Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 45

The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.

Differences in Gut Microbiome Composition between Senior Orienteering Athletes and Community-Dwelling Older Adults

Fart, Frida, Rajan, Sukithar Kochappi, Wall, Rebecca, Rangel, Ignacio, Ganda-Mall, John Peter, Tingö, Lina, Brummer, Robert J., Repsilber, Dirk, Schoultz, Ida, Lindqvist, Carl Mårten·2020·Nutrients

Abstract

Background: Gastrointestinal (GI) health is an important aspect of general health. Gastrointestinal symptoms are of specific importance for the elderly, an increasing group globally. Hence, promoting the elderly’s health and especially gastrointestinal health is important. Gut microbiota can influence gastrointestinal health by modulation of the immune system and the gut–brain axis. Diverse gut microbiota have been shown to be beneficial; however, for the elderly, the gut microbiota is often less diverse. Nutrition and physical activity, in particular, are two components that have been suggested to influence composition or diversity. Materials and Methods: In this study, we compared gut microbiota between two groups of elderly individuals: community-dwelling older adults and physically active senior orienteering athletes, where the latter group has less gastrointestinal symptoms and a reported better well-being. With this approach, we explored if certain gut microbiota were related to healthy ageing. The participant data and faecal samples were collected from these two groups and the microbiota was whole-genome sequenced and taxonomically classified with MetaPhlAn. Results: The physically active senior orienteers had a more homogeneous microbiota within the group and a higher abundance of Faecalibacterium prausnitzii compared to the community-dwelling older adults. Faecalibacterium prausnitzii has previously shown to have beneficial properties. Senior orienteers also had a lower abundance of Parasutterella excrementihominis and Bilophila unclassified, which have been associated with impaired GI health. We could not observe any difference between the groups in terms of Shannon diversity index. Interestingly, a subgroup of community-dwelling older adults showed an atypical microbiota profile as well as the parameters for gastrointestinal symptoms and well-being closer to senior orienteers. Conclusions: Our results suggest specific composition characteristics of healthy microbiota in the elderly, and show that certain components of nutrition as well as psychological distress are not as tightly connected with composition or diversity variation in faecal microbiota samples.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/nu12092610

Cites

14 of 14 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

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?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 62

