Understanding the impact of rare variants is essential to understanding human health. We analyze rare (MAF < 0.1%) variants against 4264 phenotypes in 49,960 exome-sequenced individuals from the UK Biobank and 1934 phenotypes (1821 overlapping with UK Biobank) in 21,866 members of the Healthy Nevada Project (HNP) cohort who underwent Exome + sequencing at Helix. After using our rare-variant-tailored methodology to reduce test statistic inflation, we identify 64 statistically significant gene-based associations in our meta-analysis of the two cohorts and 37 for phenotypes available in only one cohort. Singletons make significant contributions to our results, and the vast majority of the associations could not have been identified with a genotyping chip. Our results are available for interactive browsing in a webapp (https://ukb.research.helix.com). This comprehensive analysis illustrates the biological value of large, deeply phenotyped cohorts of unselected populations coupled with NGS data.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6987107PMC
http://dx.doi.org/10.1038/s41467-020-14288-yDOI Listing

Publication Analysis

Top Keywords

genome-wide rare
4
rare variant
4
variant analysis
4
analysis thousands
4
thousands phenotypes
4
phenotypes 70000
4
70000 exomes
4
exomes cohorts
4
cohorts understanding
4
understanding impact
4

Similar Publications

Limited whole genome sequencing (WGS) studies in Asian populations result in a lack of representative reference panels, thus hindering the discovery of ancestry-specific variants. Here, we present the South and East Asian reference Database (SEAD) panel ( https://imputationserver.westlake.

View Article and Find Full Text PDF

Neurodegenerative diseases present complex genetic architectures, reflecting a continuum from monogenic to oligogenic and polygenic models. Recent advances in multi-omics data, coupled with systems genetics, have significantly refined our understanding of how these data impact neurodegenerative disease mechanisms. To contextualize these genetic discoveries, we provide a comprehensive critical overview of genetic architecture concepts, from Mendelian inheritance to the latest insights from oligogenic and omnigenic models.

View Article and Find Full Text PDF

Plant AT-rich protein and zinc-binding protein (PLATZ) family in Dendrobium huoshanense: identification, evolution and expression analysis.

BMC Plant Biol

December 2024

Henan Key Laboratory of Rare Diseases, Endocrinology and Metabolism Center, The First Affiliated Hospital, College of Clinical Medicine of Henan, University of Science and Technology, Luoyang, 471003, China.

PLATZ (plant A/T-rich protein and zinc-binding protein) transcription factors are essential for plant growth, development, and responses to abiotic stress. The regulatory role of PLATZ genes in the environmental adaptation of D. huoshanense is inadequately comprehended.

View Article and Find Full Text PDF

Background: The 313-variant polygenic risk score (PRS) provides a promising tool for clinical breast cancer risk prediction. However, evaluation of the PRS across different European populations which could influence risk estimation has not been performed.

Methods: We explored the distribution of PRS across European populations using genotype data from 94,072 females without breast cancer diagnosis, of European-ancestry from 21 countries participating in the Breast Cancer Association Consortium (BCAC) and 223,316 females without breast cancer diagnosis from the UK Biobank.

View Article and Find Full Text PDF

There is growing evidence that a wide range of human diseases and physiological traits are influenced by genetic variation of cis-regulatory elements. We and others have shown that a subset of promoter elements, termed Epromoters, also function as enhancer regulators of distal genes. This opens a paradigm in the study of regulatory variants, as single nucleotide polymorphisms (SNPs) within Epromoters might influence the expression of several (distal) genes at the same time, which could disentangle the identification of disease-associated genes.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!