Eric W. Triplett

Childhood obesity is rising globally. Yet, few studies have examined the microbiome and proteome in early childhood in relation to this outcome, and most are cross-sectional by design. Early-life factors in the ABIS birth cohort ( n = 16,683) were associated with obesity up to age 26 (mean follow-up 25.3 years, range 23.7–26.5 years): psychosocial stressors, smoking, infections, and diet in the first year. We assessed biomarkers, including cord blood metabolome ( n = 290) and proteome ( n = 358), by liquid chromatography, mass spectrometry, and Olink. Gut microbial composition at age one ( n = 1,743) was assessed using stool samples and 16S rRNA sequencing. In this prospective longitudinal cohort study, significant differences were found in infants with future obesity, including elevated angiopoietin-like 4 (ANGPTL4), follistatin, and hepatocyte growth factor (independently of maternal weight) and reduced isocaproic acid, tryptophan, and oleic acid, with prenatal mediation. Akkermansia , asaccharolytic bacteria ( Phascolarctobacterium and Senegalimassiliensia ), and equol-producers ( Adlercreutzia and Slackia ) were depleted. Machine learning models selecting 40 most predictive features showed long-term prediction from birth proteomics and bacterial taxa at age one (area under the curve [AUC] = 0.83 ± .05, n = 1,877) and additional metrics, for example, parental and child body mass index in the first 8 years (AUC = 0.89 ± .02, n = 1,877), suggesting durable biological encoding. Proteomic markers across folds included fibroblast growth factor 19, ANGPTL4, sulfotransferase family 2A member 1, and interleukin 20. These findings suggest clinically relevant biomarkers indicating early-life regulation of bile acid metabolism, lipid storage vs. oxidation, and immune–metabolic signaling and pathways to prospectively prevent childhood- and adult-onset obesity across a 26-year predictive gap. IMPORTANCE: Understanding the origins of obesity is critical for developing preventive strategies, and early life represents a particularly sensitive window. This study leverages a large, general-population cohort with prospectively collected data, including parental body mass index (BMI), cord blood proteomics, and the gut microbiome at age one, linked to obesity outcomes over 26 years. Using integrated machine learning models, we show that in addition to parental BMI, specific proteomic and microbial markers present in infancy can predict long-term obesity risk, highlighting the role of early metabolic programming. Several key markers point to bile acid signaling as a mechanism connecting early microbiome development with fat accumulation and insulin regulation. By identifying these early-life predictors long before obesity manifests, these results provide new insights into intergenerational risk and suggest measurable targets for preventing obesity and related metabolic disorders from the earliest stages of life.

Cold seeps are widespread deep‐sea ecosystems sustained by methane‐rich fluid seepage and host dense chemosynthesis‐based biological communities. In 2016, a methane‐driven chemosynthetic system was discovered on the Rio Grande Cone, in the Western South Atlantic Ocean, but the structure and drivers of its prokaryotic communities remained poorly understood. Here, we investigated archaeal and bacterial communities associated with deep‐sea sediments across three geographic areas (A, C, and E) and a vertical gradient of up to 18 m below the seafloor, encompassing sediment layers within and below the sulfate–methane transition zone (SMTZ). Community composition was assessed using high‐throughput sequencing of the 16S rRNA gene (V3‐V4 region), processed into amplicon sequence variants (ASVs), and related to local geochemical gradients using multivariate analyses. To disentangle the ecological responses of methane‐cycling taxa from the broader microbiome, the prokaryotic community was analyzed by contrasting the ANME‐SRB consortium with the remaining archaeal and bacterial taxa. Both groups exhibited significant spatial structuring across areas and sediment layers. Methane concentration and depth were the dominant drivers shaping both ANME‐SRB and the remaining prokaryotic community, with conductivity further influencing the latter. Core microbiome analysis revealed a small number of widespread taxa accounting for a large proportion of total community abundance, including an atypical dominance of the archaeal genus Sulfophobococcus . Functional predictions indicated a predominance of sulfur‐ and nitrogen‐related metabolisms, with no clear depth‐structured metabolic profiles across the SMTZ. Overall, our results highlight how local geochemical gradients shape both methane‐cycling and non‐methane‐cycling prokaryotic assemblages in a poorly explored South Atlantic cold seep, providing a baseline for future genome‐resolved investigations of microbial functioning in this system.

Type 1 diabetes (T1D) is increasing globally, yet the earliest biological determinants remain poorly defined, particularly in general population studies. We studied the Swedish population-based ABIS birth cohort (n = 16,683) to identify early-life risk factors. Olink proteomic analysis (n = 286 controls, n = 146 cases) of inflammatory signals at birth shows differential abundance years before diagnosis (mean age 12.6 years), with proteins enriched for neutrophil migration, cytotoxicity, extracellular matrix remodeling, and immune regulation. Several markers remain significant in spite of prenatal and perinatal factors including family history of diabetes, and are associated with differences in compounds like stearic acid, lysine, glutamine, and persistent, environmental toxicants perfluorodecylethanoic acid and perfluorooctane sulfonate (PFOS). Using machine learning, we identify a protein subset that predicts T1D with high accuracy (AUC = 0.89 ± 0.02), independently of HLA genetic risk. These findings suggest that innate and tissue-remodeling pathways are perturbed at birth, possibly reflecting early β-cell vulnerability. Identifying these disruptions at birth with a non-invasive method opens a window for prevention, protecting β-cells before the inflammatory attack on islets begins.

