Impact of Short-term E-cigarette Cessation on the Nasal Microbiome in Young Adult Vapers
Bibliographic record
Abstract
Abstract RATIONALE: E-cigarette use has surged among young adults, raising concerns about its health impacts on the respiratory tract. E-cigarette use has been associated with alterations in the nasal microbiome, potentially leading to increased susceptibility to upper respiratory infections. Effects of vaping on nasal immunity is a growing area of research, and the associated potential for acute changes in immune-mediated endpoints upon cessation is an open question. Our study aimed to investigate changes in the nasal microbiome in young adult e-cigarette users before and after a 72-hour cessation period. METHODS: Participants (N=24) aged 19–30, who regularly vaped nicotine (≥20 of past 30 days), but did not smoke tobacco cigarettes or any other substances, provided nasal brushing samples at Visit 1 (at time of cessation) and Visit 4 (72h post-cessation). DNA was extracted from nasal brushings using the DNeasy Blood & Tissue Kit (Qiagen) and paired-end sequenced using V4 variable region 16S rRNA gene sequencing (MiSeq). Microbiome bioinformatics were performed with QIIME 2 (version 2024.5), and denoised with DADA2 to assign amplicon sequence variants (ASVs) for taxonomic classification with the SILVA 138 reference database. Statistical analyses were conducted, focusing on microbial diversity and relative abundance changes in identified taxa. RESULTS: Our analysis revealed significant changes in the nasal microbiome of young adult e-cigarette users following a brief cessation period. Specific taxa demonstrated significant shifts in relative abundance, including decreased Xanthobacteraceae (p=0.02) and Corynebacteriaceae (p=0.03), and increased Chloroplast (p=0.03) and Planococcaceae (p=0.04) (Figure 1A). Taxa such as Sphingomonadaceae (p=0.05), Corynebacterium (p=0.05), Chlamydiaceae (p=0.06), and Spirosomaceae (p=0.06) also exhibited noteworthy changes in abundance (Figure 1A). Alpha diversity, as measured by the Simpson's Diversity Index, increased significantly from 0.78 at Visit 1 to 0.83 at Visit 4 (p=0.03), indicating a shift to greater microbial evenness and diversity post-cessation (Figure 1B). CONCLUSIONS: Short-term e-cigarette cessation induces detectable shifts in the nasal microbiome of young adult vapers. Significant shifts in specific taxa highlight the nasal microbiome's dynamic response to cessation, with increases in beneficial and decreases in potentially harmful taxa suggesting a trend towards recovery. Enhanced microbial diversity suggests potential recovery from e-cigarette-induced dysbiosis, which may improve respiratory health and immune function, as higher diversity is linked to protection against respiratory infections and inflammation. Understanding these changes is essential for assessing vaping's impact on respiratory health and the potential benefits of cessation. Further research should elucidate these taxa's functional roles and long-term health effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".