Chunk #19 — Limitations and misunderstandings of clinical, translational, and research applications of PRS — Pleiotropy, confounding, and causal inference
Instead, Mendelian randomization (MR) or related methods (40) often complement PRS analyses by providing a useful approach to disentangle causal relationships among phenotypes (41). One of the most important requirements of MR is a strong instrument—one or more genetic variants that are robustly associated with the exposure of interest. MR tests whether the exposure-associated variants result in proportional effects on the outcome, assuming no confounding factors such as population stratification, pleiotropy, or other confounding. Such instruments are rare in psychiatry due to their highly polygenic nature, overlapping biology, and noisy phenotyping. Several methods attempt to account for pleiotropic bias by correcting the dose-response slope between the exposure and outcome either for the average variant or for some subset of variants. A typical MR approach to meet such strong assumptions is to require independent genome-wide significant variants (41; 42). Rigorous MR analyses with smaller numbers of highly significant variants using methods designed to account for pleiotropic bias enable causal inference that is less likely to be confounded (41). Resources such as MR-Base enable causal inference with GWAS summary statistics (43).
