Henry is an MD-PhD candidate and Knight-Hennessy Scholar in the Medical Scientist Training Program and the Biomedical Informatics Program, where he is advised by Professor Russ Altman. He develops machine-learning methods to study the effects of complex genetic variation on human disease mechanisms, with focus on neurological and ophthalmic disorders. His goal is to translate genomic discoveries into disease-modifying therapies.

He received an AB summa cum laude from Harvard University in 2017, where he studied genetic mechanisms of retinal development with Professor Joshua Sanes. He then graduated with an MPhil with distinction from the University of Cambridge as a Gates Cambridge Scholar. He previously worked at Leaps by Bayer and the Massachusetts Eye and Ear Infirmary and has received several awards related to research and teaching.

All Publications

  • Gene set proximity analysis: expanding gene set enrichment analysis through learned geometric embeddings, with drug-repurposing applications in COVID-19. Bioinformatics (Oxford, England) Cousins, H., Hall, T., Guo, Y., Tso, L., Tzeng, K. T., Cong, L., Altman, R. B. 2022


    MOTIVATION: Gene set analysis methods rely on knowledge-based representations of genetic interactions in the form of both gene set collections and protein-protein interaction (PPI) networks. However, explicit representations of genetic interactions often fail to capture complex interdependencies among genes, limiting the analytic power of such methods.RESULTS: We propose an extension of gene set enrichment analysis to a latent embedding space reflecting PPI network topology, called gene set proximity analysis (GSPA). Compared with existing methods, GSPA provides improved ability to identify disease-associated pathways in disease-matched gene expression datasets, while improving reproducibility of enrichment statistics for similar gene sets. GSPA is statistically straightforward, reducing to a version of traditional gene set enrichment analysis through a single user-defined parameter. We apply our method to identify novel drug associations with SARS-CoV-2 viral entry. Finally, we validate our drug association predictions through retrospective clinical analysis of claims data from 8 million patients, supporting a role for gabapentin as a risk factor and metformin as a protective factor for severe COVID-19.AVAILABILITY: GSPA is available for download as a command-line Python package at INFORMATION: Supplementary data are available at Bioinformatics online.

    View details for DOI 10.1093/bioinformatics/btac735

    View details for PubMedID 36394254

  • Iterative Machine Learning: A Test Case for the Detection of Disc Hemorrhage Brown, A. C., Cousins, H., Esquenazi, K., Kim, Y., Cousins, C., Elze, T., Harris, A., Coote, M. A., Pasquale, L. R. ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2022
  • Genetic Correlations between Corneal Biophysical Parameters and Anthropomorphic Traits Cousins, H., Cousins, C., Valluru, G., Liu, Y., Ahmad, S., Altman, R. B., Pasquale, L. R. ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2022
  • Automated Machine Learning vs. Inception for the Autonomous Detection of Disc Hemorrhage Brown, A. C., Cousins, H., Cousins, C., Chadha, N., Vinod, K., Harris, A., Topouzis, F., Kilintzis, V., Coote, M., Pasquale, L. R. ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2021
  • Influence of team composition on turnover and efficiency of total hip and knee arthroplasty. The bone & joint journal Cahan, E. M., Cousins, H. C., Steere, J. T., Segovia, N. A., Miller, M. D., Amanatullah, D. F. 2021; 103-B (2): 347–52


