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# AlphaMissense

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medRxiv Oct 21, 2026
Rare missense variants hid more heritability than burden tests showed: a flexible kernel lifts the lower bound from 0.54% to at least 1.27%
Rare missense contributions to complex traits have been underestimated because collapsing variants within a gene into one burden score averages away effect differences. The Kernel Allelic Series Model (KASM) builds within-gene effect covariance kernels from protein-structure and variant-effect annotations; across 786,871 exomes and 26 continuous traits it raises the lower bound on rare missense heritability from 0.54±0.04% to at least 1.27±0.09%, and to 1.83±0.11% under the most flexible model, above the 0.87±0.05% for loss-of-function variants.
Rare missense contributions to complex traits have been underestimated because collapsing variants within a gene into one burden score averages away effect differences. The Kernel Allelic Series Model (KASM) builds within-gene effect covariance kernels from protein-structure and variant-effect annotations; across 786,871 exomes and 26 continuous traits it raises the lower bound on rare missense heritability from 0.54±0.04% to at least 1.27±0.09%, and to 1.83±0.11% under the most flexible model, above the 0.87±0.05% for loss-of-function variants.
Harvard University Broad Institute
Kangcheng Hou（First author, Corresponding author）
Kernel Allelic Series Model Rare Coding Heritability Estimation AlphaMissense Effect Concordance of Variant Pairs
medRxiv Sep 16, 2026
Genomic foundation model-derived disruption profiling links somatic mutations to cancer biology and clinical outcomes
Using AlphaGenome and AlphaMissense to quantify the disruption imposed by somatic mutations across 8,800 patients and 33 cancer types from The Cancer Genome Atlas, this study found that recurrent hotspot mutations showed substantially larger predicted protein-level effects while non-hotspot mutations exhibited larger regulatory effects across most cancer types; aggregating variant-level predictions into patient-gene disruption profiles capturing transcriptional activity, chromatin accessibility, transcription factor binding, and splicing yielded gene- and modality-specific profiles that reflected tissue of origin, cancer type, and microsatellite-instability status while retaining information beyond tumor mutational burden; among patients lacking recurrent hotspot mutations, higher predicte
Using AlphaGenome and AlphaMissense to quantify the disruption imposed by somatic mutations across 8,800 patients and 33 cancer types from The Cancer Genome Atlas, this study found that recurrent hotspot mutations showed substantially larger predicted protein-level effects while non-hotspot mutations exhibited larger regulatory effects across most cancer types; aggregating variant-level predictions into patient-gene disruption profiles capturing transcriptional activity, chromatin accessibility, transcription factor binding, and splicing yielded gene- and modality-specific profiles that reflected tissue of origin, cancer type, and microsatellite-instability status while retaining information beyond tumor mutational burden; among patients lacking recurrent hotspot mutations, higher predicte
The University of Texas at Austin
Akshatha Nayak（First author）Ilias Georgakopoulos‐Soares（Corresponding author）
AlphaGenome AlphaMissense patient-gene disruption profiles cancer genomics

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