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Curriculum vitae for Joshua Chiou. Experience in statistical genetics, translational proteomics, and computational biology at Lilly and Pfizer.

Joshua Chiou, PhD
Director, Genomics · Lilly
chioujosh@gmail.com · joshchiou.github.io · Boston, MA
2025–now
Director, Genomics 2 roles
Senior Advisor, Genomics · 2025–2026
Lilly
2021–2025
Senior Principal Computational Geneticist 2 roles
Senior Computational Geneticist · 2021–2023
Pfizer
2016–2021
PhD, Biomedical Sciences
University of California, San Diego · Gaulton Lab
2015–2016
Development Scientist 2 roles
Research Associate · 2015–2016
IncellDx
2015
Microbiology Intern
National Aeronautics and Space Administration
2011–2015
BS, Microbiology, Immunology, and Molecular Genetics
University of California, Los Angeles

Experience

  • 2025–now

    Boston, MA

    LLY
    Director, Genomics
    Lilly
    Director, Genomics
    2026–now
    I lead translational proteomics across late-stage obesity and cardiometabolic trials, including head-to-head comparisons such as SURMOUNT-5, using large-scale proteomics to explain how drugs work and to find biomarkers that inform clinical development.
    Senior Advisor, Genomics
    2025–2026
    I worked with clinicians, biologists, and statisticians on large-scale proteomics from phase 2/3 obesity trials to study drug mechanisms and biomarkers, and built the analysis infrastructure for clinical omics.
  • 2021–2025

    Cambridge, MA

    PFE
    Senior Principal Computational Geneticist
    Pfizer
    Senior Principal Computational Geneticist
    2023–2025
    I worked with cross-functional teams on cardiovascular and renal target discovery, combining human genetics, functional genomics, and large language models. I also led the team that built the cloud infrastructure for genomics analysis across the organization.
    Senior Computational Geneticist
    2021–2023
    I worked with biologists to find new targets for cardiovascular and renal disease using multi-omics data, and I was the genetics expert for indication expansion teams.
  • 2016–2021

    La Jolla, CA

    UCSD
    Graduate Student Researcher
    UC San Diego
    I led the largest genome-wide association study (GWAS) of type 1 diabetes at the time and combined it with single-cell epigenomics to identify new disease-relevant cell types in the pancreas.
  • 2015–2016

    Menlo Park, CA

    IDx
    Development Scientist
    IncellDx
    Development Scientist
    2016
    Research Associate
    2015–2016
    I optimized a cell-based companion diagnostic assay for HIV; the assay was later acquired by a major pharmaceutical company.
  • 2015

    Houston, TX

    NASA
    Microbiology Intern
    National Aeronautics and Space Administration
    Johnson Space Center
    I developed a rapid assay to detect infectious herpesviruses in astronauts.

Education

Selected Publications

  1. Plasma proteomic associations with genetics and health in the UK Biobank
    Measured about 3,000 blood proteins in 54,000 UK Biobank participants and mapped more than 14,000 genetic variants that influence their levels, most of them previously unknown.
    Sun BB, Chiou J, Traylor M, and 62 more authors
    Nature, 2023
  2. Interpreting type 1 diabetes risk with genetics and single-cell epigenomics
    Combined a genetic study of type 1 diabetes in more than 500,000 samples with single-cell maps of the pancreas and implicated exocrine pancreas cells, not just immune cells, in disease risk.
    Chiou J, Geusz RJ, Okino M, and 13 more authors
    Nature, 2021
  3. Integrating genetics with single-cell multiomic measurements across disease states identifies mechanisms of beta cell dysfunction in type 2 diabetes
    Identified two beta cell subtypes whose abundance shifts in type 2 diabetes and whose accessible chromatin is enriched for type 2 diabetes risk variants.
    Wang G*, Chiou J*, Zeng C*, and 18 more authors
    *Equal contribution
    Nature Genetics, 2023
  4. Single-cell chromatin accessibility identifies pancreatic islet cell type- and state-specific regulatory programs of diabetes risk
    Mapped chromatin accessibility in thousands of individual islet cells to show which cell types and cell states carry type 2 diabetes genetic risk.
    Chiou J*, Zeng C*, Cheng Z, and 17 more authors
    *Equal contribution
    Nature Genetics, 2021
  5. Pancreatic islet chromatin accessibility and conformation reveals distal enhancer networks of type 2 diabetes risk
    Mapped 3D chromatin contacts in pancreatic islets to connect distal type 2 diabetes risk variants to the genes they likely regulate.
    Greenwald WW*, Chiou J*, Yan J*, and 19 more authors
    *Equal contribution
    Nature Communications, 2019

Honors & Awards

  • 2023
    • Solving the Science ChallengePfizer Integrative Biology
  • 2020
    • Charles J. Epstein Trainee Award for Excellence in Human Genetics Research, FinalistASHGsource
    • Annual Investigator Meeting ScholarshipHIRNsource
  • 2018–2020
    • Genetics Training Program FellowshipUC San Diegosource
  • 2018
    • Charles J. Epstein Trainee Award for Excellence in Human Genetics Research, SemifinalistASHGsource
    • Graduate Research Fellowship, Honorable MentionNSF
  • 2014
    • J.W. and Nellie MacDowell ScholarshipUCLA

Professional Activities

  • 2023
    • McKinsey Leadership Essentials
  • 2022–now
    • Ad hoc reviewer: Nature Communications, Diabetes, BMJ Open Diabetes Research & Care, Communications Biology, Scientific Reports, BBA: Molecular Basis of Disease
  • 2016–now
    • Member, American Society of Human Genetics (ASHG)

Talks & Presentations

  • 2026

    Milan, Italy

    Tirzepatide was associated with differential proteomic responses compared to semaglutide: exploratory findings from the SURMOUNT-5 trial
    EASD 62nd Annual Meeting
    • Oral presentation
  • 2025

    Boston, MA

    Advancing Early Target Discovery through Large-Scale Proteomics and Expansion Plans for the UKB-PPP
    Festival of Genomics Boston
    • Invited talk

Technical Skills

Statistical Genetics
GWAS ExWAS Fine-mapping Colocalization Mendelian randomization pQTL eQTL Polygenic risk scores Meta-analysis Causal variant-to-gene mapping PLINK REGENIE
Genomics
scRNA-seq scATAC-seq Bulk ATAC-seq Multi-omic integration
Proteomics & Translational Research
Olink SomaScan Clinical trial proteomics Biomarker discovery EHR integration Survival analysis Target identification In silico validation Phenotyping
Machine Learning & AI
Machine learning Predictive modeling Deep learning LLM integration Agentic AI workflows Prompt engineering
Programming
Python R SQL pandas polars dask scanpy PyTorch scikit-learn Plotly Dash Streamlit
Cloud & Infrastructure
AWS (S3, EC2, Batch) HPC clusters Unix Nextflow Docker Singularity Conda Pixi uv Git FAIR data principles