Using human genetics to predict the effects and side-effects of drugs

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PURPOSE OF REVIEW: 'Genetic proxies' are increasingly being used to predict the effects of drugs. We present an up-to-date overview of the use of human genetics to predict effects and adverse effects of lipid-targeting drugs.

RECENT FINDINGS: LDL cholesterol lowering variants in HMG-Coenzyme A reductase and Niemann-Pick C1-like protein 1, the targets for statins and ezetimibe, protect against ischemic heart disease (IHD). However, HMG-Coenzyme A reductase and Niemann-Pick C1-Like Protein 1-variants also increase the risk of type 2 diabetes and gallstone disease, respectively. Mutations in proprotein convertase subtilisin kexin 9 (PCSK9), apolipoprotein B, and microsomal triglyceride transfer protein cause low LDL cholesterol and protect against IHD. In addition, mutations in apolipoprotein B and microsomal triglyceride transfer protein cause hepatic steatosis, in concordance with drugs that inhibit these targets. Both mutations in PCSK9 and PCSK9-inhibition seem without adverse effects. Mutations in APOC3 cause low triglycerides and protect against IHD, and recent pharmacological APOC3-inhibition reported major reductions in plasma triglycerides. Human genetics support that low lipoprotein(a) protects against IHD, without adverse effects, and the first trial of lipoprotein(a) inhibition reduced lipoprotein(a) up to 78%.

SUMMARY: Recent genetic studies have confirmed the efficacy of statins and ezetimibe in protecting against IHD. Results from human genetics support that several lipid-lowering drugs currently under development are likely to prove efficacious in protecting against IHD, without major adverse effects.

Original languageEnglish
JournalCurrent Opinion in Lipidology
Volume27
Issue number2
Pages (from-to)105-111
Number of pages7
ISSN0957-9672
DOIs
Publication statusPublished - Apr 2016

    Research areas

  • Animals, Anticholesteremic Agents, Genetic Association Studies, Genetics, Medical, Humans, Hypercholesterolemia, Pharmacogenomic Variants, Sequence Analysis, DNA, Treatment Outcome, Journal Article, Research Support, Non-U.S. Gov't, Review

ID: 174860970