Gut microbiota-metabolite interactions meditate the effect of dietary patterns on precocious puberty.

Precocious puberty, a pediatric endocrine disorder classified as central precocious puberty (CPP) or peripheral precocious puberty (PPP), is influenced by diet, gut microbiota, and metabolites, but the specific mechanisms remain unclear. Our study found that increased alpha-diversity and abundance of short-chain fatty acid-producing bacteria led to elevated levels of luteinizing hormone and follicle-stimulating hormone, contributing to precocious puberty. The integration of specific microbiota and metabolites has potential diagnostic value for precocious puberty. The Prevotella genus-controlled interaction factor, influenced by complex carbohydrate consumption, mediated a reduction in estradiol levels. Interactions between obesity-related bacteria and metabolites mediated the beneficial effect of seafood in reducing luteinizing hormone levels, reducing the risk of obesity-induced precocious puberty, and preventing progression from PPP to CPP. This study provides valuable insights into the complex interplay between diet, gut microbiota and metabolites in the onset, development and clinical classification of precocious puberty and warrants further investigation.

Creatine Acts as a Mediator of the Causal Effect of Obesity on Puberty Onset in Girls: Evidence from Mediation Mendelian Randomization Study.

Epidemiological studies have linked obesity to the onset of puberty, while its causality and the potential metabolite mediators remain unclear. We employed a two-sample Mendelian randomization (MR) design to evaluate the causal effects of obesity on puberty onset and its associated diseases including type 2 diabetes (T2D) and cardiovascular diseases (CVDs). The potential mediators in this pathway were further explored using a two-step MR design. The robustness of our findings was evaluated using sensitivity analyses. Our MR results revealed that childhood obesity/BMI were causally associated with an increased Tanner stage in girls, younger age at menarche, and increased risk of adulthood T2D and CVD. However, neither childhood BMI nor obesity had a causal effect on the Tanner stage in boys. Mediation analysis further indicated that increased creatine served as a mediator for the causal pathway from childhood obesity/BMI to the Tanner stage of girls, while early puberty onset in girls played a mediating role in the pathway linking childhood obesity to increased risk of adulthood T2D and CVD. This study indicated that the risk of early puberty onset in girls and its associated health issues can be potentially reduced by preventing childhood obesity. The involvement of creatine in this process needs to be further validated and explored.

Temporal development and potential interactions between the gut microbiome and resistome in early childhood.

Antimicrobial resistance-associated infections have become a major threat to global health. The gut microbiome serves as a major reservoir of bacteria with antibiotic resistance genes; whereas, the temporal development of gut resistome during early childhood and the factors influencing it remain unclear. Moreover, the potential interactions between gut microbiome and resistome still need to be further explored. In this study, we found that antibiotic treatment led to destabilization of the gut microbiome and resistome structural communities, exhibiting a greater impact on the resistome than on the microbiome. The composition of the gut resistome at various developmental stages was influenced by the abundance and richness of different core microbes. First exposure to antibiotics led to a dramatic increase in the number of opportunistic pathogens carrying multidrug efflux pump encoding genes. Multiple factors could influence the gut microbiome and resistome formation. The data may provide new insights into early-life research.IMPORTANCEIn recent years, the irrational or inappropriate use of antibiotics, an important life-saving medical intervention, has led to the emergence and increase of drug-resistant and even multidrug-resistant bacteria. It remains unclear how antibiotic exposure affects various developmental stages of early childhood and how gut core microbes under antibiotic exposure affect the structural composition of the gut resistome. In this study, we focused on early antibiotic exposure and analyzed these questions in detail using samples from infants at various developmental stages. The significance of our research is to elucidate the impact of early antibiotic exposure on the dynamic patterns of the gut resistome in children and to provide new insights for early-life studies.

Causal Effects of Gut Microbiota on Sleep-Related Phenotypes: A Two-Sample Mendelian Randomization Study.

