RESUMO
Epidemiological studies show high comorbidity between different mental health problems, indicating that individuals with a diagnosis of one disorder are more likely to develop other mental health problems. Genetic studies reveal substantial sharing of genetic factors across mental health traits. However, mental health is also genetically correlated with socio-economic status (SES), and it is therefore important to investigate and disentangle the genetic relationship between mental health and SES. We used summary statistics from large genome-wide association studies (average N ~ 160,000) to estimate the genetic overlap across nine psychiatric disorders and seven substance use traits and explored the genetic influence of three different indicators of SES. Using genomic structural equation modelling, we show significant changes in patterns of genetic correlations after partialling out SES-associated genetic variation. Our approach allows the separation of disease-specific genetic variation and genetic variation shared with SES, thereby improving our understanding of the genetic architecture of mental health.
Assuntos
Escolaridade , Renda , Transtornos Mentais/genética , Saúde Mental , Classe Social , Transtornos Relacionados ao Uso de Substâncias/genética , Consumo de Bebidas Alcoólicas/genética , Anorexia Nervosa/genética , Transtornos de Ansiedade/genética , Transtorno do Deficit de Atenção com Hiperatividade/genética , Transtorno do Espectro Autista/genética , Transtorno Bipolar/genética , Transtorno Depressivo Maior/genética , Predisposição Genética para Doença , Variação Genética , Estudo de Associação Genômica Ampla , Humanos , Análise de Classes Latentes , Modelos Genéticos , Transtorno Obsessivo-Compulsivo/genética , Polimorfismo de Nucleotídeo Único , Esquizofrenia/genética , Fumar/genética , Abandono do Hábito de Fumar , Síndrome de Tourette/genéticaRESUMO
BACKGROUND: Little is known about the functional mechanisms through which genetic loci associated with substance use traits ascertain their effect. This study aims to identify and functionally annotate loci associated with substance use traits based on their role in genetic regulation of gene expression. METHODS: We evaluated expression Quantitative Trait Loci (eQTLs) from 13 brain regions and whole blood of the Genotype-Tissue Expression (GTEx) database, and from whole blood of the Depression Genes and Networks (DGN) database. The role of single eQTLs was examined for six substance use traits: alcohol consumption (Nâ¯=â¯537,349), cigarettes per day (CPD; Nâ¯=â¯263,954), former vs. current smoker (Nâ¯=â¯312,821), age of smoking initiation (Nâ¯=â¯262,990), ever smoker (Nâ¯=â¯632,802), and cocaine dependence (Nâ¯=â¯4,769). Subsequently, we conducted a gene level analysis of gene expression on these substance use traits using S-PrediXcan. RESULTS: Using an FDR-adjusted p-value <0.05 we found 2,976 novel candidate genetic loci for substance use traits, and identified genes and tissues through which these loci potentially exert their effects. Using S-PrediXcan, we identified significantly associated genes for all substance traits. DISCUSSION: Annotating genes based on transcriptomic regulation improves the identification and functional characterization of candidate loci and genes for substance use traits.
Assuntos
Usuários de Drogas/psicologia , Regulação da Expressão Gênica/genética , Predisposição Genética para Doença/genética , Locos de Características Quantitativas/genética , Transtornos Relacionados ao Uso de Substâncias/genética , Sangue/metabolismo , Encéfalo/metabolismo , Perfilação da Expressão Gênica , Humanos , Metanálise como Assunto , Fenótipo , Transtornos Relacionados ao Uso de Substâncias/psicologia , Transcriptoma/genéticaRESUMO
Methadone is known to be a risk factor for sudden death by enlarging ECG QT corrected (QTc) interval. For other medical conditions, QTc lengthening has been described as the result of interactions between pharmacological treatments and genetic factors. Former heroin-dependent subjects under methadone maintenance treatment in remission for at last 3 months were recruited. We studied the association between QTc length (Bazett formula) and 126 SNPs located on five genes (KCNE1, KCNQ1, KCNH2, NOS1AP and SCN5A) previously associated with drug-induced QT prolongation. Both SNP-based and gene-based approaches were used, and we tested also the interaction of the top SNP with methadone dosage to predict the QTc length. In our sample of 154 patients, current methadone daily dose was associated with QTc length (rPearson = 0.26; P = 10-3 ). Only one SNP, rs11911509 on KCNE1, remained significantly associated with QT length after correction for multiple testing (P = 3.84 × 10-4 ; pcorrected = 0.049). Using a gene-based approach, KCNE1 was also significantly associated with QTc length (pempirical = 0.02). We found a significant interaction between methadone dosage and rs11911509 minor allele count (allele A vs. C; P = 0.01). Stratified analysis revealed that the correlation between QTc length and methadone dosage was restricted only to AA carriers of this top SNP. Patients' genetic background should be taken into account in the case of clinically relevant QT enlargement during methadone maintenance treatment.
Assuntos
Síndrome do QT Longo/induzido quimicamente , Metadona/efeitos adversos , Tratamento de Substituição de Opiáceos/efeitos adversos , Canais de Potássio de Abertura Dependente da Tensão da Membrana/genética , Adulto , Relação Dose-Resposta a Droga , Eletrocardiografia , Feminino , Predisposição Genética para Doença , Dependência de Heroína/tratamento farmacológico , Humanos , Síndrome do QT Longo/genética , Masculino , Metadona/administração & dosagem , Pessoa de Meia-Idade , Tratamento de Substituição de Opiáceos/métodos , Polimorfismo de Nucleotídeo Único , Adulto JovemRESUMO
BACKGROUND: Alcohol and tobacco use are heritable phenotypes. However, only a small number of common genetic variants have been identified, and common variants account for a modest proportion of the heritability. Therefore, this study aims to investigate the role of low-frequency and rare variants in alcohol and tobacco use. METHODS: We meta-analyzed ExomeChip association results from eight discovery cohorts and included 12,466 subjects and 7432 smokers in the analysis of alcohol consumption and tobacco use, respectively. The ExomeChip interrogates low-frequency and rare exonic variants, and in addition a small pool of common variants. We investigated top variants in an independent sample in which ICD-9 diagnoses of "alcoholism" (Nâ¯=â¯25,508) and "tobacco use disorder" (Nâ¯=â¯27,068) had been assessed. In addition to the single variant analysis, we performed gene-based, polygenic risk score (PRS), and pathway analyses. RESULTS: The meta-analysis did not yield exome-wide significant results. When we jointly analyzed our top results with the independent sample, no low-frequency or rare variants reached significance for alcohol consumption or tobacco use. However, two common variants that were present on the ExomeChip, rs16969968 (pâ¯=â¯2.39â¯×â¯10-7) and rs8034191 (pâ¯=â¯6.31â¯×â¯10-7) located in CHRNA5 and AGPHD1 at 15q25.1, showed evidence for association with tobacco use. DISCUSSION: Low-frequency and rare exonic variants with large effects do not play a major role in alcohol and tobacco use, nor does the aggregate effect of ExomeChip variants. However, our results confirmed the role of the CHRNA5-CHRNA3-CHRNB4 cluster of nicotinic acetylcholine receptor subunit genes in tobacco use.