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PubMed2026

Mannheimia haemolytica strain-level diversity in cattle populations.

High-resolution genomic characterization is essential for understanding diversity, pathogenicity, and transmission dynamics of bacterial pathogens. Mannheimia haemolytica (Mh) is the most consequential bacterial agent associated with bovine respiratory disease (BRD) in cattle, as a leading cause of morbidity, mortality, and antimicrobial use. Historically, BRD pathogens, including Mh, have been studied using culture or PCR approaches that provided limited ability to characterize fine-scale genomic variation across communities. Here, we evaluated target-enriched (TE) shotgun sequencing, a culture-independent method capable of strain-level resolution within metagenomic data, for detecting and characterizing Mh in comparison with qPCR and 16S rRNA gene sequencing. Nasal swabs (10 individual and 2 composited DNA samples per pen) and environmental samples (three ropes hung on pen rails and three water bowl swabs per pen) were collected from four pens in each of five distinct cattle populations. DNA was extracted for TE sequencing to identify Mh at both species and genomic sequence variant (GSV) levels, and to characterize antimicrobial resistance genes across the bacterial communities. qPCR was performed to quantify Mh genome copies, and 16S rRNA gene sequencing was used to assess the broader respiratory microbiome. TE sequencing identified Mh in 100% of TE-tested samples and classified multiple GSVs in all but 3 of 121 samples. GSV profiles clustered within housing groups and varied across cattle populations, indicating structured strain-level diversity. In contrast, Mannheimia spp. were detected in only 47.7% of samples by 16S rRNA sequencing. These findings demonstrate that TE sequencing enables sensitive, strain-level characterization of Mh in cattle and environmental samples and reveals substantial within-population genomic diversity not captured by conventional approaches.IMPORTANCETarget-enriched shotgun sequencing enabled sensitive, strain-level detection of Mannheimia haemolytica (Mh), revealing multiple co-circulating genomic sequence variants (GSVs) within and among cattle groups. This demonstrates greater genetic variability of Mh populations in beef cattle than has been previously recognized. The clustering of GSVs within housing groups, together with the overlap between respiratory and environmental samples, is consistent with the hypothesis that contagious transmission contributes to Mh ecology. These results highlight the potential utility of composite nasal swab and environmental samples for future studies evaluating relationships between Mh genomic variation and disease risk.

Animals↗
PubMed2004

The gut bacteria of insects: nonpathogenic interactions.

The diversity of the Insecta is reflected in the large and varied microbial communities inhabiting the gut. Studies, particularly with termites and cockroaches, have focused on the nutritional contributions of gut bacteria in insects living on suboptimal diets. The indigenous gut bacteria, however, also play a role in withstanding the colonization of the gut by non-indigenous species including pathogens. Gut bacterial consortia adapt by the transfer of plasmids and transconjugation between bacterial strains, and some insect species provide ideal conditions for bacterial conjugation, which suggests that the gut is a "hot spot" for gene transfer. Genomic analysis provides new avenues for the study of the gut microbial community and will reveal the molecular foundations of the relationships between the insect and its microbiome. In this review the intestinal bacteria is discussed in the context of developing our understanding of symbiotic relationships, of multitrophic interactions between insects and plant or animal host, and in developing new strategies for controlling insect pests.

Animals↗
PubMed2024

Stool Protein Mass Spectrometry Identifies Biomarkers for Early Detection of Diffuse-type Gastric Cancer.

