Genetic risk scores in the prediction of plasma glucose, impaired insulin secretion, insulin resistance and incident type 2 diabetes in the METSIM study

Factors Associated With Type 2 Diabetes in Older Japanese With Similar Genetic Risk Scores: The Bunkyo Health Study

Context

Genome-wide association studies have identified numerous single-nucleotide variations (SNVs, formerly single-nucleotide polymorphisms) linked to type 2 diabetes (T2D), thus improving the accuracy of genetic risk scores (GRS) in predicting T2D.

Objective

This study aimed to investigate the association between the novel GRS and the prevalence of T2D and clarify the characteristics that differentiate individuals with and without T2D with similar genetic risk.

Methods

This cross-sectional study analyzed 1610 Japanese individuals aged 65 to 84 years. GRS were calculated using 110 SNVs associated with T2D in Japanese, and GRS classified individuals as having low, average, or high risk for T2D. The characteristics of participants with or without diabetes were compared by sex at each risk level.

Results

The prevalences of T2D were 7.8%, 14.7%, and 16.7% at low-, average-, and high-risk levels, respectively. The odds ratios at the high- and average-risk levels were significantly higher than those at the low-risk level, even after adjusting for confounding factors. The diabetes group had a higher visceral fat area (VFA) and Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) value, but a lower insulinogenic index, than the nondiabetes group across all risk levels. In the nondiabetes group, the II decreased significantly as GRS increased, but the HOMA-IR and Matsuda index values showed no association. In men with diabetes, VFA tended to decrease with higher GRS.

Conclusion

A higher GRS was significantly associated with increased T2D prevalence in older Japanese individuals. Our data demonstrated that the contribution of VFA to the development of diabetes varies with genetic risk.

Effects of Genetic Risk on Incident Type 2 Diabetes and Glycemia: The T2D-GENE Lifestyle Intervention Trial

CONTEXT

Lifestyle intervention prevents or delays type 2 diabetes (T2D) in subjects at a high risk of T2D. However, it is not known whether genetic variants modify the effect on incident T2D during lifestyle intervention.

OBJECTIVE

To investigate whether a low or high genetic risk has effects on incident T2D in a group-based lifestyle intervention study.

METHODS

The T2D-GENE trial involved 973 men from the Metabolic Syndrome in Men (METSIM) cohort, aged 50-75 years, body mass index ≥25 kg/m2, fasting plasma glucose 5.6-6.9 mmol/L, hemoglobin A1c < 48 mmol/mol, and either a low or high genetic risk score for T2D. There were 2 intervention groups, a low (n = 315) and high genetic risk for T2D (n = 313). They were provided with a 3-year group-based intervention with access to a web portal focused on healthy diet and physical activity. There were also corresponding population-based control groups at low (n = 196) and high (n = 149) genetic risk for T2D who had two laboratory visits (0 and 3 years) and general health advice as a part of their METSIM cohort protocol. The primary outcome was incident T2D, and a secondary outcome was glycemia.

RESULTS

The intervention significantly lowered the risk of T2D among the participants with a high genetic risk for T2D [hazards ratio (HR) 0.30, 95% confidence interval (CI) 0.16-0.56, P < .001) whereas in the low genetic risk group the effect was not significant (HR 0.69, 95% CI 0.36-1.32, P = .262). The intervention effect was not significantly different between the high and low genetic risk groups (P = .135). The intervention significantly ameliorated the worsening of glycemia and decreased weight both in the low and high genetic risk groups.

CONCLUSION

Our results showed that individuals with a high genetic risk for T2D benefitted from a low-cost group-based intervention focusing on healthy diet and physical activity. Therefore, all individuals at risk of T2D should be encouraged to make lifestyle changes regardless of genetic risk.

Healthy dietary pattern is associated with lower glycemia independently of the genetic risk of type 2 diabetes: a cross-sectional study in Finnish men

PURPOSE

Hyperglycemia is affected by lifestyle and genetic factors. We investigated if dietary patterns associate with glycemia in individuals with high or low genetic risk for type 2 diabetes (T2D).

METHODS

Men (n = 1577, 51-81 years) without T2D from the Metabolic Syndrome in Men (METSIM) cohort filled a food-frequency questionnaire and participated in a 2-hour oral glucose tolerance test. Polygenetic risk score (PRS) including 76 genetic variants was used to stratify participants into low or high T2D risk groups. We established two data-driven dietary patterns, termed healthy and unhealthy, and investigated their association with plasma glucose concentrations and hyperglycemia risk.

RESULTS

Healthy dietary pattern was associated with lower fasting and 2-hour plasma glucose, glucose area under the curve, and better insulin sensitivity (Matsuda insulin sensitivity index) and insulin secretion (disposition index) in unadjusted and adjusted models, whereas the unhealthy pattern was not. No interaction was observed between the patterns and PRS on glycemic measures. Healthy dietary pattern was negatively associated with the risk for hyperglycemia in an adjusted model (OR 0.69, 95% CI 0.51-0.95, in the highest tertile), whereas unhealthy pattern was not (OR 1.08, 95% CI 0.79-1.47, in the highest tertile). No interaction was found between diet and PRS on the risk for hyperglycemia (p = 0.69 for healthy diet, p = 0.54 for unhealthy diet).

CONCLUSION

Our findings suggest that healthy diet is associated with lower glucose concentrations and lower risk for hyperglycemia in men with no interaction with the genetic risk.

Higher Genetic Risk for Type 2 Diabetes Is Associated With a Faster Decline of β-Cell Function in an East Asian Population

OBJECTIVE

While most genetic variants of type 2 diabetes (T2D) are suggested to be associated with β-cell dysfunction cross sectionally, their association with the longitudinal change of β-cell function remains largely unknown.

