Online Webiner - From Proteome to Complexome: Unveiling the Next Frontier in Proteogenomics

Live webinar — Nov 18, 9:00–10:00 AM EST (online)

Abstract

Protein complexes orchestrate nearly all biological functions, yet their systemic roles and genetic regulation in human health remain largely elusive due to the limitations of traditional proteomics in capturing subunit-level interactions. We developed and applied a novel AI-based protein complex deconvolution framework, enabling in silico quantification of protein complexes using large-scale affinity proteomics data. We demonstrate via causal inference and drug validation analyses that protein complexes offer stronger and more interpretable links to disease phenotypes than conventional protein markers. Notably, complex-specific markers prioritized by genetics are substantially more likely to align with known therapeutic mechanisms. These findings underscore the great potential of protein complexes as actionable biomarkers and targets in precision medicine.

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Why attend

See the complexome, not just the proteome. Understand how AI-based deconvolution turns Olink/SomaScan–scale datasets into quantitative readouts of protein complexes—exposing biology invisible to single-protein views.

Learn causality-first triage. Watch how complex-level signals integrate with pQTLs, colocalization, and MR to move from association to mechanism and nominate actionable biomarkers.

Target & repurpose with confidence. Learn why genetics-prioritized complex markers align better with known therapeutic mechanisms than conventional markers, improving hit-to-lead decisions.

Bring your own data. Practical guidance for teams working with affinity proteomics who want to extract complex-aware insights for discovery and translational pipelines.

Ask an expert live. Q&A included; registrants receive the recording and slides.

Speaker

Dr. Xia Shen

Greater Bay Area Institute of Precision Medicine, Fudan University (Guangzhou)

Department of Medical Epidemiology & Biostatistics, Karolinska Institutet

Usher Institute, University of Edinburgh.

Selected publications

1. Repetto L, Chen J, Yang Z, Zhai R, Li T, Richmond A, et al. The genetic landscape of neuro-related proteins in human plasma. Nat Hum Behav. 2024;8:2222-2234. doi:10.1038/s41562-024-01963-z.
2. Yang Z, Macdonald-Dunlop E, Chen J, Zhai R, Li T, Richmond A, et al. Genetic landscape of the ACE2 coronavirus receptor. Circulation. 2022;145(18):1398-1411. doi:10.1161/CIRCULATIONAHA.121.057888.
3. Li T, Ning Z, Yang Z, Zhai R, Xu W, Ying K, et al. Total genetic contribution assessment across the human genome. Nat Commun. 2021;12(1):2845. doi:10.1038/s41467-021-23124-w.
4. Ning Z, Pawitan Y, Shen X. High-definition likelihood inference of genetic correlations across human complex traits. Nat Genet. 2020;52(8):859-864. doi:10.1038/s41588-020-0653-y.
5. Ning Z, Lee Y, Joshi PK, Wilson JF, Pawitan Y, Shen X. A selection operator for summary association statistics reveals allelic heterogeneity of complex traits. Am J Hum Genet. 2017;101(6):903-912. doi:10.1016/j.ajhg.2017.09.027.
6. Shen X, Klarić L, Sharapov S, Mangino M, Ning Z, Wu D, et al. Multivariate discovery and replication of five novel loci associated with immunoglobulin G N-glycosylation. Nat Commun. 2017;8(1):447. doi:10.1038/s41467-017-00453-3.

Agenda

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