👤 The Alzheimer’s Disease Neuroimaging Initiative (ADNI)

BackgroundIdentifying genetic variants conferring resilience to Alzheimer's disease and related dementia (ADRD) may hold promise for developing therapeutics.ObjectiveTo determine genetic associations with being dementia-free at age 85 (DF85).MethodsWe examined genetic associations, using whole genome sequencing data, with DF85 in three Trans-Omics for Precision Medicine cohorts and the Alzheimer's Disease Sequencing Project Phenotype Harmonization Consortium. We tested common variants individually and aggregation of rare (MAF ≤ 1%) coding and non-coding variants in DF85 participants (n = 3657) against individuals who were not DF85 (n = 20,010). We verified associations using a stricter control set who developed dementia before age 85 (n = 5552).ResultsWe observed an association at Show less

The APOE-ε4 allele is the strongest genetic risk factor for late-onset Alzheimer's disease. However, APOE-ε4 is not deterministic, highlighting the need to identify additional genetic and environmental factors. APOE-ε4 has been linked to accelerated cognitive decline, so we sought to investigate genetic factors that modify APOE-ε4-associated cognitive decline. We conduct cross-ancestry APOE-ε4-stratified and interaction GWAS using harmonized cognitive data from 32,778 participants, including 29,354 non-Hispanic White and 3,424 non-Hispanic Black individuals. Our primary outcome is late-life cognition, measured using harmonized composite scores for memory, executive function, and language, modeled as continuous traits reflecting both normative cognitive aging and disease-related decline. We identify two genome-wide significant loci in APOE-ε4 carriers, reaching genome-wide significance for executive function. These loci also demonstrate nominal associations across the other domains, suggesting broad effects on cognition. In non-carriers, we identify a genome-wide significant association at ITGB8 restricted to executive function, and another locus associated with language. We further link these loci to SEMA6D, GRIN3A, and ITGB8 through expression and methylation databases. Post-GWAS analyses implicate additional genes including SLCO1A2, and DNAH11. Genetic correlation analyses reveal differences by APOE-ε4 status for immune-related traits, suggesting immune-related predispositions may exacerbate cognitive risk in APOE-ε4 carriers. Show less

It is unclear whether the different Alzheimer's disease (AD) progression trajectories of apolipoprotein E (APOE) ɛ4 carriers is reflected by blood phosphorylated tau (p-tau) analytes. We assessed longitudinal trajectories in plasma p-tau181, 217, and 231, in amyloid beta-positive (A+) and negative (A-) APOE ɛ4 carriers (E+) or non-carriers (E-). We included 2039 participants from the observational Translational Biomarkers in Aging and Dementia (TRIAD) and Alzheimer's Disease Neuroimaging Initiative cohorts, categorized into 840 A-E-, 251 A-E+, 386 A+E4-, and 616 A+E4+. Longitudinal data were available for 1045 participants. In TRIAD, ALZpath p-tau217 (β = 0.45, p = 0.02) and p-tau217+ These findings suggest p-tau217 as a marker of faster progression in APOE ɛ4 carriers, highlighting its potential in disease stratification. Blood phosphorylated tau (p-tau)217 increases faster in apolipoprotein E (APOE) ɛ4 carriers with amyloid pathology. p-tau181 and p-tau231 do not increase faster in APOE ɛ4 carriers. APOE ɛ4 carriership does not change p-tau in individuals without amyloid pathology. Show less

The diagnosis of Alzheimer's disease (AD) traditionally relies on cerebrospinal fluid and plasma levels of amyloid beta and phosphorylated tau. Although informative, these biomarkers represent a narrow, hypothesis-driven approach to intercept the disease. Data-driven analysis was applied on demographic data, apolipoprotein E ( Statistical analyses revealed differences among groups in many cholesterol-related analytes. These findings support the hypothesis that systemic alterations also occur during the preclinical stages of dementia, which can be detected by ML models on blood biomarkers. Machine learning on blood tests detects preclinical cognitive decline.Glycolysis metabolites are predictive for distinguishing stable MCI and AD from HC.Amino acids, lipoproteins, and fatty acids are the most predictive features.Inflammatory and metabolic biomarkers represent a biosignature of cognitive health. Show less

