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1.
Am J Psychiatry ; 177(10): 917-927, 2020 10 01.
Artigo em Inglês | MEDLINE | ID: mdl-32998551

RESUMO

OBJECTIVE: Death by suicide is a highly preventable yet growing worldwide health crisis. To date, there has been a lack of adequately powered genomic studies of suicide, with no sizable suicide death cohorts available for analysis. To address this limitation, the authors conducted the first comprehensive genomic analysis of suicide death using previously unpublished genotype data from a large population-ascertained cohort. METHODS: The analysis sample comprised 3,413 population-ascertained case subjects of European ancestry and 14,810 ancestrally matched control subjects. Analytical methods included principal component analysis for ancestral matching and adjusting for population stratification, linear mixed model genome-wide association testing (conditional on genetic-relatedness matrix), gene and gene set-enrichment testing, and polygenic score analyses, as well as single-nucleotide polymorphism (SNP) heritability and genetic correlation estimation using linkage disequilibrium score regression. RESULTS: Genome-wide association analysis identified two genome-wide significant loci (involving six SNPs: rs34399104, rs35518298, rs34053895, rs66828456, rs35502061, and rs35256367). Gene-based analyses implicated 22 genes on chromosomes 13, 15, 16, 17, and 19 (q<0.05). Suicide death heritability was estimated at an h2SNP value of 0.25 (SE=0.04) and a value of 0.16 (SE=0.02) when converted to a liability scale. Notably, suicide polygenic scores were significantly predictive across training and test sets. Polygenic scores for several other psychiatric disorders and psychological traits were also predictive, particularly scores for behavioral disinhibition and major depressive disorder. CONCLUSIONS: Multiple genome-wide significant loci and genes were identified and polygenic score prediction of suicide death case-control status was demonstrated, adjusting for ancestry, in independent training and test sets. Additionally, the suicide death sample was found to have increased genetic risk for behavioral disinhibition, major depressive disorder, depressive symptoms, autism spectrum disorder, psychosis, and alcohol use disorder compared with the control sample.


Assuntos
Herança Multifatorial/genética , Suicídio Consumado/psicologia , Adulto , Estudos de Casos e Controles , Feminino , Genoma Humano/genética , Estudo de Associação Genômica Ampla , Técnicas de Genotipagem , Humanos , Desequilíbrio de Ligação/genética , Masculino , Polimorfismo de Nucleotídeo Único/genética , Análise de Componente Principal , Escócia/epidemiologia , Fatores Sexuais , Suicídio Consumado/prevenção & controle , Suicídio Consumado/estatística & dados numéricos , Utah/epidemiologia , Adulto Jovem
3.
Nat Commun ; 11(1): 4930, 2020 10 01.
Artigo em Inglês | MEDLINE | ID: mdl-33004804

RESUMO

Inference of causality between gene expression and complex traits using Mendelian randomization (MR) is confounded by pleiotropy and linkage disequilibrium (LD) of gene-expression quantitative trait loci (eQTL). Here, we propose an MR method, MR-link, that accounts for unobserved pleiotropy and LD by leveraging information from individual-level data, even when only one eQTL variant is present. In simulations, MR-link shows false-positive rates close to expectation (median 0.05) and high power (up to 0.89), outperforming all other tested MR methods and coloc. Application of MR-link to low-density lipoprotein cholesterol (LDL-C) measurements in 12,449 individuals with expression and protein QTL summary statistics from blood and liver identifies 25 genes causally linked to LDL-C. These include the known SORT1 and ApoE genes as well as PVRL2, located in the APOE locus, for which a causal role in liver was not known. Our results showcase the strength of MR-link for transcriptome-wide causal inferences.


Assuntos
LDL-Colesterol/sangue , Regulação da Expressão Gênica , Predisposição Genética para Doença , Modelos Genéticos , Locos de Características Quantitativas , Proteínas Adaptadoras de Transporte Vesicular/genética , Proteínas Adaptadoras de Transporte Vesicular/metabolismo , Apolipoproteínas E/genética , Apolipoproteínas E/metabolismo , LDL-Colesterol/metabolismo , Simulação por Computador , Conjuntos de Dados como Assunto , Pleiotropia Genética , Humanos , Desequilíbrio de Ligação , Metabolismo dos Lipídeos/genética , Análise da Randomização Mendeliana , Redes e Vias Metabólicas/genética , Herança Multifatorial , Nectinas/genética , Nectinas/metabolismo , Países Baixos , Proteômica , RNA-Seq
4.
Lancet Oncol ; 21(10): 1378-1386, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-33002439

