Lowe, Val

Abstract Introduction Alzheimer’s disease (AD) is characterized by pathologies including amyloid, tau, neurodegeneration reflected in established blood biomarkers and track with clinical changes. However, the association between peripheral cell-specific signatures and AD-related phenotypes remain poorly characterized. Methods We analyzed bulk blood transcriptome data from the Mayo Clinic Study of Aging (MCSA) and Emory University Vascular study. We used BayesPrism, CIBERSORTx, and an in-house pipeline CNNreg to deconvolute these data and obtain peripheral cell proportions. Cell type specific transcripts were estimated with BayesPrism. We compared cell proportions between cases (AD/MCI) and controls. Association analysis was performed between cell type specific transcripts and AD-related phenotypes including diagnosis and cognition. Meta-analysis of transcripts associations and gene ontology analysis were conducted to assess the enriched pathways for significant genes. Results In MCSA, B and CD4+ T cells proportions are significantly lower while that of myeloid cells higher in cases. The Emory cohort had similar trends. We identified transcripts associated with AD-related phenotypes in CD4+ T and CD8+ T cells. In CD4+ T cells, transcripts downregulated in case are enriched in response to stimulus pathway, whereas those upregulated in negative regulation of immune response. Downregulation of CD4+ T genes enriched in extracellular matrix disassembly and epigenetic regulation and upregulation of those in protein localization associate with better cognition. In CD8+T cells, genes pertinent to vascular development were downregulated while those to metabolic processes were upregulated in cases. Downregulation of CD8+T genes involved in lipid transportation and upregulation of those in mitochondria associate with better cognition. Conclusion We identified peripheral cellular transcriptional changes associated with AD/MCI phenotypes and involved in important biological pathways, revealing potential disease mechanisms in AD. Funding Source RF1 AG051504 Topic Categories Neuroimmunology (NEUR)

Abstract Introduction Patients with Parkinson’s disease commonly underreport sleep symptoms, but the extent to which such mismatch may be present in people with isolated RBD (iRBD) is unknown. We evaluated how the patient–bedpartner (PT–BP) mismatch in night-time and daytime sleep complaints relates to cognition, apathy, dopaminergic degeneration, and cortical structure in iRBD. Methods We retrospectively analyzed 425 iRBD participants (2018–2025) from the North American Prodromal Synucleinopathy (NAPS) Consortium with clinicodemographic data, dopamine transporter (DAT) imaging, and magnetic resonance imaging. Using Scales for Outcomes in Parkinson’s Disease (SCOPA)-Sleep, PT–BP mismatch was classified into overestimator (PT>BP), concordant (PT=BP), and underestimator (PT< BP) groups, separately for complaints during night and day. Outcomes included cognition (CDR-Sum of Boxes [CDR-SB], CDR-global, and individual subdomain tests), pareidolia, apathy, subregional DAT uptake, and cortical thickness. Group differences were tested with analysis of covariance adjusting for age, sex, disease duration, education, clinician-rated OSA treatment inadequacy, and the corresponding patient-reported SCOPA-Sleep domain (night or day), and estimated total intracranial volume for cortical thickness; pairwise tests used Bonferroni correction. Results The PT–BP mismatch was common (night – overestimator 127/425, 29.9% and underestimator 116/425, 27.3%; day – overestimator 77/425, 18.1% and underestimator 134/425, 31.5%). For night-time mismatch, underestimators showed lower CDR-SB and lower CDR-global than overestimators. In addition, underestimators exhibited more illusory responses, fewer correct noise rejections, and fewer total correct responses than overestimator and concordant groups. For daytime mismatch, CDR-SB was lower in underestimators versus overestimators; CDR-global was lower in underestimators and concordant participants versus overestimators. No significant associations were found for apathy. Subregional DAT uptake did not differ by mismatch group. Cortical thickness analyses revealed thinner right transverse gyrus in underestimator and concordant groups compared to the overestimator group and thinner left superior temporal gyrus in underestimator group compared to overestimator group, for night-time mismatch only. Conclusion The PT–BP subjective sleep mismatch can be used as a clinical marker associated with overall cognitive decline and cortical thinning in auditory and language processing areas, which may underlie impairment in perceptual interpretation and hallucination proneness. Further research is warranted to seek longitudinal change and phenoconversion in mismatch groups. Support (if any) #U19-AG071754 (NAPS Consortium)

