Carrasquillo, Minerva M.

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.

AbstractIntron 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.

AbstractBackgroundUsing 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.MethodWe 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.ResultThe 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).ConclusionOur data supports consideration of intra‐disease divergence with regard to case stratification and may reveal genes previously masked by heterogeneity of cohorts.

Background/Objective: The aim of this study was to determine if plasma concentrations of 5 surrogate markers of Alzheimer’s disease (AD) pathology and neuroinflammation are associated with disease status in African Americans. Methods: We evaluated 321 African Americans (159 AD, 162 controls) from the Florida Consortium for African-American Alzheimer’s Disease Studies (FCA3DS). Five plasma proteins reflecting AD neuropathology or inflammation (Aβ42, tau, IL6, IL10, TNFα) were tested for associations with AD, age, sex, APOE and MAPT genotypes, and for pairwise correlations. Results: Plasma tau levels were higher in AD when adjusted for biological and technical covariates. APOE ɛ4 was associated with lower plasma Aβ42 and tau levels. Older age was associated with higher plasma Aβ42, tau, and TNFα. Females had lower IL10 levels. Inflammatory proteins had strong pairwise correlations amongst themselves and with Aβ42. Conclusion: We identified effects of demographic and genetic variants on five potential plasma biomarkers in African Americans. Plasma inflammatory biomarkers and Aβ42 may reflect correlated pathologies and elevated plasma tau may be a biomarker of AD in this population.

AbstractIntroductionCerebrovascular pathologies including cerebral amyloid angiopathy (CAA) and blood‐brain barrier (BBB) dysregulation are prominent features in the majority of Alzheimer's disease (AD) cases.MethodsWe performed neuropathologic and biochemical studies on a large, neuropathologically confirmed human AD cohort (N = 469). Amounts of endothelial tight junction proteins claudin‐5 (CLDN5) and occludin (OCLN), and major AD‐related molecules (amyloid beta [Aβ40], Aβ42, tau, p‐tau, and apolipoprotein E) in the temporal cortex were assessed by ELISA.ResultsHigher levels of soluble tau, insoluble p‐tau, and apolipoprotein E (apoE) were independently correlated with lower levels of endothelial tight junction proteins CLDN5 and OCLN in AD brains. Although high Aβ40 levels, APOE ε4, and male sex were predominantly associated with exacerbated CAA severity, those factors did not influence tight junction protein levels.DiscussionRefining the molecular mechanisms connecting tau, Aβ, and apoE with cerebrovascular pathologies is critical for greater understanding of AD pathogenesis and establishing effective therapeutic interventions for the disease.

Abstract Background: Genetic studies have shifted to sequencing-based rare variants discovery after decades of success in identifying common disease variants by Genome-Wide Association Studies using Single Nucleotide Polymorphism chips. Sequencing-based studies require large sample sizes for statistical power but often inadvertently introduce batch effects because samples are typically collected, processed, and sequenced at multiple centers. Conventionally, batch effects are first detected and visualized using Principal Components Analysis and then controlled by including batch covariates in the disease association models. For sequencing-based genetic studies, because all variants included in the association analyses have passed quality control measures, this conventional approach treats every variant as equal and ignores the substantial differences still remaining in variant qualities and characteristics such as genotype quality scores, alternative allele fractions (fraction of reads supporting alternative allele at a variant position) and sequencing depths. Results: In the Alzheimer’s Disease Sequencing Project (ADSP) exome dataset of 9,904 cases and controls, we discovered hidden variant-level differences between sample batches of three sequencing centers and two exome capture kits. Although sequencing centers were included as a covariate in our association models, we observed differences at the variant level in genotype quality and alternative allele fraction between samples processed by different exome capture kits that significantly impacted both the confidence of variant detection and the identification of disease-associated variants. Furthermore, we found that the association signals of a subset of top disease risk variants came exclusively from samples processed by one exome capture kit that was more effective at capturing the alternative alleles compared to the other kit. Conclusions: Our findings highlight the importance of additional variant-level quality control for large sequencing-based genetic studies. More importantly, we demonstrate that automatically filtering out variants with batch differences may lead to false negatives if the batch discordance came largely from quality differences and if the variants from one batch had better quality scores.

AbstractIntroductionMAPT H1 haplotype is implicated as a risk factor for neurodegenerative diseases including Alzheimer's disease (AD).MethodsUsing 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.ResultsWe 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.DiscussionThis 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.