RESUMO

BACKGROUND: Genetic variants and lifestyle factors have been associated with gastric cancer risk, but the extent to which an increased genetic risk can be offset by a healthy lifestyle remains unknown. We aimed to establish a genetic risk model for gastric cancer and assess the benefits of adhering to a healthy lifestyle in individuals with a high genetic risk. METHODS: In this meta-analysis and prospective cohort study, we first did a fixed-effects meta-analysis of the association between genetic variants and gastric cancer in six independent genome-wide association studies (GWAS) with a case-control study design. These GWAS comprised 21 168 Han Chinese individuals, of whom 10 254 had gastric cancer and 10 914 geographically matched controls did not. Using summary statistics from the meta-analysis, we constructed five polygenic risk scores in a range of thresholds (p=5 × 10-4 p=5 × 10-5 p=5 × 10-6 p=5 × 10-7, and p=5 × 10-8) for gastric cancer. We then applied these scores to an independent, prospective, nationwide cohort of 100 220 individuals from the China Kadoorie Biobank (CKB), with more than 10 years of follow-up. The relative and absolute risk of incident gastric cancer associated with healthy lifestyle factors (defined as not smoking, never consuming alcohol, the low consumption of preserved foods, and the frequent intake of fresh fruits and vegetables), was assessed and stratified by genetic risk (low [quintile 1 of the polygenic risk score], intermediate [quintile 2-4 of the polygenic risk score], and high [quintile 5 of the polygenic risk score]). Individuals with a favourable lifestyle were considered as those who adopted all four healthy lifestyle factors, those with an intermediate lifestyle adopted two or three factors, and those with an unfavourable lifestyle adopted none or one factor. FINDINGS: The polygenic risk score derived from 112 single-nucleotide polymorphisms (p<5 × 10-5) showed the strongest association with gastric cancer risk (p=7·56 × 10-10). When this polygenic risk score was applied to the CKB cohort, we found that there was a significant increase in the relative risk of incident gastric cancer across the quintiles of the polygenic risk score (ptrend<0·0001). Compared with individuals who had a low genetic risk, those with an intermediate genetic risk (hazard ratio [HR] 1·54 [95% CI 1·22-1·94], p=2·67 × 10-4) and a high genetic risk (2·08 [1·61-2·69], p<0·0001) had a greater risk of gastric cancer. A similar increase in the relative risk of incident gastric cancer was observed across the lifestyle categories (ptrend<0·0001), with a higher risk of gastric cancer in those with an unfavourable lifestyle than those with a favourable lifestyle (2·03 [1·46-2·83], p<0·0001). Participants with a high genetic risk and a favourable lifestyle had a lower risk of gastric cancer than those with a high genetic risk and an unfavourable lifestyle (0·53 [0·29-0·99], p=0·048), with an absolute risk reduction of 1·12% (95% CI 0·62-1·56). INTERPRETATION: Chinese individuals at an increased risk of incident gastric cancer could be identified by use of our newly developed polygenic risk score. Compared with individuals at a high genetic risk who adopt an unhealthy lifestyle, those who adopt a healthy lifestyle could substantially reduce their risk of incident gastric cancer. FUNDING: National Key R&D Program of China, National Natural Science Foundation of China, 333 High-Level Talents Cultivation Project of Jiangsu Province, and China Postdoctoral Science Foundation.


Assuntos
Predisposição Genética para Doença/genética , Estilo de Vida Saudável , Neoplasias Gástricas/genética , Adulto , Idoso , Grupo com Ancestrais do Continente Asiático , China/epidemiologia , Feminino , Seguimentos , Predisposição Genética para Doença/epidemiologia , Predisposição Genética para Doença/psicologia , Estudo de Associação Genômica Ampla/estatística & dados numéricos , Humanos , Incidência , Masculino , Pessoa de Meia-Idade , Herança Multifatorial , Polimorfismo de Nucleotídeo Único , Estudos Prospectivos , Fatores de Risco , Neoplasias Gástricas/epidemiologia , Neoplasias Gástricas/psicologia
5.
Nucleic Acids Res ; 48(19): e109, 2020 11 04.
Artigo em Inglês | MEDLINE | ID: mdl-32978944

RESUMO

Transcriptome-wide association studies (TWASs) integrate expression quantitative trait loci (eQTLs) studies with genome-wide association studies (GWASs) to prioritize candidate target genes for complex traits. Several statistical methods have been recently proposed to improve the performance of TWASs in gene prioritization by integrating the expression regulatory information imputed from multiple tissues, and made significant achievements in improving the ability to detect gene-trait associations. Unfortunately, most existing multi-tissue methods focus on prioritization of candidate genes, and cannot directly infer the specific functional effects of candidate genes across different tissues. Here, we propose a tissue-specific collaborative mixed model (TisCoMM) for TWASs, leveraging the co-regulation of genetic variations across different tissues explicitly via a unified probabilistic model. TisCoMM not only performs hypothesis testing to prioritize gene-trait associations, but also detects the tissue-specific role of candidate target genes in complex traits. To make full use of widely available GWASs summary statistics, we extend TisCoMM to use summary-level data, namely, TisCoMM-S2. Using extensive simulation studies, we show that type I error is controlled at the nominal level, the statistical power of identifying associated genes is greatly improved, and the false-positive rate (FPR) for non-causal tissues is well controlled at decent levels. We further illustrate the benefits of our methods in applications to summary-level GWASs data of 33 complex traits. Notably, apart from better identifying potential trait-associated genes, we can elucidate the tissue-specific role of candidate target genes. The follow-up pathway analysis from tissue-specific genes for asthma shows that the immune system plays an essential function for asthma development in both thyroid and lung tissues.


