Objective:Neuroblastoma is the most common extracranial solid tumor in children and has complex genetic underpinnings.Previous genome-wide association studies(GWASs)have identified many loci associated with neuroblast...Objective:Neuroblastoma is the most common extracranial solid tumor in children and has complex genetic underpinnings.Previous genome-wide association studies(GWASs)have identified many loci associated with neuroblastoma susceptibility;however,their application in risk prediction for Chinese children has not been systematically explored.This study seeks to enhance neuroblastoma risk prediction by validating these loci and evaluating their performance in polygenic risk models.Methods:We validated 35 GWAS-identified neuroblastoma susceptibility loci in a cohort of Chinese children,consisting of 402 neuroblastoma patients and 473 healthy controls.Genotyping these polymorphisms was conducted via the TaqMan method.Univariable and multivariable logistic regression analyses revealed the genetic loci significantly associated with neuroblastoma risk.We constructed polygenic risk models by combining these loci and assessed their predictive performance via area under the curve(AUC)analysis.We also established a polygenic risk scoring(PRS)model for risk prediction by adopting the PLINK method.Results:Fourteen loci,including ten protective polymorphisms from CASC15,BARD1,LMO1,HSD17B12,and HACE1,and four risk variants from BARD1,RSRC1,CPZ and MMP20 were significantly associated with neuroblastoma risk.Compared with single-gene model,the 8-gene model(AUC=0.72)and 13-gene model(AUC=0.73)demonstrated superior predictive performance.Additionally,a PRS incorporating six significant loci achieved an AUC of 0.66,effectively stratifying individuals into distinct risk categories regarding neuroblastoma susceptibility.A higher PRS was significantly associated with advanced International Neuroblastoma Staging System(INSS)stages,suggesting its potential for clinical risk stratification.Conclusions:Our findings validate multiple loci as neuroblastoma risk factors in Chinese children and demonstrate the utility of polygenic risk models,particularly the PRS,in improving risk prediction.These results suggest that integrating multiple genetic variants into a PRS can enhance neuroblastoma risk stratification and potentially improve early diagnosis by guiding targeted screening programs for high-risk children.展开更多
The quantitative trait loci(QTL)-by-environment(Q × E) interaction effect is hard to detect because there are no effective ways to control the genomic background. In this study, we propose a linear mixed model th...The quantitative trait loci(QTL)-by-environment(Q × E) interaction effect is hard to detect because there are no effective ways to control the genomic background. In this study, we propose a linear mixed model that simultaneously analyzes data from multiple environments to detect Q × E interactions. This model incorporates two different kinship matrices derived from the genome-wide markers to control both main and interaction polygenic background effects. Simulation studies demonstrate that our approach is more powerful than the meta-analysis and inclusive composite interval mapping methods. We further analyze four agronomic traits of rice across four environments. A main effect QTL is identified for 1000-grain weight(KGW), while no QTL are found for tiller number. Additionally, a large QTL with a significant Q × E interaction is detected on chromosome 7 affecting grain number, yield, and KGW. This region harbors two important genes, PROG1 and Ghd7. Furthermore, we apply our mixed model to analyze lodging in barley across six environments. The six regions exhibiting Q × E interaction effects identified by our approach overlap with the SNPs previously identified using EM and MCMC-based Bayesian methods, further validating the robustness of our approach. Both simulation studies and empirical data analyses show that our method outperforms all other methods compared.展开更多
BACKGROUND Diabetic retinopathy(DR)is the leading cause of blindness among working-age adults,with an increasing prevalence due to the global burden of diabetes.AIM To develop a polygenic risk score(PRS)to identify hi...BACKGROUND Diabetic retinopathy(DR)is the leading cause of blindness among working-age adults,with an increasing prevalence due to the global burden of diabetes.AIM To develop a polygenic risk score(PRS)to identify high-risk groups for DR and evaluate its severity in patients with type 2 diabetes(T2D).METHODS This population-based study included 13335 patients with T2D,comprising 7295 patients with DR and 6040 without DR.Genetic data,duration of DR diagnosis,body mass index,systolic blood pressure,diastolic blood pressure,and glycated hemoglobin A1c levels were obtained from the study population.The PRS was constructed from a genome-wide association study conducted in a Taiwan region of China Han population.Electronic medical records were used to track patients with T2D and analyze the associations between PRS,timing of DR diagnosis,and therapeutic interventions.The hazard ratio(HR)of PRS for DR development and severity was estimated using multivariate Cox proportional hazards regression.RESULTS The results demonstrated that patients with T2D in the top PRS decile had a 1.21-fold greater risk of developing DR[HR=1.21;95%confidence interval(CI):1.01-1.45;P=0.041]over a 20-year follow-up period.Among patients with DR,those in the highest PRS decile exhibited a 4.81-fold increased risk of requiring more than four laser treatments(HR=4.81;95%CI:1.40-16.5;P=0.012)and a 1.38-fold increased risk of undergoing vitreoretinal surgery(HR=1.38;95%CI:1.01-1.90;P=0.044).CONCLUSION Patients with T2D with a higher PRS are at increased risk of developing DR and may experience more severe forms of the disease.展开更多
To evaluate whether the polygenic profile modifies the development of sporadic Alzheimer’s disease(sAD)and pathological biomarkers in cerebrospinal fluid(CSF),462 sAD patients and 463 age-matched cognitively normal(C...To evaluate whether the polygenic profile modifies the development of sporadic Alzheimer’s disease(sAD)and pathological biomarkers in cerebrospinal fluid(CSF),462 sAD patients and 463 age-matched cognitively normal(CN)controls were genotyped for 35 singlenucleotide polymorphisms(SNPs)that are significantly associated with sAD.Then,the alleles found to be associated with sAD were used to build polygenic risk score(PRS)models to represent the genetic risk.Receiver operating characteristic(ROC)analyses and the Cox proportional hazards model were used to evaluate the predictive value of PRS for the sAD risk and age at onset.We measured the CSF levels of Aβ42,Aβ42/Aβ40,total tau(T-tau),and phosphorylated tau(P-tau)in a subgroup(60 sAD and 200 CN participants),and analyzed their relationships with the PRSs.We found that 14 SNPs,including SNPs in the APOE,BIN1,CD33,EPHA1,SORL1,and TOMM40 genes,were associated with sAD risk in our cohort.The PRS models built with these SNPs showed potential for discriminating sAD patients from CN controls,and were able to predict the incidence rate of sAD and age at onset.Furthermore,the PRSs were correlated with the CSF levels of Aβ42,Aβ42/Aβ40,T-tau,and P-tau.Our study suggests that PRS models hold promise for assessing the genetic risk and development of AD.As genetic risk profiles vary among populations,large-scale genome-wide sequencing studies are urgently needed to identify the genetic risk loci of sAD in Chinese populations to build accurate PRS models for clinical practice.展开更多
Highly fecund marine species with dispersive life-history stages often display large population sizes and wide geographic distribution ranges. Consequently, they are expected to experience reduced genetic drift, effic...Highly fecund marine species with dispersive life-history stages often display large population sizes and wide geographic distribution ranges. Consequently, they are expected to experience reduced genetic drift, efficient selection fueled by frequent adaptive mutations, and high migration loads. This has important consequences for understanding how local adaptation proceeds in the sea. A key issue in this regard, relates to the genetic architecture underlying fitness traits. Theory predicts that adaptation may involve many genes but with a high variance in effect size. Therefore, the effect of selection on allele frequencies may be substantial for the largest effect size loci, but insignificant for small effect genes. In such a context, the performance of population genomic methods to unravel the genetic basis of adaptation depends on the fraction of adaptive genetic variance explained by the cumulative effect of outlier loci. Here, we address some methodological challenges associated with the detection of local adaptation using molecular approaches. We provide an overview of genome scan methods to detect selection, including those assuming complex demographic models that better describe spatial population structure. We then focus on quantitative genetics approaches that search for genotype-phenotype associations at different genomic scales, including genome-wide methods evaluating the cumulative effect of variants. We argue that the limited power of single locus tests can be alleviated by the use of polygenic scores to estimate the joint contribution of candidate variants to phenotypic variation.展开更多
