Gene-lifestyle interplay in type 2 diabetes

The fate of intracellular S1P regulates lipid droplet turnover and lipotoxicity in pancreatic beta-cells

Lipotoxicity has been considered the main cause of pancreatic beta-cell failure during type 2 diabetes development. Lipid droplets (LD) are believed to regulate the beta-cell sensitivity to free fatty acids (FFA), but the underlying molecular mechanisms are largely unclear. Accumulating evidence points, however, to an important role of intracellular sphingosine-1-phosphate (S1P) metabolism in lipotoxicity-mediated disturbances of beta-cell function. In the present study, we compared the effects of an increased irreversible S1P degradation (S1P-lyase, SPL overexpression) with those associated with an enhanced S1P recycling (overexpression of S1P phosphatase 1, SGPP1) on LD formation and lipotoxicity in rat INS1E beta-cells. Interestingly, although both approaches led to a reduced S1P concentration, they had opposite effects on the susceptibility to FFA. Overexpression of SGPP1 prevented FFA-mediated caspase-3 activation by a mechanism involving an enhanced lipid storage capacity and prevention of oxidative stress. In contrast, SPL overexpression limited lipid droplet biogenesis, content and size, while accelerating lipophagy. This was associated with FFA-induced hydrogen peroxide formation, mitochondrial fragmentation and dysfunction, as well as ER stress. These changes coincided with upregulation of proapoptotic ceramides, but were independent of lipid peroxidation rate. Also in human EndoC-βH1 beta-cells suppression of SPL with simultaneous overexpression of SGPP1 led to a similar and even more pronounced LD phenotype as that in INS1E-SGPP1 cells. Thus, intracellular S1P turnover significantly regulates LD content and size, and influences beta-cell sensitivity to FFA.

Associations of a multidimensional polygenic sleep health score and a sleep lifestyle index on health outcomes and their interaction in a clinical biobank

Sleep is a complex behavior regulated by genetic and environmental factors, and is known to influence health outcomes. However, the effect of multidimensional sleep encompassing several sleep dimensions on diseases has yet to be fully elucidated. Using the Mass General Brigham Biobank, we aimed to examine the association of multidimensional sleep with health outcomes and investigate whether sleep behaviors modulate genetic predisposition to unfavorable sleep on mental health outcomes. First, we generated a Polygenic Sleep Health Score using previously identified single nucleotide polymorphisms for sleep health and constructed a Sleep Lifestyle Index using data from self-reported sleep questions and electronic health records; second, we performed phenome-wide association analyses between these indexes and clinical phenotypes; and third, we analyzed the interaction between the indexes on prevalent mental health outcomes. Fifteen thousand eight hundred and eighty-four participants were included in the analysis (mean age 54.4; 58.6% female). The Polygenic Sleep Health Score was associated with the Sleep Lifestyle Index (β=0.050, 95%CI=0.032, 0.068) and with 114 disease outcomes spanning 12 disease groups, including obesity, sleep, and substance use disease outcomes (p<3.3×10-5). The Sleep Lifestyle Index was associated with 458 disease outcomes spanning 17 groups, including sleep, mood, and anxiety disease outcomes (p<5.1×10-5). No interactions were found between the indexes on prevalent mental health outcomes. These findings suggest that favorable sleep behaviors and genetic predisposition to healthy sleep may independently be protective of disease outcomes. This work provides novel insights into the role of multidimensional sleep on population health and highlights the need to develop prevention strategies focused on healthy sleep habits.

Investigating Gene-Diet Interactions Impacting the Association Between Macronutrient Intake and Glycemic Traits

Few studies have demonstrated reproducible gene-diet interactions (GDIs) impacting metabolic disease risk factors, likely due in part to measurement error in dietary intake estimation and insufficient capture of rare genetic variation. We aimed to identify GDIs across the genetic frequency spectrum impacting the macronutrient-glycemia relationship in genetically and culturally diverse cohorts. We analyzed 33,187 participants free of diabetes from 10 National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program cohorts with whole-genome sequencing, self-reported diet, and glycemic trait data. We fit cohort-specific, multivariable-adjusted linear mixed models for the effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and its interactions with common and rare variants genome-wide. In main effect meta-analyses, participants consuming more carbohydrate had modestly lower glycemic trait values (e.g., for glycated hemoglobin [HbA1c], -0.013% HbA1c/250 kcal substitution). In GDI meta-analyses, a common African ancestry-enriched variant (rs79762542) reached study-wide significance and replicated in the UK Biobank cohort, indicating a negative carbohydrate-HbA1c association among major allele homozygotes only. Simulations revealed that >150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error. These results generate hypotheses for further exploration of modifiable metabolic disease risk in additional cohorts with African ancestry.

