scholarly journals Interaction between physical activity and polygenic risk score for type-2 diabetes in older Americans

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
Y Y Wu ◽  
M D Thompson ◽  
F Youkhana ◽  
C M Pirkle
Keyword(s):  
Physical Activity ◽  
Type 2 Diabetes ◽  
Genetic Risk ◽  
Significant Interaction ◽  
The United States ◽  
Lifestyle Factors ◽  
Polygenic Risk Score ◽  
Environment Interaction ◽  
Polygenic Risk

Abstract Background Genetics plays an important role in the development of type-2 diabetes (T2D). Polygenic risk scores (PRS) are increasingly used to quantify genetic risk of T2D in epidemiological studies. These scores, when integrated into analyses of modifiable lifestyle factors, may improve understanding of T2D etiology, as the strength of association with T2D and some lifestyle or demographic factors may vary according to genetic predisposition. Methods We examined PRS-lifestyle factor interactions on T2D with data from the United States Health and Retirement Study (HRS), a prospective longitudinal cohort of older adults (≥50 at baseline). HRS contains nationally representative samples of Black and White Americans with pre-calculated PRS for T2D (N = 14,001). Covariates included sex, education, BMI, smoking, alcohol, and physical activity. Predicted prevalence and incidence of T2D were calculated with logistic regression models. Nonparametric bootstrap method was performed to calculate differences in T2D prevalence and incidence by PRS percentiles and interaction variables. Results Significant interaction (p_interaction=0.0096) was detected between PRS and physical activity among Whites only. In those with the lowest decile of PRS, T2D prevalence was similar (∼10%) for those reporting no physical activity compared to low or moderate activity. In those with the top decile of PRS, lower T2D prevalence (17%, 95%CI:14.8,19.6) was observed among those with moderate compared to no activity (24%, 95%CI:20.4,27.5). Incident T2D in Whites followed a similar pattern (p_interaction=0.0194). Among Black participants, no significant interaction with any lifestyle variables was detected. Conclusions Interaction of different genetic risk profiles with lifestyle factors may inform understanding of why certain inventions are more or less effective in different groups of people, potentially improving clinical and prevention interventions. Key messages Protection conferred by physical activity on T2D varied by underlying genetic risk. Gene-environment interaction studies provide insights on why lifestyle factors vary in their associations with T2D.

scholarly journals Effects of polygenic risk score of type 2 diabetes on the hippocampal topological property and episodic memory

2021 ◽  
Author(s):  
Yang Zhang ◽  
Xin Du ◽  
Yumeng Fu ◽  
Qiuyue Zhao ◽  
Zirui Wang ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Episodic Memory ◽  
Risk Score ◽  
Genetic Risk ◽  
Polygenic Risk Score ◽  
Topological Properties ◽  
Polygenic Risk ◽  
The Right ◽  
Nodal Properties

Abstract Purpose Type 2 diabetes is associated with a higher risk of dementia. The pathogenesis is complex, partly influenced by genetic factors. The hippocampus is the most vulnerable brain region in individuals with type 2 diabetes. However, whether the genetic risk of type 2 diabetes is associated with the hippocampus and episodic memory remains unclear. This study explored the influence of polygenic risk score (PRS) of type 2 diabetes on the white matter topological properties of the hippocampus among individuals with and without type 2 diabetes and its associations with episodic memory. Methods This study included 103 individuals with type 2 diabetes and 114 well-matched individuals without type 2 diabetes. All the participants were genotyped, and a diffusion tensor imaging-based structural network was constructed. PRS was calculated based on a genome-wide association study of type 2 diabetes. The PRS-by-disease interactions on the bilateral hippocampal topological network properties were evaluated by analysis of variance (ANOVA). Results There were significant PRS-by-disease interaction effects on the nodal topological properties of the right hippocampus node. In the individuals with type 2 diabetes, the PRS was correlated with the right hippocampal nodal properties, and the nodal properties were correlated with the episodic memory. In addition, the right hippocampal nodal properties mediated the effect of PRS on the episodic memory in individuals with type 2 diabetes. Conclusion Our results suggested a gene-brain-cognition biological pathway, which might help understand the neural mechanism of the genetic risk of type 2 diabetes affects episodic memory in type 2 diabetes.

