scholarly journals Genetic liability for substance use associated with medical comorbidities in electronic health records of African- and European-ancestry individuals

2021 ◽  
Author(s):  
Emily E. Hartwell ◽  
Alison K. Merikangas ◽  
Shefali S. Verma ◽  
Marylyn D. Ritchie ◽  
Henry R. Kranzler ◽  
...  
Keyword(s):  
Substance Use ◽  
Genetic Risk ◽  
Smoking Initiation ◽  
European Ancestry ◽  
Risk Scores ◽  
Opioid Use ◽  
Genetic Liability ◽  
Association Analyses ◽  
Electronic Health ◽  
Trait Associations

AbstractPolygenic risk scores (PRS) represent an individual’s summed genetic risk for a trait and can serve as biomarkers for disease. Less is known about the utility of PRS as a means to quantify genetic risk for substance use disorders (SUDs) than for many other traits. Nonetheless, the growth of large, electronic health record-based biobanks makes it possible to evaluate the association of SUD PRS with other traits. We calculated PRS for smoking initiation, alcohol use disorder (AUD), and opioid use disorder (OUD) using summary statistics from the Million Veteran Program sample. We then tested the association of each PRS with its primary phenotype in the Penn Medicine BioBank (PMBB) using all available genotyped participants of African or European ancestry (AFR and EUR, respectively) (N=18,612). Finally, we conducted phenome-wide association analyses (PheWAS) separately by ancestry and sex to test for associations across disease categories. Tobacco use disorder was the most common SUD in the PMBB, followed by AUD and OUD, consistent with the population prevalence of these disorders. All PRS were associated with their primary phenotype in both ancestry groups. PheWAS results yielded cross-trait associations across multiple domains, including psychiatric disorders and medical conditions. SUD PRS were associated with their primary phenotypes, however they are not yet predictive enough to be useful diagnostically. The cross-trait associations of the SUD PRS are indicative of a broader genetic liability. Future work should extend findings to additional population groups and for other substances of abuse.

scholarly journals Polygenic risk of psychiatric disorders exhibits cross-trait associations in electronic health record data

2019 ◽  
Author(s):  
Rachel L. Kember ◽  
Alison K. Merikangas ◽  
Shefali S. Verma ◽  
Anurag Verma ◽  
Renae Judy ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Clinical Setting ◽  
Complex Traits ◽  
Disease Risk ◽  
Risk Scores ◽  
Electronic Health Record Data ◽  
Association Analyses ◽  
Polygenic Risk ◽  
Electronic Health ◽  
Trait Associations

AbstractObjectivePrediction of disease risk is a key component of precision medicine. Common, complex traits such as psychiatric disorders have a complex polygenic architecture making the identification of a single risk predictor difficult. Polygenic risk scores (PRS) denoting the sum of an individual’s genetic liability for a disorder are a promising biomarker for psychiatric disorders, but require evaluation in a clinical setting.MethodsWe develop PRS for six psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, cross disorder, attention-deficit/hyperactivity disorder, anorexia nervosa) and 17 non-psychiatric traits in over 10,000 individuals from the Penn Medicine Biobank with accompanying electronic health records. We perform phenome-wide association analyses to test their association across disease categories.ResultsFour of the six psychiatric PRS were associated with their primary phenotypes (odds ratios between 1.2-1.6). Individuals in the highest quintile of risk had between 1.4-2.9 times higher odds of the disorder than the remaining 80% of individuals. Cross-trait associations were identified both within the psychiatric domain and across trait domains. PRS for coronary artery disease and years of education were significantly associated with psychiatric disorders, largely driven by an association with tobacco use disorder.ConclusionsWe demonstrate that the genetic architecture of common psychiatric disorders identified in a clinical setting confirms that which has been derived from large consortia. Even though the risk associated is low in this context, these results suggest that as identification of genetic markers proceeds, PRS is a promising approach for prediction of psychiatric disorders and associated conditions in clinical registries.

scholarly journals Applicability of Obesity-Related SNPs and Their Effect Size Measures Defined on Populations with European Ancestry for Genetic Risk Estimation among Roma

Genes ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 516 ◽  
Author(s):  
Erand Llanaj ◽  
Péter Pikó ◽  
Károly Nagy ◽  
Gábor Rácz ◽  
Sándor János ◽  
...  
Keyword(s):  
Effect Size ◽  
Genetic Risk ◽  
Association Studies ◽  
Strong Association ◽  
European Ancestry ◽  
Risk Scores ◽  
Nucleotide Polymorphisms ◽  
Continuous Variables ◽  
Roma Population ◽  
The Impact

