Using Genotype-Based Recall to Estimate the Effects of AMY1 Copy Number Variation in Substrate Metabolism
Year: 2016
Type: article
Abstract: By the turn of the 21st century it had become evident that type 2 diabetes has a strong genetic basis (1), but very little was known about the specific loci causing the disease. Sixteen years on, hundreds of loci have been discovered at which DNA variation and cardiometabolic traits robustly correlate (2). But, as we well know, correlation and causation are not synonymous, and there is much that must now be done to characterize the mechanisms through which genetic variants raise disease risk.
Although no single approach will be sufficient to achieve this, the use of advanced molecular assays has helped elucidate the key subphenotypes that underlie diseases such as type 2 diabetes. However, a key barrier to the application of these methods is that genetic effects are usually of small magnitude, making them difficult to estimate, and the simple solution of studying very large sample collections can prove prohibitively expensive. This has motivated studies that maximize power by selectively sampling biosamples or participants with starkly contrasting genetic characteristics from much larger cohorts and undertaking detailed phenotyping in these subsamples (Fig. 1). This approach, termed genotype-based recall (GBR) (3), can be considerably more powerful than randomly sampling participants for substudies of similar size and potentially more cost-effective than phenotyping the entire cohort.
Figure 1
The genotype-based recall paradigm: biosamples or participants are recalled from existing biobanks or cohorts, respectively, for new substudies. For example, new “omic” analyses might be undertaken in recalled biosamples …
Source: Diabetes
DOI: 10.2337/dbi16-0046
Authors: Paul W. Franks, Frida Renström
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W2538136221