The incidence of Alzheimer's disease (AD) increases with age and is becoming a significant cause of worldwide morbidity and mortality. However, the metabolic perturbation behind the onset of AD ...remains unclear. In this study, we performed metabolite profiling in both brain (n = 109) and matching serum samples (n = 566) to identify differentially expressed metabolites and metabolic pathways associated with neuropathology and cognitive performance and to identify individuals at high risk of developing cognitive impairment. The abundances of 6 metabolites, glycolithocholate (GLCA), petroselinic acid, linoleic acid, myristic acid, palmitic acid, palmitoleic acid and the deoxycholate/cholate (DCA/CA) ratio, along with the dysregulation scores of 3 metabolic pathways, primary bile acid biosynthesis, fatty acid biosynthesis, and biosynthesis of unsaturated fatty acids showed significant differences across both brain and serum diagnostic groups (P-value < 0.05). Significant associations were observed between the levels of differential metabolites/pathways and cognitive performance, neurofibrillary tangles, and neuritic plaque burden. Metabolites abundances and personalized metabolic pathways scores were used to derive machine learning models, respectively, that could be used to differentiate cognitively impaired persons from those without cognitive impairment (median area under the receiver operating characteristic curve (AUC) = 0.772 for the metabolite level model; median AUC = 0.731 for the pathway level model). Utilizing these two models on the entire baseline control group, we identified those who experienced cognitive decline in the later years (AUC = 0.804, sensitivity = 0.722, specificity = 0.749 for the metabolite level model; AUC = 0.778, sensitivity = 0.633, specificity = 0.825 for the pathway level model) and demonstrated their pre-AD onset prediction potentials. Our study provides a proof-of-concept that it is possible to discriminate antecedent cognitive impairment in older adults before the onset of overt clinical symptoms using metabolomics. Our findings, if validated in future studies, could enable the earlier detection and intervention of cognitive impairment that may halt its progression.
Abstract
Integration of the omics data, including metabolomics and proteomics, provides a unique opportunity to search for new associations within metabolic disorders, including Alzheimer’s disease. ...Using metabolomics, we have previously profiled oxylipins, endocannabinoids, bile acids, and steroids in 293 CSF and 202 matched plasma samples from AD cases and healthy controls and identified both central and peripheral markers of AD pathology within inflammation-regulating cytochrome p450/soluble epoxide hydrolase pathway. Additionally, using proteomics, we have identified five cerebrospinal fluid protein panels, involved in the regulation of energy metabolism, vasculature, myelin/oligodendrocyte, glia/inflammation, and synapses/neurons, affected in AD, and reflective of AD-related changes in the brain. In the current manuscript, using metabolomics-proteomics data integration, we describe new associations between peripheral and central lipid mediators, with the above-described CSF protein panels. Particularly strong associations were observed between cytochrome p450/soluble epoxide hydrolase metabolites, bile acids, and proteins involved in glycolysis, blood coagulation, and vascular inflammation and the regulators of extracellular matrix. Those metabolic associations were not observed at the gene-co-expression level in the central nervous system. In summary, this manuscript provides new information regarding Alzheimer’s disease, linking both central and peripheral metabolism, and illustrates the necessity for the “omics” data integration to uncover associations beyond gene co-expression.
Background Alzheimer's disease, cardiovascular disease, and other cardiometabolic disorders may share inflammatory origins. Lipid mediators, including oxylipins, endocannabinoids, bile acids, and ...steroids, regulate inflammation, energy metabolism, and cell proliferation with well-established involvement in cardiometabolic diseases. However, their role in Alzheimer's disease is poorly understood. Here, we describe the analysis of plasma and cerebrospinal fluid lipid mediators in a case-control comparison of ~150 individuals with Alzheimer's disease and ~135 healthy controls, to investigate this knowledge gap. Methods Lipid mediators were measured using targeted quantitative mass spectrometry. Data were analyzed using the analysis of covariates, adjusting for sex, age, and ethnicity. Partial least square discriminant analysis identified plasma and cerebrospinal fluid lipid mediator discriminates of Alzheimer's disease. Alzheimer's disease predictive models were constructed using machine learning combined with stepwise logistic regression. Results In both plasma and cerebrospinal fluid, individuals with Alzheimer's disease had elevated cytochrome P450/soluble epoxide hydrolase pathway components and decreased fatty acid ethanolamides compared to healthy controls. Circulating metabolites of soluble epoxide hydrolase and ethanolamides provide Alzheimer's disease predictors with areas under receiver operator characteristic curves ranging from 0.82 to 0.92 for cerebrospinal fluid and plasma metabolites, respectively. Conclusions Previous studies report Alzheimer's disease-associated soluble epoxide hydrolase upregulation in the brain and that endocannabinoid metabolism provides an adaptive response to neuroinflammation. This study supports the involvement of P450-dependent and endocannabinoid metabolism in Alzheimer's disease. The results further suggest that combined pharmacological intervention targeting both metabolic pathways may have therapeutic benefits for Alzheimer's disease. Keywords: Alzheimer's disease, Lipid mediators, Oxylipins, Endocannabinoids, Cognition
Individual-level characteristics, including socioeconomic status, have been associated with poor metabolic and cardiovascular health; however, residential area-level characteristics may also ...independently contribute to health status. In the current study, we used hierarchical clustering to aggregate 444 US Census block groups in Durham, Orange, and Wake Counties, NC, USA into six homogeneous clusters of similar characteristics based on 12 demographic factors. We assigned 2254 cardiac catheterization patients to these clusters based on residence at first catheterization. After controlling for individual age, sex, smoking status, and race, there were elevated odds of patients being obese (odds ratio (OR)=1.92, 95% confidence intervals (CI)=1.39, 2.67), and having diabetes (OR=2.19, 95% CI=1.57, 3.04), congestive heart failure (OR=1.99, 95% CI=1.39, 2.83), and hypertension (OR=2.05, 95% CI=1.38, 3.11) in a cluster that was urban, impoverished, and unemployed, compared with a cluster that was urban with a low percentage of people that were impoverished or unemployed. Our findings demonstrate the feasibility of applying hierarchical clustering to an assessment of area-level characteristics and that living in impoverished, urban residential clusters may have an adverse impact on health.
