Dyslipoproteinemia, obesity and insulin resistance are integrative constituents of the metabolic syndrome and are major risk factors for hypertension. The objective of this study was to determine ...whether hypertension specifically affects the plasma lipidome independently and differently from the effects induced by obesity and insulin resistance.
We screened the plasma lipidome of 19 men with hypertension and 51 normotensive male controls by top-down shotgun profiling on a LTQ Orbitrap hybrid mass spectrometer. The analysis encompassed 95 lipid species of 10 major lipid classes. Obesity resulted in generally higher lipid load in blood plasma, while the content of tri- and diacylglycerols increased dramatically. Insulin resistance, defined by HOMA-IR >3.5 and controlled for BMI, had little effect on the plasma lipidome. Importantly, we observed that in blood plasma of hypertensive individuals the overall content of ether lipids decreased. Ether phosphatidylcholines and ether phosphatidylethanolamines, that comprise arachidonic (20:4) and docosapentaenoic (22:5) fatty acid moieties, were specifically diminished. The content of free cholesterol also decreased, although conventional clinical lipid homeostasis indices remained unaffected.
Top-down shotgun lipidomics demonstrated that hypertension is accompanied by specific reduction of the content of ether lipids and free cholesterol that occurred independently of lipidomic alterations induced by obesity and insulin resistance. These results may form the basis for novel preventive and dietary strategies alleviating the severity of hypertension.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Telemedicine is defined by three characteristics: (1) using information and communication technologies, (2) covering a geographical distance, and (3) involving professionals who deliver care directly ...to a patient or a group of patients. It is said to improve chronic care management and self-management in patients with chronic diseases. However, currently available guidelines for the care of patients with diabetes, hypertension, or dyslipidemia do not include evidence-based guidance on which components of telemedicine are most effective for which patient populations.
The primary aim of this study was to identify, synthesize, and critically appraise evidence on the effectiveness of telemedicine solutions and their components on clinical outcomes in patients with diabetes, hypertension, or dyslipidemia.
We conducted an umbrella review of high-level evidence, including systematic reviews and meta-analyses of randomized controlled trials. On the basis of predefined eligibility criteria, extensive automated and manual searches of the databases PubMed, EMBASE, and Cochrane Library were conducted. Two authors independently screened the studies, extracted data, and carried out the quality assessments. Extracted data were presented according to intervention components and patient characteristics using defined thresholds of clinical relevance. Overall certainty of outcomes was assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) tool.
Overall, 3564 references were identified, of which 46 records were included after applying eligibility criteria. The majority of included studies were published after 2015. Significant and clinically relevant reduction rates for glycated hemoglobin (HbA
; ≤-0.5%) were found in patients with diabetes. Higher reduction rates were found for recently diagnosed patients and those with higher baseline HbA
(>8%). Telemedicine was not found to have a significant and clinically meaningful impact on blood pressure. Only reviews or meta-analyses reporting lipid outcomes in patients with diabetes were found. GRADE assessment revealed that the overall quality of the evidence was low to very low.
