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Diabet Med. 2018 Nov 30. doi: 10.1111/dme.13872. [Epub ahead of print]

The association between vascular complications during pregnancy in women with Type 1 diabetes and congenital malformations.

Author information

1
Department of Medicine, University of Calgary, Calgary Alberta, Canada.
2
Department of Obstetrics and Gynecology, University of Calgary, Calgary Alberta, Canada.
3
Department of Community Health Sciences, University of Calgary, Calgary Alberta, Canada.
4
Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary Alberta, Canada.
5
Alberta Perinatal Health Program, Alberta Health Services, Calgary Alberta, Canada.
6
Libin Cardiovascular Institute, Calgary Alberta, Canada.
7
O'Brien Institute for Public Health, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.

Abstract

AIMS:

To assess the association between vascular complications of diabetes and the risk of congenital malformations in pregnant women with Type 1 diabetes.

METHODS:

We conducted an observational retrospective cohort study in women with Type 1 diabetes who received care consecutively from three tertiary care diabetes-in-pregnancy clinics in Calgary, Alberta, Canada. Multivariable logistic regression was used to assess the association between vascular complications (retinopathy, nephropathy and pre-existing hypertension) and congenital malformations in offspring of women with Type 1 diabetes.

RESULTS:

Of 232 women with Type 1 diabetes, 49 (21%) had at least one vascular complication and there were 52 babies with congenital malformations. Maternal age (31.8 ± 5.0 vs. 29.4 ± 4.7 years, P < 0.01), diabetes duration (20.9 ± 6.7 vs. 11.2 ± 7.4 years, P < 0.01) and pre-eclampsia rate (12.5% vs. 1.3%, P < 0.01) were higher in mothers with vascular complications than in those without. Multivariable analyses showed that vascular complications were not associated with an increased risk of congenital malformations (odds ratio 1.16, 95% confidence interval 0.46 to 2.88).

CONCLUSIONS:

Vascular complications are common, occurring in one-fifth of pregnant women with Type 1 diabetes, and in this study do not appear to be associated with an increased risk of congenital malformations in children.

PMID:
30499197
DOI:
10.1111/dme.13872
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4.
Diabet Med. 2018 Nov 28. doi: 10.1111/dme.13871. [Epub ahead of print]

Two for one? Effects of a couples intervention on partners of persons with Type 2 diabetes: a randomized controlled trial.

Author information

1
Department of Psychiatry & Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA.
2
Department of Medicine, SUNY Upstate Medical University, Syracuse, NY, USA.
3
Department of Family Medicine, University of California, San Francisco, CA, USA.
4
School of Family Life, Brigham Young University, Provo, UT, USA.
5
Department of Public Health & Preventive Medicine, SUNY Upstate Medical University, Syracuse, NY, USA.

Abstract

AIMS:

To compare the outcomes of partners who participated in a telephone couples behavioural intervention to improve glycaemic control in persons with Type 2 diabetes with those of untreated partners of participants in an individual intervention or education; to explore 'ripple effects', i.e. positive behaviour changes seen in untreated partners.

METHODS:

The Diabetes Support Project was a three-arm randomized telephone intervention trial comparing outcomes of couples calls (CC), individual calls (IC) and diabetes education calls (DE). Couples included one partner with Type 2 diabetes and HbA1c ≥ 58 mmol/mol (7.5%). All arms received self-management education (two calls). CC and IC arms participated in 10 additional behaviour change calls. CC included partners, emphasizing partner communication, collaboration and support. Blinded assessments were performed at 4, 8 and 12 months. Partner outcomes were psychosocial (diabetes distress, relationship satisfaction, depressive symptoms), medical (BMI, blood pressure) and behavioural (fat intake, activity).

RESULTS:

Partners' (N = 268) mean age was 55.8 years, 64.6% were female and 29.9% were from minority ethnic groups. CC (vs. IC and DE) partners had greater reductions in diabetes distress, greater increases in marital satisfaction (4 and 8 months), and some improvements in diastolic BP. There were no consistent differences among arms in other outcomes. There was no evidence of a dietary or activity behaviour ripple effect on untreated partners, i.e. comparing partners in the IC and DE arms.

