Early life bacteria and sibling exposure associate with restoration of the infant gut microbiome after cesarean section

Domain: biology
Published: 2026-03-30
Editorial outcome: minor_revision

Abstract
Long-term gut microbiome perturbation following Cesarean section (CS) delivery has been associated with an increased risk of developing childhood asthma. Whether such CS-associated microbiome composition can be modulated by environmental exposures or ecological interactions, and thereby mitigate disease risk, is unclear. In the COPSAC 2010 birth cohort (N = 700), we develop a restoration score quantifying the degree to which the 1-year gut microbiome resembled that of vaginally delivered infants. We discover predictions of a restoration score in the 1-week gut microbiome. In addition, having older siblings is linked to a higher restoration score, mediated by increased abundances of restoration-associated bacteria. The restoration score, including association with delivery mode, older siblings and later asthma as well as early bacterial drivers, is successfully replicated in the independent Canadian birth cohort, CHILD. These insights suggest that specific early-life bacteria and sibling exposure may support microbiome restoration and confer protective effects against asthma risk.

Introduction
A Cesarean section (CS) can be a life-saving intervention when medically indicated, but can potentially also lead to short-term and long-term health consequences for women and their children1. CS is one of the most important factors determining an infant’s developing gut microbiome, and in turn, possibly the development and differentiation of their immune system2. Such perturbation of the initial infant gut colonization may be involved in the increased risk for diseases in childhood and later in life observed in CS-born individuals3,4.

The healthy fetus is considered sterile5 and the newborn child is colonized by the first microbes during and immediately after birth6–8. When comparing the gut microbiota composition, infants born by CS have gut microbiomes that resemble those found on the mother’s skin surface, while vaginally born infants harbor gut microbiomes more similar to the adult fecal and vaginal microbiome9,10. In babies delivered by CS, previous studies have reported disrupted colonization of maternal Bacteroides strains, and more prevalent colonization by opportunistic pathogens associated with the hospital environment. A low-Bacteroides profile in the infant gut microbiome is considered a hallmark of the microbiome perturbation in CS-born infants11,12. However, low-Bacteroides profiles can also be found in vaginally delivered infants13–15, which are usually used as a reference for a healthy infant gut microbiome. Such early microbiomes of vaginally delivered infants, which resembles the CS-perturbed profiles, could be caused by other perturbers such as intrapartum antibiotics16,17.

Microbiota maturation can be described by age-dependent successional stages: a “mature” microbiota contains certain taxa that are common for that child’s age group, while an “immature” or delayed microbiota resembles that of a younger child18. The microbiome composition of infants matures through three distinct, conserved stages of development, with the genus predominance shifting from Escherichia over Bifidobacterium to Bacteroides19. This ecological succession eventually stabilizes during childhood regardless of early perturbations such as birth by CS. However, such early perturbation may have long-lasting functional effects on immune development. Gut microbiota assembly and immune system development are intimately linked in early life20,21. The establishment of immune tolerance by introducing microbial antigens happens in the first few weeks of life22,23. Delayed maturation caused by early perturbation might result in a loss of tolerance and a pro-inflammatory response, which has been associated with increased risk of food allergy24 and asthma25.

The dynamics of the early life gut microbiota has been a key research area26,27, the modifiability provides a potential to promote health throughout life28. Potential approaches include pre- and probiotics29, vaginal seeding30,31 and fecal microbiota transplantation (FMT)32. Maternal FMT was reported to have the most dramatic effect on microbiota composition, shifting the composition fully to that of the vaginally born infants8. However, a CS-perturbed gut microbiota may also naturally recover, a process which may be influenced by environmental and intrinsic ecological factors in the microbiome.

Several environmental factors have been reported to promote maturation of the gut microbiome, including breastfeeding33, a rural living environment34, and having older siblings at home35. Breastfeeding is recognized as one of the most influential drivers of gut microbiome composition during infancy, which provides a dynamic source of nutrition that delivers live microbes, immunoglobulins, and bioactive compounds essential for shaping the infant gut microbiome36. Besides, Infants from rural areas often exhibit a more diverse gut microbiome and early colonization of Bacteroides, which promotes further microbiome maturation37,38. Lastly, infants with older siblings tend to have a more mature gut microbiota by the age of one year, and this maturity is linked to a higher diversity of gut bacteria, which potentially mediates the protective effects of siblings in relation to allergies35,39.

Previously, we described the link between CS and asthma risk which may be partially mediated via a prolonged perturbation of the infant gut microbiome in the 700 children from the Copenhagen Prospective Studies on Asthma in Childhood 2010 (COPSAC 2010) prospective birth cohort17. Only children who retained a CS-like gut microbiome composition at 1 year had increased risk of later asthma independent of the magnitude of their initial perturbation. Conversely, children whose gut microbiota was restored by 1 year, resembling those born vaginally, had a similar, lower, risk of asthma. In this follow-up study, we describe early-life environmental and ecological predictors of such restoration in the 1-year gut microbiome with the aim to enhance our understanding of the natural microbiome restoration process in the context of CS-associated risk of asthma.

Results
Characteristics of the COPSAC 2010 cohort
Information on maternal and child characteristics were obtained during scheduled visits to the COPSAC clinic. We observed differences in gestational age, parental age, maternal BMI, breastfeeding duration, and hospitalization after birth according to delivery mode (Supplementary Data 1). We derived a 1-year restoration score based on previous work17, which is found to be negatively associated with asthma risk at 6 years of age. This restoration score is to characterize the restoration of the 1-year gut microbiome - a higher score indicates that a child’s 1-year gut microbiome resembles that of vaginally delivered infants (Fig.1A, Fig.1B). Compared to vaginal delivery, children born by CS had a significant lower restoration score (model estimate = -0.32, 95% Confidence Interval (CI) [-0.51,-0.13], p = 8e-04). In the subgroup analysis (Fig.1C), children born by CS had a lower restoration score compared to vaginal delivery without antibiotics exposure (-0.36[-0.55,-0.16], p = 3e-04). Notably, children born by vaginal delivery whose mother received antibiotics at birth also had a lower restoration score compared to those without antibiotics exposure (-0.23[-0.48, 0.02], p = 0.07), and with a score comparable to the CS-born infants (0.13[-0.19,0.45], p = 0.43). There was no detectable differences observed between the planned and emergency procedures (0.18[-0.20,0.57], p = 0.35).

Gut microbiome diversity at 1 week associates with 1-year restoration score
Children with higher 1-year restoration scores had a higher gut microbial α-diversity at early time points (Supplementary Data 2). At age 1 week, higher Shannon and Faith’s Phylogenetic Diversity (PD) diversity were observed in children with higher 1-year restoration score (Shannon: 0.01[0.001, 0.02], p = 0.02, PD: 0.003[0, 0.006], p = 0.03). At 1 month of age, the same directionality was observed, but it was not significant for any of the indices. In the CS stratum (n=151), higher PD at 1 week of age was associated (0.006[0,0.01], p = 0.04) with higher 1-year restoration score. For other measures, similar estimates were observed but they were not statistically significant (Supplementary Data 2).

