Prolonged antibiotic treatment induces a diabetogenic intestinal microbiome that accelerates diabetes in NOD mice

Accumulating evidence supports that the intestinal microbiome is involved in Type 1 diabetes (T1D) pathogenesis through the gut-pancreas nexus. Our aim was to determine whether the intestinal microbiota in the non-obese diabetic (NOD) mouse model played a role in T1D through the gut. To examine the effect of the intestinal microbiota on T1D onset, we manipulated gut microbes by: (1) the fecal transplantation between non-obese diabetic (NOD) and resistant (NOR) mice and (2) the oral antibiotic and probiotic treatment of NOD mice. We monitored diabetes onset, quantified CD4+T cells in the Peyer''s patches, profiled the microbiome and measured fecal short-chain fatty acids (SCFA). The gut microbiota from NOD mice harbored more pathobionts and fewer beneficial microbes in comparison with NOR mice. Fecal transplantation of NOD microbes induced insulitis in NOR hosts suggesting that the NOD microbiome is diabetogenic. Moreover, antibiotic exposure accelerated diabetes onset in NOD mice accompanied by increased T-helper type 1 (Th1) and reduced Th17 cells in the intestinal lymphoid tissues. The diabetogenic microbiome was characterized by a metagenome altered in several metabolic gene clusters. Furthermore, diabetes susceptibility correlated with reduced fecal SCFAs. In an attempt to correct the diabetogenic microbiome, we administered VLS#3 probiotics to NOD mice but found that VSL#3 colonized the intestine poorly and did not delay diabetes. We conclude that NOD mice harbor gut microbes that induce diabetes and that their diabetogenic microbiome can be amplified early in life through antibiotic exposure. Protective microbes like VSL#3 are insufficient to overcome the effects of a diabetogenic microbiome.     

Low Incidence of Spontaneous Type 1 Diabetes in Non-Obese Diabetic Mice Raised on Gluten-Free Diets Is Associated with Changes in the Intestinal Microbiome

Human and animal studies strongly suggest that dietary gluten could play a causal role in the etiopathogenesis of type 1 diabetes (T1D). However, the mechanisms have not been elucidated. Recent reports indicate that the intestinal microbiome has a major influence on the incidence of T1D. Since diet is known to shape the composition of the intestinal microbiome, we investigated using non-obese diabetic (NOD) mice whether changes in the intestinal microbiome could be attributed to the pro- and anti-diabetogenic effects of gluten-containing and gluten-free diets, respectively. NOD mice were raised on gluten-containing chows (GCC) or gluten-free chows (GFC). The incidence of diabetes was determined by monitoring blood glucose levels biweekly using a glucometer. Intestinal microbiome composition was analyzed by sequencing 16S rRNA amplicons derived from fecal samples. First of all, GCC-fed NOD mice had the expected high incidence of hyperglycemia whereas NOD mice fed with a GFC had significantly reduced incidence of hyperglycemia. Secondly, when the fecal microbiomes were compared, Bifidobacterium, Tannerella, and Barnesiella species were increased (p = 0.03, 0.02, and 0.02, respectively) in the microbiome of GCC mice, where as Akkermansia species was increased (p = 0.02) in the intestinal microbiomes of NOD mice fed GFC. Thirdly, both of the gluten-free chows that were evaluated, either egg white based (EW-GFC) or casein based (C-GFC), significantly reduced the incidence of hyperglycemia. Interestingly, the gut microbiome from EW-GFC mice was similar to C-GFC mice. Finally, adding back gluten to the gluten-free diet reversed its anti-diabetogenic effect, reduced Akkermansia species and increased Bifidobacterium, Tannerella, and Barnesiella suggesting that the presence of gluten is directly responsible for the pro-diabetogenic effects of diets and it determines the gut microflora. Our novel study thus suggests that dietary gluten could modulate the incidence of T1D by changing the gut microbiome.     

The double trouble of metabolic diseases: the diabetes–cancer link

The recent recognition of the clinical association between type 2 diabetes (T2D) and several types of human cancer has been further highlighted by reports of antidiabetic drugs treating or promoting cancer. At the cellular level, a plethora of molecules operating within distinct signaling pathways suggests cross-talk between the multiple pathways at the interface of the diabetes–cancer link. Additionally, a growing body of emerging evidence implicates homeostatic pathways that may become imbalanced during the pathogenesis of T2D or cancer or that become chronically deregulated by prolonged drug administration, leading to the development of cancer in diabetes and vice versa. This notion underscores the importance of combining clinical and basic mechanistic studies not only to unravel mechanisms of disease development but also to understand mechanisms of drug action. In turn, this may help the development of personalized strategies in which drug doses and administration durations are tailored to individual cases at different stages of the disease progression to achieve more efficacious treatments that undermine the diabetes–cancer association.     

