scholarly journals The importance of gene–environment interactions in human obesity

2016 ◽  
Vol 130 (18) ◽  
pp. 1571-1597 ◽  
Author(s):  
Hudson Reddon ◽  
Jean-Louis Guéant ◽  
David Meyre
Keyword(s):  
Risk Factors ◽  
Genetic Risk ◽  
Environmental Exposures ◽  
Genetic Risk Factors ◽  
Human Obesity ◽  
Methodological Challenges ◽  
Gene Environment ◽  
The Impact

Current research has identified several environmental exposures that can moderate the impact of genetic risk factors on obesity. This paper reviews these studies (gene–environment interactions) in the obesity field and outlines the methodological challenges of these investigations.

Gene–environment interplay in the etiology of psychosis

2018 ◽  
Vol 48 (12) ◽  
pp. 1925-1936 ◽  
Author(s):  
Alyson Zwicker ◽  
Eileen M. Denovan-Wright ◽  
Rudolf Uher
Keyword(s):  
Environmental Factors ◽  
Genetic Risk ◽  
Environmental Exposures ◽  
Response To Treatment ◽  
Human Potential ◽  
Specific Gene ◽  
Environment Interaction ◽  
Gene Environment ◽  
Increased Risk ◽  
The Impact

AbstractSchizophrenia and other types of psychosis incur suffering, high health care costs and loss of human potential, due to the combination of early onset and poor response to treatment. Our ability to prevent or cure psychosis depends on knowledge of causal mechanisms. Molecular genetic studies show that thousands of common and rare variants contribute to the genetic risk for psychosis. Epidemiological studies have identified many environmental factors associated with increased risk of psychosis. However, no single genetic or environmental factor is sufficient to cause psychosis on its own. The risk of developing psychosis increases with the accumulation of many genetic risk variants and exposures to multiple adverse environmental factors. Additionally, the impact of environmental exposures likely depends on genetic factors, through gene–environment interactions. Only a few specific gene–environment combinations that lead to increased risk of psychosis have been identified to date. An example of replicable gene–environment interaction is a common polymorphism in theAKT1gene that makes its carriers sensitive to developing psychosis with regular cannabis use. A synthesis of results from twin studies, molecular genetics, and epidemiological research outlines the many genetic and environmental factors contributing to psychosis. The interplay between these factors needs to be considered to draw a complete picture of etiology. To reach a more complete explanation of psychosis that can inform preventive strategies, future research should focus on longitudinal assessments of multiple environmental exposures within large, genotyped cohorts beginning early in life.

Assessment of The Influence of Non-Genetic Risk Factors on The Disease Onset and Progression of Androgenetic Alopecia in Egyptian Males

QJM ◽  
2021 ◽  
Vol 114 (Supplement_1) ◽  
Author(s):  
Naziha Hafez Khafagy ◽  
Marwa Yassin Soltan ◽  
Ahmed Adel Ali Ali
Keyword(s):  
Risk Factors ◽  
Hair Loss ◽  
Genetic Risk ◽  
Disease Onset ◽  
Genetic Risk Factors ◽  
Androgenetic Alopecia ◽  
Major Type ◽  
Young Males ◽  
Potential Risk Factors ◽  
The Impact

Abstract Background Androgenetic alopecia (AGA) is a patterned hair loss with multifactorial background including genetic, hormonal as well as environmental and lifestyle-related risk factors. The impact of non-genetic risk factors on the onset and disease progression of androgenetic alopecia in Egyptian males. Objective To explore the potential role of non-genetic risk factors on the disease development and progression of androgenetic alopecia in Egyptian males. Patients and Methods The study included 2000 subjects with and without AGA, during the period from February 2019 to September 2019. The study protocol was approved by faculty of medicine, Ain Sham University, Research ethics committee (FWA 000017585). An informed written consent for participation in this study was obtained from patients and controls before enrollment. One thousand male patients with AGA were recruited in the study. The diagnosis was made via clinical diagnosis, dermatological findings, trichoscopic assessment. Results Our study showed that after skin examination 416 patients had acne and 344 patients had seborrhea, with statistically significant association to AGA cases. Conclusion From our study, it can be concluded that AGA became a major type of hair loss complaint among Egyptian males especially young males. Many potential risk factors were found to be associated with the disease as smoking, stress, obesity, family history, exercise, HTN and unbalanced diet. Avoidance of such risk factors may help improve the disease.

scholarly journals The impact of age on genetic risk for common diseases

2020 ◽  
Author(s):  
Xilin Jiang ◽  
Chris Holmes ◽  
Gil McVean
Keyword(s):  
Risk Factors ◽  
Recent Work ◽  
Genetic Risk ◽  
Genetic Risk Factors ◽  
Individual Risk ◽  
Uk Biobank ◽  
Common Diseases ◽  
The Impact ◽  
The Relationship ◽  
Over Time

AbstractInherited genetic variation contributes to individual risk for many complex diseases and is increasingly being used for predictive patient stratification. Recent work has shown that genetic factors are not equally relevant to human traits across age and other contexts, though the reasons for such variation are not clear. Here, we introduce methods to infer the form of the relationship between genetic risk for disease and age and to test whether all genetic risk factors behave similarly. We use a proportional hazards model within an interval-based censoring methodology to estimate age-varying individual variant contributions to genetic risk for 24 common diseases within the British ancestry subset of UK Biobank, applying a Bayesian clustering approach to group variants by their risk profile over age and permutation tests for age dependency and multiplicity of profiles. We find evidence for age-varying risk profiles in nine diseases, including hypertension, skin cancer, atherosclerotic heart disease, hypothyroidism and calculus of gallbladder, several of which show evidence, albeit weak, for multiple distinct profiles of genetic risk. The predominant pattern shows genetic risk factors having the greatest impact on risk of early disease, with a monotonic decrease over time, at least for the majority of variants although the magnitude and form of the decrease varies among diseases. We show that these patterns cannot be explained by a simple model involving the presence of unobserved covariates such as environmental factors. We discuss possible models that can explain our observations and the implications for genetic risk prediction.Author summaryThe genes we inherit from our parents influence our risk for almost all diseases, from cancer to severe infections. With the explosion of genomic technologies, we are now able to use an individual’s genome to make useful predictions about future disease risk. However, recent work has shown that the predictive value of genetic information varies by context, including age, sex and ethnicity. In this paper we introduce, validate and apply new statistical methods for investigating the relationship between age and genetic risk. These methods allow us to ask questions such as whether risk is constant over time, precisely how risk changes over time and whether all genetic risk factors have similar age profiles. By applying the methods to data from the UK Biobank, a prospective study of 500,000 people, we show that there is a tendency for genetic risk to decline with increasing age. We consider a series of possible explanations for the observation and conclude that there must be processes acting that we are currently unaware of, such as distinct phases of life in which genetic risk manifests itself, or interactions between genes and the environment.

scholarly journals Identifying Genetic Risk Factors for Diabetic Macular Edema and the Response to Treatment

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Rajya L. Gurung ◽  
Liesel M. FitzGerald ◽  
Bennet J. McComish ◽  
Nitin Verma ◽  
Kathryn P. Burdon
Keyword(s):  
Risk Factors ◽  
Macular Edema ◽  
Diabetic Macular Edema ◽  
Genetic Risk ◽  
Vision Loss ◽  
Genetic Risk Factors ◽  
Response To Treatment ◽  
Diabetic Eye Disease ◽  
Genetic And Environmental Factors ◽  
The Impact

Diabetic retinopathy (DR) is the most common microvascular complication of diabetes mellitus (DM). DR is complex and the term encompasses several clinical subtypes of diabetic eye disease, including diabetic macular edema (DME), the most frequent cause of central vision loss in DR patients. Both genetic and environmental factors contribute to the pathophysiology of DR and its subtypes. While numerous studies have identified several susceptibility genes for DR, few have investigated the impact of genetics on DME susceptibility. This review will focus on the current literature surrounding genetic risk factors associated with DME. We will also highlight the small number of studies investigating the genetics of response to antivascular endothelial growth factor (anti-VEGF) injection, which is used to treat DME.

