scholarly journals Association of Established Blood Pressure Loci With 10‐Year Change in Blood Pressure and Their Ability to Predict Incident Hypertension

2020 ◽  
Vol 9 (16) ◽  
Author(s):  
Alaitz Poveda ◽  
Naeimeh Atabaki‐Pasdar ◽  
Shafqat Ahmad ◽  
Göran Hallmans ◽  
Frida Renström ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Genetic Variants ◽  
Association Studies ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Swedish Population ◽  
Long Term Changes ◽  
Traditional Risk Factors

Background Genome‐wide association studies have identified >1000 genetic variants cross‐sectionally associated with blood pressure variation and prevalent hypertension. These discoveries might aid the early identification of subpopulations at risk of developing hypertension or provide targets for drug development, amongst other applications. The aim of the present study was to analyze the association of blood pressure‐associated variants with long‐term changes (10 years) in blood pressure and also to assess their ability to predict hypertension incidence compared with traditional risk variables in a Swedish population. Methods and Results We constructed 6 genetic risk scores (GRSs) by summing the dosage of the effect allele at each locus of genetic variants previously associated with blood pressure traits (systolic blood pressure GRS (GRS SBP ): 554 variants; diastolic blood pressure GRS (GRS DBP ): 481 variants; mean arterial pressure GRS (GRS MAP ): 20 variants; pulse pressure GRS (GRS PP ): 478 variants; hypertension GRS (GRS HTN ): 22 variants; combined GRS (GRS com b ): 1152 variants). Each GRS was longitudinally associated with its corresponding blood pressure trait, with estimated effects per GRS SD unit of 0.50 to 1.21 mm Hg for quantitative traits and odds ratios (ORs) of 1.10 to 1.35 for hypertension incidence traits. The GRS comb was also significantly associated with hypertension incidence defined according to European guidelines (OR, 1.22 per SD; 95% CI, 1.10‒1.35) but not US guidelines (OR, 1.11 per SD; 95% CI, 0.99‒1.25) while controlling for traditional risk factors. The addition of GRS comb to a model containing traditional risk factors only marginally improved discrimination (Δarea under the ROC curve = 0.001–0.002). Conclusions GRSs based on discovered blood pressure‐associated variants are associated with long‐term changes in blood pressure traits and hypertension incidence, but the inclusion of genetic factors in a model composed of conventional hypertension risk factors did not yield a material increase in predictive ability.

GWAS contribution to atrial fibrillation and atrial fibrillation-related stroke: pathophysiological implications

2019 ◽  
Vol 20 (10) ◽  
pp. 765-780 ◽  
Author(s):  
Diana Cruz ◽  
Ricardo Pinto ◽  
Margarida Freitas-Silva ◽  
José Pedro Nunes ◽  
Rui Medeiros
Keyword(s):  
Atrial Fibrillation ◽  
Genetic Variants ◽  
Complex Traits ◽  
Association Studies ◽  
Cardioembolic Stroke ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Genetic Determinants ◽  
Genome Wide ◽  
Genome Wide Significance

Atrial fibrillation (AF) and stroke are included in a group of complex traits that have been approached regarding of their study by susceptibility genetic determinants. Since 2007, several genome-wide association studies (GWAS) aiming to identify genetic variants modulating AF risk have been conducted. Thus, 11 GWAS have identified 26 SNPs (p < 5 × 10-2), of which 19 reached genome-wide significance (p < 5 × 10-8). From those variants, seven were also associated with cardioembolic stroke and three reached genome-wide significance in stroke GWAS. These associations may shed a light on putative shared etiologic mechanisms between AF and cardioembolic stroke. Additionally, some of these identified variants have been incorporated in genetic risk scores in order to elucidate new approaches of stroke prediction, prevention and treatment.

scholarly journals Critical Analysis of Genome-Wide Association Studies: Triple Negative Breast Cancer Quae Exempli Causa

