Ertekin‐Taner, Nilüfer

Background: Dementia, vascular disease, and cancer increase with age, enabling complex comorbid interactions. Understanding vascular and cancer contributions to dementia risk and neuropathology in oldest-old may improve risk modification and outcomes. Objective: Investigate the contributions of vascular factors and cancer to dementia and neuropathology. Methods: Longitudinal clinicopathologic study of prospectively followed Mayo Clinic participants dying≥95 years-old who underwent autopsy. Participants were stratified by dementia status and compared according to demographics, vascular risk factors, cancer, and neuropathology. Results: Participants (n = 161; 83% female; 99% non-Hispanic whites)≥95 years (95–106 years-old) with/without dementia did not differ based on demographics. APOE ɛ2 frequency was higher in no dementia (20/72 [28%]) versus dementia (11/88 [12%]; p = 0.03), but APOE ɛ4 frequency did not differ. Coronary artery disease was more frequent in no dementia (31/72 [43%]) versus dementia (23/89 [26%]; p = 0.03) associated with 56% lower dementia odds (odds ratio [OR] = 0.44 [confidence interval (CI) = 0.19–0.98]; p = 0.04) and fewer neuritic/diffuse plaques. Diabetes had an 8-fold increase in dementia odds (OR = 8.42 [CI = 1.39–163]; p = 0.02). Diabetes associated with higher cerebrovascular disease (Dickson score; p = 0.05). Cancer associated with 63% lower dementia odds (OR = 0.37 [CI = 0.17–0.78]; p < 0.01) and lower Braak stage (p = 0.01). Conclusion: Cancer exposure in the oldest-old was associated with lower odds of dementia and tangle pathology, whereas history of coronary artery disease was associated with lower odds of dementia and amyloid-β plaque pathology. History of diabetes mellitus was associated with increased odds of dementia and cerebrovascular disease pathology. Cancer-related mechanisms and vascular risk factor reduction strategies may alter dementia risk and neuropathology in oldest-old.

Abstract Background: Alterations in innate immunity are pathologically associated with and genetically implicated in Alzheimer’s disease (AD). In the whole exome sequence (WES) dataset generated by the Alzheimer’s Disease Sequencing Project (ADSP), only the previously identified p.R47H variant in the innate immunity gene, TREM2, shows study-wide association with risk of AD. Using a novel approach, we searched the ADSP WES data to identify additional immune pathway genes with deleterious variants that, like TREM2.pR47H, show strong association with AD. Methods: Using polygenic risk scores (PRS) to analyze association with AD, we evaluated deleterious variants (CADD Phred-scaled score > 20) with a minor allele count of 20 or more in 228 genes comprising an immune co-expression network containing TREM2 (CENTREM2). A significant polygenic component composed of deleterious stop-gain and non-synonymous variants was identified, and false discovery rates were determined for the variants in this component. In genes harboring a significant variant, PRS for all variants in the genes were then analyzed. Results: The PRS for the 182 deleterious variants in CENTREM2 showed significant association with AD that was driven by 142 deleterious variants (136 non-synonymous, 6 stop-gain). In the 142 variant polygenic component, four variants had significant AD risk association: TREM2.pR47H, two deleterious stop-gain variants (FCGR1A.pR92X, and LILRB1.pY331X) in novel AD genes and 1 non-synonymous variant (ATP8B4.pG395S). Remarkably, PRS for the 36 additional variants in these four genes also showed significant association with AD. The PRS for all 40 variants in the 4 genes, showed significant, replicable association with AD and 3 additional variants in this polygenic component had significant false discovery rates: ATP8B4.pR1059Q, LILRB1.pP7P, and LILRB1.pY327Y. Conclusions: Here, we identify 3 immune pathway genes (ATP8B4, LILRB1, and FCGR1A) with a variant that associates with AD. Like TREM2.pR47H, each of the variants has a minor allele frequency less than 1% and is a deleterious, protein altering variant with a strong effect that increases or decreases (LILRB1.pY331X) risk of AD. Additional variants in these genes also alter risk of AD. The variants identified here are ideally suited for studies aimed at understanding how the innate immune system may be modulated to alter risk of AD.