BACKGROUND Genetic variants of Helicobacter pylori(H. pylori) are involved in gastric cancer occurrence. Single nucleotide polymorphisms(SNPs) of H. pylori that are associated with gastric cancer have been reported. T...BACKGROUND Genetic variants of Helicobacter pylori(H. pylori) are involved in gastric cancer occurrence. Single nucleotide polymorphisms(SNPs) of H. pylori that are associated with gastric cancer have been reported. The combined effect of H. pylori SNPs on the risk of gastric cancer remains unclear.AIM To assess the performance of a polygenic risk score(PRS) based on H. pylori SNPs in predicting the risk of gastric cancer.METHODS A total of 15 gastric cancer-associated H. pylori SNPs were selected. The associations between these SNPs and gastric cancer were further validated in 1022 global strains with publicly available genome sequences. The PRS model was established based on the validated SNPs. The performance of the PRS for predicting the risk of gastric cancer was assessed in global strains using quintiles and random forest(RF) methods. The variation in the performance of the PRS among different populations of H. pylori was further examined.RESULTS Analyses of the association between selected SNPs and gastric cancer in the global dataset revealed that the risk allele frequencies of six SNPs were significantly higher in gastric cancer cases than non-gastric cancer cases. The PRS model constructed subsequently with these validated SNPs produced significantly higher scores in gastric cancer. The odds ratio(OR) value for gastric cancer gradually increased from the first to the fifth quintile of PRS, with the fifth quintile having an OR value as high as 9.76(95% confidence interval: 5.84-16.29). The results of RF analyses indicated that the area under the curve(AUC) value for classifying gastric cancer and non-gastric cancer was 0.75, suggesting that the PRS based on H. pylori SNPs was capable of predicting the risk of gastric cancer. Assessing the performance of the PRS among different H. pylori populations demonstrated that it had good predictive power for cancer risk for hp Europe strains, with an AUC value of 0.78.CONCLUSION The PRS model based on H. pylori SNPs had a good performance for assessment of gastric cancer risk. It would be useful in the prediction of final consequences of the H. pylori infection and beneficial for the management of the infection in clinical settings.展开更多
Genetic variations are associated with individual susceptibility to gastric cancer.Recently,polygenic risk score(PRS)models have been established based on genetic variants to predict the risk of gastric cancer.To asse...Genetic variations are associated with individual susceptibility to gastric cancer.Recently,polygenic risk score(PRS)models have been established based on genetic variants to predict the risk of gastric cancer.To assess the accuracy of current PRS models in the risk prediction,a systematic review was conducted.A total of eight eligible studies consisted of 544842 participants were included for evaluation of the performance of PRS models.The overall accuracy was moderate with Area under the curve values ranging from 0.5600 to 0.7823.Incorporation of epidemiological factors or Helicobacter pylori(H.pylori)status increased the accuracy for risk prediction,while selection of single nucleotide polymorphism(SNP)and number of SNPs appeared to have little impact on the model performance.To further improve the accuracy of PRS models for risk prediction of gastric cancer,we summarized the association between gastric cancer risk and H.pylori genomic variations,cancer associated bacteria members in the gastric microbiome,discussed the potentials for performance improvement of PRS models with these microbial factors.Future studies on comprehensive PRS models established with human SNPs,epidemiological factors and microbial factors are indicated.展开更多
BACKGROUND John Henryism(JH)is a strategy for dealing with chronic psychological stress characterized by high levels of physical effort and work.Cynicism is a belief that people are motivated primarily by self-interes...BACKGROUND John Henryism(JH)is a strategy for dealing with chronic psychological stress characterized by high levels of physical effort and work.Cynicism is a belief that people are motivated primarily by self-interest.High scores on the JH scale and cynicism measures correlate with an increased risk of cardiovascular disease.High cynicism is also a hallmark of burnout syndrome,another known risk factor for heart disease.AIM To evaluate possible interactions between JH and cynicism hoping to clarify risk factors of burnout.METHODS We analyzed genetic and psychological data available from the Database of Genotypes and Phenotypes for genome-wide associations with these traits.We split the total available samples and used plink to perform the association studies on the discovery set(n=1852,80%)and tested for replication using the validation set(n=465).We used scikit-learn to perform supervised machine learning for developing genetic risk algorithms.RESULTS We identified 2,727,and 204 genetic associations for scores on the JH,cynicism and cynical distrust(CD)scales,respectively.We also found 173 associations with high cynicism,109 with high CD,but no associations with high JH.We also produced polygenic classifiers for high cynicism using machine learning with areas under the receiver operator characteristics curve greater than 0.7.CONCLUSION We found significant genetic components to these traits but no evidence of an interaction.Therefore,while there may be a genetic risk,JH is not likely a burnout risk factor.展开更多
Most genome-wide association studies(GWAS)of Venous Thromboembolism(VTE)have used data from individuals of European descent,however,genetic factors for VTE have not been fully identified in Chinese populations,which c...Most genome-wide association studies(GWAS)of Venous Thromboembolism(VTE)have used data from individuals of European descent,however,genetic factors for VTE have not been fully identified in Chinese populations,which causes the limited use of existing polygenic risk scores(PRS)to identify subpopulations at high risk of VTE for prevention.We,therefore,aimed to curate all the potential VTE-related single-nucleotide polymorphisms(SNPs)for the construction of a new improved PRS model based on the self-adapting method,and then evaluate its utility and effectiveness in the stratification of VTE risk in Chinese populations.We comprehensively analyzed the mutation spectrum of VTE-associated SNPs in the Chinese cohort,and ranked their individual risk effects independently using risk ratio,logistic regression coefficient,and penalty regression coefficient as evaluation criteria.By integrating various algorithms and evaluating their performance,we trained the optimal prediction model of VTE risk in the Chinese population with the least SNP features,established an adaptive PRS model with progressive SNP overlay,and tested it on an independent Chinese population cohort.Self-adaptive polygenic risk score model based on all 318 SNPs or on the 44 most strongly associated SNPs performed similarly(areas under receiver-operating characteristic curves(AUCs)of 0.739 and 0.709,respectively)on the testing dataset of the Chinese VTE cohort,and that achieve the overall best level of the AUC from a conventional PRS model based on known genetic risk factors(0.620–0.718).In addition,we observed the self-adaptive PRS model was an independent effective risk stratification indicator beyond other clinical characteristics including age and smoking status.Our data revealed that only 44 SNPs-derived PRS model can be effectively used in discriminating subpopulations at high risk of VTE.To become clinically useful,our model could benefit from a practically feasible VTE screening program for precision prevention in Chinese populations.展开更多
Genetic dissection and breeding by design for polygenic traits remain substantial challenges.To ad-dress these challenges,it is important to identify as many genes as possible,including key regulatory genes.Here,we de...Genetic dissection and breeding by design for polygenic traits remain substantial challenges.To ad-dress these challenges,it is important to identify as many genes as possible,including key regulatory genes.Here,we developed a genome-wide scanning plus machine learning framework,integrated with advanced computational techniques,to propose a novel algorithm named Fast3VmrMLM.This algo-rithm aims to enhance the identification of abundant and key genes for polygenic traits in the era of big data and artificial intelligence.The algorithm was extended to identify haplotype(Fast3VmrMLM-Hap)and molecular(Fast3VmrMLM-mQTL)variants.In simulation studies,Fast3VmrMLM outperformed existing methods in detecting dominant,small,and rare variants,requiring only 3.30 and 5.43 h(20 threads)to analyze the 18K rice and UK Biobank-scale datasets,respectively.Fast3VmrMLM identified more known(211)and candidate(384)genes for 14 traits in the 18K rice dataset than FarmCPU(100 known genes).Additionally,it identified 26 known and 24 candidate genes for seven yield-related traits in a maize NC II design;Fast3VmrMLM-mQTL identified two known soybean genes near structural variants.We demonstrated that this novel two-step framework outperformed genome-wide scanning alone.In breeding by design,a genetic network constructed via machine learning using all known and candidate genes identified in this study revealed 21 key genes associated with rice yield-related traits.All associated markers yielded high prediction accuracies in rice(0.7443)and maize(0.8492),en-abling the development of superior hybrid combinations.A new breeding-by-design strategy based on the identified key genes was also proposed.This study provides an effective method for gene mining and breeding by design.展开更多
