The association between different metabolic phenotypes of childhood obesity and cardiometabolic outcomes in adulthood is inconsistent. We conducted a systematic review and meta-analysis to synthesize the evidence on the association between childhood obesity phenotypes including metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) and cardiometabolic outcomes in adulthood. Four cohort studies with 8446 participants were included in this review. A meta-analysis of three studies with 7270 participants shows that children in the MHO (pooled RR, 2.72, 95% CI, 1.14-6.48) and MUO (pooled RR, 3.94, 95% CI, 2.77-5.60) groups had a higher risk of diabetes compared with the metabolically healthy normal weight (MHNW) phenotype. Similarly, in a meta-analysis of two studies with 3772 participants, the children with MHO (pooled RR, 2.50, 95% CI, 1.62-3.84) and MUO (pooled RR, 3.33, 95% CI, 2.38-4.67) had a higher risk of metabolic syndrome. After adjustment for adult BMI, the risk of diabetes and metabolic syndrome in the MHO phenotype was substantially reduced, while the risk in MUO decreased somewhat but was still significant. Additionally, the mean carotid intimal thickness of MHO (pooled mean difference, 0.02, 95% CI, -0.01 to 0.05) and MUO (pooled mean difference, 0.05; 95% CI, -0.01 to 0.11) was greater than that of MHNW, in the meta-analysis of three studies with 3924 participants. These findings suggest that weight loss from childhood into adulthood remains a critical strategy to mitigate these long-term health risks. Additionally, regular monitoring of cardiovascular metabolic indicators and timely intervention are essential for children with MUO. Given the few studies conducted on this important topic, further research with large sample sizes is needed to confirm our findings.

Microbiota may be associated with esophageal squamous cell carcinoma (ESCC) development. However, it is not known the predictive value of microbial biomarkers combining epidemiological factors for the early detection of ESCC and precancerous lesions. A total of 449 specimens (esophageal swabs and saliva) were collected from 349 participants with different esophageal statuses in China to explore and validate ESCC-associated microbial biomarkers from genes level to species level by 16S rRNA sequencing, metagenomic sequencing and real-time quantitative polymerase chain reaction. A bacterial biomarker panel including Actinomyces graevenitzii (A.g_1, A.g_2, A.g_3, A.g_4), Fusobacteria nucleatum (F.n_1, F.n_2, F.n_3), Haemophilus haemolyticus (H.h_1), Porphyromonas gingivalis (P.g_1, P.g_2, P.g_3) and Streptococcus australis (S.a_1) was explored by metagenomic sequencing to early detect the participants in Need group (low-grade intraepithelial neoplasia, high-grade intraepithelial neoplasia and ESCC) vs participants without these lesions as the Noneed group. Significant quantitative differences existed for each microbial target in which the detection efficiency rate was higher in saliva than esophageal swab. In saliva, the area under the curve (AUC) based on the microbial biomarkers (A.g_4 ∩ P.g_3 ∩ H.h_1 ∩ S.a_1 ∩ F.n_2) was 0.722 (95