Increasing evidence suggests a correlation between changes in the composition of gut microbiota and sleep-related phenotypes. However, it remains uncertain whether these associations indicate a causal relationship. The genome-wide association study summary statistics data of gut microbiota (n = 18,340) was downloaded from the MiBioGen consortium and the data of sleep-related phenotypes were derived from the UK Biobank, the Medical Research Council-Integrative Epidemiology Unit, Jones SE, the FinnGen consortium. To test and estimate the causal effect of gut microbiota on sleep traits, a two-sample Mendelian randomization (MR) approach using multiple methods was conducted. A series of sensitive analyses, such as horizontal pleiotropy analysis, heterogeneity test, MR Steiger directionality test and "leave-one-out" analysis as well as reverse MR analysis, were conducted to assess the robustness of MR results. The genus Anaerofilum has a negative causal effect on getting up in the morning (odd ratio = 0.977, 95% confidence interval: 0.965-0.988, p = 7.28 × 10-5). A higher abundance of order Enterobacteriales and family Enterobacteriaceae contributed to becoming an "evening person". Six and two taxa were causally associated with longer and shorter sleep duration, respectively. Specifically, two SCFA-produced genera including Lachnospiraceae UCG004 (odd ratio = 1.029, 95% confidence interval = 1.012-1.046, p = 6.11 × 10-4) and Odoribacter contribute to extending sleep duration. Two obesity-related genera such as Ruminococcus torques (odd ratio = 1.024, 95% confidence interval: 1.011-1.036, p = 1.74 × 10-4) and Senegalimassilia were found to be increased and decreased risk of snoring, respectively. In addition, we found two risk taxa of insomnia such as the order Selenomonadales and one of its classes called Negativicutes. All of the sensitive analysis and reverse MR analysis results indicated that our MR results were robust. Our study revealed the causal effect of gut microbiota on sleep and identified causal risk and protective taxa for chronotype, sleep duration, snoring and insomnia, which has the potential to provide new perspectives for future mechanistic and clinical investigations of microbiota-mediated sleep abnormal patterns and provide clues for developing potential microbiota-based intervention strategies for sleep-related conditions.

Identifying and ranking causal microbial biomarkers for colorectal cancer at different cancer subsites and stages: a Mendelian randomization study.

Introduction: The gut microbiome is directly involved in colorectal carcinogenesis, but much of the epidemiological evidence for the effect of the gut microbiome on colorectal cancer (CRC) risk comes from observational studies, and it is unclear whether identified microbial alterations are the cause or consequence of CRC development. Methods: Univariate Mendelian randomization (MR) analysis and multivariate MR analysis based on Bayesian model averaging were performed to comprehensively explore the microbial risk factors associated with CRC. The Network Module Structure Shift method was used to identify microbial biomarkers associated with CRC. Mediation analysis was used to explore the dietary habits-microbiota-CRC pathway. Results: The results of the four methods showed that 9 bacteria had a robust causal relationship with the development of CRC. Among them, Streptococcus thermophilus reduced the risk of CRC; Eubacterium ventriosum and Streptococcus were beneficial bacteria of malignant tumors of colon (CC); Erysipelotrichaceae was a protective factor for malignant tumors of rectal (CR); Bacteroides ovatus was a risk factor for benign tumors. Finally, the mediation analysis revealed 10 pathways by which dietary regulation bacteria affected the risk of CRC, including alcohol consumption increased the risk of CC by reducing the abundance of Eubacterium ventriosum (mediated proportion: 43.044%), and the mediated proportion of other pathways was 7.026%-34.22%. Discussion: These findings will contribute to the understanding of the different carcinogenic mechanisms of intestinal flora in the colon and rectum and the risk of tumor transformation, thereby aiding CRC prevention, early screening, and the development of future strategies to reduce CRC risk.

Bidirectional Mediation Effects between Intratumoral Microbiome and Host DNA Methylation Changes Contribute to Stomach Adenocarcinoma.