ARTICLE HIGHLIGHTS

We aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.

Systematic review and meta-analysis of teneligliptin for treatment of type 2 diabetes

BACKGROUND AND AIM

There are efficacy and safety concerns related to teneligliptin treatment. A systematic review of randomized controlled trials (RCTs) was undertaken to comprehensively profile the efficacy and safety of teneligliptin in the treatment of type 2 diabetes mellitus (T2DM).

METHODS

Thirteen studies were chosen from a search of scientific databases for RCTs using teneligliptin as a monotherapy or as an adjunct to other glycemic agents with pre-specified inclusion criteria. We calculated weighted mean differences (WMDs) and 95% confidence intervals (CIs) in each included trial and pooled the data using a random-effects model.

RESULTS

Thirteen studies enrolled 2853 patients were identified. Teneligliptin treatment was associated with weight gain (vs. placebo, weighted mean difference (WMD) 0.28 kg; 95% CI - 0.20-0.77 kg; I² = 86%; P = 0.25). Compared to monotherapy, add on therapy with teneligliptin showed significant improvement in FPG mg/dl levels (WMD - 16.75 mg/dl; 95% CI - 19.38 to - 14.13 mg/dl), HOMA-β (WMD 7.91; 95% CI 5.38-10.45) and HOMA-IR (WMD - 0.27; 95% CI - 0.46 to - 0.07). The improvement in HbA1c was greater with monotherapy (WMD - 8.88 mmol/mol; 95% CI - 9.59 to - 8.08 mmol/mol). There was no significant risk of any hypoglycemia with teneligliptin compared to placebo (OR 0.84; 95% CI 0.44-1.60; I² = 0%; P = 0.60). However, the risk was 1.84 times high when combined with other glycemic agents. The risk of cardiovascular events was comparable, regardless of treatment duration when compared to placebo or any other active comparator (OR 0.79; 95% CI 0.40-1.57; I² = 0%; P = 0.50). [PROSPERO, CRD42022360785].

CONCLUSIONS

Teneligliptin is an effective and safe therapeutic option for patients with T2DM, both as monotherapy and as add-on therapy. However, additional large-scale, high-quality, long-term follow-up clinical trials with diverse ethnic populations are required to confirm its long-term efficacy and safety.

Exercise and inactivity as modifiers of β cell function and type 2 diabetes risk

Exercise and regular physical activity are beneficial for the prevention and management of metabolic diseases such as obesity and type 2 diabetes, whereas exercise cessation, defined as deconditioning from regular exercise or physical activity that has lasted for a period of months to years, can lead to metabolic derangements that drive disease. Adaptations to the insulin-secreting pancreatic β-cells are an important benefit of exercise, whereas less is known about how exercise cessation affects these cells. Our aim is to review the impact that exercise and exercise cessation have on β-cell function, with a focus on the evidence from studies examining glucose-stimulated insulin secretion (GSIS) using gold-standard techniques. Potential mechanisms by which the β-cell adapts to exercise, including exerkine and incretin signaling, autonomic nervous system signaling, and changes in insulin clearance, will also be explored. We will highlight areas for future research.

Does crime trigger genetic risk for type 2 diabetes in young adults? A G x E interaction study using national data

BACKGROUND

Living in neighborhoods perceived as disordered exacerbates genetic risk for type 2 diabetes (T2D) among older adults. It is unknown whether this gene-neighborhood interaction extends to younger adults. The present study aims to investigate whether crime, an objectively measured indicator of neighborhood disorder, triggers genetic risk for T2D among younger adults, and whether this hypothesized triggering occurs through exposure to obesity.