Abstract Introduction Alzheimer's disease (AD) is accompanied by metabolic alterations both in the periphery and the central nervous system. However, so far, a global view of AD‐associated metabolic changes in the brain has been missing. Methods We metabolically profiled 500 samples from the dorsolateral prefrontal cortex. Metabolite levels were correlated with eight clinical parameters, covering both late‐life cognitive performance and AD neuropathology measures. Results We observed widespread metabolic dysregulation associated with AD, spanning 298 metabolites from various AD‐relevant pathways. These included alterations to bioenergetics, cholesterol metabolism, neuroinflammation, and metabolic consequences of neurotransmitter ratio imbalances. Our findings further suggest impaired osmoregulation as a potential pathomechanism in AD. Finally, inspecting the interplay of proteinopathies provided evidence that metabolic associations were largely driven by tau pathology rather than amyloid beta pathology. Discussion This work provides a comprehensive reference map of metabolic brain changes in AD that lays the foundation for future mechanistic follow‐up studies.

AbstractIntroductionApolipoprotein E (APOE) ε4 is an important genetic risk factor for typical Alzheimer's disease (AD), influencing brain volume and tau burden. Little is known about its influence in atypical presentations of AD.MethodsAn atypical AD cohort of 140 patients diagnosed with either posterior cortical atrophy or logopenic progressive aphasia underwent magnetic resonance imaging and positron emission tomography. Linear mixed effects models were fit to assess the influence of APOE ε4 on cross‐sectional and longitudinal regional metrics.ResultsAt baseline, APOE ε4 carriers had smaller hippocampal and amygdala volumes and greater tau standardized uptake volume ratio in the hippocampus and entorhinal cortex compared to non‐carriers while longitudinally, APOE ε4 non‐carriers showed faster rates of atrophy and tau accumulation in the entorhinal cortex, with faster tau accumulation in the hippocampus.DiscussionAPOE ε4 influences patterns of neurodegeneration and tau deposition and was associated with more medial temporal involvement, although there is evidence that non‐carriers may be catching up over time.

AbstractMicroglia have fundamental roles in health and disease; however, effects of age, sex, and genetic factors on human microglia have not been fully explored. We applied bulk and single‐cell approaches to comprehensively characterize human microglia transcriptomes and their associations with age, sex, and APOE. We identified a novel microglial signature, characterized its expression in bulk tissue and single‐cell microglia transcriptomes. We discovered microglial co‐expression network modules associated with age, sex, and APOE‐ε4 that are enriched for lipid and carbohydrate metabolism genes. Integrated analyses of modules with single‐cell transcriptomes revealed significant overlap between age‐associated module genes and both pro‐inflammatory and disease‐associated microglial clusters. These modules and clusters harbor known neurodegenerative disease genes including APOE, PLCG2, and BIN1. Meta‐analyses with published bulk and single‐cell microglial datasets further supported our findings. Thus, these data represent a well‐characterized human microglial transcriptome resource and highlight age, sex, and APOE‐related microglial immunometabolism perturbations with potential relevance in neurodegeneration.