To the Editor: Esophageal cancer (EC) ranks ninth and fifth among the leading cause of global cancer-related morbidity and mortality, respectively.[1] Esophageal squamous cell carcinoma (ESCC) is the predominant histologic subtype of EC in China. Population screening effectively decreases the morbidity and mortality of ESCC, highlighting the necessity of early detection and early diagnosis.[2] However, it is hard to generalize the endoscopy screening from high-risk populations in high-risk areas to the natural populations in larger areas. With the development of high-throughput sequencing technologies, the microbiota is an emerging field to provide new clues about the primary screening of ESCC. Consequently, this study summarized indicative genera associated with ESCC progression in paired esophageal biopsy and swab specimens, and developed risk stratification models of high-risk populations based on microbial factors, epidemiological factors, and actual detection requirements. Based on the national EC screening project in China, 234 participants from Linzhou (Henan province), including 70 healthy participants, 69 participants with esophagitis, 70 participants with low-grade intraepithelial neoplasia (LGIN), 18 participants with high-grade intraepithelial neoplasia (HGIN), and seven participants with ESCC were enrolled in the present study. Trained epidemiological investigators collected their baseline information such as dietary habits, lifestyle, and oral health. All participants were informed and signed informed consent. This study was approved by the Institutional Review Board of the Cancer Hospital of the Chinese Academy of Medical Sciences. (No. 19/176-1960) Paired esophageal swab and biopsy specimens were collected from each participant. Swab specimens were collected using a sterile brush (Puritan, sterile polyester tipped applicators). If there was a lesion, five loops were taken at the lesion or else at the middle esophagus. The brush head was cut into a sterile tube containing 1.5 mL of cell-preserving fluid (Hologic, ThinPrep, PreservCyt Solution, San Diego, USA). The biopsy specimens at the brushing site were macro-dissected with sterile forceps and placed into a sterile tube. All specimens were stored at -80 °C immediately after sampling and transported to the laboratory on dry ice. Bacterial DNA was extracted using PowerSoil DNA Isolation Kit (12888100, Qiagen, Dusseldorf, Germany) and stored in Tris-Ethylene diamine tetra acetic acid buffer solution at -80 °C before other processes. The V4 region of the 16S ribosomal RNA (rRNA) gene was amplified using the universal bacterial primer (515F:5΄- GT GYCAG-CMGCCGCGGTAA-3΄ and 806R:5΄- GGACTACNVGG-GTWTCTAAT-3΄). Polymerase chain reaction (PCR) mixtures contained 1 μL of forward and reverse primer (10 μmol/L), 1 μL of template DNA, 4 μL of deoxy-ribonucleoside triphosphate (dNTPs) (2.5 mmol/L), 5 μL of 10×EasyPfu buffer, 1 μL of EasyPfu DNA polymerase (2.5 U/μL), and 1 μL of double-distilled water in 50 μL total reaction volume. The PCR thermal cycling involved steps as follows: denaturation at 95°C for 5 min, 30 cycles of denaturation at 94°C for 30 s, annealing at 60°C for 30 s, extension at 72°C for 40 s, and a final extension step at 72°C for 4 min. Amplicons were quantified using a Qubit dsDNA HS assay Kit (Thermo Fisher Scientific/Invitrogen catalog No.Q32854, Waltham, USA). Then, the amplicon libraries were pooled at an equal mass of 100 ng per sample and were sequenced on the Illumina MiniSeq platform (Illumina, San Diego, USA). Raw sequences were performed for quality control and to feature table construction using the DADA2 algorithm. Subsequent analyses were based on quantitative insights into microbial ecology (QIIME2; https://view.qiime2.org). Taxonomic assignment was determined using a pre-trained Naive Bayes classifier via the q2-feature-classifier plugin. To avoid sampling depth bias, 1000 reads were randomly selected from each sample to calculate the relative abundance of taxa. To meet the inclusion criteria, the indicative genus had to either demonstrate a statistical difference "between" or "among" normal and esophagitis, LGIN, HGIN, and/or ESCC groups. Four detection requirements were included in this study based on their capacity to distinguish: (A) normal, esophagitis, LGIN, HGIN, and ESCC; (B) normal, esophagitis, LGIN, and HGIN and above (including HGIN and ESCC); (C) normal/esophagitis, LGIN, and HGIN and above groups; (D) between normal/esophagitis and LGIN and above (including LGIN, HGIN, and ESCC) groups. The chi-squared test or Fisher's exact test was used to compare participants' data. We calculated the average relative abundance (ARA%) for each genus in each participant group. Based on the slope in the linear regression equation, we divided genera into increasing group (slope was greater than zero) and decreasing group (slope was less than zero) respectively. The tendency changed from normal, esophagitis, LGIN, and HGIN to ESCC. Then, we compared the ARA% between normal and other groups using the Wilcoxon test and among five individual groups using the Kruskal–Wallis test within and between biopsy and swab specimens, respectively. Multiple testing with the Bonferroni correction was also performed. Finally, we developed risk stratification models of ESCC and precancerous lesions based on multinomial logistic regression and plotted the receiver operator characteristic (ROC) curve with the area under the curve (AUC). Ten-fold cross-validation was used as an internal validation method and the normalized mean square error (NMSE) was calculated. All statistical analyses were performed in R studio (version 1.1.456). Statistical significance was set at P < 0.05. According to the results of the present study, significant differences were observed in age, education level, oral health (gingival bleeding), and dietary habits (drinking water, meat, fried food and scallion, ginger, or garlic) among the normal, esophagitis, LGIN, HGIN, and ESCC groups. In the esophagitis group and above, most participants were over 55 years old (P <0.05). All healthy participants or those with esophagitis never or seldom ate fried food (P <0.05). Alpha diversity of the esophageal microbiota was statistically influenced by education level, numbers of relatives with cancer, tooth loss, gingival bleeding, drinking water, vegetable, spicy food, and salty-tasting food. In the biopsy specimens, 37 indicative genera associated with ESCC progression were identified. The ARA% of Fusobacterium and Bergeyella were significantly different among the participant groups and were significantly higher in the ESCC group than in the normal group. As for precancerous lesions, Neisseria and Oribacterium were significantly different between the precancerous group (LGIN and HGIN group, respectively) and the normal group. Sphingomonas was the only genus with significant differences between the normal and other groups, and among the five groups. In swab specimens, there were more indicative genera (16 genera) with