Association of diabetes and microbiota: An update

Diabetes is an emerging health condition globally and is suggested to have a direct connection with the gut microbiota that determine our metabolic outcomes. Sensitivity to insulin and glucose metabolism is normal in healthy people as compared to those people who cannot maintain their glucose metabolism. One of the reasons of the differences is that healthy people have different microbiome that leads to achieve more short chain fatty acids and make up more branched amino acids, while the gut microbiota of the other group of people are more likely to produce compounds that affects glucose metabolism. Herein, this review will present the research related to the impact of gut microbes on diabetes carried out in the past decade. The review focus on the relation between gut microbiota and Type-1 Diabetes (T1D), Type-2 Diabetes (T2D), and how gut microbiota could be an alternative therapy for treatment of diabetes.     

Common Variants on Cytotoxic T Lymphocyte Antigen-4 Polymorphisms Contributes to Type 1 Diabetes Susceptibility: Evidence Based on 58 Studies

In the past decade, a number of case–control studies have been carried out to investigate the relationship between the CTLA4 gene polymorphisms and type 1 diabetes (T1D). However, these studies have yielded contradictory results. To investigate this inconsistency, we performed a meta-analysis of all available studies dealing with the relationship between the CTLA4 polymorphism and T1D. In total, 58 association studies on two CTLA4 polymorphisms (G49A and C60T) and risk of T1D, including a total of 30,723 T1D cases and 45,254 controls were included. In a combined analysis, the summary per-allele odds ratio (OR) for T1D of the G49A and C60T polymorphism was 1.42 [95% confidence interval (CI): 1.31–1.53, P<10⁻⁵] and 1.23 (95% CI: 1.18–1.29, P<10⁻⁵), respectively. Significant results were also observed using dominant or recessive genetic model. In the subgroup analysis by ethnicity and sample size, significantly increased risks were also found for these polymorphisms. This meta-analysis demonstrated that the G49A and C60T polymorphism of CTLA4 is a risk factor associated with increased T1D susceptibility, but these associations vary in different ethnic populations.     

The role of the gut microbiome and its metabolites in metabolic diseases

It is well known that an unhealthy lifestyle is a major risk factor for metabolic diseases,while in recent years,accumulating evidence has demonstrated that the gut microbiome and its metabolites also play a crucial role in the onset and development of many metabolic dis-eases,including obesity,type 2 diabetes,nonalcoholic fatty liver disease,cardiovascular disease and so on.Numerous microorganisms dwell in the gastrointestinal tract,which is a key interface for energy acquisition and can metabolize dietary nutrients into many bioactive substances,thus acting as a link between the gut microbiome and its host.The gut microbiome is shaped by host genetics,immune responses and dietary fac-tors.The metabolic and immune potential of the gut microbiome determines its significance in host health and diseases.Therefore,targeting the gut microbiome and relevant metabolic pathways would be effective therapeutic treatments for many metabolic diseases in the near future.This review will summarize information about the role of the gut microbiome in organism metabolism and the relationship between gut micro-biome-derived metabolites and the pathogenesis of many metabolic diseases.Furthermore,recent advan-ces in improving metabolic diseases by regulating the gut microbiome will be discussed.     

Quantitative Assessment of the Effect of KCNJ11 Gene Polymorphism on the Risk of Type 2 Diabetes

To clarify the role of potassium inwardly-rectifying-channel, subfamily-J, member 11 (KCNJ11) variation in susceptibility to type 2 diabetes (T2D), we performed a systematic meta-analysis to investigate the association between the KCNJ11 E23K polymorphism (rs5219) and the T2D in different genetic models. Databases including PubMed, Medline, EMBASE, and ISI Web of Science were searched to identify relevant studies. A total of 48 published studies involving 56,349 T2D cases, 81,800 controls, and 483 family trios were included in this meta-analysis. Overall, the E23K polymorphism was significantly associated with increased T2D risk with per-allele odds ratio (OR) of 1.12 (95% CI: 1.09–1.16; P<10⁻⁵). The summary OR for T2D was 1.09 (95% CI: 1.03–1.14; P<10⁻⁵), and 1.26 (95% CI: 1.17–1.35; P<10⁻⁵), for heterozygous and homozygous, respectively. Similar results were also detected under dominant and recessive genetic models. When stratified by ethnicity, significantly increased risks were found for the polymorphism in Caucasians and East Asians. However, no such associations were detected among Indian and other ethnic populations. Significant associations were also observed in the stratified analyses according to different mean BMI of cases and sample size. Although significant between study heterogeneity was identified, meta-regression analysis suggested that the BMI of controls significantly correlated with the magnitude of the genetic effect. The current meta-analysis demonstrated that a modest but statistically significant effect of the 23K allele of rs5219 polymorphism in susceptibility to T2D. But the contribution of its genetic variants to the epidemic of T2D in Indian and other ethnic populations appears to be relatively low.     

