Racial and Ethnic Cardiometabolic Risk Disparities in the Type 1 Diabetes Exchange Clinic Registry Cohort

ObjectiveTo determine whether individuals from a historically underrepresented racial group have a higher cardiometabolic risk than historically represented individuals with type 1 diabetes (T1D) considering socioeconomic deprivation.MethodsWe used the multivariable logistic and linear regression models to examine socioeconomic deprivation (upper 10th percentile) by race/ethnicity interaction for each cardiometabolic risk factor and cardiometabolic risk burden score, respectively, across 6320 zip code tabulation areas. We also determined the age-adjusted prevalence of low, moderate, and high cardiometabolic risks defined as 0, 1 to 2, and 3 or more risk factors for hypertension, obesity, dyslipidemia, and off-target glycemia for non-Hispanic White (n = 15 746), non-Hispanic Black (n = 1019), Hispanic (n = 1115), and other (n = 887), respectively.ResultsThe sample comprised 18 767 adolescents and adults with T1D. Those identifying as non-Hispanic Black were more likely to have a high cardiometabolic risk profile, including a 4.5-fold increase in the odds of off-target glycemia, a twofold increase in the odds of systolic hypertension, and 0.29 (unadjusted) and 0.46 (adjusted) increases in a higher cardiometabolic risk burden compared with non-Hispanic White individuals (P < .01). Those identifying as Hispanic had a 3.4-fold increase in the odds of off-target glycemia but were less likely to be overweight/obese or have systolic hypertension compared with non-Hispanic White. However, the lower likelihood of overweight/obesity and hypertension did not persist after considering covariates.ConclusionThere is a need to investigate additional determinants of racially/ethnically underrepresented cardiometabolic health, including structural racism and implicit bias in cardiometabolic care for individuals with T1D.     

Identification of New Genetic Risk Variants for Type 2 Diabetes

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

The Association of Handgrip Strength and Type 2 Diabetes Mellitus in Six Ethnic Groups: An Analysis of the HELIUS Study

We investigated whether ethnic differences in handgrip strength, a marker of poor muscle strength and quality, is a potential cause of ethnic disparities in type 2 diabetes mellitus. We included 2086 Dutch, 2216 South Asian Surinamese, 2084 African Surinamese, 1786 Ghanaian, 2223 Turkish and 2199 Moroccan origin participants from the HELIUS study. We analyzed ethnic differences in handgrip strength, and its association with type 2 diabetes mellitus using logistic regression analyses adjusted for socio-demographic factors, body composition and lifestyle factors. Additionally, we investigated whether handgrip strength explained the ethnic differences in type 2 diabetes mellitus. We found that handgrip strength differed significantly across ethnic groups. After full adjustment, we found an inverse association with type 2 diabetes mellitus (OR 0.95; 95% CI 0.92–0.97) that did not differ substantially between ethnic groups, men and among women, and lean and overweight individuals. The association was not affected by the measure used to define type 2 diabetes mellitus, but was attenuated by exclusion of people with known diabetes. The ethnic differences in type 2 diabetes mellitus were not explained by handgrip strength (e.g. the OR for the South Asian Surinamese vs. Dutch changed from 5.03; 3.69–6.68 to 4.87; 3.57–6.65). In conclusion, we found large ethnic differences in handgrip strength and a consistent association of low handgrip strength with prevalent type 2 diabetes mellitus. This suggests that handgrip strength may be investigated as a target for intervention or a marker to identify people at risk of type 2 diabetes mellitus.     

Genetic Variants of TPCN2 Associated with Type 2 Diabetes Risk in the Chinese Population

Objective

The aim of this study was to determine whether TPCN2 genetic variants are associated with type 2 diabetes and to elucidate which variants in TPCN2 confer diabetes susceptibility in the Chinese population.

Research Design and Methods

The sample population included 384 patients with type 2 diabetes and 1468 controls. Anthropometric parameters, glycemic and lipid profiles and insulin resistance were measured. We selected 6 TPCN2 tag single nucleotide polymorphisms (rs35264875, rs267603153, rs267603154, rs3829241, rs1551305, and rs3750965). Genotypes were determined using a Sequenom MassARRAY SNP genotyping system.

