scholarly journals Gastric Cancer Risk Prediction Using an Epidemiological Risk Assessment Model and Polygenic Risk Score

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 876
Author(s):  
Boyoung Park ◽  
Sarah Yang ◽  
Jeonghee Lee ◽  
Il Ju Choi ◽  
Young-Il Kim ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Risk Assessment ◽  
Risk Score ◽  
Assessment Model ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Risk Assessment Model ◽  
Infection Status ◽  
Polygenic Risk ◽  
H Pylori

We investigated the performance of a gastric cancer (GC) risk assessment model in combination with single-nucleotide polymorphisms (SNPs) as a polygenic risk score (PRS) in consideration of Helicobacter pylori (H. pylori) infection status. Six SNPs identified from genome-wide association studies and a marginal association with GC in the study population were included in the PRS. Discrimination of the GC risk assessment model, PRS, and the combination of the two (PRS-GCS) were examined regarding incremental risk and the area under the receiver operating characteristic curve (AUC), with grouping according to H. pylori infection status. The GC risk assessment model score showed an association with GC, irrespective of H. pylori infection. Conversely, the PRS exhibited an association only for those with H. pylori infection. The PRS did not discriminate GC in those without H. pylori infection, whereas the GC risk assessment model showed a modest discrimination. Among individuals with H. pylori infection, discrimination by the GC risk assessment model and the PRS were comparable, with the PRS-GCS combination resulting in an increase in the AUC of 3%. In addition, the PRS-GCS classified more patients and fewer controls at the highest score quintile in those with H. pylori infection. Overall, the PRS-GCS improved the identification of a GC-susceptible population of people with H. pylori infection. In those without H. pylori infection, the GC risk assessment model was better at identifying the high-risk group.

scholarly journals Accurate Prediction Model - Polygenic Risk Score for High-Risk Individuals Predictive of Gastric Cancer

2021 ◽  
Author(s):  
Fujiao Duan ◽  
Chunhua Song ◽  
Peng Wang ◽  
Hua Ye ◽  
Liping Dai ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Factors ◽  
Prediction Models ◽  
Information Criterion ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
H Pylori

Abstract Background The genetic variation of gastric cancer has not been fully identified. We aimed to screen and identify common variant single nucleotide polymorphisms (SNPs) and long noncoding RNA (lncRNA) related SNPs associated with the risk of gastric cancer, and construct and evaluate prediction models based on polygenic risk score (PRS). Methods Non-genetic factors such as H.pylori infection, environment, and genetic factors associated with gastric cancer were screened following meta-analysis and bioinformatics,verified by frequency matched case-control study. PRS and weighted genetic risk scores (wGRS) were derived from estimation of effect size. Net reclassification improvement (NRI), integrated discrimination improvement (IDI), akaike information criterion (AIC) and bayesian information criterion (BIC) were used to evaluate model. Results A risk gradient was observed across quantile of the PRS, the results showed that the risk of gastric cancer in the highest 10 quantile of PRS was 3.24 folds higher than that of the general population (OR=3.24,95%CI: 2.07, 5.06). The PRS with one or more risk factors (smoking, drinking and H. pylori infection) was superior to the single genetic risk model. For NRI and IDI, the PRS combinations were significantly improved compared to wGRS model combinations (P<0.001). The model of PRS combined with lncRNA SNPs, smoking, drinking and H. pylori infection was the best fitting model (AIC=117.23, BIC=122.31). Conclusion Our findings indicated that the model based on PRS combined with lncRNA SNPs, smoking, drinking, and H. pylori infection had the optimal predictive ability on the risk of gastric cancer, contributing to distinguish high-risk groups from population.

scholarly journals Pharmacogenetic Polygenic Risk Score for Bronchodilator Response in Children and Adolescents with Asthma: Proof-of-Concept

