@article {91, title = {Assessing Digital Phenotyping to Enhance Genetic Studies of Human Diseases.}, journal = {Am J Hum Genet}, volume = {106}, year = {2020}, month = {2020 05 07}, pages = {611-622}, abstract = {

Population-scale biobanks that combine genetic data and high-dimensional phenotyping for a large number of participants provide an exciting opportunity to perform genome-wide association studies (GWAS) to identify genetic variants associated with diverse quantitative traits and diseases. A major challenge for GWAS in population biobanks is ascertaining disease cases from heterogeneous data sources such as hospital records, digital questionnaire responses, or interviews. In this study, we use genetic parameters, including genetic correlation, to evaluate whether GWAS performed using cases in the UK Biobank ascertained from hospital records, questionnaire responses, and family history of disease implicate similar disease genetics across a range of effect sizes. We find that hospital record and questionnaire GWAS largely identify similar genetic effects for many complex phenotypes and that combining together both phenotyping methods improves power to detect genetic associations. We also show that family history GWAS using cases ascertained on family history of disease agrees with combined hospital record and questionnaire GWAS and that family history GWAS has better power to detect genetic associations for some phenotypes. Overall, this work demonstrates that digital phenotyping and unstructured phenotype data can be combined with structured data such as hospital records to identify cases for GWAS in biobanks and improve the ability of such studies to identify genetic associations.

}, keywords = {Asthma, Databases, Factual, Disease, Female, Genetics, Medical, Genome-Wide Association Study, Genotype, Humans, Male, Neoplasms, Phenotype, United Kingdom}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2020.03.007}, author = {DeBoever, Christopher and Tanigawa, Yosuke and Aguirre, Matthew and McInnes, Greg and Lavertu, Adam and Rivas, Manuel A} } @article {66, title = {Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology.}, journal = {Nat Commun}, volume = {10}, year = {2019}, month = {2019 Sep 06}, pages = {4064}, abstract = {

Population-based biobanks with genomic and dense phenotype data provide opportunities for generating effective therapeutic hypotheses and understanding the genomic role in disease predisposition. To characterize latent components of genetic associations, we apply truncated singular value decomposition (DeGAs) to matrices of summary statistics derived from genome-wide association analyses across 2,138 phenotypes measured in 337,199 White British individuals in the UK Biobank study. We systematically identify key components of genetic associations and the contributions of variants, genes, and phenotypes to each component. As an illustration of the utility of the approach to inform downstream experiments, we report putative loss of function variants, rs114285050 (GPR151) and rs150090666 (PDE3B), that substantially contribute to obesity-related traits and experimentally demonstrate the role of these genes in adipocyte biology. Our approach to dissect components of genetic associations across the human phenome will accelerate biomedical hypothesis generation by providing insights on previously unexplored latent structures.

}, issn = {2041-1723}, doi = {10.1038/s41467-019-11953-9}, author = {Tanigawa, Yosuke and Li, Jiehan and Justesen, Johanne M and Horn, Heiko and Aguirre, Matthew and DeBoever, Christopher and Chang, Chris and Narasimhan, Balasubramanian and Lage, Kasper and Hastie, Trevor and Park, Chong Y and Bejerano, Gill and Ingelsson, Erik and Rivas, Manuel A} } @article {28, title = {Medical relevance of protein-truncating variants across 337,205 individuals in the UK Biobank study.}, journal = {Nat Commun}, volume = {9}, year = {2018}, month = {2018 04 24}, pages = {1612}, abstract = {

Protein-truncating variants can have profound effects on gene function and are critical for clinical genome interpretation and generating therapeutic hypotheses, but their relevance to medical phenotypes has not been systematically assessed. Here, we characterize the effect of 18,228 protein-truncating variants across 135 phenotypes from the UK Biobank and find 27 associations between medical phenotypes and protein-truncating variants in genes outside the major histocompatibility complex. We perform phenome-wide analyses and directly measure the effect in homozygous carriers, commonly referred to as "human knockouts," across medical phenotypes for genes implicated as being protective against disease or associated with at least one phenotype in our study. We find several genes with strong pleiotropic or non-additive effects. Our results illustrate the importance of protein-truncating variants in a variety of diseases.

}, keywords = {Databases, Nucleic Acid, Genome-Wide Association Study, Humans, Phenotype, Proteins, Sequence Deletion, United Kingdom}, issn = {2041-1723}, doi = {10.1038/s41467-018-03910-9}, author = {DeBoever, Christopher and Tanigawa, Yosuke and Lindholm, Malene E and McInnes, Greg and Lavertu, Adam and Ingelsson, Erik and Chang, Chris and Ashley, Euan A and Bustamante, Carlos D and Daly, Mark J and Rivas, Manuel A} }