an increasing tendency from normal, esophagitis, LGIN, HGIN to ESCC than esophageal biopsy (11 genera). In addition to significance among five groups, Capnocytophaga, Aggregatibacter, Bergeyella, Streptococcus, and Megasphaera were statistically different between the normal and ESCC group, Fretibacterium, Filifactor, and Solobacterium were notable between the normal and LGIN and above. The multiple testing results suggested that the ARA% of Bergeyella was statistically higher in the ESCC group than in the normal group based on both swab (P <0.01) and biopsy (P <0.05) specimens. Ralstonia was dominant in the normal group. Fourteen identical and indicative genera (including unidentified genera) were observed between biopsy and swab specimens revealing that the ARA% of Haemophilus, Neisseria, Fusobacterium, Aggregatibacter, Bergeyella, and Alysiella increased from normal, esophagitis, LGIN, HGIN to ESCC. In contrast, the ARA% of Streptococcus, Actinomyces, Rikenellaceae RC9 gut group, Oribacterium, Filifactor, and Novosphingobium decreased from normal, esophagitis, LGIN, HGIN to ESCC. Among them, Neisseria, Rikenellaceae RC9 gut group, Oribacterium, Novosphingobium, and Alysiella were significantly different between the esophageal biopsy and swab specimens in at least one participant group. At the beginning of the risk stratification model, we used normal, esophagitis, LGIN, HGIN, and ESCC groups as the dependent variables. Based on the classification of the five groups, the accuracy of the model enrolling seven significant epidemiological factors among normal, esophagitis, LGIN, HGIN, and ESCC groups was 54.26%, which was higher than that of the model (37.23%) enrolling eight significant epidemiological factors relevant to alpha diversity. Regarding microbial factors, eight indicative genera were enrolled in the risk stratification model of the five groups with an accuracy of 41.49%. The accuracy of each model when each indicative genus was combined with seven significant epidemiological factors among five groups was: Filifactor (60.64%), Haemophilus (58.52%), Bergeyella (58.52%), Fusobacterium (58.52%), Streptococcus (58.52%), Actinomyces (57.45%), Selenomonas (56.38%), and Aggregatibacter (54.26%). Based on the results, we flexibly combined the above eight indicative genera and seven significant epidemiological factors with four detection requirements to develop risk stratification models [Supplementary Table 1, https://links.lww.com/CM9/B265]. Comparatively better models for each detection requirement (Supplementary Table 1, https://links.lww.com/CM9/B265) were model_1 (Group A: normal, esophagitis, LGIN, HGIN, and ESCC), model_6 (Group B: normal, esophagitis, LGIN, and HGIN and above), model_7 (Group C: normal/esophagitis, LGIN, and HGIN and above), and model_12 (Group D: normal/esophagitis and LGIN and above). We optimized the model by including two non-significant but clinically epidemiological factors (tooth loss and number of relatives with cancer). By adding tooth loss, the accuracies of model_1, model_6, and model_7 were higher than those of the no-tooth loss enrolled in the risk stratification models [Supplementary Table 1, https://links.lww.com/CM9/B265]. Consequently, the highest accuracy of the risk stratification models for each detection requirement were 68.09% (model_1-adding tooth loss, AUC = 0.87), 68.09% (model_6-adding tooth loss, AUC = 0.84), 73.40% (model_7-adding tooth loss, AUC = 0.88), and 84.04% (model_12-adding tooth loss, AUC = 0.90). Subsequently, we utilized a 10-fold cross-validation as an internal validation method for the four models, and the NMSE values were 0.77 (model_1-adding tooth loss), 0.89 (model_6-adding tooth loss), 0.83 (model_7-adding tooth loss) and 0.92 (model_12-adding tooth loss). Previous studies have revealed that different genera were associated with ESCC.[3] Additionally, epidemiological evidence has indicated that poor oral health is a crucial factor associated with microbiota and ESCC progression,[4] providing clues for early detection via oral specimens combined with poor oral health. Tooth loss and periodontal disease are associated with poor oral health, with tooth loss being a quantitative factor and an easier quality to control in practice.[5] In this study, we also simulated various detection requirements during primary screening for ESCC by developing risk stratification models. "Group A" was the ideal model, although it was limited by the unbalanced sample size. The screening project for ESCC in China revealed that individuals with LGIN or HGIN and above required follow-up and treatment, respectively, which explains the rationality of "Group D". More flexibly, the present study presented "Group B" and "Group C" as compromise methods to meet actual screening costs, medical personnel, and medical equipment. Furthermore, identifying an easily collected microbial specimen for early ESCC detection based on microbial and epidemiological factors was necessary. Dong et al[6] discussed the microbial characteristics associated with esophageal and oral specimens. Microbial studies on dental plaque and saliva have indicated that oral infectious bacteria in oral specimens are associated with EC. Therefore, oral specimens may be preferable alternatives. However, further studies using large sample sizes and participants from multiple centers are required for optimizing and improving the current findings. Overall, this exploratory study has some limitations. First, this study was a natural population-based study based on a national screening project in China. The detection rate of esophagitis, LGIN, HGIN, and ESCC decreased in the natural population,[7] leading to unbalanced but reasonable sample size for each participant group. Second, all participants were from the same county and had a similar lifestyle. Third, data for oral and esophageal specimens obtained from the same participants could not be validated without collecting the oral specimen. In conclusion, the vast human microbiota resources could aid in understanding their role in human health and disease, elucidate the disease etiology, and further explore relevant microbial biomarkers. This exploratory study indicated that it is feasible to combine microbial factors and epidemiological factors to differentiate ESCC and precancerous lesions from normal and esophagitis. However, collecting esophageal specimens is challenging. Therefore, an in-depth understanding of the microbial signatures and correlation between the oral cavity and esophagus is required, as oral specimens are much easier to obtain. The primary screening of ESCC and precancerous lesions using microbial biomarkers should be further promoted. Funding This study was supported by grants from the National Natural Science Foundation of China (No.81974493), the National Science & Technology Fundamental Resources Investigation Program of China (No. 2019FY101101), and the National Key Research and Development Program of Precision Medicine (No. 2016YFC091404). Conflicts of interest None.

