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Objective: The obesity paradox in which overweight/obesity is associated with mortality benefits is believed to be explained by confounding and reverse causality rather than by a genuine clinical benefit of excess body weight. We aimed to gain deeper insights into the paradox through analyzing mortality relationships with several adiposity measures; assessing subgroups with type 2 diabetes, with coronary heart disease (CHD), with cancer, and by smoking status; and adjusting for several confounders.Research Design and Methods: We studied the general UK Biobank population (N = 502,631) along with three subgroups of people with type 2 diabetes (n = 23,842), CHD (n = 24,268), and cancer (n = 45,790) at baseline. A range of adiposity exposures were considered, including BMI (continuous and categorical), waist circumference, body fat percentage, and waist-to-hip ratio, and the outcome was all-cause mortality. We used Cox regression models adjusted for age, smoking status, deprivation index, education, and disease history.Results: For BMI, the obesity paradox was observed among people with type 2 diabetes (adjusted hazard ratio for obese vs. normal BMI 0.78 [95% CI 0.65, 0.95]) but not among those with CHD (1.00 [0.86, 1.17]). The obesity paradox was pronounced in current smokers, absent in never smokers, and more pronounced in men than in women. For other adiposity measures, there was less evidence for an obesity paradox, yet smoking status consistently modified the adiposity-mortality relationship.Conclusions: The obesity paradox was observed in people with type 2 diabetes and is heavily modified by smoking status. The results of subgroup analyses and statistical adjustments are consistent with reverse causality and confounding. [ABSTRACT FROM AUTHOR]

The article discusses a study by H. Yaghootkar et al that used genetic association data from publicly available genome-wide association studies to reach insight into mechanisms linking adiposity, insulin resistance and other cardiometabolic risk factors. Topics discussed include the complex relationship of TCF7L2 variant with adiposity and insulin sensitivity depending on the presence of type 2 diabetes and the role for adipose storage and expandability.

Objective: Large-scale genome-wide association (GWA) studies have thus far identified 16 loci incontrovertibly associated with obesity-related traits in adults. We examined associations of variants in these loci with anthropometric traits in children and adolescents.Research Design and Methods: Seventeen variants representing 16 obesity susceptibility loci were genotyped in 1,252 children (mean ± SD age 9.7 ± 0.4 years) and 790 adolescents (15.5 ± 0.5 years) from the European Youth Heart Study (EYHS). We tested for association of individual variants and a genetic predisposition score (GPS-17), calculated by summing the number of effect alleles, with anthropometric traits. For 13 variants, summary statistics for associations with BMI were meta-analyzed with previously reported data (N(total) = 13,071 children and adolescents).Results: In EYHS, 15 variants showed associations or trends with anthropometric traits that were directionally consistent with earlier reports in adults. The meta-analysis showed directionally consistent associations with BMI for all 13 variants, of which 9 were significant (0.033-0.098 SD/allele; P < 0.05). The near-TMEM18 variant had the strongest effect (0.098 SD/allele P = 8.5 × 10(-11)). Effect sizes for BMI tended to be more pronounced in children and adolescents than reported earlier in adults for variants in or near SEC16B, TMEM18, and KCTD15, (0.028-0.035 SD/allele higher) and less pronounced for rs925946 in BDNF (0.028 SD/allele lower). Each additional effect allele in the GPS-17 was associated with an increase of 0.034 SD in BMI (P = 3.6 × 10(-5)), 0.039 SD, in sum of skinfolds (P = 1.7 × 10(-7)), and 0.022 SD in waist circumference (P = 1.7 × 10(-4)), which is comparable with reported results in adults (0.039 SD/allele for BMI and 0.033 SD/allele for waist circumference).Conclusions: Most obesity susceptibility loci identified by GWA studies in adults are already associated with anthropometric traits in children/adolescents. Whereas the association of some variants may differ with age, the cumulative effect size is similar. [ABSTRACT FROM AUTHOR]

