Biomarkers and prediction of myocardial triglyceride content in non-diabetic men

Granér, Marit; Gustavsson, Sara; Nyman, Kristofer; Sirén, Reijo; Pentikäinen, Markku O.; Lundbom, Jesper; Hakkarainen, Antti; Lauerma, Kirsi; Lundbom, Nina; Borén, Jan; Nieminen, Markku S.; Taskinen, Marja‐Riitta

doi:10.1016/j.numecd.2015.11.002

Cited by 5 publications

(3 citation statements)

References 30 publications

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“…Adiponectin, a highly expressed cytokine by the adipose tissue 20 , with known anti-atherogenic, anti-diabetic and anti-inflammatory properties 23 , showed significantly reduced serum levels among the subjects with elevated levels of measured ectopic fat depots. This is in agreement with previous obesity related studies reporting decreased serum levels of adiponectin among overweighed subjects 24 .…”

Section: Discussionmentioning

confidence: 99%

Characterization of different fat depots in NAFLD using inflammation-associated proteome, lipidome and metabolome

Lovrić

Granér

Arif

et al. 2018

Sci Rep

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Non-alcoholic fatty liver disease (NAFLD) is recognized as a liver manifestation of metabolic syndrome, accompanied with excessive fat accumulation in the liver and other vital organs. Ectopic fat accumulation was previously associated with negative effects at the systemic and local level in the human body. Thus, we aimed to identify and assess the predictive capability of novel potential metabolic biomarkers for ectopic fat depots in non-diabetic men with NAFLD, using the inflammation-associated proteome, lipidome and metabolome. Myocardial and hepatic triglycerides were measured with magnetic spectroscopy while function of left ventricle, pericardial and epicardial fat, subcutaneous and visceral adipose tissue were measured with magnetic resonance imaging. Measured ectopic fat depots were profiled and predicted using a Random Forest algorithm, and by estimating the Area Under the Receiver Operating Characteristic curves. We have identified distinct metabolic signatures of fat depots in the liver (TAG50:1, glutamate, diSM18:0 and CE20:3), pericardium (N-palmitoyl-sphinganine, HGF, diSM18:0, glutamate, and TNFSF14), epicardium (sphingomyelin, CE20:3, PC38:3 and TNFSF14), and myocardium (CE20:3, LAPTGF-β1, glutamate and glucose). Our analyses highlighted non-invasive biomarkers that accurately predict ectopic fat depots, and reflect their distinct metabolic signatures in subjects with NAFLD.

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Section: Discussionmentioning

confidence: 99%

Characterization of different fat depots in NAFLD using inflammation-associated proteome, lipidome and metabolome

Lovrić

Granér

Arif

et al. 2018

Sci Rep

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“…However, this study has also some limitations. First, other biomarkers could have been considered to predict MTGC, such as β-hydroxybutyrate, a ketone body that may be inversely associated with increased MTGC ( 76 ). Unfortunately, the retrospective design of our study made it impossible to include additional biological parameters that had not been measured in each cohort’s original study design.…”

Section: Discussionmentioning

confidence: 99%

Is increased myocardial triglyceride content associated with early changes in left ventricular function? A 1H-MRS and MRI strain study

et al. 2023

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BackgroundType 2 diabetes (T2D) and obesity induce left ventricular (LV) dysfunction. The underlying pathophysiological mechanisms remain unclear, but myocardial triglyceride content (MTGC) could be involved.ObjectivesThis study aimed to determine which clinical and biological factors are associated with increased MTGC and to establish whether MTGC is associated with early changes in LV function.MethodsA retrospective study was conducted using five previous prospective cohorts, leading to 338 subjects studied, including 208 well-phenotyped healthy volunteers and 130 subjects living with T2D and/or obesity. All the subjects underwent proton magnetic resonance spectroscopy and feature tracking cardiac magnetic resonance imaging to measure myocardial strain.ResultsMTGC content increased with age, body mass index (BMI), waist circumference, T2D, obesity, hypertension, and dyslipidemia, but the only independent correlate found in multivariate analysis was BMI (p=0.01; R²=0.20). MTGC was correlated to LV diastolic dysfunction, notably with the global peak early diastolic circumferential strain rate (r=-0.17, p=0.003), the global peak late diastolic circumferential strain rate (r=0.40, p<0.0001) and global peak late diastolic longitudinal strain rate (r=0.24, p<0.0001). MTGC was also correlated to systolic dysfunction via end-systolic volume index (r=-0.34, p<0.0001) and stroke volume index (r=-0.31, p<0.0001), but not with longitudinal strain (r=0.009, p=0.88). Interestingly, the associations between MTGC and strain measures did not persist in multivariate analysis. Furthermore, MTGC was independently associated with LV end-systolic volume index (p=0.01, R²=0.29), LV end-diastolic volume index (p=0.04, R²=0.46), and LV mass (p=0.002, R²=0.58).ConclusionsPredicting MTGC remains a challenge in routine clinical practice, as only BMI independently correlates with increased MTGC. MTGC may play a role in LV dysfunction but does not appear to be involved in the development of subclinical strain abnormalities.

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“…In animal studies, administration of butyrate and nitrate improved mitochondrial functions in liver, skeletal muscle and adipose tissue of insulin-resistant obese mice [120][121][122][123][124]. In addition, accumulating evidence suggests that gut metabolites affect lipid, glucose and cholesterol metabolism in peripheral tissues [18,22,[125][126][127][128]. Germ-free mice colonized with microbiota from obese donors show higher weight gain and total body fat than germ-free mice colonized with microbiota from lean mice [129].…”

Section: Obesity and Diabetesmentioning

confidence: 99%

The impact of gut microbiota metabolites on cellular bioenergetics and cardiometabolic health

et al. 2021

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Recent research demonstrates a reciprocal relationship between gut microbiota-derived metabolites and the host in controlling the energy homeostasis in mammals. On the one hand, to thrive, gut bacteria exploit nutrients digested by the host. On the other hand, the host utilizes numerous products of gut bacteria metabolism as a substrate for ATP production in the colon. Finally, bacterial metabolites seep from the gut into the bloodstream and interfere with the host’s cellular bioenergetics machinery. Notably, there is an association between alterations in microbiota composition and the development of metabolic diseases and their cardiovascular complications. Some metabolites, like short-chain fatty acids and trimethylamine, are considered markers of cardiometabolic health. Others, like hydrogen sulfide and nitrite, demonstrate antihypertensive properties. Scientific databases were searched for pre-clinical and clinical studies to summarize current knowledge on the role of gut microbiota metabolites in the regulation of mammalian bioenergetics and discuss their potential involvement in the development of cardiometabolic disorders. Overall, the available data demonstrates that gut bacteria products affect physiological and pathological processes controlling energy and vascular homeostasis. Thus, the modulation of microbiota-derived metabolites may represent a new approach for treating obesity, hypertension and type 2 diabetes.

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Biomarkers and prediction of myocardial triglyceride content in non-diabetic men

Abstract: Our data showed that β-OHB and fasting glucose were the best predictors of myocardial TG content in non-diabetic men. These data suggest that hyperglycemia and alterations in lipid oxidation may be associated with cardiac steatosis in humans.

Cited by 5 publications

References 30 publications

Characterization of different fat depots in NAFLD using inflammation-associated proteome, lipidome and metabolome

Characterization of different fat depots in NAFLD using inflammation-associated proteome, lipidome and metabolome

Is increased myocardial triglyceride content associated with early changes in left ventricular function? A 1H-MRS and MRI strain study

The impact of gut microbiota metabolites on cellular bioenergetics and cardiometabolic health

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