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GENETIC DETERMINANTS OF TYPE 2 DIABETES AND ASSOCIATED CARDIOMETABOLIC DISORDERS / DETERMINANTI GENETICI DI DIABETE MELLITO DI TIPO 2 E FENOTIPI CARDIOMETABOLICI ASSOCIATI
Full text linkIl presente progetto di ricerca si compone di tre parti: (1) revisione della letteratura relativa ai determinanti genetici di diabete mellito tipo 2, malattie coronariche e fenotipi intermedi (forme sub-diabetiche di iperglicemia, forme subcliniche di aterosclerosi e fattori di rischio associati) alla ricerca di possibili aree di sovrapposizione; (2) verificare se i determinanti di rischio genetico per diabete tipo 2, ed in particolare quelli maggiormente associati a insulino-resistenza, sono anche associati a misure di aterosclerosi subclinica; (3) verificare se uno score di rischio genetico costituito dai determinanti genetici di diabete tipo 2, infarto miocardico, stroke, fibrillazione atriale, morte cardiaca improvvisa, malattie coronariche è associato a mortalità per tutte le cause e/o mortalità per malattie cardiovascolari. Il diabete mellito di tipo 2 (T2D) è una malattia complessa ad alta prevalenza e incidenza che riconosce fattori genetici e non-genetici quali determinanti causali. Le malattie cardiovascolari (CVD) sono una delle maggiori cause di morte e sono spesso associate a T2D. Studi di associazione genome-wide hanno identificato varianti genetiche comuni associate a T2D, CVD e fenotipi cardiometabolici intermedi. Questo percorso di ricerca si è proposto di individuare le basi genetiche comuni a T2D, CVD e forme sub-diabetiche di iperglicemia attraverso tre studi esemplificativi. Nel primo studio è stato verificato se il rischio genetico per T2D sia associato, in aggregato e/o in sottogruppi funzionali distinti (disfunzione beta-cellulare o insulino-resistenza), a tratti di aterosclerosi subclinica (ATS) in coorti multi-etniche. Il secondo studio ha testato l’ipotesi che la variabilità genetica comune dei loci principalmente coinvolti nella trasduzione del segnale insulinico siano associati a insulino-resistenza, funzione beta-cellulare, anomalie elettrocardiografiche e/o aterosclerosi subclinica in soggetti affetti da T2D neo-diagnosticato. Nel terzo studio è stato indagato se il rischio genetico per T2D e tratti di rischio cardiometabolico sia associato ad aumentata mortalità nel Framingham Offspring Study.Il diabete mellito di tipo 2 (T2D) è una malattia complessa ad alta prevalenza e incidenza che riconosce fattori genetici e non-genetici quali determinanti causali. Le malattie cardiovascolari (CVD) sono una delle maggiori cause di morte e sono spesso associate a T2D. Studi di associazione genome-wide hanno identificato varianti genetiche comuni associate a T2D, CVD e fenotipi cardiometabolici intermedi. Il presente percorso di ricerca mira ad individuare le basi genetiche comuni a T2D, CVD e forme subdiabetiche di iperglicemia attraverso tre studi esemplificativi. Il primo studio si propone di verificare se il rischio genetico per T2D sia associato, in aggregato e/o in sottogruppi funzionali distinti (disfunzione beta-cellulare o insulino-resistenza), a tratti di aterosclerosi subclinica (ATS) in coorti multi-etniche; il secondo verifica l’ipotesi che la variabilità genetica comune dei loci principalmente coinvolti nella trasduzione del segnale insulinico siano associati a insulino-resistenza, funzione beta-cellulare, anomalie elettrocardiografiche e/o aterosclerosi subclinica in soggetti affetti da T2D neo-diagnosticato.; il terzo verifica l’ipotesi se il rischio genetico per T2D e tratti di rischio cardiometabolico si associno ad aumentata mortalità nello studio Framingham.T2D is a complex disease characterized by a high prevalence and incidence worldwide, and recognizes genetic and non-genetic (environmental) risk factors as underlying determinants. CVD are currently one of the leading causes of death and are also often clinically associated to T2D. Recent large-scale genome-wide association studies (GWAS) have identified common genetic risk variants associated with a higher propensity of developing T2D, CVD and intermediate cardiometabolic phenotypes. The goal of the research project herein presented was three-fold: (1) to critically revise the available literature about the genetic determinants of type 2 diabetes (T2D), coronary heart disease (CHD) and intermediate phenotypes (sub-diabetic hyperglycemia, measures of subclinical atherosclerosis (SCA) and associated risk conditions), aimed at searching for potential overlapping areas of shared genetic background; (2) to verify whether the genetic determinants of T2D, and particularly those associated with insulin resistance, are also associated with measures of SCA; (3) to verify