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1.
Sci Data ; 6(1): 180, 2019 09 24.
Artigo em Inglês | MEDLINE | ID: mdl-31551426

RESUMO

Schizophrenia and bipolar disorder are serious mental illnesses that affect more than 2% of adults. While large-scale genetics studies have identified genomic regions associated with disease risk, less is known about the molecular mechanisms by which risk alleles with small effects lead to schizophrenia and bipolar disorder. In order to fill this gap between genetics and disease phenotype, we have undertaken a multi-cohort genomics study of postmortem brains from controls, individuals with schizophrenia and bipolar disorder. Here we present a public resource of functional genomic data from the dorsolateral prefrontal cortex (DLPFC; Brodmann areas 9 and 46) of 986 individuals from 4 separate brain banks, including 353 diagnosed with schizophrenia and 120 with bipolar disorder. The genomic data include RNA-seq and SNP genotypes on 980 individuals, and ATAC-seq on 269 individuals, of which 264 are a subset of individuals with RNA-seq. We have performed extensive preprocessing and quality control on these data so that the research community can take advantage of this public resource available on the Synapse platform at http://CommonMind.org .

2.
Nat Neurosci ; 22(9): 1402-1412, 2019 09.
Artigo em Inglês | MEDLINE | ID: mdl-31455887

RESUMO

RNA editing critically regulates neurodevelopment and normal neuronal function. The global landscape of RNA editing was surveyed across 364 schizophrenia cases and 383 control postmortem brain samples from the CommonMind Consortium, comprising two regions: dorsolateral prefrontal cortex and anterior cingulate cortex. In schizophrenia, RNA editing sites in genes encoding AMPA-type glutamate receptors and postsynaptic density proteins were less edited, whereas those encoding translation initiation machinery were edited more. These sites replicate between brain regions, map to 3'-untranslated regions and intronic regions, share common sequence motifs and overlap with binding sites for RNA-binding proteins crucial for neurodevelopment. These findings cross-validate in hundreds of non-overlapping dorsolateral prefrontal cortex samples. Furthermore, ~30% of RNA editing sites associate with cis-regulatory variants (editing quantitative trait loci or edQTLs). Fine-mapping edQTLs with schizophrenia risk loci revealed co-localization of eleven edQTLs with six loci. The findings demonstrate widespread altered RNA editing in schizophrenia and its genetic regulation, and suggest a causal and mechanistic role of RNA editing in schizophrenia neuropathology.

3.
Schizophr Bull ; 2019 Aug 19.
Artigo em Inglês | MEDLINE | ID: mdl-31424081

RESUMO

BACKGROUND: Resting-state functional neuroimaging captures large-scale network organization; whether this organization is intact or disrupted during adolescent development across the psychosis spectrum is unresolved. We investigated the integrity of network organization in psychosis spectrum youth and those with first episode psychosis (FEP) from late childhood through adulthood. METHODS: We analyzed data from Philadelphia Neurodevelopmental Cohort (PNC; typically developing = 450, psychosis spectrum = 273, 8-22 years), a longitudinal cohort of typically developing youth (LUNA; N = 208, 1-3 visits, 10-25 years), and a sample of FEP (N = 39) and matched controls (N = 34). We extracted individual time series and calculated correlations from brain regions and averaged them for 4 age groups: late childhood, early adolescence, late adolescence, adulthood. Using multiple analytic approaches, we assessed network stability across 4 age groups, compared stability between controls and psychosis spectrum youth, and compared group-level network organization of FEP to controls. We explored whether variability in cognition or clinical symptomatology was related to network organization. RESULTS: Network organization was stable across the 4 age groups in the PNC and LUNA typically developing youth and PNC psychosis spectrum youth. Psychosis spectrum and typically developing youth had similar functional network organization during all age ranges. Network organization was intact in PNC youth who met full criteria for psychosis and in FEP. Variability in cognitive functioning or clinical symptomatology was not related to network organization in psychosis spectrum youth or FEP. DISCUSSION: These findings provide rigorous evidence supporting intact functional network organization in psychosis risk and psychosis from late childhood through adulthood.

