Journal Article

Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits

Mägi, Reedik, Rönnegård, Lars, Kousathanas, Athanasios, Visscher, Peter M., Ojavee, Sven E., Banos, Daniel Trejo, Holloway, Alexander, Kutalik, Zoltan, Sidorenko, Julia, Orliac, Etienne J., Patxot, Marion, Moser, Gerhard, Robinson, Matthew R.

2021

Overview

We develop a Bayesian model (BayesRR-RC) that provides robust SNP-heritability estimation, an alternative to marker discovery, and accurate genomic prediction, taking 22 seconds per iteration to estimate 8.4 million SNP-effects and 78 SNP-heritability parameters in the UK Biobank. We find that only ≤10% of the genetic variation captured for height, body mass index, cardiovascular disease, and type 2 diabetes is attributable to proximal regulatory regions within 10kb upstream of genes, while 12-25% is attributed to coding regions, 32–44% to introns, and 22-28% to distal 10-500kb upstream regions. Up to 24% of all cis and coding regions of each chromosome are associated with each trait, with over 3,100 independent exonic and intronic regions and over 5,400 independent regulatory regions having ≥95% probability of contributing ≥0.001% to the genetic variance of these four traits. Our open-source software (GMRM) provides a scalable alternative to current approaches for biobank data. Improving inference in large-scale genetic data linked to electronic medical record data requires the development of novel computationally efficient regression methods. Here, the authors develop a Bayesian approach for association analyses to improve SNP-heritability estimation, discovery, fine-mapping and genomic prediction.

• Publisher: Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
• Subject: 631/114/2415 / 631/114/794 / 631/208/205/2138 / Bayes Theorem / Bayesian analysis / Biobanks / Bioinformatics (Computational Biology) / Bioinformatik (beräkningsbiologi) / Body Height / Body Mass Index / Body size / Cardiovascular Diseases / Chromosomes / Diabetes mellitus (non-insulin dependent) / Diabetes Mellitus, Type 2 / Electronic health records / Electronic medical records / Gene mapping / Genetic diversity / Genetic Techniques / Genetic variance / Genetic Variation / Genetics / Genetik / Genome-Wide Association Study / Genomics / Genotype / Heritability / Humanities and Social Sciences / Humans / Introns / Iterative methods / Models, Statistical / multidisciplinary / Multifactorial Inheritance - genetics / Open Reading Frames / Phenotype / Probabilistic inference / Regulatory sequences / Science / Science (multidisciplinary) / Single-nucleotide polymorphism / Software / Source code / Statistical analysis