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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]

Background: Systemic inflammation plays a pivotal role in many chronic diseases including Alzheimer's disease (AD). Assessing the composition of immune pathways in neurodegenerative diseases can contribute to precision medicine. Using publicly available transcriptomic data, we sought to elucidate transcriptional networks pertinent to inflammatory pathways across brain regions and peripheral blood in AD/mild cognitive impairment (MCI) and peripheral blood in Parkinson's disease (PD). Method: For the AD/MCI vs. control dataset, we analyzed bulk‐RNAseq collected from 6 brain regions of donors from ROSMAP, Mayo Clinic, and Mount Sinai School of Medicine (MSSM) brain banks available from the AMP‐AD consortium. Ante‐mortem, blood RNAseq expression data was retrieved from the AMP‐AD Emory Vascular cohort and Mayo Clinic Study of Aging (MCSA). We also collected blood‐derived microarray expression data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). For the PD vs Control dataset, blood‐derived bulk‐RNAseq from the PDBP and PPMI cohorts were available through the AMP‐PD consortium. Following quality control, normalization, and residual generation to account for biological and technical variables, co‐expression network modules and their enriched pathways were identified using WGCNA within each dataset. Module/trait correlation tests for aging and diagnosis (cases [AD/MCI or PD] vs control) phenotypes were evaluated. Gene Ontology enrichment analyses were executed to identify enriched pathways and brain or blood cell types within the modules. Modules were tested for preservation across cohorts. Result: We identified conserved immune signatures across brain regions and cohorts. Modules involved in immune response were preserved across all cohorts. Blood consensus modules involved in immune response were preserved in the brain and vice versa. Some immune modules were associated with AD/MCI, PD, and/or aging. Brain immune modules are significantly associated with aging and/or AD. Significant correlations (q<0.05) with PD diagnosis were present. In the MCSA and Emory vascular cohorts, there were no significant (q<0.05) associations between modules and diagnosis, while in ADNI there were nominal (p<0.05) associations. Conclusion: Preserved transcriptional immune networks were identified across blood and brain and across two neurodegenerative diseases. Expanding gene co‐expression network analyses to other diseases and integrating additional omics measures and phenotypes can further strengthen these findings to unravel the immune signatures across complex diseases. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is a devastating neurodegenerative disorder with few therapies to treat, mitigate or prevent its onset. Understanding of this disease is predominantly based on research in non‐Hispanic Whites (NHW) although AD disproportionately affects African Americans (AA) and Latin Americans (LA), underrepresented in AD research. To address this knowledge gap, the Accelerating Medicine Partnership for Alzheimer's Disease (AMP‐AD) Diversity Working Group was launched to generate multi‐omics data from post‐mortem brain tissue from donors of predominantly AA and LA descent. Here, we focus on genomic and transcriptomics measures, made available through the AD Knowledge Portal (ADKP). Method: Brain tissue from dorsolateral prefrontal cortex (DLPFC), caudate nucleus (CN), superior temporal gyrus (STG) and temporal pole (TP) regions of AA (N = 299), LA (N = 344) and NHW (N = 532) donors was obtained through Mayo Clinic, Mt. Sinai School of Medicine, Emory, Columbia, Rush Alzheimer's Disease Center, Banner Sun Health, and 1Florida. DNA extracted from DLPFC tissue samples (n = 641) was utilized for whole genome sequencing (WGS) at New York Genome Center (NYGC). RNAseq of 2,224 samples was conducted either at Mayo, Rush or NYGC. Sequencing reads were processed through GenomeGPS and MAPRseq pipelines for WGS and RNAseq data, respectively. Following quality control (QC), RNAseq data was normalized and assessed for sources of variation (SOV). Integration of WGS and RNAseq data to perform comparative eQTL analysis across multi‐ethnic populations and brain regions is ongoing. Result: WGS data for 621 donors, and RNAseq data generated at Mayo (n = 1,136 samples), Rush (n = 627), and NYGC (n = 779) sequencing centers, were deposited to the ADKP. Consensus processing of RNAseq data revealed site, sex, race/ethnicity, RIN, AD diagnosis, age at death and/or library batch as SOV across various sites and brain regions. Principal component analysis of gene expression measures revealed no major stratification by disease or brain region. Accompanying clinical metadata of donors have been distributed through ADKP. Conclusion: These multi‐omics data made available to the research community is expected to be an initial step towards bridging our data and knowledge gap to elucidate conserved and distinct AD related pathways across these underrepresented at‐risk populations. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is neuropathologically characterized by amyloid‐β (Aβ) plaques and tau neurofibrillary tangles often quantified by Thal phase and Braak stage, respectively. Aβ also frequently deposits in the cerebrovasculature with severity categorized by a cerebral amyloid angiopathy (CAA) score. These and related measures often show high variability within AD suggesting distinct underlying mechanisms. We hypothesize that, within the AD brain, neuropathology and levels of core AD‐related proteins are influenced by variations in DNA methylation (DNAm). To test this, we performed epigenome‐wide association studies (EWAS) using DNAm measures from the temporal cortex (TCX) and cerebellum (CER) with AD‐related neuropathologic measures (Braak, Thal, CAA) and brain biochemical levels of five proteins (apoE, Aβ40, Aβ42, tau, p‐tau). Methods: DNAm from neuropathologically‐confirmed AD cases was measured by reduced representation bisulfite sequencing (RRBS) from 471 TCX samples, 200 of which also had CER RRBS. TCX levels of five AD‐related proteins from three tissue fractions (buffer‐, detergent‐, and in‐soluble) were measured previously by ELISA (Liu 2020). CpG methylation (CpGm) was binned by a 15‐state chromatin model (Kundaje 2015) and averaged into CpGm clusters (rCpGm). rCpGms were tested for association with each AD endophenotype and expression levels of nearby genes through multi‐variable linear regression. Replication of significant rCpGms was performed in two independent datasets with AD‐related endophenotypes (Shireby 2022, De Jager 2014). Results: Our innovative binning method demonstrated biologically relevant CpGm patterns. We found epigenome‐wide significant associations primarily with tau‐related endophenotypes including 93 that had significant and concordant associations in the replication datasets. These rCpGms also significantly associated with expression of nearby genes showing enrichment in oligodendrocyte marker genes including those related to myelination. In vitro validation of tau effects on oligodendrocyte gene expression through DNAm is ongoing. Conclusions: Although all endophenotypes tested are core to AD pathophysiology, our results suggest each has a distinct epigenetic architecture underlying their variability in the AD brain. In particular, we found evidence of DNAm variability associating with brain oligodendrocyte gene expression and TCX tau levels. By discovering AD brain endophenotype‐specific DNAm changes, we can identify core components of complex mechanisms revealing important biological insights into AD pathophysiology. [ABSTRACT FROM AUTHOR]

