scholarly journals Identification of de novo mutations in prenatal neurodevelopment-associated genes in schizophrenia in two Han Chinese patient-sibling family-based cohorts

2019 ◽  
Author(s):  
Shan Jiang ◽  
Daizhan Zhou ◽  
Yin-Ying Wang ◽  
Peilin Jia ◽  
Chunling Wan ◽  
...  
Keyword(s):  
Drug Targets ◽  
Developmental Disorders ◽  
Rare Variants ◽  
De Novo ◽  
Association Studies ◽  
Chinese Patient ◽  
Genome Wide Association Studies ◽  
De Novo Mutations ◽  
Burden Test ◽  
Family Based

AbstractSchizophrenia (SCZ) is a severe psychiatric disorder with a strong genetic component. High heritability of SCZ suggests a major role for transmitted genetic variants. Furthermore, SCZ is also associated with a marked reduction in fecundity, leading to the hypothesis that alleles with large effects on risk might often occur de novo. In this study, we conducted whole-genome sequencing for 23 families from two cohorts with matched unaffected siblings and parents. Two nonsense de novo mutations (DNMs) in GJC1 and HIST1H2AD were identified in SCZ patients. Ten genes (DPYSL2, NBPF1, SDK1, ZNF595, ZNF718, GCNT2, SNX9, AACS, KCNQ1 and MSI2) were found to carry more DNMs in SCZ patients than their unaffected siblings by burden test. Expression analyses indicated that these DNM implicated genes showed significantly higher expression in prefrontal cortex in prenatal stage. The DNM in the GJC1 gene is highly likely a loss function mutation (pLI = 0.94), leading to the dysregulation of ion channel in the glutamatergic excitatory neurons. Analysis of rare variants in independent exome sequencing dataset indicates that GJC1 has significantly more rare variants in SCZ patients than in unaffected controls. Data from genome-wide association studies suggested that common variants in the GJC1 gene may be associated with SCZ and SCZ-related traits. Genes co-expressed with GJC1 are involved in SCZ, SCZ-associated pathways and drug targets. These evidence suggest that GJC1 may be a risk gene for SCZ and its function may be involved in prenatal and early neurodevelopment, a vulnerable period for developmental disorders such as SCZ.

scholarly journals Retracted: Identification of de novo mutations in prenatal neurodevelopment-associated genes in schizophrenia in two Han Chinese patient-sibling family-based cohorts

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Shan Jiang ◽  
Daizhan Zhou ◽  
Yin-Ying Wang ◽  
Peilin Jia ◽  
Chunling Wan ◽  
...  
Keyword(s):  
Drug Targets ◽  
Developmental Disorders ◽  
Rare Variants ◽  
De Novo ◽  
Association Studies ◽  
Chinese Patient ◽  
Genome Wide Association Studies ◽  
De Novo Mutations ◽  
Burden Test ◽  
Family Based

AbstractSchizophrenia (SCZ) is a severe psychiatric disorder with a strong genetic component. High heritability of SCZ suggests a major role for transmitted genetic variants. Furthermore, SCZ is also associated with a marked reduction in fecundity, leading to the hypothesis that alleles with large effects on risk might often occur de novo. In this study, we conducted whole-genome sequencing for 23 families from two cohorts with unaffected siblings and parents. Two nonsense de novo mutations (DNMs) in GJC1 and HIST1H2AD were identified in SCZ patients. Ten genes (DPYSL2, NBPF1, SDK1, ZNF595, ZNF718, GCNT2, SNX9, AACS, KCNQ1, and MSI2) were found to carry more DNMs in SCZ patients than their unaffected siblings by burden test. Expression analyses indicated that these DNM implicated genes showed significantly higher expression in prefrontal cortex in prenatal stage. The DNM in the GJC1 gene is highly likely a loss function mutation (pLI = 0.94), leading to the dysregulation of ion channel in the glutamatergic excitatory neurons. Analysis of rare variants in independent exome sequencing dataset indicates that GJC1 has significantly more rare variants in SCZ patients than in unaffected controls. Data from genome-wide association studies suggested that common variants in the GJC1 gene may be associated with SCZ and SCZ-related traits. Genes co-expressed with GJC1 are involved in SCZ, SCZ-associated pathways, and drug targets. These evidences suggest that GJC1 may be a risk gene for SCZ and its function may be involved in prenatal and early neurodevelopment, a vulnerable period for developmental disorders such as SCZ.

