carolyn D Langen; Albert Hofman; Witte J Hoogendijk; Cornelia M van Duijn; M Arfan Ikram; Meike W Vernooij; Henning Tiemeier; André G Uitterlinden; Ype Elgersma; Ben Distel; Joost Gribnau; Tonya White; Vincenzo Bonifati; Steven A Kushner
Journal:  Mol Psychiatry       Date:  2018-01-04       Impact factor: 15.992

7.  Fast and accurate short read alignment with Burrows-Wheeler transform.

Authors:  Heng Li; Richard Durbin
Journal:  Bioinformatics       Date:  2009-05-18       Impact factor: 6.937

8.  De novo mutations in schizophrenia implicate synaptic networks.

Authors:  Menachem Fromer; Andrew J Pocklington; David H Kavanagh; Hywel J Williams; Sarah Dwyer; Padhraig Gormley; Lyudmila Georgieva; Elliott Rees; Priit Palta; Douglas M Ruderfer; Noa Carrera; Isla Humphreys; Jessica S Johnson; Panos Roussos; Douglas D Barker; Eric Banks; Vihra Milanova; Seth G Grant; Eilis Hannon; Samuel A Rose; Kimberly Chambert; Milind Mahajan; Edward M Scolnick; Jennifer L Moran; George Kirov; Aarno Palotie; Steven A McCarroll; Peter Holmans; Pamela Sklar; Michael J Owen; Shaun M Purcell; Michael C O'Donovan
Journal:  Nature       Date:  2014-01-22       Impact factor: 49.962

Review 9.  Schizophrenia.

Authors:  Michael J Owen; Akira Sawa; Preben B Mortensen
Journal:  Lancet       Date:  2016-01-15       Impact factor: 79.321

10.  Exome sequencing of Pakistani consanguineous families identifies 30 novel candidate genes for recessive intellectual disability.

Authors:  S Riazuddin; M Hussain; A Razzaq; Z Iqbal; M Shahzad; D L Polla; Y Song; E van Beusekom; A A Khan; L Tomas-Roca; M Rashid; M Y Zahoor; W M Wissink-Lindhout; M A R Basra; M Ansar; Z Agha; K van Heeswijk; F Rasheed; M Van de Vorst; J A Veltman; C Gilissen; J Akram; T Kleefstra; M Z Assir; D Grozeva; K Carss; F L Raymond; T D O'Connor; S A Riazuddin; S N Khan; Z M Ahmed; A P M de Brouwer; H van Bokhoven; S Riazuddin
Journal:  Mol Psychiatry       Date:  2016-07-26       Impact factor: 15.992

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