Metabolic phenotypes, vascular complications, and premature deaths in a population of 4,197 patients with type 1 diabetes

The role of adiponectin and its receptor signaling in ocular inflammation-associated diseases

Ocular inflammation-associated diseases are leading causes of global visual impairment, with limited treatment options. Adiponectin, a hormone primarily secreted by adipose tissue, binds to its receptors, which are widely distributed throughout the body, exerting powerful physiological regulatory effects. The protective role of adiponectin in various inflammatory diseases has gained increasing attention in recent years. Previous studies have confirmed the presence of adiponectin and its receptors in the eyes. Furthermore, adiponectin and its analogs have shown potential as novel drugs for the treatment of inflammatory eye diseases. This article summarizes the evidence for the interplay between adiponectin and inflammatory eye diseases and provides new perspectives on the diagnostic and therapeutic possibilities of adiponectin.

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.

Longitudinal metabolomics of increasing body-mass index and waist-hip ratio reveals two dynamic patterns of obesity pandemic

BACKGROUND/OBJECTIVE

This observational study dissects the complex temporal associations between body-mass index (BMI), waist-hip ratio (WHR) and circulating metabolomics using a combination of longitudinal and cross-sectional population-based datasets and new systems epidemiology tools.

SUBJECTS/METHODS

Firstly, a data-driven subgrouping algorithm was employed to simplify high-dimensional metabolic profiling data into a single categorical variable: a self-organizing map (SOM) was created from 174 metabolic measures from cross-sectional surveys (FINRISK, n = 9708, ages 25-74) and a birth cohort (NFBC1966, n = 3117, age 31 at baseline, age 46 at follow-up) and an expert committee defined four subgroups of individuals based on visual inspection of the SOM. Secondly, the subgroups were compared regarding BMI and WHR trajectories in an independent longitudinal dataset: participants of the Young Finns Study (YFS, n = 1286, ages 24-39 at baseline, 10 years follow-up, three visits) were categorized into the four subgroups and subgroup-specific age-dependent trajectories of BMI, WHR and metabolic measures were modelled by linear regression.

RESULTS

The four subgroups were characterised at age 39 by high BMI, WHR and dyslipidemia (designated TG-rich); low BMI, WHR and favourable lipids (TG-poor); low lipids in general (Low lipid) and high low-density-lipoprotein cholesterol (High LDL-C). Trajectory modelling of the YFS dataset revealed a dynamic BMI divergence pattern: despite overlapping starting points at age 24, the subgroups diverged in BMI, fasting insulin (three-fold difference at age 49 between TG-rich and TG-poor) and insulin-associated measures such as triglyceride-cholesterol ratio. Trajectories also revealed a WHR progression pattern: despite different starting points at the age of 24 in WHR, LDL-C and cholesterol-associated measures, all subgroups exhibited similar rates of change in these measures, i.e. WHR progression was uniform regardless of the cross-sectional metabolic profile.

CONCLUSIONS

Age-associated weight variation in adults between 24 and 49 manifests as temporal divergence in BMI and uniform progression of WHR across metabolic health strata.

Association of parental cardiovascular risk factors with offspring type 1 diabetes mellitus insulin sensitivity

AIM

This study aimed to determine whether the insulin resistance (IR) and lipid profiles in Type 1 Diabetes (T1D) offspring are associated with IR and other cardiovascular risk factors in their parents.

METHODS

This study included 99 T1D patients (19.6 ± 4.0 yrs.), 85 mothers and 60 fathers. Parents' IR was assessed by HOMA-IR, and the insulin sensitivity in T1D patients was assessed by the estimated Glucose Disposal Rate (eGDR).

RESULTS

The eGDR in the T1D offspring was negatively related to age (p = 0.023), weight (p = 0.004), LDL (p = 0.026), and microalbuminuria (p = 0.019). Maternal Type 2 Diabetes (p < 0.001) and HOMA-IR (p = 0.029) were negatively related to eGDR in their T1D offspring. The maternal HOMA-IR and the proband's eGDR were positively (p = 0.012) and negatively (p = 0.042) associated with the birth weight of the T1D offspring, respectively. We didn't find an association with the fathers' profiles.

CONCLUSIONS

In a cohort of offspring with T1D the insulin sensitivity was related to the IR, lipid profile, and the presence of T2D only in their mothers. Precocious screening and treatment of these risk factors beyond glycemic control will benefit T1D with this background.

The impact of diabetic nephropathy and severe diabetic retinopathy on chronic limb threatening ischemia risk in individuals with type 1 diabetes: a nationwide, population study

Background

The prevalence, incidence and risk factors and especially the effect of diabetic nephropathy (DN) and diabetic retinopathy on the risk of chronic limb threatening ischemia (CLTI) have been sparsely studied in individuals with type 1 diabetes (T1D).

Methods

The prospective cohort study consisted of 4697 individuals with T1D from the nationwide Finnish Diabetic Nephropathy (FinnDiane) Study. Medical records were thoroughly reviewed in order to ascertain all CLTI events. The key risk factors were DN and severe diabetic retinopathy (SDR).

Findings

There were 319 events of confirmed CLTI, 102 prevalent events at baseline and 217 incident events during the follow-up of 11.9 (IQR 9.3-13.8) years. The 12-year cumulative incidence of CLTI was 4.6% (95% CI 4.0-5.3). Risk factors included presence of DN, SDR, age, duration of diabetes, HbA_1c, systolic blood pressure, triglycerides and current smoking. Sub-hazard ratios (SHRs) according to combinations of DN status and presence (+) or absence (-) of SDR were 4.8 (2.0-11.7) for normoalbuminuria/SDR+, 3.2 (1.1-9.4) for microalbuminuria/SDR-, 11.9 (5.4-26.5) for microalbuminuria/SDR+, 8.7 (3.2-23.2) for macroalbuminuria/SDR-, 15.6 (7.4-33.0) for macroalbuminuria/SDR+ and 37.9 (17.2-78.9) for kidney failure compared with individuals with normal albumin excretion rate and without SDR.

Interpretation

Diabetic nephropathy, especially kidney failure, is associated with high risk of limb threatening ischemia in individuals with T1D. The risk of CLTI increases gradually according to the severity of diabetic nephropathy. Also, diabetic retinopathy is independently and additively associated with high risk of CLTI.

Funding

This research was funded by grants from Folkhälsan Research Foundation, Academy of Finland (316664), Wilhelm and Else Stockmann Foundation, Liv och Hälsa Society, Novo Nordisk Foundation (NNF OC0013659), Finnish Foundation for Cardiovascular Research, Finnish Diabetes Research Foundation, Medical Society of Finland, Sigrid Jusélius Foundation and Helsinki University Hospital Research Funds.

Whole-exome sequencing identifies novel protein-altering variants associated with serum apolipoprotein and lipid concentrations

BACKGROUND

Dyslipidemia is a major risk factor for cardiovascular disease, and diabetes impacts the lipid metabolism through multiple pathways. In addition to the standard lipid measurements, apolipoprotein concentrations provide added awareness of the burden of circulating lipoproteins. While common genetic variants modestly affect the serum lipid concentrations, rare genetic mutations can cause monogenic forms of hypercholesterolemia and other genetic disorders of lipid metabolism. We aimed to identify low-frequency protein-altering variants (PAVs) affecting lipoprotein and lipid traits.

METHODS

We analyzed whole-exome (WES) and whole-genome sequencing (WGS) data of 481 and 474 individuals with type 1 diabetes, respectively. The phenotypic data consisted of 79 serum lipid and apolipoprotein phenotypes obtained with clinical laboratory measurements and nuclear magnetic resonance spectroscopy.