The gut microbiota composition differed between children with high and low 1-year restoration scores (above vs below median values) (Fig.2) using PERMANOVA analysis. From the PCoA plots ordinated across all three timepoints, children with low 1-year restoration scores appeared to have different compositions compared to those with high 1-year restoration scores. The compositional difference of having a high vs low restoration score was most obvious at age 1-week (F = 4.9, R2 = 0.9%, p = 0.001) compared to age 1-month (F = 2.2, R2 = 0.4%, p = 0.08).In the CS stratum, there were no detectable differences in microbial composition between high and low 1-year restoration score groups at 1 week and 1 month (Supplementary Fig. 1).

Early gut taxa associate with 1-year restoration score
We next investigated individual taxa at 1 week and 1 month to determine which members of the microbiota were main drivers of the observed compositional differences using the LIMMA model (Fig. 3). At 1 week of age, children with higher restoration scores had higher relative abundances of Sutterella wadsworthensis (log fold change (logFC) = 0.12, FDR adjusted p-value (q) = 0.03) and Neglecta timonensis (logFC = 0.04, q = 0.03, Fig. 3A). On the other hand, we found that Clostridium perfringens at 1 week was negatively associated with the restoration score and was the most differentially abundant species found (logFC = -0.29, q = 0.01), followed by Enterobacter aerogenes (logFC = -0.1, q = 0.03) and Actinomyces sp. (logFC = -0.05, q =0.049). Compared to the gut microbiome at 1 week of age, the 1-month gut microbiome was less associated with the 1-year restoration score. We observed associations between the relative abundances of species at 1 month and restoration scores in the same direction as at 1 week, but they were not FDR significant.

In the CS stratum, higher relative abundances of Bifidobacterium longum and Staphylococcus simiae at 1 week and only Streptococcus equinus at 1 month were associated with higher restoration score at 1 year, but none were FDR significant (Fig.3B).

Environmental factors associate with 1-year restoration score
We next examined the relationship between early life environmental factors and the 1-year restoration score (Supplementary Data 3). We found that having older siblings was associated with a higher restoration score in the full cohort (Full cohort, 0.36 [0.21;0.51], q = 2e-04). Interestingly, the age of the youngest older sibling was negatively associated with the restoration score; i.e. the closer in age the older sibling was the higher the restoration score was at 1 year (Full cohort, -0.14 [-0.23;-0.05], q = 0.04).

To identify whether specific factors would influence the restoration process differently for children born by CS, we performed this subgroup analysis (Supplementary Data 3). In the CS stratum, having older siblings, having cats, and being born in a rural area were positively associated with the restoration score while being breastfed for more than 6 months was negatively associated with the restoration score, but none were FDR significant.

Multivariable models on the early life gut microbiome and environmental factors predict the 1-year restoration score
Multivariable analyses were used to identify species and environmental factors jointly associated with the 1-year restoration score in the full cohort (Fig.4). We employed three sparse Partial Least Squares (sPLS) models on only the 1-week gut microbiome, only environmental factors, and combined 1-week gut microbiome and environmental factors as input features, respectively. These models were evaluated based on the correlations between their cross-validated predictions and 1-year restoration scores (model on only gut microbiome, Spearman rho 0.21, p = 3e-06; model on only environmental factors, 0.16, p = 7e-04; model on combined gut microbiome and environmental factors, 0.24, p = 2e-07). The gut microbiome at 1 week was enriched for Bifidobacterium longum, Parabacteroides distasonis, Sutterella wadsworthensis, and Neglecta timonensis in children with higher restoration scores at 1 year, while Clostridium perfringens was depleted. Of these, Bifidobacterium longum was the most abundant and prevalent (see Fig 3), while Parabacteroides distasonis and Sutterella wadsworthensis were less so. Neglecta timonensis was only present in few samples (prevalence 12.4%), but had a strong association with the 1-year restoration score. Clostridium perfringens contributed the most to the model with a strong negative loading towards the restoration score. In the model with environmental factors, only maternal antibiotics at birth and having older siblings had negative and positive loadings with the 1-year restoration score, respectively. The model on combined 1-week gut microbiome and environmental factors showed a better performance than each individual model, predicting the 1-year restoration score with 7 variables selected, including the same five species selected by the model on only the gut microbiome, and Veillonella parvula and having older siblings.

At 1 month of age, the models had moderate performance on predicting restoration scores (Supplementary Fig. 2, model on gut microbiome, Spearman rho 0.10, p = 0.023; model on environmental factors, 0.15, p = 5e-04; model on combined gut microbiome and environmental factors, 0.16, p = 4e-04). The combined model’s cross-validated predictions had a higher correlation with 1-year restoration scores than each individual model, but the inclusion of the gut microbiome didn’t improve the model much compared to the model on only environmental factors. In this combined model, 3 environmental factors and 14 species were selected (Supplementary Fig. 2). Of all the selected variables, having older siblings and Clostridium perfringens were also selected in the 1-week combined model with the same directionality.

In the CS stratum, the comparatively best model was on the combined 1 week gut microbiome and environmental factors, the Spearman rho between the cross-validated predictions and the restorations scores was 0.19, p = 0.064 (Supplementary Fig. 3). However, the models on the 1 month gut microbiome and environmental factors in the CS stratum were not able to predict the restoration scores, with Spearman rho correlations around 0. The overall better performance of models on combined gut microbiome and environmental factors suggested that both might contribute to the restoration process of the perturbed gut microbiome.

Having older siblings facilitates CS restoration through gut microbiome development
We further investigated whether the species associated with having siblings were also associated with the 1-year restoration score, by comparing the logFC of the species abundances between the two outcomes (Fig.3, Fig.5, Supplementary Data 4).

At 1 week, 85 species showed a similar logFC association for both having older siblings and the 1-year restoration score (Fig.5A, 85 points, grey and blue, were in the first and third quadrants at 1 week). Among them, 5 were significantly associated with both outcomes (Fig.5B). There was a higher abundance of Bifidobacterium longum and Bifidobacterium pseudocatenulatum in the children with siblings and a high restoration score; and lower abundance of Actinomyces bowdenii, Clostridium tarantellae, and Clostridium perfringens in the children without siblings and with a low restoration score. At 1 month of age, 4 species were significantly associated with both outcomes in the same direction. At 1 year of age, the time point where the restoration score was defined, 63 species showed significant consistent positive or negative association with both outcomes. To determine whether the number of taxa that were significant for both predictors was greater than expected by chance, and whether the direction of their associations was concordant by chance, we calculated empirical p-values based on permutation tests. Both of the empirical p-values were below 0.05, indicating that the overlap and concordant direction are highly unlikely by chance.