whether a genetic risk score comprised of the genetic determinants of T2D, myocardial infarction, stroke, atrial fibrillation, sudden cardiac death, coronary heart disease, is associated with an excess risk of all-cause mortality and/or CVD death. In detail, the present research exercise aimed at exploring the common genetic background of T2D, CVD and sub-diabetic forms of hyperglycemia by means of three exemplifying studies herein outlined. The first study verified whether the genetic risk for T2D, as represented by the aggregate burden of T2D risk loci (either as a whole or by distinct functional sub-groups, representative of loci with prior evidence of association with defective beta-cell function and/or increased insulin resistance), is associated with SCA traits in multi-ethnic cohorts. The second study verified the hypothesis that the common genetic variability at loci gatekeepers of the insulin signaling transduction pathway are associated with insulin resistance, beta-cell dysfunction, pathologic electrocardiogram, and/or increased SCA in patients affect by newly-diagnosed T2D. The third study verified whether the composite of the genetic determinants of T2D and intermediate CVD risk traits is associated with a higher mortality in the Framingham Offspring Study
Current Insights into the Joint Genetic Basis of Type 2 Diabetes and Coronary Heart Disease. Curr Cardiovasc Risk Rep. 2014 Jan 1;8(1):368.
No full textThe large-scale genome-wide association studies conducted so far identified numerous allelic variants associated with type 2 diabetes (T2D), coronary heart disease (CHD) and related cardiometabolic traits. Many T2D- and some CHD-risk loci are also linked with metabolic traits that are hallmarks of insulin resistance (lipid profile, abdominal adiposity). Chromosome 9p21.3 and 2q36.3 are the most consistently replicated loci appearing to share genetic risk for both T2D and CHD. Although many glucose- or insulin-related trait variants are also linked with T2D risk, none of them is associated with CHD. Hence, while T2D and CHD are strongly clinically linked together, further ongoing analyses are needed to clarify the existence of a shared underlying genetic signature of these complex traits. The present review summarizes an updated picture of T2D-CHD genetics as of 2013, aiming to provide a platform for targeted studies dissecting the contribution of genetics to the phenotypic heterogeneity of T2D and CHD
The power of numbers
Full text linkThe technical and methodological advancements, as well as the knowledge accrued over the past decade on the haplotype block structure of the human genome, have enabled investigators to tackle the complexity of the genetic architecture of type 2 diabetes in populations of European and non-European descent by performing large-scale genome-wide association studies (GWAS) for both common and rare genetic variants. Interestingly, while interpreting the GWAS results one may observe that as the number of identified type 2 diabetes risk variants has increased over time, and the loci uncovered by earlier GWAS have been further replicated in larger association studies, the individual (per-allele) effect estimate has become smaller than the one originally detected in the discovery GWAS. This may be due to the non-mutually exclusive occurrence of two statistical phenomena, usually dubbed as "winner's curse" and "spectrum bias" effects. The present commentary discusses the work of the China Kadoorie Biobank Collaborative Group, which sought to provide a demonstration of the calculation of (relatively) unbiased allelic effect sizes for a set of 56 established type 2 diabetes risk variants in a large population-based cohort study of Chinese adult individuals. In particular we critically discuss whether theGWAS approach should remain a matter of statistical constraints only, or whether its integration with functional maps may highlight some sub-threshold loci as informative as those that reach genome-wide significance. The complementary information that could arise from the full integration of the genetic and functional maps holds the promise of potentially uncovering clinically relevant mechanistic insights and might expand the regulatory framework in which to interpret the functional follow-up and fine-mapping currently ongoing at established type 2 diabetes risk loci
Response to Comment on Olioso D. et al. "Effect of Aerobic and Resistance Training on Circulating Micro-RNA Expression Profile in Subjects with Type 2 Diabetes. J Clin Endocrinol Metab 2019; 104(4):1119-1130" by Chirumbolo S
No full text[no abstract available
Response to comment on Vassy et al. polygenic type 2 diabetes prediction at the limit of common variant detection. Diabetes 2014;63:2172-2182.
