Author

Nathan Cheng

Broad Institute

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

Biology Disciplines

Click to filter author papers

Genetic & Genomic Medicine· 2 Genomics· 2 Neuroscience· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:human· 4 Approach:statistical model· 4 Assay:GWAS summary statistics· 3 Research Focus:fine-mapping· 2 Research Focus:gene regulatory network inference· 2 Assay:bulk RNA-seq· 1 Assay:clinical cohort / trial· 1 Research Focus:database / resource· 1

Frequent Co-Authors

Hilary K. FinucaneiD· 4 shared Masahiro KanaiiD· 3 shared Eric S. LanderiD· 2 shared François AguetiD· 2 shared J EngreitziD· 2 shared Jacob C. UlirschiD· 2 shared Kristin ArdlieiD· 2 shared Rajat M. GuptaiD· 2 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

4 shared papersGenetic & Genomic Medicine

Hilary K. FinucaneORCID

Mutual co-authors in cluster

Author profile →

5 papers

Recent·Most cited

Changes in perineuronal net and parvalbumin expression in the orbitofrontal cortex of male Wistar rats following repeated fentanyl administration

Mariana I.H. Dejeux, Sarah Jewanee, Samuel Moutos, Arjun Trehan, Melody Golbarani, Joanne Kwak, Evan Farach, Nathan Cheng, Sri V. Kasaram, Aliyah Ogden, Sophia Wright, Benjamin A. Schwartz, Jacques D. Nguyen

This study examines how repeated fentanyl administration affects perineuronal nets and parvalbumin expression in rat orbitofrontal cortex, showing changes in antinociceptive tolerance and PNN/PV correlations.

Frontiers in Neuroscience · Jul 8, 2026Peer-reviewedNeuroscience

Pan-UK Biobank GWAS improves discovery, analysis of genetic architecture, and resolution into ancestry-enriched effects

Konrad J. Karczewski, Rahul Gupta, Masahiro Kanai, Wenhan Lu, Kristin Tsuo, Ying Wang, Raymond Kenney Walters, Patrick Turley, Shawneequa Callier, Nirav N. Shah, Nikolas A. Baya, Duncan S. Palmer, Jacqueline I. Goldstein, Gopal Sarma, Matthew Solomonson, , Alicia R. Martin

Meta-analyzing per-ancestry GWAS of 7,266 UK Biobank traits across six genetic ancestry groups adds 14,676 loci missed by European-only analysis, including ancestry-enriched CAMK2D and G6PD signals.

medRxiv · Mar 13, 2024 · PreprintGenetic & Genomic Medicine✦ In-depth digest

Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases

Elle M. Weeks, Jacob C. Ulirsch, Nathan Cheng, Brian L. Trippe, Rebecca S. Fine, Jenkai Miao, Tejal A. Patwardhan, Masahiro Kanai, Joseph Nasser, Charles P. Fulco, Katherine C. Tashman, François Aguet, Taibo Li, José Ordovás-Montañés, Christopher S. Smillie, , Hilary K. Finucane

The paper introduces a method to prioritize causal genes for complex traits by integrating GWAS data with gene expression and biological data, achieving high precision in gene-trait pair identification.

Nature Genetics · Jul 13, 2023Peer-reviewedGenetic & Genomic Medicine

Mapping the convergence of genes for coronary artery disease onto endothelial cell programs

Gavin R. Schnitzler, Helen Y. Kang, Vivian S. Lee-Kim, X. Rosa Ma, Tony Zeng, Ramcharan Singh Angom, Shi Fang, Shamsudheen Karuthedath Vellarikkal, Ronghao Zhou, Katherine Guo, Oscar Sias‐Garcia, Alex Bloemendal, Glen Munson, Philine Guckelberger, Tung H. Nguyen, , J Engreitz

The paper maps coronary artery disease risk loci to endothelial cell gene programs, identifying convergence on the CCM pathway and a new CAD gene, TLNRD1.

bioRxiv · Nov 1, 2022 · PreprintGenomics

Leveraging supervised learning for functionally-informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs

Qingbo S. Wang, David R. Kelley, Jacob C. Ulirsch, Masahiro Kanai, Shuvom Sadhuka, Ran Cui, Carlos Albors, Nathan Cheng, Yukinori Okada, The Biobank Japan Project, Koichi Matsuda, Yuji Yamanashi, Yoichi Furukawa, Takayuki Morisaki, Yoshinori Murakami, , Hilary K. Finucane

The paper uses supervised learning to fine-map cis-eQTLs, identifying 20,913 additional putative causal eQTLs and 310 candidate genes.

Nature Communications · Jun 7, 2021Peer-reviewedGenomics