scholarly journals Quality of dietary fat and genetic risk of type 2 diabetes: individual participant data meta-analysis

BMJ ◽  
2019 ◽  
pp. l4292 ◽  
Author(s):  
Jordi Merino ◽  
Marta Guasch-Ferré ◽  
Christina Ellervik ◽  
Hassan S Dashti ◽  
Stephen J Sharp ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Cohort Studies ◽  
Risk Score ◽  
Dietary Fat ◽  
Genetic Risk ◽  
Polygenic Risk Score ◽  
Polyunsaturated Fat ◽  
Polygenic Risk

Abstract Objective To investigate whether the genetic burden of type 2 diabetes modifies the association between the quality of dietary fat and the incidence of type 2 diabetes. Design Individual participant data meta-analysis. Data sources Eligible prospective cohort studies were systematically sourced from studies published between January 1970 and February 2017 through electronic searches in major medical databases (Medline, Embase, and Scopus) and discussion with investigators. Review methods Data from cohort studies or multicohort consortia with available genome-wide genetic data and information about the quality of dietary fat and the incidence of type 2 diabetes in participants of European descent was sought. Prospective cohorts that had accrued five or more years of follow-up were included. The type 2 diabetes genetic risk profile was characterized by a 68-variant polygenic risk score weighted by published effect sizes. Diet was recorded by using validated cohort-specific dietary assessment tools. Outcome measures were summary adjusted hazard ratios of incident type 2 diabetes for polygenic risk score, isocaloric replacement of carbohydrate (refined starch and sugars) with types of fat, and the interaction of types of fat with polygenic risk score. Results Of 102 305 participants from 15 prospective cohort studies, 20 015 type 2 diabetes cases were documented after a median follow-up of 12 years (interquartile range 9.4-14.2). The hazard ratio of type 2 diabetes per increment of 10 risk alleles in the polygenic risk score was 1.64 (95% confidence interval 1.54 to 1.75, I 2 =7.1%, τ 2 =0.003). The increase of polyunsaturated fat and total omega 6 polyunsaturated fat intake in place of carbohydrate was associated with a lower risk of type 2 diabetes, with hazard ratios of 0.90 (0.82 to 0.98, I 2 =18.0%, τ 2 =0.006; per 5% of energy) and 0.99 (0.97 to 1.00, I 2 =58.8%, τ 2 =0.001; per increment of 1 g/d), respectively. Increasing monounsaturated fat in place of carbohydrate was associated with a higher risk of type 2 diabetes (hazard ratio 1.10, 95% confidence interval 1.01 to 1.19, I 2 =25.9%, τ 2 =0.006; per 5% of energy). Evidence of small study effects was detected for the overall association of polyunsaturated fat with the risk of type 2 diabetes, but not for the omega 6 polyunsaturated fat and monounsaturated fat associations. Significant interactions between dietary fat and polygenic risk score on the risk of type 2 diabetes (P>0.05 for interaction) were not observed. Conclusions These data indicate that genetic burden and the quality of dietary fat are each associated with the incidence of type 2 diabetes. The findings do not support tailoring recommendations on the quality of dietary fat to individual type 2 diabetes genetic risk profiles for the primary prevention of type 2 diabetes, and suggest that dietary fat is associated with the risk of type 2 diabetes across the spectrum of type 2 diabetes genetic risk.

