Next-generation gene discovery for variants of large impact on lipid traits.
|Title||Next-generation gene discovery for variants of large impact on lipid traits.|
|Publication Type||Journal Article|
|Year of Publication||2015|
|Authors||Rosenthal E, Blue E, Jarvik GP|
|Journal||Curr Opin Lipidol|
|Date Published||2015 Apr|
|Keywords||Animals, Dyslipidemias, Genetic Linkage, Genetic Predisposition to Disease, Genome-Wide Association Study, High-Throughput Nucleotide Sequencing, Humans, Lipid Metabolism, Polymorphism, Single Nucleotide|
PURPOSE OF REVIEW: Detection of high-impact variants on lipid traits is complicated by complex genetic architecture. Although genome-wide association studies (GWAS) successfully identified many novel genes associated with lipid traits, it was less successful in identifying variants with a large impact on the phenotype. This is not unexpected, as the more common variants detectable by GWAS typically have small effects. The availability of large familial datasets and sequence data has changed the paradigm for successful genomic discovery of the novel genes and pathogenic variants underlying lipid disorders.
RECENT FINDINGS: Novel loci with large effects have been successfully mapped in families, and next-generation sequencing allowed for the identification of the underlying lipid-associated variants of large effect size. The success of this strategy relies on the simplification of the underlying genetic variation by focusing on large single families segregating extreme lipid phenotypes.
SUMMARY: Rare, high-impact variants are expected to have large effects and be more relevant for medical and pharmaceutical applications. Family data have many advantages over population-based data because they allow for the efficient detection of high-impact variants with an exponentially smaller sample size and increased power for follow-up studies.
|Alternate Journal||Curr. Opin. Lipidol.|
|PubMed Central ID||PMC4388051|
|Grant List||P01 HL030086 / HL / NHLBI NIH HHS / United States |
R00 AG040184 / AG / NIA NIH HHS / United States
T32 GM007454 / GM / NIGMS NIH HHS / United States