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1.
Sci Rep ; 11(1): 3100, 2021 Feb 04.
Artigo em Inglês | MEDLINE | ID: mdl-33542415

RESUMO

Individuals experiencing socioeconomic disadvantage in childhood have a higher rate of inflammation-related diseases decades later. Little is known about the mechanisms linking early life experiences to the functioning of the immune system in adulthood. To address this, we explore the relationship across social-to-biological layers of early life social exposures on levels of adulthood inflammation and the mediating role of gene regulatory mechanisms, epigenetic and transcriptomic profiling from blood, in 2,329 individuals from two European cohort studies. Consistently across both studies, we find transcriptional activity explains a substantive proportion (78% and 26%) of the estimated effect of early life disadvantaged social exposures on levels of adulthood inflammation. Furthermore, we show that mechanisms other than cis DNA methylation may regulate those transcriptional fingerprints. These results further our understanding of social-to-biological transitions by pinpointing the role of gene regulation that cannot fully be explained by differential cis DNA methylation.

2.
Transl Psychiatry ; 11(1): 96, 2021 Feb 04.
Artigo em Inglês | MEDLINE | ID: mdl-33542229

RESUMO

Studies considering the causal role of body mass index (BMI) for the predisposition of major depressive disorder (MDD) based on a Mendelian Randomization (MR) approach have shown contradictory results. These inconsistent findings may be attributable to the heterogeneity of MDD; in fact, several studies have documented associations between BMI and mainly the atypical subtype of MDD. Using a MR approach, we investigated the potential causal role of obesity in both the atypical subtype and its five specific symptoms assessed according to the Statistical Manual of Mental Disorders (DSM), in two large European cohorts, CoLaus|PsyCoLaus (n = 3350, 1461 cases and 1889 controls) and NESDA|NTR (n = 4139, 1182 cases and 2957 controls). We first tested general obesity measured by BMI and then the body fat distribution measured by waist-to-hip ratio (WHR). Results suggested that BMI is potentially causally related to the symptom increase in appetite, for which inverse variance weighted, simple median and weighted median MR regression estimated slopes were 0.68 (SE = 0.23, p = 0.004), 0.77 (SE = 0.37, p = 0.036), and 1.11 (SE = 0.39, p = 0.004). No causal effect of BMI or WHR was found on the risk of the atypical subtype or for any of the other atypical symptoms. Our findings show that higher obesity is likely causal for the specific symptom of increase in appetite in depressed participants and reiterate the need to study depression at the granular level of its symptoms to further elucidate potential causal relationships and gain additional insight into its biological underpinnings.

3.
Nat Hum Behav ; 2020 Sep 28.
Artigo em Inglês | MEDLINE | ID: mdl-32989287

RESUMO

Handedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P < 5 × 10-8) with left-handedness and 7 associated with ambidexterity. Tissue-enrichment analysis implicated the CNS in the aetiology of handedness. Pathways including regulation of microtubules and brain morphology were also highlighted. We found suggestive positive genetic correlations between left-handedness and neuropsychiatric traits, including schizophrenia and bipolar disorder. Furthermore, the genetic correlation between left-handedness and ambidexterity is low (rG = 0.26), which implies that these traits are largely influenced by different genetic mechanisms. Our findings suggest that handedness is highly polygenic and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders.

4.
Diabetes ; 69(12): 2806-2818, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-32917775

RESUMO

Leptin influences food intake by informing the brain about the status of body fat stores. Rare LEP mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in LEP, ZNF800, KLHL31, and ACTL9, and one intergenic variant near KLF14. The missense variant Val94Met (rs17151919) in LEP was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry (P = 2 × 10-16, n = 3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting that leptin regulates early adiposity.

5.
Artigo em Inglês | MEDLINE | ID: mdl-32816877

RESUMO

Major biotechnological advances have facilitated a tremendous boost to the collection of (gen-/transcript-/prote-/methyl-/metabol-)omics data in very large sample sizes worldwide. Coordinated efforts have yielded a deluge of studies associating diseases with genetic markers (genome-wide association studies) or with molecular phenotypes. Whereas omics-disease associations have led to biologically meaningful and coherent mechanisms, the identified (non-germline) disease biomarkers may simply be correlates or consequences of the explored diseases. To move beyond this realm, Mendelian randomization provides a principled framework to integrate information on omics- and disease-associated genetic variants to pinpoint molecular traits causally driving disease development. In this review, we show the latest advances in this field, flag up key challenges for the future, and propose potential solutions.

