Genomic insights into the causes of type 2 diabetes

Gut Microbiota Disorders and Metabolic Syndrome: Tales of a Crosstalk Process

The microbiota in humans consists of trillions of microorganisms that are involved in the regulation of the gastrointestinal tract and immune and metabolic homeostasis. The gut microbiota (GM) has a prominent impact on the pathogenesis of metabolic syndrome (MetS). This process is reciprocal, constituting a crosstalk process between the GM and MetS. In this review, GM directly or indirectly inducing MetS via the host-microbial metabolic axis has been systematically reviewed. Additionally, the specifically altered GM in MetS are detailed in this review. Moreover, short-chain fatty acids (SCFAs), as unique gut microbial metabolites, have a remarkable effect on MetS, and the role of SCFAs in MetS-related diseases is highlighted to supplement the gaps in this area. Finally, the existing therapeutics are outlined, and the superiority and shortcomings of different therapeutic approaches are discussed, in hopes that this review can contribute to the development of potential treatment strategies.

Association of accelerated phenotypic aging, genetic risk, and lifestyle with progression of type 2 diabetes: a prospective study using multi-state model

BACKGROUND

Aging is a major risk factor for type 2 diabetes (T2D), but individuals of the same chronological age may vary in their biological aging rate. The associations of Phenotypic Age Acceleration (PhenoAgeAccel), a new accelerated biological aging indicator based on clinical chemistry biomarkers, with the risk of dynamic progression remain unclear. We aimed to assess these associations and examine whether these associations varied by genetic risk and lifestyle.

METHODS

We conducted a prospective cohort study that included 376,083 adults free of T2D and diabetes-related events at baseline in UK Biobank. PhenoAgeAccel > 0 and ≤ 0 were defined as biologically older and younger than chronological age. The outcomes of interest were incident T2D, diabetic complications, and mortality. Hazard ratios (HRs) with 95% confidence intervals (CIs) and population attributable fractions (PAFs) for these associations were calculated using multi-state model.

RESULTS

During a median follow-up of 13.7 years, 17,615 participants developed T2D, of whom, 4,524 subsequently developed complications, and 28,373 died. Being biologically older was associated with increased risks of transitions from baseline to T2D (HR 1.77, 95% CI 1.71-1.82; PAF 24.8 [95% CI 23.5-26.2]), from T2D to diabetic complications (1.10, 1.04-1.17; 4.4 [1.4-7.4]), from baseline to all-cause death (1.53, 1.49-1.57; 17.6 [16.6-18.6]), from T2D to all-cause death (1.14, 1.03-1.26; 7.4 [1.8-13.0]), and from diabetic complications to all-cause death (1.32, 1.15-1.51; 15.4 [7.5-23.2]) than being biologically younger. Additionally, participants with older biological age and high genetic risk had a higher risk of incident T2D (4.76,4.43-5.12;18.2 [17.5-19.0]) than those with younger biological age and low genetic risk. Compared with participants with younger biological age and healthy lifestyle, those with older biological age and unhealthy lifestyle had higher risks of transitions in the T2D trajectory, with HRs and PAFs ranging from 1.34 (1.16-1.55; 3.7 [1.8-5.6]) to 5.39 (5.01-5.79; 13.0 [12.4-13.6]).

CONCLUSIONS

PhenoAgeAccel was consistently associated with an increased risk of all transitions in T2D progression. It has the potential to be combined with genetic risk to identify early T2D incidence risk and may guide interventions throughout T2D progression while tracking their effectiveness.

Associations Between TCF7L2, PPARγ, and KCNJ11 Genotypes and Insulin Response to an Oral Glucose Tolerance Test: A Systematic Review

SCOPE

Insulin responses to standardized meals differ between individuals. This variability may in part be explained by genotype. This systematic review evaluates associations between genotype and insulin response to an oral glucose tolerance test (OGTT) in terms of insulin area under the curve (AUC).

METHODS AND RESULTS

Three electronic databases (Web of Science, Embase, PubMed) were searched for studies investigating associations between insulin AUC after an OGTT and single nucleotide polymorphisms (SNPs) belonging to the transcription factor 7 like 2 (TCF7L2) gene, the peroxisome proliferator-activated receptor gamma (PPARγ) gene, or the potassium inwardly rectifying channel subfamily J member 11 (KCNJ11) gene in persons without diabetes. A total of 5199 articles were identified, of which 38 were included. Among them were family-based studies (9), twin studies (2), and studies with unrelated participants (27). Seventeen articles investigated TCF7L2 (7 SNPs), 14 investigated PPARγ (1 SNP), and 8 investigated KCNJ11 (5 SNPs). For all investigated SNPs, at least half of the reports indicated no statistically significant association with postprandial insulin AUC.

CONCLUSION

No evidence was found for associations between TCF7L2, PPARγ, and KCNJ11 genotypes and insulin AUC after an OGTT. Future studies should investigate the effect of genetic risk scores on postprandial insulin.

The association between chemosensitivity and the 10-year risk of type 2 diabetes in male patients with obstructive sleep apnea

PURPOSE

Obstructive sleep apnea (OSA) is associated with a variety of diseases, including type 2 diabetes (T2D). Chemosensitivity is an important component of the pathophysiological mechanisms of OSA, and it is not only elevated in patients with OSA but also in those with T2D. This study aimed to investigate the association between chemosensitivity and the risk of developing T2D in patients with OSA.

METHODS

A total of 135 male participants with OSA and without pre-existing T2D were enrolled in this study. Peripheral chemosensitivity was evaluated using the rebreathing test. Data on demographics, polysomnographic parameters, and clinical characteristics were collected. The QDiabetes-2018 risk calculator was employed to calculate the 10-year T2D risk. The association between peripheral chemosensitivity and 10-year T2D risk was examined using multivariate logistic regression.

RESULTS

A total of 64 participants had moderate-to-high 10-year risk of T2D. In the fully adjusted model, participants situated within the second and fifth quantiles of peripheral chemosensitivity levels demonstrated a higher risk of developing T2D, with OR of 4.87 (95% CI, 1.22-19.43) and 5.26 (95% CI, 1.27-21.68) respectively. However, across varying levels of peripheral chemosensitivity, no significant difference in the 10-year T2D risk was observed among different severities of OSA.

CONCLUSION

Higher peripheral chemosensitivity was associated with an increased 10-year T2D risk, as calculated using a risk calculator based on clinical variables. For outcomes that reflect a moderate-to-high 10-year risk of T2D, the severity of OSA did not significantly affect the risk, irrespective of whether patients exhibited relatively low or high chemosensitivity.

The association between parity and type 2 diabetes mellitus: a cross-sectional, community-based study

BACKGROUND

Limited published data exist on the association between parity (number of deliveries) and diabetes mellitus (DM). This study was conducted to evaluate the association between parity and type 2 DM (T2DM) among Sudanese women.

METHOD

A multistage sampling survey was conducted in four villages in the River Nile State, Sudan, between July and September 2022. The World Health Organization's three-level stepwise questionnaire was adopted to collect women's sociodemographic characteristics (age, sex, height, weight, marital status, parity, education level, occupation, detailed obstetric history, and family history of T2DM). Multivariate analyses were performed.

RESULTS

A total of 397 women were recruited. Their median (interquartile range) age was 45.0 (33.0‒55.7) years. A total of 154 women (38.8%) were nulliparous, whereas 93 (23.4%), 70 (17.6%), and 80 (20.2%) had para 1‒3, 4 or 5, and more than 5, respectively. A total of 112 (28.2%) women had T2DM. In multivariate analysis, older age (adjusted odds ratio, AOR, 1.04, 95%, confidence interval, CI, 1.02‒1.06), high parity (AOR, 1.1, 95% C, 1.01‒1.20), and a family history of DM (AOR, 3.26, 95% CI, 1.98‒5.38) were associated with T2DM. Compared with the nulliparity, para 1‒3 (AOR, 2.33; 95% CI, 1.17‒4.61), para 4 or 5 (AOR, 2.12; 95% CI, 1.04‒4.30), and para > 5 (AOR, 2.16; 95% CI, 1.09‒4.27) were at higher risk of T2DM. In women aged < 50 years, high parity (AOR, 1.22; 95% CI, 1.06‒1.44) was associated with T2DM. Compared with the nulliparous women, para 4 or 5 (AOR, 3.47; 95% CI, 1.16‒10.34) and para > 5 (AOR, 4.63; 95% CI, 1.54‒13.87) were associated with T2DM, whereas para 1‒3 was not associated with T2DM. In the women aged ≥ 50 years, parity and parity groups were not associated with T2DM.

CONCLUSION

There is a high prevalence of T2DM among Sudanese women. Parity and high parity are significant predictors of T2DM among these women in this part of Sudan.

