hum0541-v1Release info

Personalized Medicine Based on Genomic Data

Aims

Elucidating the association between an individual's genetic architecture, including polymorphisms, and their susceptibility to disease and complex phenotypes is fundamental to the advancement of precision medicine. This study integrates biospecimens, clinical information, and previously generated research data from BioBnk Japan (BBJ), the National Center for Geriatrics and Gerontology (NCGG), and the Tohoku Medical Megabank Organization (ToMMo) to systematically characterize genetic associations across diverse human traits and phenotypes.

Methods

Clinical data were subjected to quality control, and outliers were removed. Phenotypic values were corrected for the effects of medication use, including lipid-lowering and antihypertensive therapies, and users of specific medications were excluded from specific analyses. Phenotypes were adjusted for age, sex, and principal components using linear regression models. The residuals were transformed using inverse rank normalization to generate the final phenotype dataset (63 phenotypes). Association analyses between these phenotypes and imputed genetic variants, generated using a Japanese reference panel, were performed using BOLT-LMM.

Participants/materials

The phenotype matrix for the QTL analysis contains 63 phenotypes from the BioBank Japan (BBJ) cohort 1 (N = 176,894)

URL

• https://c-teraolab.com/ (opens in a new tab)

Principal investigator

Chikashi Terao

Affiliation

Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences