Lower Circulating miR-122 Level in Patients with HNF1A Variant-Induced Diabetes Compared with Type 2 Diabetes

miR-122, the expression of which is regulated by several transcription factors, such as HNF1A, was recently reported to be associated with type 2 diabetes (T2DM) and hepatocellular carcinoma. HNF1A variants can cause diabetes and might be involved in the development of primary liver neoplasm. Differences in miR-122 expression among different types of diabetes have not been studied. This study aimed to investigate differences in serum miR-122 levels in Chinese patients with different forms of diabetes, including T2DM, type 1 diabetes (T1DM), HNF1A variant-induced diabetes (HNF1A-DM), glucokinase variant-induced diabetes (GCK-DM), and mitochondrial A3243G mutation-induced diabetes (MDM). In total, 12 HNF1A-DM patients, 24 gender-, age-, and body mass index-matched (1 : 2) T2DM patients and 24 healthy subjects were included in this study. In addition, 30 monogenic diabetes (11 GCK-DM and 19 MDM) and 17 T1DM patients were included. Fasted blood biochemistry and miR-122 were measured. The results showed that the HNF1A-DM patients had lower miR-122 levels [0.046 (0.023, 0.121)] than T2DM patients [0.165 (0.036, 0.939), P=0.02] and healthy controls [0.249 (0.049, 1.234), P=0.019]. The area under the curve of the receiver operating characteristic curve for miR-122 to discriminate HNF1A-DM and T2DM was 0.687 (95% CI: 0.52–0.86, P=0.07). There was no difference in serum miR-122 among HNF1A-DM, GCK-DM, MDM, and T1DM patients. Lower serum miR-122 is a unique feature of HNF1A-DM patients and might partially explain the increased risk for liver neoplasm and abnormal lipid metabolism in HNF1A-DM patients.

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Type 2 diabetes-related variants influence the risk of developing multiple myeloma: results from the IMMEnSE consortium

Endocrine Related Cancer ◽

10.1530/erc-15-0029 ◽

2015 ◽

Vol 22 (4) ◽

pp. 545-559 ◽

Cited By ~ 6

Author(s):

Rafael Ríos ◽

Carmen Belén Lupiañez ◽

Daniele Campa ◽

Alessandro Martino ◽

Joaquin Martínez-López ◽

...

Keyword(s):

Type 2 Diabetes ◽

Multiple Myeloma ◽

Prediction Models ◽

Disease Risk ◽

Association Studies ◽

Area Under The Curve ◽

Genome Wide Association Studies ◽

Increased Risk ◽

Stratified Analysis

Type 2 diabetes (T2D) has been suggested to be a risk factor for multiple myeloma (MM), but the relationship between the two traits is still not well understood. The aims of this study were to evaluate whether 58 genome-wide-association-studies (GWAS)-identified common variants for T2D influence the risk of developing MM and to determine whether predictive models built with these variants might help to predict the disease risk. We conducted a case–control study including 1420 MM patients and 1858 controls ascertained through the International Multiple Myeloma (IMMEnSE) consortium. Subjects carrying the KCNQ1rs2237892T allele or the CDKN2A-2Brs2383208G/G, IGF1rs35767T/T and MADDrs7944584T/T genotypes had a significantly increased risk of MM (odds ratio (OR)=1.32–2.13) whereas those carrying the KCNJ11rs5215C, KCNJ11rs5219T and THADArs7578597C alleles or the FTOrs8050136A/A and LTArs1041981C/C genotypes showed a significantly decreased risk of developing the disease (OR=0.76–0.85). Interestingly, a prediction model including those T2D-related variants associated with the risk of MM showed a significantly improved discriminatory ability to predict the disease when compared to a model without genetic information (area under the curve (AUC)=0.645 vs AUC=0.629; P=4.05×10−06). A gender-stratified analysis also revealed a significant gender effect modification for ADAM30rs2641348 and NOTCH2rs10923931 variants (Pinteraction=0.001 and 0.0004, respectively). Men carrying the ADAM30rs2641348C and NOTCH2rs10923931T alleles had a significantly decreased risk of MM whereas an opposite but not significant effect was observed in women (ORM=0.71 and ORM=0.66 vs ORW=1.22 and ORW=1.15, respectively). These results suggest that TD2-related variants may influence the risk of developing MM and their genotyping might help to improve MM risk prediction models.