2021 ◽  
Vol 11 (4) ◽  
pp. 319
Author(s):  
Joanne E. Sordillo ◽  
Sharon M. Lutz ◽  
Michael J. McGeachie ◽  
Jessica Lasky-Su ◽  
Scott T. Weiss ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Risk Score ◽  
Association Studies ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Linear Regression Models ◽  
Standard Deviation Increase ◽  
Polygenic Risk ◽  
Bronchodilator Response ◽  
Children With Asthma

Genome-wide association studies (GWAS) of response to asthma medications have primarily focused on Caucasian populations, with findings that may not be generalizable to minority populations. We derived a polygenic risk score (PRS) for response to albuterol as measured by bronchodilator response (BDR), and examined the PRS in a cohort of Hispanic school-aged children with asthma. We leveraged a published GWAS of BDR to identify relevant genetic variants, and ranked the top variants according to their Combined Annotation Dependent Depletion (CADD) scores. Variants with CADD scores greater than 10 were used to compute the PRS. Once we derived the PRS, we determined the association of the PRS with BDR in a cohort of Hispanic children with asthma (the Genetics of Asthma in Costa Rica Study (GACRS)) in adjusted linear regression models. Mean BDR in GACRS participants was5.6% with a standard deviation of 10.2%. We observed a 0.63% decrease in BDR in response to albuterol for a standard deviation increase in the PRS (p = 0.05). We also observed decreased odds of a BDR response at or above the 12% threshold for a one standard deviation increase in the PRS (OR = 0.80 (95% CI 0.67 to 0.95)). Our findings show that combining variants from a pharmacogenetic GWAS into a PRS may be useful for predicting medication response in asthma.

scholarly journals Gene expression and DNA methylation analyses suggest that two immune related genes are prognostic factors of colorectal cancer

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Xiao-Liang Xing ◽  
Zhi-Yong Yao ◽  
Chaoqun Xing ◽  
Zhi Huang ◽  
Jing Peng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Risk Assessment ◽  
Dna Methylation ◽  
Differentially Expressed Genes ◽  
Risk Score ◽  
Immune Cells ◽  
Assessment Model ◽  
Differentially Expressed ◽  
Risk Assessment Model

Abstract Background Colorectal cancer (CRC) is the second most prevalent cancer, as it accounts for approximately 10% of all annually diagnosed cancers. Studies have indicated that DNA methylation is involved in cancer genesis. The purpose of this study was to investigate the relationships among DNA methylation, gene expression and the tumor-immune microenvironment of CRC, and finally, to identify potential key genes related to immune cell infiltration in CRC. Methods In the present study, we used the ChAMP and DESeq2 packages, correlation analyses, and Cox regression analyses to identify immune-related differentially expressed genes (IR-DEGs) that were correlated with aberrant methylation and to construct a risk assessment model. Results Finally, we found that HSPA1A expression and CCRL2 expression were positively and negatively associated with the risk score of CRC, respectively. Patients in the high-risk group were more positively correlated with some types of tumor-infiltrating immune cells, whereas they were negatively correlated with other tumor-infiltrating immune cells. After the patients were regrouped according to the median risk score, we could more effectively distinguish them based on survival outcome, clinicopathological characteristics, specific tumor-immune infiltration status and highly expressed immune-related biomarkers. Conclusion This study suggested that the risk assessment model constructed by pairing immune-related differentially expressed genes correlated with aberrant DNA methylation could predict the outcome of CRC patients and might help to identify those patients who could benefit from antitumor immunotherapy.

Distinct Genetic Profiles in Postpartum Depression With Different Trajectory of Illness

2020 ◽  
Author(s):  
Nagahide Takahashi ◽  
Hanae Tainaka ◽  
Tomoko Nishimura ◽  
Taeko Harada ◽  
Akemi Okumura ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Postpartum Depression ◽  
Risk Score ◽  
Association Studies ◽  
Depression Scale ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Gene Set Enrichment ◽  
Polygenic Risk ◽  
Gene Set

