Inflammation and the pathological progression of Alzheimer's disease are associated with low circulating choline levels.

Deficiency of dietary choline, an essential nutrient, is observed worldwide, with ~ 90% of Americans being deficient. Previous work highlights a relationship between decreased choline intake and an increased risk for cognitive decline and Alzheimer's disease (AD). The associations between blood circulating choline and the pathological progression in both mild cognitive impairment (MCI) and AD remain unknown. Here, we examined these associations in a cohort of patients with MCI with presence of either sparse or high neuritic plaque density and Braak stage and a second cohort with either moderate AD (moderate to frequent neuritic plaques, Braak stage = IV) or severe AD (frequent neuritic plaques, Braak stage = VI), compared to age-matched controls. Metabolomic analysis was performed on serum from the AD cohort. We then assessed the effects of dietary choline deficiency (Ch-) in 3xTg-AD mice and choline supplementation (Ch+) in APP/PS1 mice, two rodent models of AD. The levels of circulating choline were reduced while pro-inflammatory cytokine TNFα was elevated in serum of both MCI sparse and high pathology cases. Reduced choline and elevated TNFα correlated with higher neuritic plaque density and Braak stage. In AD patients, we found reductions in choline, its derivative acetylcholine (ACh), and elevated TNFα. Choline and ACh levels were negatively correlated with neuritic plaque load, Braak stage, and TNFα, but positively correlated with MMSE, and brain weight. Metabolites L-Valine, 4-Hydroxyphenylpyruvic, Methylmalonic, and Ferulic acids were significantly associated with circuiting choline levels. In 3xTg-AD mice, the Ch- diet increased amyloid-ß levels and tau phosphorylation in cortical tissue, and TNFα in both blood and cortical tissue, paralleling the severe human-AD profile. Conversely, the Ch+ diet increased choline and ACh while reducing amyloid-ß and TNFα levels in brains of APP/PS1 mice. Collectively, low circulating choline is associated with AD-neuropathological progression, illustrating the importance of adequate dietary choline intake to offset disease.

Metabolomic profiles of metformin in breast cancer survivors: a pooled analysis of plasmas from two randomized placebo-controlled trials.

BACKGROUND: Obesity is a major health concern for breast cancer survivors, being associated with high recurrence and reduced efficacy during cancer treatment. Metformin treatment is associated with reduced breast cancer incidence, recurrence and mortality. To better understand the underlying mechanisms through which metformin may reduce recurrence, we aimed to conduct metabolic profiling of overweight/obese breast cancer survivors before and after metformin treatment. METHODS: Fasting plasma samples from 373 overweight or obese breast cancer survivors randomly assigned to metformin (n = 194) or placebo (n = 179) administration were collected at baseline, after 6 months (Reach For Health trial), and after 12 months (MetBreCS trial). Archival samples were concurrently analyzed using three complementary methods: untargeted LC-QTOF-MS metabolomics, targeted LC-MS metabolomics (AbsoluteIDQ p180, Biocrates), and gas chromatography phospholipid fatty acid assay. Multivariable linear regression models and family-wise error correction were used to identify metabolites that significantly changed after metformin treatment. RESULTS: Participants (n = 352) with both baseline and study end point samples available were included in the analysis. After adjusting for confounders such as study center, age, body mass index and false discovery rate, we found that metformin treatment was significantly associated with decreased levels of citrulline, arginine, tyrosine, caffeine, paraxanthine, and theophylline, and increased levels of leucine, isoleucine, proline, 3-methyl-2-oxovalerate, 4-methyl-2-oxovalerate, alanine and indoxyl-sulphate. Long-chain unsaturated phosphatidylcholines (PC ae C36:4, PC ae C38:5, PC ae C36:5 and PC ae C38:6) were significantly decreased with the metformin treatment, as were phospholipid-derived long-chain n-6 fatty acids. The metabolomic profiles of metformin treatment suggest change in specific biochemical pathways known to impair cancer cell growth including activation of CYP1A2, alterations in fatty acid desaturase activity, and altered metabolism of specific amino acids, including impaired branched chain amino acid catabolism. CONCLUSIONS: Our results in overweight breast cancer survivors identify new metabolic effects of metformin treatment that may mechanistically contribute to reduced risk of recurrence in this population and reduced obesity-related cancer risk reported in observational studies. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT01302379 and EudraCT Protocol #: 2015-001001-14.

