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Genomic analysis of diet composition finds novel loci and associations with health and lifestyle.

ABSTRACT: We conducted genome-wide association studies (GWAS) of relative intake from the macronutrients fat, protein, carbohydrates, and sugar in over 235,000 individuals of European ancestries. We identified 21 unique, approximately independent lead SNPs. Fourteen lead SNPs are uniquely associated with one macronutrient at genome-wide significance (P < 5 × 10^-8), while five of the 21 lead SNPs reach suggestive significance (P < 1 × 10^-5) for at least one other macronutrient. While the phenotypes are genetically correlated, each phenotype carries a partially unique genetic architecture. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (r_g ≈ 0.15-0.5). In contrast, relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood deprivation (|r_g| ≈ 0.1-0.3) and positive genetic correlations with physical activity (r_g ≈ 0.1 and 0.2). Relative fat intake has no consistent pattern of genetic correlations with poor health but has a negative genetic correlation with educational attainment (r_g ≈-0.1). Although our analyses do not allow us to draw causal conclusions, we find no evidence of negative health consequences associated with relative carbohydrate, sugar, or fat intake. However, our results are consistent with the hypothesis that relative protein intake plays a role in the etiology of metabolic dysfunction.

SUBMITTER: Meddens SFW

PROVIDER: S-EPMC7767645 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Genomic analysis of diet composition finds novel loci and associations with health and lifestyle.

Meddens S Fleur W SFW de Vlaming Ronald R Bowers Peter P Burik Casper A P CAP Linnér Richard Karlsson RK Lee Chanwook C Okbay Aysu A Turley Patrick P Rietveld Cornelius A CA Fontana Mark Alan MA Ghanbari Mohsen M Imamura Fumiaki F McMahon George G van der Most Peter J PJ Voortman Trudy T Wade Kaitlin H KH Anderson Emma L EL Braun Kim V E KVE Emmett Pauline M PM Esko Tonũ T Gonzalez Juan R JR Kiefte-de Jong Jessica C JC Langenberg Claudia C Luan Jian'an J Muka Taulant T Ring Susan S Rivadeneira Fernando F Snieder Harold H van Rooij Frank J A FJA Wolffenbuttel Bruce H R BHR Smith George Davey GD Franco Oscar H OH Forouhi Nita G NG Ikram M Arfan MA Uitterlinden Andre G AG van Vliet-Ostaptchouk Jana V JV Wareham Nick J NJ Cesarini David D Harden K Paige KP Lee James J JJ Benjamin Daniel J DJ Chow Carson C CC Koellinger Philipp D PD

Molecular psychiatry 20200511 6

We conducted genome-wide association studies (GWAS) of relative intake from the macronutrients fat, protein, carbohydrates, and sugar in over 235,000 individuals of European ancestries. We identified 21 unique, approximately independent lead SNPs. Fourteen lead SNPs are uniquely associated with one macronutrient at genome-wide significance (P < 5 × 10<sup>-8</sup>), while five of the 21 lead SNPs reach suggestive significance (P < 1 × 10<sup>-5</sup>) for at least one other macronutrient. While ...[more]

PMID: 32393786

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Project description:Researchers studying behavioral and physiologic effects of d-amphetamine have explored individual response differences to the drug. Concurrently, genome-wide analyses have identified several single-nucleotide polymorphisms (SNPs) associated with these traits. Univariate methods can identify SNPs associated with behavioral and physiological traits, but multivariate analyses allow identification of clusters of related biologically relevant SNPs and behavioral components.The aim of the study was to identify clusters of related biologically relevant SNPs and behavioral components in the responses of healthy individuals to d-amphetamine using multivariate analysis.Individuals (N?=?375) without substance abuse histories completed surveys and detailed cardiovascular monitoring during randomized, blinded sessions: d-amphetamine (10 and 20 mg) and placebo. We applied parallel independent component analysis (Para-ICA) to data previously analyzed with univariate approaches, revealing new associations between genes and behavioral responses to d-amphetamine.Three significantly associated (p?<?.001) phenotype-genotype pairs emerged. The first component included physiologic measures of systolic and diastolic blood pressure (BP) and mean arterial pressure (MAP) along with SNPs in calcium and glutamatergic signaling pathways. The second associated components included the "Anger" items from the Profile of Mood States (POMS) questionnaire and the marijuana effects from the Addiction Research Center Inventory (Cuyas, Verdejo-Garcia et al.), with enriched genetic pathways involved in cardiomyopathy and MAPK signaling. The final pair included "Anxious," "Fatigue," and "Confusion" items from the POMS questionnaire, plus functional pathways related to cardiac muscle contraction and cardiomyopathy.Multifactorial genetic networks related to calcium signaling, glutamatergic and dopaminergic synapse function, and amphetamine addiction appear to mediate common behavioral and cardiovascular responses to d-amphetamine.

Project description:BackgroundBacterial carbohydrate metabolism is extremely diverse, since carbohydrates serve as a major energy source and are involved in a variety of cellular processes. Bacterial genes belonging to same metabolic pathway are often co-localized in the chromosome, but it is not a strict rule. Gene co-localization in linked to co-evolution and co-regulation. This study focuses on a large-scale analysis of bacterial genomic loci related to the carbohydrate metabolism.ResultsWe demonstrate that only 53% of 148,000 studied genes from over six hundred bacterial genomes are co-localized in bacterial genomes with other carbohydrate metabolism genes, which points to a significant role of singleton genes. Co-localized genes form cassettes, ranging in size from two to fifteen genes. Two major factors influencing the cassette-forming tendency are gene function and bacterial phylogeny. We have obtained a comprehensive picture of co-localization preferences of genes for nineteen major carbohydrate metabolism functional classes, over two hundred gene orthologous clusters, and thirty bacterial classes, and characterized the cassette variety in size and content among different species, highlighting a significant role of short cassettes. The preference towards co-localization of carbohydrate metabolism genes varies between 40 and 76% for bacterial taxa. Analysis of frequently co-localized genes yielded forty-five significant pairwise links between genes belonging to different functional classes. The number of such links per class range from zero to eight, demonstrating varying preferences of respective genes towards a specific chromosomal neighborhood. Genes from eleven functional classes tend to co-localize with genes from the same class, indicating an important role of clustering of genes with similar functions. At that, in most cases such co-localization does not originate from local duplication events.ConclusionsOverall, we describe a complex web formed by evolutionary relationships of bacterial carbohydrate metabolism genes, manifested as co-localization patterns.ReviewersThis article was reviewed by Daria V. Dibrova (A.N. Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Moscow, Russia), nominated by Armen Mulkidjanian (University of Osnabrück, Germany), Igor Rogozin (NCBI, NLM, NIH, USA) and Yuri Wolf (NCBI, NLM, NIH, USA).

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Genomic analysis of diet composition finds novel loci and associations with health and lifestyle.

Publications

Genomic analysis of diet composition finds novel loci and associations with health and lifestyle.

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