The utility of the polygenic risk score(PRS)to identify individuals at higher risk of stroke beyond clinical risk remains unclear,and we clarified this using Chinese population-based prospective cohorts.Cox proportion...The utility of the polygenic risk score(PRS)to identify individuals at higher risk of stroke beyond clinical risk remains unclear,and we clarified this using Chinese population-based prospective cohorts.Cox proportional hazards models were used to estimate the 10-year risk,and Fine and Gray’s models were used for hazard ratios(HRs),their 95%confidence intervals(CIs),and the lifetime risk according to PRS and clinical risk categories.A total of 41,006 individuals aged 30–75 years with a mean follow-up of 9.0 years were included.Comparing the top versus bottom 5%of the PRS,the HR was 3.01(95%CI 2.03–4.45)in the total population,and similar findings were observed within clinical risk strata.Marked gradients in the 10-year and lifetime risk across PRS categories were also found within clinical risk categories.Notably,among individuals with intermediate clinical risk,the 10-year risk for those in the top 5%of the PRS(7.3%,95%CI 7.1%–7.5%)reached the threshold of high clinical risk(≥7.0%)for initiating preventive treatment,and this effect of the PRS on refining risk stratification was evident for ischemic stroke.Even among those in the top 10%and 20%of the PRS,the 10-year risk would also exceed this level when aged≥50 and≥60 years,respectively.Overall,the combination of the PRS with the clinical risk score improved the risk stratification within clinical risk strata and distinguished actual high-risk individuals with intermediate clinical risk.展开更多
Background:Several studies have reported that polygenic risk scores(PRSs)can enhance risk prediction of coronary artery disease(CAD)in European populations.However,research on this topic is far from sufficient in non-...Background:Several studies have reported that polygenic risk scores(PRSs)can enhance risk prediction of coronary artery disease(CAD)in European populations.However,research on this topic is far from sufficient in non-European countries,including China.We aimed to evaluate the potential of PRS for predicting CAD for primary prevention in the Chinese population.Methods:Participants with genome-wide genotypic data from the China Kadoorie Biobank were divided into training(n=28,490)and testing sets(n=72,150).Ten previously developed PRSs were evaluated,and new ones were developed using clumping and thresholding or LDpred method.The PRS showing the strongest association with CAD in the training set was selected to further evaluate its effects on improving the traditional CAD risk-prediction model in the testing set.Genetic risk was computed by summing the product of the weights and allele dosages across genome-wide single-nucleotide polymorphisms.Prediction of the 10-year first CAD events was assessed using hazard ratios(HRs)and measures of model discrimination,calibration,and net reclassification improvement(NRI).Hard CAD(nonfatal I21-I23 and fatal I20-I25)and soft CAD(all fatal or nonfatal I20-I25)were analyzed separately.Results:In the testing set,1214 hard and 7201 soft CAD cases were documented during a mean follow-up of 11.2 years.The HR per standard deviation of the optimal PRS was 1.26(95%CI:1.19-1.33)for hard CAD.Based on a traditional CAD risk prediction model containing only non-laboratory-based information,the addition of PRS for hard CAD increased Harrell’s C index by 0.001(-0.001 to 0.003)in women and 0.003(0.001 to 0.005)in men.Among the different high-risk thresholds ranging from 1%to 10%,the highest categorical NRI was 3.2%(95%CI:0.4-6.0%)at a high-risk threshold of 10.0%in women.The association of the PRS with soft CAD was much weaker than with hard CAD,leading to minimal or no improvement in the soft CAD model.Conclusions:In this Chinese population sample,the current PRSs minimally changed risk discrimination and offered little improvement in risk stratification for soft CAD.Therefore,this may not be suitable for promoting genetic screening in the general Chinese population to improve CAD risk prediction.展开更多
Genome-wide association studies(GWASs)have shown that the genetic architecture of cancers are highly polygenic and enabled researchers to identify genetic risk loci for cancers.The genetic variants associated with a c...Genome-wide association studies(GWASs)have shown that the genetic architecture of cancers are highly polygenic and enabled researchers to identify genetic risk loci for cancers.The genetic variants associated with a cancer can be combined into a polygenic risk score(PRS),which captures part of an individual’s genetic susceptibility to cancer.Recently,PRSs have been widely used in cancer risk prediction and are shown to be capable of identifying groups of individuals who could benefit from the knowledge of their probabilistic susceptibility to cancer,which leads to an increased interest in understanding the potential utility of PRSs that might further refine the assessment and management of cancer risk.In this context,we provide an overview of the major discoveries from cancer GWASs.We then review the methodologies used for PRS construction,and describe steps for the development and evaluation of risk prediction models that include PRS and/or conventional risk factors.Potential utility of PRSs in cancer risk prediction,screening,and precision prevention are illustrated.Challenges and practical considerations relevant to the implementation of PRSs in health care settings are discussed.展开更多
To investigate whether genetic variants may provide additional prognostic value to improve the existing clinical staging system for gastric cancer(GC),we performed two genome-wide association studies(GWASs)of GC survi...To investigate whether genetic variants may provide additional prognostic value to improve the existing clinical staging system for gastric cancer(GC),we performed two genome-wide association studies(GWASs)of GC survival in the Jiangsu(N=1049)and Shanghai(N=1405)cohorts.By using a TCGA dataset,we validated genetic markers identified from a meta-analysis of these two Chinese cohorts to determine GC survival-associated loci.Then,we constructed a weighted polygenic hazard score(PHS)and developed a nomogram in combination with clinical variables.We also evaluated prognostic accuracy with the time-dependent receiver operating characteristic(ROC)curve,net reclassification improvement(NRI)and integrated discrimination improvement(IDI).We identified a single nucleotide polymorphism(SNP)of rs1618332 at 15q15.1 that was associated with the survival of GC patients with a P value of 4.12×10^(-8),and we also found additional 25 SNPs having consistent associations among these two Chinese cohort and TCGA cohort.The PHS derived from these 26 SNPs(PHS-26)was an independent prognostic factor for GC survival(all P<0.001).The 5-year AUC of PHS-26 was 0.68,0.66 and 0.67 for Jiangsu,Shanghai and their pooled cohorts,respectively,which increased to 0.80,0.82 and 0.81,correspondingly,after being integrated into a nomogram together with variables of the clinical model.The PHS-26 could improve the NRIs by 16.20%,4.90%and 8.70%,respectively,and the IDIs by 11.90%,8.00%and 9.70%,respectively.The 26-SNP based PHS could substantially improve the accuracy of prognostic assessment and might facilitate precision medicine for GC patients.展开更多
Background:A polygenic risk score(PRS)derived from 112 single-nucleotide polymorphisms(SNPs)for gastric cancer has been reported in Chinese populations(PRS-112).However,its performance in other populations is unknown....Background:A polygenic risk score(PRS)derived from 112 single-nucleotide polymorphisms(SNPs)for gastric cancer has been reported in Chinese populations(PRS-112).However,its performance in other populations is unknown.A functional PRS(fPRS)using functional SNPs(fSNPs)may improve the generalizability of the PRS across populations with distinct ethnicities.Methods:We performed functional annotations on SNPs in strong linkage disequilibrium(LD)with the 112 previously reported SNPs to identify fSNPs that affect protein-coding or transcriptional regulation.Subsequently,we constructed an fPRS based on the fSNPs by using the LDpred2-infinitesimal model and then analyzed the performance of the PRS-112 and fPRS in the risk prediction of gastric cancer in 457,521 European participants of the UK Biobank cohort.Finally,the performance of the fPRS in combination with lifestyle factors were evaluated in predicting the risk of gastric cancer.Results:During 4,582,045 person-years of follow-up with a total of 623 incident gastric cancer cases,we found no significant association between the PRS-112 and gastric cancer risk in the European population(hazard ratio[HR]=1.00[95%confidence interval(CI)0.93–1.09],P=0.846).We identified 125 fSNPs,including seven deleterious protein-coding SNPs and 118 regulatory non-coding SNPs,and used them to construct the fPRS-125.Our result showed that the fPRS-125 was significantly associated with gastric cancer risk(HR=1.11[95%CI,1.03–1.20],P=0.009).Compared to participants with a low fPRS-125(bottom quintile),those with a high fPRS-125(top quintile)had a higher risk of incident gastric cancer(HR=1.43[95%CI,1.12–1.84],P=0.005).Moreover,we observed that participants with both an unfavorable lifestyle and a high genetic risk had the highest risk of incident gastric cancer(HR=4.99[95%CI,1.55–16.10],P=0.007)compared to those with both a favorable lifestyle and a low genetic risk.Conclusion:These results indicate that the fPRS-125 derived from fSNPs may act as an indicator to measure the genetic risk of gastric cancer in the European population.展开更多
