Evaluation of polygenic risk score for risk prediction of gastric cancer

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.

Genome-wide associations, polygenic risk, and Mendelian randomization reveal limited interactions between John Henryism and cynicism

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.

Prediction of gastric cancer risk by a polygenic risk score of Helicobacter pylori

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.

Integrating polygenic and clinical risks to improve stroke risk stratification in prospective Chinese cohorts

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.

Construction and evaluation of the functional polygenic risk score for gastric cancer in a prospective cohort of the European population

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.

Minimal improvement in coronary artery disease risk prediction in Chinese population using polygenic risk scores:evidence from the China Kadoorie Biobank

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.

Polygenic risk score for prediction of radiotherapy efficacy and radiosensitivity in patients with non-metastatic breast 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.

Effectiveness of colorectal cancer screening integrating non-genetic and genetic risk: a prospective study based on UK Biobank data

Objective: Few studies have evaluated the benefits of colorectal cancer(CRC) screening integrating both non-genetic and genetic risk factors. Here, we aimed to integrate an existing non-genetic risk model(QCancer-10) and a 139-variant polygenic risk score to evaluate the effectiveness of screening on CRC incidence and mortality.Methods: We applied the integrated model to calculate 10-year CRC risk for 430,908 participants in the UK Biobank, and divided the participants into low-, intermediate-, and high-risk groups. We calculated the screening-associated hazard ratios(HRs) and absolute risk reductions(ARRs) for CRC incidence and mortality according to risk stratification.Results: During a median follow-up of 11.03 years and 12.60 years, we observed 5,158 CRC cases and 1,487 CRC deaths, respectively. CRC incidence and mortality were significantly lower among screened than non-screened participants in both the intermediateand high-risk groups [incidence: HR: 0.87, 95% confidence interval(CI): 0.81±0.94;0.81, 0.73±0.90;mortality: 0.75, 0.64±0.87;0.70, 0.58±0.85], which composed approximately 60% of the study population. The ARRs(95% CI) were 0.17(0.11±0.24) and 0.43(0.24±0.61), respectively, for CRC incidence, and 0.08(0.05±0.11) and 0.24(0.15±0.33), respectively, for mortality. Screening did not significantly reduce the relative or absolute risk of CRC incidence and mortality in the low-risk group. Further analysis revealed that screening was most effective for men and individuals with distal CRC among the intermediate to high-risk groups.Conclusions: After integrating both genetic and non-genetic factors, our findings provided priority evidence of risk-stratified CRC screening and valuable insights for the rational allocation of health resources.

Association of Polygenic Risk Score with Age at Onset and Cerebrospinal Fluid Biomarkers of Alzheimer’s Disease in a Chinese Cohort

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.

Detecting polygenic selection in marine populations by combining population genomics and quantitative genetics approaches

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.

Polygenic risk scores:the future of cancer risk prediction,screening,and precision prevention

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.

Polygenic risk scores: effect estimation and model optimization

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.

Predictability of polygenic risk score for progression to dementia and its interaction with APOEε4 in mild cognitive impairment

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.

Risk assessment of venous thromboembolism in inflammatory bowel disease by inherited risk in a population-based incident cohort

Inflammatory bowel disease(IBD),including Crohn’s disease(CD)and ulcerative colitis(UC),is a chronic inflammatory disease of the digestive tract with increasing prevalence globally.Although venous thromboembolism(VTE)is a major complication in IBD patients,it is often underappreciated with limited tools for risk stratification.AIM To estimate the proportion of VTE among IBD patients and assess genetic risk factors(monogenic and polygenic)for VTE.METHODS Incident VTE was followed for 8465 IBD patients in the UK Biobank(UKB).The associations of VTE with F5 factor V leiden(FVL)mutation,F2 G20210A prothrombin gene mutation(PGM),and polygenic score(PGS003332)were tested using Cox hazards regression analysis,adjusting for age at IBD diagnosis,gender,and genetic background(top 10 principal components).The performance of genetic risk factors for discriminating VTE diagnosis was estimated using the area under the receiver operating characteristic curve(AUC).RESULTS The overall proportion of incident VTE was 4.70%in IBD patients and was similar for CD(4.46%),UC(4.49%),and unclassified(6.42%),and comparable to that of cancer patients(4.66%)who are well-known at increased risk for VTE.Mutation carriers of F5/F2 had a significantly increased risk for VTE compared to non-mutation carriers,hazard ratio(HR)was 1.94,95%confidence interval(CI):1.42-2.65.In contrast,patients with the top PGS decile had a considerably higher risk for VTE compared to those with intermediate scores(middle 8 deciles),HR was 2.06(95%CI:1.57-2.71).The AUC for differentiating VTE diagnosis was 0.64(95%CI:0.61-0.67),0.68(95%CI:0.66-0.71),and 0.69(95%CI:0.66-0.71),respectively,for F5/F2 mutation carriers,PGS,and combined.CONCLUSION Similar to cancer patients,VTE complications are common in IBD patients.PGS provides more informative risk information than F5/F2 mutations(FVL and PGM)for personalized thromboprophylaxis.