Current AT(N) stratification for Alzheimer's disease (AD) accounts for complex combinations of amyloid (A), tau proteinopathy (T) and neurodegeneration (N) signatures. Understanding the transition between these different stages is a major challenge, especially in view of the recent development of disease modifying therapy. This is an observational study, CSF levels of Tau, pTau181, pTau217, Aβ38/40/42, sAPPα/β, BACE1 and neurogranin were measured in the BALTAZAR cohort of cognitively impaired patients and in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Biomarkers levels were related to the AT(N) framework. (A) and (T) were defined in BALTAZAR with CSF Aβ42/40 ratio and pTau217 respectively, and in ADNI with amyloid and tau PET. (N) was defined using total CSF tau in both cohorts. As expected, CSF Aβ42 decreased progressively with the AD continuum going from the A-T-N- to the A + T + N + profile. On the other hand, Tau and pTau181 increased progressively with the disease. The final transition from A + T + N- to A + T + N + led to a sharp increase in Aβ38, Aβ42 and sAPP levels. Synaptic CSF biomarkers BACE1 and neurogranin, were lowest in the initial A + T-N- stage and increased with T + and N + . CSF pTau181 and total tau were closely related in both cohorts. The early transition to an A + phenotype (A + T-N-) primarily impacts synaptic function. The appearance of T + and then N + is associated with a significant and progressive increase in pathological Alzheimer's disease biomarkers. Our main finding is that CSF pTau181 is an indicator of N + rather than T + , and that N + is associated with elevated levels of BACE1 protein and beta-amyloid peptides. This increase may potentially fuel the amyloid cascade in a positive feedback loop. Overall, our data provide further insights into understanding the interconnected pathological processes of amyloid, tau, and neurodegeneration underlying Alzheimer's disease. Show less

White matter (WM) injury is frequently observed along with dementia. Positron emission tomography with amyloid-ligands (Aβ-PET) recently gained interest for detecting WM injury. Yet, little is understood about the origin of the altered Aβ-PET signal in WM regions. Here, we investigated the relative contributions of diffusion MRI-based microstructural alterations, including free water and tissue-specific properties, to Aβ-PET in WM and to cognition. We included a unique cohort of 115 participants covering the spectrum of low-to-severe white matter hyperintensity (WMH) burden and cognitively normal to dementia. We applied a bi-tensor diffusion-MRI model that differentiates between (i) the extracellular WM compartment (represented via free water), and (ii) the fiber-specific compartment (via free water-adjusted fractional anisotropy [FA]). We observed that, in regions of WMH, a decrease in Aβ-PET related most closely to higher free water and higher WMH volume. In contrast, in normal-appearing WM, an increase in Aβ-PET related more closely to higher cortical Aβ (together with lower free water-adjusted FA). In relation to cognitive impairment, we observed a closer relationship with higher free water than with either free water-adjusted FA or WM PET. Our findings support free water and Aβ-PET as markers of WM abnormalities in patients with mixed dementia, and contribute to a better understanding of processes giving rise to the WM PET signal. Show less

Alzheimer's disease (AD) is a genetically complex disease for which nearly 40 loci have now been identified via genome-wide association studies (GWAS). We attempted to identify groups of rare variants (alternate allele frequency <0.01) associated with AD in a region-based, whole-genome sequencing (WGS) association study (rvGWAS) of two independent AD family datasets (NIMH/NIA; 2247 individuals; 605 families). Employing a sliding window approach across the genome, we identified several regions that achieved association p values <10 Show less

The International Genomics of Alzheimer's Project (IGAP) is a consortium for characterizing the genetic landscape of Alzheimer's disease (AD). The identified and/or confirmed 19 single-nucleotide polymorphisms (SNPs) associated with AD are located on non-coding DNA regions, and their functional impacts on AD are as yet poorly understood. We evaluated the roles of the IGAP SNPs by integrating data from many resources, based on whether the IGAP SNP was (1) a proxy for a coding SNP or (2) associated with altered mRNA transcript levels. For (1), we confirmed that 12 AD-associated coding common SNPs and five nonsynonymous rare variants are in linkage disequilibrium with the IGAP SNPs. For (2), the IGAP SNPs in CELF1 and MS4A6A were associated with expression of their neighboring genes, MYBPC3 and MS4A6A, respectively, in blood. The IGAP SNP in DSG2 was an expression quantitative trait loci (eQTL) for DLGAP1 and NETO1 in the human frontal cortex. The IGAP SNPs in ABCA7, CD2AP, and CD33 each acted as eQTL for AD-associated genes in brain. Our approach for identifying proxies and examining eQTL highlighted potentially impactful, novel gene regulatory phenomena pertinent to the AD phenotype. Show less