1645-P: Polygenic Risk Score for Prediction of Complications in Men and Women with Type 2 Diabetes

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1645-P
Author(s):  
JOHANNE TREMBLAY ◽  
REDHA ATTAOUA ◽  
MOUNSIF HALOUI ◽  
RAMZAN TAHIR ◽  
CAROLE LONG ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Risk Score ◽  
Polygenic Risk Score ◽  
Men And Women ◽  
Polygenic Risk ◽  
Prediction Of Complications

304-OR: Polygenic Risk Score Predicts Type 2 Diabetes Susceptibility in a Diverse Consumer Genetic Database

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 304-OR
Author(s):  
MICHAEL L. MULTHAUP ◽  
RYOSUKE KITA ◽  
NICHOLAS ERIKSSON ◽  
STELLA ASLIBEKYAN ◽  
JANIE SHELTON ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Risk Score ◽  
Polygenic Risk Score ◽  
Diabetes Susceptibility ◽  
Genetic Database ◽  
Polygenic Risk

1134-P: Polygenic Risk Score of Type 2 Diabetes as a Predictive Factor for Macrovascular Complications: A Prospective Population-Based UK Biobank Study

Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 1134-P
Author(s):  
SANGHYUK JUNG ◽  
DOKYOON KIM ◽  
MANU SHIVAKUMAR ◽  
HONG-HEE WON ◽  
JAE-SEUNG YUN
Keyword(s):  
Type 2 Diabetes ◽  
Risk Score ◽  
Predictive Factor ◽  
Population Based ◽  
Macrovascular Complications ◽  
Polygenic Risk Score ◽  
Uk Biobank ◽  
Polygenic Risk

scholarly journals Differing Contributions of Classical Risk Factors to Type 2 Diabetes in Multi-Ethnic Malaysian Populations

2018 ◽  
Vol 15 (12) ◽  
pp. 2813
Author(s):  
Noraidatulakma Abdullah ◽  
Nor Abdul Murad ◽  
John Attia ◽  
Christopher Oldmeadow ◽  
Mohd Kamaruddin ◽  
...  
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Family History ◽  
Characteristic Curve ◽  
Lifestyle Factors ◽  
Predictive Utility ◽  
Family History Of Diabetes ◽  
History Of

The prevalence of type 2 diabetes is escalating rapidly in Asian countries, with the rapid increase likely attributable to a combination of genetic and lifestyle factors. Recent research suggests that common genetic risk variants contribute minimally to the rapidly rising prevalence. Rather, recent changes in dietary patterns and physical activity may be more important. This nested case-control study assessed the association and predictive utility of type 2 diabetes lifestyle risk factors in participants from Malaysia, an understudied Asian population with comparatively high disease prevalence. The study sample comprised 4077 participants from The Malaysian Cohort project and included sub-samples from the three major ancestral groups: Malay (n = 1323), Chinese (n = 1344) and Indian (n = 1410). Association of lifestyle factors with type 2 diabetes was assessed within and across ancestral groups using logistic regression. Predictive utility was quantified and compared between groups using the Area Under the Receiver-Operating Characteristic Curve (AUC). In predictive models including age, gender, waist-to-hip ratio, physical activity, location, family history of diabetes and average sleep duration, the AUC ranged from 0.76 to 0.85 across groups and was significantly higher in Chinese than Malays or Indians, likely reflecting anthropometric differences. This study suggests that obesity, advancing age, a family history of diabetes and living in a rural area are important drivers of the escalating prevalence of type 2 diabetes in Malaysia.

scholarly journals The efficacy of family history, genetic risk score and physical activity in distinguishing type 2 diabetes prevalence

2019 ◽  
Author(s):  
Lukasz Szczerbinski ◽  
Joanna Goscik ◽  
Witold Bauer ◽  
Natalia Wawrusiewicz-Kurylonek ◽  
Magdalena Paczkowska-Abdulsalam ◽  
...  
Keyword(s):  
Physical Activity ◽  
Type 2 Diabetes ◽  
Family History ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Diabetes Prevalence

scholarly journals Empowering Patients for Healthy Nutrition, Physical Activity, and Self-Care Using the Diabetes Score Questionnaire