6.
Am J Med Genet B Neuropsychiatr Genet ; 183(6): 309-330, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32681593

RESUMO

It is imperative to understand the specific and shared etiologies of major depression and cardio-metabolic disease, as both traits are frequently comorbid and each represents a major burden to society. This study examined whether there is a genetic association between major depression and cardio-metabolic traits and if this association is stratified by age at onset for major depression. Polygenic risk scores analysis and linkage disequilibrium score regression was performed to examine whether differences in shared genetic etiology exist between depression case control status (N cases = 40,940, N controls = 67,532), earlier (N = 15,844), and later onset depression (N = 15,800) with body mass index, coronary artery disease, stroke, and type 2 diabetes in 11 data sets from the Psychiatric Genomics Consortium, Generation Scotland, and UK Biobank. All cardio-metabolic polygenic risk scores were associated with depression status. Significant genetic correlations were found between depression and body mass index, coronary artery disease, and type 2 diabetes. Higher polygenic risk for body mass index, coronary artery disease, and type 2 diabetes was associated with both early and later onset depression, while higher polygenic risk for stroke was associated with later onset depression only. Significant genetic correlations were found between body mass index and later onset depression, and between coronary artery disease and both early and late onset depression. The phenotypic associations between major depression and cardio-metabolic traits may partly reflect their overlapping genetic etiology irrespective of the age depression first presents.

8.
Bioinformatics ; 36(15): 4374-4376, 2020 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-32470106

RESUMO

SUMMARY: Increasing sample size is not the only strategy to improve discovery in Genome Wide Association Studies (GWASs) and we propose here an approach that leverages published studies of related traits to improve inference. Our Bayesian GWAS method derives informative prior effects by leveraging GWASs of related risk factors and their causal effect estimates on the focal trait using multivariable Mendelian randomization. These prior effects are combined with the observed effects to yield Bayes Factors, posterior and direct effects. The approach not only increases power, but also has the potential to dissect direct and indirect biological mechanisms. AVAILABILITY AND IMPLEMENTATION: bGWAS package is freely available under a GPL-2 License, and can be accessed, alongside with user guides and tutorials, from https://github.com/n-mounier/bGWAS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

9.
Nat Commun ; 11(1): 1385, 2020 03 13.
Artigo em Inglês | MEDLINE | ID: mdl-32170055

RESUMO

The growing sample size of genome-wide association studies has facilitated the discovery of gene-environment interactions (GxE). Here we propose a maximum likelihood method to estimate the contribution of GxE to continuous traits taking into account all interacting environmental variables, without the need to measure any. Extensive simulations demonstrate that our method provides unbiased interaction estimates and excellent coverage. We also offer strategies to distinguish specific GxE from general scale effects. Applying our method to 32 traits in the UK Biobank reveals that while the genetic risk score (GRS) of 376 variants explains 5.2% of body mass index (BMI) variance, GRSxE explains an additional 1.9%. Nevertheless, this interaction holds for any variable with identical correlation to BMI as the GRS, hence may not be GRS-specific. Still, we observe that the global contribution of specific GRSxE to complex traits is substantial for nine obesity-related measures (including leg impedance and trunk fat-free mass).


Assuntos
Interação Gene-Ambiente , Obesidade/genética , Fenótipo , Índice de Massa Corporal , Bases de Dados Factuais , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Humanos , Modelos Genéticos , Polimorfismo de Nucleotídeo Único , Fatores de Risco , Reino Unido
10.
Am J Hum Genet ; 106(3): 303-314, 2020 03 05.
Artigo em Inglês | MEDLINE | ID: mdl-32059761