RESULTS

The single-variant analysis identified an association between the LIPC p.Thr405Met (rs113298164) and serum apolipoprotein A1 concentrations (p=7.8×10^-8). The burden of PAVs was significantly associated with lipid phenotypes in LIPC, RBM47, TRMT5, GTF3C5, MARCHF10, and RYR3 (p<2.9×10^-6). The RBM47 gene is required for apolipoprotein B post-translational modifications, and in our data, the association between RBM47 and apolipoprotein C-III concentrations was due to a rare 21 base pair p.Ala496-Ala502 deletion; in replication, the burden of rare deleterious variants in RBM47 was associated with lower triglyceride concentrations in WES of >170,000 individuals from multiple ancestries (p=0.0013). Two PAVs in GTF3C5 were highly enriched in the Finnish population and associated with cardiovascular phenotypes in the general population. In the previously known APOB gene, we identified novel associations at two protein-truncating variants resulting in lower serum non-HDL cholesterol (p=4.8×10^-4), apolipoprotein B (p=5.6×10^-4), and LDL cholesterol (p=9.5×10^-4) concentrations.

CONCLUSIONS

We identified lipid and apolipoprotein-associated variants in the previously known LIPC and APOB genes, as well as PAVs in GTF3C5 associated with LDLC, and in RBM47 associated with apolipoprotein C-III concentrations, implicated as an independent CVD risk factor. Identification of rare loss-of-function variants has previously revealed genes that can be targeted to prevent CVD, such as the LDL cholesterol-lowering loss-of-function variants in the PCSK9 gene. Thus, this study suggests novel putative therapeutic targets for the prevention of CVD.

Cross-sectional metabolic subgroups and 10-year follow-up of cardiometabolic multimorbidity in the UK Biobank

We assigned 329,908 UK Biobank participants into six subgroups based on a self-organizing map of 51 biochemical measures (blinded for clinical outcomes). The subgroup with the most favorable metabolic traits was chosen as the reference. Hazard ratios (HR) for incident disease were modeled by Cox regression. Enrichment ratios (ER) of incident multi-morbidity versus randomly expected co-occurrence were evaluated by permutation tests; ER is like HR but captures co-occurrence rather than event frequency. The subgroup with high urinary excretion without kidney stress (HR = 1.24) and the subgroup with the highest apolipoprotein B and blood pressure (HR = 1.52) were associated with ischemic heart disease (IHD). The subgroup with kidney stress, high adiposity and inflammation was associated with IHD (HR = 2.11), cancer (HR = 1.29), dementia (HR = 1.70) and mortality (HR = 2.12). The subgroup with high liver enzymes and triglycerides was at risk of diabetes (HR = 15.6). Multimorbidity was enriched in metabolically favorable subgroups (3.4 ≤ ER ≤ 4.0) despite lower disease burden overall; the relative risk of co-occurring disease was higher in the absence of obvious metabolic dysfunction. These results provide synergistic insight into metabolic health and its associations with cardiovascular disease in a large population sample.

Is it time to change the goals of lipid management in type 1 diabetes mellitus? Changes in apolipoprotein levels during the first year of type 1 diabetes mellitus. Prospective InLipoDiab1 study

INTRODUCTION

Apolipoprotein complement is a critical determinant of lipoprotein function and metabolism. The relation between exogenous insulin and apolipoproteins (apos) in newly diagnosed type 1 diabetes mellitus (T1DM) has not yet been studied extensively. The aim of this study was to prospectively observe the changes in serum apos AI (apo AI) and AII (apo AII) in patients with newly diagnosed T1DM and their association with the daily insulin requirement.

MATERIAL AND METHODS

Thirty-four participants of the InLipoDiab1 study aged 26 (IQR: 22-32) were enrolled in this analysis. Apolipoprotein AI and AII concentrations were assessed at diagnosis and at follow-up after 3 weeks, 6 months, and 1 year of insulin treatment. The daily dose of insulin (DDI) was calculated as the amount of short- and long-acting insulin at discharge from the hospital and at follow-up visits.

RESULTS

The changes in apo AI concentration were observed after 3 weeks of insulin treatment (p = 0.04), with the largest increase between 3 weeks and 6 months of observation (p < 0.001). Apolipoprotein AII level did not change significantly after 3 weeks, while a significant increase was observed between 3 weeks and 6 months of treatment (p < 0.001). The correlations between DDI and apo concentration were not statistically significant.

CONCLUSIONS

In the first year of T1DM, there is a significant increase in apos concentration. Due to the significant deviation of apos concentration from accepted norms, changes in the recommendations of lipid control criteria in T1DM may be considered.

High pro-neurotensin levels in individuals with type 1 diabetes associate with the development of cardiovascular risk factors at follow-up

AIMS

Neurotensin (NT) is a gut hormone that promotes lipids absorption and controls appetite. Elevated circulating pro-NT, the stable precursor of NT, is associated with cardiovascular (CV) disease, metabolic syndrome (MS) and type 2 diabetes (T2D). Features of MS and insulin resistance are reported also in type 1 diabetes (T1D), with detrimental impact on the overall CV risk profile. Aims of the study were to evaluate plasma pro-NT in T1D patients and to test whether its levels are associated with and/or predictive of CV risk factors and overall risk profile.

METHODS

For this longitudinal retrospective study, we analyzed clinical data from 41 T1D individuals referring to the diabetes outpatient clinics at Sapienza University of Rome, Italy, collected at the baseline and after 10 years. Fasting plasma pro-NT levels were measured in T1D subjects at the baseline and in 34 age-, sex-, BMI-comparable healthy individuals recruited in the same period.

RESULTS

Pro-NT did not differ significantly between patients and controls (median[range] pro-NT: 156.3 [96.6-198.2] vs. 179.4 [139.7-230.7] pmol/L, p = 0.26). In T1D, greater fasting pro-NT associated with poor glycemic control at baseline and predicted increased waist circumference, reduced insulin sensitivity, dyslipidemia and hypertension at 10-year follow-up. High pro-NT predicted 10-year very-high CV risk with adjusted OR = 11 (95%C.I.: 1.4-94.5; p = 0.029).

CONCLUSIONS

In T1D individuals, elevated pro-NT levels predict the development of adverse metabolic profile, which translates in higher CV risk profile at 10-year follow-up. Pro-NT represents a novel predictor/marker of CV risk factors in adults with T1D.

Estimated glucose disposal rate as a candidate biomarker for thrombotic biomarkers in T1D: a pooled analysis

PURPOSE

To determine the utility of estimated glucose disposal rate (eGDR) as a candidate biomarker for thrombotic biomarkers in patients with type 1 diabetes (T1D).

METHODS

We reanalysed baseline pretreatment data in a subset of patients with T1D from two previous RCTs, consisting of a panel of thrombotic markers, including fibrinogen, tissue factor (TF) activity, and plasminogen-activator inhibitor (PAI)-1, and TNFα, and clinical factors (age, T1D duration, HbA1c, insulin requirements, BMI, blood pressure, and eGDR). We employed univariate linear regression models to investigate associations between clinical parameters and eGDR with thrombotic biomarkers.

RESULTS

Thirty-two patients were included [mean ± SD age 31 ± 7 years, HbA1c of 58 ± 9 mmol/mol (7.5 ± 0.8%), eGDR 7.73 ± 2.61]. eGDR negatively associated with fibrinogen (P < 0.001), PAI-1 concentrations (P = 0.005), and TF activity (P = 0.020), but not TNFα levels (P = 0.881). We identified 2 clusters of patients displaying significantly different characteristics; 56% (n = 18) were categorised as 'higher-risk', eliciting significantly higher fibrinogen (+ 1514 ± 594 μg/mL; P < 0.001), TF activity (+ 59.23 ± 9.42 pmol/mL; P < 0.001), and PAI-1 (+ 8.48 ± 1.58 pmol/dL; P < 0.001), HbA1c concentrations (+ 14.20 ± 1.04 mmol/mol; P < 0.001), age (+ 7 ± 3 years; P < 0.001), duration of diabetes (15 ± 2 years; P < 0.001), BMI (+ 7.66 ± 2.61 kg/m²; P < 0.001), and lower mean eGDR (- 3.98 ± 1.07; P < 0.001).