METHODS

Data were from the Wave I (2008) National Longitudinal Study of Adolescent to Adult Health. A standardized T2D polygenic score was created using 2014 GWAS meta-analysis results. Weighted mediation analyses using generalized structural equation models were conducted in a final sample of 7606 adults (age range: 25-34) to test the overall association of T2D polygenic scores with T2D, and the mediating path through obesity exposure in low, moderate, and high county crime-rate groups. Age, sex, ancestry, educational degree, household income, five genetic principal components, and county-level concentrated advantage and population density were adjusted.

RESULTS

The overall association between T2D polygenic score and T2D was not significant in low-crime areas (p = 0.453), marginally significant in moderate-crime areas (p = 0.064), and statistically significant in high-crime areas (p = 0.007). The mediating path through obesity was not significant in low or moderate crime areas (ps = 0.560 and 0.261, respectively), but was statistically significant in high-crime areas (p = 0.023). The indirect path through obesity accounted for 12% of the overall association in high-crime area.

CONCLUSION

A gene-crime interaction in T2D was observed among younger adults, and this association was partially explained by exposure to obesity.

Effect of Personalized Nutrition on Dietary, Physical Activity, and Health Outcomes: A Systematic Review of Randomized Trials

Personalized nutrition is an approach that tailors nutrition advice to individuals based on an individual’s genetic information. Despite interest among scholars, the impact of this approach on lifestyle habits and health has not been adequately explored. Hence, a systematic review of randomized trials reporting on the effects of personalized nutrition on dietary, physical activity, and health outcomes was conducted. A systematic search of seven electronic databases and a manual search resulted in identifying nine relevant trials. Cochrane’s Risk of Bias was used to determine the trials’ methodological quality. Although the trials were of moderate to high quality, the findings did not show consistent benefits of personalized nutrition in improving dietary, behavioral, or health outcomes. There was also a lack of evidence from regions other than North America and Europe or among individuals with diseases, affecting the generalizability of the results. Furthermore, the complex relationship between genes, interventions, and outcomes may also have contributed to the scarcity of positive findings. We have suggested several areas for improvement for future trials regarding personalized nutrition.

Effect of TCF7L2 on the relationship between lifestyle factors and glycemic parameters: a systematic review

Background

Among candidate genes related to type 2 diabetes (T2DM), one of the strongest genes is Transcription factor 7 like 2 (TCF7L2), regarding the Genome-Wide Association Studies. We aimed to conduct a systematic review of the literature on the modification effect of TCF7L2 on the relation between glycemic parameters and lifestyle factors.

Methods

A systematic literature search was done for relevant publications using electronic databases, including PubMed, EMBASE, Scopus, and Web of Science, from January 1, 2000, to November 2, 2021.

Results

Thirty-eight studies (16 observational studies, six meal test trials, and 16 randomized controlled trials (RCTs)) were included. Most observational studies had been conducted on participants with non-diabetes showing that TCF7L2 modified the association between diet (fatty acids and fiber) and insulin resistance. In addition, findings from meal test trials showed that, compared to non-risk-allele carriers, consumption of meals with different percentages of total dietary fat in healthy risk-allele carriers increased glucose concentrations and impaired insulin sensitivity. However, ten RCTs, with intervention periods of less than ten weeks and more than one year, showed that TCF7L2 did not modify glycemic parameters in response to a dietary intervention involving different macronutrients. However, two weight loss dietary RCTs with more than 1-year duration showed that serum glucose and insulin levels decreased and insulin resistance improved in non-risk allele subjects with overweight/obesity. Regarding artichoke extract supplementation (ALE), two RCTs observed that ALE supplementation significantly decreased insulin concentration and improved insulin resistance in the TT genotype of the rs7903146 variant of TCF7L2. In addition, four studies suggested that physical activity levels and smoking status modified the association between TCF7L2 and glycemic parameters. However, three studies observed no effect of TCF7L2 on glycemic parameters in participants with different levels of physical activity and smoking status.

Conclusion

The modification effects of TCF7L2 on the relation between the lifestyle factors (diet, physical activity, and smoking status) and glycemic parameters were contradictory.

