Repetitive head injury alters the neurodegenerative response and pathologic progression in Alzheimer's disease

Each year, millions of individuals receive repetitive head injuries (RHI) from playing contact sports or through military service. RHIs are a type of traumatic brain injury characterized by mild, mostly non-concussive injuries that, in the context of a sport like American football, can occur dozens of times a day for years. In addition to long-term disability and dysfunction, individuals who have a history of RHI are at an increased risk of developing neurodegenerative diseases, likely stemming from a neuroinflammatory environment that results from the constant low-level head trauma. To that end, our preliminary single nucleus RNA sequencing (snRNAseq) studies have demonstrated inflammatory SPP1+/Hif1a+ microglia are observed in cases with exposure to RHI but have not yet developed pathology, suggesting inflammation precedes protein deposition. Interestingly, it has become clear that neuropathologies like Alzheimer’s disease (AD) in the context of RHI are not identical to their non-RHI counter parts. In contrast to the normal confluent appearance of cortical hyperphosphorylated tau (ptau) distribution observed in AD, individuals with AD and an RHI history (AD+RHI) were observed to have a sulcal predominance of ptau. Additionally, preliminary bulk sequencing studies suggest AD+RHI cases have an altered neuroinflammatory environment. These observations raise the question if other “classical AD” features are altered during RHI. The implications for differences are significant, as imaging biomarkers for AD diagnosis rely on understanding the known progression pattern of neuropathology but altered pathology makes it harder to diagnose AD. Also, the altered neuropathologic burden and distribution may skew clinical symptoms, which complicates clinical assessment and results in improper treatment strategies. To better examine RHI-specific changes in AD, we will deeply characterize the neurodegeneration, pathologic protein regional progression, and clinical phenotypes observed in individuals with a history of RHI and a neuropathologic diagnosis of AD. We will use our unique resource—the NIA-funded P30 Boston University AD Research Center brain bank, the largest RHI brain bank in the world, to compare 7 groups: individuals either with Low, Intermediate, or High AD neuropathologic changes with or without exposure to RHI (n = 379), and a no pathology/no RHI control group. Overall, we hypothesize that the exposure to RHI will result in altered AD neuropathology, which will also have direct associations with clinical outcomes. Using digital pathology and artificial intelligence toolsets, we will perform disease progression modeling using a machine learning tool called subtype and stage inference algorithm (SuStaIn), to examine whole-slide digital images taken from 19 brain regions per case that are stained for ptau, Aβ, TDP43, and a-syn. SuStaIn uses spectrums of neuropathology data to predict progression patterns of diseases through the brain and can determine cases that fall outside the normal range identifying subtypes. We will compare progression patterns between AD and AD+RHI cases encompassing early, late, and end stage disease. We will also determine if specific SuStaIn subtypes correlate with distinct clinical symptom presentation. Next, we will perform snRNAseq to compare how cell population might be altered in our 7 groups using tissue taken from the dorsolateral frontal, temporal, and calcarine cortex representing early, late, and end stage pathology. In addition, we will use proximal frozen tissue to perform pTau and Aβ histology to measure pathologic accumulation directly related with the cells assayed by snRNAseq. Finally, we will perform a spatial histologic analysis across AD and AD+RHI cases to investigate how local cell populations are directly related to pathology. We will again utilize tissue from the dorsolateral frontal, temporal, and calcarine cortex to capture the full spectrum of disease related changes and investig Project Number: 1I01RD001320-01A2 | Fiscal Year: 2026 | NIH Institute/Center: Veterans Affairs (VA) | Principal Investigator: Jonathan Cherry | Institution: VA BOSTON HEALTH CARE SYSTEM, BOSTON, MA | Activity Code: I01 | Study Section: Special Emphasis Panel[ZRD1 NURD-E (01)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11298745