Introduction: Presence of apolipoprotein E (APOE) ε4 has shown greater predisposition to medial temporal involvement in posterior cortical atrophy (PCA) and logopenic progressive aphasia (LPA). Little is known about its influence on memory network connectivity, a network comprised of medial temporal structures. Methods: Fifty‐eight PCA and 82 LPA patients underwent structural and resting state functional magnetic resonance imaging (MRI). Bayesian hierarchical linear models assessed the influence of APOE ε4 on within and between‐network connectivity for five networks. Results: APOE ε4 carriers showed reduced memory and language within‐network connectivity in LPA and increased salience within‐network connectivity in PCA compared to non‐carriers. Between‐network analysis showed evidence of reduced DMN connectivity in APOE ε4 carriers, with reduced DMN‐to‐salience and DMN‐to‐language network connectivity in PCA, and reduced DMN‐to‐visual network connectivity in LPA. Discussion: The APOE genotype influences brain connectivity, both within and between‐networks, in atypical Alzheimer's disease. However, there was evidence that the modulatory effects of APOE differ across phenotype. HIGHLIGHTS: APOE genotype is associated with reductions in within‐network connectivity for the memory and language networks in LPAAPOE genotype is associated with reductions in language‐to‐visual connectivity in LPA and PCAAPOE genotype has no effect on the memory network in PCA [ABSTRACT FROM AUTHOR]

Introduction: Apolipoprotein 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. Methods: An 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. Results: At 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. Discussion: APOE 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. [ABSTRACT FROM AUTHOR]

Intron retention (IR) has been implicated in the pathogenesis of complex diseases such as cancers; its association with Alzheimer's disease (AD) remains unexplored. We performed genome‐wide analysis of IR through integrating genetic, transcriptomic, and proteomic data of AD subjects and mouse models from the Accelerating Medicines Partnership‐Alzheimer's Disease project. We identified 4535 and 4086 IR events in 2173 human and 1736 mouse genes, respectively. Quantitation of IR enabled the identification of differentially expressed genes that conventional exon‐level approaches did not reveal. There were significant correlations of intron expression within innate immune genes, like HMBOX1, with AD in humans. Peptides with a high probability of translation from intron‐retained mRNAs were identified using mass spectrometry. Further, we established AD‐specific intron expression Quantitative Trait Loci, and identified splicing‐related genes that may regulate IR. Our analysis provides a novel resource for the search for new AD biomarkers and pathological mechanisms. [ABSTRACT FROM AUTHOR]

Background: A hallmark of Alzheimer's disease is amyloid‐β (Aβ) deposition in the brain parenchyma as senile plaques which Aß frequently accompanies in the cerebral vasculature as cerebral amyloid angiopathy (CAA). Previous studies demonstrated that the cerebrovascular system is essential for Aβ clearance and interactions exist between cerebrovascular disease and AD. Neuroimaging data, including measures on small vessel disease, amyloid deposits, and microhemorrhages (MCH), can reflect both cerebrovascular disease and AD pathology, thereby serving as intermediate phenotypes of both conditions. We aim to identify genes and co‐expression networks in blood associated with these neuroimaging endophenotypes and the biological pathways enriched in these perturbed transcriptional networks. Method: We conducted differential gene expression and Weighted Gene Co‐Expression Network analyses (WGCNA) on blood RNA sequencing data of 407 participants from the longitudinally followed Mayo Clinic Study of Aging cohort. The neuroimaging phenotypes include MCH, infarction, and amyloid deposits measured by Pittsburgh compound B positron emission tomography (PiB PET). Result: WGCNA analysis showed a nominally significant association (p<0.05) between several module eigengenes (MEs) and MCH and PiB PET. One module, M42, remained significantly associated with PiB PET after Bonferroni correction for all 43 modules tested. Pathway enrichment analysis of M42 identified two significant pathways (FDR‐adjusted p<0.05) including phosphodiesterase I activity and IgE binding. These pathways contain genes such as MS4A2 encoding the high‐affinity IgE receptor involved in the immune response. Similarly, ENPP2 in the phosphodiesterase I activity pathway represents an additional candidate gene previously implicated in Alzheimer's disease. Conclusion: We generated co‐expression networks and identified one network module with a statistically significant association between brain amyloid deposits and blood transcriptome data. Further investigations of this network and its enriched pathways are necessary to understand their roles in amyloidosis, CAA, and neurodegeneration. Future studies will include seeking replication of these results in other datasets. Such studies can help elucidate the biological mechanisms of pathogenesis of cerebrovascular damage and amyloid deposits. In addition, in a clinical setting, blood levels of transcripts discovered in this study may serve as predictive or diagnostic biomarkers with mechanistic implications. [ABSTRACT FROM AUTHOR]

Background: For blood‐based biomarkers to fulfill their potential to revolutionize diagnosis and management of Alzheimer's disease (AD), additional research in diverse populations remains critical. Here, we analyzed a biracial sample to assess the profiles of blood‐based AD biomarkers and their relationships to cognition and medical comorbidities. Methods: Self‐reported African‐American (AA; n = 267) and non‐Hispanic White (NHW; n = 268) participants evaluated through the Mayo Jacksonville Alzheimer's Disease Research Center were matched on age, sex, and clinical diagnosis. Plasma AD biomarkers (Aβ42/40, p‐tau181, GFAP, NfL) were measured using the Quanterix SiMoA HD‐X analyzer. Cognition was assessed with the Mini Mental State Examination. Wilcoxon rank sum tests were used to assess for differences in plasma biomarker levels by sex. Linear models tested for associations of race, chronic kidney disease (CKD), and vascular risk factors with plasma AD biomarker levels, covarying for age and sex. Additional models assessed for interactions between race and plasma biomarkers in predicting cognition, further covarying for education. Results: The sample included adults aged 43‐100 years, with 69% women. Education was higher in NHW participants (median 16 vs. 12 years, p<0.001). APOE (apolipoprotein E) ε4 positivity was higher in AA participants (43% vs. 34%; p = 0.04). There were no differences in plasma AD biomarker levels between AA and NHW participants. These findings were unchanged after stratifying by cognitive status (unimpaired versus impaired). Although the association between p‐tau181 and cognition appeared stronger in NHW participants while the association between Aβ42/40 and cognition appeared stronger in AA participants, these findings did not survive after excluding individuals with CKD. Women displayed higher GFAP (p = 0.002) and lower p‐tau181 (p = 0.001) levels than men. Diabetes was inversely associated with GFAP levels (p<0.001). Conclusions: In a biracial, community‐based sample, we observed that sex differences, CKD, and vascular risk factors contributed to variation in plasma AD biomarkers, while self‐reported race did not. Our results reinforce the critical need to account for sex and systemic medical comorbidities in equitably deploying blood‐based AD biomarkers in the general population. [ABSTRACT FROM AUTHOR]