RESEARCH DESIGN AND METHODS

We analyzed data from 6,311 participants without T2D at baseline (mean [SD] age 51.6 [8.7] years) from a community-based prospective cohort in Korea. Participants underwent biennial 2-h 75-g oral glucose tolerance tests (OGTTs) during 14 years of follow-up, and the OGTT-derived disposition index (DI) was used as a marker for β-cell function. Genetic risk was quantified using the genome-wide polygenic risk score (PRS) and was stratified into low (1st quintile), intermediate (2nd-4th quintiles), and high (5th quintile) genetic risk. Lifestyle was assessed according to Life's Essential 8.

RESULTS

During a mean follow-up of 10.9 years, 374 (29.6%), 851 (22.5%), and 188 (14.9%) participants developed T2D in the high, intermediate, and low genetic risk groups, respectively. Compared with the low genetic risk group, participants in the high genetic risk group had a 25% lower DI at baseline. Furthermore, in longitudinal analysis, we observed a 1.83-fold faster decline in log2-transformed DI per year (-0.034 vs. -0.019, P = 2.1 × 10-3; per 1-SD increase in T2D PRS, P = 1.2 × 10-4). Healthy lifestyle attenuated the rate of decline in DI across all genetic risk groups.

CONCLUSIONS

Individuals with a higher genetic risk for T2D exhibited not only a lower OGTT-derived β-cell function at baseline but also a notably more rapid decline during follow-up. This information could be used to enable a focused precision prevention with lifestyle intervention.

Based on systematic druggable genome-wide Mendelian randomization identifies therapeutic targets for diabetes

Purpose

Diabetes and its complications cause a heavy burden of disease worldwide. In recent years, Mendelian randomization (MR) has been widely used to discover the pathogenesis and epidemiology of diseases, as well as to discover new therapeutic targets. Therefore, based on systematic "druggable" genomics, we aim to identify new therapeutic targets for diabetes and analyze its pathophysiological mechanisms to promote its new therapeutic strategies.

Material and method

We used double sample MR to integrate the identified druggable genomics to evaluate the causal effect of quantitative trait loci (eQTLs) expressed by druggable genes in blood on type 1 and 2 diabetes (T1DM and T2DM). Repeat the study using different data sources on diabetes and its complications to verify the identified genes. Not only that, we also use Bayesian co-localization analysis to evaluate the posterior probabilities of different causal variations, shared causal variations, and co-localization probabilities to examine the possibility of genetic confounding. Finally, using diabetes markers with available genome-wide association studies data, we evaluated the causal relationship between established diabetes markers to explore possible mechanisms.

Result

Overall, a total of 4,477 unique druggable genes have been gathered. After filtering using methods such as Bonferroni significance (P<1.90e-05), the MR Steiger directionality test, Bayesian co-localization analysis, and validation with different datasets, Finally, 7 potential druggable genes that may affect the results of T1DM and 7 potential druggable genes that may affect the results of T2DM were identified. Reverse MR suggests that C4B may play a bidirectional role in the pathogenesis of T1DM, and none of the other 13 target genes have a reverse causal relationship. And the 7 target genes in T2DM may each affect the biomarkers of T2DM to mediate the pathogenesis of T2DM.

Conclusion

This study provides genetic evidence supporting the potential therapeutic benefits of targeting seven druggable genes, namely MAP3K13, KCNJ11, REG4, KIF11, CCNE2, PEAK1, and NRBP1, for T2DM treatment. Similarly, targeting seven druggable genes, namely ERBB3, C4B, CD69, PTPN22, IL27, ATP2A1, and LT-β, has The potential therapeutic benefits of T1DM treatment. This will provide new ideas for the treatment of diabetes and also help to determine the priority of drug development for diabetes.

Psychometric evaluation of three-factor eating questionnaire -R18 in aging Finnish men with increased risk for type 2 diabetes

BACKGROUND

Deeper comprehension of eating-related behaviour (how and why people eat) can reveal new aspects to support health and prevent type 2 diabetes (T2D). However, such research is largely missing in aging men.

AIM

The aim was to investigate suitability of the Three-Factor Eating Questionnaire-R18 (TFEQ-R18) in Finnish aging men which is widely used to examine factors: cognitive restraint (CR), uncontrolled eating (UE), and emotional eating (EE).

METHODS

Study population consisted of 420 men aged 50-75, who completed the TFEQ-R18 at the baseline of the T2D-GENE lifestyle intervention study. Inclusion criteria were impaired fasting glucose (IFG) and body mass index ≥25 kg/m2. Confirmatory factor analysis was used to study psychometrics (reliability, validity, and model fit) and factor structure of TFEQ-R18.

RESULTS

The items loaded to the three factors (CR, UE, EE) as in previous studies, except two items at CR factor and one at UE factor, which were therefore omitted. UE was also discovered split into two sub factors (named as 'craving' and 'loss-of-control'), UE being a higher-order (h) factor. The resultant revised version was named as Three-Factor Eating Questionnaire Revised to 15-items with higher-order factor (TFEQ-R15h).

CONCLUSION

The original 18-item version of the TFEQ was not optimal in the population consisting of Finnish aging men with elevated T2D risk. A modified 15-item version of the TFEQ could be used to describe EB in this population instead.

