Author

Wei-Min Chen

University of Virginia

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genetic & Genomic Medicine· 4 Genomics· 2

Signature Assays, Organisms & Methods

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Approach:statistical model· 6 Research Focus:GWAS / association mapping· 5 Organism:human· 5 Assay:GWAS summary statistics· 3 Assay:bulk RNA-seq· 2 Research Focus:differential expression· 2 Research Focus:fine-mapping· 2 Research Focus:gene regulatory network inference· 2

Frequent Co-Authors

Laura M. RaffieldiD· 4 shared Brian E. CadeiD· 3 shared Stephen S. RichiD· 3 shared Tamar SoferiD· 3 shared Adebowale AdeyemoiD· 2 shared Alain Bertoni· 2 shared Alex P. ReineriD· 2 shared Amber Beitelshees· 2 shared

Activity by Year

2015-2026 · peak 2/yr

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10 top collaborators · 33 mutual co-author links

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4 shared papersGenetic & Genomic Medicine

Laura M. RaffieldORCID

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Author profile →

6 papers

Recent·Most cited

Cross-cohort analysis of expression and splicing quantitative trait loci in TOPMed

Peter Orchard, Thomas W. Blackwell, Linda Kachuri, Peter J. Castaldi, Michael H. Cho, Stephanie A. Christenson, Peter Durda, Stacey Gabriel, Craig P. Hersh, Scott Huntsman, S.-J. Hwang, Roby Joehanes, Mari Johnson, Xingnan Li, Honghuang Lin, , Jeffrey L. Curtis

The paper analyzes expression and splicing quantitative trait loci (e/sQTL) across multiple tissues in the TOPMed dataset and finds that secondary e/sQTL signals are still discoverable, with many GWAS signals colocalizing with these e/sQTL.

Science · Jul 16, 2026Peer-reviewedGenetic & Genomic Medicine

Mosaic Loss of Y chromosome associates with lung function, emphysema and epigenetic aging

Woei‐Yuh Saw, Kangjin Kim, Yichen Huang, Jeong Hyun Yun, Xiaolong Ma, Jason Bacon, Yash Pershad, Daniel A Levy, George T. O’Connor, Eric Boerwinkle, R. Graham Barr, Stephen S. Rich, Jerome I. Rotter, April P. Carson, Laura M. Raffield, , Michael Rutledge DeBaun

This study investigates the association between mosaic loss of Y chromosome (mLOY) and lung function, emphysema, and epigenetic aging in men across multiple cohorts.

American Journal of Respiratory and Critical Care Medicine · Mar 19, 2026Peer-reviewedGenetic & Genomic Medicine

Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications

Suzuki Ken, Konstantinos Hatzikotoulas, Lorraine Southam, Henry J. Taylor, Xianyong Yin, Kim Lorenz, Ravi Mandla, Alicia Huerta-Chagoya, Nigel W. Rayner, Ozvan Bocher, S. V. Arruda Ana Luiza de, Kyuto Sonehara, Shinichi Namba, Simon S. K. Lee, Michael H. Preuss, , H. Janaka de Silva

This study identifies 1,289 genetic signals for type 2 diabetes in 2.5 million individuals, revealing distinct clusters linked to vascular complications and highlighting ancestry-specific genetic risk factors.

Yearbook of pediatric endocrinology · Sep 8, 2023Peer-reviewedGenetic & Genomic Medicine

Trans-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

Anubha Mahajan, Cassandra Nichole Spracklen, Weihua Zhang, Maggie C.Y. Ng, Lauren E. Petty, Hidetoshi Kitajima, Grace Z. Yu, Sina Rüeger, Leo Speidel, Young Jin Kim, Momoko Horikoshi, Josep Maria Mercader, Daniel Taliun, Sanghoon Moon, Soo‐Heon Kwak, , Mary Cushman

This study identifies 277 T2D loci using diverse populations and improves fine-mapping to assess causal genes and mechanisms, enhancing clinical translation.

Discovery Research Portal (University of Dundee) · Jan 1, 2022Peer-reviewedGenetic & Genomic Medicine

A pan-cancer analysis of prognostic genes

Jordan Anaya, Brian J Reon, Wei-Min Chen, Stefan Bekiranov, Anindya Dutta

This study identifies prognostic genes across 16 cancer types using RNA-SEQ data from The Cancer Genome Atlas, finding distinct gene sets associated with survival that are shared among cancer groups.

bioRxiv · Dec 23, 2015Genomics

Using genotype data to distinguish pleiotropy from heterogeneity: deciphering coheritability in autoimmune and neuropsychiatric diseases

Buhm Han, Jennie G Pouget, Kamil Slowikowski, Eli Stahl, Cue Hyunkyu Lee, Dorothee Diogo, Xinli Hu, Yu Rang Park, Eunji Kim, Peter K Gregersen, Solbritt Rantapaa Dahqvist, Jane Worthington, Steve Eyre, Lars Klareskog, Tom Huizinga, , Soumya Raychaudhuri

The paper introduces BUHMBOX, a statistical method to distinguish pleiotropy from heterogeneity in genetic data, finding shared genetic bases in autoimmune diseases and between MDD and schizophrenia.

bioRxiv · Nov 6, 2015 · PreprintGenomics