Assessment of soluble epoxide hydrolase activity in vivo: A metabolomic approach.

Soluble epoxide hydrolase (sEH) converts several FFA epoxides to corresponding diols. As many as 15 FFA epoxide-diol ratios are measured to infer sEH activity from their ratios. Using previous data, we assessed if individual epoxide-diol ratios all behave similarly to reflect changes in sEH activity, and whether analyzing these ratios together increases the power to detect changes in in-vivo sEH activity. We demonstrated that epoxide-diol ratios correlated strongly with each other (P < 0.05), suggesting these ratios all reflect changes in sEH activity. Furthermore, we developed a modeling approach to analyze all epoxide-diol ratios simultaneously to infer global sEH activity, named SAMI (Simultaneous Analysis of Multiple Indices). SAMI improved power in detecting changes in sEH activity in animals and humans when compared to individual ratio estimates. Thus, we introduce a new powerful method to infer sEH activity by combining metabolomic determination and simultaneous analysis of all measurable epoxide-diol pairs.

Genetic regulatory signatures underlying islet gene expression and type 2 diabetes.

Genome-wide association studies (GWAS) have identified >100 independent SNPs that modulate the risk of type 2 diabetes (T2D) and related traits. However, the pathogenic mechanisms of most of these SNPs remain elusive. Here, we examined genomic, epigenomic, and transcriptomic profiles in human pancreatic islets to understand the links between genetic variation, chromatin landscape, and gene expression in the context of T2D. We first integrated genome and transcriptome variation across 112 islet samples to produce dense cis-expression quantitative trait loci (cis-eQTL) maps. Additional integration with chromatin-state maps for islets and other diverse tissue types revealed that cis-eQTLs for islet-specific genes are specifically and significantly enriched in islet stretch enhancers. High-resolution chromatin accessibility profiling using assay for transposase-accessible chromatin sequencing (ATAC-seq) in two islet samples enabled us to identify specific transcription factor (TF) footprints embedded in active regulatory elements, which are highly enriched for islet cis-eQTL. Aggregate allelic bias signatures in TF footprints enabled us de novo to reconstruct TF binding affinities genetically, which support the high-quality nature of the TF footprint predictions. Interestingly, we found that T2D GWAS loci were strikingly and specifically enriched in islet Regulatory Factor X (RFX) footprints. Remarkably, within and across independent loci, T2D risk alleles that overlap with RFX footprints uniformly disrupt the RFX motifs at high-information content positions. Together, these results suggest that common regulatory variations have shaped islet TF footprints and the transcriptome and that a confluent RFX regulatory grammar plays a significant role in the genetic component of T2D predisposition.

A diet high in sugar-sweetened beverage and low in fruits and vegetables is associated with adiposity and a pro-inflammatory adipokine profile.

Diet, obesity and adipokines play important roles in diabetes and CVD; yet, limited studies have assessed the relationship between diet and multiple adipokines. This cross-sectional study assessed associations between diet, adiposity and adipokines in Mexican Americans. The cohort included 1128 participants (age 34·7±8·2 years, BMI 29·5±5·9 kg/m2, 73·2 % female). Dietary intake was assessed by 12-month food frequency questionnaire. Adiposity was measured by BMI, total percentage body fat and percentage trunk fat using dual-energy X-ray absorptiometry. Adiponectin, apelin, C-reactive protein (CRP), dipeptidyl peptidase-4 (DPP-IV), IL-1ß, IL-1ra, IL-6, IL-18, leptin, lipocalin, monocyte chemo-attractant protein-1 (MCP-1), resistin, secreted frizzled protein 4 (SFRP-4), SFRP-5, TNF-α and visfatin were assayed with multiplex kits or ELISA. Joint multivariate associations between diet, adiposity and adipokines were analysed using canonical correlations adjusted for age, sex, energy intake and kinship. The median (interquartile range) energy intake was 9514 (7314, 11912) kJ/d. Overall, 55 % of total intake was accounted for by carbohydrates (24 % from sugar). A total of 66 % of the shared variation between diet and adiposity, and 34 % of diet and adipokines were explained by the top canonical correlation. The diet component was most represented by sugar-sweetened beverages (SSB), fruit and vegetables. Participants consuming a diet high in SSB and low in fruits and vegetables had higher adiposity, CRP, leptin, and MCP-1, but lower SFRP-5 than participants with high fruit and vegetable and low SSB intake. In Mexican Americans, diets high in SSB but low in fruits and vegetables contribute to adiposity and a pro-inflammatory adipokine profile.