Abstract BackgroundPostpartum depression (PPD) is a common and highly heritabledisorder in the postnatal period of new mothers. The development of PPD is shown to affectneurodevelopment in children and recent evidence suggests thatthe trajectory of PPDisalso associated with children’s neurodevelopment and mental conditions. Thus, early identification and intervention for individuals at high risk of PPD are urgently needed.Additionally, it is not clear whether genetic factors affect thetrajectory of PPD. Therefore, using a polygenic risk score (PRS) approach, we investigated if PRS for depression (Depression-PRS) and bipolar disorder (Bipolar-PRS) are associated with the development and clinical course of PPD.Methods Usingrecent large genome-wide association studies(GWAS) of depression and bipolar disorder as discovery cohorts, we calculatedDepression-PRS and Bipolar-PRS in each individual. Then, we investigated the possible association between Depression-PRS and Bipolar-PRS with the development andtrajectory of PPD insubjects from the Hamamatsu Birth Cohort for mothers and children (n = 136). Depressive symptoms were assessed using the Edinburgh Postpartum Depression Scale. Gene-set enrichment analyses were used to identify pathways underlying these conditions. ResultsDepression-PRS was significantly higher in subjects with PPD than in those without PPD(t = -3.283, P = 0.002)and logistic analysis showed that Depression-PRS significantly increases therisk of developing PPD(OR [SE] = 2.274 [0.585], P = 0.002). Furthermore, Depression-PRS was positively associated with continuity of PPD (β [SE]=1.621 [0.672]; P = 0.032).Gene-set enrichment analyses revealed that pathways such as“response to hormone”(β[SE] -2.285[1.002], P < 0.001) and “epigenetic regulation”(β[SE] 2.831 [1.317], P < 0.001) were involved in the continuity of PPD. ConclusionThese preliminary findings indicate that the genetic component plays an important role not only in the development but also inthe continuity of PPD. A polygenic risk score approach could be useful to identify subjects at risk for PPD, especially for persistent PPD,who needcareful monitoring and intervention after delivery.

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 Genomic Prediction of Depression Risk and Resilience Under Stress

2019 ◽  
Author(s):  
Yu Fang ◽  
Laura Scott ◽  
Peter Song ◽  
Margit Burmeister ◽  
Srijan Sen
Keyword(s):  
Risk Score ◽  
Large Scale ◽  
Association Studies ◽  
Health Study ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Risk And Resilience ◽  
Polygenic Risk ◽  
Response To Stress ◽  
Training Stress

AbstractAdvancing our ability to predict who is likely to develop depression in response to stress holds great potential in reducing the burden of the disorder. Large-scale genome-wide association studies (GWAS) of depression have, for the first time, provided a basis for meaningful depression polygenic risk score construction (MDD-PRS). The Intern Health Study utilizes the predictable and large increase in depression with physician training stress to identify predictors of depression. Applying the MDD-PRS derived from the PGC2/23andMe GWAS to 5,227 training physicians, we found that MDD-PRS predicted depression under training stress (beta=0.082, p=2.1×10−12) and that MDD-PRS was significantly more strongly associated with depression under stress than at baseline (MDD-PRS × stress interaction - beta=0.029, p=0.02). While known risk factors accounted for 85.6% of the association between MDD-PRS and depression at baseline, they only accounted for 55.4% of the association between MDD-PRS and depression under stress, suggesting that MDD-PRS can add unique predictive power to existing models of depression under stress. Further, we found that low MDD-PRS may have particular utility in identifying individuals with high resilience. Together, these findings suggest that polygenic risk score holds promise in furthering our ability to predict vulnerability and resilience under stress.

scholarly journals Performance of Khorana Risk Score for Prediction of Venous Thromboembolism in Patients With Hepatocellular Carcinoma

2017 ◽  
Vol 24 (3) ◽  
pp. 471-476 ◽  
Author(s):  
Y. Wang ◽  
B. M. Attar ◽  
H. E. Fuentes ◽  
J. Yu ◽  
Huiyuan Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Risk Assessment ◽  
Venous Thromboembolism ◽  
Risk Score ◽  
Univariate Analysis ◽  
International Classification Of Diseases ◽  
Assessment Model ◽  
Radiographic Examination ◽  
Risk Assessment Model ◽  
Mortality And Morbidity

