The largest exome sequencing in history! These genes are related to diabetes

A large-scale data study on type 2 diabetes was published online today in the leading academic journal Nature, with hundreds of scientists from around the world joining forces to challenge the genetic risks of the complex diseasethe study' other prosonsequencing techniques, nearly 50,000 people were analyzed for protein coding genes and identifying new rare variants associated with type 2 diabetesThis finding may help improve the profiling and treatment of type 2 diabetes,000-author DrJason Flannick is a member of the Harvard-MIT Broad Institute, which works to use human genetics and broader histological data to deepen understanding of human diseases and promote treatmentType 2 diabetes is one of his prioritiesHe has played a leading role in several national and international genetics and bioinformatics alliances exploring the risks of diabetes, including promoting the development of a public knowledge portal on type 2 diabetes, which will make relevant human genetic data widely available to the global research communitythe results of the exogenous subgroup association analyzed by the study can be publicly available on this knowledge portal (image source: screenshot: website screenshot)With the rapid development of gene sequencing technology, bioinformatics ians began to understand the risk of type 2 diabetes by identifying molecular changes that have a causal relationship with physiological characteristicsThe Whole Genome Association Study (GWAS) has identified thousands of gene sites associated with hundreds of traitsBut these are generally only a small part of the explanation of heredityThis may be due to the difficulty of detecting gWAS by rare mutations with low distribution frequencies (0.5% of secondary alleles)therefore, this study was supplemented by the sequencing of exobiome clustersSince exosomes are regions of the genome that encode functional proteins, exogenous sequences help to identify mutations that have a significant impact on protein function or disease, establishing a direct causal relationship between gene function and disease riskHowever, for complex diseases such as type 2 diabetes, previous exobiome sequencing studies have detected relatively few significant rare mutations, in part because of the limited size of previous samples, such as the up to 10,000 cases in past studies, DrJason Flannick, a co-author of the study, has led to collaboration between several associations for the study of type 2 diabetes (source: Broad Institute website) expanded the sample size to increase the analytical capabilities of rare coded gene variants As a result of international cooperation, the team collected and analyzed data from 20,791 people with type 2 diabetes and 24,440 control groups This is the largest sequencing study of exobiome clusters of type 2 diabetes published to date In fact, it is also the largest exome sequencing study of any disease and nearly 50,000 participants genetically included five ancestral groups, including Hispanics/Latinos, Europeans, African-Americans, East Asia and South Asia Therefore, from a biological point of view, the results of the analysis have a wide range of significance the research team identified 15 variants on seven sites through exobiome group association analysis, two of which were new variants not found in the past GWAS At the genetic level, three genes were significantly associated the most significant list of genes found in the analysis, click on the image to view the high-definition larger map (source: nature) the author's analysis suggests that it may take about 75,000 to 185,000 samples to identify significant rare mutations that are highly effective in known gene targets for type 2 diabetes Current results also demonstrate that exosome sequencing and genome-wide association studies are valuable in promoting our understanding of the genetic risks of complex diseases References: 1, Jason Flannick et al., (2019) Exome saming of 20,791 cases of type 2 diabetes and 24,440 controls Nature DOI: 10.1038/s41586-019-1231-2