Results

Ultimately, we genotyped 3 single nucleotide polymorphisms (rs3750965, rs3829241, and rs1551305) in all individuals. There was a 5.1% higher prevalence of the rs1551305 variant allele in type 2 diabetes individuals (A) compared with wild-type homozygous individuals (G). The AA genotype of rs1551305 was associated with a higher diabetes risk (p<0.05). The distributions of rs3829241 and rs3750965 polymorphisms were not significantly different between the two groups. HOMA-%B of subjects harboring the AA genotype of rs1551305 decreased by 14.87% relative to the GG genotype.

Conclusions

TPCN2 plays a role in metabolic regulation, and the rs1551305 single nucleotide polymorphism is associated with type 2 diabetes risk. Future work will begin to unravel the underlying mechanisms.     

Meta-Analysis of the Relationship between Common Type 2 Diabetes Risk Gene Variants with Gestational Diabetes Mellitus

Background

A number of case-control studies were conducted to investigate the association of common type 2 diabetes (T2D) risk gene polymorphisms with gestational diabetes mellitus (GDM). However, these studies have yielded contradictory results. We therefore performed a meta-analysis to derive a more precise estimation of the association between these polymorphisms and GDM, hence achieve a better understanding to the relationship between T2D and GDM.

Methods

PubMed, EMBASE, ISI web of science and the Chinese National Knowledge Infrastructure databases were systematically searched to identify relevant studies. Data were abstracted independently by two reviewers. A meta-analysis was performed to examine the association between 9 polymorphisms from 8 genes and susceptibility to GDM. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. Heterogeneity among articles and their publication bias were also tested.

Results

We identified 22 eligible studies including a total of 10,336 GDM cases and 17,445 controls. We found 8 genetic polymorphisms were significantly associated with GDM in a random-effects meta-analysis. These polymorphisms were in or near the following genes: TCF7L2 (rs7903146), MTNR1B (rs10830963), IGF2BP2 (rs4402960), KCNJ11 (rs5219), CDKAL1 (rs7754840), KCNQ1 (rs2237892 and rs2237895) and GCK (rs4607517); while no association was found for PPARG with GDM risk. Similar results were also observed under dominant genetic model for these polymorphisms.

Conclusions

This meta-analysis found 8 genetic variants associated with GDM. The relative contribution and relevance of the identified genes in the pathogenesis of GDM should be the focus of future studies.     

Validation of Type 2 Diabetes Risk Variants Identified by Genome-Wide Association Studies in Han Chinese Population: A Replication Study and Meta-Analysis

Background

Several genome-wide association studies (GWAS) involving European populations have successfully identified risk genetic variants associated with type 2 diabetes mellitus (T2DM). However, the effects conferred by these variants in Han Chinese population have not yet been fully elucidated.

Methods

We analyzed the effects of 24 risk genetic variants with reported associations from European GWAS in 3,040 Han Chinese subjects in Taiwan (including 1,520 T2DM cases and 1,520 controls). The discriminative power of the prediction models with and without genotype scores was compared. We further meta-analyzed the association of these variants with T2DM by pooling all candidate-gene association studies conducted in Han Chinese.

Results

Five risk variants in IGF2BP2 (rs4402960, rs1470579), CDKAL1 (rs10946398), SLC30A8 (rs13266634), and HHEX (rs1111875) genes were nominally associated with T2DM in our samples. The odds ratio was 2.22 (95% confidence interval, 1.81-2.73, P<0.0001) for subjects with the highest genetic score quartile (score>34) as compared with subjects with the lowest quartile (score<29). The incoporation of genotype score into the predictive model increased the C-statistics from 0.627 to 0.657 (P<0.0001). These estimates are very close to those observed in European populations. Gene-environment interaction analysis showed a significant interaction between rs13266634 in SLC30A8 gene and age on T2DM risk (P<0.0001). Further meta-analysis pooling 20 studies in Han Chinese confirmed the association of 10 genetic variants in IGF2BP2, CDKAL1, JAZF1, SCL30A8, HHEX, TCF7L2, EXT2, and FTO genes with T2DM. The effect sizes conferred by these risk variants in Han Chinese were similar to those observed in Europeans but the allele frequencies differ substantially between two populations.

Conclusion

We confirmed the association of 10 variants identified by European GWAS with T2DM in Han Chinese population. The incorporation of genotype scores into the prediction model led to a small but significant improvement in T2DM prediction.     

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

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

Risk Factors for Acute Stroke among South Asians Compared to Other Racial/Ethnic Groups

Background

Studies of racial/ethnic variations in stroke rarely consider the South Asian population, one of the fastest growing sub-groups in the United States. This study compared risk factors for stroke among South Asians with those for whites, African-Americans, and Hispanics.

