Take another look! Rare DNA mutations linked to diabetes were identified by analyzing exons

DOI: 10.1038/s41586-019-1231-
2 recently published a large-scale study of type 2 diabetes in the journal NatureThe study is by far the largest exon sequencingEventually, the researchers identified four rare variants that affect diabetes riskThe data suggest that hundreds more genes could be found in the futurethe team's lineup is luxurious, with an international alliance of industry bulls from Oxford University's Diabetes Medicine, director of the Department of Diabetes at Massachusetts General Hospital, Harvard Medical School's medical professor, and the Rhodes Institute's Diabetes Research GroupThey analyzed data from nearly 46,000 people of European, African-American, Latino/Latino, East Asian and South Asian descentPrevious studies have been conducted in European studies, so much so that some studies are not representative and cannot be applied to people with diabetes in other regionsMichael Boehnke, professor of biostatistics at the University of Michigan School of Public Health, said: "It's important to study a large number of individual samples from different descents, and most large population studies focus on groups of European descent, which makes it difficult to roll out the results globally." The more diverse the group of subjects, the more information they have and the more scientific they areexon sequencingIn this study, researchers sequenced all the areas of the genome that encode proteins, known as exome synodsanalysis of ex-manifest subgroups played a complementary roleCurrently, genome-wide association analysis (GWAS) is a very popular way to look for disease-related mutationsThis approach can be very effective in finding common disease variants throughout the genome, but the disadvantage is that less common exosome variants may be missedsuggested workflow for sequencing data using exonclusters in gene characterizationtherefore, studying exobiosis groups can help identify mutations that have a significant impact on protein function or disease This provides valuable advice on disease-related genes by establishing a direct causal relationship between gene function and disease risk, and thus leads to new drug targets the comparison of exobiome sequencing with array-based GWAS specifically, the team identified significant correlations between 15 variation sites at seven sites by analyzing exonclusters, 2 of which were new mutation sites not found by GWAS in the past At the genetic level, three genes were significantly associated Jason Flannick Image spic: Harvard Medical School website the study's lead author Jason Flannick said: "We now have an updated understanding of the role of rare DNA mutations in diabetes The discovery of these rare mutations may provide more valuable information for drug development In fact, we can find evidence of their disease in many genes that could be used as a target for new drugs and as a basic process for disease development the results of the study were publicly available on the knowledge portal
researchers intend to increase the sample size in future studies This may be the largest exobiome sequencing study of type 2 diabetes, with a sample size of nearly 50,000, but even those important rare mutations may require between 75,000 and 185,000 samples, as the authors note all of the team's results are made available online through the Type 2 Diabetes Knowledge Portal, enabling scientists around the world to access and use this information for their own research these genes are associated with diabetes: References: s1 s DOI: 10.1038/s41586-019-1231-2 ,