4.
Bioinformatics ; 2019 Aug 10.
Artigo em Inglês | MEDLINE | ID: mdl-31400192

RESUMO

MOTIVATION: Patterns of gene expression, quantified at the level of tissue or cells, can inform on etiology of disease. There are now rich resources for tissue-level (bulk) gene expression data, which have been collected from thousands of subjects, and resources involving single-cell RNA-sequencing (scRNA-seq) data are expanding rapidly. The latter yields cell type information, although the data can be noisy and typically are derived from a small number of subjects. RESULTS: Complementing these approaches, we develop a method to estimate subject- and cell-type-specific (CTS) gene expression from tissue using an empirical Bayes method that borrows information across multiple measurements of the same tissue per subject (e.g., multiple regions of the brain). Analyzing expression data from multiple brain regions from the Genotype-Tissue Expression project (GTEx) reveals CTS expression, which then permits downstream analyses, such as identification of CTS expression Quantitative Trait Loci (eQTL). AVAILABILITY AND IMPLEMENTATION: We implement this method as an R package MIND, hosted on https://github.com/randel/MIND. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

6.
Biol Res Nurs ; 21(3): 335-342, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-30983407

RESUMO

BACKGROUND: Sleep disturbance is a frequent comorbidity in children with autism spectrum disorder (ASD), affecting an estimated 40-80% of cases. Previous reports have shown relationships between several circadian rhythm-related genes and sleep problems in ASD. The purpose of the present study was to relate variation in and around melatonin synthesis and suprachiasmatic nucleus genes to sleep problems in a large sample of children with ASD. METHOD: This secondary analysis used existing genotypic and phenotypic data for 2,065 children, aged 4-18 years, from the Simons Simplex Collection (SSC). Sleep problems were measured with the SSC Sleep Interview. Expression quantitative trait loci and single nucleotide polymorphisms in 25 circadian genes were chosen primarily for their impact on expression levels of target genes in the brain. Associations between variants and composite sleep problems, nighttime problems, daytime problems, and sleep duration problems were calculated using logistic regression analysis. Age, sex, nonverbal IQ, ASD severity, gastrointestinal distress, seizures, and ancestry were included as covariates. Transmission disequilibrium tests were performed to test for overtransmission of alleles in the same variants. RESULTS: No significant associations or transmission disequilibrium were found between gene variants and sleep problems in this sample of children with ASD. CONCLUSION: Variation in expression of investigated genes in the melatonin synthesis and suprachiasmatic nucleus pathways did not have notable impacts on sleep problems in this large sample of children with ASD. Future research could explore translational and posttranslational effects of these genes or the effects of genes in other sleep-homeostasis pathways on sleep patterns.


Assuntos
Transtorno do Espectro Autista/complicações , Transtorno do Espectro Autista/genética , Ritmo Circadiano/genética , Melatonina/biossíntese , Melatonina/genética , Transtornos do Sono-Vigília/genética , Transtornos do Sono-Vigília/fisiopatologia , Adolescente , Transtorno do Espectro Autista/fisiopatologia , Criança , Pré-Escolar , Comorbidade , Feminino , Humanos , Masculino
7.
Nat Genet ; 51(4): 659-674, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30911161

RESUMO

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.


Assuntos
Encéfalo/fisiopatologia , Expressão Gênica/genética , Esquizofrenia/genética , Estudos de Casos e Controles , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla/métodos , Genótipo , Humanos , Polimorfismo de Nucleotídeo Único/genética , Locos de Características Quantitativas/genética , Risco , Transcriptoma/genética
8.
Nat Genet ; 51(3): 431-444, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30804558

RESUMO

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.


Assuntos
Transtorno do Espectro Autista/genética , Predisposição Genética para Doença/genética , Polimorfismo de Nucleotídeo Único/genética , Adolescente , Estudos de Casos e Controles , Criança , Pré-Escolar , Dinamarca , Feminino , Estudo de Associação Genômica Ampla/métodos , Humanos , Masculino , Herança Multifatorial/genética , Fenótipo , Fatores de Risco
9.
Proc Natl Acad Sci U S A ; 116(2): 466-471, 2019 01 08.
Artigo em Inglês | MEDLINE | ID: mdl-30587579