2020 ◽  
Vol 21 (16) ◽  
pp. 5835
Author(s):  
Maria-Ancuta Jurj ◽  
Mihail Buse ◽  
Alina-Andreea Zimta ◽  
Angelo Paradiso ◽  
Schuyler S. Korban ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Genetic Risk ◽  
Triple Negative ◽  
Cancer Susceptibility ◽  
Association Studies ◽  
Breast Cancer Susceptibility ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Genome Wide

Genome-wide association studies (GWAS) are useful in assessing and analyzing either differences or variations in DNA sequences across the human genome to detect genetic risk factors of diseases prevalent within a target population under study. The ultimate goal of GWAS is to predict either disease risk or disease progression by identifying genetic risk factors. These risk factors will define the biological basis of disease susceptibility for the purposes of developing innovative, preventative, and therapeutic strategies. As single nucleotide polymorphisms (SNPs) are often used in GWAS, their relevance for triple negative breast cancer (TNBC) will be assessed in this review. Furthermore, as there are different levels and patterns of linkage disequilibrium (LD) present within different human subpopulations, a plausible strategy to evaluate known SNPs associated with incidence of breast cancer in ethnically different patient cohorts will be presented and discussed. Additionally, a description of GWAS for TNBC will be presented, involving various identified SNPs correlated with miRNA sites to determine their efficacies on either prognosis or progression of TNBC in patients. Although GWAS have identified multiple common breast cancer susceptibility variants that individually would result in minor risks, it is their combined effects that would likely result in major risks. Thus, one approach to quantify synergistic effects of such common variants is to utilize polygenic risk scores. Therefore, studies utilizing predictive risk scores (PRSs) based on known breast cancer susceptibility SNPs will be evaluated. Such PRSs are potentially useful in improving stratification for screening, particularly when combining family history, other risk factors, and risk prediction models. In conclusion, although interpretation of the results from GWAS remains a challenge, the use of SNPs associated with TNBC may elucidate and better contextualize these studies.

scholarly journals MR-LDP: a two-sample Mendelian randomization for GWAS summary statistics accounting for linkage disequilibrium and horizontal pleiotropy

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Qing Cheng ◽  
Yi Yang ◽  
Xingjie Shi ◽  
Kar-Fu Yeung ◽  
Can Yang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Linkage Disequilibrium ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Alternative Methods ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Causal Relationships ◽  
Disease Outcomes

Abstract The proliferation of genome-wide association studies (GWAS) has prompted the use of two-sample Mendelian randomization (MR) with genetic variants as instrumental variables (IVs) for drawing reliable causal relationships between health risk factors and disease outcomes. However, the unique features of GWAS demand that MR methods account for both linkage disequilibrium (LD) and ubiquitously existing horizontal pleiotropy among complex traits, which is the phenomenon wherein a variant affects the outcome through mechanisms other than exclusively through the exposure. Therefore, statistical methods that fail to consider LD and horizontal pleiotropy can lead to biased estimates and false-positive causal relationships. To overcome these limitations, we proposed a probabilistic model for MR analysis in identifying the causal effects between risk factors and disease outcomes using GWAS summary statistics in the presence of LD and to properly account for horizontal pleiotropy among genetic variants (MR-LDP) and develop a computationally efficient algorithm to make the causal inference. We then conducted comprehensive simulation studies to demonstrate the advantages of MR-LDP over the existing methods. Moreover, we used two real exposure–outcome pairs to validate the results from MR-LDP compared with alternative methods, showing that our method is more efficient in using all-instrumental variants in LD. By further applying MR-LDP to lipid traits and body mass index (BMI) as risk factors for complex diseases, we identified multiple pairs of significant causal relationships, including a protective effect of high-density lipoprotein cholesterol on peripheral vascular disease and a positive causal effect of BMI on hemorrhoids.