  1. Dinan, 2017, The Microbiome-Gut-Brain Axis in Health and Disease, Gastroenterol. Clin. N. Am., 46, 77, 10.1016/j.gtc.2016.09.007 · DOI · Paper page
  2. Algilani, 2014, Exploring the concept of optimal functionality in old age, J. Multidiscip. Healthc., 7, 69
  3. Fart, F., Tingoe, L., Engelheart, S., Lindqvist, C.-M., Brummer, R.J., Kihlgren, A., and Schoultz, I. (2019). Gut Health, nutrient intake and well-being in community-dwelling older adults. medRxiv. · DOI
  4. Östlund-Lagerström, L., Blomberg, K., Algilani, S., Schoultz, M., Kihlgren, A., Brummer, R.J., and Schoultz, I. (2015). Senior orienteering athletes as a model of healthy aging: A mixed-method approach. BMC Geriatr., 15. · DOI
  5. Rowe, 1987, Human aging: Usual and successful, Science, 237, 143, 10.1126/science.3299702 · DOI · Paper page
  6. Ganda Mall, J.-P., Östlund-Lagerström, L., Lindqvist, C.M., Algilani, S., Rasoal, D., Repsilber, D., Brummer, R.J., Keita, Å.V., and Schoultz, I. (2018). Are self-reported gastrointestinal symptoms among older adults associated with increased intestinal permeability and psychological distress?. BMC Geriatr., 18. · DOI
  7. Mahnic, A., and Rupnik, M. (2018). Different host factors are associated with patterns in bacterial and fungal gut microbiota in Slovenian healthy cohort. PLoS ONE, 13. · DOI
  8. Hasan, 2019, Factors affecting the composition of the gut microbiota, and its modulation, PeerJ, 7, e7502, 10.7717/peerj.7502 · DOI · Paper page
  9. Kho, 2018, The Human Gut Microbiome—A Potential Controller of Wellness and Disease, Front. Microbiol., 9, 1835, 10.3389/fmicb.2018.01835 · DOI · Paper page
  10. Takiishi, 2017, Intestinal barrier and gut microbiota: Shaping our immune responses throughout life, Tissue Barriers, 5, e1373208, 10.1080/21688370.2017.1373208 · DOI · Paper page
  11. Rea, 2020, Gut Microbiota: A Perspective for Psychiatrists, Neuropsychobiology, 79, 50, 10.1159/000504495 · DOI
  12. Claesson, 2012, Gut microbiota composition correlates with diet and health in the elderly, Nature, 488, 178, 10.1038/nature11319 · DOI · Paper page
  13. Salazar, 2017, Nutrition and the gut microbiome in the elderly, Gut Microbes, 8, 82, 10.1080/19490976.2016.1256525 · DOI · Paper page
  14. Mitchell, 2019, Does Exercise Alter Gut Microbial Composition? A Systematic Review, Med. Sci. Sports Exerc., 51, 160, 10.1249/MSS.0000000000001760 · DOI
  15. Lindqvist, 2018, Differential effects of dietary fibres on colonic barrier function in elderly individuals with gastrointestinal symptoms, Sci. Rep., 8, 13404, 10.1038/s41598-018-31492-5 · DOI
  16. Svedlund, 1988, GSRS—A clinical rating scale for gastrointestinal symptoms in patients with irritable bowel syndrome and peptic ulcer disease, Dig. Dis. Sci., 33, 129, 10.1007/BF01535722 · DOI · Paper page
  17. Roberts, 2014, The validity and clinical utility of the hospital anxiety and depression scale (HADS) with older adult New Zealanders, Int. Psychogeriatr., 26, 325, 10.1017/S104161021300197X · DOI
  18. Sundh, 1995, A life span perspective on patterns of physical activity and functional performance at the age of 76, Gerontology, 41, 109, 10.1159/000213671 · DOI
  19. Brumfield, K.D., Huq, A., Colwell, R.R., Olds, J.L., and Leddy, M.B. (2020). Microbial resolution of whole genome shotgun and 16S amplicon metagenomic sequencing using publicly available NEON data. PLoS ONE, 15. · DOI
  20. Welch, 1947, The generalisation of student’s problems when several different population variances are involved, Biometrika, 34, 28
  21. Mwalili, 2008, The zero-inflated negative binomial regression model with correction for misclassification: An example in caries research, Stat. Methods Med. Res., 17, 123, 10.1177/0962280206071840 · DOI