CONCLUSIONS:

A collaborative couples intervention resulted in significant improvements in partner diabetes distress and relationship satisfaction. There were no consistent effects on behavioural or medical partner outcomes, and no evidence of diet or activity behaviour ripple effects, suggesting that partners should be targeted directly to achieve these changes. (Clinical Trial Registry No: NCT01017523).

PMID:
30485516
DOI:
10.1111/dme.13871
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5.
Diabet Med. 2018 Nov 26. doi: 10.1111/dme.13870. [Epub ahead of print]

Utility of HbA1c assessment in people with diabetes awaiting liver transplantation.

Author information

1
Medical School, University of Birmingham, Birmingham.
2
Clinical Laboratory Services, University Hospitals Birmingham NHS Foundation Trust, Birmingham.
3
Diabetes Translational Research Group, Diabetes Centre, Queen Elizabeth Hospital, University Hospitals Birmingham NHS Foundation Trust, Birmingham.
4
Institute of Translational Medicine, University Hospitals Birmingham NHS Foundation Trust, Birmingham.
5
Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham.
6
Mammalian Genetics Unit, Medical Research Council Harwell Institute, Harwell.
7
Gloucester Retinopathy Research Group, Gloucestershire Hospitals NHS Foundation Trust, Cheltenham.
8
Leeds Liver Unit,, St James's University Hospital, Leeds.
9
Diabetes Research Group, Swansea University, Swansea, UK.
10
HRB-Clinical Research Facility, University College Cork, Cork, Ireland.

Abstract

AIMS:

To investigate the relationship between HbA1c and glucose in people with co-existing liver disease and diabetes awaiting transplant, and in those with diabetes but no liver disease.

METHODS:

HbA1c and random plasma glucose data were collected for 125 people with diabetes without liver disease and for 29 people awaiting liver transplant with diabetes and cirrhosis. The median (interquartile range) Model for End Stage Liver Disease score for the study cohort was calculated as 12 (9-17; normal <6). In those with cirrhosis, this was caused by non-alcoholic fatty liver disease, hepatitis C, alcoholic liver disease, hereditary haemochromatosis, polycystic liver/kidneys, cryptogenic/non-cirrhotic portal hypertension and α-1-antitrypsin-related disease.

RESULTS:

The median (interquartile range) age of the diabetes with cirrhosis group was 55 (49-63) years compared to 60 (50-71) years (P=0.13) in the group without cirrhosis. In the diabetes with cirrhosis group there were 21 men (72%) compared with 86 men (69%) in the group with diabetes and no cirrhosis (P=0.82). Of the group with diabetes and cirrhosis, 27 people (93%) were of white European ethnicity, two (7%) were South Asian and none was of Afro-Caribbean/other ethnicity compared with 94 (75%), 16 (13%), 10 (8%)/5 (4%), respectively, in the group with diabetes and no cirrhosis (P=0.20). The median (interquartile range) HbA1c concentrations were 41 (32-56) mmol/mol [5.9 (5.1-7.3)]% vs 61 (52-70) mmol/mol [7.7 (6.9-8.6)%; P<0.001], respectively, in the diabetes with cirrhosis group vs the diabetes without cirrhosis group and the glucose concentrations were 8.4 (7.0-11.2) mmol/l vs 7.3 (5.2-11.5) mmol/l (P=0.17). HbA1c concentration was depressed by 20 mmol/mol (1.8%; P<0.001) in 28 participants with cirrhosis but elevated by 28 mmol/mol (2.6%) in the participant with α-1-antitrypsin disorder. Those with cirrhosis and depressed HbA1c concentrations had fewer larger erythrocytes, and higher red cell distribution width and reticulocyte count. This was reflected in the positive association of glucose with mean cell volume (r=0.39) and haemoglobin level (r=0.49) and the negative association for HbA1c concentration (r=-0.28 and r=-0.26, respectively) in the diabetes group.

CONCLUSION:

HbA1c is not an appropriate test for blood glucose in people with cirrhosis and diabetes awaiting transplant as it reflects altered erythrocyte presentation. This article is protected by copyright. All rights reserved.

