Four of the new datasets were generated by collaborators in AMP T2D, the parent organization of the T2DKP. AMP T2D is a pre-competitive partnership among the National Institutes of Health, industry, and not-for-profit organizations, managed by the Foundation for the National Institutes of Health, that supports the generation of genetic association data and many other kinds of genomic data as well as providing access to these data in the T2DKP, to facilitate the translation of these data into biological knowledge about T2D.
For all four of these datasets, quality control and association analysis were performed by the Analysis Team of the AMP Data Coordinating Center (AMP DCC) at the Broad Institute, using standard, state-of-the-art methods. These processes are completely transparent and fully documented: the experimental design and analysis are summarized on our Data page, and detailed reports are available for download. In this first phase of analysis, associations were determined for type 2 diabetes, fasting glucose levels, and fasting insulin levels--both unadjusted, and adjusted for body mass index. Future analyses will add more phenotypes.
One of these datasets, Diabetic Cohort - Singapore Prospective Study GWAS, was contributed by collaborators at the National University of Singapore. Consisting of 3,864 samples, it is a T2D case-control study to identify genetic and environmental risk factors for diabetes in Singapore Chinese. The other three new sets that were analyzed at the AMP DCC, contributed by collaborators at the University of Michigan, are from the Finland-United States Investigation of NIDDM Genetics (FUSION) Study that seeks to to map and identify genetic variants that predispose to type 2 diabetes or affect variability in diabetes-related traits. The three FUSION datasets include FUSION GWAS, with 1,681 samples; FUSION Metabochip, with 2,163 samples, and FUSION exome chip analysis, with 3,485 samples.
All four of these datasets now have “Early Access Phase 1” status, which is assigned to new data. This status denotes that although analysis and quality control checks have been performed, the data are not yet considered to be in their final state. During the early access period, users may analyze the data but may not submit the results of these analyses for publication. Find the full details about the different phases of data release on our Policies page.
In addition to the datasets from AMP T2D partners, we have also added or updated 6 new sets of publicly-available association summary statistics for phenotypes relevant to T2D:
- Body fat percentage GWAS (Lu et al., 2016), with 100,716 samples;
- The previous CKDGen GWAS dataset for chronic kidney disease has been replaced with a newer study from the CKDGen consortium, imputed to the 1000 Genomes reference set (Gorski et al., 2017), with 110,517 samples;
- Early Growth Genetics Consortium GWAS associations for childhood obesity (Bradfield et al., 2012), with 13,848 samples;
- Body fat distribution associations (Shungin et al., 2015), with 245,749 samples, have been added to the existing GIANT GWAS dataset;
- GIANT UK Biobank GWAS for BMI and height from 795,640 UK Biobank samples (Yengo et al., in preparation);
- Heart rate GWAS (den Hoed et al., 2013), with 181,171 samples.
Results from all the new datasets may be viewed at these locations in the T2D Knowledge Portal:
• On Gene Pages (e.g., GCKR) in the Common variants and High-impact variants tables and in LocusZoom plots;
• On Variant Pages (e.g., rs1260326) in the Associations at a glance section, the Association statistics across traits table, and in LocusZoom static plots;
• From the View full genetic association results for a phenotype search on the home page: select a phenotype and view the top variants in a Manhattan plot and table;
• Using the Variant Finder tool: specify multiple criteria and retrieve the set of variants meeting those criteria from any of these datasets.
Additionally, individual-level data from the Diabetic Cohort - Singapore Prospective Study GWAS and FUSION GWAS datasets are available for secure custom interactive analyses using these tools in the T2DKP:
• Using the Genetic Association Interactive Tool (GAIT) on Variant Pages, you may choose a phenotype for association analysis, choose custom covariates, filter the sample pool by specifying a range of values for one or more phenotypes, then run on-the-fly analysis.
• Dynamic LocusZoom plots on Gene and Variant pages allow you to run association analysis using one or more variants of your choice as covariates, in order to test whether associations are independent.
• On Gene Pages (e.g., GCKR) in the Common variants and High-impact variants tables and in LocusZoom plots;
• On Variant Pages (e.g., rs1260326) in the Associations at a glance section, the Association statistics across traits table, and in LocusZoom static plots;
• From the View full genetic association results for a phenotype search on the home page: select a phenotype and view the top variants in a Manhattan plot and table;
• Using the Variant Finder tool: specify multiple criteria and retrieve the set of variants meeting those criteria from any of these datasets.
Additionally, individual-level data from the Diabetic Cohort - Singapore Prospective Study GWAS and FUSION GWAS datasets are available for secure custom interactive analyses using these tools in the T2DKP:
• Using the Genetic Association Interactive Tool (GAIT) on Variant Pages, you may choose a phenotype for association analysis, choose custom covariates, filter the sample pool by specifying a range of values for one or more phenotypes, then run on-the-fly analysis.
• Dynamic LocusZoom plots on Gene and Variant pages allow you to run association analysis using one or more variants of your choice as covariates, in order to test whether associations are independent.