There is a high unmet need for early detection approaches for diffuse gastric cancer (DGC). We examined whether the stool proteome of mouse models of gastric cancer (GC) and individuals with hereditary diffuse gastric cancer (HDGC) have utility as biomarkers for early detection. Proteomic mass spectrometry of the stool of a genetically engineered mouse model driven by oncogenic KrasG12D and loss of p53 and Cdh1 in gastric parietal cells [known as Triple Conditional (TCON) mice] identified differentially abundant proteins compared with littermate controls. Immunoblot assays validated a panel of proteins, including actinin alpha 4 (ACTN4), N-acylsphingosine amidohydrolase 2 (ASAH2), dipeptidyl peptidase 4 (DPP4), and valosin-containing protein (VCP), as enriched in TCON stool compared with littermate control stool. Immunofluorescence analysis of these proteins in TCON stomach sections revealed increased protein expression compared with littermate controls. Proteomic mass spectrometry of stool obtained from patients with HDGC with CDH1 mutations identified increased expression of ASAH2, DPP4, VCP, lactotransferrin (LTF), and tropomyosin-2 relative to stool from healthy sex- and age-matched donors. Chemical inhibition of ASAH2 using C6 urea ceramide was toxic to GC cell lines and GC patient-derived organoids. This toxicity was reversed by adding downstream products of the S1P synthesis pathway, which suggested a dependency on ASAH2 activity in GC. An exploratory analysis of the HDGC stool microbiome identified features that correlated with patient tumors. Herein, we provide evidence supporting the potential of analyzing stool biomarkers for the early detection of DGC. Prevention Relevance: This study highlights a novel panel of stool protein biomarkers that correlate with the presence of DGC and has potential use as early detection to improve clinical outcomes.

Feces↗
PubMed2026

New approaches to uncover COPD pathobiology and develop therapies.

Chronic obstructive pulmonary disease (COPD) was the third leading cause of global mortality in 2011 but receives limited attention and research funding. This Review describes the current knowledge on COPD risk factors, including genetic and epigenetic determinants and their interactions with the microbiome and environmental exposures. Preclinical models are being refined and single-cell transcriptomic, metabolomic, and proteomic technologies are being implemented to investigate the molecular mechanisms of disease progression. Patient cohorts to define biomarkers of early disease and the latest approaches to diagnose pre-COPD are essential to accelerate the development of novel and effective therapeutic interventions and translate new findings into clinical trials. This Review is a summary of topics covered by a symposium organized by the COPD-iNET consortium, an international network of researchers who have established a platform that facilitates collaboration of this multidisciplinary group of preclinical, translational, and clinical researchers.

Humans↗
PubMed2025

The application of AI-driven and engineered intratumoral microbes in cancer therapy.

BACKGROUND: Although investigations of the intratumoral microbiota date back thousands of years, breakthrough transformations have only recently been achieved through high-throughput sequencing and multiomic technologies. These advances have revealed diverse and tumor type-specific microbial communities that drive carcinogenesis via immunomodulation, metabolic reprogramming, and genomic instability. Current cornerstones of cancer therapies-including chemotherapy, radiotherapy, immunotherapy, and targeted therapy-are limited by systemic toxicity, localized tissue damage, drug resistance, and low patient response rates. These constraints underscore the urgent need for more effective and precise therapeutic strategies. MAIN BODY: This review comprehensively integrates artificial intelligence (AI) technologies into the characterization of the intratumoral microbiota, facilitating the development of novel computational pipelines for mapping microbe-host crosstalk. We systematically summarize recent advances in engineered microbial therapeutics, including bacteria designed for targeted antitumor activity and engineered microorganisms that enable the localized delivery of therapeutic agents. Furthermore, this review critically evaluates the safety profiles of microbiota-based interventions and discusses key challenges in clinical translation. CONCLUSIONS: By combining cutting-edge computational technologies, biological research, and clinical insights, this review aims to bridge the gap between microbiome science and oncological practice, pioneering innovative strategies for microbiota-guided diagnostics and personalized cancer therapy.

Humans↗
PubMed2026

Two worlds beneath: Distinct microbial strategies of the rock-attached and planktonic subsurface biosphere.