PMID:
30474191
DOI:
10.1111/dme.13870
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6.
Diabet Med. 2018 Nov 25. doi: 10.1111/dme.13868. [Epub ahead of print]

The unmet need for better risk stratification of non-proliferative diabetic retinopathy.

Author information

1
Moorfields Eye Hospital, London, UK.
2
University College London, London, UK.

Abstract

Diabetic retinopathy is a common microvascular complication of diabetes and remains one of the leading causes of preventable blindness in working-age people. Non-proliferative diabetic retinopathy is the earliest stage of diabetic retinopathy and is typically asymptomatic. Currently, the severity of diabetic retinopathy is assessed using semi-quantitative grading systems based on the presence or absence of retinal lesions. These methods are well validated, but do not predict those at high risk of rapid progression to sight-threatening diabetic retinopathy; therefore, new approaches for identifying these people are a current unmet need. We evaluated published data reporting the lesion characteristics associated with different progression profiles in people with non-proliferative diabetic retinopathy. Based on these findings, we propose that additional assessments of features of non-proliferative diabetic retinopathy lesions may help to stratify people based on the likelihood of rapid progression. In addition to the current classification, the following measurements should be considered: the shape and size of lesions; whether lesions are angiogenic in origin; the location of lesions, including predominantly peripheral lesions; and lesion turnover and dynamics. For lesions commonly seen in hypertensive retinopathy, a detailed assessment of potential concomitant diseases is also recommended. We believe that natural history studies of these changes will help characterize these non-proliferative diabetic retinopathy progression profiles and advance our understanding of the pathogenesis of diabetic retinopathy in order to individualize management of people with diabetic retinopathy.

PMID:
30474144
DOI:
10.1111/dme.13868
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7.
Diabetes. 2018 Nov 28. pii: db180567. doi: 10.2337/db18-0567. [Epub ahead of print]

Multiethnic Genome-wide Association Study of Diabetic Retinopathy using Liability Threshold Modeling of Duration of Diabetes and Glycemic Control.

