The effect of metformin on urate metabolism: Findings from observational and Mendelian randomization analyses.

AIM: To evaluate the effect of metformin on urate metabolism. MATERIALS AND METHODS: Using the UK Biobank, we first performed association analyses of metformin use with urate levels, risk of hyperuricaemia and incident gout in patients with diabetes. To explore the causal effect of metformin on urate and gout, we identified genetic variants proxying the glycated haemoglobin (HbA1c)-lowering effect of metformin targets and conducted a two-sample Mendelian randomization (MR) utilizing the urate and gout genetic summary-level data from the CKDGen (n = 288 649) and the FinnGen cohort. We conducted two-step MR to explore the mediation effect of body mass index and systolic blood pressure. We also performed non-linear MR in the UK Biobank (n = 414 055) to show the results across HbA1c levels. RESULTS: In 18 776 patients with type 2 diabetes in UK Biobank, metformin use was associated with decreased urate [ß = -4.3 µmol/L, 95% confidence interval (CI) -7.0, -1.7, p = .001] and reduced hyperuricaemia risk (odds ratio = 0.87, 95% CI 0.79, 0.96, p = .004), but not gout. Genetically proxied averaged HbA1c-lowering effects of metformin targets, equivalent to a 0.62% reduction in HbA1c, was associated with reduced urate (ß = -12.5 µmol/L, 95% CI -21.4, -4.2, p = .004). Body mass index significantly mediated this association (proportion mediated = 33.0%, p = .002). Non-linear MR results suggest a linear trend of the effect of metformin on urate reduction across various HbA1c levels. CONCLUSIONS: The effect of metformin may reduce urate levels but not incident gout in the general population.

Sex-specific causality of MRI-derived body compositions on glycaemic traits: Mendelian randomization and observational study.

AIM: To investigate the sex-specific causality of body compositions in type 2 diabetes and related glycaemic traits using Mendelian randomization (MR). MATERIALS AND METHODS: We leveraged sex-specific summary-level statistics from genome-wide association studies for three adipose deposits adjusted for body mass index and height, including abdominal subcutaneous adipose tissue, visceral adipose tissue (VATadj) and gluteofemoral adipose tissue (GFATadj), measured by MRI (20 038 women; 19 038 men), and fat mass-adjusted appendicular lean mass (ALMadj) (244 730 women; 205 513 men) in the UK Biobank. Sex-specific statistics of type 2 diabetes were from the Diabetes Genetics Replication and Meta-analysis Consortium and those for fasting glucose and insulin were from the Meta-analyses of Glucose and Insulin-related Traits Consortium. Univariable and multivariable MR (MVMR) were performed. We also performed MR analyses of anthropometric traits and genetic association analyses using individual-level data of body composition as validation. RESULTS: Univariable MR analysis showed that, in women, higher GFATadj and ALMadj exerted a causally protective effect on type 2 diabetes (GFATadj: odds ratio [OR] 0.59, 95% confidence interval [CI; 0.50, 0.69]; ALMadj: OR 0.84, 95% CI [0.77, 0.91]) and VATadj to be riskier in glycaemic traits. MVMR showed that GFATadj retained a robust effect on type 2 diabetes (OR 0.57, 95% CI [0.42, 0.77]; P = 2.6 × 10-4 ) in women, while it was nominally significant in men (OR 0.58, 95% CI [0.35, 0.96]; P = 3.3 × 10-2 ), after adjustment for ASATadj and VATadj. MR analyses of anthropometric measures and genetic association analyses of glycaemic traits confirmed the results. CONCLUSIONS: Body composition has a sex-specific effect on type 2 diabetes, and higher GFATadj has an independent protective effect on type 2 diabetes in both sexes.

Interactive Association Between Gut Microbiota and Thyroid Cancer.

