Healthspan and lifespan extension by fecal microbiota transplantation into progeroid mice
Open accessAbstract
The gut microbiome is emerging as a key regulator of several metabolic, immune and neuroendocrine pathways 1,2. Gut microbiome deregulation has been implicated in major conditions such as obesity, type 2 diabetes, cardiovascular disease, non-alcoholic fatty acid liver disease and cancer 3-6, but its precise role in aging remains to be elucidated. Here, we find that two different mouse models of progeria are characterized by intestinal dysbiosis with alterations that include an increase in the abundance of Proteobacteria and Cyanobacteria, and a decrease in the abundance of Verrucomicrobia. Consistent with these findings, we found that human progeria patients also display intestinal dysbiosis and that long-lived humans (that is, centenarians) exhibit a substantial increase in Verrucomicrobia and a reduction in Proteobacteria. Fecal microbiota transplantation from wild-type mice enhanced healthspan and lifespan in both progeroid mouse models, and transplantation with the verrucomicrobia Akkermansia muciniphila was sufficient to exert beneficial effects. Moreover, metabolomic analysis of ileal content points to the restoration of secondary bile acids as a possible mechanism for the beneficial effects of reestablishing a healthy microbiome. Our results demonstrate that correction of the accelerated aging-associated intestinal dysbiosis is beneficial, suggesting the existence of a link between aging and the gut microbiota that provides a rationale for microbiome-based interventions against age-related diseases.
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TL;DR
Fecal microbiota transplantation from wild-type donors into progeroid mice extends healthspan and lifespan, while progeroid microbiota can induce metabolic alterations in wild-type recipients. The study links progeria-associated gut dysbiosis to loss of Akkermansia and altered bile acid metabolism, with A. muciniphila supplementation modestly extending lifespan in progeroid mice.
Key findings
- Progeroid mouse models and human progeria patients show intestinal dysbiosis; Lmna G609G/G609G mice at 4 months lose Akkermansia and show increased Enterobacteriaceae, while centenarians have higher Akkermansia, Ruminococcaceae, Christensenellaceae, and Enterobacteriaceae.
- FMT from WT donors into Lmna G609G/G609G mice improved survival (P = 0.0029), with a 13.5% increase in median lifespan (160 vs 141 days) and 9% extended maximal survival (P = 0.04); FMT from old progeroid donors reduced survival (P = 0.045; median 129 days).
- FMT from WT donors into Zmpste24−/− mice enhanced survival (P = 0.0092), with a 13.4% median lifespan increase (279 vs 246 days) and almost 8% maximal survival increase (P = 0.09).
- Oral A. muciniphila supplementation in Lmna G609G/G609G mice modestly extended lifespan (P = 0.016), induced ileal Reg3g and Tff3, thickened intestinal mucosa, and FMT restored depleted secondary bile acids and metabolites including arabinose, ribose, inosine, and PCae(18:0).
Methods
- Gut metagenomic profiling by 16S rRNA V3–V4 sequencing in Lmna G609G/G609G and Zmpste24−/− mice, human HGPS/NGPS families, centenarians (n = 17) and healthy controls (n = 14), using QIIME 2/DADA2, LEfSe, PICRUSt, and HUMAnN2.
- FMT experiments: antibiotic cocktail followed by oral gavage of microbiome suspensions from WT or old progeroid donors into progeroid or WT mice, with assessment of survival, body weight/temperature, glucose, histology, and calorimetry.
- A. muciniphila culture and oral gavage; metabolomic profiling of ileal content by GC-MS and UHPLC-MS; survival analyzed by Kaplan-Meier log-rank tests and maximal survival by Fisher’s exact test at the 80th percentile.
Limitations
- The paper states that human progeria samples were low in number and that environment may have more influence on the gut microbiome than the pathological condition.
- The paper states that future work is needed to identify the functional mechanisms by which specific bacterial species and metabolites mediate the healthspan and lifespan extension conferred by FMT, and to explore applicability in normal or accelerated aging.
- Evident from the text: human progeria analyses included only four HGPS children and one NGPS patient with siblings, and the centenarian cohort was small (17 centenarians vs 14 controls), limiting generalizability; the study also notes a possible beneficial effect of the FMT protocol per se in old-donor transplanted progeroid mice.
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Claims the paper makes
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- Findingown data
Oral gavage of Akkermansia muciniphila extends the lifespan of progeroid mice.
“Analysis of centenarians and progeria mouse models point to a beneficial role for the genus Akkermansia, as oral gavage of Akkermansia muciniphila extends the lifespan of progeroid mice.”
Quote in the paperSubstantial claim - Findingnone given
The microbiota of centenarians is characterized by the presence of both pathological- and health-associated bacterial genera.
“In turn, the microbiota of centenarians is characterized by the presence of both pathological-and healthassociated bacterial genera.”
Quote in the paperNot a substantial claim - Findingown data
FMT from progeroid donors to wild-type recipients induces metabolic alterations.
“We show that fecal microbiota transplantation (FMT) from wild-type (WT) donors to progeroid recipients attenuates the accelerated-aging phenotype and increases survival, whereas FMT from progeroid donors to WT recipients induces metabolic alterations.”
Quote in the paperSubstantial claim - Findingown data
Lmna G609G/G609G 4mo mice show a loss in Clostridiaceae, Allobaculum, Sutterella, Dehalobacterium, Rikenella and Akkermansia.
“At a lower taxonomical level, Lmna G609G/G609G 4mo mice showed a loss in Clostridiaceae, Allobaculum, Sutterella, Dehalobacterium, Rikenella and Akkermansia (Fig. 1d).”
Quote in the paperSubstantial claim - Findingown data
When samples were compared by geographical location (families), a differential clustering was observed at quantitative and qualitative levels.
“However, when samples were compared by geographical location (i.e., comparing families), a differential clustering was observed at the quantitative (Fig. 2b) and qualitative levels (Extended Data Fig. 4e).”
Quote in the paperSubstantial claim
- Findingown data
FMT from wild-type donors to progeroid recipients increases survival.
“We show that fecal microbiota transplantation (FMT) from wild-type (WT) donors to progeroid recipients attenuates the accelerated-aging phenotype and increases survival, whereas FMT from progeroid donors to WT recipients induces metabolic alterations.”
Quote in the paperSubstantial claim - Findingown data
Lmna G609G/G609G 4mo mice exhibit an increment in Mucispirillum, Enterococcus, Acinetobacter, Staphylococcus, Parabacteroides, Bacteroides, Prevotella and Enterobacteriaceae.
“By contrast, Lmna G609G/G609G 4mo exhibited an increment in Mucispirillum, Enterococcus, Acinetobacter, Staphylococcus, Parabacteroides, Bacteroides, Prevotella and Enterobacteriaceae, which contains the genus Escherichia and has been associated with dysbiosis and intestinal inflammation 20 (Fig. 1d).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [20] Maharshak, N. et al. Altered enteric microbiota ecology in interleukin 10-deficient mice during development and progression of intestinal inflammation. Gut Microbes 4, 316–324 (2013). source
Not checked in the free run.
- Findingown data
Zmpste24 -/- mice showed a tendency to a lower amount of Verrucomicrobia.
“Zmpste24 -/-mice also showed a tendency to a lower amount of Verrucomicrobia (Extended Data Fig. 3e), although this trend was less marked than in Lmna G609G/G609G animals, perhaps due to the later onset of the progeroid phenotype in Zmpste24 -/-mice.”
Quote in the paperNot a substantial claim - Findingown data
FMT from wild-type donors to progeroid recipients attenuates the accelerated-aging phenotype.
“We show that fecal microbiota transplantation (FMT) from wild-type (WT) donors to progeroid recipients attenuates the accelerated-aging phenotype and increases survival, whereas FMT from progeroid donors to WT recipients induces metabolic alterations.”
Quote in the paperSubstantial claim - Findingown data
Intestinal dysbiosis was found in both mouse models and progeria patients.
“We found intestinal dysbiosis in both mouse models and progeria patients.”
Quote in the paperSubstantial claim - Findingown data
Lmna G609G/G609G 4mo mice show differential clustering in beta-diversity by PCoA using Bray-Curtis dissimilarity and Jaccard distances.
“Next, we evaluated the beta-diversity across mouse groups, identifying a differential clustering of Lmna G609G/G609G 4mo mice in a principal coordinate analysis (PCoA) using the Bray-Curtis dissimilarity (qualitative measure) (Fig 1a) and the Jaccard distances (quantitative measure) (Extended Data Fig. 1d).”
Quote in the paperNot a substantial claim - Findingown data
No differences in bacterial diversity or richness were observed within any of the mouse groups.
“We did not observe differences in bacterial diversity or richness within any of the mouse groups (Extended Data Fig. 1b,c and Supplementary Table 1).”
Quote in the paperNot a substantial claim - Findingown data
No progeria-related features were observed in WT-oG609Gmic mice.
“We did not observe progeria-related features in WT-oG609Gmic mice.”
Quote in the paperSubstantial claim - Findingown data
Lmna G609G/G609G -WTmic exhibited an extended maximal survival (9% increment, P = 0.04).
“Lmna G609G/G609G -WTmic also exhibited an extended maximal survival (9% increment, P = 0.04) (Fig. 3f and Extended Data Fig. 6e).”
Quote in the paperSubstantial claim - Findingcitation
A. muciniphila supplementation induced ileal expression of Reg3g.
“As previously described 19 , A. muciniphila supplementation induced ileal expression of Reg3g (Fig. 4b) and favored the thickening of the intestinal mucosa layer (Fig. 4c).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [19] Everard, A. et al. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proc. Natl Acad. Sci. USA 110, 9066–9071 (2013). source
Not checked in the free run.
- Findingown data
Lmna G609G/G609 -EmptyT did not show survival differences when compared to control Lmna G609G/G609G mice.
“Lmna G609G/G609 -EmptyT did not show survival differences when compared to control Lmna G609G/G609G mice (Extended Data Fig. 6f).”
Quote in the paperNot a substantial claim - Findingown data
PCoA of beta-diversity among fecal samples by health status (Control vs Progeria) showed no significant difference (P = 0.5, PERMANOVA).
“(a,b) PCoA of beta-diversity using the Bray-Curtis dissimilarity metric among fecal samples analyzed by (a) health status (P = 0.5, PERMANOVA) (Control, n = 9 individuals; Progeria, n = 5 individuals)”
Quote in the paperNot a substantial claim - Findingown data
Phenotype-dependent hypoglycemia was avoided in Lmna G609G/G609G -WTmic.
“Phenotype-dependent hypoglycemia was avoided and renal perivascular fibrosis was attenuated in Lmna G609G/G609G -WTmic (Fig. 3d,e).”
Quote in the paperNot a substantial claim - Findingown data
Centenarians exhibited a higher abundance of Enterobacteriaceae, Ruminococcaceae and Christensenellaceae and the genera Klebsiella, Lactobacillus, Parabacteroides and Akkermansia.
