Insulin sensitivity estimates and their longitudinal association with coronary artery disease in type 1 diabetes. Does it matter?

BACKGROUND: Insulin resistance and chronic kidney disease are both associated with increased coronary artery disease risk. Many formulae estimating glucose disposal rate in type 1 diabetes infer insulin sensitivity from clinical data. We compare associations and performance relative to traditional risk factors and kidney disease severity between three formulae estimating the glucose disposal rate and coronary artery disease in people with type 1 diabetes. METHODS: The baseline glucose disposal rate was estimated by three (Williams, Duca, and Januszewski) formulae in FinnDiane Study participants and related to subsequent incidence of coronary artery disease, by baseline kidney status. RESULTS: In 3517 adults with type 1 diabetes, during median (IQR) 19.3 (14.6, 21.4) years, 539 (15.3%) experienced a coronary artery disease event, with higher rates with worsening baseline kidney status. Correlations between the three formulae estimating the glucose disposal rate were weak, but the lowest quartile of each formula was associated with higher incidence of coronary artery disease. Importantly, only the glucose disposal rate estimation by Williams showed a linear association with coronary artery disease risk in all analyses. Of the three formulae, Williams was the strongest predictor of coronary artery disease. Only age and diabetes duration were stronger predictors. The strength of associations between estimated glucose disposal rate and CAD incidence varied by formula and kidney status. CONCLUSIONS: In type 1 diabetes, estimated glucose disposal rates are associated with subsequent coronary artery disease, modulated by kidney disease severity. Future research is merited regarding the clinical usefulness of estimating the glucose disposal rate as a coronary artery disease risk factor and potential therapeutic target.

Medication profiling in women with type 1 diabetes highlights the importance of adequate, guideline-based treatment in low-risk groups.

Effective treatment may prevent kidney complications, but women might be underprescribed. Novel, data-driven insights into prescriptions and their relationship with kidney health in women with type 1 diabetes may help to optimize treatment. We identified six medication profiles in 1164 women from the FinnDiane Study with normal albumin excretion rate based on clusters of their baseline prescription data using a self-organizing map. Future rapid kidney function decline was defined as an annual estimated glomerular filtration rate (eGFR) loss > 3 ml/min/1.73 m2 after baseline. Two profiles were associated with future decline: Profile ARB with the highest proportion of angiotensin receptor blockers (odds ratio [OR] 2.75, P = 0.02) and highly medicated women in profile HighMed (OR 2.55, P = 0.03). Compared with profile LowMed (low purchases of all), profile HighMed had worse clinical characteristics, whereas in profile ARB only systolic blood pressure was elevated. Importantly, the younger women in profile ARB with fewer kidney protective treatments developed a rapid decline despite otherwise similar baseline characteristics to profile ACE & Lipids (the highest proportions of ACE inhibitors and lipid-modifying agents) without a future rapid decline. In conclusion, medication profiles identified different future eGFR trajectories in women with type 1 diabetes revealing potential treatment gaps for younger women.

L-type calcium channel blocker increases VEGF concentrations in retinal cells and human serum.

OBJECTIVE: Vascular endothelial growth factor (VEGF) plays a key role in diabetic retinopathy (DR). Previously, we have reported an association between mutations in a gene coding for the L-type calcium channel subunit, VEGF and DR. L-type calcium channel blockers (LTCCBs) have been widely used as antihypertensive medication (AHM), but their association with VEGF and DR is still unclear. Therefore, we explored the effect of LTCCBs compared to other AHMs on VEGF concentrations in retinal cells and human serum. Furthermore, we evaluated the association between the use of LTCCBs and the risk of severe diabetic eye disease (SDED). RESEARCH DESIGN AND METHODS: Müller cells (MIO-M1) were cultured as per recommended protocol and treated with LTCCBs and other AHMs. VEGF secreted from cells were collected at 24 hours intervals. In an interventional study, 39 individuals received LTCCBs or other AHM for four weeks with a four-week wash-out placebo period between treatments. VEGF was measured during the medication and placebo periods. Finally, we evaluated the risk of SDED associated with LTCCB usage in 192 individuals from the FinnDiane Study in an observational setting. RESULTS: In the cell cultures, the medium VEGF concentration increased time-dependently after amlodipine (P<0.01) treatment, but not after losartan (P>0.01), or lisinopril (P>0.01). Amlodipine, but no other AHM, increased the serum VEGF concentration (P<0.05) during the interventional clinical study. The usage of LTCCB was not associated with the risk of SDED in the observational study. CONCLUSIONS: LTCCB increases VEGF concentrations in retinal cells and human serum. However, the usage of LTCCBs does not appear to be associated with SDED in adults with type 1 diabetes.