Genetic variation in MTNR1B is associated with gestational diabetes mellitus and contributes only to the absolute level of beta cell compensation in Mexican Americans.

AIMS/HYPOTHESIS: MTNR1B is a type 2 diabetes susceptibility locus associated with cross-sectional measures of insulin secretion. We hypothesised that variation in MTNR1B contributes to the absolute level of a diabetes-related trait, temporal rate of change in that trait, or both. METHODS: We tested rs10830963 for association with cross-sectional diabetes-related traits in up to 1,383 individuals or with rate of change in the same phenotypes over a 3-5 year follow-up in up to 374 individuals from the family-based BetaGene study of Mexican Americans. RESULTS: rs10830963 was associated cross-sectionally with fasting glucose (p = 0.0069), acute insulin response (AIR; p = 0.0013), disposition index (p = 0.00078), glucose effectiveness (p = 0.018) and gestational diabetes mellitus (OR 1.48; p = 0.012), but not with OGTT 30 min Δinsulin (the difference between the 30 min and fasting plasma insulin concentration) or 30 min insulin-based disposition index. rs10830963 was also associated with rate of change in fasting glucose (p = 0.043), OGTT 30 min Δinsulin (p = 0.01) and AIR (p = 0.037). There was no evidence for an association with the rate of change in beta cell compensation for insulin resistance. CONCLUSIONS/INTERPRETATION: We conclude that variation in MTNR1B contributes to the absolute level of insulin secretion but not to differences in the temporal rate of change in insulin secretion. The observed association with the rate of change in insulin secretion reflects the natural physiological response to changes in underlying insulin sensitivity and is not a direct effect of the variant.

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

OBJECTIVE: While most genetic variants of type 2 diabetes (T2D) are suggested to be associated with ß-cell dysfunction cross sectionally, their association with the longitudinal change of ß-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 ß-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 ß-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.

Longitudinal changes in insulin sensitivity and beta cell function between women with and without a history of gestational diabetes mellitus.

AIMS/HYPOTHESIS: The aim of the study was to compare longitudinal changes in insulin sensitivity (SI) and beta cell function between women with and without a history of gestational diabetes mellitus (GDM). METHODS: The prospective follow-up cohort included 235 parous non-diabetic Mexican-American women, 93 with and 142 without a history of GDM. The participants underwent dual-energy x-ray absorptiometry, OGTTs and IVGTTs at baseline and at a median of 4.1 years follow-up. The baseline values and rates of change of metabolic measures were compared between groups. RESULTS: At baseline, women with prior GDM (mean age 36.3 years) had similar values of SI but higher percentages of body fat and trunk fat (p ≤ 0.02), a lower acute insulin response and poorer beta cell compensation (disposition index [DI]) (p < 0.0001) than women without GDM (mean age 37.9 years). During the follow-up, women with GDM had a faster decline in SI (p = 0.02) and DI (p = 0.02) than their counterparts without GDM, with no significant differences in changes of weight or fat (p > 0.50). Adjustment for baseline age, adiposity, calorie intake, physical activity, age at first pregnancy, additional pregnancies and changes in adiposity during follow-up increased the between-group differences in the rates of change of SI and DI (p ≤ 0.003). CONCLUSIONS/INTERPRETATION: Mexican-American women with recent GDM had a faster deterioration in insulin sensitivity and beta cell compensation than their parous counterparts without GDM. The differences were not explained by differences in adiposity, suggesting more deleterious effects of existing fat and/or reduced beta cell robustness in women with GDM.