Background: Given the overlap of symptoms between Alzheimer's disease (AD) and other dementias, it is essential to develop widely accessible biomarkers that will ensure an accurate diagnosis of AD to enable its proper treatment. African Americans (AA) are twice more likely to develop AD than non‐Hispanic whites (NHW) and yet they remain underrepresented in AD research. The few studies conducted in AA suggest that there are different factors that influence AD in this population; therefore, it is possible that different biomarkers and/or therapies may be needed to effectively treat AD in AA. In this study we are testing the hypothesis that genetic variants that show association with AD‐risk in AA and with plasma levels of transcript and proteins may serve as AD biomarkers which are more accessible and less costly than cerebrospinal fluid or neuroimaging biomarkers. Methods: In 189 AD cases and 183 cognitively unimpaired (CU) AA participants of the Florida Consortium of African American Alzheimer's Disease Studies (FCA3DS), we performed targeted DNA sequencing of 10 AD‐associated loci. Genetic variants were tested for association with plasma transcripts and plasma total tau protein levels previously measured in this cohort using a nanoString® custom panel (Reddy J, et al. 2022) and Simoa assays (Deniz K, et al. 2021), respectively. In receiver operating characteristic (ROC) analyses, the most significant expression/protein quantitative trait loci (eQTL/pQTL) were added sequentially to a base model that included only age and sex to identify eQTL/pQTL that improved the accuracy to correctly classify AD cases vs. CU. Results: Of the 5112 variants identified in the targeted sequencing, 71 were nominally associated (p<0.05) with plasma transcript/protein levels and with AD‐risk. ROC analysis of age, sex, eQTL/pQTL in APOE, ABCA7, AKAP9, EPHA1, SORL1, and TLR4, and plasma levels of APP, ABCA7, AKAP9, CD14, CLU, and APOE‐ɛ4 dosage achieved 77.6% area under the curve (AUC) to discriminate AD vs. CU, a 19.9% improvement over a model that only included age and sex. Conclusions: Plasma transcript levels and eQTL/pQTL are promising diagnostic biomarkers for AD that may improve accessibility and reduce costs for a more accurate diagnosis of AD. [ABSTRACT FROM AUTHOR]

Background: Cerebral amyloid angiopathy (CAA), characterized by the accumulation of amyloid‐beta in the cerebrovasculature, effects blood vessel integrity leading to brain hemorrhages and an accelerated cognitive decline in Alzheimer's disease (AD) patients. In a previous genome‐wide association study (GWAS) of 853 neuropathologically confirmed AD cases, we identified a LINC‐PINT splice variant that associated with lower CAA levels amongst individuals that did not have a copy of the APOEe4 AD risk allele (Reddy. J et al 2021). In this study, we perform GWAS to identify further genetic risk factors for CAA and AD neuropathology (Braak stage, Thal phase) in additional AD cases, and participants lacking significant AD pathology (non‐AD). Method: We expanded the original AD cohort (N = 853) with 400 additional AD cases genotyped using the Infinium Omni2.5+Exome array. We also identified 110 AD and 502 non‐AD donors from the Mayo Clinic Brain Bank, with existing CAA scores and genome‐wide genotypes. We performed QC and imputation of these genotypes to TOPMed. We will conduct GWAS in AD only (N = 1,363), non‐AD only, as well as the combined cohort (N = 1,865). We will test imputed variant dosages for association with square root transformed CAA, Braak and Thal, using linear regression in PLINK, adjusting for relevant covariates. We will perform interaction analysis of CAA‐associated variants with APOEe4 and sex; and pursue stratified analyses. Summary statistics will be utilized to perform SNP‐based gene set enrichment analysis to identify biological pathways implicated in CAA. Result: We expect that the increased power of this expanded dataset will lead to the identification of additional novel genetic risk factors for CAA and AD neuropathology. Genetic interaction analysis with sex and APOEe4 may further elucidate the role of these risk factors. The addition of 1,102 participants will enable assessment of the LINC‐PINT locus for association with CAA in an independent dataset. Conclusion: We expect this study will provide further insights into the genetic architecture underlying risk for CAA, both in the context of significant AD pathology, and without. Characterization of genetic variants in the context of neuropathology may lead to new avenues of research aimed at identifying biomarkers and therapies to treat CAA, and AD. [ABSTRACT FROM AUTHOR]

Background: Two major risk factors of Alzheimer's disease (AD) are advanced age and the APOE‐ε4 risk allele. However, despite having these risk factors, some individuals escape from developing AD or have slower cognitive decline. In this study we hypothesized that "resilient" individuals, defined as those who remain cognitively normal despite being >80 years‐old and carrying at least one copy of the APOE‐ε4 allele, have concerted changes in their blood transcriptomes that are associated with resilience to AD. Method: We generated blood RNA‐sequence data from 105 APOE‐ε4 carriers from the Mayo Clinic Study of Aging (MCSA) who remained cognitively normal after age 80 (resilient), or who developed mild cognitive impairment (MCI) or AD (non‐resilient). Weighted gene co‐expression network analysis (WGCNA) was performed to evaluate the association of the blood co‐expression network with primary phenotypes of resilience and memory scores. To validate our findings, we constructed a consensus co‐expression network using both MCSA and a replication cohort of blood microarray data from 91 Alzheimer's Disease Neuroimaging Initiative (ADNI) study participants who had a similar demographic profile. We annotated the consensus modules for their enrichment of cell types, biological processes, genes within previously published genome‐wide significant (GWS) AD‐associated loci, and genes that reside in consensus modules built from seven brain regions across three different autopsy cohorts. To identify genetic variants regulating blood consensus module co‐expression, we performed module quantitative trait locus (modQTL) analysis. Result: We found co‐expression modules significantly (q<0.05) correlated with the memory phenotype, logical memory delayed recall, across both MCSA and ADNI cohorts. Some of these modules were enriched with blood cell types and biological processes, including telomere maintenance, mitochondrial functions, and immune response. We found 1 module significantly (q<0.05) enriched with genes near GWS AD‐associated loci and 4 modules with genes in brain consensus modules. Lastly, we found 8 modQTLs significantly (Bonferroni‐p<0.05) associated with the co‐expression of 5 different modules. Conclusion: We identified blood co‐expression modules, biological pathways and specific genetic variants associated with cognitive resilience in the presence of AD risk factors. This study provides novel insights into the potential role of peripheral blood in the development of and resilience to AD. [ABSTRACT FROM AUTHOR]