PROSPERO registration number

CRD42020196327

Supplementary Information

The online version contains supplementary material available at 10.1186/s12937-022-00813-w.

Variance-quantitative trait loci enable systematic discovery of gene-environment interactions for cardiometabolic serum biomarkers

Gene-environment interactions represent the modification of genetic effects by environmental exposures and are critical for understanding disease and informing personalized medicine. These often induce differential phenotypic variance across genotypes; these variance-quantitative trait loci can be prioritized in a two-stage interaction detection strategy to greatly reduce the computational and statistical burden and enable testing of a broader range of exposures. We perform genome-wide variance-quantitative trait locus analysis for 20 serum cardiometabolic biomarkers by multi-ancestry meta-analysis of 350,016 unrelated participants in the UK Biobank, identifying 182 independent locus-biomarker pairs (p < 4.5×10-9). Most are concentrated in a small subset (4%) of loci with genome-wide significant main effects, and 44% replicate (p < 0.05) in the Women's Genome Health Study (N = 23,294). Next, we test each locus-biomarker pair for interaction across 2380 exposures, identifying 847 significant interactions (p < 2.4×10-7), of which 132 are independent (p < 0.05) after accounting for correlation between exposures. Specific examples demonstrate interaction of triglyceride-associated variants with distinct body mass- versus body fat-related exposures as well as genotype-specific associations between alcohol consumption and liver stress at the ADH1B gene. Our catalog of variance-quantitative trait loci and gene-environment interactions is publicly available in an online portal.

The association of genetic susceptibility to smoking with cardiovascular disease mortality and the benefits of adhering to a DASH diet: The Singapore Chinese Health Study

BACKGROUND

Understanding the genetic predisposition to cardiovascular disease (CVD) may help to improve clinical intervention strategies. Lifestyle factors, such as diet, may differ among ethnic groups and may, in turn, modify individuals' risks to diseases.

OBJECTIVES

We examined the genetic predisposition to ever smoking in relation to CVD mortality and assessed whether such an association could be modified by dietary intake.

METHODS

A total of 23,760 Chinese adults from the Singapore Chinese Heath Study who were free of cancer and CVD at recruitment (1993-1998) were included in the study. A weighted genetic risk score (wGRS) was calculated to define the genetically determined regular smoking behavior (never or ever). Multivariable-adjusted Cox regression models were used to assess the association between the wGRS and CVD mortality. We also conducted a 1-sample Mendelian randomization analysis for ever smoking and CVD mortality.

RESULTS

Over a mean of 22.6 years of follow-up, 2301 CVD deaths were identified. A genetic predisposition to ever smoking was significantly associated with CVD mortality; the multivariable-adjusted HR of CVD mortality was 1.07 (95% CI: 1.03-1.12), with a per-SD increment in the wGRS. However, the Mendelian randomization analysis did not support a causal relationship between ever smoking and CVD mortality (OR, 1.13; 95% CI: 0.87-1.45). Additionally, the Dietary Approaches to Stop Hypertension (DASH) score significantly modified the association between the smoking wGRS and CVD mortality; the association between a genetic predisposition to smoking and CVD mortality was only observed among individuals with a low DASH score (P-interaction = 0.004).

CONCLUSIONS

A genetic predisposition to smoking was associated with CVD mortality in the Chinese population. In addition, we detected a significant interaction showing higher CVD mortality related to genetically determined smoking among those with lower DASH scores.

Polygenic scores, diet quality, and type 2 diabetes risk: An observational study among 35,759 adults from 3 US cohorts

BACKGROUND

Both genetic and lifestyle factors contribute to the risk of type 2 diabetes, but the extent to which there is a synergistic effect of the 2 factors is unclear. The aim of this study was to examine the joint associations of genetic risk and diet quality with incident type 2 diabetes.