The results of this umbrella review indicate that telemedicine has the potential to improve clinical outcomes in patients with diabetes. Although subgroup-specific effectiveness rates favoring certain intervention and population characteristics were found, the low GRADE ratings indicate that evidence can be considered as limited. Future updates of clinical care and practice guidelines should carefully assess the methodological quality of studies and the overall certainty of subgroup-specific outcomes before recommending telemedicine interventions for certain patient populations.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Current screening algorithms for type 2 diabetes (T2D) rely on fasting plasma glucose (FPG) and/or HbA1c. This fails to identify a sizeable subgroup of individuals in early stages of metabolic ...dysregulation who are at high risk for developing diabetes or cardiovascular disease. The Matsuda index, a combination of parameters derived from a fasting and postprandial insulin assay, is an early biomarker for metabolic dysregulation (i.e. insulin resistance/compensatory hyperinsulinemia). The aim of this analysis was to compare four widely available anthropometric and biochemical markers indicative of this condition waist-to-height ratio (WHtR), hypertriglyceridemic-waist phenotype (HTW), triglycerides-to-HDL-C ratio (TG/HDL-C) and FPG to the Matsuda index. This cross-sectional analysis included 2231 individuals with normal fasting glucose (NFG, n = 1333), impaired fasting glucose (IFG, n = 599) and T2D (n = 299) from an outpatient diabetes clinic in Germany and thus extended a prior analysis from our group done on the first two subgroups. We analyzed correlations of the Matsuda index with WHtR, HTW, TG/HDL-C and FPG and their predictive accuracies by correlation and logistic regression analyses and receiver operating characteristics. In the entire group and in NFG, IFG and T2D, the best associations were observed between the Matsuda index and the WHtR (r = - 0.458), followed by HTW phenotype (r = - 0.438). As for prediction accuracy, WHtR was superior to HTW, TG/HDL-C and FPG in the entire group (AUC 0.801) and NFG, IFG and T2D. A multivariable risk score for the prediction of insulin resistance was tested and demonstrated an area under the ROC curve of 0.765 for WHtR and its interaction with sex as predictor controlled by age and sex. The predictive power increased to 0.845 when FPG and TG/HDL-C were included. Using as a comparator the Matsuda index, WHtR, compared to HTW, TG/HDL-C and FPG, showed the best predictive value for detecting metabolic dysregulation. We conclude that WHtR, a widely available anthropometric index, could refine phenotypic screening for insulin resistance/hyperinsulinemia. This may ameliorate early identification of individuals who are candidates for appropriate therapeutic interventions aimed at addressing the twin epidemic of metabolic and cardiovascular disease in settings where more extended testing such as insulin assays are not feasible.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Abstract Up to 30% of obese people do not display the “typical” metabolic obesity-associated complications. For this group of patients, the term “metabolically healthy obese (MHO)” has been ...established during the past years and has been the focus of research activities. The development and severity of insulin resistance as well as (subclinical) inflammations seems to play a key role in distinguishing metabolically healthy from metabolically non-healthy individuals. However, an internationally consistent and accepted classification that might also include inflammatory markers as well as features of non-alcoholic fatty liver disease is missing to date, and available data – in terms of prevalence, definition and severity – are heterogeneous, both during childhood/adolescence and during adulthood. In addition, the impact of MHO on future morbidity and mortality compared to obese, metabolically non-healthy as well as normal weight, metabolically healthy individuals is absolutely not clear to date and even conflicting. This review summarizes salient literature related to that topic and provides insight into our current understanding of MHO, covering all age spans from childhood to adulthood.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Type 2 diabetes mellitus (T2DM) comprises the vast majority of all diabetes cases in adults, with alarmingly increasing prevalence over the past few decades worldwide. A particularly heavy healthcare ...burden of diabetes is noted in Europe, where 8.8% of the population aged 20-79 years is estimated to have diabetes according to the International Diabetes Federation. Multiple risk factors are implicated in the pathogenesis of T2DM with complex underlying interplay and intricate gene-environment interactions. Thus, intense research has been focused on studying the role of T2DM risk factors and on identifying vulnerable groups for T2DM in the general population which can then be targeted for prevention interventions.
For this narrative review, we conducted a comprehensive search of the existing literature on T2DM risk factors, focusing on studies in adult cohorts from European countries which were published in English after January 2000.
Multiple lifestyle-related and sociodemographic factors were identified as related to high T2DM risk, including age, ethnicity, family history, low socioeconomic status, obesity, metabolic syndrome and each of its components, as well as certain unhealthy lifestyle behaviors. As Europe has an increasingly aging population, multiple migrant and ethnic minority groups and significant socioeconomic diversity both within and across different countries, this review focuses not only on modifiable T2DM risk factors, but also on the impact of pertinent demographic and socioeconomic factors.
