Family-based Helicobacter pylori infection status and transmission pattern in central China,and its clinical implications for related disease prevention

BACKGROUND Helicobacter pylori(H.pylori)has characteristics of family cluster infection;however,its family-based infection status,related factors,and transmission pattern in central China,a high-risk area for H.pylori infection and gastric cancer,have not been evaluated.We investigated family-based H.pylori infection in healthy households to understand its infection status,related factors,and patterns of transmission for related disease prevention.AIM To investigate family-based H.pylori infection status,related factors,and patterns of transmission in healthy households for related disease prevention.METHODS Blood samples and survey questionnaires were collected from 282 families including 772 individuals.The recruited families were from 10 selected communities in the greater Zhengzhou area with different living standards,and the family members’general data,H.pylori infection status,related factors,and transmission pattern were analyzed.H.pylori infection was confirmed primarily by serum H.pylori antibody arrays;if patients previously underwent H.pylori eradication therapy,an additional 13C-urea breath test was performed to obtain their current infection status.Serum gastrin and pepsinogens(PGs)were also analyzed.RESULTS Among the 772 individuals examined,H.pylori infection rate was 54.27%.These infected individuals were from 246 families,accounting for 87.23%of all 282 families examined,and 34.55%of these families were infected by the same strains.In 27.24%of infected families,all members were infected,and 68.66%of them were infected with type I strains.Among the 244 families that included both husband and wife,spouse co-infection rate was 34.84%,and in only 17.21%of these spouses,none were infected.The infection rate increased with duration of marriage,but annual household income,history of smoking,history of alcohol consumption,dining location,presence of gastrointestinal symptoms,and family history of gastric disease or GC did not affect infection rates;however,individuals who had a higher education level showed lower infection rates.The levels of gastrin-17,PGI,and PGII were significantly higher,and PGI/II ratio was significantly lower in H.pylori-infected groups than in H.pylori-negative groups.CONCLUSION In our study sample from the general public of central China,H.pylori infection rate was 54.27%,but in 87.23%of healthy households,there was at least 1 H.pylori-infected person;in 27.24%of these infected families,all members were infected.Type I H.pylori was the dominant strain in this area.Individuals with a higher education level showed significantly lower infection rates;no other variables affected infection rates.

Population Genetics of SARS-CoV-2: Disentangling Effects of Sampling Bias and Infection Clusters

A novel RNA virus,the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),is responsible for the ongoing outbreak of coronavirus disease 2019(COVID-19).Population genetic analysis could be useful for investigating the origin and evolutionary dynamics of COVID-19.However,due to extensive sampling bias and existence of infection clusters during the epidemic spread,direct applications of existing approaches can lead to biased parameter estimations and data misinterpretation.In this study,we first present robust estimator for the time to the most recent common ancestor(TMRCA)and the mutation rate,and then apply the approach to analyze 12,909 genomic sequences of SARS-CoV-2.The mutation rate is inferred to be 8.69×10^(−4) per site per year with a 95%confidence interval(CI)of[8.61×10^(−4),8.77×10^(−4)],and the TMRCA of the samples inferred to be Nov 28,2019 with a 95%CI of[Oct 20,2019,Dec 9,2019].The results indicate that COVID-19 might originate earlier than and outside of Wuhan Seafood Market.We further demonstrate that genetic polymorphism patterns,including the enrichment of specific haplotypes and the temporal allele frequency trajectories generated from infection clusters,are similar to those caused by evolutionary forces such as natural selection.Our results show that population genetic methods need to be developed to efficiently detangle the effects of sampling bias and infection clusters to gain insights into the evolutionary mechanism of SARS-CoV-2.Software for implementing VirusMuT can be downloaded at https://bigd.big.ac.cn/biocode/tools/BT007081.