Objective: The goal of this study was to investigate whether the effects of common genetic variants associated with fasting glucose in adults are detectable in healthy children.Research Design and Methods: Single nucleotide polymorphisms in MTNR1B (rs10830963), G6PC2 (rs560887), and GCK (rs4607517) were genotyped in 2,025 healthy European children aged 9-11 and 14-16 years. Associations with fasting glucose, insulin, homeostasis model assessment (HOMA)-insulin resistance (IR) and HOMA-B were investigated along with those observed for type 2 diabetes variants available in this study (CDKN2A/B, IGF2BP2, CDKAL1, SLC30A8, HHEX-IDE, and Chr 11p12).Results: Strongest associations were observed for G6PC2 and MTNR1B, with mean fasting glucose levels (95% CI) being 0.084 (0.06-0.11) mmol/l, P = 7.9 x 10(-11) and 0.069 (0.04-0.09) mmol/l, P = 1.9 x 10(-7) higher per risk allele copy, respectively. A similar but weaker trend was observed for GCK (0.028 [-0.006 to 0.06] mmol/l, P = 0.11). All three variants were associated with lower beta-cell function (HOMA-B P = 9.38 x 10(-5), 0.004, and 0.04, respectively). SLC30A8 (rs13266634) was the only type 2 diabetes variant associated with higher fasting glucose (0.033 mmol/l [0.01-0.06], P = 0.01). Calculating a genetic predisposition score adding the number of risk alleles of G6PC2, MTNR1B, GCK, and SLC30A8 showed that glucose levels were successively higher in children carrying a greater number of risk alleles (P = 7.1 x 10(-17)), with mean levels of 5.34 versus 4.91 mmol/l comparing children with seven alleles (0.6% of all children) to those with none (0.5%). No associations were found for fasting insulin or HOMA-IR with any of the variants.Conclusions: The effects of common polymorphisms influencing fasting glucose are apparent in healthy children, whereas the presence of multiple risk alleles amounts to a difference of >1 SD of fasting glucose. [ABSTRACT FROM AUTHOR]

OBJECTIVE--Genome-wide association studies have identified common variants in CDKAL1, CDKN2A/B, IGF2BP2, SLC30A8, HHEX/IDE, EXT2, and LOC387761 loci that significantly increase the risk of type 2 diabetes. We aimed to replicate these observations in a population-based cohort of Chinese Hans and examine the associations of these variants with type 2 diabetes and diabetes-related phenotypes. RESEARCH DESIGN AND METHODS--We genotyped 17 single nucleotide polymorhisms (SNPs) in 3,210 unrelated Chinese Hans, including 424 participants with type 2 diabetes, 878 with impaired fasting glucose (IFG), and 1,908 with normal fasting glucose. RESULTS--We confirmed the associations between type 2 diabetes and variants near CDKAL1 (odds ratio 1.49 [95% CI 1.27-1.75]; P = 8.91 x 10-7) and CDKN2A/B (1.31 [1.12-1.54]; P = 1.0 x 10-3). We observed significant association of SNPs in IGF2BP2 (1.17 [1.03-1.32]; P = 0.014) and SLC30A8 (1.12 [1.01-1.25]; P = 0.033) with combined IFG/type 2 diabetes. The SNPs in CDKAL1, IGF2BP2, and SLC30A8 were also associated with impaired β-cell function estimated by homeostasis model assessment of β-cell function. When combined, each additional risk allele from CDKAL1-rs9465871, CDKN2A/B-rs10811661, IGF2BP2-rs4402960, and SLC30A8-rs13266634 increased the risk for type 2 diabetes by 1.24-fold (P = 2.85 x 10-7) or for combined IFG/type 2 diabetes by 1.21-fold (P = 6.31 x 10-11). None of the SNPs in EXT2 or LOC387761 exhibited significant association with type 2 diabetes or IFG. Significant association was observed between the HHEX/IDE SNPs and type 2 diabetes in individuals from Shanghai only (P < 0.013) but not in those from Beijing (P > 0.33). CONCLUSIONS--Our results indicate that in Chinese Hans, common variants in CDKAL1, CDKN2A/B, IGF2BP2, and SLC30A8 loci independently or additively contribute to type 2 diabetes risk, likely mediated through β-cell dysfunction. Diabetes 57:2834-2842, 2008 [ABSTRACT FROM AUTHOR]

OBJECTIVE--Loss of lipin 1 activity causes lipodystrophy and insulin resistance in the fld mouse, and LPIN1 expression and common genetic variation were recently suggested to influence adiposity and insulin sensitivity in humans. We aimed to conduct a comprehensive association study to clarify the influence of common LPIN1 variation on adiposity and insulin sensitivity in U.K. populations and to examine the role of LPIN1 mutations in insulin resistance syndromes. RESEARCH DESIGN AND METHOD--Twenty-two single nucleotide polymorphisms tagging common LPIN1 variation were genotyped in Medical Research Council (MRC) Ely (n = 1,709) and Hertfordshire (n = 2,901) population-based cohorts. LPIN1 exons, exon/intron boundaries, and 3′ untranslated region were sequenced in 158 patients with idiopathic severe insulin resistance (including 23 lipodystrophic patients) and 48 control subjects. RESULTS--We found no association between LPIN1 single nucleotide polymorphisms and fasting insulin but report a nominal association between rs13412852 and BMI (P = 0.042) in a meta-analysis of 8,504 samples from in-house and publicly available studies. Three rare nonsynonymous variants (A353T, R552K, and G582R) were detected in severely insulin-resistant patients. However, these did not cosegregate with disease in affected families, and Lipin1 protein expression and phosphorylation in patients with variants were indistinguishable from those in control subjects. CONCLUSIONS--Our data do not support a major effect of common LPIN1 variation on metabolic traits and suggest that mutations in LPIN1 are not a common cause of lipodystrophy in humans. The nominal associations with BMI and other metabolic traits in U.K. cohorts require replication in larger cohorts. Diabetes 57:2527-2533, 2008 [ABSTRACT FROM AUTHOR]

