scholarly journals Identifying individuals with high risk of Alzheimer’s disease using polygenic risk scores

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ganna Leonenko ◽  
Emily Baker ◽  
Joshua Stevenson-Hoare ◽  
Annerieke Sierksma ◽  
Mark Fiers ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Prediction Accuracy ◽  
Genetic Risk Score ◽  
Low Risk ◽  
Risk Scores ◽  
Sample Mean ◽  
Polygenic Risk ◽  
Reliable Identification

AbstractPolygenic Risk Scores (PRS) for AD offer unique possibilities for reliable identification of individuals at high and low risk of AD. However, there is little agreement in the field as to what approach should be used for genetic risk score calculations, how to model the effect of APOE, what the optimal p-value threshold (pT) for SNP selection is and how to compare scores between studies and methods. We show that the best prediction accuracy is achieved with a model with two predictors (APOE and PRS excluding APOE region) with pT<0.1 for SNP selection. Prediction accuracy in a sample across different PRS approaches is similar, but individuals’ scores and their associated ranking differ. We show that standardising PRS against the population mean, as opposed to the sample mean, makes the individuals’ scores comparable between studies. Our work highlights the best strategies for polygenic profiling when assessing individuals for AD risk.

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.

scholarly journals Assessing the Clinical Utility of Genetic Risk Scores for Targeted Cancer Screening

2020 ◽  
Author(s):  
Carly Ann 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.

scholarly journals Association between a Genetic Risk Score Based on Single Nucleotide Polymorphisms of Coronary Artery Disease-Related Genes and Left Main Coronary Artery Disease

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Zhengxi Xu ◽  
Hanning Liu ◽  
Cheng Sun ◽  
Ke Si ◽  
Yan Zhao ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Risk Group ◽  
Genetic Risk Score ◽  
High Risk Group ◽  
Low Risk ◽  
Artery Disease

Coronary artery disease (CAD) is the leading cause of mortality and morbidity worldwide. Left main coronary artery disease (LMCAD) is a severe phenotype of CAD and has a genetic component. Previous studies identified 3 inflammation-related single nucleotide polymorphisms (SNPs) contributing to the development of LMCAD. We integrated these SNPs into a genetic risk score for the prediction of LMCAD. We enrolled 1544 patients with CAD between 2007 and 2011. The individual associations of the 3 SNPs with LMCAD were assessed. We then calculated the genetic risk score for each patient and stratified patients into low-risk, intermediate-risk, and high-risk categories of genetic risk. In univariable logistic regression analysis, the odds of LMCAD for the high-risk group were 2.81 (95% confidence interval [CI]: 1.72-4.60; P = 0.02) times those of the low-risk group. After adjustment for CAD-related clinical variables, the high-risk group (adjusted OR: 2.78; 95% CI: 1.69-4.58; P = 0.02) had increased odds of LMCAD when compared with the low-risk group. Comparison of model c-statistics showed greater predictive value with regard to LMCAD for the genetic risk score model than the models including single SNPs.

scholarly journals An immune-related lncRNA signature as a prognostic immunotherapy target for colon cancer

2020 ◽  
Author(s):  
Bin Wu ◽  
Yi Yao ◽  
Yi Dong ◽  
Si Qi Yang ◽  
Deng Jing Zhou ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Risk Score ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Gene Set Enrichment ◽  
Immunotherapy Target

Abstract Background：We aimed to investigate an immune-related long non-coding RNA (lncRNA) signature that may be exploited as a potential immunotherapy target in colon cancer. Materials and methods: Colon cancer samples from The Cancer Genome Atlas (TCGA) containing available clinical information and complete genomic mRNA expression data were used in our study. We then constructed immune-related lncRNA co-expression networks to identify the most promising immune-related lncRNAs. According to the risk score developed from screened immune-related lncRNAs, the high-risk and low-risk groups were separated on the basis of the median risk score, which served as the cutoff value. An overall survival analysis was then performed to confirm that the risk score developed from screened immune-related lncRNAs could predict colon cancer prognosis. The prediction reliability was further evaluated in the independent prognostic analysis and receiver operating characteristic curve (ROC). A principal component analysis (PCA) and gene set enrichment analysis (GSEA) were performed for functional annotation. Results: Information for a total of 514 patients was included in our study. After multiplex analysis, 12 immune-related lncRNAs were confirmed as a signature to evaluate the risk scores for each patient with cancer. Patients in the low-risk group exhibited a longer overall survival (OS) than those in the high-risk group. Additionally, the risk scores were an independent factor, and the Area Under Curve (AUC) of ROC for accuracy prediction was 0.726. Moreover, the low-risk and high-risk groups displayed different immune statuses based on principal components and gene set enrichment analysis.Conclusions: Our study suggested that the signature consisting of 12 immune-related lncRNAs can provide an accessible approach to measuring the prognosis of colon cancer and may serve as a valuable antitumor immunotherapy.