Background:Polygenic risk score(PRS)derived from summary statistics of genome-wide association studies(GWAS)is a useful tool to infer an individuaPs genetic risk for health outcomes and has gained increasing popularit...Background:Polygenic risk score(PRS)derived from summary statistics of genome-wide association studies(GWAS)is a useful tool to infer an individuaPs genetic risk for health outcomes and has gained increasing popularity in human genetics research.PRS in its simplest form enjoys both computational efficiency and easy accessibility,yet the predictive performance of PRS remains moderate for diseases and traits.Results:We provide an overview of recent advances in statistical methods to improve PRS's performance by incorporating information from linkage disequilibrium,functional annotation,and pleiotropy.We also introduce model validation methods that fine-tune PRS using GWAS summary statistics.Conclusion:In this review,we showcase methodological advances and current limitations of PRS,and discuss several emerging issues in risk prediction research.展开更多
Objective:To construct a novel polygenic risk scoring model,in order to predict the benefits of radiosensitivity in patients with non-metastatic breast cancer(NMBC).Methods:A total of 450 NMBC patients from The Cancer...Objective:To construct a novel polygenic risk scoring model,in order to predict the benefits of radiosensitivity in patients with non-metastatic breast cancer(NMBC).Methods:A total of 450 NMBC patients from The Cancer Genome Atlas(TCGA)were enrolled and randomly assigned 6:4(training vs.validation).The empirical Bayes differential analysis was used to perform differential expression analysis,univariate Cox regression and Kaplan-Meier analysis were used to screen for prognosisrelated genes.Finally,LASSO regression and stepwise regression were used to select key prognostic-related genes.We constructed a multivariate Cox proportional risk regression model using key genes.The pRRophetic function was used to predict drug sensitivity of radiosensitivity(RS)and radioresistance(RR)groups for adjuvant therapy.Results:Eight genes(AMH,H2BU1,HOXB13,TMEM132A,TMEM270,ODF3L1,RIIAD1 and RIMBP2)were screened to build a polygenic risk scoring model.The region of characteristic(ROC)curves were drawn based on the 3-,5-and 10-year overall survival(OS),with area under curves(AUCs)of 0.816,0.822 and 0.806,respectively.RS and RR can be effectively distinguished according to the risk score of 2.004.Gene set enrichment analysis(GSEA)showed that necroptosis was significantly enriched in RS,while complement and coagulation cascade,JAK-STAT and PPAR signaling pathways were significantly enriched in RR.Alternatively,for those radioresistant patients,the chemotherapy drugs that might be more helpful are Cisplatin,Docetaxel,Methotrexate and Vinblastine with higher drug sensitivity.Conclusion:The polygenic risk scoring model showed prediction for the benefit of radiotherapy in NMBC patients,which might be used to guide clinical practice.展开更多
Background:The combinatorial efect of multiple genetic factors calculated as a polygenic risk score(PRS)has been studied to predict disease progression to Alzheimer’s disease(AD)from mild cognitive impairment(MCI).Pr...Background:The combinatorial efect of multiple genetic factors calculated as a polygenic risk score(PRS)has been studied to predict disease progression to Alzheimer’s disease(AD)from mild cognitive impairment(MCI).Previous studies have investigated the performance of PRS in the prediction of disease progression to AD by including and excluding single nucleotide polymorphisms within the region surrounding the APOE gene.These studies may have missed the APOE genotype-specifc predictability of PRS for disease progression to AD.Methods:We analyzed 732 MCI from the Alzheimer’s Disease Neuroimaging Initiative cohort,including those who progressed to AD within 5 years post-baseline(n=270)and remained stable as MCI(n=462).The predictability of PRS including and excluding the APOE region(PRS_(+APOE) and PRS_(−APOE))on the conversion to AD and its interaction with the APOEε4 carrier status were assessed using Cox regression analyses.Results:PRS_(+APOE)(hazard ratio[HR]1.468,95%CI 1.335-1.615)and PRS_(−APOE)(HR 1.293,95%CI 1.157-1.445)were both associated with a signifcantly increased risk of MCI progression to dementia.The interaction between PRS_(+APOE) and APOEε4 carrier status was signifcant with a P-value of 0.0378.The association of PRSs with the progression risk was stronger in APOEε4 non-carriers(PRS_(+APOE):HR 1.710,95%CI 1.244-2.351;PRS_(−APOE):HR 1.429,95%CI 1.182-1.728)than in APOEε4 carriers(PRS_(+APOE):HR 1.167,95%CI 1.005-1.355;PRS_(−APOE):HR 1.172,95%CI 1.020-1.346).Conclusions:PRS could predict the conversion of MCI to dementia with a stronger association in APOEε4 noncarriers than APOEε4 carriers.This indicates PRS as a potential genetic predictor particularly for MCI with no APOEε4 alleles.展开更多
Complex genetic architecture is the major cause of heterogeneity in epilepsy,which poses challenges for accurate diagnosis and precise treatment.A large number of epilepsy candidate genes have been identified from cli...Complex genetic architecture is the major cause of heterogeneity in epilepsy,which poses challenges for accurate diagnosis and precise treatment.A large number of epilepsy candidate genes have been identified from clinical studies,particularly with the widespread use of next-generation sequencing.Validating these candidate genes is emerging as a valuable yet challenging task.Drosophila serves as an ideal animal model for validating candidate genes associated with neurogenetic disorders such as epilepsy,due to its rapid reproduction rate,powerful genetic tools,and efficient use of ethological and electrophysiological assays.Here,we systematically summarize the advantageous techniques of the Drosophila model used to investigate epilepsy genes,including genetic tools for manipulating target gene expression,ethological assays for seizure-like behaviors,electrophysiological techniques,and functional imaging for recording neural activity.We then introduce several typical strategies for identifying epilepsy genes and provide new insights into gene-gene interactions in epilepsy with polygenic causes.We summarize well-established precision medicine strategies for epilepsy and discuss prospective treatment options,including drug therapy and gene therapy for genetic epilepsy based on the Drosophila model.Finally,we also address genetic counseling and assisted reproductive technology as potential approaches for the prevention of genetic epilepsy.展开更多
Genome-wide association studies(GWASs)have identified 30 independent genetic variants associated with IgA nephropathy(IgAN).A genetic risk score(GRS)represents the number of risk alleles carried and thus captures an i...Genome-wide association studies(GWASs)have identified 30 independent genetic variants associated with IgA nephropathy(IgAN).A genetic risk score(GRS)represents the number of risk alleles carried and thus captures an individual's genetic risk.However,whether and which polygenic risk score crucial for the evaluation of any potential personal or clinical utility on risk and prognosis are still obscure.We constructed different GRS models based on different sets of variants,which were top single nucleotide polymorphisms(SNPs)reported in the previous GWASs.The case–control GRS analysis included 3365 IgAN patients and 8842 healthy individuals.The association between GRS and clinical variability,including age at diagnosis,clinical parameters,Oxford pathology classification,and kidney prognosis was further evaluated in a prospective cohort of 1747 patients.Three GRS models(15 SNPs,21 SNPs,and 55 SNPs)were constructed after quality control.The patients with the top 20%GRS had 2.42—(15 SNPs,p=8.12×10^(-40)),3.89—(21 SNPs,p=3.40×10^(-80))and 3.73—(55 SNPs,p=6.86×10^(-81))fold of risk to develop IgAN compared to the patients with the bottom 20%GRS,with area under the receiver operating characteristic curve(AUC)of 0.59,0.63,and 0.63 in group discriminations,respectively.A positive correlation between GRS and microhematuria,mesangial hypercellularity,segmental glomerulosclerosis and a negative correlation on the age at diagnosis,body mass index(BMI),mean arterial pressure(MAP),serum C3,triglycerides can be observed.Patients with the top 20%GRS also showed a higher risk of worse prognosis for all three models(1.36,1.42,and 1.36 fold of risk)compared to the remaining 80%,whereas 21 SNPs model seemed to show a slightly better fit in prediction.Collectively,a higher burden of risk variants is associated with earlier disease onset and a higher risk of a worse prognosis.This may be informational in translating knowledge on IgAN genetics into disease risk prediction and patient stratification.展开更多
基金supported by grants from the National Natural Science Foundation of China(No.82173593,32300473)Guangzhou Science and Technology Project(No.2025A04J4537,2025A04J4696)+1 种基金Guangdong Basic and Applied Basic Research Foundation(No.2023A1515220053)Postdoctoral Science Foundation of Jiangsu Province(No.2021K524C).
