scholarly journals Childhood socioeconomic status moderates genetic predisposition for peak smoking

2018 ◽  
Author(s):  
Laura Bierut ◽  
Pietro Biroli ◽  
Titus J. Galama ◽  
Kevin Thom
Keyword(s):  
At Risk ◽  
Socioeconomic Status ◽  
Genetic Predisposition ◽  
Genetic Variants ◽  
Genetic Risk ◽  
Risk Scores ◽  
Low Ses ◽  
High Genetic Risk ◽  
Childhood Socioeconomic Status ◽  
The U.S

AbstractSmoking is the leading cause of preventable disease and death in the U.S., and it is strongly influenced both by genetic predisposition and childhood socioeconomic status (SES). Using genetic variants exhibiting credible and robust associations with smoking, we construct polygenic risk scores (PGS) and evaluate whether childhood SES mediates genetic risk in determining peak-cigarette consumption in adulthood. We find a substantial protective effect of childhood SES for those genetically at risk of smoking: adult smokers who grew up in high-SES households tend to smoke roughly the same amount of cigarettesper day at peak (∼ 23 for low and ∼ 25 for high genetic risk individuals, or about 8%more), while individuals from low-SES backgrounds tend to smoke substantially more ifgenetically at risk (∼ 25 for low and ∼ 32 for high genetic risk individuals, or about 28% more).

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<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 Childhood socioeconomic status and genetic risk for poorer cognition in later life

2018 ◽  
Vol 212 ◽  
pp. 219-226 ◽  
Author(s):  
Sara M. Moorman ◽  
Kyle Carr ◽  
Emily A. Greenfield
Keyword(s):  
Socioeconomic Status ◽  
Genetic Risk ◽  
Later Life ◽  
Childhood Socioeconomic Status

scholarly journals Impact of Socioeconomic Status and Race on Sepsis Epidemiology and Outcomes

2020 ◽  
Author(s):  
Emi Minejima ◽  
Annie Wong-Beringer
Keyword(s):  
Socioeconomic Status ◽  
Low Income ◽  
Formal Education ◽  
Geographic Location ◽  
The United States ◽  
Risk Scores ◽  
Low Ses ◽  
The Relationship ◽  
Poor Health Literacy ◽  
Hispanic White

Abstract Background Socioeconomic status (SES) is a complex variable that is derived primarily from an individual’s education, income, and occupation and has been found to be inversely related to outcomes of health conditions. Sepsis is the sixth most common admitting diagnosis and one of the most costly conditions for in-hospital spending in the United States. The objective of this review is to report on the relationship between SES and sepsis incidence and associated outcomes. Content Sepsis epidemiology varies when explored by race, education, geographic location, income, and insurance status. Sepsis incidence was significantly increased in individuals of Black race compared with non-Hispanic white race; in persons who have less formal education, who lack insurance, and who have low income; and in certain US regions. People with low SES are likely to have onset of sepsis significantly earlier in life and to have poorly controlled comorbidities compared with those with higher SES. Sepsis mortality and hospital readmission is increased in individuals who lack insurance, who reside in low-income or medically underserved areas, who live far from healthcare, and who lack higher level education; however, a person’s race was not consistently found to increase mortality. Summary Interventions to minimize healthcare disparity for individuals with low SES should target sepsis prevention with increasing measures for preventive care for chronic conditions. Significant barriers described for access to care by people with low SES include cost, transportation, poor health literacy, and lack of a social network. Future studies should include polysocial risk scores that are consistently defined to allow for meaningful comparison across studies.

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 Assessment of first and second degree relatives of individuals with bipolar disorder shows increased genetic risk scores in both affected relatives and young At‐Risk Individuals

2015 ◽  
Vol 168 (7) ◽  
pp. 617-629 ◽  
Author(s):  
Janice M. Fullerton ◽  
Daniel L. Koller ◽  
Howard J. Edenberg ◽  
Tatiana Foroud ◽  
Hai Liu ◽  
...  
Keyword(s):  
At Risk ◽  
Bipolar Disorder ◽  
Genetic Risk ◽  
Risk Scores ◽  
Genetic Risk Scores ◽  
Second Degree

scholarly journals Multiomic blood correlates of genetic risk identify presymptomatic disease alterations