Performance of polygenic risk scores for cancer prediction in an academic biobank.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 1528-1528
Author(s):  
Heena Desai ◽  
Anh Le ◽  
Ryan Hausler ◽  
Shefali Verma ◽  
Anurag Verma ◽  
...  
Keyword(s):  
Risk Score ◽  
Genetic Variants ◽  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
European Americans ◽  
Genome Wide ◽  
Common Genetic Variants

1528 Background: The discovery of rare genetic variants associated with cancer have a tremendous impact on reducing cancer morbidity and mortality when identified; however, rare variants are found in less than 5% of cancer patients. Genome wide association studies (GWAS) have identified hundreds of common genetic variants significantly associated with a number of cancers, but the clinical utility of individual variants or a polygenic risk score (PRS) derived from multiple variants is still unclear. Methods: We tested the ability of polygenic risk score (PRS) models developed from genome-wide significant variants to differentiate cases versus controls in the Penn Medicine Biobank. Cases for 15 different cancers and cancer-free controls were identified using electronic health record billing codes for 11,524 European American and 5,994 African American individuals from the Penn Medicine Biobank. Results: The discriminatory ability of the 15 PRS models to distinguish their respective cancer cases versus controls ranged from 0.68-0.79 in European Americans and 0.74-0.93 in African Americans. Seven of the 15 cancer PRS trended towards an association with their cancer at a p<0.05 (Table), and PRS for prostate, thyroid and melanoma were significantly associated with their cancers at a bonferroni corrected p<0.003 with OR 1.3-1.6 in European Americans. Conclusions: Our data demonstrate that common variants with significant associations from GWAS studies can distinguish cancer cases versus controls for some cancers in an unselected biobank population. Given the small effects, future studies are needed to determine how best to incorporate PRS with other risk factors in the precision prediction of cancer risk. [Table: see text]

scholarly journals M88. EVIDENCE FOR INFLAMMATION AS A PUTATIVE SHARED MECHANISM FOR INSULIN RESISTANCE AND SCHIZOPHRENIA

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S168-S168
Author(s):  
Benjamin Perry ◽  
Stephen Burgess ◽  
Hannah Jones ◽  
Stanley Zammit ◽  
Rachel Upthegrove ◽  
...  
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Genetic Variants ◽  
Cardiometabolic Risk ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Cardiometabolic Risk Factors ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Cardiometabolic Disorders

Abstract Background Insulin Resistance (IR) predisposes to cardiometabolic disorders, which are common in schizophrenia and are associated with excess morbidity and mortality. The mechanisms of association remain unknown. We aimed 1) To use genetic data to examine the direction of association between IR and related cardiometabolic risk factors, and schizophrenia; 2) To examine whether inflammation could be a shared mechanism for IR and schizophrenia. Methods We used two-sample uni-variable Mendelian randomization (MR) to examine whether genetically-predicted IR-related cardiometabolic risk factors (Fasting insulin (FI), high-density lipoprotein (HDL), triglycerides (TG), low-density lipoprotein, fasting plasma glucose, glycated haemoglobin, leptin, body mass index, glucose tolerance and type 2 diabetes) may be causally associated with schizophrenia. We used the most recent summary statistics for genetic variants associated with schizophrenia and IR-related cardiometabolic risk factors from publicly-available large genome-wide association studies (GWAS). We used bi-directional MR to examine direction of association. To examine whether inflammation could be a shared mechanism for IR and schizophrenia, we first conducted a sensitivity analysis by performing MR using only cardiometabolic genetic variants that were also associated with inflammation, at genome-wide significance. Second, we used multi-variable MR (MVMR) to examine associations between cardiometabolic risk factors and schizophrenia after adjusting for genetically-predicted levels of C-reactive protein. Results In analyses using all associated genetic variants, genetically predicted levels of leptin were associated with risk of schizophrenia (OR=2.54 per SD increase in leptin; 95% CI, 1.02–6.31). In analyses using inflammation-related variants, genetically predicted levels of FI (OR=2.76 per SD increase in FI; 95% C.I., 1.31–6.17), TG (OR=2.90 per SD increase in TG; 95% C.I., 1.36–6.17), and HDL (OR=0.56 per SD increase in HDL; 95% C.I., 0.37–0.83) were associated with schizophrenia. The associations completely attenuated in MVMR analyses controlling for CRP. There was no evidence of an association between genetically-predicted schizophrenia liability and cardiometabolic factors. Discussion The IR phenotype of FI, TG and HDL could be associated with schizophrenia over and above common sociodemographic and lifestyle factors. This association is likely explained by a common inflammatory mechanism. Interventional studies are required to test whether inflammation could represent a putative therapeutic target for the treatment and prevention of cardiometabolic disorders in schizophrenia.