Objective: Recently, genome-wide association studies have provided evidence that several common variants within the fat mass-and obesity-associated (FTO) gene were significantly associated with obesity in populations of European origin. However, their effects in other ethnic populations remain to be elucidated.Research Design and Methods: In this study, we examined the association between three FTO variants (rs8050136, rs9939609, and rs9930506) and obesity and related traits in a population-based study of 3,210 unrelated Chinese Han subjects from Shanghai and Beijing. In secondary analyses, we also tested for association with type 2 diabetes and related traits. Logistics regression and generalized linear models were used to test for additive and dominant effects of the risk alleles.Results: The minor allele frequencies of rs8050136, rs9939609, and rs9930506 in our population (0.12, 0.12, and 0.20, respectively) were substantially lower than those observed for populations of European descent (e.g., for CEU population of HapMap: 0.45, 0.48, and 0.45, respectively). Despite our study being sufficiently powered to detect effects similar to those previously reported, none of the FTO SNPs were found to be associated with obesity, overweight, BMI, waist circumference, or body fat percentage. In addition, none of the SNPs exhibited significant associations with fasting levels of plasma glucose, A1C, insulin, or beta-cell function (estimated via homeostasis model assessment) under either an additive or a dominant model in the quantitative trait analyses. Analyses stratified by sex or geographical region did not change these observations.Conclusions: Our data do not support that the FTO common variants are major contributors of obesity or type 2 diabetes in the Chinese Han population. [ABSTRACT FROM AUTHOR]

OBJECTIVE--Recently, genome-wide association studies have provided evidence that several common variants within the fat mass-- and obesity-associated (FTO) gene were significantly associated with obesity in populations of European origin. However, their effects in other ethnic populations remain to be elucidated. RESEARCH DESIGN AND METHODS--In this study, we examined the association between three FTO variants (rs8050136, rs9939609, and rs9930506) and obesity and related traits in a population-based study of 3,210 unrelated Chinese Han subjects from Shanghai and Beijing. In secondary analyses, we also tested for association with type 2 diabetes and related traits. Logistics regression and generalized linear models were used to test for additive and dominant effects of the risk alleles. RESULTS--The minor allele frequencies of rs8050136, rs9939609, and rs9930506 in our population (0.12, 0.12, and 0.20, respectively) were substantially lower than those observed for populations of European descent (e.g., for CEU population of HapMap: 0.45, 0.48, and 0.45, respectively). Despite our study being sufficiently powered to detect effects similar to those previously reported, none of the FTO SNPs were found to be associated with obesity, overweight, BMI, waist circumference, or body fat percentage. In addition, none of the SNPs exhibited significant associations with fasting levels of plasma glucose, A1C, insulin, or β-cell function (estimated via homeostasis model assessment) under either an additive or a dominant model in the quantitative trait analyses. Analyses stratified by sex or geographical region did not change these observations. CONCLUSIONS--Our data do not support that the FTO common variants are major contributors of obesity or type 2 diabetes in the Chinese Han population. Diabetes 57:264-268, 2008 [ABSTRACT FROM AUTHOR]

