Menarche delay and menstrual irregularities persist in adolescents with type 1 diabetes

<p>Abstract</p> <p>Background</p> <p>Menarche delay has been reported in adolescent females with type 1 diabetes (T1DM), perhaps due to poor glycemic control. We sought to compare age at menarche between adolescent females with T1DM and national data, and to identify factors associated with delayed menarche and menstrual irregularity in T1DM.</p> <p>Methods</p> <p>This was a cross-sectional study and females ages 12- 24 years (n = 228) with at least one menstrual period were recruited during their outpatient diabetes clinic appointment. The National Health and Nutrition Examination Survey (NHANES) 2001-2006 data (n = 3690) for females 12-24 years were used as a control group.</p> <p>Results</p> <p>Age at menarche was later in adolescent females with T1DM diagnosed prior to menarche (12.81 +/- 0.09 years) (mean+/- SE) (n = 185) than for adolescent females diagnosed after menarche (12.17 0.19 years, <it>p = </it>0.0015) (n = 43). Average age of menarche in NHANES was 12.27 +/- 0.038 years, which was significantly earlier than adolescent females with T1DM prior to menarche (<it>p </it>< 0.0001) and similar to adolescent females diagnosed after menarche (<it>p </it>= 0.77). Older age at menarche was negatively correlated with BMI z-score (r = -0.23 <it>p = </it>0.0029) but not hemoglobin A1c (A1c) at menarche (r = 0.01, <it>p </it>= 0.91). Among 181 adolescent females who were at least 2 years post menarche, 63 (35%) reported usually or always irregular cycles.</p> <p>Conclusion</p> <p>Adolescent females with T1DM had a later onset of menarche than both adolescent females who developed T1DM after menarche and NHANES data. Menarche age was negatively associated with BMI z-score, but not A1c. Despite improved treatment in recent decades, menarche delay and high prevalence of menstrual irregularity is still observed among adolescent females with T1DM.</p

Haptoglobin genotype predicts development of coronary artery calcification in a prospective cohort of patients with type 1 diabetes

<p>Abstract</p> <p>Background</p> <p>Coronary artery disease has been linked with genotypes for haptoglobin (Hp) which modulates extracorpuscular hemoglobin. We hypothesized that the Hp genotype would predict progression of coronary artery calcification (CAC), a marker of subclinical atherosclerosis.</p> <p>Methods</p> <p>CAC was measured three times in six years among 436 subjects with type 1 diabetes and 526 control subjects participating in the Coronary Artery Calcification in Type 1 Diabetes (CACTI) study. Hp typing was performed on plasma samples by polyacrylamide gel electrophoresis.</p> <p>Results</p> <p>The Hp 2-2 genotype predicted development of significant CAC only in subjects with diabetes who were free of CAC at baseline (OR: 1.95, 95% CI: 1.07-3.56, p = 0.03), compared to those without the Hp 2-2 genotype, controlling for age, sex, blood pressure and HDL-cholesterol. Hp 2 appeared to have an allele-dose effect on development of CAC. Hp genotype did not predict CAC progression in individuals without diabetes.</p> <p>Conclusions</p> <p>Hp genotype may aid prediction of accelerated coronary atherosclerosis in subjects with type 1 diabetes.</p

Urinary Collagen Fragments Are Significantly Altered in Diabetes: A Link to Pathophysiology

Background: The pathogenesis of diabetes mellitus (DM) is variable, comprising different inflammatory and immune responses. Proteome analysis holds the promise of delivering insight into the pathophysiological changes associated with diabetes. Recently, we identified and validated urinary proteomics biomarkers for diabetes. Based on these initial findings, we aimed to further validate urinary proteomics biomarkers specific for diabetes in general, and particularity associated with either type 1 (T1D) or type 2 diabetes (T2D). Methodology/Principal Findings: Therefore, the low-molecular-weight urinary proteome of 902 subjects from 10 different centers, 315 controls and 587 patients with T1D (n = 299) or T2D (n = 288), was analyzed using capillary-electrophoresis mass-spectrometry. The 261 urinary biomarkers (100 were sequenced) previously discovered in 205 subjects were validated in an additional 697 subjects to distinguish DM subjects (n = 382) from control subjects (n = 315) with 94% (95% CI: 92-95) accuracy in this study. To identify biomarkers that differentiate T1D from T2D, a subset of normoalbuminuric patients with T1D (n = 68) and T2D (n = 42) was employed, enabling identification of 131 biomarker candidates (40 were sequenced) differentially regulated between T1D and T2D. These biomarkers distinguished T1D from T2D in an independent validation set of normoalbuminuric patients (n = 108) with 88% (95% CI: 81-94%) accuracy, and in patients with impaired renal function (n = 369) with 85% (95% CI: 81-88%) accuracy. Specific collagen fragments were associated with diabetes and type of diabetes indicating changes in collagen turnover and extracellular matrix as one hallmark of the molecular pathophysiology of diabetes. Additional biomarkers including inflammatory processes and pro-thrombotic alterations were observed. Conclusions/Significance: These findings, based on the largest proteomic study performed to date on subjects with DM, validate the previously described biomarkers for DM, and pinpoint differences in the urinary proteome of T1D and T2D, indicating significant differences in extracellular matrix remodeling