CONTEXT: The association between the gut microbiota and thyroid cancer remains controversial. OBJECTIVE: We aimed to systematically investigate the interactive causal relationships between the abundance and metabolism pathways of gut microbiota and thyroid cancer. METHODS: We leveraged genome-wide association studies for the abundance of 211 microbiota taxa from the MiBioGen study (N = 18 340), 205 microbiota metabolism pathways from the Dutch Microbiome Project (N = 7738), and thyroid cancer from the Global Biobank Meta-analysis Initiative (N cases = 6699 and N participants = 1 620 354). We performed a bidirectional Mendelian randomization (MR) to investigate the causality from microbiota taxa and metabolism pathways to thyroid cancer and vice versa. We performed a systematic review of previous observational studies and compared MR results with observational findings. RESULTS: Eight taxa and 12 metabolism pathways had causal effects on thyroid cancer, where RuminococcaceaeUCG004 genus (P = .001), Streptococcaceae family (P = .016), Olsenella genus (P = .029), ketogluconate metabolism pathway (P = .003), pentose phosphate pathway (P = .016), and L-arginine degradation II in the AST pathway (P = .0007) were supported by sensitivity analyses. Conversely, thyroid cancer had causal effects on 3 taxa and 2 metabolism pathways, where the Holdemanella genus (P = .015) was supported by sensitivity analyses. The Proteobacteria phylum, Streptococcaceae family, Ruminococcus2 genus, and Holdemanella genus were significantly associated with thyroid cancer in both the systematic review and MR, whereas the other 121 significant taxa in observational results were not supported by MR. DISCUSSIONS: These findings implicated the potential role of host-microbiota crosstalk in thyroid cancer, while the discrepancy among observational studies calls for further investigations.

Roles of gut microbiota in atrial fibrillation: insights from Mendelian randomization analysis and genetic data from over 430,000 cohort study participants.

BACKGROUND: Gut microbiota imbalances have been suggested as a contributing factor to atrial fibrillation (AF), but the causal relationship is not fully understood. OBJECTIVES: To explore the causal relationships between the gut microbiota and AF using Mendelian randomization (MR) analysis. METHODS: Summary statistics were from genome-wide association studies (GWAS) of 207 gut microbial taxa (5 phyla, 10 classes, 13 orders, 26 families, 48 genera, and 105 species) (the Dutch Microbiome Project) and two large meta-GWASs of AF. The significant results were validated in FinnGen cohort and over 430,000 UK Biobank participants. Mediation MR analyses were conducted for AF risk factors, including type 2 diabetes, coronary artery disease (CAD), body mass index (BMI), blood lipids, blood pressure, and obstructive sleep apnea, to explore the potential mediation effect of these risk factors in between the gut microbiota and AF. RESULTS: Two microbial taxa causally associated with AF: species Eubacterium ramulus (odds ratio [OR] 1.08, 95% confidence interval [CI] 1.04-1.12, P = 0.0001, false discovery rate (FDR) adjusted p-value = 0.023) and genus Holdemania (OR 1.15, 95% CI 1.07-1.25, P = 0.0004, FDR adjusted p-value = 0.042). Genus Holdemania was associated with incident AF risk in the UK Biobank. The proportion of mediation effect of species Eubacterium ramulus via CAD was 8.05% (95% CI 1.73% - 14.95%, P = 0.008), while the proportion of genus Holdemania on AF via BMI was 12.01% (95% CI 5.17% - 19.39%, P = 0.0005). CONCLUSIONS: This study provided genetic evidence to support a potential causal mechanism between gut microbiota and AF and suggested the mediation role of AF risk factors.

Dissecting Causal Relationships Between Gut Microbiota, Blood Metabolites, and Stroke: A Mendelian Randomization Study.

BACKGROUND AND PURPOSE: We investigated the causal relationships between the gut microbiota (GM), stroke, and potential metabolite mediators using Mendelian randomization (MR). METHODS: We leveraged the summary statistics of GM (n=18,340 in the MiBioGen consortium), blood metabolites (n=115,078 in the UK Biobank), and stroke (cases n=60,176 and controls n=1,310,725 in the Global Biobank Meta-Analysis Initiative) from the largest genome-wide association studies to date. We performed bidirectional MR analyses to explore the causal relationships between the GM and stroke, and two mediation analyses, two-step MR and multivariable MR, to discover potential mediating metabolites. RESULTS: Ten taxa were causally associated with stroke, and stroke led to changes in 27 taxa. In the two-step MR, Bifidobacteriales order, Bifidobacteriaceae family, Desulfovibrio genus, apolipoprotein A1 (ApoA1), phospholipids in high-density lipoprotein (HDL_PL), and the ratio of apolipoprotein B to ApoA1 (ApoB/ApoA1) were causally associated with stroke (all P<0.044). The causal associations between Bifidobacteriales order, Bifidobacteriaceae family and stroke were validated using the weighted median method in an independent cohort. The three GM taxa were all positively associated with ApoA1 and HDL_PL, whereas Desulfovibrio genus was negatively associated with ApoB/ApoA1 (all P<0.010). Additionally, the causal associations between the three GM taxa and ApoA1 remained significant after correcting for the false discovery rate (all q-values <0.027). Multivariable MR showed that the associations between Bifidobacteriales order, Bifidobacteriaceae family and stroke were mediated by ApoA1 and HDL_PL, each accounting for 6.5% (P=0.028) and 4.6% (P=0.033); the association between Desulfovibrio genus and stroke was mediated by ApoA1, HDL_PL, and ApoB/ApoA1, with mediated proportions of 7.6% (P=0.019), 4.2% (P=0.035), and 9.1% (P=0.013), respectively. CONCLUSION: The current MR study provides evidence supporting the causal relationships between several specific GM taxa and stroke and potential mediating metabolites.