Author information

1
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.
2
Department of Population and Quantitative Health Sciences, Case Western University, Cleveland, OH.
3
Cardiovascular Health Research Unit, Department of Medicine, Epidemiology and Health Services, University of Washington, Seattle, WA.
4
Institute for Translational Genomics and Population Sciences, LABioMed and Department of Pediatrics at Harbor-UCLA Medical Center, Torrance, CA.
5
Duke-NUS Medical School, Singapore.
6
Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
7
Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC.
8
Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC.
9
Department of Medicine, University of Iceland, Reykjavík, Iceland.
10
Department of Ophthalmology, Harvard Medical School, Massachusetts Eye and Ear Infirmary, Boston, MA.
11
Medical Affairs, Ophthalmology, Sun Pharmaceutical Industries, Inc, Princeton, NJ.
12
Division of Population Health Sciences, Ninewells Hospital and Medical School, University of Dundee School of Medicine, Scotland, UK.
13
Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada ᵎCurrently at: Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA.
14
Laboratory for Endocrinology, Metabolism and Kidney Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.
15
Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara, Japan.
16
Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Nishihara, Japan.
17
Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA.
18
Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX.
19
Department of Ophthalmology, Seoul National University College of Medicine, SMG-SNU Boramae Medical Center, Seoul, Korea.
20
Endocrine Unit, Diabetes Unit, Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA.
21
Section of Genetic Medicine, The University of Chicago, Chicago, IL.
22
Department of Ophthalmology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Korea.
23
Section of Diabetes and Metabolism, Harbor-UCLA Medical Center, University of California, Los Angeles, Los Angeles County, CA.
24
Department of Nephrology and Hypertension, Los Angeles Biomedical Research Institute at Harbor-University of California, Torrance, CA.
25
Department of Medicine, Case Western Reserve University, Cleveland, OH.
26
Department of Physiology and Biophysics, Case Western Reserve University, Cleveland, OH.
27
Division of Nephrology, MetroHealth System, Cleveland, OH.
28
Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC.
29
Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan.
30
School of Medicine, Chung Shan Medical University, Taichung, Taiwan.
31
School of Medicine, National Yang-Ming University, Taipei, Taiwan.
32
School of Medicine, National Defense Medical Center, Taipei, Taiwan.
33
RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan.
34
Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Kanagawa 230-0045, Japan.
35
National Cerebral and Cardiovascular Center, Research Institute, Department of Genomic Medicine, Osaka 565-8565, Japan.
36
CHU de Poitiers, Centre d'Investigation Clinique, Poitiers, France.
37
Université de Poitiers, UFR Médecine Pharmacie, CIC1402, Poitiers, France.
38
INSERM, CIC1402, Poitiers, France.
39
L'Institut du Thorax, INSERM, CNRS, CHU Nantes, Nantes, France.
40
Université Paris Diderot, Sorbonne Paris Cité, Paris, France.
41
Diabetology, Endocrinology and Nutrition Department, DHU FIRE, Bichat Hospital, AP-HP, Paris, France.
42
INSERM U1138, Centre de Recherche des Cordeliers, Paris, France.
43
Sorbonne Université, UPMC Univ. Paris 06, INSERM, UMR_S 1166, Team Genomics & Pathophysiology of Cardiovascular Diseases, Paris, France.
44
ICAN Institute for Cardiometabolism and Nutrition, Paris, France.
45
USC Roski Eye Institute, Department of Ophthalmology, Keck School of Medicine of the University of Southern California, Los Angeles, CA.
46
Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Old Road, Headington, Oxford, OX3 7LJ UK.
47
Wellcome Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK.
48
Oxford NIHR Biomedical Research Centre, Churchill Hospital, Old Road, Headington, Oxford, OX3 7LJ UK.
49
Department of Clinical Sciences, Faculty of Medicine, Lund University, Malmo, Sweden.
50
Department of Clinical Science, KG Jebsen Center for Diabetes Research, University of Bergen, Norway.
51
The Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK, EH8 9AG.
52
Molecular and Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, DD1 9SY, UK.
53
Institute of Genetics and Molecular Medicine,Western General Hospital,Crewe Road,University of Edinburgh, Edinburgh, UK,EH4 2XUT.
54
Folkhälsan Institute of Genetics, Folkhälsan Research Center, 00290, Helsinki, Finland.
55
Abdominal Center, Nephrology, University of Helsinki and Helsinki University Hospital, 00290, Helsinki, Finland.
56
Research Programs Unit, Diabetes and Obesity, University of Helsinki, 00290, Helsinki, Finland.
57
Department of Diabetes, Central Clinical School, Monash University, Melbourne, Victoria, Australia.
58
Department of Preventive Medicine, John D. Bower School of Population Health, University of Mississippi Medical Center, Jackson, MS.
59
Department of Ophthalmology, University of Mississippi Medical Center, Jackson, MS ᵎCurrently at: Retina Center, North Mississippi Medical Center, Tupelo, MS.
60
Centre for Vision Research, Westmead Institute for Medical Research, University of Sydney, Sydney, Australia.
61
Department of Ophthalmology, Flinders University, Bedford Park SA, Australia.
62
Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD.
63
Institute of Medical Sciences, University of Toronto, Toronto, Canada.
64
Program in Genetics and Genome Biology Hospital for Sick Children's, Toronto, Ontario, Canada.
65
Epidemiology & Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.
66
Grassi Retina, Naperville, IL.
67
Department of Ophthalmology and Visual Sciences, University of Illinois at Chicago, 1012 95th St., Suite 9, Chicago, IL.
68
Pat MacPherson Centre for Pharmacogenetics and Pharmacogenomics, University of Dundee, Ninewells Hospital and Medical School, Dundee, UK.
69
Genentech Inc., South San Francisco, CA.
70
Institute for Urban Health, New York Academy of Medicine, New York City, New York.
71
Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia.
72
Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
73
Department of Ophthalmology and Visual Sciences, University of Wisconsin-Madison, Madison, WI.
74
Department of Ophthalmology, Harvard Medical School, Massachusetts Eye and Ear Infirmary, Boston, MA Lucia_Sobrin@meei.harvard.edu.