RESUMO

Disease risk varies significantly between ethnic groups, however, the clinical significance and implications of these observations are poorly understood. Investigating ethnic differences within the human proteome may shed light on the impact of ancestry on disease risk. We used admixture mapping to explore the impact of genetic ancestry on 237 cardiometabolic biomarkers in 2,216 Latin Americans within the Outcomes Reduction with an Initial Glargine Intervention (ORIGIN) study. We developed a variance component model in order to determine the proportion of variance explained by inter-ancestry differences, and we applied it to the biomarker panel. Multivariable linear regression was used to identify and localize genetic loci affecting biomarker variability between ethnicities. Variance component analysis revealed that 5% of biomarkers were significantly impacted by genetic admixture (p < 0.05/237), including C-peptide, apolipoprotein-E, and intercellular adhesion molecule 1. We also identified 46 regional associations across 40 different biomarkers (p < 1.13 × 10-6). An independent analysis revealed that 34 of these 46 regions were associated at genome-wide significance (p < 5 × 10-8) with their respective biomarker in either Europeans or Latin populations. Additional analyses revealed that an admixture mapping signal associated with increased C-peptide levels was also associated with an increase in diabetes risk (odds ratio [OR] = 6.07 per SD, 95% confidence interval [CI] 1.44 to 25.56, p = 0.01) and surrogate measures of insulin resistance. Our results demonstrate the impact of ancestry on biomarker levels, suggesting that some of the observed differences in disease prevalence have a biological basis, and that reference intervals for those biomarkers should be tailored to ancestry. Specifically, our results point to a strong role of ancestry in insulin resistance and diabetes risk.


Assuntos
Proteínas Sanguíneas/genética , Grupos Populacionais/genética , Proteoma , Biomarcadores/metabolismo , Humanos
11.
Curr Diab Rep ; 20(1): 1, 2020 01 22.
Artigo em Inglês | MEDLINE | ID: mdl-31970540

RESUMO

PURPOSE OF REVIEW: Our review provides a brief summary of the most recent advances towards the identification of the genetic basis of specific aspects of obesity and the quantification of their consequences on health. We also highlight the most promising avenues to be explored in the future. RECENT FINDINGS: While obesity has been demonstrated to lead to adverse cardio-metabolic consequences, the determinants of inter-individual variability remain largely unknown. The elucidation of the molecular underpinnings of this relationship is hampered by the extremely heterogeneous nature of obesity as a human trait. Recent technological advances have facilitated a more in-depth characterization of body composition at large-scale. At the pace of current data acquisition and resolution, it is realistic to improve characterization of obesity and to advise individuals based on detailed body composition combined with tissue-specific molecular signatures. Individualized predictions of health implications would enable more personalized and effective public health interventions.


Assuntos
Adiposidade/fisiologia , Obesidade/genética , Obesidade/metabolismo , Adiposidade/genética , Composição Corporal/genética , Composição Corporal/fisiologia , Distribuição da Gordura Corporal , Índice de Massa Corporal , Heterogeneidade Genética , Humanos , Obesidade/complicações , Obesidade/diagnóstico , Fenótipo , Fatores Sexuais , Circunferência da Cintura/genética , Circunferência da Cintura/fisiologia
12.
Biol Psychiatry ; 87(5): 419-430, 2020 03 01.
Artigo em Inglês | MEDLINE | ID: mdl-31570195

RESUMO

BACKGROUND: The prevalence of depression is higher in individuals with autoimmune diseases, but the mechanisms underlying the observed comorbidities are unknown. Shared genetic etiology is a plausible explanation for the overlap, and in this study we tested whether genetic variation in the major histocompatibility complex (MHC), which is associated with risk for autoimmune diseases, is also associated with risk for depression. METHODS: We fine-mapped the classical MHC (chr6: 29.6-33.1 Mb), imputing 216 human leukocyte antigen (HLA) alleles and 4 complement component 4 (C4) haplotypes in studies from the Psychiatric Genomics Consortium Major Depressive Disorder Working Group and the UK Biobank. The total sample size was 45,149 depression cases and 86,698 controls. We tested for association between depression status and imputed MHC variants, applying both a region-wide significance threshold (3.9 × 10-6) and a candidate threshold (1.6 × 10-4). RESULTS: No HLA alleles or C4 haplotypes were associated with depression at the region-wide threshold. HLA-B*08:01 was associated with modest protection for depression at the candidate threshold for testing in HLA genes in the meta-analysis (odds ratio = 0.98, 95% confidence interval = 0.97-0.99). CONCLUSIONS: We found no evidence that an increased risk for depression was conferred by HLA alleles, which play a major role in the genetic susceptibility to autoimmune diseases, or C4 haplotypes, which are strongly associated with schizophrenia. These results suggest that any HLA or C4 variants associated with depression either are rare or have very modest effect sizes.

