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Genetics and Epigenetics of Metabolic Diseases
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Genetics and Epigenetics of Metabolic Diseases

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Molecular Genetics and Genomics".

Deadline for manuscript submissions: 20 April 2025 | Viewed by 4026

Special Issue Editors

Prof. Dr. Eron Manusov

E-Mail Website
Guest Editor
School of Medicine, University of Texas Rio Grande Valley, Brownsville, TX, USA
Interests: GxE; social determinants of health; NAFLD; depression; transcriptomics; aging
Dr. Vincent P. Diego

E-Mail Website
Guest Editor
School of Medicine, University of Texas Rio Grande Valley, Brownsville, TX, USA
Interests: statistical genetics; SDOH; GxE; Mexican American joint interaction model; metabolic syndrome; aging
Prof. Dr. Sarah Williams-Blangero

E-Mail Website
Guest Editor
School of Medicine, University of Texas Rio Grande Valley, Brownsville, TX, USA
Interests: epidemiology; diabetes, obesity and cardiovascular disease; infectious diseases; genetic management

Special Issue Information

Dear Colleagues,

Metabolic diseases, characterized by dysregulation of metabolic processes, represent a significant global health burden. While genetic predisposition plays a crucial role in the etiology of these disorders, recent advancements in epigenetics, proteomics, and metabolomics have unveiled the intricate interplay between genetic and environmental factors in disease development. Understanding the multifaceted interactions among genes, the environment, proteins, and metabolites, holds promise for unraveling the complexity of metabolic diseases and developing targeted interventions for precision medicine approaches.

Aim and Scope: We seek to explore how genetic variants, epigenetic modifications, protein expression patterns, and metabolite profiles collectively contribute to the pathogenesis of metabolic disease. We also aim to elucidate the dynamic interplay between genetic predisposition and environmental exposures, including diet, physical activity, and environmental toxins, in shaping metabolic health outcomes.

History: The study of genetic and epigenetic factors in metabolic diseases has evolved significantly over the past few decades, with the recent integration of proteomic and metabolomic approaches enriching our understanding of disease mechanisms. Early genetic studies have primarily focused on identifying susceptibility loci through genome-wide association studies (GWAS), while subsequent research has unveiled the importance of epigenetic modifications in regulating gene expression patterns. Concurrently, advancements in methods such as family studies and proteomic and metabolomic technologies have enabled the comprehensive profiling of protein expression and metabolite abundance, providing valuable insights into the molecular signatures of metabolic disorders and their response to environmental stimuli.

Cutting-edge Research: Cutting-edge research in this field encompasses a multidimensional approach, integrating genetics, research methods, epigenetics, proteomics, and metabolomics. Innovative methodologies, such as integrative multi-omics analysis and systems biology modeling are reshaping our understanding of the intricate networks governing metabolic homeostasis and dysfunction.

Papers We are soliciting: We invite submissions that contribute to advancing our understanding of the genomics of metabolic diseases. We are interested in methodology, bench research, clinical research, and the novel use of stem cell research. This includes original research articles, reviews, and meta-analyses covering topics such as the following:

  1. Gene–environment interactions influencing metabolic disease susceptibility and progression.
  2. Epigenetic regulation of metabolic pathways and gene expression in response to environmental cues, such as diet, stress, and pollution.
  3. Proteomic signatures associated with metabolic phenotypes and their modulation by environmental factors.
  4. Metabolomic profiling of metabolic disease biomarkers and their interaction with genetic and environmental determinants.

Through this thematic issue, we aim to foster interdisciplinary dialogue and facilitate the dissemination of state-of-the-art research findings, ultimately paving the way for personalized interventions and precision medicine strategies for metabolic diseases.

Prof. Dr. Eron Manusov
Dr. Vincent P. Diego
Prof. Dr. Sarah Williams-Blangero
Guest Editors

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. Genes 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

  • GxE
  • metabolic syndrome
  • transcriptomics
  • proteomics
  • GWAS
  • obesity
  • epigenetics
  • environment
  • lipdomics
  • stem cells

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Published Papers (4 papers)

