Genetic and environmental factors that increase the risk of late-onset Alzheimer disease are now well recognized but the cause of variable progression rates and phenotypes of sporadic Alzheimer's disease is largely unknown. We aimed to investigate the relationship between diverse structural assemblies of amyloid-β and rates of clinical decline in Alzheimer's disease. Using novel biophysical methods, we analysed levels, particle size, and conformational characteristics of amyloid-β in the posterior cingulate cortex, hippocampus and cerebellum of 48 cases of Alzheimer's disease with distinctly different disease durations, and correlated the data with APOE gene polymorphism. In both hippocampus and posterior cingulate cortex we identified an extensive array of distinct amyloid-β42 particles that differ in size, display of N-terminal and C-terminal domains, and conformational stability. In contrast, amyloid-β40 present at low levels did not form a major particle with discernible size, and both N-terminal and C- terminal domains were largely exposed. Rapidly progressive Alzheimer's disease that is associated with a low frequency of APOE e4 allele demonstrates considerably expanded conformational heterogeneity of amyloid-β42, with higher levels of distinctly structured amyloid-β42 particles composed of 30-100 monomers, and fewer particles composed of < 30 monomers. The link between rapid clinical decline and levels of amyloid-β42 with distinct structural characteristics suggests that different conformers may play an important role in the pathogenesis of distinct Alzheimer's disease phenotypes. These findings indicate that Alzheimer's disease exhibits a wide spectrum of amyloid-β42 structural states and imply the existence of prion-like conformational strains.
We performed a Phenome-wide association study (PheWAS) utilizing diverse genotypic and phenotypic data existing across multiple populations in the National Health and Nutrition Examination Surveys (NHANES), conducted by the Centers for Disease Control and Prevention (CDC), and accessed by the Epidemiological Architecture for Genes Linked to Environment (EAGLE) study. We calculated comprehensive tests of association in Genetic NHANES using 80 SNPs and 1,008 phenotypes (grouped into 184 phenotype classes), stratified by race-ethnicity. Genetic NHANES includes three surveys (NHANES III, 1999–2000, and 2001–2002) and three race-ethnicities: non-Hispanic whites (n = 6,634), non-Hispanic blacks (n = 3,458), and Mexican Americans (n = 3,950). We identified 69 PheWAS associations replicating across surveys for the same SNP, phenotype-class, direction of effect, and race-ethnicity at p<0.01, allele frequency >0.01, and sample size >200. Of these 69 PheWAS associations, 39 replicated previously reported SNP-phenotype associations, 9 were related to previously reported associations, and 21 were novel associations. Fourteen results had the same direction of effect across more than one race-ethnicity: one result was novel, 11 replicated previously reported associations, and two were related to previously reported results. Thirteen SNPs showed evidence of pleiotropy. We further explored results with gene-based biological networks, contrasting the direction of effect for pleiotropic associations across phenotypes. One PheWAS result was ABCG2 missense SNP rs2231142, associated with uric acid levels in both non-Hispanic whites and Mexican Americans, protoporphyrin levels in non-Hispanic whites and Mexican Americans, and blood pressure levels in Mexican Americans. Another example was SNP rs1800588 near LIPC, significantly associated with the novel phenotypes of folate levels (Mexican Americans), vitamin E levels (non-Hispanic whites) and triglyceride levels (non-Hispanic whites), and replication for cholesterol levels. The results of this PheWAS show the utility of this approach for exposing more of the complex genetic architecture underlying multiple traits, through generating novel hypotheses for future research.
Controversy remains as to which gene at the chromosome 10q26 locus confers risk for age-related macular degeneration (AMD) and statistical genetic analysis is confounded by the strong linkage disequilibrium (LD) across the region. Functional analysis of related genetic variations could solve this puzzle. Recently Fritsche et al. reported that AMD is associated with unstable ARMS2 transcripts possibly caused by a complex insertion/deletion (indel; consisting of a 443 bp deletion and an adjacent 54 bp insertion) in its 3′UTR (untranslated region). To validate this indel, we sequenced our samples. We found that this indel is even more complex and is composed of two side-by-side indels separated by 17 bp: (1) 9 bp deletion with 10bp insertion; (2) 417 bp deletion with 27 bp insertion. The indel is significantly associated with the risk of AMD, but is also in strong LD with the non-synonymous single nucleotide polymorphism (SNP) rs10490924 (A69S). We also found that ARMS2 is expressed not only in placenta and retina but also in multiple human tissues. Using quantitative PCR, we found no correlation between the indel and ARMS2 mRNA level in human retina and blood samples. The lack of functional effects of the 3′UTR indel, the amino acid substitution of rs10490924 (A69S) and strong LD between them suggest that A69S, not the indel is the variant that confers risk of AMD. To our knowledge, it is the first time it's been shown that ARMS2 is widely expressed in human tissues. Conclusively, the indel at 3′UTR of ARMS2 actually contains two side-by-side indels. The indels are associated with risk of AMD, but not correlated with ARMS2 mRNA level.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.