Clinical laboratory measurements, such as the results from blood tests, can be powerful because such quantitative phenotypes (traits) are useful in diagnosing and monitoring human diseases. Clarification of the underlying genetics, as well as inference of genetic relationships to diseases and implicated cell-types, can provide clues about disease biology. To this end, hundreds of laboratories have now carried out thousands of genome-wide association studies (GWAS) to investigate various quantitative traits –– including anthropometric (e.g. height, body mass index), metabolic (e.g. blood lipid, hemoglobin 1Ac levels), kidney-related (e.g. blood urea nitrogen, creatinine), hematological (e.g. white cell differential, hemoglobin), and blood pressure (e.g. systolic, diastolic BP in response to stress or a drug) traits.
The interplay between genetics of quantitative traits and diseases has been assessed by several approaches –– such as pleiotropy (contribution of one gene to two or more seemingly unrelated traits), genetic correlation (e.g. relationship between anorexia nervosa and schizophrenia), and Mendelian randomization (method that uses genetic variants that are robustly associated with modifiable exposures –– such as to an environmental toxicant or dose of a drug –– to generate more reliable evidence regarding which treatment response might be best). For example, recent large-scale studies of body mass index (BMI), a key measure for assessing obesity, revealed shared genetic effects on metabolic traits and the involvement of central nervous system and immune cells in determining risk of obesity. However, previous studies almost always have screened subjects of European ancestry, and each study focused separately on one or a very few quantitative traits. For the creation of a comprehensive landscape in personalized medicine, additional studies of non-European populations are necessary that simultaneously investigate a wide range of clinical measurements and extensively probe their relevance to complex diseases.
Authors [see attached report] describe (amazingly) a GWAS of 58 quantitative traits in 162,255 Japanese individuals from the BioBank Japan Project (BBJ), one of the largest non-European single-descent biobanks with detailed phenotypes (traits) –– in order to broaden the current knowledge and understanding of the genetics and biology of these traits. Moreover, authors incorporated additional GWAS of complex diseases and traits in Japanese subjects, and then evaluated pleiotropy, genetic correlation, and cell-type specificity with respect to each of these quantitative traits. These extensive data provide many new insights into the genetic basis of various quantitative traits and illuminate the complex genetic links among clinical measurements, complex diseases, and relevant cell-types. This thorough study demonstrates that, even without prior biological knowledge of cross-phenotype relationships, the genetics corresponding to clinical measurements can successfully recapture the relevance of these measurements to diseases, and thus can contribute to our understanding of unknown etiology and pathogenesis of many of these diseases.
Nature Genet Mar 2o18; 50: 390–400