Background: Context‐specific networks can capture functionally important genes that may not be differentially expressed. Leveraging seven different gene expression datasets of Alzheimer's disease (AD) and healthy control brains, we constructed a novel pipeline that includes such network analysis, augmented by in vivo validations and in silico drug repurposing to facilitate prioritization of AD therapeutic targets. Method: We utilized publicly available gene expression data from 733 AD and 454 control brains across 7 datasets and the NetDecoder (PMID: 26975659) network biology platform to build context‐specific networks. Based on the known protein‐protein interaction and gene expression correlations, information flow from the top differentially expressed genes (DEG) to transcriptional regulator genes was calculated using a process‐guided flow algorithm. Genes with the greatest informational flow changes across AD cohorts were systematically prioritized. We next validated these genes in a medium‐throughput screen of a tau‐transgenic Drosophila model (PMID: 11408621). Further, we identified existing small‐molecule drugs to target the candidate genes utilizing curated databases. Results: A total of 14 context‐specific networks were constructed across 7 datasets. We found AD‐related genes, such as APP, to have high flow differences between AD and control networks and high connectivity. Notably, many such genes were not DEGs between AD and control, suggesting that the information flow captures novel aspects of AD pathophysiology. We nominated 224 unique genes with the greatest flow differences for functional validation. We screened 111 of the 224 candidate genes with readily available, high‐confidence orthologs in Drosophila. We identified genes that suppress (N = 68) or enhance (N = 27) tau‐related neurodegeneration in this model. We confirmed the effects of previously nominated genes, such as HDAC1, which enhances tau‐neurodegeneration if overexpressed and suppresses it if knocked down. We also identified and validated additional therapeutic targets. Lastly, we applied a network‐proximity‐based algorithm and identified small molecule drugs for the candidate genes. Conclusion: We present a novel pipeline that integrates analytic approaches, experimental validation, and drug repurposing to facilitate therapeutic discovery in AD. We applied this pipeline and nominated previously known and novel genes implicated in AD pathogenesis. Our pipeline demonstrates a cross‐species, systems‐level approach to therapeutic nomination in AD and related neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is neuropathologically characterized by amyloid‐β (Aβ) plaques and tau neurofibrillary tangles often quantified by Thal phase and Braak stage, respectively. Aβ also frequently deposits in the cerebrovasculature with severity categorized by a cerebral amyloid angiopathy (CAA) score. These and related measures often show high variability within AD suggesting distinct underlying mechanisms, the identification of which may reveal important biological insights into AD pathophysiology. We hypothesize that, within the AD brain, neuropathology and levels of core AD‐related proteins are influenced by variations in DNA methylation (DNAm). To test this, we performed epigenome‐wide association studies (EWAS) using DNAm clusters from the temporal cortex (TCX) and cerebellum (CER) with AD‐related neuropathologic measures (Braak, Thal, and CAA) and brain biochemical levels of five proteins (apoE, Aβ40, Aβ42, tau, and p‐tau). Methods: DNAm from neuropathologically‐confirmed AD cases available through the Mayo Clinic brain bank was measured by reduced representation bisulfite sequencing (RRBS) from 471 brain samples, 200 of which had both TCX and CER measures. Neuropathology was scored by an experienced neuropathologist. TCX levels of five AD‐related proteins from three tissue fractions (buffer‐, detergent‐, and in‐soluble) were measured by ELISA (Liu 2020). CpG methylation (CpGm) was binned by a 15‐state chromatin model (Kundaje 2015) and averaged. Averaged CpGm clusters were tested for their association with each endophenotype through multi‐variable linear regression. The influence of CpGm clusters on expression levels of nearby genes was also investigated through multi‐variable regression. Results: Our innovative binning method demonstrated expected and biologically relevant CpGm patterns. We identified multiple epigenome‐wide significant CpGm clusters unique to each AD‐related endophenotype and brain region. Comparisons between the TCX and CER further revealed brain region‐specific enrichment of distinct CpGm clusters. Significant CpGm clusters were further characterized by their influence on gene expression. Conclusions: Although all neuropathologic and biochemical endophenotypes tested are core to AD pathophysiology, our results suggest each has a distinct epigenetic architecture underlying their variability in the AD brain. By discovering brain region‐specific DNAm changes that contribute to each neuropathologic or biochemical outcome, we can identify core components of complex mechanisms that individually and jointly contribute to AD. [ABSTRACT FROM AUTHOR]

Introduction: MAPT H1 haplotype is implicated as a risk factor for neurodegenerative diseases including Alzheimer's disease (AD). Methods: Using Alzheimer's Disease Genetics Consortium (ADGC) genome‐wide association study (GWAS) data (n = 18,841), we conducted a MAPT H1/H2 haplotype–stratified association to discover MAPT haplotype–specific AD risk loci. Results: We identified 11 loci—5 in H2‐non‐carriers and 6 in H2‐carriers—although none of the MAPT haplotype–specific associations achieved genome‐wide significance. The most significant H2 non‐carrier–specific association was with a NECTIN2 intronic (P = 1.33E‐07) variant, and that for H2 carriers was near NKX6‐1 (P = 1.99E‐06). The GABRG2 locus had the strongest epistasis with MAPT H1/H2 variant rs8070723 (P = 3.91E‐06). Eight of the 12 genes at these loci had transcriptome‐wide significant differential expression in AD versus control temporal cortex (q < 0.05). Six genes were members of the brain transcriptional co‐expression network implicated in "synaptic transmission" (P = 9.85E‐59), which is also enriched for neuronal genes (P = 1.0E‐164), including MAPT. Discussion: This stratified GWAS identified loci that may confer AD risk in a MAPT haplotype–specific manner. This approach may preferentially enrich for neuronal genes implicated in synaptic transmission. [ABSTRACT FROM AUTHOR]