Telomeres in clinical diabetes research - Moving towards precision medicine in diabetes care?

The early prediction of health outcomes for people with diabetes mellitus is desirable, as are adjunct therapies to reduce the related chronic complications and risk of premature death. The length of telomeres, protective caps on chromosome ends, is influenced by genetic and acquired factors, and shorter telomeres have been associated with and predictive of adverse cardiometabolic outcomes. Many studies have shown associations between telomere length in white blood cells (WBC) and diabetes per se and its chronic complications, and some studies show that telomeres do not always progressively shorten in people with diabetes. With the pandemic of diabetes and taking into consideration the calculations of residual risk using existent risk equations, additional tests to stratify subject risk are desirable. In this evolving era of precision medicine for people with diabetes, this 'global biomarker' of WBC telomere length may be useful to help predict health outcomes, to monitor health status, and may be a therapeutic target. We comment on the field of telomere investigations in diabetes, including recommending areas for further clinical research.

Telomeres do not always shorten over time in individuals with type 1 diabetes.

AIMS: We aimed to determine how white blood cell (WBC) telomeres and telomere length change over time are associated with health status in type 1 diabetes. METHODS: Relative telomere length (rTL) was measured in WBC DNA from two time-points (median 6.8 years apart) in 618 individuals from the Finnish Diabetic Nephropathy Study by quantitative PCR, with interassay CV ≤ 4%. RESULTS: Baseline rTL correlated inversely with age and was shorter in men. Individuals in the shortest vs. longest rTL tertile had adverse cardiometabolic profiles, worse renal function, and were prescribed more antihypertensive and lipid-lowering drugs. While overall rTL tended to decrease during the median 6.8-years of follow-up, telomeres shortened in 55.3% of subjects, lengthened in 40.0%, and did not change in 4.7%. Baseline rTL correlated inversely with rTL change. Telomere lengthening was associated with higher HDL-Cholesterol (HDL-C), HDL-C/ApoA1, and with antihypertensive drug and (inversely) with lipid-lowering drug commencement during follow-up. Correlates of rTL percentage change per-annum (adjusted model) were baseline BMI, eGFR, previous retinal laser treatment, HDL-C, and HDL-C/ApoA1. CONCLUSIONS: Telomere length measurements may facilitate the treatment and monitoring of the health status of individuals with type 1 diabetes.

Genetic Risk Score Enhances Coronary Artery Disease Risk Prediction in Individuals With Type 1 Diabetes.

OBJECTIVE: Individuals with type 1 diabetes are at a high lifetime risk of coronary artery disease (CAD), calling for early interventions. This study explores the use of a genetic risk score (GRS) for CAD risk prediction, compares it to established clinical markers, and investigates its performance according to the age and pharmacological treatment. RESEARCH DESIGN AND METHODS: This study in 3,295 individuals with type 1 diabetes from the Finnish Diabetic Nephropathy Study (467 incident CAD, 14.8 years follow-up) used three risk scores: a GRS, a validated clinical score, and their combined score. Hazard ratios (HR) were calculated with Cox regression, and model performances were compared with the Harrell C-index (C-index). RESULTS: A HR of 6.7 for CAD was observed between the highest and the lowest 5th percentile of the GRS (P = 1.8 × 10-6). The performance of GRS (C-index = 0.562) was similar to HbA1c (C-index = 0.563, P = 0.96 for difference), HDL (C-index = 0.571, P = 0.6), and total cholesterol (C-index = 0.594, P = 0.1). The GRS was not correlated with the clinical score (r = -0.013, P = 0.5). The combined score outperformed the clinical score (C-index = 0.813 vs. C-index = 0.820, P = 0.003). The GRS performed better in individuals below the median age (38.6 years) compared with those above (C-index = 0.637 vs. C-index = 0.546). CONCLUSIONS: A GRS identified individuals at high risk of CAD and worked better in younger individuals. GRS was also an independent risk factor for CAD, with a predictive power comparable to that of HbA1c and HDL and total cholesterol, and when incorporated into a clinical model, modestly improved the predictions. The GRS promises early risk stratification in clinical practice by enhancing the prediction of CAD.