scholarly journals Using multiple genetic variants as instrumental variables for modifiable risk factors

2011 ◽  
Vol 21 (3) ◽  
pp. 223-242 ◽  
Author(s):  
Tom M Palmer ◽  
Debbie A Lawlor ◽  
Roger M Harbord ◽  
Nuala A Sheehan ◽  
Jon H Tobias ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Missing Data ◽  
Instrumental Variables ◽  
Genetic Variants ◽  
Association Studies ◽  
Mendelian Randomisation ◽  
Modifiable Risk Factors ◽  
Genome Wide Association Studies ◽  
Finite Sample

Mendelian randomisation analyses use genetic variants as instrumental variables (IVs) to estimate causal effects of modifiable risk factors on disease outcomes. Genetic variants typically explain a small proportion of the variability in risk factors; hence Mendelian randomisation analyses can require large sample sizes. However, an increasing number of genetic variants have been found to be robustly associated with disease-related outcomes in genome-wide association studies. Use of multiple instruments can improve the precision of IV estimates, and also permit examination of underlying IV assumptions. We discuss the use of multiple genetic variants in Mendelian randomisation analyses with continuous outcome variables where all relationships are assumed to be linear. We describe possible violations of IV assumptions, and how multiple instrument analyses can be used to identify them. We present an example using four adiposity-associated genetic variants as IVs for the causal effect of fat mass on bone density, using data on 5509 children enrolled in the ALSPAC birth cohort study. We also use simulation studies to examine the effect of different sets of IVs on precision and bias. When each instrument independently explains variability in the risk factor, use of multiple instruments increases the precision of IV estimates. However, inclusion of weak instruments could increase finite sample bias. Missing data on multiple genetic variants can diminish the available sample size, compared with single instrument analyses. In simulations with additive genotype-risk factor effects, IV estimates using a weighted allele score had similar properties to estimates using multiple instruments. Under the correct conditions, multiple instrument analyses are a promising approach for Mendelian randomisation studies. Further research is required into multiple imputation methods to address missing data issues in IV estimation.

scholarly journals Pharmacogenomics in Hypertension: Where We Stand Today

2019 ◽  
Author(s):  
Patrick N. Cunningham ◽  
Arlene B. Chapman
Keyword(s):  
Blood Pressure ◽  
Genetic Variants ◽  
Association Studies ◽  
Pressure Control ◽  
Medical Problem ◽  
Large Individual ◽  
Specific Gene ◽  
Genome Wide Association Studies ◽  
Improve Blood Pressure Control ◽  
Antihypertensive Response

Hypertension is a common and growing medical problem that leads to enormous cardiovascular and kidney disease worldwide. While many drugs exist to treat hypertension, there is large individual variation in how a given individual responds to different agents, which contributes to dismal rates of hypertension control. While demographic factors predict which drugs may work better in certain individuals, a great degree of this variation has a genetic basis. In recent years, genome wide association studies have begun to identify specific gene variants that predict drug response to particular agents. This review identifies the major genetic variants influencing antihypertensive response that have emerged from this growing body of work. For novel genetic variants without a previously known biologic basis in blood pressure, it is crucial to validate initial findings in subsequent studies. This information may eventually lead to a more personalized approach to hypertension management that will improve blood pressure control and patient outcomes. The integration of this large amount of data and its real world application will be highly challenging, but strategies to accomplish this are discussed.

