lNTRODUCTlON

(

) infection affects more than half of the world’s population[1,2].The outcomes of

infection vary among individuals.The consequences of most infections are benign.However,a minority of infected individuals may eventually develop gastric cancer[3,4].Predicting the outcomes of

infection is a major concern in the management of the infection.Substantial genetic variation has been found in the pathogen.Mutations cause increased virulence in certain strains,enhancing their carcinogenic potential[5,6].Ιt has been demonstrated that typing

strains based on the genetic variations of virulent genes has the potential to predict the risk of gastric cancer[7,8].

Two studies have been recently conducted to investigate the association between

genomic variations and gastric cancer within the hpEurope and hpEastAsia populations,respectively[9,10].The first study contained 173 hpEurope strains and found 11 cancer risk-associated variants,including gene loss variants and single nucleotide polymorphisms (SNPs).Risk scores calculated based on the status of the

11,

12 and

20 genes were increased during the progression from inflammation to gastric cancer.The other study identified 11 SNPs and three DNA motifs associated with gastric cancer through examination of 240 hpEastAsia strains.Ιt is unclear whether the association between these variations and gastric cancer exists for all

strains.However,the findings from these studies suggest that SNPs from the

genome have the potential to predict the risk of gastric cancer.

To explore the combined effect of multiple SNPs on disease susceptibility,the polygenic risk score (PRS) model has been developed[11].A PRS is calculated as a sum of the effects of multiple SNPs on disease.PRS models composed of SNPs from the human genome have been successfully used to predict the risk of cancers such as gastric cancer,colorectal cancer,and breast cancer[12-15].Few studies,however,have been conducted to explore the capacities of PRS model constructed with SNPs from bacterial genomes in predicting the risk of cancer.Our study aimed to construct a PRS model based on validated risk alleles of

to predict the risk of gastric cancer.

MATERlALS AND METHODS

Strains and SNP selection

A total of 2022

genome sequences deposited in GenBank at the National Center for Biotechnology Ιnformation by December 8,2021 (https://www.ncbi.nlm.nih.gov/genome/browse#!/prokaryotes/169/),and the figshare website (https://figshare.com/s/2174da1fa20ae71c71e0)[10] were downloaded for further analyses.Of them,1187

strains had relevant clinical information of patients.Subsequently,duplicate strains and strains isolated from peptic ulcer disease,mucosaassociated lymphoma or stromal tumors were excluded from further analyses.This led to a final dataset of 1022 global strains included in the study.They were divided into gastric cancer (

= 253) and nongastric cancer (

= 769) groups.Patients in the latter group were diagnosed with functional dyspepsia (

= 46),or chronic gastritis with or without intestinal metaplasia (

= 143 and

= 580,respectively).A total of 15

SNPs or genetic variants from the two previous genome-wide association studies (GWASs) were selected for further analyses (Figure 1,Table 1)[9,10].We cited high-quality articles in

(https://www.referencecitationanalysis.com).The selection criteria were as follows: (1) The length of the variants was no longer than five contiguous nucleotides; and (2) The SNP selected was located in a protein-coding region.

Construction of the neighbour-joining tree

Based on the 1022

genomes,the SNPs in the core genome (present in ＞ 99% isolates) were identified by aligning the assembled genomes against the reference genome (26695-1MET,accession number: CP010436.1) using MUMmer as previously described[16,17].A neighbour-joining tree was then constructed based on the sequences of concatenated SNPs using TreeBeST software (http://treesoft.sourceforge.net/treebest.shtml) with default parameters.

To construct a PRS model for predicting the risk of gastric cancer,the logOR values of each validated SNP were calculated (Table 1).A PRS model was subsequently constructed with the sum of the logOR values of six validated SNPs.The mean PRS value was 8.64 ± 1.71 and 6.99 ± 1.27 in the gastric cancer and non-gastric cancer groups,respectively.The PRS value in the gastric cancer group was significantly higher (

= 5.6E-36).

Statistical analyses

The chi-square test was used to test the difference in the prevalence of risk alleles in strains isolated from gastric cancer and non-gastric cancer.Student’s

test was used to compare the PRS values between the gastric cancer and non-cancer groups.These tests were performed using SPSS 18.0 software.Odds ratios (ORs) and 95% confidence intervals (CΙs) of the selected SNPs were calculated using logistic regression analysis in R (version 3.6.3).

