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Defining the spectrum of alleles that contribute to blood lipid concentrations in humans

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Author

Summary, in English

Purpose of review Recently, genome-wide genetic screening of common DNA sequence variants has proven a successful approach to identify novel genetic contributors to complex traits. This review summarizes recent genome-wide association studies for lipid phenotypes, and evaluates the next steps needed to obtain a full picture of genotype-phenotype correlation and apply these findings to inform clinical practice. Recent findings So far, genome-wide association studies have defined at least 19 genomic regions that contain common DNA single nucleotide polymorphisms associated with LDL cholesterol, HDL cholesterol and/or triglycerides. Of these, eight represent novel loci in humans, whereas 11 genes have been previously implicated in lipoprotein metabolism. Many of the same loci with common variants have already been shown to lead to monogenic lipid disorders in humans and/or mice, suggesting that a spectrum of common and rare alleles at each validated locus contributes to blood lipid concentrations. Summary At least 19 loci harbor common variations that contribute to blood lipid concentrations in humans. Larger scale genome-wide association studies should identify additional loci, and sequencing of these loci should pinpoint all relevant alleles. With a full catalog of DNA polymorphisms in hand, a panel of lipid-related variants can be studied to provide clinical risk stratification and targeting of therapeutic interventions.

Publishing year

2008

Language

English

Pages

122-127

Publication/Series

Current Opinion in Lipidology

Volume

19

Issue

2

Document type

Journal article review

Publisher

Lippincott Williams & Wilkins

Topic

  • Endocrinology and Diabetes

Keywords

  • cholesterol
  • LDL
  • HDL cholesterol
  • complex trait genetics
  • genome-wide association
  • single nucleotide polymorphism
  • triglycerides

Status

Published

Research group

  • Genomics, Diabetes and Endocrinology

ISBN/ISSN/Other

  • ISSN: 1473-6535