Methods

Data on 3290 stroke patients were analyzed to examine risk differences among the four racial/ethnic groups. Data on 3290 patients admitted to a regional stroke center were analyzed to examine risk differences for ischemic stroke (including subtypes of small and large vessel disease) among South Asians, whites, African Americans and Hispanics.

Results

South Asians were younger and had higher rates of diabetes mellitus, blood pressure, and fasting blood glucose levels than other race/ethnicities. Prevalence of diabetic and antiplatelet medication use, as well as the incidence of small-artery occlusion ischemic stroke was also higher among South Asians. South Asians were almost a decade younger and had comparable socioeconomic levels as whites; however, their stroke risk factors were comparable to that of African Americans and Hispanics.

Discussion

Observed differences in stroke may be explained by dietary and life style choices of South Asian-Americans, risk factors that are potentially modifiable. Future population and epidemiologic studies should consider growing ethnic minority groups in the examination of the nature, outcome, and medical care profiles of stroke.     

Variations in BMI and Prevalence of Health Risks in Diverse Racial and Ethnic Populations

When examining health risks associated with the BMI, investigators often rely on the customary BMI thresholds of the 1995 World Health Organization report. However, within‐interval variations in morbidity and mortality can be substantial, and the thresholds do not necessarily correspond to identifiable risk increases. Comparing the prevalence of hypertension, diabetes, coronary heart disease (CHD), asthma, and arthritis among non‐Hispanic whites, blacks, East Asians and Hispanics, we examine differences in the BMI‐health‐risk relationships for small BMI increments. The analysis is based on 11 years of data of the National Health Interview Survey (NHIS), with a sample size of 337,375 for the combined 1997–2007 Sample Adult. The analysis uses multivariate logistic regression models, employing a nonparametric approach to modeling the BMI‐health‐risk relationship, while relying on narrowly defined BMI categories. Rising BMI levels are associated with higher levels of chronic disease burdens in four major racial and ethnic groups, even after adjusting for many socio‐demographic characteristics and three important health‐related behaviors (smoking, physical activity, alcohol consumption). For all population groups, except East Asians, a modestly higher disease risk was noted for persons with a BMI <20 compared with persons with BMI in the range of 20–21. Using five chronic conditions as risk criteria, a categorization of the BMI into normal weight, overweight, or obesity appears arbitrary. Although the prevalence of disease risks differs among racial and ethnic groups regardless of BMI levels, the evidence presented here does not support the notion that the BMI‐health‐risk profile of East Asians and others warrants race‐specific BMI cutoff points.     

Investigation of Variants in UCP2 in Chinese Type 2 Diabetes and Diabetic Retinopathy

Purpose

The aim of this study was to investigate variants in UCP2 genes in type 2 diabetes mellitus (DM) and diabetic retinopathy (DR) in Chinese population.

Materials and Methods

We conducted a single nucleotide polymorphism-based and haplotype-based case-control study between the variants of UCP2 and DM and between the variants of UCP2 and DR in 479 Chinese patients with type 2 DM and 479 control subjects without DM. Two SNPs (rs660339 and rs659366) were selected as genetic markers.

Results

The risk allele C at UCP2 rs660339 was closely associated with DM in Chinese population. There was significant difference in rs660339 between DM and controls (P = 0.0016; OR [95%CI]  = 1.37 (1.14–1.65)). Subjects who were homozygous of the C allele were more likely to develop DM. The frequency of C allele was higher in DM (58%) than in control (51%). But this locus didn''t have a definite effect on the onset of non-proliferative diabetic retinopathy (NPDR) (P = 0.44; OR [95%CI]  = 0.80 (0.56–1.14)) and proliferative diabetic retinopathy (PDR) (P = 1.00; OR [95%CI]  = 0.99 (0.74–1.34)) comparing to subjects with DM without retinopathy (DWR), respectively. Moreover, the UCP2 rs659366 polymorphism showed no significant difference between DM and control (P = 0.66; OR [95%CI]  = 1.10 (0.91–1.32)). However, there was a significant difference between PDR and DWR (P = 0.016; OR [95%CI]  = 0.66 (0.49–0.90)), but there was no difference between NPDR and DWR (P = 1.00; OR [95%CI]  = 0.96 (0.67–1.37)). Participants who carried the G allele at rs659366 were more likely to develop PDR. For the haplotype, C-A was present more frequently in DM than in control (16% vs 7%), indicating that it was risky, and T-A was present less in DM than in control (29% vs 35%). Haplotype frequencies in DR and DWR showed no significant difference (P = 0.068).

