Genetic factors play a major role in sporadic late onset Alzheimer's disease (LOAD). Despite progress in the search for AD-risk genes, translation of genetic associations into targetable mechanisms remains a challenge. Recent metabolomics studies have identified bile acids (BA) as associated with AD. However, their relationship to genetic variation and AD pathophysiological markers has not been investigated. Here, we investigate the association between genetic variations, BA levels and AD brain imaging phenotypes using a systems biology approach. Non-Hispanic Caucasian participants (N=1,414) from the AD Neuroimaging Initiative with bile acid, MRI, and genotyping data were included[1]. We tested the association between serum levels of fifteen BA metabolites, profiled by the AD Metabolomics Consortium that passed quality controls, and 20 AD-relevant MRI ROI measures. We generated an integrative network by combining metabolite-protein interactions from RECON2 and functional protein-protein interactions from REACTOME. We mapped significant BAs onto the integrated network and extracted candidate genes including upstream enzymes directly mediating those BAs and genes regulating these enzymes. Finally, we performed a targeted association analysis using SNPs within ±50 kb boundary of each gene and the 20 MRI ROI values. Age, sex, education, intracranial volume, MRI field strength, and APOE ε4 status were used as covariates. Nine BAs were significantly associated with >=1 neuroimaging endophenotypes after multiple test correction (FDR-corrected p< 0.05). After mapping them onto the integrated network, we identified 25 candidate genes. The targeted analysis identified rs9607782 from EP300 and 22 SNPs from ACOT7 as significantly associated with neuroimaging phenotypes (corrected p<0.05). In the functional interaction network, EP300 was found to regulate 14 known AD risk genes (Fig. 1) including APOE. rs9607782 in EP300 is associated with EP300 expression levels in the temporal cortex (p=0.0011) of healthy individuals (www.braineac.org). Functional interaction networks between EP300 and AD-risk genes reported in. Only regulatory links that have direction information and are curated from pathways are included. Yellow: AD-risk genes; Orange: EP300, Turquoise: linker genes. EP300 modulating AD-associated BA levels was associated with AD-related neuroimaging endophenotypes and regulated APOE indirectly with PPARG as a linker gene, which is neuroprotective and a potential therapeutic target for AD[2]. EP300 has been suggested a key role in learning and memory. This study suggests a potential pathway underlying AD from genotype to metabolism and neuroimaging phenotypes. [1] Saykin, AJ, et al., Alzheimers&Dementia, 2015. [2] Malm, T., et al., J Neuroinflammation, 2015.
This paper proposes a data-driven longitudinal model that brings together factor graphs and learning methods to demonstrate a significant improvement in predictability in clinical outcomes of patients with major depressive disorder treated with antidepressants. Using data from the Mayo Clinic PGRN-AMPS trial and the STAR*D trial for validation, this work makes two significant contributions in the context of predictability in psychiatric therapeutic outcomes. First, we establish symptom dynamics in response to antidepressants by using the forward algorithm on a factor graph. Symptom dynamics are the changes in the symptom severity that are most likely to occur because of the antidepressants taken during the trial, and the associated clinical outcomes at 4 weeks and 8 weeks into the trial. The structure of the factor graph is inferred by using unsupervised learning to stratify patients by the similarity of their overall symptom severity. Second, by using metabolomics data as an accurate biological measure in addition to symptom survey data and other patient history information, the prediction of clinical outcomes such as response and remission significantly improved from 30% to 68% in men, and from 35% to 72% in women. This work demonstrates a significant difference in how men and women respond to antidepressants in terms of their symptom dynamics, and also shows that top predictors of clinical outcomes for men and women are significantly different and known to play a role in behavioral sciences.
The brain isoform of creatine kinase has been implicated in cellular transformation processes. Cyclocreatine, a creatine kinase substrate analog, was previously shown to be cytotoxic to a broad spectrum of solid tumors. We have synthesized, enzymatically characterized, and evaluated the antitumor activity of a series of substrate analogs of creatine kinase. Using in vitro assays, we demonstrate that several of these analogs are cytotoxic to the human ME-180 cervical carcinoma, the MCF-7 breast adenocarcinoma and the HT-29 colon adenocarcinoma cell lines at low mM concentrations. Analogs that were active in vitro delayed the growth of a subcutaneously implanted rat 13,762 mammary adenocarcinoma. Tumor growth delays of 6-8 days were achieved, which is comparable to effects seen with standard regimens of currently used anticancer drugs. These studies further establish the creatine kinase system as a promising and novel target for anticancer chemotherapy drug design.