Assuntos
Estudo de Associação Genômica Ampla , Modelos Estatísticos , Locos de Características Quantitativas , Transcriptoma , Asma/genética , Asma/imunologia , Predisposição Genética para Doença , Humanos , Pulmão/imunologia , Herança Multifatorial/genética , Especificidade de Órgãos , Glândula Tireoide/imunologia
6.
PLoS Genet ; 16(9): e1008780, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32925905

RESUMO

Genome-Wide Association Studies (GWAS) in large human cohorts have identified thousands of loci associated with complex traits and diseases. For identifying the genes and gene-associated variants that underlie complex traits in livestock, especially where sample sizes are limiting, it may help to integrate the results of GWAS for equivalent traits in humans as prior information. In this study, we sought to investigate the usefulness of results from a GWAS on human height as prior information for identifying the genes and gene-associated variants that affect stature in cattle, using GWAS summary data on samples sizes of 700,000 and 58,265 for humans and cattle, respectively. Using Fisher's exact test, we observed a significant proportion of cattle stature-associated genes (30/77) that are also associated with human height (odds ratio = 5.1, p = 3.1e-10). Result of randomized sampling tests showed that cattle orthologs of human height-associated genes, hereafter referred to as candidate genes (C-genes), were more enriched for cattle stature GWAS signals than random samples of genes in the cattle genome (p = 0.01). Randomly sampled SNPs within the C-genes also tend to explain more genetic variance for cattle stature (up to 13.2%) than randomly sampled SNPs within random cattle genes (p = 0.09). The most significant SNPs from a cattle GWAS for stature within the C-genes did not explain more genetic variance for cattle stature than the most significant SNPs within random cattle genes (p = 0.87). Altogether, our findings support previous studies that suggest a similarity in the genetic regulation of height across mammalian species. However, with the availability of a powerful GWAS for stature that combined data from 8 cattle breeds, prior information from human-height GWAS does not seem to provide any additional benefit with respect to the identification of genes and gene-associated variants that affect stature in cattle.


Assuntos
Estatura/genética , Bovinos/genética , Estudo de Associação Genômica Ampla/métodos , Animais , Cruzamento/métodos , Bases de Dados Genéticas , Variação Genética/genética , Humanos , Gado/genética , Herança Multifatorial/genética , Fenótipo , Polimorfismo de Nucleotídeo Único/genética , Locos de Características Quantitativas/genética
7.
PLoS Genet ; 16(9): e1009036, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32941431

RESUMO

The polygenic nature and the contribution of common genetic variation to autism spectrum disorder (ASD) allude to a high degree of pleiotropy between ASD and other psychiatric and behavioral traits. In a pleiotropic system, a single genetic variant contributes small effects to several phenotypes or disorders. While analyzed broadly, there is a paucity of research studies investigating the shared genetic information between specific neurodevelopmental domains and ASD. We performed a phenome-wide association study of ASD polygenetic risk score (PRS) against 491 neurodevelopmental subdomains ascertained in 4,309 probands from the Philadelphia Neurodevelopmental Cohort (PNC) who lack an ASD diagnosis. Our main analysis calculated ASD PRS in 4,309 PNC probands using the per-SNP effects reported in a recent genome-wide association study of ASD in a case-control design. In a high-resolution manner, our main analysis regressed ASD PRS against 491 neurodevelopmental phenotypes with age, sex, and ten principal components of ancestry as covariates. Follow-up analyses included in the regression model PRS derived from brain-related traits genetically correlated with ASD. Our main finding demonstrated that 11-17-year old probands with the highest ASD genetic risk were able to identify angry faces (R2 = 1.06%, p = 1.38 × 10-7, pBonferroni-corrected = 1.9 × 10-3). This ability replicated in older probands (>18 years; R2 = 0.55%, p = 0.036) and persisted after covarying with other psychiatric disorders, brain imaging traits, and educational attainment (R2 = 0.2%, p = 0.019). We also detected several suggestive associations between ASD PRS and emotionality and connectedness with others. These data (i) indicate how genetic liability to ASD may influence neurodevelopment in the general population, (ii) reinforce epidemiological findings of heightened ability of ASD cases to predict certain social psychological events based on increased systemizing skills, and (iii) recapitulate theories of imbalance between empathizing and systemizing in ASD etiology.


