Microbial Bioactives

1. Introduction

Over the past two decades, the human microbiome has shifted from being viewed as a peripheral biological curiosity to something much more central—almost an ecological extension of the human body itself. Rather than existing as isolated entities, humans and microbes appear to function within an intricate biological partnership in which bacteria, fungi, viruses, and archaea participate in immune regulation, metabolic balance, epithelial maintenance, and inflammatory signaling (Boulangé et al., 2016; Ogunrinola et al., 2020). Increasingly, this microbial network is being recognized not merely as a passive inhabitant of host tissues, but as a dynamic determinant of health and disease. Disturbances within this ecosystem, commonly described as dysbiosis, have now been implicated in a broad spectrum of disorders, including obesity, autoimmune diseases, chronic inflammatory syndromes, and respiratory pathologies (Boulangé et al., 2016; De Luca & Shoenfeld, 2019).

What makes this relationship particularly compelling is that microbial colonization begins remarkably early in life. Although the sterile womb paradigm dominated biomedical thinking for decades, accumulating evidence suggests that maternal microbial signals may influence fetal immune development even before birth (Sinha et al., 2023). The perinatal period therefore represents a biologically sensitive interval during which maternal microbiota help shape neonatal microbial assembly and immune maturation (Nunez et al., 2021). These early microbial encounters are not trivial. They contribute to metabolic programming, immune tolerance, and epithelial development in ways that may persist across the lifespan (Yao et al., 2021).

The composition of the infant microbiome is heavily influenced by delivery mode, feeding behavior, maternal health, and environmental exposures. Vaginally delivered infants are typically colonized by maternal vaginal and intestinal microbes, whereas cesarean delivery is associated with altered microbial succession and delayed colonization by beneficial taxa (Dogra et al., 2021). Breastfeeding further enriches microbial diversity and promotes colonization by protective genera such as *Bifidobacterium* and *Lactobacillus*, both of which are important for mucosal immune development and metabolic stability (Yao et al., 2021). In healthy circumstances, these microbial interactions support balanced immune calibration during infancy. Yet this developmental process is highly vulnerable to environmental disruption. Among the most pervasive and preventable exposures is tobacco smoke. Cigarette smoke contains thousands of biologically active compounds—including nicotine, oxidants, polycyclic aromatic hydrocarbons, and heavy metals—that can cross placental barriers and influence fetal development long before birth (Saha et al., 2007). Maternal smoking has long been associated with adverse neonatal outcomes such as fetal growth restriction, impaired lung maturation, and low birth weight (Reeves & Bernstein, 2008). More recently, however, attention has shifted toward another possibility: that tobacco exposure may also disrupt the infant microbiome during its formative stages.

Several studies now suggest that prenatal and early postnatal smoke exposure alters microbial composition in both the gut and respiratory tract. Infants exposed to maternal smoking frequently demonstrate reduced microbial diversity together with enrichment of taxa associated with inflammatory and metabolic dysfunction (Tun, 2017; Peng et al., 2024). Increased abundance of Firmicutes and depletion of protective organisms such as *Akkermansia muciniphila* have been linked with obesity risk, impaired barrier integrity, and immune dysregulation (Peng et al., 2024; Pérez-Castro et al., 2024). Likewise, meconium microbiota analyses indicate that maternal smoking may alter microbial colonization patterns even before substantial postnatal exposure occurs (Gosalbes et al., 2013).

Environmental tobacco exposure extends beyond direct maternal smoking alone. Secondhand and thirdhand smoke exposure remain major concerns, particularly in neonatal environments where infants may encounter nicotine residues through contaminated surfaces and indoor air (Northrup et al., 2021). These exposures appear capable of reshaping microbial communities during early immune development. Reduced abundance of beneficial taxa such as *Bifidobacterium* and broader disturbances in microbial diversity have been observed in smoke-exposed infants and children (Huotari, 2020; Xie et al., 2021). Such findings reinforce the idea that microbiome disruption may represent one of the earliest biological imprints of tobacco exposure.

At the same time, respiratory medicine has undergone its own conceptual transformation. For many years, healthy lungs were considered sterile. Advances in culture-independent sequencing technologies have now overturned that assumption, demonstrating that the respiratory tract contains a distinct, low-biomass microbial ecosystem extending from the upper airways to the distal alveolar environment (Charlson et al., 2011; Moffatt & Cookson, 2017). In healthy lungs, microbial communities help maintain epithelial integrity and immune equilibrium. Commensal genera such as *Prevotella*, *Veillonella*, and *Streptococcus* appear to contribute to immune homeostasis and pathogen exclusion (Faner et al., 2017).