scholarly journals Demographic history mediates the effect of stratification on polygenic scores

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Arslan A Zaidi ◽  
Iain Mathieson
Keyword(s):  
Principal Components ◽  
Population Stratification ◽  
Rare Variants ◽  
Association Studies ◽  
Demographic History ◽  
Hybrid Approach ◽  
Genome Wide Association Studies ◽  
Environmental Structure ◽  
Polygenic Scores ◽  
Family Based

Population stratification continues to bias the results of genome-wide association studies (GWAS). When these results are used to construct polygenic scores, even subtle biases can cumulatively lead to large errors. To study the effect of residual stratification, we simulated GWAS under realistic models of demographic history. We show that when population structure is recent, it cannot be corrected using principal components of common variants because they are uninformative about recent history. Consequently, polygenic scores are biased in that they recapitulate environmental structure. Principal components calculated from rare variants or identity-by-descent segments can correct this stratification for some types of environmental effects. While family-based studies are immune to stratification, the hybrid approach of ascertaining variants in GWAS but reestimating effect sizes in siblings reduces but does not eliminate stratification. We show that the effect of population stratification depends not only on allele frequencies and environmental structure but also on demographic history.

De novo germline mutation in the dual specificity phosphatase 10 gene accelerates autoimmune diabetes

2021 ◽  
Vol 118 (47) ◽  
pp. e2112032118
Author(s):  
Anne-Perrine Foray ◽  
Sophie Candon ◽  
Sara Hildebrand ◽  
Cindy Marquet ◽  
Fabrice Valette ◽  
...  
Keyword(s):  
Rare Variants ◽  
De Novo ◽  
Association Studies ◽  
Nod Mice ◽  
Individual Risk ◽  
Type I ◽  
Genome Wide Association Studies ◽  
Dual Specificity Phosphatase ◽  
Dual Specificity ◽  
Significant Difference

Insulin-dependent or type 1 diabetes (T1D) is a polygenic autoimmune disease. In humans, more than 60 loci carrying common variants that confer disease susceptibility have been identified by genome-wide association studies, with a low individual risk contribution for most variants excepting those of the major histocompatibility complex (MHC) region (40 to 50% of risk); hence the importance of missing heritability due in part to rare variants. Nonobese diabetic (NOD) mice recapitulate major features of the human disease including genetic aspects with a key role for the MHC haplotype and a series of Idd loci. Here we mapped in NOD mice rare variants arising from genetic drift and significantly impacting disease risk. To that aim we established by selective breeding two sublines of NOD mice from our inbred NOD/Nck colony exhibiting a significant difference in T1D incidence. Whole-genome sequencing of high (H)- and low (L)-incidence sublines (NOD/NckH and NOD/NckL) revealed a limited number of subline-specific variants. Treating age of diabetes onset as a quantitative trait in automated meiotic mapping (AMM), enhanced susceptibility in NOD/NckH mice was unambiguously attributed to a recessive missense mutation of Dusp10, which encodes a dual specificity phosphatase. The causative effect of the mutation was verified by targeting Dusp10 with CRISPR-Cas9 in NOD/NckL mice, a manipulation that significantly increased disease incidence. The Dusp10 mutation resulted in islet cell down-regulation of type I interferon signature genes, which may exert protective effects against autoimmune aggression. De novo mutations akin to rare human susceptibility variants can alter the T1D phenotype.

scholarly journals Recent genetic findings in schizophrenia and their therapeutic relevance

2014 ◽  
Vol 29 (2) ◽  
pp. 85-96 ◽  
Author(s):  
Paul J Harrison
Keyword(s):  
Drug Targets ◽  
Rare Variants ◽  
Therapeutic Potential ◽  
Association Studies ◽  
Biological Significance ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Molecular Events ◽  
Mediating Mechanisms ◽  
Almost All

