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Current Opinion in HIV & AIDS:
doi: 10.1097/COH.0b013e32833f2087
Biomarkers of outcomes of disease, treatment and complications: Edited by H. Clifford Lane and Jens D. Lundgren

Mendelian randomization: potential use of genetics to enable causal inferences regarding HIV-associated biomarkers and outcomes

He, Weijinga,b; Castiblanco, Johna,b; Walter, Elizabeth Ab; Okulicz, Jason Fd; Ahuja, Sunil Ka,b,c

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Abstract

Purpose of review: It is unknown whether biomarkers simply correlate with or are causal for HIV-associated outcomes. Mendelian randomization is a genetic epidemiologic approach used to disentangle causation from association. Here, we discuss the potential use of Mendelian randomization for differentiating whether biomarkers are correlating with or causal for HIV-associated outcomes.

Recent findings: Mendelian randomization refers to the random allocation of alleles at the time of gamete formation. In observational epidemiology, this refers to the use of genetic variants to estimate a causal effect between a modifiable risk factor and an outcome of interest. A formal Mendelian randomization study using a genetic marker as a proxy for the biomarker has not been conducted in the HIV field. However, in the postgenomic era, this approach is being used increasingly. Examples are evidence for the causal role of BMI in blood pressure and noncausal role of C-reactive protein in coronary heart disease. We discuss the conceptual framework, uses, and limitations of Mendelian randomization in the context of HIV infection as well as specific biomarkers (IL-6, C-reactive protein) and genetic determinants (e.g., in CCR5, chemokine, and DARC genes) that associate with HIV-related outcomes.

Summary: Making the distinction between correlation and causality has particular relevance when a biomarker (e.g., IL-6) is potentially modifiable, in which case a biomarker-guided targeted treatment strategy may be feasible. Although the tenets of Mendelian randomization rest on strong assumptions, and conducting a Mendelian randomization study in HIV infection presents many challenges, it may offer the potential to identify causal biomarkers for HIV-associated outcomes.

© 2010 Lippincott Williams & Wilkins, Inc.

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