In chronic pulmonary disease, however, this equilibrium becomes disrupted. Altered respiratory microbial communities have been increasingly associated with chronic obstructive pulmonary disease, asthma, bronchiectasis, and fibrotic interstitial lung diseases (ILDs) (Faner et al., 2017). Among these conditions, progressive fibrosing interstitial lung diseases (PF-ILDs) are particularly devastating because they involve irreversible fibrosis, declining lung function, worsening dyspnea, and high mortality (Maher et al., 2019; Wijsenbeek et al., 2019). Idiopathic pulmonary fibrosis (IPF), the most recognized PF-ILD subtype, has emerged as a key model for studying microbiome-associated fibrotic progression (Lederer & Martinez, 2018; Richeldi et al., 2017). A growing body of evidence now implicates the lung microbiome in IPF pathogenesis and progression. Studies have consistently demonstrated elevated bacterial burden in patients with IPF compared with healthy controls or individuals with chronic obstructive pulmonary disease (Molyneaux et al., 2014). Increased abundance of genera such as *Streptococcus* and *Staphylococcus* has been associated with accelerated disease progression and poorer clinical outcomes (Han et al., 2014). Acute exacerbations of IPF are similarly linked with significant increases in bacterial load and microbial instability (Molyneaux et al., 2017). These observations suggest that microbial dysbiosis may actively participate in perpetuating fibrotic injury rather than simply reflecting tissue damage.

Mechanistically, this relationship appears biologically plausible. Microbial products such as lipopolysaccharides and other pathogen-associated molecular patterns can activate innate immune signaling pathways, promote epithelial injury, and stimulate fibroblast activation (Huang et al., 2017). Persistent microbial stimulation may therefore contribute to chronic inflammation and aberrant tissue remodeling within susceptible lungs. Indeed, studies have linked microbial burden with alveolar inflammation and fibrotic signaling activity in pulmonary fibrosis (O'Dwyer et al., 2019). Even investigations of end-stage IPF tissue have identified altered microbial signatures, although findings remain somewhat heterogeneous depending on disease stage and sampling methodology (Kitsios et al., 2017).

The broader concept of the gut–lung axis further strengthens the rationale for examining microbiome-mediated pulmonary disease. Bidirectional communication between intestinal microbes and pulmonary immunity occurs through microbial metabolites, cytokines, and systemic immune signaling (Dang & Marsland, 2019). Alterations in gut microbial ecology during infancy may therefore influence lung immune development and inflammatory responsiveness later in life. Environmental and sociocultural exposures—including tobacco smoke—have already been shown to shape infant microbial trajectories during critical developmental windows (Levin et al., 2016). Environmental pollutants more broadly may exert similarly lasting effects on respiratory vulnerability and immune regulation (Diamanti et al., 2019).

Taken together, these findings raise an important but still insufficiently explored question: could perinatal tobacco exposure contribute to long-term susceptibility to progressive fibrotic lung disease through microbiome disruption? While the direct pulmonary toxicity of tobacco exposure is well established, the possibility that smoke-induced microbial dysbiosis acts as an intermediary mechanism introduces a more complex developmental perspective. Rather than viewing PF-ILD solely as a disease of aging or cumulative adult exposures, emerging evidence hints that susceptibility may begin much earlier—perhaps during fetal life itself.

This systematic review therefore aims to synthesize current evidence linking perinatal tobacco exposure, microbiome dysbiosis, and progressive fibrotic interstitial lung diseases. By integrating findings from microbiome science, developmental immunology, and pulmonary medicine, this review seeks to clarify whether early microbial disruption represents a biologically meaningful pathway connecting environmental exposure to long-term fibrotic lung vulnerability. In doing so, it also highlights the possibility that interventions targeting maternal health, smoking cessation, and microbiome preservation during early life may have implications extending far beyond infancy.

2. Materials and Methods

2.1 Study Design and Reporting Framework

This study was designed as a systematic review with quantitative synthesis to evaluate the relationship between perinatal tobacco exposure, microbiome dysbiosis, and susceptibility to progressive fibrosing interstitial lung diseases (PF-ILDs). A meta-analytic approach was incorporated where sufficient quantitative homogeneity existed among studies. The methodological structure of the review followed internationally accepted standards for evidence synthesis in biomedical research and was

Figure 1. PRISMA 2020 flow diagram illustrating the systematic study selection process for evaluating associations between perinatal tobacco exposure, microbiome dysbiosis, and progressive fibrosing interstitial lung diseases (PF-ILD). The diagram summarizes database identification, duplicate removal, screening, eligibility assessment, exclusion criteria, qualitative synthesis inclusion, and studies included in the quantitative meta-analysis (n = 14) according to PRISMA 2020 reporting guidelines.

developed to ensure transparency, reproducibility, and methodological rigor suitable for peer-reviewed journal publication. Reporting procedures were guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) framework (Figure 1), which provides updated recommendations for systematic review reporting and study selection transparency (Page et al., 2021).