Whole Blood-based Transcriptional Risk Score for Nonobese Type 2 Diabetes Predicts Dynamic Changes in Glucose Metabolism.

CONTEXT: The performance of peripheral blood transcriptional markers in evaluating risk of type 2 diabetes (T2D) with normal body mass index (BMI) is unknown. OBJECTIVE: We developed a whole blood-based transcriptional risk score (wb-TRS) for nonobese T2D and assessed its contributions on disease risk and dynamic changes in glucose metabolism. METHODS: Using a community-based cohort with blood transcriptome data, we developed the wb-TRS in 1105 participants aged ≥40 years who maintained a normal BMI for up to 10 years, and we validated the wb-TRS in an external dataset. Potential biological significance was explored. RESULTS: The wb-TRS included 144 gene transcripts. Compared to the lowest tertile, wb-TRS in tertile 3 was associated with 8.91-fold (95% CI, 3.53-22.5) higher risk and each 1-unit increment was associated with 2.63-fold (95% CI, 1.87-3.68) higher risk of nonobese T2D. Furthermore, baseline wb-TRS significantly associated with dynamic changes in average, daytime, nighttime, and 24-hour glucose, HbA1c values, and area under the curve of glucose measured by continuous glucose monitoring over 6 months of intervention. The wb-TRS improved the prediction performance for nonobese T2D, combined with fasting glucose, triglycerides, and demographic and anthropometric parameters. Multi-contrast gene set enrichment (Mitch) analysis implicated oxidative phosphorylation, mTORC1 signaling, and cholesterol metabolism involved in nonobese T2D pathogenesis. CONCLUSION: A whole blood-based nonobese T2D-associated transcriptional risk score was validated to predict dynamic changes in glucose metabolism. These findings suggested several biological pathways involved in the pathogenesis of nonobese T2D.

Evaluation of the Effect of Sodium-Glucose Cotransporter 2 Inhibition on Fracture Risk: Evidence From Mendelian Randomization and Genetic Association Study.

This study aims to evaluate the causal effect of sodium-glucose cotransporter 2 (SGLT2) inhibition on bone mineral density (BMD), osteoporosis, and fracture risk using genetics. Two-sample Mendelian randomization (MR) analyses were performed utilizing two sets of genetic variants as instruments (six and two single-nucleotide polymorphisms [SNPs]) associated with SLC5A2 gene expression and glycated hemoglobin A1c levels. Summary statistics of BMD from the Genetic Factors for Osteoporosis consortium (BMD for total body, n = 66,628; femoral neck, n = 32,735; lumbar spine, n = 28,498; forearm, n = 8143) and osteoporosis (6303 cases, 325,717 controls) and 13 types of fracture (≤17,690 cases, ≤328,382 controls) data from the FinnGen study were obtained. One-sample MR and genetic association analyses were conducted in UK Biobank using the individual-level data of heel BMD (n = 256,286) and incident osteoporosis (13,677 cases, 430,262 controls) and fracture (25,806 cases, 407,081 controls). Using six SNPs as the instrument, genetically proxied SGLT2 inhibition showed little evidence of association with BMD of total body, femoral neck, lumbar spine, and forearm (all p ≥ 0.077). Similar results were observed using two SNPs as instruments. Little evidence was found for the SGLT2 inhibition effect on osteoporosis (all p ≥ 0.112) or any 11 major types of fracture (all p ≥ 0.094), except for a nominal significance for fracture of lower leg (p = 0.049) and shoulder and upper arm (p = 0.029). One-sample MR and genetic association analysis showed that both the weighted genetic risk scores constructed from the six and two SNPs were not causally associated with heel BMD, osteoporosis, and fracture (all p ≥ 0.387). Therefore, this study does not support an effect of genetically proxied SGLT2 inhibition on fracture risk. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Causal relationships between the gut microbiome, blood lipids, and heart failure: a Mendelian randomization analysis.

