ArticlebioRxiv : the preprint server for biology2026
GeneSIS: enhancing transferability of polygenic scores with variant-level gene-by-sex interaction effects.
Yosuke Tanigawa, Manolis Kellis
Abstract readPreprint
In one paragraphArticle in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 · Who and what moneyAuthors and funding
2 authors.
Yosuke TanigawaComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0001-9759-157X Manolis KellisComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0001-7113-9630 Funding
Single Cell Transcriptomic and Epigenomic Dissection of Opioid and Cocaine Responses in HIVU01DA053631 · NIDA · BROAD INSTITUTE, INC. · PI HEIMAN, MYRIAM, KELLIS, MANOLIS · 2021 to 2025
$12.6MMapping the vulnerable locus coeruleus pathways in aging and ADU01AG077227 · NIA · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Kwanghun Chung, Li-Huei Tsai · 2022 to 2026
$9.6MIdentification of TDP-43 Modifiers Through Single-Cell Transcriptional and Epigenomic Dissection of ALS and FTLD-MNDR01NS127187 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BELZIL, VERONIQUE, DONNELLY, CHRISTOPHER JAMES · 2021 to 2025
$9.1MEpigenomic, transcriptional and cellular dissection of Alzheimer's variantsR01AG058002 · NIA · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI HYMAN, BRADLEY T., JAENISCH, RUDOLF · 2017 to 2021
$7.9MElucidating the Molecular Mechanisms of Neuropsychiatric Symptoms in Alzheimer's DiseaseR01AG062335 · NIA · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI KELLIS, MANOLIS, TSAI, LI-HUEI · 2018 to 2022
$6.5MSingle-cell epigenomic and trancriptional dissection of sex-specific differences in Alzheimer’s DiseaseR01AG074003 · NIA · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI KELLIS, MANOLIS, TSAI, LI-HUEI · 2021 to 2025
$5.4MSingle-cell transcriptional and epigenomic dissection of Alzheimer's Disease and Related DementiasU01NS110453 · NINDS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI KELLIS, MANOLIS, TSAI, LI-HUEI · 2018 to 2020
$4.0MCell type specific epigenetic analysis to understand complex mechanisms underlying Alzheimer's disease phenotypesRF1AG054012 · NIA · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI KELLIS, MANOLIS, TSAI, LI-HUEI · 2016 to 2016
$3.9MSingle-Cell Transcriptional and Epigenomic Dissection to Identify Therapeutic Targets for ALS and FTDR01AG067151 · NIA · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BELZIL, VERONIQUE, KELLIS, MANOLIS · 2021 to 2025
$3.7MDissection of endosomal trafficking mechanisms in Alzheimer's DiseaseRF1AG062377 · NIA · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI TSAI, LI-HUEI · 2018 to 2018
$3.6MConstruction of an Integrated Immune-Vascular Brain - Chip as a Platform for the Study, Drug Screening, and Treatments of Alzheimer's DiseaseUH3NS115064 · NINDS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BLANCHARD, JOEL WILLIAM, KELLIS, MANOLIS · 2021 to 2023
$3.5MSingle-cell multi-region transcriptional and epigenomic dissection of VCID.RF1NS129032 · NINDS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI HEIMAN, MYRIAM, KELLIS, MANOLIS · 2022 to 2022
$3.1MNHGRI NIH HHS R01 HG008155NIA NIH HHS R01 AG058002NIA NIH HHS R01 AG062335NIA NIH HHS R01 AG067151NIA NIH HHS R01 AG074003NIA NIH HHS R01 AG081017NIA NIH HHS R56 AG067151NIA NIH HHS RF1 AG054012NIA NIH HHS RF1 AG062377NIA NIH HHS U01 AG077227NIDA NIH HHS U01 DA053631NIMH NIH HHS R01 MH109978NIMH NIH HHS U01 MH119509NINDS NIH HHS R01 NS127187NINDS NIH HHS R01 NS129032NINDS NIH HHS RF1 NS129032NINDS NIH HHS U01 NS110453NINDS NIH HHS UG3 NS115064NINDS NIH HHS UH3 NS115064
6 · The paper itselfAbstract
Advancing precision medicine requires accurate prediction of disease liability across populations and contexts. A major challenge is the limited transferability of polygenic scores (PGS) across genetic ancestry groups. We present GeneSIS (GENE and Sex Interaction Score), a supervised statistical learning framework for jointly modeling additive and context-dependent genetic effects at single-variant resolution directly from individual-level data. We analyze 406,659 individuals, including admixed individuals, in the UK Biobank and 1.3 million variants to develop predictive models for 99 complex traits. We report that ~8% of selected variables capture gene-by-sex (GxS) effects, validated by sex-stratified analyses. Modeling GxS effects improves prediction across 32 traits in non-European individuals. For predicting hip circumference in Africans, GeneSIS achieves a 3.7-fold improvement (p=8.0×10-7) over linear-only PGS and highlights biologically plausible hypotheses, such as pleiotropic GxS effects of
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PMID42779975
PMCPMC13596362
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