In the UK Biobank (10 traits), ML/DL models outperformed additive PGSs for traits known to show dominance - including lipoprotein(a), alkaline phosphatase, and ApoB - but not for height (no dominance).

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Across most scenarios, additive PGSs were remarkably robust - even when up to 20% of SNP-h² came from dominance SNPs.

Performance dropped mainly for traits with:
• high SNP-h²
• low polygenicity
• strong dominance deviations

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Most PGS methods assume additivity - each allele contributes linearly to risk - but real traits can show dominance deviations.

We simulated phenotypes varying in:
• SNP heritability (SNP h²)
• % heritability from dominance
• polygenicity
• dominance deviation strength

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