Inflammatory proteins in plasma are associated with severity of Alzheimer's disease.

Published onlineComparative StudyResearch Support, Non-U.S. Gov'tThis is a freely-available open access publication. Please cite the published version which is available via the DOI link in this record.Markers of Alzheimer's disease (AD) are being widely sought with a number of studies suggesting blood measures of inflammatory proteins as putative biomarkers. Here we report findings from a panel of 27 cytokines and related proteins in over 350 subjects with AD, subjects with Mild Cognitive Impairment (MCI) and elderly normal controls where we also have measures of longitudinal change in cognition and baseline neuroimaging measures of atrophy. In this study, we identify five inflammatory proteins associated with evidence of atrophy on MR imaging data particularly in whole brain, ventricular and entorhinal cortex measures. In addition, we observed six analytes that showed significant change (over a period of one year) in people with fast cognitive decline compared to those with intermediate and slow decline. One of these (IL-10) was also associated with brain atrophy in AD. In conclusion, IL-10 was associated with both clinical and imaging evidence of severity of disease and might therefore have potential to act as biomarker of disease progression.National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre and Dementia Biomedical Research Unit at South London and Maudsley NHS Foundation Trust and King’s College LondonEuropean Union of the Sixth Framework progra

Linking Genetics of Brain Changes to Alzheimer's Disease:Sparse Whole Genome Association Scan of Regional MRI Volumes in the ADNI and AddNeuroMed Cohorts

Background: Alzheimer's disease (AD) is a highly heritable disease, but until recently few replicated genetic markers have been identified. Markers identified so far are likely to account for only a tiny fraction of the heritability of AD and many more genetic risk alleles are thought to be undiscovered.  Objective: Identifying genetic markers for AD using combined analysis of genetics and brain imaging data.  Methods: Imaging quantitative trait loci (iQTLs) has recently emerged as an interesting research area for linking genetics of brain changes to AD. We consider a genome-wide association scan of 109 brain-wide regional imaging phenotypes to identify genetic susceptibility loci for AD from a combined set of 1,045 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the AddNeuroMed studies. We use one-SNP-at-a-time as well as multi-SNP Hyperlasso based iQTL methods for the analysis.  Results: We identified several novel markers associated with AD, namely HOMER2 (rs1256429; intronic, p = 8.7x10(-10)), EOMES (rs2724509; flanking), JAM2 (rs2829841; intronic), and WEE1 (rs10770042; coding). The SNP rs1256429 (HOMER2) was one of the top hits in Hyperlasso as well as in the single-SNP analysis showing an association with the volume of the right thalamus and AD, a brain region reported to be linked with AD in several studies.  Conclusion: We believe that the markers identified in this study are novel additions to the existing list of genetic variants associated with AD which can be validated in future replicated studies

A blood gene expression marker of early Alzheimer's disease.

PublishedJournal ArticleResearch Support, N.I.H., ExtramuralResearch Support, Non-U.S. Gov'tA marker of Alzheimer's disease (AD) that can accurately diagnose disease at the earliest stage would significantly support efforts to develop treatments for early intervention. We have sought to determine the sensitivity and specificity of peripheral blood gene expression as a diagnostic marker of AD using data generated on HT-12v3 BeadChips. We first developed an AD diagnostic classifier in a training cohort of 78 AD and 78 control blood samples and then tested its performance in a validation group of 26 AD and 26 control and 118 mild cognitive impairment (MCI) subjects who were likely to have an AD-endpoint. A 48 gene classifier achieved an accuracy of 75% in the AD and control validation group. Comparisons were made with a classifier developed using structural MRI measures, where both measures were available in the same individuals. In AD and control subjects, the gene expression classifier achieved an accuracy of 70% compared to 85% using MRI. Bootstrapping validation produced expression and MRI classifiers with mean accuracies of 76% and 82%, respectively, demonstrating better concordance between these two classifiers than achieved in a single validation population. We conclude there is potential for blood expression to be a marker for AD. The classifier also predicts a large number of people with MCI, who are likely to develop AD, are more AD-like than normal with 76% of subjects classified as AD rather than control. Many of these people do not have overt brain atrophy, which is known to emerge around the time of AD diagnosis, suggesting the expression classifier may detect AD earlier in the prodromal phase. However, we accept these results could also represent a marker of diseases sharing common etiology.InnoMed, European Union of the Sixth Framework programAlzheimer’s Research UKJohn and Lucille van Geest FoundationNIHRBiomedical Research Centre for Mental Health, South London and Maudsley NHS Foundation TrustInstitute of Psychiatry Kings College LondonNIA/NIH RC

Mitochondrial dysfunction and immune activation are detectable in early Alzheimer's disease blood.