Assuntos
Transtorno do Espectro Autista/genética , Reconhecimento Facial/fisiologia , Adolescente , Adulto , Ira/fisiologia , Estudos de Casos e Controles , Criança , Estudos de Coortes , Feminino , Pleiotropia Genética/genética , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Humanos , Masculino , Herança Multifatorial/genética , Fenótipo , Reconhecimento Psicológico/fisiologia , Fatores de Risco
8.
PLoS Genet ; 16(9): e1009015, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32956347

RESUMO

Evidence from both GWAS and clinical observation has suggested that certain psychiatric, metabolic, and autoimmune diseases are heterogeneous, comprising multiple subtypes with distinct genomic etiologies and Polygenic Risk Scores (PRS). However, the presence of subtypes within many phenotypes is frequently unknown. We present CLiP (Correlated Liability Predictors), a method to detect heterogeneity in single GWAS cohorts. CLiP calculates a weighted sum of correlations between SNPs contributing to a PRS on the case/control liability scale. We demonstrate mathematically and through simulation that among i.i.d. homogeneous cases generated by a liability threshold model, significant anti-correlations are expected between otherwise independent predictors due to ascertainment on the hidden liability score. In the presence of heterogeneity from distinct etiologies, confounding by covariates, or mislabeling, these correlation patterns are altered predictably. We further extend our method to two additional association study designs: CLiP-X for quantitative predictors in applications such as transcriptome-wide association, and CLiP-Y for quantitative phenotypes, where there is no clear distinction between cases and controls. Through simulations, we demonstrate that CLiP and its extensions reliably distinguish between homogeneous and heterogeneous cohorts when the PRS explains as low as 3% of variance on the liability scale and cohorts comprise 50, 000 - 100, 000 samples, an increasingly practical size for modern GWAS. We apply CLiP to heterogeneity detection in schizophrenia cohorts totaling > 50, 000 cases and controls collected by the Psychiatric Genomics Consortium. We observe significant heterogeneity in mega-analysis of the combined PGC data (p-value 8.54 × 0-4), as well as in individual cohorts meta-analyzed using Fisher's method (p-value 0.03), based on significantly associated variants. We also apply CLiP-Y to detect heterogeneity in neuroticism in over 10, 000 individuals from the UK Biobank and detect heterogeneity with a p-value of 1.68 × 10-9. Scores were not significantly reduced when partitioning by known subclusters ("Depression" and "Worry"), suggesting that these factors are not the primary source of observed heterogeneity.


Assuntos
Variação Genética/genética , Estudo de Associação Genômica Ampla/métodos , Herança Multifatorial/genética , Algoritmos , Transtorno Bipolar/genética , Estudos de Casos e Controles , Bases de Dados Genéticas , Transtorno Depressivo Maior/genética , Feminino , Heterogeneidade Genética , Predisposição Genética para Doença/genética , Humanos , Masculino , Modelos Teóricos , Polimorfismo de Nucleotídeo Único/genética , Fatores de Risco , Esquizofrenia/genética
9.
Proc Natl Acad Sci U S A ; 117(34): 20672-20680, 2020 08 25.
Artigo em Inglês | MEDLINE | ID: mdl-32817464

RESUMO

Rapid phenotypic adaptation is often observed in natural populations and selection experiments. However, detecting the genome-wide impact of this selection is difficult since adaptation often proceeds from standing variation and selection on polygenic traits, both of which may leave faint genomic signals indistinguishable from a noisy background of genetic drift. One promising signal comes from the genome-wide covariance between allele frequency changes observable from temporal genomic data (e.g., evolve-and-resequence studies). These temporal covariances reflect how heritable fitness variation in the population leads changes in allele frequencies at one time point to be predictive of the changes at later time points, as alleles are indirectly selected due to remaining associations with selected alleles. Since genetic drift does not lead to temporal covariance, we can use these covariances to estimate what fraction of the variation in allele frequency change through time is driven by linked selection. Here, we reanalyze three selection experiments to quantify the effects of linked selection over short timescales using covariance among time points and across replicates. We estimate that at least 17 to 37% of allele frequency change is driven by selection in these experiments. Against this background of positive genome-wide temporal covariances, we also identify signals of negative temporal covariance corresponding to reversals in the direction of selection for a reasonable proportion of loci over the time course of a selection experiment. Overall, we find that in the three studies we analyzed, linked selection has a large impact on short-term allele frequency dynamics that is readily distinguishable from genetic drift.