Enhanced Detection of Short-Chain Fatty Acids Using Gas Chromatography Mass Spectrometry.

Short-chain fatty acids (SCFAs) are produced mainly by intestinal microbiota and play an important role in many host biological processes such as immune system development, glucose and energy homeostasis, and regulation of immune response and inflammation. In addition, they participate in the regulation of anorectic hormones, which have a role in appetite control, tumor suppression, and regulating the central and peripheral nervous systems. As such, there is great interest in monitoring levels of SCFAs in various biological samples. Due to the highly hydrophilic and volatile characteristics of SCFAs, optimizing extraction and sample preparation procedures is often a central component to further improve SCFA quantification. Here, we describe a rapid and highly sensitive analytical method for measuring SCFAs in human serum and feces. Briefly, SCFAs are protected by adding sodium hydroxide, followed by a one-step extraction (pH > 7). Then, SCFAs are quantified by gas chromatography coupled to mass spectrometry (GC-MS) after derivatization with N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide (MTBSTFA). This method demonstrates excellent sensitivity, linearity, and derivatization efficiency for simultaneous determination of 14 different SCFAs. Further, this validated method can be successfully applied to quantify SCFAs in micro-scale biological samples. In summary, we describe efficient and advanced sample preparation and detection procedures that are critically needed for monitoring SCFA concentrations in human biological samples. © 2021 Wiley Periodicals LLC. Basic Protocol: SCFA extraction and detection from fecal and serum samples with gas chromatography-mass spectrometry.

Early Breast Cancer Detection Using Untargeted and Targeted Metabolomics.

Breast cancer (BC) is a common cause of morbidity and mortality, particularly in women. Moreover, the discovery of diagnostic biomarkers for early BC remains a challenging task. Previously, we [Jasbi et al. J. Chromatogr. B. 2019, 1105, 26-37] demonstrated a targeted metabolic profiling approach capable of identifying metabolite marker candidates that could enable highly sensitive and specific detection of BC. However, the coverage of this targeted method was limited and exhibited suboptimal classification of early BC (EBC). To expand the metabolome coverage and articulate a better panel of metabolites or mass spectral features for classification of EBC, we evaluated untargeted liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) data, both individually as well as in conjunction with previously published targeted LC-triple quadruple (QQQ)-MS data. Variable importance in projection scores were used to refine the biomarker panel, whereas orthogonal partial least squares-discriminant analysis was used to operationalize the enhanced biomarker panel for early diagnosis. In this approach, 33 altered metabolites/features were detected by LC-QTOF-MS from 124 BC patients and 86 healthy controls. For EBC diagnosis, significance testing and analysis of the area under receiver operating characteristic (AUROC) curve identified six metabolites/features [ethyl (R)-3-hydroxyhexanoate; caprylic acid; hypoxanthine; and m/z 358.0018, 354.0053, and 356.0037] with p < 0.05 and AUROC > 0.7. These metabolites informed the construction of EBC diagnostic models; evaluation of model performance for the prediction of EBC showed an AUROC = 0.938 (95% CI: 0.895-0.975), with sensitivity = 0.90 when specificity = 0.90. Using the combined untargeted and targeted data set, eight metabolic pathways of potential biological relevance were indicated to be significantly altered as a result of EBC. Metabolic pathway analysis showed fatty acid and aminoacyl-tRNA biosynthesis as well as inositol phosphate metabolism to be most impacted in response to the disease. The combination of untargeted and targeted metabolomics platforms has provided a highly predictive and accurate method for BC and EBC diagnosis from plasma samples. Furthermore, such a complementary approach yielded critical information regarding potential pathogenic mechanisms underlying EBC that, although critical to improved prognosis and enhanced survival, are understudied in the current literature. All mass spectrometry data and deidentified subject metadata analyzed in this study have been deposited to Mendeley Data and are publicly available (DOI: 10.17632/kcjg8ybk45.1).