METHODS AND FINDINGS

We analyzed data from 35,759 men and women in the United States participating in the Nurses' Health Study (NHS) I (1986 to 2016) and II (1991 to 2017) and the Health Professionals Follow-up Study (HPFS; 1986 to 2016) with available genetic data and who did not have diabetes, cardiovascular disease, or cancer at baseline. Genetic risk was characterized using both a global polygenic score capturing overall genetic risk and pathway-specific polygenic scores denoting distinct pathophysiological mechanisms. Diet quality was assessed using the Alternate Healthy Eating Index (AHEI). Cox models were used to calculate hazard ratios (HRs) for type 2 diabetes after adjusting for potential confounders. With over 902,386 person-years of follow-up, 4,433 participants were diagnosed with type 2 diabetes. The relative risk of type 2 diabetes was 1.29 (95% confidence interval [CI] 1.25, 1.32; P < 0.001) per standard deviation (SD) increase in global polygenic score and 1.13 (1.09, 1.17; P < 0.001) per 10-unit decrease in AHEI. Irrespective of genetic risk, low diet quality, as compared to high diet quality, was associated with approximately 30% increased risk of type 2 diabetes (Pinteraction = 0.69). The joint association of low diet quality and increased genetic risk was similar to the sum of the risk associated with each factor alone (Pinteraction = 0.30). Limitations of this study include the self-report of diet information and possible bias resulting from inclusion of highly educated participants with available genetic data.

CONCLUSIONS

These data provide evidence for the independent associations of genetic risk and diet quality with incident type 2 diabetes and suggest that a healthy diet is associated with lower diabetes risk across all levels of genetic risk.

To Be or Not to Be: The Divergent Action and Metabolism of Sphingosine-1 Phosphate in Pancreatic Beta-Cells in Response to Cytokines and Fatty Acids

Sphingosine-1 phosphate (S1P) is a bioactive sphingolipid with multiple functions conveyed by the activation of cell surface receptors and/or intracellular mediators. A growing body of evidence indicates its important role in pancreatic insulin-secreting beta-cells that are necessary for maintenance of glucose homeostasis. The dysfunction and/or death of beta-cells lead to diabetes development. Diabetes is a serious public health burden with incidence growing rapidly in recent decades. The two major types of diabetes are the autoimmune-mediated type 1 diabetes (T1DM) and the metabolic stress-related type 2 diabetes (T2DM). Despite many differences in the development, both types of diabetes are characterized by chronic hyperglycemia and inflammation. The inflammatory component of diabetes remains under-characterized. Recent years have brought new insights into the possible mechanism involved in the increased inflammatory response, suggesting that environmental factors such as a westernized diet may participate in this process. Dietary lipids, particularly palmitate, are substrates for the biosynthesis of bioactive sphingolipids. Disturbed serum sphingolipid profiles were observed in both T1DM and T2DM patients. Many polymorphisms were identified in genes encoding enzymes of the sphingolipid pathway, including sphingosine kinase 2 (SK2), the S1P generating enzyme which is highly expressed in beta-cells. Proinflammatory cytokines and free fatty acids have been shown to modulate the expression and activity of S1P-generating and S1P-catabolizing enzymes. In this review, the similarities and differences in the action of extracellular and intracellular S1P in beta-cells exposed to cytokines or free fatty acids will be identified and the outlook for future research will be discussed.

Sphingosine-1 Phosphate Lyase Regulates Sensitivity of Pancreatic Beta-Cells to Lipotoxicity

Elevated levels of free fatty acids (FFAs) have been related to pancreatic beta-cell failure in type 2 diabetes (T2DM), though the underlying mechanisms are not yet fully understood. FFAs have been shown to dysregulate formation of bioactive sphingolipids, such as ceramides and sphingosine-1 phosphate (S1P) in beta-cells. The aim of this study was to analyze the role of sphingosine-1 phosphate lyase (SPL), a key enzyme of the sphingolipid pathway that catalyzes an irreversible degradation of S1P, in the sensitivity of beta-cells to lipotoxicity. To validate the role of SPL in lipotoxicity, we modulated SPL expression in rat INS1E cells and in human EndoC-βH1 beta-cells. SPL overexpression in INS1E cells (INS1E-SPL), which are characterized by a moderate basal expression level of SPL, resulted in an acceleration of palmitate-mediated cell viability loss, proliferation inhibition and induction of oxidative stress. SPL overexpression affected the mRNA expression of ER stress markers and mitochondrial chaperones. In contrast to control cells, in INS1E-SPL cells no protective effect of oleate was detected. Moreover, Plin2 expression and lipid droplet formation were strongly reduced in OA-treated INS1E-SPL cells. Silencing of SPL in human EndoC-βH1 beta-cells, which are characterized by a significantly higher SPL expression as compared to rodent beta-cells, resulted in prevention of FFA-mediated caspase-3/7 activation. Our findings indicate that an adequate control of S1P degradation by SPL might be crucially involved in the susceptibility of pancreatic beta-cells to lipotoxicity.