“Notably, centenarians exhibited a higher abundance of Enterobacteriaceae, Ruminococcaceae and Christensenellaceae and the genera Klebsiella, Lactobacillus, Parabacteroides and Akkermansia (Fig. 2f).”
Quote in the paperNot a substantial claim - Findingown data
PCoA of beta-diversity of healthy controls and centenarians showed significant difference (P = 0.001, PERMANOVA).
“(d) PCoA of beta-diversity using the Bray-Curtis dissimilarity metric of healthy controls (HC; n = 14 individuals) and centenarians (Ce; n = 17 individuals) (P = 0.001, PERMANOVA).”
Quote in the paperNot a substantial claim - Findingown data
Supplementing Lmna G609G/G609G mice with A. muciniphila through oral gavage produced a modest lifespan extension (P = 0.016).
“By supplementing Lmna G609G/G609G mice with A. muciniphila through oral gavage, we obtained a modest lifespan extension (P = 0.016) (Fig. 4a), suggesting a protective role of this microorganism against accelerated aging manifestations.”
Quote in the paperSubstantial claim - Findingown data
Lmna G609G/G609G mice ileal content exhibited a depletion of the monosaccharides arabinose and ribose, the nucleoside inosine, and the ether-phospholipid PCae (18:0) that was reversed upon FMT with WT microbiota.
“Moreover, Lmna G609G/G609G mice ileal content exhibited a depletion of the monosaccharides arabinose and ribose, the nucleoside inosine, and the ether-phospholipid PCae (18:0) that was reversed upon FMT with WT microbiota (Fig. 4f).”
Quote in the paperNot a substantial claim - Findingcitation
A. muciniphila supplementation favored the thickening of the intestinal mucosa layer.
“As previously described 19 , A. muciniphila supplementation induced ileal expression of Reg3g (Fig. 4b) and favored the thickening of the intestinal mucosa layer (Fig. 4c).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [19] Everard, A. et al. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proc. Natl Acad. Sci. USA 110, 9066–9071 (2013). source
Not checked in the free run.
- Findingown data
Centenarians and controls clustered differentially based on quantitative and qualitative beta-diversity indexes, indicating a different microbial community structure.
“Also, both groups clustered differentially, based on quantitative (Fig. 2d) and qualitative (Extended Data Fig. 5d) beta-diversity indexes, indicating that centenarians had a different microbial community structure than controls.”
Quote in the paperSubstantial claim - Findingown data
Lmna G609G/G609G -WTmic manifested a delayed loss of body weight and temperature.
“Lmna G609G/G609G -WTmic manifested a delayed loss of body weight and temperature (Fig. 3b,c).”
Quote in the paperSubstantial claim - Findingown data
In each of the studied families, the progeria patients had a different gut microbiome profile compared to their healthy siblings.
“Yet, in each of the studied families, the progeria patients had a different profile compared to their healthy siblings.”
Quote in the paperNot a substantial claim - Findingown data
LEfSe analysis showed bacterial genera whose abundance significantly differed between progeria patients and their healthy siblings.
“(c).Results of LEfSe analysis showing bacterial genera whose abundance significantly differed between progeria patients and their healthy siblings (Control=9 individuals; Progeria=5 individuals).”
Quote in the paperNot a substantial claim - Findingown data
Some intestinal inflammation markers were also decreased in Lmna G609G/G609G -oG609Gmic.
“Surprisingly, some markers were also decreased in Lmna G609G/G609G -oG609Gmic, pointing to a possible beneficial effect of the FMT protocol per se (Extended Data Fig. 6d).”
Quote in the paperNot a substantial claim - Findingown data
PCoA of beta-diversity between Zmpste24-/- and WT mice shows a significant difference (P = 0.003, PERMANOVA).
“(f) PCoA of beta-diversity using the Bray-Curtis dissimilarity metric between Zmpste24 -/-and WT mice (P = 0.003, PERMANOVA).”
Quote in the paperNot a substantial claim - Findingown data
LEfSe analysis showed bacterial classes significantly different in abundance between Zmpste24-/- and WT mice.
“(h).LEfSe analysis showing bacterial classes that were significantly different in abundance between Zmpste24 -/-and WT mice.”
Quote in the paperNot a substantial claim - Findingown data
Renal perivascular fibrosis was attenuated in Lmna G609G/G609G -WTmic.
“Phenotype-dependent hypoglycemia was avoided and renal perivascular fibrosis was attenuated in Lmna G609G/G609G -WTmic (Fig. 3d,e).”
Quote in the paperSubstantial claim - Findingown data
Metabolite set enrichment analysis detected an enrichment in 'secondary bile acid biosynthesis'.
“Significant changes were analyzed by metabolite set enrichment analysis using KEGG pathways, detecting an enrichment in 'secondary bile acid biosynthesis' (Fig. 4d).”
Quote in the paperNot a substantial claim - Findingown data
Lmna G609G/G609G mice receiving A. muciniphila showed an increment in the intestinal trefoil factor Tff3.
“Lmna G609G/G609G mice receiving A. muciniphila also showed an increment in the intestinal trefoil factor Tff3 (Fig. 4b), which might promote wound healing and repair of the mucosa layer 27 .”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [27] Kalabis, J., Rosenberg, I. & Podolsky, D. K. Vangl1 protein acts as a downstream effector of intestinal trefoil factor (ITF)/TFF3 signaling and regulates wound healing of intestinal epithelium. J. Biol. Chem. 281, 6434–6441 (2006). source
Not checked in the free run.
- Findingown data
Gut dysbiosis occurs in Lmna G609G/G609G and Zmpste24-/- progeroid mice.
“Gut dysbiosis in Lmna G609G/G609G and Zmpste24 -/-progeroid mice.”
Quote in the paperSubstantial claim - Findingown data
Maximum survival was increased by almost 8% in Zmpste24 -/--WTmic mice (P = 0.09).
“Maximum survival was increased by almost 8% (P = 0.09) (Fig. 3o and Extended Data Fig. 8b).”
Quote in the paperNot a substantial claim - Findingown data
LEfSe analysis showed bacteria at the lowest taxonomic level significantly different in abundance in centenarians vs healthy controls.
“(f) Results of LEfSe analysis showing bacteria, at the lowest taxonomic level, that were significantly different in abundance in centenarians (Ce; n = 17 individuals) vs healthy controls (HC; n = 14 individuals).”
Quote in the paperNot a substantial claim - Interpretationown data
The environment has more influence on the gut microbiome than the pathological condition in human progeria.
“Despite the low number of samples, these results suggest that the environment has more influence on the gut microbiome than the pathological condition, which is in accordance with recent findings 22,23 .”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [22] Rothschild, D. et al. Environment dominates over host genetics in shaping human gut microbiota. Nature 555, 210–215 (2018). source
Not checked in the free run.
- cites [23] Lloyd-Price, J. et al. Strains, functions and dynamics in the expanded Human Microbiome Project. Nature 550, 61–66 (2017). source
Not checked in the free run.
- Interpretationown data
Analysis of centenarians and progeria mouse models points to a beneficial role for the genus Akkermansia.
“Analysis of centenarians and progeria mouse models point to a beneficial role for the genus Akkermansia, as oral gavage of Akkermansia muciniphila extends the lifespan of progeroid mice.”
Quote in the paperSubstantial claim - Study design and conductown data
Changes in Escherichia and Akkermansia were validated at the species level by qPCR in a second, independent group of Lmna G609G/G609G mice.
“Changes in Escherichia and Akkermansia were validated afterwards at the species level by qPCR in a second, independent group of Lmna G609G/G609G mice (Fig. 1e).”
Quote in the paperNot a substantial claim - Study design and conductown data
Effective gut colonization was validated by comparing the metagenomic profiles of control, transplanted and donor mice.
“Effective gut colonization was validated by comparing the metagenomic profiles of control, transplanted and donor mice (Extended Data Fig. 6a,b).”
Quote in the paperSubstantial claim - Study design and conductown data
FMT effectiveness was evaluated by comparing the gut metagenomic profiles of control, transplanted and donor mice, showing that transplanted progeroid mice acquired the donor microbiota.
“FMT effectiveness was evaluated by comparing the gut metagenomic profiles of control, transplanted and donor mice, showing that transplanted progeroid mice acquired the donor microbiota (Extended Data Fig. 6a,b).”
Quote in the paperSubstantial claim - Interpretationreasoning
The restoration of secondary bile acids and other metabolites (arabinose, ribose, inosine) by FMT might contribute to extend healthspan and lifespan in progeroid mice.
“Considering that bile acids regulate metabolism and anti-inflammatory signals 40 and that they are depleted in Lmna G609G/G609G mice 28 , the restoration of secondary bile acidsand other metabolites (arabinose, ribose, inosine)by FMT might contribute to extend healthspan and lifespan in progeroid mice (Fig. 4g).”
Quote in the paperSubstantial claim - Premisecitation
Bile acids are depleted in Lmna G609G/G609G mice.
“Considering that bile acids regulate metabolism and anti-inflammatory signals 40 and that they are depleted in Lmna G609G/G609G mice 28 , the restoration of secondary bile acidsand other metabolites (arabinose, ribose, inosine)by FMT might contribute to extend healthspan and lifespan in progeroid mice (Fig. 4g).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [28] Barcena, C. et al. Methionine restriction extends lifespan in progeroid mice and alters lipid and bile acid metabolism. Cell Rep. 24, 2392–2403 (2018). source
Not checked in the free run.
- May combine two claims. 34
- Classified as probably not a substantial claim. 18
- The quote only partly states this claim. 2
May combine two claims.
Findingown dataWT and Lmna G609G/G609G mice at 1 month of age have a similar gut bacterial profile, with only an increment in Allobaculum, Desulfovibrio, and Clostridiales in Lmna G609G/G609G 1mo.
“We noted a similar profile for WT and Lmna G609G/G609G mice at 1 month of age (Fig. 1b and Extended Data Fig. 2a), observing solely an increment in the genera Allobaculum from the family Erysipelotrichaceae, Desulfovibrio (class deltaproteobacteria) and Clostridiales of the families Ruminococcaceae and Lachnospiraceae, in Lmna G609G/G609G 1mo (Extended Data Fig. 2b).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataWhen comparing progeria patients with their healthy controls, no differences were found in alpha-diversity or beta-diversity indices.
“When comparing progeria patients with their healthy controls, we found no differences in alpha-diversity (Extended Data Fig. 4b,c) or beta-diversity indices (Fig. 2a and Extended Data Fig. 4d).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe gut microbiome of a fraction of WT 22mo exhibited a tendency towards intestinal dysbiosis, but the only significant shift was the loss in Rikenella.
“The gut microbiome of a fraction of WT 22mo exhibited a tendency towards intestinal dysbiosis (Extended Data Fig. 2a); however, the only significant shift consisted in the loss in Rikenella (Extended Data Fig. 2e), a change also found when comparing Lmna G609G/G609G 4mo to WT 4mo mice (Fig. 1d).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataHierarchical clustering grouped Lmna G609G/G609G 4mo mice together and separated them from all other groups.