AIMS: Studies have linked gut microbiome and heart failure (HF). However, their causal relationships and potential mediating factors have not been well defined. To investigate the causal relationships between the gut microbiome and HF and the mediating effect of potential blood lipids by using genetics. METHODS AND RESULTS: We performed a bidirectional and mediation Mendelian randomization (MR) study using summary statistics from the genome-wide association studies of gut microbial taxa (Dutch Microbiome Project, n = 7738), blood lipids (UK Biobank, n = 115 078), and a meta-analysis of HF (115 150 cases and 1550 331 controls). We applied the inverse-variance weighted estimation method as the primary method, with several other estimators as complementary methods. The multivariable MR approach based on Bayesian model averaging (MR-BMA) was used to prioritize the most likely causal lipids. Six microbial taxa are suggestively associated with HF causally. The most significant taxon was the species Bacteroides dorei [odds ratio = 1.059, 95% confidence interval (CI) = 1.022-1.097, P-value = 0.0017]. The MR-BMA analysis showed that apolipoprotein B (ApoB) was the most likely causal lipid for HF (the marginal inclusion probability = 0.717, P-value = 0.005). The mediation MR analysis showed that ApoB mediated the causal effects of species B. dorei on HF (proportion mediated = 10.1%, 95% CI = 0.2-21.6%, P-value = 0.031). CONCLUSION: The study suggested a causal relationship between specific gut microbial taxa and HF and that ApoB might mediate this relationship as the primary lipid determinant of HF.

We conducted a Mendelian randomization analysis to examine the causal relationships between the gut microbiome and heart failure and the mediating role of blood lipids. • Six gut microbial taxa were identified as having potentially causal effects on heart failure, with Bacteroides dorei being the most significant one. • Apolipoprotein B was found to be the primary lipid determinant of heart failure among five common lipids and mediated 10.1% of the causal effect of B. dorei on heart failure.

Dissecting the causal effect between gut microbiota, DHA, and urate metabolism: A large-scale bidirectional Mendelian randomization.

Objectives: Our aim was to investigate the interactive causal effects between gut microbiota and host urate metabolism and explore the underlying mechanism using genetic methods. Methods: We extracted summary statistics from the abundance of 211 microbiota taxa from the MiBioGen (N =18,340), 205 microbiota metabolism pathways from the Dutch Microbiome Project (N =7738), gout from the Global Biobank Meta-analysis Initiative (N =1,448,128), urate from CKDGen (N =288,649), and replication datasets from the Global Urate Genetics Consortium (N gout =69,374; N urate =110,347). We used linkage disequilibrium score regression and bidirectional Mendelian randomization (MR) to detect genetic causality between microbiota and gout/urate. Mediation MR and colocalization were performed to investigate potential mediators in the association between microbiota and urate metabolism. Results: Two taxa had a common causal effect on both gout and urate, whereas the Victivallaceae family was replicable. Six taxa were commonly affected by both gout and urate, whereas the Ruminococcus gnavus group genus was replicable. Genetic correlation supported significant results in MR. Two microbiota metabolic pathways were commonly affected by gout and urate. Mediation analysis indicated that the Bifidobacteriales order and Bifidobacteriaceae family had protective effects on urate mediated by increasing docosahexaenoic acid. These two bacteria shared a common causal variant rs182549 with both docosahexaenoic acid and urate, which was located within MCM6/LCT locus. Conclusions: Gut microbiota and host urate metabolism had a bidirectional causal association, implicating the critical role of host-microbiota crosstalk in hyperuricemic patients. Changes in gut microbiota can not only ameliorate host urate metabolism but also become a foreboding indicator of urate metabolic diseases.

Incorporation of tissue factor-integrated liposome and silica nanoparticle into collagen hydrogel as a promising hemostatic system.

Bleeding complications are associated with substantial tissue morbidities and mortalities. Biomimetic composite materials that possess the ability to sufficiently stimulate and augment different physiological mechanisms of hemostasis are highly desirable to reduce bleeding-related casualties, which, however, are still largely under-explored. This study aims to develop a composite hemostatic system by combining collagen hydrogel with tissue factor (TF)-integrated liposome and silica nanoparticle, which could integrate the platelet plug-promoting capacity of collagen with the abilities of the latter two components to activate the extrinsic and intrinsic pathways of coagulation respectively. Several hydrogel compositions were synthesized and characterized. We show that lipidated TF and silica were evenly distributed in the collagen-based hydrogels, while exhibiting tunable release kinetics in simulated body fluid. Time-to-coagulation test revealed that each component in the TF-liposome/silica/collagen ternary hydrogels was hemostasis-active, and their combination showed enhanced and potent procoagulant performance, without detectable cytotoxicity against NIH/3T3 model cells. These results suggest that collagen hydrogels with embedded TF-liposome and silica nanoparticle may serve as a platform for an effective hemostatic composite that incorporates all the basic known pathways of coagulation.

