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.ImportanceUnderstanding 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.

Historically, glycomics has lagged behind other omics fields, owing to analytical challenges. However, recent technological advances are rapidly transforming the field, enabling a growing number of large-scale studies to harness the wealth of information encoded by glycans. In this Review, we provide an overview of the current state of large-scale glycomics and its role in understanding the functional importance of glycans. We discuss the main challenges in high-throughput glycoanalytical methods and highlight recent progress, with a particular emphasis on standardization and reproducibility. Special attention is given to the necessity of large, well-designed and ideally longitudinal and multicohort studies that use rigorous statistical approaches to uncover robust biological associations. Finally, we conclude with selected applications and perspectives, emphasizing the potential of large-scale glycomics to drive biomarker discovery and enhance the understanding of glycan-mediated biology.

Naïve T cell output from the thymus varies across the human lifespan and is a key determinant of health, differing between individuals by age, sex, and genetics. How thymic output is dynamically regulated early in life in response to initial microbial colonization remains unclear. We report longitudinal thymic output dynamics, measured as T cell receptor excision circles (TRECs), in 136 newborns from Stockholm, Sweden. Thymic output increases after birth following initial microbial colonization, peaking at 3-4 mo. Peak height correlates with plasma levels of RANKL and lymphotoxin-α and with a common genetic variant in the TCRD locus previously linked to adult thymopoiesis. B cell lymphopoiesis measured by KRECs reveals divergent dynamics between B and T cell branches of the adaptive immune system in early life. Findings are corroborated by thymic tissue analyses, in which local RANKL secretion correlates with medullary, but not cortical, epithelial cell numbers. These results illuminate the establishment of healthy immune-microbe interactions in early human life.

Microbial contamination in food processing remains a persistent and complex challenge. Understanding the sources, contributing factors, and control measures is essential for effective mitigation. In this study we employed a combination of metagenomic sequencing, targeted culturomics, and whole-genome sequencing of key isolates to gain a comprehensive view of bacterial dynamics and functional capabilities throughout a working shift in a beef slaughter and cutting facility. This allowed us to identify which bacteria are i) most prevalent in the clean facility before the start of the work, ii) able to establish themselves over time, and iii) detectable in the final product. We further generated a functional profile of the microbial community within the facility, with a particular focus on antimicrobial resistance and biofilm formation genes, and the presence of specific pathogens and spoilage organisms. Both culture-based and sequencing data showed that Psychrobacter and Pseudomonas strains present in the final product were also detected on the membrane skinner, a machine used to remove all the excess tissues from meat, and in the drains even after cleaning. We found a high number of genes involved in biofilm formation in Psychrobacter immobilis, a characteristic that may explain their biofilm capacity and the survival of this species during the cleaning process and persistence throughout the facility. Taken together, our findings suggest potential sources of contamination and highlight the advantages of integrating culture-dependent methods with high-throughput sequencing technologies to enhance microbial monitoring and control strategies in food production environments.

Emerging evidence suggests a bidirectional relationship between sleep and the gut microbiome. In this study, we explore the associations of sleep characteristics with lifestyle factors and gut microbiome composition in 6941 participants from the Lifelines Dutch Microbiome Project. We show that lower alpha diversity is associated with poorer sleep quality, later chronotype, and greater social jet lag, while beta diversity is linked to both sleep quality and social jet lag. Of the 137 bacterial species associated with sleep, 35.6% are validated in an independent cohort. Mediation analyses indicate that, while changes in species abundance are largely a consequence of sleep behavior, certain species may mediate diet's influence on sleep. For example, we find that Clostridia species UC5_1_1E11 and SGB14844 mediate the effect of coffee intake on social jet lag. These findings highlight the intricate relationship between diet, the gut microbiome, and sleep, suggesting the potential for microbiome-targeted interventions to improve sleep health.

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.

Early-life microbial exposures are essential for optimal development of human physiology. Yet, understanding of the human microbiome during pregnancy and childhood is still far from being complete. To identify knowledge gaps and establish research priorities, a multidisciplinary expert panel used the Delphi method for consensus development and conducted a literature search on early-life microbiome determinants. Responses from 55 researchers from an online survey were analyzed alongside keyword frequency from 20 501 publications. This approach enabled us to categorize existing evidence and highlight areas requiring investigation. While the main routes for mother-to-child bacterial transmission and their contributions to the newborn microbiome have been studied, many gaps remain. Priority areas include non-bacterial microbes, ecological principles of colonization, environmental and social influences, body sites beyond the gut, and factors affecting the maternal microbiome and its effects on the child's microbiome. Significance of factors such as hygiene habits, non-antibiotic medications, and pollution remains to be uncovered. Knowledge is also limited on postnatal microbial sharing via household contacts and shared environments (e.g. family members, peers) and the contribution of these pathways to microbiome assembly. We hope this report will guide and inspire future research into the early-life microbiome as a modifiable factor in reducing disease risk.

Emerging studies reveal that gut microbes can conjugate diverse amino acids to bile acids, known as microbially conjugated bile acids. However, their regulation and health effects remain unclear. Here, we analyzed early-life microbially conjugated bile acid patterns and their link to islet autoimmunity. We quantified 110 microbial bile acids in 303 stool samples collected longitudinally (3-36 months) from children who developed one or more islet autoantibodies and controls who remained autoantibody-negative. We identified distinct age-dependent trajectories of these bile acid amidates and correlated them with gut microbiome composition. We found that altered levels of ursodeoxycholic and deoxycholic acid conjugates were linked to islet autoimmunity as well as modulated monocyte activation in response to immunostimulatory lipopolysaccharide and Th17/Treg cell balance. These findings suggest that microbially conjugated bile acids influence immune development and type 1 diabetes risk.

Horizontal gene transfer (HGT) is a major driver of bacterial evolution, but its role in shaping the human gut microbiome over time remains poorly understood. Here, we present a longitudinal metagenomic analysis of 676 fecal samples from 338 individuals in the Lifelines-DEEP study collected ~4 years apart, using a newly developed workflow to detect recent HGT events from metagenome-assembled genomes. We identified 5,644 high-confidence HGT events occurring within the past ~10,000 years across 116 gut bacterial species. We find that species pairs with an HGT relationship were significantly more likely to maintain stable co-abundance relationships over the 4-year period, suggesting that gene exchange contributes to community stability. Notably, HGT and strain replacement act together to disseminate mobile genes in the population. Furthermore, our observation that an individual's mobile gene pool remains highly personalized and stable over time indicates that host lifestyles drive specific gene transfer. For example, proton pump inhibitor usage is linked to increased transfer of multidrug transporter genes. Our findings demonstrate, at the individual gut microbiome level, that HGT is both an integral and stabilizing force in the human gut ecosystem and an important mechanism for disseminating adaptive functions, underscoring HGT potential for tracking host lifestyle.