Conclusion

It was indicated that UCP2 may be implicated in the pathogenesis of type 2 DM and DR in Chinese population.     

Association between the Fatty Liver Index and Risk of Type 2 Diabetes in the EPIC-Potsdam Study

The fatty liver index (FLI) predicts fatty liver by using BMI, waist circumference, γ-glutamyltransferase and triglycerides. We investigated the association between the FLI and the risk of type 2 diabetes and evaluated to what extent single FLI components contribute to the diabetes risk. We analysed a case-cohort study (random sub-cohort: 1922; incident cases: 563) nested within the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study. The proportion of exposure effect (PEE) explained by single FLI components was evaluated and effect decomposition using inverse probability weighting (IPW) was applied. Women and men with a FLI ≥60 compared to those with a FLI <30 had a multivariable-adjusted Hazard Ratio (HR) of 17.6; 95% confidence interval (CI) 11.1-28.0 and HR: 10.9; 95% CI 6.22-19.2, respectively. Adjustment for BMI or waist circumference attenuated this association in men [PEE_BMI (95% CI) = 53.8% (43.9%-65.8%); PEE_waist (95% CI) = 54.8% (44.2%-68.8%)]. In women, adjustment for waist circumference attenuated the association to a lesser degree than in men [PEE_waist (95% CI) = 31.1%; (21.9%-43.1%)] while BMI had no appreciable effect [PEE_BMI (95% CI) = 11.0% (2.68%-21.0%)]. γ-glutamyltransferase and triglycerides showed only a small attenuation in women [PEE_GGT(95% CI) = 3.11% (-0.72%-4.48%); PEE_TG (95% CI) = 6.36% (3.81%-9.92%)] and in men [PEE_GGT = 0%; PEE_TG (95% CI) = 6.23% (2.03%-11.8%)]. In women, the total effect was decomposed into a direct effect and 4 indirect effects (HR_BMI = 1.10; HR_waist = 1.28; HR_GGT = 0.97 and HR_TG = 1.03). In men, the 4 indirect effects were HR_BMI = 1.25; HR_waist = 1.29; HR_GGT = 0.97 and HR_TG = 0.99. These data suggest that the FLI, as a proxy for fatty liver, is associated with risk of type 2 diabetes. This association is only partly explained by standard estimates of overall and abdominal body fatness, particularly among women.     

Association of Lower Serum Cholesterol Levels with Higher Risk of Osteoporosis in Type 2 Diabetes

ObjectiveTo determine whether a correlation exists between bone mineral density and circulating lipoprotein levels and whether these variables are independently associated with osteoporosis in patients with type 2 diabetes.MethodsIn a cross-sectional analysis, 159 patients with type 2 diabetes were compared with 70 patients without diabetes selected from an outpatient endocrinology clinic in a tertiary care institute during a 1-year period. Variables were gathered through history, physical examination, and laboratory findings, including blood chemistry studies and dual-energy x-ray absorptiometry.ResultsOf the 229 study patients, 86 (37.6%) had osteoporosis. In the patients with diabetes, the mean ± SD of age, weight, total cholesterol, and low-density lipoprotein (LDL) cholesterol in those with and without osteoporosis was 72.3 ± 10.4 years versus 63.6 ± 11.0 years, 74.2 ± 14.4 kg versus 83.7 ± 15.5 kg, 178.4 ± 33.7 mg/dL versus 194.1 ± 33.9 mg/dL, and 100.0 ± 27.1 mg/dL versus 114.2 ± 30.2 mg/dL, respectively (P < 0.01 for all variables). After adjustment for other variables, multiple logistic regression analysis showed that the presence of diabetes was associated with a lower risk of osteoporosis. Similarly, older age and lower body weight, LDL levels, and serum calcium levels were independently associated with lumbar spine osteoporosis in patients with diabetes, in comparison with older age and lower weight in patients without diabetes. Lower weight and older age were associated with femoral neck and total hip osteoporosis in patients with diabetes, in comparison with only older age in patients without diabetes.ConclusionThe presence of type 2 diabetes is associated with a lower risk of osteoporosis. In patients with type 2 diabetes, a lower LDL level is more likely to be associated with osteoporosis at the lumbar spine. (Endocr Pract. 2007;13:620-628)     