BACKGROUND: Microorganisms in groundwater ecosystems exist either as planktonic cells or as attached communities on aquifer rock surfaces. Attached cells outnumber planktonic ones by at least three orders of magnitude, suggesting a critical role in aquifer ecosystem function. However, particularly in consolidated carbonate aquifers, where research has predominantly focused on planktonic microbes, the metabolic potential and ecological roles of attached communities remain poorly understood. RESULTS: To investigate the differences between attached and planktonic communities, we sampled the attached microbiome from passive samplers filled with crushed carbonate rock exposed to oxic and anoxic groundwater in the Hainich Critical Zone Exploratory and compared it to a previously published, extensive dataset of planktonic communities from the same aquifer ecosystem. Microbial lifestyle (attached vs. planktonic) explained more variance in community composition than redox conditions, prompting us to further investigate its role in shaping functional and activity profiles. Metagenomic analysis revealed a striking taxonomic and functional segregation: the 605 metagenome-assembled genomes (MAGs) from attached communities were dominated by Proteobacteria (358 MAGs) and were enriched in genes for biofilm formation, chemolithoautotrophy, and redox cycling (e.g., iron and sulfur metabolism). In contrast, the 891 MAGs from planktonic communities were dominated by Cand. Patescibacteria (464 MAGs) and Nitrospirota (60 MAGs) and showed lower functional versatility. Only a few genera were shared, and even closely related MAGs (> 90% average nucleotide identity) differed in assembly size and metabolic traits, demonstrating lifestyle-specific functional adaptation. Analysis of active replication indicated that the active fraction of the attached community was primarily represented by the most abundant MAGs. Planktonic communities featured a higher fraction of active MAGs compared to attached communities, but overall with lower relative abundances. CONCLUSIONS: The high abundance, metabolic specialization, and carbon fixation potential of attached microbes suggest that they are key drivers of subsurface biogeochemical processes. Carbonate aquifers may act as much larger inorganic carbon sinks than previously estimated based on CO2 fixation rates of the planktonic communities alone. Our findings underscore the need to incorporate attached microbial communities into models of subsurface ecosystem function. Video Abstract.

Plankton↗
PubMed2026

Experimental insights in taxon-specific functional responses to droughts in glacier-fed stream biofilms.

BACKGROUND: Glacier-fed streams are predicted to face increasingly frequent and intense droughts. However, the impacts of drought events on benthic biofilm, including bacteria, eukaryotes, and viruses, the dominating life form in glacier-fed streams, remain poorly understood. RESULTS: Using streamside flume mesocosms in the Swiss Alps, we grew glacier-fed stream biofilms over 103 days and exposed them to three droughts. Using a multi-omics approach (metagenomics, metatranscriptomics, and metaproteomics), we assessed the effects of a series of droughts on the taxonomy and metabolic activity of bacterial, eukaryotic, and viral metagenome-assembled genomes (MAGs). We found that the first drought (6 h) caused only minor changes, including mild upregulation of heterotrophic metabolism and signs of stress in diatoms. In contrast, the second drought (24 h) significantly altered both the composition and functionality of the microbiome, shifting phototrophic dominance from diatoms to Cyanobacteriota, while maintaining overall phototropic biomass and further upregulating the heterotrophic metabolism. Interestingly, a third 24 h drought had no detectable transcriptomic effect between pre- and post-drought conditions, suggesting a certain level of adaptive responses to droughts, but with the low diatom abundance being maintained. CONCLUSIONS: These findings indicate that glacier-fed biofilm microorganisms initially resisted short-term drought, but a second longer drought caused important shifts in their community structure, activity, and function. Climate-induced increases in drought frequency or duration may therefore have a lasting impact on microbial ecosystem functioning in glacier-fed streams. Video Abstract.

Biofilms↗
PubMed2026

Sulfated mannan of diatoms selects host-specific microbiota in the sunlit ocean.