ObjectiveThe latest European Society of Gastroenterology Hepatology and Nutrition (ESPGHAN) criteria for celiac disease (CD) diagnosis reduced the requirement for a small intestinal biopsy but still, for most of the cases a small intestinal biopsy is required for a safe diagnosis: hence the attempt to identify serum biomarkers that could replace, in most of these latter cases, the requirement of the biopsy (what is called a "liquid biopsy"). The aim of this study is to identify a set of serum biomarkers able to differentiate celiac patients from age and human leukocyte antigen (HLA)-matched healthy controls.MethodsRelative concentration of 92 inflammation-linked proteins was examined in the sera of 50 children with CD compared with 50 HLA DQ2/8 and age-matched healthy controls born in genetically at-risk families, using proximity extension immunoassay technology (Olink Proteomics®) with the ProSeek Multiplex Inflammation panel.ResultsThree different multivariate analysis (Univariate and multivariate distribution analysis, random forest classification and linear discriminant analysis) localized a cluster of seven molecules (CASP8, CXCL9, NT-3, SIRT2, STAMBP, ST1A1, and TNFSF14) with a remarkable diagnostic potential, able to differentiate around 90% (95% confidence interval [CI]; 0.7-0.99) of CD patients from controls.ConclusionPatients with CD, compared to age- and HLA-matched healthy controls, show in their sera an increased expression of inflammatory molecules, involved in NF-κB cytokine signaling, cell apoptosis, and crypt proliferation pathways. A set of seven of these proteins can differentiate cases from controls with an accuracy higher than 90%. The implementation of this approach in clinical setting could in future facilitate a noninvasive and individualized approach for CD diagnosis.

Summary The human hippocampus is a critical brain region for learning, memory, and stress regulation, distinguished by its ability to sustain neurogenesis after birth. This plasticity is driven by hippocampal neural stem cells (NSCs), which generate new neurons and maintain circuit integrity, but are highly sensitive to environmental and pathological influences. Mechanistic insight into human hippocampal development and neurogenesis remains limited by the absence of physiologically relevant models. Here, we establish an optimized protocol to generate human induced pluripotent stem cell-derived hippocampal organoids that recapitulate key features of hippocampal development. These organoids maintain organized NSC niches, support ongoing neurogenesis, and generate hippocampus-specific cell types. Cellular, transcriptomic, and electrophysiological analyses confirm progressive neuronal maturation, synapse formation, and functional activity, highlighting the physiological relevance of the system. Using this model, we modeled excess prenatal glucocorticoid exposure with dexamethasone, which perturbed NSC dynamics by reducing proliferation and inducing a precocious quiescent-like state. RNA sequencing revealed downregulation of NSC activation genes and upregulation of quiescence- and autophagy-associated programs, suggesting that glucocorticoid signaling enforces an early transition toward quiescence. These findings reveal a mechanism by which excessive glucocorticoid exposure may impair hippocampal growth. Together, this study introduces a robust human hippocampal organoid platform for dissecting the regulation of hippocampal development and for modeling the impact of environmental stressors on human neurogenesis.

BackgroundHuman milk dynamically adapts its composition of immunoglobulins (Igs), cytokines, and other proteins as lactation progresses, influencing the infant's immune development and protection. Understanding how maternal factors, such as parity, influence the composition of human milk can provide strategies aimed at enhancing infant immune protection and reducing early-life infections. This study aims to investigate whether the immune composition of human milk differs based on parity, and if so, how these changes are related to infections in early life.MethodsThe study included 75 healthy mother-infant pairs from the MAMI cohort (Clinical Trial Registry NCT03552939), with milk samples collected from the same mothers at days 7 and 15 postpartum, during transitional lactation stage. Igs, cytokines, and adipokines were quantified using multiplex immunoassays and ELISA. A comparison was conducted between primiparous and multiparous mothers regarding both the overall and individual composition of immune components in human milk at each time point, as well as their evolution throughout the transitional phase.ResultsInfants from multiparous mothers recorded higher infection rates in early life than those of primiparous mothers. Some human milk immune components also differed by parity, with multiparous mothers exhibiting higher levels of IgA, total IgG, IgG1, IgG2, IgG3, IgE, and IL-23 at the beginning of the transitional phase (day 7), as well as higher IL-18 and IL-21 levels toward its end (day 15), compared to primiparous mothers. Additionally, the evolutionary pattern in levels of Igs, cytokines, and adipokines throughout the transitional milk stage also differed. Moreover, in multiparous mothers, higher levels of IgG, particularly IgG1 and IgG2 (day 7), as well as IL-18 and IL-22 (day 15), were associated with reduced infant infections, highlighting their potential protective role.ConclusionsParity is a maternal factor that influences some immune components of human milk during the transitional stage and may be linked to the susceptibility of infants to infections during the first 6 months of life. Future studies aimed at analyzing the impact of the parity factor, among others, on the progression of immune components in human milk may contribute to a better understanding and improved strategies for newborn health.

Diagnosing celiac disease (CD) via esophagogastroduodenoscopy (EGDS) is necessary when anti-transglutaminase (anti-TG) antibody levels are below 10× the upper limit of normal (ULN). This study evaluates patients with low anti-TG titers, particularly when endomysial antibodies (EMA) are negative. In this retrospective study (2022-2024), patients undergoing EGDS for suspected CD were grouped by EMA status: Group 1 (EMA negative) and Group 2 (EMA positive), with similar low anti-TG titers. Group 1 (N = 25) had a mean anti-TG titer of 1.86× ULN and villous atrophy (VA) in only 8% (2/25). Group 2 (N = 100) had VA in 35% (35/100), a 6.16-fold higher risk. Nonatrophic cases showed no significant histological and immunohistochemical differences. In conclusion, low-titer anti-TG with negative EMA indicates a low likelihood of VA. Most asymptomatic patients may not require immediate intervention but should be monitored. EGDS can be reserved to later stages if clinical suspicion persists.

Early-life gut microbiome-metabolome crosstalk plays a crucial role in maintaining host physiology. The microbially produced metabolites often convey effects on host health and physiology. This study investigates the gut metabolites, including short-chain fatty acids (SCFAs), bile acids (BAs), and polar metabolites, and their relationship to gut microbiota composition in a birth cohort of 670 children. Samples were collected at 2.5 (n = 272), 6 (n = 232), 14 (n = 289), and 30 months (n = 157) of age. We identified the trajectories of the fecal metabolome that relate to the maturation of the early-life gut microbiota. We found that prevalent gut microbial abundances were associated with microbial metabolite levels, particularly in 2.5-month-old infants. Here, the abundances of early colonizers, e.g., Bacteroides, Escherichia, and Bifidobacterium, were associated with microbial metabolites, especially secondary BAs, particularly in breastfed infants. Our results suggest that early-life gut microbiota associates with changes in metabolome composition, particularly BAs, which may have physiological implications.

Human development and physiology are fundamentally linked with the microbiome. This is particularly true during early life, a critical period for microbiome assembly and its impact on the host. Understanding microbial acquisition in early life is thus central to both our basic understanding of the human microbiome and strategies for disease prevention and treatment. Here, we review the historical approaches to categorize microbial transmission originating from the fields of infectious disease epidemiology and evolutionary biology and discuss how this lexicon has influenced our approach to studying the early-life microbiome, often leading to confusion and misinterpretation. We then present a conceptual framework to capture the multifaceted nature of human microbiome acquisition based on four key components: what, where, who, and when. We present ways these parameters may be assigned, with a particular focus on the 'transmitted strain' through metagenomics to capture these elements. We end with a discussion of approaches for implementing this framework toward defining each component of microbiome acquisition.

