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Non-invasive measurement of a metabolic marker of infant brain function.

ABSTRACT: While near-infrared spectroscopy (NIRS) haemodynamic measures have proven to be vastly useful in investigating human brain development, the haemodynamic response function (HRF) in infants is not yet fully understood. NIRS measurements of the oxidation state of mitochondrial enzyme cytochrome-c-oxidase (oxCCO) have the potential to yield key information about cellular oxygen utilisation and therefore energy metabolism. We used a broadband NIRS system to measure changes in oxCCO, in addition to haemodynamic changes, during functional activation in a group of 33 typically developing infants aged between 4 and 6 months. The responses were recorded over the right temporal lobe while the infants were presented with engaging videos containing social content. A significant increase in oxCCO was found in response to the social stimuli, with maximum increase of 0.238 ± 0.13 μM. These results are the first reported significant change in oxCCO in response to stimulus-evoked activation in human infants and open new vistas for investigating human infant brain function and its energy metabolism.

SUBMITTER: Siddiqui MF

PROVIDER: S-EPMC5430960 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Non-invasive measurement of a metabolic marker of infant brain function.

Siddiqui Maheen F MF Lloyd-Fox Sarah S Kaynezhad Pardis P Tachtsidis Ilias I Johnson Mark H MH Elwell Clare E CE

Scientific reports 20170502 1

While near-infrared spectroscopy (NIRS) haemodynamic measures have proven to be vastly useful in investigating human brain development, the haemodynamic response function (HRF) in infants is not yet fully understood. NIRS measurements of the oxidation state of mitochondrial enzyme cytochrome-c-oxidase (oxCCO) have the potential to yield key information about cellular oxygen utilisation and therefore energy metabolism. We used a broadband NIRS system to measure changes in oxCCO, in addition to ha ...[more]

PMID: 28465584

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Project description:Alzheimer's disease (AD) is an incurable neurodegenerative disorder. Early screening, particularly in blood plasma, has been demonstrated as a promising approach to the diagnosis and prevention of AD. In addition, metabolic dysfunction has been demonstrated to be closely related to AD, which might be reflected in the whole blood transcriptome. Hence, we hypothesized that the establishment of a diagnostic model based on the metabolic signatures of blood is a workable strategy. To that end, we initially constructed metabolic pathway pairwise (MPP) signatures to characterize the interplay among metabolic pathways. Then, a series of bioinformatic methodologies, e.g., differential expression analysis, functional enrichment analysis, network analysis, etc., were used to investigate the molecular mechanism behind AD. Moreover, an unsupervised clustering analysis based on the MPP signature profile via the Non-Negative Matrix Factorization (NMF) algorithm was utilized to stratify AD patients. Finally, aimed at distinguishing AD patients from non-AD groups, a metabolic pathway-pairwise scoring system (MPPSS) was established using multi-machine learning methods. As a result, many metabolic pathways correlated to AD were disclosed, including oxidative phosphorylation, fatty acid biosynthesis, etc. NMF clustering analysis divided AD patients into two subgroups (S1 and S2), which exhibit distinct activities of metabolism and immunity. Typically, oxidative phosphorylation in S2 exhibits a lower activity than that in S1 and non-AD group, suggesting the patients in S2 might possess a more compromised brain metabolism. Additionally, immune infiltration analysis showed that the patients in S2 might have phenomena of immune suppression compared with S1 and the non-AD group. These findings indicated that S2 probably has a more severe progression of AD. Finally, MPPSS could achieve an AUC of 0.73 (95%CI: 0.70, 0.77) in the training dataset, 0.71 (95%CI: 0.65, 0.77) in the testing dataset, and an AUC of 0.99 (95%CI: 0.96, 1.00) in one external validation dataset. Overall, our study successfully established a novel metabolism-based scoring system for AD diagnosis using the blood transcriptome and provided new insight into the molecular mechanism of metabolic dysfunction implicated in AD.

Project description:BackgroundIsolated limb perfusion (ILP) is a regional surgical treatment for localized metastatic disease. High doses of chemotherapeutic agents are administered within an extracorporeal circulated isolated extremity, treating the metastasis, while systemic toxicity is avoided. To our knowledge, indexed oxygen supply/demand relationship during ILP has not previously been described. Our aim was to measure and describe oxygen metabolism, specifically oxygen delivery, consumption, and extraction, in an isolated leg/arm during ILP. Also investigate whether invasive oxygenation measurement during ILP correlates and can be used interchangeable with the non-invasive method, near infrared spectroscopy (NIRS).MethodsData from 40 patients scheduled for ILP were included. At six time points blood samples were drawn during the procedure. DO2, VO2, and O2ER were calculated according to standard formulas. NIRS and hemodynamics were recorded every 10 min.ResultsFor all observations, the mean of DO2 was 190±59 ml/min/m2, VO2 was 35±8 ml/min/m2, and O2ER was 21±8%. VO2 was significantly higher in legs compared to arms (38±8 vs. 29±7 ml/min/m2, p=0.02). Repeated measures showed a significant decrease in DO2 in legs (209±65 to 180±66 ml/min/m2, p=<0.01) and in arms (252±72 to 150±57 ml/min/m2, p=<0.01). Significant increase in O2ER in arms was also found (p=0.03). Significant correlation was detected between NIRS and venous extremity oxygen saturation (SveO2) (rrm=0.568, p=<. 001, 95% CI 0.397-0.701). When comparing SveO2 and NIRS using a Bland-Altman analysis, the mean difference (bias) was 8.26±13.03 (p=<. 001) and the limit of agreement was - 17.28-33.09, with an error of 32.5%.ConclusionDO2 above 170 ml/min/m2 during ILP kept O2ER below 30% for all observations. NIRS correlates significant to SveO2; however, the two methods do not agree sufficiently to work interchangeable. Clinical Trial Registration URL: https://www.clinicaltrials.gov. Unique identifier: NCT04460053 and NCT03073304.

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Non-invasive measurement of a metabolic marker of infant brain function.

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Non-invasive measurement of a metabolic marker of infant brain function.

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