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Validity of ICD-10-CM codes for determination of diabetes type for persons with youth-onset type 1 and type 2 diabetes

BMJ Open Diabetes Research & Care ◽

10.1136/bmjdrc-2018-000547 ◽

2019 ◽

Vol 7 (1) ◽

pp. e000547 ◽

Cited By ~ 9

Author(s):

Gloria C Chi ◽

Xia Li ◽

Sara Y Tartof ◽

Jeff M Slezak ◽

Corinna Koebnick ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Predictive Value ◽

Gold Standard ◽

Characteristic Curve ◽

Diabetes Type ◽

Predictive Values ◽

Icd 10

ObjectiveDiagnosis codes might be used for diabetes surveillance if they accurately distinguish diabetes type. We assessed the validity ofInternational Classification of Disease, 10th Revision, Clinical Modification(ICD-10-CM) codes to discriminate between type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) among health plan members with youth-onset (diagnosis age <20 years) diabetes.Research design and methods. Diabetes case identification and abstraction of diabetes type was done as part of the SEARCH for Diabetes in Youth Study. The gold standard for diabetes type is the physician-assigned diabetes type documented in patients’ medical records. Using all healthcare encounters with ICD-10-CM codes for diabetes, we summarized codes within each encounter and determined diabetes type using percent of encounters classified as T2DM. We chose 50% as the threshold from a receiver operating characteristic curve because this threshold yielded the largest Youden’s index. Persons with ≥50% T2DM-coded encounters were classified as having T2DM. Otherwise, persons were classified as having T1DM. We calculated sensitivity, specificity, positive and negative predictive values, and accuracy overall and by demographic characteristics.ResultsAccording to the gold standard, 1911 persons had T1DM and 652 persons had T2DM (mean age (SD): 19.1 (6.5) years). We obtained 90.6% (95% CI 88.4% to 92.9%) sensitivity, 96.3% (95% CI 95.4% to 97.1%) specificity, 89.3% (95% CI 86.9% to 91.6%) positive predictive value, 96.8% (95% CI 96.0% to 97.6%) negative predictive value, and 94.8% (95% CI 94.0% to 95.7%) accuracy for discriminating T2DM from T1DM.ConclusionsICD-10-CM codes can accurately classify diabetes type for persons with youth-onset diabetes, showing promise for rapid, cost-efficient diabetes surveillance.

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HLA Class II Allele Analyses Implicate Common Genetic Components in Type 1 and Non–Insulin-Treated Type 2 Diabetes

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/clinem/dgaa027 ◽

2020 ◽

Vol 105 (3) ◽

pp. e245-e254 ◽

Cited By ~ 1

Author(s):

Thomas Jacobi ◽

Lucas Massier ◽

Nora Klöting ◽

Katrin Horn ◽

Alexander Schuch ◽

...

Keyword(s):