scholarly journals Evidence, and replication thereof, that molecular-genetic and environmental risks for psychosis impact through an affective pathway

2020 ◽  
pp. 1-13
Author(s):  
Jim van Os ◽  
Lotta-Katrin Pries ◽  
Margreet ten Have ◽  
Ron de Graaf ◽  
Saskia van Dorsselaer ◽  
...  
Keyword(s):  
Risk Factors ◽  
Genetic Risk ◽  
Molecular Genetic ◽  
Population Sample ◽  
Genetic Risk Factors ◽  
Schizophrenia Spectrum Disorders ◽  
Affective Dysregulation ◽  
Delusional Ideation ◽  
Schizophrenia Spectrum ◽  
The Impact

Abstract Background There is evidence that environmental and genetic risk factors for schizophrenia spectrum disorders are transdiagnostic and mediated in part through a generic pathway of affective dysregulation. Methods We analysed to what degree the impact of schizophrenia polygenic risk (PRS-SZ) and childhood adversity (CA) on psychosis outcomes was contingent on co-presence of affective dysregulation, defined as significant depressive symptoms, in (i) NEMESIS-2 (n = 6646), a representative general population sample, interviewed four times over nine years and (ii) EUGEI (n = 4068) a sample of patients with schizophrenia spectrum disorder, the siblings of these patients and controls. Results The impact of PRS-SZ on psychosis showed significant dependence on co-presence of affective dysregulation in NEMESIS-2 [relative excess risk due to interaction (RERI): 1.01, p = 0.037] and in EUGEI (RERI = 3.39, p = 0.048). This was particularly evident for delusional ideation (NEMESIS-2: RERI = 1.74, p = 0.003; EUGEI: RERI = 4.16, p = 0.019) and not for hallucinatory experiences (NEMESIS-2: RERI = 0.65, p = 0.284; EUGEI: −0.37, p = 0.547). A similar and stronger pattern of results was evident for CA (RERI delusions and hallucinations: NEMESIS-2: 3.02, p < 0.001; EUGEI: 6.44, p < 0.001; RERI delusional ideation: NEMESIS-2: 3.79, p < 0.001; EUGEI: 5.43, p = 0.001; RERI hallucinatory experiences: NEMESIS-2: 2.46, p < 0.001; EUGEI: 0.54, p = 0.465). Conclusions The results, and internal replication, suggest that the effects of known genetic and non-genetic risk factors for psychosis are mediated in part through an affective pathway, from which early states of delusional meaning may arise.

Non-genetic risk factors for atrial fibrillation are equally important in both young and old age: A nationwide population-based study

2020 ◽  
pp. 204748732091566
Author(s):  
Yun Gi Kim ◽  
Kyung-Do Han ◽  
Jong-Il Choi ◽  
Yun Young Choi ◽  
Ha Young Choi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Alcohol Consumption ◽  
Genetic Risk ◽  
Age Groups ◽  
Genetic Risk Factors ◽  
Population Based ◽  
The Impact ◽  
Onset Atrial Fibrillation ◽  
New Onset

Aims There are several non-genetic risk factors for new-onset atrial fibrillation, including age, sex, obesity, hypertension, diabetes, and alcohol consumption. However, whether these non-genetic risk factors have equal significance among different age groups is not known. We performed a nationwide population-based analysis to compare the clinical significance of non-genetic risk factors for new-onset atrial fibrillation in various age groups. Methods and results A total of 9,797,409 people without a prior diagnosis of atrial fibrillation who underwent a national health check-up in 2009 were included. During 80,130,090 person-years of follow-up, a total of 196,136 people were diagnosed with new-onset atrial fibrillation. The impact of non-genetic risk factors on new-onset atrial fibrillation was examined in different age groups. Obesity, male sex, heavy alcohol consumption, smoking, hypertension, diabetes and chronic kidney disease were associated with an increased risk of new-onset atrial fibrillation. With minor variations, these risk factors were consistently associated with the risk of new-onset atrial fibrillation among various age groups. Using these risk factors, we created a scoring system to predict future risk of new-onset atrial fibrillation in different age groups. In receiver operating characteristic curve analysis, the predictive value of these risk factors ranged between 0.556 and 0.603, and no significant trends were observed. Conclusions Non-genetic risk factors for new-onset atrial fibrillation may have a similar impact on different age groups. Except for sex, these non-genetic risk factors can be modifiable. Therefore, efforts to control non-genetic risk factors might have relevance for both the young and old.