Human milk is important for infant development, but few large studies have comprehensively investigated milk composition. Here, we characterized human milk oligosaccharides (HMOs) and milk microbiota, their shaping factors, and their links to infant gut microbiota in the longitudinal Dutch Lifelines NEXT cohort. We measured 24 HMOs in 1,542 milk samples from 524 mothers at 0.5-6 months postpartum, profiled microbiota in milk and maternal and infant feces, genotyped mothers, and recorded 174 environmental, maternal, and infant characteristics. HMO concentrations were associated with maternal genetic loci (FUT2, FUT3/FUT6, ABO, and ST3GAL6), lactation stage, and subclinical mastitis. The human milk microbiota varied during lactation and with different feeding practices. Both HMOs and milk microbiota remained stable across multiple pregnancies in the same individual. Some milk bacteria were present in infant feces, but the milk and infant fecal microbiota diverged as the infant aged. Furthermore, individual HMOs were associated with infant fecal microbiota characteristics.

BackgroundMaternal nutritional status and dietary profile during pregnancy and lactation have short- and long-term impacts on offspring health. However, there is an incomplete understanding of the mechanisms behind these health effects. This study aims to assess the effect of maternal diet on the health of offspring by examining to unravel the impact of maternal diet on offspring health outcomes and evaluate the link between maternal nutrition, human milk immune components and neonatal colonisation as potential mechanisms that mediate the influence of maternal diet in the incidence of infant infections.MethodsTo assess this objective, we used two complementary approaches by which a clinical observational study based on the MAMI birth cohort guided a preclinical interventional analysis using a neonatal rat model of rotavirus-induced gastroenteritis.FindingsThe findings in both approaches demonstrated that a maternal diet rich in plant-based protein, fibre and polyunsaturated fatty acids, was linked to reduced incidence and severity of infections in offspring that would be mediated by beneficial modulation of the gut microbiota and immune system. Specifically, in the suckling rats, a predominant Th1 immune response and an enhanced virus-specific response were observed. Moreover, human milk IgA and rat milk IgG2c played a key protective role that complemented the effects of maternal diet.InterpretationThese results strengthen the importance of maternal diet during pregnancy and lactation supporting infant health.FundingThe study was supported by LaMarató-TV3 (DIM-2-ELI, ref. 2018-27/30-31).

Contaminant sequences of external origin complicate the study of host-associated viromes, particularly in low-biomass samples obtained through viral-like particle (VLP) enrichment. However, the prevalence and impact of external contaminants on low-biomass samples are under-studied. Here, we analyze 1321 gut virome samples and 55 negative controls (NCs) from four early-life virome studies. Virus sequences identified in NCs, termed negativeome, were used as a proxy for the contamination assessment. We show that 61% of samples share at least one identical strain with negativeome, likely representing external contamination. While the median abundance of contaminant strains in these samples is only 1%, it ranges from 0 to 99% and exceeds 10% in 11% of infant samples. We further demonstrate that contamination is largely study-specific and has a greater impact on infant samples than on maternal samples. Based on our results, we propose a contamination assessment method using a publicly available database of sequences detected in NCs and a strain-level decontamination strategy.

The assembly of the gut resistome in early life is key to infant health. Specific perinatal factors such as cesarean section (C-section), antibiotic exposure and lack of breastfeeding practices are detrimental to proper microbial development and increase the antimicrobial resistance genes (ARGs). Using 265 gut longitudinal metagenomes from 66 mother-infant pairs, we investigated how perinatal factors influence the acquisition and dynamics of ARGs during the first year of life. Our findings reveal that Bifidobacterium plays a crucial role in modulating the infant resistome, with its high relative abundance being associated with a lower ARG load. Exclusive breastfeeding during the first month of life accelerates the reduction of ARGs and ensures a lower resistome burden at six months. Moreover, early breastfeeding cessation correlates with a higher ARG load, underscoring its long-term influence on microbial resilience. Importantly, we identify exclusive breastfeeding as a key strategy to mitigate the impact of C-section delivery on the infant gut resistome, counteracting the early-life antibiotic exposure associated with this procedure and the resulting resistance acquisition. By promoting a microbiome enriched in Bifidobacterium, breastfeeding may help suppress ARG-carrying taxa, reducing the risk of resistance dissemination. Our findings underscore the importance of breastfeeding as a natural intervention to shape the infant microbiome and resistome. Supporting breastfeeding through public health policies could help limit the spread of antimicrobial resistance in early life.

More than a half of plasma proteins are N-glycosylated. Most of them are synthesized, glycosylated, and secreted to the bloodstream by liver and lymphoid tissues. While associations with N-glycosylation are implicated in the rising number of liver, cardiometabolic, and immune diseases, little is known about the genetic regulation of this process. Here, we performed the largest genome-wide association study of N-glycosylation of the blood plasma proteome in 10,000 individuals. We doubled the number of genetic loci known to be associated with blood N-glycosylation by identifying 16 novel loci and prioritizing 13 novel genes contributing to N-glycosylation. Among these were the GCKR, TRIB1, HP, SERPINA1 and CFH genes. These genes are predominantly expressed in the liver and show a previously unknown genetic link between plasma protein N-glycosylation, metabolic and liver diseases, and inflammatory response. By integrating glycomics, proteomics, transcriptomics, and genomics, we provide a resource that facilitates deeper exploration of disease pathogenesis and supports the discovery of glycan-based biomarkers.

Bifidobacterium species are well-established members of the human gut microbiome, particularly prominent during infancy, contributing to host health. Within this genus, Bifidobacterium longum ( BL. ) is a widespread species found in both infant and adult guts, known for its complexity and functional diversity among its known subspecies: BL. longum , BL. infantis and BL. suis . Here, using genomic and phylogenetic tools we propose a novel subspecies within the BL. species, Bifidobacterium longum subsp. nexti subspecies novel. We analyzed 435 BL. genomes using a polyphasic taxonomic approach comprising average nucleotide identity (ANI), digital DNA–DNA hybridization (dDDH), and pangenome analysis. We identified nine BL. strains, isolated from human infants and adults stool samples, as members of a distinct lineage within the BL. species. The type strain, LL6991, was isolated from the stool of a two-week-old Dutch infant in the Lifelines NEXT birth cohort. Phenotypically, BL. nexti exhibits a distinct morphological pattern, predominantly forming rod-shaped cells, often in chains with visible septa, contrasting with the Y-shaped morphology commonly observed for other BL. subspecies. Furthermore, BL. nexti demonstrates unique metabolic capabilities, including efficient utilization of fructose, and starch, carbohydrates not metabolized well by other tested BL. subspecies. This ability may be attributed to specific genes, such as a gene predicted to encode an extracellular amylopullulanase. This characterization expands the known diversity within the BL. species and provides insights into BL. nexti ’s unique adaptations and potential ecological roles within the human gut, especially in infants. Based on the consistent results from genotypic, phylogenetic, and phenotypic analyses, a novel subspecies with the name Bifidobacterium longum subsp. nexti , with type strain LL6991 (=NCCB 101085 =DSM 120337), is proposed.