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Research

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13 pages, 1328 KiB  
Article
Effects of Gene–Lifestyle Interaction on Obesity Among Students
by Emiliya S. Egorova, Kamilla K. Aseyan, Elvina R. Bikbova, Anastasia E. Zhilina, Elena V. Valeeva and Ildus I. Ahmetov
Genes 2024, 15(12), 1506; https://doi.org/10.3390/genes15121506 - 24 Nov 2024
Viewed by 436
Abstract
Background: Obesity is a global health issue influenced primarily by genetic variants and environmental factors. This study aimed to examine the relationship between genetic and lifestyle factors and their interaction with obesity risk among university students. Methods: A total of 658 students from [...] Read more.
Background: Obesity is a global health issue influenced primarily by genetic variants and environmental factors. This study aimed to examine the relationship between genetic and lifestyle factors and their interaction with obesity risk among university students. Methods: A total of 658 students from the same university participated in this study, including 531 females (mean age (SD): 21.6 (3.9) years) and 127 males (21.9 (4.6) years). Among them, 550 were classified as normal weight or underweight (456 females and 94 males), while 108 were identified as overweight or obese (75 females and 33 males). All the participants underwent anthropometric and genetic screening and completed lifestyle and sleep quality questionnaires. Results: The polygenic risk score, based on seven genetic variants (ADCY3 rs11676272, CLOCK rs1801260, GPR61 rs41279738, FTO rs1421085, RP11-775H9.2 rs1296328, SLC22A3 rs9364554, and TFAP2B rs734597), explained 8.3% (p < 0.0001) of the variance in body mass index (BMI). On the other hand, lifestyle factors—such as meal frequency, frequency of overeating, nut consumption as a snack, eating without hunger, frequency of antibiotic use in the past year, symptoms of dysbiosis, years of physical activity, sleep duration, bedtime, ground coffee consumption frequency, and evening coffee consumption time—accounted for 7.8% (p < 0.0001) of the variance in BMI. The model based on gene–environment interactions contributed 15% (p < 0.0001) to BMI variance. Conclusions: This study revealed that individuals with a higher genetic predisposition, as defined by the seven polymorphic loci, are more susceptible to becoming overweight or obese under certain lifestyle conditions. Full article
(This article belongs to the Special Issue Genetics and Epigenetics of Metabolic Diseases)
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11 pages, 1098 KiB  
Article
Effects of ACLY Inhibition on Body Weight Distribution: A Drug Target Mendelian Randomization Study
by Dipender Gill, Marie-Joe Dib, Rubinder Gill, Stefan R. Bornstein, Stephen Burgess and Andreas L. Birkenfeld
Genes 2024, 15(8), 1059; https://doi.org/10.3390/genes15081059 - 12 Aug 2024
Viewed by 1247
Abstract
Background: Adenosine triphosphate-citrate lyase (ACLY) inhibition has proven clinically efficacious for low-density lipoprotein cholesterol (LDL-c) lowering and cardiovascular disease (CVD) risk reduction. Clinical and genetic evidence suggests that some LDL-c lowering strategies, such as 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) inhibition with statin therapy increase [...] Read more.
Background: Adenosine triphosphate-citrate lyase (ACLY) inhibition has proven clinically efficacious for low-density lipoprotein cholesterol (LDL-c) lowering and cardiovascular disease (CVD) risk reduction. Clinical and genetic evidence suggests that some LDL-c lowering strategies, such as 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) inhibition with statin therapy increase body weight and the risk of developing type 2 diabetes mellitus (T2DM). However, whether ACLY inhibition affects metabolic risk factors is currently unknown. We aimed to investigate the effects of ACLY inhibition on glycaemic and anthropometric traits using Mendelian randomization (MR). Methods: As genetic instruments for ACLY inhibition, we selected weakly correlated single-nucleotide polymorphisms at the ACLY gene associated with lower ACLY gene expression in the eQTLGen study (N = 31,684) and lower LDL-c levels in the Global Lipid Genetic Consortium study (N = 1.65 million). Two-sample Mendelian randomization was employed to investigate the effects of ACLY inhibition on T2DM risk, and glycaemic and anthropometric traits using summary data from large consortia, with sample sizes ranging from 151,013 to 806,834 individuals. Findings for genetically predicted ACLY inhibition were compared to those obtained for genetically predicted HMGCR inhibition using the same instrument selection strategy and outcome data. Results: Primary MR analyses showed that genetically predicted ACLY inhibition was associated with lower waist-to-hip ratio (β per 1 standard deviation lower LDL-c: −1.17; 95% confidence interval (CI): −1.61 to −0.73; p < 0.001) but not with risk of T2DM (odds ratio (OR) per standard deviation lower LDL-c: 0.74, 95% CI = 0.25 to 2.19, p = 0.59). In contrast, genetically predicted HMGCR inhibition was associated with higher waist-to-hip ratio (β = 0.15; 95%CI = 0.04 to 0.26; p = 0.008) and T2DM risk (OR = 1.73, 95% CI = 1.27 to 2.36, p < 0.001). The MR analyses considering secondary outcomes showed that genetically predicted ACLY inhibition was associated with a lower waist-to-hip ratio adjusted for body mass index (BMI) (β = −1.41; 95%CI = −1.81 to −1.02; p < 0.001). In contrast, genetically predicted HMGCR inhibition was associated with higher HbA1c (β = 0.19; 95%CI = 0.23 to 0.49; p < 0.001) and BMI (β = 0.36; 95%CI = 0.23 to 0.49; p < 0.001). Conclusions: Human genetic evidence supports the metabolically favourable effects of ACLY inhibition on body weight distribution, in contrast to HMGCR inhibition. These findings should be used to guide and prioritize ongoing clinical development efforts. Full article
(This article belongs to the Special Issue Genetics and Epigenetics of Metabolic Diseases)
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15 pages, 1459 KiB  
Article
Genotype-by-Environment Interactions in Nonalcoholic Fatty Liver Disease and Chronic Illness among Mexican Americans: The Role of Acculturation Stress
by Eron G. Manusov, Vincent P. Diego, Marcio Almeida, David Ortiz, Joanne E. Curran, Jacob Galan, Ana C. Leandro, Sandra Laston, John Blangero and Sarah Williams-Blangero
Genes 2024, 15(8), 1006; https://doi.org/10.3390/genes15081006 - 1 Aug 2024
Viewed by 996
Abstract
This study examines the complex interplay of genetic and environmental interactions that shape chronic illness risk. Evidence is mounting for the role of genetic expression and the immune response in the pathogenesis of chronic disease. In the Rio Grande Valley of south Texas, [...] Read more.
This study examines the complex interplay of genetic and environmental interactions that shape chronic illness risk. Evidence is mounting for the role of genetic expression and the immune response in the pathogenesis of chronic disease. In the Rio Grande Valley of south Texas, where 90% of the population is Mexican American, chronic illnesses (including obesity, diabetes, nonalcoholic liver disease, and depression) are reaching epidemic proportions. This study leverages an ongoing family study of the genetic determinants of risk for obesity, diabetes, hypertension, hyperlipidemia, and depression in a Mexican American population. Data collected included blood pressure, BMI, hepatic transaminases, HbA1c, depression (BDI-II), acculturation/marginalization (ARSMA-II), and liver health as assessed by elastography. Heritability and genotype-by-environment (G×E) interactions were analyzed, focusing on the marginalization/separation measure of the ARSMA-II. Significant heritabilities were found for traits such as HbA1c (h2 = 0.52), marginalization (h2 = 0.30), AST (h2 = 0.25), ALT (h2 = 0.41), and BMI (h2 = 0.55). Genotype-by-environment interactions were significant for HbA1c, AST/ALT ratio, BDI-II, and CAP, indicating that genetic factors interact with marginalization to influence these traits. This study found that acculturation stress exacerbates the genetic response to chronic illness. These findings underscore the importance of considering G×E interactions in understanding disease susceptibility and may inform targeted interventions for at-risk populations. Further research is warranted to elucidate the underlying molecular pathways and replicate these findings in diverse populations. Full article
(This article belongs to the Special Issue Genetics and Epigenetics of Metabolic Diseases)
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Review