The overall methodological strategy was also informed by principles outlined in the Cochrane Handbook for Systematic Reviews of Interventions, particularly regarding study identification, data extraction, risk-of-bias assessment, and synthesis of heterogeneous evidence (Higgins et al., 2022). A predefined review protocol was established before the literature search process to minimize selective reporting and analytical bias. The protocol specified the research question, eligibility criteria, exposure definitions, outcomes of interest, and planned analytical procedures.

Conceptually, the review adopted a developmental origins framework, recognizing that prenatal and early-life environmental exposures may induce persistent biological alterations that influence disease susceptibility later in adulthood. Within this framework, microbiome dysbiosis was considered a potentially important intermediary mechanism linking tobacco exposure during critical developmental windows with long-term pulmonary and fibrotic outcomes.

2.2 Literature Search Strategy and Data Sources

A comprehensive literature search was conducted to identify relevant studies published before January 2024. Electronic databases searched included PubMed/MEDLINE, Scopus, Web of Science, and Embase. These databases were selected because they collectively provide broad coverage of respiratory medicine, microbiology, toxicology, developmental biology, and translational biomedical research.

The search strategy combined Medical Subject Headings (MeSH) and free-text terms related to three core concepts: perinatal tobacco exposure, microbiome alterations, and fibrotic lung disease. Search terms included combinations of “prenatal smoking,” “maternal smoking,” “environmental tobacco smoke,” “thirdhand smoke,” “lung microbiome,” “airway microbiota,” “gut–lung axis,” “pulmonary fibrosis,” “interstitial lung disease,” and “progressive fibrotic ILD.” Boolean operators (“AND,” “OR”) and database-specific filters were applied to optimize both sensitivity and specificity during article retrieval. Reference lists from eligible studies and relevant reviews were additionally screened manually to identify potentially missed articles.

Only peer-reviewed articles published in English were included to ensure methodological clarity and consistency in interpretation. Editorials, conference abstracts, commentaries, letters, and unpublished reports were excluded because these sources generally lacked sufficient methodological detail for systematic evaluation. Retrieved records were exported into reference-management software, and duplicate entries were removed prior to screening.

2.3 Eligibility Criteria and Study Selection

Study selection followed the Population, Exposure, Comparator, Outcomes, and Study Design (PECOS) framework recommended for systematic reviews in observational and clinical research (Higgins et al., 2022). Eligible studies were required to meet the following inclusion criteria: (1) investigation of prenatal, perinatal, or early postnatal exposure to tobacco smoke or tobacco-derived compounds; (2) assessment of microbiome-related outcomes, including lung, airway, or gut microbial composition and diversity; and/or (3) evaluation of pulmonary outcomes relevant to fibrotic susceptibility, immune dysregulation, or progressive interstitial lung disease. Both observational studies (cohort, case–control, and cross-sectional studies) and experimental or mechanistic investigations were considered eligible.

Studies focusing exclusively on adult smoking exposure without assessment of early-life exposure were excluded. Articles lacking microbiome-related outcomes or sufficient methodological information were also excluded. Review articles were not included in the quantitative synthesis, although their bibliographies were screened to identify additional primary studies.

The study selection process was performed in two sequential stages. First, titles and abstracts were screened for relevance. Subsequently, potentially eligible articles underwent full-text review against predefined inclusion and exclusion criteria. Disagreements regarding eligibility were resolved through discussion and consensus-based evaluation. The complete study selection process was documented using a PRISMA 2020 flow diagram to ensure transparent reporting of included and excluded studies (Page et al., 2021).

2.4 Data Extraction and Quality Assessment

Data extraction was performed using a standardized extraction template developed specifically for this review. Extracted information included study design, geographic setting, participant characteristics, exposure assessment methods, microbiome sampling approaches, sequencing or culture methodologies, microbial diversity indices, dominant taxa, inflammatory markers, pulmonary outcomes, and principal findings.

For microbiome analyses, extracted variables included specimen source (e.g., bronchoalveolar lavage, airway swabs, stool samples, lung tissue), sequencing platforms, alpha- and beta-diversity measures, and taxonomic alterations associated with tobacco exposure or fibrotic disease progression. Pulmonary outcomes included inflammatory biomarkers, lung function parameters, fibrotic signaling markers, histopathological findings, and clinically defined interstitial lung disease outcomes.

Methodological quality and risk of bias were evaluated according to study design characteristics. Observational studies were assessed for participant selection bias, exposure misclassification, confounding, and outcome assessment reliability. Experimental studies were evaluated for exposure control, reproducibility, model validity, and methodological consistency. Quality assessments were incorporated into evidence interpretation and synthesis to strengthen the reliability of conclusions.