Assuntos
Adaptação Biológica/genética , Frequência do Gene/genética , Seleção Genética/genética , Aclimatação/genética , Adaptação Fisiológica/genética , Alelos , Animais , Evolução Biológica , Evolução Molecular , Frequência do Gene/fisiologia , Deriva Genética , Genética Populacional/métodos , Genômica/métodos , Humanos , Modelos Genéticos , Herança Multifatorial/genética , Densidade Demográfica
10.
Am J Hum Genet ; 107(3): 418-431, 2020 09 03.
Artigo em Inglês | MEDLINE | ID: mdl-32758451

RESUMO

While genome-wide association studies have identified susceptibility variants for numerous traits, their combined utility for predicting broad measures of health, such as mortality, remains poorly understood. We used data from the UK Biobank to combine polygenic risk scores (PRS) for 13 diseases and 12 mortality risk factors into sex-specific composite PRS (cPRS). These cPRS were moderately associated with all-cause mortality in independent data within the UK Biobank: the estimated hazard ratios per standard deviation were 1.10 (95% confidence interval: 1.05, 1.16) and 1.15 (1.10, 1.19) for women and men, respectively. Differences in life expectancy between the top and bottom 5% of the cPRS were estimated to be 4.79 (1.76, 7.81) years and 6.75 (4.16, 9.35) years for women and men, respectively. These associations were substantially attenuated after adjusting for non-genetic mortality risk factors measured at study entry (i.e., middle age for most participants). The cPRS may be useful in counseling younger individuals at higher genetic risk of mortality on modification of non-genetic factors.


Assuntos
Doenças Genéticas Inatas/mortalidade , Predisposição Genética para Doença , Herança Multifatorial/genética , Medição de Risco/estatística & dados numéricos , Bancos de Espécimes Biológicos , Feminino , Doenças Genéticas Inatas/genética , Doenças Genéticas Inatas/patologia , Estudo de Associação Genômica Ampla , Humanos , Masculino , Pessoa de Meia-Idade , Fenótipo , Polimorfismo de Nucleotídeo Único/genética , Modelos de Riscos Proporcionais , Fatores de Risco , Reino Unido
11.
Am J Hum Genet ; 107(3): 432-444, 2020 09 03.
Artigo em Inglês | MEDLINE | ID: mdl-32758450

RESUMO

Accurate colorectal cancer (CRC) risk prediction models are critical for identifying individuals at low and high risk of developing CRC, as they can then be offered targeted screening and interventions to address their risks of developing disease (if they are in a high-risk group) and avoid unnecessary screening and interventions (if they are in a low-risk group). As it is likely that thousands of genetic variants contribute to CRC risk, it is clinically important to investigate whether these genetic variants can be used jointly for CRC risk prediction. In this paper, we derived and compared different approaches to generating predictive polygenic risk scores (PRS) from genome-wide association studies (GWASs) including 55,105 CRC-affected case subjects and 65,079 control subjects of European ancestry. We built the PRS in three ways, using (1) 140 previously identified and validated CRC loci; (2) SNP selection based on linkage disequilibrium (LD) clumping followed by machine-learning approaches; and (3) LDpred, a Bayesian approach for genome-wide risk prediction. We tested the PRS in an independent cohort of 101,987 individuals with 1,699 CRC-affected case subjects. The discriminatory accuracy, calculated by the age- and sex-adjusted area under the receiver operating characteristics curve (AUC), was highest for the LDpred-derived PRS (AUC = 0.654) including nearly 1.2 M genetic variants (the proportion of causal genetic variants for CRC assumed to be 0.003), whereas the PRS of the 140 known variants identified from GWASs had the lowest AUC (AUC = 0.629). Based on the LDpred-derived PRS, we are able to identify 30% of individuals without a family history as having risk for CRC similar to those with a family history of CRC, whereas the PRS based on known GWAS variants identified only top 10% as having a similar relative risk. About 90% of these individuals have no family history and would have been considered average risk under current screening guidelines, but might benefit from earlier screening. The developed PRS offers a way for risk-stratified CRC screening and other targeted interventions.


Assuntos
Neoplasias Colorretais/epidemiologia , Predisposição Genética para Doença , Genoma Humano/genética , Medição de Risco , Idoso , Grupo com Ancestrais do Continente Asiático/genética , Teorema de Bayes , Neoplasias Colorretais/genética , Neoplasias Colorretais/patologia , Feminino , Estudo de Associação Genômica Ampla , Humanos , Masculino , Pessoa de Meia-Idade , Herança Multifatorial/genética , Polimorfismo de Nucleotídeo Único/genética , Fatores de Risco
12.
Am J Hum Genet ; 107(3): 461-472, 2020 09 03.
Artigo em Inglês | MEDLINE | ID: mdl-32781045

RESUMO

RNA sequencing (RNA-seq) is a powerful technology for studying human transcriptome variation. We introduce PAIRADISE (Paired Replicate Analysis of Allelic Differential Splicing Events), a method for detecting allele-specific alternative splicing (ASAS) from RNA-seq data. Unlike conventional approaches that detect ASAS events one sample at a time, PAIRADISE aggregates ASAS signals across multiple individuals in a population. By treating the two alleles of an individual as paired, and multiple individuals sharing a heterozygous SNP as replicates, we formulate ASAS detection using PAIRADISE as a statistical problem for identifying differential alternative splicing from RNA-seq data with paired replicates. PAIRADISE outperforms alternative statistical models in simulation studies. Applying PAIRADISE to replicate RNA-seq data of a single individual and to population-scale RNA-seq data across many individuals, we detect ASAS events associated with genome-wide association study (GWAS) signals of complex traits or diseases. Additionally, PAIRADISE ASAS analysis detects the effects of rare variants on alternative splicing. PAIRADISE provides a useful computational tool for elucidating the genetic variation and phenotypic association of alternative splicing in populations.


