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Objective: Hippocampal sclerosis of aging (HS-Aging) is a common cause of dementia in older adults. We tested the variability in cerebrospinal fluid (CSF) proteins associated with previously identified HS-Aging risk single nucleotide polymorphisms (SNPs)., Methods: Alzheimer's Disease Neuroimaging Initiative cohort (ADNI; n=237) data, combining both multiplexed proteomics CSF and genotype data, were used to assess the association between CSF analytes and risk SNPs in four genes (SNPs): GRN (rs5848), TMEM106B (rs1990622), ABCC9 (rs704180), and KCNMB2 (rs9637454). For controls, non-HS-Aging SNPs in APOE (rs429358/rs7412) and MAPT (rs8070723) were also analyzed against Aβ1-42 and total tau CSF analytes., Results: The GRN risk SNP (rs5848) status correlated with variation in CSF proteins, with the risk allele (T) associated with increased levels of AXL Receptor Tyrosine Kinase (AXL), TNF-Related Apoptosis-Inducing Ligand Receptor 3 (TRAIL-R3), Vascular Cell Adhesion Molecule-1 (VCAM-1) and clusterin (CLU) (all p<0.05 after Bonferroni correction). The TRAIL-R3 correlation was significant in meta-analysis with an additional dataset (p=5.05×10 -5 ). Further, the rs5848 SNP status was associated with increased CSF tau protein - a marker of neurodegeneration (p=0.015). These data are remarkable since this GRN SNP has been found to be a risk factor for multiple types of dementia-related brain pathologies., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Alzheimer's disease (AD) is a neurodegenerative disorder lacking early biochemical diagnosis and treatment. Lipids have been implicated in neurodegenerative disorders including AD. A shotgun lipidomic approach was undertaken to determine if lipid biomarkers exist that can discriminate AD cases from controls. The discovery study involved sera from 29 different stage AD cases and 32 controls. Lipid extraction was performed using organic solvent and the samples were directly infused into a time-of-flight mass spectrometer. Differences between AD cases and controls were detected with 87 statistically significant lipid candidate markers found. These potential lipid markers were reevaluated in a second confirmatory study involving 27 cases and 30 controls. Of the 87 candidates from the first study, 35 continued to be statistically significant in the second confirmatory set. Tandem MS studies were performed and almost all confirmed markers were characterized and classified. Using a Bayesian lasso probit regression model on the confirmed markers, a multi-marker set with AUC = 0.886 was developed comparing all stages of AD with controls. Additionally, using confirmed biomarkers, multi-marker sets with AUCs >0.90 were developed for each specific AD Clinical Dementia Rating versus controls, including the earliest stage of AD. More conservative and likely more realistic statistical analyses still found multi-marker sets that appeared useful in diagnosing AD. Finally, using ordinal modeling a set of markers was developed that staged AD accurately 70% of the time, p = 0.0079. These results suggest that these serum lipidomic biomarkers may help diagnose and perhaps even stage AD.

Background: Alzheimer's disease (AD) remains challenging to diagnose, especially early disease. Having serum AD biomarkers would be of significant interest both in the clinical setting and in drug development efforts., Objective: We applied a novel serum proteomic approach to interrogate the low-molecular weight proteome for serum AD biomarkers., Methods: A discovery study used sera from 58 any-stage AD cases and 55 matched controls analyzed by capillary liquid chromatography-electrospray ionization-tandem mass spectrometry. Candidate biomarkers were statistically modeled and promising biomarkers were retested in a second, blinded confirmatory study (AD cases = 68, controls = 57). Biomarkers that replicated in the second study were modeled for the diagnosis of any-stage and very early stage AD. Further, they were chemically identified by tandem MS., Results: The initial discovery study found 59 novel potential AD biomarkers. Thirteen recurred in more than one multi-marker panel. In a second, blinded, confirmatory study, these same biomarkers were retested in separate specimens. In that study, four markers validated comparing controls to patients with any-stage AD and also with very early AD. The four biomarkers with replicable ability to diagnose AD were then chemically identified., Conclusion: These results suggest novel serum AD diagnostic biomarkers can be found using this approach.