Over 100 loci are now associated with schizophrenia risk as identified by single nucleotide polymorphisms (SNPs) in genome-wide association studies. These findings mean that ‘genes for schizophrenia’ have unquestionably been found. However, many questions remain unanswered, including several which affect their therapeutic significance. The SNPs individually have minor effects, and even cumulatively explain only a modest fraction of the genetic predisposition. The remainder likely results from many more loci, from rare variants, and from gene–gene and gene–environment interactions. The risk SNPs are almost all non-coding, meaning that their biological significance is unclear; probably their effects are mediated via an influence on gene regulation, and emerging evidence suggests that some key molecular events occur during early brain development. The loci include novel genes of unknown function as well as genes and pathways previously implicated in the pathophysiology of schizophrenia, e.g. NMDA receptor signalling. Genes in the latter category have the clearer therapeutic potential, although even this will be a challenging process because of the many complexities concerning the genetic architecture and mediating mechanisms. This review summarises recent schizophrenia genetic findings and some key issues they raise, particularly with regard to their implications for identifying and validating novel drug targets.

scholarly journals Deep genotype imputation captures virtually all heritability of autoimmune vitiligo

2020 ◽  
Vol 29 (5) ◽  
pp. 859-863 ◽  
Author(s):  
Genevieve H L Roberts ◽  
Stephanie A Santorico ◽  
Richard A Spritz
Keyword(s):  
Complex Disease ◽  
Rare Variants ◽  
Association Studies ◽  
Genotype Imputation ◽  
Genome Wide Association Studies ◽  
Common Variants ◽  
Genome Wide ◽  
Autoimmune Vitiligo ◽  
Family Based ◽  
Project Data

Abstract Autoimmune vitiligo is a complex disease involving polygenic risk from at least 50 loci previously identified by genome-wide association studies. The objectives of this study were to estimate and compare vitiligo heritability in European-derived patients using both family-based and ‘deep imputation’ genotype-based approaches. We estimated family-based heritability (h2FAM) by vitiligo recurrence among a total 8034 first-degree relatives (3776 siblings, 4258 parents or offspring) of 2122 unrelated vitiligo probands. We estimated genotype-based heritability (h2SNP) by deep imputation to Haplotype Reference Consortium and the 1000 Genomes Project data in unrelated 2812 vitiligo cases and 37 079 controls genotyped genome wide, achieving high-quality imputation from markers with minor allele frequency (MAF) as low as 0.0001. Heritability estimated by both approaches was exceedingly high; h2FAM = 0.75–0.83 and h2SNP = 0.78. These estimates are statistically identical, indicating there is essentially no remaining ‘missing heritability’ for vitiligo. Overall, ~70% of h2SNP is represented by common variants (MAF > 0.01) and 30% by rare variants. These results demonstrate that essentially all vitiligo heritable risk is captured by array-based genotyping and deep imputation. These findings suggest that vitiligo may provide a particularly tractable model for investigation of complex disease genetic architecture and predictive aspects of personalized medicine.

scholarly journals Exome sequencing in families with severe mental illness identifies novel and rare variants in genes implicated in Mendelian neuropsychiatric syndromes

2018 ◽  
Author(s):  
Suhas Ganesh ◽  
Ahmed P Husayn ◽  
Ravi Kumar Nadella ◽  
Ravi Prabhakar More ◽  
Manasa Sheshadri ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Exome Sequencing ◽  
Rare Variants ◽  
Association Studies ◽  
Mental Illnesses ◽  
Disease Genes ◽  
Mendelian Disease ◽  
Genome Wide Association Studies ◽  
Complex Disorders ◽  
Family Based

