scholarly journals Carbohydrate and sodium intake and physical activity interact with genetic risk scores of four genetic variants mainly related to lipid metabolism to modulate metabolic syndrome risk in Korean middle-aged adults

2019 ◽  
Vol 122 (8) ◽  
pp. 919-927 ◽  
Author(s):  
Jun-Yu Zhou ◽  
Mi Young Song ◽  
Sunmin Park
Keyword(s):  
Physical Activity ◽  
Metabolic Syndrome ◽  
Genetic Variants ◽  
Genetic Risk ◽  
Risk Scores ◽  
Moderate Activity ◽  
Middle Aged ◽  
Genetic Risk Scores ◽  
Daily Physical Activities ◽  
Middle Aged Adults

AbstractMetabolic syndrome (MetS) risk is influenced by genetic and environmental factors. The present study explored genetic risk scores (GRS) of genetic variants that influence the MetS and the effect of interactions between GRS and nutrient intake on MetS risk. The genetic variants that influence MetS risk were selected by genome-wide association study after adjusting for age, sex, area of residence and BMI in 8840 middle-aged adults. GRS were calculated by summing the risk alleles of the selected SNP and divided into low (0–1), medium (2–3) and high (4–7) risk groups, and the relationships between the MetS and GRS were determined by logistic regression after adjusting covariates involved in MetS risk. We also analysed the interaction between GRS and lifestyles. Four genetic variants (APOA5_rs651821, EFCAB4B_rs4766165, ZNF259_rs2160669 and APOBEC1_rs10845640) were selected because they increased MetS risk after adjusting for covariates. Individuals with medium-GRS and high-GRS alleles had a higher MetS risk by 1·48- and 2·23-fold, respectively, compared with those with low-GRS after adjusting for covariates. The increase in MetS risk was mainly related to serum TAG and HDL-cholesterol concentrations. The GRS had an interaction with carbohydrate (CHO) and Na intakes and daily physical activities for MetS risk. In conclusion, Asian middle-aged adults with high-GRS alleles were at increased MetS risk mainly due to dyslipidaemia. High daily physical activity (≥1 h moderate activity per d) reduced the MetS risk but a low-CHO diet (<65 % of total energy intake) increased the risk in carriers with high-GRS alleles. Low Na intake (<1·6 g Na intake/4 MJ) did not decrease its risk.

Has the time come to integrate genetic risk scores into clinical practice?

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
F.V Moniz Mendonca ◽  
M.I Mendonca ◽  
A Pereira ◽  
J Monteiro ◽  
J Sousa ◽  
...  
Keyword(s):  
Risk Factors ◽  
Clinical Practice ◽  
Genetic Variants ◽  
Genetic Risk ◽  
Odds Ratio ◽  
Risk Scores ◽  
Cumulative Number ◽  
Genetic Risk Scores ◽  
Risk Alleles ◽  
Cad Risk

Abstract Background The risk for Coronary Artery Disease (CAD) is determined by both genetic and environmental factors, as well as by the interaction between them. It is estimated that genetic factors could account for 40% to 55% of the existing variability among the population (inheritability). Therefore, some authors have advised that it is time we integrated genetic risk scores into clinical practice. Aim The aim of this study was to evaluate the magnitude of the association between an additive genetic risk score (aGRS) and CAD based on the cumulative number of risk alleles in these variants, and to estimate whether their use is valuable in clinical practice. Methods A case-control study was performed in a Portuguese population. We enrolled 3120 participants, of whom 1687 were CAD patients and 1433 were normal controls. Controls were paired to cases with respect to gender and age. 33 genetic variants known to be associated with CAD were selected, and an aGRS was calculated for each individual. The aGRS was further subdivided into deciles groups, in order to estimate the CAD risk in each decile, defined by the number of risk alleles. The magnitude of the risk (odds ratio) was calculated for each group by multiple logistic regression using the 5th decile as the reference group (median). In order to evaluate the ability of the aGRS to discriminate susceptibility to CAD, two genetic models were performed, the first with traditional risk factors (TRF) and second with TRF plus aGRS. The AUC of the two ROC curves was calculated. Results A higher prevalence of cases over controls became apparent from the 6th decile of the aGRS, reflecting the higher number of risk alleles present (see figure). The difference in CAD risk was only significant from the 6th decile, increasing gradually until the 10th decile. The odds ratio (OR) for the last decile related to 5th decile (median) was 1.87 (95% CI:1.36–2.56; p&lt;0.0001). The first model yielded an AUC=0.738 (95% CI:0.720–0.755) and the second model was slightly more discriminative for CAD risk (AUC=0.748; 95% CI:0.730–0.765). The DeLong test was significant (p=0.0002). Conclusion Adding an aGRS to the non-genetic risk factors resulted in a modest improvement in the ability to discriminate the risk of CAD. Such improvement, even if statistically significant, does not appear to be of real value in clinical practice yet. We anticipate that with the development of further knowledge about different SNPs and their complex interactions, and with the inclusion of rare genetic variants, genetic risk scores will be better suited for use in a clinical setting. Funding Acknowledgement Type of funding source: None

