A very-low carbohydrate content in a high-fat diet modifies the plasma metabolome and impacts systemic inflammation and experimental atherosclerosis.

Ketogenic diets (KDs) are very high-fat low-carbohydrate diets that promote nutritional ketosis and are widely used for weight loss, although concerns about potential adverse cardiovascular effects remain. We investigated a very high-fat KD's vascular impact and plasma metabolic signature compared to a non-ketogenic high-fat diet (HFD). Apolipoprotein E deficient (ApoE -/-) mice were fed a KD (%kcal:81:1:18, fat/carbohydrate/protein), a non-ketogenic high-fat diet with half of the fat content (HFD) (%kcal:40:42:18, fat/carbohydrate/protein) for 12 weeks. Plasma samples were used to quantify the major ketone body beta-hydroxybutyrate (BHB) and several pro-inflammatory cytokines (IL-6, MCP-1, MIP-1alpha, and TNF alpha), and to targeted metabolomic profiling by mass spectrometry. In addition, aortic atherosclerotic lesions were quantified ex-vivo by magnetic resonance imaging (MRI) on a 14-tesla system. KD was atherogenic when compared to the control diet, but KD mice, when compared to the HFD group (1) had markedly higher levels of BHB and lower levels of cytokines, confirming the presence of ketosis that alleviated the well-established fat-induced systemic inflammation; (2) displayed significant changes in the plasma metabolome that included a decrease in lipophilic metabolites and an increase in hydrophilic metabolites; (3) had significantly lower levels of several atherogenic lipid metabolites, including phosphatidylcholines, cholesterol esters, sphingomyelins, and ceramides; and (4) presented significantly lower aortic plaque burden. KD was atherogenic and was associated with specific metabolic changes but alleviated the fat-induced inflammation and lessened the progression of atherosclerosis when compared to the HFD.

Targeted metabolomic analysis in Parkinson's disease brain frontal cortex and putamen with relation to cognitive impairment.

We performed liquid chromatography tandem mass spectrometry analysis with the targeted metabolomic kit Biocrates MxP Quant 500, in human brain cortex (Brodmann area 9) and putamen, to reveal metabolic changes characteristic of Parkinson's disease (PD) and PD-related cognitive decline. This case-control study involved 101 subjects (33 PD without dementia, 32 PD with dementia (cortex only), 36 controls). We found changes associated with PD, cognitive status, levodopa levels, and disease progression. The affected pathways include neurotransmitters, bile acids, homocysteine metabolism, amino acids, TCA cycle, polyamines, ß-alanine metabolism, fatty acids, acylcarnitines, ceramides, phosphatidylcholines, and several microbiome-derived metabolites. Previously reported levodopa-related homocysteine accumulation in cortex still best explains the dementia status in PD, which can be modified by dietary supplementation. Further investigation is needed to reveal the exact mechanisms behind this pathological change.

Targeted Metabolomic Analysis in Alzheimer's Disease Plasma and Brain Tissue in Non-Hispanic Whites.

BACKGROUND: Metabolites are biological compounds reflecting the functional activity of organs and tissues. Understanding metabolic changes in Alzheimer's disease (AD) can provide insight into potential risk factors in this multifactorial disease and suggest new intervention strategies or improve non-invasive diagnosis. OBJECTIVE: In this study, we searched for changes in AD metabolism in plasma and frontal brain cortex tissue samples and evaluated the performance of plasma measurements as biomarkers. METHODS: This is a case-control study with two tissue cohorts: 158 plasma samples (94 AD, 64 controls; Texas Alzheimer's Research and Care Consortium - TARCC) and 71 postmortem cortex samples (35 AD, 36 controls; Banner Sun Health Research Institute brain bank). We performed targeted mass spectrometry analysis of 630 compounds (106 small molecules: UHPLC-MS/MS, 524 lipids: FIA-MS/MS) and 232 calculated metabolic indicators with a metabolomic kit (Biocrates MxP® Quant 500). RESULTS: We discovered disturbances (FDR≤0.05) in multiple metabolic pathways in AD in both cohorts including microbiome-related metabolites with pro-toxic changes, methylhistidine metabolism, polyamines, corticosteroids, omega-3 fatty acids, acylcarnitines, ceramides, and diglycerides. In AD, plasma reveals elevated triglycerides, and cortex shows altered amino acid metabolism. A cross-validated diagnostic prediction model from plasma achieves AUC = 82% (CI95 = 75-88%); for females specifically, AUC = 88% (CI95 = 80-95%). A reduced model using 20 features achieves AUC = 79% (CI95 = 71-85%); for females AUC = 84% (CI95 = 74-92%). CONCLUSION: Our findings support the involvement of gut environment in AD and encourage targeting multiple metabolic areas in the design of intervention strategies, including microbiome composition, hormonal balance, nutrients, and muscle homeostasis.