Abstract

To identify genetic variants associated with diabetic retinopathy (DR), we performed a large, multiethnic genome-wide association study (GWAS). Discovery included eight European cohorts (n = 3,246) and seven African American cohorts (n = 2,611). We meta-analyzed across cohorts using inverse-variance weighting, with and without liability threshold modeling of glycemic control and duration of diabetes. Variants with a P value < 1 X 10-5 were investigated in replication cohorts that included 18,545 Europeans, 16,453 Asians and 2,710 Hispanics. After correction for multiple testing, the C allele of rs142293996 in an intron of nuclear VCP-like (NVL) was associated with DR in European discovery cohorts (P = 2.1 x 10-9), but did not reach genome-wide significance after meta-analysis with replication cohorts. We applied the Disease Association Protein-Protein Link Evaluator (DAPPLE) to our discovery results to test for evidence of risk being spread across underlying molecular pathways. One protein-protein interaction network built from genes in regions associated with proliferative DR (PDR) was found to have significant connectivity (P=0.0009) and corroborated with gene set enrichment analyses. These findings suggest that genetic variation in NVL, as well as variation within a protein-protein interaction network that includes genes implicated in inflammation, may influence risk for DR.

PMID:
30487263
DOI:
10.2337/db18-0567
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8.
Diabetes. 2018 Nov 28. pii: db180525. doi: 10.2337/db18-0525. [Epub ahead of print]

Dynamic Contrast-Enhanced Magnetic Resonance Imaging of OATP Dysfunction in Diabetes.

Author information

1
Department of Radiology, Michigan State University, East Lansing, MI.
2
Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, MI.
3
Department of Comparative Medicine and Integrative Biology Program, Michigan State University, East Lansing, MI.
4
Department of Pharmacology, Toxicology, and Therapeutics, University of Kansas Medical Center, Kansas City, MO.
5
Department of Radiology, Michigan State University, East Lansing, MI erik.shapiro@rad.msu.edu.

Abstract

Diabetes mellitus is associated with hepatic metabolic dysfunction predisposing patients to drug induced liver injury. Mouse models of Type 2 diabetes (T2D) have dramatically reduced expression of Organic Anion Transporting Polypeptide (OATP) 1A1, a transporter expressed in hepatocytes and in the kidneys. Effects of diabetes on OATP1B2 expression are less studied and less consistent. OATP1A1 and OATP1B2 both transport endogenous substrates such as bile acids and hormone-conjugates as well as numerous drugs including Gd-EOB-DTPA. As master pharmacokinetic regulators, altered expression of OATPs in diabetes mellitus could have a profound and clinically significant influence on drug therapies. Here, we report a method to non-invasively measure OATP activity in T2D mice by quantifying the transport of hepatobiliary-specific gadolinium based contrast agents (GBCAs) within the liver and kidneys using dynamic contrast enhanced MRI (DCE-MRI). By comparing GBCA uptake in control and OATP knockout mice, we confirmed liver clearance of the hepatobiliary-specific GBCAs, Gd-EOB-DTPA and Gd-BOPTA, primarily though OATP transporters. Then, we measured a reduction in the hepatic uptake of these hepatobiliary GBCAs in T2D ob/ob mice, which mirrored significant reductions in the mRNA and protein expression of OATP1A1 and OATP1B2. As these GBCAs are FDA approved agents and DCE-MRI is a standard clinical protocol, studies to determine OATP1B1/1B3 deficiencies in human diabetics can be easily envisioned.

PMID:
30487262
DOI:
10.2337/db18-0525
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9.
Diabetes Care. 2018 Nov 28. pii: dc181491. doi: 10.2337/dc18-1491. [Epub ahead of print]

Inclisiran Lowers LDL-C and PCSK9 Irrespective of Diabetes Status: The ORION-1 Randomized Clinical Trial.