文摘Objective:Neuroblastoma is the most common extracranial solid tumor in children and has complex genetic underpinnings.Previous genome-wide association studies(GWASs)have identified many loci associated with neuroblastoma susceptibility;however,their application in risk prediction for Chinese children has not been systematically explored.This study seeks to enhance neuroblastoma risk prediction by validating these loci and evaluating their performance in polygenic risk models.Methods:We validated 35 GWAS-identified neuroblastoma susceptibility loci in a cohort of Chinese children,consisting of 402 neuroblastoma patients and 473 healthy controls.Genotyping these polymorphisms was conducted via the TaqMan method.Univariable and multivariable logistic regression analyses revealed the genetic loci significantly associated with neuroblastoma risk.We constructed polygenic risk models by combining these loci and assessed their predictive performance via area under the curve(AUC)analysis.We also established a polygenic risk scoring(PRS)model for risk prediction by adopting the PLINK method.Results:Fourteen loci,including ten protective polymorphisms from CASC15,BARD1,LMO1,HSD17B12,and HACE1,and four risk variants from BARD1,RSRC1,CPZ and MMP20 were significantly associated with neuroblastoma risk.Compared with single-gene model,the 8-gene model(AUC=0.72)and 13-gene model(AUC=0.73)demonstrated superior predictive performance.Additionally,a PRS incorporating six significant loci achieved an AUC of 0.66,effectively stratifying individuals into distinct risk categories regarding neuroblastoma susceptibility.A higher PRS was significantly associated with advanced International Neuroblastoma Staging System(INSS)stages,suggesting its potential for clinical risk stratification.Conclusions:Our findings validate multiple loci as neuroblastoma risk factors in Chinese children and demonstrate the utility of polygenic risk models,particularly the PRS,in improving risk prediction.These results suggest that integrating multiple genetic variants into a PRS can enhance neuroblastoma risk stratification and potentially improve early diagnosis by guiding targeted screening programs for high-risk children.
基金supported by the National Key Research and Development Programs of China(2024YFF1000100 and 2021YFD1301102)the National Natural Science Foundation of China (32172702)+3 种基金the State Key Laboratory of Animal Biotech Breeding (XQSWYZQZ-KFYX-4)Zaozhuang Elite Industrial Innovation ProgramAgricultural Science and Technology Innovation Program (ASTIP-IAS-TS-6)supported by the United States National Science Foundation (NSF) Collaborative Research Grant (DBI-1458515)
文摘The quantitative trait loci(QTL)-by-environment(Q × E) interaction effect is hard to detect because there are no effective ways to control the genomic background. In this study, we propose a linear mixed model that simultaneously analyzes data from multiple environments to detect Q × E interactions. This model incorporates two different kinship matrices derived from the genome-wide markers to control both main and interaction polygenic background effects. Simulation studies demonstrate that our approach is more powerful than the meta-analysis and inclusive composite interval mapping methods. We further analyze four agronomic traits of rice across four environments. A main effect QTL is identified for 1000-grain weight(KGW), while no QTL are found for tiller number. Additionally, a large QTL with a significant Q × E interaction is detected on chromosome 7 affecting grain number, yield, and KGW. This region harbors two important genes, PROG1 and Ghd7. Furthermore, we apply our mixed model to analyze lodging in barley across six environments. The six regions exhibiting Q × E interaction effects identified by our approach overlap with the SNPs previously identified using EM and MCMC-based Bayesian methods, further validating the robustness of our approach. Both simulation studies and empirical data analyses show that our method outperforms all other methods compared.
基金Supported by China Medical University Hospital,No.DMR-113-105.
文摘BACKGROUND Diabetic retinopathy(DR)is the leading cause of blindness among working-age adults,with an increasing prevalence due to the global burden of diabetes.AIM To develop a polygenic risk score(PRS)to identify high-risk groups for DR and evaluate its severity in patients with type 2 diabetes(T2D).METHODS This population-based study included 13335 patients with T2D,comprising 7295 patients with DR and 6040 without DR.Genetic data,duration of DR diagnosis,body mass index,systolic blood pressure,diastolic blood pressure,and glycated hemoglobin A1c levels were obtained from the study population.The PRS was constructed from a genome-wide association study conducted in a Taiwan region of China Han population.Electronic medical records were used to track patients with T2D and analyze the associations between PRS,timing of DR diagnosis,and therapeutic interventions.The hazard ratio(HR)of PRS for DR development and severity was estimated using multivariate Cox proportional hazards regression.RESULTS The results demonstrated that patients with T2D in the top PRS decile had a 1.21-fold greater risk of developing DR[HR=1.21;95%confidence interval(CI):1.01-1.45;P=0.041]over a 20-year follow-up period.Among patients with DR,those in the highest PRS decile exhibited a 4.81-fold increased risk of requiring more than four laser treatments(HR=4.81;95%CI:1.40-16.5;P=0.012)and a 1.38-fold increased risk of undergoing vitreoretinal surgery(HR=1.38;95%CI:1.01-1.90;P=0.044).CONCLUSION Patients with T2D with a higher PRS are at increased risk of developing DR and may experience more severe forms of the disease.
基金supported by the National Basic Research Development Programof Ministry of Science and Technology of China (2016YFC1306401)the National Natural Science Foundation of China (91749206)。
文摘To evaluate whether the polygenic profile modifies the development of sporadic Alzheimer’s disease(sAD)and pathological biomarkers in cerebrospinal fluid(CSF),462 sAD patients and 463 age-matched cognitively normal(CN)controls were genotyped for 35 singlenucleotide polymorphisms(SNPs)that are significantly associated with sAD.Then,the alleles found to be associated with sAD were used to build polygenic risk score(PRS)models to represent the genetic risk.Receiver operating characteristic(ROC)analyses and the Cox proportional hazards model were used to evaluate the predictive value of PRS for the sAD risk and age at onset.We measured the CSF levels of Aβ42,Aβ42/Aβ40,total tau(T-tau),and phosphorylated tau(P-tau)in a subgroup(60 sAD and 200 CN participants),and analyzed their relationships with the PRSs.We found that 14 SNPs,including SNPs in the APOE,BIN1,CD33,EPHA1,SORL1,and TOMM40 genes,were associated with sAD risk in our cohort.The PRS models built with these SNPs showed potential for discriminating sAD patients from CN controls,and were able to predict the incidence rate of sAD and age at onset.Furthermore,the PRSs were correlated with the CSF levels of Aβ42,Aβ42/Aβ40,T-tau,and P-tau.Our study suggests that PRS models hold promise for assessing the genetic risk and development of AD.As genetic risk profiles vary among populations,large-scale genome-wide sequencing studies are urgently needed to identify the genetic risk loci of sAD in Chinese populations to build accurate PRS models for clinical practice.
文摘Highly fecund marine species with dispersive life-history stages often display large population sizes and wide geographic distribution ranges. Consequently, they are expected to experience reduced genetic drift, efficient selection fueled by frequent adaptive mutations, and high migration loads. This has important consequences for understanding how local adaptation proceeds in the sea. A key issue in this regard, relates to the genetic architecture underlying fitness traits. Theory predicts that adaptation may involve many genes but with a high variance in effect size. Therefore, the effect of selection on allele frequencies may be substantial for the largest effect size loci, but insignificant for small effect genes. In such a context, the performance of population genomic methods to unravel the genetic basis of adaptation depends on the fraction of adaptive genetic variance explained by the cumulative effect of outlier loci. Here, we address some methodological challenges associated with the detection of local adaptation using molecular approaches. We provide an overview of genome scan methods to detect selection, including those assuming complex demographic models that better describe spatial population structure. We then focus on quantitative genetics approaches that search for genotype-phenotype associations at different genomic scales, including genome-wide methods evaluating the cumulative effect of variants. We argue that the limited power of single locus tests can be alleviated by the use of polygenic scores to estimate the joint contribution of candidate variants to phenotypic variation.
基金Supported by the National Natural Science Foundation of China,No. 31870777。
文摘BACKGROUND Genetic variants of Helicobacter pylori(H. pylori) are involved in gastric cancer occurrence. Single nucleotide polymorphisms(SNPs) of H. pylori that are associated with gastric cancer have been reported. The combined effect of H. pylori SNPs on the risk of gastric cancer remains unclear.AIM To assess the performance of a polygenic risk score(PRS) based on H. pylori SNPs in predicting the risk of gastric cancer.METHODS A total of 15 gastric cancer-associated H. pylori SNPs were selected. The associations between these SNPs and gastric cancer were further validated in 1022 global strains with publicly available genome sequences. The PRS model was established based on the validated SNPs. The performance of the PRS for predicting the risk of gastric cancer was assessed in global strains using quintiles and random forest(RF) methods. The variation in the performance of the PRS among different populations of H. pylori was further examined.RESULTS Analyses of the association between selected SNPs and gastric cancer in the global dataset revealed that the risk allele frequencies of six SNPs were significantly higher in gastric cancer cases than non-gastric cancer cases. The PRS model constructed subsequently with these validated SNPs produced significantly higher scores in gastric cancer. The odds ratio(OR) value for gastric cancer gradually increased from the first to the fifth quintile of PRS, with the fifth quintile having an OR value as high as 9.76(95% confidence interval: 5.84-16.29). The results of RF analyses indicated that the area under the curve(AUC) value for classifying gastric cancer and non-gastric cancer was 0.75, suggesting that the PRS based on H. pylori SNPs was capable of predicting the risk of gastric cancer. Assessing the performance of the PRS among different H. pylori populations demonstrated that it had good predictive power for cancer risk for hp Europe strains, with an AUC value of 0.78.CONCLUSION The PRS model based on H. pylori SNPs had a good performance for assessment of gastric cancer risk. It would be useful in the prediction of final consequences of the H. pylori infection and beneficial for the management of the infection in clinical settings.