Urinary metabolite profiling and risk of progression of diabetic nephropathy in 2670 individuals with type 1 diabetes.

AIMS/HYPOTHESIS: This prospective, observational study examines associations between 51 urinary metabolites and risk of progression of diabetic nephropathy in individuals with type 1 diabetes by employing an automated NMR metabolomics technique suitable for large-scale urine sample collections. METHODS: We collected 24-h urine samples for 2670 individuals with type 1 diabetes from the Finnish Diabetic Nephropathy study and measured metabolite concentrations by NMR. Individuals were followed up for 9.0 ± 5.0 years until their first sign of progression of diabetic nephropathy, end-stage kidney disease or study end. Cox regressions were performed on the entire study population (overall progression), on 1999 individuals with normoalbuminuria and 347 individuals with macroalbuminuria at baseline. RESULTS: Seven urinary metabolites were associated with overall progression after adjustment for baseline albuminuria and chronic kidney disease stage (p < 8 × 10-4): leucine (HR 1.47 [95% CI 1.30, 1.66] per 1-SD creatinine-scaled metabolite concentration), valine (1.38 [1.22, 1.56]), isoleucine (1.33 [1.18, 1.50]), pseudouridine (1.25 [1.11, 1.42]), threonine (1.27 [1.11, 1.46]) and citrate (0.84 [0.75, 0.93]). 2-Hydroxyisobutyrate was associated with overall progression (1.30 [1.16, 1.45]) and also progression from normoalbuminuria (1.56 [1.25, 1.95]). Six amino acids and pyroglutamate were associated with progression from macroalbuminuria. CONCLUSIONS/INTERPRETATION: Branched-chain amino acids and other urinary metabolites were associated with the progression of diabetic nephropathy on top of baseline albuminuria and chronic kidney disease. We found differences in associations for overall progression and progression from normo- and macroalbuminuria. These novel discoveries illustrate the utility of analysing urinary metabolites in entire population cohorts.

The Relationship Between Body Fat Distribution and Nonalcoholic Fatty Liver in Adults With Type 1 Diabetes.

OBJECTIVE: Obesity, which is associated with nonalcoholic fatty liver (NAFL), has increased among people with type 1 diabetes. Therefore, we explored the associations between body fat distribution and NAFL in this population. RESEARCH DESIGN AND METHODS: This study included 121 adults with type 1 diabetes from the Finnish Diabetic Nephropathy (FinnDiane) Study for whom NAFL was determined by magnetic resonance imaging. Body composition was assessed by dual-energy X-ray absorptiometry. Genetic data concerning PNPLA3 rs738409 and TM6SF2 rs58542926 were available as a directly genotyped polymorphism. Associations between body fat distribution, waist-to-height ratio (WHtR), BMI, and NAFL were explored using logistic regression. A receiver operating characteristic (ROC) curve was used to determine the WHtR and BMI thresholds with the highest sensitivity and specificity to detect NAFL. RESULTS: Median age was 38.5 (33-43.7) years, duration of diabetes was 21.2 (17.9-28.4) years, 52.1% were women, and the prevalence of NAFL was 11.6%. After adjusting for sex, age, duration of diabetes, and PNPLA3 rs738409, the volume (P = 0.03) and percentage (P = 0.02) of visceral adipose tissue were associated with NAFL, whereas gynoid, appendicular, and total adipose tissues were not. The area under the curve between WHtR and NAFL was larger than BMI and NAFL (P = 0.04). The WHtR cutoff of 0.5 showed the highest sensitivity (86%) and specificity (55%), whereas the BMI of 26.6 kg/m2 showed 79% sensitivity and 57% specificity. CONCLUSIONS: Visceral adipose tissue is associated with NAFL in adults with type 1 diabetes, and WHtR may be considered when screening for NAFL in this population.