Author information

1
Division of Endocrinology and Metabolism, Li Ka Shing Knowledge Institute of St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada leiterl@smh.ca.
2
Division of Endocrinology and Metabolism, Li Ka Shing Knowledge Institute of St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada.
3
Division of Cardiac Surgery, Keenan Research Centre for Biomedical Science and Li Ka Shing Knowledge Institute of St. Michael's Hospital, Toronto, Ontario, Canada.
4
The Medicines Company, Parsippany, NJ.
5
Department of Cardiology, Mayo Clinic, Rochester, MN.
6
Department of Cardiology, Charité-Universitätsmedizin Berlin, Berlin Institute of Health and German Center for Cardiovascular Research, Partner Site Berlin, Berlin, Germany.
7
Department of Vascular Medicine, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands.
8
Department of Primary Care and Public Health, Imperial Centre for Cardiovascular Disease Prevention, Imperial College London, London, U.K.

Abstract

OBJECTIVE:

To evaluate the efficacy and safety of inclisiran by diabetes status.

RESEARCH DESIGN AND METHODS:

ORION-1 (ClinicalTrials.gov, NCT02597127) randomized 501 subjects with atherosclerotic cardiovascular disease (ASCVD) or ASCVD risk equivalents and high LDL cholesterol (LDL-C), despite maximally tolerated LDL-C-lowering therapies, to one or two doses of placebo or inclisiran. Levels of lipids and proprotein convertase subtilisin/kexin type 9 (PCSK9) at baseline and day 180 were compared.

RESULTS:

Inclisiran was associated with marked declines in LDL-C (median -28% to -52%, P < 0.0001 and -28% to -55%, P < 0.005 for all doses in the without- and with-diabetes groups, respectively) and PCSK9. The inclisiran-treated groups also had lower apolipoprotein B, non-HDL cholesterol, and lipoprotein(a) but higher HDL cholesterol. Inclisiran had an adverse profile similar to that of placebo, and adverse events were proportionally balanced in the baseline with- and without-diabetes groups.

CONCLUSIONS:

PCSK9-targeted siRNA-driven strategies may provide a novel therapeutic option for managing dyslipidemia in the presence and absence of diabetes.

PMID:
30487231
DOI:
10.2337/dc18-1491
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10.
Diabetes Care. 2018 Nov 28. pii: dc181258. doi: 10.2337/dc18-1258. [Epub ahead of print]

Real-World Database Examining the Association Between Avascular Necrosis of the Femoral Head and Diabetes in Taiwan.

Lai SW1,2, Lin CL3,4, Liao KF5,6.

Author information

1
College of Medicine, China Medical University, Taichung, Taiwan kuanfuliaog@gmail.com.
2
Department of Family Medicine, China Medical University Hospital, Taichung, Taiwan.
3
College of Medicine, China Medical University, Taichung, Taiwan.
4
Management Office for Health Data, China Medical University Hospital, Taichung, Taiwan.
5
College of Medicine, Tzu Chi University, Hualien, Taiwan kuanfuliaog@gmail.com.
6
Division of Hepatogastroenterology, Department of Internal Medicine, Taichung Tzu Chi Hospital, Taichung, Taiwan.

Abstract

OBJECTIVE:

No study has been conducted to evaluate the association between avascular necrosis of the femoral head and diabetes. This study's aim was to assess this issue in Taiwan.

RESEARCH DESIGN AND METHODS:

A population-based cohort study was performed to analyze the database of Taiwan's National Health Insurance Program. There were 27,869 subjects aged 20-84 years with newly diagnosed diabetes from 2000 to 2012 as the group with diabetes. The group without diabetes included 111,476 sex- and age-matched subjects without diabetes. The incidence of avascular necrosis of the femoral head at the end of 2013 was measured. A multivariable Cox proportional hazards regression model was used to measure the hazard ratio (HR) and 95% CI for avascular necrosis of the femoral head associated with diabetes.

RESULTS:

The overall incidence of avascular necrosis of the femoral head was 1.37-fold higher in the group with diabetes than in the group without diabetes (6.53 vs. 4.76 per 1,000 person-years [95% CI 1.31-1.43]). After adjusting for confounders, the HR of avascular necrosis of the femoral head was 1.16 (95% CI 1.11-1.21) for the subjects with diabetes compared with the subjects without diabetes.

CONCLUSIONS:

Patients with diabetes have a 1.16-fold increased risk for developing avascular necrosis of the femoral head.