Assuntos
Processamento Alternativo/genética , Predisposição Genética para Doença , Herança Multifatorial/genética , Transcriptoma/genética , Alelos , Feminino , Perfilação da Expressão Gênica , Genética Populacional/métodos , Estudo de Associação Genômica Ampla , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Masculino , Modelos Estatísticos , RNA-Seq , Sequenciamento Completo do Exoma
13.
Nat Commun ; 11(1): 3981, 2020 08 07.
Artigo em Inglês | MEDLINE | ID: mdl-32769997

RESUMO

Thyroid stimulating hormone (TSH) is critical for normal development and metabolism. To better understand the genetic contribution to TSH levels, we conduct a GWAS meta-analysis at 22.4 million genetic markers in up to 119,715 individuals and identify 74 genome-wide significant loci for TSH, of which 28 are previously unreported. Functional experiments show that the thyroglobulin protein-altering variants P118L and G67S impact thyroglobulin secretion. Phenome-wide association analysis in the UK Biobank demonstrates the pleiotropic effects of TSH-associated variants and a polygenic score for higher TSH levels is associated with a reduced risk of thyroid cancer in the UK Biobank and three other independent studies. Two-sample Mendelian randomization using TSH index variants as instrumental variables suggests a protective effect of higher TSH levels (indicating lower thyroid function) on risk of thyroid cancer and goiter. Our findings highlight the pleiotropic effects of TSH-associated variants on thyroid function and growth of malignant and benign thyroid tumors.


Assuntos
Pleiotropia Genética , Estudo de Associação Genômica Ampla , Neoplasias da Glândula Tireoide/genética , Tireotropina/genética , Loci Gênicos , Predisposição Genética para Doença , Bócio/genética , Humanos , Análise da Randomização Mendeliana , Herança Multifatorial/genética , Mutação de Sentido Incorreto/genética , Fenótipo , Mapeamento Físico do Cromossomo , Prevalência , Fatores de Risco , Tireoglobulina/genética , Neoplasias da Glândula Tireoide/epidemiologia
14.
Am J Psychiatry ; 177(10): 944-954, 2020 10 01.
Artigo em Inglês | MEDLINE | ID: mdl-32791893

RESUMO

OBJECTIVE: Efforts to prevent depression, the leading cause of disability worldwide, have focused on a limited number of candidate factors. Using phenotypic and genomic data from over 100,000 UK Biobank participants, the authors sought to systematically screen and validate a wide range of potential modifiable factors for depression. METHODS: Baseline data were extracted for 106 modifiable factors, including lifestyle (e.g., exercise, sleep, media, diet), social (e.g., support, engagement), and environmental (e.g., green space, pollution) variables. Incident depression was defined as minimal depressive symptoms at baseline and clinically significant depression at follow-up. At-risk individuals for incident depression were identified by polygenic risk scores or by reported traumatic life events. An exposure-wide association scan was conducted to identify factors associated with incident depression in the full sample and among at-risk individuals. Two-sample Mendelian randomization was then used to validate potentially causal relationships between identified factors and depression. RESULTS: Numerous factors across social, sleep, media, dietary, and exercise-related domains were prospectively associated with depression, even among at-risk individuals. However, only a subset of factors was supported by Mendelian randomization evidence, including confiding in others (odds ratio=0.76, 95% CI=0.67, 0.86), television watching time (odds ratio=1.09, 95% CI=1.05, 1.13), and daytime napping (odds ratio=1.34, 95% CI=1.17, 1.53). CONCLUSIONS: Using a two-stage approach, this study validates several actionable targets for preventing depression. It also demonstrates that not all factors associated with depression in observational research may translate into robust targets for prevention. A large-scale exposure-wide approach combined with genetically informed methods for causal inference may help prioritize strategies for multimodal prevention in psychiatry.


Assuntos
Depressão/prevenção & controle , Adulto , Bases de Dados como Assunto , Depressão/etiologia , Depressão/genética , Dieta , Exercício Físico/psicologia , Feminino , Humanos , Masculino , Análise da Randomização Mendeliana , Herança Multifatorial/genética , Fatores de Risco , Tempo de Tela , Higiene do Sono
15.
Proc Natl Acad Sci U S A ; 117(35): 21813-21820, 2020 09 01.
Artigo em Inglês | MEDLINE | ID: mdl-32817414