Full text linkAbbasi et al. (1) raise excellent points about the current and future states of type 2 diabetes risk prediction. Two issues in particular are worth consideration.
First, our clinical and polygenic prediction models do not include time-varying assessments of known risk factors such as BMI and fasting glucose (2). Abbasi et al. are correct that doing so would likely improve the models’ predictive accuracy. Instead, we patterned our models on what is more common in clinical practice. In many ways, the Framingham Heart Study cardiovascular disease risk score defines the paradigm of using a “snapshot in time” approach to risk assessment. That is, what can the characteristics of a patient sitting in front of the clinician tell him or her about that patient’s risk of an outcome 10 years from now? The dynamic risk factors Abbasi et al. propose will be especially salient if clinicians increasingly incorporate risk factor trajectories into their clinical decision making.
Second, their tiered approach to risk stratification (i.e., obtaining more resource-intensive information only among those individuals whose history suggests higher risk) places an appropriate emphasis on the risks, benefits, and costs of screening. We agree with their call for an evaluation of such screening strategies, although we would argue that anthropometry and basic laboratory analyses are already routinely measured in the many clinical settings. An interesting question, then, is whether collection of genome-wide data will be increasingly routine in the clinical setting or even brought by the patients themselves after consulting genotyping services outside of the standard clinical setting. We think our analyses show that even if each individual had his or her genotype for common genetic variation stored in the electronic medical record, its marginal value in diabetes risk prediction would be small. Whether more sophisticated genetic information available soon from high-throughput whole-genome sequencing with detailed functional annotation will improve type 2 diabetes risk prediction, drug targeting, or patient care overall remains an important question for the future
Probiotic Soy Milk: A Call to Action
Full text linkIn a recently published clinical trial, Ghiasvand R et al have shown that the 8-week consumption of 200 mL/day probiotic soy milk fortified with Lactobacillus plantarum A7 may exert favorable changes on biomarkers of oxidative stress in patients with type 2 diabetes and concomitant diabetic kidney disease (DKD)
Depressive symptoms and glycaemic control in adults with type 1 diabetes: an exploratory study on the role of family functioning
No full textPsychological distress and family functioning have a considerable impact on diabetes self-management and glycaemic control in individuals with type 1 diabetes (T1D). However, the influence of both individual and family factors on glycaemic control has not been adequately investigated yet. This study aimed at examining the relationship between perceived family functioning and depressive symptoms with the frequency of capillary self-monitoring of blood glucose (SMBG) and glycaemic control (HbA1c) in a large sample of adults with T1D
Effects of Aerobic and Resistance Training on Circulating micro-RNA Expression Profile in Subjects with Type 2 Diabetes
No full textContext: Structured exercise programs are of great benefit for the treatment of type 2 diabetes (T2DM). However, whether aerobic (AER) or resistance (RES) exercise training exerts specific epigenetic changes through the expression profile of circulating miRNAs (c-miRNAs) is still largely unknown. Objective: To assess whether the c-miRNAs profile changes after either AER or RES training in subjects with T2DM. Design: Twenty-four patients with T2DM randomized to AER or RES training protocols were randomly selected from the Resistance vs. Aerobic Exercise in Type 2 Diabetes (RAED2) Trial (NAER = 12; NRES = 12). The baseline and post-training levels of 179 c-miRNAs were initially measured by RT-PCR in 6 individuals (NAER = 3; NRES = 3). C-miRNAs exhibiting $40% fold change variation and/or nominal significance from baseline were measured in the whole group. Results: Nineteen c-miRNAs were eventually assessed in the whole group. Compared with baseline, the post-training levels of miR-423-3p, miR-451a, and miR-766-3p were significantly up-regulated, irrespective of exercise type (P<0.0026; 0.05/19), and targeted upstream pathways relevant to fatty acids biosynthesis and metabolic regulation. MiR-451a and miR-423-3p were significantly correlated with fat loss (p = 0.45 and 0.43, respectively) and resulted, alone or in combination, in being predictors of fat loss in generalized linear regression models including exercise type as covariate. Only the association with miR-451a eventually retained significance after further correction for age, sex, body mass index, and HbA1c. Conclusions: Exercise training in T2DM is associated with substantial c-miRNAs profile changes, irrespective of exercise type and other relevant metabolic covariates. The mechanistic significance of the observed relationship between fat loss and the epigenetic modifications induced by exercise warrants further investigation in larger datasets. © 2019 Endocrine Society