Type 2 Diabetes ◽

Type 1 Diabetes ◽

Class Ii ◽

Hla Class Ii ◽

Risk Haplotype ◽

Genetic Components ◽

Hla Genotypes ◽

Increased Risk

Abstract Context Common genetic susceptibility may underlie the frequently observed co-occurrence of type 1 and type 2 diabetes in families. Given the role of HLA class II genes in the pathophysiology of type 1 diabetes, the aim of the present study was to test the association of high density imputed human leukocyte antigen (HLA) genotypes with type 2 diabetes. Objectives and Design Three cohorts (Ntotal = 10 413) from Leipzig, Germany were included in this study: LIFE-Adult (N = 4649), LIFE-Heart (N = 4815) and the Sorbs (N = 949) cohort. Detailed metabolic phenotyping and genome-wide single nucleotide polymorphism (SNP) data were available for all subjects. Using 1000 Genome imputation data, HLA genotypes were imputed on 4-digit level and association tests for type 2 diabetes, and related metabolic traits were conducted. Results In a meta-analysis including all 3 cohorts, the absence of HLA-DRB5 was associated with increased risk of type 2 diabetes (P = 0.001). In contrast, HLA-DQB*06:02 and HLA-DQA*01:02 had a protective effect on type 2 diabetes (P = 0.005 and 0.003, respectively). Both alleles are part of the well-established type 1 diabetes protective haplotype DRB1*15:01~DQA1*01:02~DQB1*06:02, which was also associated with reduced risk of type 2 diabetes (OR 0.84; P = 0.005). On the contrary, the DRB1*07:01~DQA1*02:01~DQB1*03:03 was identified as a risk haplotype in non–insulin-treated diabetes (OR 1.37; P = 0.002). Conclusions Genetic variation in the HLA class II locus exerts risk and protective effects on non–insulin-treated type 2 diabetes. Our data suggest that the genetic architecture of type 1 diabetes and type 2 diabetes might share common components on the HLA class II locus.

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Diabetes increases the risk of breast cancer: a meta-analysis

Endocrine Related Cancer ◽

10.1530/erc-12-0242 ◽

2012 ◽

Vol 19 (6) ◽

pp. 793-803 ◽

Cited By ~ 58

Author(s):

Prue J Hardefeldt ◽

Senarath Edirimanne ◽

Guy D Eslick

Keyword(s):

Breast Cancer ◽

Type 2 Diabetes ◽

Reference Lists ◽

Meta Analysis ◽

Statistical Significance ◽

Increased Risk ◽

And Gender ◽

Study Participants

The aim of this meta-analysis was to collate and analyse all primary observational studies investigating the risk of breast cancer (BC) associated with diabetes. In addition, we aimed to complete subgroup analyses by both type of diabetes and gender of study participants to further clarify the origin of any such association between the two. Studies were obtained from a database search of MEDLINE, EMBASE, PubMed, Current Contents Connect and Google Scholar with additional cross-checking of reference lists. Collated data were assessed for heterogeneity and a pooled odds ratio (OR) calculated. Forty-three studies were included in the meta-analysis with 40 studies investigating BC in women and six studies investigating BC in men. Overall, we found a significantly increased risk of BC associated with diabetes in women (OR 1.20, 95% confidence interval (CI) 1.13–1.29). After subgroup analysis by type of diabetes, the association was unchanged with type 2 diabetes (OR 1.22, 95% CI 1.07–1.40) and nullified with gestational diabetes (OR 1.06, 95% CI 0.79–1.40). There were insufficient studies to calculate a pooled OR of the risk of BC associated with type 1 diabetes. There was an increased risk of BC in males with diabetes mellitus; however, the results did not reach statistical significance (OR 1.29, 95% CI 0.99–1.67). In conclusion, diabetes increases the risk of BC in women. This association is confirmed in women with type 2 diabetes and supports the hypothesis that diabetes is an independent risk factor for BC.

