RESUMEN
Per- and polyfluoroalkyl substances (PFAS) are a group of synthetic, highly fluorinated aliphatic compounds, commonly utilised in a wide variety of consumer products with diverse applications. Since the genesis of these compounds, a growing body of evidence has demonstrated adverse health effects associated with PFAS exposure. In a racially diverse cohort of 459 pregnant mothers, demographically weighted towards minority representation (black 44.4%, white 38.4%, other 17.2%), across three major populous cities of the US, PFAS profiling was performed. Nine distinct PFAS species were quantified using mass spectrometry in plasma samples collected during the third trimester. Multivariable logistic and linear regression analyses were conducted to interrogate the associations of PFAS with gestational and birth outcomes: gestational diabetes, preeclampsia, gestational age at delivery, low birth weight, birth weight-, birth length- and head circumference-for-gestational-age. Detectable levels for eight out of nine profiled PFAS species were found in the plasma of pregnant mothers with a median range of 0.1-2.70 ng ml-1. Using a mixtures approach, we observe that increased quantile-based g-computation (Qg-comp) "total" PFAS levels were associated with increased newborn birth-weight-for-gestational-age (ß 1.28; 95% CI 1.07-1.52; FDR p 0.006). In study centre-stratified analyses, we observed a similar trend in Boston pregnant mothers, with Qg-comp total PFAS associated with higher newborn birth-weight-for-gestational-age (ß 1.39; 95% CI 1.01-1.92, FDR p 0.05). We additionally found elevated PFUA concentrations were associated with longer gestational terms in San Diego pregnant mothers (ß 0.60; 95% CI 0.18-1.02, FDR p 0.05). In this multi-city study, we detected lower levels of PFAS than in many previous US environmental studies, concordant with current US trends indicating environmental PFAS levels are falling, and we note geographical variation in the associations between PFAS levels and birth outcomes.
RESUMEN
BACKGROUND: As new infectious diseases (ID) emerge and others continue to mutate, there remains an imminent threat, especially for vulnerable individuals. Yet no generalizable framework exists to identify the at-risk group prior to infection. Metabolomics has the advantage of capturing the existing physiologic state, unobserved via current clinical measures. Furthermore, metabolomics profiling during acute disease can be influenced by confounding factors such as indications, medical treatments, and lifestyles. METHODS: We employed metabolomic profiling to cluster infection-free individuals and assessed their relationship with COVID severity and influenza incidence/recurrence. FINDINGS: We identified a metabolomic susceptibility endotype that was strongly associated with both severe COVID (ORICUadmission = 6.7, p-value = 1.2 × 10-08, ORmortality = 4.7, p-value = 1.6 × 10-04) and influenza (ORincidence = 2.9; p-values = 2.2 × 10-4, ßrecurrence = 1.03; p-value = 5.1 × 10-3). We observed similar severity associations when recapitulating this susceptibility endotype using metabolomics from individuals during and after acute COVID infection. We demonstrate the value of using metabolomic endotyping to identify a metabolically susceptible group for two-and potentially more-IDs that are driven by increases in specific amino acids, including microbial-related metabolites such as tryptophan, bile acids, histidine, polyamine, phenylalanine, and tyrosine metabolism, as well as carbohydrates involved in glycolysis. INTERPRETATIONS: These metabolites may be identified prior to infection to enable protective measures for these individuals. FUNDING: The Longitudinal EMR and Omics COVID-19 Cohort (LEOCC) and metabolomic profiling were supported by the National Heart, Lung, and Blood Institute and the Intramural Research Program of the National Center for Advancing Translational Sciences, National Institutes of Health.