PublishedJournal ArticleResearch Support, Non-U.S. Gov'tAlzheimer's disease (AD), like other dementias, is characterized by progressive neuronal loss and neuroinflammation in the brain. The peripheral leukocyte response occurring alongside these brain changes has not been extensively studied, but might inform therapeutic approaches and provide relevant disease biomarkers. Using microarrays, we assessed blood gene expression alterations occurring in people with AD and those with mild cognitive changes at increased risk of developing AD. Of the 2,908 differentially expressed probes identified between the three groups (p < 0.01), a quarter were altered in blood from mild cognitive impairment (MCI) and AD subjects, relative to controls, suggesting a peripheral response to pathology may occur very early. There was strong evidence for mitochondrial dysfunction with decreased expression of many of the respiratory complex I-V genes and subunits of the core mitochondrial ribosome complex. This mirrors changes previously observed in AD brain. A number of genes encoding cell adhesion molecules were increased, along with other immune-related genes. These changes are consistent with leukocyte activation and their increased the transition from circulation into the brain. In addition to expression changes, we also found increased numbers of basophils in people with MCI and AD, and increased monocytes in people with an AD diagnosis. Taken together this study provides both an insight into the functional response of circulating leukocytes during neurodegeneration and also identifies potential targets such as the respiratory chain for designing and monitoring future therapeutic interventions using blood.InnoMed, European Union of the Sixth Framework programAlzheimer’s Research TrustJohn and Lucille van Geest FoundationNIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation TrustInstitute of Psychiatry Kings College Londo

Plasma based markers of [11C] PiB-PET brain amyloid burden.

PublishedJournal ArticleResearch Support, N.I.H., ExtramuralResearch Support, Non-U.S. Gov'tChanges in brain amyloid burden have been shown to relate to Alzheimer's disease pathology, and are believed to precede the development of cognitive decline. There is thus a need for inexpensive and non-invasive screening methods that are able to accurately estimate brain amyloid burden as a marker of Alzheimer's disease. One potential method would involve using demographic information and measurements on plasma samples to establish biomarkers of brain amyloid burden; in this study data from the Alzheimer's Disease Neuroimaging Initiative was used to explore this possibility. Sixteen of the analytes on the Rules Based Medicine Human Discovery Multi-Analyte Profile 1.0 panel were found to associate with [(11)C]-PiB PET measurements. Some of these markers of brain amyloid burden were also found to associate with other AD related phenotypes. Thirteen of these markers of brain amyloid burden--c-peptide, fibrinogen, alpha-1-antitrypsin, pancreatic polypeptide, complement C3, vitronectin, cortisol, AXL receptor kinase, interleukin-3, interleukin-13, matrix metalloproteinase-9 total, apolipoprotein E and immunoglobulin E--were used along with co-variates in multiple linear regression, and were shown by cross-validation to explain >30% of the variance of brain amyloid burden. When a threshold was used to classify subjects as PiB positive, the regression model was found to predict actual PiB positive individuals with a sensitivity of 0.918 and a specificity of 0.545. The number of APOE [Symbol: see text] 4 alleles and plasma apolipoprotein E level were found to contribute most to this model, and the relationship between these variables and brain amyloid burden was explored.Alzheimer's Disease Neuroimaging Initiative (ADNI)Canadian Institutes of Health ResearchFoundation for the National Institutes of HealthNational Institutes of HealthInnoMed, European Union of the Sixth Framework programNational Institutes for Health Research Biomedical Research Centre for Mental Health at the South London and Maudsley National Health Service Foundation TrustInstitute of Psychiatry, King's College Londo

Validation of the Mini Nutritional Assessment-Short Form in a population of frail elders without disability. Analysis of the Toulouse Frailty Platform population in 2013

**Objective** To assess the validity of the Mini Nutritional Assessment-Short Form (MNA-SF) in elderly patients from the Toulouse Frailty Platform. **Participants** Overall, 267 patients aged 65 and over, without severe cognitive impairment (i.e. Mini Mental Status Examination > 20 and CDR<1), no physical disability (i.e. Activities of Daily Living ≥ 5) and no active cancer history (over the past 12 months) were included in 2013. **Measurements** Receiver operating characteristic (ROC) analyses were used to assess the predictive validity of the French version of the MNA-SF for good nutritional status (defined as a full MNA score≥24/30). Analyses were conducted in the overall sample and then in subgroups of frail and pre-frail subjects according to the frailty phenotype. Optimal cut-off points were determined to obtain the best sensitivity/specificity ratio and the highest number of correctly classified subjects. **Results** Among 267 patients, mean age=81.5±5.8; women=67.0%; 138 (51.7%) were frail, 98 (36.7%) were pre-frail and 31 (11.6%) were robust. Given their MNA-SF scores, 201 (75.3%) had a good nutritional status, 61 (22.8%) were at risk of malnutrition and 5 (1.9%) were malnourished. In the overall sample, but also in subgroups of pre-frail or frail elders, the areas under ROC curves were 0.954, 0.948 and 0.958 respectively. The 11 points cut-off provided the best correct classification ratio (91.4%); sensitivity=94.0%, specificity=83.3%. **Conclusion** The MNA-SF appeared to be a validated and effective tool for malnutrition screening in frail elders. Implementing this tool in clinical routine should contribute to improving the screening of malnourished frail individuals

Genetic predisposition to increased blood cholesterol and triglyceride lipid levels and risk of Alzheimer disease: a Mendelian randomization analysis.