Introduction: Our primary goal was to examine demographic and clinicopathologic differences across an ethnoracially diverse autopsy‐confirmed cohort of Alzheimer's disease cases. Methods: A retrospective study was conducted in the Florida Autopsied Multi‐Ethnic cohort on 1625 Alzheimer's disease cases, including decedents who self‐reported as Hispanic/Latino (n = 67), black/African American (n = 19), and white/European American (n = 1539). Results: Hispanic decedents had a higher frequency of family history of cognitive impairment (58%), an earlier age at onset (median age of 70 years), longer disease duration (median of 12 years), and lower MMSE proximal to death (median of 4 points) compared with the other ethnoracial groups. Black decedents had a lower Braak tangle stage (stage V) and higher frequency of coexisting hippocampal sclerosis (21%); however, only hippocampal sclerosis differences survived adjustment for sex, age at onset, and disease duration. Neither Thal amyloid phase nor coexisting Lewy body disease differed across ethnoracial groups. Discussion: Despite a smaller sample size, Hispanics demonstrated longer disease duration with Alzheimer's disease, but not greater lifespan. Neuropathologic differences across ethnoracial groups supported differences in tau pathology distribution and coexisting hippocampal sclerosis, which may impact biomarker studies. [ABSTRACT FROM AUTHOR]

Introduction: Comparative transcriptome analyses in Alzheimer's disease (AD) and other neurodegenerative proteinopathies can uncover both shared and distinct disease pathways. Methods: We analyzed 940 brain transcriptomes including patients with AD, progressive supranuclear palsy (PSP; a primary tauopathy), and control subjects. Results: We identified transcriptional coexpression networks implicated in myelination, which were lower in PSP temporal cortex (TCX) compared with AD. Some of these associations were retained even after adjustments for brain cell population changes. These TCX myelination network structures were preserved in cerebellum but they were not differentially expressed in cerebellum between AD and PSP. Myelination networks were downregulated in both AD and PSP, when compared with control TCX samples. Discussion: Downregulation of myelination networks may underlie both PSP and AD pathophysiology, but may be more pronounced in PSP. These data also highlight conservation of transcriptional networks across brain regions and the influence of cell type changes on these networks. Highlights: Brain myelination transcriptional networks are down in PSP and AD.Myelination networks are higher in AD vs. PSP but lower compared with controls.Network structures are preserved between temporal cortex and cerebellum. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder neuropathologically characterized by amyloid‐β (Aβ) plaques and tau neurofibrillary tangles often measured by Thal phase and Braak stage, respectively. Frequently, Aβ also deposits in the brain vasculature with severity categorized by a cerebral amyloid angiopathy (CAA) score. Assessment of these and related endophenotypes can reveal biological insights into the phenotypic variability in AD. We hypothesize that, amongst AD patients, severity of neuropathology and brain levels of AD‐related proteins are influenced by variation in DNA methylation (DNAm), the identification of which may uncover biological pathways for AD pathogenesis. To test this, we performed epigenome‐wide association studies (EWAS) using DNAm from the temporal cortex (TCX) and cerebellum (CER) with AD‐related neuropathology measures (Braak, Thal, and CAA) and brain levels of five proteins (apoE, Aβ40, Aβ42, tau, and p‐tau). Methods: DNAm from autopsy‐confirmed AD cases available through the Mayo Clinic Brain Bank was measured by reduced representation bisulfite sequencing (RRBS) from 471 brain samples, 200 of which had both TCX and CER measures. Bisulfite converted reads were sequenced on the Illumina High Seq4000 and quality filtered. Neuropathology scoring was performed by an experienced neuropathologist. TCX levels of five AD‐related proteins from three fractions (buffer‐soluble, detergent‐soluble, and insoluble) were measured by ELISA (Liu et al. 2020). Individual CpG methylation ratios were tested for association with each neuropathological and biochemical measure using the R package CpGassoc. Results: We identified multiple epigenome‐wide significant CpGs unique to each AD‐related measure. Comparisons between the TCX and CER revealed region specific CpG associations. The effects of sex, age at death, APOE genotype, and presence of genetic variants for each significant CpG association were also identified. Conclusions: Although all neuropathological and biochemical measures tested reflect core AD pathologies, our results demonstrate unique associations of epigenetic factors with these individual phenotypes, suggesting that their variability may be governed by distinct epigenetic processes. Discovery of DNAm changes that underlie specific neuropathological or biochemical outcomes can enhance our understanding of AD pathophysiology and may lead to the identification of novel gene or pathway targets for the different facets of this complex condition. [ABSTRACT FROM AUTHOR]

Background: Progressive supranuclear palsy (PSP) is a neurodegenerative disorder characterized by cell‐type‐specific tau lesions in neurons and glia. Using bulk brain RNAseq, we previously identified PSP‐associated genes and co‐expression networks that are enriched with cell‐type marker genes. We extended our work to identify cell‐type‐specific expression perturbations in PSP using a systems approach and in vivo validations in a model system. Method: Single‐nucleus RNAseq (snRNAseq) was performed using 33 frozen brain temporal cortex (TCX) samples from PSP and control brains. After quality control (QC), integration, and clustering of nuclei, each cluster was annotated for its cell type. We identified differentially expressed genes (DEG) in PSP and further investigated them using an independent bulk RNAseq dataset comprising 408 PSP and control TCX samples for replication and assessing co‐expression patterns. Top DEGs were identified and then validated using external bulk RNAseq datasets from a tau transgenic mouse model. Further, the ability of the validated DEGs to rescue tau‐mediated cellular toxicity was evaluated in a tau transgenic Drosophila model. Result: After QC, 30 clusters comprised of 27,284 nuclei were obtained, encompassing two neuronal and six glial cell types. DEGs of each cluster revealed cell‐type‐specific PSP associations. Notably, many of the up‐regulated DEGs in the astroglial clusters were members of the bulk RNAseq co‐expression modules that were also up‐regulated in PSP and enriched with astrocytic markers. There were also consistent findings for the up‐regulated DEGs in the endothelial and microglial clusters, and for down‐regulated DEGs in the oligodendroglial clusters. Subsequently, we prioritized 240 DEGs with congruent cell‐type‐specific perturbations in snRNAseq and bulk RNAseq and validated 29 of those using transgenic mouse model data. Lastly, a significant number of the up‐regulated glial genes, when knocked down in a tau transgenic Drosophila model, led to reduced tau‐mediated cellular toxicity, suggesting novel potential therapeutic avenues. Conclusion: PSP brains demonstrated robust cell‐type‐specific gene expression perturbations in the glial cells populations that were validated across different datasets. Importantly, inhibiting the up‐regulated expression perturbations rescued tau‐mediated toxicity in a Drosophila model. Our findings highlight the cell‐type‐specific transcriptome changes in PSP and provide potential therapeutic options for primary tauopathies. [ABSTRACT FROM AUTHOR]