CONCLUSIONS

Compared to BMI and insulin requirements, classical surrogates of insulin resistance, eGDR is a suitable and superior thrombotic risk indicator in T1D.

TRIAL REGISTRATION

ISRCTN4081115; registered 27 June 2017.

Cardiovascular risk factors in children and adolescents with type 1 diabetes in Italy: a multicentric observational study

AIMS

To assess the prevalence of cardiovascular risk factors (CVRFs) and to identify the variables associated with CVRFs in a cohort of children and adolescents with Type 1 Diabetes.

METHODS

2021 subjects, 2-18 year-old, were recruited in 17 Italian Pediatric Diabetes Centers. Anthropometric, blood pressure, biochemical (HbA1c, lipid profile, ACR), insulin therapy, physical activity level, smoking and family socio-economic status data were collected. CVRFs prevalence and their distribution were analyzed according to age and binary logistic regression was performed with positivity for at least one major CVRF (BMI-SDS > +2SD, blood pressure > 90th percentile, LDL cholesterol>100 mg/dL) as dependent variable and age, duration of illness, gender, HbA1c and physical activity, as independent variables.

RESULTS

The prevalence of CVFRs not at the recommended target was respectively: 32.5% one CVRF, 6.7% two CVRFs and 0.6% three CVRFs, with no significant differences across the 3 age groups (2-10, 10-15, 15-18 years). In the total sample, HbA1c and inadequate physical activity were associated with a higher probability of having at least one major CVRF. This probability was associated with physical activity in the 2-10-year-old group, with physical activity and HbA1c in the 10-15-year-old group and with HbA1c only in subjects older than 15 years.

CONCLUSIONS

More than 30% of subjects had at least a major CVRF. Early detection of CVRFs may be useful to enforce the therapeutic intervention in this subgroup, in order to reduce the risk to develop cardiovascular complications.

Sphingomyelin and progression of renal and coronary heart disease in individuals with type 1 diabetes

AIMS/HYPOTHESIS

Lipid abnormalities are associated with diabetic kidney disease and CHD, although their exact role has not yet been fully explained. Sphingomyelin, the predominant sphingolipid in humans, is crucial for intact glomerular and endothelial function. Therefore, the objective of our study was to investigate whether sphingomyelin impacts kidney disease and CHD progression in individuals with type 1 diabetes.

METHODS

Individuals (n = 1087) from the Finnish Diabetic Nephropathy (FinnDiane) prospective cohort study with serum sphingomyelin measured using a proton NMR metabolomics platform were included. Kidney disease progression was defined as change in eGFR or albuminuria stratum. Data on incident end-stage renal disease (ESRD) and CHD were retrieved from national registries. HRs from Cox regression models and regression coefficients from the logistic or linear regression analyses were reported per 1 SD increase in sphingomyelin level. In addition, receiver operating curves were used to assess whether sphingomyelin improves eGFR decline prediction compared with albuminuria.

RESULTS

During a median (IQR) 10.7 (6.4, 13.5) years of follow-up, sphingomyelin was independently associated with the fastest eGFR decline (lowest 25%; median [IQR] for eGFR change: <-4.4 [-6.8, -3.1] ml min^-1 [1.73 m^-2] year^-1), even after adjustment for classical lipid variables such as HDL-cholesterol and triacylglycerols (OR [95% CI]: 1.36 [1.15, 1.61], p < 0.001). Similarly, sphingomyelin increased the risk of progression to ESRD (HR [95% CI]: 1.53 [1.19, 1.97], p = 0.001). Moreover, sphingomyelin increased the risk of CHD (HR [95% CI]: 1.24 [1.01, 1.52], p = 0.038). However, sphingomyelin did not perform better than albuminuria in the prediction of eGFR decline.

CONCLUSIONS/INTERPRETATION

This study demonstrates for the first time in a prospective setting that sphingomyelin is associated with the fastest eGFR decline and progression to ESRD in type 1 diabetes. In addition, sphingomyelin is a risk factor for CHD. These data suggest that high sphingomyelin level, independently of classical lipid risk factors, may contribute not only to the initiation and progression of kidney disease but also to CHD. Graphical abstract.

EpiMetal: an open-source graphical web browser tool for easy statistical analyses in epidemiology and metabolomics

MOTIVATION

An intuitive graphical interface that allows statistical analyses and visualizations of extensive data without any knowledge of dedicated statistical software or programming.

IMPLEMENTATION

EpiMetal is a single-page web application written in JavaScript, to be used via a modern desktop web browser.

GENERAL FEATURES

Standard epidemiological analyses and self-organizing maps for data-driven metabolic profiling are included. Multiple extensive datasets with an arbitrary number of continuous and category variables can be integrated with the software. Any snapshot of the analyses can be saved and shared with others via a www-link. We demonstrate the usage of EpiMetal using pilot data with over 500 quantitative molecular measures for each sample as well as in two large-scale epidemiological cohorts (N >10 000).

AVAILABILITY

The software usage exemplar and the pilot data are open access online at [http://EpiMetal.computationalmedicine.fi]. MIT licensed source code is available at the Github repository at [https://github.com/amergin/epimetal].

Data-driven multivariate population subgrouping via lipoprotein phenotypes versus apolipoprotein B in the risk assessment of coronary heart disease

BACKGROUND AND AIMS

Population subgrouping has been suggested as means to improve coronary heart disease (CHD) risk assessment. We explored here how unsupervised data-driven metabolic subgrouping, based on comprehensive lipoprotein subclass data, would work in large-scale population cohorts.

METHODS

We applied a self-organizing map (SOM) artificial intelligence methodology to define subgroups based on detailed lipoprotein profiles in a population-based cohort (n = 5789) and utilised the trained SOM in an independent cohort (n = 7607). We identified four SOM-based subgroups of individuals with distinct lipoprotein profiles and CHD risk and compared those to univariate subgrouping by apolipoprotein B quartiles.

RESULTS

The SOM-based subgroup with highest concentrations for non-HDL measures had the highest, and the subgroup with lowest concentrations, the lowest risk for CHD. However, apolipoprotein B quartiles produced better resolution of risk than the SOM-based subgroups and also striking dose-response behaviour.

CONCLUSIONS

These results suggest that the majority of lipoprotein-mediated CHD risk is explained by apolipoprotein B-containing lipoprotein particles. Therefore, even advanced multivariate subgrouping, with comprehensive data on lipoprotein metabolism, may not advance CHD risk assessment.

Using Data Science to Understand Complexity and Quantify Heterogeneity in the Onset and Progression of Chronic Disease

Novel discoveries in genomics and other omics sciences are rapidly redefining our understanding of health and disease as well as advancing the development of targeted therapeutics for improving health outcomes. The scale of these findings, fueled by vast increases in computing power and new techniques in data analytics, easily supersedes that of phenomena observed using more traditional research approaches. Until recently, the classification and diagnosis of disease has involved rather subjective processes, whereby signs and late symptom patterns are linked with clinical outcomes. However, symptom patterns, disease trajectories, and health outcomes are complex entities characterized by a wide range of clinical manifestations and progression patterns. The burgeoning fields of data science and bioinformatics are opening opportunities for nurse scientists to quantify disease heterogeneity by defining and categorizing disease phenotypes and endotypes. Nurse scientists and clinicians can play a critical role in engaging patients and the larger scientific community in these efforts. The purpose of this article is to provide an introduction to concepts critical to understanding and quantifying heterogeneity in the onset and progression of chronic disease. To present and exemplify key concepts, we (1) discuss evidence for heterogeneity in the onset and progression of Type 1 diabetes, (2) link emerging research approaches in data science with principles in network science and systems biology to lay the groundwork for stratifying subclinical and advanced chronic disease, thus expanding the purview of symptom science, and (3) describe the computational skills needed to engage in these analyses.