BACKGROUND: Although altered lipid metabolism has been extensively implicated in the pathogenesis of Alzheimer disease (AD) through cell biological, epidemiological, and genetic studies, the molecular mechanisms linking cholesterol and AD pathology are still not well understood and contradictory results have been reported. We have used a Mendelian randomization approach to dissect the causal nature of the association between circulating lipid levels and late onset AD (LOAD) and test the hypothesis that genetically raised lipid levels increase the risk of LOAD. METHODS AND FINDINGS: We included 3,914 patients with LOAD, 1,675 older individuals without LOAD, and 4,989 individuals from the general population from six genome wide studies drawn from a white population (total n=10,578). We constructed weighted genotype risk scores (GRSs) for four blood lipid phenotypes (high-density lipoprotein cholesterol [HDL-c], low-density lipoprotein cholesterol [LDL-c], triglycerides, and total cholesterol) using well-established SNPs in 157 loci for blood lipids reported by Willer and colleagues (2013). Both full GRSs using all SNPs associated with each trait at p<5×10-8 and trait specific scores using SNPs associated exclusively with each trait at p<5 × 10-8 were developed. We used logistic regression to investigate whether the GRSs were associated with LOAD in each study and results were combined together by meta-analysis. We found no association between any of the full GRSs and LOAD (meta-analysis results: odds ratio [OR]=1.005, 95% CI 0.82-1.24, p = 0.962 per 1 unit increase in HDL-c; OR=0.901, 95% CI 0.65-1.25, p=0.530 per 1 unit increase in LDL-c; OR=1.104, 95% CI 0.89-1.37, p=0.362 per 1 unit increase in triglycerides; and OR=0.954, 95% CI 0.76-1.21, p=0.688 per 1 unit increase in total cholesterol). Results for the trait specific scores were similar; however, the trait specific scores explained much smaller phenotypic variance. CONCLUSIONS: Genetic predisposition to increased blood cholesterol and triglyceride lipid levels is not associated with elevated LOAD risk. The observed epidemiological associations between abnormal lipid levels and LOAD risk could therefore be attributed to the result of biological pleiotropy or could be secondary to LOAD. Limitations of this study include the small proportion of lipid variance explained by the GRS, biases in case-control ascertainment, and the limitations implicit to Mendelian randomization studies. Future studies should focus on larger LOAD datasets with longitudinal sampled peripheral lipid measures and other markers of lipid metabolism, which have been shown to be altered in LOAD. Please see later in the article for the Editors' Summary

Circulating Proteomic Signatures of Chronological Age

To elucidate the proteomic features of aging in plasma, the subproteome targeted by the SOMAscan assay was profiled in blood samples from 202 females from the TwinsUK cohort. Findings were replicated in 677 independent individuals from the AddNeuroMed, Alzheimer's Research UK, and Dementia Case Registry cohorts. Results were further validated using RNAseq data from whole blood in TwinsUK and the most significant proteins were tested for association with aging-related phenotypes after adjustment for age. Eleven proteins were associated with chronological age and were replicated at protein level in an independent population. These were further investigated at gene expression level in 384 females from the TwinsUK cohort. The two most strongly associated proteins were chordin-like protein 1 (meta-analysis β [SE] = 0.013 [0.001], p = 3.66 × 10−46) and pleiotrophin (0.012 [0.005], p = 3.88 × 10−41). Chordin-like protein 1 was also significantly correlated with birthweight (0.06 [0.02], p = 0.005) and with the individual Framingham 10-years cardiovascular risk scores in TwinsUK (0.71 [0.18], p = 9.9 × 10−5). Pleiotrophin is a secreted growth factor with a plethora of functions in multiple tissues and known to be a marker for cardiovascular risk and osteoporosis. Our study highlights the importance of proteomics to identify some molecular mechanisms involved in human health and agin

Plasma proteins predict conversion to dementia from prodromal disease.

PublishedJournal ArticleMulticenter StudyResearch Support, Non-U.S. Gov'tBACKGROUND: The study aimed to validate previously discovered plasma biomarkers associated with AD, using a design based on imaging measures as surrogate for disease severity and assess their prognostic value in predicting conversion to dementia. METHODS: Three multicenter cohorts of cognitively healthy elderly, mild cognitive impairment (MCI), and AD participants with standardized clinical assessments and structural neuroimaging measures were used. Twenty-six candidate proteins were quantified in 1148 subjects using multiplex (xMAP) assays. RESULTS: Sixteen proteins correlated with disease severity and cognitive decline. Strongest associations were in the MCI group with a panel of 10 proteins predicting progression to AD (accuracy 87%, sensitivity 85%, and specificity 88%). CONCLUSIONS: We have identified 10 plasma proteins strongly associated with disease severity and disease progression. Such markers may be useful for patient selection for clinical trials and assessment of patients with predisease subjective memory complaints.Medical Research Council (MRC)Alzheimer’s Research UKThe National Institute for Health Research (NIHR) Biomedical Research CentreBiomedical Research Unit for DementiaAddNeuroMed through the EU FP6 programInnovative Medicines Initiative Joint Undertaking under an EMIF grantEuropean Union’s Seventh Framework Programme (FP7/2007-2013