Intake of dietary fats and fatty acids and the incidence of type 2 diabetes: A systematic review and dose-response meta-analysis of prospective observational studies

BackgroundThe role of fat quantity and quality in type 2 diabetes (T2D) prevention is controversial. Thus, this systematic review and meta-analysis aimed to investigate the associations between intake of dietary fat and fatty acids and T2D, and to evaluate the certainty of evidence.Methods and findingsWe systematically searched PubMed and Web of Science through 28 October 2019 for prospective observational studies in adults on the associations between intake of dietary fat and fatty acids and T2D incidence. The systematic literature search and data extraction were conducted independently by 2 researchers. We conducted linear and nonlinear random effects dose–response meta-analyses, calculated summary relative risks (SRRs) with their corresponding 95% confidence intervals (95% CIs), and assessed the certainty of evidence. In total, 15,070 publications were identified in the literature search after the removal of duplicates. Out of the 180 articles screened in full text, 23 studies (19 cohorts) met our inclusion criteria, with 11 studies (6 cohorts) conducted in the US, 7 studies (7 cohorts) in Europe, 4 studies (5 cohorts) in Asia, and 1 study (1 cohort) in Australia. We mainly observed no or weak linear associations between dietary fats and fatty acids and T2D incidence. In nonlinear dose–response meta-analyses, the protective association for vegetable fat and T2D was steeper at lower levels up to 13 g/d (SRR [95% CI]: 0.81 [0.76; 0.88], p_nonlinearity = 0.012, n = 5 studies) than at higher levels. Saturated fatty acids showed an apparent protective association above intakes around 17 g/d with T2D (SRR [95% CI]: 0.95 [0.90; 1.00], p_nonlinearity = 0.028, n = 11). There was a nonsignificant association of a decrease in T2D incidence for polyunsaturated fatty acid intakes up to 5 g/d (SRR [95% CI]: 0.96 [0.91; 1.01], p_nonlinearity = 0.023, n = 8), and for alpha-linolenic acid consumption up to 560 mg/d (SRR [95% CI]: 0.95 [0.90; 1.00], p_nonlinearity = 0.014, n = 11), after which the curve rose slightly, remaining close to no association. The association for long-chain omega-3 fatty acids and T2D was approximately linear for intakes up to 270 mg/d (SRR [95% CI]: 1.10 [1.06; 1.15], p_nonlinearity < 0.001, n = 16), with a flattening curve thereafter. Certainty of evidence was very low to moderate. Limitations of the study are the high unexplained inconsistency between studies, the measurement of intake of dietary fats and fatty acids via self-report on a food group level, which is likely to lead to measurement errors, and the possible influence of unmeasured confounders on the findings.ConclusionsThere was no association between total fat intake and the incidence of T2D. However, for specific fats and fatty acids, dose–response curves provided insights for significant associations with T2D. In particular, a high intake of vegetable fat was inversely associated with T2D incidence. Thus, a diet including vegetable fat rather than animal fat might be beneficial regarding T2D prevention.

Manuela Neuenschwander and colleagues study associations between intake of different types of fat and incidence of type 2 diabetes.     

Association of Type 2 Diabetes Genetic Variants with Breast Cancer Survival among Chinese Women