Using Self Organizing Maps to Compare Sepsis Patients from the Neonatal and Adult Intensive Care Unit

Neonatal sepsis, a blood infection occurring in infants younger than 90 days old, represents a significant source of mortality and morbidity among infants.¹ Mortality rates increase with postnatal age and can be as high as 52% (36% in newborns aged 8-14 days and 52% in those aged 15-28 days).² While sepsis in adults has a generally accepted definition, the definition for clinical diagnosis in infants is less well defined. Using the Medical Information Mart for Intensive Care database (MIMIC-III), patient diagnoses and microbiology results records were processed with an artificial neural network trained using unsupervised learning known as a self-organizing map (SOM). The results of this feasibility study suggest a low degree of overlap between the presentation of sepsis in neonate and adult intensive care unit populations. As a consequence, it supports the need for dedicated research in neonatal sepsis, which may manifest differently than adult sepsis.

Accumulation of advanced glycation end products in the skin is accelerated in relation to insulin resistance in people with Type 1 diabetes mellitus

AIM

To evaluate the association between skin advanced glycation end products and insulin resistance in Type 1 diabetes.

METHODS

The study group consisted of 476 people with Type 1 diabetes (247 men) with a median (interquartile range) age of 42 (33-53) years, disease duration of 24 (19-32) years and HbA_1c concentration of 63 (55-74) mmol/mol [7.9 (7.2-8.9)%]. Insulin resistance was assessed according to estimated glucose disposal rate. Advanced glycation product accumulation in the skin was measured by autofluorescence using an AGE Reader. The group was divided into three subgroups based on estimated glucose disposal rate tertiles (<5.5, 5.5-9.5 and >9.5 mg/kg/min, respectively). The higher the estimated glucose disposal rate, the lower the insulin resistance.

RESULTS

Skin autofluoresence level decreased with increasing estimated glucose disposal rate; comparing people below the lower tertile, with those between the first and third tertiles, and with those above the third tertile, the median autofluoresences were, respectively: 2.5 (2.2-2.9) vs 2.3 (2.0-2.7) vs 2.1 (1.9-2.5) AU (P<0.0001). A negative correlation was observed between skin autofluorescence and estimated glucose disposal rate (Spearman's correlation coefficient=-0.31, P <0.001). Multiple logistic regression showed a significant, two-way association of insulin resistance with skin autofluorescence.

CONCLUSION

The results of this study offer strong evidence for a two-way relationship between insulin resistance and advanced glycation product accumulation in the skin in people with Type 1 diabetes.

Transcriptional networks of progressive diabetic peripheral neuropathy in the db/db mouse model of type 2 diabetes: An inflammatory story

Diabetic peripheral neuropathy is the most common complication of diabetes and a source of considerable morbidity. Numerous molecular pathways are linked to neuropathic progression, but it is unclear whether these pathways are altered throughout the course of disease. Moreover, the methods by which these molecular pathways are analyzed can produce significantly different results; as such it is often unclear whether previously published pathways are viable targets for novel therapeutic approaches. In the current study we examine changes in gene expression patterns in the sciatic nerve (SCN) and dorsal root ganglia (DRG) of db/db diabetic mice at 8, 16, and 24 weeks of age using microarray analysis. Following the collection and verification of gene expression data, we utilized both self-organizing map (SOM) analysis and differentially expressed gene (DEG) analysis to detect pathways that were altered at all time points. Though there was some variability between SOM and DEG analyses, we consistently detected altered immune pathways in both the SCN and DRG over the course of disease. To support these results, we further used multiplex analysis to assess protein changes in the SCN of diabetic mice; we found that multiple immune molecules were upregulated at both early and later stages of disease. In particular, we found that matrix metalloproteinase-12 was highly upregulated in microarray and multiplex data sets suggesting it may play a role in disease progression.

Metabolomics and Lipidomics Study of Mouse Models of Type 1 Diabetes Highlights Divergent Metabolism in Purine and Tryptophan Metabolism Prior to Disease Onset

With the increase in incidence of type 1 diabetes (T1DM), there is an urgent need to understand the early molecular and metabolic alterations that accompany the autoimmune disease. This is not least because in murine models early intervention can prevent the development of disease. We have applied a liquid chromatography (LC-) and gas chromatography (GC-) mass spectrometry (MS) metabolomics and lipidomics analysis of blood plasma and pancreas tissue to follow the progression of disease in three models related to autoimmune diabetes: the nonobese diabetic (NOD) mouse, susceptible to the development of autoimmune diabetes, and the NOD-E (transgenic NOD mice that express the I-E heterodimer of the major histocompatibility complex II) and NOD-severe combined immunodeficiency (SCID) mouse strains, two models protected from the development of diabetes. All three analyses highlighted the metabolic differences between the NOD-SCID mouse and the other two strains, regardless of diabetic status indicating that NOD-SCID mice are poor controls for metabolic changes in NOD mice. By comparing NOD and NOD-E mice, we show the development of T1DM in NOD mice is associated with changes in lipid, purine, and tryptophan metabolism, including an increase in kynurenic acid and a decrease in lysophospholipids, metabolites previously associated with inflammation.

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.

Data-driven metabolic subtypes predict future adverse events in individuals with type 1 diabetes

AIMS/HYPOTHESIS

Previously, we proposed that data-driven metabolic subtypes predict mortality in type 1 diabetes. Here, we analysed new clinical endpoints and revisited the subtypes after 7 years of additional follow-up.

METHODS

Finnish individuals with type 1 diabetes (2059 men and 1924 women, insulin treatment before 35 years of age) were recruited by the national multicentre FinnDiane Study Group. The participants were assigned one of six metabolic subtypes according to a previously published self-organising map from 2008. Subtype-specific all-cause and cardiovascular mortality rates in the FinnDiane cohort were compared with registry data from the entire Finnish population. The rates of incident diabetic kidney disease and cardiovascular endpoints were estimated based on hospital records.

RESULTS

The advanced kidney disease subtype was associated with the highest incidence of kidney disease progression (67.5% per decade, p < 0.001), ischaemic heart disease (26.4% per decade, p < 0.001) and all-cause mortality (41.5% per decade, p < 0.001). Across all subtypes, mortality rates were lower in women compared with men, but standardised mortality ratios (SMRs) were higher in women. SMRs were indistinguishable between the original study period (1994-2007) and the new period (2008-2014). The metabolic syndrome subtype predicted cardiovascular deaths (SMR 11.0 for men, SMR 23.4 for women, p < 0.001), and women with the high HDL-cholesterol subtype were also at high cardiovascular risk (SMR 16.3, p < 0.001). Men with the low-cholesterol or good glycaemic control subtype showed no excess mortality.

CONCLUSIONS/INTERPRETATION

Data-driven multivariable metabolic subtypes predicted the divergence of complication burden across multiple clinical endpoints simultaneously. In particular, men with the metabolic syndrome and women with high HDL-cholesterol should be recognised as important subgroups in interventional studies and public health guidelines on type 1 diabetes.

Glucose-independent association of adiposity and diet composition with cardiovascular risk in children and adolescents with type 1 diabetes

AIMS

To test the hypothesis that diet composition, adiposity and glycometabolic control could independently contribute to an increase in the cardiovascular risk (CVR) for children/adolescents with type 1 diabetes (T1D).

METHODS

One hundred and eighty children/adolescents with T1D (age range 5-18 years) were enrolled. Diet (3-day weighed dietary record), physical (height, weight, waist circumference, bioelectrical impedance analysis) and biochemical (HbA1c, lipid profile) parameters were recorded. Regression models, using non-HDL cholesterol (a gross index of CVR) as the dependent variable and HbA1c (mmol/mol), fat mass (FM) %, lipid-to-carbohydrate intake ratio as independent ones, were calculated.