In the CS stratum, 87 species, and 73 species showed consistent associations with having older siblings and the restoration score, at 1 week and 1 month time point, respectively, but less significant compared to the associations in the full cohort (Supplementary Fig. 4, Supplementary Data 5). Nevertheless, higher abundance of Bifidobacterium longum was still found positively associated with having older siblings and higher restoration score. We also found the same directionality at 1 year of age in the CS stratum, which further suggests a positive role of having older siblings on the restoration of the gut microbiome by such very early influences. The number of taxa associated with both predictors and concordant direction in the CS stratum was significant in the permutation test.

Having identified older siblings as a potential protective factor that may facilitate the restoration of a CS-perturbed gut microbiome, we next considered these factors together: We performed a mediation analysis to investigate the possible mediating role of the 1-week gut microbiome between having older siblings and the restoration of the gut microbiome by 1 year. Here, we used the cross-validated predictions from the sPLS model of the 1-week gut microbiome to predict the 1 year restoration score and expressed it as a 1-week microbial score representing the degree to which a child’s 1-week microbiome looked like it would be restored by 1 year of age (Supplementary Fig. 5). After adjusting for delivery, the results showed a significant mediation effect of older siblings on the 1-year restoration score through the 1-week microbial score (model estimate = 0.002[0, 0.005], p = 0.004), but also a strong direct effect of older siblings on the 1-year restoration score (model estimate = 0.02[0.009, 0.03], p < 2e-16). The indirect pathway accounted for a portion of 11.2% of the total effect (model estimate = 0.11[0.04,0.26], p = 0.004). This suggests that older siblings may contribute to the restoration partially through influencing the very early gut microbiome.

Early gut taxa and environmental factors associated with restoration scores in the vaginal stratum
While the restoration score was conceived in the context of CS delivery, we also wanted to investigate its dynamics in vaginally delivered children, where low restoration scores would indicate that other factors than CS may have contributed to having a CS-like composition at 1 year. We separately investigated the early gut microbiome associated with the 1-year restoration scores in the vaginal stratum (Supplementary Fig. 6), and perinatal events during vaginal delivery in addition to the previously described prenatal and postnatal factors (Supplementary Data 7). At 1 week of age, children with higher 1-year restoration scores had higher relative abundances of Sutterella wadsworthensis (logFC = 0.16, q = 0.02) and Neglecta timonensis (logFC = 0.06, q = 0.02) as we saw in the full cohort. In contrast, Veillonella parvula (logFC = -0.22, q = 0.01), Actinomyces sp. (logFC = -0.08, q = 0.006), and Howardella ureilytica (logFC = -0.05, q = 0.01) were associated with lower restoration scores at 1 year of age in the vaginal stratum. Having older siblings was significantly associated with higher 1-year restoration scores as we saw in the CS stratum (0.02[0.01,0.03], q = 2e-03). In contrast, we found antibiotics exposure to mothers and children at birth and meconium-stained amniotic fluid exposure to be negatively associated with the 1-year restoration score, however not FDR significant.

Validation of the 1-year restoration score on the CHILD cohort
We next sought to validate our findings in an independent dataset. The CHILD study is the largest prospective longitudinal birth cohort study in Canada40. We observed similar differences in gestational age, parental age, maternal BMI, and hospitalization after birth according to delivery mode in the CHILD study. On the other hand, compared to the COPSAC 2010 cohort, CS-born children had higher antibiotics exposure at 3 months and shorter breastfeeding duration in the CHILD study (Supplementary Data 1).

We applied the sPLS model trained on the COPSAC 2010 cohort17 on the CHILD cohort’s 1-year samples (n=325) to create a restoration score (Fig. 6A). This 1-year restoration score was, like in COPSAC 2010, negatively associated with delivery by CS and positively associated with older siblings in the CHILD cohort (Fig. 6B). Additionally, the CHILD 1-year restoration score was associated with reduced asthma risk at 5 years in both univariate and adjusted logistic regression models (OR 0.63[0.44, 0.87], p = 0.005, aOR 0.47 [0.26, 0.82], p = 0.0084, Fig. 6B). This replicates the results in our previous study17 and is consistent with the hypothesis that an appropriate restoration of the gut microbiota could mitigate the increased asthma risk associated with gut microbial changes due to CS delivery.

To identify species at early time points associated with the 1-year restoration score, we trained an sPLS model on the gut microbiome at 3 months in the CHILD cohort, to predict the 1-year restoration score(Fig. 6C). Clostridium perfringens was selected in the model with the highest negative loading as we saw in the COPSAC 2010 cohort, while Bacteroides sp. had the highest positive loading in the model, followed by Bacteroides uniforms, Bacteroides caccae, Bifidobacterium sp., Bacteroides fragilis, and Bacteroides ovatus. Having older siblings was positively associated with the 1-year restoration score, which supports the idea that older siblings promote the restoration of a CS-perturbed gut microbiome(Fig. 6B).

Methods
The COPSAC 2010 cohort
Ethics
The study was conducted in accordance with the guiding principles of the Declaration of Helsinki and was approved by the Local Ethics Committee (H-B-2008-093) and the Danish Data Protection Agency (2015-41-3696). Both parents gave oral and written informed consent before enrolment.

Study population
The COPSAC 2010 cohort is a population-based mother-child cohort of 700 children and their families, recruited in pregnancy and followed prospectively at the COPSAC research unit. The children were followed by COPSAC study physicians and nurses collecting all biosamples, clinical measurements and diagnoses during clinical visits scheduled at 1 week, 1, 3, 6, 12, 18, 24, 30, and 36 months, thereafter yearly until the age of 6 and again at age 8 and 10 years.

Study endpoints
This study is a follow-up of our prior study17, investigating the gut microbiome development and asthma risk after birth by CS in the COPSAC 2010 mother-child cohort.

In the present study, we focused on the association between early environmental factors and fecal microbiota composition at 1 week and 1 month, using a 1-year restoration score as the outcome measure. This restoration score was first introduced in our previous paper as a CS score, calculated by constructing a cross-validated sparse partial least squares (sPLS) model on gut microbial composition at 1 year of age predicting delivery mode (vaginal/CS)17. The model identified the gut microbial composition at 1 year of age most associated with CS delivery. By reversing the CS microbial score, we define this restoration score as our outcome measure to characterize the restoration of 1-year gut microbiome. Thus, a higher restoration score means a child’s microbiome resembles being born vaginally, while a low restoration score means that a child retains a CS-like gut microbiota composition. This score was used as either a continuous score or dichotomized (above and below median value).