High-fat diet is associated with obesity-mediated insulin resistance and ß-cell dysfunction in Mexican Americans.

Consumption of energy-dense, nutrient-poor foods has contributed to the rising incidence of obesity and may underlie insulin resistance and ß-cell dysfunction. Macronutrient intake patterns were examined in relation to anthropometric and metabolic traits in participants of BetaGene, a family-based study of obesity, insulin resistance, and ß-cell dysfunction in Mexican Americans. Dietary intake, body composition, insulin sensitivity (SI), and ß-cell function [Disposition Index (DI)] were assessed by food-frequency questionnaires, dual-energy X-ray absorptiometry, and intravenous glucose-tolerance tests, respectively. Patterns of macronutrient intake were identified by using a K-means model based on the proportion of total energy intake per day attributable to carbohydrate, fat, and protein and were tested for association with anthropometric and metabolic traits. Among 1150 subjects aged 18-65 y (73% female), tertiles of fat intake were associated with greater adiposity and lower SI, after adjustment for age, sex, and daily energy intake. Moreover, 3 distinct dietary patterns were identified: "high fat" (35% fat, 44% carbohydrate, 21% protein; n = 238), "moderate fat" (28% fat, 54% carbohydrate, 18% protein; n = 520), and "low fat" (20% fat, 65% carbohydrate, 15% protein; n = 392). Compared with the low-fat group, the high-fat group had higher age- and sex-adjusted mean body mass index, body fat percentage, and trunk fat and lower SI and DI. Further adjustment for daily energy intake by matching individuals across dietary pattern groups yielded similar results. None of the observed associations were altered after adjustment for physical activity; however, associations with SI and DI were attenuated after adjustment for adiposity. These findings suggest that high-fat diets may contribute to increased adiposity and concomitant insulin resistance and ß-cell dysfunction in Mexican Americans.

Mind- and Body-Based Interventions Improve Glycemic Control in Patients with Type 2 Diabetes: A Systematic Review and Meta-Analysis.

Aims/Hypothesis: Only 51% of patients with type 2 diabetes achieve the hemoglobin A1c (HbA1c) <7% target. Mind and body practices have been increasingly used to improve glycemic control among patients with type 2 diabetes, but studies show inconsistent efficacy. The authors conducted a systematic review and meta-analysis to assess the association between mind and body practices, and mean change in HbA1c and fasting blood glucose (FBG) in patients with type 2 diabetes. Methods: The authors conducted a literature search of Ovid MEDLINE, Embase, and ClinicalTrials.gov seeking through June 10, 2022, published articles on mind and body practices and type 2 diabetes. Two reviewers independently appraised full text of articles. Only intervention studies were included. Reviewers extracted data for meta-analysis. Restricted maximum likelihood random-effects modeling was used to calculate the mean differences and summary effect sizes. The authors assessed heterogeneity using Cochran's Q and I2 statistics. Funnel plots were generated for each outcome to gauge publication bias. Weighted linear models were used to conduct study-level meta-regression analyses of practice frequency. Results: The authors identified 587 articles with 28 meeting the inclusion criteria. A statistically significant and clinically relevant mean reduction in HbA1c of -0.84% (95% confidence interval [CI]: -1.10% to -0.58%; p < 0.0001) was estimated. Reduction was observed in all intervention subgroups: mindfulness-based stress reduction: -0.48% (95% CI: -0.72% to -0.23%; p = 0.03), qigong: -0.66% (95% CI: -1.18% to -0.14%; p = 0.01), and yoga: -1.00% (95% CI: -1.38% to -0.63%; p < 0.0001). Meta-regression revealed that for every additional day of yoga practice per week, the raw mean HbA1c differed by -0.22% (95% CI: -0.44% to -0.003%; p = 0.046) over the study period. FBG significantly improved following mind and body practices, with overall mean difference of -22.81 mg/dL (95% CI: -33.07 to -12.55 mg/dL; p < 0.0001). However, no significant association was found between the frequency of weekly yoga practice and change in FBG over the study period. Conclusions/Interpretation: Mind and body practices are strongly associated with improvement in glycemic control in patients with type 2 diabetes. The overall mean reduction in HbA1c and FBG was clinically significant, suggesting that mind and body practices may be an effective, complementary nonpharmacological intervention for type 2 diabetes. Additional analyses revealed that the mean decrease in HbA1c was greater in studies requiring larger number of yoga practice sessions each week.