Investigations on the impact of genetic factors on the development of obesity have been limited regarding the Roma population—the largest and most vulnerable ethnic minority in Europe of Asian origin. Genetic variants identified from genetic association studies are primarily from European populations. With that in mind, we investigated the applicability of data on selected obesity-related single nucleotide polymorphisms (SNPs), obtained from the Hungarian general (HG) population of European origin, on the Hungarian Roma (HR) population. Twenty preselected SNPs in susceptible alleles, known to be significantly associated with obesity-related phenotypes, were used to estimate the effect of these SNPs on body mass index (BMI) and waist circumference (WC) in HG (N = 1783) and HR (N = 1225) populations. Single SNP associations were tested using linear and logistic regression models, adjusted for known covariates. Out of 20 SNPs, four located in FTO (rs1121980, rs1558902, rs9939609, and rs9941349) showed strong association with BMI and WC as continuous variables in both samples. Computations based on Adult Treatment Panel III (ATPIII) and the International Diabetes Federation’s (IDF) European and Asian criteria showed rs9941349 in FTO to be associated only with WC among both populations, and two SNPs (rs2867125, rs6548238) in TMEM18 associated with WC only in HG population. A substantial difference (both in direction and effect size) was observed only in the case of rs1801282 in PPARγ on WC as a continuous outcome. Findings suggest that genetic risk scores based on counting SNPs with relatively high effect sizes, defined based on populations with European ancestry, can sufficiently allow estimation of genetic susceptibility for Roma. Further studies are needed to clarify the role of SNP(s) with protective effect(s).

scholarly journals Testing Familial Transmission of Smoking With Two Different Research Designs

2017 ◽  
Vol 20 (7) ◽  
pp. 836-842 ◽  
Author(s):  
Jorien L Treur ◽  
Karin J H Verweij ◽  
Abdel Abdellaoui ◽  
Iryna O Fedko ◽  
Eveline L de Zeeuw ◽  
...  
Keyword(s):  
The Netherlands ◽  
Family Environment ◽  
Genetic Risk ◽  
Genetic Factors ◽  
Environmental Influence ◽  
Smoking Initiation ◽  
Risk Scores ◽  
Environment Interaction ◽  
Polygenic Risk ◽  
Children Of Twins

Abstract Introduction Classical twin studies show that smoking is heritable. To determine if shared family environment plays a role in addition to genetic factors, and if they interact (G×E), we use a children-of-twins design. In a second sample, we measure genetic influence with polygenic risk scores (PRS) and environmental influence with a question on exposure to smoking during childhood. Methods Data on smoking initiation were available for 723 children of 712 twins from the Netherlands Twin Register (64.9% female, median birth year 1985). Children were grouped in ascending order of risk, based on smoking status and zygosity of their twin-parent and his/her co-twin: never smoking twin-parent with a never smoking co-twin; never smoking twin-parent with a smoking dizygotic co-twin; never smoking twin-parent with a smoking monozygotic co-twin; and smoking twin-parent with a smoking or never smoking co-twin. For 4072 participants from the Netherlands Twin Register (67.3% female, median birth year 1973), PRS for smoking were computed and smoking initiation, smoking heaviness, and exposure to smoking during childhood were available. Results Patterns of smoking initiation in the four group children-of-twins design suggested shared familial influences in addition to genetic factors. PRS for ever smoking were associated with smoking initiation in all individuals. PRS for smoking heaviness were associated with smoking heaviness in individuals exposed to smoking during childhood, but not in non-exposed individuals. Conclusions Shared family environment influences smoking, over and above genetic factors. Genetic risk of smoking heaviness was only important for individuals exposed to smoking during childhood, versus those not exposed (G×E). Implications This study adds to the very few existing children-of-twins (CoT) studies on smoking and combines a CoT design with a second research design that utilizes polygenic risk scores and data on exposure to smoking during childhood. The results show that shared family environment affects smoking behavior over and above genetic factors. There was also evidence for gene–environment interaction (G×E) such that genetic risk of heavy versus light smoking was only important for individuals who were also exposed to (second-hand) smoking during childhood. Together, these findings give additional incentive to recommending parents not to expose their children to cigarette smoking.

scholarly journals 1389Do associations between a healthy lifestyle and incidence of cancer differ by genetic risk?

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Stephanie Byrne ◽  
Terry Boyle ◽  
Beben Benyamin ◽  
Sang Hong Lee ◽  
Muktar Ahmed ◽  
...  
Keyword(s):  
Cancer Risk ◽  
Cancer Incidence ◽  
Genetic Risk ◽  
Cox Regression ◽  
Healthy Lifestyle ◽  
Lymphocytic Leukemia ◽  
European Ancestry ◽  
Risk Scores ◽  
Increased Risk ◽  
Cancer Types