AbstractIntroductionSevere Mental Illnesses (SMI), such as bipolar disorder and schizophrenia, are highly heritable, and have a complex pattern of inheritance. Genome wide association studies detect a part of the heritability, which can be attributed to common genetic variation. Examination of rare variants with Next Generation Sequencing (NGS) may add to the understanding of genetic architecture of SMIs.MethodsWe analyzed 32 ill subjects (with diagnosis of Bipolar Disorder, n=26; schizophrenia, n=4; schizoaffective disorder, n=1 schizophrenia like psychosis, n=1) from 8 multiplex families; and 33 healthy individuals by whole exome sequencing. Prioritized variants were selected by a 4-step filtering process, which included deleteriousness by 5 in silico algorithms; sharing within families, absence in the controls and rarity in South Asian sample of Exome Aggregation Consortium.ResultsWe identified a total of 42 unique rare, non-synonymous deleterious variants in this study with an average of 5 variants per family. None of the variants were shared across families, indicating a ‘private’ mutational profile. Twenty (47.6%) of the variant harboring genes identified in this sample have been previously reported to contribute to the risk of neuropsychiatric syndromes. These include genes which are related to neurodevelopmental processes, or have been implicated in different monogenic syndromes with a severe neurodevelopmental phenotype.ConclusionNGS approaches in family based studies are useful to identify novel and rare variants in genes for complex disorders like SMI. The study further validates the phenotypic burden of rare variants in Mendelian disease genes, indicating pleiotropic effects in the etiology of severe mental illnesses.

scholarly journals Prioritization of schizophrenia risk genes from GWAS results by integrating multi-omics data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dan He ◽  
Cong Fan ◽  
Mengling Qi ◽  
Yuedong Yang ◽  
David N. Cooper ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
De Novo ◽  
Association Studies ◽  
Bayesian Framework ◽  
Snp Markers ◽  
Genome Wide Association Studies ◽  
Omics Data ◽  
De Novo Mutations ◽  
Gwas Study ◽  
Risk Genes

AbstractSchizophrenia (SCZ) is a polygenic disease with a heritability approaching 80%. Over 100 SCZ-related loci have so far been identified by genome-wide association studies (GWAS). However, the risk genes associated with these loci often remain unknown. We present a new risk gene predictor, rGAT-omics, that integrates multi-omics data under a Bayesian framework by combining the Hotelling and Box–Cox transformations. The Bayesian framework was constructed using gene ontology, tissue-specific protein–protein networks, and multi-omics data including differentially expressed genes in SCZ and controls, distance from genes to the index single-nucleotide polymorphisms (SNPs), and de novo mutations. The application of rGAT-omics to the 108 loci identified by a recent GWAS study of SCZ predicted 103 high-risk genes (HRGs) that explain a high proportion of SCZ heritability (Enrichment = 43.44 and $$p = 9.30 \times 10^{ - 9}$$ p = 9.30 × 1 0 − 9 ). HRGs were shown to be significantly ($$p_{\mathrm{adj}} = 5.35 \times 10^{ - 7}$$ p adj = 5.35 × 1 0 − 7 ) enriched in genes associated with neurological activities, and more likely to be expressed in brain tissues and SCZ-associated cell types than background genes. The predicted HRGs included 16 novel genes not present in any existing databases of SCZ-associated genes or previously predicted to be SCZ risk genes by any other method. More importantly, 13 of these 16 genes were not the nearest to the index SNP markers, and them would have been difficult to identify as risk genes by conventional approaches while ten out of the 16 genes are associated with neurological functions that make them prime candidates for pathological involvement in SCZ. Therefore, rGAT-omics has revealed novel insights into the molecular mechanisms underlying SCZ and could provide potential clues to future therapies.

scholarly journals Predicting regulatory variants using a dense epigenomic mapped CNN model elucidated the molecular basis of trait-tissue associations

2020 ◽  
Author(s):  
Guangsheng Pei ◽  
Ruifeng Hu ◽  
Yulin Dai ◽  
Astrid Marilyn Manuel ◽  
Zhongming Zhao ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Molecular Basis ◽  
Complex Disease ◽  
De Novo ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
De Novo Mutations ◽  
Cell Type Specificity ◽  
The Impact ◽  
Human Complex

