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Graff‐Radford, Neill R.

Mayo Clinic

WinnMed

Citations 3

Novel set of plasma proteins classifies Alzheimer's dementia in African Americans with high accuracy
Hurst, Cheyenne , Huang, Yen‐Ning, Opdenbosch, Bianca M., Reddy, Joseph S. , Nguyen, Thuy T., Casellas, Heidi L., Sotelo, Katie D., Reddy, Delila J., Tsai, Wei, Lucas, John A. , Day, Gregory S, Willis, Floyd B. , Ramanan, Vijay K., Graff‐Radford, Neill R., Ertekin‐Taner, Nilüfer, Nho, Kwangsik, Carrasquillo, Minerva M., Kuchenbecker, Lindsey A. , Thompson, Kevin J. , Huang, Yen-Ning , Heckman, Michael G. , Nguyen, Thuy T. , Sotelo, Katie D., Day, Gregory S. , Ramanan, Vijay K. , Graff‐Radford, Neill R. , Ertekin‐Taner, Nilüfer , Nho, Kwangsik T. , Kalari, Krishna R. , Carrasquillo, Minerva M.

Alzheimer's & Dementia | December 25, 2025 | Volume: 21 | Issue: S2 | Pages: No page available

10.1002/alz70856_100297 Get It

Abstract Background Plasma biomarkers offer improved accessibility compared to established diagnostic modalities for Alzheimer's disease (AD). However, current plasma biomarker candidates have not been tested comprehensively in diverse populations, and represent only a fraction of pathways dysregulated in AD. This study seeks to address these knowledge gaps through untargeted plasma biomarker discovery in African Americans (AA), an underrepresented group in AD research despite having a higher risk of developing dementia compared to non‐Hispanic Whites (NHW). Method Untargeted proteomics were generated using the SomaScan 7k platform on plasma samples from AA study participants clinically diagnosed as AD dementia ( n = 181) or cognitively unimpaired (CU; n = 142). Machine learning was implemented to identify a set of plasma proteins to distinguish between AD dementia and CU. Predictive models were constructed by elastic net regression optimized with nested cross‐validation on 6,853 proteins and evaluated by receiver operating characteristic analysis. The generalizability of plasma protein predictors was evaluated in an external Alzheimer's Disease Research Center cohort of 369 NHW and AA study participants diagnosed as AD dementia or CU. Result Thirty‐six proteins were selected as predictors. Proteins selected by machine learning were enriched for processes previously associated with AD including synaptic dysfunction, inflammation, vascular dysfunction, and amyloid processing. The 36 plasma proteins alone achieved an area under the curve (AUC) of 0.94 to classify AD dementia in the discovery cohort, representing a 22% improvement over a model including age and sex. The 36 proteins were validated in an external cohort also achieving AUC=0.94, a 35% improvement over age and sex. Conclusion Biomarker discovery combining untargeted proteomics and machine learning identified a set of plasma proteins that could serve as a novel and highly accurate diagnostic plasma biomarker panel for AD. Work is underway to assess the association of the predictive panel with p ‐tau217, medical comorbidities, and social/structural determinants of health.
Superficial Cortical Aβ Clearance and ARIA Pathology in Aducanumab‐Treated Alzheimer's Disease
Boon, Baayla D.C., Piura, Yoav , Chalk, Jessica L , Lincoln, Sarah, Rutledge, Matthew H., Reichard, R. Ross, Graff‐Radford, Jonathan, Knopman, D S, Graff‐Radford, Neill R., Murray, Melissa E., Boon, Baayla D.C. , Moloney, Christina M. , Johnson, Derek R. , Dickson, Dennis W. , Nguyen, Aivi T. , Reichard, R. Ross , Graff‐Radford, Jonathan , Knopman, David S. , Graff‐Radford, Neill R. , Murray, Melissa E.

Alzheimer's & Dementia | December 25, 2025 | Volume: 21 | Issue: S1 | Pages: No page available