BACKGROUND: Diatoms, a keystone phylum in Earth's ecosystems, are responsible for substantial oxygen production and the fixation of carbon dioxide in the form of carbohydrates that fuel global food webs. They host diverse prokaryotes, yet how diatoms preferentially recruit those with complementary metabolic traits remains unknown. RESULTS: We discovered that diatoms exude a C6-sulfated α-1,3-mannan that serves as a selective carbon source for adapted Polaribacter. Its structure was resolved using NMR spectroscopy, chromatography, chemical synthesis, and enzymatic dissection. Biochemical, physiological, and structural analyses demonstrated, that specialized Bacteroidota employ a four-enzyme pathway to metabolize this glycan. Metagenomic and transcriptomic data revealed that sulfated mannan utilization loci are globally abundant and actively expressed in surface ocean bacterioplankton. Because this mannan provides only carbon, oxygen, sulfur, and hydrogen, bacteria must obtain other essential elements elsewhere, reinforcing metabolic interdependence. CONCLUSIONS: Together, these results define a chemically specific interaction between diatoms and specialized bacteria that is mediated by a single sulfated polysaccharide and a dedicated four-enzyme degradation pathway. Presence of this pathway in marine metagenomes and transcriptomes indicates that a sulfated mannan from diatoms exerts selection pressure in the sunlit ocean microbiome. Video Abstract.

Diatoms↗
PubMed2026

The need for standardization and improved open (meta)data practices in metaproteomics.

Metaproteomics enables functional insight into microbial communities by identifying and quantifying proteins in complex samples. Yet, heterogeneous analytical workflows and the lack of standardization across experimental and bioinformatics stages hinder reproducibility and comparability, limiting integration with other omics data. We here present a community-developed reporting checklist tailored to the specific needs of metaproteomics. We also outline current efforts to enable structured and interoperable metadata capture, drawing on standards from proteomics and microbiome research wherever possible. By promoting transparent reporting and advancing metadata practices, our recommendations aim to align metaproteomics more closely with FAIR principles and support reproducible and interoperable research practices. Video Abstract.

Proteomics↗
PubMed2026

Longitudinal Clinical, Physiological, and Molecular Profiling of Female Patients With Metastatic Cancer: Protocol and Feasibility of a Multicenter High-Definition Oncology Study.

PURPOSE: A substantial proportion of patients receiving genomically matched therapies do not achieve clinical benefit, underscoring the influence of nongenetic factors on cancer outcomes. High-Definition Oncology (HDO) proposes integrating longitudinal, multimodal patient data-spanning clinical, molecular, physiological, and behavioral domains-to enable truly individualized cancer care. This manuscript describes the HDO study design, framework, and feasibility results in women with metastatic cancer. METHODS: We initiated a prospective, multicenter observational study (HDO study; ClinicalTrials.gov identifier: NCT06590506) enrolling 300 female patients with newly diagnosed metastatic breast, lung, or colorectal cancer. Here, we report the study design, standardized workflows, prespecified feasibility criteria, and early internal pilot results. Eleven data modalities are collected longitudinally, including tumor and germline genomics, germline epigenomics, gut microbiome, blood and stool metabolomics and proteomics, exposome characterization, wearable-derived physiological monitoring, digital footprint assessment, medical imaging, and patient-reported outcomes. Standardized workflows govern clinical procedures, data acquisition, biospecimen processing, and quality control across all participating sites. RESULTS: Feasibility was evaluated in the first 30 participants (10% of planned accrual). Patients completed 100% of scheduled clinical visits, 97.4% of planned plasma collections, 80.7% of stool samples, and all tumor biopsies. Wearable devices captured activity, heart rate, sleep, and blood oxygen saturation data during 95.0%, 84.2%, 90.6%, and 70.7% of total patient-days, respectively. Biospecimens met predefined quality control metrics across all molecular modalities. Engagement with mobile applications for pain and emotion reporting exceeded 80%. CONCLUSION: The HDO study demonstrates the feasibility of comprehensive, longitudinal, multimodal data collection in women with metastatic cancer. This internal pilot establishes an integrated framework for future analyses aimed at characterizing disease trajectories, defining molecular and physiological determinants of outcomes, and developing patient-specific computational models.