Effects of endocrine disrupting chemicals and their interactions with genetic risk scores on cardiometabolic traits

Ubiquitous non-persistent endocrine disrupting chemicals (EDCs) have inconsistent associations with cardiometabolic traits. Additionally, large-scale genome-wide association studies (GWASs) have yielded many genetic risk variants for cardiometabolic traits and diseases. This study aimed to investigate the associations between a wide range of EDC exposures (parabens, bisphenols, and phthalates) and 14 cardiometabolic traits and whether these are moderated by their respective genetic risk scores (GRSs). Data were from 1074 participants aged 18 years or older of the Lifelines Cohort Study, a large population-based biobank. GRSs for 14 cardiometabolic traits were calculated based on genome-wide significant common variants from recent GWASs. The concentrations of 15 EDCs in 24-hour urine were measured by isotope dilution liquid chromatography tandem mass spectrometry technology. The main effects of trait-specific GRSs and each of the EDC exposures and their interaction effects on the 14 cardiometabolic traits were examined in multiple linear regression. The present study confirmed significant main effects for all GRSs on their corresponding cardiometabolic trait. Regarding the main effects of EDC exposures, 26 out of 280 EDC-trait tests were significant with explained variances ranging from 0.43 % (MMP- estimated glomerular filtration rate (eGFR)) to 2.37 % (PrP-waist-hip ratio adjusted body mass index (WHRadjBMI)). We confirmed the association of MiBP and MBzP with WHRadjBMI and body mass index (BMI), and showed that parabens, bisphenol F, and many other phthalate metabolites significantly contributed to the variance of WHRadjBMI, BMI, high-density lipoprotein (HDL), eGFR, fasting glucose (FG), and diastolic blood pressure (DBP). Only one association between BMI and bisphenol F was nominally significantly moderated by the GRS explaining 0.36 % of the variance. However, it did not survive multiple testing correction. We showed that non-persistent EDC exposures exerted effects on BMI, WHRadjBMI, HDL, eGFR, FG, and DBP. However no evidence for a modulating role of GRSs was found.

Lifestyle Intervention Guided by Group and Internet-Based Counseling in the T2D-GENE Trial Supports Its Applicability and Feasibility

Type 2 diabetes (T2D) can be prevented or postponed by lifestyle modifications as shown by previous intervention studies. In most of these studies, participants have received resource-demanding individual counseling. In the 3-year T2D-GENE trial with lifestyle intervention, we investigated whether a less resource-demanding form of group and internet-based counseling is feasible and effective in preventing T2D in people with an increased risk for T2D. Altogether, 628 middle-aged to elderly men either with a high number or low number of T2D risk alleles were recruited. Five to seven group sessions were organized during the intervention, in addition to information and activities delivered via the web portal, and weekly monitoring of body weight and physical activity. Four-day food records with personal feedback were documented five times during the study. Of the 549 participants completing the study, over 90% participated in the group sessions and kept the food records. The four self-feedback tasks delivered during the second and the third years of the study were completed by 80-89% of the participants. In conclusion, a group and web portal-based lifestyle intervention is applicable for middle-aged to elderly men as a lifestyle modification aiming to prevent T2D.

Association between Genotype and the Glycemic Response to an Oral Glucose Tolerance Test: A Systematic Review

The inter-individual variability of metabolic response to foods may be partly due to genetic variation. This systematic review aims to assess the associations between genetic variants and glucose response to an oral glucose tolerance test (OGTT). Three databases (PubMed, Web of Science, Embase) were searched for keywords in the field of genetics, OGTT, and metabolic response (PROSPERO: CRD42021231203). Inclusion criteria were available data on single nucleotide polymorphisms (SNPs) and glucose area under the curve (gAUC) in a healthy study cohort. In total, 33,219 records were identified, of which 139 reports met the inclusion criteria. This narrative synthesis focused on 49 reports describing gene loci for which several reports were available. An association between SNPs and the gAUC was described for 13 gene loci with 53 different SNPs. Three gene loci were mostly investigated: transcription factor 7 like 2 (TCF7L2), peroxisome proliferator-activated receptor gamma (PPARγ), and potassium inwardly rectifying channel subfamily J member 11 (KCNJ11). In most reports, the associations were not significant or single findings were not replicated. No robust evidence for an association between SNPs and gAUC after an OGTT in healthy persons was found across the identified studies. Future studies should investigate the effect of polygenic risk scores on postprandial glucose levels.

Effects of SLCO1B1 Genetic Variant on Metabolite Profile in Participants on Simvastatin Treatment

Organic-anion-transporting polypeptide 1B1 (OATP1B1), encoded by the solute carrier organic anion transporter family member 1B1 gene (SLCO1B1), is highly expressed in the liver and transports several endogenous metabolites into the liver, including statins. Previous studies have not investigated the association of SLCO1B1 rs4149056 variant with the risk of type 2 diabetes (T2D) or determined the metabolite signature of the C allele of SLCO1B1 rs4149056 (SLCO1B1 rs4149056-C allele) in a large randomly selected population. SLCO1B1 rs4149056-C inhibits OATP1B1 transporter and is associated with increased levels of blood simvastatin concentrations. Our study is to first to show that SLCO1B1 rs4149056 variant is not significantly associated with the risk of T2D, suggesting that simvastatin has a direct effect on the risk of T2D. Additionally, we investigated the effects of SLCO1B1 rs4149056-C on plasma metabolite concentrations in 1373 participants on simvastatin treatment and in 1368 age- and body-mass index (BMI)-matched participants without any statin treatment. We found 31 novel metabolites significantly associated with SLCO1B1 rs4149056-C in the participants on simvastatin treatment and in the participants without statin treatment. Simvastatin decreased concentrations of dicarboxylic acids, such as docosadioate and dodecanedioate, that may increase beta- and peroxisomal oxidation and increased the turnover of cholesterol into bile acids, resulting in a decrease in steroidogenesis due to limited availability of cholesterol for steroid synthesis. Our findings suggest that simvastatin exerts its effects on the lowering of low-density lipoprotein (LDL) cholesterol concentrations through several distinct pathways in the carriers of SLCO1B1 rs4149056-C, including dicarboxylic acids, bile acids, steroids, and glycerophospholipids.