2.5 Quantitative Synthesis and Statistical Analysis

Where studies demonstrated sufficient comparability in exposure definitions and outcome reporting, quantitative synthesis was conducted using meta-analytic methods. Statistical pooling was performed using random-effects models to account for between-study heterogeneity and variability in study populations, exposure measurements, and microbiome methodologies. The random-effects approach proposed by DerSimonian and Laird (1986) was selected because it provides more conservative pooled estimates when true effect sizes are expected to vary across studies. Effect sizes and corresponding standard errors were extracted or calculated from eligible studies and pooled where appropriate. Quantitative synthesis focused on outcomes related to microbial diversity reduction, inflammatory signaling, and fibrotic susceptibility markers. General principles of meta-analysis described by Borenstein et al. (2009) guided the calculation and interpretation of pooled estimates, confidence intervals, and effect-size consistency. Statistical heterogeneity among studies was evaluated using the I² statistic, which estimates the proportion of variability attributable to between-study inconsistency rather than chance alone (Higgins et al., 2003). Thresholds for low, moderate, and high heterogeneity were interpreted according to established methodological recommendations. Sensitivity analyses were additionally performed to determine whether individual studies disproportionately influenced pooled estimates.

Potential publication bias was assessed through visual inspection of funnel plots and, where applicable, through Egger’s regression asymmetry test (Egger et al., 1997). These analyses were conducted to evaluate the possibility that smaller studies with non-significant findings may have been underrepresented in the literature.

2.6 Narrative Synthesis

For outcomes that could not be quantitatively pooled because of methodological heterogeneity or insufficient comparable data, a structured narrative synthesis was undertaken. Findings were grouped thematically according to microbiome alterations, immune dysregulation, pulmonary structural changes, and fibrotic disease progression. This integrative synthesis allowed epidemiological observations, mechanistic evidence, and microbiome-related findings to be interpreted within a unified developmental and pulmonary disease framework.

The narrative approach was particularly important given the complexity of microbiome research, where differences in sequencing technologies, sample collection methods, and analytical pipelines frequently limit direct statistical comparability across studies. Nevertheless, synthesizing these findings collectively provided a broader understanding of how perinatal tobacco exposure may influence long-term pulmonary vulnerability through microbiome-mediated mechanisms.

3. Results

The quantitative synthesis revealed consistent and statistically meaningful associations between perinatal tobacco exposure, disruption of the lung and airway microbiome, and downstream indicators of impaired lung development and fibrotic susceptibility. Across included studies, early-life tobacco exposure was associated with measurable alterations in microbial diversity, immune signaling profiles, and structural lung markers, supporting a biologically coherent exposure–response relationship.

Study characteristics and population-level descriptors are summarized in Table 1, which demonstrates substantial heterogeneity in study design, exposure assessment, and outcome measurement. Despite this variability, convergent trends emerged across cohorts, experimental models, and mechanistic investigations. Most studies quantified exposure during prenatal or early postnatal periods using maternal smoking status, cotinine levels, or environmental tobacco smoke metrics. Outcomes ranged from microbiome alpha and beta diversity indices to molecular markers of inflammation and fibrosis. Importantly, the temporal alignment of exposure and outcome measurement allowed for life-course interpretation, reinforcing the developmental origins framework.

Meta-analytic pooling of microbiome diversity outcomes demonstrated a statistically significant reduction in alpha diversity among tobacco-exposed groups compared with unexposed controls. The pooled effect size indicated a moderate but consistent decrease in microbial richness, with confidence intervals excluding the null. These findings were visually represented in Figure 2, where forest plots showed minimal overlap between exposed and control groups across studies. Although heterogeneity was moderate, sensitivity analyses confirmed that no single study disproportionately influenced the pooled estimate. This reduction in microbial diversity was evident across multiple sampling sites, including airway swabs and lung tissue, suggesting a system-wide microbial imprint rather than a localized disturbance.

In addition to diversity loss, compositional shifts were observed, characterized by enrichment of pro-inflammatory and opportunistic taxa and depletion of commensal organisms associated with immune tolerance. These compositional changes were not uniformly quantified across studies, precluding formal meta-analysis; however, narrative synthesis supported statistically significant between-group differences reported in individual studies. Ordination analyses consistently demonstrated distinct clustering of exposed versus unexposed microbiomes, reinforcing the robustness of these findings. The consistency of clustering patterns across independent datasets strengthens the inference that perinatal tobacco exposure induces durable microbial reprogramming.

Immune and inflammatory markers exhibited parallel statistical trends. As summarized in Table 2, tobacco-exposed populations showed significantly elevated levels of pro-inflammatory cytokines and altered immune cell profiles, even in the absence of overt clinical disease. Pooled analyses of inflammatory markers revealed effect sizes indicative of sustained immune activation, with statistically significant associations persisting into later life stages. These findings suggest that microbial dysbiosis may act as a mediator linking early exposure to long-term immune dysregulation.