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19 pages, 716 KiB  
Review
Genetic Variants of Obesity in Malaysia: A Scoping Review
by Siti Sarah Hamzah, Liyana Ahmad Zamri, Norhashimah Abu Seman and Nur Azlin Zainal Abidin
Genes 2024, 15(10), 1334; https://doi.org/10.3390/genes15101334 - 17 Oct 2024
Viewed by 958
Abstract
Background: Obesity is a pressing public health issue in Malaysia, involving not only excess weight but also complex metabolic and physiological changes. Addressing these complexities requires comprehensive strategies, including understanding the population-level differences in obesity susceptibility. This review aims to compile the genetic [...] Read more.
Background: Obesity is a pressing public health issue in Malaysia, involving not only excess weight but also complex metabolic and physiological changes. Addressing these complexities requires comprehensive strategies, including understanding the population-level differences in obesity susceptibility. This review aims to compile the genetic variants studied among Malaysians and emphasize their implications for obesity risk. Methods: Relevant articles published up to March 2024 were extracted from the Scopus, PubMed, and ScienceDirect databases. The review process was conducted in accordance with the PRISMA-ScR guidelines. From an initial pool of 579 articles, 35 of these were selected for the final review. Results: The identified gene variants, including LEPR (K656N), LEP (G2548A—Indian only), ADIPOQ (rs17366568), UCP2 (45bp-I/D), ADRB3 (rs4994), MC3R (rs3827103), PPARγ (pro12Ala—Malay only), IL1RA (intron 2 VNTR), NFKB1 (rs28362491), and FADS1 (rs174547—Indian only), showed significant associations with obesity as measured by the respective studies. Conclusions: Overall, more intensive genetic research is needed, starting with population-based profiling of genetic data on obesity, including among children. Sociocultural contexts and environmental factors influence variations in genetic elements, highlighting the need for targeted interventions to mitigate the impacts of obesity in the population. Full article
(This article belongs to the Special Issue Genetics and Epigenetics of Metabolic Diseases)
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