Expressive

rs10054063 - CPEB4 - C5orf47

Magnitude 2.2 · 6 studies on file

Reported associations

  • Inference of chronic obstructive pulmonary disease with deep learning on raw spirograms identifies new genetic loci and improves risk models. - Nature genetics (2023) · Cosentino J, Behsaz B, Alipanahi B, McCaw ZR, Hill D, Schwantes-An TH, Lai D, Carroll A, Hobbs BD, Cho MH, McLean CY, Hormozdiari F · PubMed 37069358

    Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, is highly heritable. While COPD is clinically defined by applying thresholds to summary measures of lung function, a quantitative liability score has more power to identify genetic signals. Here we train a deep convolutional neural network on noisy self-reported and International Classification of Diseases labels to predict COPD case-control status from high-dimensional raw spirograms and use the model's predictions as a liability score. The machine-learning-based (ML-based) liability score accurately discriminates COPD cases and controls, and predicts COPD-related hospitalization without any domain-specific knowledge. Moreover, the ML-based liability score is associated with overall survival and exac

  • Leveraging Polygenic Functional Enrichment to Improve GWAS Power. - American journal of human genetics (2019) · Kichaev G, Bhatia G, Loh PR, Gazal S, Burch K, Freund MK, Schoech A, Pasaniuc B, Price AL · PubMed 30595370

    Functional genomics data has the potential to increase GWAS power by identifying SNPs that have a higher prior probability of association. Here, we introduce a method that leverages polygenic functional enrichment to incorporate coding, conserved, regulatory, and LD-related genomic annotations into association analyses. We show via simulations with real genotypes that the method, functionally informed novel discovery of risk loci (FINDOR), correctly controls the false-positive rate at null loci and attains a 9%-38% increase in the number of independent associations detected at causal loci, depending on trait polygenicity and sample size. We applied FINDOR to 27 independent complex traits and diseases from the interim UK Biobank release (average N = 130K). Averaged across traits, we attaine

  • Heritability informed power optimization (HIPO) leads to enhanced detection of genetic associations across multiple traits - Unknown journal (n.d.) · Unknown authors · PubMed 30289880

    ABSTRACT: Genome-wide association studies have shown that pleiotropy is a common phenomenon that can potentially be exploited for enhanced detection of susceptibility loci. We propose heritability informed power optimization (HIPO) for conducting powerful pleiotropic analysis using summary-level association statistics. We find optimal linear combinations of association coefficients across traits that are expected to maximize non-centrality parameter for the underlying test statistics, taking into account estimates of heritability, sample size variations and overlaps across the traits. Simulation studies show that the proposed method has correct type I error, robust to population stratification and leads to desired genome-wide enrichment of association signals. Application of the proposed m

  • Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry - Unknown journal (n.d.) · Unknown authors · PubMed 30239722

    ABSTRACT: Abstract More than one in three adults worldwide is either overweight or obese. Epidemiological studies indicate that the location and distribution of excess fat, rather than general adiposity, are more informative for predicting risk of obesity sequelae, including cardiometabolic disease and cancer. We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio (WHR) adjusted for body mass index (WHRadjBMI), and identified 463 signals in 346 loci. Heritability and variant effects were generally stronger in women than men, and we found approximately one-third of all signals to be sexually dimorphic. The 5% of individuals carrying the most WHRadjBMI-increasing alleles were 1.62 times more likely than the bottom 5% to have a WHR

  • Inherited basis of visceral, abdominal subcutaneous and gluteofemoral fat depots - Unknown journal (n.d.) · Unknown authors · PubMed 35773277

    ABSTRACT: For any given level of overall adiposity, individuals vary considerably in fat distribution. The inherited basis of fat distribution in the general population is not fully understood. Here, we study up to 38,965 UK Biobank participants with MRI-derived visceral (VAT), abdominal subcutaneous (ASAT), and gluteofemoral (GFAT) adipose tissue volumes. Because these fat depot volumes are highly correlated with BMI, we additionally study six local adiposity traits: VAT adjusted for BMI and height (VATadj), ASATadj, GFATadj, VAT/ASAT, VAT/GFAT, and ASAT/GFAT. We identify 250 independent common variants (39 newly-identified) associated with at least one trait, with many associations more pronounced in female participants. Rare variant association studies extend prior evidence for PDE3B as

  • A genetic map of human metabolism across the allele frequency spectrum - Unknown journal (n.d.) · Unknown authors · PubMed 41044249

    ABSTRACT: Genetic studies of human metabolism have been limited in scale and allelic breadth. Here we provide a data-driven map of the genetic regulation of circulating small molecules and lipoprotein characteristics (249 traits) measured using proton nuclear magnetic resonance spectroscopy across the allele frequency spectrum in ~450,000 individuals. Trans-ancestral meta-analyses identify 29,824 locus-metabolite associations mapping to 753 regions with effects largely consistent between men and women and large ancestral groups represented in UK Biobank. We observe and classify extreme genetic pleiotropy, identify regulators of lipid metabolism, and assign effector genes at >100 loci through rare-to-common allelic series. We propose roles for genes less established in metabolic control (

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