scholarly journals Subcutaneous fat mass is associated with genetic risk scores related to proinflammatory cytokine signaling and interact with physical activity in middle-aged obese adults

2019 ◽  
Vol 16 (1) ◽  
Author(s):  
James W. Daily ◽  
Hye Jeong Yang ◽  
Meiling Liu ◽  
Min Jung Kim ◽  
Sunmin Park
Keyword(s):  
Physical Activity ◽  
Fat Mass ◽  
Visceral Fat ◽  
Genetic Variants ◽  
Genetic Risk ◽  
Odds Ratio ◽  
Subcutaneous Fat ◽  
Risk Scores ◽  
Obese Adults ◽  
High Physical Activity

Abstract Background and aims Subcutaneous fat mass is negatively correlated with atherogenic risk factors, but its putative benefits remain controversial. We hypothesized that genetic variants that influence subcutaneous fat mass would modulate lipid and glucose metabolism and have interactions with lifestyles in Korean middle-aged adults with high visceral fat. Materials and methods Subcutaneous fat mass was categorized by dividing the average of subscapular skin-fold thickness by BMI and its cutoff point was 1.2. Waist circumferences were used for representing visceral fat mass with Asian cutoff points. GWAS of subjects aged 40–65 years with high visceral fat (n = 3303) were conducted and the best gene-gene interactions from the genetic variants related to subcutaneous fat were selected and explored using the generalized multifactor dimensionality reduction. Genetic risk scores (GRS) were calculated by weighted GRS that was divided into low, medium and high groups. Results Subjects with high subcutaneous fat did not have dyslipidemia compared with those with low subcutaneous fat, although both subject groups had similar amounts of total fat. The best model to influence subcutaneous fat included IL17A_rs4711998, ADCY2_rs326149, ESRRG_rs4846514, CYFIP2_rs733730, TCF7L2_rs7917983, ZNF766_rs41497444 and TGFBR3_rs7526590. The odds ratio (OR) for increasing subcutaneous fat was higher by 2.232 folds in the high-GRS group, after adjusting for covariates. However, total and LDL cholesterol, triglyceride and C-reactive protein concentrations in the circulation were not associated with GRS. Subjects with high-GRS had higher serum HDL cholesterol levels than those with low-GRS. Physical activity and GRS had an interaction with subcutaneous fat. In subjects with low physical activity, the odds ratio for high subcutaneous fat increased by 2.232, but subcutaneous fat deposition was not affected in the high-GRS group with high physical activity. Conclusion Obese adults with high-GRS had more subcutaneous fat, but they did not show more dyslipidemia and inflammation compared to low-GRS. High physical activity prevented subcutaneous fat deposition in subjects with high GRS for subcutaneous fat.

scholarly journals HUMAN LONGEVITY IS INFLUENCED BY MANY GENETIC VARIANTS: EVIDENCE FROM 75,000 UK BIOBANK PARTICIPANTS

2016 ◽  
Author(s):  
Luke C Pilling ◽  
Janice L Atkins ◽  
Kirsty Bowman ◽  
Samuel E Jones ◽  
Jessica Tyrrell ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Genetic Variants ◽  
Genetic Risk ◽  
Paternal Age ◽  
Risk Scores ◽  
Human Longevity ◽  
Uk Biobank ◽  
Age At Death ◽  
Genetic Risk Scores ◽  
A Genome

Variation in human lifespan is 20 to 30% heritable but few genetic variants have been identified. We undertook a Genome Wide Association Study (GWAS) using age at death of parents of middle-aged UK Biobank participants of European decent (n=75,244 with father's and/or mother's data). Genetic risk scores for 19 phenotypes (n=777 proven variants) were also tested. Genotyped variants (n=845,997) explained 10.2% (SD=1.3%) of combined parental longevity. In GWAS, a locus in the nicotine receptor CHRNA3 - previously associated with increased smoking and lung cancer - was associated with paternal age at death, with each protective allele (rs1051730[G]) being associated with 0.03 years later age at father's death (p=3x10-8). Offspring of longer lived parents had more protective alleles (lower genetic risk scores) for coronary artery disease, systolic blood pressure, body mass index, cholesterol and triglyceride levels, type-1 diabetes, inflammatory bowel disease and Alzheimer's disease. In candidate gene analyses, variants in the TOMM40/APOE locus were associated with longevity (including rs429358, p=3x10-5), but FOXO variants were not associated. These results support a multiple protective factors model for achieving longer lifespans in humans, with a prominent role for cardiovascular-related pathways. Several of these genetically influenced risks, including blood pressure and tobacco exposure, are potentially modifiable.

