scholarly journals Plasma metabolites associated with healthy Nordic dietary indexes and risk of type 2 diabetes—a nested case-control study in a Swedish population

2018 ◽  
Vol 108 (3) ◽  
pp. 564-575 ◽  
Author(s):  
Lin Shi ◽  
Carl Brunius ◽  
Ingegerd Johansson ◽  
Ingvar A Bergdahl ◽  
Bernt Lindahl ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Case Control Study ◽  
Conditional Logistic Regression ◽  
Case Control ◽  
Plasma Metabolites ◽  
Healthy Controls ◽  
Swedish Population ◽  
Nordic Diet ◽  
Control Study

ABSTRACT Background Epidemiologic evidence on the association of a healthy Nordic diet and future type 2 diabetes (T2D) is limited. Exploring metabolites as biomarkers of healthy Nordic dietary patterns may facilitate investigation of associations between such patterns and T2D. Objectives We aimed to identify metabolites related to a priori-defined healthy Nordic dietary indexes, the Baltic Sea Diet Score (BSDS) and Healthy Nordic Food Index (HNFI), and evaluate associations with the T2D risk in a case-control study nested in a Swedish population-based prospective cohort. Design Plasma samples from 421 case-control pairs at baseline and samples from a subset of 151 healthy controls at a 10-y follow-up were analyzed with the use of untargeted liquid chromatography-mass spectrometry metabolomics. Index-related metabolites were identified through the use of random forest modelling followed by partial correlation analysis adjustment for lifestyle confounders. Metabolite patterns were derived via principal component analysis (PCA). ORs of T2D were estimated via conditional logistic regression. Reproducibility of metabolites was assessed by intraclass correlation (ICC) in healthy controls. Associations were also assessed for 10 metabolites previously identified as linking a healthy Nordic diet with T2D. Results In total, 31 metabolites were associated with BSDS and/or HNFI (−0.19 ≤ r ≤ 0.21, 0.10 ≤ ICC ≤ 0.59). Two PCs were determined from index-related metabolites: PC1 strongly correlated to the indexes (r = 0.27 for BSDS, r = 0.25 for HNFI, ICC = 0.45) but showed no association with T2D risk. PC2 was weakly associated with the indexes, but more strongly with foods not part of the indexes, e.g., pizza, sausages, and hamburgers. PC2 was also significantly associated with T2D risk. Predefined metabolites were confirmed to be reflective of consumption of whole grains, fish, or vegetables, but not related to T2D risk. Conclusions Our study did not support an association between healthy Nordic dietary indexes and T2D. However, foods such as hamburger, sausage, and pizza not covered by the indexes appeared to be more important for T2D risk in the current population.

scholarly journals Plasma metabolites associated with type 2 diabetes in a Swedish population: a case–control study nested in a prospective cohort

Diabetologia ◽  
2018 ◽  
Vol 61 (4) ◽  
pp. 849-861 ◽  
Author(s):  
Lin Shi ◽  
Carl Brunius ◽  
Marko Lehtonen ◽  
Seppo Auriola ◽  
Ingvar A. Bergdahl ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Prospective Cohort ◽  
Case Control Study ◽  
Case Control ◽  
Plasma Metabolites ◽  
Swedish Population ◽  
Control Study

scholarly journals Comparative functional exercise capacity of patients with type 2-diabetes and healthy controls: a case control study

2014 ◽  
Vol 19 ◽  
Author(s):  
Taofeek Oluwole Awotidebe ◽  
Rufus Adesoji. Adedoyin ◽  
Abraar Olalakan Yusuf ◽  
Chidozie Emmanuel Mbada ◽  
Rose Opiyo ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Exercise Capacity ◽  
Case Control Study ◽  
Case Control ◽  
Healthy Controls ◽  
Functional Exercise ◽  
Functional Exercise Capacity ◽  
Control Study

scholarly journals Headache and type 2 diabetes association: a US national ambulatory case-control study

