A1 Refereed original research article in a scientific journal
Early-life proteomic and microbiome features signal obesity risk across 26 years of follow-up; 
Authors: Ahrens, Angelica P.; Dias, Raquel; Hyötyläinen, Tuulia; White, Pär Anderson; Orešič, Matej; Triplett, Eric W.; Ludvigsson, Johnny
Editors: van der Hooft Justin J. J.
Publisher: American Society for Microbiology
Publication year: 2026
Journal: MSystems
Article number: 01424-25
eISSN: 2379-5077
DOI: https://doi.org/10.1128/msystems.01424-25
Publication's open availability at the time of reporting: Open Access
Publication channel's open availability : Open Access publication channel
Web address : https://doi.org/10.1128/msystems.01424-25
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/526538645
Self-archived copy's licence: CC BY
Self-archived copy's version: Publisher`s PDF
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.
Keywords:
ANGPTL4, bile acids, Carbohydrates, environmental toxins, FGF19, Metabolic disease, metabolome
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Funding information in the publication:
We acknowledge the fundamental contributions of our ABIS participants and their families. We are grateful to Hanna Karlsson and Austeja Rutkauskaite for help with ABIS data and delivery of samples.
This work was made possible by funding from Barndiabetesfonden (Swedish Child Diabetes Foundation); Swedish Council for Working Life and Social Research; Swedish Research Council; Östgöta Brandstodsbolag; Medical Research Council of Southeast Sweden; JDRF-Wallenberg Foundation; ALF County Council, Östergötland; and Joanna Cocozza Foundation. This work was also funded by the “Inflammation in human early life: targeting impacts on life-course health” (INITIALISE) consortium funded by the Horizon Europe Program of the European Union under Grant Agreement 101094099.