Honghuang Lin, PhD
Adjunct Associate Professor
Boston University Chobanian & Avedisian School of Medicine
Computational Biomedicine

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

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.

Boston University
BU-BMC Cancer Center

Framingham Heart Study

Boston University
Evans Center for Interdisciplinary Biomedical Research

Integrated Digital Technology Platform for Optimization of Precision Brain Health
07/01/2020 - 06/30/2024 (Multi-PI)
PI: Honghuang Lin, PhD
American Heart Association

Identification of digital biomarkers for Alzheimer's disease
03/01/2020 - 02/28/2023 (PI)
Alzheimer's Association

Assessing Alzheimer disease risk and heterogeneity using multimodal machine learning approaches
09/15/2021 - 12/31/2021 (Multi-PI)
PI: Honghuang Lin, PhD
NIH/National Institute on Aging


Biostatistical analysis of TOPMed genetics data
06/01/2019 - 05/31/2020 (PI)
University of Connecticut Health Center

Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.

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  1. Zhang Y, Wang X, Pathiravasan CH, Spartano NL, Lin H, Borrelli B, Benjamin EJ, McManus DD, Larson MG, Vasan RS, Shah RV, Lewis GD, Liu C, Murabito JM, Nayor M. Association of Smartwatch-Based Heart Rate and Physical Activity With Cardiorespiratory Fitness Measures in the Community: Cohort Study. J Med Internet Res. 2024 Jun 13; 26:e56676.View Related Profiles. PMID: 38870519; DOI: 10.2196/56676;
  2. Xu H, Gupta S, Dinsmore I, Kollu A, Cawley AM, Anwar MY, Chen HH, Petty LE, Seshadri S, Graff M, Below P, Brody JA, Chittoor G, Fisher-Hoch SP, Heard-Costa NL, Levy D, Lin H, Loos RJ, Mccormick JB, Rotter JI, Mirshahi T, Still CD, Destefano A, Cupples LA, Mohlke KL, North KE, Justice AE, Liu CT. Integrating Genetic and Transcriptomic Data to Identify Genes Underlying Obesity Risk Loci. medRxiv. 2024 Jun 12.View Related Profiles. PMID: 38903089; PMCID: PMC11188121; DOI: 10.1101/2024.06.11.24308730;
  3. Herbert C, Wang B, Lin H, Yan Y, Hafer N, Pretz C, Stamegna P, Wright C, Suvarna T, Harman E, Schrader S, Nowak C, Kheterpal V, Orvek E, Wong S, Zai A, Barton B, Gerber BS, Lemon SC, Filippaios A, Gibson L, Greene S, Colubri A, Achenbach C, Murphy R, Heetderks W, Manabe YC, O'Connor L, Fahey N, Luzuriaga K, Broach J, Roth K, McManus DD, Soni A. Performance of and Severe Acute Respiratory Syndrome Coronavirus 2 Diagnostics Based on Symptom Onset and Close Contact Exposure: An Analysis From the Test Us at Home Prospective Cohort Study. Open Forum Infect Dis. 2024 Jun; 11(6):ofae304. PMID: 38911947; PMCID: PMC11191649; DOI: 10.1093/ofid/ofae304;
  4. Frederiksen TC, Benjamin EJ, Trinquart L, Lin H, Dahm CC, Christiansen MK, Jensen HK, Preis SR, Kornej J. Bidirectional Association Between Atrial Fibrillation and Myocardial Infarction, and Relation to Mortality in the Framingham Heart Study. J Am Heart Assoc. 2024 Jun 04; 13(11):e032226.View Related Profiles. PMID: 38780172; DOI: 10.1161/JAHA.123.032226;
