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Data-driven identification of imaging-based and genetic-based hemodynamic biomarkers of Alzheimer's Disease

Award Number: R01AG096687
ORGANIZATION: NATIONAL INSTITUTE ON AGING
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 09/15/2026
PERIOD OF PERFORMANCE END DATE: 05/31/2031

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Data-driven identification of imaging-based and genetic-based hemodynamic biomarkers of Alzheimer's Disease - Summary The main hallmarks of Alzheimer’s Disease (AD) are the extracellular amyloid-β (Aβ) plaques and intraneuronal aggregates of hyperphosphorylated tau - neurofibrillary tangles [1]. However, alterations in hemodynamic and vascular parameters, such as vessel size, number of vessels, and occlusions in a range of locations, that occur over the lifespan underlie numerous pathologies, including AD [1–5], carotid stenosis [6], stroke [7], moyamoya disease [8], and vascular dementia [9]. Changes in the distribution of blood in the cerebral vasculature due to alterations in one or more vessels will result in a shift in the pattern of blood flow between and within arterial territories; the regional blood supply may therefore no longer be adequate to meet the brain’s circulatory needs. Recent studies show that vascular alterations are present in more than 50% of clinically diagnosed AD cases [1], and some suggest that vascular dysfunction as a major factor in AD development, rather than simply a side effect [10]. Detecting incipient vascular pathology could potentially allow early detection and intervention to restore normal blood flow, mitigating the significant neuronal damage of AD and significantly improving patient outcomes. We have developed novel methods for retrospectively characterizing cerebral hemodynamics using resting state fMRI data. This includes both 1) measuring relative arrival time and strength of low frequency oscillations (LFOs) in the blood at different regions to characterize bulk blood flow, and 2) extracting the cardiac waveform and mapping cardiac pulsatility over the cardiac cycle. We have established in multiple studies since 2010 that the LFOs, which constitute a major fraction of the “physiological noise” in fMRI, are carried by the blood itself, and therefore show up at different parts of the brain at different times as the blood travels through the vascular tree [11–16]. Similarly, we have shown that aliased pulsatile cardiac noise in the fMRI data can be extracted using our HAPPy technique and remapped to generate flow maps using hypersampling [17]. We therefore can use existing resting state datasets to estimate a range of hemodynamic parameters retrospectively, including blood arrival time (BAT), relative cerebral blood volume (rCBV), cardiac pulsatility (CP), and cardiac waveform propagation speed (CWPS). This rich hemodynamic profiling method, in conjunction with sophisticated imaging genomics methods, will be applied to the UK Biobank dataset to develop a hybrid imaging/genetics model to identify perfusion deficits which may be indicative of prodromal AD, which will be validated in two independent datasets (the Open Access Series of Imaging Studies (OASIS)-3, and the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset.)


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 = $687,568 )
2026	2026	THE MCLEAN HOSPITAL CORPORATION	115 MILL ST	BELMONT	MA	02478	MIDDLESEX	USA	Aging Research	000	1	9/4/2026	NEW	$687,568
														Subtotal = $687,568

Grand Total All Awards = $687,568

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Data-driven identification of imaging-based and genetic-based hemodynamic biomarkers of Alzheimer's Disease

Award Number: R01AG096687

ORGANIZATION: NATIONAL INSTITUTE ON AGING

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 09/15/2026

PERIOD OF PERFORMANCE END DATE: 05/31/2031

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