Fecal sample collection and sequencing
All children with fecal samples collected and characterized by 16S rRNA sequencing (requiring at least 2000 reads) at any of the three time points of 1 week (n = 552), 1 month (n = 607), and 1 year (n = 625) were included in the analyses. Fecal samples were collected either at the research clinic or by the parents at home using detailed instructions. Each sample arrived at the laboratory within 24 hours and was mixed on arrival with 1 ml of 10% (v/v) glycerol broth (SSI, Copenhagen, Denmark) and frozen at −80°C. DNA was extracted using the PowerMag Soil DNA Isolation Kit (MO-BIO Laboratories, Inc., Carlsberg, CA, USA) on an epMotion 5075 (Eppendorf), amplified using a two-step polymerase chain reaction (PCR) with 515F and 806R primers flanking the V4 region of 16S rRNA gene, and sequenced using the v2 kit (paired-end 250–base pair reads) on the MiSeq platform (Illumina Inc., San Diego, CA). A full description of the laboratory workflow has been described previously65.

Bioinformatic processing
Raw fastq files were demultiplexed using the MiSeq controller software prior to downstream analysis. As described in previous study69, the primers and adaptors in sequencing reads were removed using Cutadapt70. The determination of amplicon sequence variants (ASVs) was performed on QIIME2 Core 2020.11 platform71 using Amplicon Denoising Algorithm 2 (DADA2) analysis pipelines72. The resulting ASV sequences were annotated using the AnnotIEM73 pipeline (v.1.3), which combines sequence alignment against four databases: EzBioCloud74 (r. 2018-05), NCBI75 (v. refseq 202), RDP76 (v.11.5), and Silva77 (v. 138SSU) followed by a high confidence selection of best probable annotation73. Genus annotations were correctly annotated for all genera in the mock community, and 15/20 was annotated to the correct species. Therefore, species annotations should be considered putative.

Maternal and child characteristics
Information on antibiotics in pregnancy, antibiotics to mother and child at birth, antibiotics to children during the first year of life, gestational age, age when starting daycare, maternal age, maternal BMI, having older sibling at home, age of the youngest sibling, physician-diagnosed asthma, rhinitis, and dermatitis in the mother and father, paternal age, duration of exclusive and total breastfeeding period, hospitalization after birth, any furred animal at home, cats at home, dogs at home, and birth area was obtained during the scheduled visits to the research clinic. Delivery mode was encoded as “vaginal” and “CS” (including planned and emergency CS). Information on intrapartum antibiotics was validated against birth records from hospitals and information on antibiotic use during pregnancy and childhood was validated against national registries78. Information on perinatal exposures (asphyxia including meconium-stained amniotic fluid, vacuum-assisted delivery, and prelabor membrane-rupture) was obtained from national registries78. Living environment was based on home address at birth using the CORINE satellite-based land cover database79.

The CHILD cohort
Ethics
Ethical approval for the CHILD Cohort Study, including the oversight of the CHILD biological samples and the CHILD database (CHILDdb), was obtained from the local Research Ethics Board of each study site: the University of British Columbia, the University of Alberta, the University of Manitoba, the Hospital for Sick Children and McMaster University.

Study population
CHILD study is a prospective longitudinal birth cohort study, which enrolled 3,405 subjects since pregnancy from 4 largely urban study centers across Canada (Vancouver, Edmonton, Winnipeg, and Toronto) from 2008 to 201240. All children with fecal samples collected and characterized by 16s rRNA sequencing at around 1 year visit (9 months to 12 months, n = 325) were included in the analyses (Supplementary Data 8). Questionnaires related to environmental exposures, psychosocial stresses, nutrition and general health were administered at recruitment, prenatally, at 3, 6, 12, 18, 24, 30 months, and at 3, 4, and 5 years. Covariates used in this study were: delivery mode, gestational age, hospitalization after birth, gender, antibiotics exposure to children at 1 year, family asthma history, race (mother and father), birth season and study center.

Study endpoints
Childhood asthma was diagnosed (as Yes/Possible/No) by an expert study physician at the clinical assessment at the age of 5 years based on published approach40. For this study, children were considered to have asthma only if the response was ‘Yes’ and the asthma phenotype was defined as comparing children with asthma at 5 years versus children without asthma at 5 years, children diagnosed as “possible” were excluded.

Fecal sample collection and sequencing
Sequencing data generation for infant stool microbiota has been previously described80. Briefly, a soiled diaper was provided on the same day for infant stool collection. Samples were refrigerated at home for up to 24 hours before being collected and processed by study staff. An additional infant stool sample was provided at the 1-year clinical assessment. DNA was extracted from fecal samples using the commercial kits (Qiagen Mo Bio PowerSoil) optimized for the Thermofisher KingFisher® robot. The V4 hypervariable region of the 16S rRNA gene of fecal DNA was amplified by PCR using universal bacterial primers (V4-515f: V4-806r).

Bioinformatic processing
Pooled PCR amplicons were subjected to paired-end sequencing on the Illumina MiSeq platform. Using VSEARCH and Deblur81 within the QIIME2 pipeline71, forward and reverse demultiplexed reads were assembled for a final length of 247 bp (unassembled sequences were discarded) and filtered against the GREENGENES reference database ((v13·8)82,83. Taxonomic classification of the resulting unique amplicon sequence variants (ASVs) was achieved using a naïve Bayes classifier trained on reference reads extracted from the reference database at 97% sequence similarity.

Statistics and data analysis
Chao 1 index, Shannon diversity and Faith’s Phylogenetic Diversity (PD) were used as measures of the within-sample diversity (α-diversity). Chao 1 index and Shannon diversity were calculated using estimate_richness() from package phyloseq v1.48.0, PD was calculated using pd() from package picante v1.8.2. Linear regression was used for analyzing simple associations between α-diversity and the 1-year restoration score. A p-value of 0.05 was considered statistically significant. The between-sample diversity metrics (β-diversity) were computed as weighted UniFrac distances84. Differences in β-diversity were visualized with principal coordinates analysis (PCoA) plots, where the restoration score was dichotomized into high and low groups (above/below the median), and tested for inference using permutational multivariable analysis of variance (PERMANOVA; adonis2 from the package vegan v2.6-8 with 999 permutations). A p-value of 0.05 was considered statistically significant.