13.
Stat Methods Med Res ; 29(8): 2063-2073, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-31640504

RESUMO

In order to design efficient interventions aimed to improve public health, policy makers need to be provided with reliable information of the health burden of different risk factors. For this purpose, we are interested in the proportion of cases that could be prevented had some harmful exposure been eliminated from the population, i.e. the attributable fraction. The attributable fraction is a causal measure; thus, to estimate the attributable fraction from observational data, we have to make appropriate adjustment for confounding. However, some confounders may be unobserved, or even unknown to the investigator. A possible solution to this problem is to use instrumental variable analysis. In this work, we present how the attributable fraction can be estimated with instrumental variable methods based on the two-stage estimator or the G-estimator. One situation when the problem of unmeasuredconfounding may be particularly severe is when assessing the effect of low educational qualifications on coronary heart disease. By using Mendelian randomization, a special case of instrumental variable analysis, it has been claimed that low educational qualifications is a causal risk factor for coronary heart disease. We use Mendelian randomization to estimate the causal risk ratio and causal odds ratio of low educational qualifications as a risk factor for coronary heart disease with data from the UK Biobank. We compare the two-stage and G-estimator as well as the attributable fraction based on the two estimators. The plausibility of drawing causal conclusion in this analysis is thoroughly discussed and alternative genetic instrumental variables are tested.

14.
J Biol Chem ; 295(7): 1889-1897, 2020 02 14.
Artigo em Inglês | MEDLINE | ID: mdl-31862735

RESUMO

Sphingolipids (SLs) are structurally diverse lipids that are defined by the presence of a long-chain base (LCB) backbone. Typically, LCBs contain a single Δ4E double bond (DB) (mostly d18:1), whereas the dienic LCB sphingadienine (d18:2) contains a second DB at the Δ14Z position. The enzyme introducing the Δ14Z DB is unknown. We analyzed the LCB plasma profile in a gender-, age-, and BMI-matched subgroup of the CoLaus cohort (n = 658). Sphingadienine levels showed a significant association with gender, being on average ∼30% higher in females. A genome-wide association study (GWAS) revealed variants in the fatty acid desaturase 3 (FADS3) gene to be significantly associated with the plasma d18:2/d18:1 ratio (p = -log 7.9). Metabolic labeling assays, FADS3 overexpression and knockdown approaches, and plasma LCB profiling in FADS3-deficient mice confirmed that FADS3 is a bona fide LCB desaturase and required for the introduction of the Δ14Z double bond. Moreover, we showed that FADS3 is required for the conversion of the atypical cytotoxic 1-deoxysphinganine (1-deoxySA, m18:0) to 1-deoxysphingosine (1-deoxySO, m18:1). HEK293 cells overexpressing FADS3 were more resistant to m18:0 toxicity than WT cells. In summary, using a combination of metabolic profiling and GWAS, we identified FADS3 to be essential for forming Δ14Z DB containing LCBs, such as d18:2 and m18:1. Our results unravel FADS3 as a Δ14Z LCB desaturase, thereby disclosing the last missing enzyme of the SL de novo synthesis pathway.


Assuntos
Ácidos Graxos Dessaturases/genética , Estudo de Associação Genômica Ampla , Esfingolipídeos/genética , Animais , Ácidos Graxos Dessaturases/sangue , Células HEK293 , Humanos , Lipídeos/genética , Camundongos , Esfingolipídeos/sangue , Esfingosina/análogos & derivados , Esfingosina/metabolismo , Coluna Vertebral/metabolismo
15.
Am J Hum Genet ; 105(5): 947-958, 2019 11 07.
Artigo em Inglês | MEDLINE | ID: mdl-31668704

