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Objective: This study was undertaken to apply established and emerging cerebrospinal fluid (CSF) biomarkers to improve diagnostic accuracy in patients with rapidly progressive dementia (RPD). Overlap in clinical presentation and results of diagnostic tests confounds etiologic diagnosis in patients with RPD. Objective measures are needed to improve diagnostic accuracy and to recognize patients with potentially treatment‐responsive causes of RPD. Methods: Biomarkers of Alzheimer disease neuropathology (amyloid‐β 42/40 ratio, phosphorylated tau [p‐tau181, p‐tau231]), neuroaxonal/neuronal injury (neurofilament light chain [NfL], visinin‐like protein‐1 [VILIP‐1], total tau), neuroinflammation (chitinase‐3‐like protein [YKL‐40], soluble triggering receptor expressed on myeloid cells 2 [sTREM2], glial fibrillary acidic protein [GFAP], monocyte chemoattractant protein‐1 [MCP‐1]), and synaptic dysfunction (synaptosomal‐associated protein 25kDa, neurogranin) were measured in CSF obtained at presentation from 78 prospectively accrued patients with RPD due to neurodegenerative, vascular, and autoimmune/inflammatory diseases; 35 age‐ and sex‐matched patients with typically progressive neurodegenerative disease; and 72 cognitively normal controls. Biomarker levels were compared across etiologic diagnoses, by potential treatment responsiveness, and between patients with typical and rapidly progressive presentations of neurodegenerative disease. Results: Alzheimer disease biomarkers were associated with neurodegenerative causes of RPD. High NfL, sTREM2, and YKL‐40 and low VILIP‐1 identified patients with autoimmune/inflammatory diseases. MCP‐1 levels were highest in patients with vascular causes of RPD. A multivariate model including GFAP, MCP‐1, p‐tau181, and sTREM2 identified the 44 patients with treatment‐responsive causes of RPD with 89% accuracy. Minimal differences were observed between typical and rapidly progressive presentations of neurodegenerative disease. Interpretation: Selected CSF biomarkers at presentation were associated with etiologic diagnoses and treatment responsiveness in patients with heterogeneous causes of RPD. The ability of cross‐sectional biomarkers to inform upon mechanisms that drive rapidly progressive neurodegenerative disease is less clear. ANN NEUROL 2024;95:299–313 [ABSTRACT FROM AUTHOR]

Background: African Americans (AA) and Latin Americans (LA) are at a higher risk of developing AD compared to non‐Hispanic whites (NHW) but are traditionally underrepresented in AD research. The disproportionate risk is likely multifactorial including differences in co‐morbidities and structural and social determinants of health (SSDoH). AD risk is thought to result from multiple genetic and environmental factors, and their interactions (GxE). However, the molecular mechanisms underlying these interactions are largely unknown. The best‐established genetic risk factor for AD is APOE‐ε4, while APOE‐ε2 is protective. Environmental factors, such as living in neighborhoods with greater socioeconomic disadvantage, have been associated with greater AD neuropathology and worse cognitive function. Studying the potential modifying role of neighborhood disadvantage regarding associations of APOE‐ε4 and APOE‐ε2 with AD risk using a socioeconomic metric like the Area Deprivation Index (ADI) in a multiethnic post‐mortem cohort could offer valuable insights for precision medicine. Method: We analyzed a post‐mortem cohort of 421 multi‐ethnic donors (NHW: N = 234, AD = 70, non‐AD = 164; LA: N = 145, AD = 102, non‐AD = 43; AA: N = 42, AD = 24, non‐AD = 18), from Mayo Clinic Florida, Banner Sun Health Research Institute, and the University of Florida Brain Banks as part of the AMP AD Diversity initiative. This study used the same neuropathological criteria to categorize AD vs. non‐AD as in the MayoRNAseq study (syn5550404). ADI from the Neighborhood Atlas® was obtained from de‐identified addresses. Associations of APOE‐ε4, APOE‐ε2, and ADI with AD risk were examined using logistic regression models adjusted for age‐at‐death, sex, and ethnic group; interactions of APOE genotype with ADI were also assessed. Result: APOE‐ε4 and APOE‐ε2 showed a significant association with AD diagnosis (APOE‐ε4combined cohort OR = 3.23, P = 3.14E‐08; APOE‐ε2combined cohort OR = 0.30, P = 0.003). However, contrary to prior findings, our study found no association between ADI and AD diagnosis [OR = 1.023 (per each 10 unit increase in ADI), P = 0.629]. No significant interactions of ADI with APOE‐ε4 or APOE‐ε2 regarding association with AD diagnosis were identified (P = 0.083, P = 0.781). Conclusion: This is the first study evaluating the potential interaction of neighborhood disadvantage with APOE on AD risk in a multi‐ethnic autopsy cohort. However, these findings require further investigation in larger, more well‐powered cohorts for validation. [ABSTRACT FROM AUTHOR]

Introduction: African Americans (AA) are widely underrepresented in plasma biomarker studies for Alzheimer's disease (AD) and current diagnostic biomarker candidates do not reflect the heterogeneity of AD., Methods: Untargeted proteome measurements were obtained using the SomaScan 7k platform to identify novel plasma biomarkers for AD in a cohort of AA clinically diagnosed as AD dementia (n=183) or cognitively unimpaired (CU, n=145). Machine learning approaches were implemented to identify the set of plasma proteins that yields the best classification accuracy., Results: A plasma protein panel achieved an area under the curve (AUC) of 0.91 to classify AD dementia vs CU. The reproducibility of this finding was observed in the ANMerge plasma and AMP-AD Diversity brain datasets (AUC=0.83; AUC=0.94)., Discussion: This study demonstrates the potential of biomarker discovery through untargeted plasma proteomics and machine learning approaches. Our findings also highlight the potential importance of the matrisome and cerebrovascular dysfunction in AD pathophysiology., Competing Interests: Conflict of Interest Statement: LAK, CDH, BMO, and MMC report no disclosures.