ObjectiveTo evaluate whether the genetic susceptibility of T2D was associated with overall survival (OS) and disease-free survival (DFS) outcomes for breast cancer (BC).MethodsIncluded in the study were 6346 BC patients who participated in three population-based epidemiological studies of BC and were genotyped with either GWAS or Exome-chip. We constructed a genetic risk score (GRS) for diabetes using risk variants identified from the GWAS catalog (http://genome.gov/gwastudies) that were associated with T2D risk at a minimum significance level of P ≤ 5.0E-8 among Asian population and evaluated its associations with BC outcomes with Cox proportional hazards models.ResultsDuring a median follow-up of 8.08 years (range, 0.01–16.95 years), 1208 deaths were documented in 6346 BC patients. Overall, the diabetes GRS was not associated with OS and DFS. Analyses stratified by estrogen receptor status (ER) showed that the diabetes GRS was inversely associated with OS among women with ER- but not in women with ER+ breast cancer; the multivariable adjusted HR was 1.38 (95% CI: 1.05–1.82) when comparing the highest to the lowest GRS quartiles. The association of diabetes GRS with OS varied by diabetes status (P for interaction <0.01). In women with history of diabetes, higher diabetes GRS was significantly associated with worse OS, with HR of 2.22 (95% CI: 1.28–3.88) for the highest vs. lowest quartile, particularly among women with an ER- breast cancer, with corresponding HR being 4.59 (95% CI: 1.04–20.28). No significant association between the diabetes GRS and OS was observed across different BMI and PR groups.ConclusionsOur study suggested that genetic susceptibility of T2D was positively associated with total mortality among women with ER- breast cancer, particularly among subjects with a history of diabetes. Additional studies are warranted to verify the associations and elucidate the underlying biological mechanism.     

Identification of New Genetic Risk Variants for Type 2 Diabetes

Although more than 20 genetic susceptibility loci have been reported for type 2 diabetes (T2D), most reported variants have small to moderate effects and account for only a small proportion of the heritability of T2D, suggesting that the majority of inter-person genetic variation in this disease remains to be determined. We conducted a multistage, genome-wide association study (GWAS) within the Asian Consortium of Diabetes to search for T2D susceptibility markers. From 590,887 SNPs genotyped in 1,019 T2D cases and 1,710 controls selected from Chinese women in Shanghai, we selected the top 2,100 SNPs that were not in linkage disequilibrium (r²<0.2) with known T2D loci for in silico replication in three T2D GWAS conducted among European Americans, Koreans, and Singapore Chinese. The 5 most promising SNPs were genotyped in an independent set of 1,645 cases and 1,649 controls from Shanghai, and 4 of them were further genotyped in 1,487 cases and 3,316 controls from 2 additional Chinese studies. Consistent associations across all studies were found for rs1359790 (13q31.1), rs10906115 (10p13), and rs1436955 (15q22.2) with P-values (per allele OR, 95%CI) of 6.49×10⁻⁹ (1.15, 1.10–1.20), 1.45×10⁻⁸ (1.13, 1.08–1.18), and 7.14×10⁻⁷ (1.13, 1.08–1.19), respectively, in combined analyses of 9,794 cases and 14,615 controls. Our study provides strong evidence for a novel T2D susceptibility locus at 13q31.1 and the presence of new independent risk variants near regions (10p13 and 15q22.2) reported by previous GWAS.     

Obesity and the relation between joint exposure to ambient air pollutants and incident type 2 diabetes: A cohort study in UK Biobank

BackgroundAir pollution has been related to incidence of type 2 diabetes (T2D). We assessed the joint association of various air pollutants with the risk of T2D and examined potential modification by obesity status and genetic susceptibility on the relationship.Methods and findingsA total of 449,006 participants from UK Biobank free of T2D at baseline were included. Of all the study population, 90.9% were white and 45.7% were male. The participants had a mean age of 56.6 (SD 8.1) years old and a mean body mass index (BMI) of 27.4 (SD 4.8) kg/m². Ambient air pollutants, including particulate matter (PM) with diameters ≤2.5 μm (PM_2.5), between 2.5 μm and 10 μm (PM_2.5–10), nitrogen dioxide (NO₂), and nitric oxide (NO) were measured. An air pollution score was created to assess the joint exposure to the 4 air pollutants. During a median of 11 years follow-up, we documented 18,239 incident T2D cases. The air pollution score was significantly associated with a higher risk of T2D. Compared to the lowest quintile of air pollution score, the hazard ratio (HR) (95% confidence interval [CI]) for T2D was 1.05 (0.99 to 1.10, p = 0.11), 1.06 (1.00 to 1.11, p = 0.051), 1.09 (1.03 to 1.15, p = 0.002), and 1.12 (1.06 to 1.19, p < 0.001) for the second to fifth quintile, respectively, after adjustment for sociodemographic characteristics, lifestyle factors, genetic factors, and other covariates. In addition, we found a significant interaction between the air pollution score and obesity status on the risk of T2D (p-interaction < 0.001). The observed association was more pronounced among overweight and obese participants than in the normal-weight people. Genetic risk score (GRS) for T2D or obesity did not modify the relationship between air pollution and risk of T2D. Key study limitations include unavailable data on other potential T2D-related air pollutants and single-time measurement on air pollutants.ConclusionsWe found that various air pollutants PM_2.5, PM_2.5–10, NO_2, and NO, individually or jointly, were associated with an increased risk of T2D in the population. The stratified analyses indicate that such associations were more strongly associated with T2D risk among those with higher adiposity.

