Use of the Michigan Neuropathy Screening Instrument as a measure of distal symmetrical peripheral neuropathy in Type 1 diabetes: results from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications

Aims  The Michigan Neuropathy Screening Instrument (MNSI) is used to assess distal symmetrical peripheral neuropathy in diabetes. It includes two separate assessments: a 15‐item self‐administered questionnaire and a lower extremity examination that includes inspection and assessment of vibratory sensation and ankle reflexes. The purpose of this study was to evaluate the performance of the MNSI in detecting distal symmetrical peripheral neuropathy in patients with Type 1 diabetes and to develop new scoring algorithms. Methods  The MNSI was performed by trained personnel at each of the 28 Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications clinical sites. Neurologic examinations and nerve conduction studies were performed during the same year. Confirmed clinical neuropathy was defined by symptoms and signs of distal symmetrical peripheral neuropathy based on the examination of a neurologist and abnormal nerve conduction findings in ≥ 2 anatomically distinct nerves among the sural, peroneal and median nerves. Results  We studied 1184 subjects with Type 1 diabetes. Mean age was 47 years and duration of diabetes was 26 years. Thirty per cent of participants had confirmed clinical neuropathy, 18% had ≥ 4 and 5% had ≥ 7 abnormal responses on the MNSI questionnaire, and 33% had abnormal scores (≥ 2.5) on the MNSI examination. New scoring algorithms were developed and cut points defined to improve the performance of the MNSI questionnaire, examination and the combination of the two. Conclusions  Altering the cut point to define an abnormal test from ≥ 7 abnormal to ≥ 4 abnormal items improves the performance of the MNSI questionnaire. The MNSI is a simple, non‐invasive and valid measure of distal symmetrical peripheral neuropathy in Type 1 diabetes.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/92152/1/j.1464-5491.2012.03644.x.pd