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Susceptibility of ApoB and PCSK9 Genetic Polymorphisms to Diabetic Kidney Disease Among Chinese Diabetic Patients

Frontiers in Medicine ◽

10.3389/fmed.2021.659188 ◽

2021 ◽

Vol 8 ◽

Author(s):

Liang Ma ◽

Shaoting Wang ◽

Hailing Zhao ◽

Meijie Yu ◽

Xiangling Deng ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Kidney Disease ◽

Diabetic Kidney Disease ◽

Chinese Patients ◽

Diabetic Patients ◽

Diabetic Kidney ◽

Increased Risk

This study aimed to investigate the susceptibility of 8 polymorphisms in ApoB and PCSK9 genes to diabetic kidney disease (DKD) in Chinese patients with type 2 diabetes mellitus. This is a case-control association study, including 575 DKD cases and 653 controls. Genotypes were determined using ligase detection reaction method, and data are analyzed using STATA software. The genotype distributions of rs1042034 and rs12720838 differed significantly between the two groups (P < 0.001 and P = 0.008, respectively). After adjusting for confounding factors, the mutations of rs1042034 and rs12720838 were associated with the significantly increased risk of DKD. For instance, carriers of rs1042034 T allele (CT and TT genotypes) were 1.07 times more likely to have DKD than carriers of rs1042034 CC genotype [odds ratio (OR) = 1.07, 95% confidence interval (CI): 1.03–1.10, P < 0.001]. Further, haplotype T-A-G-T in ApoB gene was overrepresented in cases (18.10%) compared with controls (12.76%) (PSimulated = 0.045), and haplotype T-A-G-T was associated with a 33% increased risk of DKD (OR = 1.33, 95% CI: 1.04, 1.70). In further haplotype-phenotype analysis, significant association was only noted for hypertension and omnibus haplotypes in ApoB gene (PSimulated = 0.001). Our findings indicate that ApoB gene is a candidate gene for DKD in Chinese patients with type 2 diabetes mellitus.

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Association between uric acid level and incidence of macroalbuminuria in people with type 2 diabetes mellitus: A 4.5-year cohort study

10.21203/rs.2.18350/v1 ◽

2019 ◽

Author(s):

Yun-Ju Lai ◽

Yu-Yen Chen ◽

Li-Jung Chen ◽

Po-Wen Ku ◽

Kuo-Chuan Hung ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Uric Acid ◽

Serum Uric Acid ◽

Cox Regression ◽

Characteristic Curve ◽

Cox Regression Analysis ◽

Increased Risk

Abstract Background: Using animal models and molecular biology researches, hyperuricemia has been shown to instruct renal arteriolopathy, arterial hypertension, and microvascular injury involving the renin-angiotensin system and resulting in renal function impairment. Nevertheless, the association between uric acid levels and the development of macroalbuminuria has been under-investigated in people with type 2 diabetes mellitus. Methods: Patients with type 2 diabetes and regular outpatient visits were recruited from a community hospital in Taiwan since January 2014. Demographics, lifestyle features, and medical history were gathered by well-trained interviewers. All participants underwent comprehensive physical examinations, including a biochemical assay of venous blood specimens and urine samples after an 8-hour overnight fast. Participants were followed until June 2018. The primary outcome was the macroalbuminuria incidence. Univariable and multivariable Cox regression analysis were employed to explore the relation between uric acid and incident macroalbuminuria. Uric acid cutoffs for incident macroalbuminuria were determined with the receiver operator characteristic curve. Results: We included 247 qualified subjects (mean age: 64.78 years old [standard deviation=11.29 years]; 138 [55.87%] men). During a 4.5-year follow-up duration, 20 subjects with incident macroalbuminuria were recognized. Serum uric acid was significantly associated with an increased risk of incident macroalbuminuria (adjusted hazard ratio=2.39; 95% confidence interval: 1.53-3.75; p<0.001) with potential confounders adjustment. The uric acid cutoff point was 6.9 mg/dL (area under the curve 0.708, sensitivity 60.0%, specificity 84.58%) for incident macroalbuminuria. Conclusions: Serum uric acid was associated with incident macroalbuminuria among people with type 2 diabetes.