Xiang Li and co-workers study the potential influence of obesity on associations between air pollutants and incidence of type 2 diabetes.     

The Association between KCNQ1 Gene Polymorphism and Type 2 Diabetes Risk: A Meta-Analysis

Background

KCNQ1 (potassium voltage-gated channel KQT-like sub-family, member 1) encodes a pore-forming subunit of a voltage-gated K⁺ channel (KvLQT1) that plays a key role for the repolarization of the cardiac action potential as well as water and salt transport in epithelial tissues. Recently, genome-wide association studies have identified KCNQ1 as a type 2 diabetes (T2D) susceptibility gene in populations of Asian descent. After that, a number of studies reported that the rs2237892 and rs2237895 polymorphism in KCNQ1 has been implicated in T2D risk. However, studies on the association between these polymorphism and T2D remain conflicting. To investigate this inconsistency, we performed this meta-analysis.

Methods

Databases including Pubmed, EMBASE, Web of Science and China National Knowledge Infrastructure (CNKI) were searched to find relevant studies. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of association. Potential sources of heterogeneity were also assessed by subgroup analysis and meta-regression.

Results

A total of 25 articles involving 70,577 T2D cases and 99,068 controls were included. Overall, the summary odds ratio of C allele for T2D was 1.32 (95% CI 1.26–1.38; P<10−5) and 1.24 (95% CI: 1.20–1.29; P<10−5) for KCNQ1 rs2237892 and rs2237895 polymorphisms, respectively. Significant results were also observed using co-dominant, dominant and recessive genetic models. After stratifying by ethnicity, sample size, and diagnostic criteria, significant associations were also obtained.

Conclusions

This meta-analysis suggests that the rs2237892 and rs2237895 polymorphisms in KCNQ1 are associated with elevated type 2 diabetes susceptibility.     

Consistent Association of Type 2 Diabetes Risk Variants Found in Europeans in Diverse Racial and Ethnic Groups

It has been recently hypothesized that many of the signals detected in genome-wide association studies (GWAS) to T2D and other diseases, despite being observed to common variants, might in fact result from causal mutations that are rare. One prediction of this hypothesis is that the allelic associations should be population-specific, as the causal mutations arose after the migrations that established different populations around the world. We selected 19 common variants found to be reproducibly associated to T2D risk in European populations and studied them in a large multiethnic case-control study (6,142 cases and 7,403 controls) among men and women from 5 racial/ethnic groups (European Americans, African Americans, Latinos, Japanese Americans, and Native Hawaiians). In analysis pooled across ethnic groups, the allelic associations were in the same direction as the original report for all 19 variants, and 14 of the 19 were significantly associated with risk. In summing the number of risk alleles for each individual, the per-allele associations were highly statistically significant (P<10⁻⁴) and similar in all populations (odds ratios 1.09–1.12) except in Japanese Americans the estimated effect per allele was larger than in the other populations (1.20; P_het = 3.8×10⁻⁴). We did not observe ethnic differences in the distribution of risk that would explain the increased prevalence of type 2 diabetes in these groups as compared to European Americans. The consistency of allelic associations in diverse racial/ethnic groups is not predicted under the hypothesis of Goldstein regarding “synthetic associations” of rare mutations in T2D.     

Novel association in chromosome 4q27 region with rheumatoid arthritis and confirmation of type 1 diabetes point to a general risk locus for autoimmune diseases

Recently, association of celiac disease with common single-nucleotide polymorphism (SNP) variants in an extensive linkage-disequilibrium block of 480 kb containing the KIAA1109, Tenr, IL2, and IL21 genes has been demonstrated in three independent populations (rs6822844 P_combined=1.3×10^-14). The KIAA1109/Tenr/IL2/IL21 block corresponds to the Idd3 locus in the nonobese diabetic mouse model of type 1 diabetes (T1D). This block was recently found to be associated with T1D in a genomewide association study, although this finding lacks unequivocal confirmation. We therefore aimed to investigate whether the KIAA1109/Tenr/IL2/IL21 region is involved in susceptibility to multiple autoimmune diseases. We tested SNP rs6822844 for association with disease in 350 T1D-affected and 1,047 rheumatoid arthritis (RA)–affected Dutch patients and in 929 controls. We replicated the association with T1D (P=.0006; OR 0.64 [95% CI 0.50–0.83]), and revealed a similar novel association with RA (P=.0002; OR 0.72 [95% CI 0.61–0.86]). Our results replicate and extend the association found in the KIAA1109/Tenr/IL2/IL21 gene region with autoimmune diseases, implying that this locus is a general risk factor for multiple autoimmune diseases.     