Introduction: Genetic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) have been crucial in advancing the understanding of Alzheimer's disease (AD) pathophysiology. Here, we provide an update on sample collection, scientific progress and opportunities, conceptual issues, and future plans., Methods: Lymphoblastoid cell lines and DNA and RNA samples from blood have been collected and banked, and data and biosamples have been widely disseminated. To date, APOE genotyping, genome-wide association study (GWAS), and whole exome and whole genome sequencing data have been obtained and disseminated., Results: ADNI genetic data have been downloaded thousands of times, and >300 publications have resulted, including reports of large-scale GWAS by consortia to which ADNI contributed. Many of the first applications of quantitative endophenotype association studies used ADNI data, including some of the earliest GWAS and pathway-based studies of biospecimen and imaging biomarkers, as well as memory and other clinical/cognitive variables. Other contributions include some of the first whole exome and whole genome sequencing data sets and reports in healthy controls, mild cognitive impairment, and AD., Discussion: Numerous genetic susceptibility and protective markers for AD and disease biomarkers have been identified and replicated using ADNI data and have heavily implicated immune, mitochondrial, cell cycle/fate, and other biological processes. Early sequencing studies suggest that rare and structural variants are likely to account for significant additional phenotypic variation. Longitudinal analyses of transcriptomic, proteomic, metabolomic, and epigenomic changes will also further elucidate dynamic processes underlying preclinical and prodromal stages of disease. Integration of this unique collection of multiomics data within a systems biology framework will help to separate truly informative markers of early disease mechanisms and potential novel therapeutic targets from the vast background of less relevant biological processes. Fortunately, a broad swath of the scientific community has accepted this grand challenge., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Alzheimer disease (AD) is a progressive disorder that affects cognitive function. There is increasing support for the role of neuroinflammation and aberrant immune regulation in the pathophysiology of AD. The immunoregulatory human leukocyte antigen (HLA) complex has been linked to susceptibility for a number of neurodegenerative diseases, including AD; however, studies to date have failed to consistently identify a risk HLA haplotype for AD. Contributing to this difficulty are the complex genetic organization of the HLA region, differences in sequencing and allelic imputation methods, and diversity across ethnic populations.Methods and Findings: Building on prior work linking the HLA to AD, we used a robust imputation method on two separate case-control cohorts to examine the relationship between HLA haplotypes and AD risk in 309 individuals (191 AD, 118 cognitively normal [CN] controls) from the San Francisco-based University of California, San Francisco (UCSF) Memory and Aging Center (collected between 1999-2015) and 11,381 individuals (5,728 AD, 5,653 CN controls) from the Alzheimer's Disease Genetics Consortium (ADGC), a National Institute on Aging (NIA)-funded national data repository (reflecting samples collected between 1984-2012). We also examined cerebrospinal fluid (CSF) biomarker measures for patients seen between 2005-2007 and longitudinal cognitive data from the Alzheimer's Disease Neuroimaging Initiative (n = 346, mean follow-up 3.15 ± 2.04 y in AD individuals) to assess the clinical relevance of identified risk haplotypes. The strongest association with AD risk occurred with major histocompatibility complex (MHC) haplotype A*03:01~B*07:02~DRB1*15:01~DQA1*01:02~DQB1*06:02 (p = 9.6 x 10-4, odds ratio [OR] [95% confidence interval] = 1.21 [1.08-1.37]) in the combined UCSF + ADGC cohort. Secondary analysis suggested that this effect may be driven primarily by individuals who are negative for the established AD genetic risk factor, apolipoprotein E (APOE) ɛ4. Separate analyses of class I and II haplotypes further supported the role of class I haplotype A*03:01~B*07:02 (p = 0.03, OR = 1.11 [1.01-1.23]) and class II haplotype DRB1*15:01- DQA1*01:02- DQB1*06:02 (DR15) (p = 0.03, OR = 1.08 [1.01-1.15]) as risk factors for AD. We followed up these findings in the clinical dataset representing the spectrum of cognitively normal controls, individuals with mild cognitive impairment, and individuals with AD to assess their relevance to disease. Carrying A*03:01~B*07:02 was associated with higher CSF amyloid levels (p = 0.03, β ± standard error = 47.19 ± 21.78). We also found a dose-dependent association between the DR15 haplotype and greater rates of cognitive decline (greater impairment on the 11-item Alzheimer's Disease Assessment Scale cognitive subscale [ADAS11] over time [p = 0.03, β ± standard error = 0.7 ± 0.3]; worse forgetting score on the Rey Auditory Verbal Learning Test (RAVLT) over time [p = 0.02, β ± standard error = -0.2 ± 0.06]). In a subset of the same cohort, dose of DR15 was also associated with higher baseline levels of chemokine CC-4, a biomarker of inflammation (p = 0.005, β ± standard error = 0.08 ± 0.03). The main study limitations are that the results represent only individuals of European-ancestry and clinically diagnosed individuals, and that our study used imputed genotypes for a subset of HLA genes.Conclusions: We provide evidence that variation in the HLA locus-including risk haplotype DR15-contributes to AD risk. DR15 has also been associated with multiple sclerosis, and its component alleles have been implicated in Parkinson disease and narcolepsy. Our findings thus raise the possibility that DR15-associated mechanisms may contribute to pan-neuronal disease vulnerability. [ABSTRACT FROM AUTHOR]