Cancer-associated venous thromboembolism (VTE) is one of the leading causes of mortality and morbidity among patients with malignancy. The Khorana risk score (KRS) is currently the best validated risk assessment model to stratify risks of VTE development in ambulatory patients with cancer. In the current study, we assessed the performance of KRS in patients with hepatocellular carcinoma (HCC). We retrospectively analyzed patients with diagnosis of HCC (screened by International Classification of Diseases [ ICD-9] and ICD-10 code, confirmed with radiographic examination and/or histopathology) at a large public hospital over 15 years (January 2000 through July 2015). Cases with VTE were identified through radiographic examination and blindly adjudicated. Khorana risk score was calculated for each patient, and its association with VTE development and mortality was assessed. Among 270 patients with HCC, 16 (5.9%) cases of VTE were identified, including 7 (43.8%) pulmonary embolism, 4 (25%) peripheral deep vein thrombosis, and 6 (37.5%) intra-abdominal thrombosis. One hundred eighty-four (68.1%) patients had a KRS of 0 and 86 (31.9%) patients had a KRS >0. Most of the thrombotic (n = 9, 56%) events occurred in the low-risk group. In univariate analysis, only prechemotherapy leukocyte count equal to or greater than 11 000/μL was statistically significant in the prediction of VTE incidence. After adjusting for confounding factors in multivariate analysis, KRS >0 was not predictive of VTE (hazard ratio [HR] = 1.83, 95% confidence interval [CI] = 0.81-4.15, P = .15) or mortality (HR = 1.61, 95% CI = 0.92-2.81, P = .09). Khorana risk score did not predict VTE development or mortality in patients with HCC. Design of HCC-specific risk assessment model for VTE development is necessary.

scholarly journals Analysis of the Interaction between Polygenic Risk Score and Calorie Intake in Obesity in the Korean Population

2020 ◽  
pp. 1-10
Author(s):  
Won-Jun Lee ◽  
Ji Eun Lim ◽  
Hae Un Jung ◽  
Ji-One Kang ◽  
Taesung Park ◽  
...  
Keyword(s):  
Risk Score ◽  
Significant Interaction ◽  
Association Studies ◽  
Calorie Intake ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Polygenic Risk ◽  
Total Calorie ◽  
Total Calorie Intake

<b><i>Introduction:</i></b> Obesity results from an imbalance in the intake and expenditure of calories that leads to lifestyle-related diseases. Although genome-wide association studies (GWAS) have revealed many obesity-related genetic factors, the interactions of these factors and calorie intake remain unknown. This study aimed to investigate interactions between calorie intake and the polygenic risk score (PRS) of BMI. <b><i>Methods:</i></b> Three cohorts, i.e., from the Korea Association REsource (KARE; <i>n</i> = 8,736), CArdioVAscular Disease Association Study (CAVAS; <i>n</i> = 9,334), and Health EXAminee (HEXA; <i>n</i> = 28,445), were used for this study. BMI-related genetic loci were selected from previous GWAS. Two scores, PRS, and association (a)PRS, were used; the former was determined from 193 single-nucleotide polymorphisms (SNPs) from 5 GWAS datasets, and the latter from 62 SNPs (potentially associated) from 3 Korean cohorts (meta-analysis, <i>p</i> &#x3c; 0.01). <b><i>Results:</i></b> PRS and aPRS were significantly associated with BMI in all 3 cohorts but did not exhibit a significant interaction with total calorie intake. Similar results were obtained for obesity. PRS and aPRS were significantly associated with obesity but did not show a significant interaction with total calorie intake. We further analyzed the interaction with protein, fat, and carbohydrate intake. The results were similar to those for total calorie intake, with PRS and aPRS found to not be associated with the interaction of any of the 3 nutrition components for either BMI or obesity. <b><i>Discussion:</i></b> The interaction of BMI PRS with calorie intake was investigated in 3 independent Korean cohorts (total <i>n</i> = 35,094) and no interactions were found between PRS and calorie intake for obesity.

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