Extremely preterm infants are at risk of immune-mediated complications such as infections and inflammatory conditions like bronchopulmonary dysplasia and necrotizing enterocolitis. Preterm infants are immunologically distinct from term infants at birth, but subsequently undergo adaptive postnatal changes resulting in immunological convergence during their first 3 months. Here, we performed a systems-level analysis of immune development in 72 preterm infants born as early as 22 weeks to investigate factors associated with variation. We find similar immune trajectories during early postnatal immune development but occurring more slowly in infants born at 22-24 weeks. Immune development showed a greater resemblance to that of term-born children in preterm infants fed mother's own milk compared to donor milk. This developmental normalization was manifested by NK cell development and was not explained by differences in microbial colonization between feeding groups, possibly suggesting direct effects of bioactive milk molecules on developing immune cells in extremely preterm infants.

Mobile genetic elements (MGE) are critical yet understudied determinants of gut microbiome composition. In this secondary analysis of a randomized controlled trial (NCT06030713), we characterized the gut virome and plasmidome in 195 samples from 28 mother-infant dyads delivered by cesarean section. Infant mobilome increases in richness over the first 6 postnatal weeks, demonstrating high individual-specificity and temporal stability, establishing a personal persistent mobilome. Formula-fed infants exhibit greater mobilome richness than breastfed infants, with plasmid composition being influenced by antibiotic exposure and birth weight. Plasmids constitute a reservoir of antibiotic resistance genes (ARG), with around 5% of infant gut plasmid taxonomic units carrying ARG. Notably, ARG profiles do not differ with antibiotic exposure at birth. Mother-infant sharing of viral and plasmid strains primarily occurs after 6 months of age. Overall, our integrative analysis offers insights into the dynamics, modulation, and origin of MGE in the developing gut microbiome.

Abstract Horizontal gene transfer (HGT) is a major driver of bacterial evolution, but its role in shaping the human gut microbiome over time remains poorly understood. Here, we present a longitudinal metagenomic analysis of 676 fecal samples from 338 individuals collected ~4 years apart, using a newly developed workflow to detect recent HGT events from metagenome-assembled genomes. We identified 5,644 high-confidence HGT events occurring within the past ~10,000 years across 116 gut bacterial species. We find that species pairs with a HGT relationship were significantly more likely to maintain stable ecological relationships over the 4-year period, suggesting that gene exchange contributes to ecological stability. Notably, HGT and strain replacement act together to disseminate mobile genes in the population. Furthermore, our observation that an individual's mobile gene pool remains highly personalized and stable over time indicates that host lifestyles drive specific gene transfer. For example, proton pump inhibitor usage was linked to increased transfer of multidrug transporter genes. Our findings demonstrate, at individual gut microbiome level, that HGT is both an integral and stabilizing force in the human gut ecosystem and an important mechanism for disseminating adaptive functions, underscoring their potential for tracking host lifestyle.

The human gut harbors thousands of microbial species, each exhibiting significant inter-individual genetic variability. Although many studies have associated microbial relative abundances with human-health-related phenotypes, the substantial intraspecies genetic variability of gut microbes has not yet been comprehensively considered, limiting the potential of linking such genetic traits with host conditions. Here, we analyzed 32,152 metagenomes from 94 microbiome studies across the globe to investigate the human microbiome intraspecies genetic diversity. We reconstructed 583 species-specific phylogenies and linked them to geographic information and species' horizontal transmissibility. We identified 484 microbial-strain-level associations with 241 host phenotypes, encompassing human anthropometric factors, biochemical measurements, diseases, and lifestyle. We observed a higher prevalence of a Ruminococcus gnavus clade in nonagenarians correlated with distinct plasma bile acid profiles and a melanoma and prostate-cancer-associated Collinsella clade. Our large-scale intraspecies genetic analysis highlights the relevance of strain diversity as it relates to human health.

BackgroundExtracorporeal photopheresis (ECP) has emerged as a prophylactic and therapeutic immunomodulatory option for managing acute rejection in heart transplants (HTx). The underlying mechanisms through which ECP exerts its immunomodulatory effects remain under investigation. Regulatory T cells (Treg) are a heterogeneous subset of immune lymphocytes that ensure the maintenance of tissue homeostasis, avoiding graft rejection. The transcription factor forkhead box protein 3 (FoxP3) is an essential molecular marker of Treg, acting as a "master regulator" of their genesis, stability, and functions. No study has investigated whether ECP impacts FoxP3 expression and its highly suppressive variants containing the exon 2 (FoxP3-E2), particularly in HTx.MethodsIn the current study, we recruited 14 HTx participants who had undergone ECP therapy. We explored the effect of in vivo ECP on CD4 + FoxP3 + Treg frequency and in vitro suppressive function in 8 HTx participants before (T0) and after 3 (T1), 6 (T2), and 12 (T3) mo of treatment. As a control group, we included 4 HTx individuals who had not undergone ECP therapy.ResultsWe found that ECP increases the frequency of CD4 + FoxP3 + Treg subset with highly suppressive phenotype, including CD4 + FoxP3-E2 + Treg. At functional levels, we observed that ECP treatment in HTx individuals effectively improves Treg suppressive ability in controlling the proliferation of autologous conventional CD4 + T lymphocytes.ConclusionsOur findings collectively suggest that ECP exerts its immunomodulatory effects in HTx individuals by positively impacting the frequency and regulatory function of the FoxP3 + Treg compartment.

BackgroundMaternal smoking and foetal exposure to nicotine and other harmful chemicals in utero remains a serious public health issue with little knowledge about the underlying genetics and consequences of maternal smoking in ageing individuals. Here, we investigated the epidemiology and genomic architecture of maternal smoking in a middle-aged population and compare the results to effects observed in the developing foetus.MethodsIn the current project, we included 351,562 participants from the UK Biobank (UKB) and estimated exposure to maternal smoking status during pregnancy through self-reporting from the UKB participants about the mother's smoking status around their birth. In addition, we analysed 64 foetal liver transcriptomic expression datasets collected from women seeking elective pregnancy terminations. Foetal maternal smoking exposure was confirmed through measurement of foetal plasma cotinine levels.FindingsFoetal exposure to maternal smoking had a greater impact on males than females, with more differentially expressed genes in liver tissue (3313 vs. 1163) and higher liver pathway activation. In the UKB, maternal smoking exposure was linked to an unhealthy lifestyle, lower education, and liver damage. In a genome-wide analysis in the UKB, we leveraged the shared genetic basis between affected offspring and their mothers and identified five genome-wide significant regions. We found a low heritability of the trait (∼4%) and implicated several disease-related genes in a transcriptome-wide association study. Maternal smoking increased all-cause mortality risk (Hazard ratio and 95% CI: 1.10 [1.04; 1.16], P = 4.04 × 10-4), which was attenuated in non-smoking males.InterpretationAlthough male foetuses are more affected than females by maternal smoking in pregnancy, this effect was largely reduced in middle-aged individuals. Importantly, our results highlight that the overall 10% increased mortality due to maternal smoking in pregnancy was greatly attenuated in non-smokers. This study demonstrates the importance of campaigns promoting offspring smoking prevention in families where the parent(s) smoke.FundingFunding for this project was provided by the University of Aberdeen, the Science Initiative Panel of the Institute of Medical Science, the UK Medical Research Council, the Seventh Framework Programme of the European Union under Grant Agreement 212885 (REEF), NHS Grampian Endowments grants and the European Commission Horizon Europe research grant Agreement 101094099 (INITIALISE).