Genetics of Type 2 Diabetes: Past, Present, and Future

Diabetes has reached epidemic proportions worldwide. Currently, approximately 537 million adults (20–79 years) have diabetes, and the total number of people with diabetes is continuously increasing. Diabetes includes several subtypes. About 80% of all cases of diabetes are type 2 diabetes (T2D). T2D is a polygenic disease with an inheritance ranging from 30 to 70%. Genetic and environment/lifestyle factors, especially obesity and sedentary lifestyle, increase the risk of T2D. In this review, we discuss how studies on the genetics of diabetes started, how they expanded when genome-wide association studies and exome and whole-genome sequencing became available, and the current challenges in genetic studies of diabetes. T2D is heterogeneous with respect to clinical presentation, disease course, and response to treatment, and has several subgroups which differ in pathophysiology and risk of micro- and macrovascular complications. Currently, genetic studies of T2D focus on these subgroups to find the best diagnoses and treatments for these patients according to the principles of precision medicine.

Insulin resistance in children

PURPOSE OF REVIEW

Insulin resistance (IR) is a clinical condition due to the decline in the efficiency of insulin promoting glucose uptake and utilization. The aim of this review is to provide an overview of the current knowledge on IR in children, focusing on its physiopathology, the most appropriate methods of measurement of IR, the assessment of risk factors, the effects of IR in children, and finally giving indications on screening and treatment.

RECENT FINDINGS

IR has evolved more and more to be a global public health problem associated with several chronic metabolic diseases.

SUMMARY

Detecting a correct measurement method and specific risk predictors, in order to reduce the incidence of IR, represents a challenging goal.

Genetic Susceptibility to Insulin Resistance and Its Association with Estimated Longevity in the Hungarian General and Roma Populations

Diabetes mellitus is a major public health problem with a wide range of prevalence among different ethnic groups. Early recognition of pre-diabetes is important to prevent the development of the disease, its complications, co-morbidities, and consequently early death. Insulin resistance (IR) is considered a condition that precedes type 2 diabetes; thus, understanding its underlying causes (genetic and non-genetic factors) will bring us closer to preventing it. The present study aimed to investigate the genetic susceptibility to IR and its impact on estimated longevity in populations with different ethnic origins using randomly selected samples of 372 Hungarian general (HG, as a reference with Caucasian origin) and 334 Roma participants (largest ethnic minority in Europe, with a northern India origin). In the present study, we used the Homeostasis Model Assessment—Insulin Resistance (HOMA—IR) to identify people with IR (>3.63) at the population level. To investigate the genetic predisposition to IR, 29 single nucleotide polymorphisms (SNPs) identified in a systematic literature search were selected and genotyped in sample populations. In the analyses, the adjusted p < 0.0033 was considered significant. Of these 29 SNPs, the commutative effects of 15 SNPs showing the strongest association with HOMA—IR were used to calculate an optimized genetic risk score (oGRS). The oGRS was found nominally significantly (p = 0.019) higher in the Roma population compared to HG one, and it was more strongly correlated with HOMA—IR. Therefore, it can be considered as a stronger predictor of the presence of IR among the Roma (AUCRoma = 0.673 vs. AUCHG = 0.528). Furthermore, oGRS also showed a significant correlation with reduced estimated longevity in the Roma population (β = −0.724, 95% CI: −1.230−−0.218; p = 0.005), but not in the HG one (β = 0.065, 95% CI: −0.388−0.518; p = 0.779). Overall, IR shows a strong correlation with a genetic predisposition among Roma, but not in the HG population. Furthermore, the increased genetic risk of Roma is associated with shorter estimated longevity, whereas this association is not observed in the HG one. Increased genetic susceptibility of Roma to IR should be considered in preventive programs targeting the development of type 2 diabetes, which may also reduce the risk of preventable premature death among them.

Relationship between glucose homeostasis and obesity in early life-a study of Italian children and adolescents

Epidemic obesity is the most important risk factor for prediabetes and type 2 diabetes (T2D) in youth as it is in adults. Obesity shares pathophysiological mechanisms with T2D and is likely to share part of the genetic background. We aimed to test if weighted genetic risk scores (GRSs) for T2D, fasting glucose (FG) and fasting insulin (FI) predict glycaemic traits and if there is a causal relationship between obesity and impaired glucose metabolism in children and adolescents. Genotyping of 42 SNPs established by genome-wide association studies for T2D, FG and FI was performed in 1660 Italian youths aged between 2 and 19 years. We defined GRS for T2D, FG and FI and tested their effects on glycaemic traits, including FG, FI, indices of insulin resistance/beta cell function and body mass index (BMI). We evaluated causal relationships between obesity and FG/FI using one-sample Mendelian randomization analyses in both directions. GRS-FG was associated with FG (beta = 0.075 mmol/l, SE = 0.011, P = 1.58 × 10-11) and beta cell function (beta = -0.041, SE = 0.0090 P = 5.13 × 10-6). GRS-T2D also demonstrated an association with beta cell function (beta = -0.020, SE = 0.021 P = 0.030). We detected a causal effect of increased BMI on levels of FI in Italian youths (beta = 0.31 ln (pmol/l), 95%CI [0.078, 0.54], P = 0.0085), while there was no effect of FG/FI levels on BMI. Our results demonstrate that the glycaemic and T2D risk genetic variants contribute to higher FG and FI levels and decreased beta cell function in children and adolescents. The causal effects of adiposity on increased insulin resistance are detectable from childhood age.

Genetic risk score to improve prediction and treatment in gestational diabetes mellitus

Diabetes mellitus is a chronic disease caused by the interaction of genetics and the environment that can lead to chronic damage to many organ systems. Genome-wide association studies have identified accumulating single-nucleotide polymorphisms related to type 2 diabetes mellitus and gestational diabetes mellitus. Genetic risk score (GRS) has been utilized to evaluate the incidence risk to improve prediction and optimize treatments. This article reviews the research progress in the use of the GRS in diabetes mellitus in recent years and discusses future prospects.