Where Next for Microbiome Research?

The development of high-throughput sequencing technologies has transformed our capacity to investigate the composition and dynamics of the microbial communities that populate diverse habitats. Over the past decade, these advances have yielded an avalanche of metagenomic data. The current stage of “van Leeuwenhoek”–like cataloguing, as well as functional analyses, will likely accelerate as DNA and RNA sequencing, plus protein and metabolic profiling capacities and computational tools, continue to improve. However, it is time to consider: what’s next for microbiome research? The short pieces included here briefly consider the challenges and opportunities awaiting microbiome research.

This Perspective is part of the “Where next?” Series.

Soon, we will enter an era when “the number of population genomes deposited in public databases will dwarf those from isolates and single cells” (Gene Tyson). Clearly, as all authors noted in the following, our focus will move from describing the composition of microbial communities to elucidating the principles that govern their assembly, dynamics, and functions. How will such principles be discovered? Elhanan Borenstein proposes that a systems biology–based approach, particularly the development of mathematical and computational models of the interactions between the specific community components, will be critical for understanding the function and dynamics of microbiomes. Evolutionary biologists Howard Ochman and Andrew Moeller want to decipher how microbial assemblies evolve but challenge us to also consider the role of microbial communities in organismal evolution, and they make the exciting prediction that microbes will be implicated in the evolution of eusociality and cooperation. Brett Finlay underscores the need for deciphering the mechanistic bases—particularly the chemical/metabolite signals—for interactions between members of microbial communities and their hosts. He emphasizes how this knowledge will enable creation of new tools to manipulate the microbiota, a key challenge for future investigation. Heidi Kong also encourages deciphering the mechanisms that underlie associations between particular skin surfaces and disorders and their respective microbiota. Jeffrey Gordon considers several intriguing opportunities as well as challenges that manipulation of the gut microbiota presents for improved human nutrition and health. Finally, Karen Nelson, Karim Dabbagh and Hamilton Smith suggest that using synthetic genomes to create novel microbes or even synthetic microbiomes offers a new way to engineer the microbiota. Overall, future microbiome research regarding the molecules and mechanisms mediating interactions between members of microbial communities and their hosts should lead to discovery of exciting new biology and transformative therapeutics.     

Associations between UCP1 -3826A/G,UCP2 -866G/A,Ala55Val and Ins/Del,and UCP3 -55C/T Polymorphisms and Susceptibility to Type 2 Diabetes Mellitus: Case-Control Study and Meta-Analysis

Background

Some studies have reported associations between five uncoupling protein (UCP) 1–3 polymorphisms and type 2 diabetes mellitus (T2DM). However, other studies have failed to confirm the associations. This paper describes a case-control study and a meta-analysis conducted to attempt to determine whether the following polymorphisms are associated with T2DM: -3826A/G (UCP1); -866G/A, Ala55Val and Ins/Del (UCP2) and -55C/T (UCP3).

Methods

The case-control study enrolled 981 T2DM patients and 534 nondiabetic subjects, all of European ancestry. A literature search was run to identify all studies that investigated associations between UCP1–3 polymorphisms and T2DM. Pooled odds ratios (OR) were calculated for allele contrast, additive, recessive, dominant and co-dominant inheritance models. Sensitivity analyses were performed after stratification by ethnicity.

Results

In the case-control study the frequencies of the UCP polymorphisms did not differ significantly between T2DM and nondiabetic groups (P>0.05). Twenty-three studies were eligible for the meta-analysis. Meta-analysis results showed that the Ala55Val polymorphism was associated with T2DM under a dominant model (OR = 1.27, 95% CI 1.03–1.57); while the -55C/T polymorphism was associated with this disease in almost all genetic models: allele contrast (OR = 1.17, 95% CI 1.02–1.34), additive (OR = 1.32, 95% CI 1.01–1.72) and dominant (OR = 1.18, 95% CI 1.02–1.37). However, after stratification by ethnicity, the UCP2 55Val and UCP3 -55C/T alleles remained associated with T2DM only in Asians (OR = 1.25, 95% CI 1.02–1.51 and OR = 1.22, 95% CI 1.04–1.44, respectively; allele contrast model). No significant association of the -3826A/G, -866G/A and Ins/Del polymorphisms with T2DM was observed.