RESULTS

Non-HDL cholesterol was significantly associated with adiposity (FM%; r = 0.27, 95% CI 0.13-0.43), body fat distribution (waist-to-height ratio; r = 0.16, 95% CI 0.02-0.31), lipid intake [% of energy intake (EI)] (r = 0.25, 95% CI 0.11-0.41), carbohydrate intake (% EI; r = -0.24, 95% CI 0.10-0.40), lipid-to-carbohydrate intake ratio (r = 0.26, 95% CI 0.12-0.42) and blood glucose control (HbA1c; r = 0.24, 95% CI 0.10-0.40). A p value cutoff of 0.10 was used for covariates to be included in the regression analysis. Multiple regression analysis showed that adiposity (FM%), blood glucose control (HbA1c) and lipid-to-carbohydrate intake ratio independently contributed to explaining the inter-individual variability of non-HDL cholesterol (R ² = 0.163, p < 0.05).

CONCLUSIONS

Adiposity and lipid-to-carbohydrate intake ratio affect non-HDL cholesterol, a gross index of CVR, regardless of HbA1c, in children and adolescents with T1D. Intervention to reduce CVR in T1D patients should focus not only on glycometabolic control but also on adiposity and diet composition.

Lipoprotein composition in patients with type 1 diabetes mellitus: Impact of lipases and adipokines

OBJECTIVE

High cardiovascular mortality in patients with type 1 diabetes (T1DM) is widely recognized. Paradoxically, these patients have been shown to have elevated HDL-C and reduced apoB-containing lipoproteins. The purpose of this investigation was to further characterize the lipoprotein composition in T1DM and to assess the role that lipases and adipokines may play in these differences.

METHODS

T1DM patients (89) attending the Diabetes Clinic at the University of Miami and 42 healthy controls were recruited. Clinical characteristics, lipoprotein composition (by ultracentrifugation and HPLC), leptin, and adiponectin were measured in the full cohort, while a subgroup had LPL and hepatic lipase measured.

RESULTS

Subjects were predominately Caucasian and Hispanic. HgbA1c's were above goal while their mean duration of diabetes was >20 years. LPL was 2-fold elevated in diabetic women versus controls (+107%{p=0.001}) with no difference in men. Hepatic lipase was reduced 50% {p<0.001} in women but increased 50% {p=0.079} in men. Leptin was similar to controls in women but reduced in men (-60%{p<0.001}). Adiponectin was elevated in both genders (men: +55%{p=0.018}; women: +46%{p=0.007}). LDL-C was reduced in both diabetic men (-33%{p<0.001}) and women (-24%{p<0.001}) while HDL-C trended higher only in men (+13%{p=0.064}). Both total apoB (men: -31%{p<0.001}; women: -17%{p=0.016}) and triglycerides (men: -49%{p<0.001}; women: -31%{p=0.011}) were reduced in both genders while total apoA-I was increased in both (men: +31%{p<0.001}; women: +19%{p=0.008}). Both men and women had increases in LpA-I (+66%{p<0.001}; +40%{p=0.001}) which accounted for essentially the entire increase in HDL mass. VLDL lipids (men: -53→70%; women: -31→57%) were lower as was apoB (particle number) in men (-51{p<0.001}) with a similar trend in women (-35%{p=0.066}). Cholesterol esters in the particle core were depleted in both genders relative to both apoB (men: -41%; women: -37%) and triglycerides (men: -38%; women: -34%) (all{p<0.009}). There were similar differences in IDL. HDL-L lipids (except triglycerides) (men: +45→74%; women: +49→77%{p<0.006}), apoA-1 (men: +162%; women: +117%{p<0.001}), and apoA-II (men: +64%{p=0.008}; women: +55%{p=0.014}) were higher in T1DM patients. These differences produced dramatic increases in LpA-I (men: +221%; women +139%{p<0.001}) and total HDL-L mass (men: +85%; women: +78%{p<0.001}). ApoM (men: +190%; women: +149%{p<0.001}) was also dramatically increased. Conversely, HDL-D lipids were lower in both genders (-20%→50%) while apoA-I was not different in either. ApoA-II was lower only in the diabetic women (-25%{p=0.015}). LPL activity correlated primarily with IDL(-), LDL(-), HDL-L(+), and HDL-D(-) only in the women. HL correlated weakly with VLDL(+), LDL(+), HDL-L(-), and HDL-D(+) in women but had much stronger correlations with VLDL(-), IDL(-), and HDL-L(+). Adiponectin correlated with VLDL(-), IDL(-), LDL(-), HDL-L(+), and HDL-D(-) in women but only HDL-L(+) and HDL-D(-) in men. Leptin correlated with very few parameters in women but did correlate weakly with several HDL-L(-) and HDL-M(-) parameters.

CONCLUSION

Lipoprotein composition and adipokine concentrations in both genders as well as lipase activities in the women would be expected to reduce the atherosclerotic risk in these patients with T1DM. These data suggest that there are functional lipoprotein abnormalities responsible for their CV risk that are not reflected in their plasma concentrations.

Metabolomics in diabetic complications

With a global prevalence of 9%, diabetes is the direct cause of millions of deaths each year and is quickly becoming a health crisis. Major long-term complications of diabetes arise from persistent oxidative stress and dysfunction in multiple metabolic pathways. The most serious complications involve vascular damage and include cardiovascular disease as well as microvascular disorders such as nephropathy, neuropathy, and retinopathy. Current clinical analyses like glycated hemoglobin and plasma glucose measurements hold some value as prognostic indicators of the severity of complications, but investigations into the underlying pathophysiology are still lacking. Advancements in biotechnology hold the key to uncovering new pathways and establishing therapeutic targets. Metabolomics, the study of small endogenous molecules, is a powerful toolset for studying pathophysiological processes and has been used to elucidate metabolic signatures of diabetes in various biological systems. Current challenges in the field involve correlating these biomarkers to specific complications to provide a better prediction of future risk and disease progression. This review will highlight the progress that has been made in the field of metabolomics including technological advancements, the identification of potential biomarkers, and metabolic pathways relevant to macro- and microvascular diabetic complications.

Added value of soluble tumor necrosis factor-α receptor 1 as a biomarker of ESRD risk in patients with type 1 diabetes

OBJECTIVE

Recent studies have suggested that circulating levels of the tumor necrosis factor-α receptor 1 (sTNFαR1) may be a useful predictor for the risk of end-stage renal disease (ESRD) in patients with diabetes. However, its potential utility as a biomarker has not been formally quantified.

RESEARCH DESIGN AND METHODS

Circulating levels of sTNFαR1 were assessed in 429 patients with type 1 diabetes and overt nephropathy from the Finnish Diabetic Nephropathy (FinnDiane) cohort study. Predictors of incident ESRD over a median of 9.4 years of follow-up were determined by Cox regression and Fine-Gray competing risk analyses. The added value of sTNFαR1 was estimated via time-dependent receiver operating characteristic curves, net reclassification index (NRI), and integrated discrimination improvement (IDI) for survival data.

RESULTS

A total of 130 individuals developed ESRD (28%; ESRD incidence rate of 3.4% per year). In cause-specific modeling, after adjusting for baseline renal status, predictors of increased incidence of ESRD in patients with overt nephropathy were an elevated HbA1c, shorter duration of diabetes, and circulating levels of sTNFαR1. Notably, sTNFαR1 outperformed estimated glomerular filtration rate in terms of R(2). Circulating levels of the sTNFαR1 also remained associated with ESRD after adjusting for the competing risk of death. A prediction model including sTNFαR1 (as a -0.5 fractional polynomial) was superior to a model without it, as demonstrated by better global fit, an increment of R(2), the C index, and area under the curve. Estimates of IDI and NRI(>0) were 0.22 (95% CI 0.16-0.28; P < 0.0001) and 0.98 (0.78-1.23; P < 0.0001), respectively. The median increment in the risk score after including sTNFαR1 in the prediction model was 0.18 (0.12-0.30; P < 0.0001).