To the Editor: In this study, we observed the long-term effect of caesarean section (CS) on the gut microbiome of pre-school age children, both on the microbial taxonomical profile and metabolic function. Interestingly, taxonomical differences due to CS were mostly found in children of younger age, but the microbial functional alterations were observed in children of older age. Gut microbiome is constantly evolving and adapting to the surrounding environments, especially during the early months of life when the microbial composition is undergoing turbulent changes.1 The gut microbiome of children tends to stabilise after 3 years of age,2 but continues to mature slowly thereafter.3 To date, only limited studies3, 4 have investigated the effect of CS on gut microbial profile of children beyond infancy (up to 12 months). These studies employed fluorescence in situ4 or 16S rRNA3 for microbial analysis, which were insufficient to explore microbial functions. We conducted this study with metagenomic sequencing method to examine the effect of CS on the gut microbiome of children of pre-school age. Between March and April 2017, 2199 children were recruited from 16 public kindergartens in Guangzhou, China. Faecal samples were collected and randomly selected (n = 1104) for gut microbial analysis. Among these children, 1034 with valid data regarding their parental, perinatal and birth characteristics derived from parent-administered questionnaires were included in this analysis. All participants provided written consents, and this study was approved by Guangzhou Women and Children's Medical Center ethic committee. Detailed methodologies regarding the study design, microbial analysis for faecal samples and statistical analysis are available in Supporting Information. Forty-three percent of the participants were delivered via CS (Table 1). CS-born children had higher weight Z-score at birth (.30 vs. .07, p < .001) than those delivered vaginally. Mothers who gave birth via CS were significantly elder at sampling (33 vs. 32 years, p < .001), had higher pre-pregnancy body mass index (BMI) (p < .001) than those who underwent vaginal delivery. Overall, for the entire population, the top five most abundant microbial phylum were Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria and Verrucomicrobia (Figure 1A), together representing nearly 96% of the total microbial composition. CS-born children scored significantly lower for richness (p = .019, FDR p = .076, FDR p = .110 for adjustment by age and sex; Figure 1B), but were similar to that of those born vaginally regarding other indices. The microbial beta-diversity of children born via different modes was significantly different after adjustment for age and sex (Figure 1C, Bray–Curtis p = .001, Jaccard p = .002). Significant enrichment of Clostridium spp. was observed in children born via CS as compared to those born vaginally (Figure 1E), and many of these are classified as opportunistic pathogens. Clostridium bolteae were found to be enriched in children of autism spectrum disorder (ASD) than in children without it.4 Clostridium ramosum enhances lipids uptake and hence promotes obesity as demonstrated in the in vitro study.6 In addition, several gene segments of C. bolteae, Clostridium clostridioforme and C. ramosum have been related to the antimicrobial resistance in various cultures.7 Altogether, these strains might possess adverse health implications on the host. Stratification by age groups revealed that the microbial beta-diversity was significantly different between children born via different modes of delivery in those of younger age only (p = .037 for age under 5, p = .012 for age 5, p = .744 for age above 5), although no differences for alpha-diversity in all age groups (Figure S1). Differences in microbial profile were mainly found at or below 5 years (age ranges were ≥60 and <72 months, <60 months, respectively; Figure S2). Notably, 51 downregulated pathways, mostly related to vitamin metabolism (35%), were found in CS born children aged above 5 (≥72 months), when compared to their vaginally born counterparts (Figure 2E,F; Table S1). It is possible that the children are exposed to more complexed environmental factors and food system over time, which then replaced mode of delivery and became the key determinants of microbial composition.2, 3 Previous meta-transcriptomic analysis has shown that the ability of gut microbiome to produce K and B group vitamins are at comparable levels across healthy population,8 and these microbiome-derived vitamins collectively contribute to 30% of our dietary requirement, lack of which might have adverse health consequences on the host. It is known that breastfeeding experience shapes the trajectory of gut microbial development,9 whether breast milk (BM) could ameliorate the adverse effect of CS on childhood gut microbiota is therefore of interest to explore. Over 60% CS-delivered children were fed on a predominantly BM diet within their first 6 months of life (Table S2). Infant formula (IF)-fed CS-born children scored lowest for gut microbial richness, as compared to either vaginally born or BM-fed CS-born children, although no other alpha-diversity indices were different (Table S3). On the whole population level, it seems that BM feeding ameliorated CS-induced changes in gut microbial metabolic functions. However, when breakdown by age groups (Tables S4–S6), for children born via same delivery mode, only minor differences in the gut microbial profile and metabolic activities were found to be due to early feeding practices. Our previous finding was largely driven by the younger age group, in whom the effect of BM is likely to be more substantial.9 This is the first study to examine the effect of CS on the gut microbiome of children at pre-school age using metagenomic sequencing. Recall bias was unavoidable due to information collected through questionnaire in a retrospective manner. In addition, information regarding medical history, the use of antibiotics and diet were not collected in this trial, both of which could substantially affect the gut microbiome of children. It must be acknowledged that our samples were derived from a single time point, limiting interpretation of changes or trajectory of gut microbiome of children over time. In addition, our interpretation regarding altered metabolic functions was based on metagenomic sequencing results only. Further study should combine the use of meta-transcriptomic data to confirm these observations. In conclusion, we found that CS-induced microbial change in pre-school age children is featured by enrichment of Clostridium spp. The altered microbial metabolic functions in older children are mostly related to vitamin metabolism, consequences of which remain to be explored. We would like to thank all families that have participated in this study, and the coordinating staff members on the grounds. We would also like to acknowledge BGI Shenzhen that has performed the microbial analysis work on our behalf. We are grateful to Prof. Jing-Yuan Fu and Dr. Hong-Wei Wang for their valuable feedbacks on our manuscript. The authors declare they have no conflicts of interest. Key Program of GuangDong Basic and Applied Basic Research Foundation, Grant Number: 2022B1515120080, 2020B1111170001; China Postdoctoral Science Foundation, Grant Number: 2022M710883; National Natural Science Foundation of China, Grant Number: 82173525, 82003471; GuangDong Basic and Applied Basic Research Foundation, Grant Number: 2021A1515110194; Guangzhou Science and Technology Project, Grant Number: 202201020656. The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Background: Previous studies suggested associations between the oral microbiome and lung cancer, but studies were predominantly cross-sectional and underpowered. Methods: Using a case-cohort design, 1306 incident lung cancer cases were identified in the Agricultural Health Study; National Institutes of Health-AARP Diet and Health Study; and Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Referent subcohorts were randomly selected by strata of age, sex, and smoking history. DNA was extracted from oral wash specimens using the DSP DNA Virus Pathogen kit, the 16S rRNA gene V4 region was amplified and sequenced, and bioinforrnatics were conducted using QIIME 2. Hazard ratios and 95% confidence intervals were calculated using weighted Cox proportional hazards models. Results: Higher alpha diversity was associated with lower lung cancer risk (Shannon index hazard ratio = 0.90, 95% confidence interval = 0.84 to 0.96). Specific principal component vectors of the microbial communities were also statistically significantly associated with lung cancer risk. After multiple testing adjustment, greater relative abundance of 3 genera and presence of 1 genus were associated with greater lung cancer risk, whereas presence of 3 genera were associated with lower risk. For example, every SD increase in Streptococcus abundance was associated with 1.14 times the risk of lung cancer (95% confidence interval = 1.06 to 1.22). Associations were strongest among squamous cell carcinoma cases and former smokers. Conclusions: Multiple oral microbial measures were prospectively associated with lung cancer risk in 3 US cohort studies, with associations varying by smoking history and histologic subtype. The oral microbiome may offer new opportunities for lung cancer prevention.