    AIMS: Surgical costs are a major component of healthcare expenditures in the USA. Intraoperative communication is a key factor contributing to patient outcomes. However, the effectiveness of communication is only partially determined by the surgeon, and understanding how non-surgeon personnel affect intraoperative communication is critical for the development of safe and cost-effective staffing guidelines. Operative efficiency is also dependent on high-functioning teams and can offer a proxy for effective communication in highly standardized procedures like primary total hip and knee arthroplasty. We aimed to evaluate how the composition and dynamics of surgical teams impact operative efficiency during arthroplasty.METHODS: We performed a retrospective review of staff characteristics and operating times for 112 surgeries (70 primary total hip arthroplasties (THAs) and 42 primary total knee arthroplasties (TKAs)) conducted by a single surgeon over a one-year period. Each surgery was evaluated in terms of operative duration, presence of surgeon-preferred staff, and turnover of trainees, nurses, and other non-surgical personnel, controlling cases for body mass index, presence of osteoarthritis, and American Society of Anesthesiologists (ASA) score.RESULTS: Turnover among specific types of operating room staff, including the anaesthesiologist (p = 0.011), circulating nurse (p = 0.027), and scrub nurse (p = 0.006), was significantly associated with increased operative duration. Furthermore, the presence of medical students and nursing students were associated with improved intraoperative efficiency in TKA (p = 0.048) and THA (p = 0.015), respectively. The presence of surgical fellows (p > 0.05), vendor representatives (p > 0.05), and physician assistants (p > 0.05) had no effect on intraoperative efficiency. Finally, the presence of the surgeon's 'preferred' staff did not significantly shorten operative duration, except in the case of residents (p = 0.043).CONCLUSION: Our findings suggest that active management of surgical team turnover and composition may provide a means of improving intraoperative efficiency during THA and TKA. Cite this article: Bone Joint J 2021;103-B(2):347-352.

    View details for DOI 10.1302/0301-620X.103B2.BJJ-2020-0170.R2

    View details for PubMedID 33517742

  • Regional Infoveillance of COVID-19 Case Rates: Analysis of Search-Engine Query Patterns. Journal of medical Internet research Cousins, H., Cousins, C., Harris, A., Pasquale, L. 2020


    BACKGROUND: Timely allocation of medical resources for COVID-19 requires early detection of regional outbreaks. Internet browsing data may predict case outbreaks in local populations that are yet to be confirmed.OBJECTIVE: We investigated whether search-engine query patterns can help to predict COVID-19 case rates at the state and metropolitan-area level in the United States.METHODS: We used regional confirmed case data from the New York Times and Google Trends results from 50 states and 166 county-based designated market areas (DMA). We identified search terms whose activity precedes and correlates with confirmed case rates at the national level. We used univariate regression to construct a composite explanatory variable based on best-fitting search queries offset by temporal lags. We measured the raw and z-transformed Pearson correlation and root-mean-square error (RMSE) of the explanatory variable with out-of-sample case rate data at the state and DMA level.RESULTS: Predictions were highly correlated with confirmed case rates at the state (mean r = .69; 95% confidence interval (CI): .51-.81; median RMSE 1.27; interquartile range (IQR) 1.48) and DMA level (mean r = .51, 95% CI .39-.61; median RMSE 4.38; IQR: 1.80), using search data available up to 10 days prior to confirmed case rates. They fit case-rate activity in 49 of 50 states and in 103 of 166 DMA at a significance level of .05.CONCLUSIONS: Identifiable patterns in search query activity may help to predict emerging regional outbreaks of COVID-19, although they remain vulnerable to stochastic changes in search intensity.

    View details for DOI 10.2196/19483

    View details for PubMedID 32692691

  • Toward Precision Medicine for Neurological and Neuropsychiatric Disorders CELL STEM CELL Gibbs, R. M., Lipnick, S., Bateman, J. W., Chen, L., Cousins, H. C., Hubbard, E. G., Jowett, G., LaPointe, D. S., McGredy, M. J., Odonkor, M. N., Repetti, G., Thomas, E., Rubin, L. L. 2018; 23 (1): 21–24


    The genetic complexity, clinical variability, and inaccessibility of affected tissue in neurodegenerative and neuropsychiatric disorders have largely prevented the development of effective disease-modifying therapeutics. A precision medicine approach that integrates genomics, deep clinical phenotyping, and patient stem cell models may facilitate identification of underlying biological drivers and targeted drug development.