Genetic insights into resting heart rate and its role in cardiovascular disease

Funding Information: We thank all participants for their participation and valuable contributions. This research has been conducted using the UK Biobank Resource under application number 12010. The work of N.V. was supported by NWO VENI grant 016.186.125. We thank 23andMe and the 23andMe Research Team for their contribution sharing their data and performing the GWAS analysis in the 23andMe cohort. P.V. received an unrestricted grant from GlaxoSmithkline to build the CoLaus study. N.J.T. is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215-2001), the MRC Integrative Epidemiology Unit (MC_UU_00011/1) and works within the CRUK Integrative Cancer Epidemiology Program (C18281/A29019). A detailed list of acknowledgements and funding is provided in Supplementary Data per cohort. We also thank all individuals that contributed to the generation of software programs, algorithms and genetic summary statistics. Support for title page creation and format was provided by AuthorArranger, a tool developed at the National Cancer Institute. Authors involved in the funding of the cohorts are listed below. Meta-analyses, Lifelines, PREVEND, UK Biobank: P.v.d.H.; ADDITION-PRO: T.H.; ADVANCE: C.I.; ADVANCE: T.A.; AGES: L.Launer, V.G.; ASCOT: P.Sever, P.B.M.; BC1936: N.G.; BioMe: E.P.B., R.J.F.L.; BRIGHT: P.B.M.; CHS: B.M.P.; CoLaus: P.V.; Croatia-Korcula: O.P., C.H.; DCCT/EDIC: D.R., The DCCT/EDIC Research Group, A.D.P.; DESIR: B.B., P.F.; DGI: L.G.; EPIC-Norfolk: N.J.W.; ERF: C.M.v.D.; Fenland: N.J.W.; FINCAVAS: M.K.; Finrisk: M.P.; FUSION: M.B.; GENOA: P.A.P., S.L.R.K.; GerMIFSs: H.Schunkert, J.E.; GoDARTS: C.N.A.P; GOOD: M.L., C.O.; HBCS: J.G.E.; HERITAGE: T.R., D.C.R., C.B.; HPFS / NHS: P.K.; HRS: D.R.Weir; HYPERGENES: K.S.S., D.C.; InCHIANTI: S.Bandinelli, L.Ferrucci; INGI-CARL: M.P.C.; INGI-FVG: G.G.; JHS: A.Correa; KORA F3: T.M., S.K.; KORA S4: K.Strauch., A.P.; LOLIPOP: J.C.C., J.S.K.; LURIC: W.M.; MESA: J.I.R.; MICROS: A.H.; MPP: O.M.; J.G.S.; NBS: L.A.L.M.K.; NEO: R.d.M.; NESDA: B.W.J.H.P.; NSPHS: Å.J.; ORCADES: J.F.W.; PIVUS: L.L.; PROSPER: P.W.M., J.W.J.; SardiNIA: E.L.L.; SCES: C.Y.C.; SHIP: S.B.F., M.D.; SIMES: T.Y.W.; TRAILS: A.J.O.; TWINS: J.O.; ULSAM: A.P.M., C.Lindgren; YFS: O.T.R., T.L. Funding Information: We thank all participants for their participation and valuable contributions. This research has been conducted using the UK Biobank Resource under application number 12010. The work of N.V. was supported by NWO VENI grant 016.186.125. We thank 23andMe and the 23andMe Research Team for their contribution sharing their data and performing the GWAS analysis in the 23andMe cohort. P.V. received an unrestricted grant from GlaxoSmithkline to build the CoLaus study. N.J.T. is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215-2001), the MRC Integrative Epidemiology Unit (MC_UU_00011/1) and works within the CRUK Integrative Cancer Epidemiology Program (C18281/A29019). A detailed list of acknowledgements and funding is provided in Supplementary Data 1 per cohort. We also thank all individuals that contributed to the generation of software programs, algorithms and genetic summary statistics. Support for title page creation and format was provided by AuthorArranger, a tool developed at the National Cancer Institute. Authors involved in the funding of the cohorts are listed below. Meta-analyses, Lifelines, PREVEND, UK Biobank : P.v.d.H.; ADDITION-PRO : T.H.; ADVANCE : C.I.; ADVANCE : T.A.; AGES : L.Launer, V.G.; ASCOT : P.Sever, P.B.M.; BC1936 : N.G.; BioMe : E.P.B., R.J.F.L.; BRIGHT : P.B.M.; CHS : B.M.P.; CoLaus : P.V.; Croatia-Korcula : O.P., C.H.; DCCT/EDIC : D.R., The DCCT/EDIC Research Group, A.D.P.; DESIR : B.B., P.F.; DGI : L.G.; EPIC-Norfolk : N.J.W.; ERF : C.M.v.D.; Fenland : N.J.W.; FINCAVAS : M.K.; Finrisk : M.P.; FUSION : M.B.; GENOA : P.A.P., S.L.R.K.; GerMIFSs : H.Schunkert, J.E.; GoDARTS : C.N.A.P; GOOD : M.L., C.O.; HBCS : J.G.E.; HERITAGE : T.R., D.C.R., C.B.; HPFS / NHS: P.K.; HRS : D.R.Weir; HYPERGENES : K.S.S., D.C.; InCHIANTI : S.Bandinelli, L.Ferrucci; INGI-CARL: M.P.C.; INGI-FVG: G.G.; JHS: A.Correa; KORA F3: T.M., S.K.; KORA S4 : K.Strauch., A.P.; LOLIPOP : J.C.C., J.S.K.; LURIC : W.M.; MESA : J.I.R.; MICROS : A.H.; MPP : O.M.; J.G.S.; NBS : L.A.L.M.K.; NEO : R.d.M.; NESDA : B.W.J.H.P.; NSPHS : Å.J.; ORCADES : J.F.W.; PIVUS : L.L.; PROSPER : P.W.M., J.W.J.; SardiNIA : E.L.L.; SCES : C.Y.C.; SHIP : S.B.F., M.D.; SIMES : T.Y.W.; TRAILS : A.J.O.; TWINS : J.O.; ULSAM : A.P.M., C.Lindgren; YFS : O.T.R., T.L. Publisher Copyright: © 2023, The Author(s).Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.Peer reviewe