In addition to other T2DM risk factors, low socioeconomic status can significantly increase the risk for prediabetes and T2DM, but is often overlooked. In multinational and multicultural regions such as Europe, a holistic approach, which will take into account both traditional and socioeconomic/socioecological factors, is becoming increasingly crucial in order to implement multidimensional public health programs and integrated community-based interventions for effective T2DM prevention.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Prevalence of childhood obesity has worldwide more than doubled since 1980. Underlying factors are complex and are far from completely understood. Strategies to prevent childhood obesity have mainly ...focused on behavioral intervention; and obesity therapy was mainly based on lifestyle modification to date. However, effects for both have been quite limited so far and no country has succeeded in fighting the obesity epidemy we are facing.
Normalization of body weight before onset of puberty is crucial for several reasons: First, obese children and adolescents frequently stay obese until adulthood. Second, obesity during adolescence is significantly associated with increased risk for cardiovascular and metabolic disease such as type 2 diabetes in adulthood. And third, recent data have shown a strong association between higher body mass index (BMI) during adolescence and increased risk for several malignancies such as leukemia, Hodgkin's disease, colorectal cancer, breast cancer and others in adulthood.
This review summarizes our current understanding of epidemiology, underlying factors, concomitant disease, as well as available intervention strategies and gives an overview of what has been reached so far and what measures should be undertaken to counteract the obesogenic environment.
•Prevalence of childhood obesity has doubled in many countries since 1980.•Effects of preventive or therapeutic approaches have been rather small to date.•Childhood/adolescent obesity leads to markedly increased morbidity and mortality due to cardiometabolic disease in adulthood.•Evidence for strong association between higher body mass index during adolescence and increased cancer risk in adulthood•Obesity induces major changes in the cytokine and hormone status of the growing organism.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Real life implementation studies performed in different settings and populations proved that lifestyle interventions in prevention of type 2 diabetes can be effective. However, little is known about ...long term results of these translational studies. Therefore, the purpose of this study was to examine the maintenance of diabetes type 2 risk factor reduction achieved 1 year after intervention and during 3 year follow-up in primary health care setting in Poland.
Study participants (n = 262), middle aged, slightly obese, with increased type 2 diabetes risk ((age 55.5 (SD = 11.3), BMI 32 (SD = 4.8), Finnish Diabetes Risk Score FINDRISC 18.4 (SD = 2.9)) but no diabetes at baseline, were invited for 1 individual and 10 group lifestyle counselling sessions as well as received 6 motivational phone calls and 2 letters followed by organized physical activity sessions combined with counselling to increase physical activity. Measurements were performed at baseline and then repeated 1 and 3 years after the initiation of the intervention.
One hundred five participants completed all 3 examinations (baseline age 56.6 (SD = 10.7)), BMI 31.1 (SD = 4.9)), FINDRISC 18.57 (SD = 3.09)). Males comprised 13% of the group, 10% of the patients presented impaired fasting glucose (IFG) and 14% impaired glucose tolerance (IGT). Mean weight of participants decreased by 2.27 kg (SD = 5.25) after 1 year (p = <0.001). After 3 years a weight gain by 1.13 kg (SD = 4.6) (p = 0.04) was observed. In comparison with baseline however, the mean total weight loss at the end of the study was maintained by 1.14 kg (SD = 5.8) (ns). Diabetes risk (FINDRISC) declined after one year by 2.8 (SD = 3.6) (p = 0.001) and the decrease by 2.26 (SD = 4.27) was maintained after 3 years (p = 0.001). Body mass reduction by >5% was achieved after 1 and 3 years by 27 and 19% of the participants, respectively. Repeated measures analysis revealed significant changes observed from baseline to year 1 and year 3 in: weight (p = 0.048), BMI (p = 0.001), total cholesterol (p = 0.013), TG (p = 0.061), fasting glucose level (p = 0.037) and FINDRISC (p = 0.001) parameters. The conversion rate to diabetes was 2% after 1 year and 7% after 3 years.