Disease-specific data processing: An intelligent digital platform for diabetes based on model prediction and data analysis utilizing big data technology.

Background: Artificial intelligence technology has become a mainstream trend in the development of medical informatization. Because of the complex structure and a large amount of medical data generated in the current medical informatization process, big data technology to assist doctors in scientific research and analysis and obtain high-value information has become indispensable for medical and scientific research. Methods: This study aims to discuss the architecture of diabetes intelligent digital platform by analyzing existing data mining methods and platform building experience in the medical field, using a large data platform building technology utilizing the Hadoop system, model prediction, and data processing analysis methods based on the principles of statistics and machine learning. We propose three major building mechanisms, namely the medical data integration and governance mechanism (DCM), data sharing and privacy protection mechanism (DPM), and medical application and medical research mechanism (MCM), to break down the barriers between traditional medical research and digital medical research. Additionally, we built an efficient and convenient intelligent diabetes model prediction and data analysis platform for clinical research. Results: Research results from this platform are currently applied to medical research at Shanghai T Hospital. In terms of performance, the platform runs smoothly and is capable of handling massive amounts of medical data in real-time. In terms of functions, data acquisition, cleaning, and mining are all integrated into the system. Through a simple and intuitive interface operation, medical and scientific research data can be processed and analyzed conveniently and quickly. Conclusions: The platform can serve as an auxiliary tool for medical personnel and promote the development of medical informatization and scientific research. Also, the platform may provide the opportunity to deliver evidence-based digital therapeutics and support digital healthcare services for future medicine.

Sexual Dimorphism in the Association of Serum Retinol-Binding Protein-4 With Long-Term Dynamic Metabolic Profiles in Non-Diabetes.

Objectives: We aimed to investigate the association of circulating retinol-binding protein-4 (RBP4) levels with long-term cardiometabolic risk profiles and whether sex disparity mattered. Methods: We included 784 non-diabetic participants aged 40 years and above from a well-defined community-based cohort at baseline in 2005 and they were invited to attend the on-site follow-up examination for two consecutive times with 3-year intervals in 2008 and 2011, respectively. Serum RBP4 was measured at baseline, and the anthropometry and biochemical measurements were performed at each visit. Generalized estimating equation models were used to assess the association of serum RBP4 levels with the dynamic changes in adiposity and glucolipid profile. Results: Based on all the baseline and the 3- and 6-year follow-up data, baseline serum RBP4 levels (each 1-unit of log10RBP4) were significantly associated with waist circumference [ß=3.12, 95% confidence interval (CI) (0.77, 5.47), P=0.01], fasting, and 2-h post-loading glucose [ß=0.26 (0.05, 0.47), P=0.02, and 1.70 (1.29, 2.12), P< 0.0001], serum triglycerides [ß=0.75, 95% CI (0.54, 0.96), P< 0.0001], total cholesterol [ß=0.47, 95% CI [0.23 0.70], P<0.0001), and marginally with body mass index (ß=0.97, 95% CI (0.02, 1.93), P=0.046], in total participants, after adjusting potential confounders. The association of RBP4 with 2-h post-loading glucose was stronger in women than that in men [ß=1.99, 95% CI (1.49, 2.50) vs. 0.61 (-0.14, 1.36), P for interaction=0.001]. The analysis of change in Z-score of cardiometabolic profiles corresponding to each 1-unit increment in log10RBP4 showed consistent results. Conclusions: Higher RBP4 levels are associated with longitudinal increase in adiposity and deteriorated glucolipid profile defined by repeated measurements. The associations differ in sex regarding to the 2-h post-loading glucose.

Changes in adiposity modulate the APOA5 genetic effect on blood lipids: A longitudinal cohort study.