“Similar differences were revealed by hierarchical clustering, where Lmna G609G/G609G 4mo mice were grouped together and separated from all other groups (Extended Data Fig. 1e,f).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataZmpste24 -/- mice showed no differences in bacterial diversity but exhibited higher bacterial richness.
“Although Zmpste24 -/-mice showed no differences in bacterial diversity (Extended Data Fig. 3b), they exhibited higher bacterial richness (Extended Data Fig. 3c).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataLEfSe analysis detected an increase in KEGG pathways related to pathological bacteria such as 'Bacterial invasion of epithelial cells' (ko05100) and 'Flagellar assembly' (ko02040), and a differential enrichment in multiple metabolic pathways.
“LEfSe analysis detected an increase in KEGG pathways related to pathological bacteria such as 'Bacterial invasion of epithelial cells' (ko05100) and 'Flagellar assembly' (ko02040), and a differential enrichment in multiple metabolic pathways (Extended Data Fig. 2f and Supplemental Table S3).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataZmpste24 -/- animals showed differences in beta diversity at quantitative and qualitative levels, clustering differently from WT mice, and exhibited signs of dysbiosis with high abundance of Proteobacteria and Cyanobacteria.
“Like Lmna G609G/G609G mice, Zmpste24 -/-animals showed differences in beta diversity at the quantitative (Fig. 1f) and qualitative level (Extended Data Fig. 3d), clustering differently from WT mice, and exhibited signs of dysbiosis (Fig. 1g, Extended Data Fig. 3e) with a high abundance of Proteobacteria (class Alphaproteobacteria) and Cyanobacteria (Fig. 1g, Extended Data Fig. 3e and Supplementary”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataAlterations in the gut microbiome occur in progeria patients and long-lived humans.
“Alterations in the gut microbiome in progeria patients and long-lived humans.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataPCoA of beta-diversity among fecal samples by family showed significant difference (P = 0.001, PERMANOVA).
“(b) family (P = 0.001, PERMANOVA) (Family A, n = 3; Family B, n = 3; Family C, n = 3; Family D, n = 2; Family E, n = 3).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataBody weight loss and hypoglycemia were avoided in Zmpste24 -/--WTmic mice.
“Body weight loss (Fig. 3m and Extended Data Fig. 8a) and hypoglycemia (Fig. 3n) were avoided in Zmpste24 -/--WTmic mice.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataLmna G609G/G609G -WTmic showed improved survival compared to control Lmna G609G/G609G mice, with a 13.5% increase in median lifespan (160 vs 141 days).
“Most importantly, Lmna G609G/G609G -WTmic showed improved survival compared to control Lmna G609G/G609G mice (P = 0.0029), with a 13.5% increase in median lifespan (160 vs 141 days, respectively) (Fig. 3f).”
Quote in the paperSubstantial claimThe quote only partly states this claim.
Findingown dataIn beta-diversity PCoA, G609G 4mo mice show statistical differences with each of the other groups (P = 0.001; PERMANOVA).
“G609G 4mo mice show statistical differences with each of the other groups (see Supplementary Table 1).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIntestinal inflammation markers increased in Lmna G609G/G609G mice and were recovered in Lmna G609G/G609G -WTmic.
“We also noted an increase in intestinal inflammation markers in Lmna G609G/G609G mice that was recovered in Lmna G609G/G609G -WTmic (Extended Data Fig. 6d).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataLmna G609G/G609G -oG609Gmic showed reduced survival compared to control Lmna G609G/G609G mice, with a reduction in median lifespan (129 days).
“In contrast, Lmna G609G/G609G -oG609Gmic showed reduced survival compared to control Lmna G609G/G609G mice (P = 0.045), with a reduction in median lifespan (129 days) (Fig. 3f).”
Quote in the paperSubstantial claimMay combine two claims.
FindingcitationDifferent bile acids were decreased in Lmna G609G/G609G compared to WT mice, and recovered in Lmna G609G/G609G -WTmic.
“As recently described 28 , different bile acids were decreased in Lmna G609G/G609G compared to WT mice, and recovered in Lmna G609G/G609G -WTmic (Fig. 4e).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [28] Barcena, C. et al. Methionine restriction extends lifespan in progeroid mice and alters lipid and bile acid metabolism. Cell Rep. 24, 2392–2403 (2018). source
Not checked in the free run.
May combine two claims.
Findingown dataCentenarians showed lower alpha-diversity and considerably lower bacterial richness compared to controls.
“Centenarians showed lower alpha-diversity compared to their controls (Extended Data Fig. 5b), and a considerably lower bacterial richness (Extended Data Fig. 5c).”
Quote in the paperSubstantial claimMay combine two claims. The quote only partly states this claim.
Findingown dataFMT from old Lmna G609G/G609G donors into WT mice caused metabolic alterations, including higher body weight, higher glucose levels, lower O2 consumption, lower CO2 production and reduced energy expenditure.
“However, this maneuver caused metabolic alterations, including a higher body weight, higher glucose levels, lower O2 consumption, lower CO2 production and reduced energy expenditure (Fig. 3g-k and Extended Data Fig. 7a-d).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataqPCR validation showed differences in abundance of E. coli (W = 6, P = 0.0046) and A. muciniphila (W = 52, P = 0.03) between WT (n = 8) and G609G mice (n = 8) at 10 weeks of age.
“(e) Validation using qPCR of the differences in abundance of E. coli (W = 6, P = 0.0046) and A. muciniphila (W = 52, P = 0.03) between WT (n = 8) and G609G mice (n = 8) at 10 weeks of age.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataCentenarians were characterized by a lower abundance of Desulfovibrionaceae, Lachnospiraceae and Erysipelotrichaceae and Prevotella, Sutterella, Roseburia, or Butyricicoccus, among other differences.
“At a lower taxonomic level, centenarians were characterized by a lower abundance of Desulfovibrionaceae, Lachnospiraceae and Erysipelotrichaceaethe last two enriched in progeria patientsand Prevotella, Sutterella, Roseburia, or Butyricicoccus, among other differences (Fig. 2f).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe changes in microbiota from 1 to 4 months were more profound in progeroid mice, displaying a loss in Akkermansia and Dehalobacterium and an enrichment in Parabacteroides, Prevotella and the Enterobacteriaceae.
“however, the changes from 1 to 4 months were more profound in progeroid mice, displaying a loss in Akkermansia and Dehalobacterium and an enrichment in Parabacteroides, Prevotella and the Enterobacteriaceae, among other differences (Extended Data Fig. 2d).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataFMT from WT mice into Zmpste24 -/- mice caused a less pronounced cervicothoracic lordokyphosis, larger body size and maintained grooming.
“This manipulation caused Zmpste24 -/- mice to manifest a less pronounced cervicothoracic lordokyphosis, larger body size and maintained grooming (Fig. 3l).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataSpleen weight was similar in Lmna G609G/G609G -WTmic and Lmna G609G/G609G controls, but lower in Lmna G609G/G609G -oG609Gmic.
“Spleen weight, typically reduced in progeroid mice, was similar in Lmna G609G/G609G -WTmic and Lmna G609G/G609G controls, but lower in Lmna G609G/G609G -oG609Gmic (Extended Data Fig. 6c).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataLEfSe analysis pointed to a loss in Gemmiger (family Ruminococcaceae) and an enrichment in Clostridium from families Erysipelotrichaceae and Lachnospiraceae in progeria patients.
“LEfSe analysis pointed to a loss in Gemmiger -family Ruminococcaceae-and an enrichment in Clostridium from families Erysipelotrichaceae and Lachnospiraceae in progeria patients (Fig. 2c).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataLEfSe analysis showed that centenarians presented less Betaproteobacteria and more Synergistia and Verrucomicrobiae, among others.
“LEfSe analysis showed that centenarians presented less Betaproteobacteria and more Synergistia and Verrucomicrobiae, among others (Fig. 2e and Supplementary Table 2).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataZmpste24 -/--WTmic mice exhibited enhanced survival, with a median lifespan increase of 13.4% (279 vs 246 days).
“Like Lmna G609G/G609G mice transplanted with WT microbiota, Zmpste24 -/--WTmic mice also exhibited enhanced survival (P = 0.0092), with a median lifespan increase of 13.4% (279 vs 246 days) (Fig. 3o).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataRelative expression levels of Reg3g and Tff3 differ between G609G and AKK mice (Reg3g: t = 2.33, df = 13, P = 0.0365; Tff3: t = 2.42, df = 13, P = 0.0306).
“(b) Relative expression levels of Reg3g and Tff3 in G609G (n = 8) and AKK (n = 7) mice.Differences were analyzed with an unpaired two-tailed Student's t-test.For Reg3g, t = 2.33, df = 13, P = 0.0365; for Tff3, t = 2.42, df = 13, P = 0.0306.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationIn mammals, the gut microbiota is involved in food processing, activation of satiety pathways, protection against pathogens, and production of metabolites including vitamins, short chain fatty acids and secondary bile acids.
“In mammals, the gut microbiota is involved in food processing, activation of satiety pathways, protection against pathogens, and production of metabolites including vitamins, short chain fatty acids and secondary bile acids [8][9][10] .”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [8] Rios-Covian, D. et al. Intestinal short chain fatty acids and their link with diet and human health. Front. Microbiol. 7, 185 (2016). source
Not checked in the free run.
- cites [9] Breton, J. et al. Gut commensal E. coli proteins activate host satiety pathways following nutrient-induced bacterial growth. Cell Metab. 23, 324–334 (2016). source
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- cites [10] Wahlstrom, A., Sayin, S. I., Marschall, H. U. & Backhed, F. Intestinal crosstalk between bile acids and microbiota and its impact on host metabolism. Cell Metab. 24, 41–50 (2016). source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe gut microbiota has essential metabolic and immunological functions conserved from worms to humans.
“It is now known that the microbiota has essential metabolic and immunological functions conserved from worms 7 to humans 1,2 .”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [1] Thaiss, C. A., Zmora, N., Levy, M. & Elinav, E. The microbiome and innate immunity. Nature 535, 65–74 (2016). source
Not checked in the free run.
- cites [2] Leulier, F. et al. Integrative physiology: at the crossroads of nutrition, microbiota, animal physiology and human health. Cell Metab. 25, 522–534 (2017). source
Not checked in the free run.
Classified as probably not a substantial claim.
PremisecitationThe gut microbiota signals to distant organs, contributing to the maintenance of host physiology.
“The gut microbiota also signals to distant organs, contributing to the maintenance of host physiology 11 .”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [11] Schroeder, B. O. & Backhed, F. Signals from the gut microbiota to distant organs in physiology and disease. Nat. Med. 22, 1079–1089 (2016). source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationIntestinal microbiota alterations are associated with major conditions like obesity, type-2 diabetes, cardiovascular disease, non-alcoholic fatty acid liver disease, cancer, and the response to antineoplastic therapy.