CONCLUSIONS

Circulating levels of sTNFαR1 are independently associated with the cumulative incidence of ESRD. This association is both significant and biologically plausible and appears to provide added value as a biomarker, based on the absolute values of NRI and IDI.

Novel genetic susceptibility loci for diabetic end-stage renal disease identified through robust naive Bayes classification

AIMS/HYPOTHESIS

Diabetic nephropathy is a major diabetic complication, and diabetes is the leading cause of end-stage renal disease (ESRD). Family studies suggest a hereditary component for diabetic nephropathy. However, only a few genes have been associated with diabetic nephropathy or ESRD in diabetic patients. Our aim was to detect novel genetic variants associated with diabetic nephropathy and ESRD.

METHODS

We exploited a novel algorithm, 'Bag of Naive Bayes', whose marker selection strategy is complementary to that of conventional genome-wide association models based on univariate association tests. The analysis was performed on a genome-wide association study of 3,464 patients with type 1 diabetes from the Finnish Diabetic Nephropathy (FinnDiane) Study and subsequently replicated with 4,263 type 1 diabetes patients from the Steno Diabetes Centre, the All Ireland-Warren 3-Genetics of Kidneys in Diabetes UK collection (UK-Republic of Ireland) and the Genetics of Kidneys in Diabetes US Study (GoKinD US).

RESULTS

Five genetic loci (WNT4/ZBTB40-rs12137135, RGMA/MCTP2-rs17709344, MAPRE1P2-rs1670754, SEMA6D/SLC24A5-rs12917114 and SIK1-rs2838302) were associated with ESRD in the FinnDiane study. An association between ESRD and rs17709344, tagging the previously identified rs12437854 and located between the RGMA and MCTP2 genes, was replicated in independent case-control cohorts. rs12917114 near SEMA6D was associated with ESRD in the replication cohorts under the genotypic model (p < 0.05), and rs12137135 upstream of WNT4 was associated with ESRD in Steno.

CONCLUSIONS/INTERPRETATION

This study supports the previously identified findings on the RGMA/MCTP2 region and suggests novel susceptibility loci for ESRD. This highlights the importance of applying complementary statistical methods to detect novel genetic variants in diabetic nephropathy and, in general, in complex diseases.

Latent structure modeling underlying theophylline tablet formulations using a Bayesian network based on a self-organizing map clustering

The "quality by design" concept in pharmaceutical formulation development requires the establishment of a science-based rationale and design space. In this article, we integrate thin-plate spline (TPS) interpolation, Kohonen's self-organizing map (SOM) and a Bayesian network (BN) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline tablets were prepared using a standard formulation. We measured the tensile strength and disintegration time as response variables and the compressibility, cohesion and dispersibility of the pretableting blend as latent variables. We predicted these variables quantitatively using nonlinear TPS, generated a large amount of data on pretableting blends and tablets and clustered these data into several clusters using a SOM. Our results show that we are able to predict the experimental values of the latent and response variables with a high degree of accuracy and are able to classify the tablet data into several distinct clusters. In addition, to visualize the latent structure between the causal and latent factors and the response variables, we applied a BN method to the SOM clustering results. We found that despite having inserted latent variables between the causal factors and response variables, their relation is equivalent to the results for the SOM clustering, and thus we are able to explain the underlying latent structure. Consequently, this technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline tablet formulation.

Type 1 diabetes, metabolic syndrome and cardiovascular risk

Patients with type 1 diabetes mellitus (T1DM) traditionally had a low body mass index and microangiopathic complications were common, while macroangiopathy and the metabolic syndrome were exceptional. The Diabetes Control and Complications Trial, published in 1993, demonstrated that therapy aimed at maintaining HbA1c levels as close to normal as feasible reduced the incidence of microangiopathy. Since then, the use of intensive insulin therapy to optimize metabolic control became generalized. Improved glycemic control resulted in a lower incidence of microangiopathy; however, its side effects included a higher rate of severe hypoglycemia and increased weight gain. Approximately 50% of patients with T1DM are currently obese or overweight, and between 8% and 40% meet the metabolic syndrome criteria. The components of the metabolic syndrome and insulin resistance have been linked to chronic T1DM complications, and cardiovascular disease is now the leading cause of death in these patients. Therefore, new therapeutic strategies are required in T1DM subjects, not only to intensively lower glycemia, but to control all associated metabolic syndrome traits.

Triglyceride-cholesterol imbalance across lipoprotein subclasses predicts diabetic kidney disease and mortality in type 1 diabetes: the FinnDiane Study

BACKGROUND

Circulating cholesterol (C) and triglyceride (TG) levels are associated with vascular injury in type 1 diabetes (T1DM). Lipoproteins are responsible for transporting lipids, and alterations in their subclass distributions may partly explain the increased mortality in individuals with T1DM.

DESIGN AND SUBJECTS

A cohort of 3544 individuals with T1DM was recruited by the nationwide multicentre FinnDiane Study Group. At baseline, six very low-density lipoprotein VLDL, one intermediate-density lipoprotein IDL, three low-density lipoprotein LDL and four higher high-density lipoprotein HDL subclasses were quantified by proton nuclear magnetic resonance spectroscopy. At follow-up, the baseline data were analysed for incident micro- or macroalbuminuria (117 cases in 5.3 years), progression from microalbuminuria (63 cases in 6.1 years), progression from macroalbuminuria (109 cases in 5.9 years) and mortality (385 deaths in 9.4 years). Univariate associations were tested by age-matched cases and controls and multivariate lipoprotein profiles were analysed using the self-organizing map (SOM).

RESULTS

TG and C levels in large VLDL were associated with incident albuminuria, TG and C in medium VLDL were associated with progression from microalbuminuria, and TG and C in all VLDL subclasses were associated with mortality. Large HDL-C was inversely associated with mortality. Three extreme phenotypes emerged from SOM analysis: (i) low C (<3% mortality), (ii) low TG/C ratio (6% mortality), and (iii) high TG/C ratio (40% mortality) in all subclasses.

CONCLUSIONS

TG-C imbalance is a general lipoprotein characteristic in individuals with T1DM and high vascular disease risk.

Association of dietary sodium intake with atherogenesis in experimental diabetes and with cardiovascular disease in patients with Type 1 diabetes

It is recommended that individuals with diabetes restrict their dietary sodium intake. However, although salt intake is correlated with BP (blood pressure), it also partly determines the activation state of the RAAS (renin–angiotensin–aldosterone system), a key mediator of diabetes-associated atherosclerosis. apoE KO (apolipoprotein E knockout) mice were allocated for the induction of diabetes with streptozotocin or citrate buffer (controls) and further randomized to isocaloric diets containing 0.05%, 0.3% or 3.1% sodium with or without the ACEi [ACE (angiotensin-converting enzyme) inhibitor] perindopril. After 6 weeks of study, plaque accumulation was quantified and markers of atherogenesis were assessed using RT–PCR (reverse transcription–PCR) and ELISA. The association of sodium intake and adverse cardiovascular and mortality outcomes were explored in 2648 adults with Type 1 diabetes without prior CVD (cardiovascular disease) from the FinnDiane study. A 0.05% sodium diet was associated with increased plaque accumulation in diabetic apoE KO mice, associated with activation of the RAAS. By contrast, a diet containing 3.1% sodium suppressed atherogenesis associated with suppression of the RAAS, with an efficacy comparable with ACE inhibition. In adults with Type 1 diabetes, low sodium intake was also associated with an increased risk of all-cause mortality and new-onset cardiovascular events. However, high sodium intake was also associated with adverse outcomes, leading to a J-shaped relationship overall. Although BP lowering is an important goal for the management of diabetes, off-target actions to activate the RAAS may contribute to an observed lack of protection from cardiovascular complications in patients with Type 1 diabetes with low sodium intake.