At species level, we filtered species based on the threshold of mean relative abundance > 0.01%. Differential abundance analysis against 1-year restoration score at species level was performed using LIMMA85 (Linear Models for Microarray Data, DA.lli2 from DAtest86 package), which fits a linear model to compositional data (log-transformed) for each taxa, multiple testing was controlled using the False Discovery Rate (FDR) adjustment87 within the function. The associations between the 1-year restoration score and environmental factors were tested using linear regression, multiple testing was controlled using the False Discovery Rate (FDR) adjustment. We performed supervised sparse partial least squares (sPLS) regression models on fecal microbiome and environmental factors separately and jointly using package mixOmics v6.28.0. This multivariable model is designed to reduce the high dimensionality of data and perform simultaneous variable selection. By using sPLS, we were to reveal microbial taxa and environmental factors most descriptive of 1-year restoration score. We log10-transformed counts data, using the lowest non-zero value as a pseudocount, and then calibrated the data for sequence depth by adjusting the number of reads and the log-transformed number of reads in the linear model. We selected the optimum number of input variables using 11-repeated 10-fold cross-validation of the correlation statistic to avoid overfitting and chose the median repeat for stability. The performance of the model was evaluated by assessing the correlation between predictions from the model and true restoration score. To evaluate the mediation role of the 1-week gut microbiome in the association between having older siblings and the 1-year restoration score, we applied mediation analysis using R package mediation (v4.5.1). A p-value of 0.05 was considered statistically significant. We performed a permutation test to determine whether the number of taxa that are significant for both the 1-year restoration score and older siblings’ status was greater than expected by chance, and whether the direction of their associations was concordant by chance. Using 10,000 permutations, we randomly shuffled the two predictor vectors in the data at each time point, recalculated differential abundance for each predictor (adjusting for reads and delivery mode), and merged the results by species. For each permutation, we counted how many species were significant for both predictors and computed the Spearman correlation between their log-fold-changes. The empirical p-values were calculated as P_perm_rho = (sum(rho_perm >= rho_obs) +1) / (10,000 + 1) and P_perm_n = (sum(n_perm >= n_obs) +1) / (10,000 + 1) for the direction and the number of associations, respectively. Analyses were conducted in the full cohort and within the stratum of children born by CS throughout and for vaginal born children for specific analyses. Regression-based P values were calculated using two-sided tests, permutation-based P values were calculated using one-sided (upper-tail) permutation tests. All analyses were conducted in R v4.4.0.