Although statins are widely prescribed medications, there remains considerable variability in therapeutic response.Genetics can explain only part of this variability.Metabolomics is a global biochemical approach that provides powerful tools for mapping pathways implicated in disease and in response to treatment.Metabolomics captures net interactions between genome, microbiome and the environment.In this study, we used a targeted GC-MS metabolomics platform to measure a panel of metabolites within cholesterol synthesis, dietary sterol absorption, and bile acid formation to determine metabolite signatures that may predict variation in statin LDL-C lowering efficacy.Measurements were performed in two subsets of the total study population in the Cholesterol and Pharmacogenetics (CAP) study: Full Range of Response (FR), and Good and Poor Responders (GPR) were 100 individuals randomly selected from across the entire range of LDL-C responses in CAP.GPR were 48 individuals, 24 each from the top and bottom 10% of the LDL-C response distribution matched for body mass index, race, and gender.We identified three secondary, bacterial-derived bile acids that contribute to predicting the magnitude of statin-induced LDL-C lowering in good responders.Bile acids and statins share transporters in the liver and intestine; we observed that increased plasma concentration of simvastatin positively correlates with higher levels of several secondary bile acids.Genetic analysis of these subjects identified associations between levels of seven bile acids and a single nucleotide polymorphism (SNP), rs4149056, in the gene encoding the organic anion transporter SLCO1B1.These findings, along with recently published results that the gut microbiome plays an important role in cardiovascular disease, indicate that interactions between genome, gut microbiome and environmental influences should be considered in the study and management of cardiovascular disease.Metabolic profiles could provide valuable information about treatment outcomes and could contribute to a more personalized approach to therapy.
Background While aspirin is a well‐established and generally effective anti‐platelet agent, considerable inter‐individual variation in drug response exists, for which mechanisms are not completely understood. Metabolomics allows for extensive measurement of small molecules in biological samples, enabling detailed mapping of pathways involved in drug response. Methods and Results We used a mass‐spectrometry‐based metabolomics platform to investigate the changes in the serum oxylipid metabolome induced by an aspirin intervention (14 days, 81 mg/day) in healthy subjects (n=156). We observed a global decrease in serum oxylipids in response to aspirin (25 metabolites decreased out of 30 measured) regardless of sex. This decrease was concomitant with a significant decrease in serum linoleic acid levels (−19%, P =1.3×10 −5 ), one of the main precursors for oxylipid synthesis. Interestingly, several linoleic acid‐derived oxylipids were not significantly associated with arachidonic‐induced ex vivo platelet aggregation, a widely accepted marker of aspirin response, but were significantly correlated with platelet reactivity in response to collagen. Conclusions Together, these results suggest that linoleic acid‐derived oxylipids may contribute to the non‐ COX 1 mediated variability in response to aspirin. Pharmacometabolomics allowed for more comprehensive interrogation of mechanisms of action of low dose aspirin and of variation in aspirin response.
Abstract Introduction Increasing evidence suggests a role for the gut microbiome in central nervous system disorders and specific role for the gut-brain axis in neurodegeneration. Bile acids (BA), products of cholesterol metabolism and clearance, are produced in the liver and are further metabolized by gut bacteria. They have major regulatory and signaling functions and seem dysregulated in Alzheimer disease (AD). Methods Serum levels of 15 primary and secondary BAs and their conjugated forms were measured in 1,464 subjects including 370 cognitively normal older adults (CN), 284 with early mild cognitive impairment (MCI), 505 with late MCI, and 305 AD cases enrolled in the AD Neuroimaging Initiative. We assessed associations of BA profiles including selected ratios with diagnosis, cognition, and AD-related genetic variants, adjusting for cofounders and multiple testing. Results In AD compared to CN, we observed significantly lower serum concentrations of a primary BA (cholic acid CA) and increased levels of the bacterially produced, secondary BA, deoxycholic acid (DCA), and its glycine and taurine conjugated forms. An increased ratio of DCA:CA, which reflects 7α-dehydroxylation of CA by gut bacteria, strongly associated with cognitive decline, a finding replicated in serum and brain samples in the Rush Religious Orders and Memory and Aging Project. Several genetic variants in immune response related genes implicated in AD showed associations with BA profiles. Conclusion We report for the first time an association between altered BA profile, genetic variants implicated in AD and cognitive changes in disease using a large multicenter study. These findings warrant further investigation of gut dysbiosis and possible role of gut liver brain axis in the pathogenesis of AD.