Pancreatic iron and glucose dysregulation in thalassemia major.

Pancreatic iron overload and diabetes mellitus (DM) are common in thalassemia major patients. However, the relationship between iron stores and glucose disturbances is not well defined. We used a frequently sampled oral glucose tolerance test (OGTT), coupled with mathematical modeling, and magnetic resonance imaging (MRI) to examine the impact of pancreatic, cardiac, and hepatic iron overload on glucose regulation in 59 patients with thalassemia major. According to OGTT results, 11 patients had DM, 12 had impaired glucose tolerance (IGT), 8 had isolated impaired fasting glucose (IFG), and 28 patients had normal glucose tolerance (NGT). Patients with DM had significantly impaired insulin sensitivity and insulin release. Insulin resistance was most strongly associated with markers of inflammation and somatic iron overload, while disposition index (DI) (a measure of beta cell function) was most strongly correlated with pancreas R2*. Patients with DM and IGT had significantly worse DI than those with NGT or IFG, suggesting significant beta cell toxicity. One-third of patients having elevated pancreas R2* had normal glucose regulation (preclinical iron burden), but these patients were younger and had lower hepatic iron burdens. Our study indicates that pancreatic iron is the strongest predictor of beta cell toxicity, but total body iron burden, age, and body habitus also influence glucose regulation. We also demonstrate that MRI and fasting glucose/insulin are complementary screening tools, reducing the need for oral glucose tolerance testing, and identify high-risk patients before irreversible pancreatic damage.

A principal components-based clustering method to identify variants associated with complex traits.

BACKGROUND: Multivariate methods ranging from joint SNP to principal components analysis (PCA) have been developed for testing multiple markers in a region for association with disease and disease-related traits. However, these methods suffer from low power and/or the inability to identify the subset of markers contributing to evidence for association under various scenarios. METHODS: We introduce orthoblique principal components-based clustering (OPCC) as an alternative approach to identify specific subsets of markers showing association with a quantitative outcome of interest. We demonstrate the utility of OPCC using simulation studies and an example from the literature on type 2 diabetes. RESULTS: Compared to traditional methods, OPCC has similar or improved power under various scenarios of linkage disequilibrium structure and genotype availability. Most importantly, our simulations show how OPCC accurately parses large numbers of markers to a subset containing the causal variant or its proxy. CONCLUSION: OPCC is a powerful and efficient data reduction method for detecting associations between gene variants and disease-related traits. Unlike alternative methodologies, OPCC has the ability to isolate the effect of causal SNP(s) from among large sets of markers in a candidate region. Therefore, OPCC is an improvement over PCA for testing multiple SNP associations with phenotypes of interest.

Corrigendum: Insulin Action, Glucose Homeostasis and Free Fatty Acid Metabolism: Insights From a Novel Model.

[This corrects the article DOI: 10.3389/fendo.2021.625701.].

Insulin Action, Glucose Homeostasis and Free Fatty Acid Metabolism: Insights From a Novel Model.