Effect of lifestyle intervention on the risk of incident diabetes in individuals with impaired fasting glucose and low or high genetic risk for the development of type 2 diabetes in men: a T2D-GENE trial

Purpose

Genetic and lifestyle/environmental factors as well as their interplay contribute to the pathogenesis of type 2 diabetes (T2D). Several trials have shown that lifestyle intervention is effective in the prevention of T2D, but there are no trials that have taken into account the genetic risk of the participants. The aim of our T2D-GENE trial (ClinicalTrials.gov ID: NCT02709057) is to investigate the effects of lifestyle intervention on the prevention of T2D in participants with a high genetic risk of T2D compared with participants with a low genetic risk of T2D.

Methods

Both intervention and control groups include 300 participants with low and 300 participants with high genetic risk for T2D. Genetic risk was evaluated by genetic risk score, and these two groups were matched additionally for fasting plasma glucose concentration, age, and body mass index. Corresponding control groups (300 participants each) do not have lifestyle intervention. The inclusion criteria are impaired fasting glucose at entry with or without impaired glucose tolerance, age 50-75 years, and body mass index ≥25 kg/m². The primary outcome is incident T2D and the intervention lasts for 3 years.

Conclusion

If the effects of the lifestyle intervention are independent from the genetic risk of the participants, our study will be of great importance for the entire T2D research community, health care providers, and individuals at high risk for T2D. In this case, lifestyle intervention is beneficial for all individuals at risk for developing T2D, independently of genetic risk.

ClinicalTrialsgov ID

NCT02709057 March 15, 2016.

The "Common Soil Hypothesis" Revisited-Risk Factors for Type 2 Diabetes and Cardiovascular Disease

The prevalence and the incidence of type 2 diabetes (T2D), representing >90% of all cases of diabetes, are increasing rapidly worldwide. Identification of individuals at high risk of developing diabetes is of great importance, as early interventions might delay or even prevent full-blown disease. T2D is a complex disease caused by multiple genetic variants in interaction with lifestyle and environmental factors. Cardiovascular disease (CVD) is the major cause of morbidity and mortality. Detailed understanding of molecular mechanisms underlying in CVD events is still largely missing. Several risk factors are shared between T2D and CVD, including obesity, insulin resistance, dyslipidemia, and hyperglycemia. CVD can precede the development of T2D, and T2D is a major risk factor for CVD, suggesting that both conditions have common genetic and environmental antecedents and that they share “common soil”. We analyzed the relationship between the risk factors for T2D and CVD based on genetics and population-based studies with emphasis on Mendelian randomization studies.

The β Cell in Diabetes: Integrating Biomarkers With Functional Measures

The pathogenesis of hyperglycemia observed in most forms of diabetes is intimately tied to the islet β cell. Impairments in propeptide processing and secretory function, along with the loss of these vital cells, is demonstrable not only in those in whom the diagnosis is established but typically also in individuals who are at increased risk of developing the disease. Biomarkers are used to inform on the state of a biological process, pathological condition, or response to an intervention and are increasingly being used for predicting, diagnosing, and prognosticating disease. They are also proving to be of use in the different forms of diabetes in both research and clinical settings. This review focuses on the β cell, addressing the potential utility of genetic markers, circulating molecules, immune cell phenotyping, and imaging approaches as biomarkers of cellular function and loss of this critical cell. Further, we consider how these biomarkers complement the more long-established, dynamic, and often complex measurements of β-cell secretory function that themselves could be considered biomarkers.

Genetic Risk Score for Type 2 Diabetes and Traits Related to Glucose-Insulin Homeostasis in Youth: The Exploring Perinatal Outcomes Among Children (EPOCH) Study

OBJECTIVE

The metabolic phenotype of youth-onset type 2 diabetes (T2D) differs from that of adult-onset T2D, but little is known about genetic contributions. We aimed to evaluate the association between a T2D genetic risk score (GRS) and traits related to glucose-insulin homeostasis among healthy youth.

RESEARCH DESIGN AND METHODS

We used data from 356 youth (mean age 16.7 years; 50% female) in the Exploring Perinatal Outcomes Among Children (EPOCH) cohort to calculate a standardized weighted GRS based on 271 single nucleotide polymorphisms associated with T2D in adults. We used linear regression to assess associations of the GRS with log-transformed fasting glucose, 2-h glucose, HOMA of insulin resistance (HOMA-IR), oral disposition index, and insulinogenic index adjusted for age, sex, BMI z score, in utero exposure to maternal diabetes, and genetic principal components. We also evaluated effect modification by BMI z score, in utero exposure to maternal diabetes, and ethnicity.

RESULTS

Higher weighted GRS was associated with lower oral disposition index (β = -0.11; 95% CI -0.19, -0.02) and insulinogenic index (β = -0.08; 95% CI -0.17, -0.001), but not with fasting glucose (β = 0.01; 95% CI -0.01, 0.02), 2-h glucose (β = 0.03; 95% CI -0.0004, 0.06), or HOMA-IR (β = 0.02; 95% CI -0.04, 0.07). BMI z score and in utero exposure to maternal diabetes increased the effect of the GRS on glucose levels.

CONCLUSIONS

Our results suggest that T2D genetic risk factors established in adults are relevant to glucose-insulin homeostasis in youth and that maintaining a healthy weight may be particularly important for youth with high genetic risk of T2D.