Abstract Background It is unknown whether relationships between lifestyle and cancer differ by genetic risk. We investigated this for 13 cancer types using prospective data from the UK Biobank. Methods In 2006-2010, participants aged 37-73 years completed an assessment and provided biological samples. Those of European ancestry with no history of malignant cancer were included in our analysis (n = 196,485). For each individual, a healthy lifestyle index (HLI) was calculated based on recommendations, and polygenic risk scores (PRSs) were computed for 13 cancer types. Relationships with cancer incidence were assessed by cox regression, adjusting for age, sex, assessment centre, birth location, and measures of socioeconomic status. Interactions between the HLI and PRSs were explored. Results For all cancer outcomes, a high genetic risk was associated with an increased cancer risk, or there was a trend in that direction. Those in the top PRS tertile had a greater than 2-fold increased risk of colorectal cancer (HR[95%CI]=2.18[1.90,2.49]), pancreatic cancer (2.39[1.71,3.32]) and lymphocytic leukemia (2.45[1.67,3.59]). An unhealthy lifestyle was associated with a higher cancer risk for 8 cancer types, with strong relationships observed for lung (3.41[2.76,4.20]), pancreatic (2.06[1.47,2.91]), bladder (1.95[1.43,2.66]) and kidney cancers (1.90[1.43,2.54]). No interactions between HLI and PRSs were detected (all interaction p-values>0.10). Conclusions Associations between lifestyle and cancer incidence did not differ by genetic risk. Key messages A healthy lifestyle can reduce the risk of several cancers, even in those who are genetically predisposed to develop cancer.

Genetic liability to suicide attempt, suicide death, and psychiatric and substance use disorders on the risk for suicide attempt and suicide death: a Swedish national study

2021 ◽  
pp. 1-10
Author(s):  
Kenneth S. Kendler ◽  
Henrik Ohlsson ◽  
Eve K. Mościcki ◽  
Jan Sundquist ◽  
Alexis C. Edwards ◽  
...  
Keyword(s):  
Suicide Attempt ◽  
Psychiatric Disorders ◽  
Genetic Risk ◽  
Risk Scores ◽  
National Study ◽  
Multivariate Models ◽  
Genetic Liability ◽  
Suicide Death ◽  
Younger Age ◽  
The Impact

Abstract Background How does genetic liability to suicide attempt (SA), suicide death (SD), major depression (MD), bipolar disorder (BD), schizophrenia (SZ), alcohol use disorder (AUD), and drug use disorder (DUD) impact on risk for SA and SD? Methods In the Swedish general population born 1932–1995 and followed through 2017 (n = 7 661 519), we calculate family genetic risk scores (FGRS) for SA, SD, MD, BD, SZ, AUD, and DUD. Registration for SA and SD was assessed from Swedish national registers. Results In univariate and multivariate models predicting SA, FGRS were highest for SA, AUD, DUD, and MD. In univariate models predicting SD, the strongest FGRS were AUD, DUD, SA, and SD. In multivariate models, the FGRS for SA and AUD were higher in predicting SA while the FGRS for SD, BD, and SZ were higher in predicting SD. Higher FGRS for all disorders significantly predicted both younger age at first SA and frequency of attempts. For SD, higher FGRS for MD, AUD, and SD predicted later age at SD. Mediation of FGRS effects on SA and SD was more pronounced for SD than SA, strongest for AUD, DUD, and SZ FGRS and weakest for MD. Conclusions FGRS for both SA and SD and for our five psychiatric disorders impact on risk for SA and SD in a complex manner. While some of the impact of genetic risk factors for psychiatric disorders on risk for SA and SD is mediated through developing the disorders, these risks also predispose directly to suicidal behaviors.

scholarly journals Interaction between Genetic Risk Scores for reduced pulmonary function and smoking, asthma and endotoxin

Thorax ◽  
2021 ◽  
pp. thoraxjnl-2020-215624
Author(s):  
Sinjini Sikdar ◽  
Annah B Wyss ◽  
Mi Kyeong Lee ◽  
Thanh T Hoang ◽  
Marie Richards ◽  
...  
Keyword(s):  
Pulmonary Function ◽  
Genetic Risk ◽  
Association Studies ◽  
European Ancestry ◽  
Risk Scores ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Inverse Association ◽  
Genetic Risk Scores ◽  
Genome Wide

RationaleGenome-wide association studies (GWASs) have identified numerous loci associated with lower pulmonary function. Pulmonary function is strongly related to smoking and has also been associated with asthma and dust endotoxin. At the individual SNP level, genome-wide analyses of pulmonary function have not identified appreciable evidence for gene by environment interactions. Genetic Risk Scores (GRSs) may enhance power to identify gene–environment interactions, but studies are few.MethodsWe analysed 2844 individuals of European ancestry with 1000 Genomes imputed GWAS data from a case–control study of adult asthma nested within a US agricultural cohort. Pulmonary function traits were FEV1, FVC and FEV1/FVC. Using data from a recent large meta-analysis of GWAS, we constructed a weighted GRS for each trait by combining the top (p value<5×10−9) genetic variants, after clumping based on distance (±250 kb) and linkage disequilibrium (r2=0.5). We used linear regression, adjusting for relevant covariates, to estimate associations of each trait with its GRS and to assess interactions.ResultsEach trait was highly significantly associated with its GRS (all three p values<8.9×10−8). The inverse association of the GRS with FEV1/FVC was stronger for current smokers (pinteraction=0.017) or former smokers (pinteraction=0.064) when compared with never smokers and among asthmatics compared with non-asthmatics (pinteraction=0.053). No significant interactions were observed between any GRS and house dust endotoxin.ConclusionsEvaluation of interactions using GRSs supports a greater impact of increased genetic susceptibility on reduced pulmonary function in the presence of smoking or asthma.