Prevalence of diabetic peripheral neuropathy and relation to glycemic control therapies at baseline in the BARI 2D cohort

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74968/1/j.1529-8027.2009.00200.x.pd

Practical steps to improving the management of type 1 diabetes: recommendations from the Global Partnership for Effective Diabetes Management

The Diabetes Control and Complications Trial (DCCT) led to considerable improvements in the management of type 1 diabetes, with the wider adoption of intensive insulin therapy to reduce the risk of complications. However, a large gap between evidence and practice remains, as recently shown by the Pittsburgh Epidemiology of Diabetes Complications (EDC) study, in which 30-year rates of microvascular complications in the ‘real world’ EDC patients were twice that of DCCT patients who received intensive insulin therapy. This gap may be attributed to the many challenges that patients and practitioners face in the day-to-day management of the disease. These barriers include reaching glycaemic goals, overcoming the reality and fear of hypoglycaemia, and appropriate insulin therapy and dose adjustment. As practitioners, the question remains: how do we help patients with type 1 diabetes manage glycaemia while overcoming barriers? In this article, the Global Partnership for Effective Diabetes Management provides practical recommendations to help improve the care of patients with type 1 diabetes

Impact of changes in metabolic control on progression to photocoagulation for clinically significant macular oedema:a 20 year study of type 1 diabetes

AIMS/HYPOTHESIS: Although increasing hyperglycaemia, arterial hypertension and longer duration of diabetes raise the risk of progression of diabetic retinopathy, short-term benefits in terms of improved metabolic control and lowered blood pressure have not been demonstrated. We therefore examined the effect of changes in glycaemia and arterial blood pressure on the incidence of clinically significant macular oedema in a population of diabetic patients. METHODS: We performed a retrospective review of all patients with type 1 diabetes who attended the retinopathy screening clinic at the Steno Diabetes Center from 1988 to 2008, using the endpoint referral to first photocoagulation treatment for clinically significant diabetic macular oedema. The analysis included 1,878 patients (median observation, 8 years). Changes were defined as the inter-visit change; in the case of an event the last event-free interval before referral, where the median screening interval was 6 months. RESULTS: Risk of progression to photocoagulation for macular oedema increased with duration of diabetes (p < 0.001), current HbA(1c) (p < 0.0001) and with the magnitude of changes in HbA(1c) (p = 0.0002) and systolic blood pressure (p < 0.0001) in a multiple regression model. A recent decrease of ≥0.5 percentage points or an increase in HbA(1c) of >0.5 percentage points per 6 months was associated with HRs of 3.04 and 1.28, respectively, compared with lesser changes in HbA(1c). CONCLUSIONS/INTERPRETATION: In this study, large recent changes in metabolic control and systolic blood pressure, irrespective of direction, were independent risk factors for progression to photocoagulation for diabetic macular oedema. The effects of metabolic and haemodynamic stability on diabetic retinopathy should be examined in prospective studies

Skin collagen advanced glycation endproducts (AGEs) and the long-term progression of sub-clinical cardiovascular disease in type 1 diabetes