基金Supported by the National Natural Science Foundation of China,No.31870777.
文摘Genetic variations are associated with individual susceptibility to gastric cancer.Recently,polygenic risk score(PRS)models have been established based on genetic variants to predict the risk of gastric cancer.To assess the accuracy of current PRS models in the risk prediction,a systematic review was conducted.A total of eight eligible studies consisted of 544842 participants were included for evaluation of the performance of PRS models.The overall accuracy was moderate with Area under the curve values ranging from 0.5600 to 0.7823.Incorporation of epidemiological factors or Helicobacter pylori(H.pylori)status increased the accuracy for risk prediction,while selection of single nucleotide polymorphism(SNP)and number of SNPs appeared to have little impact on the model performance.To further improve the accuracy of PRS models for risk prediction of gastric cancer,we summarized the association between gastric cancer risk and H.pylori genomic variations,cancer associated bacteria members in the gastric microbiome,discussed the potentials for performance improvement of PRS models with these microbial factors.Future studies on comprehensive PRS models established with human SNPs,epidemiological factors and microbial factors are indicated.
文摘BACKGROUND John Henryism(JH)is a strategy for dealing with chronic psychological stress characterized by high levels of physical effort and work.Cynicism is a belief that people are motivated primarily by self-interest.High scores on the JH scale and cynicism measures correlate with an increased risk of cardiovascular disease.High cynicism is also a hallmark of burnout syndrome,another known risk factor for heart disease.AIM To evaluate possible interactions between JH and cynicism hoping to clarify risk factors of burnout.METHODS We analyzed genetic and psychological data available from the Database of Genotypes and Phenotypes for genome-wide associations with these traits.We split the total available samples and used plink to perform the association studies on the discovery set(n=1852,80%)and tested for replication using the validation set(n=465).We used scikit-learn to perform supervised machine learning for developing genetic risk algorithms.RESULTS We identified 2,727,and 204 genetic associations for scores on the JH,cynicism and cynical distrust(CD)scales,respectively.We also found 173 associations with high cynicism,109 with high CD,but no associations with high JH.We also produced polygenic classifiers for high cynicism using machine learning with areas under the receiver operator characteristics curve greater than 0.7.CONCLUSION We found significant genetic components to these traits but no evidence of an interaction.Therefore,while there may be a genetic risk,JH is not likely a burnout risk factor.
基金National High Level Hospital Clinical Research Funding 2023-NHLHCRF-YGJH-03.
文摘Most genome-wide association studies(GWAS)of Venous Thromboembolism(VTE)have used data from individuals of European descent,however,genetic factors for VTE have not been fully identified in Chinese populations,which causes the limited use of existing polygenic risk scores(PRS)to identify subpopulations at high risk of VTE for prevention.We,therefore,aimed to curate all the potential VTE-related single-nucleotide polymorphisms(SNPs)for the construction of a new improved PRS model based on the self-adapting method,and then evaluate its utility and effectiveness in the stratification of VTE risk in Chinese populations.We comprehensively analyzed the mutation spectrum of VTE-associated SNPs in the Chinese cohort,and ranked their individual risk effects independently using risk ratio,logistic regression coefficient,and penalty regression coefficient as evaluation criteria.By integrating various algorithms and evaluating their performance,we trained the optimal prediction model of VTE risk in the Chinese population with the least SNP features,established an adaptive PRS model with progressive SNP overlay,and tested it on an independent Chinese population cohort.Self-adaptive polygenic risk score model based on all 318 SNPs or on the 44 most strongly associated SNPs performed similarly(areas under receiver-operating characteristic curves(AUCs)of 0.739 and 0.709,respectively)on the testing dataset of the Chinese VTE cohort,and that achieve the overall best level of the AUC from a conventional PRS model based on known genetic risk factors(0.620–0.718).In addition,we observed the self-adaptive PRS model was an independent effective risk stratification indicator beyond other clinical characteristics including age and smoking status.Our data revealed that only 44 SNPs-derived PRS model can be effectively used in discriminating subpopulations at high risk of VTE.To become clinically useful,our model could benefit from a practically feasible VTE screening program for precision prevention in Chinese populations.
基金supported by the National Natural Science Foundation of China,China(32470657 and 32270673).
文摘Genetic dissection and breeding by design for polygenic traits remain substantial challenges.To ad-dress these challenges,it is important to identify as many genes as possible,including key regulatory genes.Here,we developed a genome-wide scanning plus machine learning framework,integrated with advanced computational techniques,to propose a novel algorithm named Fast3VmrMLM.This algo-rithm aims to enhance the identification of abundant and key genes for polygenic traits in the era of big data and artificial intelligence.The algorithm was extended to identify haplotype(Fast3VmrMLM-Hap)and molecular(Fast3VmrMLM-mQTL)variants.In simulation studies,Fast3VmrMLM outperformed existing methods in detecting dominant,small,and rare variants,requiring only 3.30 and 5.43 h(20 threads)to analyze the 18K rice and UK Biobank-scale datasets,respectively.Fast3VmrMLM identified more known(211)and candidate(384)genes for 14 traits in the 18K rice dataset than FarmCPU(100 known genes).Additionally,it identified 26 known and 24 candidate genes for seven yield-related traits in a maize NC II design;Fast3VmrMLM-mQTL identified two known soybean genes near structural variants.We demonstrated that this novel two-step framework outperformed genome-wide scanning alone.In breeding by design,a genetic network constructed via machine learning using all known and candidate genes identified in this study revealed 21 key genes associated with rice yield-related traits.All associated markers yielded high prediction accuracies in rice(0.7443)and maize(0.8492),en-abling the development of superior hybrid combinations.A new breeding-by-design strategy based on the identified key genes was also proposed.This study provides an effective method for gene mining and breeding by design.
基金supported by the Chinese Academy of Medical Sciences(CAMS)Innovation Fund for Medical Sciences(2021-I2M-1-010,2019-I2M-2-003,and 2017-I2M-1-004)the National High Level Hospital Clinical Research Funding(2022-GSP-GG-1,2022-GSPGG-2)+5 种基金Research Unit of Prospective Cohort of Cardiovascular Diseases and Cancers,CAMS(2019RU038)the National Key Research and Development Program of China(2018YFE0115300 and 2017YFC0211700)the National Natural Science Foundation of China(82030102,1212660291857118)Taikang Yicai Public Health and Epidemic Control Fund(TKYC-GW-2020)the National Clinical Research Center for Cardiovascular Diseases,Fuwai Hospital,Chinese Academy of Medical Sciences(NCRC2020006)。
文摘The utility of the polygenic risk score(PRS)to identify individuals at higher risk of stroke beyond clinical risk remains unclear,and we clarified this using Chinese population-based prospective cohorts.Cox proportional hazards models were used to estimate the 10-year risk,and Fine and Gray’s models were used for hazard ratios(HRs),their 95%confidence intervals(CIs),and the lifetime risk according to PRS and clinical risk categories.A total of 41,006 individuals aged 30–75 years with a mean follow-up of 9.0 years were included.Comparing the top versus bottom 5%of the PRS,the HR was 3.01(95%CI 2.03–4.45)in the total population,and similar findings were observed within clinical risk strata.Marked gradients in the 10-year and lifetime risk across PRS categories were also found within clinical risk categories.Notably,among individuals with intermediate clinical risk,the 10-year risk for those in the top 5%of the PRS(7.3%,95%CI 7.1%–7.5%)reached the threshold of high clinical risk(≥7.0%)for initiating preventive treatment,and this effect of the PRS on refining risk stratification was evident for ischemic stroke.Even among those in the top 10%and 20%of the PRS,the 10-year risk would also exceed this level when aged≥50 and≥60 years,respectively.Overall,the combination of the PRS with the clinical risk score improved the risk stratification within clinical risk strata and distinguished actual high-risk individuals with intermediate clinical risk.
