Citations

AbstractBackgroundA 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.MethodWe 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).ResultWGCNA 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.ConclusionWe 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.

AbstractBackgroundGiven 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.MethodsIn 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.ResultsOf 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.ConclusionsPlasma 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.

AbstractBackgroundInter‐cellular communication within the gliovascular unit (GVU) is critical for cerebral blood flow regulation, and maintenance of the blood‐brain‐barrier (BBB) properties. The breakdown of BBB in Alzheimer’s disease (AD) is well‐established, but precise underlying molecular changes remain unclear. Additionally, whether GVU molecular alterations observed in AD brains are also detected in blood from living patients is unknown. Further, these GVU molecular perturbations require further investigation in different model systems to identify both human brain‐specific and cross‐species conserved alterations. In this study, we investigated prioritized GVU molecules altered in AD brains for their conservation in blood and cross‐species model systems.MethodsWe performed single nucleus RNA sequencing (snRNAseq) of temporal cortex tissue in AD and control brains. We analyzed this data to detect cell‐specific GVU molecular perturbations and their interactions. We investigated molecular interactions between vascular and astrocyte clusters, the major cell types of the GVU of the BBB. To determine whether GVU transcriptional alterations detected in the brain are preserved in the blood, existing blood expression, genetic, and neuroimaging data from two longitudinal antemortem cohorts were analyzed. Using model systems, including mouse, drosophila, and zebrafish, we evaluated the cross‐species conservation of the top GVU alterations detected in AD brains.ResultsBrain snRNAseq revealed transcriptional profiles of 6,541 astrocytes and 2,210 vascular cells. The latter formed three distinct vascular clusters characterized as pericytes, endothelia and perivascular fibroblasts. We identified differentially expressed genes and their enriched pathways within these clusters and observed the highest levels of transcriptional changes within pericytes. Vascular targets that interact with astrocytic ligands have biological functions in cell signaling, angiogenesis, amyloid ß metabolism, and cytoskeletal architecture. We discovered that genetic variants influencing blood expression levels of some of the prioritized GVU genes were associated with neuroimaging burden of cerebrovascular disease in living human cohorts. Our ongoing studies in model systems revealed conservation of some of the top prioritized molecular perturbations across species.ConclusionOur findings prioritized by multiscale, cross‐tissue human data revealed GVU perturbations within interacting pericyte and astrocyte molecules, which are conserved across multiple cross‐species models. These results nominate new molecular targets and mechanistic insights for BBB disruptions in AD.

AbstractBackgroundCerebral 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).MethodWe 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.ResultWe 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.ConclusionWe 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.

AbstractBackgroundAlzheimer’s disease (AD) is a complex, multicellular disease with immunological and genetic components. Previous studies demonstrated associations between AD and the missense variants ABI3‐rs616338‐T and PLCG2‐rs72824905‐G. The perturbed expression of these genes has been demonstrated to disrupt microglial function. To date, the transcriptomic profiles of variant carriers in the context of microglial subtype and state have not been explored in human brain. This represents a knowledge gap in our understanding of AD risk and resilience. We have developed and optimized a single nucleus RNAseq (snRNAseq) approach to study the impact of ABI3 and PLCG2 variants on microglial enriched nuclei from frozen human brain.MethodDOCK8 was identified as a nuclear microglial marker based on previous brain snRNAseq data. DOCK8 based microglial enrichment using fluorescent activated nuclei sorting (FANS) was validated using RT‐qPCR and snRNAseq in human cerebellum and temporal cortex (TCX), respectively. We are applying this enrichment and snRNAseq approach to TCX tissue from a cohort of 30 donors harboring ABI3 or PLCG2 missense mutations, or neither. Standard snRNAseq alignment and quality control pipelines will be applied, and nuclei annotated based on putative microglial markers. Differential gene expression will be assessed using pseudo bulk and MAST approaches, for association with ABI3 and PLCG2 genotype, diagnosis groups, risk factors, and pathology scores.ResultDOCK8 has several commercially available antibodies, making it an ideal microglia‐selection marker. Using RT‐qPCR in microglia enriched nuclei, we demonstrated an enrichment of microglia marker genes and depletion of other brain cell type markers. This is further supported by snRNA‐seq data from DOCK8‐sorted TCX tissue that yielded a 5x increase in microglia proportion (56% vs. 11% in unselected nuclei), enabling analyses of microglia sub‐populations. Leveraging this approach, we will investigate affected genes and pathways and uncover the resilience and risk mechanisms within microglia sub‐populations in ABI3 and PLCG2 variant‐carriers.ConclusionOur study presents a novel method for enriching microglial nuclei from frozen human brains and enables transcriptomic profiling of microglial subpopulations in ABI3 and PLCG2 missense variant‐carriers. We expect these insights will reveal novel genes and pathways that may play a key role in microglial function in AD.

AbstractBackgroundAlzheimer’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).MethodsDNAm 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.ResultsOur 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.ConclusionsAlthough 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.