AbstractBackgroundThe apolipoprotein ε4 (APOE4) allele is the most common and well established risk factor for typical late‐onset amnestic Alzheimer’s dementia. Less is known about the role of APOE in patients with atypical clinical presentations of AD, with studies often disagreeing on APOE4 frequencies in these cohorts. We aimed to assess relationships between APOE genotype and age, amyloid‐beta (Aβ) deposition and clinical phenotype in Alzheimer’s disease.Method138 atypical AD patients (57 posterior cortical atrophy and 81 logopenic aphasia) were recruited by the Neurodegenerative Research Group at Mayo Clinic, and underwent APOE testing and Pittsburgh Compound B PET. 318 typical AD patients with APOE genotype and known onset age were identified from ADNI (121 had Aβ‐PET). Aβ‐PET was quantified using the centiloid scale. Logistic regression was used to estimate the proportion of APOE4 carriers by onset age and clinical group. Linear regression was used to estimate mean Aβ centiloid by age, APOE4 status, and clinical group in patients who were Aβ‐positive (centiloid≥19).ResultThe overall frequency of APOE4 carriers was lower in atypical AD (52%) compared to typical AD (66%), particularly for ε4ε4 homozygotes (9% vs 20%). APOE4 frequency increased with age in atypical AD, but showed a bell‐shaped curve in typical AD where highest frequencies were observed between 65‐70 years (Figure). Typical AD showed higher APOE4 frequencies than atypical AD only between the ages of 57 and 69 years. Aβ centiloid was higher in atypical AD compared to typical AD by approximately 16 centiloid units, but did not differ according to APOE4 status (Figure). Aβ centiloid stayed relatively flat with increasing age for both carriers and non‐carriers in atypical AD, but declines with increasing age in typical AD. Relationships between APOE4 and age, as well as centiloid, did not differ between the two atypical AD phenotypes.ConclusionAPOE4 frequency differs between atypical and typical AD but is highly dependent upon age, with higher APOE4 frequency in typical AD only observed between 57 and 69 years. The findings highlight the importance of age and clinical phenotype in understanding the effects of APOE genotype in Alzheimer’s disease.

Abstract Background Genetics play an important role in late-onset Alzheimer’s Disease (AD) etiology and dozens of genetic variants have been implicated in AD risk through large-scale GWAS meta-analyses. However, the precise mechanistic effects of most of these variants have yet to be determined. Deeply phenotyped cohort data can reveal physiological changes associated with genetic risk for AD across an age spectrum that may provide clues to the biology of the disease. Methods We utilized over 2000 high-quality quantitative measurements obtained from blood of 2831 cognitively normal adult clients of a consumer-based scientific wellness company, each with CLIA-certified whole-genome sequencing data. Measurements included: clinical laboratory blood tests, targeted chip-based proteomics, and metabolomics. We performed a phenome-wide association study utilizing this diverse blood marker data and 25 known AD genetic variants, adjusting for sex, age, vendor (for clinical labs), and the first four genetic principal components; sex-SNP interactions were also assessed. Results We observed statistically significant SNP-analyte associations for five genetic variants after correction for multiple testing (for SNPs in or near NYAP1, ABCA7, INPP5D, and APOE), with effects detectable from early adulthood. The ABCA7 SNP and the APOE2 and APOE4 encoding alleles were associated with lipid variability, as seen in previous studies; in addition, six novel proteins were associated with the e2 allele. The most statistically significant finding was between the NYAP1 variant and PILRA and PILRB protein levels, supporting previous functional genomic studies in the identification of a putative causal variant within the PILRA gene. Sex modified the effects of four genetic variants, with multiple interrelated immune-modulating effects associated with the PICALM variant. In post-hoc analysis, sex-stratified GWAS results from an independent AD case-control meta-analysis supported sex-specific disease effects of the PICALM variant, highlighting the importance of sex as a biological variable. Conclusions Known AD genetic variation influenced lipid metabolism and immune response systems in a population of non-AD individuals, with associations observed from early adulthood onward. Further research is needed to determine whether and how these effects are implicated in early-stage biological pathways to AD. These analyses aim to complement ongoing work on the functional interpretation of AD-associated genetic variants.

