Search

Background: The risk for late‐onset Alzheimer disease (AD) in APOEε4 carriers differs between ancestral groups, where APOEε4's odds ratio for AD risk is lower in African (AFR) homozygous carriers than in non‐Hispanic White (NHW) or Japanese (JPT) carriers (odds ratio ∼2‐5 vs >15). Local ancestry (LA) analyses in APOEε4 carrier populations have shown the protective effect in AFR relative to EUR/JPT is due to noncoding factors lying in the LA surrounding APOEε4. Thus, regulatory differences between risk and protective LA haplotypes are most likely involved in the differential risk effect seen for APOEε4 on different backgrounds. Methods: We identified 56 significant sequence differences between AFR and EUR/JPT APOEε4 haplotypes from the 1000 genomes in the immediate topologically associated domain surrounding APOE. We performed two different Massively Parallel Reporter Assay (MPRA) designs; one assessing small haplotype (∼900bp) effects and one based upon single variant effects. We supplemented these results with single fragment luciferase reporter assays. All assays were performed in at least duplicate in HMC3 (microglia), U118 (astrocytes) and SH‐SY5Y (neurons) cell lines. Additionally, we integrated chromatin interaction information from promoter capture C chromatin conformation assays in the same cell types. Results: We identified a region in the first introns of TOMM40 with increased EUR/JPT enhancer activity, supported by both MPRA analyses and APOE promoter interaction in astrocytes and microglia. Two additional regions with differential enhancer activity in neurons, but no promoter interaction, were identified; downstream of APOE and in PVRL2 introns upstream of APOE presenting with higher EUR or higher JPT haplotype variant enhancer activity compared to AFR, respectively. Conclusions: Our results indicate several areas of differential regulation in this LA region on APOEε4 haplotypes dependent on cell type. As APOE is mostly expressed in glial cells, the data in TOMM40 introns points to this region as having the biggest impact on APOE expression in our study and thus highly supports the involvement of this region in the differential risk effects seen for APOEε4. Follow‐up of the identified regulatory regions is currently ongoing using in‐house iPSC derived cell lines. [ABSTRACT FROM AUTHOR]

Background: To identify LOAD risk genes in Puerto Ricans (PR), a population underrepresented in genetic studies, linkage analysis of whole genome sequencing (WGS) in 23 multiplex PR families identified a peak on chromosome 9p21 (MLOD = 3.9). The 1‐LOD unit down region spans from 31∼38Mb; identity‐by‐descent (IBD) sharing region spans from 23‐39 Mb. Two genes in the linkage region, UNC13B, located in the center of the linkage peak (35.1∼35.4 Mb), and ELAVL2 (23.7∼23.8 Mb), at the edge of the IBD sharing region, are of interest. Both genes have multiple rare variants with low minor allele frequencies (MAF) and high CADD scores that segregate with LOAD in the families. UNC13B encodes a protein involved in Ca2+ release at the synapse, and calcium dysfunction has been associated with LOAD. ELAVL2 encodes a neural‐specific protein involved in RNA processing. Method: Recombinant plasmids for testing overexpression (UNC13B) and promoter activity (ELAVL2) were made by site‐directed mutagenesis and transfected into the neuronal SH‐SY5Y. Result: Two UNC13B missense variants, rs35199210 (Asp238Glu, CADD = 22, MAF = 0.5%) or rs41276043 (Phe1096Leu, CADD = 26.5, MAF = 0.5%) have been cloned into overexpression vectors and are currently being evaluated for their effect on Ca2+ release rates. One promoter variant rs542037226 (CADD = 16.6, MAF = 0.03%) in the ELAVL2 demonstrated strong activity (∼200x higher than the empty vector), and the rare allele showed reduced activity compared to the reference allele (10% reduction, p = 0.03). Conclusion: Two potential new LOAD genes with rare variants have been identified within the linkage 9p21 linkage peak. Using segregation and in‐silico analysis we have prioritized rare variants in each gene for testing. Successful demonstration of functional changes in the ELAVL2 variants provide support for this approach. Evaluation of UNC13B variants are underway. Those variants with functional effects will be further evaluated in our inducible pluripotent stem cell models. [ABSTRACT FROM AUTHOR]

