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 7/21/2025

    Smit RAJ, Wade KH, Hui Q, Arias JD, Yin X, Christiansen MR, Yengo L, Preuss MH, Nakabuye M, Rocheleau G, Graham SE, Buchanan VL, Chittoor G, Graff M, Guindo-Martínez M, Lu Y, Marouli E, Sakaue S, Spracklen CN, Vedantam S, Wilson EP, Chen SH, Ferreira T, Ji Y, Karaderi T, Lüll K, Machado M, Malden DE, Medina-Gomez C, Moore A, Rüeger S, Akiyama M, Allison MA, Alvarez M, Andersen MK, Appadurai V, Arbeeva L, Bartell E, Bhaskar S, Bielak LF, Bis JC, Bollepalli S, Bork-Jensen J, Bradfield JP, Bradford Y, Brandl C, Braund PS, Brody JA, Broeckel U, Burgdorf KS, Cade BE, Cai Q, Camarda S, Campbell A, Cañadas-Garre M, Chai JF, Chesi A, Choi SH, Christofidou P, Couture C, Cuellar-Partida G, Danning R, Degenhardt F, Delgado GE, Delitala A, Demirkan A, Deng X, Dietl A, Dimitriou M, Dimitrov L, Dorajoo R, Eichelmann F, Eliasen AU, Engmann JE, Erdos MR, Fairhurst-Hunter Z, Farmaki AE, Faul JD, Fernandez-Lopez JC, Forer L, Frank M, Freitag-Wolf S, Fritsche LG, Fuchsberger C, Galesloot TE, Gao Y, Geller F, Giannakopoulou O, Giulianini F, Gjesing AP, Goel A, Gordon SD, Gorski M, Grove J, Guo X, Gustafsson S, Haessler J, Hansen TF, Havulinna AS, Haworth SJ, Heard-Costa N, Hemerich D, Highland HM, Hindy G, Ho YL, Hofer E, Holliday E, Horn K, Hornsby WE, Hottenga JJ, Huang H, Huang J, Huerta-Chagoya A, Huo S, Hwang MY, Hwu CM, Iha H, Ikeda DD, Isono M, Jackson AU, Jansen IE, Jiang Y, Johansson I, Jonsson A, Jørgensen T, Kalafati IP, Kanai M, Kanoni S, Kårhus LL, Kasturiratne A, Katsuya T, Kawaguchi T, Kember RL, Kentistou KA, Kim D, Kim HN, Kim YJ, Kleber ME, Knol MJ, Kurbasic A, Lauzon M, Le P, Lea R, Lee JY, Lee WJ, Leonard HL, Li H, Li SA, Li X, Li X, Liang J, Lin H, Lin K, Liu J, Liu X, Lo KS, Long J, Lores-Motta L, Luan J, Lyssenko V, Lyytikäinen LP, Mahajan A, Malik MZ, Mamakou V, Mangino M, Manichaikul A, Marten J, Mattheisen M, McDaid AF, Mei Q, Meiselbach H, Melendez TL, Milaneschi Y, Miller JE, Millwood IY, Mishra PP, Mitchell RE, Møllehave LT, Mononen N, Mucha S, Munz M, Mykkänen J, Nakatochi M, Nardone GG, Nelson CP, Nethander M, Nho CW, Nielsen AA, Nolte IM, Nongmaithem SS, Noordam R, Ntalla I, Nutile T, Pandit A, Pauper M, Petersen ERB, Petersen LV, Piluso F, Polašek O, Poveda A, Pyarajan S, Raffield LM, Rakugi H, Ramirez J, Rasheed A, Raven D, Rayner NW, Riveros C, Rohde R, Ruggiero D, Ruotsalainen SE, Ryan KA, Sabater-Lleal M, Santin A, Saxena R, Scholz M, Shen B, Shi J, Shin JH, Sidore C, Sidorenko J, Sim X, Slieker RC, Smith AV, Smith JA, Smyth LJ, Southam L, Steinthorsdottir V, Sun L, Takeuchi F, Taylor KD, Tayo BO, Tcheandjieu C, Terzikhan N, Tesolin P, Teumer A, Theusch E, Thompson DJ, Thorleifsson G, Timmers PRHJ, Trompet S, Turman C, Vaccargiu S, van der Laan SW, van der Most PJ, van Klinken JB, van Setten J, Verma SS, Verweij N, Veturi Y, Wang CA, Wang C, Wang JS, Wang L, Wang YX, Wang Z, Warren HR, Bin Wei W, Wen W, Wheeler WA, Wickremasinghe AR, Wielscher M, Winsvold BS, Wong A, Wuttke M, Xia R, Yamamoto K, Yang J, Yao J, Young H, Yousri NA, Yu L, Zeng L, Zhang W, Zhang X, Zhao JH, Zhao W, Zhou W, Zimmermann ME, Zoledziewska M, 't Hart LM, Adair LS, Adams HHH, Aguilar-Salinas CA, Al-Mulla F, Arnett DK, Asselbergs FW, Åsvold BO, Attia J, Banas B, Bandinelli S, Beilin LJ, Bennett DA, Bergler T, Bharadwaj D, Biino G, Boerwinkle E, Böger CA, Borja JB, Bouchard C, Bowden DW, Brandslund I, Brumpton B, Buring JE, Caulfield MJ, Chambers JC, Chandak GR, Chanock SJ, Chaturvedi N, Ida Chen YD, Chen Z, Cheng CY, Cho YS, Christensen K, Christophersen IE, Ciullo M, Cole JW, Collins FS, Concas MP, Cooper RS, Cruz M, Cucca F, Cutler MJ, Damrauer SM, Dantoft TM, de Borst GJ, de Geus EJC, de Groot LCPGM, De Jager PL, de Kleijn DPV, de Silva HJ, Dedoussis GV, den Hollander AI, Du S, Easton DF, Eckardt KU, Elders PJM, Eliassen AH, Ellinor PT, Elmståhl S, Erdmann J, Evans MK, Fatkin D, Feenstra B, Feitosa MF, Ferrucci L, Florez JC, Ford I, Fornage M, Franke A, Franks PW, Freedman BI, Gieger C, Girotto G, Golightly YM, et al. Polygenic prediction of body mass index and obesity through the life course and across ancestries. Nat Med. 2025 Jul 21. PMID: 40691366.