Biomarkers of insulin sensitivity/resistance

In recent years, remarkable advancements in elucidating the intricate molecular underpinnings of type 2 diabetes mellitus (T2D) have been achieved. Insulin resistance (IR) has been unequivocally acknowledged as the driving pathogenetic mechanism of T2D, preceding disease onset by several years. Nonetheless, diagnostic tools for ascertaining IR are lacking in current clinical practice, representing a critical unmet need; use of the hyperinsulinemic-euglycemic glucose clamp, widely accepted as the gold standard method for evaluating IR at present, is cumbersome in a clinical setting. Thus, the development of well-validated, reliable, and affordable biomarkers of IR has attracted considerable attention from the research community. The biomarkers under investigation can be divided into two major categories: (1) indices or ratios, comprising parameters obtained from a basic or comprehensive metabolic panel and/or derived from anthropometric measurements, and (2) circulating molecules implicated in pathophysiological processes associated with IR. Furthermore, numerous novel biomarkers, including markers of β-cell dysfunction, radiographic quantification of excess visceral adipose tissue, T2D prediction models, certain microRNAs and metabolomic biomarkers, have also provided promising preliminary results. This narrative review aims to present current evidence pertaining to the most notable and exciting biomarkers of IR that are under rigorous evaluation.

Association study between adiponectin gene variants, serum levels and the risk of type 2 diabetes in Tunisian women: Insights from BMI stratification

Although prior studies have shown that adiponectin synthesis is genetically determined and that its levels influence susceptibility to T2D, the results in this regard have been inconsistent. This study aims, to investigate the relationship between adiponectin gene variants with the risk of developing T2D among Tunisian women and in relation to their BMI status. A cohort of 491 Tunisian T2D women and 373 non-diabetic subjects participated in the study. Nine ADIPOQ variants namely rs16861194, rs17300539, rs266729, rs822395, rs822396, rs2241766, rs1501299, rs2241767 and rs3774261 were selected and genotyped using the TaqMan® SNP genotyping assay. Fasting serum adiponectin levels were quantified using ELISA. The results showed that only the rs17300539 variant exhibited a significant association with the risk of T2D. However, upon considering T2D group stratification based on BMI (normal weight [18-24.99 Kg/m2], overweight [25-29.99 Kg/m2] and obese [30-34.99 Kg/m2]), the ADIPOQ rs2241766 variant emerged as a contributing risk factor for increased BMI in obese women with T2D. Linear regression analysis revealed that the minor allele (A), (GA) and (AA) genotypes of rs17300539 as well as the (G) allele and (GG) genotype of rs2241766 were significantly associated with hypoadiponectinemia in T2D subjects. Two haplotypes namely GGCAATGAA and AGCCGTGGA, were identified as conferring a higher risk of T2D with the GGCAATGAA haplotype also correlating with hypoadiponectinemia. Our study underscores the importance of the rs17300539 variant and the GGCAATGAA haplotype in the risk of T2D and hypoadiponectinemia. Additionally, the presence of the rs2241766 variant highlights its association with 'diabesity' and hypoadiponectinemia among Tunisian T2D women.

Mass spectrometry for metabolomics analysis: Applications in neonatal and cancer screening

Chemical analysis by analytical instrumentation has played a major role in disease diagnosis, which is a necessary step for disease treatment. While the treatment process often targets specific organs or compounds, the diagnostic step can occur through various means, including physical or chemical examination. Chemically, the genome may be evaluated to give information about potential genetic outcomes, the transcriptome to provide information about expression actively occurring, the proteome to offer insight on functions causing metabolite expression, or the metabolome to provide a picture of both past and ongoing physiological function in the body. Mass spectrometry (MS) has been elevated among other analytical instrumentation because it can be used to evaluate all four biological machineries of the body. In addition, MS provides enhanced sensitivity, selectivity, versatility, and speed for rapid turnaround time, qualities that are important for instance in clinical procedures involving the diagnosis of a pediatric patient in intensive care or a cancer patient undergoing surgery. In this review, we provide a summary of the use of MS to evaluate biomarkers for newborn screening and cancer diagnosis. As many reviews have recently appeared focusing on MS methods and instrumentation for metabolite analysis, we sought to describe the biological basis for many metabolomic and additional omics biomarkers used in newborn screening and how tandem MS methods have recently been applied, in comparison to traditional methods. Similar comparison is done for cancer screening, with emphasis on emerging MS approaches that allow biological fluids, tissues, and breath to be analyzed for the presence of diagnostic metabolites yielding insight for treatment options based on the understanding of prior and current physiological functions of the body.

Body mass index stratification optimizes polygenic prediction of type 2 diabetes in cross-biobank analyses

Type 2 diabetes (T2D) shows heterogeneous body mass index (BMI) sensitivity. Here, we performed stratification based on BMI to optimize predictions for BMI-related diseases. We obtained BMI-stratified datasets using data from more than 195,000 individuals (nT2D = 55,284) from BioBank Japan (BBJ) and UK Biobank. T2D heritability in the low-BMI group was greater than that in the high-BMI group. Polygenic predictions of T2D toward low-BMI targets had pseudo-R2 values that were more than 22% higher than BMI-unstratified targets. Polygenic risk scores (PRSs) from low-BMI discovery outperformed PRSs from high BMI, while PRSs from BMI-unstratified discovery performed best. Pathway-specific PRSs demonstrated the biological contributions of pathogenic pathways. Low-BMI T2D cases showed higher rates of neuropathy and retinopathy. Combining BMI stratification and a method integrating cross-population effects, T2D predictions showed greater than 37% improvements over unstratified-matched-population prediction. We replicated findings in the Tohoku Medical Megabank (n = 26,000) and the second BBJ cohort (n = 33,096). Our findings suggest that target stratification based on existing traits can improve the polygenic prediction of heterogeneous diseases.

Polygenic Risk for Type 2 Diabetes in African Americans

African Americans (AAs) have been underrepresented in polygenic risk score (PRS) studies. Here, we integrated genome-wide data from multiple observational studies on type 2 diabetes (T2D), encompassing a total of 101,987 AAs, to train and optimize an AA-focused T2D PRS (PRSAA), using a Bayesian polygenic modeling method. We further tested the score in three independent studies with a total of 7,275 AAs and compared the PRSAA with other published scores. Results show that a 1-SD increase in the PRSAA was associated with 40-60% increase in the odds of T2D (odds ratio [OR] 1.60, 95% CI 1.37-1.88; OR 1.40, 95% CI 1.16-1.70; and OR 1.45, 95% CI 1.30-1.62) across three testing cohorts. These models captured 1.0-2.6% of the variance (R2) in T2D on the liability scale. The positive predictive values for three calculated score thresholds (the top 2%, 5%, and 10%) ranged from 14 to 35%. The PRSAA, in general, performed similarly to existing T2D PRS. The need remains for larger data sets to continue to evaluate the utility of within-ancestry scores in the AA population.

ARTICLE HIGHLIGHTS

Danish Diabetes Birth Registry 2: a study protocol of a national prospective cohort study to monitor outcomes of pregnancies of women with pre-existing diabetes

INTRODUCTION

Despite technological developments and intensified care, pregnancies in women with pre-existing diabetes are still considered high-risk pregnancies. The rate of adverse outcomes in pregnancies affected by diabetes in Denmark is currently unknown, and there is a limited understanding of mechanisms contributing to this elevated risk. To address these gaps, the Danish Diabetes Birth Registry 2 (DDBR2) was established. The aims of this registry are to evaluate maternal and fetal-neonatal outcomes based on 5 years cohort data, and to identify pathophysiology and risk factors associated with short-term and long-term outcomes of pregnancies in women with pre-existing diabetes.

METHODS AND ANALYSIS

The DDBR2 registry is a nationwide 5-year prospective cohort with an inclusion period from February 2023 to February 2028 of pregnancies in women with all types of pre-existing diabetes and includes registry, clinical and questionnaire data and biological samples of mother-partner-child trios. Eligible families (parents age ≥18 years and sufficient proficiency in Danish or English) can participate by either (1) basic level data obtained from medical records (mother and child) and questionnaires (partner) or (2) basic level data and additional data which includes questionnaires (mother and partner) and blood samples (all). The primary maternal outcome is Hemoglobin A1c (HbA1c) levels at the end of pregnancy and the primary offspring endpoint is the birth weight SD score. The DDBR2 registry will be complemented by genetic, epigenetic and metabolomic data as well as a biobank for future research, and the cohort will be followed through data from national databases to illuminate possible mechanisms that link maternal diabetes and other parental factors to a possible increased risk of adverse long-term child outcomes.

ETHICS AND DISSEMINATION

Approval from the Ethical Committee is obtained (S-20220039). Findings will be sought published in international scientific journals and shared among the participating hospitals and policymakers.

TRIAL REGISTRATION NUMBER

NCT05678543.

Identification of a Novel Mitochondrial tRNA Mutation in Chinese Family with Type 2 Diabetes Mellitus

Background

Mutations in mitochondrial tRNA (mt-tRNA) could be the origin of some type 2 diabetes mellitus (T2DM) cases, but the mechanism remained largely unknown.

Aim

The aim of this study was to assess the impact of a novel mitochondrial tRNACys/tRNATyr A5826G mutation on the development and progression of T2DM.