Background: The risk for late‐onset Alzheimer disease (AD) in ApoEε4 carriers differs between ancestral groups. ApoEε4 Non‐Hispanic White (NHW) homozygotes have an odds ratio of 14.9 while the risk is much lower in Africans (AF) (OR 2.2‐5.7). Local ancestry (LA) analyses in ApoEε4 carrier populations have shown the protective effect in Africans relative to NHW is due to factors lying in the LA surrounding ApoEε4. No coding differences between genes in the LA have been observed between AF and NHW ancestries. Thus regulatory differences in LA non‐coding regions are most likely involved in the protective factor(s) lowering the risk for AF carriers of ApoEε4. Enhancers are the most common regulatory element, and thus we sought to identify if any of these variants had functional enhancer effects between the two ancestries. Little functional characterization of genetic regulation in AF ancestries has been investigated. Method: We identified 56 significant sequence differences among AF and ApoEε4 haplotypes from the 1000 genomes in a topologically associated area (56kb) surrounding ApoE. None of these differences were identified to be protein coding. We applied Massively Parallel Reporter Assay (MPRA) supplemented with single variant reporter assays using Promega Dual Glo‐Luciferase System in AD relevant cell lines to identify the regulatory potential of these variants and their surrounding regions and to assess the differential effect sizes of the variant alleles on enhancer activity. Result: For MPRA and complementary single variants reporter assays, we generated ∼900bp PCR fragments surrounding these variants to ensure full representation of potential regulatory elements. MPRA vector library or single reporter vectors were transfected in three cell lines (SHY‐SY5Y neuronal cells, U‐118 astrocytes and HMC3 microglia). We identified evidence for differential regulation between AF and EU variant haplotypes in intron 5 of PVRL2, TOMM40 intronic regions and a large region located 3' of APOC1. The latter encompasses a putative enhancer identified through ENCODE analyses in brains with NHW ancestry. Conclusion: Our results indicate several areas of differential regulation in this LA region on ApoEε4 haplotypes. Follow‐up of the identified regulatory regions is currently ongoing using publicly available data and in‐house iPSC derived cell lines. [ABSTRACT FROM AUTHOR]

Background: Genetic risk factors for Alzheimer disease (AD) demonstrate distinct effects across diverse ancestral populations. The ancestral heterogeneity (admixture) of Caribbean Hispanics from Puerto Rico (PR), makes studies of the PR population important in the discovery of ancestry‐specific factors in AD. To expand ongoing genomic investigations of AD in PR individuals, it is necessary to characterize functional downstream effects by studying gene expression and regulation. Here we characterized the differences in gene expression, splicing, and RNA editing of the protein coding transcriptome from peripheral blood in PR individuals. to identify case vs control differential expression, splicing, and RNA editing in this diverse population. Method: Poly‐A selected RNA was from peripheral whole blood of 76 PR individuals over the age of 65 (39 AD, 37 cognitively normal controls) was sequenced and analyzed with a standard bioinformatics pipeline. Differential expression between PR cases and controls was calculated using DESeq2, alternative splicing using LeafCutter software, and RNA editing with REDITools and linear models. All analyses were adjusted for sex, age, and sequencing coverage. For each analysis, pathway enrichment analysis of Gene Ontology Biological Processes and KEGG gene sets were used to identify underlying biological pathways. Result: A total of 761 genes (518 up‐regulated, 243 down‐regulated) were differentially expressed between PR AD and controls (adjusted p ≤ 0.05). At the transcript level, 561 genes had a significant (FDR ≤ 0.05) differential splicing event. We also identified 35,246 total RNA editing sites. While there was no significant difference globally, 422 sites in 159 genes showed nominally significant editing difference (p ≤ 0.05). These genes, isoforms, and RNA editing sites overlap little with previous investigations of the transcriptomes of Non‐Hispanic Whites and African‐American AD with only a few genes in common. However, pathway enrichment across all three PR transcriptomic analyses consistently reveals differences in both the adaptive and innate immune response pathways, consistent with other ancestries. Conclusion: Transcriptomic analyses of diverse populations in AD, shows stark divergence at the single gene level. However, the convergence on immune molecular pathways suggest shared underlying disease etiology and the possibility of broad therapeutic options. [ABSTRACT FROM AUTHOR]

Background: Understanding the effects of genetic factors that drive Alzheimer's Disease (AD) pathogenesis, including genetic differences across diverse ancestral populations, will drive discovery of novel pharmacological targets. Weighted gene co‐expression network analysis (WGCNA) is a powerful method for finding gene clusters (modules) with correlated expression, relating these modules to phenotypes, and thus identifying key upstream regulatory elements. To study networks of transcriptional dysregulation in AD across ancestries, we performed WGCNA in African‐American (AA), Non‐Hispanic White (NHW), and Puerto Rican (PR) populations. Method: RNA sequencing was performed on peripheral blood specimens from 275 AD cases (115 AA, 121 NHW, 39 PR) and 276 age and sex matched controls (119 AA, 120 NHW, 37 PR), all over age 65. We performed WGCNA and calculated the correlation between each co‐expression module and AD affection status within each ancestry group, adjusting for sex, age, and sequencing batch. Ingenuity Pathway Analysis (IPA) was used to identify enriched pathways and upstream regulators. Result: We identified 13 co‐expression modules that were significantly associated with AD. Across all ancestries, modules were enriched for pathways related to endocytosis and inflammation. These modules largely differed between African and European ancestry, though there was some overlap in the admixed PR population. Only one module had significantly decreased expression in cases across all three ancestries. It was enriched for immune signaling pathways and showed especially strong enrichment (p = 1.09*10−19) for upstream regulation by granulocyte‐colony stimulating factor (G‐CSF). G‐CSF activates JAK2 and STAT1, which were central hub genes within this module, as were AD‐associated genes CR1 and TLR4. G‐CSF acts as a cytokine, hormone, and neurotrophic factor. In AD mouse models, G‐CSF decreases brain amyloid burden and reverses cognitive impairment. A recombinant form of G‐CSF is approved for use in neutropenia and has completed Phase II clinical trials for the treatment of AD (NCT01617577, NCT03656042). A current Phase II trial for the closely related GM‐CSF is ongoing (NCT01409915). Conclusion: Through analyses of multiple populations, we have identified AD‐associated gene expression networks. Though these networks largely differ by ancestral background, convergence on pathways relevant to AD pathology suggest that shared underlying disease etiology can be targeted pharmacologically. [ABSTRACT FROM AUTHOR]

Background: The ApoEε4 allele is a major risk factor for AD whose effect shows strong racial/ethnic differences. Among the populations ApoE shows the strongest effect in East Asians (EA) (ε3/ε4 odds ratio OR: 3.1–5.6; ε4/ε4 OR: 11.8–33.1) and has a relatively lower effect in non‐Hispanic Whites (NHW) (ε3/ε4 OR: 3.2; ε4/ε4 OR: 14.9). The effect of ApoEε4 in populations with Amerindian (AI) ancestry is unknown. Peruvians with high AI (∼80%) genetic ancestry provide an opportunity to assess the effect of ApoEε4 in AD individuals with AI genetic ancestry. Our aim is to use data from the Peruvian population to assess the role of AI genetic ancestry and the ApoE gene on AD. Method: Genotyping including both ApoE and Illumina GSA array was performed in 147 Peruvians (54 AD cases and 93 cognitively intact (CI) controls). PC‐AiR and model‐based ADMIXTURE approach inferred population structure. To assess local ancestry, phasing using SHAPEIT (with 1kGP reference) was followed by RFMix (HGDP reference panels). Association between affection status and ApoEε4 dose was analyzed using logistic regression, adjusting for age, gender, PC1‐3. Result: Admixture analysis showed that Peruvians have a substantial AI (62%) ancestral component (31% European, 4% African and 3% EA genetic ancestry). AD individuals have higher frequency of ApoEε4 allele than CI individuals (7.4% vs 3.7%, respectively, p‐value = 3e‐4). Logistic regression analysis showed ApoEε4 dose significantly associated with AD in Peruvians (OR = 4.92, CI: 2.07‐12.83, p = 6e‐4). The average of the local ancestry proportions around the ApoE were close to the average global ancestry proportions (AI:56%, EU:37% and AF:7%). Conclusion: Our results showed that the risk for AD from ApoEε4 in Peruvians is higher than we have observed in NHW populations. Given the high admixture of AI in the Peruvian population, it suggests that the AI local ancestry is contributing to a strong risk for AD in ApoEε4 carriers. This would align with the current believed migration pattern of AI from East Asia, where ApoEε4 carriers have the highest ApoEε4 risk for AD. Further ascertainment is ongoing to identify additional AI ApoEε4 carriers to directly ascertain risk. [ABSTRACT FROM AUTHOR]