The validation study was conducted by applying the sPLS model from our previous study17 to the CHILD 1-year gut microbiome. In the previous work, the sPLS model was trained on 1-year gut microbiome in the COPSAC 2010 cohort and selected 5 genera to predict if the child was born by CS or not (1/0). Those taxa were: Bacteroides, Family Enterobacteriaceae, Sutterella, Escherichia/Shigella, and Dysgonomonas. We found the same or the closest annotation in the CHILD cohort as the input of the model: Bacteroides, Family Enterobacteriaceae, Sutterella, Escherichia/Shigella, and Dysgonomonas. The preprocessing of the abundance was the same as described in the original work, where we agglomerated the rank into genus level, log transformed the relative abundance, using half the lowest nonzero value as a pseudocount. We then used the predict() function from mixOmics package to apply the model on these five genera, and output the CHILD 1-year restoration score. To test the association between the CHILD 1-year restoration score and asthma endpoint, we performed both univariate logistic regression and multivariable logistic regression. The covariates adjusted in the multivariable logistic regression models were: gestational age, hospitalization after birth (days), gender, antibiotics exposure to child at 1 year, maternal asthma history, paternal asthma history, maternal race, paternal race, birth season, and study center. The performance of the model was evaluated by associating the CHILD 1-year restoration score with the outcome of the model - delivery mode - using the univariate logistic regression. And the validation of the association between having older siblings and restoration score was tested using univariate logistic regression as well.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Jiang and colleagues describe the impact of specific fecal bacteria present in the first weeks of life and environmental factors on a “restoration score” of the microbiome at 1 year of age upon Cesarean section delivery using data from the COPSAC2010 study. Moreover, these findings were replicated in the Canadian CHILD study.\nWhile most of the analyses are sound and the question on what is driving development of the microbiome in early life is a relevant topic, I have some reservations regarding the interpretation and the framing of the data.\nThe authors developed a score that captures to what extend the microbiome of C-section delivered infants is restored towards a vaginal-like microbiome composition by 1 year of age. The findings are interesting, particularly with respect to the association between the score and asthma risk which was also replicated. My main concerns is however the framing of this score as a restoration score for the C-section disturbed microbiome for several reasons:\n- It suggests that vaginal born infants have a “normal” or undisturbed microbiome (Fig 1A), but in fact the authors show that also within vaginally delivered infants many have a relatively low restoration score at 1 year. In fact, there is a significant overlap between the restoration scores of C-section and vaginally delivered infants as can be seen in Fig1C (both with only slightly different medians but also largely overlapping ranges). Is the restoration score actually statistically significantly different unadjusted or when adjusted for important confounding factors? This information seems lacking from Figure 1. In general conceptually these data indicate that this score captures amongst others delayed colonization with Bacteroides species, something that is not only limited to C-section born infants but also to part of the vaginally born infants.\n- The explained variance of the early-life microbiota on the restoration score appears very low (R2 0.9% and 0.4% for the 1 week and 1 month microbiota data). It would be good to elaborate on the magnitude of the impact beyond merely the statistical significance.\n- The authors themselves conclude that vaginally born infants could have a CS-like gut microbiome – for example due to antibiotic-induced perturbations. Many vaginally born infants without antibiotic exposure also have a CS-like microbiome suggesting that other determinants, likely intrapartum events (e.g., (premature) rupture of amniotic membranes, defecation during labor, assisted vaginal delivery) could play an important role. It would therefore be of significant added value when the authors could elucidate what explains the CS-like microbiome in vaginally delivered newborns based on amongst other intrapartum events.\n- In this respect also the distinction between emergency and elective C-section would likely play an important role – could the authors distinguish between scheduled and emergency procedures?\n- Most of the associations that the authors report in relation to the restoration score are only statistically significant in the full cohort and not in the stratum of CS-delivered infants. For example, no detectable differences were observed in microbial composition at 1 week and 1 month between CS-delivered infants in the high- and low 1-year restoration groups. Also, no differentially abundant taxa in the CS stratum were observed upon adjustment of multiple comparisons. Finally none of the environmental determinants appeared to be significantly linked to the restoration score in the CS stratum. This further suggests that the observed findings are not specific for CS-delivered infants but more likely resemble a different maturation among infants that start of with amongst others a low abunandance of Bacteroides and Sutterella, and high abundance of Escherichia-Shigella and other Enterobacteriaceae.\n- While, given the focus on restoration of the microbiota composition in CS-born infants, it might seem logical to only present the CS stratum in subgroup analyses from a methodological point of view it is important to also present and discuss the VD stratum. It would be important to check if the few findings that were observed in the CS stratum in association to the restoration score would be similar or not in the VD stratum. If similar findings would be observed in both strata this would further underscore that it is mainly a general restoration of delayed colonization during birth rather than a CS-specific restoration.\nAdditional comments:\n- The phrasing “one genus from the family Enterobacteriaceae” as one of the main loadings in CHILD cohort data (Fig 6) is somewhat ambiguous. It is not entirely clear whether this refers to a single, well-defined genus that could not be further annotated, or whether it represents a catch-all category of sequencing reads within Enterobacteriaceae that could not be classified to the genus level and might therefore comprise a heterogeneous set of taxa. Clarifying this point would help readers better interpret the taxonomic resolution and biological relevance of this finding.\n- Shigella comes out as another important loading in the CHILD cohort data but this is extremely unlikely as Shigella is a strict pathogen resulting in dysentery. This is a typical and common misclassification as Shigella is basically pathogenic lineage of E. coli and is often 100% identical to other E. coli lineages at the 16S v4 region. It would be important to correct this in order to not provide wrong suggestions.\nMinor comments:\n- Line 148 – the Chao1 index is not a microbial diversity index but a richness index\n- Fig 2 – The PCoA on the 1-year data is somewhat suggestive and misleading as the strong difference is to be expected since the 1-year microbiota was used to create the restoration score.\n- Would be nice to apply permutation testing on the bacteria associated with both having older siblings and 1-year restoration index to check if number of bacteria associated with both is statistically significantly higher than expected based on the associations with either one of these alone.", "reviewer_2": "In this manuscript, the authors showed using sparse Partial Least Squares models several microbiome and environmental factors that contribute to the so-called restoration of the gut microbiome in caesarean-section born children in a previously established cohort. Furthermore, the authors were able to externally validate the models’ performance using a separate cohort, also previously established, from a different child population. The results seem to be sufficiently discussed and references relevant to the field of early microbiome development, C-section and asthma have been included both in the introduction and discussion. The methodology and interpretation of results seem sound, although I was left with a couple of comments in these sections that might help the authors improve the manuscript further. Overall, I would recommend sending the manuscript back to the authors for minor revisions.\n-Results, overall: Continually, both FDR-adjusted and nominal P-values are being used here. The results get somewhat confusing when these results are being mixed and matched, sometimes both are being reported, and sometimes a P-value has been reported without clarification on whether it’s nominal or FDR-adjusted. I think it would be best to either stick to one (preferably FDR-adjusted values) or write the results more clearly in this regard.\n-Figure 1D, Figure 4, Figure 6C: What does “loading” in the x-axis mean? Might be helpful to explain this somewhere.\n-Results, line 149: Here’s an abbreviation that has not been explained earlier (PD). This should be opened up here.\n-Results, line 176: The figure reference here (Fig. 2A) does not seem correct. This should be fixed.\n-Results, Figure 6B: Does the legend mean that the top line is COPSAC dataset and bottom line is CHILD? Might be useful to also have some visual differences, such as dotting in one or having differently colored lines to highlight which result represents which dataset.\n-Methods: The methods don’t describe how the statistical testing for the environmental factors associated with 1-year restoration were performed. It would be helpful if this was also included here."