AbstractBackgroundAfrican Americans (AA) remain underrepresented in Alzheimer’s disease (AD) research, despite the prevalence of AD being ∼2X higher in this population compared to non‐Hispanic whites. To address this disparity, our group has established the Florida Consortium for African American Alzheimer’s Disease Studies (FCA3DS), focusing primarily on the identification of genetic risk factors and novel plasma biomarkers.MethodUtilizing plasma samples from FCA3DS AD cases (n=158) and cognitively unimpaired elderly controls (n=272), we have performed differential gene expression (DEG) and expression quantitative trait locus (eQTL) analyses on 50 transcripts measured with a custom NanoString® panel that we have designed to measure transcript levels in plasma of genes relevant to AD. Transcript counts were determined using the NanoString® nCounter system, following manufacturer’s protocols. Transcript counts from 43 of the 50 customs assays passed pre‐established quality control thresholds and were utilized for the DEG and eQTL analyses. Our published FCA3DS whole exome sequence (WES) data was utilized for the eQTL analyses. Linear mixed models adjusted for relevant biological and technical covariates were implemented with the lme4 package in R software (v3.6.2) for the DEG and eQTL analyses.ResultAn association with higher plasma CLU in controls compared to AD remained significant after Bonferroni correction for the 43 transcripts tested. The eQTL analysis revealed significant association (FDR q‐value<0.05) with 105 WES variants in cis with 22 of 43 genes tested, including variants in genes previously associated with AD risk in AA. ConclusionThe results from this AA plasma eQTL analysis revealed ABCA7 variants that are significantly associated with lower plasma ABCA7 transcript levels. One of the significant plasma ABCA7 eQTLs was previously shown by our group to be associated with increased AD risk in AA, suggesting that this may be a functional eQTL underlying the risk of AD in AA. The association of higher levels of CLU transcript in plasma from controls compared to AD is in line with results published by others which showed that higher baseline concentration of clusterin protein in plasma was associated with slower rates of brain atrophy. These results support plasma transcripts as novel endophenotypes in AD biomarker studies.

AbstractBackgroundThe Neurodegenerative Research Group (NRG) at Mayo clinic has followed patients with degenerative speech and/or language disorders for over a decade. In this presentation I will present data from this cohort to inform a broader discussion about the importance of apraxia of speech (AOS) and its subtypes, heterogeneity within the agrammatic PPA variant, and perils of mixed phenotypes.MethodWe reviewed the NRG database to identify patients who initially presented with isolated (PPAOS), AOS in conjunction with agrammatic aphasia (AOS‐PAA), isolated agrammatic aphasia (PAA), and patients who had PAA or AOS overlapping with another degenerative diagnosis. Data from the following clinical instruments were abstracted: WAB AQ (aphasia severity), UPDRS III (parkinsonism), WAB Praxis (ideomotor apraxia), and the MoCA (cognitive ability). We assessed the effect of baseline diagnosis and AOS subtype on these outcomes over time using Bayesian linear mixed effects models. We qualitatively reviewed longitudinal diagnostic trajectories. Preliminary analyses were done on available autopsy data.ResultPAA was associated with greater aphasia at baseline and more rapid decline; PPAOS was associated with normal language at baseline and slow decline; and PAA‐AOS with intermediate baseline aphasia and decline. However, for those with AOS longitudinal decline differed based on AOS subtype: prosodic PPAOS was associated with the slowest decline and phonetic PAA‐AOS with the fastest. Some patients met criteria for non‐PPA disorders during follow up. However, compared to patients who met criteria for these disorders at enrollment, the speech/language‐first patients remained qualitatively distinct, and neither resembled the cases that were mixed at onset. Preliminary autopsy data suggests that AOS is predictive of tau and that the specific tauopathy may be related to the initial syndrome and AOS subtype.ConclusionThe differences between PAA, PAA‐AOS and PPAOS suggest that these disorders should not be lumped. In fact, the longitudinal trajectories are sufficiently different that doing so would add noise to observational and interventional studies. Instead, more detailed phenotyping, including AOS subtype, can aid prognostication and may improve prediction of the underlying pathology. Finally, caution should be exercised when considering PPAOS and PPA patients for other FTLD diagnostic categories.