Human cortical development is a complex process involving the proliferation, differentiation, and migration of progenitor cells, all coordinated within a dynamic extracellular matrix (ECM). ECM plays a crucial role in guiding these processes, yet its specific contributions and the implications of its dysregulation in neurodevelopmental disorders (NDDs) remain underexplored. In this study, we conducted a meta-analysis of single-cell RNA sequencing (scRNA-seq) data from 37 donors, gestational weeks (GWs) 8 to 26 across six independent studies to elucidate cell type-specific matrisome gene expression signatures and their dynamics in the developing human cortex. Our analysis identified distinct matrisome gene signatures across various cell types, with significant temporal changes during cortical development. Notably, a substantial proportion of matrisome genes are associated with NDDs, exhibiting cell type, temporal and disease specificity. These findings highlight the critical role of cell type-specific matrisome regulation in cortical development and its potential involvement in NDD pathogenesis. This study provides a comprehensive map of cell type-specific matrisome signatures in the developing human cortex and highlights the importance of ECM in both normal development and the pathogenesis of NDDs.

Metagenomics has revealed the incredible diversity of phages within the human gut. However, very few of these phages have been subjected to in-depth experimental characterization. One promising method of obtaining novel phages for experimental characterization is through induction of the prophages integrated into the genomes of cultured gut bacteria. Here, we developed a bioinformatic approach to prophage identification that builds on prophage genomic properties, existing prophage-detecting software, and publicly available virome sequencing data. We applied our approach to 22 strains of bacteria belonging to the genus Faecalibacterium, resulting in identification of 15 candidate prophages, and validated the approach by demonstrating the activity of five prophages from four of the strains. The genomes of three active phages were identical or similar to those of known phages, while the other two active phages were not represented in the Viral RefSeq database. Four of the active phages possessed a diversity-generating retroelement (DGR), and one retroelement had two variable regions. DGRs of two phages were active at the time of the induction experiments, as evidenced by nucleotide variation in sequencing reads. We also predicted that the host range of two active phages may include multiple bacterial species. Finally, we noted that four phages were less prevalent in the metagenomes of inflammatory bowel disease patients compared to a general population cohort, a difference mainly explained by differences in the abundance of the host bacteria. Our study highlights the utility of prophage identification and induction for unraveling phage molecular mechanisms and ecological interactions.IMPORTANCEWhile hundreds of thousands of phage genomes have been discovered in metagenomics studies, only a few of these phages have been characterized experimentally. Here, we explore phage characterization through bioinformatic identification of prophages in genomes of cultured bacteria, followed by prophage induction. Using this approach, we detect the activity of five prophages in four strains of commensal gut bacteria Faecalibacterium. We further note that four of the prophages possess diversity-generating retroelements implicated in rapid mutation of phage genome loci associated with phage-host and phage-environment interactions and analyze the intricate patterns of retroelement activity. Our study highlights the potential of prophage characterization for elucidating complex molecular mechanisms employed by the phages.

ScopeHuman milk (HM) is rich in bioactive compounds and essential nutrients. While research has focused on lipids, minerals, immune markers, microbiota, and oligosaccharides, specific metabolites are less studied. This study uses targeted metabolomics to identify and quantify metabolites in HM and explores the impact of perinatal and dietary factors on the metabolomic profile.Methods and resultsIn a cross-sectional study of 123 healthy lactating women, HM samples were collected up to 1 month postpartum and analyzed using the Biocrates MxP Quant 500 kit. Maternal and neonatal clinical, anthropometric, and nutritional data were collected. A total of 432 metabolites were quantified and categorized into 20 groups. The metabolomic profiles formed three distinct clusters, primarily driven by triglyceride concentration differences. Docosahexaenoic acid (DHA) levels were higher in HM from mothers with vaginal delivery compared to C-section births and differences in hexoses were found between exclusive and mixed-feeding practices. Maternal diets rich in lipids and animal proteins were associated with elevated amino acids, sphingolipids, and glycosyl-ceramides.ConclusionThe HM metabolome was grouped into three clusters influenced by delivery mode, lactation practices, and maternal diet. This comprehensive analysis opens new avenues to explore HM composition and offers valuable insights for future dietary interventions aimed at modulating HM.

Human brain development depends on the coordinated interaction of diverse cell types and extracellular matrix (ECM) components, which are essential for proper neurogenesis and cortical organization. Epidemiological and animal studies have demonstrated that maternal immune activation (MIA) disrupts brain development, leading to impaired neurogenesis and increased risk of neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD) and schizophrenia. However, the cellular and molecular mechanisms by which MIA impacts human cortical development remain poorly understood. Here we introduce a 3D ex vivo culture system, termed ‘cerebroids,’ derived from dorsolateral prefrontal cortex of human fetal brain tissue, which faithfully preserves key developmental processes, along with critical cellular diversity and structural integrity of the developing human cortex. Using this platform, we show that IL-17A, a cytokine strongly implicated in NDDs, induces premature cortical folding, increases cortical thickness, and accelerates neurogenesis and neuronal maturation. Transcriptomic and proteomic analyses reveal significant dysregulation of ECM-related pathways, including the upregulation of proteoglycans such as brevican and versican. Notably, treatment with the anti-inflammatory agent parthenolide, an inhibitor of NF-κB and HDAC1 pathways, reverses IL-17A-induced cortical abnormalities, restoring normal cortical thickness, folding, and neurogenesis. These findings provide valuable insights into how IL-17A disrupts human cortical development during MIA, advancing our understanding of NDD-associated structural cortical alterations.

Environmental contamination complicates the study of low-biomass microbial communities like the human gut virome. In 1,321 early-life gut viromes and 55 negative controls (NCs) from four datasets, we identified viral contaminants and their prevalence across studies. Samples and NCs were indistinguishable in genomic and ecological features, with 71.5% of samples sharing at least one identical strain with NCs. This work demonstrates the efficacy of strain-aware decontamination for preserving biological signals.