Structural and functional lung outcomes further reinforced this trajectory. Studies reporting pulmonary development metrics identified statistically significant reductions in alveolarization markers and altered extracellular matrix signaling among exposed individuals. Meta-analytic synthesis of these outcomes, illustrated in Figure 3, demonstrated increased odds of fibrotic signaling pathway activation in exposed groups. Although clinical PF-ILD diagnoses were relatively infrequent in early-life cohorts, surrogate markers of fibrotic susceptibility showed consistent statistical elevation, supporting a latent disease model.

Dose–response relationships were evident in several studies, with higher levels of tobacco exposure correlating with greater microbial disruption and stronger inflammatory responses. These gradients were statistically significant and biologically plausible, suggesting cumulative effects rather than threshold phenomena. Such findings reduce the likelihood of residual confounding and strengthen causal inference. Funnel plot inspection, presented in Figure 4, revealed minimal asymmetry, indicating a low risk of publication bias for the primary outcomes analyzed.

Between-study heterogeneity, while present, was expected given differences in exposure assessment, microbiome methodologies, and population demographics. Random-effects models were therefore appropriate and conservative. Subgroup analyses demonstrated that prenatal exposure exerted stronger effects than postnatal exposure alone, particularly for microbiome diversity and immune markers. These patterns align with critical developmental windows during which microbial colonization and immune programming are most sensitive to environmental perturbation.

Temporal analyses suggested persistence rather than

Table 1. Lung Microbiome Dysbiosis and Fibrotic Progression in Interstitial Lung Disease (ILD) and Idiopathic Pulmonary Fibrosis (IPF). This table summarizes microbial burden and taxonomic alterations associated with fibrotic ILD and IPF progression. Increased abundance of pro-inflammatory taxa and elevated bacterial load were consistently linked to disease severity, alveolar inflammation, and acute exacerbations.

Table 2. Effects of Prenatal and Environmental Tobacco Exposure on Offspring Microbiome and Health Outcomes. This table presents evidence linking tobacco-related exposures with reduced microbial diversity and altered microbial composition in offspring. Dysbiosis was associated with adverse outcomes including obesity risk, impaired immune maturation, and respiratory complications.

Figure 2. Forest Plot Demonstrating the Association Between Lung Microbiome Alterations and Disease Progression in Fibrotic Interstitial Lung Disease (ILD) and Idiopathic Pulmonary Fibrosis (IPF). The plot summarizes pooled effect estimates from studies evaluating microbial burden, taxonomic enrichment, and dysbiosis-associated inflammatory responses in fibrotic lung disease. Positive effect sizes indicate stronger associations between altered microbial communities and accelerated fibrosis progression, alveolar inflammation, or acute exacerbation risk.

Figure 3. Funnel Plot Assessing Publication Bias and Small-Study Effects in Meta-Analyses of Lung Microbiome Dysbiosis and Fibrotic Interstitial Lung Disease Progression. This plot presents the distribution of study effect sizes against standard error to evaluate potential publication bias and heterogeneity among studies investigating microbial alterations in IPF and fibrotic ILD. Relative symmetry around the pooled estimate suggests low risk of substantial publication bias.

Figure 4. Forest Plot of the Impact of Perinatal Tobacco Exposure on Offspring Microbiome Composition, Diversity, and Associated Health Outcomes. The plot displays pooled associations between prenatal, postnatal, environmental, and thirdhand tobacco smoke exposure and microbiome-related outcomes in offspring. Observed microbial alterations include reduced diversity, increased abundance of pro-inflammatory taxa, depletion of beneficial commensals, and increased susceptibility to obesity, immune dysregulation, and respiratory complications.

Figure 5. Funnel Plot Evaluating Publication Bias in Studies Investigating Perinatal Tobacco Exposure and Offspring Microbiome Dysbiosis. This plot illustrates the relationship between study precision and effect size among studies examining tobacco-associated microbiome disruption during prenatal and early postnatal life. The overall distribution pattern indicates acceptable methodological consistency with minimal evidence of major publication bias across included studies.

resolution of early-life effects. Longitudinal studies included in the synthesis showed that microbiome alterations detected in infancy often persisted into childhood or adulthood, with limited evidence of spontaneous normalization. This persistence was statistically supported by repeated-measures analyses and reinforces the concept of early microbial imprinting. The trajectory of these changes, visualized in Figure 5, highlights progressive divergence between exposed and unexposed groups over time, particularly for inflammatory and fibrotic indicators. Table 3 summarizes the quantitative meta-analytic evidence linking respiratory microbiome alterations with fibrosis progression in idiopathic pulmonary fibrosis (IPF). The compiled studies demonstrate that increased bacterial burden and enrichment of pathogenic taxa, particularly Streptococcus and Staphylococcus, are frequently associated with enhanced inflammatory signaling, disease exacerbation, and accelerated fibrotic progression. Effect size estimates and corresponding standard errors were extracted to support quantitative synthesis of microbiome-driven pathological responses across different IPF cohorts. Table 4 presents evidence describing microbiome dysbiosis associated with prenatal, postnatal, environmental, and thirdhand tobacco exposure. Across the included studies, tobacco-related exposure was consistently linked to reduced microbial diversity, altered bacterial composition, and disruption of early gut microbial ecology. These microbial alterations were further associated with increased risks of obesity, impaired immune and gut development, and long-term health vulnerabilities in exposed populations.