Glucose and free fatty acids (FFA) are essential nutrients that are both partly regulated by insulin. Impaired insulin secretion and insulin resistance are hallmarks of aberrant glucose disposal, and type 2 diabetes (T2DM). In the current study, a novel model of FFA kinetics is proposed to estimate the role insulin action on FFA lipolysis and oxidation allowing estimation of adipose tissue insulin sensitivity (SIFFA ). Twenty-five normal volunteers were recruited for the current study. To participate, volunteers had to be less than 40 years of age and have a body mass index (BMI) < 30 kg/m2, and be free of medical comorbidity. The proposed model of FFA kinetics was used to analyze the data derived from the insulin-modified FSIGT. Mean fractional standard deviations of the parameter estimates were all less than 20%. Standardized residuals of the fit of the model to the FFA temporal data were randomly distributed, with only one estimated point lying outside the 2-standard deviation range, suggesting an acceptable fit of the model to the FFA data. The current study describes a novel one-compartment non-linear model of FFA kinetics during an FSIGT that provides an FFA metabolism insulin sensitivity parameter (SIFFA ). Furthermore, the models suggest a new role of glucose as the modulator of FFA disposal. Estimates of SIFFA confirmed previous findings that FFA metabolism is more sensitive to changes in insulin than glucose metabolism. Novel derived indices of insulin sensitivity of FFA (SIFFA ) were correlated with minimal model indices. These associations suggest a cooperative rather than competitive interplay between the two primary nutrients (glucose and FFA) and allude to the FFA acting as the buffer, such that glucose homeostasis is maintained.

The genetics of insulin resistance: Where's Waldo?

The physiologic hallmarks of type 2 diabetes are insulin resistance in hepatic and peripheral tissues and pancreatic ß-cell dysfunction. Thus, genetic loci underlying susceptibility to type 2 diabetes are likely to map to one of these endophenotypes. Genome-wide association studies have now identified up to 38 susceptibility loci for type 2 diabetes and a number of other loci underlying variation in type 2 diabetes-related quantitative traits. The majority are of unknown biology or map to pancreatic ß-cell dysfunction. A seemingly disproportionate minority map to insulin resistance. We briefly discuss the known insulin resistance loci identified from genome-wide association, and then discuss reasons why additional insulin resistance loci have not been identified. We present alternative views that may partly explain the apparent dearth of insulin resistance loci contributing to genetic susceptibility to type 2 diabetes, rather than focus on traditional issues such as study design and sampling, which have been addressed elsewhere.

Prioritized subset analysis: improving power in genome-wide association studies.

BACKGROUND: Genome-wide association studies (GWAS) are now feasible for studying the genetics underlying complex diseases. For many diseases, a list of candidate genes or regions exists and incorporation of such information into data analyses can potentially improve the power to detect disease variants. Traditional approaches for assessing the overall statistical significance of GWAS results ignore such information by inherently treating all markers equally. METHODS: We propose the prioritized subset analysis (PSA), in which a prioritized subset of markers is pre-selected from candidate regions, and the false discovery rate (FDR) procedure is carried out in the prioritized subset and its complementary subset, respectively. RESULTS: The PSA is more powerful than the whole-genome single-step FDR adjustment for a range of alternative models. The degree of power improvement depends on the fraction of associated SNPs in the prioritized subset and their nominal power, with higher fraction of associated SNPs and higher nominal power leading to more power improvement. The power improvement can be substantial; for disease loci not included in the prioritized subset, the power loss is almost negligible. CONCLUSION: The PSA has the flexibility of allowing investigators to combine prior information from a variety of sources, and will be a useful tool for GWAS.

Genome-Wide Association Study Identifies Loci for Liver Enzyme Concentrations in Mexican Americans: The GUARDIAN Consortium.

