Local genetic correlation via knockoffs reduces confounding due to cross-trait assortative mating
(2024) In American Journal of Human Genetics 111(12). p.2839-2848- 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... (More)
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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- author
- Ma, Shiyang ; Wang, Fan ; Border, Richard ; Buxbaum, Joseph ; Zaitlen, Noah and Ionita-Laza, Iuliana LU
- organization
- publishing date
- 2024-12-05
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- cross-trait assortative mating, Local genetic correlation, synthetic data
- in
- American Journal of Human Genetics
- volume
- 111
- issue
- 12
- pages
- 10 pages
- publisher
- Cell Press
- external identifiers
-
- scopus:85210402153
- pmid:39547235
- ISSN
- 0002-9297
- DOI
- 10.1016/j.ajhg.2024.10.012
- language
- English
- LU publication?
- yes
- id
- 2b2f9413-47ae-47bb-bdda-1068f38333ac
- date added to LUP
- 2025-01-08 09:51:40
- date last changed
- 2025-07-10 01:21:46
@article{2b2f9413-47ae-47bb-bdda-1068f38333ac,
abstract = {{<p>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.</p>}},
author = {{Ma, Shiyang and Wang, Fan and Border, Richard and Buxbaum, Joseph and Zaitlen, Noah and Ionita-Laza, Iuliana}},
issn = {{0002-9297}},
keywords = {{cross-trait assortative mating; Local genetic correlation; synthetic data}},
language = {{eng}},
month = {{12}},
number = {{12}},
pages = {{2839--2848}},
publisher = {{Cell Press}},
series = {{American Journal of Human Genetics}},
title = {{Local genetic correlation via knockoffs reduces confounding due to cross-trait assortative mating}},
url = {{http://dx.doi.org/10.1016/j.ajhg.2024.10.012}},
doi = {{10.1016/j.ajhg.2024.10.012}},
volume = {{111}},
year = {{2024}},
}