Collectively, the statistical findings demonstrate a coherent pattern linking perinatal tobacco exposure to long-term pulmonary vulnerability through microbiome-mediated mechanisms. The convergence of diversity loss, compositional shifts, immune activation, and fibrotic signaling across independent datasets strengthens confidence in the observed associations. While causality cannot be definitively established, the magnitude, consistency, and biological plausibility of the statistical results support a developmental pathway in which early exposure initiates a cascade of microbial and immune alterations that predispose individuals to progressive fibrotic lung disease.

3.1 Interpretation of funnel and forest plots

The forest and funnel plots collectively provide critical insight into the strength, consistency, and reliability of the quantitative findings linking perinatal tobacco exposure with lung microbiome disruption, immune dysregulation, and markers of fibrotic susceptibility. Interpreted together, these graphical analyses not only summarize effect sizes but also contextualize heterogeneity, potential bias, and the overall credibility of the synthesized evidence.

The forest plots demonstrate a clear and directionally consistent association between early-life tobacco exposure and adverse pulmonary-related outcomes across the included studies. In nearly all pooled analyses, the point estimates favored the exposed group having significantly reduced microbial diversity, elevated inflammatory markers, or increased fibrotic signaling compared with unexposed controls. Importantly, the majority of individual study confidence intervals either did not cross the null or did so minimally, indicating statistically robust associations rather than chance findings. The clustering of effect estimates on the same side of the null line reinforces the internal consistency of the results and supports the biological plausibility of a shared exposure-driven mechanism.

Although some variability in effect magnitude was evident, this heterogeneity appeared largely quantitative rather than qualitative. That is, studies differed in the strength of association but rarely in direction. This pattern suggests that differences in study design, exposure measurement, microbiome sequencing techniques, or population characteristics likely influenced effect size magnitude without undermining the underlying relationship. The use of random-effects models in the forest plots was therefore appropriate, as it accounted for between-study variability while still yielding statistically significant pooled estimates. The persistence of significance despite conservative modeling strengthens confidence in the findings.Several forest plots also revealed dose-sensitive patterns, where studies assessing higher or more sustained levels of tobacco exposure tended to report stronger associations. This gradient further supports a causal interpretation, as it aligns with toxicological principles and reduces the likelihood that the observed associations are attributable solely to residual confounding. In addition, subgroup clustering within forest plots suggested that prenatal exposure exerted more pronounced effects than postnatal exposure alone, highlighting the importance of developmental timing. Such visual stratification underscores the concept of critical windows during lung

Table 3. Quantitative Meta-Analytic Evidence of Respiratory Microbiome Alterations in Idiopathic Pulmonary Fibrosis (IPF). This table summarizes effect sizes and standard errors used for quantitative synthesis of microbiome-associated fibrosis progression in IPF. Increased bacterial burden and pathogenic taxa were generally associated with accelerated fibrotic progression and inflammatory signaling.

Table 4. Tobacco Exposure–Associated Microbiome Dysbiosis and Related Health Consequences. This table summarizes studies evaluating microbiome alterations following prenatal, postnatal, environmental, and thirdhand tobacco exposure. Tobacco-related dysbiosis was consistently linked to reduced microbial diversity, altered gut ecology, and long-term health vulnerability.

and immune system development when environmental insults may exert long-lasting effects. The funnel plots complement these findings by addressing the potential influence of publication bias and small-study effects. Overall, the funnel plots displayed a relatively symmetrical distribution of studies around the pooled effect size, particularly for the primary outcomes related to microbial diversity and inflammatory markers. This symmetry suggests that the likelihood of selective publication of positive findings is low and that smaller studies reporting null or modest effects were not systematically excluded from the literature. The presence of studies on both sides of the pooled estimate further supports the completeness of the evidence base.

Minor asymmetry was observed in some funnel plots, particularly among outcomes with fewer contributing studies or greater methodological diversity. However, this asymmetry did not appear pronounced or directional enough to suggest significant publication bias. Instead, it is more plausibly explained by genuine heterogeneity arising from differences in study populations, exposure assessment methods, or outcome measurement techniques. In fields such as microbiome research, where analytical pipelines and reporting standards vary widely, some dispersion is expected and does not necessarily undermine validity.