SGLT1 and SGLT1 Inhibitors: A Role to Be Assessed in the Current Clinical Practice
Full text linkDiabetes is a complex disease of increasingly common occurrence worldwide. Attaining optimal glycemic control is the main challenge to prevent the development of diabetes-related complications and/or to stop their progression. In recent years, the pharmacologic toolkit for the treatment of diabetes has considerably expanded, thus paving the way to more pathophysiology-oriented therapies. For instance, the sodium-glucose cotransporters SGLT2 and SGLT1 have been in the spotlight because of better knowledge of their physiology and therapeutic potential. At present, whereas the SGLT2 inhibitors are widely applied in current clinical practice as an effective and well-tolerated treatment that increases the urinary excretion of glucose, less is known about the use of SGLT1 inhibitors. SGLT1s are of primary importance in the small intestine, an organ that does not express SGLT2, while in the kidney they are expressed in the late renal proximal tubules, where it reabsorbs the glucose escaped from the upstream SGLT2. Hence, SGLT1-mediated glucose reabsorption in the kidney is increased when the tubular glucose load overwhelms the capacity of SGLT2 or when the latter is inhibited. The role of SGLT1 in intestinal and renal glucose transport makes the transporter a potential target for antidiabetic therapy. Here, we briefly report the evidence on LX2761, a new inhibitor against SGLT1 and SGLT2 in vitro, which acts in vivo as a selective inhibitor of SGLT1 in the gastrointestinal tract. LX2761 improves glycemic control without the glycosuria-related side effects of SGLT2 inhibitors, particularly genitourinary tract infections. However, whether it represents a valid therapeutic option for all patients with diabetes or is more appropriate for specific phenotypes, e.g., patients with concomitant diabetes and chronic kidney disease, who may benefit less from the renal mechanism of selective SGLT2 inhibitors, remains to be tested in large randomized controlled trials
American Diabetes Association - 75th Scientific Meeting; Section: Epidemiology/Genetics; Poster n. 1581-P: "Nonalcoholic Fatty Liver Disease Is Associated with Heart Valve Calcification in Type 2 Diabetes"
No full textAortic valve sclerosis (AVS) and mitral annulus calcifi cation (MAC) are powerfulpredictors of adverse cardiovascular outcomes in patients with type 2diabetes (T2D), but the aetiology of valvular calcifi cation is uncertain. Nonalcoholicfatty liver disease (NAFLD) is an emerging cardiovascular risk factorcommonly present in T2D patients, but its association with valvular calcifi -cation is unknown. We sought to investigate whether NAFLD is associatedwith AVS and/or MAC in T2D patients. We conducted a cross-sectional studyby performing a conventional echocardiography and liver ultrasonography ina sample of 247 consecutive outpatients with T2D (179 men; mean age 68years) free of known liver diseases, prior history of chronic heart failure andmoderate-to-severe valvular heart disease. Overall, 139 (56.3%) patients hadno calcifi cation at both aortic and mitral valve (HVC-0), 65 (26.3%) had onevalve affected (HVC-1) and 43 (17.4%) patients had both valves affected (HVC-2). NAFLD was present in 175 (70.8%) patients and its prevalence markedlyincreased in patients with HVC-2 compared with either HVC-1 or HVC-0 (86.1%vs. 83.1% vs. 60.4%, respectively; p<0.001). NAFLD was associated with AVSand/or MAC (unadjusted-odds ratio [OR] 3.51, 95% CI 1.89-6.51, p<0.001). Adjustmentsfor age, sex, smoking history, alcohol consumption, diastolic bloodpressure, hemoglobin A1c, LDL-cholesterol, estimated glomerular fi ltrationrate, use of hypoglycemic, lipid-lowering and anti-hypertensive medicationsand echocardiographic variables did not substantially attenuate the strong associationof NAFLD with AVS and/or MAC (adjusted-OR 2.97, 95% CI 1.31-6.70,p<0.01). In conclusion, these results show for the fi rst time that NAFLD is astrong and independent predictor of cardiac calcifi cation in both aortic andmitral valves in patients affected by T2D. Further research is needed to betterelucidate the mechanisms underlying this association
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