Impact of cognition-related single nucleotide polymorphisms on brain imaging phenotype in Parkinson’s disease

Multiple single nucleotide polymorphisms may contribute to cognitive decline in Parkinson’s disease. However, the mechanism by which these single nucleotide polymorphisms modify brain imaging phenotype remains unclear. The aim of this study was to investigate the potential effects of multiple single nucleotide polymorphisms on brain imaging phenotype in Parkinson’s disease. Forty-eight Parkinson’s disease patients and 39 matched healthy controls underwent genotyping and 7 T magnetic resonance imaging. A cognitive-weighted polygenic risk score model was designed, in which the effect sizes were determined individually for 36 single nucleotide polymorphisms. The correlations between polygenic risk score, neuroimaging features, and clinical data were analyzed. Furthermore, individual single nucleotide polymorphism analysis was performed to explore the main effects of genotypes and their interactive effects with Parkinson’s disease diagnosis. We found that, in Parkinson’s disease, the polygenic risk score was correlated with the neural activity of the hippocampus, parahippocampus, and fusiform gyrus, and with hippocampal-prefrontal and fusiform-temporal connectivity, as well as with gray matter alterations in the orbitofrontal cortex. In addition, we found that single nucleotide polymorphisms in α-synuclein(SNCA) were associated with white matter microstructural changes in the superior corona radiata, corpus callosum, and external capsule. A single nucleotide polymorphism in catechol-O-methyltransferase was associated with the neural activities of the lingual, fusiform, and occipital gyri, which are involved in visual cognitive dysfunction. Furthermore, DRD3 was associated with frontal and temporal lobe function and structure. In conclusion, imaging genetics is useful for providing a better understanding of the genetic pathways involved in the pathophysiologic processes underlying Parkinson’s disease. This study provides evidence of an association between genetic factors, cognitive functions, and multi-modality neuroimaging biomarkers in Parkinson’s disease.

Evaluating the potential of(epi)genotype‑by‑low pass nanopore sequencing in dairy cattle:a study on direct genomic value and methylation analysis

Background Genotype-by-sequencing has been proposed as an alternative to SNP genotyping arrays in genomic selection to obtain a high density of markers along the genome.It requires a low sequencing depth to be cost effective,which may increase the error at the genotype assigment.Third generation nanopore sequencing technology offers low cost sequencing and the possibility to detect genome methylation,which provides added value to genotype-by-sequencing.The aim of this study was to evaluate the performance of genotype-by-low pass nanopore sequencing for estimating the direct genomic value in dairy cattle,and the possibility to obtain methylation marks simultaneously.Results Latest nanopore chemistry(LSK14 and Q20)achieved a modal base calling accuracy of 99.55%,whereas previous kit(LSK109)achieved slightly lower accuracy(99.1%).The direct genomic value accuracy from genotype-by-low pass sequencing ranged between 0.79 and 0.99,depending on the trait(milk,fat or protein yield),with a sequencing depth as low as 2×and using the latest chemistry(LSK114).Lower sequencing depth led to biased estimates,yet with high rank correlations.The LSK109 and Q20 achieved lower accuracies(0.57-0.93).More than one million high reliable methylated sites were obtained,even at low sequencing depth,located mainly in distal intergenic(87%)and promoter(5%)regions.Conclusions This study showed that the latest nanopore technology in useful in a LowPass sequencing framework to estimate direct genomic values with high reliability.It may provide advantages in populations with no available SNP chip,or when a large density of markers with a wide range of allele frequencies is needed.In addition,low pass sequencing provided nucleotide methylation status of>1 million nucleotides at≥10×,which is an added value for epigenetic studies.