Rapidly accumulating evidence shows that common T-cell transcription factor (TCF)7L2 polymorphisms confer risk of type 2 diabetes through unknown mechanisms. We examined the association between four TCF7L2 single nucleotide polymorphisms (SNPs), including rs7903146, and measures of insulin sensitivity and insulin secretion in 1,697 Europid men and women of the population-based MRC (Medical Research Council)-Ely study. The T-(minor) allele of rs7903146 was strongly and positively associated with fasting proinsulin (P = 4.55 x 10(-9)) and 32,33 split proinsulin (P = 1.72 x 10(-4)) relative to total insulin levels; i.e., differences between T/T and C/C homozygotes amounted to 21.9 and 18.4% respectively. Notably, the insulin-to-glucose ratio (IGR) at 30-min oral glucose tolerance test (OGTT), a frequently used surrogate of first-phase insulin secretion, was not associated with the TCF7L2 SNP (P > 0.7). However, the insulin response (IGR) at 60-min OGTT was significantly lower in T-allele carriers (P = 3.5 x 10(-3)). The T-allele was also associated with higher A1C concentrations (P = 1.2 x 10(-2)) and reduced beta-cell function, assessed by homeostasis model assessment of beta-cell function (P = 2.8 x 10(-2)). Similar results were obtained for the other TCF7L2 SNPs. Of note, both major genes involved in proinsulin processing (PC1, PC2) contain TCF-binding sites in their promoters. Our findings suggest that the TCF7L2 risk allele may predispose to type 2 diabetes by impairing beta-cell proinsulin processing. The risk allele increases proinsulin levels and diminishes the 60-min but not 30-min insulin response during OGTT. The strong association between the TCF7L2 risk allele and fasting proinsulin but not insulin levels is notable, as, in this unselected and largely normoglycemic population, external influences on beta-cell stress are unlikely to be major factors influencing the efficiency of proinsulin processing. [ABSTRACT FROM AUTHOR]

Mutations in the LMNA gene, encoding the nuclear envelope protein lamin A/C, are responsible for a number of distinct disease entities including Dunnigan-type familial partial lipodystrophy. Dunningan-type lipodystrophy is characterized by loss of subcutaneous adipose tissue, insulin resistance, dyslipidemia, and type 2 diabetes and shares many of the features of the metabolic syndrome. Furthermore, several genome-wide linkage scans for type 2 diabetes have found evidence of linkage at chromosome 1q21.2, the region that harbors the LMNA gene. Therefore, LMNA is a biological and positional candidate for type 2 diabetes susceptibility. Previous studies have reported association between a common LMNA variant (1908C>T; rs4641) and adverse metabolic traits in ethnically diverse populations from Asia and North America. In the present study, we characterized the common variation across the LMNA gene (including rs4641) and tested for association with type 2 diabetes in two large case-control studies (n = 2,052) and with features of the metabolic syndrome in a separate cohort study (n = 1,572). Despite our study being sufficiently powered to detect effects similar and even smaller in magnitude than those previously reported, none of the LMNA single nucleotide polymorphisms were statistically significantly associated with type 2 diabetes or the metabolic syndrome. Thus, it appears unlikely that variation at LMNA substantially increases the risk of type 2 diabetes or related traits in U.K. Europids. Diabetes 56:884-889, 2007 [ABSTRACT FROM AUTHOR]

Objective: There is strong evidence that low birth weight is associated with glucose intolerance and diabetes in adults. We have carried out a twin study to distinguish among maternal influences, which affect both twins; fetoplacental influences, which are unique to each twin; and the genetic factors that may underlie this association.Research Design and Methods: We identified a sample of 423 twin pairs (250 monozygotic and 173 dizygotic) from the East Flanders Prospective Twin Survey who were born between 1964 and 1982. Data collected in this study included the mother's body composition and weight gain during pregnancy, the twins' birth weights, and gestational age. The twins (aged 18-34 years) attended a research center for measurement of height, weight, and waist-to-hip ratio as well as fasting glucose, proinsulin, and insulin concentrations.Results: Among twin pairs discordant for birth weight, we found little evidence that the lighter twin had abnormal glucose-insulin metabolism in adult life. However, both a low prepregnancy maternal BMI and older maternal age at delivery were associated with hyperinsulinemia and evidence of insulin resistance in the offspring. Fasting insulin increased by 1.3% (95% CI 0.1-2.6%) per unit fall in maternal BMI and by 1.1% (0.02-2.0%) per year increase in maternal age. These associations were independent of the twins' BMI and waist-to-hip ratio and their zygosity.Conclusions: These novel findings suggest that in twin pregnancies, maternal factors are more important than fetoplacental factors in determining glucose-insulin metabolism in the offspring. [ABSTRACT FROM AUTHOR]