Cardiovascular health, genetic predisposition, and lifetime risk of type 2 diabetes

AIMS

Data on the lifetime risk of type 2 diabetes (T2D) incidence across different cardiovascular health (CVH) categories are scarce. Moreover, it remains unclear whether a genetic predisposition modifies this association.

METHODS AND RESULTS

Using data from the prospective population-based Rotterdam Study, a CVH score (body mass index, blood pressure, total cholesterol, smoking status, diet, and physical activity) was calculated and further categorized at baseline. Genetic predisposition to T2D was assessed and divided into tertiles by creating a genetic risk score (GRS). We estimated the lifetime risk for T2D within different CVH and GRS categories. Among 5993 individuals free of T2D at baseline [mean (standard deviation) age, 69.1 (8.5) years; 58% female], 869 individuals developed T2D during follow-up. At age 55 years, the remaining lifetime risk of T2D was 22.6% (95% CI: 19.4-25.8) for ideal, 28.3% (25.8-30.8) for intermediate, and 32.6% (29.0-36.2) for poor CVH. After further stratification by GRS tertiles, the lifetime risk for T2D was still the lowest for ideal CVH in the lowest GRS tertiles [21.5% (13.7-29.3)], in the second GRS tertile [20.8% (15.9-25.8)], and in the highest tertile [23.5% (18.5-28.6)] when compared with poor and intermediate CVH.

CONCLUSION

Our results highlight the importance of favourable CVH in preventing T2D among middle-aged individuals regardless of their genetic predisposition.

Genome-wide gene-diet interaction analysis in the UK Biobank identifies novel effects on hemoglobin A1c

Diet is a significant modifiable risk factor for type 2 diabetes (T2D), and its effect on disease risk is under partial genetic control. Identification of specific gene-diet interactions (GDIs) influencing risk biomarkers such as glycated hemoglobin (HbA1c) is a critical step towards precision nutrition for T2D prevention, but progress has been slow due to limitations in sample size and accuracy of dietary exposure measurement. We leveraged the large UK Biobank (UKB) cohort and a diverse group of dietary exposures, including 30 individual dietary traits and 8 empirical dietary patterns, to conduct genome-wide interaction studies in ~340 000 European-ancestry participants to identify novel GDIs influencing HbA1c. We identified five variant-dietary trait pairs reaching genome-wide significance (P < 5 × 10-8): two involved dietary patterns (meat pattern with rs147678157 and a fruit & vegetable-based pattern with rs3010439) and three involved individual dietary traits (bread consumption with rs62218803, dried fruit consumption with rs140270534 and milk type [dairy vs. other] with 4:131148078_TAGAA_T). These were affected minimally by adjustment for geographical and lifestyle-related confounders, and four of the five variants lacked genetic main effects that would have allowed their detection in a traditional genome-wide association study for HbA1c. Notably, multiple loci near transient receptor potential subfamily M genes (TRPM2 and TRPM3) interacted with carbohydrate-containing food groups. These interactions were further characterized using non-European UKB subsets and alternative measures of glycaemia (fasting glucose and follow-up HbA1c measurements). Our results highlight GDIs influencing HbA1c for future investigation, while reinforcing known challenges in detecting and replicating GDIs.

Effect of familial diabetes status and age at diagnosis on type 2 diabetes risk: a nation-wide register-based study from Denmark

AIMS/HYPOTHESIS

We assessed whether the risk of developing type 2 diabetes and the age of onset varied with the age at diabetes diagnosis of affected family members.