BACKGROUND AND AIMS: The Apolipoprotein A5 (APOA5) rs662799 was significantly associated with blood lipid level at genome-wide significance level. Whether dynamic changes of adiposity influence the effect of lipid loci on long-term blood lipid profile remains unclear. We assessed interactions of 5-year body mass index (BMI) change and rs662799 genotypes with risk of incident dyslipidemia and longitudinal changes in serum lipids in a prospective cohort. METHODS: We included 4329 non-dyslipidemia participants aged ≥ 40 years at baseline from a well-defined community-based cohort and followed up for an average of 5 years. BMI and blood lipids were measured at baseline and follow-up. RESULTS: The association of each rs662799 A-allele with risk of incident dyslipidemia was stronger along with the increase in BMI change level, with the odds ratios (OR) increasing from 1.03 in the lowest tertile of BMI change (< 0.02 kg/m2) to 1.17 in the second (0.02-1.29), and 1.46 in the highest tertile (> 1.29) (pfor interaction< 0.001). Associations of each 1-unit of BMI (kg/m2) increase with incident dyslipidemia were more prominent in the AA carriers (OR = 1.50, 95%CI [1.26-1.80], p < 0.001), while much weaker in the GA (OR = 1.10) or GG carriers (OR = 1.09) (pfor interaction = 0.002). Similar results were found for the risk of incident higher triglycerides (TG) and lower high-density lipoprotein cholesterol (HDL-c), or the longitudinal changes in log10-TG (all pfor interaction ≤ 0.02). CONCLUSIONS: BMI changes significantly modulate rs662799 genetic contribution to dyslipidemia and long-term lipid profile, which provide new evidence for personalized clinical management of lipids according to individual genetic background.

New clusters of serum electrolytes aid in stratification of diabetes and metabolic risk.

BACKGROUND: Serum electrolytes were found to associate with type 2 diabetes. Our study aimed to stratify nondiabetes by clusters based on multiple serum electrolytes and evaluate their associations with risk of developing diabetes and longitudinal changes in glucose and lipid metabolic traits. METHODS: We performed a data-driven cluster analysis in 4937 nondiabetes individuals aged ≥40 years at baseline from a cohort follow-up for an average of 4.4 years. Cluster analysis was based on seven commonly measured serum electrolytes (iron, chlorine, magnesium, sodium, potassium, calcium, and phosphorus) by using the k-means method. RESULTS: A total of 4937 nondiabetes individuals were classified into three distinct clusters, with 1635 (33.1%) assigned to Cluster A, 1490 (30.2%) to Cluster B, and 1812 (36.7%) to Cluster C. Individuals in Cluster A had higher serum chlorine, were older, and more were women. Individuals in Cluster B had higher serum iron and body mass index (BMI). Individuals in Cluster C had higher serum phosphorus, were younger, and had lower BMI. Cluster B had 1.41-fold higher risk of developing diabetes and Cluster C's risk was 1.33-fold higher compared with Cluster A. Over an average follow-up of 4.4 years, Cluster A showed a moderate and stable BMI, Cluster B showed an accelerated deterioration in glucose metabolism, and Cluster C showed the most sharply increased serum low-density lipoprotein cholesterol level. CONCLUSIONS: Clusters based on seven common serum electrolytes differed in diabetes risk and progression of glucose and lipid metabolic traits. Serum electrolytes clusters could provide a powerful tool to differentiate individuals into different risk stratification for developing type 2 diabetes.

Associations of body shapes with insulin resistance and cardiometabolic risk in middle-aged and elderly Chinese.

BACKGROUND: We aimed to define refined body shapes by using multiple anthropometric traits that represent fat distribution, and evaluate their associations with risk of insulin resistance (IR) and cardiometabolic disorders in a Chinese population. METHODS: We performed a cross-sectional analysis in 6570 community-based participants aged ≥ 40 years. Four body circumferences (neck, waist, hip, and thigh) and their ratios were put simultaneously into an open-source Waikato Environment for Knowledge Analysis platform to select the worthiest indicators in determining IR. The ratio of the top 3 fat distribution indicators was used to define the refined body shapes. RESULTS: We defined 8 distinct body shapes based on sex-specific combinations of waist-to-hip ratio (WHR), waist-to-thigh ratio (WTR), and waist-to-neck ratio (WNR), which differed in participants' distribution and risk of IR and related cardiometabolic disorders. In women, as compared to the low WHR-low WTR-low WNR shape, all body shapes were significantly associated with IR and related cardiometabolic disorders; while in men, the low WHR-high WTR-high WNR shape and the higher WHR related shapes were significantly associated with IR and related cardiometabolic disorders. Stratified by WHR, the results were consistent in women; however, no significant associations were detected in men. CONCLUSIONS: We defined 8 distinct body shapes by taking WHR, WTR, and WNR, simultaneously into account, which differed in association with the risk of IR and related cardiometabolic disorders in women. This study suggests that body shapes defined by multiple anthropometric traits could provide a useful, convenient, and easily available method for identifying cardiometabolic risk.