  22. Calle, 2019, Statistical Analysis of Metagenomics Data, Genom. Inform., 17, e6, 10.5808/GI.2019.17.1.e6 · DOI · Paper page
  23. Xia, 2017, Hypothesis Testing and Statistical Analysis of Microbiome, Genes Dis., 4, 138, 10.1016/j.gendis.2017.06.001 · DOI
  24. Boulesteix, 2006, Maximally selected chi-square statistics for ordinal variables, Biom. J., 48, 451, 10.1002/bimj.200510161 · DOI
  25. Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis, Springer. · DOI · Paper page
  26. McGill, 1978, Variations of Box Plots, Am. Stat., 32, 12, 10.1080/00031305.1978.10479236 · DOI · Paper page
  27. Zeileis, A., Kleiber, C., and Jackman, S. (2008). Regression Models for Count Data in R. J. Stat. Soft., 27. · DOI · Paper page
  28. Benjamini, 1995, Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing, J. R. Stat. Soc. Ser. B, 57, 289, 10.1111/j.2517-6161.1995.tb02031.x · DOI · Paper page
  29. Miquel, 2013, Faecalibacterium prausnitzii and human intestinal health, Curr. Opin. Microbiol., 16, 255, 10.1016/j.mib.2013.06.003 · DOI · Paper page
  30. Saxelin, 2010, Persistence of probiotic strains in the gastrointestinal tract when administered as capsules, yoghurt, or cheese, Int. J. Food Microbiol., 144, 293, 10.1016/j.ijfoodmicro.2010.10.009 · DOI
  31. Wan, 2019, Effects of dietary fat on gut microbiota and faecal metabolites, and their relationship with cardiometabolic risk factors: A 6-month randomised controlled-feeding trial, Gut, 68, 1417, 10.1136/gutjnl-2018-317609 · DOI · Paper page
  32. David, 2014, Diet rapidly and reproducibly alters the human gut microbiome, Nature, 505, 559, 10.1038/nature12820 · DOI · Paper page
  33. Venkataraman, 2016, Variable responses of human microbiomes to dietary supplementation with resistant starch, Microbiome, 4, 33, 10.1186/s40168-016-0178-x · DOI · Paper page
  34. Duncan, 2002, Growth requirements and fermentation products of Fusobacterium prausnitzii, and a proposal to reclassify it as Faecalibacterium prausnitzii gen. nov., comb. nov, Int. J. Syst. Evol. Microbiol., 52, 2141
  35. Collins, 1994, The Phylogeny of the Genus Clostridium: Proposal of Five New Genera and Eleven New Species Combinations, Int. J. Syst. Bacteriol., 44, 812, 10.1099/00207713-44-4-812 · DOI · Paper page
  36. Louis, 2009, Diversity, metabolism and microbial ecology of butyrate-producing bacteria from the human large intestine, FEMS Microbiol. Lett., 294, 1, 10.1111/j.1574-6968.2009.01514.x · DOI · Paper page
  37. Andrade, 2017, Action and function of Faecalibacterium prausnitzii in health and disease, Best Pract. Res. Clin. Gastroenterol., 31, 643, 10.1016/j.bpg.2017.09.011 · DOI · Paper page
  38. Stumpff, 2012, Microbial butyrate and its role for barrier function in the gastrointestinal tract: Butyrate and the gastrointestinal barrier, Ann. N. Y. Acad. Sci., 1258, 52, 10.1111/j.1749-6632.2012.06553.x · DOI · Paper page
  39. Salazar, 2017, Adherence to a Mediterranean Diet Influences the Fecal Metabolic Profile of Microbial-Derived Phenolics in a Spanish Cohort of Middle-Age and Older People, J. Agric. Food Chem., 65, 586, 10.1021/acs.jafc.6b04408 · DOI
  40. Arumugam, 2011, Enterotypes of the human gut microbiome, Nature, 473, 174, 10.1038/nature09944 · DOI · Paper page
  41. Mueller, 2006, Differences in fecal microbiota in different European study populations in relation to age, gender, and country: A cross-sectional study, Appl. Environ. Microbiol., 72, 1027, 10.1128/AEM.72.2.1027-1033.2006 · DOI · Paper page
  42. Zhu, Q., Jiang, S., and Du, G. (2020). Effects of exercise frequency on the gut microbiota in elderly individuals. Microbiologyopen, e1053. · DOI · Paper page
  43. Xu, 2020, Influence of Exercise on the Human Gut Microbiota of Healthy Adults: A Systematic Review, Clin. Transl. Gastroenterol., 11, e00126, 10.14309/ctg.0000000000000126 · DOI
