Chromosome Mapping ; Genome-Wide Association Study ; methods ; Humans

Genome-Wide Association Study ; Genotype ; Humans ; Molecular Epidemiology ; methods

Bipolar Disorder ; genetics ; Genome-Wide Association Study ; Genomics ; methods ; Humans

Next-generation sequencing has revolutionized family-based association tests for rare variants. As the lower power of genome wide association study for detecting casual rare variants, methods aggregating effects of multiple variants have been proposed, such as burden tests and variance component tests. This paper summarizes the methods of rare variants association test that can be applied for family data, introduces their principles, characteristics and applicable conditions and discusses the shortcomings and the improvement of the present methods.
Computer Simulation ; Family Relations ; Genetic Association Studies ; Genetic Variation ; Genome-Wide Association Study/methods* ; Humans

China ; Genes, Neoplasm ; Genome, Human ; Genome-Wide Association Study ; methods ; Humans ; Neoplasms ; genetics ; Polymorphism, Single Nucleotide

"Active health" has been emphasized in "Healthy China 2030" in dealing with the challenges of population aging, so the anti-aging strategies are requires to be more precise and effective at both individual and population levels. Aging is influenced by both genetic and environmental factors. In the recent 20 years, the research of genetics of human ageing has been greatly facilitated owning to the development of high-throughput sequencing techniques, statistical methodology for multi-omics data, as well as the growing qualified evidence of large-scale population-based genomic research. This paper provides a review of genome-wide association research of aging.
Aging/genetics* ; Genome-Wide Association Study/methods* ; Genomics/methods* ; High-Throughput Nucleotide Sequencing ; Humans ; Phenotype

The meta-analysis has become a widely used tool for many applications in bioinformatics, including genome-wide association studies. A commonly used approach for meta-analysis is the fixed effects model approach, for which there are two popular methods: the inverse variance-weighted average method and weighted sum of z-scores method. Although previous studies have shown that the two methods perform similarly, their characteristics and their relationship have not been thoroughly investigated. In this paper, we investigate the optimal characteristics of the two methods and show the connection between the two methods. We demonstrate that the each method is optimized for a unique goal, which gives us insight into the optimal weights for the weighted sum of z-scores method. We examine the connection between the two methods both analytically and empirically and show that their resulting statistics become equivalent under certain assumptions. Finally, we apply both methods to the Wellcome Trust Case Control Consortium data and demonstrate that the two methods can give distinct results in certain study designs.
Case-Control Studies ; Computational Biology ; Genome-Wide Association Study ; Methods* ; Weights and Measures

Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still exits limitations in explaining the missing heritability. One approach to solving this missing heritability problem is to investigate gene-gene interactions, rather than a single-locus approach. For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely applied, since the constructive induction algorithm of MDR efficiently reduces high-order dimensions into one dimension by classifying multi-level genotypes into high- and low-risk groups. The MDR method has been extended to various phenotypes and has been improved to provide a significance test for gene-gene interactions. In this paper, we propose a simple method, called accelerated failure time (AFT) UM-MDR, in which the idea of a unified model-based MDR is extended to the survival phenotype by incorporating AFT-MDR into the classification step. The proposed AFT UM-MDR method is compared with AFT-MDR through simulation studies, and a short discussion is given.
Classification ; Genome-Wide Association Study ; Genotype ; Methods* ; Multifactor Dimensionality Reduction* ; Phenotype

Mosaic chromosomal alteration (mCA) is referred to as large-scale somatic mutations on chromosomes, which results in diverse karyotypes in body. The mCA is regarded as one of the phenotypes of aging. Studies have revealed its associations with many chronic diseases such as hematopoietic cancers and cardiovascular diseases, but its genetic basis (e.g. genetic susceptibility variants) is still under-investigated. This paper reviews GWAS studies for mCA on autosomal chromosomes and sex chromosomes [mosaic loss of the Y chromosome (mLOY) and mosaic loss of the X chromosome (mLOX)] based on large population, respectively. Most of the genetic susceptibility loci found in studies for autosomal mCA were associated with copy-neutral loss of heterozygosity. The study of sex chromosome mCA focused on mosaic loss mutations. The number of genetic susceptibility loci for mLOY was high (up to 156), but it was relatively less for mLOX.
Humans ; Male ; Genome-Wide Association Study/methods* ; Mosaicism ; Genetic Predisposition to Disease ; Chromosomes, Human, Y ; Mutation

Chronic obstructive pulmonary disease (COPD) is a common and frequently-occurring disease in the department of respiratory medicine,the pathogenesis of which involves both environmental factors and genetic factors.In recent years,with the application of new methods such as genome-wide association study,researchers have discovered a large number of gene mutations associated with lung function and COPD,providing a new perspective on the pathogenesis of COPD and potential therapeutic targets.This article reviews the research achievements and application progress of genomics in COPD.
Genome-Wide Association Study/methods* ; Genomics ; Humans ; Pulmonary Disease, Chronic Obstructive/genetics*