Introduction Genetic loci for Alzheimer's disease (AD) have been identified in whites of European ancestry, but the genetic architecture of AD among other populations is less understood. Methods We conducted a transethnic genome-wide association study (GWAS) for late-onset AD in Stage 1 sample including whites of European Ancestry, African-Americans, Japanese, and Israeli-Arabs assembled by the Alzheimer's Disease Genetics Consortium. Suggestive results from Stage 1 from novel loci were followed up using summarized results in the International Genomics Alzheimer's Project GWAS dataset. Results Genome-wide significant (GWS) associations in single-nucleotide polymorphism (SNP)–based tests ( P < 5 × 10 −8 ) were identified for SNPs in PFDN1/HBEGF , USP6NL/ECHDC3 , and BZRAP1-AS1 and for the interaction of the (apolipoprotein E) APOE ε4 allele with NFIC SNP. We also obtained GWS evidence ( P < 2.7 × 10 −6 ) for gene-based association in the total sample with a novel locus, TPBG ( P = 1.8 × 10 −6 ). Discussion Our findings highlight the value of transethnic studies for identifying novel AD susceptibility loci. [ABSTRACT FROM AUTHOR]

Introduction We hypothesized that common Alzheimer's disease (AD)-associated variants within the triggering receptor expressed on myeloid ( TREM ) gene cluster influence disease through gene expression. Methods Expression microarrays on temporal cortex and cerebellum from ∼400 neuropathologically diagnosed subjects and two independent RNAseq replication cohorts were used for expression quantitative trait locus analysis. Results A variant within a DNase hypersensitive site 5′ of TREM2 , rs9357347-C, associates with reduced AD risk and increased TREML1 and TREM2 levels (uncorrected P = 6.3 × 10 −3 and 4.6 × 10 −2 , respectively). Meta-analysis on expression quantitative trait locus results from three independent data sets ( n = 1006) confirmed these associations (uncorrected P = 3.4 × 10 −2 and 3.5 × 10 −3 , Bonferroni-corrected P = 6.7 × 10 −2 and 7.1 × 10 −3 , respectively). Discussion Our findings point to rs9357347 as a functional regulatory variant that contributes to a protective effect observed at the TREM locus in the International Genomics of Alzheimer's Project genome-wide association study meta-analysis and suggest concomitant increase in TREML1 and TREM2 brain levels as a potential mechanism for protection from AD. [ABSTRACT FROM AUTHOR]

Introduction The genetics underlying posterior cortical atrophy (PCA), typically a rare variant of Alzheimer's disease (AD), remain uncertain. Methods We genotyped 302 PCA patients from 11 centers, calculated risk at 24 loci for AD/DLB and performed an exploratory genome-wide association study. Results We confirm that variation in/near APOE/TOMM40 ( P = 6 × 10 −14 ) alters PCA risk, but with smaller effect than for typical AD (PCA: odds ratio [OR] = 2.03, typical AD: OR = 2.83, P = .0007). We found evidence for risk in/near CR1 ( P = 7 × 10 −4 ), ABCA7 ( P = .02) and BIN1 ( P = .04). ORs at variants near INPP5D and NME8 did not overlap between PCA and typical AD. Exploratory genome-wide association studies confirmed APOE and identified three novel loci: rs76854344 near CNTNAP5 ( P = 8 × 10 −10 OR = 1.9 [1.5–2.3]); rs72907046 near FAM46A ( P = 1 × 10 −9 OR = 3.2 [2.1–4.9]); and rs2525776 near SEMA3C ( P = 1 × 10 −8 , OR = 3.3 [2.1–5.1]). Discussion We provide evidence for genetic risk factors specifically related to PCA. We identify three candidate loci that, if replicated, may provide insights into selective vulnerability and phenotypic diversity in AD. [ABSTRACT FROM AUTHOR]

Background: Inter‐cellular communication within the gliovascular unit (GVU) is critical for cerebral blood flow regulation, maintenance of the blood‐brain‐barrier (BBB) properties, and brain energy metabolism. Although numerous cell biology studies demonstrate the role of the GVU for BBB breakdown in Alzheimer's disease (AD), the precise molecular changes contributing to its pathophysiology are unclear. Method: We performed single nucleus RNA sequencing (snRNAseq) of temporal cortex tissue in 24 AD and control brains to understand the transcriptional changes in the cells of GVU. We acquired the snRNAseq profile of 79,751 total brain cells that comprise 6,541 astrocytes and 2,210 vascular cells. The latter formed three distinct vascular clusters characterized as activated pericytes, endothelia and resting pericytes. We identified differentially expressed genes (DEGs) and their enriched pathways in these clusters and detected the most transcriptional changes within activated pericytes. Using our data and a knowledge‐based predictive algorithm, we discovered and prioritized molecular interactions between vascular and astrocyte clusters, the main cell types of the GVU of the BBB. Results: Vascular targets predicted to interact with astrocytic ligands have biological functions in signalling, angiogenesis, amyloid ß metabolism and cytoskeletal structure. Top astrocytic and vascular interacting molecules include both novel and known AD risk genes such as APOE, APP and ECE1. We validated gene expression changes using qPCR. We are in the process of evaluating these gene expression changes in antemortem blood from AD and control participants. Conclusion: Our findings provide valuable information into the transcriptional changes in predicted vascular‐astrocytic partners at the GVU, highlighting insights into the molecular mechanisms of BBB breakdown in AD. [ABSTRACT FROM AUTHOR]