“Intestinal microbiota alterations are associated with major conditions like obesity, type-2 diabetes, cardiovascular disease, non-alcoholic fatty acid liver disease, cancer, and the response to antineoplastic therapy [3][4][5][6] .”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [3] Koeth, R. A. et al. Intestinal microbiota metabolism of l-carnitine, a nutrient in red meat, promotes atherosclerosis. Nat. Med. 19, 576–585 (2013). source
Not checked in the free run.
- cites [4] Loomba, R. et al. Gut microbiome-based metagenomic signature for non-invasive detection of advanced fibrosis in human nonalcoholic fatty liver disease. Cell Metab. 25, 1054–1062 (2017). source
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- cites [5] Qin, J. et al. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 490, 55–60 (2012). source
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May combine two claims.
Interpretationown dataThe in vivo results suggest that therapeutic interventions on the intestinal microbiome may lead to healthspan and even lifespan improvements.
“The promising in vivo results obtained in this study suggest that therapeutic interventions on the intestinal microbiome may lead to healthspan end even lifespan improvements.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationPrevious studies reported high levels of Akkermansia and Christensenellaceae and low levels of Roseburia in centenarians.
“These results are in line with previous studies reporting high levels of Akkermansia and Christensenellaceae and low levels of Roseburia in centenarians 12,24 .”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationSecondary bile acids are produced by the gut microbiota and positively correlate with Akkermansia levels in mice.
“Of note, secondary bile acids are produced by the gut microbiota 38 and positively correlate with Akkermansia levels in mice 39 .”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [38] de Aguiar Vallim, T. Q., Tarling, E. J. & Edwards, P. A. Pleiotropic roles of bile acids in metabolism. Cell Metab. 17, 657–669 (2013). source
Not checked in the free run.
- cites [39] Pierre, J. F. et al. Activation of bile acid signaling improves metabolic phenotypes in high-fat diet-induced obese mice. Am. J. Physiol. Gastrointest. Liver Physiol. 311, G286–G304 (2016). source
Not checked in the free run.
Classified as probably not a substantial claim. May combine two claims.
PremisecitationBile acids regulate metabolism and anti-inflammatory signals.
“Considering that bile acids regulate metabolism and anti-inflammatory signals 40 and that they are depleted in Lmna G609G/G609G mice 28 , the restoration of secondary bile acidsand other metabolites (arabinose, ribose, inosine)by FMT might contribute to extend healthspan and lifespan in progeroid mice (Fig. 4g).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [40] Postler, T. S. & Ghosh, S. Understanding the holobiont: how microbial metabolites affect human health and shape the immune system. Cell Metab. 26, 110–130 (2017). source
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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationHigh abundance of Akkermansia has been associated with improved immunomodulation and metabolic homeostasis, reduced inflammation, and protection against atherosclerosis.
“Of note, high abundance of Akkermansia has been associated with improved immunomodulation and metabolic homeostasis, reduced inflammation, and protection against atherosclerosis [17][18][19] .”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [17] Plovier, H. et al. A purified membrane protein from Akkermansia muciniphila or the pasteurized bacterium improves metabolism in obese and diabetic mice. Nat. Med. 23, 107–113 (2017). source
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- cites [18] Schneeberger, M. et al. Akkermansia muciniphila inversely correlates with the onset of inflammation, altered adipose tissue metabolism and metabolic disorders during obesity in mice. Sci. Rep. 5, 16643 (2015). source
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- cites [19] Everard, A. et al. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proc. Natl Acad. Sci. USA 110, 9066–9071 (2013). source
Not checked in the free run.
Classified as probably not a substantial claim. May combine two claims.
PremisecitationPrevious studies have described that successful FMT treatment of recurrent infection by C. difficile relies on restoration of correct bile acid metabolism, and that antibiotic-induced microbiome depletion reduces the secondary bile acid pool.
“Previous studies have described that successful FMT treatment of recurrent infection by C. difficile relies on restoration of correct bile acid metabolism 35,36 , and that antibioticinduced microbiome depletion reduces the secondary bile acid pool 37 .”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [35] Weingarden, A. R. et al. Microbiota transplantation restores normal fecal bile acid composition in recurrent Clostridium difficile infection. Am. J. Physiol. Gastrointest. Liver Physiol. 306, G310–G319 (2014). source
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- cites [36] Buffie, C. G. et al. Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile. Nature 517, 205–208 (2015). source
Not checked in the free run.
- cites [37] Zarrinpar, A. et al. Antibiotic-induced microbiome depletion alters metabolic homeostasis by affecting gut signaling and colonic metabolism. Nat. Commun. 9, 2872 (2018). source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationEnterobacteriaceae contains the genus Escherichia and has been associated with dysbiosis and intestinal inflammation.
“By contrast, Lmna G609G/G609G 4mo exhibited an increment in Mucispirillum, Enterococcus, Acinetobacter, Staphylococcus, Parabacteroides, Bacteroides, Prevotella and Enterobacteriaceae, which contains the genus Escherichia and has been associated with dysbiosis and intestinal inflammation 20 (Fig. 1d).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [20] Maharshak, N. et al. Altered enteric microbiota ecology in interleukin 10-deficient mice during development and progression of intestinal inflammation. Gut Microbes 4, 316–324 (2013). source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationFMT might modulate obesity and metabolism in humans and mice, ameliorate metabolic syndrome in patients, and contribute to the treatment of refractory immune checkpoint inhibitor (ICI)-associated colitis and recurrent infections by Clostridium difficile.
“FMT might modulate obesity and metabolism in humans and mice 29,30 , ameliorate metabolic syndrome in patients 31 , and contribute to the treatment of refractory immune checkpoint inhibitor (ICI)-associated colitis 32 and recurrent infections by Clostridium difficile 33 .”
Quote in the paperNot a substantial claim0 of 4 sources checked- cites [29] Ridaura, V. K. et al. Gut microbiota from twins discordant for obesity modulate metabolism in mice. Science 341, 1241214 (2013). source
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- cites [30] Cox, L. M. et al. Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences. Cell 158, 705–721 (2014). source
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- cites [31] Vrieze, A. et al. Transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome. Gastroenterology 143, 913–916 (2012). source
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- cites [32] Wang, Y. et al. Fecal microbiota transplantation for refractory immune checkpoint inhibitor-associated colitis. Nat. Med. 24, 1804–1808 (2018). source
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Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe QC sample was re-injected in each batch to monitor and correct analytical bias.
“This QC sample was re-injected in each batch to monitor and correct analytical bias.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationDifferentially expressed metabolites in each condition were identified using moderate t-statistic implemented in limma, using sex as a covariate.
“Differentially expressed metabolites in each condition were identified using moderate t-statistic implemented in the R/Bioconductor package limma 46 , using sex as a covariate.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [46] Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015). source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenNormalization was performed by correcting the area of the MS picks across the batches using the QC pooled samples and by centering their values around the mean of the QC areas.
“Normalization was performed by correcting the area of the MS picks across the batches using the QC pooled samples and by centering their values around the mean of the QC areas.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenResearch involving humans was approved by the Ethical Committee of Regional Clinical Research of the Principality of Asturias, project no.105/16.
“Research involving humans was approved by the Ethical Committee of Regional Clinical Research of the Principality of Asturias, project no.105/16.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataNumber of mice allocated per group was based on previous experiments and their distribution was randomized.
“Number of mice allocated per group was based on previous experiments and their distribution was randomized, being indicated in each Figure legend.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenAll participants read and signed an informed consent.
“All participants read and signed an informed consent.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
No alterations in the gut microbiome have been described in accelerated aging syndromes.
“Although some works have explored the microbiome profile of long-lived humans 12,13 , no alterations have been described in accelerated aging syndromes.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Many studies have shown that Akkermansia can effectively improve symptoms in mouse models of ALS, progeria, and chronic colitis by promoting healing and recovery of intestinal mucosal layer and reducing the expression of proinflammatory cytokines such as TNF-α and IFN-γ in the colon.
“Many studies have shown that Akkermansia can effectively improve symptoms in mouse models of diseases such as ALS [34], progeria [35], and chronic colitis [36] by promoting healing and recovery of intestinal mucosal layer and reducing the expression of proinflammatory cytokines such as TNF-α and interferon gamma (IFN-γ) in the colon.”
From Neuroprotective Effect of Ceftriaxone on MPTP‐Induced Parkinson’s Disease Mouse Model by Regulating Inflammation and Intestinal Microbiota (2021) · cites this paper as [35]
In aged mice, receiving microbiota from young mice has been reported to extend life span or halt functional decline in the mucosal immune system.
“Similar beneficial effects have been reported in aged mice receiving microbiota from young mice to extend life span [8, 61] or halt the functional decline in the mucosal immune system [112].”
From Fecal microbiota transfer between young and aged mice reverses hallmarks of the aging gut, eye, and brain (2022) · cites this paper as [8]
Members of the Bifidobacteriaceae, Akkermansiaceae, and Eubacteriaceae families are associated with beneficial effects on intestinal and extra-intestinal health in both mice and humans.
“Members of the Bifidobacteriaceae, Akkermansiaceae, and Eubacteriaceae families that are associated with beneficial effects on intestinal and extra-intestinal health in both mice and humans”
From Fecal microbiota transfer between young and aged mice reverses hallmarks of the aging gut, eye, and brain (2022) · cites this paper as [8]
Bifidobacterium animalis and Akkermansia muciniphila are associated with promoting intestinal and extra-intestinal health and healthy aging.
“and are associated with promoting intestinal and extra-intestinal health and healthy aging.”
From Fecal microbiota transfer between young and aged mice reverses hallmarks of the aging gut, eye, and brain (2022) · cites this paper as [8]
In mouse models of accelerated aging, supplementation with A. muciniphila can attenuate age-related decline in colon thickness and immune activation, and exert beneficial effects on lifespan and healthspan.
“In mouse models of accelerated aging, supplementation with A. muciniphila can also attenuate age-related decline in colon thickness and immune activation [73], and exert beneficial effects on lifespan and healthspan [8].”
From Fecal microbiota transfer between young and aged mice reverses hallmarks of the aging gut, eye, and brain (2022) · cites this paper as [8]
Giving Akkermansia species by mouth improves cancer immunosurveillance in tumor-bearing mice.
“oral administration of Akkermansia species not only improves cancer immunosurveillance in tumor-bearing mice but also prolongs lifespan in progeroid mice 57”
From Impact of the ONCOBIOME network in cancer microbiome research (2025) · cites this paper as [57]
Giving Akkermansia species by mouth extends lifespan in progeroid mice.
“oral administration of Akkermansia species not only improves cancer immunosurveillance in tumor-bearing mice but also prolongs lifespan in progeroid mice 57”
From Impact of the ONCOBIOME network in cancer microbiome research (2025) · cites this paper as [57]
Studies in the past decade have demonstrated that gut microbiome composition changes with age, that exceptionally long-lived individuals have a different microbiome composition from average older adults, and that certain microorganisms and the metabolites they produce are beneficial to human health.