Air pollution is a worldwide contributor to cardiovascular disease mortality and morbidity. Traffic-related air pollution is a widespread environmental exposure and is associated with multiple ...cardiovascular outcomes such as coronary atherosclerosis, peripheral arterial disease, and myocardial infarction. Despite the recognition of the importance of both genetic and environmental exposures to the pathogenesis of cardiovascular disease, studies of how these two contributors operate jointly are rare. We performed a genome-wide interaction study (GWIS) to examine gene-traffic exposure interactions associated with coronary atherosclerosis. Using race-stratified cohorts of 538 African-Americans (AA) and 1562 European-Americans (EA) from a cardiac catheterization cohort (CATHGEN), we identify gene-by-traffic exposure interactions associated with the number of significantly diseased coronary vessels as a measure of chronic atherosclerosis. We found five suggestive (P<1x10-5) interactions in the AA GWIS, of which two (rs1856746 and rs2791713) replicated in the EA cohort (P < 0.05). Both SNPs are in the PIGR-FCAMR locus and are eQTLs in lymphocytes. The protein products of both PIGR and FCAMR are implicated in inflammatory processes. In the EA GWIS, there were three suggestive interactions; none of these replicated in the AA GWIS. All three were intergenic; the most significant interaction was in a regulatory region associated with SAMSN1, a gene previously associated with atherosclerosis and B cell activation. In conclusion, we have uncovered several novel genes associated with coronary atherosclerosis in individuals chronically exposed to increased ambient concentrations of traffic air pollution. These genes point towards inflammatory pathways that may modify the effects of air pollution on cardiovascular disease risk.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
There is a growing literature indicating that genetic variants modify many of the associations between environmental exposures and clinical outcomes, potentially by increasing susceptibility to these ...exposures. However, genome-scale investigations of these interactions have been rarely performed particularly in the case of air pollution exposures. We performed race-stratified genome-wide gene-environment interaction association studies on European-American (EA, N = 1623) and African-American (AA, N = 554) cohorts to investigate the joint influence of common single nucleotide polymorphisms (SNPs) and residential exposure to traffic ("traffic exposure")-a recognized vascular disease risk factor-on peripheral arterial disease (PAD). Traffic exposure was estimated via the distance from the primary residence to the nearest major roadway, defined as the nearest limited access highways or major arterial. The rs755249-traffic exposure interaction was associated with PAD at a genome-wide significant level (P = 2.29x10-8) in European-Americans. Rs755249 is located in the 3' untranslated region of BMP8A, a member of the bone morphogenic protein (BMP) gene family. Further investigation revealed several variants in BMP genes associated with PAD via an interaction with traffic exposure in both the EA and AA cohorts; this included interactions with non-synonymous variants in BMP2, which is regulated by air pollution exposure. The BMP family of genes is linked to vascular growth and calcification and is a novel gene family for the study of PAD pathophysiology. Further investigation of BMP8A using the Genotype Tissue Expression Database revealed multiple variants with nominally significant (P < 0.05) interaction P-values in our EA cohort were significant BMP8A eQTLs in tissue types highlight relevant for PAD such as rs755249 (tibial nerve, eQTL P = 3.6x10-6) and rs1180341 (tibial artery, eQTL P = 5.3x10-6). Together these results reveal a novel gene, and possibly gene family, associated with PAD via an interaction with traffic air pollution exposure. These results also highlight the potential for interactions studies, particularly at the genome scale, to reveal novel biology linking environmental exposures to clinical outcomes.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Sex disparities in serum bile acid (BA) levels and Alzheimer's disease (AD) prevalence have been established. However, the precise link between changes in serum BAs and AD development remains ...elusive. Here, authors quantitatively determined 33 serum BAs and 58 BA features in 4 219 samples collected from 1 180 participants from the Alzheimer's Disease Neuroimaging Initiative. The findings revealed that these BA features exhibited significant correlations with clinical stages, encompassing cognitively normal (CN), early and late mild cognitive impairment, and AD, as well as cognitive performance. Importantly, these associations are more pronounced in men than women. Among participants with progressive disease stages (n = 660), BAs underwent early changes in men, occurring before AD. By incorporating BA features into diagnostic and predictive models, positive enhancements are achieved for all models. The area under the receiver operating characteristic curve improved from 0.78 to 0.91 for men and from 0.76 to 0.83 for women for the differentiation of CN and AD. Additionally, the key findings are validated in a subset of participants (n = 578) with cerebrospinal fluid amyloid‐beta and tau levels. These findings underscore the role of BAs in AD progression, offering potential improvements in the accuracy of AD prediction.