Background: In the Alzheimer's disease sequencing project (ADSP) whole exome dataset, only the well‐known TREM2.pR47H variant shows genome‐wide significance by conventional single variant analysis. To identify novel AD genes related to TREM2, we used gene‐based polygenic score analysis (PGSA) to evaluate an immune, temporal cortical co‐expression network with 229 genes including TREM2. Method: The most recent whole exome variant call files from the ADSP (NG00067.v7) were subjected to stringent quality control. Post‐QC samples were divided into discovery (4174 samples sequenced at Broad), test (3299 samples sequenced at WashU), and follow‐up (2273 samples sequenced at Baylor) sets. The pruned variants (r2 < 0.2) with a minor allele count over 20 in each gene were analyzed by Broad/WashU PGSA thereby obtaining P‐values (gPbr.wa) for each gene in WashU samples. To assess significance in independent Baylor samples, cumulative Broad/Baylor PGSA was performed using a novel approach in which variants were stratified by both gene (gPbr.wa) and variant (Broad.P). Result: After excluding TREM2, the five variants with gPbr.wa ≤ 0.08 and Broad.P ≤ 0.03 showed significant association in Broad/Baylor PGSA. One of these variants showed no evidence of association with AD in the combined dataset. Polygenic scores for the other four variants, which were in three genes, showed significant association in Baylor samples, and significant, essentially identical association in WashU samples. Polygenic scores for nine additional variants in these genes (0.03> Broad.P ≤ 0.13) also showed significant, essentially identical association in Baylor and WashU samples. The association of these 13 variants with AD was driven primarily by six deleterious, protein‐altering variants with minor allele frequencies less than 1%, but the other 7 variants also contributed. Conclusion: Using gene‐based polygenic score analysis to analyze an immune co‐expression network, we identify three novel immune genes with actionable nonsynonymous and stopgain variants that show significant, replicable association with AD in the most recent release of the ADSP whole exome dataset. [ABSTRACT FROM AUTHOR]

Background: African 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. Method: Utilizing 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. Result: An 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. Conclusion: The 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. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder neuropathologically characterized by amyloid‐β (Aβ) plaques and neurofibrillary tangles. Assessment of AD‐related endophenotypes can reveal novel insights into aspects of the heterogeneity of AD. We hypothesize that, amongst AD patients, the levels and solubility of AD‐related proteins are influenced by genetic variants; identifying these may provide key insights into disease pathogenesis. To test this, we performed a genome‐wide association study (GWAS) for the levels of five AD‐related proteins (apoE, Aβ40, Aβ42, tau, and p‐tau) in the brain. Methods: Genome‐wide genotypes were collected from 441 autopsy‐confirmed AD cases on the Infinium Omni2.5Exome‐8 v1.3 genotyping array, imputed to the haplotype reference consortium (HRC) panel, and quality filtered. Temporal cortex levels of the five AD‐related proteins from three fractions, i.e. buffer‐soluble (TBS), detergent‐soluble (Triton‐X=TX), and insoluble (Formic acid=FA) were measured by ELISA. Using linear regression, genetic variants were tested for association with each biochemical measure, and the Aβ40/42 ratio. Pathway analysis was done using GSA‐SNP2 to identify enriched Gene Ontology (GO) terms. Results: We identified 9 unique GWS variants (genome‐wide significant, p<2.89E‐08), 2 at the APOE locus and 7 novel. Variants within the APOE locus were significantly associated with Aβ40 levels in the TX and FA fractions, the Aβ40/42 ratio in the FA fraction, and apoE levels in the TBS and FA fractions. Of the novel GWS variants, four were associated with Aβ40 residing on chromosomes 17 (TBS), 3, 4, and 15 (TX), and three with apoE levels on chromosomes 19 (TBS), 7, and 14 (TX). Pathway analysis revealed both shared and distinct pathways significantly enriched for the GWAS results. Conclusions: Although all biochemical measures tested reflect proteins core to AD pathology, our results strongly suggest each have unique genetic factors and enriched pathways which influence their brain levels. Furthermore, discovery of genetic factors that underlie specific biochemical outcomes may lead to the identification of novel genes that influence biochemical properties of AD proteins. These findings can enhance our understanding of the pathophysiology of proteostasis in AD and may have implications for other neurodegenerative diseases also characterized by abnormal protein accumulation in the brain. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is a complex proteinopathy with abnormal accumulation of amyloid β and tau in which the temporal cortex (TCx) is severely affected. Progressive supranuclear palsy (PSP) is a primary tau proteinopathy. Neurodegeneration in the TCx is less severe in PSP than in AD. In contrast, the cerebellum (CER) is relatively spared from gross pathology especially in AD. To determine if there are shared molecular changes that occur in both AD and PSP and explore these in the context of neuropathological burden, we analyzed RNAseq data from post‐mortem TCx and CER of AD and PSP patients, as well as controls without neurodegenerative disease. Method: For each brain region, we performed differential gene expression analyses between AD and normal controls (ADvC), and between PSP and controls (PSPvC) using two linear regression models independently. The first model adjusted for sex, age, and technical variables, whereas the second model adjusted for cellular composition in addition to the variables included in the first. We performed comparative analysis (Pearson correlation) of the results between disease groups and brain regions. Result: The slope and Pearson correlation between β coefficients of DEGs obtained from PSPvC and those from ADvC were highly significant for both TCx (slope=0.31, R2=0.27, p<1.0E‐10) and CER (slope=0.78, R2=0.69, p<1.0E‐10). The slope and correlation between the β coefficients increased with increasing significance of DEGs, approaching R2=1 for DEGs with q<0.01. These observations held for both models. Comparison of β coefficients between TCx ADvC and CER ADvC, and between TCx PSPvC and CER PSPvC revealed similar trends. Enrichment analysis identified shared pathways implicated in both diseases. Conclusion: There is a striking correlation in the directionality and magnitude of significant gene expression changes in brain transcriptomes between AD and PSP and between the temporal and cerebellar cortices. These findings indicate conservation in transcriptomic alterations due to common proteinopathies or their downstream effects and demonstrate the widespread perturbations of systems in the whole brain in neurodegenerative diseases. This work highlights the presence of transcriptome changes in pathologically "unaffected" brain regions and identifies biological pathways that are ubiquitously altered across brain regions and distinct neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Background: Tau neurofibrillary tangles and senile plaques comprised of insoluble amyloid beta are the major histopathological hallmarks of Alzheimer's disease (AD). More than 85% of autopsy‐confirmed AD cases also exhibit some degree of cerebral amyloid angiopathy (CAA), which is characterized by amyloid beta peptide deposits predominantly in blood vessels in the meningeal and intracerebral blood vessels. Consequently, CAA predisposes individuals with AD to cerebral infarction and hemorrhages, accounting for ∼20% of cases in the elderly, which could lead to faster cognitive decline through neurovascular pathway dysfunction. We sought to identify cellular composition changes and characterize cell type‐specific expression associated with CAA pathology in AD patients. Methods: Using 10x Genomics single nuclei RNA sequencing, we profiled nuclei from frozen post‐mortem temporal cortex tissue of 80 individuals with neuropathologic diagnosis of AD and varying levels of CAA, ranging from zero to severe CAA pathology. Braak and Thal measures were also obtained. Downstream analyses were performed in R using Seurat v3.2.3. Quality control filtering based on percentage of genes mapped to the mitochondrial genome and number of genes and UMIs detected resulted in 135,092 nuclei for analysis. Differential gene expression analyses were performed using R package MAST. Results: We identified 30 clusters which were annotated using established cell type marker genes. There were 3 oligodendrocyte, 14 neuronal (2 excitatory and 3 inhibitory), 5 microglial, 3 endothelial, 4 astrocyte and 1 oligodendrocyte precursor cell cluster. We observed a significant increase in microglial cell proportions with increasing CAA severity, for 3 of the microglial clusters. Conversely, the excitatory neuronal proportion were decreased in individuals with more severe CAA. Further investigation is ongoing to identify the genes underlying the dysregulation of these cell types in CAA. Conclusion: We observed cellular proportion changes for multiple cell types with increasing CAA severity. Additional analyses to determine the effects of CAA independent of AD severity will be performed by adjusting for Braak and Thal measures. Deeper characterization of cell type‐specific expression profiles is expected to provide novel insights into cell‐type specific transcriptome changes associated with vascular risk factors in AD. [ABSTRACT FROM AUTHOR]