METHODS

We performed a national register-based open cohort study of individuals living in Denmark between 1995 and 2012. The population under study consisted of all individuals aged 30 years or older without diagnosed diabetes at the start date of the cohort (1 January 1995) and who had information about their parents' identity. Individuals who turned 30 years of age during the observation period and had available parental identity information were also added to the cohort from that date (open cohort design). These criteria restricted the study population mostly to people born between 1960 and 1982. Multivariable Poisson regression models adjusted for current age and highest educational attainment were used to estimate incidence rate ratios (IRRs) of type 2 diabetes.

RESULTS

We followed 2,000,552 individuals for a median of 14 years (24,034,059 person-years) and observed 76,633 new cases of type 2 diabetes. Compared with individuals of the same age and sex who did not have a parent or full sibling with diabetes, the highest risk of developing type 2 diabetes was observed in individuals with family members diagnosed at an early age. The IRR was progressively lower with a higher age at diabetes diagnosis in family members: 3.9 vs 1.4 for those with a parental age at diagnosis of 50 or 80 years, respectively; and 3.3 vs 2.0 for those with a full sibling's age at diagnosis of 30 or 60 years, respectively.

CONCLUSIONS/INTERPRETATION

People with a family member diagnosed with diabetes at an earlier age are more likely to develop diabetes and also to develop it at an earlier age than those with a family member diagnosed in later life. This finding highlights the importance of expanding our understanding of the interplay between genetic diabetes determinants and the social, behavioural and environmental diabetes determinants that track in families across generations. Accurate registration of age at diagnosis should form an integral part of recording a diabetes family history, as it provides easily obtainable and highly relevant detail that may improve identification of individuals at increased risk of younger onset of type 2 diabetes. In particular, these individuals may benefit from closer risk factor assessment and follow-up, as well as prevention strategies that may involve the family.

Efficacy and Safety of Teneligliptin in Patients With Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Background: Teneligliptin is a 3rd-generation dipeptidyl peptidase-4 (DPP-4) inhibitor. There is a limited evidence regarding the effect of teneligliptin. Therefore, this study is to assess the efficacy and safety of teneligliptin in type 2 diabetes mellitus (T2DM) patients with inadequately glycemic controlled.

Methods: A search of PubMed, Medline, Embase, and The Cochrane Library during 2000.01–2018.03 was performed for randomized controlled trials of teneligliptin compared to placebo in patients with T2DM with monotherapy or add-on treatment.

Results: Ten trials with 2119 patients were analyzed. Teneligliptin produced absolute reductions in glycated hemoglobin A1c (HbA1c) levels (weighted mean difference (WMD) 0.82%, 95% confidence interval (CI) [−0.91 to −0.72], p < 0.00001) compared with placebo. However, after 36–42 weeks of follow-up (open-label), HbA1c level rise higher than duration (double-blind) in teneligliptin group. Teneligliptin led to greater decrease of fasting plasma glucose (FPG) level (vs. placebo, WMD −18.32%, 95% CI [−21.05 to −15.60], p < 0.00001). Teneligliptin also significantly decreased the 2 h post-prandial plasma glucose (2 h PPG) (WMD −46.94%, 95% CI [−51.58 to −42.30], p < 0.00001) and area under the glucose plasma concentration-time curve from 0 to 2 h (AUC_0−2h) for PPG (WMD −71.50%, 95% CI [−78.09 to −64.91], p < 0.00001) compared with placebo. Patients treated with teneligliptin achieved increased homeostasis model assessment of β cell function (HOMA-β) with 9.31 (WMD, 95% CI [7.78–10.85], p < 0.00001). However, there was no significant difference between teneligliptin and placebo in overall adverse effects (0.96 risk ratio (RR), 95% CI [0.87, 1.06], p = 0.06). The risks of hypoglycemia were not significantly different between teneligliptin and placebo (1.16 RR, 95% CI [0.59, 2.26], p = 0.66).

Conclusions: Teneligliptin improved blood glucose levels and β-cells function with low risk of hypoglycemia in patients with T2DM. Common adverse effects of teneligliptin including hypoglycemia were identified and reviewed. Risks of cardiovascular events are less certain, and more data for long-term effects are needed.