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BACKGROUNDPreclinical studies suggest that cholesterol accumulation leads to insulin resistance. We previously reported that alterations in a monocyte cholesterol metabolism transcriptional network (CMTN) - suggestive of cellular cholesterol accumulation - were cross-sectionally associated with obesity and type 2 diabetes (T2D). Here, we sought to determine whether the CMTN alterations independently predict incident prediabetes/T2D risk, and correlate with cellular cholesterol accumulation.METHODSMonocyte mRNA expression of 11 CMTN genes was quantified among 934 Multi-Ethnic Study of Atherosclerosis (MESA) participants free of prediabetes/T2D; cellular cholesterol was measured in a subset of 24 monocyte samples.RESULTSDuring a median 6-year follow-up, lower expression of 3 highly correlated LXR target genes - ABCG1 and ABCA1 (cholesterol efflux) and MYLIP (cholesterol uptake suppression) - and not other CMTN genes, was significantly associated with higher risk of incident prediabetes/T2D. Lower expression of the LXR target genes correlated with higher cellular cholesterol levels (e.g., 47% of variance in cellular total cholesterol explained by ABCG1 expression). Further, adding the LXR target genes to overweight/obesity and other known predictors significantly improved prediction of incident prediabetes/T2D.CONCLUSIONThese data suggest that the aberrant LXR/ABCG1-ABCA1-MYLIP pathway (LAAMP) is a major T2D risk factor and support a potential role for aberrant LAAMP and cellular cholesterol accumulation in diabetogenesis.FUNDINGThe MESA Epigenomics and Transcriptomics Studies were funded by NIH grants 1R01HL101250, 1RF1AG054474, R01HL126477, R01DK101921, and R01HL135009. This work was supported by funding from NIDDK R01DK103531 and NHLBI R01HL119962.

The dynamin-related guanosine triphosphatase, Drp1 (encoded by Dnm1l), plays a central role in mitochondrial fission and is requisite for numerous cellular processes; however, its role in muscle metabolism remains unclear. Here, we show that, among human tissues, the highest number of gene correlations with DNM1L is in skeletal muscle. Knockdown of Drp1 (Drp1-KD) promoted mitochondrial hyperfusion in the muscle of male mice. Reduced fatty acid oxidation and impaired insulin action along with increased muscle succinate was observed in Drp1-KD muscle. Muscle Drp1-KD reduced complex II assembly and activity as a consequence of diminished mitochondrial translocation of succinate dehydrogenase assembly factor 2 (Sdhaf2). Restoration of Sdhaf2 normalized complex II activity, lipid oxidation, and insulin action in Drp1-KD myocytes. Drp1 is critical in maintaining mitochondrial complex II assembly, lipid oxidation, and insulin sensitivity, suggesting a mechanistic link between mitochondrial morphology and skeletal muscle metabolism, which is clinically relevant in combatting metabolic-related diseases.

Chronic kidney disease is a leading cause of death and disability globally and impacts individuals of African ancestry (AFR) or with ancestry in the Americas (AMS) who are under-represented in genome-wide association studies (GWASs) of kidney function. To address this bias, we conducted a large meta-analysis of GWASs of estimated glomerular filtration rate (eGFR) in 145,732 AFR and AMS individuals. We identified 41 loci at genome-wide significance (p

Background and aimsTo investigate associations between avocado intake and glycemia in adults with Hispanic/Latino ancestry.Methods and resultsThe associations of avocado intake with measures of insulin and glucose homeostasis were evaluated in a cross-sectional analysis of up to 14,591 Hispanic/Latino adults, using measures of: average glucose levels (hemoglobin A1c; HbA1c), fasting glucose and insulin, glucose and insulin levels after an oral glucose tolerance test (OGTT), and calculated measures of insulin resistance (HOMA-IR, and HOMA-%β), and insulinogenic index. Associations were assessed using multivariable linear regression models, which controlled for sociodemographic factors and health behaviors, and which were stratified by dysglycemia status. In those with normoglycemia, avocado intake was associated with a higher insulinogenic index (β = 0.17 ± 0.07, P = 0.02). In those with T2D (treated and untreated), avocado intake was associated with lower hemoglobin A1c (HbA1c; β = -0.36 ± 0.21, P = 0.02), and lower fasting glucose (β = -0.27 ± 0.12, P = 0.02). In the those with untreated T2D, avocado intake was additionally associated with HOMA-%β (β = 0.39 ± 0.19, P = 0.04), higher insulin values 2-h after an oral glucose load (β = 0.62 ± 0.23, P = 0.01), and a higher insulinogenic index (β = 0.42 ± 0.18, P = 0.02). No associations were observed in participants with prediabetes.ConclusionsWe observed an association of avocado intake with better glucose/insulin homeostasis, especially in those with T2D.