BACKGROUND: We recently reported strong associations between eight skin collagen AGEs and two solubility markers from skin biopsies obtained at DCCT study closeout and the long-term progression of microvascular disease in EDIC, despite adjustment for mean glycemia. Herein we investigated the hypothesis that some of these AGEs (fluorescence to be reported elsewhere) correlate with long-term subclinical cardiovascular disease (CVD) measurements, i.e. coronary artery calcium score (CAC) at EDIC year 7-9 (n = 187), change of carotid intima-media thickness (IMT) from EDIC year 1 to year 6 and 12 (n = 127), and cardiac MRI outcomes at EDIC year 15-16 (n = 142). METHODS: Skin collagen AGE measurements obtained from stored specimens were related to clinical data from the DCCT/EDIC using Spearman correlations and multivariable logistic regression analyses. RESULTS: Spearman correlations showed furosine (early glycation) was associated with future mean CAC (p \u3c 0.05) and CAC \u3e0 (p = 0.39), but not with CAC score100. Glucosepane and pentosidine crosslinks, methylglyoxal hydroimidazolones (MG-H1) and pepsin solubility (inversely) correlated with IMT change from year 1 to 6(all P \u3c 0.05). Left ventricular (LV) mass (cMRI) correlated with MG-H1, and inversely with pepsin solubility (both p \u3c 0.05), while the ratio LV mass/end diastolic volume correlated with furosine and MG-H1 (both p \u3c 0.05), and highly with CML (p \u3c 0.01). In multivariate analysis only furosine (p = 0.01) was associated with CAC. In contrast IMT was inversely associated with lower collagen pepsin solubility and positively with glucosepane, CONCLUSIONS: In type 1 diabetes, multiple AGEs are associated with IMT progression in spite of adjustment for A1c implying a likely participatory role of glycation and AGE mediated crosslinking on matrix accumulation in coronary arteries. This may also apply to functional cardiac MRI outcomes, especially left ventricular mass. In contrast, early glycation measured by furosine, but not AGEs, was associated with CAC score, implying hyperglycemia as a risk factor in calcium deposition perhaps via processes independent of glycation. TRIAL REGISTRATION: Registered at Clinical trial reg. nos. NCT00360815 and NCT00360893, http://www.clinicaltrials.gov

Predictive Clinical Parameters for the Therapeutic Efficacy of Sitagliptin in Korean Type 2 Diabetes Mellitus

BackgroundSitagliptin is a highly selective dipeptidyl peptide-4 (DPP-4) inhibitor that increases blood levels of active glucagon-like peptide (GLP)-1 and glucose-dependent insulinotrophic polypeptide (GIP), resulting in increased insulin secretion. While studies conducted in other countries have indicated the efficacy and safety of using sitagliptin to treat type 2 diabetes mellitus (T2DM), its predictors of effects to sitagliptin are not well understood. Therefore, we evaluated the predictive clinical parameters for the therapeutic benefits of sitagliptin when added to an ongoing metformin or sulfonylurea therapy in Korean T2DM subjects.MethodsWe obtained data from 251 Korean T2DM subjects who had recently started taking sitagliptin as add-on therapy. Exclusion criteria included any insulin use. Changes in HbA1c (ΔHbA1c) and fasting plasma glucose (ΔFPG) were assessed by comparing baseline levels prior to sitagliptin administration to levels 12 and 24 weeks after treatment. Responders were defined as subjects who experienced decrease from baseline of >10% in ΔHbA1c or >20% in ΔFPG levels at 24 weeks.ResultsWe classified 81% of the subjects (204 out of 251) as responders. The responder group had a lower mean body mass index (23.70±2.40 vs. 26.00±2.26, P≤0.01) and were younger (58.83±11.57 years vs. 62.87±12.09 years, P=0.03) than the non-responder group.ConclusionIn Korean T2DM subjects, sitagliptin responders had lower body mass index and were younger compared to non-responders

Significance of Epicardial and Intrathoracic Adipose Tissue Volume among Type 1 Diabetes Patients in the DCCT/EDIC: A Pilot Study.

Introduction Type 1 diabetes (T1DM) patients are at increased risk of coronary artery disease (CAD). This pilot study sought to evaluate the relationship between epicardial adipose tissue (EAT) and intra-thoracic adipose tissue (IAT) volumes and cardio-metabolic risk factors in T1DM. Method EAT/IAT volumes in 100 patients, underwent non-contrast cardiac computed tomography in the Diabetes Control and Complications Trial /Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study were measured by a certified reader. Fat was defined as pixels’ density of -30 to -190 Hounsfield Unit. The associations were assessed using–Pearson partial correlation and linear regression models adjusted for gender and age with inverse probability sample weighting. Results The weighted mean age was 43 years (range 32–57) and 53% were male. Adjusted for gender, Pearson correlation analysis showed a significant correlation between age and EAT/IAT volumes (both p Conclusion T1DM patients with greater BMI, WTH ratio, weighted HbA1c level, triglyceride level and AER≥300/ESRD had significantly larger EAT/IAT volumes. Larger sample size studies are recommended to evaluate independency