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Discovery and Machine Learning Classification of Metabolite Biomarkers of Neurocognitive Impairment in Older People with HIV

Award Number: K23AG102190
ORGANIZATION: NATIONAL INSTITUTE ON AGING
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: TRAINING/TRAINEESHIP
PERIOD OF PERFORMANCE START DATE: 07/01/2026
PERIOD OF PERFORMANCE END DATE: 04/30/2031

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Discovery and Machine Learning Classification of Metabolite Biomarkers of Neurocognitive Impairment in Older People with HIV - PROJECT SUMMARY Despite advances in antiretroviral therapy that have led to widespread viral suppression, nearly half of older people with HIV (PWH) still suffer from neurocognitive impairment (NCI). The elevated rates of NCI in this population are primarily due to the deleterious synergistic effects of HIV and aging on the brain, and exacerbating inflammatory, genetic, environmental, and lifestyle influences. Metabolomics, which quantifies small molecule byproducts of metabolic processes from biospecimens to provide a comprehensive view of intrinsic and extrinsic influences on an individual’s health status, may serve as the optimal tool for studying the complex heterogeneity of NCI in PWH, but this emerging technology is still critically underutilized in neuroHIV research. For example, recent NIH initiatives advocating for advanced data-driven methods for modeling biotypes of HIV brain health disorders have yet to incorporate metabolomics data, despite the unprecedented amount of biological information that can be obtained from this approach. Thus, the current K23 study proposes cross-disciplinary integration between the metabolomics and neuroHIV fields by leveraging cutting-edge metabolomics and machine learning methods to discover and classify novel metabolite biomarkers of NCI in older PWH. For Specific Aim 1, I will leverage untargeted metabolomics data from fecal samples of 403 older PWH enrolled in cohort studies at the UC San Diego HIV Neurobehavioral Research Center (HNRC) to first identify candidate biomarkers of NCI, then validate them using CSF and plasma metabolomics data from 598 PWH enrolled in the CNS HIV Antiretroviral Therapy Effects Research (CHARTER) study. For Specific Aim 2, I will then leverage the best-in-class analytic approach established by the Multimodal Integrated Analysis and Assessment Development for NeuroHIV Outcomes (MIAAD-NHIV) initiative and conduct machine learning models to identify and characterize metabolite biomarker subgroups. This K23 is well-supported by my mentorship team of world-renowned scientists with expertise in areas related to metabolomics (Dr. Pieter Dorrestein [primary]; pioneer of metabolomics technology and data repositories), biological mechanisms underlying neuroHIV (Dr. Ronald Ellis [co-primary]; HNRC and CHARTER PI), HIV and aging (Dr. David Moore; HNRC PI), and brain-based biotypes (Dr. Robert Paul; MIAAD-NHIV investigator). The proposed study strongly aligns with the 2020-2025 National Institute on Aging Strategic Directions (e.g., Goal D- 2: “Identify the genetic, molecular, and cellular mechanisms underlying the pathogenesis of AD/ADRD and other neurodegenerative disorders of aging” and Goal D-4: “Translate basic discovery into effective treatment and/or prevention strategies”). Results will provide proof of concept and critical preliminary data to inform a future R01 application that will examine the mechanistic and causal pathways of the metabolite biomarkers identified in this K23 with NCI through in vivo and in vitro experiments, and thus facilitate my independence as a clinical and translational scientist.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $163,867 )
2026	2026	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR	LA JOLLA	CA	92093	SAN DIEGO	USA	Aging Research	000	1	6/29/2026	NEW	$163,867
														Subtotal = $163,867

Grand Total All Awards = $163,867

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Discovery and Machine Learning Classification of Metabolite Biomarkers of Neurocognitive Impairment in Older People with HIV

Award Number: K23AG102190

ORGANIZATION: NATIONAL INSTITUTE ON AGING

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: TRAINING/TRAINEESHIP

PERIOD OF PERFORMANCE START DATE: 07/01/2026

PERIOD OF PERFORMANCE END DATE: 04/30/2031

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