The induction of aberrant DNA methylation is the major pathway by which Helicobacter pylori infection induces stomach adenocarcinoma (STAD). The involvement of the non-H. pylori gastric microbiota in this mechanism remains to be examined. RNA sequencing data, clinical information, and DNA methylation data were obtained from The Cancer Genome Atlas (TCGA) STAD project. The Kraken 2 pipeline was employed to explore the microbiome profiles. The microbiome was associated with occurrence, distal metastasis, and prognosis, and differential methylation changes related to distal metastasis and prognosis were analyzed. Bi-directional mediation effects of the intratumoral microbiome and host DNA methylation changes on the metastasis and prognosis of STAD were identified by mediation analysis. The expression of the ZNF215 gene was verified by real-time quantitative PCR (RT-qPCR). A cell counting kit 8 (CCK8) cell proliferation experiment and a cell clone formation experiment were used to evaluate the proliferation and invasion abilities of gastric cells. Our analysis revealed that H. pylori and other cancer-related microorganisms were related to the occurrence, progression, or prognosis of STAD. The related methylated genes were particularly enriched in related cancer pathways. Kytococcus sedentarius and Actinomyces oris, which interacted strongly with methylation changes in immune genes, were associated with prognosis. Cell experiments verified that Staphylococcus saccharolyticus could promote the proliferation and cloning of gastric cells by regulating the gene expression level of the ZNF215 gene. Our study suggested that the bi-directional mediation effect between intratumoral microorganisms and host epigenetics was key to the distal metastasis of cancer cells and survival deterioration in the tumor microenvironment of stomach tissues of patients with STAD. IMPORTANCE The burgeoning field of oncobiome research declared that members of the intratumoral microbiome besides Helicobacter pylori existed in tumor tissues and participated in the occurrence and development of gastric cancer, and the methylation of host DNA may be a potential target of microbes and their metabolites. Current research focuses mostly on species composition, but the functional genes of the members of the microbiota are also key to their interaction with the host. Therefore, we focused on characterizing the species composition and functional gene composition of microbes in gastric cancer, and we suggest that microbes may further participate in the occurrence and development of cancer by influencing abnormal epigenetic changes in the host. Some key bioinformatics analysis results were verified by in vitro experiments. Thus, we consider that the tumor microbiota-host epigenetic axis of gastric cancer microorganisms and the host explains the mechanism of the microbiota participating in cancer occurrence and development, and we make some verifiable experimental predictions.

Prospective, longitudinal analysis of the gut microbiome in patients with locally advanced rectal cancer predicts response to neoadjuvant concurrent chemoradiotherapy.

BACKGROUND: Neoadjuvant concurrent chemoradiotherapy (nCCRT) is a standard treatment for locally advanced rectal cancer (LARC). The gut microbiome may be reshaped by radiotherapy through its effects on microbial composition, mucosal immunity, and the systemic immune system. We sought to clarify dynamic, longitudinal changes in the gut microbiome and blood immunomodulators throughout nCCRT and to explore the relationship of such changes with outcomes after nCCRT. METHODS: A total of 39 patients with LARC were recruited for this study. Fecal samples and peripheral blood samples were collected from all 39 patients before nCCRT, during nCCRT (at week 3), and after nCCRT (at week 5). The gut microbiota and the microbial community structure were analyzed by 16S rRNA sequencing of the V3-V4 region. Levels of blood immunomodulatory proteins were measured with a Millipore HCKPMAG-11 K kit and Luminex 200 platform (Luminex, USA). RESULTS: Cross-sectional and longitudinal analyses revealed that the gut microbiome profile and enterotype exhibited characteristic variations that could distinguish patients with good response (AJCC TRG classification 0-1) vs poor response (TRG 2-3) to nCCRT. Sparse partial least squares regression and canonical correspondence analyses showed multivariate associations between specific microbial taxa, host immunomodulatory proteins, immune cells, and outcomes after nCCRT. An integrated model consisting of baseline Clostridium sensu stricto 1 levels, fold changes in Intestinimonas, blood levels of the herpesvirus entry mediator (HVEM/CD270), and lymphocyte counts could predict good vs poor outcome after nCCRT [area under the receiver-operating characteristics curve (AUC)= 0.821; area under the precision-recall curve [AUPR] = 0.911]. CONCLUSIONS: Our results showed that longitudinal variations in specific gut taxa, associated host immune cells, and immunomodulatory proteins before and during nCCRT could be useful for early predictions of the efficacy of nCCRT, which could guide the choice of individualized treatment for patients with LARC.

The Interaction between Intratumoral Microbiome and Immunity Is Related to the Prognosis of Ovarian Cancer.

