ABSTRACT
We constructed an age-to-age infection matrix to characterize the household transmission pattern of coronavirus disease 2019 (COVID-19) in Korea. Among 4,048 household clusters, within-age group infection dominated the overall household transmissions. Transmission of severe acute respiratory syndrome coronavirus 2 was more common from adults to children than from children to adults.
ABSTRACT
We constructed an age-to-age infection matrix to characterize the household transmission pattern of coronavirus disease 2019 (COVID-19) in Korea. Among 4,048 household clusters, within-age group infection dominated the overall household transmissions. Transmission of severe acute respiratory syndrome coronavirus 2 was more common from adults to children than from children to adults.
ABSTRACT
Over the last decade, genome-wide association studies (GWASs) have provided an unprecedented amount of genetic variations that are associated with various phenotypes. However, previous GWAS were mostly conducted in European populations, and these biased results for non-Europeans may result in a significant reduction in risk prediction for non-Europeans. An issue with the early GWAS was the winner's curse problem, which led to misleading results when constructing the polygenic risk scores (PRS). Therefore, more non-European population-based studies are needed to validate reported variants and improve genetic risk assessment across diverse populations. In this study, we validated 422 variants independently associated with glycemic indexes, liver enzymes, and type 2 diabetes in 125,872 samples from a Korean population, and further validated the results by assessing publicly available summary statistics from European GWAS (n = 898,130). Among the 422 independently associated variants, 284, 320, and 361 variants were replicated in Koreans, Europeans, and either one of the two populations. In addition, the effect sizes for Koreans and Europeans were moderately correlated (r = 0.33–0.68). However, 61 variants were not replicated in both Koreans and Europeans. Our findings provide valuable information on effect sizes and statistical significance, which is essential to improve the assessment of disease risk using PRS analysis.
ABSTRACT
Over the last decade, genome-wide association studies (GWASs) have provided an unprecedented amount of genetic variations that are associated with various phenotypes. However, previous GWAS were mostly conducted in European populations, and these biased results for non-Europeans may result in a significant reduction in risk prediction for non-Europeans. An issue with the early GWAS was the winner's curse problem, which led to misleading results when constructing the polygenic risk scores (PRS). Therefore, more non-European population-based studies are needed to validate reported variants and improve genetic risk assessment across diverse populations. In this study, we validated 422 variants independently associated with glycemic indexes, liver enzymes, and type 2 diabetes in 125,872 samples from a Korean population, and further validated the results by assessing publicly available summary statistics from European GWAS (n = 898,130). Among the 422 independently associated variants, 284, 320, and 361 variants were replicated in Koreans, Europeans, and either one of the two populations. In addition, the effect sizes for Koreans and Europeans were moderately correlated (r = 0.33–0.68). However, 61 variants were not replicated in both Koreans and Europeans. Our findings provide valuable information on effect sizes and statistical significance, which is essential to improve the assessment of disease risk using PRS analysis.
Subject(s)
Humans , Asian People , Bias , Genetic Variation , Genome-Wide Association Study , Glycemic Index , Liver , Phenotype , Polymorphism, Single Nucleotide , Risk AssessmentABSTRACT
Biomarkers are characteristic biological properties that can be detected and measured in a variety of biological matrices in the human body, including the blood and tissue, to give an indication of whether there is a threat of disease, if a disease already exists, or how such a disease may develop in an individual case. Along the continuum from exposure to clinical disease and progression, exposure, internal dose, biologically effective dose, early biological effect, altered structure and/or function, clinical disease, and disease progression can potentially be observed and quantified using biomarkers. While the traditional discovery of biomarkers has been a slow process, the advent of molecular and genomic medicine has resulted in explosive growth in the discovery of new biomarkers. In this review, issues in evaluating biomarkers will be discussed and the biomarkers of environmental exposure, early biologic effect, and susceptibility identified and validated in epidemiological studies will be summarized. The spectrum of genomic approaches currently used to identify and apply biomarkers and strategies to validate genomic biomarkers will also be discussed.