Roger Pero-Gascon

The placenta is the interface between maternal exposome and fetal development. However, analytical platforms for simultaneous analysis of its (semi-)polar metabolome and lipidome from a single tissue aliquot are lacking. We developed and validated a dual-extraction method for metabolomics and lipidomics analyses of human placenta.,A Design of Experiments approach was based on 54 targeted metabolites and lipids (log P=–3.24-10.59) and untargeted feature count to optimize bead mill homogenization, solvent composition and dilution for sequential extraction, prior to ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry. Method validation was performed on pooled porcine (as a proxy) and human placenta samples. Targeted validation demonstrated a coefficient of variation (CV) ≤20% for repeatability and inter-day precision and a coefficient of determination (R²) ≥0.99 for >26/27 metabolites and >17/27 lipids. Untargeted analysis consistently detected 2,811 and 5,412 features (CV ≤30%) in metabolite and lipid fractions, respectively.,The method was applied to 371 placental samples from the ENVIRONAGE birth cohort to assess metabolic perturbations associated with maternal lifestyle factors and adverse neonatal outcomes (small for gestational age (SGA) status, preterm birth, and low 1-minute Appearance, Pulse, Grimace, Activity and Respiration (APGAR)). Notably, placental cotinine levels showed associations with self-reported maternal smoking behavior (η² =0.14, FDR p <0.2). Pathway enrichment and targeted analyses identified outcome-specific metabolic signatures under basic covariate adjustment, though these were sensitive to extended covariate correction.,Our validated dual-extraction platform enables reproducible, resource-efficient placental phenotyping with demonstrated sensitivity to exposome signals, supporting large-scale birth cohort research into adverse neonatal outcomes.

Esophageal cancer (EC) results in high mortality due to difficulty in early diagnosis, particularly in low- and middle-income countries, including the African EC belt typified by high prevalence, early onset, and poor prognosis. While the precise etiological factors remain unknown, emerging data suggest links to the oral microbiota. In this study, we conducted a secondary analysis using V4 16S rRNA sequencing from a cross-sectional study of treatment-naive, newly diagnosed EC patients ( N = 103) and healthy controls ( N = 108) residing in agricultural regions of Ethiopia. We report that the salivary microbiota in the healthy Ethiopian controls is highly diverse, forming two functionally distinct community clusters differing in diversity, composition, and absolute abundance. Microbiota composition was associated with sex and alcohol consumption, but not age. Comparisons against groups from geographically distinct populations representing Tanzania, Uganda, Venezuela, and the United States ( N = 641) showed that cluster 2 resembled other East African populations, while cluster 1 was unique to the Ethiopian cohort. Both EC subtypes, esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma, were associated with a loss of microbial diversity and an increased probability of having a cluster 2 microbiota (adjusted OR = 2.9 [95% CI 1.5–5.9]). Classifiers trained to discriminate healthy and EC samples were further validated on two external EC cohorts from China ( N = 161). Models trained on the Ethiopian cohort could predict disease status in an external cohort of mid- and late-stage ESCC from China (AUROC = 0.70 ± 0.03 [mean ± SD]), demonstrating the generalization of microbial features of ESCC across populations. IMPORTANCE: Recent reports in North America and China have correlated oral microbiota composition with esophageal cancer, although the translation of this knowledge into the African esophageal cancer belt is hampered by a lack of data on the oral microbiota of East Africans and limited cross-cohort comparative analyses validating the utility of these biomarkers. We report that the human salivary microbiota is a meaningful biomarker of later-stage esophageal cancer that transcends geography and ethnicity and may provide utility for large-population screening. A lower-diversity and lower-abundance salivary microbiota correlated with esophageal cancer warrants further investigation to understand the role of oral microbes in mediating carcinogenesis.

Mycotoxin contamination is a global threat to food safety and human health, especially in regions facing food insecurity, such as Sub-Saharan Africa. This intervention study evaluates the effectiveness of nixtamalization, a traditional alkaline cooking method, in reducing mycotoxin levels in maize and corresponding urinary biomarkers of exposure. Forty adult healthy volunteers from an informal settlement in Kliptown, Soweto (South Africa), were randomly assigned to consume control maize or visibly moldy maize subjected to nixtamalization. Nixtamalization achieved a reduction in fumonisin B3 and deoxynivalenol (DON) to unquantifiable or undetectable levels in maize, while reducing fumonisin B1 (FB1), fumonisin B2, and zearalenone (ZEN) by 95%, 95%, and 89%, respectively. Aflatoxin B1 was unquantifiable before and eliminated after treatment. Biomarker analysis revealed that after consumption of either control or nixtamalized maize, urinary levels of FB1, ZEN, and its metabolites α- and β-zearalenol (α- and β-ZEL) did not show significant differences between groups (p > 0.05). DON and tenuazonic acid levels were not affected by the intervention (p > 0.05), with urinary detection frequencies remaining above 90%. These results demonstrate nixtamalization effectively lowers mycotoxin levels in maize, resulting in exposure levels comparable to control maize, and highlight human biomonitoring as a sensitive tool for evaluating food safety interventions.