Association of Faecalibacterium, Lachnospira, Veillonella, and Rothia with childhood wheezing
Bibliographic record
Abstract
Wheezing symptoms among children, present major health and economic problems globally. A recent study conducted in Canada observed a reduction in stool bacterial genera Faecalibacterium, Lachnospira, Veillonella and Rothia (FLVR) in three-month old infants with atopy-wheeze symptoms. It is not known whether this is true in different human populations worldwide. The overall aim of this dissertation was to investigate the contribution of any of the FLVR bacteria or their combination in the occurrence of infant wheezing within the Drakenstein Child Health Study (DCHS), South Africa. To address this aim, I began my thesis's project by conducting a systematic literature review which investigated the association of FLVR bacteria with the occurrence of different respiratory diseases in humans. My review provided evidence for the possible involvement of FLVR bacteria in human respiratory diseases, including asthma, pulmonary tuberculosis and pneumonia. Furthermore, this review highlighted the need for a well-designed and large study to investigate the contribution of the FLVR bacteria in respiratory diseases, in an African setting. Secondly, I optimized SYBR Green based real-time quantitative polymerase chain reaction (qPCR) as well as conventional PCR assays for the detection of FLVR bacteria. Using the optimized assays, I screened 533 stool samples collected from 140 wheezing and 140 nonwheezing infants. The optimized assays demonstrated good performance in the detection of FLVR bacteria from human stool samples. Using qPCR, Rothia, Veillonella, Faecalibacterium and Lachnospira were detected in 90% (479/533), 73% (388/533), 51% (274/533) and 14% (77/533) of the samples, respectively. Conventional PCR permitted the detection of Rothia, Veillonella, Faecalibacterium and Lachnospira in 55% (263/479), 74% (289/388), 53% (145/274) and 0% (0/77) of the qPCR positive samples, respectively. I also determined the factors associated with faecal colonization by FLVR bacteria in the first year of life. I showed that reduced colonisation by Faecalibacterium was associated with male gender (adjusted OR = 0.65, 95%CI: 0.42 - 0.98) and TC-Newman residence (adjusted OR = 0.52, 95%CI: 0.29 - 0.91). Breastfeeding was associated with less colonisation by both Lachnospira, (adjusted OR = 0.17, 95%CI: 0.05 - 0.49) and Veilonella (adjusted OR = 0.32, 95%CI: 0.10 - 0.91). Mother's tertiary education was significantly associated with high Rothia colonisation (adjusted OR = 11.73, 95%CI: 1.36 - 2.58). In the last section of my thesis, I assessed the association of FLVR bacteria with infant wheezing using logistic regression models. I found a significant association of Rothia with reduced risk of infant wheezing (adjusted odds ratio (aOR)=0.54, 95%CI: 0.28-0.93) and recurrent wheezing (aOR=0.29, 95%CI: 0.05-0.88). Using receiver operating characteristic curves (ROC), I showed that among all FLVR bacteria, Lachnospira (AUROC = 0.833, 95%CI: 0.64-1.00) and Rothia (AUC=0.707, 95%CI: 0.62-0.79) could serve as biomarkers for early prediction of infant wheezing. Overall, this is the first study on FLVR bacteria and infant wheezing to be conducted in Africa. Its findings encourage more research to be conducted in order to elucidate the potential protective role of Rothia against childhood wheeze and asthma, as well as the contribution of Lachnospira in asthma development.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".