Evidence map›Paper›PMID 39143108›Full record

ArticleNPJ biofilms and microbiomes2024

Associations between gut microbiota and incident fractures in the FINRISK cohort.

Louise Grahnemo, Oleg Kambur, Leo Lahti, Pekka Jousilahti, Teemu Niiranen, Rob Knight, Veikko Salomaa, Aki S Havulinna, Claes Ohlsson

Abstract read
In one paragraph

Article in NPJ biofilms and microbiomes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Review
  2. Review
  3. Links between bone fractures and the gut microbiota.Nature reviews. Endocrinology · 2026
    Review
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  7. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Louise Grahnemo *Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.ORCID http://orcid.org/0000-0001-5276-6612
Oleg Kambur *Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland.
Leo LahtiDepartment of Computing, University of Turku, Turku, Finland.ORCID http://orcid.org/0000-0001-5537-637X
Pekka JousilahtiDepartment of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland.ORCID http://orcid.org/0000-0001-7190-0979
Teemu NiiranenDepartment of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland.
Rob KnightDepartment of Pediatrics, University of California San Diego, La Jolla, CA, USA.
Veikko SalomaaDepartment of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland.ORCID http://orcid.org/0000-0001-7563-5324
Aki S HavulinnaDepartment of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland.ORCID http://orcid.org/0000-0002-4787-8959
Claes OhlssonDepartment of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. claes.ohlsson@medic.gu.se.ORCID http://orcid.org/0000-0002-9633-2805

Funding

European Research Council 101096347IngaBritt och Arne Lundbergs Forskningsstiftelse (Ingabritt and Arne Lundberg Research Foundation) LU2021-0096Knut och Alice Wallenbergs Stiftelse (Knut and Alice Wallenberg Foundation) KAW 2015.0317Novo Nordisk Fonden (Novo Nordisk Foundation) NNF 190C0055250 and 22OC0078421Vetenskapsrådet (Swedish Research Council) 2020-01392
6 · The paper itself

Abstract

The gut microbiota (GM) can regulate bone mass, but its association with incident fractures is unknown. We used Cox regression models to determine whether the GM composition is associated with incident fractures in the large FINRISK 2002 cohort (n = 7043, 1092 incident fracture cases, median follow-up time 18 years) with information on GM composition and functionality from shotgun metagenome sequencing. Higher alpha diversity was associated with decreased fracture risk (hazard ratio [HR] 0.92 per standard deviation increase in Shannon index, 95% confidence interval 0.87-0.96). For beta diversity, the first principal component was associated with fracture risk (Aitchison distance, HR 0.90, 0.85-0.96). In predefined phyla analyses, we observed that the relative abundance of Proteobacteria was associated with increased fracture risk (HR 1.14, 1.07-1.20), while the relative abundance of Tenericutes was associated with decreased fracture risk (HR 0.90, 0.85-0.96). Explorative sub-analyses within the Proteobacteria phylum showed that higher relative abundance of Gammaproteobacteria was associated with increased fracture risk. Functionality analyses showed that pathways related to amino acid metabolism and lipopolysaccharide biosynthesis associated with fracture risk. The relative abundance of Proteobacteria correlated with pathways for amino acid metabolism, while the relative abundance of Tenericutes correlated with pathways for butyrate synthesis. In conclusion, the overall GM composition was associated with incident fractures. The relative abundance of Proteobacteria, especially Gammaproteobacteria, was associated with increased fracture risk, while the relative abundance of Tenericutes was associated with decreased fracture risk. Functionality analyses demonstrated that pathways known to regulate bone health may underlie these associations.

Indexed as

Fractures, BoneGastrointestinal MicrobiomeAdultAgedBacteriaCohort StudiesFemaleFinlandHumansIncidenceMaleMetagenomeMetagenomicsMiddle AgedProteobacteriaRisk Factors

Identifiers

PMID39143108
PMCPMC11324742

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.