BackgroundWhether red meat consumption is associated with higher inflammation or confounded by increased adiposity remains unclear. Plasma metabolites capture the effects of diet after food is processed, digested, and absorbed, and correlate with markers of inflammation, so they can help clarify diet-health relationships.ObjectiveTo identify whether any metabolites associated with red meat intake are also associated with inflammation.MethodsA cross-sectional analysis of observational data from older adults (52.84% women, mean age 63 ± 0.3 y) participating in the Multi-Ethnic Study of Atherosclerosis (MESA). Dietary intake was assessed by food-frequency questionnaire, alongside C-reactive protein (CRP), interleukin-2, interleukin-6, fibrinogen, homocysteine, and tumor necrosis factor alpha, and untargeted proton nuclear magnetic resonance (1H NMR) metabolomic features. Associations between these variables were examined using linear regression models, adjusted for demographic factors, lifestyle behaviors, and body mass index (BMI).ResultsIn analyses that adjust for BMI, neither processed nor unprocessed forms of red meat were associated with any markers of inflammation (all P > 0.01). However, when adjusting for BMI, unprocessed red meat was inversely associated with spectral features representing the metabolite glutamine (sentinel hit: β = -0.09 ± 0.02, P = 2.0 × 10-5), an amino acid which was also inversely associated with CRP level (β = -0.11 ± 0.01, P = 3.3 × 10-10).ConclusionsOur analyses were unable to support a relationship between either processed or unprocessed red meat and inflammation, over and above any confounding by BMI. Glutamine, a plasma correlate of lower unprocessed red meat intake, was associated with lower CRP levels. The differences in diet-inflammation associations, compared with diet metabolite-inflammation associations, warrant further investigation to understand the extent that these arise from the following: 1) a reduction in measurement error with metabolite measures; 2) the extent that which factors other than unprocessed red meat intake contribute to glutamine levels; and 3) the ability of plasma metabolites to capture individual differences in how food intake is metabolized.

ContextBoth type 1 diabetes (T1D) and type 2 diabetes (T2D) have significant genetic contributions to risk and understanding their overlap can offer clinical insight.ObjectiveWe examined whether a T1D polygenic score (PS) was associated with a diagnosis of T2D in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.MethodsWe constructed a T1D PS using 79 known single nucleotide polymorphisms associated with T1D risk. We analyzed 13 792 T2D cases and 14 169 controls from CHARGE cohorts to determine the association between the T1D PS and T2D prevalence. We validated findings in an independent sample of 2256 T2D cases and 27 052 controls from the Mass General Brigham Biobank (MGB Biobank). As secondary analyses in 5228 T2D cases from CHARGE, we used multivariable regression models to assess the association of the T1D PS with clinical outcomes associated with T1D.ResultsThe T1D PS was not associated with T2D both in CHARGE (P = .15) and in the MGB Biobank (P = .87). The partitioned human leukocyte antigens only PS was associated with T2D in CHARGE (OR 1.02 per 1 SD increase in PS, 95% CI 1.01-1.03, P = .006) but not in the MGB Biobank. The T1D PS was weakly associated with insulin use (OR 1.007, 95% CI 1.001-1.012, P = .03) in CHARGE T2D cases but not with other outcomes.ConclusionIn large biobank samples, a common variant PS for T1D was not consistently associated with prevalent T2D. However, possible heterogeneity in T2D cannot be ruled out and future studies are needed do subphenotyping.

Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.

BackgroundAvocado consumption is linked to better glucose homeostasis, but small associations suggest potential population heterogeneity. Metabolomic data capture the effects of food intake after digestion and metabolism, thus accounting for individual differences in these processes.ObjectivesTo identify metabolomic biomarkers of avocado intake and to examine their associations with glycemia.MethodsBaseline data from 6224 multi-ethnic older adults (62% female) included self-reported avocado intake, fasting glucose and insulin, and untargeted plasma proton nuclear magnetic resonance metabolomic features (metabolomic data were available for a randomly selected subset; N = 3438). Subsequently, incident type 2 diabetes (T2D) was assessed over an ∼18 y follow-up period. A metabolome-wide association study of avocado consumption status (consumer compared with nonconsumer) was conducted, and the relationship of these features with glycemia via cross-sectional associations with fasting insulin and glucose and longitudinal associations with incident T2D was examined.ResultsThree highly-correlated spectral features were associated with avocado intake at metabolome-wide significance levels (P < 5.3 ∗ 10-7) and combined into a single biomarker. We did not find evidence that these features were additionally associated with overall dietary quality, nor with any of 47 other food groups (all P > 0.001), supporting their suitability as a biomarker of avocado intake. Avocado intake showed a modest association only with lower fasting insulin (β = -0.07 +/- 0.03, P = 0.03), an association that was attenuated to nonsignificance when additionally controlling for body mass index (kg/m2). However, our biomarker of avocado intake was strongly associated with lower fasting glucose (β = -0.22 +/- 0.02, P < 2.0 ∗ 10-16), lower fasting insulin (β = -0.17 +/- 0.02, P < 2.0 ∗ 10-16), and a lower incidence of T2D (hazard ratio: 0.68; 0.63-074, P < 2.0 ∗ 10-16), even when adjusting for BMI.ConclusionsHighly significant associations between glycemia and avocado-related metabolomic features, which serve as biomarkers of the physiological impact of dietary intake after digestion and absorption, compared to modest relationships between glycemia and avocado consumption, highlights the importance of considering individual differences in metabolism when considering diet-health relationships.

Distinct tissue-specific mechanisms mediate insulin action in fasting and postprandial states. Previous genetic studies have largely focused on insulin resistance in the fasting state, where hepatic insulin action dominates. Here we studied genetic variants influencing insulin levels measured 2 h after a glucose challenge in >55,000 participants from three ancestry groups. We identified ten new loci (P

Few studies have demonstrated reproducible gene-diet interactions (GDIs) impacting metabolic disease risk factors, likely due in part to measurement error in dietary intake estimation and insufficient capture of rare genetic variation. We aimed to identify GDIs across the genetic frequency spectrum impacting the macronutrient-glycemia relationship in genetically and culturally diverse cohorts. We analyzed 33,187 participants free of diabetes from 10 National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program cohorts with whole-genome sequencing, self-reported diet, and glycemic trait data. We fit cohort-specific, multivariable-adjusted linear mixed models for the effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and its interactions with common and rare variants genome-wide. In main effect meta-analyses, participants consuming more carbohydrate had modestly lower glycemic trait values (e.g., for glycated hemoglobin [HbA1c], -0.013% HbA1c/250 kcal substitution). In GDI meta-analyses, a common African ancestry-enriched variant (rs79762542) reached study-wide significance and replicated in the UK Biobank cohort, indicating a negative carbohydrate-HbA1c association among major allele homozygotes only. Simulations revealed that >150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error. These results generate hypotheses for further exploration of modifiable metabolic disease risk in additional cohorts with African ancestry.Article highlightsWe aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.

The Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases workshop was a 1.5-day scientific conference at the National Institutes of Health (Bethesda, MD) that engaged clinical and basic science investigators interested in diseases of the pancreas. This report provides a summary of the proceedings from the workshop. The goals of the workshop were to forge connections and identify gaps in knowledge that could guide future research directions. Presentations were segregated into six major theme areas, including 1) pancreas anatomy and physiology, 2) diabetes in the setting of exocrine disease, 3) metabolic influences on the exocrine pancreas, 4) genetic drivers of pancreatic diseases, 5) tools for integrated pancreatic analysis, and 6) implications of exocrine-endocrine cross talk. For each theme, multiple presentations were followed by panel discussions on specific topics relevant to each area of research; these are summarized here. Significantly, the discussions resulted in the identification of research gaps and opportunities for the field to address. In general, it was concluded that as a pancreas research community, we must more thoughtfully integrate our current knowledge of normal physiology as well as the disease mechanisms that underlie endocrine and exocrine disorders so that there is a better understanding of the interplay between these compartments.

[This corrects the article DOI: 10.1016/j.xhgg.2022.100099.].

Gut microbiome studies have documented depletion of butyrate-producing taxa in type 2 diabetes. We analyzed associations between butyrate-producing taxa and detailed measures of insulin homeostasis, whose dysfunction underlies diabetes in 224 non-Hispanic Whites and 129 African Americans, all of whom completed an oral glucose tolerance test. Stool microbiome was assessed by whole-metagenome shotgun sequencing with taxonomic profiling. We examined associations among 36 butyrate-producing taxa (n = 7 genera and 29 species) and insulin sensitivity, insulin secretion, disposition index, insulin clearance, and prevalence of dysglycemia (prediabetes plus diabetes, 46% of cohort), adjusting for age, sex, BMI, and race. The genus Coprococcus was associated with higher insulin sensitivity (β = 0.14; P = 0.002) and disposition index (β = 0.12; P = 0.012) and a lower rate of dysglycemia (odds ratio [OR] 0.91; 95% CI 0.85-0.97; P = 0.0025). In contrast, Flavonifractor was associated with lower insulin sensitivity (β = -0.13; P = 0.004) and disposition index (β = -0.11; P = 0.04) and higher prevalence of dysglycemia (OR 1.22; 95% CI 1.08-1.38; P = 0.0013). Species-level analyses found 10 bacteria associated with beneficial directions of effects and two bacteria with adverse associations on insulin homeostasis and dysglycemia. Although most butyrate producers analyzed appear to be metabolically beneficial, this is not the case for all such bacteria, suggesting that microbiome-directed therapeutic measures to prevent or treat diabetes should be targeted to specific butyrate-producing taxa rather than all butyrate producers.

Nontargeted metabolomics methods have increased potential to identify new disease biomarkers, but assessments of the additive information provided in large human cohorts by these less biased techniques are limited. To diversify our knowledge of diabetes-associated metabolites, we leveraged a method that measures 305 targeted or "known" and 2,342 nontargeted or "unknown" compounds in fasting plasma samples from 2,750 participants (315 incident cases) in the Jackson Heart Study (JHS)-a community cohort of self-identified African Americans-who are underrepresented in omics studies. We found 307 unique compounds (82 known) associated with diabetes after adjusting for age and sex at a false discovery rate of

AbstractThe "Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases" Workshop was a 1.5-day scientific conference at the National Institutes of Health (Bethesda, MD) that engaged clinical and basic science investigators interested in diseases of the pancreas. This report summarizes the workshop proceedings. The goal of the workshop was to forge connections and identify gaps in knowledge that could guide future research directions. Presentations were segregated into 6 major themes, including (a) Pancreas Anatomy and Physiology; (b) Diabetes in the Setting of Exocrine Disease; (c) Metabolic Influences on the Exocrine Pancreas; (d) Genetic Drivers of Pancreatic Diseases; (e) Tools for Integrated Pancreatic Analysis; and (f) Implications of Exocrine-Endocrine Crosstalk. For each theme, there were multiple presentations followed by panel discussions on specific topics relevant to each area of research; these are summarized herein. Significantly, the discussions resulted in the identification of research gaps and opportunities for the field to address. In general, it was concluded that as a pancreas research community, we must more thoughtfully integrate our current knowledge of the normal physiology as well as the disease mechanisms that underlie endocrine and exocrine disorders so that there is a better understanding of the interplay between these compartments.

Background & aimsMitochondrial dysfunction disrupts the synthesis and secretion of digestive enzymes in pancreatic acinar cells and plays a primary role in the etiology of exocrine pancreas disorders. However, the transcriptional mechanisms that regulate mitochondrial function to support acinar cell physiology are poorly understood. Here, we aim to elucidate the function of estrogen-related receptor γ (ERRγ) in pancreatic acinar cell mitochondrial homeostasis and energy production.MethodsTwo models of ERRγ inhibition, GSK5182-treated wild-type mice and ERRγ conditional knock-out (cKO) mice, were established to investigate ERRγ function in the exocrine pancreas. To identify the functional role of ERRγ in pancreatic acinar cells, we performed histologic and transcriptome analysis with the pancreas isolated from ERRγ cKO mice. To determine the relevance of these findings for human disease, we analyzed transcriptome data from multiple independent human cohorts and conducted genetic association studies for ESRRG variants in 2 distinct human pancreatitis cohorts.ResultsBlocking ERRγ function in mice by genetic deletion or inverse agonist treatment results in striking pancreatitis-like phenotypes accompanied by inflammation, fibrosis, and cell death. Mechanistically, loss of ERRγ in primary acini abrogates messenger RNA expression and protein levels of mitochondrial oxidative phosphorylation complex genes, resulting in defective acinar cell energetics. Mitochondrial dysfunction due to ERRγ deletion further triggers autophagy dysfunction, endoplasmic reticulum stress, and production of reactive oxygen species, ultimately leading to cell death. Interestingly, ERRγ-deficient acinar cells that escape cell death acquire ductal cell characteristics, indicating a role for ERRγ in acinar-to-ductal metaplasia. Consistent with our findings in ERRγ cKO mice, ERRγ expression was significantly reduced in patients with chronic pancreatitis compared with normal subjects. Furthermore, candidate locus region genetic association studies revealed multiple single nucleotide variants for ERRγ that are associated with chronic pancreatitis.ConclusionsCollectively, our findings highlight an essential role for ERRγ in maintaining the transcriptional program that supports acinar cell mitochondrial function and organellar homeostasis and provide a novel molecular link between ERRγ and exocrine pancreas disorders.

The present study was designed to evaluate if mode of delivery at birth is associated with body mass index (BMI) and glucose homeostasis traits in later life, controlling for possible confounders, including maternal history of diabetes. Data were obtained through a racially diverse, prospective cohort study of nondiabetic, older adults, the Microbiome and Insulin Longitudinal Evaluation Study (MILES). We used generalized linear models to estimate the association between mode of delivery and glycemic status, BMI (kg/m2), waist circumference (cm), fasting glucose, fasting insulin, insulin secretion, insulin sensitivity, and insulin clearance. Further, we estimated the direct and indirect effects of cesarean delivery on glucose and insulin-related traits, as mediated by BMI status. Relative to vaginal delivery, cesarean delivery was associated with a significantly higher BMI (adjusted beta [aβ] 3.53 kg/m2; 95% CI 0.15, 6.91) and fasting glucose (aβ 5.12; 95% CI 0.01, 10.23), a 14% decrease in insulin sensitivity (aβ -0.14; 95% CI -0.28, -0.01), and a 58% increased risk (adjusted relative risk [aRR] 1.58; 95% CI 1.08, 2.31) for prediabetes/diabetes. Associations were mediated in part by BMI, with the strongest evidence observed for glycemic status (proportion mediated 22.6%; P = .03), fasting insulin (proportion mediated 58.0%; P = .05), and insulin sensitivity index (proportion mediated 45.9%; P = .05). Independent of mediation, a significant direct effect of cesarean delivery on glycemic status was observed (aRR 1.88; 95% CI 1.16, 2.60). Cesarean delivery may lead to reduced insulin sensitivity and, ultimately, increased risk for developing prediabetes and diabetes.

Background and aimsThe DASH diet conveys protection against type 2 diabetes mellitus (T2D) Via plant-based and non-plant-based recommendations. Research has not identified which glucose homeostasis pathways are improved. We examined associations between adherence to a DASH diet and six glucose homeostasis traits, probing whether associations could be attributed to the plant-based (DASH-P) and/or non-plant based (DASH-NP) components.Methods and resultsWe included data from 295 adults without T2D (age 59.3 ± 9.00 years; 63.46% non-Hispanic White and 36.54% African American, self-reported race ancestry) participating in the Microbiome and Insulin Longitudinal Evaluation Study (MILES). An oral glucose tolerance test (OGTT) yielded fasting plasma glucose, insulin, C-peptide, and insulin secretion, sensitivity, and disposition index. Habitual dietary intake was assessed by food frequency questionnaire (FFQ). Associations between DASH components and glucose homeostasis traits were examined, controlling for demographics, body mass index (BMI), physical activity, and energy intake. For significant associations, the models were repeated with scores for DASH-P and DASH-NP as predictors in the same model. DASH and DASH-P scores were inversely associated with fasting plasma glucose (DASH:β = -0.036 ± 0.012,P = 0.005; DASH-P: β = -0.04 ± 0.017,P = 0.002), and positively associated with insulin sensitivity (DASH:β = 0.022 ± 0.012,P = 0.042; DASH-P: = 0.036 ± 0.015,P = 0.014). The DASH score was also associated with disposition index (β = 0.026 ± 0.013,P = 0.038), but this association did not reach significance with DASH-P (β = 0.035 ± 0.018,P = 0.051). No associations were observed with DASH-NP score (all P > 0.05).ConclusionsDASH diet is associated with improvement in specific glucose homeostasis traits, likely arising from increased plant-based foods. Such research may help tailor future dietary advice to specific metabolic risk, and to food groups most effective at improving these.

Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite their notable anthropometric variability, ancestry proportions, and high burden of growth stunting and overweight/obesity. To address this knowledge gap, we analyzed densely imputed genetic data in a sample of Hispanic/Latino adults to identify and fine-map genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (stage 1, n = 59,771) and generalized our findings in 9 additional studies (stage 2, n = 10,538). We conducted a trans-ancestral GWAS with summary statistics from HISLA stage 1 and existing consortia of European and African ancestries. In our HISLA stage 1 + 2 analyses, we discovered one BMI locus, as well as two BMI signals and another height signal each within established anthropometric loci. In our trans-ancestral meta-analysis, we discovered three BMI loci, one height locus, and one WHRadjBMI locus. We also identified 3 secondary signals for BMI, 28 for height, and 2 for WHRadjBMI in established loci. We show that 336 known BMI, 1,177 known height, and 143 known WHRadjBMI (combined) SNPs demonstrated suggestive transferability (nominal significance and effect estimate directional consistency) in Hispanic/Latino adults. Of these, 36 BMI, 124 height, and 11 WHRadjBMI SNPs were significant after trait-specific Bonferroni correction. Trans-ancestral meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our findings demonstrate that future studies may also benefit from leveraging diverse ancestries and differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification.

ObjectiveType 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed β-cell, proinsulin, obesity, lipodystrophy, and liver/lipid. The relationship between these clusters and individual-level metabolic disease outcomes has not been assessed.Research design and methodsHere we constructed individual-level partitioned polygenic scores (pPS) for these five clusters in 12 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (n = 454,193) and tested for cross-sectional association with T2D-related outcomes, including blood pressure, renal function, insulin use, age at T2D diagnosis, and coronary artery disease (CAD).ResultsDespite all clusters containing T2D risk-increasing alleles, they had differential associations with metabolic outcomes. Increased obesity and lipodystrophy cluster pPS, which had opposite directions of association with measures of adiposity, were both significantly associated with increased blood pressure and hypertension. The lipodystrophy and liver/lipid cluster pPS were each associated with CAD, with increasing and decreasing effects, respectively. An increased liver/lipid cluster pPS was also significantly associated with reduced renal function. The liver/lipid cluster includes known loci linked to liver lipid metabolism (e.g., GCKR, PNPLA3, and TM6SF2), and these findings suggest that cardiovascular disease risk and renal function may be impacted by these loci through their shared disease pathway.ConclusionsOur findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes.

Non-O blood groups are associated with decreased insulin sensitivity and risk of type 2 diabetes. A recent study pinpointed the associations between ABO blood groups and gut microbiome, which may serve as potential mediators for the observed increased disease risks. We aimed to characterize associations between ABO haplotypes and insulin-related traits as well as potential mediating pathways. We assessed insulin homeostasis in African Americans (AAs; n = 109) and non-Hispanic whites (n = 210) from the Microbiome and Insulin Longitudinal Evaluation Study. The ABO haplotype was determined by six SNPs located in the ABO gene. Based on prior knowledge, we included 21 gut bacteria and 13 plasma metabolites for mediation analysis. In the white study cohort (60 ± 9 years, 42% male), compared to the O1 haplotype, A1 was associated with a higher Matsuda insulin sensitivity index, while a lower relative abundance of Bacteroides massiliensis and lactate levels. Lactate was a likely mediator of this association but not Bacteroides massiliensis. In the AAs group (57 ± 8 years, 33% male), we found no association between any haplotype and insulin-related traits. In conclusion, the A1 haplotype may promote healthy insulin sensitivity in non-Hispanic whites and lactate likely play a role in this process but not selected gut bacteria.

BackgroundWorsening glycemic control indicates elevated risk of pancreatic ductal adenocarcinoma (PDAC). We developed prediction models for PDAC among those with worsening glycemic control after diabetes diagnosis.MethodsIn 2000-2016 records within the Veterans Affairs Health System (VA), we identified three cohorts with progression of diabetes: (i) insulin initiation (n = 449,685), (ii) initiation of combination oral hypoglycemic medication (n = 414,460), and (iii) hemoglobin A1c (HbA1c) ≥8% with ≥Δ1% within 15 months (n = 593,401). We computed 12-, 36-, and 60-month incidence of PDAC and developed prediction models separately for males and females, with consideration of >30 demographic, behavioral, clinical, and laboratory variables. Models were selected to optimize Akaike's Information Criterion, and performance for predicting 12-, 36-, and 60-month incident PDAC was evaluated by bootstrap.ResultsIncidence of PDAC was highest for insulin initiators and greater in males than in females. Optimism-corrected c-indices of the models for predicting 36-month incidence of PDAC in the male population were: (i) 0.72, (ii) 0.70, and (iii) 0.71, respectively. Models performed better for predicting 12-month incident PDAC [c-index (i) 0.78, (ii) 0.73, (iii) 0.76 for males], and worse for predicting 60-month incident PDAC [c-index (i) 0.69, (ii) 0.67, (iii) 0.68 for males]. Model performance was lower among females. For subjects whose model-predicted 36-month PDAC risks were ≥1%, the observed incidences were (i) 1.9%, (ii) 2.2%, and (iii) 1.8%.ConclusionsSex-specific models for PDAC can estimate risk of PDAC at the time of progression of diabetes.ImpactOur models can identify diabetes patients who would benefit from PDAC screening.

ObjectiveThis study examines the value of risk stratification by documented diagnosis of diabetes and objectively measured height and weight (BMI) in COVID-19 severity and mortality in a large sample of patients in an urban hospital located in Southern California.MethodsData from a retrospective cohort study of COVID-19 patients treated at Cedars-Sinai Medical Center between March 8, 2020, and January 25, 2021, was analyzed. Sociodemographic characteristics and pre-existing conditions were extracted from electronic medical records. Univariable and multivariable logistic regression models identified associated risk factors, and a regression causal mediation analysis examined the role of diabetes in the association between obesity and illness severity. All analyses were stratified by age (

The genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI's Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well as APOB, PTPRT, and ROBO1. Functional annotation resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions creating a foundation for future sequencing-based investigations of glycemic traits.