Hypoxia promotes erythroid differentiation through the development of progenitors and proerythroblasts.

Oxygen is a critical noncellular component of the bone marrow microenvironment that plays an important role in the development of hematopoietic cell lineages. In this study, we investigated the impact of low oxygen (hypoxia) on ex vivo myeloerythroid differentiation of human cord blood-derived CD34+ hematopoietic stem and progenitor cells. We characterized the culture conditions to demonstrate that low oxygen inhibits cell proliferation and causes a metabolic shift in the stem and progenitor populations. We found that hypoxia promotes erythroid differentiation by supporting the development of progenitor populations. Hypoxia also increases the megakaryoerythroid potential of the common myeloid progenitors and the erythroid potential of megakaryoerythroid progenitors and significantly accelerates maturation of erythroid cells. Specifically, we determined that hypoxia promotes the loss of CD71 and the appearance of the erythroid markers CD235a and CD239. Further, evaluation of erythroid populations revealed a hypoxia-induced increase in proerythroblasts and in enucleation of CD235a+ cells. These results reveal the extensive role of hypoxia at multiple steps during erythroid development. Overall, our work establishes a valuable model for further investigations into the relationship between erythroid progenitors and/or erythroblast populations and their hypoxic microenvironment.

Metabolomics Analysis of Viral Therapeutics.

Virotherapy, enabled by recent advances in the transdisciplinary field of biotechnology, has emerged as a powerful tool for use in anticancer treatment, gene therapy, immunotherapy, etc. Examining the effects of viruses and virus-derived immune-modulating therapeutics is of great fundamental and clinical interest. Here we describe a sample preparation protocol for metabolite extraction from virus-infected tissue, in addition to liquid chromatography-mass spectrometry conditions essential for subsequent analysis. This metabolomics approach delivers highly sensitive and specific metabolite information on various biospecimens. Such an approach may be adopted to monitor biological changes in over 30 relevant metabolic pathways in response to viral infection and also viral therapeutics.

Comprehensive Isotopic Targeted Mass Spectrometry: Reliable Metabolic Flux Analysis with Broad Coverage.

Metabolic flux analysis (MFA) is highly relevant to understanding metabolic mechanisms of various biological processes. While the pace of methodology development in MFA has been rapid, a major challenge the field continues to witness is limited metabolite coverage, often restricted to a small to moderate number of well-known compounds. In addition, isotopic peaks from an enriched metabolite tend to have low abundances, which makes liquid chromatography tandem mass spectrometry (LC-MS/MS) highly useful in MFA due to its high sensitivity and specificity. Previously we have built large-scale LC-MS/MS approaches that can be routinely used for measurement of up to ∼1,900 metabolite/feature levels [Gu et al. Anal. Chem. 2015, 87, 12355-12362. Shi et al. Anal. Chem. 2019, 91, 13737-13745.]. In this study, we aim to expand our previous studies focused on metabolite level measurements to flux analysis and establish a novel comprehensive isotopic targeted mass spectrometry (CIT-MS) method for reliable MFA analysis with broad coverage. As a proof-of-principle, we have applied CIT-MS to compare the steady-state enrichment of metabolites between Myc(oncogene)-On and Myc-Off Tet21N human neuroblastoma cells cultured with U-13C6-glucose medium. CIT-MS is operationalized using multiple reaction monitoring (MRM) mode and is able to perform MFA of 310 identified metabolites (142 reliably detected, 46 kinetically profiled) selected from >35 metabolic pathways of strong biological significance. Further, we developed a novel concept of relative flux, which eliminates the requirement of absolute quantitation in traditional MFA and thus enables comparative MFA under the pseudosteady state. As a result, CIT-MS was shown to possess the advantages of broad coverage, easy implementation, fast throughput, and more importantly, high fidelity and accuracy in MFA. In principle, CIT-MS can be easily adapted to track the flux of other labeled tracers (such as 15N-tracers) in any metabolite detectable by LC-MS/MS and in various biological models (such as mice). Therefore, CIT-MS has great potential to bring new insights to both basic and clinical metabolism research.