scholarly journals Combined Utility of 25 Disease and Risk Factor Polygenic Risk Scores for Stratifying Risk of All-Cause Mortality

2020 ◽  
Author(s):  
Allison Meisner ◽  
Prosenjit Kundu ◽  
Yan Dora Zhang ◽  
Lauren V. Lan ◽  
Sungwon Kim ◽  
...  
Keyword(s):  
Risk Factors ◽  
Mortality Risk ◽  
Association Studies ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Hazard Ratios ◽  
Risk Of Mortality ◽  
All Cause Mortality ◽  
The Uk

ABSTRACTWhile genome-wide association studies have identified susceptibility variants for numerous traits, their combined utility for predicting broad measures of health, such as mortality, remains poorly understood. We used data from the UK Biobank to combine polygenic risk scores (PRS) for 13 diseases and 12 mortality risk factors into sex-specific composite PRS (cPRS). These cPRS were moderately associated with all-cause mortality in independent data: the estimated hazard ratios per standard deviation were 1.10 (95% confidence interval: 1.05, 1.16) and 1.15 (1.10, 1.19) for women and men, respectively. Differences in life expectancy between the top and bottom 5% of the cPRS were estimated to be 4.79 (1.76, 7.81) years and 6.75 (4.16, 9.35) years for women and men, respectively. These associations were substantially attenuated after adjusting for non-genetic mortality risk factors measured at study entry. The cPRS may be useful in counseling younger individuals at higher genetic risk of mortality on modification of non-genetic factors.

scholarly journals Chemotherapy-Related Cardiac Dysfunction

2018 ◽  
Vol 11 (1) ◽  
Author(s):  
Marijke Linschoten ◽  
Arco J. Teske ◽  
Maarten J. Cramer ◽  
Elsken van der Wall ◽  
Folkert W. Asselbergs
Keyword(s):  
Risk Factors ◽  
Risk Stratification ◽  
Genetic Variants ◽  
Cardiac Dysfunction ◽  
Genetic Risk ◽  
Drug Transport ◽  
Association Studies ◽  
Genetic Risk Factors ◽  
Candidate Gene Approach ◽  
Genome Wide Association Studies

Chemotherapy-related cardiac dysfunction is a significant side effect of anticancer treatment. Risk stratification is based on clinical- and treatment-related risk factors that do not adequately explain individual susceptibility. The addition of genetic variants may improve risk assessment. We conducted a systematic literature search in PubMed and Embase, to identify studies investigating genetic risk factors for chemotherapy-related cardiac dysfunction. Included were articles describing genetic variants in humans altering susceptibility to chemotherapy-related cardiac dysfunction. The validity of identified studies was assessed by 10 criteria, including assessment of population stratification, statistical methodology, and replication of findings. We identified 40 studies: 34 exploring genetic risk factors for anthracycline-induced cardiotoxicity (n=9678) and 6 studies related to trastuzumab-associated cardiotoxicity (n=642). The majority (35/40) of studies had a candidate gene approach, whereas 5 genome-wide association studies have been performed. We identified 25 genetic variants in 20 genes and 2 intergenic variants reported significant at least once. The overall validity of studies was limited, with small cohorts, failure to assess population ancestry and lack of replication. SNPs with the most robust evidence up to this point are CELF4 rs1786814 (sarcomere structure and function), RARG rs2229774 (topoisomerase-2β expression), SLC28A3 rs7853758 (drug transport), UGT1A6 rs17863783 (drug metabolism), and 1 intergenic variant (rs28714259). Existing evidence supports the hypothesis that genetic variation contributes to chemotherapy-related cardiac dysfunction. Although many variants identified by this systematic review show potential to improve risk stratification, future studies are necessary for validation and assessment of their value in a diagnostic and prognostic setting.

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