RESUMO

Motivated by the dynamics of development, in which cells of recognizable types, or pure cell types, transition into other types over time, we propose a method of semisoft clustering that can classify both pure and intermediate cell types from data on gene expression from individual cells. Called semisoft clustering with pure cells (SOUP), this algorithm reveals the clustering structure for both pure cells and transitional cells with soft memberships. SOUP involves a two-step process: Identify the set of pure cells and then estimate a membership matrix. To find pure cells, SOUP uses the special block structure in the expression similarity matrix. Once pure cells are identified, they provide the key information from which the membership matrix can be computed. By modeling cells as a continuous mixture of K discrete types we obtain more parsimonious results than obtained with standard clustering algorithms. Moreover, using soft membership estimates of cell type cluster centers leads to better estimates of developmental trajectories. The strong performance of SOUP is documented via simulation studies, which show its robustness to violations of modeling assumptions. The advantages of SOUP are illustrated by analyses of two independent datasets of gene expression from a large number of cells from fetal brain.


Assuntos
Algoritmos , Diferenciação Celular , Proliferação de Células , Processamento Eletrônico de Dados , Modelos Biológicos , Animais , Humanos
10.
Science ; 362(6420)2018 12 14.
Artigo em Inglês | MEDLINE | ID: mdl-30545852

RESUMO

Whole-genome sequencing (WGS) has facilitated the first genome-wide evaluations of the contribution of de novo noncoding mutations to complex disorders. Using WGS, we identified 255,106 de novo mutations among sample genomes from members of 1902 quartet families in which one child, but not a sibling or their parents, was affected by autism spectrum disorder (ASD). In contrast to coding mutations, no noncoding functional annotation category, analyzed in isolation, was significantly associated with ASD. Casting noncoding variation in the context of a de novo risk score across multiple annotation categories, however, did demonstrate association with mutations localized to promoter regions. We found that the strongest driver of this promoter signal emanates from evolutionarily conserved transcription factor binding sites distal to the transcription start site. These data suggest that de novo mutations in promoter regions, characterized by evolutionary and functional signatures, contribute to ASD.


Assuntos
Transtorno do Espectro Autista/genética , Mutação , Regiões Promotoras Genéticas/genética , Sítios de Ligação/genética , Sequência Conservada , Análise Mutacional de DNA , Loci Gênicos , Variação Genética , Humanos , Linhagem , Risco , Fatores de Transcrição/metabolismo
11.
Ann Appl Stat ; 12(1): 609-632, 2018 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-30174778

RESUMO

Recent advances in technology have enabled the measurement of RNA levels for individual cells. Compared to traditional tissue-level bulk RNA-seq data, single cell sequencing yields valuable insights about gene expression profiles for different cell types, which is potentially critical for understanding many complex human diseases. However, developing quantitative tools for such data remains challenging because of high levels of technical noise, especially the "dropout" events. A "dropout" happens when the RNA for a gene fails to be amplified prior to sequencing, producing a "false" zero in the observed data. In this paper, we propose a Unified RNA-Sequencing Model (URSM) for both single cell and bulk RNA-seq data, formulated as a hierarchical model. URSM borrows the strength from both data sources and carefully models the dropouts in single cell data, leading to a more accurate estimation of cell type specific gene expression profile. In addition, URSM naturally provides inference on the dropout entries in single cell data that need to be imputed for downstream analyses, as well as the mixing proportions of different cell types in bulk samples. We adopt an empirical Bayes' approach, where parameters are estimated using the EM algorithm and approximate inference is obtained by Gibbs sampling. Simulation results illustrate that URSM outperforms existing approaches both in correcting for dropouts in single cell data, as well as in deconvolving bulk samples. We also demonstrate an application to gene expression data on fetal brains, where our model successfully imputes the dropout genes and reveals cell type specific expression patterns.

12.
Nat Genet ; 50(7): 1032-1040, 2018 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-29892012

RESUMO

Identifying disease-associated missense mutations remains a challenge, especially in large-scale sequencing studies. Here we establish an experimentally and computationally integrated approach to investigate the functional impact of missense mutations in the context of the human interactome network and test our approach by analyzing ~2,000 de novo missense mutations found in autism subjects and their unaffected siblings. Interaction-disrupting de novo missense mutations are more common in autism probands, principally affect hub proteins, and disrupt a significantly higher fraction of hub interactions than in unaffected siblings. Moreover, they tend to disrupt interactions involving genes previously implicated in autism, providing complementary evidence that strengthens previously identified associations and enhances the discovery of new ones. Importantly, by analyzing de novo missense mutation data from six disorders, we demonstrate that our interactome perturbation approach offers a generalizable framework for identifying and prioritizing missense mutations that contribute to the risk of human disease.

