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Biomedicines
Special Issues
Genetics, Obesity, Diabetes and Metabolic Syndrome
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Genetics, Obesity, Diabetes and Metabolic Syndrome

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Endocrinology and Metabolism Research".

Deadline for manuscript submissions: 30 April 2024 | Viewed by 2385

Special Issue Editor

Dr. Guanglin Zhang

E-Mail Website
Guest Editor
Division of Life Sciences, University of California, Los Angeles, Los Angeles, CA, USA
Interests: metabolic syndrome; microbiome; next-generation sequencing; neurodegenerative diseases
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Obesity, diabetes, and metabolic syndrome are interconnected conditions that influenced by multiple factors, including genetic, environmental, and lifestyle factors. Each condition has both unique genetic components and genetic mechanisms that contribute to their development. Genetics play a significant role in determining an individual’s susceptibility to obesity and type 2 diabetes. Certain genetic variations can influence factors, such as metabolism, appetite regulation, fat storage, and insulin sensitivity.

Obesity is closely linked to the development of type 2 diabetes. Excess body fat, particularly abdominal fat, can contribute to the development of type 2 diabetes. Additionally, shared genetic factors can contribute to both obesity and insulin resistance, further connecting the two conditions. Both obesity and type 2 diabetes involve metabolic dysfunction. In obesity, there is often an imbalance between energy intake and expenditure, leading to the excess accumulation of fat and disruptions in metabolic processes. Similarly, type 2 diabetes is characterized by impaired glucose metabolism, insulin resistance, and the dysregulation of various metabolic pathways. These metabolic dysfunctions contribute to the development and progression of both conditions.

Understanding the connections among genetic factors, obesity, diabetes, and metabolic dysfunction is important for identifying individuals at higher risk, developing preventive strategies, and tailoring personalized interventions for the better management of these conditions.

This Special Issue aims to present cutting-edge research and comprehensive reviews that provide the most updated explanations of topics concerning metabolic diseases:

  1. The identification of genetic markers associated with obesity, type 2 diabetes, and metabolic dysfunction;
  2. Molecular and biochemical mechanisms underlying metabolic diseases;
  3. Novel natural approaches for the potential prevention and therapeutic strategies of obesity, diabetes, and related conditions;
  4. Multiomics used to study metabolic diseases.

Dr. Guanglin Zhang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomedicines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • obesity
  • diabetes
  • metabolic syndrome
  • metabolic diseases
  • genomics
  • multiomics
  • RNAseq
  • single-cell sequencing
  • GWAS
  • metabolomics

Published Papers (2 papers)

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17 pages, 1210 KiB  
Article
DNA Methylation Signatures in Paired Placenta and Umbilical Cord Samples: Relationship with Maternal Pregestational Body Mass Index and Offspring Metabolic Outcomes
by Ariadna Gómez-Vilarrubla, Berta Mas-Parés, Gemma Carreras-Badosa, Alexandra Bonmatí-Santané, Jose-Maria Martínez-Calcerrada, Maria Niubó-Pallàs, Francis de Zegher, Lourdes Ibáñez, Abel López-Bermejo and Judit Bassols
Biomedicines 2024, 12(2), 301; https://doi.org/10.3390/biomedicines12020301 - 27 Jan 2024
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Abstract
An epigenomic approach was used to study the impact of maternal pregestational body mass index (BMI) on the placenta and umbilical cord methylomes and their potential effect on the offspring’s metabolic phenotype. DNA methylome was assessed in 24 paired placenta and umbilical cord [...] Read more.
An epigenomic approach was used to study the impact of maternal pregestational body mass index (BMI) on the placenta and umbilical cord methylomes and their potential effect on the offspring’s metabolic phenotype. DNA methylome was assessed in 24 paired placenta and umbilical cord samples. The differentially methylated CpGs associated with maternal pregestational BMI were identified and the metabolic pathways and the potentially related diseases affected by their annotated genes were determined. Two top differentially methylated CpGs were studied in 90 additional samples and the relationship with the offspring’s metabolic phenotype was determined. The results showed that maternal pregestational BMI is associated with the methylation of genes involved in endocrine and developmental pathways with potential effects on type 2 diabetes and obesity. The methylation and expression of HADHA and SLC2A8 genes in placenta and umbilical cord were related to several metabolic parameters in the offspring at 6 years (weight SDS, height SDS, BMI SDS, Δ BW-BMI SDS, FM SDS, waist, SBP, TG, HOMA-IR, perirenal fat; all p < 0.05). Our data suggest that epigenetic analysis in placenta and umbilical cord may be useful for identifying individual vulnerability to later metabolic diseases. Full article
(This article belongs to the Special Issue Genetics, Obesity, Diabetes and Metabolic Syndrome)
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10 pages, 939 KiB  
Brief Report
Shared Genetics between Age at Menarche and Type 2 Diabetes Mellitus: Genome-Wide Genetic Correlation Study
by Yuan-Fang Cheng, Cheng-Yi Yang and Meng-Che Tsai
Biomedicines 2024, 12(1), 157; https://doi.org/10.3390/biomedicines12010157 - 11 Jan 2024
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Abstract
Background: Age at menarche (AAM) has been associated with type 2 diabetes mellitus (T2DM). However, little is known about their shared heritability. Methods: Our data comes from the Taiwan Biobank. Genome-wide association studies (GWASs) were conducted to identify single-nucleotide polymorphisms (SNPs) related to [...] Read more.
Background: Age at menarche (AAM) has been associated with type 2 diabetes mellitus (T2DM). However, little is known about their shared heritability. Methods: Our data comes from the Taiwan Biobank. Genome-wide association studies (GWASs) were conducted to identify single-nucleotide polymorphisms (SNPs) related to AAM-, T2DM-, and T2DM-related phenotypes, such as body fat percentage (BFP), fasting blood glucose (FBG), and hemoglobin A1C (HbA1C). Further, the conditional false discovery rate (cFDR) method was applied to examine the shared genetic signals. Results: Conditioning on AAM, Quantile-quantile plots showed an earlier departure from the diagonal line among SNPs associated with BFP and FBG, indicating pleiotropic enrichments among AAM and these traits. Further, the cFDR analysis found 39 independent pleiotropic loci that may underlie the AAM-T2DM association. Among them, FN3KRP rs1046896 (cFDR = 6.84 × 10−49), CDKAL1 rs2206734 (cFDR = 6.48 × 10−10), B3GNTL1 rs58431774 (cFDR = 2.95 × 10−10), G6PC2 rs1402837 (cFDR = 1.82 × 10−8), and KCNQ1 rs60808706 (cFDR = 9.49 × 10−8) were highlighted for their significant genetic enrichment. The protein–protein interaction analysis revealed a significantly enriched network among novel discovered genes that were mostly found to be involved in the insulin and glucagon signaling pathways. Conclusions: Our study highlights potential pleiotropic effects across AAM and T2DM. This may shed light on identifying the genetic causes of T2DM. Full article
(This article belongs to the Special Issue Genetics, Obesity, Diabetes and Metabolic Syndrome)
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