scholarly journals Gender Differences of Health Behaviors in the Risk of Metabolic Syndrome for Middle-Aged Adults: A National Cross-Sectional Study in South Korea

2021 ◽  
Vol 18 (7) ◽  
pp. 3699
Author(s):  
Jaehee Yoon ◽  
Jeewuan Kim ◽  
Heesook Son
Keyword(s):  
Physical Activity ◽  
Metabolic Syndrome ◽  
Gender Differences ◽  
Alcohol Use ◽  
Health Behaviors ◽  
Health Practice ◽  
Middle Aged ◽  
Cross Sectional ◽  
Men And Women ◽  
Middle Aged Adults

This study examined gender differences in health behaviors for the risk of metabolic syndrome (MetS) among middle-aged adults using nationally representative data from the Seventh Korea National Health and Nutrition Examination Survey (2016–2018). The sample included data from 8677 middle-aged adults. The Health Practice Index measured health behaviors, including smoking, alcohol use, physical activity, sleeping, eating breakfast, working hours, nutritionally balanced diet, and mental stress. Complex sample multiple logistic regression analyses were conducted to determine the association between the Health Practice Index (HPI) and MetS. Men and women with poor or moderate HPI scores had significantly higher risks of having MetS than those with good HPI scores. Controlling for covariates, high-risk alcohol use (p < 0.001) and physical activity (p = 0.008) were associated with the risk of MetS in men and women, respectively. Men reporting alcohol use and women lacking a healthy diet were, respectively, 2.056 times (adjusted odds ratio (OR) = 2.056, 95% CI: 1.681–2.514) and 1.306 times (adjusted OR = 1.306, 95% CI: 1.075–1.587) more likely to have increased risks of MetS. Given these gender differences in health behaviors, developing tailored interventions could be beneficial in preventing MetS among middle-aged men and women.

scholarly journals Assessing the clinical utility of genetic risk scores for targeted cancer screening

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Carly A. Conran ◽  
Zhuqing Shi ◽  
William Kyle Resurreccion ◽  
Rong Na ◽  
Brian T. Helfand ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Primary Care ◽  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Clinical Utility ◽  
Low Risk ◽  
Risk Scores ◽  
Average Risk ◽  
Genetic Risk Scores

Abstract Background Genome-wide association studies have identified thousands of disease-associated single nucleotide polymorphisms (SNPs). A subset of these SNPs may be additively combined to generate genetic risk scores (GRSs) that confer risk for a specific disease. Although the clinical validity of GRSs to predict risk of specific diseases has been well established, there is still a great need to determine their clinical utility by applying GRSs in primary care for cancer risk assessment and targeted intervention. Methods This clinical study involved 281 primary care patients without a personal history of breast, prostate or colorectal cancer who were 40–70 years old. DNA was obtained from a pre-existing biobank at NorthShore University HealthSystem. GRSs for colorectal cancer and breast or prostate cancer were calculated and shared with participants through their primary care provider. Additional data was gathered using questionnaires as well as electronic medical record information. A t-test or Chi-square test was applied for comparison of demographic and key clinical variables among different groups. Results The median age of the 281 participants was 58 years and the majority were female (66.6%). One hundred one (36.9%) participants received 2 low risk scores, 99 (35.2%) received 1 low risk and 1 average risk score, 37 (13.2%) received 1 low risk and 1 high risk score, 23 (8.2%) received 2 average risk scores, 21 (7.5%) received 1 average risk and 1 high risk score, and no one received 2 high risk scores. Before receiving GRSs, younger patients and women reported significantly more worry about risk of developing cancer. After receiving GRSs, those who received at least one high GRS reported significantly more worry about developing cancer. There were no significant differences found between gender, age, or GRS with regards to participants’ reported optimism about their future health neither before nor after receiving GRS results. Conclusions Genetic risk scores that quantify an individual’s risk of developing breast, prostate and colorectal cancers as compared with a race-defined population average risk have potential clinical utility as a tool for risk stratification and to guide cancer screening in a primary care setting.

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