Type 2 diabetes prevention in real life primary health care setting through lifestyle intervention delivered by trained nurses leads to modest weight reduction, favorable cardiovascular risk factors changes and decrease of diabetes risk. These beneficial outcomes can be maintained at a 3-year follow-up.
ISRCTN, ID ISRCTN96692060 , registered 03.08.2016 retrospectively.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Glucolipotoxicity is a major pathophysiological mechanism in the development of insulin resistance and type 2 diabetes mellitus (T2D). We aimed to detect subtle changes in the circulating lipid ...profile by shotgun lipidomics analyses and to associate them with four different insulin sensitivity indices.
The cross-sectional study comprised 90 men with a broad range of insulin sensitivity including normal glucose tolerance (NGT, n = 33), impaired glucose tolerance (IGT, n = 32) and newly detected T2D (n = 25). Prior to oral glucose challenge plasma was obtained and quantitatively analyzed for 198 lipid molecular species from 13 different lipid classes including triacylglycerls (TAGs), phosphatidylcholine plasmalogen/ether (PC O-s), sphingomyelins (SMs), and lysophosphatidylcholines (LPCs). To identify a lipidomic signature of individual insulin sensitivity we applied three data mining approaches, namely least absolute shrinkage and selection operator (LASSO), Support Vector Regression (SVR) and Random Forests (RF) for the following insulin sensitivity indices: homeostasis model of insulin resistance (HOMA-IR), glucose insulin sensitivity index (GSI), insulin sensitivity index (ISI), and disposition index (DI). The LASSO procedure offers a high prediction accuracy and and an easier interpretability than SVR and RF.
After LASSO selection, the plasma lipidome explained 3% (DI) to maximal 53% (HOMA-IR) variability of the sensitivity indexes. Among the lipid species with the highest positive LASSO regression coefficient were TAG 54:2 (HOMA-IR), PC O- 32:0 (GSI), and SM 40:3:1 (ISI). The highest negative regression coefficient was obtained for LPC 22:5 (HOMA-IR), TAG 51:1 (GSI), and TAG 58:6 (ISI).
Although a substantial part of lipid molecular species showed a significant correlation with insulin sensitivity indices we were able to identify a limited number of lipid metabolites of particular importance based on the LASSO approach. These few selected lipids with the closest connection to sensitivity indices may help to further improve disease risk prediction and disease and therapy monitoring.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Insulin resistance is the underlying mechanism for the metabolic syndrome and associated dyslipidaemia that theoretically implies a practical tool for identifying individuals at risk for ...cardiovascular disease and type-2-diabetes. Another screening tool is the hypertriglyceremic-waist phenotype (HTW). There is important impact of the ethnic background but a lack of studied European populations for the association of the triglyceride/high-density lipoprotein cholesterol (HDL-C) ratio and insulin resistance. This observational, retrospective study evaluated lipid ratios and the HTW for predicting the metabolic syndrome/insulin resistance in 1932 non-diabetic individuals from Germany in the fasting state and during a glucose tolerance test. The relations of triglyceride/HDL-C, total-cholesterol/HDL-C, and low-density lipoprotein cholesterol/HDL-C with 5 surrogate estimates of insulin resistance/sensitivity and metabolic syndrome were analysed by linear regression analysis and receiver operating characteristics (ROC) in participants with normal (n=1 333) or impaired fasting glucose (n=599), also for the impact of gender. Within the lipid ratios, triglyceride/HDL-C had the strongest associations with insulin resistance/sensitivity markers. In the prediction of metabolic syndrome, diagnostic accuracy was good for triglyceride/HDL-C (area under the ROC curve 0.817) with optimal cut-off points (in mg/dl units) of 2.8 for men (80% sensitivity, 71% specificity) and 1.9 for women (80% sensitivity, 75% specificity) and fair for HTW and HOMA-IR (area under the curve 0.773 and 0.761). These data suggest the triglyceride/HDL-C ratio as a physiologically relevant and practical index for predicting the concomitant presence of metabolic syndrome, insulin resistance and dyslipidaemia for therapeutic and preventive care in apparently healthy European populations.
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