Association of Combined TCF7L2 and KCNQ1 Gene Polymorphisms with Diabetic Micro- and Macrovascular Complications in Type 2 Diabetes Mellitus

BACKGROUND

Vascular complications are the major morbid consequences of type 2 diabetes mellitus (T2DM). The transcription factor 7-like 2 (TCF7L2), potassium voltage-gated channel subfamily Q member 1 (KCNQ1), and inwardly-rectifying potassium channel, subfamily J, member 11 gene (KCNJ11) are common T2DM susceptibility genes in various populations. However, the associations between polymorphisms in these genes and diabetic complications are controversial. This study aimed to investigate the effects of combined gene-polymorphisms within TCF7L2, KCNQ1, and KCNJ11 on vascular complications in Thai subjects with T2DM.

METHODS

We conducted a case-control study comprising 960 T2DM patients and 740 non-diabetes controls. Single nucleotide polymorphisms in TCF7L2, KCNQ1, and KCNJ11 were genotyped and evaluated for their association with diabetic vascular complications.

RESULTS

The gene variants TCF7L2 rs290487-T, KCNQ1 rs2237892-C, and KCNQ1 rs2237897-C were associated with increased risk of T2DM. TCF7L2 rs7903146-C, TCF7L2 rs290487-C, KCNQ1 rs2237892-T, and KCNQ1 rs2237897-T revealed an association with hypertension. The specific combination of risk-alleles that have effects on T2DM and hypertension, TCF7L2 rs7903146-C, KCNQ1 rs2237892-C, and KCNQ1 rs2237897-T, as genetic risk score (GRS), pronounced significant association with coronary artery disease (CAD), cumulative nephropathy and CAD, and cumulative microvascular and macrovascular complications (respective odds ratios [ORs] with 95% confidence interval [95% CI], comparing between GRS 2-3 and GRS 5-6, were 7.31 [2.03 to 26.35], 3.92 [1.75 to 8.76], and 2.33 [1.13 to 4.79]).

CONCLUSION

This study demonstrated, for the first time, the effect conferred by specific combined genetic variants in TCF7L2 and KCNQ1 on diabetic vascular complications, predominantly with nephropathy and CAD. Such a specific pattern of gene variant combination may implicate in the progression of T2DM and life-threatening vascular complications.

A Genetic Risk Score Improves the Prediction of Type 2 Diabetes Mellitus in Mexican Youths but Has Lower Predictive Utility Compared With Non-Genetic Factors

Background

Type 2 diabetes (T2D) is a multifactorial disease caused by a complex interplay between environmental risk factors and genetic predisposition. To date, a total of 10 single nucleotide polymorphism (SNPs) have been associated with pediatric-onset T2D in Mexicans, with a small individual effect size. A genetic risk score (GRS) that combines these SNPs could serve as a predictor of the risk for pediatric-onset T2D.

Objective

To assess the clinical utility of a GRS that combines 10 SNPs to improve risk prediction of pediatric-onset T2D in Mexicans.

Methods

This case-control study included 97 individuals with pediatric-onset T2D and 84 controls below 18 years old without T2D. Information regarding family history of T2D, demographics, perinatal risk factors, anthropometric measurements, biochemical variables, lifestyle, and fitness scores were then obtained. Moreover, 10 single nucleotide polymorphisms (SNPs) previously associated with pediatric-onset T2D in Mexicans were genotyped. The GRS was calculated by summing the 10 risk alleles. Pediatric-onset T2D risk variance was assessed using multivariable logistic regression models and the area under the receiver operating characteristic curve (AUC).

Results

The body mass index Z-score (Z-BMI) [odds ratio (OR) = 1.7; p = 0.009] and maternal history of T2D (OR = 7.1; p < 0.001) were found to be independently associated with pediatric-onset T2D. No association with other clinical risk factors was observed. The GRS also showed a significant association with pediatric-onset T2D (OR = 1.3 per risk allele; p = 0.006). The GRS, clinical risk factors, and GRS plus clinical risk factors had an AUC of 0.66 (95% CI 0.56-0.75), 0.72 (95% CI 0.62-0.81), and 0.78 (95% CI 0.70-0.87), respectively (p < 0.01).

Conclusion

The GRS based on 10 SNPs was associated with pediatric-onset T2D in Mexicans and improved its prediction with modest significance. However, clinical factors, such the Z-BMI and family history of T2D, continue to have the highest predictive utility in this population.

Biomarkers for type 2 diabetes

Background

The prevalence and incidence of type 2 diabetes (T2D), representing >90% of all cases of diabetes, are increasing rapidly worldwide. Identification of individuals at high risk of developing diabetes is of great importance as early interventions might delay or even prevent full-blown disease. T2D is a complex disease caused by multiple genetic loci in interplay with lifestyle and environmental factors. Recently over 400 distinct association signals were published; these explain 18% of the risk of T2D.

Scope of review

In this review there is a major focus on risk factors and genetic and non-genetic biomarkers for the risk of T2D identified especially in large prospective population-based studies, and studies testing causality of the biomarkers for T2D in Mendelian randomization studies. Another focus is on understanding genome-phenome interplay in the classification of individuals with T2D into subgroups.

Major conclusions

Several recent large population-based studies and their meta-analyses have identified multiple potential genetic and non-genetic biomarkers for the risk of T2D. Combination of genetic variants and physiologically characterized pathways improves the classification of individuals with T2D into subgroups, and is also paving the way to a precision medicine approach, in T2D.

Genetic Modifiers of Cystic Fibrosis-Related Diabetes Have Extensive Overlap With Type 2 Diabetes and Related Traits

CONTEXT

Individuals with cystic fibrosis (CF) develop a distinct form of diabetes characterized by β-cell dysfunction and islet amyloid accumulation similar to type 2 diabetes (T2D), but generally have normal insulin sensitivity. CF-related diabetes (CFRD) risk is determined by both CFTR, the gene responsible for CF, and other genetic variants.

OBJECTIVE

To identify genetic modifiers of CFRD and determine the genetic overlap with other types of diabetes.