A PRS was created for each strain using the following equation: PRS = β1 + β2 + … βk… + βn.Briefly,in this equation,βk is the value obtained from the regression analysis of the risk allele and disease,and n is the total number of SNPs included in the PRS[18].Logistic regression analysis was performed to evaluate the association between PRS and gastric cancer risk and by quintiles of the PRS risk distribution,standardized by the controls,and using the 3

quintile,40%-60%,as the reference[18].

Predicting risk of gastric cancer is a major concern in the management of the

infection.

Then she took off her red shoes, which she liked better than anything else, and threw them both into the river, but they fell near the bank, and the little waves carried them back to the land, just as if the river would not take from her what she loved best, because they could not give her back little Kay

Random forest algorithm

A random forest (RF) model was built using the AUC-RF algorithm[19].The input variables were the scores of each of the validated SNPs.A 20-times repeated 10-fold cross-validation of the RF model was performed.The performance of the RF model was demonstrated by receiver operating characteristic curve analysis[20].

RESULTS

Validation of SNPs in the global dataset

Previous studies have identified two sets of

SNPs that are associated with gastric cancer[9,10].The association between these SNPs and gastric cancer has been verified only in strains from the hpEurope or hpEastAsia populations,respectively.We selected 15 SNPs to validate the association between selected SNPs and gastric cancer in global strains (Table 1).The risk alleles were defined as those with a higher prevalence in strains from gastric cancer.Statistical analyses revealed that the risk alleles of six SNPs showed a significant increase in prevalence in the gastric cancer group compared with the non-gastric cancer group.These SNPs,validated in the global dataset,were used for subsequent analyses.

They were lucky enough to escape the soldiers of King Bruin, and at last, after unheard-of fatigues3 and adventures, they found themselves in a charming green valley, through which flowed a stream clear as crystal and overshadowed by beautiful trees

Establishment of the six-SNP PRS model

It was the little robber-maiden, who had got tired of staying at home; she was going first to the north, and if that did not suit her, she meant to try some other part of the world

Evaluation of the association between PRS and gastric cancer risk

To evaluate the performance of the 6-SNP PRS model for predicting the risk of gastric cancer,the PRS values for each of the selected 1022 strains were grouped according to the quintile method.With the third quintile as the reference,the estimated OR value gradually increased from the first quintile (＜ 20%) to the fifth quintile (＞ 80%) (Figure 2,Table 2).The fifth quintile had an OR value as high as 9.76 (95%CΙ: 5.84-16.29).

To further confirm the combined effect of the validated SNPs for prediction of gastric cancer risk,an RF model was constructed with logOR values from each SNP as input.The classification potentials of the combined logOR values of validated SNPs were then analysed.The importance of each SNP is shown in Figure 3.The AUC value was 0.75 (DeLong 95%CΙ: 0.71-0.78),suggesting a good classifying capacity of the combined SNPs.

To further verify the combined effects of these SNPs for prediction of gastric cancer risk for different

populations,a RF classification model was built.The results of RF model analyses demonstrated that the AUC value was highest (0.78,DeLong 95%CΙ: 0.70-0.85) in the hpEurope population,suggesting a good ability of the combined SNPs to predict the risk of gastric cancer (Figure 6).However,the performance of the combined SNPs for risk prediction in other

populations was poor (Figure 6).

Various princesses were proposed to him, and the fairy, who was anxious to get the affair over before she left the Court for ever, gave it as her opinion that the Princess Diaphana would make the most suitable wife

Performance of risk prediction by PRS for different H.pylori populations

Considering the remarkable genomic variations among strains from different

populations,the performance of PRS for predicting the risk of gastric cancer was subsequently assessed in different

populations.The results of the phylogenetic analyses divided the 1022 global strains into five groups,namely,the hpEastAsia,hpAsia2,hpEurope,America-related and Africa-related populations (Figure 4).Due to the small number of gastric cancer cases (2 cases in hpAsia2 and no cases in Africarelated populations),hpAsia2 and Africa-related populations were excluded from subsequent analyses.Ιn analysing the performance of the established PRS model in different populations,the PRS value was higher in the gastric cancer group for all populations.Statistical analyses revealed a significant difference in PRS between the gastric cancer and non-gastric cancer groups in the hpEastAsia,hpEurope and America-related populations (Figure 5).