Waist-height ratio and waist are the best estimators of visceral fat in type 1 diabetes.

Visceral fat is associated with cardiovascular and kidney disease. However, the relationship between body composition and anthropometric measures in type 1 diabetes is unknown. Using z-statistics, we ranked the ability of body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), waist-height ratio (WHtR) and a body shape index (ABSI) to capture measures of body composition from 603 Dual-energy-X-Ray-Absorptiometry scans of adults with type 1 diabetes. Albuminuria was defined as urinary albumin excretion rate of at least 30 mg/24 h. Women with albuminuria had higher visceral fat mass % (VFM%) (0.9 vs. 0.5%, p = 0.0017) and lower appendicular lean mass % (AppLM%) (25.4 vs 26.4%, p = 0.03) than those without. Men with albuminuria had higher VFM% (1.5 vs. 1.0%, p = 0.0013) and lower AppLM% (30.0 vs 32.3, p < 0.0001) than those without. In men, WHtR estimated VFM% best (z-statistics = 21.1), followed by WC (z = 19.6), BMI (z = 15.1), WHR (z = 14.6) and ABSI (z = 10.1). In women, the ranking was WC (z = 28.9), WHtR (z = 27.3), BMI (z = 20.5), WHR (z = 12.7) and ABSI (z = 10.5). Overall, the ranking was independent of albuminuria. Adults with type 1 diabetes and albuminuria have greater VFM% and lower AppLM% than those without. WHtR and WC best estimate the VFM% in this population, independently of albuminuria and sex.

Resistant Hypertension and Risk of Adverse Events in Individuals With Type 1 Diabetes: A Nationwide Prospective Study.

OBJECTIVE: To estimate the risk of diabetic nephropathy (DN) progression, incident coronary heart disease (CHD) and stroke, and all-cause mortality associated with resistant hypertension (RH) in individuals with type 1 diabetes stratified by stages of DN, renal function, and sex. RESEARCH DESIGN AND METHODS: This prospective study included a nationally representative cohort of individuals with type 1 diabetes from the Finnish Diabetic Nephropathy Study who had purchases of antihypertensive drugs at (±6 months) baseline visit (1995-2008). Individuals (N = 1,103) were divided into three groups: 1) RH, 2) uncontrolled blood pressure (BP) but no RH, and 3) controlled BP. DN progression, cardiovascular events, and deaths were identified from the individuals' health care records and national registries until 31 December 2015. RESULTS: At baseline, 18.7% of the participants had RH, while 23.4% had controlled BP. After full adjustments for clinical confounders, RH was associated with increased risk of DN progression (hazard ratio 1.95 [95% CI 1.37, 2.79], P = 0.0002), while no differences were observed in those with no RH (1.05 [0.76, 1.44], P = 0.8) compared with those who had controlled BP. The risk of incident CHD, incident stroke, and all-cause mortality was higher in individuals with RH compared with those who had controlled BP but not beyond albuminuria and reduced kidney function. Notably, in those with normo- and microalbuminuria, the risk of stroke remained higher in the RH compared with the controlled BP group (3.49 [81.20, 10.15], P = 0.02). CONCLUSIONS: Our findings highlight the importance of identifying and providing diagnostic and therapeutic counseling to these very-high-risk individuals with RH.

Meal timing, meal frequency, and breakfast skipping in adult individuals with type 1 diabetes - associations with glycaemic control.