2021 ◽  
Vol 27 (4) ◽  
pp. 131-136
Author(s):  
Muhammad Jawad Hashim ◽  
Halla Mustafa
Keyword(s):  
Physical Activity ◽  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Glycemic Control ◽  
Lifestyle Change ◽  
Lifestyle Factors ◽  
Health Care Center ◽  
Healthy Nutrition ◽  
Patients With Diabetes

<b><i>Objectives:</i></b> Lifestyle factors such as nutrition and physical activity play an important role in the management of diabetes mellitus. Unfortunately, adherence to lifestyle change remains low among patients with diabetes. The aim of this study was to evaluate the effectiveness of the Diabetes Score questionnaire in a clinical setting. <b><i>Methods:</i></b> The Diabetes Score is a 10-item shared decision-making tool designed to empower lifestyle change in individuals with diabetes. It yields an intuitive score from 0 to 100 based on a patient’s adherence to lifestyle recommendations. An observational study was conducted at an ambulatory health care center. After obtaining written informed consent, adult patients with type 2 diabetes mellitus were interviewed by a trained researcher using the Diabetes Score questionnaire. Patients’ Diabetes Score values were analyzed in reference to their glycemic control and other clinical and demographic factors. <b><i>Results:</i></b> A total of 60 individuals with type 2 diabetes participated in the study. The mean age was 56 years (minimum 43 years, maximum 70 years) with 60% being males. Higher Diabetes Scores correlated with better glycemic control (hemoglobin A1C; <i>r</i> = −0.23, <i>p</i> = 0.044) indicating the effect of lifestyle factors such as healthy nutrition, smaller portion sizes, active lifestyle, and aerobic exercise. The questionnaire showed internal consistency (alpha 0.66), construct validity, and high patient satisfaction (98%). <b><i>Conclusion:</i></b> Diabetes Score, a behavioral lifestyle questionnaire, correlates with glycemic control in type 2 diabetes. Diabetes Score can be used in clinical settings for measuring, discussing, and setting targets for lifestyle change among patients with diabetes.

scholarly journals Interactions between genetic polymorphisms of glucose metabolizing genes and smoking and alcohol consumption in the risk of type 2 diabetes mellitus

2017 ◽  
Vol 42 (12) ◽  
pp. 1316-1321 ◽  
Author(s):  
Kaiping Gao ◽  
Yongcheng Ren ◽  
Jinjin Wang ◽  
Zichen Liu ◽  
Jianna Li ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Lifestyle Factors ◽  
Environment Interaction ◽  
Nucleotide Polymorphisms ◽  
Gene Environment ◽  
Increased Risk ◽  
The Impact

The impact of gene-environment interaction on diabetes remains largely unknown. We aimed to investigate if interaction between glucose metabolizing genes and lifestyle factors is associated with type 2 diabetes mellitus (T2DM). Interactions between genotypes of 4 glucose metabolizing genes (MTNR1B, KCNQ1, KLF14, and GCKR) and lifestyle factors were estimated in 722 T2DM patients and 759 controls, using multiple logistic regression. No significant associations with T2DM were detected for the single nucleotide polymorphisms of MTNR1B, KLF14 and GCKR. However, rs151290 (KCNQ1) polymorphisms were found to be associated with risk of T2DM. Compared with AA, the odds ratios (ORs) of AC or CC genotypes for developing T2DM were 1.545 (P = 0.0489) and 1.603 (P = 0.0383), respectively. In stratified analyses, the associations were stronger in smokers with CC than smokers with AA (OR = 3.668, P = 0.013); drinkers with AC (OR = 5.518, P = 0.036), CC (OR = 8.691, P = 0.0095), and AC+CC (OR = 6.764, P = 0.016) than drinkers with AA. Compared with nondrinkers with AA, drinkers who carry AC and CC had 12.072-fold (P = 0.0007) and 8.147-fold (P = 0.0052) higher risk of developing T2DM. In conclusions, rs151290 (KCNQ1) polymorphisms are associated with increased risk of T2DM, alone and especially in interaction with smoking and alcohol.

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