Methods

A four-generation Han Chinese family with maternally inherited diabetes underwent clinical, genetic and biochemical analyses. The mitochondrial DNA (mtDNA) mutations of three matrilineal relatives were screened by PCR-Sanger sequencing. Furthermore, to see whether m.A5826G mutations affected mitochondrial functions, the cybrid cell lines were derived from three subjects with m.A5826G mutation and three controls without this mutation. ATP was evaluated by luminescent cell viability assay, mitochondrial membrane potential (MMP), and reactive oxygen species (ROS) were determined by flow cytometry. The student's two-tailed, unpaired t-test was used to assess the statistical significance between the control and mutant results.

Results

The age at onset of diabetes in this pedigree varied from 40 to 63 years, with an average of 54 years. Mutational analysis of mitochondrial genomes revealed the presence of a novel m.A5826G mutation. Interestingly, the m.A5826G mutation occurred at the conjunction between tRNACys and tRNATyr, a very conserved position that was critical for tRNAs processing and functions. Using trans-mitochondrial cybrid cells, we found that mutant cells carrying the m.A5826G showed approximately 36.5% and 22.4% reductions in ATP and MMP, respectively. By contrast, mitochondrial ROS levels increased approximately 33.3%, as compared with the wild type cells.

Conclusion

A novel m.A5826G mutation was identified in a pedigree with T2DM, and this mutation would lead to mitochondrial dysfunction. Thus, the genetic spectrum of mitochondrial diabetes was expanded by including m.A5826G mutation in tRNACys/tRNATyr, our study provided novel insight into the molecular pathogenesis, early diagnosis, prevention and clinical treatment for mitochondrial diabetes.

Dual active pyrimidine-based carbocyclic nucleoside derivatives: synthesis, and in silico and in vitro anti-diabetic and anti-microbial studies

Diabetes mellitus (DM) is a chronic metabolic disorder marked by high blood glucose levels, impairing glucose production in the body. Its prevalence has steadily risen over the past decades, leading to compromised immunity and heightened susceptibility to microbial infections. Immune dysfunction associated with diabetes raises vulnerability, while neuropathy dulls sensation in the extremities, reducing injury awareness. Hence, the development of novel chemical compounds for anti-diabetic and anti-infective treatments is imperative to mitigate adverse effects. In this study, we designed and synthesized pyrimidine-based carbocyclic nucleoside derivatives with C-4 substitution to assess their potential in inhibiting α-glucosidase for managing diabetes mellitus (DM) and microbial infections. Compounds 8b and 10a displayed promising IC50 values against α-glucosidase (43.292 nmol and 48.638 nmol, respectively) and noteworthy docking energies (-9.4 kcal mol-1 and -10.3 kcal mol-1, respectively). Additionally, compounds 10a and 10b exhibited better antimicrobial activity against Bacillus cereus, with the zone of inhibition values of 2.2 ± 0.25 mm and 1.4 ± 0.1 mm at a 100 μl concentration, respectively. Compound 10a also exhibited a modest zone of inhibition of 1.2 ± 0.15 mm against Escherichia coli at 100 μl.

Postprandial glucose variability and clusters of sex hormones, liver enzymes, and cardiometabolic factors in a South African cohort of African ancestry

INTRODUCTION

This study aimed to, first, determine the clusters of sex hormones, liver enzymes, and cardiometabolic factors associated with postprandial glucose (PPG) and, second to evaluate the variation these clusters account for jointly and independently with polygenic risk scores (PRSs) in South Africans of African ancestry men and women.

RESEARCH DESIGN AND METHODS

PPG was calculated as the integrated area under the curve for glucose during the oral glucose tolerance test (OGTT) using the trapezoidal rule in 794 participants from the Middle-aged Soweto Cohort. Principal component analysis was used to cluster sex hormones, liver enzymes, and cardiometabolic factors, stratified by sex. Multivariable linear regression was used to assess the proportion of variance in PPG accounted for by principal components (PCs) and type 2 diabetes (T2D) PRS while adjusting for selected covariates in men and women.

RESULTS

The T2D PRS did not contribute to the PPG variability in both men and women. In men, the PCs' cluster of sex hormones, liver enzymes, and cardiometabolic explained 10.6% of the variance in PPG, with PC1 (peripheral fat), PC2 (liver enzymes and steroid hormones), and PC3 (lipids and peripheral fat) contributing significantly to PPG. In women, PC factors of sex hormones, cardiometabolic factors, and liver enzymes explained a similar amount of the variance in PPG (10.8%), with PC1 (central fat) and PC2 (lipids and liver enzymes) contributing significantly to PPG.

CONCLUSIONS

We demonstrated that inter-individual differences in PPG responses to an OGTT may be differentially explained by body fat distribution, serum lipids, liver enzymes, and steroid hormones in men and women.

Differences in gut microbiota between Dutch and South-Asian Surinamese: potential implications for type 2 diabetes mellitus

Gut microbiota, or the collection of diverse microorganisms in a specific ecological niche, are known to significantly impact human health. Decreased gut microbiota production of short-chain fatty acids (SCFAs) has been implicated in type 2 diabetes mellitus (T2DM) disease progression. Most microbiome studies focus on ethnic majorities. This study aims to understand how the microbiome differs between an ethnic majority (the Dutch) and minority (the South-Asian Surinamese (SAS)) group with a lower and higher prevalence of T2DM, respectively. Microbiome data from the Healthy Life in an Urban Setting (HELIUS) cohort were used. Two age- and gender-matched groups were compared: the Dutch (n = 41) and SAS (n = 43). Microbial community compositions were generated via DADA2. Metrics of microbial diversity and similarity between groups were computed. Biomarker analyses were performed to determine discriminating taxa. Bacterial co-occurrence networks were constructed to examine ecological patterns. A tight microbiota cluster was observed in the Dutch women, which overlapped with some of the SAS microbiota. The Dutch gut contained a more interconnected microbial ecology, whereas the SAS network was dispersed, i.e., contained fewer inter-taxonomic correlational relationships. Bacteroides caccae, Butyricicoccus, Alistipes putredinis, Coprococcus comes, Odoribacter splanchnicus, and Lachnospira were enriched in the Dutch gut. Haemophilus, Bifidobacterium, and Anaerostipes hadrus discriminated the SAS gut. All but Lachnospira and certain strains of Haemophilus are known to produce SCFAs. The Dutch gut microbiome was distinguished from the SAS by diverse, differentially abundant SCFA-producing taxa with significant cooperation. The dynamic ecology observed in the Dutch was not detected in the SAS. Among several potential gut microbial biomarkers, Haemophilus parainfluenzae likely best characterizes the ethnic minority group, which is more predisposed to T2DM. The higher prevalence of T2DM in the SAS may be associated with the gut dysbiosis observed.

Association between alcohol consumption and latent fasting blood glucose trajectories among midlife women

Background

This investigation sought to elucidate the correlations between alcohol intake and trajectories of fasting blood glucose (FBG) among American women in midlife.

Methods

Our analysis was rooted in the foundational data from the Study of Women's Health Across the Nation (SWAN), a comprehensive longitudinal study centered on US women during their midlife transition. We employed group-based trajectory modeling to chart the FBG trajectories spanning from 1996 to 2005. Employing logistic regression, we gauged the odds ratios (ORs) and 95% confidence intervals (CIs) to draw connections between initial alcohol consumption and FBG trajectory patterns, whilst controlling for predominant potential confounders.

Results

Our cohort comprised 2,578 women in midlife, ranging in age from 42 to 52, each having a minimum of three subsequent FPG assessments. We discerned two distinct FBG trajectories: a low-stable pattern (n = 2,467) and a high-decreasing pattern (n = 111). Contrasted with the low-stable group, our data showcased an inverse relationship between alcohol intake and the high-decreasing FBG trajectory in the fully adjusted model 3. The most pronounced reduction was evident in the highest tertile of daily servings of alcoholic beverages (OR: 0.23, 95% CI: 0.10-0.52, p < 0.001), percentage of kilocalories sourced from alcoholic beverages (OR: 0.30, 95% CI: 0.16-0.58, p < 0.001), and daily caloric intake from alcoholic beverages (OR: 0.31, 95% CI: 0.16-0.62, p < 0.001).

Conclusion

Moderate alcohol consumption may protect against high FPG trajectories in middle-aged women in a dose-response manner. Further researches are needed to investigate this causality in midlife women.

Frequency of Adding Salt to Foods, Genetic Susceptibility, and Incident Type 2 Diabetes: A Prospective Cohort Study

CONTEXT

Excessive salt consumption is known to increase the risk of hypertension and cardiovascular disease, but the association between salt intake and incident type 2 diabetes has not been extensively researched.

OBJECTIVE

In this study, we aimed to investigate the relationships between the frequency of adding salt to foods and incident type 2 diabetes, as well as any potential interactions with genetic predisposition.

METHODS

We included 368 137 eligible participants, aged 37 to 73 years, from the UK Biobank. The frequency of adding salt to foods was assessed via a food frequency questionnaire.