Objective: To identify genetic risk factors for incident cardiovascular disease (CVD) among people with type 2 diabetes (T2D)., Research Design and Methods: We conducted a multiancestry time-to-event genome-wide association study for incident CVD among people with T2D. We also tested 204 known coronary artery disease (CAD) variants for association with incident CVD., Results: Among 49,230 participants with T2D, 8,956 had incident CVD events (event rate 18.2%). We identified three novel genetic loci for incident CVD: rs147138607 (near CACNA1E/ZNF648, hazard ratio [HR] 1.23, P = 3.6 × 10-9), rs77142250 (near HS3ST1, HR 1.89, P = 9.9 × 10-9), and rs335407 (near TFB1M/NOX3, HR 1.25, P = 1.5 × 10-8). Among 204 known CAD loci, 5 were associated with incident CVD in T2D (multiple comparison-adjusted P < 0.00024, 0.05/204). A standardized polygenic score of these 204 variants was associated with incident CVD with HR 1.14 (P = 1.0 × 10-16)., Conclusions: The data point to novel and known genomic regions associated with incident CVD among individuals with T2D., (© 2024 by the American Diabetes Association.)

African Americans (AAs) have been underrepresented in polygenic risk score (PRS) studies. Here, we integrated genome-wide data from multiple observational studies on type 2 diabetes (T2D), encompassing a total of 101,987 AAs, to train and optimize an AA-focused T2D PRS (PRSAA), using a Bayesian polygenic modeling method. We further tested the score in three independent studies with a total of 7,275 AAs and compared the PRSAA with other published scores. Results show that a 1-SD increase in the PRSAA was associated with 40-60% increase in the odds of T2D (odds ratio [OR] 1.60, 95% CI 1.37-1.88; OR 1.40, 95% CI 1.16-1.70; and OR 1.45, 95% CI 1.30-1.62) across three testing cohorts. These models captured 1.0-2.6% of the variance (R2) in T2D on the liability scale. The positive predictive values for three calculated score thresholds (the top 2%, 5%, and 10%) ranged from 14 to 35%. The PRSAA, in general, performed similarly to existing T2D PRS. The need remains for larger data sets to continue to evaluate the utility of within-ancestry scores in the AA population., (© 2024 by the American Diabetes Association.)

Objective: Automated algorithms to identify individuals with type 1 diabetes using electronic health records are increasingly used in biomedical research. It is not known whether the accuracy of these algorithms differs by self-reported race. We investigated whether polygenic scores improve identification of individuals with type 1 diabetes., Research Design and Methods: We investigated two large hospital-based biobanks (Mass General Brigham [MGB] and BioMe) and identified individuals with type 1 diabetes using an established automated algorithm. We performed medical record reviews to validate the diagnosis of type 1 diabetes. We implemented two published polygenic scores for type 1 diabetes (developed in individuals of European or African ancestry). We assessed the classification algorithm before and after incorporating polygenic scores., Results: The automated algorithm was more likely to incorrectly assign a diagnosis of type 1 diabetes in self-reported non-White individuals than in self-reported White individuals (odds ratio 3.45; 95% CI 1.54-7.69; P = 0.0026). After incorporating polygenic scores into the MGB Biobank, the positive predictive value of the type 1 diabetes algorithm increased from 70 to 97% for self-reported White individuals (meaning that 97% of those predicted to have type 1 diabetes indeed had type 1 diabetes) and from 53 to 100% for self-reported non-White individuals. Similar results were found in BioMe., Conclusions: Automated phenotyping algorithms may exacerbate health disparities because of an increased risk of misclassification of individuals from underrepresented populations. Polygenic scores may be used to improve the performance of phenotyping algorithms and potentially reduce this disparity., (© 2023 by the American Diabetes Association.)

Objective: Type 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 Methods: Here 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)., Results: Despite 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., Conclusions: Our findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes., (© 2022 by the American Diabetes Association.)

The pathogenesis of type 2 diabetes (T2D) might change with increasing age. Here, we used a stratification based on age of diagnosis to gain insight into the genetics and causal risk factors of T2D across different age-groups. We performed genome-wide association studies (GWAS) on T2D and T2D subgroups based on age of diagnosis (<50, 50-60, 60-70, and >70 years) (total of 24,986 cases). As control subjects, participants were at least 70 years of age at the end of follow-up without developing T2D ( N =187,130). GWAS identified 208 independent lead single nucleotide polymorphism (SNPs) mapping to 69 loci associated with T2D ( P < 1.0e-8). Among others, SNPs mapped to CDKN2B-AS1 and multiple independent SNPs mapped to TCF7L2 were more strongly associated with cases diagnosed after age 70 years than with cases diagnosed before age 50 years. Based on the different case groups, we performed two-sample Mendelian randomization. Most notably, we observed that of the investigated risk factors, the association between BMI and T2D attenuated with increasing age of diagnosis. Collectively, our results indicate that stratification of T2D based on age of diag-nosis reveals subgroup-specific genetics and causal determinants, supporting the hypothesis that the pathogenesis of T2D changes with increasing age., (© 2021 by the American Diabetes Association.)