Abstract Introduction The relationship between sleep and brain metabolism remains unclear. This study aimed to examine whether overnight sleep features, using a home sleep apnea system based on peripheral arterial tonometry, are associated with regional FDG-PET changes in older adults. Methods We analyzed cognitively unimpaired adults (≥60 years) from the Mayo Clinic Study of Aging (MCSA) cohort who were not receiving sleep apnea treatment. Participants underwent overnight sleep assessment with the WatchPAT system, followed by FDG-PET imaging the next morning. FDG-PET data were co-registered to 3T MRI and automatically segmented into 122 anatomical regions. PET signal was referenced to the pons (SUVR). We computed voxel-weighted median FDG signal across 47 bilateral cortical and subcortical regions of interest (ROIs), excluding brainstem and cerebellum. Associations between sleep architecture and sleep apnea/hypoxemia burden and regional metabolism were assessed using partial Spearman’s rank correlation, adjusting for age. Results Thirty-seven participants were included (70.3% female; median [IQR] age: 72.0 [68.0–78.0] years). Wake after sleep onset (WASO) showed widespread negative associations with FDG uptake in cortical regions (p< 0.05), particularly the ventromedial/ventrolateral (rs=–0.47 to –0.33) prefrontal cortex, lateral temporal (rs=–0.38 to –0.33), and occipital (rs=–0.47 to –0.37) cortices. Total sleep time (TST) was positively associated with medial structures (p< 0.05), including the posterior cingulate (rs=0.39), retrosplenial cortex (rs=0.48), hippocampus/parahippocampal (rs=0.34 to 0.36), calcarine cortex (ρ=0.38), thalamus (rs=0.37), and caudate (rs=0.43). Hypoxic burden was positively associated with medial occipital regions (rs=0.35 to 0.39) and AHI-4% with cuneus (rs=0.33). Regional gray matter volume did not mediate these associations. WASO correlated with Insomnia Severity Index (rs=0.43, p=0.008) and self-reported refreshing sleep (rs=0.046). Conclusion Overnight sleep macrostructure features (WASO and TST) and hypoxic burden are significantly associated with brain metabolism, potentially underlying symptoms of sleep disturbance and cognitive aging. Support (if any) Mayo Clinic Alzheimer’s Disease Research Center Development Award (P30 AG062677), R01 AG056366, U01 AG006786, R01 AG056366, R01 AG034676, R37 AG011378, R01 AG041851, R01 NS097495, R01 AG068206, P30 AG062677, R01 HL065176. CLARA project work with funding from the European Union’s HORIZON EUROPE research and innovation programme (No 101136607).

Background TAR DNA-binding protein 43 (TDP-43) proteinopathy contributes to Alzheimer's disease progression, but diagnosis remains autopsy-dependent. Objective This study aimed to develop a predictive model using FDG-PET imaging to identify brain regions associated with TDP-43 pathology in vivo. Methods Penalized logistic regression analyzed data from 294 participants and a subset of 159 with Braak and Thal ≥4. Features included FDG standard uptake value ratios (SUVRs) from 123 brain regions and age. Participants were split into training (90%) and testing (10%) datasets, with significant predictors identified by non-zero coefficients at optimal lambda. Results The model achieved 68% accuracy (AUC = 0.70) in 294 participants, highlighting the middle temporal gyrus, parahippocampal gyrus, and hippocampus. In the subset (n = 159), accuracy was 65% (AUC = 0.71), with the medial amygdala and precentral gyrus as key predictors of TDP-43 pathology. Conclusions This study suggests a moderate predictive accuracy of FDG-PET to identify brain regions associated with Alzheimer's disease-related TDP-43 proteinopathy.