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Anders Rosengren

Postdoctoral research fellow

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Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes article

Author

  • Anubha Mahajan
  • Jennifer Wessel
  • Sara M Willems
  • Wei Zhao
  • Neil R Robertson
  • Audrey Y. Chu
  • Jasmina Kravic
  • Emma Ahlqvist
  • Anders Rosengren
  • Leif Groop
  • Tibor V Varga
  • Paul Franks
  • Peter Almgren
  • Olle Melander
  • Marju Orho-Melander
  • Mark I. McCarthy

Summary, in English

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition. © 2018 The Author(s).

Department/s

  • Genomics, Diabetes and Endocrinology
  • Diabetes - Islet Patophysiology
  • Genetic and Molecular Epidemiology
  • EpiHealth: Epidemiology for Health
  • Diabetes - Cardiovascular Disease
  • Cardiovascular Research - Hypertension

Publishing year

2018

Language

English

Pages

559-571

Publication/Series

Nature Genetics

Volume

50

Issue

4

Document type

Journal article

Publisher

Nature Publishing Group

Topic

  • Medical Genetics
  • Endocrinology and Diabetes

Keywords

  • ancestry group
  • Article
  • disease predisposition
  • gene locus
  • gene mapping
  • gene sequence
  • genetic association
  • genetic code
  • genetic variability
  • genome
  • human
  • major clinical study
  • non insulin dependent diabetes mellitus
  • odds ratio
  • priority journal

Status

Published

Research group

  • Genomics, Diabetes and Endocrinology
  • Diabetes - Islet Patophysiology
  • Genetic and Molecular Epidemiology
  • Diabetes - Cardiovascular Disease
  • Cardiovascular Research - Hypertension

ISBN/ISSN/Other

  • ISSN: 1546-1718