A recent study reported that the prevalence of high-risk human papillomavirus (hrHPV) decreased with age from 20 to 40 years old, then increased until 64 years old, and thereafter decreased from 65 years old among women who attended an health check-up in clinics in China. 1 Previous studies have demonstrated age-specific prevalence of HPV infection in different continents.2 There is considerable heterogeneity in the hrHPV prevalence across regions with different economic development. Due to limited resources in developing areas, screening priorities should be given to women at high risk of HPV infection.

Upper gastrointestinal (UGI) tract cancer is one of the most common cancers worldwide, while limited attention has been paid to the UGI microbiota. Microbial biomarkers, such as Fusobacteria nucleatum and Helicobacter pylori, bring new ideas for early detection of UGI tract cancer, which may be a highly feasible method to reduce its disease burden. The objective of this study was to describe and compare the dynamic microbiota characteristics in the gastrointestinal (GI) tract in Chinese participants via high-throughput sequencing techniques. The study collected saliva, esophageal swab, cardia biopsy, noncardia biopsy, gastric juice, and fecal specimens from 40 participants who underwent upper GI tract cancer screening in Linzhou (Henan, China) in August 2019. The V4 region of 16S rRNA genes was amplified and sequenced using the Illumina MiniSeq platform. The observed amplicon sequence variants (ASVs) gradually decreased from saliva to esophageal swab, cardia biopsy, noncardia biopsy, and gastric juice specimens and then increased from gastric juice to fecal specimens (P < 0.05). Each GI site had its own microbial characteristics that overlapped those of adjacent sites. Characteristic genera for each site were as follows: Neisseria and Prevotella in saliva, Streptococcus and Haemophilus in the esophagus, Helicobacter in the noncardia, Pseudomonas in gastric juice, Faecalibacterium, Roseburia, and Blautia in feces, and Weissella in the cardia. Helicobacter pylori-positive participants had decreased observed ASVs (cardia, P < 0.01; noncardia, P < 0.001) and Shannon index values (cardia, P < 0.001; noncardia, P < 0.001) compared with H. pylori-negative participants both in cardia and noncardia specimens. H. pylori infection played a more important role in the microbial composition of noncardia than of cardia specimens. In gastric juice, the gastric pH and H. pylori infection had similar additive effects on the microbial diversity and composition. These results show that each GI site has its own microbial characteristics that overlap those of adjacent sites and that differences and commonalities between and within microbial compositions coexist, providing essential foundations for the continuing exploration of disease-associated microbiota. IMPORTANCE Upper gastrointestinal (UGI) tract cancer is one of the most common cancers worldwide, while limited attention has been paid to the UGI microbiota. Microbial biomarkers, such as Fusobacteria nucleatum and Helicobacter pylori, bring new ideas for early detection of UGI tract cancer, which may be a highly feasible method to reduce its disease burden. This study revealed that each gastrointestinal site had its own microbial characteristics that overlapped those of adjacent sites. There were significant differences between the microbial compositions of the UGI sites and feces. Helicobacter pylori played a more significant role in the microbial composition of the noncardia stomach than in that of the cardia. Gastric pH and Helicobacter pylori had similar additive effects on the microbial diversity of gastric juice. These findings played a key role in delineating the microbiology spectrum of the gastrointestinal tract and provided baseline information for future microbial exploration covering etiology, primary screening, treatment, outcome, and health care products.

What is already known about this topic?:Little is known about the infection pattern for high-risk human papillomavirus (hrHPV) subtypes in rural areas in southern China.What is added by this report?:The prevalence of HPV-16, 18, and the other 12 hrHPV subtypes were 0.71%, 0.34%, and 4.50%, respectively, among rural women in Guangzhou. The prevalence of HPV-16 and the other 12 hrHPV subtypes increased with age, but there was no evident age trend for HPV-18 prevalence.What are the implications for public health practice?:Epidemiological characteristics of hrHPV prevalence in rural Guangzhou should be considered to identify high-risk populations of hrHPV infection and determine follow-up strategies.