2018 ◽  
Author(s):  
Anthony Nash ◽  
Alejo J Nevado Holgado ◽  
Simon Lovestone ◽  
M. Zameel Cader ◽  
Caleb Webber
Keyword(s):  
Type 2 Diabetes ◽  
Odds Ratio ◽  
Molecular Mechanisms ◽  
Case Control Study ◽  
Conditional Logistic Regression ◽  
Prescription Medication ◽  
Case Control ◽  
Care Survey ◽  
Control Study

AbstractObjectiveWe investigate the joint observation between type 2 diabetes and headache using a case-control study of a US ambulatory dataset.BackgroundRecent whole-population cohort studies propose that type 2 diabetes may have a protective effect against headache prevalence. With headaches ranked as a leading cause of disability, headache-associated comorbidities could help identify shared molecular mechanisms.MethodsWe performed a case-control study using the US National Ambulatory Medical Care Survey, 2009, on the joint observation between headache and specific comorbidities, namely type 2 diabetes, hypertension and anxiety, for all patients between 18 and 65 years of age. The odds ratio of having a headache and a comorbidity were calculated using conditional logistic regression, controlling for gender and age over a study population of 3,327,947 electronic health records in the absence of prescription medication data.ResultsWe observed estimated odds ratio of 0.89 (95% CI: 0.83-0.95) of having a headache and a record of type 2 diabetes over the population, and 0.83 (95% CI: 2.02-2.57) and 0.89 (95% CI: 3.00-3.49) for male and female, respectively.ConclusionsWe find that patients with type 2 diabetes are less likely to present a recorded headache indication. Patients with hypertension are almost twice as likely of having a headache indication and patients with an anxiety disorder are almost three times as likely. Given the possibility of confounding indications and prescribed medications, additional studies are recommended.

scholarly journals Influence of GSTT1 and GSTP1 polymorphisms on type 2 diabetes mellitus and diabetic retinopathy risk in the Chinese population: a case control study

2021 ◽  
Author(s):  
Xinqian Geng ◽  
Ling Zha ◽  
Yuxin Xiong ◽  
Fan Xu ◽  
Bo Xu ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Chinese Population ◽  
Case Control Study ◽  
Case Control ◽  
Diabetic Patients ◽  
Healthy Controls ◽  
Gstp1 Gene ◽  
Control Study

Abstract Background: Studies have revealed the association of glutathione S-transferases (GSTM1 and GSTT1) deletion (null) polymorphism with the risks of developing type 2 diabetes mellitus (T2DM) and its complications. The present study aimed to investigate the relationship between GSTT1/ GSTP1 gene polymorphisms and the risks of T2DM and diabetic retinopathy (DR) in a Chinese population.Methods: In this case-control study, a total of 336 subjects with T2DM and a defined ophthalmologic status were recruited from the Second People’s Hospital of Yunnan Province between June 2014 and October 2016. Seventy-two age-matched healthy controls were also enrolled. Physical examinations and laboratory tests were performed. The frequencies of GSTT1 genotypes in all participants were determined by polymerase chain reaction (PCR) followed by agarose gel electrophoresis. Genotyping of GSTP1 gene was identified by PCR amplification followed by sequencing.Results: Compared with healthy controls, the GSTT1-null genotype was significantly more common in diabetic patients with or without DR (all P < 0.05). However, there was no difference in the frequencies of the GSTP1 genotype (AA, GA, GG) between diabetic patients with or without DR and healthy controls. Furthermore, neither the GSTP1 nor GSTT1 genetic polymorphism was associated with the development of DR. In the present study, the risk of developing T2DM was significantly higher in subjects carrying the combined heterozygous GSTP1 (AG) and null GSTT1 genotypes (OR = 0.40, 95% CI = 0.21-0.74, P = 0.02).Conclusions: The deletion of the GSTT1 genotype was associated with a higher risk of developing T2DM, whether alone or in combination with GSTP1, indicating that the null genotype of GSTT1 may serve as a potential biomarker for T2DM in the Chinese population, which is helpful for clinicians to make more effective risk-based decisions.

scholarly journals Diabetic dyslipidemia and type 2 diabetes mellitus as early as six weeks post-partum: a nested case control study

2021 ◽  
Vol 8 (6) ◽  
pp. 3116
Author(s):  
Meesha Iqbal ◽  
Paramjit Gill ◽  
Iqbal Azam ◽  
Romaina Iqbal
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Case Control Study ◽  
Post Partum ◽  
Conditional Logistic Regression ◽  
Case Control ◽  
Increased Risk ◽  
Control Study

