Stanford Advisors

All Publications

  • Multi-omics microsampling for the profiling of lifestyle-associated changes in health. Nature biomedical engineering Shen, X., Kellogg, R., Panyard, D. J., Bararpour, N., Castillo, K. E., Lee-McMullen, B., Delfarah, A., Ubellacker, J., Ahadi, S., Rosenberg-Hasson, Y., Ganz, A., Contrepois, K., Michael, B., Simms, I., Wang, C., Hornburg, D., Snyder, M. P. 2023


    Current healthcare practices are reactive and use limited physiological and clinical information, often collected months or years apart. Moreover, the discovery and profiling of blood biomarkers in clinical and research settings are constrained by geographical barriers, the cost and inconvenience of in-clinic venepuncture, low sampling frequency and the low depth of molecular measurements. Here we describe a strategy for the frequent capture and analysis of thousands of metabolites, lipids, cytokines and proteins in 10 μl of blood alongside physiological information from wearable sensors. We show the advantages of such frequent and dense multi-omics microsampling in two applications: the assessment of the reactions to a complex mixture of dietary interventions, to discover individualized inflammatory and metabolic responses; and deep individualized profiling, to reveal large-scale molecular fluctuations as well as thousands of molecular relationships associated with intra-day physiological variations (in heart rate, for example) and with the levels of clinical biomarkers (specifically, glucose and cortisol) and of physical activity. Combining wearables and multi-omics microsampling for frequent and scalable omics may facilitate dynamic health profiling and biomarker discovery.

    View details for DOI 10.1038/s41551-022-00999-8

    View details for PubMedID 36658343

  • The metabolomics of human aging: Advances, challenges, and opportunities. Science advances Panyard, D. J., Yu, B., Snyder, M. P. 2022; 8 (42): eadd6155


    As the global population becomes older, understanding the impact of aging on health and disease becomes paramount. Recent advancements in multiomic technology have allowed for the high-throughput molecular characterization of aging at the population level. Metabolomics studies that analyze the small molecules in the body can provide biological information across a diversity of aging processes. Here, we review the growing body of population-scale metabolomics research on aging in humans, identifying the major trends in the field, implicated biological pathways, and how these pathways relate to health and aging. We conclude by assessing the main challenges in the research to date, opportunities for advancing the field, and the outlook for precision health applications.

    View details for DOI 10.1126/sciadv.add6155

    View details for PubMedID 36260671

  • Cerebrospinal Fluid Sphingomyelins in Alzheimer's Disease, Neurodegeneration, and Neuroinflammation. Journal of Alzheimer's disease : JAD Morrow, A., Panyard, D. J., Deming, Y. K., Jonaitis, E., Dong, R., Vasiljevic, E., Betthauser, T. J., Kollmorgen, G., Suridjan, I., Bayfield, A., Van Hulle, C. A., Zetterberg, H., Blennow, K., Carlsson, C. M., Asthana, S., Johnson, S. C., Engelman, C. D. 2022


    BACKGROUND: Sphingomyelin (SM) levels have been associated with Alzheimer's disease (AD), but the association direction has been inconsistent and research on cerebrospinal fluid (CSF) SMs has been limited by sample size, breadth of SMs examined, and diversity of biomarkers available.OBJECTIVE: Here, we seek to build on our understanding of the role of SM metabolites in AD by studying a broad range of CSF SMs and biomarkers of AD, neurodegeneration, and neuroinflammation.METHODS: Leveraging two longitudinal AD cohorts with metabolome-wide CSF metabolomics data (n = 502), we analyzed the relationship between the levels of 12 CSF SMs, and AD diagnosis and biomarkers of pathology, neurodegeneration, and neuroinflammation using logistic, linear, and linear mixed effects models.RESULTS: No SMs were significantly associated with AD diagnosis, mild cognitive impairment, or amyloid biomarkers. Phosphorylated tau, neurofilament light, alpha-synuclein, neurogranin, soluble triggering receptor expressed on myeloid cells 2, and chitinase-3-like-protein 1 were each significantly, positively associated with at least 5 of the SMs.CONCLUSION: The associations between SMs and biomarkers of neurodegeneration and neuroinflammation, but not biomarkers of amyloid or diagnosis of AD, point to SMs as potential biomarkers for neurodegeneration and neuroinflammation that may not be AD-specific.

    View details for DOI 10.3233/JAD-220349

    View details for PubMedID 36155504