Microbiota can influence the occurrence, development, and therapeutic response of a wide variety of cancer types by modulating immune responses to tumors. Recent studies have demonstrated the existence of intratumor bacteria inside ovarian cancer (OV). However, whether intratumor microbes are associated with tumor microenvironment (TME) and prognosis of OV still remains unknown. The RNA-sequencing data and clinical and survival data of 373 patients with OV in The Cancer Genome Atlas (TCGA) were collected and downloaded. According to the knowledge-based functional gene expression signatures (Fges), OV was classified into two subtypes, termed immune-enriched and immune-deficient subtypes. The immune-enriched subtype, which had higher immune infiltration enriched with CD8+ T cells and the M1 type of macrophages (M1) and higher tumor mutational burden, exhibited a better prognosis. Based on the Kraken2 pipeline, the microbiome profiles were explored and found to be significantly different between the two subtypes. A prediction model consisting of 32 microbial signatures was constructed using the Cox proportional-hazard model and showed great prognostic value for OV patients. The prognostic microbial signatures were strongly associated with the hosts' immune factors. Especially, M1 was strongly associated with five species (Achromobacter deleyi and Microcella alkaliphila, Devosia sp. strain LEGU1, Ancylobacter pratisalsi, and Acinetobacter seifertii). Cell experiments demonstrated that Acinetobacter seifertii can inhibit macrophage migration. Our study demonstrated that OV could be classified into immune-enriched and immune-deficient subtypes and that the intratumoral microbiota profiles were different between the two subtypes. Furthermore, the intratumoral microbiome was closely associated with the tumor immune microenvironment and OV prognosis. IMPORTANCE Recent studies have demonstrated the existence of intratumoral microorganisms. However, the role of intratumoral microbes in the development of ovarian cancer and their interaction with the tumor microenvironment are largely unknown. Our study demonstrated that OV could be classified into immune-enriched and -deficient subtypes and that the immune enrichment subtype had a better prognosis. Microbiome analysis showed that intratumor microbiota profiles were different between the two subtypes. Furthermore, the intratumor microbiome was an independent predictor of OV prognosis that could interact with immune gene expression. Especially, M1 was closely associated with intratumoral microbes, and Acinetobacter seifertii could inhibit macrophage migration. Together, the findings of our study highlight the important roles of intratumoral microbes in the TME and prognosis of OV, paving the way for further investigation into its underlying mechanisms.

The dual role of glioma exosomal microRNAs: glioma eliminates tumor suppressor miR-1298-5p via exosomes to promote immunosuppressive effects of MDSCs.

Clear evidence shows that tumors could secrete microRNAs (miRNAs) via exosomes to modulate the tumor microenvironment (TME). However, the mechanisms sorting specific miRNAs into exosomes are still unclear. In order to study the biological function and characterization of exosomal miRNAs, we performed whole-transcriptome sequencing in 59 patients' whole-course cerebrospinal fluid (CSF) small extracellular vesicles (sEV) and matched glioma tissue samples. The results demonstrate that miRNAs could be divided into exosome-enriched miRNAs (ExomiRNAs) and intracellular-retained miRNAs (CLmiRNAs), and exosome-enriched miRNAs generally play a dual role. Among them, miR-1298-5p was enriched in CSF exosomes and suppressed glioma progression in vitro and vivo experiments. Interestingly, exosomal miR-1298-5p could promote the immunosuppressive effects of myeloid-derived suppressor cells (MDSCs) to facilitate glioma. Therefore, we found miR-1298-5p had different effects on glioma cells and MDSCs. Mechanically, downstream signaling pathway analyses showed that miR-1298-5p plays distinct roles in glioma cells and MDSCs via targeting SETD7 and MSH2, respectively. Moreover, reverse verification was performed on the intracellular-retained miRNA miR-9-5p. Thus, we confirmed that tumor-suppressive miRNAs in glioma cells could be eliminated through exosomes and target tumor-associated immune cells to induce tumor-promoting phenotypes. Glioma could get double benefit from it. These findings uncover the mechanisms that glioma selectively sorts miRNAs into exosomes and modulates tumor immunity.

SPI1-induced downregulation of FTO promotes GBM progression by regulating pri-miR-10a processing in an m6A-dependent manner.