Women who develop diabetes during pregnancy (Gestational diabetes mellitus-GDM) increase their risk of developing type 2 diabetes mellitus (T2DM) post-partum by 70%. The average time to develop T2DM varies and is not widely studied. T2DM is associated with increased risk of developing dyslipidemia leading to cardiovascular diseases. We intended to study the association of dyslipidemia and T2DM as early as 6 weeks post-partum. A matched case control study was designed, and conditional logistic regression analysis applied to get adjusted matched odds with 95% confidence intervals. Our study revealed increased serum LDL levels in the cases compared to the controls (p=0.03). However, no association was seen with other lipid parameters. 

scholarly journals Plasma metabolites associated with exposure to perfluoroalkyl substances and risk of type 2 diabetes – A nested case-control study

2021 ◽  
Vol 146 ◽  
pp. 106180
Author(s):  
Tessa Schillemans ◽  
Lin Shi ◽  
Carolina Donat-Vargas ◽  
Kati Hanhineva ◽  
Andreas Tornevi ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Case Control Study ◽  
Case Control ◽  
Perfluoroalkyl Substances ◽  
Plasma Metabolites ◽  
Nested Case Control ◽  
Control Study

scholarly journals Association of Plasma β-amyloid 40 and 42 Concentration with Type 2 Diabetes Among Chinese Adults

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 64-64
Author(s):  
Xiaobo Peng ◽  
Zihui Xu ◽  
Xiaoxing Mo ◽  
Qianqian Guo ◽  
Jiawei Yin ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Case Control Study ◽  
Conditional Logistic Regression ◽  
Case Control ◽  
Family History Of Diabetes ◽  
Joint Research Project ◽  
Β Amyloid ◽  
Nested Case Control ◽  
Control Study

Abstract Objectives We aimed to investigate the association of plasma β-amyloid (Aβ) 40 and Aβ42 with risk of type 2 diabetes. Methods We performed a case-control study and a nested case-control study within a prospective cohort study. In the case-control study, we included 1063 newly diagnosed type 2 diabetes cases and 1063 controls matched by age and sex. In the nested case-control study, we included 121 incident type 2 diabetes cases and 242 matched controls. Plasma Aβ40 and Aβ42 concentrations were simultaneously measured with electrochemiluminescence immunoassay. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using conditional logistic regression with adjustment for age, sex, BMI, current smoking status, current drinking status, physical activity, family history of diabetes, and hypertension. Results In the case-control study, the multivariable-adjusted ORs of type 2 diabetes comparing the highest with the lowest quartile of plasma Aβ concentrations were 1.97 (95% CI: 1.46, 2.66) for plasma Aβ40 and 2.01 (95% CI: 1.50, 2.69) for plasma Aβ42. Each 30 ng/L increment of plasma Aβ40 was associated with 28% (95% CI: 15%, 43%) higher odds of type 2 diabetes, and each 5 ng/L increment of plasma Aβ42 was associated with 37% (95% CI: 21%, 55%) higher odds of type 2 diabetes. In the nested case-control study, the multivariable-adjusted ORs of type 2 diabetes for the highest versus the lowest quartile were 3.79 (95% CI: 1.81, 7.94) for plasma Aβ40 and 2.88 (95% CI: 1.44, 5.75) for plasma Aβ42. The multivariable-adjusted ORs of type 2 diabetes were 1.44 (95% CI: 1.18, 1.74) and 1.47 (95% CI: 1.15, 1.88) associated with each 30 ng/L increment in plasma Aβ40 and each 5 ng/L increment in plasma Aβ42, respectively. Conclusions Our findings suggested positive associations of plasma Aβ40 and Aβ42 concentration with risk of type 2 diabetes. Further studies are warranted to elucidate the underlying mechanism and explore the potential roles of plasma Aβ in linking type 2 diabetes and Alzheimer's disease. Funding Sources This work was funded by the National Key Research and Development Program of China, the Major International (Regional) Joint Research Project, and the National Natural Science Foundation of China.

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