  44. Fragiadakis, 2019, Links between environment, diet, and the hunter-gatherer microbiome, Gut Microbes, 10, 216, 10.1080/19490976.2018.1494103 · DOI
  45. Fabre, 2017, Associations between hepatic miRNA expression, liver triacylglycerols and gut microbiota during metabolic adaptation to high-fat diet in mice, Diabetologia, 60, 690, 10.1007/s00125-017-4209-3 · DOI
  46. Chen, 2018, Parasutterella, in association with irritable bowel syndrome and intestinal chronic inflammation, J. Gastroenterol. Hepatol., 33, 1844, 10.1111/jgh.14281 · DOI · Paper page
  47. Rosenberg, E., DeLong, E.F., Lory, S., Stackebrandt, E., and Thompson, F. (2014). The Family Sutterellaceae. The Prokaryotes: Alphaproteobacteria and Betaproteobacteria, Springer. · DOI
  48. Shin, 2015, Proteobacteria: Microbial signature of dysbiosis in gut microbiota, Trends Biotechnol., 33, 496, 10.1016/j.tibtech.2015.06.011 · DOI · Paper page
  49. Scanlan, 2009, Culture-independent analysis of desulfovibrios in the human distal colon of healthy, colorectal cancer and polypectomized individuals, FEMS Microbiol. Ecol., 69, 213, 10.1111/j.1574-6941.2009.00709.x · DOI
  50. Xiao, 2014, A gut microbiota-targeted dietary intervention for amelioration of chronic inflammation underlying metabolic syndrome, FEMS Microbiol. Ecol., 87, 357, 10.1111/1574-6941.12228 · DOI · Paper page
  51. Yazici, 2017, Race-dependent association of sulfidogenic bacteria with colorectal cancer, Gut, 66, 1983, 10.1136/gutjnl-2016-313321 · DOI · Paper page
  52. Baron, 1997, Bilophila wadsworthia: A unique Gram-negative anaerobic rod, Anaerobe, 3, 83, 10.1006/anae.1997.0075 · DOI
  53. Baron, 1992, Bilophila wadsworthia isolates from clinical specimens, J. Clin. Microbiol., 30, 1882, 10.1128/jcm.30.7.1882-1884.1992 · DOI
  54. Feng, 2017, A human stool-derived Bilophila wadsworthia strain caused systemic inflammation in specific-pathogen-free mice, Gut Pathog., 9, 59, 10.1186/s13099-017-0208-7 · DOI
  55. McOrist, 2001, Colonic infection by Bilophila wadsworthia in pigs, J. Clin. Microbiol., 39, 1577, 10.1128/JCM.39.4.1577-1579.2001 · DOI
  56. Jackson, 2016, Proton pump inhibitors alter the composition of the gut microbiota, Gut, 65, 749, 10.1136/gutjnl-2015-310861 · DOI · Paper page
  57. Mu, 2019, Antibiotic effects on gut microbiota, metabolism, and beyond, Appl. Microbiol. Biotechnol., 103, 9277, 10.1007/s00253-019-10165-x · DOI
  58. Livanos, 2016, Antibiotic-mediated gut microbiome perturbation accelerates development of type 1 diabetes in mice, Nat Microbiol, 1, 16140, 10.1038/nmicrobiol.2016.140 · DOI · Paper page
  59. Santini, 2020, Social disconnectedness, perceived isolation, and symptoms of depression and anxiety among older Americans (NSHAP): A longitudinal mediation analysis, Lancet Public Health, 5, e62, 10.1016/S2468-2667(19)30230-0 · DOI · Paper page
  60. Cheung, 2019, Systematic Review of Gut Microbiota and Major Depression, Front. Psychiatry, 10, 34, 10.3389/fpsyt.2019.00034 · DOI · Paper page
  61. McBurney, 2019, Establishing What Constitutes a Healthy Human Gut Microbiome: State of the Science, Regulatory Considerations, and Future Directions, J. Nutr., 149, 1882, 10.1093/jn/nxz154 · DOI · Paper page
  62. Halfvarson, 2017, Dynamics of the human gut microbiome in inflammatory bowel disease, Nature Microbiol., 2, 17004, 10.1038/nmicrobiol.2017.4 · DOI · Paper page

Cited by

See all 45

Metadata

Authors
Fart, F., Rajan, S. K., Wall, R., Rangel, I., Ganda-Mall, J. P., Tingö, L., Brummer, R. J., Repsilber, D., Schoultz, I., & Lindqvist, C. M.
Venue
Nutrients
Publisher
MDPI AG
Published
2020-08-27
Volume
12
Issue
9
Pages
2610
ISSN
2072-6643
Cited by
45
References
14
Language
en
Funders
  • