Integration of targeted metabolomics and transcriptomics identifies deregulation of phosphatidylcholine metabolism in Huntington’s disease peripheral blood samples

Mastrokolias, Anastasios; Pool, René; Mina, Eleni; Hettne, Kristina; Duijn, Erik van; Mast, Roos C. van der; Ommen, Gert-Jan van; Hoen, Peter A.C. ‘t; Prehn, Cornelia; Adamski, Jerzy; Roon-Mom, Willeke van

doi:10.1007/s11306-016-1084-8

Cited by 44 publications

(47 citation statements)

References 90 publications

(91 reference statements)

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“…In addition, MBOAT1, which was enriched in glycerolipid metabolism pathway, also showed higher expression in the F line. MBOAT1 has been reported to be associated with phosphatidylcholine metabolism [46] and large intestine lipid metabolism [47]. An upregulation of MBOAT1 may, thus, also be associated with differences in IMF deposition between the two lines.…”

Section: Other Pathways Contribute To Increased Imf Deposition In F Linementioning

confidence: 99%

Effect of Divergent Selection for Intramuscular Fat Content on Muscle Lipid Metabolism in Chickens

Liu

Cui

Xing

et al. 2019

Animals

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Simple Summary: Intramuscular fat is an important factor affecting meat quality and consumer acceptance. Appropriate increases in the intramuscular fat content contribute to the improvement of meat quality, and genetic selection is an effective method to increase the intramuscular fat content in chickens. In this study, chicken lines divergently selected for their intramuscular fat content were used to investigate the mechanisms behind differential intramuscular fat deposition. These results found in this study may contribute to the improvement of meat quality in chickens.Abstract: Intramuscular fat (IMF)-an important factor affecting meat quality-can be appropriately increased by genetic selection. Chicken lines divergently selected for IMF content were used in this study to investigate the mechanisms behind differential IMF deposition. Sixty 15th generation chickens were genotyped using the IASCHICK 55K single nucleotide polymorphism (SNP) chip. After quality control, 59 chickens and 36,893 SNPs were available for subsequent analysis. Population structure assessment indicated that the lines were genetically differentiated. Based on the top 1% paired fixation index values, three pathways were significantly (p < 0.05) enriched, and nine genes were considered candidate genes for differential IMF deposition. Differences between the lines in the expressions of representative genes involved in the above pathways were detected in 16th generation chickens. This study suggests that genetic selection for increased IMF in the pectoralis major muscle may enhance fatty acid synthesis, transport, and esterification, and reduce triglyceride hydrolysis. The peroxisome proliferator-activated receptor (PPAR) signaling pathway, glycerolipid metabolism, and fatty acid degradation pathway may have contributed to the differences in IMF deposition between the lines. These results contribute to the understanding of the genetic mechanisms behind IMF deposition, and the improvement of chicken meat quality.

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Section: Other Pathways Contribute To Increased Imf Deposition In F Linementioning

confidence: 99%

Effect of Divergent Selection for Intramuscular Fat Content on Muscle Lipid Metabolism in Chickens

Liu

Cui

Xing

et al. 2019

Animals

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“…CE‐MS based serum metabolome analysis was found to be useful tool for investigation of representative polar metabolites contributing to the progression of AD . The serine, threonine and phosphatidylcholine levels was determined by the flow injection electrospray ionization tandem MS and found to be changed significantly in HD, which exhibited a significant association with the disease severity of HD …”

Section: Mass Spectrometry‐based Metabolomics Research On Neurodegenementioning

confidence: 99%

“…43,44 The serine, threonine and phosphatidylcholine levels was determined by the flow injection electrospray ionization tandem MS and found to be changed significantly in HD, which exhibited a significant association with the disease severity of HD. 45 The chemical structure of trimethylamine N-oxide was validated by comparing the obtained tandem mass spectra with the spectra from reference library the distinctive smell of urine, which was linked to the significant development of Alzheimer-related problems in animal models. 46…”

Section: Blood Metabolomementioning

confidence: 99%

“…4,57,58 Gut microbiota has the ability to promote the serotonin biosynthesis and regulate bloodbrain barrier permeability for modulating the distribution and subsequent the CNS fate of serotonin. 45 The study using microbiota deficient Germ-Free mice provided a helpful insight into the effect of gut microbiota on brain. Increased plasma tryptophan concentrations and hippocampal serotonin levels were found in the Germ-Free mice from LC-MS analysis.…”