Humans↗
PubMed2026

Characterization of the oral microbiota and antimicrobial resistance genes in shelter dogs in Japan.

Companion animals can serve as reservoirs of antimicrobial resistance genes and zoonotic microorganisms, yet information on shelter dogs remains limited. This study characterized the oral microbiota and screened for antimicrobial resistance genes in shelter dogs in Japan. Oral swabs were collected from 81 dogs, microbial genomic DNA was extracted, bacterial communities were profiled by 16S rRNA gene amplicon sequencing, and antimicrobial resistance genes were screened by PCR. We detected genes conferring resistance to several antimicrobial classes, including β-lactams, tetracyclines, macrolide-lincosamide-streptogramin B, phenicols, and sulfonamides. cfxA was detected in all 81 samples, followed by sul1 (66/81), tet(M) and sul2 (65/81), floR (39/81), mecA (17/81), and erm(B) (15/81). We identified potentially pathogenic genera including Capnocytophaga, Pasteurella, Fusobacterium, Campylobacter and Corynebacterium. Microbiome analysis revealed that at the phylum level, Pseudomonadota and Bacteroidota were the most dominant, while Porphyromonas, Frederiksenia and Moraxella were the most prevalent genera. Our findings highlight that (i) the oral microbiota of shelter dogs broadly resembles that reported in companion dogs and (ii) shelter dogs represent an overlooked reservoir of clinically relevant antimicrobial resistance genes and potentially zoonotic bacteria. Therefore, it is necessary to include shelter animals in antimicrobial resistance surveillance programs to capture any potential gaps in the antimicrobial resistance prevalence in companion animals and prevent dissemination of resistant bacteria to humans following adoption of shelter dogs and cats.

antimicrobial resistance gene↗
PubMed2025

Benchmarking with synthetic communities provides a baseline for virus-host inferences from Hi-C proximity linking.

Microbiomes influence diverse ecosystems, and viruses increasingly appear to impose key constraints. While viromics has expanded genomic catalogs, host identification for these viruses remains challenging due to the limitations in scaling cultivation-based approaches and the uncertain reliability and relative low resolution of in silico predictions - particularly for understudied viral taxa. Towards this, Hi-C proximity ligation uses sequenced, cross-linked virus and host genomic fragments to infer virus-host linkages and has now been applied in at least 10 studies. However, its accuracy remains unknown. Here we assess Hi-C performance in recovering virus-host interactions using synthetic communities (SynComs) composed of four marine bacterial strains and nine phages with known interactions and then apply optimized bioinformatic protocols to natural soil samples. In SynComs, standard Hi-C sample preparations and analyses showed poor normalized contact score performance (26% specificity, 100% sensitivity, incorrect matches up to class level) that could be dramatically improved by Z-score filtering (Z ≥ 0.5, 99% specificity), though at reduced sensitivity (62% down from 100%). Detection limits were established as reproducibility was poor below minimal phage abundances of 105 PFU/mL. Applying optimized bioinformatic protocols to natural soil samples, we compared virus-host linkages inferred from proximity-ligated Hi-C sequencing with predictions generated by in silico homology-based and machine learning-based bioinformatic approaches. Prior to Z-score thresholding, agreement was relatively high at the phylum to family levels (72%), but not at the genus (43%) or species (15%) levels. Z-score thresholding reduced sensitivity (only 34% of predictions were retained), with only modest improvements in congruence with bioinformatic methods (48% or 18% at genus or species levels, respectively). Regardless, this led to 79 genus-level-congruent virus-host linkages and 293 new ones revealed by Hi-C alone, i.e., providing many new virus-host interactions to explore in already well-studied climate-critical soils. Overall, these findings provide empirical benchmarks and methodological guidelines to improve the accuracy and reliability of Hi-C for virus-host linkage studies in complex microbial communities.

Benchmarking↗
PubMed2025

HighDimMixedModels.jl: Robust high-dimensional mixed-effects models across omics data.