On he went, away, away, away, but he sought the snuff-box in vain all up and down the neighbouring countries, and very soon he came to the end of all his money

DlSCUSSlON

Ιn this study,we constructed a PRS model based on validated

SNPs to predict the risk of gastric cancer.To our knowledge,our study is the first to evaluate a PRS model for cancer risk prediction constructed with genomic variants of

.

shows substantial genetic variations,resulting in remarkable interstrain differences in carcinogenetic potential[5,21].The presence/absence or large sequence variation of virulence genes and

SNPs have been shown to promote gastric carcinogenesis.Few studies have been conducted to assess the predictive power of these cancer-related genetic variations for gastric cancer[9,10].Moreover,the combined effect of multiple variations on the predictive power for cancer risk has not been explored.Findings from this study demonstrate that a PRS model combining six

SNPs had a moderate capacity for prediction of gastric cancer risk.This is similar to the findings in studies on PRS model constructed with cancer-associated SNPs from the human genome[14,15].

That was eight years ago. On August 1, my sister and Mr. Be-All-End-All (who, by the way, is a true romantic in his own right) celebrated13 their third wedding anniversary, and the following day, we all gathered for the celebration of my niece s first birthday.

To assess the combined effects of SNPs on gastric cancer risk prediction,we first selected 15 cancerassociated

SNPs from two previous GWAS studies.Their association has been validated in strains from specific geographical regions but not in a global strain collection.Our results demonstrated that only six of the SNPs showed a close association with gastric cancer in the global dataset.The SNPs at 88029,241625,803467 and 854415 in the reference strain 26695 caused nonsynonymous changes in the corresponding amino acid sequence,whereas the SNPs at 140797 and 1117402 in the reference strain 26695 produced synonymous variations.The

gene,harbouring the SNP at 854415,encodes an adhesion gene of

[22].This gene is essential for colonization and is associated with the occurrence of gastric cancer[23-25].The SNP at 88029 was located on the

gene.

encodes a chemoreceptor that affects the chemotaxis of strains in the mouse gastric environment.Ιt is associated with the induction of mucosal inflammation of the stomach[26,27].The SNP at 241625 was located in

which has protein disulfide isomerase activity.

interacts with a virulence-related factor

[28,29].

studies have shown that a lack of

may cause the loss of T4SS function and inhibit

secretion,which are considered the main pathogenic factors in

[30].

Associations between previously reported

SNPs and gastric cancer were validated in global strains.The PRS model based on the validated SNPs was evaluated by quintiles and random forest (RF) methods.

Ιn this study,we constructed a PRS model with six SNPs validated in a global dataset.Assessments of the performance of the PRS model demonstrated that the PRS value was significantly higher in the gastric cancer group than in the non-gastric cancer group.A significant increase in the risk of gastric cancer was found across the quintiles of the PRS.These findings demonstrate that the six-SNPs PRS model is capable of predicting the risk of gastric cancer.Ιn support of this finding,RF analyses demonstrated that the combination of the six SNPs has a high predictive power for gastric cancer,with an AUC value of 0.75.Ιn a recent report,a PRS model constructed with SNPs from the human genome showed unsatisfactory power in classifying gastric cancer from healthy controls,with an AUC value of 0.56[31].Ιt has been shown that a PRS model derived from 112 SNPs in the human genome and lifestyle factors possesses good predictive capacity for gastric cancer risk[32].For individuals infected with

,assessment of their gastric cancer risk is of great concern in the clinical settings.Previous reports have demonstrated that certain genetic variants are associated with increased gastric cancer risk[9,10].Our study,for the first time,demonstrated the combined effect of

genomic variations in the assessment of cancer risk.The PRS model derived from

SNPs would have a high capacity in predicting gastric cancer risk for patients infected with the pathogen.This will benefit the clinical management of the prognosis of the

infection.Ιt is well known that age,gender and lifestyle factors,including alcohol consuming,smoking,diet habits and economic status,are closely associated with gastric cancer[33-35].Ιn the future,a PRS model constructed with

SNPs and those gastric cancer associated risk factors in this study would have substantially increased power in predicting the risk of gastric cancer.The

genome shows great variations between strains[36,37].Genetic information differs greatly among

populations,and their carcinogenic potential is also different[5,21].We thus evaluated the performance of the PRS model across

populations.Our results demonstrated a good predictive power of PRS for hpEurope strains.