BackgroundThe plasma metabolome reflects the physiological state of various biological processes and can serve as a proxy for disease risk. Plasma metabolite variation, influenced by genetic and epigenetic mechanisms, can also affect the cellular microenvironment and blood cell epigenetics. The interplay between the plasma metabolome and the blood cell epigenome remains elusive. In this study, we performed an epigenome-wide association study (EWAS) of 1183 plasma metabolites in 693 participants from the LifeLines-DEEP cohort and investigated the causal relationships in DNA methylation-metabolite associations using bidirectional Mendelian randomization and mediation analysis.ResultsAfter rigorously adjusting for potential confounders, including genetics, we identified five robust associations between two plasma metabolites (L-serine and glycine) and three CpG sites located in two independent genomic regions (cg14476101 and cg16246545 in PHGDH and cg02711608 in SLC1A5) at a false discovery rate of less than 0.05. Further analysis revealed a complex bidirectional relationship between plasma glycine/serine levels and DNA methylation. Moreover, we observed a strong mediating role of DNA methylation in the effect of glycine/serine on the expression of their metabolism/transport genes, with the proportion of the mediated effect ranging from 11.8 to 54.3%. This result was also replicated in an independent population-based cohort, the Rotterdam Study. To validate our findings, we conducted in vitro cell studies which confirmed the mediating role of DNA methylation in the regulation of PHGDH gene expression.ConclusionsOur findings reveal a potential feedback mechanism in which glycine and serine regulate gene expression through DNA methylation.

Pregnant women undergoing a cesarean section (CS) typically receive antibiotics prior to skin incision to prevent infections. To investigate if the timing of antibiotics influences the infant gut microbiome, we conducted a randomized controlled trial (NCT06030713) in women delivering via a scheduled CS who received antibiotics either before skin incision or after umbilical cord clamping. We performed a longitudinal analysis on 172 samples from 28 infants at 8 post-birth time points and a cross-sectional analysis at 1 month in 79 infants from 3 cohorts. Although no significant associations with bacterial composition, metabolic pathways, short-chain fatty acids, and bile acids were found, we observed subtle differences between the groups at the bacterial strain level and in the load of antibiotic resistance genes. Rather, feeding mode was a predominant and defining factor impacting infant microbial composition. In conclusion, antibiotic administration during CS has only limited effects on the early-life gut microbiome.

The molecular mechanisms that govern differential T cell development from CD4+CD25-conventional T (Tconv) into CD4+CD25+ forkhead-box-P3+ (FoxP3+) inducible regulatory T (iTreg) cells remain unclear. Herein, we investigated the relative contribution of protein kinase A (PKA) in this process. Mechanistically, we found that PKA controlled the efficiency of human iTreg cell generation through the expression of different FoxP3 splicing variants containing or not the exon 2. We found that transient PKA inhibition reduced the recruitment of cAMP-responsive element-binding protein (CREB) on regulatory regions of the FoxP3 gene, a condition that is associated with an impaired acquisition of their suppressive capacity in vitro. To corroborate our findings in a human model of autoimmunity, we measured CREB phosphorylation and FoxP3 levels in iTreg cells from treatment-naïve relapsing-remitting (RR)-multiple sclerosis (MS) subjects. Interestingly, both phospho-CREB and FoxP3 induction directly correlated and were significantly reduced in RR-MS patients, suggesting a previously unknown mechanism involved in the induction and function of human iTreg cells.

Potential celiac disease (PCD) is a clinical condition characterised by the presence of a positive CD-specific serology and a normal intestinal architecture. Asymptomatic PCD patients are generally advised to continue on a gluten-containing diet (GCD), but long-term risks of this approach have never been explored. In the present study, we aimed to investigate nutritional and autoimmune complications possibly developing overtime in a cohort of asymptomatic PCD children on a GCD. We compared children's parameters of growth, nutritional status, and autoimmunity between the time of diagnosis and on the occasion of their last medical check, after a long-term gluten-containing diet. Altogether, we collected data from 171 PCD children with a mean follow-up time of 3 years (range 0.35-15.3 years). During follow-up, although patients did not reduce their amount of daily gluten intake, their anti-tissue transglutaminase (anti-TG2) antibodies spontaneously and significantly decreased. Most parameters analysed had not changed during follow-up (height centile, ferritin, albumin, cholesterol, calcium, alkaline phosphatase, parathormone, and vitamin D) or even improved significantly (weight and BMI centile, haemoglobin, blood iron, HDL, glycaemia, and HbA1C, p < 0.05), always remaining within the limit of normality. Equally, autoantibodies for other concomitant autoimmune disorders did not increase overtime. Similar results were obtained excluding from analysis patients who had stopped producing anti-TG2 and those with a follow-up time < 3 years. Our pilot study has provided reassuring results regarding the maintenance of a gluten-containing diet in asymptomatic PCD children, even when long-term follow-up was considered.

Metabolites from feces provide important insights into the functionality of the gut microbiome. As immediate freezing is not always feasible in gut microbiome studies, there is a need for sampling protocols that provide the stability of the fecal metabolome and microbiome at room temperature (RT). Here, we investigated the stability of various metabolites and the microbiome (16S rRNA) in feces collected in 95% ethanol (EtOH) and commercially available sample collection kits with specific preservatives OMNImet•GUT/OMNIgene•GUT. To simulate field-collection scenarios, the samples were stored at different temperatures at varying durations (24 h + 4 °C, 24 h RT, 36 h RT, 48 h RT, and 7 days RT) and compared to aliquots immediately frozen at -80 °C. We applied several targeted and untargeted metabolomics platforms to measure lipids, polar metabolites, endocannabinoids, short-chain fatty acids (SCFAs), and bile acids (BAs). We found that SCFAs in the nonstabilized samples increased over time, while a stable profile was recorded in sample aliquots stored in 95% EtOH and OMNImet•GUT. When comparing the metabolite levels between aliquots stored at room temperature and at +4 °C, we detected several changes in microbial metabolites, including multiple BAs and SCFAs. Taken together, we found that storing samples at RT and stabilizing them in 95% EtOH yielded metabolomic results comparable to those from flash freezing. We also found that the overall composition of the microbiome did not vary significantly between different storage types. However, notable differences were observed in the α diversity. Altogether, the stability of the metabolome and microbiome in 95% EtOH provided results similar to those of the validated commercial collection kits OMNImet•GUT and OMNIgene•GUT, respectively.

Encounters with pathogens and other molecules can imprint long-lasting effects on our immune system, influencing future physiological outcomes. Given the wide range of microbes to which humans are exposed, their collective impact on health is not fully understood. To explore relations between exposures and biological aging and inflammation, we profiled an antibody-binding repertoire against 2,815 microbial, viral, and environmental peptides in a population cohort of 1,443 participants. Utilizing antibody-binding as a proxy for past exposures, we investigated their impact on biological aging, cell composition, and inflammation. Immune response against cytomegalovirus (CMV), rhinovirus, and gut bacteria relates with telomere length. Single-cell expression measurements identified an effect of CMV infection on the transcriptional landscape of subpopulations of CD8 and CD4 T-cells. This examination of the relationship between microbial exposures and biological aging and inflammation highlights a role for chronic infections (CMV and Epstein-Barr virus) and common pathogens (rhinoviruses and adenovirus C).