As one of the most common post-transcriptional modifications of mRNAs and noncoding RNAs, N6-methyladenosine (m6A) modification regulates almost every aspect of RNA metabolism. Evidence indicates that dysregulation of m6A modification and associated proteins contributes to glioblastoma (GBM) progression. However, the function of fat mass and obesity-associated protein (FTO), an m6A demethylase, has not been systematically and comprehensively explored in GBM. Here, we found that decreased FTO expression in clinical specimens correlated with higher glioma grades and poorer clinical outcomes. Functionally, FTO inhibited growth and invasion in GBM cells in vitro and in vivo. Mechanistically, FTO regulated the m6A modification of primary microRNA-10a (pri-miR-10a), which could be recognized by reader HNRNPA2B1, recruiting the microRNA microprocessor complex protein DGCR8 and mediating pri-miR-10a processing. Furthermore, the transcriptional activity of FTO was inhibited by the transcription factor SPI1, which could be specifically disrupted by the SPI1 inhibitor DB2313. Treatment with this inhibitor restored endogenous FTO expression and decreased GBM tumor burden, suggesting that FTO may serve as a novel prognostic indicator and therapeutic molecular target of GBM.

Identification of Tumor Microenvironment-Related Prognostic Biomarkers for Ovarian Serous Cancer 3-Year Mortality Using Targeted Maximum Likelihood Estimation: A TCGA Data Mining Study.

Ovarian serous cancer (OSC) is one of the leading causes of death across the world. The role of the tumor microenvironment (TME) in OSC has received increasing attention. Targeted maximum likelihood estimation (TMLE) is developed under a counterfactual framework to produce effect estimation for both the population level and individual level. In this study, we aim to identify TME-related genes and using the TMLE method to estimate their effects on the 3-year mortality of OSC. In total, 285 OSC patients from the TCGA database constituted the studying population. ESTIMATE algorithm was implemented to evaluate immune and stromal components in TME. Differential analysis between high-score and low-score groups regarding ImmuneScore and StromalScore was performed to select shared differential expressed genes (DEGs). Univariate logistic regression analysis was followed to evaluate associations between DEGs and clinical pathologic factors with 3-year mortality. TMLE analysis was conducted to estimate the average effect (AE), individual effect (IE), and marginal odds ratio (MOR). The validation was performed using three datasets from Gene Expression Omnibus (GEO) database. Additionally, 355 DEGs were selected after differential analysis, and 12 genes from DEGs were significant after univariate logistic regression. Four genes remained significant after TMLE analysis. In specific, ARID3C and FREM2 were negatively correlated with OSC 3-year mortality. CROCC2 and PTF1A were positively correlated with OSC 3-year mortality. Combining of ESTIMATE algorithm and TMLE algorithm, we identified four TME-related genes in OSC. AEs were estimated to provide averaged effects based on the population level, while IEs were estimated to provide individualized effects and may be helpful for precision medicine.

Identification of microenvironment related potential biomarkers of biochemical recurrence at 3 years after prostatectomy in prostate adenocarcinoma.

Prostate adenocarcinoma is one of the leading adult malignancies. Identification of multiple causative biomarkers is necessary and helpful for determining the occurrence and prognosis of prostate adenocarcinoma. We aimed to identify the potential prognostic genes in the prostate adenocarcinoma microenvironment and to estimate the causal effects simultaneously. We obtained the gene expression data of prostate adenocarcinoma from TCGA project and identified the differentially expressed genes based on immune-stromal components. Among these genes, 68 were associated with biochemical recurrence at 3 years after prostatectomy in prostate adenocarcinoma. After adjusting for the minimal sets of confounding covariates, 14 genes (TNFRSF4, ZAP70, ERMN, CXCL5, SPINK6, SLC6A18, CHRM2, TG, CLLU1OS, POSTN, CTSG, NETO1, CEACAM7, and IGLV3-22) related to the microenvironment were identified as prognostic biomarkers using the targeted maximum likelihood estimation. Both the average and individual causal effects were obtained to measure the magnitude of the effect. CIBERSORT and gene set enrichment analyses showed that these prognostic genes were mainly associated with immune responses. POSTN and NETO1 were correlated with androgen receptor expression, a main driver of prostate adenocarcinoma progression. Finally, five genes were validated in another prostate adenocarcinoma cohort (GEO: GSE70770). These findings might lead to the improved prognosis of prostate adenocarcinoma.

Causal Effects of Overall and Abdominal Obesity on Insulin Resistance and the Risk of Type 2 Diabetes Mellitus: A Two-Sample Mendelian Randomization Study.