13.
Am J Hum Genet ; 102(6): 1169-1184, 2018 06 07.
Artigo em Inglês | MEDLINE | ID: mdl-29805045

RESUMO

Causal genes and variants within genome-wide association study (GWAS) loci can be identified by integrating GWAS statistics with expression quantitative trait loci (eQTL) and determining which variants underlie both GWAS and eQTL signals. Most analyses, however, consider only the marginal eQTL signal, rather than dissect this signal into multiple conditionally independent signals for each gene. Here we show that analyzing conditional eQTL signatures, which could be important under specific cellular or temporal contexts, leads to improved fine mapping of GWAS associations. Using genotypes and gene expression levels from post-mortem human brain samples (n = 467) reported by the CommonMind Consortium (CMC), we find that conditional eQTL are widespread; 63% of genes with primary eQTL also have conditional eQTL. In addition, genomic features associated with conditional eQTL are consistent with context-specific (e.g., tissue-, cell type-, or developmental time point-specific) regulation of gene expression. Integrating the 2014 Psychiatric Genomics Consortium schizophrenia (SCZ) GWAS and CMC primary and conditional eQTL data reveals 40 loci with strong evidence for co-localization (posterior probability > 0.8), including six loci with co-localization of conditional eQTL. Our co-localization analyses support previously reported genes, identify novel genes associated with schizophrenia risk, and provide specific hypotheses for their functional follow-up.

14.
Mol Psychiatry ; 2018 May 08.
Artigo em Inglês | MEDLINE | ID: mdl-29740122

RESUMO

Transcription at enhancers is a widespread phenomenon which produces so-called enhancer RNA (eRNA) and occurs in an activity-dependent manner. However, the role of eRNA and its utility in exploring disease-associated changes in enhancer function, and the downstream coding transcripts that they regulate, is not well established. We used transcriptomic and epigenomic data to interrogate the relationship of eRNA transcription to disease status and how genetic variants alter enhancer transcriptional activity in the human brain. We combined RNA-seq data from 537 postmortem brain samples from the CommonMind Consortium with cap analysis of gene expression and enhancer identification, using the assay for transposase-accessible chromatin followed by sequencing (ATACseq). We find 118 differentially transcribed eRNAs in schizophrenia and identify schizophrenia-associated gene/eRNA co-expression modules. Perturbations of a key module are associated with the polygenic risk scores. Furthermore, we identify genetic variants affecting expression of 927 enhancers, which we refer to as enhancer expression quantitative loci or eeQTLs. Enhancer expression patterns are consistent across studies, including differentially expressed eRNAs and eeQTLs. Combining eeQTLs with a genome-wide association study of schizophrenia identifies a genetic variant that alters enhancer function and expression of its target gene, GOLPH3L. Our novel approach to analyzing enhancer transcription is adaptable to other large-scale, non-poly-A depleted, RNA-seq studies.

15.
Nat Genet ; 50(5): 727-736, 2018 May.
Artigo em Inglês | MEDLINE | ID: mdl-29700473

RESUMO

Genomic association studies of common or rare protein-coding variation have established robust statistical approaches to account for multiple testing. Here we present a comparable framework to evaluate rare and de novo noncoding single-nucleotide variants, insertion/deletions, and all classes of structural variation from whole-genome sequencing (WGS). Integrating genomic annotations at the level of nucleotides, genes, and regulatory regions, we define 51,801 annotation categories. Analyses of 519 autism spectrum disorder families did not identify association with any categories after correction for 4,123 effective tests. Without appropriate correction, biologically plausible associations are observed in both cases and controls. Despite excluding previously identified gene-disrupting mutations, coding regions still exhibited the strongest associations. Thus, in autism, the contribution of de novo noncoding variation is probably modest in comparison to that of de novo coding variants. Robust results from future WGS studies will require large cohorts and comprehensive analytical strategies that consider the substantial multiple-testing burden.