RESULTS

During a median follow-up of 12.6 years, we documented 10 981 incident type 2 diabetes cases. After adjustment for major confounders, participants who sometimes, usually, and always added salt to foods had 7% (hazard ratio [HR]: 1.07; 95% CI, 1.03-1.12), 9% (HR: 1.09; 95% CI, 1.03-1.16), 28% (HR: 1.28; 95% CI, 1.19-1.38) higher risks of developing type 2 diabetes, respectively, than those that never/rarely added salt to foods (P for trend < .001). We found these associations to be consistent across stratified and sensitivity analyses. However, we did not observe any statistically significant multiplicative or additive interactions between the frequency of adding salt to foods and genetic predisposition regarding incident type 2 diabetes.

CONCLUSION

Our findings suggest that consuming salt regularly, regardless of genetic susceptibility, may increase the risk of type 2 diabetes. Therefore, public health interventions aimed at reducing excessive salt consumption may help prevent the onset of type 2 diabetes.

The first exome wide association study in Tunisia: identification of candidate loci and pathways with biological relevance for type 2 diabetes

Introduction

Type 2 diabetes (T2D) is a multifactorial disease involving genetic and environmental components. Several genome-wide association studies (GWAS) have been conducted to decipher potential genetic aberrations promoting the onset of this metabolic disorder. These GWAS have identified over 400 associated variants, mostly in the intronic or intergenic regions. Recently, a growing number of exome genotyping or exome sequencing experiments have identified coding variants associated with T2D. Such studies were mainly conducted in European populations, and the few candidate-gene replication studies in North African populations revealed inconsistent results. In the present study, we aimed to discover the coding genetic etiology of T2D in the Tunisian population.

Methods

We carried out a pilot Exome Wide Association Study (EWAS) on 50 Tunisian individuals. Single variant analysis was performed as implemented in PLINK on potentially deleterious coding variants. Subsequently, we applied gene-based and gene-set analyses using MAGMA software to identify genes and pathways associated with T2D. Potential signals were further replicated in an existing large in-silico dataset, involving up to 177116 European individuals.

Results

Our analysis revealed, for the first time, promising associations between T2D and variations in MYORG gene, implicated in the skeletal muscle fiber development. Gene-set analysis identified two candidate pathways having nominal associations with T2D in our study samples, namely the positive regulation of neuron apoptotic process and the regulation of mucus secretion. These two pathways are implicated in the neurogenerative alterations and in the inflammatory mechanisms of metabolic diseases. In addition, replication analysis revealed nominal associations of the regulation of beta-cell development and the regulation of peptidase activity pathways with T2D, both in the Tunisian subjects and in the European in-silico dataset.

Conclusions

The present study is the first EWAS to investigate the impact of single genetic variants and their aggregate effects on T2D risk in Africa. The promising disease markers, revealed by our pilot EWAS, will promote the understanding of the T2D pathophysiology in North Africa as well as the discovery of potential treatments.

Interaction between the GCKR rs1260326 variant and serum HDL cholesterol contributes to HOMA-β and ISIMatusda in the middle-aged T2D individuals

This study aims to investigate the correlations between islet function/ insulin resistance and serum lipid levels, as well as to assess whether the strength of such correlations is affected by the GCKR rs1260326 variant in healthy and T2D individuals. We performed an oral glucose tolerance test (OGTT) on 4889 middle-aged adults, including 3135 healthy and 1754 T2D individuals from the REACTION population study in the Nanjing region. We also measured their serum lipid levels and genotyped for rs1260326. We found that serum high-density lipoprotein (HDL) cholesterol and triglyceride (TG) levels were independently correlated with indexes of islet function (HOMA-β and IGI [insulinogenic index]) and insulin resistance (HOMO-IR and ISIMatsuda) in both healthy and T2D individuals. The correlations were significantly decreased in T2D individuals, with significant heterogeneities compared to healthy controls (I2 > 75%, Phet < 0.05). Although no correlation was observed between serum total cholesterol (TC) level and islet function/ insulin resistance in healthy controls, significant correlations were found in T2D individuals, with significant heterogeneity to healthy controls in the correlation with ISIMatsuda(I2 = 85.3%, Phet = 0.009). Furthermore, we found significant interactions of the GCKR rs1260326 variant for the correlations between serum HDL cholesterol and HOMA-β/ISIMatsuda in T2D subjects (P = 0.015 and 0.038, respectively). These findings illustrate that distinct correlations between serum lipid levels and islet function/ insulin resistance occurred in T2D subjects compared to healthy individuals. Common gene variants, such as rs1260326, might interact substantially when studied in specific populations, especially T2D disease status.

Genetic variants associated with weight loss and metabolic outcomes after bariatric surgery: A systematic review

The extent to which genetic variations contribute to interindividual differences in weight loss and metabolic outcomes after bariatric surgery is unknown. Identifying genetic variants that impact surgery outcomes may contribute to clinical decision making. This review evaluates current evidence addressing the association of genetic variants with weight loss and changes in metabolic parameters after bariatric surgery. A search was conducted using Medline, Embase, Scopus, Web of Science, and Cochrane Library. Fifty-two eligible studies were identified. Single nucleotide polymorphisms (SNPs) at ADIPOQ (rs226729, rs1501299, rs3774261, and rs17300539) showed a positive association with postoperative change in measures of glucose homeostasis and lipid profiles (n = 4), but not with weight loss after surgery (n = 6). SNPs at FTO (rs11075986, rs16952482, rs8050136, rs9939609, rs9930506, and rs16945088) (n = 10) and MC4R (rs11152213, rs476828, rs2229616, rs9947255, rs17773430, rs5282087, and rs17782313) (n = 9) were inconsistently associated with weight loss and metabolic improvement. Four studies examining the UCP2 SNP rs660339 reported associations with postsurgical weight loss. In summary, there is limited evidence supporting a role for specific genetic variants in surgical outcomes after bariatric surgery. Most studies have adopted a candidate gene approach, limiting the scope for discovery, suggesting that the absence of compelling evidence is not evidence of absence.

Emerging therapeutic options in the management of diabetes: recent trends, challenges and future directions

Diabetes is a serious health issue that causes a progressive dysregulation of carbohydrate metabolism due to insufficient insulin hormone, leading to consistently high blood glucose levels. According to the epidemiological data, the prevalence of diabetes has been increasing globally, affecting millions of individuals. It is a long-term condition that increases the risk of various diseases caused by damage to small and large blood vessels. There are two main subtypes of diabetes: type 1 and type 2, with type 2 being the most prevalent. Genetic and molecular studies have identified several genetic variants and metabolic pathways that contribute to the development and progression of diabetes. Current treatments include gene therapy, stem cell therapy, statin therapy, and other drugs. Moreover, recent advancements in therapeutics have also focused on developing novel drugs targeting these pathways, including incretin mimetics, SGLT2 inhibitors, and GLP-1 receptor agonists, which have shown promising results in improving glycemic control and reducing the risk of complications. However, these treatments are often expensive, inaccessible to patients in underdeveloped countries, and can have severe side effects. Peptides, such as glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1), are being explored as a potential therapy for diabetes. These peptides are postprandial glucose-dependent pancreatic beta-cell insulin secretagogues and have received much attention as a possible treatment option. Despite these advances, diabetes remains a major health challenge, and further research is needed to develop effective treatments and prevent its complications. This review covers various aspects of diabetes, including epidemiology, genetic and molecular basis, and recent advancements in therapeutics including herbal and synthetic peptides.

High-frequency variants in PKA signaling-related genes within a large pediatric cohort with obesity or metabolic abnormalities

Introduction

Pediatric obesity has steadily increased in recent decades. Large-scale genome-wide association studies (GWAS) conducted primarily in Eurocentric adult populations have identified approximately 100 loci that predispose to obesity and type II diabetes. GWAS in children and individuals of non-European descent, both disproportionately affected by obesity, are fewer. Rare syndromic and monogenic obesities account for only a small portion of childhood obesity, so understanding the role of other genetic variants and their combinations in heritable obesities is key to developing targeted and personalized therapies. Tight and responsive regulation of the cAMP-dependent protein kinase (PKA) signaling pathway is crucial to maintaining healthy energy metabolism, and mutations in PKA-linked genes represent the most common cause of monogenic obesity.

Methods

For this study, we performed targeted exome sequencing of 53 PKA signaling-related genes to identify variants in genomic DNA from a large, ethnically diverse cohort of obese or metabolically challenged youth.

Results

We confirmed 49 high-frequency variants, including a novel variant in the PDE11A gene (c.152C>T). Several other variants were associated with metabolic characteristics within ethnic groups.

Discussion

We conclude that a PKA pathway-specific variant search led to the identification of several new genetic associations with obesity in an ethnically diverse population.

The Interaction of Dietary Patterns and Genetic Variants on the Risk of Cardiovascular Diseases in Chinese Patients with Type 2 Diabetes

SCOPE

Diabetes is an important risk factor for cardiovascular disease (CVD), which in turn is the most common and serious complication of diabetes. This study analyzes dietary patterns and single nucleotide polymorphisms (SNPs) in 543 diabetes patients with new-onset cardiovascular events and 461 diabetic patients without.