Central obesity is a leading health concern with a great burden carried by ethnic minority populations, especially Hispanics/Latinos. Genetic factors contribute to the obesity burden overall and to inter-population differences. We aimed to identify the loci associated with central adiposity measured as waist-to-hip ratio (WHR), waist circumference (WC) and hip circumference (HIP) adjusted for body mass index (adjBMI) by using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL); determine if differences in associations differ by background group within HCHS/SOL and determine whether previously reported associations generalize to HCHS/SOL. Our analyses included 7472 women and 5200 men of mainland (Mexican, Central and South American) and Caribbean (Puerto Rican, Cuban and Dominican) background residing in the USA. We performed genome-wide association analyses stratified and combined across sexes using linear mixed-model regression. We identified 16 variants for waist-to-hip ratio adjusted for body mass index (WHRadjBMI), 22 for waist circumference adjusted for body mass index (WCadjBMI) and 28 for hip circumference adjusted for body mass index (HIPadjBMI), which reached suggestive significance (P

Insulin resistance and insufficient insulin secretion are well-recognized contributors to type 2 diabetes. A potential role of reduced insulin clearance has been suggested, but few studies have investigated the contribution of insulin clearance while simultaneously examining decreased insulin sensitivity and secretion. The goal of this study was to conduct such an investigation in a cohort of 353 non-Hispanic White and African American individuals recruited in the Microbiome and Insulin Longitudinal Evaluation Study (MILES). Participants underwent oral glucose tolerance tests from which insulin sensitivity, insulin secretion, insulin clearance, and disposition index were calculated. Regression models examined the individual and joint contributions of these traits to early dysglycemia (prediabetes or newly diagnosed diabetes). In separate models, reduced insulin sensitivity, reduced disposition index, and reduced insulin clearance were associated with dysglycemia. In a joint model, only insulin resistance and reduced insulin secretion were associated with dysglycemia. Models with insulin sensitivity, disposition index, or three insulin traits had the highest discriminative value for dysglycemia (area under the receiver operating characteristics curve of 0.82 to 0.89). These results suggest that in the race groups studied, insulin resistance and compromised insulin secretion are the main independent underlying defects leading to early dysglycemia.

AimTo investigate the role of the gut microbiome in regulating key insulin homeostasis traits (insulin sensitivity, insulin secretion and insulin clearance) whose dysfunction leads to type 2 diabetes (T2D).Materials and methodsThe Microbiome and Insulin Longitudinal Evaluation Study (MILES) focuses on African American and non-Hispanic white participants aged 40-80 years without diabetes. Three study visits are planned (at baseline, 15 and 30 months). Baseline measurements include assessment of the stool microbiome and administration of an oral glucose tolerance test, which will yield indexes of insulin sensitivity, insulin secretion and insulin clearance. The gut microbiome profile (composition and function) will be determined using whole metagenome shotgun sequencing along with analyses of plasma short chain fatty acids. Additional data collected include dietary history, sociodemographic factors, health habits, anthropometry, medical history, medications and family history. Most assessments are repeated 15 and 30 months following baseline.ResultsAfter screening 875 individuals, 129 African American and 224 non-Hispanic white participants were enrolled. At baseline, African American participants have higher blood pressure, weight, body mass index, waist and hip circumferences but similar waist-hip ratio compared with the non-Hispanic white participants. On average, African American participants are less insulin-sensitive and have higher acute insulin secretion and lower insulin clearance.ConclusionsThe longitudinal design and robust characterization of potential mediators will allow for the assessment of glucose and insulin homeostasis and gut microbiota as they change over time, improving our ability to discern causal relationships between the microbiome and the insulin homeostasis traits whose deterioration determines T2D, setting the stage for future microbiome-directed therapies to prevent and treat T2D.

ObjectiveTo assess the relationship of physical activity with bone mineral density (BMD) at various sites and examine potential modifying metabolic factors.MethodsResponses from physical activity questionnaires were used to determine total physical activity (PA), moderate physical activity (mod-PA), and sedentary time. Regression analyses were performed to evaluate association of activity traits with insulin sensitivity by euglycemic clamp, adiponectin, C-reactive protein (CRP), and plasminogen activator inhibitor-1 (PAI-1) in 741 healthy subjects.ResultsThe cohort was relatively sedentary. Activity level was associated with arm, pelvis, and leg BMD in univariate analyses. In multivariate association analyses of arm BMD, only female sex (β = -0.73, P < 0.0001) and adiponectin (β = -0.076, P = 0.0091) were significant. Multivariate analyses of pelvis BMD found independent associations with body mass index (BMI) (β = 0.33, P < 0.0001), adiponectin (β = -0.10, P = 0.013), female sex (β = -0.18, P < 0.0001), sedentary time (β = -0.088, P = 0.034), PA (β = 0.11, P = 0.01), and mod-PA (β = 0.11, P = 0.014). Age (β = -0.10, P = 0.0087), female sex (β = -0.63, P < 0.0001), BMI (β = 0.24, P < 0.0001), and mod-PA (β = 0.10, P = 0.0024) were independently associated with leg BMD.ConclusionsThese results suggest that BMD increases with physical activity in the arms, legs, and pelvis and is inversely related to sedentary time in the pelvis and legs; these associations may be modified by age, sex, BMI, and adiponectin, depending on the site, with physical activity being more important to pelvis and leg BMD than arm BMD and sedentary time being important for pelvis BMD. Moreover, we demonstrated that CRP, PAI-1, and insulin sensitivity play a minor role in BMD.