scholarly journals Progression from islet autoimmunity to clinical type 1 diabetes is influenced by genetic factors: results from the prospective TEDDY study

2018 ◽  
Vol 56 (9) ◽  
pp. 602-605 ◽  
Author(s):  
Andreas Beyerlein ◽  
Ezio Bonifacio ◽  
Kendra Vehik ◽  
Markus Hippich ◽  
Christiane Winkler ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Factors ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Islet Autoimmunity ◽  
Islet Autoantibody ◽  
Clinical Type

BackgroundProgression time from islet autoimmunity to clinical type 1 diabetes is highly variable and the extent that genetic factors contribute is unknown.MethodsIn 341 islet autoantibody-positive children with the human leucocyte antigen (HLA) DR3/DR4-DQ8 or the HLA DR4-DQ8/DR4-DQ8 genotype from the prospective TEDDY (The Environmental Determinants of Diabetes in the Young) study, we investigated whether a genetic risk score that had previously been shown to predict islet autoimmunity is also associated with disease progression.ResultsIslet autoantibody-positive children with a genetic risk score in the lowest quartile had a slower progression from single to multiple autoantibodies (p=0.018), from single autoantibodies to diabetes (p=0.004), and by trend from multiple islet autoantibodies to diabetes (p=0.06). In a Cox proportional hazards analysis, faster progression was associated with an increased genetic risk score independently of HLA genotype (HR for progression from multiple autoantibodies to type 1 diabetes, 1.27, 95% CI 1.02 to 1.58 per unit increase), an earlier age of islet autoantibody development (HR, 0.68, 95% CI 0.58 to 0.81 per year increase in age) and female sex (HR, 1.94, 95% CI 1.28 to 2.93).ConclusionsGenetic risk scores may be used to identify islet autoantibody-positive children with high-risk HLA genotypes who have a slow rate of progression to subsequent stages of autoimmunity and type 1 diabetes.

scholarly journals A Weighted Genetic Risk Score Predicts Surgical Recurrence Independent of High-Risk Clinical Features in Dupuytren’s Disease

2019 ◽  
Vol 143 (2) ◽  
pp. 512-518 ◽  
Author(s):  
Sophie A. Riesmeijer ◽  
Oliver W. G. Manley ◽  
Michael Ng ◽  
Ilja M. Nolte ◽  
Dieuwke C. Broekstra ◽  
...  
Keyword(s):  
High Risk ◽  
Clinical Features ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Dupuytren’S Disease ◽  
Dupuytren's Disease ◽  
Surgical Recurrence ◽  
Weighted Genetic Risk Score

scholarly journals Prognostic Implications of Immune-Related Gene Pairs Signatures in Bladder Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Hui Xiong ◽  
Hui Gao ◽  
Jinding Hu ◽  
Yun Dai ◽  
Hanbo Wang ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
High Risk ◽  
Risk Score ◽  
Immune Cells ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Related Gene ◽  
Gene Pairs ◽  
Immune Related Gene

Compelling evidence indicates that immune function is correlated with the prognosis of bladder cancer (BC). Here, we aimed to develop a clinically translatable immune-related gene pairs (IRGPs) prognostic signature to estimate the overall survival (OS) of bladder cancer. From the 251 prognostic-related IRGPs, 37 prognostic-related IRGPs were identified using LASSO regression. We identified IRGPs with the potential to be prognostic markers. The established risk scores divided BC patients into high and low risk score groups, and the survival analysis showed that risk score was related to OS in the TCGA-training set ( p < 0.001 ; HR = 7.5 [5.3, 10]). ROC curve analysis showed that the AUC for the 1-year, 3-year, and 5-year follow-up was 0.820, 0.883, and 0.879, respectively. The model was verified in the TCGA-testing set and external dataset GSE13507. Multivariate analysis showed that risk score was an independent prognostic predictor in patients with BC. In addition, significant differences were found in gene mutations, copy number variations, and gene expression levels in patients with BC between the high and low risk score groups. Gene set enrichment analysis showed that, in the high-risk score group, multiple immune-related pathways were inhibited, and multiple mesenchymal phenotype-related pathways were activated. Immune infiltration analysis revealed that immune cells associated with poor prognosis of BC were upregulated in the high-risk score group, whereas immune cells associated with a better prognosis of BC were downregulated in the high-risk score group. Other immunoregulatory genes were also differentially expressed between high and low risk score groups. A 37 IRGPs-based risk score signature is presented in this study. This signature can efficiently classify BC patients into high and low risk score groups. This signature can be exploited to select high-risk BC patients for more targeted treatment.