Adiponectin in renal disease--a review of the evidence as a risk factor for cardiovascular and all-cause mortality

Adiponectin, an adipokine, was discovered in 1995. The initial evidence led to the study of adiponectin as a determinant of insulin sensitivity and blood glucose levels. The literature then evolved to reports of the inverse association of adiponectin with incident Type 2 diabetes mellitus and coronary heart disease. Shortly thereafter, reports of a positive association with heart failure and mortality appeared and were replicated. We review here the basic science evidence and clinical studies of the role of renal function and kidney disease as a determinant of adiponectin.

Early signs of atherosclerosis are associated with insulin resistance in non-obese adolescent and young adults with type 1 diabetes

Background

Patients with type 1 diabetes have a substantial risk of developing cardiovascular complications early in life. We aimed to explore the role of insulin sensitivity (S_i) as an early factor of atherosclerosis in young type 1 diabetes vs. non-diabetic subjects.

Methods

Forty adolescent and young adult individuals (20 type 1 diabetics and 20 non-diabetics), age 14–20 years, without characteristics of the metabolic syndrome, participated in this cross-sectional study. After an overnight fast, S_i was measured by hyperinsulinemic euglycemic clamp (40 mU/m²) and calculated by glucose infusion rate (GIR). Carotid intima-media thickness (cIMT) was measured in the common carotid artery with high-resolution ultrasonography. Risk factors of atherosclerosis (Body mass index [BMI], waist circumference, systolic blood pressure [sBP], triglycerides, low HDL-cholesterol and HbA_1c) were also investigated.

Results

cIMT was increased (0.52 ± 0.1 vs. 0.47 ± 0.1 mm, P < 0.01), whereas GIR was decreased (5.0 ± 2.1 vs. 7.1 ± 2.2 mg/kg/min, P < 0.01) in type 1 diabetics vs. non-diabetics. The differences in cIMT were negatively associated with S_i (r = −0.4, P < 0.01) and positively associated with waist circumference (r = 0.34, P = 0.03), with no such associations between BMI (r = 0.15, P = 0.32), sBP (r = 0.09, P = 0.58), triglycerides (r = 0.07, P = 0.66), HDL-cholesterol (r = 0.10, P = 0.55) and HbA_1c (r = 0.24, P = 0.13). In a multivariate regression model, between cIMT (dependent) and group (explanatory), only adjustment for S_i affected the significance (ß = 0.08, P = 0.11) vs. (ß = 0.07, P < 0.01) for the whole model. No interaction between cIMT, groups and S_i was observed.

Conclusions

cIMT is increased and associated with insulin resistance in adolescent, non-obese type 1 diabetic subjects. Although, no conclusions toward a causal relationship can be drawn from current findings, insulin resistance emerges as an important factor reflecting early signs of atherosclerosis in this small cohort.

The interplay between lipoprotein phenotypes, adiponectin, and alcohol consumption

CONTEXT AND OBJECTIVE

Lipoproteins are involved in the pathophysiology of several metabolic diseases. Here we focus on the interplay between lipoprotein metabolism and adiponectin with the extension of alcohol intake.

DESIGN AND SUBJECTS

Eighty-three low-to-moderate and 80 heavy alcohol drinkers were studied. Plasma adiponectin, other biochemical and extensive lipoprotein data were measured. Self-organizing maps were applied to characterize lipoprotein phenotypes and their interrelationships with biochemical measures and alcohol consumption.

RESULTS

Alcohol consumption and plasma adiponectin had a strong positive association. Heavy alcohol consumption was associated with decreased low-density lipoprotein cholesterol (LDL-C). Nevertheless, two distinct lipoprotein phenotypes were identified, one with elevated high-density lipoprotein cholesterol (HDL-C) and decreased very-low-density lipoprotein triglycerides (VLDL-TG) together with low prevalence of metabolic syndrome, and the other vice versa. The HDL particles were enlarged in both phenotypes related to the heavy drinkers. The low-to-moderate alcohol drinkers were characterized with high LDL-C and C-enriched LDL particles.

CONCLUSIONS

The analyses per se illustrated the multi-faceted and non-linear nature of lipoprotein metabolism. The heavy alcohol drinkers were characterized either by an anti-atherogenic lipoprotein phenotype (with also the highest adiponectin concentrations) or by a phenotype with pro-atherogenic and metabolic syndrome-like features. Clinically this underlines the need to distinguish the differing individual risk for lipid-related metabolic disturbances also in heavy alcohol drinkers.

Sphingomyelin is associated with kidney disease in type 1 diabetes (The FinnDiane Study)

Diabetic kidney disease, diagnosed by urinary albumin excretion rate (AER), is a critical symptom of chronic vascular injury in diabetes, and is associated with dyslipidemia and increased mortality. We investigated serum lipids in 326 subjects with type 1 diabetes: 56% of patients had normal AER, 17% had microalbuminuria (20 ≤ AER < 200 μg/min or 30 ≤ AER < 300 mg/24 h) and 26% had overt kidney disease (macroalbuminuria AER ≥ 200 μg/min or AER ≥ 300 mg/24 h). Lipoprotein subclass lipids and low-molecular-weight metabolites were quantified from native serum, and individual lipid species from the lipid extract of the native sample, using a proton NMR metabonomics platform. Sphingomyelin (odds ratio 2.53, P < 10(-7)), large VLDL cholesterol (odds ratio 2.36, P < 10(-10)), total triglycerides (odds ratio 1.88, P < 10(-6)), omega-9 and saturated fatty acids (odds ratio 1.82, P < 10(-5)), glucose disposal rate (odds ratio 0.44, P < 10(-9)), large HDL cholesterol (odds ratio 0.39, P < 10(-9)) and glomerular filtration rate (odds ratio 0.19, P < 10(-10)) were associated with kidney disease. No associations were found for polyunsaturated fatty acids or phospholipids. Sphingomyelin was a significant regressor of urinary albumin (P < 0.0001) in multivariate analysis with kidney function, glycemic control, body mass, blood pressure, triglycerides and HDL cholesterol. Kidney injury, sphingolipids and excess fatty acids have been linked in animal models-our exploratory approach provides independent support for this relationship in human patients with diabetes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0343-y) contains supplementary material, which is available to authorized users.

Utility of the estimated glucose disposal rate as a marker of microvascular complications in young adults with type 1 diabetes

In 61 young adults with type 1 diabetes mellitus, the estimated glucose disposal rate (eGDR), a validated marker for insulin resistance, correlated positively with the prevalence of microvascular complications. In the absence of an established vascular risk calculator specific to diabetes, the eGDR may present a useful clinical tool in the assessment of complication risk in type 1 diabetes.

Cardiovascular risk in double diabetes mellitus--when two worlds collide

Historically, clinical management of patients with type 1 diabetes mellitus (T1DM) has been focused on glycaemic control, which is sometimes achieved at the expense of weight gain on intensive insulin regimes. Although HbA(1c) level is an important contributor to increased macrovascular risk, several prospective studies have concluded that factors related to obesity, metabolic syndrome and insulin resistance are more important than HbA(1c) for the prediction of cardiovascular risk, especially for coronary heart disease events. 'Double diabetes mellitus' describes a combination of T1DM with characteristics associated with type 2 diabetes mellitus, including central adiposity and exacerbation of insulin resistance. In lean patients with T1DM, portal insulinopaenia might actually confer cardioprotective effects via changes in hepatic lipid profiles (mainly increased HDL cholesterol levels) and a reduction in hepatic steatosis. In patients with double diabetes mellitus, this situation is reversed and atherothrombotic pathophysiology is potentially accelerated by the combination of chronic hyperglycaemia and abnormal lipid partitioning. The prevalence of double diabetes mellitus is increasing in parallel with the societal trend of increased adiposity. This Review discusses how to identify patients susceptible to double diabetes mellitus and suggests alterations to their clinical management that might reduce their risk of future premature coronary disease.