Purpose of reviewAn increasing body of evidence suggests that the gut microbiome influences the pathogenesis of insulin resistance and type 2 diabetes (T2D). In this review, we will discuss the latest findings regarding the mechanisms linking the gut microbiome and microbial metabolites with T2D and therapeutic approaches based on the gut microbiota for the prevention and treatment of T2D.Recent findingsAlterations in the gut microbial composition are associated with the risk of T2D. The gut microbiota can metabolize dietary- and host-derived factors to produce numerous microbial metabolites, which are involved in metabolic processes modulating nutrition and energy harvest, gut barrier function, systemic inflammation, and glucose metabolism. Microbial metabolites are important mediators of microbial-host crosstalk impacting host glucose metabolism. Furthermore, microbiome-based interventions may have beneficial effects on glycemic control. Future research is required to develop personalized T2D therapy based on microbial composition and/or metabolites.

It remains unclear whether the increased risk of new-onset type 2 diabetes (T2D) seen in statin users is due to low LDL-C concentrations, or due to the statin-induced proportional change in LDL-C. In addition, genetic instruments have not been proposed before to examine whether liability to T2D might cause greater proportional statin-induced LDL-C lowering. Using summary-level statistics from the Genomic Investigation of Statin Therapy (GIST, nmax = 40,914) and DIAGRAM (nmax = 159,208) consortia, we found a positive genetic correlation between LDL-C statin response and T2D using LD score regression (rgenetic = 0.36, s.e. = 0.13). However, mendelian randomization analyses did not provide support for statin response having a causal effect on T2D risk (OR 1.00 (95% CI: 0.97, 1.03) per 10% increase in statin response), nor that liability to T2D has a causal effect on statin-induced LDL-C response (0.20% increase in response (95% CI: -0.40, 0.80) per doubling of odds of liability to T2D). Although we found no evidence to suggest that proportional statin response influences T2D risk, a definitive assessment should be made in populations comprised exclusively of statin users, as the presence of nonstatin users in the DIAGRAM dataset may have substantially diluted our effect estimate.

AimsCausal transcripts at genomic loci associated with type 2 diabetes (T2D) are mostly unknown. The chr8p23.1 variant rs4841132, associated with an insulin-resistant diabetes risk phenotype, lies in the second exon of a long non-coding RNA (lncRNA) gene, LOC157273, located 175 kilobases from PPP1R3B, which encodes a key protein regulating insulin-mediated hepatic glycogen storage in humans. We hypothesized that LOC157273 regulates expression of PPP1R3B in human hepatocytes.MethodsWe tested our hypothesis using Stellaris fluorescent in situ hybridization to assess subcellular localization of LOC157273; small interfering RNA (siRNA) knockdown of LOC157273, followed by RT-PCR to quantify LOC157273 and PPP1R3B expression; RNA-seq to quantify the whole-transcriptome gene expression response to LOC157273 knockdown; and an insulin-stimulated assay to measure hepatocyte glycogen deposition before and after knockdown.ResultsWe found that siRNA knockdown decreased LOC157273 transcript levels by approximately 80%, increased PPP1R3B mRNA levels by 1.7-fold, and increased glycogen deposition by >50% in primary human hepatocytes. An A/G heterozygous carrier (vs. three G/G carriers) had reduced LOC157273 abundance due to reduced transcription of the A allele and increased PPP1R3B expression and glycogen deposition.ConclusionWe show that the lncRNA LOC157273 is a negative regulator of PPP1R3B expression and glycogen deposition in human hepatocytes and a causal transcript at an insulin-resistant T2D risk locus.

Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.

ObjectivePopulations 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.MethodsLevels 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.ResultsIn 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.ConclusionsPNPLA3, 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.

IntroductionDiabetes mellitus (DM) is a complication of chronic pancreatitis (CP). Whether pancreatogenic diabetes associated with CP-DM represents a discrete pathophysiologic entity from type 2 DM (T2DM) remains uncertain. Addressing this question is needed for development of specific measures to manage CP-DM. We approached this question from a unique standpoint, hypothesizing that if CP-DM and T2DM are separate disorders, they should be genetically distinct. To test this hypothesis, we sought to determine whether a genetic risk score (GRS) based on validated single nucleotide polymorphisms for T2DM could distinguish between groups with CP-DM and T2DM.MethodsWe used 60 T2DM single nucleotide polymorphisms to construct a weighted GRS in 1,613 subjects from the North American Pancreatitis Study 2 and 2,685 subjects from the Multi-Ethnic Study of Atherosclerosis, all of European origin.ResultsThe mean GRS was identical between 321 subjects with CP-DM and 423 subjects with T2DM (66.53 vs 66.42, P = 0.95), and the GRS of both diabetic groups was significantly higher than that of nondiabetic controls (n = 3,554, P < 0.0001). Exploratory analyses attempting to enrich the CP-DM group for pancreatogenic diabetes, such as eliminating diabetes diagnosed before CP, requiring pancreas-specific comorbidities, or removing those with a family history of diabetes, did not improve the ability of the GRS to distinguish between CP-DM and T2DM.DiscussionRecognizing that we lacked a gold standard to define CP-DM, our study suggests that CP-DM may be a subtype of T2DM, a notion that should be tested in future, large prospective studies.