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Evaluation of the Association between Obesity Markers and Type 2 Diabetes: A Cohort Study Based on a Physical Examination Population

Journal of Diabetes Research ◽

10.1155/2021/6503339 ◽

2021 ◽

Vol 2021 ◽

pp. 1-8

Author(s):

Tengfei Yang ◽

Bo Zhao ◽

Dongmei Pei

Keyword(s):

Type 2 Diabetes ◽

Cohort Study ◽

Physical Examination ◽

Roc Curve ◽

Risk Model ◽

Characteristic Curve ◽

Area Under The Curve ◽

Visceral Adiposity Index ◽

Digital Repository

Purpose. To evaluate the predictive effect of different obesity markers on the risk of developing type 2 diabetes in a population of healthy individuals who underwent physical examination and to provide a reference for the early detection of individuals at risk of diabetes. Methods. This retrospective cohort study included 15206 healthy subjects who underwent a physical examination (8307 men and 6899 women). Information on the study population was obtained from the Dryad Digital Repository. Cox proportional risk models were used to calculate the hazard ratio (HR) and 95% confidence interval (CI) of different obesity markers, including the lipid accumulation index (LAP), body mass index (BMI), waist-to-height ratio (WHtR), visceral adiposity index (VAI), and body roundness index (BRI) on the development of type 2 diabetes. The effectiveness of each obesity marker in predicting the risk of developing type 2 diabetes was analyzed using the receiver operating characteristic curve (ROC curve) and the area under the curve (AUC). Results. After a mean follow-up of 5.4 years, there were 372 new cases of type 2 diabetes. After correcting for confounding factors such as age, sex, smoking, alcohol consumption, exercise, and blood pressure, Cox proportional risk model analysis showed that elevations in BMI, LAP, WHtR, VAI, and BRI increased the risk of developing type 2 diabetes. The ROC curve results showed that LAP was the best predictor of the risk of developing diabetes, with an AUC (95% CI) of 0.759 (0.752–0.766), an optimal cutoff value of 16.04, a sensitivity of 0.72, and a specificity of 0.69. Conclusion. An increase in the BMI, LAP, WHtR, VAI, and BRI can increase the risk of developing type 2 diabetes, with LAP being the best predictor of this risk.

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Systematic Review of Polygenic Risk Scores for Type 1 and Type 2 Diabetes

International Journal of Molecular Sciences ◽

10.3390/ijms21051703 ◽

2020 ◽

Vol 21 (5) ◽

pp. 1703 ◽

Cited By ~ 1

Author(s):

Felipe Padilla-Martínez ◽

Francois Collin ◽

Miroslaw Kwasniewski ◽

Adam Kretowski

Keyword(s):

Systematic Review ◽

Type 2 Diabetes ◽

Area Under The Curve ◽

Healthy People ◽

Risk Scores ◽

Polygenic Risk Score ◽

Polygenic Risk ◽

Diabetes Patients

Recent studies have led to considerable advances in the identification of genetic variants associated with type 1 and type 2 diabetes. An approach for converting genetic data into a predictive measure of disease susceptibility is to add the risk effects of loci into a polygenic risk score. In order to summarize the recent findings, we conducted a systematic review of studies comparing the accuracy of polygenic risk scores developed during the last two decades. We selected 15 risk scores from three databases (Scopus, Web of Science and PubMed) enrolled in this systematic review. We identified three polygenic risk scores that discriminate between type 1 diabetes patients and healthy people, one that discriminate between type 1 and type 2 diabetes, two that discriminate between type 1 and monogenic diabetes and nine polygenic risk scores that discriminate between type 2 diabetes patients and healthy people. Prediction accuracy of polygenic risk scores was assessed by comparing the area under the curve. The actual benefits, potential obstacles and possible solutions for the implementation of polygenic risk scores in clinical practice were also discussed. Develop strategies to establish the clinical validity of polygenic risk scores by creating a framework for the interpretation of findings and their translation into actual evidence, are the way to demonstrate their utility in medical practice.

