Malphrus, Kimberly G.

Abstract Identification of gene expression changes in post-mortem brain tissue of Alzheimer’s disease donors compared to controls have implicated numerous biological pathways for Alzheimer’s disease pathophysiology. Nonetheless, there is still limited understanding of how gene expression dysregulation underpins specific proteinopathies core to Alzheimer’s disease. Here we investigate brain transcriptomic changes in a well characterized cohort of Alzheimer’s disease donors to identify genes and networks that associate with Alzheimer’s disease endophenotypes including neuropathology measures (Braak stage, Thal phase and cerebral amyloid angiopathy score) and Alzheimer’s disease-related brain protein levels (Apolipoprotein E, Amyloid-β 40, Amyloid-β 42, tau, and phospho-Tau). Bulk transcriptome measures were collected from the temporal cortex tissue of 477 Alzheimer’s disease donors. Following quality control, transcriptome-wide association studies were performed for each endophenotype. We used weighted gene co-expression network analysis to build co-expression networks and integrated transcriptome with epigenetic and genetic data from the same donors. We detected a total of 5,740 Bonferroni significant temporal cortex gene associations with Alzheimer’s disease endophenotypes, most of which were with brain tau levels. We discovered tau-associated co-expression modules enriched in known and novel Alzheimer’s disease pathways. We found that a beneficial (or neutral) brain biochemical state of higher total tau and lower phospho-Tau are associated with increased levels of synaptic, DNA damage/repair, nucleic acid metabolism and myelin processes. In contrast, in a detrimental state of lower total and higher phospho-Tau, there is upregulation of vascular and immune, and downregulation of mitochondrial and myelin pathways. There are brain gene expression perturbations that are associated with Alzheimer’s disease endophenotypes. While some of these associations are common across multiple endophenotypes, many are distinct for different Alzheimer’s disease-related proteins. Based on these findings, we propose a hypothetical model of dynamic brain gene expression changes that track with progressive Alzheimer’s disease proteostasis. These expression changes hold potential to serve as dynamic, precision biomarkers of brain Alzheimer’s disease progression. This study demonstrates the potential of integrative multiomics and deep Alzheimer’s disease endophenotype analyses in well-characterized brain tissues to uncover with precision the complex biology of Alzheimer’s disease.

Abstract Background African Americans (AA) are twice as likely to develop dementia than non‐Hispanic Whites but remain underrepresented in Alzheimer's Disease (AD) research. Recent studies have identified AA specific risk factors for AD. Therefore, targeted biomarkers and/or therapies may be needed to effectively treat AD in AA. In this study, we aimed to determine if genetic variants that show association with AD‐risk, plasma transcript or protein levels in AA, may serve as accurate and accessible AD biomarkers. Method In 189 clinically diagnosed AA AD cases and 183 AA cognitively unimpaired (CU) controls, we performed targeted DNA sequencing of 10 AD‐associated loci. Genetic variants at these loci were tested for association with corresponding plasma transcripts and total tau protein levels previously measured in this cohort using a custom nanoString panel and Simoa assays, respectively. Utilizing phased haplotypes (SHAPEIT4) from target sequencing, we inferred local ancestry (RFMix v2) using five superpopulations from the 1000 Genomes Project as anchors. Subsequently, we tested the association of each ancestry specific allelic dosages with endophenotypes using Tractor. In receiver operating characteristic (ROC) analyses, the most significant e/pQTLs were added sequentially to a base model that included age and sex to identify e/pQTLs that improved the accuracy to correctly classify AD cases and CU controls. Result Of the 5,112 variants that were tested, 70 were nominally associated with AD‐risk and with plasma transcript or protein levels. Seven of these 70 variants also showed nominally significant associations of AD‐risk and transcript levels with either African or East Asian local ancestry. ROC analysis of age, sex, 33 e/pQTLs in APOE , SORL1 , TLR4 , EPHA1 , ABCA7 , CLU , and CR1 , and plasma levels of APP, ABCA7, AKAP9, CD14, CLU, and APOE ‐ɛ4 dosage achieved 88.2% area under the curve to discriminate AD vs. CU, a 30.4% improvement over the base model that only included age and sex. Conclusion Plasma transcript levels and e/pQTLs are promising diagnostic biomarkers for AD that may improve accessibility and reduce costs for a more accurate diagnosis of AD.

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.

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.