Bio


Postdoctoral researcher in the Snyder Lab. My research focuses on the human gut microbiome, and I am involved in multiple multiomic projects investigating how physiological systems through the human body interact across different lifestyles and health states. I perform both wet and dry lab aspects of multiomics analyses, and am involved in two coronavirus research projects including handling of positive SARS-COV-2 samples.

Stanford Advisors


Lab Affiliations


All Publications


  • Early Detection of SARS-CoV-2 and other Infections in Solid Organ Transplant Recipients and Household Members using Wearable Devices. Transplant international : official journal of the European Society for Organ Transplantation Keating, B. J., Mukhtar, E. H., Elftmann, E. D., Eweje, F. R., Gao, H., Ibrahim, L. I., Kathawate, R. G., Lee, A. C., Li, E. H., Moore, K. A., Nair, N., Chaluvadi, V., Reason, J., Zanoni, F., Honkala, A. T., Al-Ali, A. K., Alrubaish, F. A., Ahmad Al-Mozaini, M., Al-Muhanna, F. A., Al-Romaih, K., Goldfarb, S. B., Kellogg, R., Kiryluk, K., Kizilbash, S. J., Kohut, T. J., Kumar, J., O'Connor, M. J., Rand, E. B., Redfield, R. R., Rolnik, B., Rossano, J., Sanchez, P. G., Alavi, A., Bahmani, A., Bogu, G. K., Brooks, A. W., Metwally, A. A., Mishra, T., Marks, S. D., Montgomery, R. A., Fishman, J. A., Amaral, S., Jacobson, P. A., Wang, M., Snyder, M. P. 2021

    Abstract

    The increasing global prevalence of SARS-CoV-2 and the resulting COVID-19 disease pandemic pose significant concerns for clinical management of solid organ transplant recipients (SOTR). Wearable devices that can measure physiologic changes in biometrics including heart rate, heart rate variability, body temperature, respiratory, activity (such as steps taken per day) and sleep patterns and blood oxygen saturation, show utility for the early detection of infection before clinical presentation of symptoms. Recent algorithms developed using preliminary wearable datasets show that SARS-CoV-2 is detectable before clinical symptoms in >80% of adults. Early detection of SARS-CoV-2, influenza, and other pathogens in SOTR, and their household members, could facilitate early interventions such as self-isolation and early clinical management of relevant infection(s). Ongoing studies testing the utility of wearable devices such as smartwatches for early detection of SARS-CoV-2 and other infections in the general population are reviewed here, along with the practical challenges to implementing these processes at scale in pediatric and adult SOTR, and their household members. The resources and logistics, including transplant specific analyses pipelines to account for confounders such as polypharmacy and comorbidities, required in studies of pediatric and adult SOTR for the robust early detection of SARS-CoV-2 and other infections are also reviewed.

    View details for DOI 10.1111/tri.13860

    View details for PubMedID 33735480

  • Pre-symptomatic detection of COVID-19 from smartwatch data. Nature biomedical engineering Mishra, T., Wang, M., Metwally, A. A., Bogu, G. K., Brooks, A. W., Bahmani, A., Alavi, A., Celli, A., Higgs, E., Dagan-Rosenfeld, O., Fay, B., Kirkpatrick, S., Kellogg, R., Gibson, M., Wang, T., Hunting, E. M., Mamic, P., Ganz, A. B., Rolnik, B., Li, X., Snyder, M. P. 2020

    Abstract

    Consumer wearable devices that continuously measure vital signs have been used to monitor the onset of infectious disease. Here, we show that data from consumer smartwatches can be used for the pre-symptomatic detection of coronavirus disease 2019 (COVID-19). We analysed physiological and activity data from 32 individuals infected with COVID-19, identified from a cohort of nearly 5,300 participants, and found that 26 of them (81%) had alterations in their heart rate, number of daily steps or time asleep. Of the 25 cases of COVID-19 with detected physiological alterations for which we had symptom information, 22 were detected before (or at) symptom onset, with four cases detected at least nine days earlier. Using retrospective smartwatch data, we show that 63% of the COVID-19 cases could have been detected before symptom onset in real time via a two-tiered warning system based on the occurrence of extreme elevations in resting heart rate relative to the individual baseline. Our findings suggest that activity tracking and health monitoring via consumer wearable devices may be used for the large-scale, real-time detection of respiratory infections, often pre-symptomatically.

    View details for DOI 10.1038/s41551-020-00640-6

    View details for PubMedID 33208926