Reply To: Re-Evaluating Local Genetic Correlation Analysis in the HDL Framework

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Abstract

The LAVA method has been proposed for detecting local genetic correlations between traits. We show, using theoretical analysis and simulations, that LAVA’s “fixed-effects” model does not estimate genetic correlation in the statistical genetics sense, but instead detects the presence of regional genetic effects. This mis-specification leads to inflated type-I error under the null, particularly when causal variants are sparse, and can produce apparent “correlations” arising solely from unshared, trait-specific signals. In contrast, the random-effects model implemented in HDL-L correctly targets variant-level genetic correlation and remains well-calibrated. Our results indicate that LAVA findings may be widely misinterpreted, and we recommend caution and the use of random-effects–based approaches such as HDL-L for valid inference.

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