Leptin influences food intake by informing the brain about the status of body fat stores. Rare LEP mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in LEP , ZNF800 , KLHL31 , and ACTL9 , and one intergenic variant near KLF14. The missense variant Val94Met (rs17151919) in LEP was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry ( P = 2 × 10 -16 , n = 3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting that leptin regulates early adiposity., (© 2020 by the American Diabetes Association.)

Objective: We aimed to identify hemoglobin A 1c (HbA 1c )-associated genetic variants and examine their implications for glycemic status evaluated by HbA 1c in U.S. Hispanics/Latinos with diverse genetic ancestries., Research Design and Methods: We conducted a genome-wide association study (GWAS) of HbA 1c in 9,636 U.S. Hispanics/Latinos without diabetes from the Hispanic Community Health Study/Study of Latinos, followed by a replication among 4,729 U.S. Hispanics/Latinos from three independent studies., Results: Our GWAS and replication analyses showed 10 previously known and novel loci associated with HbA 1c at genome-wide significance levels ( P < 5.0 × 10 -8 ). In particular, two African ancestry-specific variants, HBB- rs334 and G6PD -rs1050828, which are causal mutations for sickle cell disease and G6PD deficiency, respectively, had ∼10 times larger effect sizes on HbA 1c levels (β = -0.31% [-3.4 mmol/mol]) and -0.35% [-3.8 mmol/mol] per minor allele, respectively) compared with other HbA 1c -associated variants (0.03-0.04% [0.3-0.4 mmol/mol] per allele). A novel Amerindian ancestry-specific variant, HBM -rs145546625, was associated with HbA 1c and hematologic traits but not with fasting glucose. The prevalence of hyperglycemia (prediabetes and diabetes) defined using fasting glucose or oral glucose tolerance test 2-h glucose was similar between carriers of HBB- rs334 or G6PD -rs1050828 HbA 1c -lowering alleles and noncarriers, whereas the prevalence of hyperglycemia defined using HbA 1c was significantly lower in carriers than in noncarriers (12.2% vs. 28.4%, P < 0.001). After recalibration of the HbA 1c level taking HBB -rs334 and G6PD -rs1050828 into account, the prevalence of hyperglycemia in carriers was similar to noncarriers (31.3% vs. 28.4%, P = 0.28)., Conclusions: This study in U.S. Hispanics/Latinos found several ancestry-specific alleles associated with HbA 1c through erythrocyte-related rather than glycemic-related pathways. The potential influences of these nonglycemic-related variants need to be considered when the HbA 1c test is performed., (© 2019 by the American Diabetes Association.)

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci ( P < 5 × 10 -8 ), including variants near the GLP2R , GIP , and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology., (© 2017 by the American Diabetes Association.)

Elevated concentrations of albumin in the urine, albuminuria, are a hallmark of diabetic kidney disease and are associated with an increased risk for end-stage renal disease and cardiovascular events. To gain insight into the pathophysiological mechanisms underlying albuminuria, we conducted meta-analyses of genome-wide association studies and independent replication in up to 5,825 individuals of European ancestry with diabetes and up to 46,061 without diabetes, followed by functional studies. Known associations of variants in CUBN, encoding cubilin, with the urinary albumin-to-creatinine ratio (UACR) were confirmed in the overall sample (P = 2.4 × 10(-10)). Gene-by-diabetes interactions were detected and confirmed for variants in HS6ST1 and near RAB38/CTSC. Single nucleotide polymorphisms at these loci demonstrated a genetic effect on UACR in individuals with but not without diabetes. The change in the average UACR per minor allele was 21% for HS6ST1 (P = 6.3 × 10(-7)) and 13% for RAB38/CTSC (P = 5.8 × 10(-7)). Experiments using streptozotocin-induced diabetic Rab38 knockout and control rats showed higher urinary albumin concentrations and reduced amounts of megalin and cubilin at the proximal tubule cell surface in Rab38 knockout versus control rats. Relative expression of RAB38 was higher in tubuli of patients with diabetic kidney disease compared with control subjects. The loci identified here confirm known pathways and highlight novel pathways influencing albuminuria., (© 2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.)