PMID:
30487230
DOI:
10.2337/dc18-1258
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11.
Diabetes Care. 2018 Nov 27. pii: dc181527. doi: 10.2337/dc18-1527. [Epub ahead of print]

Serum Uromodulin Predicts Less Coronary Artery Calcification and Diabetic Kidney Disease Over 12 years in Adults With Type 1 Diabetes: The CACTI Study.

Author information

1
Department of Pediatric Endocrinology, University of Colorado School of Medicine, Aurora, CO petter.bjornstad@childrenscolorado.org.
2
Barbara Davis Center for Diabetes, University of Colorado Denver, Aurora, CO.
3
Department of Pediatric Endocrinology, University of Colorado School of Medicine, Aurora, CO.
4
Department of Medicine, Division of Nephrology, and Department of Physiology, University of Toronto, Ontario, Canada.
5
Department of Nephrology, University of Colorado School of Medicine, Aurora, CO.

Abstract

OBJECTIVE:

Novel biomarkers are needed to better predict coronary artery calcification (CAC), a marker of subclinical atherosclerosis, and diabetic kidney disease (DKD) in type 1 diabetes. We evaluated the associations between serum uromodulin (SUMOD [a biomarker associated with anti-inflammatory and renal protective properties]), CAC progression and DKD development over 12 years.

RESEARCH DESIGN AND METHODS:

Participants (n = 527, 53% females) in the Coronary Artery Calcification in Type 1 Diabetes (CACTI) study were examined during 2002-2004, at a mean age of 39.6 ± 9.0 years and a median duration of diabetes of 24.8 years. Urine albumin-to-creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) determined by the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) creatinine equation were measured at baseline and after a mean follow-up period of 12.1 ± 1.5 years. Elevated albumin excretion was defined as ACR ≥30 mg/g, rapid GFR decline (>3 mL/min/1.73 m2/year), and impaired GFR as eGFR <60 mL/min/1.73 m2. SUMOD was measured on stored baseline plasma samples (Meso Scale Diagnostics). CAC was measured using electron beam computed tomography. CAC progression was defined as a change in the square root-transformed CAC volume of ≥2.5.

RESULTS:

Higher baseline SUMOD level conferred lower odds of CAC progression (odds ratio 0.68; 95% CI 0.48-0.97) per 1 SD increase in SUMOD (68.44 ng/mL), incident elevated albumin excretion (0.37; 0.16-0.86), rapid GFR decline (0.56, 0.35-0.91), and impaired GFR (0.44; 0.24-0.83) after adjustment for baseline age, sex, systolic blood pressure, LDL, albuminuria/GFR. The addition of SUMOD to models with traditional risk factors also significantly improved the prediction performance for CAC progression and incident DKD.

CONCLUSIONS:

Higher baseline SUMOD level predicted lower odds of both CAC progression and incident DKD over 12 years in adults with type 1 diabetes.

PMID:
30482755
DOI:
10.2337/dc18-1527
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12.
J Clin Endocrinol Metab. 2018 Nov 21. doi: 10.1210/jc.2018-02064. [Epub ahead of print]

Early Clinical Indicators of Addison's Disease in Adults with Type 1 Diabetes: a Nationwide, Observational, Cohort Study.

Author information

1
Department of Internal Medicine and Clinical Nutrition, Institute of Medicine at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
2
Department of Endocrinology-Diabetes-Metabolism, Sahlgrenska University Hospital, Gothenburg, Sweden.
3
National Diabetes Register, Centre of Registers, Department of Medicine, University of Gothenburg, Gothenburg, Sweden.

Abstract

Context:

Patients with type 1 diabetes mellitus (T1DM) have an increased risk of Addison's disease (AD) development but prediction of those at risk is not possible.

Objective:

To determine whether there are early clinical indicators that may denote the development of AD in adults with T1DM.

Design:

Observational, matched-cohort study.

Setting:

Patient data from Swedish national registries (National Diabetes Register [NDR], Inpatient Register, Prescription Drug Register).

Participants:

All T1DM patients diagnosed with concomitant AD (n=66) among the 36,514 adult patients with T1DM in the NDR between 1998-2013. Each case was matched to five controls with T1DM alone (n=330).