  5. Herbert C, Manabe YC, Filippaios A, Lin H, Wang B, Achenbach C, Kheterpal V, Hartin P, Suvarna T, Harman E, Stamegna P, Rao LV, Hafer N, Broach J, Luzuriaga K, Fitzgerald KA, McManus DD, Soni A. Differential Viral Dynamics by Sex and Body Mass Index During Acute SARS-CoV-2 Infection: Results From a Longitudinal Cohort Study. Clin Infect Dis. 2024 May 15; 78(5):1185-1193. PMID: 37972270; PMCID: PMC11093673; DOI: 10.1093/cid/ciad701;
  6. Jiang MZ, Gaynor SM, Li X, Van Buren E, Stilp A, Buth E, Wang FF, Manansala R, Gogarten SM, Li Z, Polfus LM, Salimi S, Bis JC, Pankratz N, Yanek LR, Durda P, Tracy RP, Rich SS, Rotter JI, Mitchell BD, Lewis JP, Psaty BM, Pratte KA, Silverman EK, Kaplan RC, Avery C, North KE, Mathias RA, Faraday N, Lin H, Wang B, Carson AP, Norwood AF, Gibbs RA, Kooperberg C, Lundin J, Peters U, Dupuis J, Hou L, Fornage M, Benjamin EJ, Reiner AP, Bowler RP, Lin X, Auer PL, Raffield LM. Whole genome sequencing based analysis of inflammation biomarkers in the Trans-Omics for Precision Medicine (TOPMed) consortium. Hum Mol Genet. 2024 May 15.View Related Profiles. PMID: 38747556; DOI: 10.1093/hmg/ddae050;
  7. Ding H, Wang B, Hamel AP, Karjadi C, Ang TFA, Au R, Lin H. Exploring cognitive progression subtypes in the Framingham Heart Study. Alzheimers Dement (Amst). 2024; 16(1):e12574.View Related Profiles. PMID: 38515438; PMCID: PMC10955221; DOI: 10.1002/dad2.12574;
  8. Wang Y, Sarnowski C, Lin H, Pitsillides AN, Heard-Costa NL, Choi SH, Wang D, Bis JC, Blue EE, Boerwinkle E, De Jager PL, Fornage M, Wijsman EM, Seshadri S, Dupuis J, Peloso GM, DeStefano AL. Key variants via the Alzheimer's Disease Sequencing Project whole genome sequence data. Alzheimers Dement. 2024 May; 20(5):3290-3304.View Related Profiles. PMID: 38511601; PMCID: PMC11095439; DOI: 10.1002/alz.13705;
  9. Ding H, Kim M, Searls E, Sunderaraman P, De Anda-Duran I, Low S, Popp Z, Hwang PH, Li Z, Goyal K, Hathaway L, Monteverde J, Rahman S, Igwe A, Kolachalama VB, Au R, Lin H. Digital neuropsychological measures by defense automated neurocognitive assessment: reference values and clinical correlates. Front Neurol. 2024; 15:1340710.View Related Profiles. PMID: 38426173; PMCID: PMC10902432; DOI: 10.3389/fneur.2024.1340710;
  10. Leung YY, Naj AC, Chou YF, Valladares O, Schmidt M, Hamilton-Nelson K, Wheeler N, Lin H, Gangadharan P, Qu L, Clark K, Kuzma AB, Lee WP, Cantwell L, Nicaretta H, Haines J, Farrer L, Seshadri S, Brkanac Z, Cruchaga C, Pericak-Vance M, Mayeux RP, Bush WS, Destefano A, Martin E, Schellenberg GD, Wang LS. Human whole-exome genotype data for Alzheimer's disease. Nat Commun. 2024 Jan 23; 15(1):684.View Related Profiles. PMID: 38263370; PMCID: PMC10805795; DOI: 10.1038/s41467-024-44781-7;
Showing 10 of 224 results. Show More

This graph shows the total number of publications by year, by first, middle/unknown, or last author.

Bar chart showing 224 publications over 20 distinct years, with a maximum of 29 publications in 2023

In addition to these self-described keywords below, a list of MeSH based concepts is available here.

Machine learning
Microarray data analysis
Next generation sequencing
Multi-omics data integration

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