scholarly journals Inclusion of Variants Discovered from Diverse Populations Improves Polygenic Risk Score Transferability

2020 ◽  
Author(s):  
Taylor B. Cavazos ◽  
John S. Witte
Keyword(s):  
Genetic Risk ◽  
African Ancestry ◽  
European Ancestry ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
Genetic Risk Prediction ◽  
Causal Variants ◽  
The Uk ◽  
The Relationship

ABSTRACTThe majority of polygenic risk scores (PRS) have been developed and optimized in individuals of European ancestry and may have limited generalizability across other ancestral populations. Understanding aspects of PRS that contribute to this issue and determining solutions is complicated by disease-specific genetic architecture and limited knowledge of sharing of causal variants and effect sizes across populations. Motivated by these challenges, we undertook a simulation study to assess the relationship between ancestry and the potential bias in PRS developed in European ancestry populations. Our simulations show that the magnitude of this bias increases with increasing divergence from European ancestry, and this is attributed to population differences in linkage disequilibrium and allele frequencies of European discovered variants, likely as a result of genetic drift. Importantly, we find that including into the PRS variants discovered in African ancestry individuals has the potential to achieve unbiased estimates of genetic risk across global populations and admixed individuals. We confirm our simulation findings in an analysis of HbA1c, asthma, and prostate cancer in the UK Biobank. Given the demonstrated improvement in PRS prediction accuracy, recruiting larger diverse cohorts will be crucial—and potentially even necessary—for enabling accurate and equitable genetic risk prediction across populations.

Prostate cancer meta-analysis from more than 145,000 men to identify 65 novel prostate cancer susceptibility loci.

2017 ◽  
Vol 35 (6_suppl) ◽  
pp. 1-1
Author(s):  
Rosalind Eeles ◽  
Ali Amin Al Olama ◽  
Sonja Berndt ◽  
Fredrik Wiklund ◽  
David V Conti ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Relative Risk ◽  
Genetic Risk ◽  
Cancer Susceptibility ◽  
Association Studies ◽  
Genetic Risk Score ◽  
European Ancestry ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Susceptibility Loci

1 Background: Currently genome-wide association studies (GWAS) have identified over 100 prostate cancer (PrCa) susceptibility loci, capturing 33% of the PrCa familial relative risk (FRR) in Europeans. To identify further susceptibility variants, we conducted a PrCa GWAS, larger than previous studies, comprising ~49,000 cases and ~29,000 controls among individuals of European and Asian descent using the OncoArray, a platform consisting of a 260K GWAS backbone and 310K custom content selected from previous GWAS and fine-mapping studies of multiple cancers ( http://epi.grants.cancer.gov/oncoarray/ ). Methods: Genotypes from the OncoArray were used to impute genotypes from ~70M variants using the October 2014 release of the 1000 genomes project as a reference, and then combined with several previous PrCa GWAS of European ancestry: UK stage 1 (1,906 cases/1,934 controls) and stage 2 (3,888 cases/3,956 controls); CaPS 1 (498 cases/502 controls) and CaPS 2 (1,483 cases/519 controls); BPC3 (2,137 cases/3,101 controls); NCI PEGASUS (4,622 cases/2,954 controls); and iCOGS (21,209 cases/ 20,440 controls). Risk analyses for overall PrCa risk, aggressive PrCa (several definitions defined by PrCa clinical characteristics), and Gleason score were performed. Logistic and linear regression summary statistics were meta-analysed using an inverse variance fixed effect approach. Results: We identified novel loci significantly associated ( P < 5.0x10-8) with overall PrCa (N = 65). Our novel findings are comprised of several missense variants, including a SNP in the ATM gene - a key member of the DNA repair pathway. When combined multiplicatively, the 65 novel PrCa loci identified here increases the captured heritability of PrCa, explaining 38.5% of the FRR when combining novel and previously identified PrCa loci. Conclusions: In risk stratification, men in the top 1% of the genetic risk score group have a relative risk of 5.6 fold for developing PrCa compared with the median risk group. These results will improve the utility of genetic risk scores for targeted screening and prevention for prostate cancer.

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