Main outcome measures:

Clinical data and drug prescriptions were assessed prior to baseline (inclusion into the study) and prior to AD diagnosis. Analysis of covariance and estimated group proportions were used for comparisons.

Results:

Prior to baseline, cases had a higher frequency of thyroid/antithyroid drug prescription than controls (9.1% vs 1.8%). Prior to AD diagnosis, cases had higher frequencies of diabetic retinopathy (12.1% vs 2.1%), infections requiring hospital admission (16.7% vs 2.1%), thyroid/antithyroid drug prescription (28.8% vs 7.0%), and glucagon prescription (18.2% vs 6.4%). There was no difference in glycated hemoglobin between the groups prior to baseline or prior to AD diagnosis.

Conclusions:

These data suggest that medical treatment for thyroid disease, a severe infection, and glucagon prescription for severe hypoglycemia should raise the suspicion of AD development in adults with T1DM. Development of diabetic retinopathy might also be associated with glucocorticoid deficiency and the development of AD among patients with T1DM.

13.
Transplant Proc. 2018 Dec;50(10):3381-3385. doi: 10.1016/j.transproceed.2018.08.007. Epub 2018 Aug 9.

Incidence and Risk Factors of Posttransplantation Diabetes Mellitus in Living Donor Kidney Transplantation: A Single-Center Retrospective Study in China.

Author information

1
Medical School of Chinese People's Liberation Army, the Chinese People's Liberation Army General Hospital, Beijing, China; Organ Transplant Institute of People's Liberation Army, Beijing Key Laboratory of Immunology Regulatory and Organ Transplantation, the 309th Hospital of People's Liberation Army, Beijing, China.
2
Organ Transplant Institute of People's Liberation Army, Beijing Key Laboratory of Immunology Regulatory and Organ Transplantation, the 309th Hospital of People's Liberation Army, Beijing, China.
3
Medical School of Chinese People's Liberation Army, the Chinese People's Liberation Army General Hospital, Beijing, China; Organ Transplant Institute of People's Liberation Army, Beijing Key Laboratory of Immunology Regulatory and Organ Transplantation, the 309th Hospital of People's Liberation Army, Beijing, China. Electronic address: caiming2002@hotmail.com.

Abstract

BACKGROUND:

Posttransplantation diabetes mellitus (PTDM) is a frequent metabolic complication following solid organ transplantation and was proven to be associated with adverse outcome. This study aimed to identify the incidence and risk factors of PTDM under the background of relative-living renal transplantation in China.

METHODS:

We conducted a retrospective cohort study that included 358 recipients who underwent relative-living donor kidney transplantation in the Organ Transplant Institute of 309th Hospital of People's Liberation Army between January 1, 2010, and December 31, 2014. PTDM was defined based on American Diabetes Association criteria. Demographics and laboratory results were compared between patients with PTDM and non-PTDM; multivariate analysis was performed using a logistic regression model.

RESULTS:

One hundred ten out of a total of 358 recipients were diagnosed with PTDM (30.72%) within 3 years after transplantations. Seven risk factors for PTDM were identified in multivariate analysis: body mass index ≥25 (odds ratio [OR] 1.905, 95% confidence interval [CI]: 1.114-3.258), family history of diabetes (OR 1.898, CI: 1.051-3.258), hypomagnesemia pretransplantation (OR 1.871, CI: 1.133-3.092), acute rejection episodes in 3 months posttransplantation (OR 2.312, CI: 1.015-5.268), tacrolimus use (OR 1.952, CI: 1.169-3.258), impaired fasting glucose diagnosed pretransplantation (OR 1.807, CI: 1.091-2.993), and hyperglycemia in the first week posttransplantation (OR 1.856, CI: 1.133-3.043).

CONCLUSION:

Our study suggests high body mass index, family diabetes history, hypomagnesemia pretransplantation, acute rejection episodes within the first 3 months after transplantation, tacrolimus use, impaired fasting glucose diagnosed pretransplantation, and hyperglycemia within the first week after transplantation are independent risk factors of PTDM in relative-living donor transplantation.

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