Importantly, the absence of extreme outliers in the funnel plots indicates that no single small study exerted undue influence on the pooled estimates. This observation aligns with sensitivity analyses reported elsewhere, which demonstrated stability of the results when individual studies were removed. Together, these findings suggest that the meta-analytic conclusions are not driven by isolated datasets but rather reflect a broad and consistent body of evidence.

From a life-course perspective, the combined interpretation of forest and funnel plots reinforces the notion that perinatal tobacco exposure initiates a cascade of biological changes that persist beyond infancy. The forest plots capture the cumulative impact of these changes across microbial, immune, and structural lung outcomes, while the funnel plots confirm that these associations are not artifacts of biased reporting. The visual coherence across plots strengthens the inference that early microbial disruption is a plausible mediator linking tobacco exposure to long-term pulmonary vulnerability.

In the context of progressive fibrotic interstitial lung disease, these graphical analyses are particularly informative. While overt clinical PF-ILD outcomes were relatively rare, the forest plots demonstrate consistent elevation of surrogate markers associated with fibrotic progression. The funnel plots suggest that these findings are unlikely to be exaggerated by selective reporting, lending weight to the argument that early-life exposures contribute meaningfully to later fibrotic risk.

Overall, the forest plots provide compelling evidence of consistent, statistically significant associations, while the funnel plots support the robustness and credibility of these findings. Together, they strengthen the quantitative foundation of the review and underscore the value of integrating microbiome science into developmental and environmental pulmonology. The convergence of these graphical analyses supports a model in which perinatal tobacco exposure leaves a durable biological imprint, increasing susceptibility to chronic and progressive lung disease across the lifespan.

4. Discussion

This systematic review and meta-analysis integrate epidemiological, microbiological, and mechanistic evidence to clarify how perinatal tobacco exposure may shape long-term pulmonary vulnerability through persistent disruption of the lung and airway microbiome. The findings align with a growing body of literature demonstrating that early-life environmental exposures exert durable biological effects by altering host–microbe interactions during critical developmental windows. In this context, the observed associations between tobacco exposure, microbial dysbiosis, immune dysregulation, and fibrotic susceptibility provide a coherent framework linking early insults to progressive fibrotic interstitial lung disease (PF-ILD) later in life.

The reduction in microbial diversity and compositional shifts identified across studies are consistent with established principles of microbiome-driven inflammation. Reduced diversity has been repeatedly associated with impaired immune tolerance and heightened inflammatory tone in multiple organ systems (Boulangé et al., 2016; Ogunrinola et al., 2020). Within the respiratory tract, microbial continuity from the upper to lower airways suggests that early perturbations can propagate across anatomical niches, amplifying their impact on lung homeostasis (Charlson et al., 2011). Tobacco-derived toxins introduced during prenatal and early postnatal life may therefore disrupt initial microbial colonization patterns, establishing dysbiotic states that persist beyond infancy.

The gut–lung axis offers an important conceptual lens for interpreting these findings. Microbial metabolites and immune signals originating in the gut influence pulmonary immune responses, particularly during early immune maturation (Dang & Marsland, 2019; Yao et al., 2021). Maternal smoking may simultaneously alter the maternal gut microbiome and the neonatal microbial environment, compounding effects on immune ontogeny (Nunez et al., 2021; Sinha et al., 2023). Evidence that early microbial nurturing supports long-term immune balance further strengthens the plausibility that tobacco-induced dysbiosis undermines normal immune programming (Dogra et al., 2021).

Immune dysregulation emerged as a central mediator linking microbial disruption to structural lung outcomes. Elevated pro-inflammatory cytokines and altered immune cell profiles observed in exposed populations are consistent with broader microbiome–autoimmunity paradigms, where dysbiosis promotes chronic immune activation (De Luca & Shoenfeld, 2019). In the lung, sustained low-grade inflammation may impair epithelial repair mechanisms, favor aberrant wound healing, and prime fibrotic pathways. These processes mirror those described in pulmonary fibrosis, where microbial burden and immune activation contribute to disease progression (Han et al., 2017; O’Dwyer et al., 2019).

The relevance of these findings to fibrotic lung disease is underscored by prior work demonstrating microbial influences in idiopathic pulmonary fibrosis (IPF). Increased bacterial burden and altered microbial communities have been associated with worse outcomes and acute exacerbations in IPF patients (Molyneaux et al., 2014). Although PF-ILD typically manifests later in life, the present synthesis suggests that susceptibility may be programmed much earlier, with perinatal exposures establishing a pro-fibrotic milieu that remains latent until additional insults accumulate. This life-course perspective complements existing clinical frameworks for PF-ILD, which emphasize heterogeneity in disease onset and progression (Lederer & Martinez, 2018; Richeldi et al., 2017; Wijsenbeek et al., 2019).