BackgroundPrenatal exposure to environmental contaminants is a significant health concern because it has the potential to interfere with host metabolism, leading to adverse health effects in early childhood and later in life. Growing evidence suggests that genetic and environmental factors, as well as their interactions, play a significant role in the development of autoimmune diseases.ObjectiveIn this study, we hypothesized that prenatal exposure to environmental contaminants impacts cord serum metabolome and contributes to the development of autoimmune diseases.MethodsWe selected cord serum samples from All Babies in Southeast Sweden (ABIS) general population cohort, from infants who later developed one or more autoimmune-mediated and inflammatory diseases: celiac disease (CD), Crohn's disease (IBD), hypothyroidism (HT), juvenile idiopathic arthritis (JIA), and type 1 diabetes (T1D) (all cases, N = 62), along with matched controls (N = 268). Using integrated exposomics and metabolomics mass spectrometry (MS) based platforms, we determined the levels of environmental contaminants and metabolites.ResultsDifferences in exposure levels were found between the controls and those who later developed various diseases. High contaminant exposure levels were associated with changes in metabolome, including amino acids and free fatty acids. Specifically, we identified marked associations between metabolite profiles and exposure levels of deoxynivalenol (DON), bisphenol S (BPS), and specific per- and polyfluorinated substances (PFAS).Impact statementAbnormal metabolism is a common feature preceding several autoimmune and inflammatory diseases. However, few studies compared common and specific metabolic patterns preceding these diseases. Here we hypothesized that exposure to environmental contaminants impacts cord serum metabolome, which may contribute to the development of autoimmune diseases. We found differences in exposure levels between the controls and those who later developed various diseases, and importantly, on the metabolic changes associated with the exposures. High contaminant exposure levels were associated with specific changes in metabolome. Our study suggests that prenatal exposure to specific environmental contaminants alters the cord serum metabolomes, which, in turn, might increase the risk of various immune-mediated diseases.

Background and objectivesThe role of B cells in the pathogenic events leading to relapsing multiple sclerosis (R-MS) has only been recently elucidated. A pivotal step in defining this role has been provided by therapeutic efficacy of anti-CD20 monoclonal antibodies. Indeed, treatment with anti-CD20 can also alter number and function of other immune cells not directly expressing CD20 on their cell surface, whose activities can contribute to unknown aspects influencing therapeutic efficacy. We examined the phenotype and function of cytotoxic lymphocytes and Epstein-Barr virus (EBV)-specific immune responses in people with R-MS before and after ocrelizumab treatment.MethodsIn this prospective study, we collected blood samples from people with R-MS (n = 41) before and 6 and 12 months after initiating ocrelizumab to assess the immune phenotype and the indirect impact on cytotoxic functions of CD8+ T and NK cells. In addition, we evaluated the specific anti-EBV proliferative responses of both CD8+ T and NK lymphocytes as surrogate markers of anti-EBV activity.ResultsWe observed that while ocrelizumab depleted circulating B cells, it also reduced the expression of activation and migratory markers on both CD8+ T and NK cells as well as their in vitro cytotoxic activity. A comparable pattern in the modulation of immune molecules by ocrelizumab was observed in cytotoxic cells even when patients with R-MS were divided into groups based on their prior disease-modifying treatment. These effects were accompanied by a significant and selective reduction of CD8+ T-cell proliferation in response to EBV antigenic peptides.DiscussionTaken together, our findings suggest that ocrelizumab-while depleting B cells-affects the cytotoxic function of CD8+ and NK cells, whose reduced cross-activity against myelin antigens might also contribute to its therapeutic efficacy during MS.

Early development of the gut ecosystem is crucial for lifelong health. While infant gut bacterial communities have been studied extensively, the infant gut virome remains under-explored. To study the development of the infant gut virome over time and the factors that shape it, we longitudinally assess the composition of gut viruses and their bacterial hosts in 30 women during and after pregnancy and in their 32 infants during their first year of life. Using shotgun metagenomic sequencing applied to dsDNA extracted from Virus-Like Particles (VLPs) and bacteria, we generate 205 VLP metaviromes and 322 total metagenomes. With this data, we show that while the maternal gut virome composition remains stable during late pregnancy and after birth, the infant gut virome is dynamic in the first year of life. Notably, infant gut viromes contain a higher abundance of active temperate phages compared to maternal gut viromes, which decreases over the first year of life. Moreover, we show that the feeding mode and place of delivery influence the gut virome composition of infants. Lastly, we provide evidence of co-transmission of viral and bacterial strains from mothers to infants, demonstrating that infants acquire some of their virome from their mother's gut.

The lack of standardization in the methods of DNA extraction from fecal samples represents the major source of experimental variation in the microbiome research field. In this study, we aimed to compare the metagenomic profiles and microbiome-phenotype associations obtained by applying two commercially available DNA extraction kits: the AllPrep DNA/RNA Mini Kit (APK) and the QIAamp Fast DNA Stool Mini Kit (FSK). Using metagenomic sequencing data available from 745 paired fecal samples from two independent population cohorts, Lifelines-DEEP (LLD, n = 292) and the 500 Functional Genomics project (500FG, n = 453), we confirmed significant differences in DNA yield and the recovered microbial communities between protocols, with the APK method resulting in a higher DNA concentration and microbial diversity. Further, we observed a massive difference in bacterial relative abundances at species-level between the APK and the FSK protocols, with > 75% of species differentially abundant between protocols in both cohorts. Specifically, comparison with a standard mock community revealed that the APK method provided higher accuracy in the recovery of microbial relative abundances, with the absence of a bead-beating step in the FSK protocol causing an underrepresentation of gram-positive bacteria. This heterogeneity in the recovered microbial composition led to remarkable differences in the association with anthropometric and lifestyle phenotypes. The results of this study further reinforce that the choice of DNA extraction method impacts the metagenomic profile of human gut microbiota and highlight the importance of harmonizing protocols in microbiome studies.

Expression quantitative trait loci (eQTL) offer insights into the regulatory mechanisms of trait-associated variants, but their effects often rely on contexts that are unknown or unmeasured. We introduce PICALO, a method for hidden variable inference of eQTL contexts. PICALO identifies and disentangles technical from biological context in heterogeneous blood and brain bulk eQTL datasets. These contexts are biologically informative and reproducible, outperforming cell counts or expression-based principal components. Furthermore, we show that RNA quality and cell type proportions interact with thousands of eQTLs. Knowledge of hidden eQTL contexts may aid in the inference of functional mechanisms underlying disease variants.

Aims/hypothesisType 1 diabetes is an autoimmune disorder that is characterised by destruction of pancreatic beta cells by autoreactive T lymphocytes. Although islet autoantibodies (AAb) are an indicator of disease progression, specific immune biomarkers that can be used as target molecules to halt development of type 1 diabetes have not been discovered. Soluble immune checkpoint molecules (sICM) play a pivotal role in counteracting excessive lymphocyte responses, but their role in type 1 diabetes is unexplored. In this longitudinal study, we measured sICM levels in AAb-positive (AAb+) children to identify molecules related to type 1 diabetes progression.MethodsWe measured the levels of 14 sICM in the sera of AAb+ children (n=57) compared to those with recent-onset type 1 diabetes (n=79) and healthy children (n=44), obtained from two cohorts. AAb+ children were followed up and divided based on their progression to type 1 diabetes (AAbP) or not (AAbNP) (if they lost islet autoimmunity and did not develop disease in subsequent years). sICM were also measured in the sample taken at the visit closest to disease onset in AAbP children.ResultsWe found that AAb+ children had a distinct sICM profile compared with healthy children and those with recent-onset type 1 diabetes. In addition, AAb+ children who progressed to type 1 diabetes (AAbP) had higher sICM concentrations than non-progressors (AAbNP). Further, sICM levels decreased in AAbP children close to disease onset. Application of Cox regression models highlighted that high concentrations of soluble programmed cell death protein 1 (sPD-1) are associated with type 1 diabetes progression (HR 1.71; 95% CI 1.16, 2.51; p=0.007).Conclusions/interpretationThis study reveals an sICM profile that is dysregulated during the preclinical stage of type 1 diabetes, and identifies sPD-1 as a pathophysiologically-relevant molecule that is associated with disease progression, offering a potential target for early interventions in autoimmune diabetes.