ObjectiveTo identify differences in the transcriptomic profiles during placentation from pregnancies conceived spontaneously vs. those with infertility using non-in vitro fertilization (IVF) fertility treatment (NIFT) or IVF.DesignCohort study.SettingAcademic medical center.Patient(s)Women undergoing chorionic villus sampling at gestational age 11-13 weeks (n = 141), with pregnancies that were conceived spontaneously (n = 74), with NIFT (n = 33), or with IVF (n = 34), resulting in the delivery of viable offspring.Intervention(s)Collection of chorionic villus samples from women who conceived spontaneously, with NIFT, or with IVF for gene expression analysis using RNA sequencing.Main outcome measure(s)Baseline maternal, paternal, and fetal demographics, maternal medical conditions, pregnancy complications, and outcomes. Differential gene expression of first-trimester placenta.Result(s)There were few differences in the transcriptome of first-trimester placenta from NIFT, IVF, and spontaneous pregnancies. There was one protein-coding differentially expressed gene (DEG) between the spontaneous and infertility groups, CACNA1I, one protein-coding DEG between the spontaneous and IVF groups, CACNA1I, and five protein-coding DEGs between the NIFT and IVF groups, SLC18A2, CCL21, FXYD2, PAEP, and DNER.Conclusion(s)This is the first and largest study looking at transcriptomic profiles of first-trimester placenta demonstrating similar transcriptomic profiles in pregnancies conceived using NIFT or IVF and spontaneous conceptions. Gene expression differences found to be highest in the NIFT group suggest that the underlying infertility, in addition to treatment-related factors, may contribute to the observed gene expression profiles.

ObjectiveAging is associated with impaired insulin sensitivity and increased prevalence of type 2 diabetes. However, it remains unclear whether aging-associated insulin resistance is due to increased adiposity or other age-related factors. To address this question, the impact of aging on insulin sensitivity was investigated independently of changes in body composition.MethodsCohorts of mice aged 4 to 8 months ("young") and 18 to 27 months ("aged") exhibiting similar body composition were characterized for glucose metabolism on chow and high-fat diets. Insulin sensitivity was assessed by hyperinsulinemic-euglycemic clamp analyses. The relationship between aging and insulin resistance in humans was investigated in 1,250 nondiabetic Mexican Americans who underwent hyperinsulinemic-euglycemic clamps.ResultsIn mice with similar body composition, age had no detrimental effect on plasma glucose and insulin levels. While aging did not diminish glucose tolerance, hyperinsulinemic-euglycemic clamps demonstrated impaired insulin sensitivity and reduced insulin clearance in aged mice on chow and high-fat diets. Consistent with results in the mouse, age remained an independent determinant of insulin resistance after adjustment for body composition in Mexican American males.ConclusionsThis study demonstrates that in addition to altered body composition, adiposity-independent mechanisms also contribute to aging-associated insulin resistance in mice and humans.

BackgroundDevelopment of the placenta during the late first trimester is critical to ensure normal growth and development of the fetus. Developmental differences in this window such as sex-specific variation are implicated in later placental disease states, yet gene expression at this time is poorly understood.MethodsRNA-sequencing was performed to characterize the transcriptome of 39 first trimester human placentas using chorionic villi following genetic testing (17 females, 22 males). Gene enrichment analysis was performed to find enriched canonical pathways and gene ontologies in the first trimester. DESeq2 was used to find sexually dimorphic gene expression. Patient demographics were analyzed for sex differences in fetal weight at time of chorionic villus sampling and birth.ResultsRNA-sequencing analyses detected 14,250 expressed genes, with chromosome 19 contributing the greatest proportion (973/2852, 34.1% of chromosome 19 genes) and Y chromosome contributing the least (16/568, 2.8%). Several placenta-enriched genes as well as histone-coding genes were identified to be unique to the first trimester and common to both sexes. Further, we identified 58 genes with significantly different expression between males and females: 25 X-linked, 15 Y-linked, and 18 autosomal genes. Genes that escape X inactivation were highly represented (59.1%) among X-linked genes upregulated in females. Many genes differentially expressed by sex consisted of X/Y gene pairs, suggesting that dosage compensation plays a role in sex differences. These X/Y pairs had roles in parallel, ancient canonical pathways important for eukaryotic cell growth and survival: chromatin modification, transcription, splicing, and translation.ConclusionsThis study is the first characterization of the late first trimester placenta transcriptome, highlighting similarities and differences among the sexes in ongoing human pregnancies resulting in live births. Sexual dimorphism may contribute to pregnancy outcomes, including fetal growth and birth weight, which was seen in our cohort, with males significantly heavier than females at birth. This transcriptome provides a basis for development of early diagnostic tests of placental function that can indicate overall pregnancy heath, fetal-maternal health, and long-term adult health.

ObjectivePatients with type 2 diabetes mellitus have an increased risk of fracture despite normal or increased bone mineral density (BMD). Studies on the relationship of glucose homeostasis with BMD phenotypes have been inconclusive because distinguishing the roles of insulin resistance and hyperglycaemia in bone remodelling is challenging. In this study, we sought to define the relationship of site-specific BMD with glucose homeostasis traits and anthropometric traits.Design/patients/measurementsIn a cross-sectional study, we examined 787 subjects from the Mexican-American Coronary Artery Disease (MACAD) cohort who had undergone euglycaemic-hyperinsulinaemic clamps, oral glucose tolerance testing and dual X-ray absorptiometry. Glucose homeostasis traits included insulinogenic index (IGI30), insulin sensitivity (M value), insulin clearance (MCRI), fasting insulin, fasting glucose and 2-hour glucose. Univariate and multivariate analyses were performed to assess the association of glucose homeostasis and anthropometric traits with site-specific BMD.ResultsTwo-hour glucose was negatively associated with arm BMD in women, which remained significant in multivariate analysis (β = -.15, P = .0015). Positive correlations between fasting insulin and BMD at weight-bearing sites, including pelvis (β = .22, P