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DIABETIC ENCEPHALOPATHY IN TYPE 2 DIABETES

Journal of Medicine and Pharmacy ◽

10.34071/jmp.2016.6.8 ◽

2017 ◽

pp. 52-58

Author(s):

Van Vy Hau Nguyen ◽

Hai Thuy Nguyen ◽

Dinh Toan Nguyen

Keyword(s):

Type 2 Diabetes ◽

Cognitive Deficits ◽

Organ Damage ◽

Diabetic Encephalopathy ◽

Downstream Effects ◽

Increased Risk ◽

Underlying Mechanisms ◽

The Brain

Type 2 diabetes is a common metabolic disease with a rising global prevalence. It is associated with slowly progressive end-organ damage in the eyes and kidneys, but also in the brain. The latter complication is often referred to as "diabetic encephalopathy" and is characterized by mild to moderate impairments in cognitive functioning. It is also associated with an increased risk of dementia. Diabetic encephalopathies are now accepted complications of diabetes. To date, its pathogenetic mechanisms are largely unclear. They appear to differ in type 1 and type 2 diabetes as to underlying mechanisms and the nature of resulting cognitive deﬁcits. The increased incidence of Alzheimer’s disease in type 2 diabetes is associated with insulin resistance, hyperinsulinemia and hyperglycemia, and commonly accompanying attributes such as hypercholesterolemia, hypertension and obesity. However, cognitive impairement in type 1 diabetes have other differences with type 2 diabetes. The major underlying component here appears to be insulin deﬁciency with downstream effects on the expression of neurotrophic factors, neurotransmitters, oxidative and apoptotic stressors resulting in defects in neuronal integrity, connectivity and loss commonly occurring in the still developing brain.

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Reduced Serum Levels of Brain-Derived Neurotrophic Factor Are Related to Mild Cognitive Impairment in Chinese Patients with Type 2 Diabetes Mellitus

Annals of Nutrition and Metabolism ◽

10.1159/000493275 ◽

2018 ◽

Vol 73 (4) ◽

pp. 271-281 ◽

Cited By ~ 4

Author(s):

Zhi-chun Sun ◽

Jing Yu ◽

Yi-Lan Liu ◽

Zhen-zhen Hong ◽

Lin Ling ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Logistic Regression ◽

Serum Levels ◽

Chinese Patients ◽

Diabetic Patients ◽

Regression Analyses ◽

Increased Risk

Background: Brain-derived neurotrophic factor (BDNF) is involved in obesity, type 2 diabetes mellitus (T2DM), and cognitive dysfunction. The present study sought to assess the role of serum levels of BDNF in the pathophysiological process of mild cognitive impairment (MCI), a preclinical phase of dementia in 715 Chinese patients with T2DM. Methods: Cross-sectional data were obtained from 715 patients with T2DM recruited from a Chinese diabetes center. Serum levels of BDNF were measured with sandwich enzyme-linked immunosorbent assay. The influence of BDNF on MCI was examined using univariate and multivariate binary logistic regression analyses. Results: In univariate and multivariate logistic regression analyses, for each one-unit increase of BDNF, the unadjusted and adjusted risk of MCI decreased by 9% (OR 0.91; 95% CI 0.88–0.93, p < 0.001) and 6% (0.94; 0.87–0.98, p < 0.001) respectively. In multivariate models comparing the first (Q1), second and third quartiles against the fourth quartile of BDNF, BDNF in Q1 and Q2 were associated with MCI, and increased risk of MCI by 275% (OR 3.75; 95% CI 2.38–6.03) and 155% (2.55; 1.32–4.02). These results suggested that for each 1 ng/mL increase of serum level of BDNF, the association became stronger among obese diabetic patients (OR 0.91, 95% CI 0.85–0.96; p < 0.001) versus nonobese diabetic patients (OR 0.95, 95% CI 0.86–0.98; p = 0.001). Conclusion: The present data demonstrated that reduced serum levels of BDNF were associated with increased risk of MCI and might be useful for identifying diabetic patients at risk of dementia for early prevention strategies.

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