scholarly journals Influence of Acquired and Genetic Risk Factors on the Prevention, Management, and Treatment of Thromboembolic Disease

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Raghid Kreidy
Keyword(s):  
Risk Factors ◽  
Genetic Risk ◽  
Genetic Risk Factors ◽  
Thromboembolic Disease ◽  
Postthrombotic Syndrome ◽  
Gene Interactions ◽  
Recurrent Thrombosis ◽  
Gene Environment ◽  
Venous Thromboembolic ◽  
Associated Risk Factors

Prevention, management, and treatment of venous thromboembolism requires understanding of the epidemiology and associated risk factors, particularly in recognizing populations warranting prophylaxis, in evaluating patients with high risk situations, and in determining the duration of anticoagulation required to minimize recurrent thrombosis and to avoid postthrombotic syndrome. The present paper reviews recent advances concerning acquired and genetic risk factors for venous thrombosis, analyses individual risks related to age, and focuses on thrombotic genetic risk factors and the synergistic gene-environment and gene-gene interactions and their importance in the management and treatment of venous thromboembolic disease.

AWARE: Randomized study of an EMR-based intervention targeting hereditary cancer (CA) risk awareness in peri-op CA patients (pts).

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e13119-e13119
Author(s):  
Michael J. Hall ◽  
Elizabeth Handorf ◽  
Yana Chertock ◽  
Cindy A Keleher ◽  
Mark Siemon ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Genetic Risk ◽  
Perceived Risk ◽  
Information Needs ◽  
Randomized Study ◽  
Genetic Risk Factors ◽  
Risk Awareness ◽  
The Impact

e13119 Background: Pts having CA surgery have high information needs related to diagnosis, stage, and what caused their CA. Direct EMR access via web portals has grown, and offers a novel means to integrate supplemental health information into the e-chart, such as relevant genetic risk of CA. The AWARE trial (Advancing Web-based Medical Record Access and Risk Evaluation for Cancer Patients) studied the impact of providing personalized pathology (pPATH) and pers/fam history (PFHx) summaries enhanced with information about genetic CA risk and risk assessment. Methods: Peri-op CA pts completed baseline and 3-mo follow-up surveys. Pts randomized to enhanced (E) arm received pPATH & PFHx summaries with embedded tailored info about genetic CA risk and relevant high-risk features. Unenhanced (U) arm got pPATH & PFHx only. Use of summaries and 2 “Genetic risk: Learn more” links was tracked. Outcomes-Primary: awareness, knowledge (of genetic CA risk); Secondary: perceived risk, use of “Learn more” links, intentions/actions toward risk assessment--were stratified by genetic risk factors reported at baseline (0-1, 2+) & use of “Learn more” links. Results: 171 pts consented; men (p = 0.003) & non-White (p = 0.02) were more likely to decline the study. Overall 149 (87%) were randomized & eligible to use AWARE: 109 (73%) logged in, 120 (81%) completed follow-up. Predictors of AWARE use: White race (p < 0.05), sib w/CA (p < 0.05), and use intention (p = 0.005). Reporting 2+ genetic risk factors at baseline predicted use of pPATH, PFHx, and “Learn more” (all p < 0.001). Awareness increased overall (p < 0.002), but between arm changes in primary outcomes were not significant. E arm (vs U) was borderline more likely to seek risk assessment (32% v 18%, p = 0.09), with impact stronger in pts reporting baseline 0-1 (p = 0.035) vs 2+ risk factors (p = 0.7). Among E arm pts who used “Learn more” links, intentions (p = 0.054) & behaviors (p = 0.035) to seek risk assessment increased. Conclusions: AWARE increased genetic risk awareness overall, but primary outcomes were not met. Usage data and secondary outcomes highlight potential for EMR-based interventions to positively impact preventive behaviors toward genetic risk assessment.

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