Genetic susceptibility loci of lung cancer are associated with malignant risk of pulmonary nodules and improve malignancy diagnosis based on CEA levels

Objective:The heightened prevalence of pulmonary nodules(PN)has escalated its significance as a public health concern.While the precise identification of high-risk PN carriers for malignancy remains an ongoing challenge,genetic variants hold potentials as determinants of disease susceptibility that can aid in diagnosis.Yet,current understanding of the genetic loci associated with malignant PN(MPN)risk is limited.Methods:A frequency-matched case-control study was performed,comprising 247 MPN cases and 412 benign NP(BNP)controls.We genotyped 11 established susceptibility loci for lung cancer in a Chinese cohort.Loci associated with MPN risk were utilized to compute a polygenic risk score(PRS).This PRS was subsequently incorporated into the diagnostic evaluation of MPNs,with emphasis on serum tumor biomarkers.Results:Loci rs10429489G>A,rs17038564A>G,and rs12265047A>G were identified as being associated with an increased risk of MPNs.The PRS,formulated from the cumulative risk effects of these loci,correlated with the malignant risk of PNs in a dose-dependent fashion.A high PRS was found to amplify the MPN risk by 156%in comparison to a low PRS[odds ratio(OR)=2.56,95%confidence interval(95%CI),1.40−4.67].Notably,the PRS was observed to enhance the diagnostic accuracy of serum carcinoembryonic antigen(CEA)in distinguishing MPNs from BPNs,with diagnostic values rising from 0.716 to 0.861 across low-to high-PRS categories.Further bioinformatics investigations pinpointed rs10429489G>A as an expression quantitative trait locus.Conclusions:Loci rs10429489G>A,rs17038564A>G,and rs12265047A>G contribute to MPN risk and augment the diagnostic precision for MPNs based on serum CEA concentrations.

A novel multimodal prediction model based on DNA methylation biomarkers and low-dose computed tomography images for identifying early-stage lung cancer

Objective:DNA methylation alterations are early events in carcinogenesis and immune signalling in lung cancer.This study aimed to develop a model based on short stature homeobox 2 gene (SHOX2)/prostaglandin E receptor 4gene (PTGER4) DNA methylation in plasma,appearance subtype of pulmonary nodules (PNs) and low-dose computed tomography (LDCT) images to distinguish early-stage lung cancers.Methods:We developed a multimodal prediction model with a training set of 257 individuals.The performance of the multimodal prediction model was further validated in an independent validation set of 42 subjects.In addition,we explored the association between SHOX2/PTGER4 DNA methylation and driver gene mutations in lung cancer based on data from The Cancer Genome Atlas (TCGA) portal.Results:There were significant differences between the early-stage lung cancers and benign groups in the methylation levels.The area under a receiver operator characteristic curve (AUC) of SHOX2 in patients with solid nodules,mixed ground-glass opacity nodules and pure ground-glass opacity nodules were 0.693,0.497 and 0.864,respectively,while the AUCs of PTGER4 were 0.559,0.739 and 0.619,respectively.With the highest AUC of0.894,the novel multimodal prediction model outperformed the Mayo Clinic model (0.519) and LDCT-based deep learning model (0.842) in the independent validation set.Database analysis demonstrated that patients with SHOX2/PTGER4 DNA hypermethylation were enriched in TP53 mutations.Conclusions:The present multimodal prediction model could more efficiently distinguish early-stage lung cancer from benign PNs.A prognostic index based on DNA methylation and lung cancer driver gene alterations may separate the patients into groups with good or poor prognosis.

Construction and evaluation of a polygenic hazard score for prognostic assessment in localized gastric cancer

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.

Study on Inheritance Mechanism of Tomato Fruit Firmness

[Objective] This study aimed to investigate the inheritance mechanism of tomato fruit firmness.[Method] Two tomato cultivars significantly different in fruit firmness were selected for investigation of the inheritance mechanism of tomato fruit firmness using combination analysis of six generations （P1,P2,F1,F2,B1 and B2）.[Result] The results indicated that the heredity of tomato fruit firmness was consistent with the additive-dominant model controlled by one pair of major genes; the additive effect （d）,dominant effect （h） and degree of dominance （h/d） of major genes were 17.37,-7.96 and-0.46,respectively,showing positive additive effect and incompletely dominant-negative effect; the hereditability of major gene effect in B1,B2 and F2 generation was 88.59％,45.81％ and 85.62％,respectively.[Conclusion] The heredity of fruit firmness was controlled by one pair of major gene,showing significant additive effect and dominant effect.