    View details for DOI 10.1016/j.stem.2018.05.019

    View details for Web of Science ID 000438144700010

    View details for PubMedID 29887317

  • Role for Wnt Signaling in Retinal Neuropil Development: Analysis via RNA-Seq and In Vivo Somatic CRISPR Mutagenesis NEURON Sarin, S., Zuniga-Sanchez, E., Kurmangaliyev, Y. Z., Cousins, H., Patel, M., Hernandez, J., Zhang, K. X., Samuel, M. A., Morey, M., Sanes, J. R., Zipursky, S. 2018; 98 (1): 109-+


    Screens for genes that orchestrate neural circuit formation in mammals have been hindered by practical constraints of germline mutagenesis. To overcome these limitations, we combined RNA-seq with somatic CRISPR mutagenesis to study synapse development in the mouse retina. Here synapses occur between cellular layers, forming two multilayered neuropils. The outer neuropil, the outer plexiform layer (OPL), contains synapses made by rod and cone photoreceptor axons on rod and cone bipolar dendrites, respectively. We used RNA-seq to identify selectively expressed genes encoding cell surface and secreted proteins and CRISPR-Cas9 electroporation with cell-specific promoters to assess their roles in OPL development. Among the genes identified in this way are Wnt5a and Wnt5b. They are produced by rod bipolars and activate a non-canonical signaling pathway in rods to regulate early OPL patterning. The approach we use here can be applied to other parts of the brain.

    View details for DOI 10.1016/j.neuron.2018.03.004

    View details for Web of Science ID 000429192100013

    View details for PubMedID 29576390

    View details for PubMedCentralID PMC5930001

  • Nailfold Capillary Morphology in Alzheimer's Disease Dementia JOURNAL OF ALZHEIMERS DISEASE Cousins, C. C., Alosco, M. L., Cousins, H. C., Chua, A., Steinberg, E. G., Chapman, K. R., Bing-Canar, H., Tripodis, Y., Knepper, P. A., Stern, R. A., Pasquale, L. R. 2018; 66 (2): 601–11


    Cerebrovascular disease (CVD) is highly comorbid with Alzheimer's disease (AD), yet its role is not entirely understood. Nailfold video capillaroscopy (NVC) is a noninvasive method of live imaging the capillaries near the fingernail's cuticle and may help to describe further vascular contributions to AD.To examine finger nailfold capillary morphology using NVC in subjects with AD dementia, mild cognitive impairment (MCI), and normal cognition (NC).We evaluated nailfold capillary hemorrhages, avascular zones ≥100 microns, and degree of tortuosity in 28 NC, 15 MCI, and 18 AD dementia subjects using NVC. Tortuosity was measured with a semi-quantitative rating scale. To assess the relation between nailfold capillary morphological features and diagnostic grouping, univariate and multivariable logistic regression models were fit to the data.56% of subjects with AD dementia compared to 14% with NC and 13% with MCI displayed moderate to severe tortuosity. Greater severity of tortuosity was associated with 10.6-fold (95% confidence interval [CI]: 2.4, 46.2; p = 0.0018) and 7.4-fold (95% CI: 1.3, 41.3; p = 0.023) increased odds of AD dementia relative to NC and MCI, respectively, after adjusting for multiple covariates.Greater nailfold capillary tortuosity was found in participants with AD dementia compared to those with MCI or NC. These data provide preliminary evidence of a systemic microvasculopathy in AD that may be noninvasively and inexpensively evaluated through NVC.

    View details for DOI 10.3233/JAD-180658

    View details for Web of Science ID 000451224700017

    View details for PubMedID 30320588

  • Roles for Wnt signaling in synapse organization revealed by CRISPR/Cas9-mediated mutagenesis in the mouse retina. Sarin, S., Zuniga-Sanchez, E., Patel, M. B., Zhang, K., Cousins, H., Sanes, J. R., Zipursky, S. AMER SOC CELL BIOLOGY. 2016