16.
Psychiatry Res ; 261: 148-153, 2018 03.
Artigo em Inglês | MEDLINE | ID: mdl-29306175

RESUMO

Several studies have indicated infectious and immune-related abnormalities in schizophrenia (Scz), including elevated serum C-reactive protein (CRP) - a well-known proxy for infections/immune abnormalities. A portion of the genetic risk for Scz can be estimated using the polygenic risk score (PGRS). It is not known whether there is an interaction in the risks traceable to CRP and PGRS. Patients with Scz and individuals without psychosis were evaluated systematically using DSM IV criteria (N=794, N=446, respectively). To estimate risk for Scz attributable to CRP and PGRS, serum from these participants was assayed for CRP levels using enzyme linked immunosorbent assays. PGRS was estimated from common DNA polymorphisms associated with Scz from genome wide association studies. CRP level and PGRS were not significantly correlated. Using a generalized linear logistic model, case/control status was evaluated in relation to the following predictors: CRP, PGRS, and demographic variables. CRP and PGRS were individually associated with case status; CRP: odds ratio (OR) 1.27, 95% confidence intervals (95% CI) 1.12, 1.43; p = 0.0001; PGRS: OR 1.66, 95% CI 1.47, 1.89; p = 1.28 ×10-15. There were no significant interactions between PGRS and CRP for predicting Scz versus control status.


Assuntos
Proteína C-Reativa/genética , Proteína C-Reativa/metabolismo , Predisposição Genética para Doença/genética , Herança Multifatorial/genética , Esquizofrenia/sangue , Esquizofrenia/genética , Adulto , Estudos de Casos e Controles , Feminino , Estudo de Associação Genômica Ampla , Humanos , Masculino , Pessoa de Meia-Idade , Transtornos Psicóticos/sangue , Transtornos Psicóticos/diagnóstico , Transtornos Psicóticos/genética , Fatores de Risco , Esquizofrenia/diagnóstico
17.
Biol Psychiatry ; 83(7): 589-597, 2018 Apr 01.
Artigo em Inglês | MEDLINE | ID: mdl-29100626

RESUMO

BACKGROUND: Autism spectrum disorder (ASD) has both genetic and environmental origins, including potentially maternal effects. Maternal effects describe the association of one or more maternal phenotypes with liability to ASD in progeny that are independent of maternally transmitted risk alleles. While maternal effects could play an important role, consistent with association to maternal traits such as immune status, no study has estimated maternal, additive genetic, and environmental effects in ASD. METHODS: Using a population-based sample consisting of all children born in Sweden from 1998 to 2007 and their relatives, we fitted statistical models to family data to estimate the variance in ASD liability originating from maternal, additive genetic, and shared environmental effects. We calculated sibling and cousin family recurrence risk ratio as a direct measure of familial, genetic, and environmental risk factors and repeated the calculations on diagnostic subgroups, specifically autistic disorder (AD) and spectrum disorder (SD), which included Asperger's syndrome and/or pervasive developmental disorder not otherwise specified. RESULTS: The sample consisted of 776,212 children of whom 11,231 had a diagnosis of ASD: 4554 with AD, 6677 with SD. We found support for large additive genetic contribution to liability; heritability (95% confidence interval [CI]) was estimated to 84.8% (95% CI: 73.1-87.3) for ASD, 79.6% (95% CI: 61.2-85.1) for AD, and 76.4% (95% CI: 63.0-82.5) for SD. CONCLUSIONS: There was modest, if any, contribution of maternal effects to liability for ASD, including subtypes AD and SD, and there was no support for shared environmental effects. These results show liability to ASD arises largely from additive genetic variation.