Abstract 18093: Bleeding Events in Clopidogrel-Treated Patients with STEMI is Associated with a Genetic Risk Score Based on High-Risk Genetic Polymorphisms

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Jia-Hui Zhang ◽  
Jin-Qing Yuan ◽  
Xian-Min Meng ◽  
Xiao-Fang Tang ◽  
Jing Wang ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Major Bleeding ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Multivariate Logistic Regression Analysis ◽  
Bleeding Events ◽  
Genetic Score ◽  
Clinical Safety ◽  
Increased Risk

Introduction: Gene polymorphisms of ABCB1, CYP2C19, PON1 and P2Y12 may influence pharmacodynamics and clinical events of clopidogrel treatment. Hypothesis: We assessed the hypothesis that a genetic risk score based on identified high-risk single nucleotide polymorphisms (SNPs) would be associated with bleedings in clopidogrel-treated Chinese STEMI patients after percutaneous coronary intervention (PCI). Methods: A total of 503 consecutive patients with STEMI who received an uneventful PCI and were exposed to clopidogrel treatment for 12 months, were enrolled in the single-center registry. There were 38 tag SNPs selected from ABCB1, CYP2C19, PON1 and P2Y12 genes, which were detected by the ligase detection reaction. The primary clinical safety endpoint was the incidence of major bleeding events. Major bleeding was quantified according to bleeding academic research consortium definition (BARC) criteria, including type 3 and 5 in the analysis. The follow-up period was 12 months. Results: Overall, 46 BARC≥3 bleeding events (9.1%) occurred, which included 11 (2.1%) cases of BARC 3b bleedings and 35 (7.0%) cases of BARC 3a bleedings. After adjustment for traditional clinical risk factors, multivariate logistic regression analysis identified SNPs significantly associated with bleedings were ABCB1 (rs1045642, rs2235047, rs7779562), P2Y12 (rs6809699) and CYP2C19*17. A genetic risk score was constructed by summing the number of risk alleles. Bleedings were significantly associated with increased genetic risk score tertile. Patients in the top tertile of the genetic score were estimated to have a 3.268-fold (95%CI=1.198-8.929, p=0.021) increased risk of bleedings compared with those in the bottom tertile. As a continuous variable, the risk score resulted in an OR of 1.326 per unit increase in score (95%CI=1.098-1.601, p=0.003). Conclusions: This genetic score was significantly associated with bleedings after PCI in our study population.

The BARCODE1 pilot study targeting men with increased genetic risk of developing prostate cancer: Examining the feasibility of a community-based screening program using polygenic risk score to target screening.

2021 ◽  
Vol 39 (6_suppl) ◽  
pp. 227-227
Author(s):  
Jana Kathlyn McHugh ◽  
Sarah Benafif ◽  
Holly ni Raghallaigh ◽  
Elizabeth Bancroft ◽  
Zsofia Kote-Jarai ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Primary Care ◽  
Dna Extraction ◽  
Risk Score ◽  
Genetic Risk ◽  
Population Screening ◽  
Low Risk ◽  
Polygenic Risk Score ◽  
Genetic Profiling ◽  
Polygenic Risk

227 Background: A significant proportion of Prostate cancer (PrCa) risk is attributable to heritable risk factors of which only a minority are high risk Mendelian traits. A greater proportion of PrCa is due to the combined effect of multiple low risk variants. There have been approximately 170 single nucleotide polymorphisms (SNPs) identified that are associated with PrCa risk in Europeans. Although each of these confer a low to moderate risk of PrCa, the cumulative risk (polygenic risk score, PRS) of increasing numbers of these risk alleles may confer a substantial relative risk. In PrCa genetic profiling, using PRS, could be used to target population screening to those at highest risk. BARCODE1 is the first study to prospectively review the use of a genetic profile in PrCa screening in the general population in the UK. Methods: Our study invited healthy males aged 55-69 to participate through their Primary Care physicians. Collection kits were mailed to retrieve saliva samples. Genotyping was carried out after DNA extraction using a study specific assay and the PRS was calculated for each participant using the sum of weighted alleles for 130 risk loci. Prostate MRI and Biopsy were then offered to men in the top 10% of the genetic risk profile. Results: 1434 men were invited by letter to participate. The uptake was 26%, of whom 87% of men were eligible for inclusion. Following DNA extraction, genotyping, and quality control checks, data were available for 297 men. 25 participants had PRS in the top 10% and were invited for screening; 19 underwent a prostate MRI, and 18 went on to have a systematic (+/- targeted prostate biopsy. There were 7 diagnoses of PrCa (38.9%). The cancers detected were low-risk and are being managed with Active Surveillance (AS). Results of the first year of follow up will be presented and an update of the main study which aims to recruit 5000 men. Conclusions: The BARCODE1 pilot has shown the feasibility of this population-based study, with an overall uptake of 26% and a cancer incidence of nearly 40%. We have identified approximately 70 Primary care providers who have contributed to the transition to the full BARCODE1 study, which will aim to recruit 5,000 men. The BARCODE1 study results will be important in defining the role of PRS genetic profiling in targeted PrCa population screening. Clinical trial information: IRAS257684.

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