Section: Serotonin and Tryptophan Catabolitesmentioning

confidence: 99%

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Mass spectrometry‐based metabolomics: Targeting the crosstalk between gut microbiota and brain in neurodegenerative disorders

Luan

Xian

Cai

2017

Mass Spectrometry Reviews

140

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Metabolomics seeks to take a "snapshot" in a time of the levels, activities, regulation and interactions of all small molecule metabolites in response to a biological system with genetic or environmental changes. The emerging development in mass spectrometry technologies has shown promise in the discovery and quantitation of neuroactive small molecule metabolites associated with gut microbiota and brain. Significant progress has been made recently in the characterization of intermediate role of small molecule metabolites linked to neural development and neurodegenerative disorder, showing its potential in understanding the crosstalk between gut microbiota and the host brain. More evidence reveals that small molecule metabolites may play a critical role in mediating microbial effects on neurotransmission and disease development. Mass spectrometry-based metabolomics is uniquely suitable for obtaining the metabolic signals in bidirectional communication between gut microbiota and brain. In this review, we summarized major mass spectrometry technologies including liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and imaging mass spectrometry for metabolomics studies of neurodegenerative disorders. We also reviewed the recent advances in the identification of new metabolites by mass spectrometry and metabolic pathways involved in the connection of intestinal microbiota and brain. These metabolic pathways allowed the microbiota to impact the regular function of the brain, which can in turn affect the composition of microbiota via the neurotransmitter substances. The dysfunctional interaction of this crosstalk connects neurodegenerative diseases, including Parkinson's disease, Alzheimer's disease and Huntington's disease. The mass spectrometry-based metabolomics analysis provides information for targeting dysfunctional pathways of small molecule metabolites in the development of the neurodegenerative diseases, which may be valuable for the investigation of underlying mechanism of therapeutic strategies.

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“…[5][6][7][8][9] In addition, the identification, quantification and analysis of metabolic pathways using metabolomics has identified candidate biomarkers in other neurodegenerative diseases including Alzheimer's, Huntington's and Parkinson's diseases. [10][11][12] However, there is limited evidence on metabolomic abnormalities in FTLD:…”

Section: Introductionmentioning

confidence: 99%

Metabolomic changes associated with frontotemporal lobar degeneration syndromes

Murley

Jones

Gilchrist

et al. 2020

Preprint

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Objective: Widespread metabolic changes are seen in neurodegenerative disease and could be used as biomarkers for diagnosis and disease monitoring. They may also reveal disease mechanisms that could be a target for therapy. In this study we looked for blood-based biomarkers in syndromes associated with frontotemporal lobar degeneration. Methods: Plasma metabolomic profiles were measured from 134 patients with frontotemporal lobar degeneration (behavioural variant frontotemporal dementia n=30, non fluent variant primary progressive aphasia n=26, progressive supranuclear palsy n=45, corticobasal syndrome n=33) and 32 healthy controls. Results: Forty-nine of 842 metabolites were significantly altered in frontotemporal lobar degeneration (after false-discovery rate correction for multiple comparisons). These were distributed across a wide range of metabolic pathways including amino acids, energy and carbohydrate, cofactor and vitamin, lipid and nucleotide pathways. The metabolomic profile supported classification between frontotemporal lobar degeneration and controls with high accuracy (88.1-96.6%) while classification accuracy was lower between the frontotemporal lobar degeneration syndromes (72.1-83.3%). One metabolic profile, comprising a range of different pathways, was consistently identified as a feature of each disease versus controls: the degree to which a patient expressed this metabolomic profile was associated with their subsequent survival (hazard ratio 0.74 [0.59-0.93], p=0.0018). Conclusions: The metabolic changes in FTLD are promising diagnostic and prognostic biomarkers. Further work is required to replicate these findings, examine longitudinal change, and test their utility in differentiating between FTLD syndromes that are pathologically distinct but phenotypically similar.

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Integration of targeted metabolomics and transcriptomics identifies deregulation of phosphatidylcholine metabolism in Huntington’s disease peripheral blood samples

Cited by 44 publications

References 90 publications

Effect of Divergent Selection for Intramuscular Fat Content on Muscle Lipid Metabolism in Chickens

Effect of Divergent Selection for Intramuscular Fat Content on Muscle Lipid Metabolism in Chickens

Mass spectrometry‐based metabolomics: Targeting the crosstalk between gut microbiota and brain in neurodegenerative disorders

Metabolomic changes associated with frontotemporal lobar degeneration syndromes

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