Local genetic correlation via knockoffs reduces confounding due to cross-trait assortative mating.

Am J Hum Genet

Department of Biostatistics, Columbia University, New York, NY 10032, USA; Department of Statistics, Lund University, Lund, Sweden. Electronic address:

Published: December 2024

AI Article Synopsis

  • Local genetic correlation analysis helps identify genetic links between different traits but can yield false positives due to cross-trait assortative mating (xAM).
  • LAVA-Knock is a new method that enhances an existing technique (LAVA) by generating synthetic data to minimize confounding from xAM while maintaining the genetic relationships in the data.
  • Simulations show that LAVA-Knock significantly reduces bias caused by xAM and correlates well with known trait pairs that exhibit high cross-mate correlations, indicating its effectiveness in improving genetic correlation analyses.

Article Abstract

Local genetic correlation analysis is an important tool for identifying genetic loci with shared biology across traits. Recently, Border et al. have shown that the results of these analyses are confounded by cross-trait assortative mating (xAM), leading to many false-positive findings. Here, we describe LAVA-Knock, a local genetic correlation method that builds off an existing genetic correlation method, LAVA, and augments it by generating synthetic data in a way that preserves local and long-range linkage disequilibrium (LD), allowing us to reduce the confounding induced by xAM. We show in simulations based on a realistic xAM model and in genome-wide association study (GWAS) applications for 630 trait pairs that LAVA-Knock can greatly reduce the bias due to xAM relative to LAVA. Furthermore, we show a significant positive correlation between the reduction in local genetic correlations and estimates in the literature of cross-mate phenotype correlations; in particular, pairs of traits that are known to have high cross-mate phenotype correlation values have a significantly higher reduction in the number of local genetic correlations compared with other trait pairs. A few representative examples include education and intelligence, education and alcohol consumption, and attention-deficit hyperactivity disorder and depression. These results suggest that LAVA-Knock can reduce confounding due to both short-range LD and long-range LD induced by xAM.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11639086PMC
http://dx.doi.org/10.1016/j.ajhg.2024.10.012DOI Listing

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