The FTO gene harbors variation with the strongest effect on adiposity and obesity risk. Previous data support a role for FTO variation in influencing food intake. We conducted a combined analysis of 16,094 boys and girls aged 1-18 years from 14 studies to examine the following: 1) the association between the FTO rs9939609 variant (or a proxy) and total energy and macronutrient intake; and 2) the interaction between the FTO variant and dietary intake, and the effect on BMI. We found that the BMI-increasing allele (minor allele) of the FTO variant was associated with increased total energy intake (effect per allele = 14.3 kcal/day [95% CI 5.9, 22.7 kcal/day], P = 6.5 × 10(-4)), but not with protein, carbohydrate, or fat intake. We also found that protein intake modified the association between the FTO variant and BMI (interactive effect per allele = 0.08 SD [0.03, 0.12 SD], P for interaction = 7.2 × 10(-4)): the association between FTO genotype and BMI was much stronger in individuals with high protein intake (effect per allele = 0.10 SD [0.07, 0.13 SD], P = 8.2 × 10(-10)) than in those with low intake (effect per allele = 0.04 SD [0.01, 0.07 SD], P = 0.02). Our results suggest that the FTO variant that confers a predisposition to higher BMI is associated with higher total energy intake, and that lower dietary protein intake attenuates the association between FTO genotype and adiposity in children and adolescents., (© 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.)

Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes, but its causal role remains controversial. We used a Mendelian randomization approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics-based genetic risk scores to test the associations with gold-standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 case subjects and 64,731 control subjects). In conventional regression analyses, a 1-SD decrease in adiponectin levels was correlated with a 0.31-SD (95% CI 0.26-0.35) increase in fasting insulin, a 0.34-SD (0.30-0.38) decrease in insulin sensitivity, and a type 2 diabetes odds ratio (OR) of 1.75 (1.47-2.13). The instrumental variable analysis revealed no evidence of a causal association between genetically lower circulating adiponectin and higher fasting insulin (0.02 SD; 95% CI -0.07 to 0.11; N = 29,771), nominal evidence of a causal relationship with lower insulin sensitivity (-0.20 SD; 95% CI -0.38 to -0.02; N = 1,860), and no evidence of a relationship with type 2 diabetes (OR 0.94; 95% CI 0.75-1.19; N = 2,777 case subjects and 13,011 control subjects). Using the ADIPOQ summary statistics genetic risk scores, we found no evidence of an association between adiponectin-lowering alleles and insulin sensitivity (effect per weighted adiponectin-lowering allele: -0.03 SD; 95% CI -0.07 to 0.01; N = 2,969) or type 2 diabetes (OR per weighted adiponectin-lowering allele: 0.99; 95% CI 0.95-1.04; 15,960 case subjects vs. 64,731 control subjects). These results do not provide any consistent evidence that interventions aimed at increasing adiponectin levels will improve insulin sensitivity or risk of type 2 diabetes.

Substantial progress has been made in identification of type 2 diabetes (T2D) risk loci in the past few years, but our understanding of the genetic basis of T2D in ethnically diverse populations remains limited. We performed a genome-wide association study and a replication study in Chinese Hans comprising 8,569 T2D case subjects and 8,923 control subjects in total, from which 10 single nucleotide polymorphisms were selected for further follow-up in a de novo replication sample of 3,410 T2D case and 3,412 control subjects and an in silico replication sample of 6,952 T2D case and 11,865 control subjects. Besides confirming seven established T2D loci (CDKAL1, CDKN2A/B, KCNQ1, CDC123, GLIS3, HNF1B, and DUSP9) at genome-wide significance, we identified two novel T2D loci, including G-protein-coupled receptor kinase 5 (GRK5) (rs10886471: P = 7.1 × 10(-9)) and RASGRP1 (rs7403531: P = 3.9 × 10(-9)), of which the association signal at GRK5 seems to be specific to East Asians. In nondiabetic individuals, the T2D risk-increasing allele of RASGRP1-rs7403531 was also associated with higher HbA(1c) and lower homeostasis model assessment of β-cell function (P = 0.03 and 0.0209, respectively), whereas the T2D risk-increasing allele of GRK5-rs10886471 was also associated with higher fasting insulin (P = 0.0169) but not with fasting glucose. Our findings not only provide new insights into the pathophysiology of T2D, but may also shed light on the ethnic differences in T2D susceptibility.

Gene-lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13-0.31], P = 1.63 × 10(-6)). All SNPs were associated with 2-h glucose (β = 0.06-0.12 mmol/allele, P ≤ 1.53 × 10(-7)), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene-lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions.

Objective: Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology., Research Design and Methods: We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates., Results: Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets., Conclusions: We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis.