“Studies in the past decade have demonstrated that gut microbiome composition changes with age, that exceptionally long-lived individuals have a different microbiome composition from average older adults131–133, and that certain microorganisms131,134,135 and the metabolites they produce132,134,136 are beneficial to human health.”
From Measuring biological age using omics data (2022) · cites this paper as [134]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Akkermansia treatment has conflicting start ages
MajorThe Methods say oral gavage began at 12 weeks of age, whereas the Figure 4 legend says it began at 7-8 weeks. These are different treatment schedules for the same survival experiment.
“Lmna G609G/G609G mice were treated by oral gavage with 100 L of either Akkermansia suspension (AKK group, n = 9) or anaerobic PBS (control group, n=12) three days a week beginning at 12 weeks of age and until decease.”
“A. muciniphila transplantation was performed starting at 7-8 weeks of age.”
Cites
limma powers differential expression analyses for RNA-sequencing and microarray studies
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv007 · Cited by 40,458 · see citing works
Metagenomic biomarker discovery and explanation
Segata, N., Izard, J., Waldron, L., Gevers, D., Miropolsky, L., Garrett, W. S., & Huttenhower, C. (2011) · Genome Biology · doi:10.1186/gb-2011-12-6-r60 · Cited by 16,192 · see citing works
Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences
Langille, M. G. I., Zaneveld, J., Caporaso, J. G., McDonald, D., Knights, D., Reyes, J. A., Clemente, J. C., Burkepile, D. E., Vega Thurber, R. L., Knight, R., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2676 · Cited by 9,116 · see citing works
A metagenome-wide association study of gut microbiota in type 2 diabetes
Qin, J., Li, Y., Cai, Z., Li, S., Zhu, J., Zhang, F., Liang, S., Zhang, W., Guan, Y., Shen, D., et al. (2012) · Nature · doi:10.1038/nature11450 · Cited by 6,762 · see citing works
Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors
Routy, B., Le Chatelier, E., Derosa, L., Duong, C. P. M., Alou, M. T., Daillère, R., Fluckiger, A., Messaoudene, M., Rauber, C., Roberti, M. P., et al. (2018) · Science · doi:10.1126/science.aan3706 · Cited by 5,671 · see citing works
Self-citationGut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients
Gopalakrishnan, V., Spencer, C. N., Nezi, L., Reuben, A., Andrews, M. C., Karpinets, T. V., Prieto, P. A., Vicente, D., Hoffman, K., Wei, S. C., et al. (2018) · Science · doi:10.1126/science.aan4236 · Cited by 4,812 · see citing works
Everard, A., Belzer, C., Geurts, L., Ouwerkerk, J. P., Druart, C., Bindels, L. B., Guiot, Y., Derrien, M., Muccioli, G. G., Delzenne, N. M., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1219451110 · Cited by 4,511 · see citing works
Intestinal microbiota metabolism of l-carnitine, a nutrient in red meat, promotes atherosclerosis
Koeth, R. A., Wang, Z., Levison, B. S., Buffa, J. A., Org, E., Sheehy, B. T., Britt, E. B., Fu, X., Wu, Y., Li, L., et al. (2013) · Nature Medicine · doi:10.1038/nm.3145 · Cited by 4,386 · see citing works
Gut Microbiota from Twins Discordant for Obesity Modulate Metabolism in Mice
Ridaura, V. K., Faith, J. J., Rey, F. E., Cheng, J., Duncan, A. E., Kau, A. L., Griffin, N. W., Lombard, V., Henrissat, B., Bain, J. R., et al. (2013) · Science · doi:10.1126/science.1241214 · Cited by 3,788 · see citing works
Duodenal Infusion of Donor Feces for Recurrent <i>Clostridium difficile</i>
van Nood, E., Vrieze, A., Nieuwdorp, M., Fuentes, S., Zoetendal, E. G., de Vos, W. M., Visser, C. E., Kuijper, E. J., Bartelsman, J. F. W. M., Tijssen, J. G. P., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1205037 · Cited by 3,708 · see citing works
Human Genetics Shape the Gut Microbiome
Goodrich, J. K., Waters, J. L., Poole, A. C., Sutter, J. L., Koren, O., Blekhman, R., Beaumont, M., Van Treuren, W., Knight, R., Bell, J. T., et al. (2014) · Cell · doi:10.1016/j.cell.2014.09.053 · Cited by 3,164 · see citing works
Vrieze, A., Van Nood, E., Holleman, F., Salojärvi, J., Kootte, R. S., Bartelsman, J. F. W. M., Dallinga–Thie, G. M., Ackermans, M. T., Serlie, M. J., Oozeer, R., et al. (2012) · Gastroenterology · doi:10.1053/j.gastro.2012.06.031 · Cited by 2,913 · see citing works
Intestinal Crosstalk between Bile Acids and Microbiota and Its Impact on Host Metabolism
Wahlstrom, A. M., Sayin, S. I., Marschall, H., & Bäckhed, F. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2016.05.005 · Cited by 2,903 · see citing works
Environment dominates over host genetics in shaping human gut microbiota
Rothschild, D., Weissbrod, O., Barkan, E., Kurilshikov, A., Korem, T., Zeevi, D., Costea, P. I., Godneva, A., Kalka, I. N., Bar, N., et al. (2018) · Nature · doi:10.1038/nature25973 · Cited by 2,859 · see citing works
Intestinal Short Chain Fatty Acids and their Link with Diet and Human Health
Ríos-Covián, D., Ruas‐Madiedo, P., Margollés, A., Gueimonde, M., Reyes‐Gavilán, C. G. D. L., & Salazar, N. (2016) · Frontiers in Microbiology · doi:10.3389/fmicb.2016.00185 · Cited by 2,215 · see citing works
Self-citationPlovier, H., Everard, A., Druart, C., Depommier, C., Van Hul, M., Geurts, L., Chilloux, J., Ottman, N., Duparc, T., Lichtenstein, L., et al. (2017) · Nature Medicine · doi:10.1038/nm.4236 · Cited by 2,204 · see citing works
The microbiome and innate immunity
Thaiss, C. A., Zmora, N., Levy, M., & Elinav, E. (2016) · Nature · doi:10.1038/nature18847 · Cited by 2,012 · see citing works
Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile
Buffie, C. G., Bucci, V., Stein, R. R., McKenney, P. T., Ling, L., Gobourne, A., No, D., Liu, H., Kinnebrew, M., Viale, A., et al. (2015) · Nature · doi:10.1038/nature13828 · Cited by 1,872 · see citing works
Cox, L. M., Yamanishi, S., Sohn, J., Alekseyenko, A. V., Leung, J. M., Cho, I., Kim, S. G., Li, H., Gao, Z., Mahana, D., et al. (2014) · Cell · doi:10.1016/j.cell.2014.05.052 · Cited by 1,859 · see citing works
Signals from the gut microbiota to distant organs in physiology and disease
Schroeder, B. O., & Bäckhed, F. (2016) · Nature Medicine · doi:10.1038/nm.4185 · Cited by 1,409 · see citing works
Strains, functions and dynamics in the expanded Human Microbiome Project
Lloyd-Price, J., Mahurkar, A., Rahnavard, G., Crabtree, J., Orvis, J., Hall, A. B., Brady, A., Creasy, H. H., McCracken, C., Giglio, M. G., et al. (2017) · Nature · doi:10.1038/nature23889 · Cited by 1,267 · see citing works
Pleiotropic Roles of Bile Acids in Metabolism
de Aguiar Vallim, T. Q., Tarling, E. J., & Edwards, P. A. (2013) · Cell Metabolism · doi:10.1016/j.cmet.2013.03.013 · Cited by 1,209 · see citing works
O’Toole, P. W., & Jeffery, I. B. (2015) · Science · doi:10.1126/science.aac8469 · Cited by 1,202 · see citing works
Loomba, R., Seguritan, V., Li, W., Long, T., Klitgord, N., Bhatt, A., Dulai, P. S., Caussy, C., Bettencourt, R., Highlander, S. K., et al. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2017.04.001 · Cited by 1,123 · see citing works
Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome
Abubucker, S., Segata, N., Goll, J. B., Schubert, A. M., Izard, J., Cantarel, B. L., Rodriguez-Mueller, B., Zucker, J., Thiagarajan, M., Henrissat, B., et al. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002358 · Cited by 1,050 · see citing works
Gut Microbiota and Extreme Longevity
Biagi, E., Franceschi, C., Rampelli, S., Severgnini, M., Ostan, R., Turroni, S., Consolandi, C., Quercia, S., Scurti, M., Monti, D., et al. (2016) · Current Biology · doi:10.1016/j.cub.2016.04.016 · Cited by 1,025 · see citing works
Postler, T. S., & Ghosh, S. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2017.05.008 · Cited by 876 · see citing works
Schneeberger, M., Everard, A., Gómez-Valadés, A. G., Matamoros, S., Ramírez, S., Delzenne, N. M., Gomis, R., Claret, M., & Cani, P. D. (2015) · Scientific Reports · doi:10.1038/srep16643 · Cited by 798 · see citing works
Fecal microbiota transplantation for refractory immune checkpoint inhibitor-associated colitis
Wang, Y., Wiesnoski, D. H., Helmink, B. A., Gopalakrishnan, V., Choi, K., DuPont, H. L., Jiang, Z.-D., Abu-Sbeih, H., Sanchez, C. A., Chang, C.-C., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0238-9 · Cited by 740 · see citing works
Zarrinpar, A., Chaix, A., Xu, Z. Z., Chang, M. W., Marotz, C. A., Saghatelian, A., Knight, R., & Panda, S. (2018) · Nature Communications · doi:10.1038/s41467-018-05336-9 · Cited by 546 · see citing works
Anticancer effects of the microbiome and its products
Zitvogel, L., Daillère, R., Roberti, M. P., Routy, B., & Kroemer, G. (2017) · Nature Reviews Microbiology · doi:10.1038/nrmicro.2017.44 · Cited by 538 · see citing works
Self-citationAccelerated ageing in mice deficient in Zmpste24 protease is linked to p53 signalling activation
Varela, I., Cadiñanos, J., Pendás, A. M., Gutiérrez-Fernández, A., Folgueras, A. R., Sánchez, L. M., Zhou, Z., Rodríguez, F. J., Stewart, C. L., Vega, J. A., et al. (2005) · Nature · doi:10.1038/nature04019 · Cited by 466 · see citing works
Self-citationSplicing-directed therapy in a new mouse model of human accelerated aging
Osorio, F. G., Navarro, C. L., Cadiñanos, J., López-Mejía, I. C., Quirós, P. M., Bartoli, C., Rivera, J., Tazi, J., Guzmán, G., Varela, I., et al. (2011) · Science Translational Medicine · doi:10.1126/scitranslmed.3002847 · Cited by 432 · see citing works
Self-citationWeingarden, A. R., Chen, C., Bobr, A., Yao, D., Lu, Y., Nelson, V. M., Sadowsky, M. J., & Khoruts, A. (2014) · American Journal of Physiology-Gastrointestinal and Liver Physiology · doi:10.1152/ajpgi.00282.2013 · Cited by 423 · see citing works
Breton, J., Tennoune, N., Lucas, N., Francois, M., Legrand, R., Jacquemot, J., Goichon, A., Guérin, C., Peltier, J., Pestel-Caron, M., et al. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2015.10.017 · Cited by 321 · see citing works
Duodenal Infusion of Donor Feces for Recurrent Clostridium Difficile
Mathew, S., Barton, J., & Ong, A. W. (2019) · CRC Press eBooks · doi:10.1201/9780429316944-30 · Cited by 282 · see citing works
Osorio, F. G., Bárcena, C., Soria-Valles, C., Ramsay, A. J., de Carlos, F., Cobo, J., Fueyo, A., Freije, J. M. P., & López-Otín, C. (2012) · Genes & Development · doi:10.1101/gad.197954.112 · Cited by 276 · see citing works
Self-citationProgeria: A Paradigm for Translational Medicine
Gordon, L. B., Rothman, F. G., López-Otı́n, C., & Misteli, T. (2014) · Cell · doi:10.1016/j.cell.2013.12.028 · Cited by 276 · see citing works
Self-citationCrosstalk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity
Everard, A., Belzer, C., Geurts, L., Ouwerkerk, J. P., Druart, C., Bindels, L. B., Guiot, Y., Derrien, M., Muccioli, G., Delzenne, N. M., et al. (2013) · Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) · Cited by 218 · see citing works
Puente, X. S., Quesada, V., Osorio, F. G., Cabanillas, R., Cadiñanos, J., Fraile, J. M., Ordóñez, G. R., Puente, D. A., Gutiérrez‐Fernández, A., Fanjul‐Fernández, M., et al. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.04.010 · Cited by 209 · see citing works
Self-citationStatistical methods for testing effects on “maximum lifespan”
Wang, C., Li, Q., Redden, D. T., Weindruch, R., & Allison, D. B. (2004) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2004.07.003 · Cited by 208 · see citing works
Worms need microbes too: microbiota, health and aging in Caenorhabditis elegans
Cabreiro, F., & Gems, D. (2013) · EMBO Molecular Medicine · doi:10.1002/emmm.201100972 · Cited by 196 · see citing works
Methionine Restriction Extends Lifespan in Progeroid Mice and Alters Lipid and Bile Acid Metabolism
Bárcena, C., Quirós, P. M., Durand, S., Mayoral, P., Rodríguez, F., Caravia, X. M., Mariño, G., Garabaya, C., Fernández-García, M. T., Kroemer, G., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.07.089 · Cited by 185 · see citing works
Self-citationCommensal bacteria contribute to insulin resistance in aging by activating innate B1a cells
Bodogai, M., O’Connell, J., Kim, K., Kim, Y., Moritoh, K., Chen, C., Gusev, F., Vaughan, K., Shulzhenko, N., Mattison, J. A., et al. (2018) · Science Translational Medicine · doi:10.1126/scitranslmed.aat4271 · Cited by 182 · see citing works
Maharshak, N., Packey, C. D., Ellermann, M., Manick, S., Siddle, J. P., Huh, E. Y., Plevy, S., Sartor, R. B., & Carroll, I. M. (2013) · Gut Microbes · doi:10.4161/gmic.25486 · Cited by 174 · see citing works
Leulier, F., MacNeil, L. T., Lee, W., Rawls, J. F., Cani, P. D., Schwarzer, M., Zhao, L., & Simpson, S. J. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2017.02.001 · Cited by 143 · see citing works
Activation of bile acid signaling improves metabolic phenotypes in high-fat diet-induced obese mice
Pierre, J. F., Martinez, K., Ye, H., Nadimpalli, A., Morton, T. C., Yang, J., Wang, Q., Patno, N., Chang, E. B., & Yin, D. (2016) · American Journal of Physiology-Gastrointestinal and Liver Physiology · doi:10.1152/ajpgi.00202.2016 · Cited by 82 · see citing works
Kalabis, J., Rosenberg, I., & Podolsky, D. K. (2006) · Journal of Biological Chemistry · doi:10.1074/jbc.m512905200 · Cited by 55 · see citing works
Enot, D. P., Niso‐Santano, M., Durand, S., Chery, A., Pietrocola, F., Vacchelli, E., Madeo, F., Galluzzi, L., & Kroemer, G. (2015) · Cell Cycle · doi:10.1080/15384101.2015.1064206 · Cited by 32 · see citing works
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Hallmarks of aging: An expanding universe
López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M., & Kroemer, G. (2023) · Cell · doi:10.1016/j.cell.2022.11.001 · Cited by 6,549 · see citing works
Self-citationMucus barrier, mucins and gut microbiota: the expected slimy partners?
Paone, P., & Cani, P. D. (2020) · Gut · doi:10.1136/gutjnl-2020-322260 · Cited by 1,602 · see citing works
Bile acids and the gut microbiota: metabolic interactions and impacts on disease
Collins, S. L., Stine, J. G., Bisanz, J. E., Okafor, C. D., & Patterson, A. D. (2023) · Nature Reviews Microbiology · doi:10.1038/s41579-022-00805-x · Cited by 1,214 · see citing works
Akkermansia muciniphila: paradigm for next-generation beneficial microorganisms
Cani, P. D., Depommier, C., Derrien, M., Everard, A., & de Vos, W. M. (2022) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-022-00631-9 · Cited by 1,192 · see citing works
The gut microbiome as a modulator of healthy ageing
Ghosh, T. S., Shanahan, F., & O’Toole, P. W. (2022) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-022-00605-x · Cited by 817 · see citing works
Gut microbiome pattern reflects healthy ageing and predicts survival in humans
Wilmanski, T. M., Diener, C., Rappaport, N., Patwardhan, S., Wiedrick, J. T., Lapidus, J., Earls, J. C., Zimmer, A., Glusman, G., Robinson, M., et al. (2021) · Nature Metabolism · doi:10.1038/s42255-021-00348-0 · Cited by 693 · see citing works
Derosa, L., Routy, B., Thomas, A. M., Iebba, V., Zalcman, G., Friard, S., Mazieres, J., Audigier-Valette, C., Moro-Sibilot, D., Goldwasser, F., et al. (2022) · Nature Medicine · doi:10.1038/s41591-021-01655-5 · Cited by 685 · see citing works
Self-citationNovel bile acid biosynthetic pathways are enriched in the microbiome of centenarians
Sato, Y., Atarashi, K., Plichta, D. R., Arai, Y., Sasajima, S., Kearney, S. M., Suda, W., Takeshita, K., Sasaki, T., Okamoto, S., et al. (2021) · Nature · doi:10.1038/s41586-021-03832-5 · Cited by 632 · see citing works
Measuring biological age using omics data
Rutledge, J., Oh, H., & Wyss-Coray, T. (2022) · Nature Reviews Genetics · doi:10.1038/s41576-022-00511-7 · Cited by 570 · see citing works
Meta-hallmarks of aging and cancer
López-Otín, C., Pietrocola, F., Roiz-Valle, D., Galluzzi, L., & Kroemer, G. (2023) · Cell Metabolism · doi:10.1016/j.cmet.2022.11.001 · Cited by 529 · see citing works
Self-citationLópez-Otín, C., & Kroemer, G. (2021) · Cell · doi:10.1016/j.cell.2020.11.034 · Cited by 499 · see citing works
Self-citationMolecular physiology of bile acid signaling in health, disease, and aging
Perino, A., Demagny, H., Velazquez-Villegas, L., & Schoonjans, K. (2021) · Physiological Reviews · doi:10.1152/physrev.00049.2019 · Cited by 481 · see citing works
The aging gut microbiome and its impact on host immunity
Bosco, N., & Noti, M. (2021) · Genes and Immunity · doi:10.1038/s41435-021-00126-8 · Cited by 418 · see citing works
The links between gut microbiota and obesity and obesity related diseases
Geng, J., Ni, Q., Sun, W., Li, L., & Feng, X. (2022) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2022.112678 · Cited by 410 · see citing works
The Gut Microbiota and Unhealthy Aging: Disentangling Cause from Consequence
DeJong, E. N., Surette, M. G., & Bowdish, D. M. E. (2020) · Cell Host & Microbe · doi:10.1016/j.chom.2020.07.013 · Cited by 370 · see citing works
Parker, A., Romano, S., Ansorge, R., Aboelnour, A., Le Gall, G., Savva, G. M., Pontifex, M. G., Telatin, A., Baker, D., Jones, E., et al. (2022) · Microbiome · doi:10.1186/s40168-022-01243-w · Cited by 368 · see citing works
Ling, Z., Liu, X., Cheng, Y., Yan, X., & Wu, S. (2020) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2020.1867054 · Cited by 366 · see citing works
Gut Microbiota Dysbiosis: Pathogenesis, Diseases, Prevention, and Therapy
Shen, Y., Fan, N., Ma, S., Cheng, X., Yang, X., & Wang, G. (2025) · MedComm · doi:10.1002/mco2.70168 · Cited by 360 · see citing works
A single-cell nanocoating of probiotics for enhanced amelioration of antibiotic-associated diarrhea
Pan, J., Gong, G., Wang, Q., Shang, J., He, Y., Catania, C., Birnbaum, D., Li, Y., Jia, Z., Zhang, Y., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29672-z · Cited by 315 · see citing works
D’Amato, A., Di Cesare Mannelli, L., Lucarini, E., Man, A. L., Le Gall, G., Branca, J. J. V., Ghelardini, C., Amedei, A., Bertelli, E., Regoli, M., et al. (2020) · Microbiome · doi:10.1186/s40168-020-00914-w · Cited by 269 · see citing works
Human trials exploring anti-aging medicines
Guarente, L., Sinclair, D. A., & Kroemer, G. (2024) · Cell Metabolism · doi:10.1016/j.cmet.2023.12.007 · Cited by 257 · see citing works
Self-citationBioinspired oral delivery of gut microbiota by self-coating with biofilms
Wang, X., Cao, Z., Zhang, M., Meng, L., Ming, Z., & Liu, J. (2020) · Science Advances · doi:10.1126/sciadv.abb1952 · Cited by 255 · see citing works