METHODS AND RESULTS

SNPs are determined and analyzed using real time PCR and gene chip method. Factor analysis and logistic regression are used to determine dietary patterns and evaluate the level of associations and interaction effects, respectively. The legumes and edible fungi pattern and vegetable pattern show a significant negative correlation with complication risk. ADIPOQ rs37563 and legumes and edible fungi pattern have a significant interactive effect on disease, and patients with a high score of C polymorphism genotype (GC + CC) have a lower risk of disease. 5-10-Methylenetetrahydrofolate reductase (MTHFR) rs1801131 and vegetable pattern have a borderline interaction effect on disease, and those patients with TT genotype have a lower risk of disease.

CONCLUSION

These findings provide new insights into the role of the interactive protection of dietary patterns and SNPs. And participants with specific alleles show a lower risk of cardiovascular complications.

Asprosin, a novel glucogenic adipokine implicated in type 2 diabetes mellitus

Asprosin, encoded by penultimate two exons (exon 65 and exon 66) of the gene Fibrillin 1 (FBN1), has been recently discovered to be a novel hormone secreted by white adipose tissues during fasting. The glucose metabolism disorders are often accompanied by increased asprosin level. Previous research suggests that asprosin may contribute to the development of diabetes by regulating glucose homeostasis, appetite, insulin secretion, and insulin sensitivity. In this review, we summarize the recent findings from studies on asprosin and its association with Type 2 diabetes mellitus, and discusses its mechanisms from various aspects, so as to provide clinical diagnosis and treatment ideas for T2DM.

mtDNA Single-Nucleotide Variants Associated with Type 2 Diabetes

Type 2 diabetes (T2D) is a chronic systemic disease with a complex etiology, characterized by insulin resistance and mitochondrial dysfunction in various cell tissues. To explore this relationship, we conducted a secondary analysis of complete mtDNA sequences from 1261 T2D patients and 1105 control individuals. Our findings revealed significant associations between certain single-nucleotide polymorphisms (SNPs) and T2D. Notably, the variants m.1438A>G (rs2001030) (controls: 32 [27.6%], T2D: 84 [72.4%]; OR: 2.46; 95%CI: 1.64-3.78; p < 0.001), m.14766C>T (rs193302980) (controls: 498 [36.9%], T2D: 853 [63.1%]; OR: 2.57, 95%CI: 2.18-3.04, p < 0.001), and m.16519T>C (rs3937033) (controls: 363 [43.4%], T2D: 474 [56.6%]; OR: 1.24, 95%CI: 1.05-1.47, p = 0.012) were significantly associated with the likelihood of developing diabetes. The variant m.16189T>C (rs28693675), which has been previously documented in several studies across diverse populations, showed no association with T2D in our analysis (controls: 148 [13.39] T2D: 171 [13.56%]; OR: 1.03; 95%CI: 0.815-1.31; p = 0.83). These results provide evidence suggesting a link between specific mtDNA polymorphisms and T2D, possibly related to association rules, topological patterns, and three-dimensional conformations associated with regions where changes occur, rather than specific point mutations in the sequence.

An early prediction model for type 2 diabetes mellitus based on genetic variants and nongenetic risk factors in a Han Chinese cohort

Aims

We aimed to construct a prediction model of type 2 diabetes mellitus (T2DM) in a Han Chinese cohort using a genetic risk score (GRS) and a nongenetic risk score (NGRS).

Methods

A total of 297 Han Chinese subjects who were free from type 2 diabetes mellitus were selected from the Tianjin Medical University Chronic Disease Cohort for a prospective cohort study. Clinical characteristics were collected at baseline and subsequently tracked for a duration of 9 years. Genome-wide association studies (GWASs) were performed for T2DM-related phenotypes. The GRS was constructed using 13 T2DM-related quantitative trait single nucleotide polymorphisms (SNPs) loci derived from GWASs, and NGRS was calculated from 4 biochemical indicators of independent risk that screened by multifactorial Cox regressions.

Results

We found that HOMA-IR, uric acid, and low HDL were independent risk factors for T2DM (HR >1; P<0.05), and the NGRS model was created using these three nongenetic risk factors, with an area under the ROC curve (AUC) of 0.678; high fasting glucose (FPG >5 mmol/L) was a key risk factor for T2DM (HR = 7.174, P< 0.001), and its addition to the NGRS model caused a significant improvement in AUC (from 0.678 to 0.764). By adding 13 SNPs associated with T2DM to the GRS prediction model, the AUC increased to 0.892. The final combined prediction model was created by taking the arithmetic sum of the two models, which had an AUC of 0.908, a sensitivity of 0.845, and a specificity of 0.839.

Conclusions

We constructed a comprehensive prediction model for type 2 diabetes out of a Han Chinese cohort. Along with independent risk factors, GRS is a crucial element to predicting the risk of type 2 diabetes mellitus.

Gene-environment interactions in the associations of PFAS exposure with insulin sensitivity and beta-cell function in a Faroese cohort followed from birth to adulthood

BACKGROUND

Exposure to perfluoroalkyl substances (PFAS) has been associated with changes in insulin sensitivity and pancreatic beta-cell function in humans. Genetic predisposition to diabetes may modify these associations; however, this hypothesis has not been yet studied.

OBJECTIVES

To evaluate genetic heterogeneity as a modifier in the PFAS association with insulin sensitivity and pancreatic beta-cell function, using a targeted gene-environment (GxE) approach.

METHODS

We studied 85 single-nucleotide polymorphisms (SNPs) associated with type 2 diabetes, in 665 Faroese adults born in 1986-1987. Perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) were measured in cord whole blood at birth and in participants' serum from age 28 years. We calculated the Matsuda-insulin sensitivity index (ISI) and the insulinogenic index (IGI) based on a 2 h-oral glucose tolerance test performed at age 28. Effect modification was evaluated in linear regression models adjusted for cross-product terms (PFAS*SNP) and important covariates.

RESULTS

Prenatal and adult PFOS exposures were significantly associated with decreased insulin sensitivity and increased beta-cell function. PFOA associations were in the same direction but attenuated compared to PFOS. A total of 58 SNPs were associated with at least one PFAS exposure variable and/or Matsuda-ISI or IGI in the Faroese population and were subsequently tested as modifiers in the PFAS-clinical outcome associations. Eighteen SNPs showed interaction p-values (PGxE) < 0.05 in at least one PFAS-clinical outcome association, five of which passed False Discovery Rate (FDR) correction (PGxE-FDR<0.20). SNPs for which we found stronger evidence for GxE interactions included ABCA1 rs3890182, FTO rs9939609, FTO rs3751812, PPARG rs170036314 and SLC12A3 rs2289116 and were more clearly shown to modify the PFAS associations with insulin sensitivity, rather than with beta-cell function.

DISCUSSION

Findings from this study suggest that PFAS-associated changes in insulin sensitivity could vary between individuals as a result of genetic predisposition and warrant replication in independent larger populations.

Gene-environment interaction in long-term effects of polychlorinated biphenyls exposure on glucose homeostasis and type 2 diabetes: The modifying effects of genetic risk and lifestyle

The longitudinal relationships of polychlorinated biphenyls (PCBs) exposure with glucose homeostasis and type 2 diabetes (T2D) risk among Chinese population have not been assessed, and interactions of PCB exposure with genetic susceptibility and lifestyle are unclear. In this prospective cohort study, fasting plasma glucose (FPG) and insulin (FPI) and seven serum indicator-PCBs were measured for each participant. We constructed polygenic risk score (PRS) of T2D and healthy lifestyle score. Each 1-unit increment of ln-transformed PCB-118 was related with a 0.141 mmol/L, 11.410 pmol/L, 0.661, and 74.5% increase in FPG, FPI, homeostasis model assessment of insulin resistance, and incident T2D risk over 6 years, respectively. Each 1-unit increment in T2D-PRS was related with a 0.169 mmol/L elevation of FPG and 65.5% elevation of incident T2D risk during 6 years. Compared with participants who had low T2D-PRS and low PCB-118, participants with high T2D-PRS and high PCB-118 showed a significant increase in FPG (0.162 mmol/L; P for interaction <0.001) and incident T2D risk [hazard ratio (HR)= 2.222]. Participants with low PCB-118, low PRS, and healthy lifestyle had the lowest incident T2D risk (HR=0.232). Our findings highlighted the significance of reducing PCB exposure and improvement in lifestyle for T2D prevention and management, especially for individuals with higher genetic risk of T2D.

Association between serum S100A11 levels and glucose metabolism in diabetic process

BACKGROUND

Diabetes mellitus (DM) is a prevalent non-communicable metabolic disease, and S100A11 is a newly identified gene closely related to metabolism. The association of S100A11 with diabetes is unclear. This study aimed to assess the relationship between S100A11 and markers of glucose metabolism in patients with different glucose tolerance and gender.

METHODS

This study included 97 participants. Baseline data were obtained, and the serum levels of S100A11 and metabolic markers (glycated hemoglobin [HbA1c], insulin release test, and oral glucose tolerance test) were measured. Linear and nonlinear correlations between serum S100A11 levels and HOMA-IR, HOMA of β, HbA1c, insulin sensitivity index (ISI), corrected insulin response (CIR), and oral disposition index (DIo) were analyzed. The expression of S100A11 was also detected in mice.

RESULTS

Serum S100A11 levels increased in patients with impaired glucose tolerance (IGT) of both genders. S100A11 mRNA and protein expression increased in obese mice. There were nonlinear correlations between S10011 levels and CIR, FPI, HOMA-IR, whole-body ISI in the IGT group. S100A11 was nonlinearly correlated with HOMA-IR, hepatic ISI, FPG, FPI, and HbA1c in the DM group. In the male group, S100A11 was linearly correlated with HOMA-IR and nonlinearly correlated with DIo (derived from hepatic ISI) and HbA1c. In the female population, S100A11 was nonlinearly correlated with CIR.

CONCLUSIONS

Serum S100A11 levels were highly expressed in patients with IGT and in the liver of obese mice. In addition, there were linear and nonlinear correlations between S100A11 and markers of glucose metabolism, demonstrating that S100A11 has a role in diabetes. Trial registration ChiCTR1900026990.

Molecular Genetics of Abnormal Redox Homeostasis in Type 2 Diabetes Mellitus

Numerous studies have shown that oxidative stress resulting from an imbalance between the production of free radicals and their neutralization by antioxidant enzymes is one of the major pathological disorders underlying the development and progression of type 2 diabetes (T2D). The present review summarizes the current state of the art advances in understanding the role of abnormal redox homeostasis in the molecular mechanisms of T2D and provides comprehensive information on the characteristics and biological functions of antioxidant and oxidative enzymes, as well as discusses genetic studies conducted so far in order to investigate the contribution of polymorphisms in genes encoding redox state-regulating enzymes to the disease pathogenesis.

Tuberous Sclerosis, Type II Diabetes Mellitus and the PI3K/AKT/mTOR Signaling Pathways-Case Report and Literature Review

Tuberous sclerosis complex (TSC) is a rare autosomal dominant neurocutaneous syndrome. It is manifested mainly in cutaneous lesions, epilepsy and the emergence of hamartomas in several tissues and organs. The disease sets in due to mutations in two tumor suppressor genes: TSC1 and TSC2. The authors present the case of a 33-year-old female patient registered with the Bihor County Regional Center of Medical Genetics (RCMG) since 2021 with a TSC diagnosis. She was diagnosed with epilepsy at eight months old. At 18 years old she was diagnosed with tuberous sclerosis and was referred to the neurology department. Since 2013 she has been registered with the department for diabetes and nutritional diseases with a type 2 diabetes mellitus (T2DM) diagnosis. The clinical examination revealed: growth delay, obesity, facial angiofibromas, sebaceous adenomas, depigmented macules, papillomatous tumorlets in the thorax (bilateral) and neck, periungual fibroma in both lower limbs, frequent convulsive seizures; on a biological level, high glycemia and glycated hemoglobin levels. Brain MRI displayed a distinctive TS aspect with five bilateral hamartomatous subependymal nodules associating cortical/subcortical tubers with the frontal, temporal and occipital distribution. Molecular diagnosis showed a pathogenic variant in the TSC1 gene, exon 13, c.1270A>T (p. Arg424*). Current treatment targets diabetes (Metformin, Gliclazide and the GLP-1 analog semaglutide) and epilepsy (Carbamazepine and Clonazepam). This case report presents a rare association between type 2 diabetes mellitus and Tuberous Sclerosis Complex. We suggest that the diabetes medication Metformin may have positive effects on both the progression of the tumor associated with TSC and the seizures specific to TSC and we assume that the association of TSC and T2DM in the presented cases is accidental, as there are no similar cases reported in the literature.

The impact of family history of type 2 diabetes on clinical heterogeneity in idiopathic type 1 diabetes

AIM

To investigate the impact of family history of type 2 diabetes (T2D) on the clinical phenotypes of patients with idiopathic type 1 diabetes (T1D).

METHODS

In clinically diagnosed T1D cases, a total of 335 idopathic T1D patients were included in the study, after excluding autoimmune T1D using islet autoantibody testing and monogenic diabetes using a custom monogenic diabetes gene panel obtained from clinically diagnosed T1D cases. A semi-structured questionnaire was used to collect information on the presence of T2D in first-degree relatives. The demographic and metabolic markers of idiopathic T1D patients were analysed. Subgroup analysis was performed to investigate potential interactions between T2D family history and human leukocyte antigen (HLA) genotypes.

RESULTS

A total of 18.2% of individuals with idiopathic T1D had a T2D family history, and these individuals were more likely to have features associated with T2D, such as older age of onset, higher body mass index at diagnosis, lower insulin dosage and better beta-cell function, as indicated by higher levels of fasting C-peptide and 2-hour postprandial C-peptide (all P < 0.05). Additionally, regardless of HLA susceptible genotypes, the impact of family history of T2D was consistently observed in idiopathic T1D patients. Multivariable analyses showed that T2D family history was negatively correlated with the risk of beta-cell function failure in idiopathic T1D patients (P < 0.05).

CONCLUSIONS

Family history of T2D may be implicated in the heterogeneity of idiopathic T1D patients.

Genetic Variants of SIRT1 Gene Promoter in Type 2 Diabetes

Type 2 diabetes (T2D) is a highly heterogeneous and polygenic disease. To date, genetic causes and underlying mechanisms for T2D remain unclear. SIRT1, one member of highly conserved NAD-dependent class III deacetylases, has been implicated in many human diseases. Accumulating evidence indicates that SIRT1 is involved in insulin resistance and impaired pancreatic β-cell function, the two hallmarks of T2D. Thus, we speculated that altered SIRT1 levels, resulting from the genetic variants within its regulatory region of SIRT1 gene, may contribute to the T2D development. In this study, the SIRT1 gene promoter was genetically analyzed in T2D patients (n = 218) and healthy controls (n = 358). A total of 20 genetic variants, including 7 single-nucleotide polymorphisms (SNPs), were identified. Five heterozygous genetic variants (g.4114-15InsA, g.4801G > A, g.4816G > C, g.4934G > T, and g.4963_64Ins17bp) and one SNP (g.4198A > C (rs35706870)) were identified in T2D patients, but in none of the controls. The frequencies of two SNPs (g.4540A > G (rs3740051) (OR: 1.75, 95% CI: 1.24-2.47, P < 0.001 in dominant genetic model) and g.4821G > T (rs35995735)) (OR: 3.58, 95% CI: 1.94-6.60, P < 0.001 in dominant genetic model) were significantly higher in T2D patients. Further association and haplotype analyses confirmed that these two SNPs were strongly linked, contributing to the T2D (OR: 1.442, 95% CI: 1.080-1.927, P < 0.05). Moreover, most of the genetic variants identified in T2D were disease-specific. Taken together, the genetic variants within SIRT1 gene promoter might contribute to the T2D development by altering SIRT1 levels. Underlying molecular mechanism needs to be further explored.

Damaging missense variants in IGF1R implicate a role for IGF-1 resistance in the etiology of type 2 diabetes

Type 2 diabetes (T2D) is a heritable metabolic disorder. While population studies have identified hundreds of common genetic variants associated with T2D, the role of rare (frequency < 0.1%) protein-coding variation is less clear. We performed exome sequence analysis in 418,436 (n = 32,374 T2D cases) individuals in the UK Biobank. We identified previously reported genes (GCK, GIGYF1, HNF1A) in addition to missense variants in ZEB2 (n = 31 carriers; odds ratio [OR] = 5.5 [95% confidence interval = 2.5-12.0]; p = 6.4 × 10-7), MLXIPL (n = 245; OR = 2.3 [1.6-3.2]; p = 3.2 × 10-7), and IGF1R (n = 394; OR = 2.4 [1.8-3.2]; p = 1.3 × 10-10). Carriers of damaging missense variants within IGF1R were also shorter (-2.2 cm [-1.8 to -2.7]; p = 1.2 × 10-19) and had higher circulating insulin-like growth factor-1 (IGF-1) protein levels (2.3 nmol/L [1.7-2.9]; p = 2.8 × 10-14), indicating relative IGF-1 resistance. A likely causal role of IGF-1 resistance was supported by Mendelian randomization analyses using common variants. These results increase understanding of the genetic architecture of T2D and highlight the growth hormone/IGF-1 axis as a potential therapeutic target.

Epigenetics and genetics of hepatoblastoma: Linkage and treatment

Hepatoblastoma is a malignant embryonal tumor with multiple differentiation modes and is the clearest liver malignancy in children. However, little is known about genetic and epigenetic events in Hepatoblastoma. Increased research has recently demonstrated, unique genetic and epigenetic events in Hepatoblastoma, providing insights into its origin and precise treatment. Some genetic disorders and congenital factors are associated with the risk of Hepatoblastoma development, such as the Beckwith-Wiedemann syndrome, Familial Adenomatous polyposis, and Hemihypertrophy. Epigenetic modifications such as DNA modifications, histone modifications, and non-coding RNA regulation are also essential in the development of Hepatoblastoma. Herein, we reviewed genetic and epigenetic events in Hepatoblastoma, focusing on the relationship between these events and cancer susceptibility, tumor growth, and prognosis. By deciphering the genetic and epigenetic associations in Hepatoblastoma, tumor pathogenesis can be clarified, and guide the development of new anti-cancer drugs and prevention strategies.