}, "author_response": "Thank you for the constructive and insightful comments. Concerns about the framing of the restoration scores and the statistical testing are very valid, and we have fully and thoroughly addressed them in this revised version of the manuscript. We also considered the suggestion to perform analyses in the vaginal strata and have incorporated those analyses into the manuscript. Additionally, we appreciate the detailed comments on terminology and plots. Below is a point-by-point response that addresses all comments and outlines the specific changes made, which have greatly improved the manuscript. We thank the reviewers for their valuable feedback and look forward to any further comments on this revised version.\nReviewer #1 (Remarks to the Author):\nJiang and colleagues describe the impact of specific fecal bacteria present in the first weeks of life and environmental factors on a “restoration score” of the microbiome at 1 year of age upon Cesarean section delivery using data from the COPSAC2010 study. Moreover, these findings were replicated in the Canadian CHILD study.\nWhile most of the analyses are sound and the question on what is driving development of the microbiome in early life is a relevant topic, I have some reservations regarding the interpretation and the framing of the data.\nThe authors developed a score that captures to what extend the microbiome of C-section delivered infants is restored towards a vaginal-like microbiome composition by 1 year of age. The findings are interesting, particularly with respect to the association between the score and asthma risk which was also replicated. My main concerns is however the framing of this score as a restoration score for the C-section disturbed microbiome for several reasons:\n- It suggests that vaginal born infants have a “normal” or undisturbed microbiome (Fig 1A), but in fact the authors show that also within vaginally delivered infants many have a relatively low restoration score at 1 year. In fact, there is a significant overlap between the restoration scores of C-section and vaginally delivered infants as can be seen in Fig1C (both with only slightly different medians but also largely overlapping ranges). Is the restoration score actually statistically significantly different unadjusted or when adjusted for important confounding factors? This information seems lacking from Figure 1. In general conceptually these data indicate that this score captures amongst others delayed colonization with Bacteroides species, something that is not only limited to C-section born infants but also to part of the vaginally born infants.\nResponse 1: Thank you for this very good observation. According to the comment, we have now added the association tests between the restoration score and delivery mode in the crude group (vaginal/C-section), and in the subgroups (Vaginal, no ABX/Vaginal, ABX/C-section) to the figure. C-section is associated with significantly lower restoration scores (Estimate:-0.32[-0.51,-0.13],P=8e-04) compared to vaginal delivery; while in the subgroup analyses, compared to Vaginal, no ABX, Vaginal, ABX was negatively associated with restoration scores (-0.23[-0.48, 0.02], P=0.07), so was the C-section group with pronounced significance (-0.36[-0.55,-0.16],P=3e-04). There was no detectable difference in the restoration scores between the Vaginal, ABX and CS group(-0.13[-0.45,0.19],P=0.43), which suggests vaginally born infants whose mother received antibiotics at birth can indeed have a skewed gut microbiome, which is also the point of using the restoration score. These tests have now been added to the plot Fig. 1C, and Fig 1 legend. Line 139\n- The explained variance of the early-life microbiota on the restoration score appears very low (R2 0.9% and 0.4% for the 1 week and 1 month microbiota data). It would be good to elaborate on the magnitude of the impact beyond merely the statistical significance.\nResponse 2: Thank you for the comments. The restoration score explains only a modest proportion of the variance in the early gut microbiota as quantified by the adonis2 permanova. This is a common observation in microbiome studies due to the high dimensionality and dynamic nature of the infant gut microbiome. This likely reflects the rapid ecological changes occurring during the first year of life, where many taxa are competing in this developing niche.\nWe have now addressed this in the limitation section of the discussion. Line 592\n- The authors themselves conclude that vaginally born infants could have a CS-like gut microbiome – for example due to antibiotic-induced perturbations. Many vaginally born infants without antibiotic exposure also have a CS-like microbiome suggesting that other determinants, likely intrapartum events (e.g., (premature) rupture of amniotic membranes, defecation during labor, assisted vaginal delivery) could play an important role. It would therefore be of significant added value when the authors could elucidate what explains the CS-like microbiome in vaginally delivered newborns based on amongst other intrapartum events.\nResponse 3:\nThank you for these comments. We agree that it is of interest and have now performed additional analyses in the vaginal stratum, including how the restoration score is associated with environmental factors and the early gut microbiome. Please refer to response 6 for details.\n- In this respect also the distinction between emergency and elective C-section would likely play an important role – could the authors distinguish between scheduled and emergency procedures?\nResponse 4: Thank you for bringing up this point. We have tested the difference in the restoration scores between the planned and emergency procedures with linear regression using planned C-section as the reference, and no detectable differences were observed (Estimate 0.18[-0.20,0.57], P=0.35, number of planned / emergency C-section: n = 69 / 93).\nFor this reason we have kept all C-sections in one category. We have added the additional analysis in the results. Line 146\n- Most of the associations that the authors report in relation to the restoration score are only statistically significant in the full cohort and not in the stratum of CS-delivered infants. For example, no detectable differences were observed in microbial composition at 1 week and 1 month between CS-delivered infants in the high- and low 1-year restoration groups. Also, no differentially abundant taxa in the CS stratum were observed upon adjustment of multiple comparisons. Finally none of the environmental determinants appeared to be significantly linked to the restoration score in the CS stratum. This further suggests that the observed findings are not specific for CS-delivered infants but more likely resemble a different maturation among infants that start of with amongst others a low abunandance of Bacteroides and Sutterella, and high abundance of Escherichia-Shigella and other Enterobacteriaceae.\nResponse 5: Please refer to response 6.\n- While, given the focus on restoration of the microbiota composition in CS-born infants, it might seem logical to only present the CS stratum in subgroup analyses from a methodological point of view it is important to also present and discuss the VD stratum. It would be important to check if the few findings that were observed in the CS stratum in association to the restoration score would be similar or not in the VD stratum. If similar findings would be observed in both strata this would further underscore that it is mainly a general restoration of delayed colonization during birth rather than a CS-specific restoration.\nResponse 6:\nThank you for this very relevant suggestion. It is indeed interesting to examine prenatal and postnatal factors among vaginally delivered infants who exhibit a “CS-like” gut microbiome. In this response, we consider not only the restoration score at 1 year of age but also the early restoration scores at 1 week and 1 month (again derived from Stokholm, Science Transl Med 2020). As with the 1-year score, the 1-week and 1-month scores indicate the extent to which an infant’s gut microbiome resembles that of infants born vaginally. Within the vaginal-delivery stratum, low restoration scores quantify how similar the gut microbiome is to that of infants born by CS, reflecting perturbations due to other factors. These scores were calculated separately, predicting CS on gut microbiome at each time point, but they are highly correlated (restoration score 1 week vs 1 month: rho 0.52, P<2e-16; 1 week vs 1 year: rho 0.16, P=3e-04; 1 month vs 1 year: rho 0.17, P=4e-05).\nWe examined associations between these restoration scores in the vaginal stratum and various perinatal factors (intrapartum antibiotics, prelabor membrane rupture, and Meconium-Stained Amniotic Fluid (MSAF) exposure) as well as postnatal factors (hospitalization, presence of older siblings, and all other factors previously reported in the manuscript). As you can see from the table below, antibiotics to mothers and children at birth and hospitalization after birth were negatively associated with early restoration scores. MSAF exposure was negatively associated with the 1-year restoration score. There is a limited number of studies investigating the influence of MSAF exposure on the infants’ gut microbiome, but it’s reported that MSAF exposure can be a risk factor for many different conditions.\nWe next looked into the bacterial species at 1 week and 1 month associated with restoration scores in the vaginal stratum. At 1 week of age, children with higher restoration scores had higher relative abundances of Sutterella wadsworthensis and Neglecta timonensis as we saw in the full cohort (FDR adjusted P<0.05). In contrast, Veillonella parvula, Actinomyces sp., and Howardella ureilytica were associated with lower restoration scores at 1 year of age (FDR adjusted P<0.05).\nWe acknowledge the relevance of the inclusion of analyses in the vaginal stratum, and have made a whole new separate paragraph in the results section investigating the associations with 1-year restoration scores in the manuscript:\n“Early gut taxa and environmental factors associated with restoration scores in the vaginal stratum”,\nLine 389\nEnvironmental factors\nRestoration score at 1 week Restoration score at 1 month Restoration score at 1 year\nEstimate[LowCI,HighCI], P\nStats\nGestational age in days 0.06[-0.08,0.19],P=0.42 0.13[0.01,0.25],P=0.03 0[0,0.01],P=0.4\nN=396 N=434 N=491\nAntibiotics to child at birth -0.93[-1.53,-0.34],P=2e-03 -0.73[-1.26,-0.2],P=7e-03 -0.02[-0.05,0],P=0.05\nno 384 / yes 9 no 419 / yes 12 no 473 / yes 15\nAntibiotics to mother at birth -0.36[-0.63,-0.1],P=7e-03 -0.26[-0.51,0],P=0.05 -0.01[-0.02,0],P=0.07\nno 343 / yes 50 no 374 / yes 57 no 425 / yes 63\nPreeclampsy -0.22[-0.67,0.22],P=0.33 -0.26[-0.72,0.2],P=0.27 -0.01[-0.03,0.01],P=0.38\nno 361 / yes 16 no 392 / yes 17 no 443 / yes 21\nInduction -0.12[-0.34,0.1],P=0.27 -0.08[-0.3,0.13],P=0.44 -0.01[-0.02,0],P=0.17\nno 291 / yes 85 no 306 / yes 102 no 350 / yes 113\nAsphyxia -0.1[-0.34,0.13],P=0.38 -0.06[-0.29,0.17],P=0.63 -0.01[-0.02,0],P=0.27\nno 307 / yes 70 no 328 / yes 81 no 371 / yes 93\nMeconium-stained amniotic -0.3[-0.7,0.1],P=0.14 -0.03[-0.44,0.38],P=0.88 -0.02[-0.04,0],P=0.02\nfluid no 357 / yes 20 no 387 / yes 22 no 440 / yes 24\nVacuum-assisted delivery -0.16[-0.46,0.14],P=0.3 -0.17[-0.48,0.13],P=0.27 0[-0.02,0.01],P=0.66\nno 339 / yes 38 no 369 / yes 40 no 418 / yes 46\nPrelabor membrane-rupture -0.19[-0.52,0.15],P=0.28 -0.19[-0.53,0.15],P=0.28 -0.01[-0.03,0],P=0.1\nno 347 / yes 30 no 377 / yes 32 no 427 / yes 37\nPrelabor membrane-rupture >= -0.21[-0.56,0.14],P=0.25 -0.15[-0.51,0.21],P=0.42 -0.01[-0.03,0.01],P=0.25\n37w no 350 / yes 27 no 381 / yes 28 no 432 / yes 32\nPreterm-Prelabor membrane- 0.03[-0.99,1.05],P=0.95 -0.42[-1.35,0.51],P=0.37 -0.03[-0.08,0.01],P=0.13\nrupture no 374 / yes 3 no 405 / yes 4 no 459 / yes 5\nHospitalization after birth -0.81[-1.13,-0.49],P=9e-07 -0.73[-1.02,-0.45],P=8e-07 -0.01[-0.02,0.01],P=0.3\nno 365 / yes 31 no 392 / yes 42 no 443 / yes 48\nAdditional comments:\n- The phrasing “one genus from the family Enterobacteriaceae” as one of the main loadings in CHILD cohort data (Fig 6) is somewhat ambiguous. It is not entirely clear whether this refers to a single, well-defined genus that could not be further annotated, or whether it represents a catch-all category of sequencing reads within Enterobacteriaceae that could not be classified to the genus level and might therefore comprise a heterogeneous set of taxa. Clarifying this point would help readers better interpret the taxonomic resolution and biological relevance of this finding.\nResponse 7: Thank you for pointing this out. In the CHILD cohort, the annotation was Enterobacteriaceae at the family level, which refers to a generic-level assignment that could not be resolved to a specific genus. This taxon is therefore a heterogeneous, unclassified clade within the Enterobacteriaceae that may comprise several related genera, which was at the same level as what we had in the COPSAC cohort. Therefore, we changed the name of the loading into “Family Enterobacteriaceae” in the Fig 6, and clarified it in the methods section. Line 783\n- Shigella comes out as another important loading in the CHILD cohort data but this is extremely unlikely as Shigella is a strict pathogen resulting in dysentery. This is a typical and common misclassification as Shigella is basically pathogenic lineage of E. coli and is often 100% identical to other E. coli lineages at the 16S v4 region. It would be important to correct this in order to not provide wrong suggestions.\nResponse 8: Thank you for this one as well. We fully agree, and have changed the label into “Escherichia/Shigella” in Fig 6, and clarified it in the methods section. Line 786\nMinor comments:\n- Line 148 – the Chao1 index is not a microbial diversity index but a richness index\nResponse 9: Thank you for pointing this out. We have changed the wording and will be careful not to mix them. Line 727\n- Fig 2 – The PCoA on the 1-year data is somewhat suggestive and misleading as the strong difference is to be expected since the 1-year microbiota was used to create the restoration score.\nResponse 10: We thank you for raising this point, but argue to keep it to show the development over time. To avoid confusion, we have removed the P value at 1 year from the plot, colored the 1-year time point with a grey shadow, and have now clarified this point additionally in the figure legend. Line 189\n- Would be nice to apply permutation testing on the bacteria associated with both having older siblings and 1-year restoration index to check if number of bacteria associated with both is statistically significantly higher than expected based on the associations with either one of these alone.\nResponse 11:Thank you for the great suggestion for analysis, which will strengthen the argument substantially. We have now performed a permutation test to determine whether the number of taxa that are significant for both the 1-year restoration score and older siblings status is greater than expected by chance, and whether the direction of their associations is concordant by chance. Using 10,000 permutations, we randomly shuffled the two predictor vectors in the data at each time point, recalculated differential abundance for each predictor, and merged the results by species. For each permutation, we counted how many species were significant for both predictors and computed the Spearman correlation between their log-fold-changes. The empirical p-values were calculated as P_perm_rho = (sum(rho_perm >= rho_obs) +1 ) / (10,000 + 1) and P_perm_n = (sum(n_perm >= n_obs) +1 ) / (10,000 + 1) for the direction and the number of associations, respectively. Both of the empirical p-values were below 0.05, indicating that the overlap and concordant direction are highly unlikely under the null.\nThese results confirm that a subset of gut taxa is indeed jointly associated with 1-year restoration score and sibling exposure. We have added this in the manuscript. Line 350, Fig 5, Line 364, Line 755\nReviewer #2 (Remarks to the Author):\nIn this manuscript, the authors showed using sparse Partial Least Squares models several microbiome and environmental factors that contribute to the so-called restoration of the gut microbiome in caesarean-section born children in a previously established cohort. Furthermore, the authors were able to externally validate the models’ performance using a separate cohort, also previously established, from a different child population. The results seem to be sufficiently discussed and references relevant to the field of early microbiome development, C-section and asthma have been included both in the introduction and discussion. The methodology and interpretation of results seem sound, although I was left with a couple of comments in these sections that might help the authors improve the manuscript further. Overall, I would recommend sending the manuscript back to the authors for minor revisions.\n-Results, overall: Continually, both FDR-adjusted and nominal P-values are being used here. The results get somewhat confusing when these results are being mixed and matched, sometimes both are being reported, and sometimes a P-value has been reported without clarification on whether it’s nominal or FDR-adjusted. I think it would be best to either stick to one (preferably FDR-adjusted values) or write the results more clearly in this regard.\nResponse 12: Thank you for this comment, after consideration, we would like to keep the figures with/without FDR adjustment because of the biological meaning (potential to compare between strata and between timepoints, potential for replication by future studies), but we agree to keep it clean in the text, only write about FDR significant findings, when the multiple testing had been done. Line 208-211, Line 241-252, Line 396-404.\n-Figure 1D, Figure 4, Figure 6C: What does “loading” in the x-axis mean? Might be helpful to explain this somewhere.\nResponse 13: Thank you for raising this point of potential confusion for the reader. We have explained the meaning of loadings in each of the figure legends. Line: 160, Line 296, Line 466.\n-Results, line 149: Here’s an abbreviation that has not been explained earlier (PD). This should be opened up here.\nResponse 14: Thank you very much for this comment. We have added the full name of Faith’s Phylogenetic Diversity (PD) in Line 168.\n-Results, line 176: The figure reference here (Fig. 2A) does not seem correct. This should be fixed.\nResponse 15: Thank you for spotting this error, we have corrected it as Fig.3A in line 205.\n-Results, Figure 6B: Does the legend mean that the top line is COPSAC dataset and bottom line is CHILD? Might be useful to also have some visual differences, such as dotting in one or having differently colored lines to highlight which result represents which dataset.\nResponse 16: Yes, exactly. We have now used different colors to additionally illustrate the differences.\n-Methods: The methods don’t describe how the statistical testing for the environmental factors associated with 1-year restoration were performed. It would be helpful if this was also included here.\nResponse 17: Thank you for spotting this, we have added the description of the statistical analysis for the environmental factors in the methods section. Line 742\nReviewer #2 (Remarks on code availability):\nWhile not having physically tested whether the code works, I have confirmed that the code for the manuscript has a working link, includes detailed instructions on performing the analyses and the code itself seems good.\nResponse 18: Thank you very much."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have significantly revised the manuscript and addressed all remarks I previously raised. Especially the additional analyses on microbial and environmental factors associated with the restoration score in the vaginally born infants are very interesting and of additional value. I have no further comments.", "reviewer_2": "The manuscript has been significantly improved with revisions. I have no further comments.\n(Remarks on code availability)\nI did suggest including the code for the analysis. I appreciate that the methods have been very much expanded but it seems that the authors have not shared their code. I would not recommend rejection solely based on this but I would strongly recommend for the authors to reconsider publishing their code for this manuscript as well as any other future manuscripts for transparency."}, "author_response": ""}]

Decision letter