Objective: To explore the correlation between age and diversity and microbial composition in saliva and feces microbiota in high-risk population of upper gastrointestinal cancer. Methods: Based on the national project on early diagnosis and early treatment of upper gastrointestinal cancer, 38 participants were enrolled in Linzhou in Henan province in August 2019. The participant information was collected by questionnaire. Saliva and feces specimens were collected from each participant for 16S rRNA sequencing and bioinformatics analysis. Spearman rank correlation was used to analyze the correlation between age and α diversity (Observed ASVs and Shannon index) and relative abundance of microbiota (phyla, genera, and species) in saliva and feces. Results: The median age (age range) of 38 participants was 54 (43-60) years old, and there were 16 males (42.1%). The Observed ASVs of saliva was negatively correlated with age (rs=-0.35, P<0.05), but the observed ASVs of feces was not correlated with age. In saliva, the relative abundance of Treponema (rs=‒0.44, P<0.05), Alloprevotella (rs=‒0.42, P<0.05), and Porphyromonas (rs=‒0.41,P<0.05) were significantly negatively correlated with age. At the species level, the relative abundance of Porphyromonas endodontalis, Alloprevotella tannerae, Haemophilus influenza, Moraxella bovoculi, Prevotella sp.oral clone ID019, and Prevotella sp.oral clone ASCG10 in saliva were significantly negatively correlated with age, and the rs values were -0.50, -0.40, -0.38, -0.35, -0.33 and -0.33 (P<0.05), respectively. In feces, the relative abundance of Enterobacteria (rs=-0.35, P<0.05), Escherichia (rs=-0.33, P<0.05), and Bifidobacteria (rs=0.33, P<0.05) were correlated with age. At the species level, the relative abundance of Romboutsia sedimentorum, Citrobacter murliniae, and bacteroides uniformis in feces were correlated with age, and the rs values were -0.42, -0.37 and 0.36 (P<0.05), respectively. Conclusion: Age of the high-risk population of upper gastrointestinal cancer is correlated with the relative abundance of microbiota in saliva and feces.

菌群在维持人类健康和疾病发生发展中发挥重要作用.培养组学是一种采用多种培养条件,利用基质辅助激光解吸-飞行时间(MALDO-TOF)质谱和16 S rRNA测序鉴定菌种、菌属的培养方法,为人体菌群研究带来新机遇.然而,目前培养组学运用于健康和疾病的研究仍然较少,以横断面、小样本量研究为主,尚处于初步发展阶段.现有培养组学与健康和疾病的研究采用生物标本类型多样化,但以粪便标本为主,其研究结果可从菌群角度为早诊早治、临床治疗、疾病预后、康复保健、卫生护理等方面提供依据.而为进一步推动培养组学研究,需针对不同部位标本开展预培养时长、取样方案等方法优化研究,有效增加分离培养的菌种数目,同时在尽可能保证菌种鉴定的基础上降低工作量.此外,在不断优化、规范化、标准化培养组学研究方案的同时,需注重与高通量测序技术的有效结合,注重与多组学技术的有效结合.

Background: Increasing attention has been devoted to cancer screening and microbiota in recent decades, but currently there is less focus on microbiota characterization among screeners and its relationship to anxiety and depression. Methods: We characterized the microbial communities of fecal samples collected through the FOBT card from anxiety and depression screeners and paired controls in Henan, China (1:2, N = 69). DNA was extracted using the MOBIO PowerSoil kit. The V4 region of the 16S rRNA gene was sequenced using MiniSeq and processed using QIIME1. LEfSe was used to identify differentially abundant microbes, the Wilcoxon rank-sum test was used to test alpha diversity differences, and permutational multivariate analysis of variance was used to test for differences in beta diversity. Results: Similar fecal microbiota signatures in composition were found among screeners. The intestinal microbial environments by phylum were all composed primarily of Firmicutes, Bacteroidetes, and Proteobacteria, and the corresponding top genera were Faecalibacterium, Roseburia, and Prevotella. Compared with controls, the ranking of the top five genera in the anxiety and depression group changed, and the dominant genus was Prevotella in the anxiety and depression group and Faecalibacterium in the control group. There was a lower relative abundance of Gemmiger (1.4 vs. 2.3%, P = 0.025), Ruminococcus (0.6 vs. 0.8%, P = 0.037), and Veillonella (0.6 vs. 1.3%, P = 0.020). This may be linked to the lower alpha diversity in participants with anxiety and depression (Observed OTUs: 122.35 vs. 143.24; Chao1: 127.35 vs. 149.98), although no significant differences were observed. Distinct clustering in microbial composition between the two groups was detected for the Jaccard distance (P = 0.011). Conclusions: Our study showed differing microbial characterization among participants with anxiety and depression in the endoscopic screening of upper gastrointestinal cancer. Gemmiger, Ruminococcus, and Veillonella were informative and have potential clinical implications, which need to be confirmed by large-scale, prospective cohort studies and biological mechanism research.