Citrus greening disease, or Huanglongbing (HLB), has caused devastating losses to citrus production in Florida, with yields declining by over 90% since 2005. Despite extensive efforts, no sustainable solution has been widely effective. Here, transgenic ‘Hamlin’ sweet orange lines engineered to constitutively express the Arabidopsis NPR1 ( AtNPR1 ) gene, a key regulator of systemic acquired resistance, are evaluated for health and environmental risks. These citrus lines exhibit strong HLB tolerance, with reduced disease symptoms, sustained fruit production, and no apparent negative phenotypic abnormalities. Comprehensive risk assessment reveals minimal exposure, health, or environmental risk. The AtNPR1 protein is: (1) barely detectable in fruit, (2) rapidly degraded in simulated gastrointestinal fluids, and (3) not similar to known allergens or toxins. Whole‐genome sequencing identified the T‐DNA insertion sites as heterozygous in either chromosome 1 or 6, with no disruptions in known fruit‐producing genes. PCR markers were developed for rapid line identification. The selected lines are currently in a small field trial under high HLB pressure and continue to exhibit low visual HLB symptoms and positive horticultural traits. These findings support the initial requirements for regulatory approval of these transgenic citrus varieties, offering a promising strategy for sustainable citrus production.

Longitudinal study of the microbial dysbiosis preceding celiac disease (CD) is needed, particularly in the first several years of life. Within the Environmental Determinants of Diabetes in the Young (TEDDY) multi-national prospective cohort study, a case-cohort study of 306 CD cases (i.e., seroconverting by 48 months of age), with controls matched 2:1 by site, gender, and time of birth, was assessed. Temporal microbiome case-control dynamics were modelled by 16S rRNA analysis of monthly sequential stool samples taken from age three months up to age four (or until the development of CD). Significant differences were identified across time, including key taxa that break down gluten and influence inflammation, all before the development of autoantibodies. Key bacterial associations with environmental factors such as diet were assessed using detailed longitudinal nutrient intake and diary data, along with genetic variants conferring high CD risk.

The goal of the TEDDY (The Environmental Determinants of Diabetes in the Young) study is to elucidate factors leading to the initiation of islet autoimmunity (first primary outcome) and those related to progression to type 1 diabetes mellitus (T1DM; second primary outcome). This Review outlines the key findings so far, particularly related to the first primary outcome. The background, history and organization of the study are discussed. Recruitment and follow-up (from age 4 months to 15 years) of 8,667 children showed high retention and compliance. End points of the presence of autoantibodies against insulin, GAD65, IA-2 and ZnT8 revealed the HLA-associated early appearance of insulin autoantibodies (1–3 years of age) and the later appearance of GAD65 autoantibodies. Competing autoantibodies against tissue transglutaminase (marking coeliac disease autoimmunity) also appeared early (2–4 years). Genetic and environmental factors, including enterovirus infection and gastroenteritis, support mechanistic differences underlying one phenotype of autoimmunity against insulin and another against GAD65. Infant growth and both probiotics and high protein intake affect the two phenotypes differently, as do serious life events during pregnancy. As the end of the TEDDY sampling phase is approaching, major omics approaches are in progress to further dissect the mechanisms that might explain the two possible endotypes of T1DM.

The standard use of antibiotics in newborns to empirically treat early-onset sepsis can adversely affect the neonatal gut microbiome, with potential long-term health impacts. Research into the escalating issue of antimicrobial resistance in preterm infants and antibiotic practices in neonatal intensive care units is limited. A deeper understanding of the effects of early antibiotic intervention on antibiotic resistance in preterm infants is crucial. This retrospective study employed metagenomic sequencing to evaluate antibiotic resistance genes (ARGs) in the meconium and subsequent stool samples of preterm infants enrolled in the Routine Early Antibiotic Use in Symptomatic Preterm Neonates study. Microbial metagenomics was conducted using a subset of fecal samples from 30 preterm infants for taxonomic profiling and ARG identification. All preterm infants exhibited ARGs, with 175 unique ARGs identified, predominantly associated with beta-lactam, tetracycline, and aminoglycoside resistance. Notably, 23% of ARGs was found in preterm infants without direct or intrapartum antibiotic exposure. Post-natal antibiotic exposure increases beta-lactam/tetracycline resistance while altering mechanisms that aid bacteria in withstanding antibiotic pressure. Microbial profiling revealed 774 bacterial species, with antibiotic-naive infants showing higher alpha diversity ( P = 0.005) in their microbiota and resistome compared with treated infants, suggesting a more complex ecosystem. High ARG prevalence in preterm infants was observed irrespective of direct antibiotic exposure and intensifies with age. Prolonged membrane ruptures and maternal antibiotic use during gestation and delivery are linked to alterations in the preterm infant resistome and microbiome, which are pivotal in shaping the ARG profiles in the neonatal gut. This study is registered with ClinicalTrials.gov as NCT02784821 . IMPORTANCE: A high burden of antibiotic resistance in preterm infants poses significant challenges to neonatal health. The presence of antibiotic resistance genes, along with alterations in signaling, energy production, and metabolic mechanisms, complicates treatment strategies for preterm infants, heightening the risk of ineffective therapy and exacerbating outcomes for these vulnerable neonates. Despite not receiving direct antibiotic treatment, preterm infants exhibit a concerning prevalence of antibiotic-resistant bacteria. This underscores the complex interplay of broader influences, including maternal antibiotic exposure during and beyond pregnancy and gestational complications like prolonged membrane ruptures. Urgent action, including cautious antibiotic practices and enhanced antenatal care, is imperative to protect neonatal health and counter the escalating threat of antimicrobial resistance in this vulnerable population.