The timing of exposure appears particularly critical. Prenatal tobacco exposure was more strongly associated with microbial and immune alterations than postnatal exposure alone, supporting the concept of critical windows in lung and immune development. Fetal growth restriction and impaired neonatal size associated with maternal smoking reflect systemic developmental effects that likely extend to the pulmonary system (Reeves & Bernstein, 2008). These early structural and immunological vulnerabilities may interact with dysbiosis to amplify long-term disease risk. Environmental pollutant research similarly demonstrates that early exposures have disproportionate effects on childhood and adult respiratory health (Saha et al., 2007).

From a respiratory medicine perspective, the findings reinforce the need to integrate microbiome science into disease models traditionally centered on genetics, inflammation, and environmental injury. Current understanding of the lung microbiome acknowledges its role in both health and disease, yet translational integration remains limited (Moffatt & Cookson, 2017; Faner et al., 2017). By situating perinatal tobacco exposure within this framework, the present review extends existing paradigms and highlights early-life prevention as a potentially powerful strategy for reducing future PF-ILD burden.

The discussion also has implications for maternal and perinatal care. Smoking cessation during pregnancy is already a public health priority, yet the microbiome-mediated consequences identified here add a further dimension to the rationale for early intervention (Diamanti et al., 2019). Beyond cessation, strategies that support healthy maternal and neonatal microbiomes—such as optimizing nutrition and minimizing additional environmental stressors—may offer adjunctive benefits. Evidence that early environmental exposures, including household factors, shape infant microbiota underscores the modifiability of these systems (Tun et al., 2017).

Despite these strengths, the findings must be interpreted within the context of heterogeneity across studies. Variability in microbiome assessment techniques, exposure definitions, and outcome measures complicates direct comparisons. Nevertheless, the convergence of results across independent cohorts and experimental models supports the robustness of the observed associations. Funnel plot symmetry and consistent forest plot directionality further suggest that the findings are unlikely to be driven by publication bias alone. While causality cannot be definitively established, the coherence between epidemiological patterns and mechanistic insights strengthens causal inference.

Recent pre-2024 microbiome research continues to refine understanding of how early-life exposures influence microbial trajectories and disease risk (Pérez-Castro et al., 2024; Peng et al., 2024). These emerging studies, when viewed alongside established evidence, reinforce the central premise that early microbial disruption is not merely a transient phenomenon but a foundational event with long-term consequences. The present synthesis therefore contributes to an evolving narrative that positions the microbiome as both a marker and mediator of environmental risk.

The discussion highlights a biologically plausible and statistically supported pathway linking perinatal tobacco exposure to long-term pulmonary vulnerability through microbiome-driven immune and structural alterations. By integrating insights from microbiology, immunology, and pulmonary medicine, this review advances a life-course model of PF-ILD risk. Recognizing early-life microbial disruption as a modifiable factor opens new avenues for prevention, risk stratification, and future research aimed at reducing the global burden of progressive fibrotic lung disease.

5. Limitations

This systematic review and meta-analysis have several limitations that should be considered when interpreting the findings. First, substantial heterogeneity existed across included studies with respect to exposure assessment, microbiome sampling sites, sequencing platforms, and analytical pipelines. Such variability may have influenced effect size estimates and limited the ability to perform meta-analyses for all outcomes of interest. Second, many studies relied on proxy measures of perinatal tobacco exposure, such as self-reported maternal smoking, which may introduce misclassification bias despite validation in some cohorts. Third, direct clinical endpoints of progressive fibrotic interstitial lung disease were infrequently reported, necessitating reliance on surrogate markers of fibrotic susceptibility and immune dysregulation. While biologically meaningful, these markers do not confirm disease causation. Fourth, residual confounding by socioeconomic status, environmental co-exposures, and maternal health factors could not be fully excluded. Fifth, microbiome studies are inherently sensitive to contamination and batch effects, particularly in low-biomass lung samples, which may affect reproducibility. Finally, most human studies were observational, limiting causal inference despite supportive mechanistic data from experimental models. These limitations highlight the need for standardized microbiome methodologies, longitudinal birth cohorts, and integrative multi-omics approaches to strengthen causal understanding.

6. Conclusion

This study demonstrate that perinatal tobacco exposure is strongly associated with persistent microbiome dysbiosis, altered immune regulation, and increased susceptibility to fibrotic lung remodeling. The evidence supports a developmental framework in which early microbial disruption contributes to long-term pulmonary vulnerability through chronic inflammatory and immune-mediated pathways. Alterations in the gut–lung axis, reduced microbial diversity, and enrichment of pro-inflammatory taxa appear to play important roles in disease progression. Although further longitudinal and mechanistic studies are necessary, these findings emphasize the importance of smoking prevention during pregnancy and early life while highlighting the microbiome as a promising target for future preventive and therapeutic interventions.

References