OBJECTIVE: Populations of Mexican American ancestry are at an increased risk for nonalcoholic fatty liver disease. The objective of this study was to determine whether loci in known and novel genes were associated with variation in aspartate aminotransferase (AST) (n = 3,644), alanine aminotransferase (ALT) (n = 3,595), and gamma-glutamyl transferase (GGT) (n = 1,577) levels by conducting the first genome-wide association study (GWAS) of liver enzymes, which commonly measure liver function, in individuals of Mexican American ancestry. METHODS: Levels of AST, ALT, and GGT were determined by enzymatic colorimetric assays. A multi-cohort GWAS of individuals of Mexican American ancestry was performed. Single-nucleotide polymorphisms (SNP) were tested for association with liver outcomes by multivariable linear regression using an additive genetic model. Association analyses were conducted separately in each cohort, followed by a nonparametric meta-analysis. RESULTS: In the PNPLA3 gene, rs4823173 (P = 3.44 × 10-10 ), rs2896019 (P = 7.29 × 10-9 ), and rs2281135 (P = 8.73 × 10-9 ) were significantly associated with AST levels. Although not genome-wide significant, these same SNPs were the top hits for ALT (P = 7.12 × 10-8 , P = 1.98 × 10-7 , and P = 1.81 × 10-7 , respectively). The strong correlation (r2 = 1.0) for these SNPs indicated a single hit in the PNPLA3 gene. No genome-wide significant associations were found for GGT. CONCLUSIONS: PNPLA3, a locus previously identified with ALT, AST, and nonalcoholic fatty liver disease in European and Japanese GWAS, is also associated with liver enzymes in populations of Mexican American ancestry.

Screening of 134 single nucleotide polymorphisms (SNPs) previously associated with type 2 diabetes replicates association with 12 SNPs in nine genes.

More than 120 published reports have described associations between single nucleotide polymorphisms (SNPs) and type 2 diabetes. However, multiple studies of the same variant have often been discordant. From a literature search, we identified previously reported type 2 diabetes-associated SNPs. We initially genotyped 134 SNPs on 786 index case subjects from type 2 diabetes families and 617 control subjects with normal glucose tolerance from Finland and excluded from analysis 20 SNPs in strong linkage disequilibrium (r(2) > 0.8) with another typed SNP. Of the 114 SNPs examined, we followed up the 20 most significant SNPs (P < 0.10) on an additional 384 case subjects and 366 control subjects from a population-based study in Finland. In the combined data, we replicated association (P < 0.05) for 12 SNPs: PPARG Pro12Ala and His447, KCNJ11 Glu23Lys and rs5210, TNF -857, SLC2A2 Ile110Thr, HNF1A/TCF1 rs2701175 and GE117881_360, PCK1 -232, NEUROD1 Thr45Ala, IL6 -598, and ENPP1 Lys121Gln. The replication of 12 SNPs of 114 tested was significantly greater than expected by chance under the null hypothesis of no association (P = 0.012). We observed that SNPs from genes that had three or more previous reports of association were significantly more likely to be replicated in our sample (P = 0.03), although we also replicated 4 of 58 SNPs from genes that had only one previous report of association.

Physiologic Interpretation of GWAS Signals for Type 2 Diabetes.

This chapter reviews both statistical and physiologic issues related to the pathophysiologic effects of genetic variation in the context of type 2 diabetes. The goal is to review current methodologies used to analyze disease-related quantitative traits for those who do not have extensive quantitative and physiologic background, as an attempt to bridge that gap. We leverage mathematical modeling to illustrate the strengths and weaknesses of different approaches and attempt to reinforce with real data analysis. Topics reviewed include phenotype selection, phenotype specificity, multiple variant analysis via the genetic risk score, and consideration of multiple disease-related phenotypes. Type 2 diabetes is used as the example, not only because of the extensive existing knowledge at the genetic, physiologic, clinical, and epidemiologic levels, but also because type 2 diabetes has been at the forefront of complex disease genetics, with many examples to draw from.

Longitudinal Increases in Adiposity Contribute to Worsening Adipokine Profile over Time in Mexican Americans.

