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Record W4390600689 · doi:10.1093/jbmr/zjad017

Alteration in the gut microbiome is associated with changes in bone metabolism after laparoscopic sleeve gastrectomy

2024· article· en· W4390600689 on OpenAlexaff
Karin C Wu, Kathryn McCauley, Susan V. Lynch, Renuka R. Nayak, Nicole J King, Sheena Patel, Tiffany Y. Kim, Katherine Condra, Doug Fadrosh, Dat Nguyen, Din L. Lin, Kole Lynch, Stanley J. Rogers, Jonathan Carter, Andrew M. Posselt, Lygia Stewart, Anne L. Schafer

Bibliographic record

VenueJournal of Bone and Mineral Research · 2024
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersNational Center for Advancing Translational SciencesNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Diabetes and Digestive and Kidney DiseasesUniversity of California, San FranciscoNational Institutes of HealthNorthern California Institute for Research and EducationAmgenU.S. Department of Veterans Affairs
KeywordsBone remodelingMicrobiomeSleeve gastrectomyMedicineN-terminal telopeptideInternal medicineObesityEndocrinologyFecesGut floraPhysiologyGastroenterologyBiologyWeight lossBioinformaticsImmunologyMicrobiologyBiochemistryGastric bypass

Abstract

fetched live from OpenAlex

Laparoscopic sleeve gastrectomy (LSG), the most common bariatric surgical procedure, leads to durable weight loss and improves obesity-related comorbidities. However, it induces abnormalities in bone metabolism. One unexplored potential contributor is the gut microbiome, which influences bone metabolism and is altered after surgery. We characterized the relationship between the gut microbiome and skeletal health in severe obesity and after LSG. In a prospective cohort study, 23 adults with severe obesity underwent skeletal health assessment and stool collection preoperatively and 6 mo after LSG. Gut microbial diversity and composition were characterized using 16S rRNA gene sequencing, and fecal concentrations of short-chain fatty acids (SCFA) were measured with LC-MS/MS. Spearman's correlations and PERMANOVA analyses were applied to assess relationships between the gut microbiome and bone health measures including serum bone turnover markers (C-terminal telopeptide of type 1 collagen [CTx] and procollagen type 1 N-terminal propeptide [P1NP]), areal BMD, intestinal calcium absorption, and calciotropic hormones. Six months after LSG, CTx and P1NP increased (by median 188% and 61%, P < .01) and femoral neck BMD decreased (mean -3.3%, P < .01). Concurrently, there was a decrease in relative abundance of the phylum Firmicutes. Although there were no change in overall microbial diversity or fecal SCFA concentrations after LSG, those with greater within-subject change in gut community microbial composition (β-diversity) postoperatively had greater increases in P1NP level (ρ = 0.48, P = .02) and greater bone loss at the femoral neck (ρ = -0.43, P = .04). In addition, within-participant shifts in microbial richness/evenness (α-diversity) were associated with changes in IGF-1 levels (ρ = 0.56, P < .01). The lower the postoperative fecal butyrate concentration, the lower the IGF-1 level (ρ = 0.43, P = .04). Meanwhile, the larger the decrease in butyrate concentration, the higher the postoperative CTx (ρ = -0.43, P = .04). These findings suggest that LSG-induced gut microbiome alteration may influence skeletal outcomes postoperatively, and microbial influences on butyrate formation and IGF-1 are possible mechanisms.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.041
GPT teacher head0.353
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2024
Admission routes1
Has abstractyes

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