Fat mass to fat-free mass ratio and the risk of non-alcoholic fatty liver disease and fibrosis in non-obese and obese individuals.

CONTEXT: Body composition may explain partially why non-obese individuals still at the risk of developing non-alcoholic fatty liver disease (NAFLD). The ratio of fat mass to fat-free mass (FM/FFM) has been proposed to assess the combined effect of different body compositions. OBJECTIVE: We aimed to investigate the associations of FM/FFM ratio with the risk of developing NAFLD and fibrosis and to identify the potential mediators according to obesity status. METHODS: This cohort study comprised 3419 adults age ≥ 40 years and free of NAFLD at baseline. Body composition was measured by bioelectrical impedance analysis. NAFLD was ascertained by ultrasonography and fibrosis was assessed by non-invasive score systems. RESULTS: For each 1 standard deviation increment in FM/FFM ratio, the odds ratio for the risk of NAFLD was 1.55 (95% confidence interval [CI] 1.23-1.95) in non-obese men, 1.33 (95% CI 1.08-1.65) in obese men, 1.42 (95% CI 1.44-1.67) in non-obese women, and 1.29 (95% CI 1.12-1.50) in obese women. Similar associations were also found between FM/FFM ratio and NAFLD with fibrosis. Mediation analysis showed that insulin resistance, triglycerides, high-density lipoprotein cholesterol, white blood cells, and total cholesterol mediated the association of FM/FFM ratio with NAFLD risk in specific sex and obesity subgroups. CONCLUSIONS: The FM/FFM ratio significantly associated with the NAFLD and fibrosis risk in both non-obese and obese individuals. Different factors may mediate the association between body composition and NAFLD risk according to different obesity status.

Fruit intake, genetic risk and type 2 diabetes: a population-based gene-diet interaction analysis.

PURPOSE: Whether the association between fruit and type 2 diabetes (T2D) is modified by the genetic predisposition of T2D was yet elucidated. The current study is meant to examine the gene-dietary fruit intake interactions in the risk of T2D and related glycemic traits. METHODS: We performed a cross-sectional study in 11,657 participants aged ≥ 40 years from a community-based population in Shanghai, China. Fruit intake information was collected by a validated food frequency questionnaire by asking the frequency of consumption of typical food items over the previous 12 months. T2D-genetic risk score (GRS) was constructed by 34 well established T2D common variants in East Asians. The risk of T2D, fasting, 2 h-postprandial plasma glucose, and glycated hemoglobin A1c associated with T2D-GRS and each individual single nucleotide polymorphisms (SNPs) were tested. RESULTS: The risk of T2D associated with each 1-point of T2D-GRS was gradually decreased from the lower fruit intake level (< 1 times/week) [the odds ratio (OR) and 95% confidence interval (CI) was 1.10 (1.07-1.13)], to higher levels (1-3 and > 3 times/week) [the corresponding ORs and 95% CIs were 1.08 (1.05-1.10) and 1.07 (1.05-1.08); P for interaction = 0.04]. Analyses for associations with fasting, 2 h-postprandial plasma glucose and glycated hemoglobin A1c demonstrated consistent tendencies (all P for interaction ≤ 0.03). The inverse associations of fruit intake with risk of T2D and glucose traits were more prominent in the higher T2D-GRS tertile. CONCLUSIONS: Fruit intakes interact with the genetic predisposition of T2D on the risk of diabetes and related glucose metabolic traits. Fruit intake alleviates the association between genetic predisposition of T2D and the risk of diabetes; the association of fruit intake with a lower risk of diabetes was more prominent in population with a stronger genetic predisposition of T2D.

Serum lipoprotein (a) associates with a higher risk of reduced renal function: a prospective investigation.