18.
Ann Appl Stat ; 11(3): 1810-1831, 2017 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-29081874

RESUMO

Scientists routinely compare gene expression levels in cases versus controls in part to determine genes associated with a disease. Similarly, detecting case-control differences in co-expression among genes can be critical to understanding complex human diseases; however statistical methods have been limited by the high dimensional nature of this problem. In this paper, we construct a sparse-Leading-Eigenvalue-Driven (sLED) test for comparing two high-dimensional covariance matrices. By focusing on the spectrum of the differential matrix, sLED provides a novel perspective that accommodates what we assume to be common, namely sparse and weak signals in gene expression data, and it is closely related with Sparse Principal Component Analysis. We prove that sLED achieves full power asymptotically under mild assumptions, and simulation studies verify that it outperforms other existing procedures under many biologically plausible scenarios. Applying sLED to the largest gene-expression dataset obtained from post-mortem brain tissue from Schizophrenia patients and controls, we provide a novel list of genes implicated in Schizophrenia and reveal intriguing patterns in gene co-expression change for Schizophrenia subjects. We also illustrate that sLED can be generalized to compare other gene-gene "relationship" matrices that are of practical interest, such as the weighted adjacency matrices.

19.
Psychiatr Genet ; 27(5): 169-177, 2017 10.
Artigo em Inglês | MEDLINE | ID: mdl-28570395

RESUMO

OBJECTIVES: Inbreeding increases the probability of homozygosity of deleterious alleles. Inbreeding and runs of homozygosity (ROH) are associated with an increased risk for disease phenotypes, including schizophrenia and other psychiatric disorders. The effects of inbreeding, ROH, homozygous deletions, and other copy number variations (CNVs) on risk for depression and suicide attempt (SA) were quantified in an Arab Bedouin Kindred. METHODS: We carried out genetic analyses of 439 individuals from an Arab kindred with high rates of depression and suicidal behavior. We obtained complete ascertainment of SAs and first-degree relatives of individuals who have attempted or died by suicide. RESULTS: We found extensive regions of ROH. On average, 5% of the genome is covered by ROH for these individuals, two-fold higher than ROH rates for individuals from populations of European ancestry. Inbreeding and total length of ROH were not associated with risk for depression or attempt. For CNVs, an increased number of duplications more than 500 kb was associated with an increased risk for attempt (odds ratio: 2.9; P=0.01; 95% confidence interval: 1.3-6.6). Although not significant after correction for multiple testing, the risk for SA appears to increase with copy number for a CNV on chromosome 9p24.1. This possibility is intriguing because the CNV covers GLDC, which encodes glycine dehydrogenase that binds to glycine, a co-agonist at N-methyl-D-aspartate glutamate receptors, and is involved in glutamatergic neurotransmission. CONCLUSION: Our findings add to the growing evidence of genetic risk factors that act pleiotropically to increase the risk for several neuropsychiatric disorders, including depression and SA, irrespective of ancestry.


Assuntos
Árabes/genética , Variações do Número de Cópias de DNA/genética , Depressão/genética , Grupos Étnicos/genética , Predisposição Genética para Doença , Ideação Suicida , Adolescente , Adulto , Consanguinidade , Feminino , Homozigoto , Humanos , Masculino , Pessoa de Meia-Idade , Linhagem , Reprodutibilidade dos Testes , Fatores de Risco , Adulto Jovem
20.
Nat Genet ; 49(7): 978-985, 2017 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-28504703

RESUMO

Autism spectrum disorder (ASD) risk is influenced by common polygenic and de novo variation. We aimed to clarify the influence of polygenic risk for ASD and to identify subgroups of ASD cases, including those with strongly acting de novo variants, in which polygenic risk is relevant. Using a novel approach called the polygenic transmission disequilibrium test and data from 6,454 families with a child with ASD, we show that polygenic risk for ASD, schizophrenia, and greater educational attainment is over-transmitted to children with ASD. These findings hold independent of proband IQ. We find that polygenic variation contributes additively to risk in ASD cases who carry a strongly acting de novo variant. Lastly, we show that elements of polygenic risk are independent and differ in their relationship with phenotype. These results confirm that the genetic influences on ASD are additive and suggest that they create risk through at least partially distinct etiologic pathways.


Assuntos
Transtorno do Espectro Autista/genética , Variação Genética , Herança Multifatorial , Adulto , Transtorno do Espectro Autista/epidemiologia , Criança , Estudos de Coortes , Escolaridade , Grupos Étnicos/genética , Saúde da Família , Feminino , Estudos de Associação Genética , Predisposição Genética para Doença , Genética Comportamental , Humanos , Deficiência Intelectual/genética , Inteligência/genética , Masculino , Fenótipo , Fatores de Risco , Esquizofrenia/genética , Deleção de Sequência
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