We assessed meal timing, meal frequency, and breakfast consumption habits of adult individuals with type 1 diabetes (n = 1007) taking part in the Finnish Diabetic Nephropathy Study, and studied whether they are associated with glycaemic control. Data on dietary intake and blood glucose measurements were retrieved from food records. HbA1c was measured at the study visit. In the whole sample, four peaks of energy intake emerged. Energy intake was the greatest in the evening, followed by midday. Altogether 7% of the participants reported no energy intake between 05:00 and 09:59 (breakfast skippers). While breakfast skippers reported lower number of meals, no difference was observed in the total energy intake between those eating and omitting breakfast. In a multivariable model, skipping breakfast was associated with higher mean blood glucose concentrations and lower odds of good glycaemic control. A median of 6 daily meals was reported. Adjusted for confounders, the number of meals was negatively associated with HbA1c, and the mean of the blood glucose measurements, but positively associated with the variability of these measurements. Our observations support the habit of a regular meal pattern, including consumption of breakfast and multiple smaller meals for good glycaemic control in adults with type 1 diabetes. However, an increase in the blood glucose variability may additionally be expected with an increase in the number of meals eaten.

Statistical reporting of metabolomics data: experience from a high-throughput NMR platform and epidemiological applications.

INTRODUCTION: Meta-analysis is the cornerstone of robust biomedical evidence. OBJECTIVES: We investigated whether statistical reporting practices facilitate metabolomics meta-analyses. METHODS: A literature review of 44 studies that used a comparable platform. RESULTS: Non-numeric formats were used in 31 studies. In half of the studies, less than a third of all measures were reported. Unadjusted P-values were missing from 12 studies and exact P-values from 9 studies. CONCLUSION: Reporting practices can be improved. We recommend (i) publishing all results as numbers, (ii) reporting effect sizes of all measured metabolites and (iii) always reporting unadjusted exact P-values.

Numero: a statistical framework to define multivariable subgroups in complex population-based datasets.

Large-scale epidemiological and population data provide opportunities to identify subgroups of people who are at risk of disease or exposed to adverse environments. Clustering algorithms are popular data-driven tools to identify these subgroups; however, relying exclusively on algorithms may not produce the best results if the dataset does not have a clustered structure. For this reason, we propose a framework (the R-library Numero) that combines the self-organizing map algorithm, permutation analysis for statistical evidence and a final expert-driven subgrouping step. We used Numero to define subgroups in two examples without an obvious clustering structure: a biomedical dataset of kidney disease and another dataset of community-level socioeconomic indicators. We benchmarked the Numero subgroupings against popular clustering algorithms (principal components, K-means and hierarchical clustering). The Numero subgroupings were more intuitive and easier to interpret without losing mathematical quality. Therefore, we expect Numero to be useful for exploratory analyses of population-based epidemiological datasets.

Multivariable Analysis of Nutritional and Socio-Economic Profiles Shows Differences in Incident Anemia for Northern and Southern Jiangsu in China.

Anemia is a prevalent public health problem associated with nutritional and socio-economic factors that contribute to iron deficiency. To understand the complex interplay of risk factors, we investigated a prospective population sample from the Jiangsu province in China. At baseline, three-day food intake was measured for 2849 individuals (20 to 87 years of age, mean age 47 ± 14, range 20-87 years, 64% women). At a five-year follow-up, anemia status was re-assessed for 1262 individuals. The dataset was split and age-matched to accommodate cross-sectional (n = 2526), prospective (n = 837), and subgroup designs (n = 1844). We applied a machine learning framework (self-organizing map) to define four subgroups. The first two subgroups were primarily from the less affluent North: the High Fibre subgroup had a higher iron intake (35 vs. 21 mg/day) and lower anemia incidence (10% vs. 25%) compared to the Low Vegetable subgroup. However, the predominantly Southern subgroups were surprising: the Low Fibre subgroup showed a lower anemia incidence (10% vs. 27%), yet also a lower iron intake (20 vs. 28 mg/day) compared to the High Rice subgroup. These results suggest that interventions and iron intake guidelines should be tailored to regional, nutritional, and socio-economic subgroups.