Database-Assisted Globally Optimized Targeted Mass Spectrometry (dGOT-MS): Broad and Reliable Metabolomics Analysis with Enhanced Identification.

Targeted mass spectrometry (MS) is an important measurement approach in metabolomics with strong analytical performance, given its specificity, sensitivity, and quantitative capacity. However, traditional targeted-MS relies heavily on chemical standards for the development of various detection panels; thus, its metabolite coverage is often limited to those well-known and commercially available compounds. To address this fundamental gap, we previously developed a novel approach [ H. Gu et al. Anal. Chem. 2015 , 87 , 12355 - 12362 ], globally optimized targeted (GOT)-MS, which enables reliable metabolic analysis with broad coverage using a single triple quadrupole instrument. In the present study, we further developed and optimized an innovative targeted MS approach, database-assisted globally optimized targeted (dGOT)-MS, which utilizes the HMDB and METLIN databases to significantly improve both identification and metabolite coverage. As it is well-known, these metabolomics databases have a comprehensive collection of metabolites and their tandem MS spectra; therefore, in this study, multiple reaction monitoring transitions (MRMs) were directly obtained from the databases and, after optimizing MS parameters for those MRMs, 927 metabolites were measured from a plasma aqueous extract sample with high reliability by dGOT-MS. Of these, 310 were confirmed using pure chemical standards while the rest were annotated by identification level using database entries. Furthermore, using breast cancer diagnosis as a proof-of-principle metabolomics application, we showed dGOT-MS to significantly outperform a traditional large-scale targeted MS assay for potential biomarker discovery. In principle, dGOT-MS is able to cover all metabolites (including lipids) that have been characterized in these comprehensive metabolomics databases from various types of biological samples. Therefore, dGOT-MS opens a novel avenue for MS measurements and may play an important role in many future metabolomics studies.

Breast cancer detection using targeted plasma metabolomics.

Breast cancer (BC) is a major cause of human morbidity and mortality, especially among women. Despite the important role of metabolism in the molecular pathogenesis of cancer, robust metabolic markers to enable enhanced screening and disease monitoring of BC are still critically needed. In this study, a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) metabolic profiling approach is presented for the identification of metabolic marker candidates that could enable highly sensitive and specific detection of all-stage as well as early-stage BC. In this targeted approach, 105 metabolites from >35 metabolic pathways of potential biological relevance were reliably detected in 201 plasma samples taken from two groups of subjects (102 BC patients and 99 healthy controls). The results of our general linear model and partial least squares-discriminant analysis (PLS-DA) informed the construction of a novel 6-metabolite panel of potential biomarkers. A receiver operating characteristic (ROC) curve generated based on an improved PLS-DA model showed relatively high sensitivity (0.80), specificity (0.75), and area under the receiver-operating characteristic curve (AUROC = 0.89). Similar classification performance of the model was observed for detection of early-stage BC (AUROC = 0.87, sensitivity: 0.86, specificity: 0.75). Bioinformatics analyses revealed significant disturbances in arginine/proline metabolism, tryptophan metabolism, and fatty acid biosynthesis. Our univariate and multivariate results indicate the effectiveness of this metabolomics approach for all-stage as well as early-stage BC diagnosis; our bioinformatics results indicate affected pathways related to tumor growth, metastasis, and immune escape mechanisms. Future studies should validate these results using more samples from different locations.