Ambient air pollution, lifestyle, and genetic predisposition associated with type 2 diabetes: findings from a national prospective cohort study

BACKGROUND

The combined effects of ambient air pollution, lifestyle, and genetic predisposition on incident Type 2 Diabetes (T2D) have not been well documented.

METHODS

A total of 263,733 participants without T2D at baseline were identified from the UK Biobank. Annual concentrations of five air pollutants were estimated using Land Use Regression, while a healthy lifestyle score (HLS) was constructed using 7 major lifestyle factors, and polygenic risk score (PRS) was generated using 73 genetic variants. Cox regression was used to determine the association between air pollution and incident T2D for different HLS/PRS categories. Potential HLS/PRS interactions and population attributable fraction (PAF) were also examined.

RESULTS

During a median follow-up of 11.94 years, 7827 (2.97 %) incident T2D cases were identified. Association between air pollution and incident T2D was stronger among those with higher HLS/PRS in a dose-response fashion. In addition, synergistic interactions between lifestyles and air pollution were observed. Lifestyle was the leading risk factor of T2D with a weighted PAF of 25.54 % (95 % CI: 19.22 %, 27.77 %) for intermediate HLS and 24.24 % (18.24 %, 26.36 %) due to unhealthy HLS. Overall, we estimated that about 25 % of T2D cases could be attributable to air pollution and associated interactions.

CONCLUSIONS

Associations between air pollution and T2D were stronger among individuals with unhealthier lifestyle on an additive interaction scale. Public health interventions that address both reduction of exposure to high levels of air pollution in addition to lifestyle changes may have more benefit on reducing T2D risk than focusing on lifestyle changes alone.

Role of potential bioactive metabolites from traditional Chinese medicine for type 2 diabetes mellitus: An overview

Type 2 diabetes mellitus (T2DM) is a metabolic disease with persistent hyperglycemia primarily caused by insulin resistance (IR). The number of diabetic patients globally has been rising over the past decades. Although significant progress has been made in treating diabetes mellitus (DM), existing clinical drugs for diabetes can no longer fully meet patients when they face complex and huge clinical treatment needs. As a traditional and effective medical system, traditional Chinese medicine (TCM) has a unique understanding of diabetes treatment and has developed many classic and practical prescriptions targeting DM. With modern medicine and pharmacy advancements, researchers have discovered that various bioactive metabolites isolated from TCM show therapeutic on DM. Compared with existing clinical drugs, these bioactive metabolites demonstrate promising prospects for treating DM due to their excellent biocompatibility and fewer adverse reactions. Accordingly, these valuable metabolites have attracted the interest of researchers worldwide. Despite the abundance of research works and specialized-topic reviews published over the past years, there is a lack of updated and systematic reviews concerning this fast-growing field. Therefore, in this review, we summarized the bioactive metabolites derived from TCM with the potential treatment of T2DM by searching several authoritative databases such as PubMed, Web of Science, Wiley Online Library, and Springer Link. For the convenience of readers, the content is divided into four parts according to the structural characteristics of these valuable compounds (flavonoids, terpenoids, alkaloids, and others). Meanwhile, the detailed mechanism and future directions of these promising compounds curing DM are also summarized in the related sections. We hope this review inspires increasingly valuable and significant research focusing on potential bioactive metabolites from TCM to treat DM in the future.

Organokines, Sarcopenia, and Metabolic Repercussions: The Vicious Cycle and the Interplay with Exercise

Sarcopenia is a disease that becomes more prevalent as the population ages, since it is directly linked to the process of senility, which courses with muscle atrophy and loss of muscle strength. Over time, sarcopenia is linked to obesity, being known as sarcopenic obesity, and leads to other metabolic changes. At the molecular level, organokines act on different tissues and can improve or harm sarcopenia. It all depends on their production process, which is associated with factors such as physical exercise, the aging process, and metabolic diseases. Because of the seriousness of these repercussions, the aim of this literature review is to conduct a review on the relationship between organokines, sarcopenia, diabetes, and other metabolic repercussions, as well the role of physical exercise. To build this review, PubMed-Medline, Embase, and COCHRANE databases were searched, and only studies written in English were included. It was observed that myokines, adipokines, hepatokines, and osteokines had direct impacts on the pathophysiology of sarcopenia and its metabolic repercussions. Therefore, knowing how organokines act is very important to know their impacts on age, disease prevention, and how they can be related to the prevention of muscle loss.

Diabetes precision medicine: plenty of potential, pitfalls and perils but not yet ready for prime time

Rapid advances in technology and data science have the potential to improve the precision of preventive and therapeutic interventions, and enable the right treatment to be recommended, at the right time, to the right person. There are well-described examples of successful precision medicine approaches for monogenic conditions such as specific diets for phenylketonuria, and sulfonylurea treatments for certain types of MODY. However, the majority of chronic diseases are polygenic, and it is unlikely that the research strategies used for monogenic diseases will deliver similar changes to practice for polygenic traits. Type 2 diabetes, for example, is a multifactorial, heterogeneous, polygenic palette of metabolic disorders. In this non-systematic review I highlight limitations of the evidence, and the challenges that need to be overcome prior to implementation of precision medicine in the prevention and management of type 2 diabetes. Most precision medicine approaches are spuriously precise, overly complex and too narrowly focused on predicting blood glucose levels with a limited set of characteristics of individuals rather than the whole person and their context. Overall, the evidence to date is insufficient to justify widespread implementation of precision medicine approaches into routine clinical practice for type 2 diabetes. We need to retain a degree of humility and healthy scepticism when evaluating novel strategies, and to demand that existing evidence thresholds are exceeded prior to implementation.

Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiology

Mendelian randomization (MR) harnesses genetic variants as instrumental variables (IVs) to study the causal effect of exposure on outcome using summary statistics from genome-wide association studies. Classic MR assumptions are violated when IVs are associated with unmeasured confounders, i.e., when correlated horizontal pleiotropy (CHP) arises. Such confounders could be a shared gene or inter-connected pathways underlying exposure and outcome. We propose MR-CUE (MR with Correlated horizontal pleiotropy Unraveling shared Etiology and confounding), for estimating causal effect while identifying IVs with CHP and accounting for estimation uncertainty. For those IVs, we map their cis-associated genes and enriched pathways to inform shared genetic etiology underlying exposure and outcome. We apply MR-CUE to study the effects of interleukin 6 on multiple traits/diseases and identify several S100 genes involved in shared genetic etiology. We assess the effects of multiple exposures on type 2 diabetes across European and East Asian populations.

Galectin-1 in Obesity and Type 2 Diabetes

Galectin-1 is a carbohydrate-binding protein expressed in many tissues. In recent years, increasing evidence has emerged for the role of galectin-1 in obesity, insulin resistance and type 2 diabetes. Galectin-1 has been highly conserved through evolution and is involved in key cellular functions such as tissue maturation and homeostasis. It has been shown that galectin-1 increases in obesity, both in the circulation and in the adipose tissue of human and animal models. Several proteomic studies have independently identified an increased galectin-1 expression in the adipose tissue in obesity and in insulin resistance. Large population-based cohorts have demonstrated associations for circulating galectin-1 and markers of insulin resistance and incident type 2 diabetes. Furthermore, galectin-1 is associated with key metabolic pathways including glucose and lipid metabolism, as well as insulin signalling and inflammation. Intervention studies in animal models alter animal weight and metabolic profile. Several studies have also linked galectin-1 to the progression of complications in diabetes, including kidney disease and retinopathy. Here, we review the current knowledge on the clinical potential of galectin-1 in obesity and type 2 diabetes.

The genetics of bipolar disorder with obesity and type 2 diabetes

BACKGROUND

Bipolar disorder (BD) presents with high obesity and type 2 diabetes (T2D) and pathophysiological and phenomenological abnormalities shared with cardiometabolic disorders. Genomic studies may help define if they share genetic liability. This selective review of BD with obesity and T2D will focus on genomic studies, stress their current limitations and guide future steps in developing the field.

METHODS

We searched electronic databases (PubMed, Scopus) until December 2021 to identify genome-wide association studies, polygenic risk score analyses, and functional genomics of BD accounting for body mass index (BMI), obesity, or T2D.

RESULTS

The first genome-wide association studies (GWAS) of BD accounting for obesity found a promising genome-wide association in an intronic gene variant of TCF7L2 that was further replicated. Polygenic risk scores of obesity and T2D have also been associated with BD, yet, no genetic correlations have been demonstrated. Finally, human-induced stem cell studies of the intronic variant in TCF7L2 show a potential biological impact of the products of this genetic variant in BD risk.

LIMITATIONS

The narrative nature of this review.

CONCLUSIONS

Findings from BD GWAS accounting for obesity and their functional testing, have prompted potential biological insights. Yet, BD, obesity, and T2D display high phenotypic, genetic, and population-related heterogeneity, limiting our ability to detect genetic associations. Further studies should refine cardiometabolic phenotypes, test gene-environmental interactions and add population diversity.

