Honghuang Lin, PhD

Adjunct Associate Professor, Boston University Chobanian & Avedisian School of Medicine

Biography

I am a bioinformatician/biostatistician with training in mathematics, machine learning, genetics, and digital medicine. Our lab is mainly focused on the development and application of computational tools to study complex diseases.

1. Identification of genetic causes of complex diseases. We have been involved in multiple large-scale genetic consortiums, such as the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, Trans-Omics for Precision Medicine (TOPMed) program, and Alzheimer's Disease Sequencing Project (ADSP). These studies have identified hundreds of genetic loci associated with atrial fibrillation, heart failure, hypertension, and Alzheimer’s disease.

2. Integration of multi-omics data to understand disease molecular mechanisms. Complex diseases are usually caused by the interplay of genetic and environmental factors. We have identified numerous molecular signatures from gene expression, protein expression, and DNA methylation that are related to aging and cardiovascular disease. We are also developing computational methods to integrate different molecular signatures and build gene interaction networks to study potential disease regulation networks.

3. Development of machine learning models for early disease diagnosis. We have built multiple machine learning models to predict dementia risk from midlife risk factors and neuropsychological tests. In combination with neuroimaging and blood-based measures, we are also developing multimodal machine learning methods to identify new biomarkers that are predictive of future cognitive impairment.

4. Exploration of digital and wearable devices for health monitoring. We have deployed thousands of wearable devices and mobile apps to monitor cardiovascular health and cognitive health. We are integrating active engagement with passive engagement technologies from the habitual environment to make sustained monitoring feasible. Novel analytic strategies are also being developed to analyze big unstructured data to identify potential digital biomarkers that are predictive of future health outcomes.

Publications

  • Published 7/16/2026

    Orchard P, Blackwell TW, Kachuri L, Castaldi PJ, Cho MH, Christenson SA, Durda P, Gabriel S, Hersh CP, Huntsman S, Hwang S, Joehanes R, Johnson M, Li X, Lin H, Liu CT, Liu Y, Mak ACY, Manichaikul AW, Paik DT, Saferali A, Smith JD, Taylor KD, Tracy RP, Wang J, Wang M, Weinstock JS, Weiss J, Wheeler HE, Zhou Y, Zöllner S, Wu JC, Mestroni L, Graw S, Taylor MRG, Ortega VE, Johnson WC, Gan W, Abecasis G, Nickerson DA, Gupta N, Ardlie K, Woodruff PG, Bowler RP, Meyers DA, Reiner A, Kooperberg C, Ziv E, Vasan RS, Larson MG, Cupples LA, Silverman EK, Rich SS, Heard-Costa N, Tang H, Rotter JI, Smith AV, Levy D, Aguet F, Scott LJ, Raffield LM, Parker SCJ, Abe N, Almasy L, Ament S, Anugu P, Auer P, Avramopoulos D, Balasubramanian A, Barr RG, Barwick L, Beaty T, Becker D, Becker L, Beitelshees A, Benos T, Bezerra M, Bis J, Brody J, Broeckel U, Broome J, Bunting K, Buth E, Carey V, Carty C, Casaburi R, Chaffin M, Chang C, Chang YC, Chavan S, Chen BJ, Chen WM, Choi SH, Chuang LM, Chung RH, Conomos M, Cornell E, Crandall C, Crapo J, Curtis J, Damcott C, David S, de Las Fuentes L, de Vries P, Deka R, DeMeo D, Devine S, Dinh H, Doddapaneni H, Duan Q, Duggirala R, Eaton C, Ekunwe L, El Boueiz A, Emery L, Farber C, Farek J, Franceschini N, Frazar C, Fu M, Fullerton SM, Fulton L, Gao S, Gao Y, Gass M, Geiger H, Ghosh A, Gignoux C, Glahn D, Gogarten S, Gong DW, Goring H, Grine D, Gu CC, Guan Y, Hall M, Han Y, Harris D, Heavner B, Herrington D, Hobbs B, Hong E, Hoth K, Hsiung CA, Hu J, Hung YJ, Huston H, Hwu CM, Jackson R, Jain D, Johnsen J, Johnston R, Jones K, Kessler M, Khan A, Khan Z, Kim W, Kimoff J, Kinney G, Kramer H, Lange C, Lange E, Laurie C, Laurie C, LeBoff M, Lee S, Lee WJ, Levine D, Lewis J, Li Y, Lin X, Liu S, Liu Y, Make B, Manning A, Manson J, Martin L, Marton M, Mathai S, May S, McArdle P, McDonald ML, McFarland S, McGoldrick D, McHugh C, Mei H, Meigs J, Menon V, Min N, Moll M, Momin Z, Montasser M, Mychaleckyj JC, Naik R, Naseri T, Natarajan P, Nelson SC, Neltner B, Nessner C, Nkechinyere O, O'Connell J, O'Connor T, Ochs-Balcom H, Okwuonu G, Pankow J, Parker C, Peloso G, Peralta JM, Perez M, Perry J, Peters U, Phillips LS, Pollin T, Becker JP, Boorgula MP, Psaty B, Qiao D, Rafaels N, Rajendran M, Rasmussen-Torvik L, Ratan A, Reed R, Regan E, Reupena MS, Robillard R, Roselli C, Ruczinski I, Runnels A, Russell P, Ryan K, Sabino EC, Salimi S, Salvi S, Salzberg S, Sandow K, Santibanez J, Schwander K, Sciurba F, Sériès F, Shetty A, Shetty A, Silver B, Skomro R, Smith T, Smoller S, Snively B, Stilp AM, Storm G, Streeten E, Su JL, Sung YJ, Sylvia J, Szpiro A, Taub M, Taylor S, Thornton TA, Threlkeld M, Tinker L, Tirschwell D, Tiwari H, Tong C, Tsai M, Vaidya D, Walker T, Wallace R, Walts A, Wang FF, Wang H, Watson K, Watt J, Weng LC, Wessel J, Williams K, Wilson C, Wilson J, Winterkorn L, Wong Q, Wu B, Xu H, Yanek L, Yang I, Zekavat SM, Zhao SX, Zhao W, Zhu X. Cross-cohort analysis of expression and splicing quantitative trait loci in TOPMed. Science. 2026 Jul 16; 393(6808):eadx2989. PMID: 42462027.