2020 ◽  
Vol 117 (35) ◽  
pp. 21813-21820
Author(s):  
Michael Wainberg ◽  
Andrew T. Magis ◽  
John C. Earls ◽  
Jennifer C. Lovejoy ◽  
Nasa Sinnott-Armstrong ◽  
...  
Keyword(s):  
Biological Networks ◽  
Genetic Risk ◽  
Complex Traits ◽  
Clinical Laboratory ◽  
Clinical Symptoms ◽  
Association Studies ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
High Genetic Risk ◽  
Genetic And Environmental Factors

Transitions from health to disease are characterized by dysregulation of biological networks under the influence of genetic and environmental factors, often over the course of years to decades before clinical symptoms appear. Understanding these dynamics has important implications for preventive medicine. However, progress has been hindered both by the difficulty of identifying individuals who will eventually go on to develop a particular disease and by the inaccessibility of most disease-relevant tissues in living individuals. Here we developed an alternative approach using polygenic risk scores (PRSs) based on genome-wide association studies (GWAS) for 54 diseases and complex traits coupled with multiomic profiling and found that these PRSs were associated with 766 detectable alterations in proteomic, metabolomic, and standard clinical laboratory measurements (clinical labs) from blood plasma across several thousand mostly healthy individuals. We recapitulated a variety of known relationships (e.g., glutamatergic neurotransmission and inflammation with depression, IL-33 with asthma) and found associations directly suggesting therapeutic strategies (e.g., Ω-6 supplementation and IL-13 inhibition for amyotrophic lateral sclerosis) and influences on longevity (leukemia inhibitory factor, ceramides). Analytes altered in high-genetic-risk individuals showed concordant changes in disease cases, supporting the notion that PRS-associated analytes represent presymptomatic disease alterations. Our results provide insights into the molecular pathophysiology of a range of traits and suggest avenues for the prevention of health-to-disease transitions.

scholarly journals Effective elements of Dutch care-physical activity initiatives for low socioeconomic status adults

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
L S Mulderij ◽  
F Wolters ◽  
M A E Wagemakers ◽  
K T Verkooijen
Keyword(s):  
Physical Activity ◽  
At Risk ◽  
Health Promotion ◽  
Socioeconomic Status ◽  
Concept Mapping ◽  
Low Socioeconomic Status ◽  
Intersectoral Collaboration ◽  
Low Ses ◽  
Low Socioeconomic ◽  
Lifestyle Related Diseases

Abstract Background In care-physical activity (care-PA) initiatives, primary care and sports collaborate to stimulate PA among adults at risk of lifestyle related diseases. Preliminary results of Dutch care-PA initiatives for low socioeconomic status (SES) adults indicate that these initiatives successfully lower participants’ body weight and improve quality of life. However, insight into elements that make these initiatives work is lacking. Therefore, this research aims to unravel the effective elements of care-PA initiatives for low SES adults. Methods Concept Mapping (CM) was used as tool to identify and cluster the effective elements. Nineteen Dutch health promotion experts individually listed as many elements as they felt were of importance to the effectiveness of care-PA initiatives. Next, each expert was asked to cluster the elements and to score them on importance. Then, CS Global MAX software was used for multidimensional scaling and a hierarchical cluster analysis to develop a cluster map. Finally, the cluster map was presented, discussed, and refined in a group meeting with 11 of the experts. Results The experts came up with 113 unique effective elements of care-PA initiatives for low SES adults, clustered into 11 clusters: 1) approach of professionals, 2) barriers experienced during the programme, 3) local embedding, 4) customisation of the programme to target population, 5) social support, 6) methods within the programme, 7) competencies of professionals, 8) accessibility of the programme, 9) actions within the programme, 10) recruitment of participants, and 11) intersectoral collaboration. Conclusions A valuable overview of the effective elements of care-PA initiatives for low SES adults was created. The results can be used to improve existing care-PA initiatives and to develop new ones targeted at low SES adults at risk of lifestyle related diseases. This may eventually help to reduce health inequalities between low and high SES adults. Key messages Concept mapping has been a useful group-based tool to obtain information on the effective elements of care-PA initiatives, in which individual input from health promotion experts has been collected. The overview of effective elements of care-PA initiatives for low SES adults as presented in this study is valuable for the development of care-PA initiatives specifically targeted at low SES adults.

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