One-Carbon Metabolism in Alzheimer's Disease and Parkinson's Disease Brain Tissue.

Disruptions in one-carbon metabolism and elevated homocysteine have been previously implicated in the development of dementia associated with Alzheimer's disease (AD) and Parkinson's disease (PD). Moreover, a PD diagnosis itself carries substantial risk for the development of dementia. This is the first study that explores alterations in one-carbon metabolism in AD and PD directly in the human brain frontal cortex, the primary center of cognition. Applying targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS), we analyzed post-mortem samples obtained from 136 subjects (35 AD, 65 PD, 36 controls). We found changes in one-carbon metabolites that indicate inefficient activation of cystathionine ß-synthase (CBS) in AD and PD subjects with dementia, the latter seemingly accompanied by a restricted re-methylation flow. Levodopa-carbidopa is known to reduce available vitamin B6, which would explain the hindered CBS activity. We present evidence of temporary non-protein-bound homocysteine accumulation upon levodopa intake in the brain of PD subjects with dementia but not in non-demented PD subjects. Importantly, this homocysteine elevation is not related to levodopa dosage, disease progression, or histopathological markers but exclusively to the dementia status. We hypothesize that this levodopa-induced effect is a direct cause of dementia in PD in susceptible subjects with reduced re-methylation capacity. Furthermore, we show that betaine best correlates with cognitive score even among PD subjects alone and discuss nutritional recommendations to improve one-carbon metabolism function.

Integrative analysis of breast cancer profiles in TCGA by TNBC subgrouping reveals novel microRNA-specific clusters, including miR-17-92a, distinguishing basal-like 1 and basal-like 2 TNBC subtypes.

BACKGROUND: The term triple-negative breast cancer (TNBC) is used to describe breast cancers without expression of estrogen receptor, progesterone receptor or HER2 amplification. To advance targeted treatment options for TNBC, it is critical that the subtypes within this classification be described in regard to their characteristic biology and gene expression. The Cancer Genome Atlas (TCGA) dataset provides not only clinical and mRNA expression data but also expression data for microRNAs. RESULTS: In this study, we applied the Lehmann classifier to TCGA-derived TNBC cases which also contained microRNA expression data and derived subtype-specific microRNA expression patterns. Subsequent analyses integrated known and predicted microRNA-mRNA regulatory nodes as well as patient survival data to identify key networks. Notably, basal-like 1 (BL1) TNBCs were distinguished from basal-like 2 TNBCs through up-regulation of members of the miR-17-92 cluster of microRNAs and suppression of several known miR-17-92 targets including inositol polyphosphate 4-phosphatase type II, INPP4B. CONCLUSIONS: These data demonstrate TNBC subtype-specific microRNA and target mRNA expression which may be applied to future biomarker and therapeutic development studies.

PrimAlign: PageRank-inspired Markovian alignment for large biological networks.

Motivation: Cross-species analysis of large-scale protein-protein interaction (PPI) networks has played a significant role in understanding the principles deriving evolution of cellular organizations and functions. Recently, network alignment algorithms have been proposed to predict conserved interactions and functions of proteins. These approaches are based on the notion that orthologous proteins across species are sequentially similar and that topology of PPIs between orthologs is often conserved. However, high accuracy and scalability of network alignment are still a challenge. Results: We propose a novel pairwise global network alignment algorithm, called PrimAlign, which is modeled as a Markov chain and iteratively transited until convergence. The proposed algorithm also incorporates the principles of PageRank. This approach is evaluated on tasks with human, yeast and fruit fly PPI networks. The experimental results demonstrate that PrimAlign outperforms several prevalent methods with statistically significant differences in multiple evaluation measures. PrimAlign, which is multi-platform, achieves superior performance in runtime with its linear asymptotic time complexity. Further evaluation is done with synthetic networks and results suggest that popular topological measures do not reflect real precision of alignments. Availability and implementation: The source code is available at http://web.ecs.baylor.edu/faculty/cho/PrimAlign. Supplementary information: Supplementary data are available at Bioinformatics online.