    Read at: PubMed

  • Published 7/4/2026

    Foris V, Kim K, Tern C, Qian Y, Yu J, Washko G, Wade RC, Wells JM, Lin H, O'Connor GT, Smith AV, Gabriel SB, Gupta N, Silverman EK, Boueiz A, Cho MH. Genetic Determinants of Pulmonary Artery Size in over 50,000 Subjects with and without COPD. medRxiv. 2026 Jul 04. PMID: 42428084.

    Read at: PubMed

  • Published 6/23/2026

    Pope MK, Chugh H, Truyen TTTT, Mathias M, Uy-Evanado A, Lin H, Atar D, Bosson N, Reinier K, Benjamin EJ, Chugh SS. Dynamic Risk Trajectories for Sudden Cardiac Arrest: The Role of Recurrent Cardiovascular Events. J Am Heart Assoc. 2026 Jul 07; 15(13):e049853. PMID: 42333668.

    Read at: PubMed

  • Published 5/6/2026

    Shireen Kanamgode S, Cucchi E, Anders S, Fouayzi H, Hughes AL, Lin H, Bosch N, Walkey A. Validation and Early Application of the ProVent Score in a Contemporary ICU Cohort. J Intensive Care Med. 2026 May 06; 8850666261447248. PMID: 42089714.

    Read at: PubMed

  • Published 4/23/2026

    Ye Z, Zai A, Wang B, Bennett A, Guilarte-Walker YG, Wong K, Zai AH, Erban S, Lin H. Leveraging routine clinical data for dementia risk prediction using machine learning. J Alzheimers Dis. 2026 Jun; 111(4):1516-1526. PMID: 42024083.

    Read at: PubMed

Other Positions

  • Member, BU-BMC Cancer Center
    Boston University
  • Investigator
    Framingham Heart Study
  • Member, Evans Center for Interdisciplinary Biomedical Research
    Boston University

Education

  • National University of Singapore (NUS), PhD
  • Peking University, BA
  • Peking University, BS