Zhang, X., Zhong, H., Li, Y., Shi, Z., Ren, H., Zhang, Z., Zhou, X., Tang, S., Han, X., Lin, Y., et al. (2021) · Nature Aging · doi:10.1038/s43587-020-00014-2 · Cited by 250 · see citing works
Aging and Rejuvenation of Neural Stem Cells and Their Niches
Navarro Negredo, P., Yeo, R. W., & Brunet, A. (2020) · Cell Stem Cell · doi:10.1016/j.stem.2020.07.002 · Cited by 246 · see citing works
Qu, S., Fan, L., Qi, Y., Xu, C., Hu, Y., Chen, S., Liu, W., Liu, W., & Si, J. (2021) · Microbiology Spectrum · doi:10.1128/spectrum.00730-21 · Cited by 245 · see citing works
The role of T cells in age-related diseases
Carrasco, E., Heras, M. M. G. D. L., Gabandé‐Rodríguez, E., Desdín-Micó, G., Aranda, J. F., & Mittelbrunn, M. (2021) · Nature reviews. Immunology · doi:10.1038/s41577-021-00557-4 · Cited by 243 · see citing works
Wu, M., Tian, T., Mao, Q., Zou, T., Zhou, C., Xie, J., & Chen, J. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-01038-3 · Cited by 235 · see citing works
Salazar, N., Arboleya, S., Fernández-Navarro, T., Reyes‐Gavilán, C. G. D. L., González, S., & Gueimonde, M. (2019) · Nutrients · doi:10.3390/nu11081765 · Cited by 231 · see citing works
Self-citationThe Microbiome as a Modifier of Neurodegenerative Disease Risk
Fang, P., Kazmi, S. A., Jameson, K. G., & Hsiao, E. Y. (2020) · Cell Host & Microbe · doi:10.1016/j.chom.2020.06.008 · Cited by 226 · see citing works
The changing metabolic landscape of bile acids – keys to metabolism and immune regulation
Mohanty, I., Allaband, C., Mannochio-Russo, H., Abiead, Y. E., Hagey, L. R., Knight, R. D., & Dorrestein, P. C. (2024) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-024-00914-3 · Cited by 225 · see citing works
Wu, M., Luo, Q., Nie, R., Yang, X., Tang, Z., & Chen, H. (2020) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2020.1773390 · Cited by 207 · see citing works
Montégut, L., López-Otı́n, C., & Kroemer, G. (2024) · Molecular Cancer · doi:10.1186/s12943-024-02020-z · Cited by 202 · see citing works
Self-citationLiu, S., Rezende, R. M., Moreira, T. G., Tankou, S. K., Cox, L. M., Wu, M., Song, A., Dhang, F. H., Wei, Z., Costamagna, G., et al. (2019) · Cell Host & Microbe · doi:10.1016/j.chom.2019.10.008 · Cited by 196 · see citing works
Aging and InflammationPreprint
Singh, A., Schurman, S. H., Bektas, A., Kaileh, M., Roy, R., Wilson, D. M., Sen, R., & Ferrucci, L. (2023) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a041197 · Cited by 194 · see citing works
Procedures for Fecal Microbiota Transplantation in Murine Microbiome Studies
Bokoliya, S. C., Dorsett, Y., Panier, H. A., & Zhou, Y. (2021) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2021.711055 · Cited by 186 · see citing works
Strasser, B., Wolters, M., Weyh, C., Krüger, K., & Ticinesi, A. (2021) · Nutrients · doi:10.3390/nu13062045 · Cited by 181 · see citing works
Jian, H., Liu, Y., Wang, X., Dong, X., & Zou, X. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24043900 · Cited by 177 · see citing works
A. Muciniphila Suppresses Colorectal Tumorigenesis by Inducing TLR2/NLRP3-Mediated M1-Like TAMs
Fan, L., Xu, C., Ge, Q., Lin, Y., Wong, C. C., Qi, Y., Ye, B., Lian, Q., Zhuo, W., Si, J., et al. (2021) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-20-1019 · Cited by 175 · see citing works
Ding, Y., Bu, F., Chen, T., Shi, G., Yuan, X., Feng, Z., Duan, Z., Wang, R., Zhang, S., Wang, Q., et al. (2021) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-021-11622-2 · Cited by 173 · see citing works
Ma, J., Hong, Y., Zheng, N., Xie, G., Lyu, Y., Gu, Y., Xi, C., Chen, L., Wu, G., Li, Y., et al. (2020) · Gut Microbes · doi:10.1080/19490976.2020.1763770 · Cited by 171 · see citing works
Oral nanomedicine for modulating immunity, intestinal barrier functions, and gut microbiome
Lee, Y., Kamada, N., & Moon, J. J. (2021) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2021.114021 · Cited by 168 · see citing works
Zhu, L., Yu, T., Wang, W., Xu, T., Geng, W., Li, N., & Zan, X. (2024) · Advanced Materials · doi:10.1002/adma.202308728 · Cited by 166 · see citing works
Grajeda-Iglesias, C., Durand, S., Daillère, R., Iribarren, K., Lemaitre, F., Derosa, L., Aprahamian, F., Bossut, N., Nirmalathasan, N., Madeo, F., et al. (2021) · Aging · doi:10.18632/aging.202739 · Cited by 161 · see citing works
Self-citationGheorghe, C. E., Ritz, N. L., Martin, J. A., Wardill, H. R., Cryan, J. F., & Clarke, G. A. (2021) · Gut Microbes · doi:10.1080/19490976.2021.1941711 · Cited by 149 · see citing works
Correlation Between Fecal Metabolomics and Gut Microbiota in Obesity and Polycystic Ovary Syndrome
Zhou, L., Ni, Z., Yu, J., Cheng, W., Cai, Z., & Yu, C. (2020) · Frontiers in Endocrinology · doi:10.3389/fendo.2020.00628 · Cited by 148 · see citing works
Zhou, W., Yang, T., Xu, W., Huang, Y., Ran, L., Yan, Y., Mi, J., Lu, L., Sun, Y., Zeng, X., et al. (2022) · Carbohydrate Polymers · doi:10.1016/j.carbpol.2022.119626 · Cited by 148 · see citing works
Yan, J., Pan, Y., Shao, W., Wang, C., Wang, R., He, Y., Zhang, M., Wang, Y., Li, T., Wang, Z., et al. (2022) · Microbiome · doi:10.1186/s40168-022-01390-0 · Cited by 148 · see citing works
Bile Acids, Intestinal Barrier Dysfunction, and Related Diseases
Shi, L., Jin, L., & Huang, W. (2023) · Cells · doi:10.3390/cells12141888 · Cited by 148 · see citing works
Next-generation probiotics: a promising approach towards designing personalized medicine
Singh, T. P., & Nataraj, B. H. (2021) · Critical Reviews in Microbiology · doi:10.1080/1040841x.2021.1902940 · Cited by 145 · see citing works
The microbiome: An emerging key player in aging and longevity
Kim, M., & Benayoun, B. A. (2020) · Translational Medicine of Aging · doi:10.1016/j.tma.2020.07.004 · Cited by 142 · see citing works
Cheng, X. M., Tan, Y., Li, H., Huang, J., Zhao, D., Zhang, Z., Yi, M., Zhu, L., Hui, S., Yang, J., et al. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.106312 · Cited by 141 · see citing works
Álvarez, J., Fernández‐Real, J. M., Guarner, F., Gueimonde, M., Rodríguez, J. M., de Pipaón, M. S., & Sanz, Y. (2021) · Gastroenterología y Hepatología · doi:10.1016/j.gastrohep.2021.01.009 · Cited by 135 · see citing works
Ma, J., Liu, Z., Gao, X., Bao, Y., Hong, Y., He, X., Zhu, W., Li, Y., Huang, W., Zheng, N., et al. (2023) · Pharmacological Research · doi:10.1016/j.phrs.2023.106687 · Cited by 131 · see citing works
Toward an improved definition of a healthy microbiome for healthy aging
Ghosh, T. S., Shanahan, F., & O’Toole, P. W. (2022) · Nature Aging · doi:10.1038/s43587-022-00306-9 · Cited by 128 · see citing works
Luo, Y., Lan, C., Li, H., Ouyang, Q., Kong, F., Wu, A., Ren, Z., Tian, G., Cai, J., Yu, B., et al. (2022) · npj Biofilms and Microbiomes · doi:10.1038/s41522-022-00338-4 · Cited by 127 · see citing works
Zhao, Q., Yu, J., Zhou, H., Zhang, C., Wang, X., Hu, J., Hu, Y., HU, Y., Zeng, F., Zeng, F., et al. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-01219-0 · Cited by 127 · see citing works
Wang, Y., Wang, K., Huang, L., Dong, P., Wang, S., Chen, H., Lu, Z., Hou, D., & Zhang, D. (2020) · Microbiome · doi:10.1186/s40168-020-00879-w · Cited by 126 · see citing works
Age-related changes in intestinal immunity and the microbiome
Walrath, T., Dyamenahalli, K. U., Hulsebus, H. J., McCullough, R. L., Idrovo, J., Boe, D. M., McMahan, R. H., & Kovacs, E. J. (2020) · Journal of Leukocyte Biology · doi:10.1002/jlb.3ri0620-405rr · Cited by 124 · see citing works
Identification of Allobaculum mucolyticum as a novel human intestinal mucin degrader
van Muijlwijk, G. H., van Mierlo, G., Jansen, P. W. T. C., Vermeulen, M., Bleumink‐Pluym, N. M. C., Palm, N. W., van Putten, J. P. M., & de Zoete, M. R. (2021) · Gut Microbes · doi:10.1080/19490976.2021.1966278 · Cited by 118 · see citing works
Li, N., Tan, S., Wang, Y., Deng, J., Wang, N., Zhu, S., Tian, W., Xu, J., & Wang, Q. (2023) · Gut Microbes · doi:10.1080/19490976.2023.2252764 · Cited by 117 · see citing works
Shin, J., Noh, J., Choe, D., Lee, N., Song, Y., Cho, S., Kang, E., Go, M., Ha, S. K., Chang, D., et al. (2021) · Microbiome · doi:10.1186/s40168-021-01189-5 · Cited by 116 · see citing works
A review of a potential and promising probiotic candidate— Akkermansia muciniphila
Cheng, D., & Xie, M. Z. (2020) · Journal of Applied Microbiology · doi:10.1111/jam.14911 · Cited by 113 · see citing works
Chen, T., & Yang, C. S. (2019) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2019.1654430 · Cited by 111 · see citing works
Álvarez, J., Fernández‐Real, J. M., Guarner, F., Gueimonde, M., Rodríguez, J. M., de Pipaon, M. S., & Sanz, Y. (2021) · Gastroenterología y Hepatología (English Edition) · doi:10.1016/j.gastre.2021.01.002 · Cited by 109 · see citing works
Kim, S., Park, S., Hwang, S.-H., Lee, E.-Y., Kim, J.-H., Lee, G. S., Lee, G., Chang, D., Lee, J. G., Hwang, J., et al. (2023) · Cell Host & Microbe · doi:10.1016/j.chom.2023.05.007 · Cited by 108 · see citing works
Microbiota-gut-brain axis drives overeating disorders
Fan, S., Guo, W., Xiao, D., Guan, M., Liao, T., Peng, S., Feng, A., Wang, Z., Yin, H., Li, M., et al. (2023) · Cell Metabolism · doi:10.1016/j.cmet.2023.09.005 · Cited by 104 · see citing works