Multicentric validation of proteomic biomarkers in urine specific for diabetic nephropathy

Background: Urine proteome analysis is rapidly emerging as a tool for diagnosis and prognosis in disease states. For diagnosis of diabetic nephropathy (DN), urinary proteome analysis was successfully applied in a pilot study. The validity of the previously established proteomic biomarkers with respect to the diagnostic and prognostic potential was assessed on a separate set of patients recruited at three different European centers. In this case-control study of 148 Caucasian patients with diabetes mellitus type 2 and duration &gt;= 5 years, cases of DN were defined as albuminuria &gt;300 mg/d and diabetic retinopathy (n = 66). Controls were matched for gender and diabetes duration (n = 82). Methodology/Principal Findings: Proteome analysis was performed blinded using high-resolution capillary electrophoresis coupled with mass spectrometry (CE-MS). Data were evaluated employing the previously developed model for DN. Upon unblinding, the model for DN showed 93.8% sensitivity and 91.4% specificity, with an AUC of 0.948 (95% CI 0.898-0.978). Of 65 previously identified peptides, 60 were significantly different between cases and controls of this study. In &lt;10% of cases and controls classification by proteome analysis not entirely resulted in the expected clinical outcome. Analysis of patient's subsequent clinical course revealed later progression to DN in some of the false positive classified DN control patients. Conclusions: These data provide the first independent confirmation that profiling of the urinary proteome by CE-MS can adequately identify subjects with DN, supporting the generalizability of this approach. The data further establish urinary collagen fragments as biomarkers for diabetes-induced renal damage that may serve as earlier and more specific biomarkers than the currently used urinary albumin

A Targeted Multiomics Approach to Identify Biomarkers Associated with Rapid eGFR Decline in Type 1 Diabetes

Background: Individuals with type 1 diabetes (T1D) demonstrate varied trajectories of estimated glomerular filtration rate (eGFR) decline. The molecular pathways underlying rapid eGFR decline in T1D are poorly understood, and individual-level risk of rapid eGFR decline is difficult to predict. Methods: We designed a case-control study with multiple exposure measurements nested within 4 well-characterized T1D cohorts (FinnDiane, Steno, EDC, and CACTI) to identify biomarkers associated with rapid eGFR decline. Here, we report the rationale for and design of these studies as well as results of models testing associations of clinical characteristics with rapid eGFR decline in the study population, upon which "omics" studies will be built. Cases (n = 535) and controls (n = 895) were defined as having an annual eGFR decline of >= 3 andPeer reviewe

Progression to microalbuminuria in type 1 diabetes: development and validation of a prediction rule

AIMS/HYPOTHESIS: Microalbuminuria is common in type 1 diabetes and is associated with an increased risk of renal and cardiovascular disease. We aimed to develop and validate a clinical prediction rule that estimates the absolute risk of microalbuminuria. METHODS: Data from the European Diabetes Prospective Complications Study (n = 1115) were used to develop the prediction rule (development set). Multivariable logistic regression analysis was used to assess the association between potential predictors and progression to microalbuminuria within 7 years. The performance of the prediction rule was assessed with calibration and discrimination (concordance statistic [c-statistic]) measures. The rule was validated in three other diabetes studies (Pittsburgh Epidemiology of Diabetes Complications [EDC] study, Finnish Diabetic Nephropathy [FinnDiane] study and Coronary Artery Calcification in Type 1 Diabetes [CACTI] study). RESULTS: Of patients in the development set, 13% were microalbuminuric after 7 years. Glycosylated haemoglobin, AER, WHR, BMI and ever smoking were found to be the most important predictors. A high-risk group (n = 87 [8%]) was identified with a risk of progression to microalbuminuria of 32%. Predictions showed reasonable discriminative ability, with c-statistic of 0.71. The rule showed good calibration and discrimination in EDC, FinnDiane and CACTI (c-statistic 0.71, 0.79 and 0.79, respectively). CONCLUSIONS/INTERPRETATION: We developed and validated a clinical prediction rule that uses relatively easily obtainable patient characteristics to predict microalbuminuria in patients with type 1 diabetes. This rule can help clinicians to decide on more frequent check-ups for patients at high risk of microalbuminuria in order to prevent long-term chronic complication