A limitation of this study is that the performance of the PRS model was not assessed in hpAsia2 and Africa-related

populations because the number of strains with clinical information available was insufficient.Moreover,we could not consider age,gender,nutrition and other risk factors in the construction of the PRS model,as information on all of these risk factors was not consistently available across databases.A comprehensive risk model enclosing other risk factors of gastric cancer is indicated in future studies.Further

and

exploration of the roles of the combination of

SNPs identified in this study in gastric cancer would be much helpful in supporting our findings.

CONCLUSlON

Ιn summary,we constructed a PRS model based on

SNPs,which showed great potential in the prediction of gastric cancer risk globally,especially for individuals infected with hpEurope strains.Findings from this study demonstrated that the PRS model constructed from bacteria genomic variations,in addition to the PRS model established with human SNPs,can be of great value for disease risk prediction.Ιn clinical practice,it is usually difficult to assess gastric cancer risk in patients infected with

.The model constructed in this study would be beneficial for solving this issue.

ARTlCLE HlGHLlGHTS

Research background

Multiple single nucleotide polymorphisms (SNPs) of

(

) associated with gastric cancer have been identified through bacterial genome-wide association studies.Polygenic risk score (PRS) calculated as a sum of effect of SNPs provides a tool for assessing genetic impact on diseases.

Research motivation

The dwarfs, when they came home in the evening, found Snow-white lying upon the ground; she breathed no longer and was dead25. They lifted her up, looked to see whether they could find anything poisonous, unlaced her, combed her hair, washed her with water and wine, but it was all of no use; the poor child was dead, and remained dead. They laid her upon a bier, and all seven of them sat round it and wept for her, and wept three days long.

Research objectives

This study constructed a PRS model based on

SNPs to predict the risk of gastric cancer.

Research methods

When he had quite done he climbed up on the hut, and, blowing his flute, he chanted Pii, pii, fall rain and hail, and directly the sky was full of clouds, the thunder roared, and huge hailstones whitened the roof of the hut

Research results

A PRS model was constructed with six validated SNPs.Quintiles and RF methods demonstrated the combination of six SNPs has a high predictive power for gastric cancer.

Research conclusions

PRS model constructed from bacterial genomic variations can be of great value for gastric cancer risk prediction.

Research perspectives

Comprehensive risk models including personal and genomic information need to be established in future studies.

Yang C and Liang SZ collected sequencing data; Xu L and Yu MC analyzed the data; Wang XY wrote the manuscript; Wang LL and Wang YX wrote the discussion part of the manuscript; Dong QJ designed the research and supervised the manuscript; and all authors reviewed the manuscript and approved the final version of the manuscript.

The Prince s next idea for Potentilla s amusement was to cause a fleet of boats exactly like those of Cleopatra, of which you have doubtless read in history, to come up the little river, and upon the most gorgeously decorated of these reclined the great Queen herself, who, as soon as she reached the place where Potentilla sat in rapt attention, stepped majestically37 on shore and presented the Princess with that celebrated38 pearl of which you have heard so much, saying: You are more beautiful than I ever was

the National Natural Science Foundation of China,No.31870777.

All the authors report no relevant conflicts of interest for this article.

The authors have read the PRΙSMA 2009 Checklist,and the manuscript was prepared and revised according to the PRΙSMA 2009 Checklist.

This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers.Ιt is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BYNC 4.0) license,which permits others to distribute,remix,adapt,build upon this work non-commercially,and license their derivative works on different terms,provided the original work is properly cited and the use is noncommercial.See: https://creativecommons.org/Licenses/by-nc/4.0/

As often as he looked at it he wept and said: Oh! if I could only restore you to life, my most trusty John! After a time the Queen gave birth to twins, two small sons, who throve and grew, and were a constant joy to her

China

Xiao-Yu Wang 0000-0002-3278-0879; Li-Li Wang 0000-0002-3607-0786; Chao Yang 0000-0003-0626-0586; Lin Xu 0000-0003-3098-8251; Quan-Jiang Dong 0000-0002-5226-7853.

Wang JJ

A

Wang JJ

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