Although the impact of host genetics on gut microbial diversity and the abundance of specific taxa is well established1-6, little is known about how host genetics regulates the genetic diversity of gut microorganisms. Here we conducted a meta-analysis of associations between human genetic variation and gut microbial structural variation in 9,015 individuals from four Dutch cohorts. Strikingly, the presence rate of a structural variation segment in Faecalibacterium prausnitzii that harbours an N-acetylgalactosamine (GalNAc) utilization gene cluster is higher in individuals who secrete the type A oligosaccharide antigen terminating in GalNAc, a feature that is jointly determined by human ABO and FUT2 genotypes, and we could replicate this association in a Tanzanian cohort. In vitro experiments demonstrated that GalNAc can be used as the sole carbohydrate source for F. prausnitzii strains that carry the GalNAc-metabolizing pathway. Further in silico and in vitro studies demonstrated that other ABO-associated species can also utilize GalNAc, particularly Collinsella aerofaciens. The GalNAc utilization genes are also associated with the host's cardiometabolic health, particularly in individuals with mucosal A-antigen. Together, the findings of our study demonstrate that genetic associations across the human genome and bacterial metagenome can provide functional insights into the reciprocal host-microbiome relationship.

The gut microbiome has important roles in host metabolism and immunity, and microbial dysbiosis affects human physiology and health. Maternal immunity and microbial metabolites during pregnancy, microbial transfer during birth, and transfer of immune factors, microorganisms and metabolites via breastfeeding provide critical sources of early-life microbial and immune training, with important consequences for human health. Only a few studies have directly examined the interactions between the gut microbiome and the immune system during pregnancy, and the subsequent effect on offspring development. In this Review, we aim to describe how the maternal microbiome shapes overall pregnancy-associated maternal, fetal and early neonatal immune systems, focusing on the existing evidence and highlighting current gaps to promote further research.

Prenatal exposure to environmental contaminants is a significant health concern because it has the potential to interfere with host metabolism, leading to adverse health effects in early childhood and later in life. Growing evidence suggests that genetic and environmental factors, as well as their interactions, play a significant role in the development of autoimmune diseases. In this study, we hypothesized that prenatal exposure to environmental contaminants impacts cord serum metabolome and contributes to the development of autoimmune diseases. We selected cord serum samples from All Babies in Southeast Sweden (ABIS) general population cohort, from infants who later developed one or more autoimmune-mediated and inflammatory diseases: celiac disease (CD), Crohn’s disease (IBD), hypothyroidism (HT), juvenile idiopathic arthritis (JIA), and type 1 diabetes (T1D) (all cases, N = 62), along with matched controls (N = 268). Using integrated exposomics and metabolomics mass spectrometry (MS) based platforms, we determined the levels of contaminants and metabolites. Differences in exposure levels were found between the controls and those who later developed various diseases. High contaminant exposure levels were associated with changes in metabolome, including amino acids and free fatty acids. Specifically, we identified marked associations between metabolite levels and exposure levels of deoxynivalenol (DON), bisphenol S (BPS), and specific per- and polyfluorinated substances (PFAS). Our study suggests that prenatal exposure to specific environmental contaminants alters the cord serum metabolomes, which, in turn, might increase the risk of various immune-mediated disease later in life.

Aims/hypothesisAppearance of multiple islet cell autoantibodies in early life is indicative of future progression to overt type 1 diabetes, however, at varying rates. Here, we aimed to study whether distinct metabolic patterns could be identified in rapid progressors (RP, disease manifestation within 18 months after the initial seroconversion to autoantibody positivity) vs. slow progressors (SP, disease manifestation at 60 months or later from the appearance of the first autoantibody).MethodsLongitudinal samples were collected from RP (n=25) and SP (n=41) groups at the ages of 3, 6, 12, 18, 24, or ≥ 36 months. We performed a comprehensive metabolomics study, analyzing both polar metabolites and lipids. The sample series included a total of 239 samples for lipidomics and 213 for polar metabolites.ResultsWe observed that metabolites mediated by gut microbiome, such as those involved in tryptophan metabolism, were the main discriminators between RP and SP. The study identified specific circulating molecules and pathways, including amino acid (threonine), sugar derivatives (hexose), and quinic acid that may define rapid vs. slow progression to type 1 diabetes. However, the circulating lipidome did not appear to play a major role in differentiating between RP and SP.Conclusion/interpretationOur study suggests that a distinct metabolic profile is linked with the type 1 diabetes progression. The identification of specific metabolites and pathways that differentiate RP from SP may have implications for early intervention strategies to delay the development of type 1 diabetes.

Recent advancements in omics technologies have generated a wealth of biological data. Integrating these data within mathematical models is essential to fully leverage their potential. Genome-scale metabolic models (GEMs) provide a robust framework for studying complex biological systems. GEMs have significantly contributed to our understanding of human metabolism, including the intrinsic relationship between the gut microbiome and the host metabolism. In this review, we highlight the contributions of GEMs and discuss the critical challenges that must be overcome to ensure their reproducibility and enhance their prediction accuracy, particularly in the context of precision medicine. We also explore the role of machine learning in addressing these challenges within GEMs. The integration of omics data with GEMs has the potential to lead to new insights, and to advance our understanding of molecular mechanisms in human health and disease.

Phage-displayed immunoprecipitation sequencing (PhIP-seq) has enabled high-throughput profiling of human antibody repertoires. However, a comprehensive overview of environmental and genetic determinants shaping human adaptive immunity is lacking. In this study, we investigated the effects of genetic, environmental, and intrinsic factors on the variation in human antibody repertoires. We characterized serological antibody repertoires against 344,000 peptides using PhIP-seq libraries from a wide range of microbial and environmental antigens in 1,443 participants from a population cohort. We detected individual-specificity, temporal consistency, and co-housing similarities in antibody repertoires. Genetic analyses showed the involvement of the HLA, IGHV, and FUT2 gene regions in antibody-bound peptide reactivity. Furthermore, we uncovered associations between phenotypic factors (including age, cell counts, sex, smoking behavior, and allergies, among others) and particular antibody-bound peptides. Our results indicate that human antibody epitope repertoires are shaped by both genetics and environmental exposures and highlight specific signatures of distinct phenotypes and genotypes.