Various studies have suggested that the mitochondrial genome plays a role in late-onset Alzheimer’s disease, although results are mixed. We used an endophenotype-based approach to further characterize mitochondrial genetic variation and its relationship to risk markers for Alzheimer’s disease. We analyzed longitudinal data from non-demented, mild cognitive impairment, and late-onset Alzheimer’s disease participants in the Alzheimer’s Disease Neuroimaging Initiative with genetic, brain imaging, and behavioral data. We assessed the relationship of structural MRI and cognitive biomarkers with mitochondrial genome variation using TreeScanning, a haplotype-based approach that concentrates statistical power by analyzing evolutionarily meaningful groups (or clades) of haplotypes together for association with a phenotype. Four clades were associated with three different endophenotypes: whole brain volume, percent change in temporal pole thickness, and left hippocampal atrophy over two years. This is the first study of its kind to identify mitochondrial variation associated with brain imaging endophenotypes of Alzheimer’s disease. Our results provide additional evidence that the mitochondrial genome plays a role in risk for Alzheimer’s disease. [ABSTRACT FROM AUTHOR]

Recent genome-wide association studies of Alzheimer's disease (AD) have identified variants in BIN1, CLU, CR1 and PICALM that show replicable association with risk for disease. We have thoroughly sampled common variation in these genes, genotyping 355 variants in over 600 individuals for whom measurements of two AD biomarkers, cerebrospinal fluid (CSF) 42 amino acid amyloid beta fragments (Aβ42) and tau phosphorylated at threonine 181 (ptau181), have been obtained. Association analyses were performed to determine whether variants in BIN1, CLU, CR1 or PICALM are associated with changes in the CSF levels of these biomarkers. Despite adequate power to detect effects as small as a 1.05 fold difference, we have failed to detect evidence for association between SNPs in these genes and CSF Aβ42 or ptau181 levels in our sample. Our results suggest that these variants do not affect risk via a mechanism that results in a strong additive effect on CSF levels of Aβ42 or ptau181. [ABSTRACT FROM AUTHOR]

There is substantial evidence that cerebrospinal fluid (CSF) levels of both Aβ42 and tau/ptau are promising biomarkers for Alzheimer's disease (AD). We show that both Aβ and tau exhibit more than 10-fold interindividual variation in CSF levels suggesting that these biomarkers may also be effectively used as endophenotypes for genetic studies of AD. To test the role of common variation in the gene encoding microtubule associated protein tau (MAPT) in influencing CSF tau/ptau levels, we genotyped 21 MAPT single nucleotide polymorphisms (SNPs) in 313 individuals and tested for association with CSF tau/ptau levels. We identified alleles of several SNPs that show association with increased CSF tau/ptau levels. When CSF Aβ42 levels were used to stratify the sample into those with and without likely Aβ deposition in the brain the association was only observed in individuals with evidence of Aβ deposition. This association was replicated in an independent CSF series. When these SNPs were evaluated in a late-onset AD case control series the alleles associated with higher CSF tau/ptau were associated with an earlier age at onset but had no effect on risk for AD. In vivo gene expression studies show that these alleles are associated with increased MAPT mRNA levels in individuals with evidence of brain Aβ deposition. This endophenotype-based approach provides evidence for a gene (MAPT SNPs)-physiological environment (Aβ deposition) interaction that places changes in CSF tau after Aβ deposition and suggest that this interaction predisposes for the development of tauopathy and accelerated disease progression. [ABSTRACT FROM AUTHOR]