Objective: To investigate whether associations of common genetic variants recently identified for fasting glucose or insulin levels in nondiabetic adults are detectable in healthy children and adolescents., Research Design and Methods: A total of 16 single nucleotide polymorphisms (SNPs) associated with fasting glucose were genotyped in six studies of children and adolescents of European origin, including over 6,000 boys and girls aged 9-16 years. We performed meta-analyses to test associations of individual SNPs and a weighted risk score of the 16 loci with fasting glucose., Results: Nine loci were associated with glucose levels in healthy children and adolescents, with four of these associations reported in previous studies and five reported here for the first time (GLIS3, PROX1, SLC2A2, ADCY5, and CRY2). Effect sizes were similar to those in adults, suggesting age-independent effects of these fasting glucose loci. Children and adolescents carrying glucose-raising alleles of G6PC2, MTNR1B, GCK, and GLIS3 also showed reduced β-cell function, as indicated by homeostasis model assessment of β-cell function. Analysis using a weighted risk score showed an increase [β (95% CI)] in fasting glucose level of 0.026 mmol/L (0.021-0.031) for each unit increase in the score., Conclusions: Novel fasting glucose loci identified in genome-wide association studies of adults are associated with altered fasting glucose levels in healthy children and adolescents with effect sizes comparable to adults. In nondiabetic adults, fasting glucose changes little over time, and our results suggest that age-independent effects of fasting glucose loci contribute to long-term interindividual differences in glucose levels from childhood onwards.

Objective: Glycated hemoglobin (HbA₁(c)), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA₁(c). We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA₁(c) levels., Research Design and Methods: We studied associations with HbA₁(c) in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA₁(c) loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening., Results: Ten loci reached genome-wide significant association with HbA(1c), including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10⁻²⁶), HFE (rs1800562/P = 2.6 × 10⁻²⁰), TMPRSS6 (rs855791/P = 2.7 × 10⁻¹⁴), ANK1 (rs4737009/P = 6.1 × 10⁻¹²), SPTA1 (rs2779116/P = 2.8 × 10⁻⁹) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10⁻⁹), and four known HbA₁(c) loci: HK1 (rs16926246/P = 3.1 × 10⁻⁵⁴), MTNR1B (rs1387153/P = 4.0 × 10⁻¹¹), GCK (rs1799884/P = 1.5 × 10⁻²⁰) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10⁻¹⁸). We show that associations with HbA₁(c) are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA₁(c)) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA₁(c)., Conclusions: GWAS identified 10 genetic loci reproducibly associated with HbA₁(c). Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA₁(c) levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA₁(c).

Objective: Genome-wide association studies have identified common variants in CDKAL1, CDKN2A/B, IGF2BP2, SLC30A8, HHEX/IDE, EXT2, and LOC387761 loci that significantly increase the risk of type 2 diabetes. We aimed to replicate these observations in a population-based cohort of Chinese Hans and examine the associations of these variants with type 2 diabetes and diabetes-related phenotypes., Research Design and Methods: We genotyped 17 single nucleotide polymorhisms (SNPs) in 3,210 unrelated Chinese Hans, including 424 participants with type 2 diabetes, 878 with impaired fasting glucose (IFG), and 1,908 with normal fasting glucose., Results: We confirmed the associations between type 2 diabetes and variants near CDKAL1 (odds ratio 1.49 [95% CI 1.27-1.75]; P = 8.91 x 10(-7)) and CDKN2A/B (1.31 [1.12-1.54]; P = 1.0 x 10(-3)). We observed significant association of SNPs in IGF2BP2 (1.17 [1.03-1.32]; P = 0.014) and SLC30A8 (1.12 [1.01-1.25]; P = 0.033) with combined IFG/type 2 diabetes. The SNPs in CDKAL1, IGF2BP2, and SLC30A8 were also associated with impaired beta-cell function estimated by homeostasis model assessment of beta-cell function. When combined, each additional risk allele from CDKAL1-rs9465871, CDKN2A/B-rs10811661, IGF2BP2-rs4402960, and SLC30A8-rs13266634 increased the risk for type 2 diabetes by 1.24-fold (P = 2.85 x 10(-7)) or for combined IFG/type 2 diabetes by 1.21-fold (P = 6.31 x 10(-11)). None of the SNPs in EXT2 or LOC387761 exhibited significant association with type 2 diabetes or IFG. Significant association was observed between the HHEX/IDE SNPs and type 2 diabetes in individuals from Shanghai only (P < 0.013) but not in those from Beijing (P > 0.33)., Conclusions: Our results indicate that in Chinese Hans, common variants in CDKAL1, CDKN2A/B, IGF2BP2, and SLC30A8 loci independently or additively contribute to type 2 diabetes risk, likely mediated through beta-cell dysfunction.