ABSTRACT Background Major depressive disorder (MDD) is a highly heterogenous disease, both in terms of clinical profiles and pathobiological alterations. Recently, immunometabolic dysregulations were shown to be correlated with atypical, energy-related symptoms but less so with the Melancholic or Anxious distress symptom dimensions of depression in The Netherlands Study of Depression and Anxiety (NESDA) study. In this study, we aimed to replicate these immunometabolic associations and to characterize the metabolomic correlates of each of the three MDD dimensions. Methods Using three clinical rating scales, Melancholic, and Anxious distress, and Immunometabolic (IMD) dimensions were characterized in 158 patients who participated in the Predictors of Remission to Individual and Combined Treatments (PReDICT) study and from whom plasma and serum samples were available. The NESDA-defined inflammatory index, a composite measure of interleukin-6 and C-reactive protein, was measured from pre-treatment plasma samples and a metabolomic profile was defined using serum samples analyzed on three metabolomics platforms targeting fatty acids and complex lipids, amino acids, acylcarnitines, and gut microbiome-derived metabolites among other metabolites of central metabolism. Results The IMD clinical dimension and the inflammatory index were positively correlated (r=0.19, p=.019) after controlling for age, sex, and body mass index, whereas the Melancholic and Anxious distress dimensions were not, replicating the previous NESDA findings. The three symptom dimensions had distinct metabolomic signatures using both univariate and set enrichment statistics. IMD severity correlated mainly with gut-derived metabolites and a few acylcarnitines and long chain saturated free fatty acids. Melancholia severity was significantly correlated with several phosphatidylcholines, primarily the ether-linked variety, lysophosphatidylcholines, as well as several amino acids. Anxious distress severity correlated with several medium and long chain free fatty acids, both saturated and polyunsaturated ones, sphingomyelins, as well as several amino acids and bile acids. Conclusion The IMD dimension of depression is reliably associated with markers of inflammation. Metabolomics provides powerful tools to inform about depression heterogeneity and molecular mechanisms related to clinical dimensions in MDD, which include a link to gut microbiome and lipids implicated in membrane structure and function.
To investigate the association of triglyceride (TG) principal component scores with Alzheimer disease (AD) and the amyloid, tau, neurodegeneration, and cerebrovascular disease (A/T/N/V) biomarkers for AD.
Methods
Serum levels of 84 TG species were measured with untargeted lipid profiling of 689 participants from the Alzheimer9s Disease Neuroimaging Initiative cohort, including 190 cognitively normal older adults (CN), 339 with mild cognitive impairment (MCI), and 160 with AD. Principal component analysis with factor rotation was used for dimension reduction of TG species. Differences in principal components between diagnostic groups and associations between principal components and AD biomarkers (including CSF, MRI and [18F]fluorodeoxyglucose-PET) were assessed with a generalized linear model approach. In both cases, the Bonferroni method of adjustment was used to correct for multiple comparisons.
Results
The 84 TGs yielded 9 principal components, 2 of which, consisting of long-chain, polyunsaturated fatty acid–containing TGs (PUTGs), were significantly associated with MCI and AD. Lower levels of PUTGs were observed in MCI and AD compared to CN. PUTG principal component scores were also significantly associated with hippocampal volume and entorhinal cortical thickness. In participants carrying the APOE ε4 allele, these principal components were significantly associated with CSF β-amyloid1–42 values and entorhinal cortical thickness.
Conclusion
This study shows that PUTG component scores were significantly associated with diagnostic group and AD biomarkers, a finding that was more pronounced in APOE ε4 carriers. Replication in independent larger studies and longitudinal follow-up are warranted.
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