Discovery of early-stage biomarkers for diabetic kidney disease using ms-based metabolomics (FinnDiane study)

Diabetic kidney disease (DKD) is a devastating complication that affects an estimated third of patients with type 1 diabetes mellitus (DM). There is no cure once the disease is diagnosed, but early treatment at a sub-clinical stage can prevent or at least halt the progression. DKD is clinically diagnosed as abnormally high urinary albumin excretion rate (AER). We hypothesize that subtle changes in the urine metabolome precede the clinically significant rise in AER. To test this, 52 type 1 diabetic patients were recruited by the FinnDiane study that had normal AER (normoalbuminuric). After an average of 5.5 years of follow-up half of the subjects (26) progressed from normal AER to microalbuminuria or DKD (macroalbuminuria), the other half remained normoalbuminuric. The objective of this study is to discover urinary biomarkers that differentiate the progressive form of albuminuria from non-progressive form of albuminuria in humans. Metabolite profiles of baseline 24 h urine samples were obtained by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) to detect potential early indicators of pathological changes. Multivariate logistic regression modeling of the metabolomics data resulted in a profile of metabolites that separated those patients that progressed from normoalbuminuric AER to microalbuminuric AER from those patients that maintained normoalbuminuric AER with an accuracy of 75% and a precision of 73%. As this data and samples are from an actual patient population and as such, gathered within a less controlled environment it is striking to see that within this profile a number of metabolites (identified as early indicators) have been associated with DKD already in literature, but also that new candidate biomarkers were found. The discriminating metabolites included acyl-carnitines, acyl-glycines and metabolites related to tryptophan metabolism. We found candidate biomarkers that were univariately significant different. This study demonstrates the potential of multivariate data analysis and metabolomics in the field of diabetic complications, and suggests several metabolic pathways relevant for further biological studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0291-6) contains supplementary material, which is available to authorized users.

Metabolic diversity of progressive kidney disease in 325 patients with type 1 diabetes (the FinnDiane Study)

Type 1 diabetic patients with varying severity of kidney disease were investigated to create multimetabolite models of the disease process. Urinary albumin excretion rate was measured for 3358 patients with type 1 diabetes. Prospective records were available for 1051 patients, of whom 163 showed progression of albuminuria (8.3-year follow-up), and 162 were selected as stable controls. At baseline, serum lipids, lipoprotein subclasses, and low-molecular weight metabolites were quantified by NMR spectroscopy (325 samples). The data were analyzed by the self-organizing map. In cross-sectional analyses, patients with no complications had low serum lipids, less inflammation, and better glycemic control, whereas patients with advanced kidney disease had high serum cystatin-C and sphingomyelin. These phenotype extremes shared low unsaturated fatty acids (UFAs) and phospholipids. Prospectively, progressive albuminuria was associated with high UFAs, phospholipids, and IDL and LDL lipids. Progression at longer duration was associated with high HDL lipids, whereas earlier progression was associated with poor glycemic control, increased saturated fatty acids (SFAs), and inflammation. Diabetic kidney disease consists of diverse metabolic phenotypes: UFAs, phospholipids, IDL, and LDL may be important in the subclinical phase, high SFAs and low HDL suggest accelerated progression, and the sphingolipid pathway in advanced kidney injury deserves further research.

Soluble receptor for AGE (RAGE) is a novel independent predictor of all-cause and cardiovascular mortality in type 1 diabetes

AIMS/HYPOTHESIS

Activation of the receptor for AGE (RAGE) is implicated in the development and progression of vascular complications of diabetes. In this study, we explore factors and mortality outcomes associated with soluble RAGE (sRAGE) in a multicentre nationwide cohort of Finnish adults with type 1 diabetes.

METHODS

Baseline sRAGE concentrations were estimated in 3,100 adults with type 1 diabetes. Clinical and biological variables independently associated with sRAGE were identified using multivariate regression analysis. Independent predictors of mortality were determined using Cox and Fine-Gray proportional-hazards models.

RESULTS

The main independent determinants of sRAGE concentrations were estimated glomerular filtration rate, albuminuria, body mass index, age, duration of diabetes, HbA(1c) and insulin dose (all p < 0.05). During a median of 9.1 years of follow-up there were 202 deaths (7.4 per 1,000 patient years). sRAGE was independently associated with all-cause (Cox model: HR 1.03) and cardiovascular mortality (Fine-Gray competing risks model: HR 1.06) such that patients with the highest sRAGE concentrations had the greatest risk of mortality, after adjusting for age, sex, macrovascular disease, HDL-cholesterol, HbA(1c), triacylglycerol, high-sensitivity C-reactive protein (hsCRP) and the presence and severity of chronic kidney disease. Although polymorphisms in the gene coding for RAGE were significantly associated with sRAGE concentrations, none were associated with mortality outcomes.

CONCLUSIONS/INTERPRETATION

Increased concentrations of sRAGE are associated with increased all-cause and cardiovascular mortality in type 1 diabetes, potentially reflecting the activation and production of RAGE in the context of accelerated vascular disease. These novel findings highlight the importance of the RAGE activation in the prevention and management of diabetic complications.

Macrovascular angiopathy in children and adolescents with type 1 diabetes

Diabetes represents one of the most common diseases globally. Worryingly, the worldwide incidence of type 1 diabetes (T1D) is rising by 3% per year. Despite the rapid increase in diabetes incidence, recent advances in diabetes treatment have been successful in decreasing morbidity and mortality from diabetes-related retinopathy, nephropathy, and neuropathy. In contrast, there is clear evidence for the lack of improvement in mortality for cardiovascular diseases (CVDs). This emphasizes the importance of focusing childhood diabetes care strategies for the prevention of CVD in adulthood. Furthermore, although most work on diabetes and macrovascular disease relates to type 2 diabetes, it has been shown that the age-adjusted relative risk of CVD in T1D far exceeds that in type 2 diabetes. As T1D appears predominantly during childhood, those with T1D are at greater risk for coronary events early in life and require lifelong medical attention. Because of the important health effects of CVDs in children and adolescents with T1D, patients, family members, and care providers should understand the interaction of T1D and cardiovascular risk. In addition, optimal cardiac care for the patient with diabetes should focus on aggressive management of traditional cardiovascular risk factors to optimize those well-recognized as well as new specific risk factors which are becoming available. Therefore, a complete characterization of the molecular mechanisms involved in the development and progression of macrovascular angiopathy is needed. Furthermore, as vascular abnormalities begin as early as in childhood, potentially modifiable risk factors should be identified at an early stage of vascular disease development.

Metabolomics study of alcohol-induced liver injury and hepatocellular carcinoma xenografts in mice

Alcohol abuse is one of the major causes of liver injury and a promoter for hepatocellular carcinoma (HCC). To understand the disease-associated metabolic changes, we investigated and compared the profiles of metabolites in nude mice with alcohol-induced liver injury or bearing a HCC xenograft (HCCX). Alcohol-induced liver injury was achieved by daily administration of grain liquor, and HCC xenografts were generated by subcutaneous inoculation of HepG2 cells in nude mice. Metabolites in serum samples were profiled by ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF MS). The acquired data was analyzed by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) to identify potential disease-specific biomarkers. Results showed that the phosphatidylcholine (PC) levels were significantly higher in both liver injury and HCCX mice compared with the control. Interestingly, lysophosphatidylcholines (LPCs) that contain saturated or monounsaturated fatty acids were reduced in both liver injury and HCCX mice, but polyunsaturated fatty acids LPCs were elevated in liver injury mice only. These data delineated the disease-related metabolic alterations of LPCs in liver injury and HCC, suggesting that the LPC profile in serum may be biomarkers for these two common liver diseases.