+1 Recommend
0 collections
      • Record: found
      • Abstract: found
      • Article: not found

      Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations


      Read this article at

          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.


          A key public health need is to identify individuals at high risk for a given disease to enable enhanced screening or preventive therapies. Because most common diseases have a genetic component, one important approach is to stratify individuals based on inherited DNA variation. 1 Proposed clinical applications have largely focused on finding carriers of rare monogenic mutations at several-fold increased risk. Although most disease risk is polygenic in nature, 25 it has not yet been possible to use polygenic predictors to identify individuals at risk comparable to monogenic mutations. Here, we develop and validate genome-wide polygenic scores for five common diseases. The approach identifies 8.0%, 6.1%, 3.5%, 3.2% and 1.5% of the population at greater than three-fold increased risk for coronary artery disease (CAD), atrial fibrillation, type 2 diabetes, inflammatory bowel disease, and breast cancer, respectively. For CAD, this prevalence is 20-fold higher than the carrier frequency of rare monogenic mutations conferring comparable risk. 6 We propose that it is time to contemplate the inclusion of polygenic risk prediction in clinical care and discuss relevant issues.

          Related collections

          Most cited references11

          • Record: found
          • Abstract: not found
          • Article: not found

          Inflammatory bowel disease.

            • Record: found
            • Abstract: not found
            • Article: not found

            Rare and common variants: twenty arguments.

            Genome-wide association studies have greatly improved our understanding of the genetic basis of disease risk. The fact that they tend not to identify more than a fraction of the specific causal loci has led to divergence of opinion over whether most of the variance is hidden as numerous rare variants of large effect or as common variants of very small effect. Here I review 20 arguments for and against each of these models of the genetic basis of complex traits and conclude that both classes of effect can be readily reconciled.
              • Record: found
              • Abstract: found
              • Article: not found

              An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans

              To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10−8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action–associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.

                Author and article information

                Nat Genet
                Nat. Genet.
                Nature genetics
                22 June 2018
                13 August 2018
                September 2018
                13 February 2019
                : 50
                : 9
                : 1219-1224
                [1 ]Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
                [2 ]Cardiology Division of the Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
                [3 ]Harvard Medical School, Boston, MA, USA
                [4 ]Cardiovascular Disease Initiative of the Broad Institute of Harvard and MIT, Cambridge, MA, USA
                Author notes
                [* ]Correspondence to: Sekar Kathiresan, MD, Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge Street, CPZN 5.821A, Boston, MA 02114, skathiresan1@ 123456mgh.harvard.edu , Phone: 617 724 3091

                Author Contributions:

                Concept and design: A.V.K., M.C., S.K. Acquisition, analysis, or interpretation of data: A.V.K., M.C., K.G.A., M.E.H., C.R., S-H.C, S.A.L. Drafting of the manuscript: A.V.K., M.C., E.S.L., S.K. Critical revision of the manuscript for important intellectual content: A.V.K., M.C., P.N., E.S.L., P.T.E, S.K.


                Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms




                Comment on this article