DESIGN AND PATIENTS

A genome-wide association study was conducted for CFRD onset on 5740 individuals with CF. Weighted polygenic risk scores (PRSs) for type 1 diabetes (T1D), T2D, and diabetes endophenotypes were tested for association with CFRD.

RESULTS

Genome-wide significance was obtained for variants at a novel locus (PTMA) and 2 known CFRD genetic modifiers (TCF7L2 and SLC26A9). PTMA and SLC26A9 variants were CF-specific; TCF7L2 variants also associated with T2D. CFRD was strongly associated with PRSs for T2D, insulin secretion, postchallenge glucose concentration, and fasting plasma glucose, and less strongly with T1D PRSs. CFRD was inconsistently associated with PRSs for insulin sensitivity and was not associated with a PRS for islet autoimmunity. A CFRD PRS comprising variants selected from these PRSs (with a false discovery rate < 0.1) and the genome-wide significant variants was associated with CFRD in a replication population.

CONCLUSIONS

CFRD and T2D have more etiologic and mechanistic overlap than previously known, aligning along pathways involving β-cell function rather than insulin sensitivity. Two CFRD risk loci are unrelated to T2D and may affect multiple aspects of CF. An 18-variant PRS stratifies risk of CFRD in an independent population.

Prevention of Potential Adverse Metabolic Effects of a Supplementation with Omega-3 Fatty Acids Using a Genetic Score Approach

INTRODUCTION

The consumption of long-chain omega-3 polyunsaturated fatty acids (n-3 PUFA) has been reported to have beneficial health effects, notably, by reducing plasma triglyceride levels. Nonetheless, a concomitant decrease in insulin sensitivity has also been observed, but is highly variable among subjects. Herein, we aimed to determine the importance of the genetic background in the interindividual variability of the insulin sensitivity response following an n-3 PUFA supplementation.

METHODS

A total of 210 participants completed a 6-week n-3 PUFA supplementation with 5 g/day of fish oil (providing 1.9-2.2 g of eicosapentaenoic acid + 1.1 g of docosahexaenoic acid). Insulin resistance was estimated by the homeostatic model assessment (HOMA-IR), and participants were further classified as high-risk or low-risk depending on their HOMA-IR change following the n-3 PUFA supplementation, as compared to pre-supplementation values. Genome-wide genotyping data were obtained for 138 participants using HumanOmni-5-Quad BeadChips containing 4,301,331 single nucleotide polymorphisms. A genome-wide association analysis (GWAS) was carried out between high-risk and low-risk participants. The population study was split into training (60%) and testing (40%) datasets to assess the predictive accuracy of a genetic risk score (GRS) constructed by summing the number of risk alleles.

RESULTS

Following the n-3 PUFA supplementation, 32 participants had increased HOMA-IR as compared to initial values and were classified as high risk (23.2%), whereas remaining subjects were classified as low risk (n = 106, 76.8%). A total of 8 loci had frequency differences between high-risk and low-risk participants at a suggestive GWAS association threshold (p value <1 × 10-5). After applying 10-fold cross validation, the GRS showed a significant association with the risk of increased HOMA-IR in the testing dataset (OR = 3.16 [95% CI, 1.85-7.14]), with a predictive accuracy of 0.85, and explained 40% of variation in HOMA-IR change.

CONCLUSIONS

These results suggest that the genetic background has a relevant role in the interindividual variability observed in the insulin sensitivity response following an n-3 PUFA supplementation. Subjects being at risk of insulin sensitivity lowering following an n-3 PUFA supplementation may be identified using genetic-based precision nutrition approaches.

Effects of variants of 50 genes on diabetes risk among the Chinese population born in the early 1960s

BACKGROUND

Genome-wide association studies have identified loci that significantly increase diabetes risk. This study explored the genetic susceptibility in relation to diabetes risk in adulthood among a Chinese population born in the early 1960s.

METHODS

In all, 2129 subjects (833 males, 1296 females) were selected from the cross-sectional 2010 to 2012 China National Nutrition and Health Survey. Fifty diabetes-related single nucleotide polymorphisms (SNPs) were detected. Two diabetes genetic risk scores (GRSs) based on the 50 diabetes-predisposing variants were developed to examine the association of these SNPs with diabetes risk.

RESULTS

Associations were found between diabetes risk and SNPs in the MTNR1B (rs10830963), KLHDC5 (rs10842994), GRK5 (rs10886471), cyclindependentkinase 5 regulatory subunit associated protein 1 (rs10946398), adaptorrelated protein complex 3 subunit sigma 2 (rs2028299), diacylglycerol kinase beta/transmembrane protein 195 (rs2191349), SREBF chaperone (rs4858889), ankyrin1 (rs516946), RAS guanyl releasing protein 1 (rs7403531), and zinc finger AN1-type containing 3 (rs9470794) genes. As a continuous variable, with a 1-point increase in the GRS or weighted (w) GRS, fasting plasma glucose (FPG) increased 0.045 and 0.044 mM, respectively (P < 0.001 for both), after adjusting for confounders. Both GRS and wGRS showed an association with diabetes, with a multivariable-adjusted odds ratio (95% confidence interval) of 1.09 (1.00-1.19) and 1.12 (1.03-1.22), respectively, among all subjects. No significant associations were found between the GRS or wGRS and impaired fasting glucose or impaired glucose tolerance.

CONCLUSIONS

The data suggest the association of 10 SNPs and the GRS or wGRS with diabetes risk. Genetic susceptibility to diabetes may synergistically affect the risk of diabetes in adulthood.

