Evidence map›Paper›PMID 39731011›Full record

ReviewMolecular medicine (Cambridge, Mass.)2024

The interplay of factors in metabolic syndrome: understanding its roots and complexity.

Md Sharifull Islam, Ping Wei, Md Suzauddula, Ishatur Nime, Farahnaaz Feroz, Mrityunjoy Acharjee, Fan Pan

Abstract readReview
In one paragraph

Review in Molecular medicine (Cambridge, Mass.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 108 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
108citing papers in PubMed, 8 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

108 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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48 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Md Sharifull IslamCenter for Cancer Immunology, Institute of Biomedicine and Biotechnology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Ping WeiCenter for Cancer Immunology, Institute of Biomedicine and Biotechnology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Md SuzauddulaDepartment of Food Nutrition Dietetics and Health, Kansas State University, Manhattan, KS, 66506, USA.
Ishatur NimeKey Laboratory of Environment Correlative Dietology, College of Food Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, China.
Farahnaaz FerozDepartment of Microbiology, Stamford University Bangladesh, 51, Siddeswari Road, Dhaka, 1217, Bangladesh.
Mrityunjoy AcharjeeDepartment of Microbiology, Stamford University Bangladesh, 51, Siddeswari Road, Dhaka, 1217, Bangladesh.
Fan PanCenter for Cancer Immunology, Institute of Biomedicine and Biotechnology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China. fan.pan@siat.ac.cn.

Funding

Clinical Research Project of Shenzhen Medical Academy of Research and Translation C2301008National Key Research and Development Program of China 2022YFC2403000National Natural Science Foundation of China 32170925Shenzhen Science and Technology Program QTD20210811090115019
6 · The paper itself

Abstract

Metabolic syndrome (MetS) is an indicator and diverse endocrine syndrome that combines different metabolic defects with clinical, physiological, biochemical, and metabolic factors. Obesity, visceral adiposity and abdominal obesity, dyslipidemia, insulin resistance (IR), elevated blood pressure, endothelial dysfunction, and acute or chronic inflammation are the risk factors associated with MetS. Abdominal obesity, a hallmark of MetS, highlights dysfunctional fat tissue and increased risk for cardiovascular disease and diabetes. Insulin, a vital peptide hormone, regulates glucose metabolism throughout the body. When cells become resistant to insulin's effects, it disrupts various molecular pathways, leading to IR. This condition is linked to a range of disorders, including obesity, diabetes, fatty liver disease, cardiovascular disease, and polycystic ovary syndrome. Atherogenic dyslipidemia is characterized by three key factors: high levels of small, low-dense lipoprotein (LDL) particles and triglycerides, alongside low levels of high-density lipoprotein (HDL), the "good" cholesterol. Such a combination is a major player in MetS, where IR is a driving force. Atherogenic dyslipidemia contributes significantly to the development of atherosclerosis, which can lead to cardiovascular disease. On top of that, genetic alteration and lifestyle factors such as diet and exercise influence the complexity and progression of MetS. To enhance our understanding and consciousness, it is essential to understand the fundamental pathogenesis of MetS. This review highlights current advancements in MetS research including the involvement of gut microbiome, epigenetic regulation, and metabolomic profiling for early detection of Mets. In addition, this review emphasized the epidemiology and fundamental pathogenesis of MetS, various risk factors, and their preventive measures. The goal of this effort is to deepen understanding of MetS and encourage further research to develop effective strategies for preventing and managing complex metabolic diseases.

Indexed as

Metabolic SyndromeAnimalsDisease SusceptibilityHumansInsulin ResistanceRisk FactorsDyslipidemiaEpidemiologyInsulin resistanceMetabolic syndromeObesityPathogenesis

Identifiers

PMID39731011
PMCPMC11673706

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.