There are sex differences in serum bile acid (BA) levels and Alzheimer's disease (AD) incidence. With a longitudinal ADNI study, it is found that BAs trend in relation to AD progression and the alteration is earlier in men than women. Sex‐specific features associated with disease stages, cognitive functions, and progression highlighted BA roles in AD progression.
Alzheimer's disease (AD) is the most common neurodegenerative disease presenting major health and economic challenges that continue to grow. Mechanisms of disease are poorly understood but ...significant data point to metabolic defects that might contribute to disease pathogenesis. The Alzheimer Disease Metabolomics Consortium (ADMC) in partnership with Alzheimer Disease Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for AD. Using targeted and non- targeted metabolomics and lipidomics platforms we are mapping metabolic pathway and network failures across the trajectory of disease. In this report we present quantitative metabolomics data generated on serum from 199 control, 356 mild cognitive impairment and 175 AD subjects enrolled in ADNI1 using AbsoluteIDQ-p180 platform, along with the pipeline for data preprocessing and medication classification for confound correction. The dataset presented here is the first of eight metabolomics datasets being generated for broad biochemical investigation of the AD metabolome. We expect that these collective metabolomics datasets will provide valuable resources for researchers to identify novel molecular mechanisms contributing to AD pathogenesis and disease phenotypes.
The molecular diagnosis of muscle disorders is challenging: genetic heterogeneity (>100 causal genes for skeletal and cardiac muscle disease) precludes exhaustive clinical testing, prioritizing ...sequencing of specific genes is difficult due to the similarity of clinical presentation, and the number of variants returned through exome sequencing can make the identification of the disease-causing variant difficult. We have filtered variants found through exome sequencing by prioritizing variants in genes known to be involved in muscle disease while examining the quality and depth of coverage of those genes. We ascertained two families with autosomal dominant limb-girdle muscular dystrophy of unknown etiology. To identify the causal mutations in these families, we performed exome sequencing on five affected individuals using the Agilent SureSelect Human All Exon 50 Mb kit and the Illumina HiSeq 2000 (2×100 bp). We identified causative mutations in desmin (IVS3+3A>G) and filamin C (p.W2710X), and augmented the phenotype data for individuals with muscular dystrophy due to these mutations. We also discuss challenges encountered due to depth of coverage variability at specific sites and the annotation of a functionally proven splice site variant as an intronic variant.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract Introduction The Alzheimer's Disease Research Summits of 2012 and 2015 incorporated experts from academia, industry, and nonprofit organizations to develop new research directions to ...transform our understanding of Alzheimer's disease (AD) and propel the development of critically needed therapies. In response to their recommendations, big data at multiple levels are being generated and integrated to study network failures in disease. We used metabolomics as a global biochemical approach to identify peripheral metabolic changes in AD patients and correlate them to cerebrospinal fluid pathology markers, imaging features, and cognitive performance. Methods Fasting serum samples from the Alzheimer's Disease Neuroimaging Initiative (199 control, 356 mild cognitive impairment, and 175 AD participants) were analyzed using the AbsoluteIDQ-p180 kit. Performance was validated in blinded replicates, and values were medication adjusted. Results Multivariable-adjusted analyses showed that sphingomyelins and ether-containing phosphatidylcholines were altered in preclinical biomarker-defined AD stages, whereas acylcarnitines and several amines, including the branched-chain amino acid valine and α-aminoadipic acid, changed in symptomatic stages. Several of the analytes showed consistent associations in the Rotterdam, Erasmus Rucphen Family, and Indiana Memory and Aging Studies. Partial correlation networks constructed for Aβ1–42 , tau, imaging, and cognitive changes provided initial biochemical insights for disease-related processes. Coexpression networks interconnected key metabolic effectors of disease. Discussion Metabolomics identified key disease-related metabolic changes and disease-progression-related changes. Defining metabolic changes during AD disease trajectory and its relationship to clinical phenotypes provides a powerful roadmap for drug and biomarker discovery.
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