    Read at: PubMed

  • Published 6/20/2025

    Rizvi N, Lin H, Beiser AS, Spartano NL. How Do Occupational Sedentary Behavior and Occupational Cognitive Complexity Relate to Cognitive Function? A Cross-Sectional Study. Health Sci Rep. 2025 Jun; 8(6):e70949. PMID: 40547068.

    Read at: PubMed

  • Published 5/20/2025

    Truyen TTTT, Lin H, Mathias M, Chugh H, Reinier K, Benjamin EJ, Chugh SS. Validation of a Novel Risk Prediction Score for Sudden Cardiac Death in the Framingham Heart Study. Circ Arrhythm Electrophysiol. 2025 Jun; 18(6):e013647. PMID: 40391444.

    Read at: PubMed

  • Published 4/22/2025

    Ding H, Madan S, Searls E, McNulty M, Low S, Li Z, Ho K, Rahman S, Igwe A, Popp Z, Hwang PH, De Anda-Duran I, Kolachalama VB, Mez J, Alosco ML, Thomas RJ, Au R, Lin H. Exploring nightly variability and clinical influences on sleep measures: insights from a digital brain health platform. Sleep Med. 2025 Jul; 131:106532. PMID: 40306226.

    Read at: PubMed

  • Published 4/3/2025

    Paul TJ, Sadaniantz K, Soni A, Asaker JC, Pathiravasan CH, Mehawej J, Filippaios A, Zhang Y, Wang Z, Liu C, Lin H, Murabito JM, McManus DD, Kovell L. Patterns of Adherence to Home Blood Pressure Monitoring Among Men and Women in the Electronic Framingham Heart Study. medRxiv. 2025 Apr 03. PMID: 40236403.

    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