Objective: The risk prediction model is an effective tool for risk stratification and is expected to play an important role in the early detection and prevention of esophageal cancer. This study sought to summarize the available evidence of esophageal cancer risk predictions models and provide references for their development, validation, and application. Methods: We searched PubMed, EMBASE, and Cochrane Library databases for original articles published in English up to October 22, 2021. Studies that developed or validated a risk prediction model of esophageal cancer and its precancerous lesions were included. Two reviewers independently extracted study characteristics including predictors, model performance and methodology, and assessed risk of bias and applicability with PROBAST (Prediction model Risk Of Bias Assessment Tool). Results: A total of 20 studies including 30 original models were identified. The median area under the receiver operating characteristic curve of risk prediction models was 0.78, ranging from 0.68 to 0.94. Age, smoking, body mass index, sex, upper gastrointestinal symptoms, and family history were the most commonly included predictors. None of the models were assessed as low risk of bias based on PROBST. The major methodological deficiencies were inappropriate date sources, inconsistent definition of predictors and outcomes, and the insufficient number of participants with the outcome. Conclusions: This study systematically reviewed available evidence on risk prediction models for esophageal cancer in general populations. The findings indicate a high risk of bias due to several methodological pitfalls in model development and validation, which limit their application in practice.

The relationship between microbiota and esophageal squamous cell carcinoma (ESCC) progression is still unclear, especially esophageal microbiota. We collected esophageal biopsy and swab samples from 236 participants in health and esophageal diseases in Linzhou. With the average relative abundance (ARA%) of in health as baseline, this study compared the baseline with other groups by Wilcoxon test respectively, and the ARA% among five groups was analyzed by the Kruskal-Wallis test. A number of 109 microorganisms were characterized into genus level both in esophageal biopsy and swab specimens on the basis of 16SrRNA sequencing data. There were 12 indicative, same, consistent and identified microorganisms between two specimens, including Neisseria, Haemophilus, Aggregatibacter, Fusobacterium, Bergeyella, Selenomonas, Oribacterium, Alysiella, Filifactor, Novosphingobium, Streptococcus and f__Lachnospiraceae. The ARA% of the first eight microorganisms was increasing from normal to ESCC, while the ARA% of others was decreasing. Sphingomonas was the unique one with statistical difference between normal and others four groups respectively but only in biopsy. There were four flora with statistical difference between normal and LGIN above groups, including Aeromonas, Fretibacterium, Filifactor and Solobacterium, which were all with decreasing tendency. There are complicated and dynamic changing of indicative esophageal microorganisms with the progression of ESCC, which provides scientific evidence for early detection and diagnosis ESCC via easy-collected oral sample. However, more multi-center, large sample size, prospective studies are needed in the future.

With the development of multi-omics and high throughput sequencing technology, studies have shown that the disorder of microbiota is related to various cancers. Nevertheless, the research on the relationship between upper digestive tract cancer or precancerous lesions and gastrointestinal microecology is still less. Fusobacterium nucleatum, one of the oral symbiotic bacteria, is also an opportunistic pathogen, which can promote the formation of tumor microenvironment and can be used as a new biomarker for the early detection and early diagnosis of cancer. In this study, by searching CNKI, Wanfang data, PubMed and Embase databases, it was found that the abundance of F. nucleatum in cancer tissues is higher than that in paracancerous tissues and associated with poor prognosis. The research of relationship between F. nucleatum and precancerous lesions needs to be carried out urgently. In addition, the types of specimens, sequencing technology, strain subtypes, carcinogenic mechanism and other directions still need to be explored.

The composition of human oral microorganism is numerous and complex and is easily affected by many factors. With the development of metagenomic technology, the important role of oral microbiome in the development of tumor has attracted extensive attention. A literature retrieval was conducted through PubMed, Embase, CNKI and WanFang database for an analysis on the characteristics of oral bacteria and its association with oral cancer, esophageal cancer and gastric cancer. The results indicated that oral microbiome can be influenced by age, gender, race, and lifestyle. Specific oral bacteria were associated with high risk of upper gastrointestinal cancer, indicating a potential role of oral microbiota to be the biomarker for upper gastrointestinal cancer. This paper summarizes the progress in the research of the association between oral microbiome and upper gastrointestinal cancer, showing a new direction for the exploration of microbiological etiology of upper gastrointestinal cancer and providing scientific evidence for the optimization of early detection and treatment of upper gastrointestinal cancer.

OBJECTIVE:Esophageal squamous cell carcinoma (ESCC) is one of the dominant malignances worldwide, but currently there is less focus on the microbiota with ESCC and its precancerous lesions.METHODS:Paired esophageal biopsy and swab specimens were obtained from 236 participants in Linzhou, China. Data from 16S ribosomal RNA gene sequencing were processed using quantitative insights into microbial ecology (QIIME2) and R Studio to evaluate differences. The Wilcoxon rank sum test and Kruskal-Wallis rank sum test were used to compare diversity and characteristic genera by specimens and participant groups. Ordinal logistic regression model was used to build microbiol prediction model.RESULTS:Microbial diversity was similar between biopsy and swab specimens, including operational taxonomic unit (OTU) numbers and Shannon index. There were variations and similarities of esophageal microbiota among different pathological characteristics of ESCC. Top 10 relative abundance genera in all groups include Streptococcus, Prevotella, Veillonella, Actinobacillus, Haemophilus, Neisseria, Alloprevotella, Rothia, Gemella and Porphyromonas. Genus Streptococcus, Haemophilus, Neisseria and Porphyromonas showed significantly difference in disease groups when compared to normal control, whereas Streptococcus showed an increasing tendency with the progression of ESCC and others showed a decreasing tendency. About models based on all combinations of characteristic genera, only taken Streptococcus and Neisseria into model, the prediction performance was the ideal one, of which the area under the curve (AUC) was 0.738.CONCLUSIONS:Esophageal biopsy and swab specimens could yield similar microbial characterization. The combination of Streptococcus and Neisseria has the potential to predict the progression of ESCC, which is needed to confirm by large-scale, prospective cohort studies.