Alcohol consumption and its interaction with genetic variants are strongly associated with the risk of type 2 diabetes: a prospective cohort study

Background

Both genetic and lifestyle factors contribute to the incidence of type 2 diabetes. It yet remains controversial whether and how alcohol consumption, one of the most prevalent lifestyle habits, influences type 2 diabetes. Moreover, whether alcohol consumption interacts with genetic risk is inconclusive. Thus, we aimed to explore the effects of alcohol, genetic risk and their potential interactions on type 2 diabetes risk.

Methods

The Shanghai Diabetes study (SHDS) had a total of 2546 participants with 611 incident cases of combined type 2 diabetes and impaired glucose regulation (IGR). We constructed weighted genetic risk score (GRS) for type 2 diabetes and categorized the GRS into three strata. And the homeostatic model assessment of β-cell function (HOMA-B) and insulin resistance (HOMA-IR) were calculated. Then we used logistic regression models and multiple linear regression models to examine the influence of both baseline alcohol consumption and genetic risk on blood glucose deterioration, insulin resistance (IR) and beta cell function (BC), respectively. Moreover, we investigated the interactions of alcohol intake with: (1) GRSs for type 2 diabetes, IR, BC, body mass index (BMI) and waist-to-hip ratio (WHR); and (2) each of the single nucleotide polymorphisms (SNPs) used to establish the GRSs mentioned above.

Results

Alcohol consumption and higher T2D-GRS both contributed to a higher incidence rate of blood glucose deterioration [odds ratio (OR), 2.24, 95% confidence interval (CI), 1.76–2.87; OR, 1.25, 95% CI, 1.11–1.42; respectively]. Alcohol reduced insulin sensitivity and compensated by enhancing beta cell function (β = 1.98, P < .0001 and β = − 1.97, P < .0001 for HOMA-IR and inverse HOMA-β, respectively). T2D-GRS deteriorated insulin secretion (β = 0.10, P = 0.0069 for inverse HOMA-B) but not insulin sensitivity (P = 0.0856). Moreover, there was a significant interaction between alcohol and T2D-GRS (P_interaction = 0.0318), suggesting the association between alcohol and type 2 diabetes was much stronger in the lower T2D-GRS group than in the higher T2D-GRS group. And this interaction was more pronounced in men (P_interaction = 0.0176) than in women (P_interaction = 0.3285). No single SNP interacted strongly with alcohol intake.

Conclusions/interpretation

Alcohol consumption strongly increased the risk of type 2 diabetes by increasing IR, especially in men with low T2D-GRS, highlighting the importance of refraining from drinking alcohol when making recommendations for healthy lifestyle habits to prevent diabetes.

Associations of statin use with glycaemic traits and incident type 2 diabetes

AIMS

There are several epidemiological studies on the association between statins and incident diabetes, but most of them lack details. In this study, we aimed to investigate the association of statin use with glycaemic traits and incident type 2 diabetes.

METHODS

Using the prospective population-based Rotterdam Study, we included 9535 individuals free from diabetes at baseline (>45 years) during the study period between 1997 and 2012. Linear regression analysis was applied to examine the cross-sectional associations between statin use and glycaemic traits including fasting blood serum of glucose and insulin concentrations, and insulin resistance. In a longitudinal follow-up study, we applied a Cox regression analysis to determine adjusted hazard ratios (HR) for incident type 2 diabetes in new users of statins.

RESULTS

The mean age at baseline was 64.3 ± 10.1 years and 41.7% were men. In the fully adjusted model, compared to never users of statins, baseline use of statins was associated with higher concentrations of serum fasting insulin (β = 0.07; 95% CI: 0.02-0.13) and insulin resistance (β = 0.09; 95% CI: 0.03-0.14). Ever use of statins was associated with a 38% higher risk of incident type 2 diabetes (HR = 1.38; 95% CI: 1.09-1.74). This risk was more prominent in subjects with impaired glucose homeostasis and in overweight/obese individuals.

CONCLUSIONS

Individuals using statins may be at higher risk for hyperglycaemia, insulin resistance and eventually type 2 diabetes. Rigorous preventive strategies such as glucose control and weight reduction in patients when initiating statin therapy might help minimize the risk of diabetes.

Genetic Determinants of Glycemic Traits and the Risk of Gestational Diabetes Mellitus

Many common genetic polymorphisms are associated with glycemic traits and type 2 diabetes (T2D), but knowledge about genetic determinants of glycemic traits in pregnancy is limited. We tested genetic variants known to be associated with glycemic traits and T2D in the general population for associations with glycemic traits in pregnancy and gestational diabetes mellitus (GDM). Participants in two cohorts (Genetics of Glucose regulation in Gestation and Growth [Gen3G] and Hyperglycemia and Adverse Pregnancy Outcome [HAPO]) underwent oral glucose tolerance testing at 24-32 weeks' gestation. We built genetic risk scores (GRSs) for elevated fasting glucose and insulin, reduced insulin secretion and sensitivity, and T2D, using variants discovered in studies of nonpregnant individuals. We tested for associations between these GRSs, glycemic traits in pregnancy, and GDM. In both cohorts, the fasting glucose GRS was strongly associated with fasting glucose. The insulin secretion and sensitivity GRSs were also significantly associated with these traits in Gen3G, where insulin measurements were available. The fasting insulin GRS was weakly associated with fasting insulin (Gen3G) or C-peptide (HAPO). In HAPO (207 GDM case subjects), all five GRSs (T2D, fasting glucose, fasting insulin, insulin secretion, and insulin sensitivity) were significantly associated with GDM. In Gen3G (43 GDM case subjects), both the T2D and insulin secretion GRSs were associated with GDM; effect sizes for the other GRSs were similar to those in HAPO. Thus, despite the profound changes in glycemic physiology during pregnancy, genetic determinants of fasting glucose, fasting insulin, insulin secretion, and insulin sensitivity discovered outside of pregnancy influence GDM risk.