High-dimensional mixed-effects models are an increasingly important form of regression in which the number of covariates rivals or exceeds the number of samples, which are collected in groups or clusters. The penalized likelihood approach to fitting these models relies on a coordinate descent algorithm that lacks guarantees of convergence to a global optimum. Here, we empirically study the behavior of this algorithm on simulated and real examples of three types of data that are common in modern biology: transcriptome, genome-wide association, and microbiome data. Our simulations provide new insights into the algorithm's behavior in these settings, and, comparing the performance of two popular penalties, we demonstrate that the smoothly clipped absolute deviation (SCAD) penalty consistently outperforms the least absolute shrinkage and selection operator (LASSO) penalty in terms of both variable selection and estimation accuracy across omics data. To empower researchers in biology and other fields to fit models with the SCAD penalty, we implement the algorithm in a Julia package, HighDimMixedModels.jl.

Algorithms↗
PubMed2025

kMermaid: Ultrafast metagenomic read assignment to protein clusters by hashing of amino acid k-mer frequencies.

Shotgun metagenomic sequencing can determine both the taxonomic and functional content of microbiomes. However, functional classification for metagenomic reads remains highly challenging as protein mapping tools require substantial computational resources and yield ambiguous classifications when short reads map to homologous proteins originating from different bacteria. Here we introduce kMermaid for the purpose of uniquely mapping bacterial short reads to taxa-agnostic clusters of homologous proteins, which can then be used for downstream analysis tasks such as read quantification and pathway or global functional analysis. Using a nested hash map containing amino acid k-mer profiles as a model for protein assignment, kMermaid achieves the sensitivity of popular existing protein mapping tools while remaining highly resource efficient. We evaluate kMermaid on simulated data and data from human fecal samples as well as demonstrate the utility of kMermaid for classifying reads originating from new, unseen proteins. kMermaid allows for highly accurate, unambiguous and ultrafast metagenomic read assignment into protein clusters, with a fixed memory usage, and can easily be employed on a typical computer.

Metagenomics↗
PubMed2022

Identification of shared bacterial strains in the vaginal microbiota of related and unrelated reproductive-age mothers and daughters using genome-resolved metagenomics.

It has been suggested that the human microbiome might be vertically transmitted from mother to offspring and that early colonizers may play a critical role in development of the immune system. Studies have shown limited support for the vertical transmission of the intestinal microbiota but the derivation of the vaginal microbiota remains largely unknown. Although the vaginal microbiota of children and reproductive age women differ in composition, the vaginal microbiota could be vertically transmitted. To determine whether there was any support for this hypothesis, we examined the vaginal microbiota of daughter-mother pairs from the Baltimore metropolitan area (ages 14-27, 32-51; n = 39). We assessed whether the daughter's microbiota was similar in composition to their mother's using metataxonomics. Permutation tests revealed that while some pairs did have similar vaginal microbiota, the degree of similarity did not exceed that expected by chance. Genome-resolved metagenomics was used to identify shared bacterial strains in a subset of the families (n = 22). We found a small number of bacterial strains that were shared between mother-daughter pairs but identified more shared strains between individuals from different families, indicating that vaginal bacteria may display biogeographic patterns. Earlier-in-life studies are needed to demonstrate vertical transmission of the vaginal microbiota.

Child↗
PubMed2024

Effectiveness of stabilization methods for the immediate and short-term preservation of bovine fecal and upper respiratory tract genomic DNA.

Previous research on stabilization methods for microbiome investigations has largely focused on human fecal samples. There are a few studies using feces from other species, but no published studies investigating preservation of samples collected from cattle. Given that microbial taxa are differentially impacted during storage it is warranted to study impacts of preservation methods on microbial communities found in samples outside of human fecal samples. Here we tested methods of preserving bovine fecal respiratory specimens for up to 2 weeks at four temperatures (room temperature, 4°C, -20°C, and -80°C) by comparing microbial diversity and community composition to samples extracted immediately after collection. Importantly, fecal specimens preserved and analyzed were technical replicates, providing a look at the effects of preservation method in the absence of biological variation. We found that preservation with the OMNIgene®•GUT kit resulted in community structure most like that of fresh samples extracted immediately, even when stored at room temperature (~20°C). Samples that were flash-frozen without added preservation solution were the next most representative of original communities, while samples preserved with ethanol were the least representative. These results contradict previous reports that ethanol is effective in preserving fecal communities and suggest for studies investigating cattle either flash-freezing of samples without preservative or preservation with OMNIgene®•GUT will yield more representative microbial communities.

Cattle↗
PubMed2024

Diverse RNA viruses discovered in multiple seagrass species.

Seagrasses are marine angiosperms that form highly productive and diverse ecosystems. These ecosystems, however, are declining worldwide. Plant-associated microbes affect critical functions like nutrient uptake and pathogen resistance, which has led to an interest in the seagrass microbiome. However, despite their significant role in plant ecology, viruses have only recently garnered attention in seagrass species. In this study, we produced original data and mined publicly available transcriptomes to advance our understanding of RNA viral diversity in Zostera marina, Zostera muelleri, Zostera japonica, and Cymodocea nodosa. In Z. marina, we present evidence for additional Zostera marina amalgavirus 1 and 2 genotypes, and a complete genome for an alphaendornavirus previously evidenced by an RNA-dependent RNA polymerase gene fragment. In Z. muelleri, we present evidence for a second complete alphaendornavirus and near complete furovirus. Both are novel, and, to the best of our knowledge, this marks the first report of a furovirus infection naturally occurring outside of cereal grasses. In Z. japonica, we discovered genome fragments that belong to a novel strain of cucumber mosaic virus, a prolific pathogen that depends largely on aphid vectoring for host-to-host transmission. Lastly, in C. nodosa, we discovered two contigs that belong to a novel virus in the family Betaflexiviridae. These findings expand our knowledge of viral diversity in seagrasses and provide insight into seagrass viral ecology.

RNA Viruses↗
PubMed2024

Design of the SPIROMICS Study of Early COPD Progression: SOURCE Study.

BACKGROUND: The biological mechanisms leading some tobacco-exposed individuals to develop early-stage chronic obstructive pulmonary disease (COPD) are poorly understood. This knowledge gap hampers development of disease-modifying agents for this prevalent condition. OBJECTIVES: Accordingly, with National Heart, Lung and Blood Institute support, we initiated the SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study of Early COPD Progression (SOURCE), a multicenter observational cohort study of younger individuals with a history of cigarette smoking and thus at-risk for, or with, early-stage COPD. Our overall objectives are to identify those who will develop COPD earlier in life, characterize them thoroughly, and by contrasting them to those not developing COPD, define mechanisms of disease progression. METHODS/DISCUSSION: SOURCE utilizes the established SPIROMICS clinical network. Its goal is to enroll n=649 participants, ages 30-55 years, all races/ethnicities, with ≥10 pack-years cigarette smoking, in either Global initiative for chronic Obstructive Lung Disease (GOLD) groups 0-2 or with preserved ratio-impaired spirometry; and an additional n=40 never-smoker controls. Participants undergo baseline and 3-year follow-up visits, each including high-resolution computed tomography, respiratory oscillometry and spirometry (pre- and postbronchodilator administration), exhaled breath condensate (baseline only), and extensive biospecimen collection, including sputum induction. Symptoms, interim health care utilization, and exacerbations are captured every 6 months via follow-up phone calls. An embedded bronchoscopy substudy involving n=100 participants (including all never-smokers) will allow collection of lower airway samples for genetic, epigenetic, genomic, immunological, microbiome, mucin analyses, and basal cell culture. CONCLUSION: SOURCE should provide novel insights into the natural history of lung disease in younger individuals with a smoking history, and its biological basis.

SPIROMICS↗