OBJECTIVE: Limited studies have assessed the relationship between longitudinal changes in adiposity and changes in multiple adipokines over time. This study examined changes in BMI, total body fat, and trunk fat associated with changes in 16 circulating adipokines in Mexican Americans at risk for type 2 diabetes. METHODS: Participants included 1,213 individuals with cross-sectional data and a subset of 368 individuals with follow-up measures (mean 4.6 ± 1.5 years from baseline). Joint multivariate associations between 3 adiposity measures and 16 adipokines were assessed by canonical correlation analysis. RESULTS: Longitudinal increases in adiposity were most strongly associated with increasing leptin, C-reactive protein (CRP), and interleukin 1 receptor antagonist (IL-1Ra) and decreasing adiponectin and secreted frizzled protein 5 (SFRP5) over time. Participants with BMI ≥ 30 kg/m2 at baseline had greater increases in leptin, CRP, IL-1Ra, and interleukin 6 (IL-6) and greater decreases in adiponectin and SFRP5, associated with increasing adiposity over follow-up, than those with BMI < 30 kg/m2 . Associations between adiposity and adipokines were most accounted for by leptin; adjustment for leptin greatly reduced the magnitude of all associations between adiposity and remaining adipokines. CONCLUSIONS: Increasing adiposity contributes to a worsening imbalance of pro- and anti-inflammatory adipokines over time, in which leptin may have an important role as a key mediator of metabolic disease risk in Mexican Americans.

Association of weight gain and fifteen adipokines with declining beta-cell function in Mexican Americans.

Obesity and adipokines are associated with development of type 2 diabetes. However, limited longitudinal studies have examined their roles on declining ß-cell function over time. This report assessed three adiposity measures (BMI, percent body fat, trunk fat), insulin resistance, and fifteen adipokines in relationship to longitudinal change in ß-cell function measured by disposition index (DI) from frequently-sampled-intravenous-glucose-tolerance testing. The results showed that three factors were significantly and independently associated with rate of change in DI over time: rate of change in BMI (negative), rate of change in IL-6 (negative), and baseline adiponectin (positive). The association was the strongest for changing BMI and was largely explained by changing insulin resistance; the association with changing IL-6 was also largely explained by changing insulin resistance. Baseline adiponectin remained positively associated after adjustment for changing insulin resistance, suggesting an independent effect of adiponectin to preserve or improve ß-cell function. These findings provide evidence and potential mechanisms for the role of obesity in promoting ß-cell dysfunction, highlighting the potential importance of mitigating obesity and its metabolic effects in preventing and treating type 2 diabetes.

Exome Sequencing Identifies Genetic Variants Associated with Circulating Lipid Levels in Mexican Americans: The Insulin Resistance Atherosclerosis Family Study (IRASFS).

Genome-wide association studies have identified numerous variants associated with lipid levels; yet, the majority are located in non-coding regions with unclear mechanisms. In the Insulin Resistance Atherosclerosis Family Study (IRASFS), heritability estimates suggest a strong genetic basis: low-density lipoprotein (LDL, h2 = 0.50), high-density lipoprotein (HDL, h2 = 0.57), total cholesterol (TC, h2 = 0.53), and triglyceride (TG, h2 = 0.42) levels. Exome sequencing of 1,205 Mexican Americans (90 pedigrees) from the IRASFS identified 548,889 variants and association and linkage analyses with lipid levels were performed. One genome-wide significant signal was detected in APOA5 with TG (rs651821, PTG = 3.67 × 10-10, LODTG = 2.36, MAF = 14.2%). In addition, two correlated SNPs (r2 = 1.0) rs189547099 (PTG = 6.31 × 10-08, LODTG = 3.13, MAF = 0.50%) and chr4:157997598 (PTG = 6.31 × 10-08, LODTG = 3.13, MAF = 0.50%) reached exome-wide significance (P < 9.11 × 10-08). rs189547099 is an intronic SNP in FNIP2 and SNP chr4:157997598 is intronic in GLRB. Linkage analysis revealed 46 SNPs with a LOD > 3 with the strongest signal at rs1141070 (LODLDL = 4.30, PLDL = 0.33, MAF = 21.6%) in DFFB. A total of 53 nominally associated variants (P < 5.00 × 10-05, MAF ≥ 1.0%) were selected for replication in six Mexican-American cohorts (N = 3,280). The strongest signal observed was a synonymous variant (rs1160983, PLDL = 4.44 × 10-17, MAF = 2.7%) in TOMM40. Beyond primary findings, previously reported lipid loci were fine-mapped using exome sequencing in IRASFS. These results support that exome sequencing complements and extends insights into the genetics of lipid levels.