Uncovering the extensive trade-off between adaptive evolution and disease susceptibility

Favored mutations in the human genome may make the carriers adapt to changing environments and lifestyles but also susceptible to specific diseases. The scale and details of the trade-off between adaptive evolution and disease susceptibility are unclear because most favored mutations in different populations remain unidentified. As no statistical test can discriminate favored mutations from nearby hitchhiking neutral ones, we report a deep-learning network (DeepFavored) to integrate multiple statistical tests and divide identifying favored mutations into two subtasks. We identify favored mutations in three human populations and analyzed the correlation between favored/hitchhiking mutations and genome-wide association study (GWAS) sites. Both favored and hitchhiking neutral mutations are enriched in GWAS sites with population-specific features, and the enrichment and population specificity are prominent in genes in specific Gene Ontology (GO) terms. These provide evidence for extensive and population-specific trade-offs between adaptive evolution and disease susceptibility. The unveiled scale helps understand and investigate differences and diseases of humans.

Current Understanding on the Genetic Basis of Key Metabolic Disorders: A Review

Simple Summary

Metabolic disorders (MD) are a challenge to healthcare systems; the emergence of the modern socio-economic system has led to a profound change in lifestyles in terms of dietary habits, exercise regimens, and behavior, all of which complement the genetic factors associated with MD. Diabetes Mellitus and Familial hypercholesterolemia are two of the 14 most widely researched MD, as they pose the greatest challenge to the public healthcare system and have an impact on productivity and the economy. Research findings have led to the development of new therapeutic molecules for the mitigation of MD as well as the invention of experimental strategies, which target the genes themselves via gene editing and RNA interference. Although these approaches may herald the emergence of a new toolbox to treat MD, the current therapeutic approaches still heavily depend on substrate reduction, dietary restrictions based on genetic factors, exercise, and the maintenance of good mental health. The development of orphan drugs for the less common MD such as Krabbe, Farber, Fabry, and Gaucher diseases, remains in its infancy, owing to the lack of investment in research and development, and this has driven the development of personalized therapeutics based on gene silencing and related technologies.

Abstract

Advances in data acquisition via high resolution genomic, transcriptomic, proteomic and metabolomic platforms have driven the discovery of the underlying factors associated with metabolic disorders (MD) and led to interventions that target the underlying genetic causes as well as lifestyle changes and dietary regulation. The review focuses on fourteen of the most widely studied inherited MD, which are familial hypercholesterolemia, Gaucher disease, Hunter syndrome, Krabbe disease, Maple syrup urine disease, Metachromatic leukodystrophy, Mitochondrial encephalopathy lactic acidosis stroke-like episodes (MELAS), Niemann-Pick disease, Phenylketonuria (PKU), Porphyria, Tay-Sachs disease, Wilson’s disease, Familial hypertriglyceridemia (F-HTG) and Galactosemia based on genome wide association studies, epigenetic factors, transcript regulation, post-translational genetic modifications and biomarker discovery through metabolomic studies. We will delve into the current approaches being undertaken to analyze metadata using bioinformatic approaches and the emerging interventions using genome editing platforms as applied to animal models.

PROTAC degraders as chemical probes for studying target biology and target validation

Small molecule degraders such as PROTACs (PROteolysis TArgeting Chimeras) have emerged as new promising pharmacological modalities and the first PROTAC drug candidates are now studied clinically. The catalytic properties of PROTACs, acting as chemical degraders of a protein of interest (POI), represent an attractive new strategy for drug development. The development and characterization of PROTACs requires an array of additional assay systems that track the degradation pathway leading ultimately to degradation of the POI, identifying critical steps for PROTAC optimization. In addition to their exciting translational potential, PROTACs represent versatile chemical tools that considerably expanded our chemical biology toolbox and significantly enlarged the proteome that can be modulated by small molecules. Similar to conventional chemical probes, PROTACs used as chemical probes in target validation require comprehensive characterization. As a consequence, PROTAC-specific quality criteria should be defined by the chemical biology community. These criteria need to comprise additional or alternative parameters compared to those for conventional occupancy-driven chemical probes, such as the maximum level of target degradation (D_max), confirmation of a proteasome dependent degradation mechanism and, importantly, also kinetic parameters of POI degradation. The kinetic aspects are particularly relevant for PROTACs that harbor covalent binding moieties. Here, we review recent progress in the development of assay systems for PROTAC characterization and suggest a set of criteria for PROTACs as high quality chemical probes.

Type 2 diabetes is more closely associated with risk of colorectal cancer based on elevated DNA methylation levels of ADCY5

Type 2 diabetes mellitus (T2DM) has an increased risk of cancer. In the present study, the relationship between T2DM and 13 types of cancer was analyzed and key methylation genes were searched. First, DNA methylation and mRNA expression were obtained data for T2DM and 13 types of cancer from The Cancer Genome Atlas and Gene Expression Omnibus. The t-test was used to screen the differentially methylated expression overlapping genes (DE-MGs) in T2DM and cancer on both methylation and expression levels. DE-MGs are weighted based on the methylation and projected into the human protein interaction network. The correlation between T2DM and each type of cancer was analyzed, and key genes were identified. The results showed that 293 DE-MGs were related to T2DM and 3307 were related to cancer. The network found that T2DM is more related to colorectal cancer (CRC) compare with the other 12 types of cancer. A total of 5 from 8 candidate genes were associated with CRC. A total of 28 clinical patients were used to validate these 5 genes. A CRC tissue sample was collected from each patient, as well as a paracancerous sample that served as a control. A total of 56 tissue samples were divided into 4 groups: control group, T2DM group, CRC group and T2DM with CRC group (combination group). Compared with the control group, the methylation level of adenylate cyclase 5 (ADCY5), neuregulin 1 and ELAV-like RNA-binding protein 4 in the combination group was significantly upregulated, and the mRNA level was significantly downregulated. Furthermore, based on the methylation level of ADCY5, the correlation coefficient between the combination group and the T2DM group was greater than that of the CRC group. In conclusion, T2DM is most likely to be associated with CRC among 13 common types of cancer based on methylation characteristics. An upregulated methylation of ADCY5 in T2DM may have a higher risk of CRC.

Epigenetics of type 2 diabetes mellitus and weight change - a tool for precision medicine?

Pioneering studies performed over the past few decades demonstrate links between epigenetics and type 2 diabetes mellitus (T2DM), the metabolic disorder with the most rapidly increasing prevalence in the world. Importantly, these studies identified epigenetic modifications, including altered DNA methylation, in pancreatic islets, adipose tissue, skeletal muscle and the liver from individuals with T2DM. As non-genetic factors that affect the risk of T2DM, such as obesity, unhealthy diet, physical inactivity, ageing and the intrauterine environment, have been associated with epigenetic modifications in healthy individuals, epigenetics probably also contributes to T2DM development. In addition, genetic factors associated with T2DM and obesity affect the epigenome in human tissues. Notably, causal mediation analyses found DNA methylation to be a potential mediator of genetic associations with metabolic traits and disease. In the past few years, translational studies have identified blood-based epigenetic markers that might be further developed and used for precision medicine to help patients with T2DM receive optimal therapy and to identify patients at risk of complications. This Review focuses on epigenetic mechanisms in the development of T2DM and the regulation of body weight in humans, with a special focus on precision medicine.

Genetics and Epigenetics in Personalized Nutrition: Evidence, Expectations and Experiences

With the presentation of the blueprint of the first human genome in 2001 and the advent of technologies for high-throughput genetic analysis, personalized nutrition (PN) became a new scientific field and the first commercial offerings of genotype-based nutrition advice emerged at the same time. Here, we summarize the state of evidence for the effect of genetic and epigenetic factors in the development of obesity, the metabolic syndrome and resulting illnesses such as non-insulin-dependent diabetes mellitus and cardiovascular diseases. We also critically value the concepts of PN that were built around the new genetic avenue from both the academic and a commercial perspective and their effectiveness in causing sustained changes in diet, lifestyle and for improving health. Despite almost 20 years of research and commercial direct-to-consumer offerings, evidence for the success of gene-based dietary recommendations is still generally lacking. This calls for new concepts of future PN solutions that incorporate more phenotypic measures and provide a panel of instruments (e.g., self- and bio-monitoring tools, feedback systems, algorithms based on artificial intelligence) that increases compliance based on the individual´s physical and social environment and value system. This article is protected by copyright. All rights reserved.

mGWAS-Explorer: Linking SNPs, Genes, Metabolites, and Diseases for Functional Insights

Tens of thousands of single-nucleotide polymorphisms (SNPs) have been identified to be significantly associated with metabolite abundance in over 65 genome-wide association studies with metabolomics (mGWAS) to date. Obtaining mechanistic or functional insights from these associations for translational applications has become a key research area in the mGWAS community. Here, we introduce mGWAS-Explorer, a user-friendly web-based platform to help connect SNPs, metabolites, genes, and their known disease associations via powerful network visual analytics. The application of the mGWAS-Explorer was demonstrated using a COVID-19 and a type 2 diabetes case studies.