10.1002/alz70855_105890 Get It

Abstract Background Monoclonal antibodies targeting amyloid‐β (Aβ), including aducanumab, have been tested to treat Alzheimer's disease (AD). However, limited data exist on neuropathology following treatment and the effects of amyloid‐related imaging abnormalities (ARIA). We report on such data from five aducanumab‐treated study participants with AD of whom two experienced ARIA. Methods Aducanumab‐treated study participants who came to autopsy ( n = 5) were matched to AD controls ( n = 12) based on the presence/type of autosomal dominant AD mutation, APOE genotype, age at cognitive symptom onset, and sex. We assessed cognitive measures, 18 F‐florbetapir PET centiloid, ARIA risk factors, and AD neuropathologic change. Using multiplex immunofluorescence, brain regions affected along Thal Aβ phases were stained for Aβ isoforms and phosphorylated tau, as well as for ARIA‐associated markers, including Perls’ Prussian blue to detect ferric iron, fibrinogen‐α for blood brain barrier integrity, membrane attack complex (C5b‐C9) for complement activation, and activated microglia (IBA1, CD68). Results Study participants included four males and one female, all carrying at least one APOE ε4 allele. Two participants carried a PSEN1 NM_000021.4:c.817G>A , p.Glu273Lys mutation. Cumulative aducanumab dosage ranged between 5–241 mg/kg, with death occurring 5–41 months after the last infusion. Amyloid burden on PET declined in all participants (range 15‐100 centiloids). Two participants experienced ARIA. Compared to AD controls, Aβ aa1‐8 and Aβ 42 were selectively reduced in cortical layer I of aducanumab‐treated study participants ( p <0.05) but not in the total cortex, as shown for the middle frontal cortex in Figure 1. No differences were observed in phosphorylated tau burden. Prussian blue‐stained hemosiderin was present in both treated and untreated AD cases. However, in participants with ARIA, hemosiderin accumulated in superficial cortical layers near CAA‐laden meningeal and penetrating vessels, which also exhibited extensive complement and microglial activation (Figure 2). Conclusions Aβ clearance and ARIA‐related findings were localized predominantly in superficial cortical layers, suggesting that aducanumab biodistribution is more pronounced in these regions rather than deeper cortical layers.
Socioeconomic deprivation and medical comorbidity burden associations with clinicopathologic characteristics in an ethnoracially diverse Alzheimer's disease autopsy series
Lachner, Christian, Emrani, Sheina , Dunlop, Sara , Rawlinson, Bailey, Engelberg‐Cook, Erica, Ventura, Josalen, Velez‐Uribe, Idaly, Graff‐Radford, Neill R., Day, Gregory S, Lucas, John A. , Murray, Melissa E., Lachner, Christian , Kuchenbecker, Lindsey A. , Engelberg-Cook, Erica , Vélez-Uribe, Idaly , Peng, Zhongwei , Haydu, Lauren E. , Dickson, Dennis W. , Graff‐Radford, Neill R. , Day, Gregory S. , Murray, Melissa E.

Alzheimer's & Dementia | December 25, 2025 | Volume: 21 | Issue: S1 | Pages: No page available

10.1002/alz70855_107360 Get It

Abstract Background Population aging is expected to increase the burden of Alzheimer's disease (AD) and related dementias (ADRD), yet up to 45% of ADRD risk may be modified. Disparities in ADRD burden among Hispanic/Latino and Black/African Americans suggests that socioeconomic deprivation and medical comorbidities may influence AD risk. The relationship between these factors, symptomatic age of onset, and neuropathologic findings in AD remains unclear. This study aims to investigate these associations in an ethnoracially diverse, neuropathologically diagnosed AD case series. Understanding these risk factors may help develop more effective AD risk reduction strategies. Method We queried the Florida Autopsied Multi‐Ethnic (FLAME) cohort database for neuropathologically‐diagnosed AD cases with available age onset of cognitive symptoms, who self‐identified as Hispanic/Latino ( n = 75) or Black/African American ( n = 22). Cases were matched to non‐Hispanic White decedents ( n = 101) by sex and year of birth. Medical records at the time of brain donation were retrospectively reviewed, assessing completeness for demographics, clinical characteristics, and medical comorbidities (Table 1). Result The table shows a comparative analysis stratified by young‐onset AD (YOAD, onset <65 years) and late‐onset AD (LOAD, onset ≥65 years). YOAD cases had a significantly higher level of education compared to LOAD ( p = 0.003). No differences were observed in sex , APOE ε4 carriership, or Area Deprivation Index between YOAD and LOAD. However, YOAD cases had a longer disease duration and were more likely to present with atypical clinical features compared to LOAD (both p <0.001). YOAD cases also showed a faster rate of decline on MMSE compared to LOAD ( p = 0.002), higher frequency of depression ( p = 0.018), and lower frequency of stroke/TIA ( p = 0.025). YOAD cases also had lower brain weight ( p = 0.041), less cerebrovascular disease burden ( p = 0.003) and higher neurofibrillary tangle density in association cortices ( p <0.001) compared to LOAD cases. Conclusion Socioeconomic deprivation and most medical comorbidities were not associated with AD symptomatic onset. Despite having higher education levels and lower cerebrovascular burden, YOAD decedents experienced faster cognitive decline but a longer disease course, with more frequent atypical clinical presentations and depression compared to LOAD. Further discussion will address the topographic distribution of tangle and plaque pathology.