Overall and abdominal obesity were significantly associated with insulin resistance and type 2 diabetes mellitus (T2DM) risk in observational studies, though these associations cannot avoid the bias induced by confounding effects and reverse causation. This study aimed to test whether these associations are causal, and it compared the causal effects of overall and abdominal obesity on T2DM risk and glycemic traits by using a two-sample Mendelian randomization (MR) design. Based on summary-level statistics from genome-wide association studies, the instrumental variables for body mass index (BMI), waist-to-hip ratio (WHR), and WHR adjusted for BMI (WHRadjBMI) were extracted, and the horizontal pleiotropy was analyzed using MR-Egger regression and the MR-pleiotropy residual sum and outlier (PRESSO) method. Thereafter, by using the conventional MR method, the inverse-variance weighted method was applied to assess the causal effect of BMI, WHR, and WHRadjBMI on T2DM risk, Homeostatic model assessment of insulin resistance (HOMA-IR), fasting insulin, fasting glucose, and Hemoglobin A1c (HbA1c). A series of sensitivity analyses, including the multivariable MR (diastolic blood pressure, systolic blood pressure, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol as covariates), MR-Egger regression, weighted median, MR-PRESSO, and leave-one-out method, were conducted to test the robustness of the results from the conventional MR. Despite the existence of horizontal pleiotropy, consistent results were found in the conventional MR results and sensitivity analyses, except for the association between BMI and fasting glucose, and WHRadjBMI and fasting glucose. Each one standard deviation higher BMI was associated with an increased T2DM risk [odds ratio (OR): 2.741; 95% confidence interval (CI): 2.421-3.104], higher HbA1c [1.054; 1.04-1.068], fasting insulin [1.202; 1.173-1.231], and HOMA-IR [1.221; 1.187-1.255], similar to findings for causal effect of WHRadjBMI on T2DM risk [1.993; 1.704-2.33], HbA1c [1.061; 1.042-1.08], fasting insulin [1.102; 1.068-1.136], and HOMA-IR [1.127; 1.088-1.167]. Both BMI (P = 0.546) and WHRadjBMI (P = 0.443) were unassociated with fasting glucose in the multivariable MR analysis. In conclusion, overall and abdominal obesity have causal effects on T2DM risk and insulin resistance but no causal effect on fasting glucose. Individuals can substantially reduce their insulin resistance and T2DM risk through reduction of body fat mass and modification of body fat distribution.

Identification of gene biomarkers in patients with postmenopausal osteoporosis.

Postmenopausal osteoporosis (PMOP) is a major public health concern worldwide. The present study aimed to provide evidence to assist in the development of specific novel biomarkers for PMOP. Differentially expressed genes (DEGs) were identified between PMOP and normal controls by integrated microarray analyses of the Gene Expression Omnibus (GEO) database, and the optimal diagnostic gene biomarkers for PMOP were identified with LASSO and Boruta algorithms. Classification models, including support vector machine (SVM), decision tree and random forests models, were established to test the diagnostic value of identified gene biomarkers for PMOP. Functional annotations and protein­protein interaction (PPI) network constructions were also conducted. Integrated microarray analyses (GSE56815, GSE13850 and GSE7429) of the GEO database were employed, and 1,320 DEGs were identified between PMOP and normal controls. An 11­gene combination was also identified as an optimal biomarker for PMOP by feature selection and classification methods using SVM, decision tree and random forest models. This combination was comprised of the following genes: Dehydrogenase E1 and transketolase domain containing 1 (DHTKD1), osteoclast stimulating factor 1 (OSTF1), G protein­coupled receptor 116 (GPR116), BCL2 interacting killer, adrenoceptor ß1 (ADRB1), neogenin 1 (NEO1), RB binding protein 4 (RBBP4), GPR87, cylicin 2, EF­hand calcium binding domain 1 and DEAH­box helicase 35. RBBP4 (degree=12) was revealed to be the hub gene of this PMOP­specific PPI network. Among these 11 genes, three genes (OSTF1, ADRB1 and NEO1) were speculated to serve roles in PMOP by regulating the balance between bone formation and bone resorption, while two genes (GPR87 and GPR116) may be involved in PMOP by regulating the nuclear factor­κB signaling pathway. Furthermore, DHTKD1 and RBBP4 may be involved in PMOP by regulating mitochondrial dysfunction and interacting with ESR1, respectively. In conclusion, the findings of the current study provided an insight for exploring the mechanism and developing novel biomarkers for PMOP. Further studies are required to test the diagnostic value for PMOP prior to use in a clinical setting.