Abstract Assessing the causal tissues of human complex diseases is important for the prioritization of trait-associated genetic variants. Yet, the biological underpinnings of trait-associated variants are extremely difficult to infer due to statistical noise in genome-wide association studies (GWAS), and because >90% of genetic variants from GWAS are located in non-coding regions. Here, we collected the largest human epigenomic map from ENCODE and Roadmap consortia and implemented a deep-learning-based convolutional neural network (CNN) model to predict the regulatory roles of genetic variants across a comprehensive list of epigenomic modifications. Our model, called DeepFun, was built on DNA accessibility maps, histone modification marks, and transcription factors. DeepFun can systematically assess the impact of non-coding variants in the most functional elements with tissue or cell-type specificity, even for rare variants or de novo mutations. By applying this model, we prioritized trait-associated loci for 51 publicly-available GWAS studies. We demonstrated that CNN-based analyses on dense and high-resolution epigenomic annotations can refine important GWAS associations in order to identify regulatory loci from background signals, which yield novel insights for better understanding the molecular basis of human complex disease. We anticipate our approaches will become routine in GWAS downstream analysis and non-coding variant evaluation.

scholarly journals Retraction Note: Identification of de novo mutations in prenatal neurodevelopment-associated genes in schizophrenia in two Han Chinese patient-sibling family-based cohorts

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Shan Jiang ◽  
Daizhan Zhou ◽  
Yin-Ying Wang ◽  
Peilin Jia ◽  
Chunling Wan ◽  
...  
Keyword(s):  
De Novo ◽  
Chinese Patient ◽  
Han Chinese ◽  
De Novo Mutations ◽  
Retraction Notice ◽  
Family Based ◽  
Sibling Family

This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1038/s41398-020-00987-z.

Family-based exome-sequencing approach identifies rare susceptibility variants for lithium-responsive bipolar disorder

Genome ◽  
2013 ◽  
Vol 56 (10) ◽  
pp. 634-640 ◽  
Author(s):  
Cristiana Cruceanu ◽  
Amirthagowri Ambalavanan ◽  
Dan Spiegelman ◽  
Julie Gauthier ◽  
Ronald G. Lafrenière ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Rare Variants ◽  
Association Studies ◽  
Phenotypic Heterogeneity ◽  
Exome Capture ◽  
Genome Wide Association Studies ◽  
Complex Disorder ◽  
Genome Wide ◽  
High Throughput Dna Sequencing ◽  
Family Based

Bipolar disorder (BD) is a psychiatric condition characterized by the occurrence of at least two episodes of clinically disturbed mood including mania and depression. A vast literature describing BD studies suggests that a strong genetic contribution likely underlies this condition; heritability is estimated to be as high as 80%. Many studies have identified BD susceptibility loci, but because of the genetic and phenotypic heterogeneity observed across individuals, very few loci were subsequently replicated. Research in BD genetics to date has consisted of classical linkage or genome-wide association studies, which have identified candidate genes hypothesized to present common susceptibility variants. Although the observation of such common variants is informative, they can only explain a small fraction of the predicted BD heritability, suggesting a considerable contribution would come from rare and highly penetrant variants. We are seeking to identify such rare variants, and to increase the likelihood of being successful, we aimed to reduce the phenotypic heterogeneity factor by focusing on a well-defined subphenotype of BD: excellent response to lithium monotherapy. Our group has previously shown positive response to lithium therapy clusters in families and has a consistent clinical presentation with minimal comorbidity. To identify such rare variants, we are using a targeted exome capture and high-throughput DNA sequencing approach, and analyzing the entire coding sequences of BD affected individuals from multigenerational families. We are prioritizing rare variants with a frequency of less than 1% in the population that segregate with affected status within each family, as well as being potentially highly penetrant (e.g., protein truncating, missense, or frameshift) or functionally relevant (e.g., 3′UTR, 5′UTR, or splicing). By focusing on rare variants in a familial cohort, we hope to explain a significant portion of the missing heritability in BD, as well as to narrow our current insight on the key biochemical pathways implicated in this complex disorder.

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