Background: Using an objective mathematical algorithm to assess corticolimbic involvement of neurofibrillary tangle pathology, we identified three AD subtypes: hippocampal sparing (HpSp) AD, typical AD, and limbic predominant AD. Typical AD brains were representative of the expected patterns of hippocampal and cortical involvement as outlined by Braak tangle stage. In contrast, we discovered an extreme phenotype that exists outside of the Braakian‐concept of neurofibrillary tangle patterns. Hippocampal sparing AD cases demonstrate unexpected sparing of the hippocampus relative to severely involved association cortices and limbic predominant AD cases demonstrate inundation of the hippocampus relative to mildly involved association cortices. Using these AD subtypes, our objective was to leverage our understanding of disease spectrum to uncover transcriptomic changes that underlie selective vulnerability of the hippocampus in AD. Method: We performed RNA‐sequencing in 40 neuropathologically diagnosed AD cases (10 HpSp, 20 Typical and 10 Limbic) and 15 controls to uncover gene expression changes associated with phenotype differences allowing us to prioritize 44 genes for further exploration. Validation with NanoString and quantification with digital pathology were performed in an expanded cohort of 158 AD cases (36 HpSp, 79 Typical and 35 Limbic) and 32 controls. We quantified digital pathology measures of early tangle pathology (CP13), mature tangle pathology (Ab39), amyloid‐β (33.1.1). In addition, we measured cellular markers for microglia (CD68), endothelia (CD34), and astroglia (GFAP). Deep learning based prediction models were employed, which nominated the SLC38A2 gene as a predictor of AD. Result: The SLC38A2 gene was originally prioritized in our RNA‐sequencing data based upon differential expression between controls and typical AD. We observed upregulation of SLC38A2 in all AD subtypes. RNA‐seq gene expression measures validated well with NanoString for SLC38A2 (R=0.97, p<0.001). Regression analysis identified early tangle (p=0.011) and late tangle measures (p=0.026) as significant predictors of gene expression, but not amyloid measures (p=0.74). Microgliosis approached significance (p=0.052), but with no contribution from endothelial cell burden (p=0.17) or astrogliosis (p=0.58). Age approached significance (p=0.06), but not sex (p=0.88) or APOE‐ε4 status (p=0.10). Conclusion: Our data supports consideration of intra‐disease divergence with regard to case stratification and may reveal genes previously masked by heterogeneity of cohorts. [ABSTRACT FROM AUTHOR]

Background: Progressive Supranuclear Palsy (PSP) is an incurable, neurodegenerative parkinsonian disorder characterized by tau proteinopathy in multiple brain cell types. We previously reported global gene expression changes associated with neuropathologic endophenotypes in PSP. In this study, we expanded this work to brain RNA sequence (RNAseq) transcriptome data from two independent cohorts and assessed both bulk and analytically deconvoluted transcriptome integrated with other omics data from humans and mice to discover dysregulated genes and networks in PSP. Method: Transcriptome was measured in 408 temporal cortex samples from two independent cohorts of PSP and control brains, all of which had quantitative neuropathology scores. Differentially expressed genes (DEG) were identified using both bulk and analytically deconvoluted transcriptome for each brain cell type. Weighted Gene Co‐expression Network Analysis (WGCNA) was used to construct modules, which were annotated for enrichment of Gene Ontology terms and cell type markers. We sought validations using a multitude of complementary datasets, including PSP GWAS, eQTL, proteome data and tau transgenic mouse models. Results: There were 22,560 genes detected in both cohorts of which 1,709 were significantly differentially expressed. Among the DEGs, 721 genes also had nominal associations with one or more neuropathology endophenotypes. Additionally, 104 of the bulk DEGs were also differentially expressed in one of the brain cell types, i.e. were cell‐intrinsic DEGs (CI‐DEGs). There were 23 co‐expression network modules, 10 of which were enriched for brain cell type markers; 8 of these also demonstrated enrichment of CI‐DEGs of the corresponding cell‐type. Importantly, 3 of these 8 modules also associated with PSP diagnosis. The most significant modules were enriched for oligodendrocyte and astrocyte genes and CI‐DEGs. Most notably, we identified one module with enrichment of oligodendrocyte gene markers that are likewise downregulated in PSP. This module was also enriched with myelin gene expression changes identified in oligodendrocyte CI‐DEGs. Conclusion: The expression profile of PSP brain changes in a cell‐specific manner. Astrocyte and oligodendrocyte gene expression appears most impacted in PSP. Our findings implicate novel genes and pathways which underlie disease risk and neuropathology in PSP and may serve as novel therapeutic and biomarker targets. [ABSTRACT FROM AUTHOR]