RESUMO

Transitions from health to disease are characterized by dysregulation of biological networks under the influence of genetic and environmental factors, often over the course of years to decades before clinical symptoms appear. Understanding these dynamics has important implications for preventive medicine. However, progress has been hindered both by the difficulty of identifying individuals who will eventually go on to develop a particular disease and by the inaccessibility of most disease-relevant tissues in living individuals. Here we developed an alternative approach using polygenic risk scores (PRSs) based on genome-wide association studies (GWAS) for 54 diseases and complex traits coupled with multiomic profiling and found that these PRSs were associated with 766 detectable alterations in proteomic, metabolomic, and standard clinical laboratory measurements (clinical labs) from blood plasma across several thousand mostly healthy individuals. We recapitulated a variety of known relationships (e.g., glutamatergic neurotransmission and inflammation with depression, IL-33 with asthma) and found associations directly suggesting therapeutic strategies (e.g., Ω-6 supplementation and IL-13 inhibition for amyotrophic lateral sclerosis) and influences on longevity (leukemia inhibitory factor, ceramides). Analytes altered in high-genetic-risk individuals showed concordant changes in disease cases, supporting the notion that PRS-associated analytes represent presymptomatic disease alterations. Our results provide insights into the molecular pathophysiology of a range of traits and suggest avenues for the prevention of health-to-disease transitions.


Assuntos
Biomarcadores/sangue , Predisposição Genética para Doença/genética , Estudo de Associação Genômica Ampla/métodos , Doenças Assintomáticas/epidemiologia , Estudos de Coortes , Bases de Dados Genéticas , Progressão da Doença , Testes Genéticos/métodos , Humanos , Metabolômica/métodos , Herança Multifatorial/genética , Polimorfismo de Nucleotídeo Único/genética , Proteômica/métodos , Fatores de Risco
16.
Nat Commun ; 11(1): 3635, 2020 08 20.
Artigo em Inglês | MEDLINE | ID: mdl-32820175

RESUMO

Genetic variation can predispose to disease both through (i) monogenic risk variants that disrupt a physiologic pathway with large effect on disease and (ii) polygenic risk that involves many variants of small effect in different pathways. Few studies have explored the interplay between monogenic and polygenic risk. Here, we study 80,928 individuals to examine whether polygenic background can modify penetrance of disease in tier 1 genomic conditions - familial hypercholesterolemia, hereditary breast and ovarian cancer, and Lynch syndrome. Among carriers of a monogenic risk variant, we estimate substantial gradients in disease risk based on polygenic background - the probability of disease by age 75 years ranged from 17% to 78% for coronary artery disease, 13% to 76% for breast cancer, and 11% to 80% for colon cancer. We propose that accounting for polygenic background is likely to increase accuracy of risk estimation for individuals who inherit a monogenic risk variant.


Assuntos
Predisposição Genética para Doença , Herança Multifatorial/genética , Penetrância , Idoso , Neoplasias da Mama/genética , Estudos de Casos e Controles , Neoplasias Colorretais/genética , Doença da Artéria Coronariana/genética , Feminino , Genoma Humano , Humanos , Masculino , Pessoa de Meia-Idade , Razão de Chances , Fatores de Risco
17.
Nat Commun ; 11(1): 4016, 2020 08 11.
Artigo em Inglês | MEDLINE | ID: mdl-32782260

RESUMO

Brainstem regions support vital bodily functions, yet their genetic architectures and involvement in common brain disorders remain understudied. Here, using imaging-genetics data from a discovery sample of 27,034 individuals, we identify 45 brainstem-associated genetic loci, including the first linked to midbrain, pons, and medulla oblongata volumes, and map them to 305 genes. In a replication sample of 7432 participants most of the loci show the same effect direction and are significant at a nominal threshold. We detect genetic overlap between brainstem volumes and eight psychiatric and neurological disorders. In additional clinical data from 5062 individuals with common brain disorders and 11,257 healthy controls, we observe differential volume alterations in schizophrenia, bipolar disorder, multiple sclerosis, mild cognitive impairment, dementia, and Parkinson's disease, supporting the relevance of brainstem regions and their genetic architectures in common brain disorders.


Assuntos
Encefalopatias/genética , Encefalopatias/patologia , Tronco Encefálico/anatomia & histologia , Encefalopatias/diagnóstico por imagem , Encefalopatias/metabolismo , Tronco Encefálico/diagnóstico por imagem , Tronco Encefálico/metabolismo , Tronco Encefálico/patologia , Homologia de Genes , Loci Gênicos , Estudo de Associação Genômica Ampla , Humanos , Imagem por Ressonância Magnética , Herança Multifatorial , Tamanho do Órgão/genética
18.
Nat Commun ; 11(1): 4020, 2020 08 11.
Artigo em Inglês | MEDLINE | ID: mdl-32782262

RESUMO

While variance components analysis has emerged as a powerful tool in complex trait genetics, existing methods for fitting variance components do not scale well to large-scale datasets of genetic variation. Here, we present a method for variance components analysis that is accurate and efficient: capable of estimating one hundred variance components on a million individuals genotyped at a million SNPs in a few hours. We illustrate the utility of our method in estimating and partitioning variation in a trait explained by genotyped SNPs (SNP-heritability). Analyzing 22 traits with genotypes from 300,000 individuals across about 8 million common and low frequency SNPs, we observe that per-allele squared effect size increases with decreasing minor allele frequency (MAF) and linkage disequilibrium (LD) consistent with the action of negative selection. Partitioning heritability across 28 functional annotations, we observe enrichment of heritability in FANTOM5 enhancers in asthma, eczema, thyroid and autoimmune disorders.