基金supported by grants from the National Natural Science Foundation of China(Nos.82192904,82192901,82192900,and 91846303)The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation in Hong Kong.The long-term follow-up is supported by grants from the UK Wellcome Trust(Nos.212946/Z/18/Z,202922/Z/16/Z,104085/Z/14/Z,and 088158/Z/09/Z)+2 种基金the National Key Research and Development Program of China(No.2016 YFC0900500)National Natural Science Foundation of China(No.81390540)Chinese Ministry of Science and Technology(No.2011BAI09B01).
文摘Background:Several studies have reported that polygenic risk scores(PRSs)can enhance risk prediction of coronary artery disease(CAD)in European populations.However,research on this topic is far from sufficient in non-European countries,including China.We aimed to evaluate the potential of PRS for predicting CAD for primary prevention in the Chinese population.Methods:Participants with genome-wide genotypic data from the China Kadoorie Biobank were divided into training(n=28,490)and testing sets(n=72,150).Ten previously developed PRSs were evaluated,and new ones were developed using clumping and thresholding or LDpred method.The PRS showing the strongest association with CAD in the training set was selected to further evaluate its effects on improving the traditional CAD risk-prediction model in the testing set.Genetic risk was computed by summing the product of the weights and allele dosages across genome-wide single-nucleotide polymorphisms.Prediction of the 10-year first CAD events was assessed using hazard ratios(HRs)and measures of model discrimination,calibration,and net reclassification improvement(NRI).Hard CAD(nonfatal I21-I23 and fatal I20-I25)and soft CAD(all fatal or nonfatal I20-I25)were analyzed separately.Results:In the testing set,1214 hard and 7201 soft CAD cases were documented during a mean follow-up of 11.2 years.The HR per standard deviation of the optimal PRS was 1.26(95%CI:1.19-1.33)for hard CAD.Based on a traditional CAD risk prediction model containing only non-laboratory-based information,the addition of PRS for hard CAD increased Harrell’s C index by 0.001(-0.001 to 0.003)in women and 0.003(0.001 to 0.005)in men.Among the different high-risk thresholds ranging from 1%to 10%,the highest categorical NRI was 3.2%(95%CI:0.4-6.0%)at a high-risk threshold of 10.0%in women.The association of the PRS with soft CAD was much weaker than with hard CAD,leading to minimal or no improvement in the soft CAD model.Conclusions:In this Chinese population sample,the current PRSs minimally changed risk discrimination and offered little improvement in risk stratification for soft CAD.Therefore,this may not be suitable for promoting genetic screening in the general Chinese population to improve CAD risk prediction.
基金the National Natural Science Foundation of China(81820108028,81922061,82003530).
文摘Genome-wide association studies(GWASs)have shown that the genetic architecture of cancers are highly polygenic and enabled researchers to identify genetic risk loci for cancers.The genetic variants associated with a cancer can be combined into a polygenic risk score(PRS),which captures part of an individual’s genetic susceptibility to cancer.Recently,PRSs have been widely used in cancer risk prediction and are shown to be capable of identifying groups of individuals who could benefit from the knowledge of their probabilistic susceptibility to cancer,which leads to an increased interest in understanding the potential utility of PRSs that might further refine the assessment and management of cancer risk.In this context,we provide an overview of the major discoveries from cancer GWASs.We then review the methodologies used for PRS construction,and describe steps for the development and evaluation of risk prediction models that include PRS and/or conventional risk factors.Potential utility of PRSs in cancer risk prediction,screening,and precision prevention are illustrated.Challenges and practical considerations relevant to the implementation of PRSs in health care settings are discussed.
基金supported by National Natural Science Foundation of China(82125033,81872702,82103932,82003534)Natural Science Foundation of Jiangsu Province(BK20200674).
文摘To investigate whether genetic variants may provide additional prognostic value to improve the existing clinical staging system for gastric cancer(GC),we performed two genome-wide association studies(GWASs)of GC survival in the Jiangsu(N=1049)and Shanghai(N=1405)cohorts.By using a TCGA dataset,we validated genetic markers identified from a meta-analysis of these two Chinese cohorts to determine GC survival-associated loci.Then,we constructed a weighted polygenic hazard score(PHS)and developed a nomogram in combination with clinical variables.We also evaluated prognostic accuracy with the time-dependent receiver operating characteristic(ROC)curve,net reclassification improvement(NRI)and integrated discrimination improvement(IDI).We identified a single nucleotide polymorphism(SNP)of rs1618332 at 15q15.1 that was associated with the survival of GC patients with a P value of 4.12×10^(-8),and we also found additional 25 SNPs having consistent associations among these two Chinese cohort and TCGA cohort.The PHS derived from these 26 SNPs(PHS-26)was an independent prognostic factor for GC survival(all P<0.001).The 5-year AUC of PHS-26 was 0.68,0.66 and 0.67 for Jiangsu,Shanghai and their pooled cohorts,respectively,which increased to 0.80,0.82 and 0.81,correspondingly,after being integrated into a nomogram together with variables of the clinical model.The PHS-26 could improve the NRIs by 16.20%,4.90%and 8.70%,respectively,and the IDIs by 11.90%,8.00%and 9.70%,respectively.The 26-SNP based PHS could substantially improve the accuracy of prognostic assessment and might facilitate precision medicine for GC patients.
基金supported by grants from the National Natural Science Foundation of China(Nos.82125033,82230110,81872702,82003534,and 82273714)the Natural Science Foundation of Jiangsu Province(No.BK20200674)CAMS Innovation Fund for Medical Sciences(No.2019RU038).
文摘Background:A polygenic risk score(PRS)derived from 112 single-nucleotide polymorphisms(SNPs)for gastric cancer has been reported in Chinese populations(PRS-112).However,its performance in other populations is unknown.A functional PRS(fPRS)using functional SNPs(fSNPs)may improve the generalizability of the PRS across populations with distinct ethnicities.Methods:We performed functional annotations on SNPs in strong linkage disequilibrium(LD)with the 112 previously reported SNPs to identify fSNPs that affect protein-coding or transcriptional regulation.Subsequently,we constructed an fPRS based on the fSNPs by using the LDpred2-infinitesimal model and then analyzed the performance of the PRS-112 and fPRS in the risk prediction of gastric cancer in 457,521 European participants of the UK Biobank cohort.Finally,the performance of the fPRS in combination with lifestyle factors were evaluated in predicting the risk of gastric cancer.Results:During 4,582,045 person-years of follow-up with a total of 623 incident gastric cancer cases,we found no significant association between the PRS-112 and gastric cancer risk in the European population(hazard ratio[HR]=1.00[95%confidence interval(CI)0.93–1.09],P=0.846).We identified 125 fSNPs,including seven deleterious protein-coding SNPs and 118 regulatory non-coding SNPs,and used them to construct the fPRS-125.Our result showed that the fPRS-125 was significantly associated with gastric cancer risk(HR=1.11[95%CI,1.03–1.20],P=0.009).Compared to participants with a low fPRS-125(bottom quintile),those with a high fPRS-125(top quintile)had a higher risk of incident gastric cancer(HR=1.43[95%CI,1.12–1.84],P=0.005).Moreover,we observed that participants with both an unfavorable lifestyle and a high genetic risk had the highest risk of incident gastric cancer(HR=4.99[95%CI,1.55–16.10],P=0.007)compared to those with both a favorable lifestyle and a low genetic risk.Conclusion:These results indicate that the fPRS-125 derived from fSNPs may act as an indicator to measure the genetic risk of gastric cancer in the European population.
文摘Background:Polygenic risk score(PRS)derived from summary statistics of genome-wide association studies(GWAS)is a useful tool to infer an individuaPs genetic risk for health outcomes and has gained increasing popularity in human genetics research.PRS in its simplest form enjoys both computational efficiency and easy accessibility,yet the predictive performance of PRS remains moderate for diseases and traits.Results:We provide an overview of recent advances in statistical methods to improve PRS's performance by incorporating information from linkage disequilibrium,functional annotation,and pleiotropy.We also introduce model validation methods that fine-tune PRS using GWAS summary statistics.Conclusion:In this review,we showcase methodological advances and current limitations of PRS,and discuss several emerging issues in risk prediction research.
基金This study was supported by National Natural Science Foundation of China(81773363,81872558 and 81972969)Key R&D Project of the Department of Science and Technology of Zhejiang Province(2020C03028)+1 种基金Key Project Jointly Built by the Ministry of Zhejiang Health Commission(2021438235)Major Project of Wenzhou Bureau of Science and Technology(2020ZY0011),China.
