Characteristic MicroRNAs Linked to Dysregulated Metabolic Pathways in Qatari Adult Subjects With Obesity and Metabolic Syndrome

Mir, Fayaz Ahmad; Mall, Raghvendra; Iskandarani, Ahmad; Ullah, Ehsan; Samra, Tareq A.; Cyprian, Farhan S.; Parray, Aijaz; Alkasem, Meis; Abdalhakam, Ibrahem; Farooq, Faisal; Abou‐Samra, Abdul‐Badi

doi:10.3389/fendo.2022.937089

Cited by 17 publications

(13 citation statements)

References 60 publications

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“…In a previous study, sphingomyelins were found to be related to obesity measures [ 24 ]. It is suspected that in sphingolipids, the saturation level of fatty acids and the length of the carbon chain may cause insulin resistance [ 25 , 26 ]. Higher plasma sphingomyelin levels have also been found in obese people [ 24 , 27 ].…”

Section: Discussionmentioning

confidence: 99%

Dysregulated Metabolic Pathways in Subjects with Obesity and Metabolic Syndrome

Mir

Ullah

Mall

et al. 2022

IJMS

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Background: Obesity coexists with variable features of metabolic syndrome, which is associated with dysregulated metabolic pathways. We assessed potential associations between serum metabolites and features of metabolic syndrome in Arabic subjects with obesity. Methods: We analyzed a dataset of 39 subjects with obesity only (OBO, n = 18) age-matched to subjects with obesity and metabolic syndrome (OBM, n = 21). We measured 1069 serum metabolites and correlated them to clinical features. Results: A total of 83 metabolites, mostly lipids, were significantly different (p < 0.05) between the two groups. Among lipids, 22 sphingomyelins were decreased in OBM compared to OBO. Among non-lipids, quinolinate, kynurenine, and tryptophan were also decreased in OBM compared to OBO. Sphingomyelin is negatively correlated with glucose, HbA1C, insulin, and triglycerides but positively correlated with HDL, LDL, and cholesterol. Differentially enriched pathways include lysine degradation, amino sugar and nucleotide sugar metabolism, arginine and proline metabolism, fructose and mannose metabolism, and galactose metabolism. Conclusions: Metabolites and pathways associated with chronic inflammation are differentially expressed in subjects with obesity and metabolic syndrome compared to subjects with obesity but without the clinical features of metabolic syndrome.

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Section: Discussionmentioning

confidence: 99%

Dysregulated Metabolic Pathways in Subjects with Obesity and Metabolic Syndrome

Mir

Ullah

Mall

et al. 2022

IJMS

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“…We utilized the microRNA Data Integration Portal, mirDIP v4.1 ( http://ophid.utoronto.ca/mirDIP/ ), which consists of over 152 million human microRNA–target predictions collected from 30 different resources [ 30 – 32 ]. The mirDIP integrative score was constructed by taking a statistical consensus from the predictions available through myriad resources and was assigned to each unique miRNA-target interaction to provide a unified measure of confidence.…”

Section: Methodsmentioning

confidence: 99%

An integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case–control study

et al. 2023

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Objectives To examine the hypothesis that obesity complicated by the metabolic syndrome, compared to uncomplicated obesity, has distinct molecular signatures and metabolic pathways. Methods We analyzed a cohort of 39 participants with obesity that included 21 with metabolic syndrome, age-matched to 18 without metabolic complications. We measured in whole blood samples 754 human microRNAs (miRNAs), 704 metabolites using unbiased mass spectrometry metabolomics, and 25,682 transcripts, which include both protein coding genes (PCGs) as well as non-coding transcripts. We then identified differentially expressed miRNAs, PCGs, and metabolites and integrated them using databases such as mirDIP (mapping between miRNA-PCG network), Human Metabolome Database (mapping between metabolite-PCG network) and tools like MetaboAnalyst (mapping between metabolite-metabolic pathway network) to determine dysregulated metabolic pathways in obesity with metabolic complications. Results We identified 8 significantly enriched metabolic pathways comprising 8 metabolites, 25 protein coding genes and 9 microRNAs which are each differentially expressed between the subjects with obesity and those with obesity and metabolic syndrome. By performing unsupervised hierarchical clustering on the enrichment matrix of the 8 metabolic pathways, we could approximately segregate the uncomplicated obesity strata from that of obesity with metabolic syndrome. Conclusions The data suggest that at least 8 metabolic pathways, along with their various dysregulated elements, identified via our integrative bioinformatics pipeline, can potentially differentiate those with obesity from those with obesity and metabolic complications.

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“…2). In recent years, many studies have extensively explored the role of miRNAs as biomarkers for predicting IR development in populations with obesity [62][63][64][65][66][67][68][69][70][71][72][73]. The downstream miRNA targets have also been investigated [74][75][76][77][78][79][80][81][82][83][84][85].…”

Section: Mirnas: Potential Biomarkers Of Obesity-associated Irmentioning

confidence: 99%

Biomarkers of obesity-mediated insulin resistance: focus on microRNAs

Cai

Liu

et al. 2023

Diabetol Metab Syndr

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Obesity and metabolic syndromes are becoming increasingly prevalent worldwide. Insulin resistance (IR) is a common complication of obesity. However, IR occurrence varies across individuals with obesity and may involve epigenetic factors. To rationalize the allocation of healthcare resources, biomarkers for the early risk stratification of individuals with obesity should be identified. MicroRNAs (miRNAs) are closely associated with metabolic diseases and involved in epigenetic regulation. In this review, we have summarized the changes in miRNA expression in the peripheral circulation and tissues of patients and animals with obesity-associated IR over the last 5 years and identified several candidate biomarkers that predict obesity-related IR. There are areas for improvement in existing studies. First, more than the predictive validity of a single biomarker is required, and a biomarker panel needs to be formed. Second, miRNAs are often studied in isolation and do not form a network of signaling pathways. We believe that early biomarkers can help clinicians accurately predict individuals prone to obesity-related IR at an early stage. Epigenetic regulation may be one of the underlying causes of different clinical outcomes in individuals with obesity. Future studies should focus on objectively reflecting the differences in miRNA profile expression in individuals with obesity-related IR, which may help identify more reliable biomarkers. Understanding the metabolic pathways of these miRNAs can help design new metabolic risk prevention and management strategies, and support the development of drugs to treat obesity and metabolic disorders.

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Characteristic MicroRNAs Linked to Dysregulated Metabolic Pathways in Qatari Adult Subjects With Obesity and Metabolic Syndrome

Cited by 17 publications

References 60 publications

Dysregulated Metabolic Pathways in Subjects with Obesity and Metabolic Syndrome

Dysregulated Metabolic Pathways in Subjects with Obesity and Metabolic Syndrome

An integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case–control study

Biomarkers of obesity-mediated insulin resistance: focus on microRNAs

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