Assuntos
Variação Genética/genética , Genoma Humano/genética , Modelos Genéticos , Alelos , Frequência do Gene , Genótipo , Humanos , Desequilíbrio de Ligação , Herança Multifatorial/genética , Fenótipo , Polimorfismo de Nucleotídeo Único , Característica Quantitativa Herdável
19.
Nat Commun ; 11(1): 3861, 2020 07 31.
Artigo em Inglês | MEDLINE | ID: mdl-32737316

RESUMO

Integrating results from genome-wide association studies (GWASs) and gene expression studies through transcriptome-wide association study (TWAS) has the potential to shed light on the causal molecular mechanisms underlying disease etiology. Here, we present a probabilistic Mendelian randomization (MR) method, PMR-Egger, for TWAS applications. PMR-Egger relies on a MR likelihood framework that unifies many existing TWAS and MR methods, accommodates multiple correlated instruments, tests the causal effect of gene on trait in the presence of horizontal pleiotropy, and is scalable to hundreds of thousands of individuals. In simulations, PMR-Egger provides calibrated type I error control for causal effect testing in the presence of horizontal pleiotropic effects, is reasonably robust under various types of model misspecifications, is more powerful than existing TWAS/MR approaches, and can directly test for horizontal pleiotropy. We illustrate the benefits of PMR-Egger in applications to 39 diseases and complex traits obtained from three GWASs including the UK Biobank.


Assuntos
Pleiotropia Genética , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla/estatística & dados numéricos , Análise da Randomização Mendeliana/estatística & dados numéricos , Modelos Genéticos , Transcriptoma , Doenças Cardiovasculares/diagnóstico , Doenças Cardiovasculares/genética , Doenças Cardiovasculares/patologia , Simulação por Computador , Bases de Dados Factuais , Gastroenteropatias/diagnóstico , Gastroenteropatias/genética , Gastroenteropatias/patologia , Humanos , Doenças do Sistema Imunitário/diagnóstico , Doenças do Sistema Imunitário/genética , Doenças do Sistema Imunitário/patologia , Funções Verossimilhança , Doenças Metabólicas/diagnóstico , Doenças Metabólicas/genética , Doenças Metabólicas/patologia , Herança Multifatorial , Neoplasias/diagnóstico , Neoplasias/genética , Neoplasias/patologia , Doenças Neurodegenerativas/diagnóstico , Doenças Neurodegenerativas/genética , Doenças Neurodegenerativas/patologia
20.
Nat Commun ; 11(1): 3865, 2020 07 31.
Artigo em Inglês | MEDLINE | ID: mdl-32737319

RESUMO

Polygenic scores (PGS) have been widely used to predict disease risk using variants identified from genome-wide association studies (GWAS). To date, most GWAS have been conducted in populations of European ancestry, which limits the use of GWAS-derived PGS in non-European ancestry populations. Here, we derive a theoretical model of the relative accuracy (RA) of PGS across ancestries. We show through extensive simulations that the RA of PGS based on genome-wide significant SNPs can be predicted accurately from modelling linkage disequilibrium (LD), minor allele frequencies (MAF), cross-population correlations of causal SNP effects and heritability. We find that LD and MAF differences between ancestries can explain between 70 and 80% of the loss of RA of European-based PGS in African ancestry for traits like body mass index and type 2 diabetes. Our results suggest that causal variants underlying common genetic variation identified in European ancestry GWAS are mostly shared across continents.


Assuntos
Asma/genética , Diabetes Mellitus Tipo 2/genética , Hipertensão/genética , Modelos Genéticos , Herança Multifatorial , Polimorfismo de Nucleotídeo Único , Adulto , África/epidemiologia , Idoso , Alelos , Ásia/epidemiologia , Asma/diagnóstico , Asma/epidemiologia , Asma/etnologia , Índice de Massa Corporal , Colesterol/sangue , Simulação por Computador , Diabetes Mellitus Tipo 2/diagnóstico , Diabetes Mellitus Tipo 2/epidemiologia , Diabetes Mellitus Tipo 2/etnologia , Europa (Continente)/epidemiologia , Feminino , Frequência do Gene , Estudo de Associação Genômica Ampla , Humanos , Hipertensão/diagnóstico , Hipertensão/epidemiologia , Hipertensão/etnologia , Desequilíbrio de Ligação , Masculino , Pessoa de Meia-Idade , Prognóstico , Característica Quantitativa Herdável , Risco
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