RESUMO

Human-specific duplications at chromosome 16p11.2 mediate recurrent pathogenic 600 kbp BP4-BP5 copy-number variations, which are among the most common genetic causes of autism. These copy-number polymorphic duplications are under positive selection and include three to eight copies of BOLA2, a gene involved in the maturation of cytosolic iron-sulfur proteins. To investigate the potential advantage provided by the rapid expansion of BOLA2, we assessed hematological traits and anemia prevalence in 379,385 controls and individuals who have lost or gained copies of BOLA2: 89 chromosome 16p11.2 BP4-BP5 deletion carriers and 56 reciprocal duplication carriers in the UK Biobank. We found that the 16p11.2 deletion is associated with anemia (18/89 carriers, 20%, p = 4e-7, OR = 5), particularly iron-deficiency anemia. We observed similar enrichments in two clinical 16p11.2 deletion cohorts, which included 6/63 (10%) and 7/20 (35%) unrelated individuals with anemia, microcytosis, low serum iron, or low blood hemoglobin. Upon stratification by BOLA2 copy number, our data showed an association between low BOLA2 dosage and the above phenotypes (8/15 individuals with three copies, 53%, p = 1e-4). In parallel, we analyzed hematological traits in mice carrying the 16p11.2 orthologous deletion or duplication, as well as Bola2+/- and Bola2-/- animals. The Bola2-deficient mice and the mice carrying the deletion showed early evidence of iron deficiency, including a mild decrease in hemoglobin, lower plasma iron, microcytosis, and an increased red blood cell zinc-protoporphyrin-to-heme ratio. Our results indicate that BOLA2 participates in iron homeostasis in vivo, and its expansion has a potential adaptive role in protecting against iron deficiency.


Assuntos
Anemia/genética , Transtorno Autístico/genética , Duplicação Cromossômica/genética , Cromossomos Humanos Par 16/genética , Homeostase/genética , Proteínas/genética , Animais , Deleção Cromossômica , Transtornos Cromossômicos/genética , Variações do Número de Cópias de DNA/genética , Feminino , Genótipo , Heterozigoto , Humanos , Ferro , Masculino , Fenótipo
17.
Nat Methods ; 16(9): 843-852, 2019 09.
Artigo em Inglês | MEDLINE | ID: mdl-31471613

RESUMO

Many bioinformatics methods have been proposed for reducing the complexity of large gene or protein networks into relevant subnetworks or modules. Yet, how such methods compare to each other in terms of their ability to identify disease-relevant modules in different types of network remains poorly understood. We launched the 'Disease Module Identification DREAM Challenge', an open competition to comprehensively assess module identification methods across diverse protein-protein interaction, signaling, gene co-expression, homology and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies. Our robust assessment of 75 module identification methods reveals top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets. This community challenge establishes biologically interpretable benchmarks, tools and guidelines for molecular network analysis to study human disease biology.


Assuntos
Biologia Computacional/métodos , Doença/genética , Redes Reguladoras de Genes , Estudo de Associação Genômica Ampla , Modelos Biológicos , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas , Algoritmos , Perfilação da Expressão Gênica , Humanos , Fenótipo , Mapas de Interação de Proteínas
19.
Nat Commun ; 10(1): 3300, 2019 07 24.
Artigo em Inglês | MEDLINE | ID: mdl-31341166

RESUMO

Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene-trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits.


Assuntos
Estudo de Associação Genômica Ampla , Locos de Características Quantitativas , Encefalopatias/genética , Subunidades gama da Proteína de Ligação ao GTP , Perfilação da Expressão Gênica , Predisposição Genética para Doença , Variação Genética , Humanos , Análise da Randomização Mendeliana , Fenótipo , Polimorfismo de Nucleotídeo Único , Transcriptoma
20.
PLoS Comput Biol ; 15(7): e1007162, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31269015

RESUMO

The evolutionarily conserved nature of the few well-known anti-aging interventions that affect lifespan, such as caloric restriction, suggests that aging-related research in model organisms is directly relevant to human aging. Since human lifespan is a complex trait, a systems-level approach will contribute to a more comprehensive understanding of the underlying aging landscape. Here, we integrate evolutionary and functional information of normal aging across human and model organisms at three levels: gene-level, process-level, and network-level. We identify evolutionarily conserved modules of normal aging across diverse taxa, and notably show proteostasis to be conserved in normal aging. Additionally, we find that mechanisms related to protein quality control network are enriched for genes harboring genetic variants associated with 22 age-related human traits and associated to caloric restriction. These results demonstrate that a systems-level approach, combined with evolutionary conservation, allows the detection of candidate aging genes and pathways relevant to human normal aging.


Assuntos
Envelhecimento/metabolismo , Proteostase , Adulto , Idoso , Envelhecimento/genética , Animais , Caenorhabditis elegans , Restrição Calórica , Biologia Computacional , Drosophila melanogaster , Evolução Molecular , Feminino , Perfilação da Expressão Gênica , Marcadores Genéticos , Humanos , Longevidade/genética , Longevidade/fisiologia , Masculino , Camundongos , Pessoa de Meia-Idade , Modelos Biológicos , Proteostase/genética , Especificidade da Espécie , Adulto Jovem
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