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

Background

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

Methods

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

Results

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

Conclusions

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

Weight Change and Risk of Developing Type 2 Diabetes

Objective: To examine the association between weight change and risk of type 2 diabetes and whether initial weight modifies the association. Research Methods and Procedures: This is a prospective cohort study of 20, 187 alumni from Harvard University and the University of Pennsylvania. At baseline in 1962 or 1966, men (mean age, 45.9 years) reported their weight, height, and other risk factors. They also had had their weight and height measured at university entry (mean age, 18.5 years). Participants were followed from baseline to 1998 for type 2 diabetes. Results: During follow‐up, 1223 men developed type 2 diabetes. Weight gain significantly increased the risk of this disease. The multivariate relative risks associated with BMI change from university entry to baseline of <?0.5, ±0.5, >0.5 to 1.0, >1.0 to 1.5, >1.5 to 2.0, >2.0 to 3.0, and >3.0 kg/m² per decade were 0.88, 1.00 (referent), 1.29, 2.09, 2.69, 4.67, and 7.02, respectively (p for trend < 0.0001). Even among men with a low initial BMI < 21 kg/m², weight gain significantly increased risk; the corresponding relative risks were (no cases), 1.00 (referent), 1.00, 1.93, 2.47, 4.82, and 7.68, respectively (p for trend < 0.0001). Discussion: A low initial BMI does not ameliorate the increase in risk of type 2 diabetes with weight gain. Avoidance of weight gain, even among lean individuals, is important to reduce the risk of this disease.     

Association between Adolescents' Physical Activity and Sedentary Behaviors with Change in BMI and Risk of Type 2 Diabetes

This study aims at identifying the association between physical activity (PA) and sedentary behavior (SB) patterns during adolescents on the future increase in BMI and risk of diabetes during young adulthood. A total of 3,717 participants aged 11 to 21 at baseline who completed Waves I (1994–1995), II (1996), III (2001–2002), and IV (2008) surveys of the National Longitudinal Study of Adolescent Health (Add Health) were analyzed. Physical activity and sedentary behavior patterns were assessed using an interviewer-administered questionnaire at Waves I, II, and III. A participant was classified as having diabetes at Wave IV according to WHO guidelines. The k-means cluster analysis was used to identify the number of PA and SB patterns assessed using interviewer-administered questionnaire. The k-means cluster analysis identified three clusters; 575 (15.5%), 2,140 (57.6%), and 1,002 (27.0%) participants belonged to the low PA high SB (LPAHSB), the LPALSB, and the HPALSB cluster respectively. Relative to the LPALSB cluster, the HPALSB cluster had lower increase in BMI from Wave III to Wave IV (P = 0.03), whereas the difference between LPAHSB cluster and LPALSB cluster was not significant (P = 0.09). The odds of developing diabetes at Wave IV was significant for the LPAHSB cluster (OR = 1.69, 95% CI = 1.04, 2.75) but not significant for the HPALSB cluster (OR = 0.87, 95% CI = 0.52, 1.47) relative to the LPALSB cluster. To conclude, PA but not SB during adolescence predicted change in BMI during young adulthood. SB but not PA during adolescence predicted type 2 diabetes during young adulthood.     

Genetic Variants Associated with Lipid Profiles in Chinese Patients with Type 2 Diabetes

Dyslipidemia is a strong risk factor for cardiovascular disease among patients with type 2 diabetes (T2D). The aim of this study was to identify lipid-related genetic variants in T2D patients of Han Chinese ancestry. Among 4,908 Chinese T2D patients who were not taking lipid-lowering medications, single nucleotide polymorphisms (SNPs) in seven genes previously found to be associated with lipid traits in genome-wide association studies conducted in populations of European ancestry (ABCA1, GCKR, BAZ1B, TOMM40, DOCK7, HNF1A, and HNF4A) were genotyped. After adjusting for multiple covariates, SNPs in ABCA1, GCKR, BAZ1B, TOMM40, and HNF1A were identified as significantly associated with triglyceride levels in T2D patients (P < 0.05). The associations between the SNPs in ABCA1 (rs3890182), GCKR (rs780094), and BAZ1B (rs2240466) remained significant even after correction for multiple testing (P = 8.85×10⁻³, 7.88×10⁻⁷, and 2.03×10⁻⁶, respectively). BAZ1B (rs2240466) also was associated with the total cholesterol level (P = 4.75×10⁻²). In addition, SNP rs157580 in TOMM40 was associated with the low-density lipoprotein cholesterol level (P = 6.94×10⁻³). Our findings confirm that lipid-related genetic loci are associated with lipid profiles in Chinese patients with type 2 diabetes.