Lipoprotein (a) [Lp(a)] is a well-known risk factor for cardiovascular disease, but analysis on Lp(a) and renal dysfunction is scarce. We aimed to investigate prospectively the association of serum Lp(a) with the risk of reduced renal function, and further investigated whether diabetic or hypertensive status modified such association. Six thousand two hundred and fifty-seven Chinese adults aged ≤40 years and free of reduced renal function at baseline were included in the study. Reduced renal function was defined as estimated glomerular filtration rate <60 ml/min/1.73 m2 During a mean follow-up of 4.4 years, 158 participants developed reduced renal function. Each one-unit increase in log10-Lp(a) (milligrams per deciliter) was associated with a 1.99-fold (95% CI 1.15-3.43) increased risk of incident reduced renal function; the multivariable-adjusted odds ratio (OR) for the highest tertile of Lp(a) was 1.61 (95% CI 1.03-2.52) compared with the lowest tertile (P for trend = 0.03). The stratified analysis showed the association of serum Lp(a) and incident reduced renal function was more prominent in participants with prevalent diabetes [OR 4.04, 95% CI (1.42-11.54)] or hypertension [OR 2.18, 95% CI (1.22-3.89)]. A stronger association was observed in the group with diabetes and high Lp(a) (>25 mg/dl), indicating a combined effect of diabetes and high Lp(a) on the reduced renal function risk. An elevated Lp(a) level was independently associated with risk of incident reduced renal function, especially in diabetic or hypertensive patients.

Association of QTc Interval with Risk of Cardiovascular Diseases and Related Vascular Traits: A Prospective and Longitudinal Analysis.

Background: Prolonged heart rate corrected QT (QTc) interval was reported to be associated with cardiovascular diseases (CVDs). Objective: There exists little data on the association between QTc interval and cardiovascular risk in Asian populations. We prospectively investigated the association of QTc interval with CVDs and vascular traits in a large cohort of Chinese adults. Methods: A total of 7,605 participants aged 40 years or older from a well-defined community without CVDs at baseline were included and followed up for an average of 4.5 years. Association of baseline QTc interval with incident CVDs was evaluated using Cox regression analysis. Associations of QTc interval with brachial-ankle pulse wave velocity (baPWV), carotid intima-media thickness (CIMT), and risk of microalbuminuria and peripheral arterial diseases (PAD) were secondarily examined. Results: Prolonged QTc interval (≥460 ms in women and ≥450 ms in men) was associated with 51% higher risk of total major CVDs (hazard ratio [HR] = 1.51, 95% confidence interval [CI] [1.20, 1.90]), particularly, 48% increased risk of stroke (95% CI [1.16, 1.88]). Prolonged QTc interval was positively associated with baPWV (ß = 38.10 cm/s, standard error [SE] = 8.04, P < 0.0001) and CIMT (ß = 0.01 mm, SE = 0.01, P = 0.04). Prolonged QTc interval was associated with increased risk of incident microalbuminuria (odds ratio [OR] = 1.65, 95% CI [1.21, 2.24]) and PAD (2.49, 95% CI [1.35, 4.59]). Conclusions: Prolonged QTc interval is positively and significantly associated with increased risk of CVDs and related vascular traits in Chinese population.

Serum total bile acids associate with risk of incident type 2 diabetes and longitudinal changes in glucose-related metabolic traits.

BACKGROUND: Bile acids have been found to be related to changes in gut microbiota and multiple metabolic disorders, including type 2 diabetes (T2D). We aimed to prospectively investigate associations of serum total bile acids (TBAs) with risk of incident T2D and longitudinal changes in glycemic traits. METHODS: A community-based study was conducted at baseline in 2010, including 4968 nondiabetic participants aged ≥40 years followed up for an average of 4.3 years. Incident T2D was defined by using the 1999 WHO criteria based on 75-g oral glucose tolerance tests. Multivariate Cox proportional hazards regression was used to examine the association of serum TBAs with incident T2D. Fasting plasma glucose (FPG), 2-hour postload plasma glucose (2-h PPG), and fasting serum insulin (FSI) were measured at baseline and follow-up. RESULTS: During 21 653.7 person-years of follow-up, 605 cases of incident diabetes were identified (incidence rate 2.8%). Comparing to quartile 1 of serum TBAs, quartile 2, 3, and 4 were significantly associated with a 14.2%, 15.0%, and 31.4% higher risk of incident T2D (P = .029). Each one unit of log-TBAs was associated with an increase of 0.034 mmol/L in FPG, 0.111 mmol/L in 2-h PPG, 0.023 in log-FSI, and 0.012 in log-HOMA-IR (homeostasis model assessment of insulin resistance) (all P ≤ .024). The association was attenuated after further adjustment for HOMA-IR. Mediation analysis showed that insulin resistance indicated by HOMA-IR might mediate 28.5% of indirect effect on the association of TBAs with T2D (P = .0004). CONCLUSIONS: Baseline serum TBAs were significantly associated with incident T2D and longitudinal changes in glycemic traits. Insulin resistance might partially mediate the association of TBAs and T2D.