Conclusions

In our case-control study of people with European ancestry we were not able to demonstrate any association between the UCP polymorphisms and T2DM; however, our meta-analysis detected a significant association between the UCP2 Ala55Val and UCP3 -55C/T polymorphisms and increased susceptibility for T2DM in Asians.     

Associations among circulating sphingolipids, β-cell function,and risk of developing type 2 diabetes: A population-based cohort study in China

BackgroundAnimal studies suggest vital roles of sphingolipids, especially ceramides, in the pathogenesis of type 2 diabetes (T2D) via pathways involved in insulin resistance, β-cell dysfunction, and inflammation, but human studies are limited. We aimed to evaluate the associations of circulating sphingolipids with incident T2D and to explore underlying mechanisms.Methods and findingsThe current study included 826 men and 1,148 women who were aged 50–70 years, from Beijing and Shanghai, and without T2D in 2005 and who were resurveyed in 2011. Cardiometabolic traits were measured at baseline and follow-up surveys. A total of 76 sphingolipids were quantified using high-coverage targeted lipidomics. Summary data for 2-sample Mendelian randomization were obtained from genome-wide association studies of circulating sphingolipids and the China Health and Nutrition Survey (n = 5,731). During the 6-year period, 529 participants developed T2D. Eleven novel and 3 reported sphingolipids, namely ceramides (d18:1/18:1, d18:1/20:0, d18:1/20:1, d18:1/22:1), saturated sphingomyelins (C34:0, C36:0, C38:0, C40:0), unsaturated sphingomyelins (C34:1, C36:1, C42:3), hydroxyl-sphingomyelins (C34:1, C38:3), and a hexosylceramide (d18:1/20:1), were positively associated with incident T2D (relative risks [RRs]: 1.14–1.21; all P < 0.001), after multivariate adjustment including lifestyle characteristics and BMI. Network analysis further identified 5 modules, and 2 modules containing saturated sphingomyelins showed the strongest associations with increased T2D risk (RR_{Q4 versus Q1} = 1.59 and 1.43; both P_trend < 0.001). Mediation analysis suggested that the detrimental associations of 13 sphingolipids with T2D were largely mediated through β-cell dysfunction, as indicated by HOMA-B (mediation proportion: 11.19%–42.42%; all P < 0.001). Moreover, Mendelian randomization evidenced a positive association between a genetically instrumented ceramide (d18:1/20:1) and T2D (odds ratio: 1.15 [95% CI 1.05–1.26]; P = 0.002). Main limitations in the current study included potential undiagnosed cases and lack of an independent population for replication.ConclusionsIn this study, we observed that a panel of novel sphingolipids with unique structures were positively associated with incident T2D, largely mediated through β-cell dysfunction, in Chinese individuals.     

No Interaction with Alcohol Consumption,but Independent Effect of C12orf51 (HECTD4) on Type 2 Diabetes Mellitus in Korean Adults Aged 40-69 Years: The KoGES_Ansan and Ansung Study

Previously, genetic polymorphisms of C12orf51 (HECTD4) (rs2074356 and/or rs11066280) have been shown to be related to alcohol consumption and type 2 diabetes (T2D). This study aimed to prospectively examine whether C12orf51 had an interaction with or independent effect on alcohol consumption and the risk of T2D. The present study included 3,244 men and 3,629 women aged 40 to 69 years who participated in the Korean Genome and Epidemiology Study (KoGES)_Ansan and Ansung Study. Cox proportional hazards models were used to estimate HRs and 95% CIs for T2D. rs2074356 and rs11066280 were associated with the risk of T2D after adjusting for alcohol consumption (rs2074356 for AA: HR = 0.39 and 95% CI = 0.17–0.87 in men, and HR = 0.36 and 95% CI = 0.13–0.96 in women; rs11066280 for AA: HR = 0.44 and 95% CI = 0.23–0.86 in men, and HR = 0.39 and 95% CI = 0.16–0.94 in women). We identified that the association of each variant (rs2074356 and rs11065756) in C12orf51 was nearly unchanged after adjusted for alcohol consumption. Therefore, the association of 2 SNPs in C12orf51 with diabetes may not be mediated by alcohol use. There was no interaction effect between alcohol consumption and the SNPs with T2D. However, even in never-drinkers, minor allele homozygote strongly influenced T2D risk reduction (rs2074356 for AA: HR = 0.35, 95% CI = 0.14–0.90, and p-trend = 0.0035 in men and HR = 0.34, 95% CI = 0.13–0.93, and p-trend = 0.2348 in women; rs11066280 for AA: HR = 0.36, 95% CI = 0.16–0.82, and p-trend = 0.0014 in men and HR = 0.39, 95% CI = 0.16–0.95, and p-trend = 0.3790 in women), while alcohol consumption did not influence the risk of T2D within each genotype. rs2074356 and rs11066280 in or near C12orf51, which is related to alcohol drinking behavior, may longitudinally decrease the risk of T2D, but not through regulation of alcohol consumption.     