文摘Objective:To construct a novel polygenic risk scoring model,in order to predict the benefits of radiosensitivity in patients with non-metastatic breast cancer(NMBC).Methods:A total of 450 NMBC patients from The Cancer Genome Atlas(TCGA)were enrolled and randomly assigned 6:4(training vs.validation).The empirical Bayes differential analysis was used to perform differential expression analysis,univariate Cox regression and Kaplan-Meier analysis were used to screen for prognosisrelated genes.Finally,LASSO regression and stepwise regression were used to select key prognostic-related genes.We constructed a multivariate Cox proportional risk regression model using key genes.The pRRophetic function was used to predict drug sensitivity of radiosensitivity(RS)and radioresistance(RR)groups for adjuvant therapy.Results:Eight genes(AMH,H2BU1,HOXB13,TMEM132A,TMEM270,ODF3L1,RIIAD1 and RIMBP2)were screened to build a polygenic risk scoring model.The region of characteristic(ROC)curves were drawn based on the 3-,5-and 10-year overall survival(OS),with area under curves(AUCs)of 0.816,0.822 and 0.806,respectively.RS and RR can be effectively distinguished according to the risk score of 2.004.Gene set enrichment analysis(GSEA)showed that necroptosis was significantly enriched in RS,while complement and coagulation cascade,JAK-STAT and PPAR signaling pathways were significantly enriched in RR.Alternatively,for those radioresistant patients,the chemotherapy drugs that might be more helpful are Cisplatin,Docetaxel,Methotrexate and Vinblastine with higher drug sensitivity.Conclusion:The polygenic risk scoring model showed prediction for the benefit of radiotherapy in NMBC patients,which might be used to guide clinical practice.
基金Alzheimer’s Disease Neuroimaging Initiative(National Institutes of Health Grant U01 AG024904)and DOD ADNI(Department of Defense award number W81XWH-12–2-0012).ADNI is funded by the National Institute on Agingthe National Institute of Biomedical Imaging and Bioengineering,and through generous contributions from the following:AbbVie,Alzheimer’s Association+28 种基金Alzheimer’s Drug Discovery FoundationAraclon BiotechBioClinica,Inc.BiogenBristol-Myers Squibb CompanyCereSpir,Inc.CogstateEisai Inc.Elan Pharmaceuticals,Inc.Eli Lilly and CompanyEuroImmunF.Hofmann-La Roche Ltd and its afliated company Genentech,Inc.FujirebioGE HealthcareIXICO Ltd.Janssen Alzheimer Immunotherapy Research&Development,LLC.Johnson&Johnson Pharmaceutical Research&Development LLC.LumosityLundbeckMerck&Co.,Inc.Meso Scale Diagnostics,LLC.NeuroRx ResearchNeurotrack TechnologiesNovartis Pharmaceuticals CorporationPfzer Inc.Piramal ImagingServierTakeda Pharmaceutical Companyand Transition Therapeutics.The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada.Private sector contributions are facilitated by the Foundation for the National Institutes of Health(www.fnih.org).The grantee organization is the Northern California Institute for Research and Education,and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California.ADNI data are dis‑seminated by the Laboratory for Neuro Imaging at the University of Southern California.
文摘Background:The combinatorial efect of multiple genetic factors calculated as a polygenic risk score(PRS)has been studied to predict disease progression to Alzheimer’s disease(AD)from mild cognitive impairment(MCI).Previous studies have investigated the performance of PRS in the prediction of disease progression to AD by including and excluding single nucleotide polymorphisms within the region surrounding the APOE gene.These studies may have missed the APOE genotype-specifc predictability of PRS for disease progression to AD.Methods:We analyzed 732 MCI from the Alzheimer’s Disease Neuroimaging Initiative cohort,including those who progressed to AD within 5 years post-baseline(n=270)and remained stable as MCI(n=462).The predictability of PRS including and excluding the APOE region(PRS_(+APOE) and PRS_(−APOE))on the conversion to AD and its interaction with the APOEε4 carrier status were assessed using Cox regression analyses.Results:PRS_(+APOE)(hazard ratio[HR]1.468,95%CI 1.335-1.615)and PRS_(−APOE)(HR 1.293,95%CI 1.157-1.445)were both associated with a signifcantly increased risk of MCI progression to dementia.The interaction between PRS_(+APOE) and APOEε4 carrier status was signifcant with a P-value of 0.0378.The association of PRSs with the progression risk was stronger in APOEε4 non-carriers(PRS_(+APOE):HR 1.710,95%CI 1.244-2.351;PRS_(−APOE):HR 1.429,95%CI 1.182-1.728)than in APOEε4 carriers(PRS_(+APOE):HR 1.167,95%CI 1.005-1.355;PRS_(−APOE):HR 1.172,95%CI 1.020-1.346).Conclusions:PRS could predict the conversion of MCI to dementia with a stronger association in APOEε4 noncarriers than APOEε4 carriers.This indicates PRS as a potential genetic predictor particularly for MCI with no APOEε4 alleles.
基金supported by the Guangdong Basic and Applied Basic Research Foundation,No.2022A1515111123(to JQ)。
文摘Complex genetic architecture is the major cause of heterogeneity in epilepsy,which poses challenges for accurate diagnosis and precise treatment.A large number of epilepsy candidate genes have been identified from clinical studies,particularly with the widespread use of next-generation sequencing.Validating these candidate genes is emerging as a valuable yet challenging task.Drosophila serves as an ideal animal model for validating candidate genes associated with neurogenetic disorders such as epilepsy,due to its rapid reproduction rate,powerful genetic tools,and efficient use of ethological and electrophysiological assays.Here,we systematically summarize the advantageous techniques of the Drosophila model used to investigate epilepsy genes,including genetic tools for manipulating target gene expression,ethological assays for seizure-like behaviors,electrophysiological techniques,and functional imaging for recording neural activity.We then introduce several typical strategies for identifying epilepsy genes and provide new insights into gene-gene interactions in epilepsy with polygenic causes.We summarize well-established precision medicine strategies for epilepsy and discuss prospective treatment options,including drug therapy and gene therapy for genetic epilepsy based on the Drosophila model.Finally,we also address genetic counseling and assisted reproductive technology as potential approaches for the prevention of genetic epilepsy.
基金supported by National Science Foundation of China(82022010,82370709,81970613,82070733,82000680)Beijing Natural Science Foundation(Z190023)+3 种基金Academy of Medical Sciences–Newton Advanced Fellowship(NAFR13\1033)Fok Ying Tung Education Foundation(171030)Chinese Academy of Medical Sciences(CAMS)Innovation Fund for Medical Sciences(2019-I2M-5–046,2020-JKCS-009)National High Level Hospital Clinical Research Funding(Interdisciplinary Clinical Research Project of Peking University First Hospital,2022CR41)。
文摘Genome-wide association studies(GWASs)have identified 30 independent genetic variants associated with IgA nephropathy(IgAN).A genetic risk score(GRS)represents the number of risk alleles carried and thus captures an individual's genetic risk.However,whether and which polygenic risk score crucial for the evaluation of any potential personal or clinical utility on risk and prognosis are still obscure.We constructed different GRS models based on different sets of variants,which were top single nucleotide polymorphisms(SNPs)reported in the previous GWASs.The case–control GRS analysis included 3365 IgAN patients and 8842 healthy individuals.The association between GRS and clinical variability,including age at diagnosis,clinical parameters,Oxford pathology classification,and kidney prognosis was further evaluated in a prospective cohort of 1747 patients.Three GRS models(15 SNPs,21 SNPs,and 55 SNPs)were constructed after quality control.The patients with the top 20%GRS had 2.42—(15 SNPs,p=8.12×10^(-40)),3.89—(21 SNPs,p=3.40×10^(-80))and 3.73—(55 SNPs,p=6.86×10^(-81))fold of risk to develop IgAN compared to the patients with the bottom 20%GRS,with area under the receiver operating characteristic curve(AUC)of 0.59,0.63,and 0.63 in group discriminations,respectively.A positive correlation between GRS and microhematuria,mesangial hypercellularity,segmental glomerulosclerosis and a negative correlation on the age at diagnosis,body mass index(BMI),mean arterial pressure(MAP),serum C3,triglycerides can be observed.Patients with the top 20%GRS also showed a higher risk of worse prognosis for all three models(1.36,1.42,and 1.36 fold of risk)compared to the remaining 80%,whereas 21 SNPs model seemed to show a slightly better fit in prediction.Collectively,a higher burden of risk variants is associated with earlier disease onset and a higher risk of a worse prognosis.This may be informational in translating knowledge on IgAN genetics into disease risk prediction and patient stratification.