Higarza, S. G., Arboleya, S., Arias, J. L., Gueimonde, M., & Arias, N. (2021) · Gut Microbes · doi:10.1080/19490976.2021.1880240 · Cited by 103 · see citing works
Wu, L., Xie, X., Li, Y., Liang, T., Zhong, H., Yang, L., Yu, X., Zhang, J., Ding, Y., & Wu, Q. (2022) · npj Biofilms and Microbiomes · doi:10.1038/s41522-022-00366-0 · Cited by 102 · see citing works
Luo, H., Wu, F. Q., Wang, X., Lin, S., Zhang, M., Cao, Z., & Liu, J. (2023) · Materials Today · doi:10.1016/j.mattod.2023.01.001 · Cited by 102 · see citing works
Akkermansia muciniphila plays critical roles in host health
Zhao, Q., Yu, J., Hao, Y., Zhou, H., Hu, Y., Zhang, C., Zheng, H., Wang, X., Zeng, F., Hu, J., et al. (2022) · Critical Reviews in Microbiology · doi:10.1080/1040841x.2022.2037506 · Cited by 101 · see citing works
Intratumoural microbiome can predict the prognosis of hepatocellular carcinoma after surgery
Sun, L., Ke, X., Guan, A., Jin, B., Qu, J., Wang, Y., Xu, X., Li, C., Sun, H., Xu, H., et al. (2023) · Clinical and Translational Medicine · doi:10.1002/ctm2.1331 · Cited by 101 · see citing works
The 3 I’s of immunity and aging: immunosenescence, inflammaging, and immune resilience
Wrona, M. V., Ghosh, R. B., Coll, K., Chun, C., & Yousefzadeh, M. J. (2024) · Frontiers in Aging · doi:10.3389/fragi.2024.1490302 · Cited by 102 · see citing works
Luo, D., Chen, K., Li, J., Fang, Z., Pang, H., Yin, Y., Rong, X., & Guo, J. (2019) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2019.109550 · Cited by 100 · see citing works
Zhang, P., Liu, J., Xiong, B., Zhang, C., Kang, B., Gao, Y., Li, Z., Ge, W., Cheng, S., Hao, Y., et al. (2020) · Microbiome · doi:10.1186/s40168-020-00886-x · Cited by 99 · see citing works
Tan, R., Dong, H., Chen, Z., Jin, M., Yin, J., Li, H., Shi, D., Shao, Y., Wang, H., Chen, T., et al. (2021) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2021.654074 · Cited by 99 · see citing works
Gut Microbiota and Atherosclerosis—Focusing on the Plaque Stability
Shen, X., Li, L., Sun, Z., Zang, G., Zhang, L., Shao, C., & Wang, Z. (2021) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2021.668532 · Cited by 99 · see citing works
Organ System Crosstalk in Cardiometabolic Disease in the Age of Multimorbidity
Oishi, Y., & Manabe, I. (2020) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2020.00064 · Cited by 96 · see citing works
The hallmarks of aging as a conceptual framework for health and longevity research
Tartiere, A. G., Freije, J. M. P., & López-Otı́n, C. (2024) · Frontiers in Aging · doi:10.3389/fragi.2024.1334261 · Cited by 96 · see citing works
Self-citationYe, M., Yu, J., Shi, X., Zhu, J., Gao, X., & Liu, W. Y. (2020) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2020.1803198 · Cited by 95 · see citing works
Xu, R., Zhang, Y., Chen, S., Zeng, Y., Fu, X., Chen, T., Luo, S., & Zhang, X. (2022) · Critical Reviews in Microbiology · doi:10.1080/1040841x.2022.2044286 · Cited by 95 · see citing works
Zhuge, A., Li, S., Han, S., Yuan, Y., Shen, J., Wu, W., Wang, K., Xia, J., Wang, Q., Gu, Y., et al. (2024) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2024.10.010 · Cited by 94 · see citing works
Investiture of next generation probiotics on amelioration of diseases – Strains do matter
Lin, T., Shu, C.-C., Lai, W.-F., Tzeng, C., Lai, H., & Lu, C. (2019) · Medicine in Microecology · doi:10.1016/j.medmic.2019.100002 · Cited by 93 · see citing works
Gut microbiota and renin-angiotensin system: a complex interplay at local and systemic levels
Jaworska, K., Koper, M., & Ufnal, M. (2021) · American Journal of Physiology-Gastrointestinal and Liver Physiology · doi:10.1152/ajpgi.00099.2021 · Cited by 93 · see citing works
The Role of Rapamycin in Healthspan Extension via the Delay of Organ Aging
Zhang, Y., Zhang, J., & Wang, S. (2021) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101376 · Cited by 92 · see citing works
Li, Z., Hu, G.-A., Zhu, L., Sun, Z., Jiang, Y., Gao, M., & Zhan, X. (2021) · BMC Microbiology · doi:10.1186/s12866-021-02111-7 · Cited by 92 · see citing works
Interventions on Gut Microbiota for Healthy Aging
Zeppa, S. D., Agostini, D., Ferrini, F., Gervasi, M., Barbieri, E., Bartolacci, A., Piccoli, G., Saltarelli, R., Sestili, P., & Stocchi, V. (2022) · Cells · doi:10.3390/cells12010034 · Cited by 91 · see citing works
Bladder cancer, inflammageing and microbiomes
Martin, A., Woolbright, B. L., Umar, S., Ingersoll, M. A., & Taylor, J. A. (2022) · Nature Reviews Urology · doi:10.1038/s41585-022-00611-3 · Cited by 89 · see citing works
Abnormalities in microbiota/butyrate/FFAR3 signaling in aging gut impair brain function
Mishra, S. P., Jain, S., Wang, B., Wang, S., Miller, B. C., Lee, J.-Y., Borlongan, C. V., Jiang, L., Pollak, J., Taraphder, S., et al. (2024) · JCI Insight · doi:10.1172/jci.insight.168443 · Cited by 89 · see citing works
Hou, Q., Huang, J., Zhao, L., Pan, X., Liao, C., Jiang, Q., Lei, J., Guo, F., Cui, J., Guo, Y., et al. (2023) · Pharmacological Research · doi:10.1016/j.phrs.2023.106676 · Cited by 88 · see citing works
FTZ polysaccharides ameliorate kidney injury in diabetic mice by regulating gut-kidney axis
Lan, T., Tang, T., Li, Y., Duan, Y., Yuan, Q., Liu, W., Ren, Y., Li, N., Liu, X., Zhang, Y., et al. (2023) · Phytomedicine · doi:10.1016/j.phymed.2023.154935 · Cited by 88 · see citing works
Gut microbiota and microbial metabolites for osteoporosis
Zheng, X.-Q., Wang, D.-B., Jiang, Y., & Song, C. (2024) · Gut Microbes · doi:10.1080/19490976.2024.2437247 · Cited by 89 · see citing works
Jiang, L., Ye, Y., Han, Y., Wang, Q., Lu, H., Li, J., Qian, W., Zeng, X. Y., Zhang, Z., Zhao, Y., et al. (2024) · Cell Discovery · doi:10.1038/s41421-024-00665-0 · Cited by 86 · see citing works
Zhou, X., Lu, J., Wei, K., Wei, J., Tian, P., Yue, M., Wang, Y., Hong, D., Li, F., Wang, B., et al. (2021) · Oxidative Medicine and Cellular Longevity · doi:10.1155/2021/9424582 · Cited by 85 · see citing works
Gut microbial-derived phenylacetylglutamine accelerates host cellular senescence
Yang, H., Wang, T., Qian, C., Wang, H., Yu, D. S., Shi, M., Fu, M., Liu, X., Pan, M., Rong, X., et al. (2025) · Nature Aging · doi:10.1038/s43587-024-00795-w · Cited by 85 · see citing works
Barathikannan, K., Chelliah, R., Rubab, M., Daliri, E. B., Elahi, F., Kim, D.-H., Agastian, P., Oh, S.-Y., & Oh, D. H. (2019) · Microorganisms · doi:10.3390/microorganisms7100456 · Cited by 84 · see citing works
Hohman, L. S., & Osborne, L. C. (2022) · Aging Cell · doi:10.1111/acel.13700 · Cited by 83 · see citing works
Chang, Z., Deng, G.-F., Shao, Y., Xu, D., Zhao, Y., Sun, Y.-F., Zhang, S.-Q., Hou, R., & Liu, J. (2021) · Frontiers in Pharmacology · doi:10.3389/fphar.2021.670054 · Cited by 81 · see citing works
Warman, D. J., Jia, H., & Kato, H. (2022) · Nutrients · doi:10.3390/nu14040747 · Cited by 79 · see citing works
Zhou, C., Zou, Y., Xu, R., Han, X., Xiang, Z., Guo, H., Li, X., Liang, J., Zhang, X., Fan, Y., et al. (2023) · Materials Horizons · doi:10.1039/d3mh00033h · Cited by 78 · see citing works
- Authors
- Bárcena, C., Valdés-Mas, R., Mayoral, P., Garabaya, C., Durand, S., Rodríguez, F., Fernández-García, M. T., Salazar, N., Nogacka, A. M., Garatachea, N., Bossut, N., Aprahamian, F., Lucia, A., Kroemer, G., Freije, J. M. P., Quirós, P. M., & López-Otín, C.
- Affiliations
- Universidad de Oviedo (ES)
- Inserm (FR)
- Consejo Superior de Investigaciones Científicas (ES)
- Universidad de Zaragoza (ES)
- Karolinska University Hospital (SE)
- Corresponding author
- Quirós, Pedro M.
- ORCID
- Venue
- Nature Medicine
- Published
- 2019-07-22
- Volume
- 25
- Issue
- 8
- Pages
- 1234-1242
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W2963531283
- Cited by
- 661
- References
- 49
- Citations by year
- 2026: 78 · 2025: 110 · 2024: 124 · 2023: 90 · 2022: 95 · 2021: 86 · 2020: 65 · 2019: 12
- FWCI
- 22.10
- Type
- journal article
- Language
- en
- Open access
- green
- hal.science
- Licence
- Locations
- Nature Medicine (publishedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion, cc-by-nc-nd)
- ABACUS. Repositorio de Producción Científica (Universidad Europea) (submittedVersion)
- Consultation of the Doctoral Thesis Database (TESEO) (Ministerio de Educación, Cultura y Deporte) (submittedVersion, cc-by-nc-nd)
- DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, other-oa)
- Funders
- Agence Nationale de la Recherche (ANR-16-ECVD-0008)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Life Sciences › Agricultural and Biological Sciences › Food Science › Probiotics and Fermented Foods
- Keywords
- fecal microbiota transplantation, gut microbiota, aging, healthspan, lifespan extension, Hutchinson-Gilford progeria syndrome, gut dysbiosis, Akkermansia muciniphila, Verrucomicrobia, Proteobacteria, centenarians, secondary bile acids, microbiota-targeted interventions
- MeSH terms
- Gastrointestinal Microbiome, Fecal Microbiota Transplantation, Animals, Disease Models, Animal, Female, Humans, Longevity, Male, Mice, Inbred C57BL, Progeria, Mice, Metabolomics, Dysbiosis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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