Mendelian randomization study of B-type natriuretic peptide and type 2 diabetes: evidence of causal association from population studies

Background

Genetic and epidemiological evidence suggests an inverse association between B-type natriuretic peptide (BNP) levels in blood and risk of type 2 diabetes (T2D), but the prospective association of BNP with T2D is uncertain, and it is unclear whether the association is confounded.

Methods and Findings

We analysed the association between levels of the N-terminal fragment of pro-BNP (NT-pro-BNP) in blood and risk of incident T2D in a prospective case-cohort study and genotyped the variant rs198389 within the BNP locus in three T2D case-control studies. We combined our results with existing data in a meta-analysis of 11 case-control studies. Using a Mendelian randomization approach, we compared the observed association between rs198389 and T2D to that expected from the NT-pro-BNP level to T2D association and the NT-pro-BNP difference per C allele of rs198389. In participants of our case-cohort study who were free of T2D and cardiovascular disease at baseline, we observed a 21% (95% CI 3%–36%) decreased risk of incident T2D per one standard deviation (SD) higher log-transformed NT-pro-BNP levels in analysis adjusted for age, sex, body mass index, systolic blood pressure, smoking, family history of T2D, history of hypertension, and levels of triglycerides, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol. The association between rs198389 and T2D observed in case-control studies (odds ratio = 0.94 per C allele, 95% CI 0.91–0.97) was similar to that expected (0.96, 0.93–0.98) based on the pooled estimate for the log-NT-pro-BNP level to T2D association derived from a meta-analysis of our study and published data (hazard ratio = 0.82 per SD, 0.74–0.90) and the difference in NT-pro-BNP levels (0.22 SD, 0.15–0.29) per C allele of rs198389. No significant associations were observed between the rs198389 genotype and potential confounders.

Conclusions

Our results provide evidence for a potential causal role of the BNP system in the aetiology of T2D. Further studies are needed to investigate the mechanisms underlying this association and possibilities for preventive interventions. Please see later in the article for the Editors'' Summary     

Circadian gene variants and susceptibility to type 2 diabetes: a pilot study

Background

Disruption of endogenous circadian rhythms has been shown to increase the risk of developing type 2 diabetes, suggesting that circadian genes might play a role in determining disease susceptibility. We present the results of a pilot study investigating the association between type 2 diabetes and selected single nucleotide polymorphisms (SNPs) in/near nine circadian genes. The variants were chosen based on their previously reported association with prostate cancer, a disease that has been suggested to have a genetic link with type 2 diabetes through a number of shared inherited risk determinants.

Methodology/Principal Findings

The pilot study was performed using two genetically homogeneous Punjabi cohorts, one resident in the United Kingdom and one indigenous to Pakistan. Subjects with (N = 1732) and without (N = 1780) type 2 diabetes were genotyped for thirteen circadian variants using a competitive allele-specific polymerase chain reaction method. Associations between the SNPs and type 2 diabetes were investigated using logistic regression. The results were also combined with in silico data from other South Asian datasets (SAT2D consortium) and white European cohorts (DIAGRAM+) using meta-analysis. The rs7602358G allele near PER2 was negatively associated with type 2 diabetes in our Punjabi cohorts (combined odds ratio [OR] = 0.75 [0.66–0.86], p = 3.18×10⁻⁵), while the BMAL1 rs11022775T allele was associated with an increased risk of the disease (combined OR = 1.22 [1.07–1.39], p = 0.003). Neither of these associations was replicated in the SAT2D or DIAGRAM+ datasets, however. Meta-analysis of all the cohorts identified disease associations with two variants, rs2292912 in CRY2 and rs12315175 near CRY1, although statistical significance was nominal (combined OR = 1.05 [1.01–1.08], p = 0.008 and OR = 0.95 [0.91–0.99], p = 0.015 respectively).

Conclusions/significance

None of the selected circadian gene variants was associated with type 2 diabetes with study-wide significance after meta-analysis. The nominal association observed with the CRY2 SNP, however, complements previous findings and confirms a role for this locus in disease susceptibility.