Background Little is known about the microbiota and upper gastrointestinal tumors. Esophageal squamous cell carcinoma (ESCC) and gastric cardia adenocarcinoma (GCA) occur in adjacent organs, co-occur geographically, and share many risk factors despite being of different tissue types. Methods This study characterized the microbial communities of paired tumor and nontumor samples from 67 patients with ESCC and 36 patients with GCA in Henan, China. DNA was extracted with the MoBio PowerSoil kit. The V4 region of the 16S ribosomal RNA gene was sequenced with MiniSeq and was processed with Quantitative Insights Into Microbial Ecology 1. The linear discriminant analysis effect size method was used to identify differentially abundant microbes, the Wilcoxon rank-sum test was used to test alpha diversity differences, and permutational multivariate analysis of variance was used to test for differences in beta diversity. Results The microbial environments of ESCC and GCA tissues were all composed primarily of Firmicutes, Bacteroidetes, and Proteobacteria. ESCC tumor tissues contained more Fusobacterium (3.2% vs 1.3%) and less Streptococcus (12.0% vs 30.2%) than nontumor tissues. GCA nontumor tissues had a greater abundance of Helicobacter (60.5% vs 11.8%), which may have been linked to the lower alpha diversity (58.0 vs 102.5; P = .0012) in comparison with tumor tissues. A comparison of ESCC and GCA nontumor tissues showed that the microbial composition (P = .0040) and the alpha diversity (87.0 vs 58.0; P = .00052) were significantly different. No significant differences were detected for alpha diversity within ESCC and GCA tumor tissues. Conclusions This study showed differences in the microbial compositions of paired ESCC and GCA tumor and nontumor tissues and differences by organ site. Large-scale, prospective cohort studies are needed to confirm these findings.

IntroductionOesophageal cancer (OC) is one of the most common cancers worldwide and about 50% of all new cases occurred in China. Population-based screening has been conducted in high-risk areas in China since 1970s, however, a few factors have limited the integration of the results from previous studies and the sharing of existing resources, such as the difference in screening methods and protocols, inconsistencies in questionnaires for risk factors investigation, lack of standards for sample collection and incomplete follow-up information.Methods and analysisThe National Cohort of Esophageal Cancer-Prospective Cohort Study of Esophageal Cancer and Precancerous Lesions based on High-Risk Population (NCEC-HRP) is a prospective cohort study of OC screening based on high-risk population in China supported by the National Key R&D Programme. Eight areas located at eastern, central and western China are selected as screening centres to represent three economical-geographical regions. All local residents aged 40–69 years in the selected areas are invited to take endoscopic examination and risk factors investigation unless they meet the exclusion criteria. The recruitment began on June 2017 and a total of 100 000 participants will be enrolled by December 2020 and all subjects will be followed for a long time. This study is designed as open-ended and has broad research aims. Summary statistics for baseline information will be reported after the completion of recruitment. We will develop a series of standards and guidelines for OC screening during the study. An open and shared research platform linked with epidemiological databases and biobank will be built up for further research.Ethics and disseminationThe study is approved by the Ethics Committee of Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (approval number 16-171/1250). The findings of the study will be disseminated through scientific peer-reviewed journals as well as the public via the study website (http://www.ncec-china.cn).Trial registration numberChiCTR-EOC-17010553; Pre-results.

Objective: To describe the status of non-steroidal anti-inflammatory drugs (NSAIDs) use in areas with a high incidence of upper gastrointestinal cancer in China. Methods: This study was based on the National Key Research and Development Program of "National Precision Medicine Cohort of Esophageal Cancer" and "Study on Identification and Prevention of High-risk Populations of Gastrointestinal Malignancies (Esophageal cancer, Gastric cancer and Colorectal cancer)" . From January 2017 to August 2018, 212 villages or communities with a high incidence of esophageal cancer or gastric cancer were selected from 12 regions in 6 provinces. A total of 35 910 residents aged between 40 and 69 years old who met the inclusion criteria and signed the informed consent were investigated and enrolled in this study. The use of NSAIDs, demographic characteristics, health-related habits, height, weight, and blood pressure were collected by the questionnaire and physical examination. The status of main NSAIDs (aspirin, acetaminophen and ibuprofen) use with the difference varying in genders, age groups and regions were analyzed by using χ(2) test and Cochran-Armitage trend analysis method. Results: Of 35 910 subjects, the mean age was (54.6±7.1) years old and males accounted for 43.42% (15 591). The overall prevalence of NSAIDs intake was 4.56% (1 638), but it significantly varied in different provinces (P<0.001). The overall prevalence of NSAIDs intake was 4.87% (1 750) in females, which was significantly higher than that in males 4.24% (1 524) (P<0.001). The prevalence of NSAIDs intake increased with age (P for trend <0.001). As the frequency of NSAIDs intake increased, the incidence of gastrointestinal symptoms, gastrointestinal ulcers and black stools increased (P for trend <0.05 for all). Conclusion: The use of NSAIDs is prevalent in some areas with a high incidence of upper gastrointestinal cancer in China. The increased use of NSAIDs may lead to more adverse effects related to the gastrointestinal tract.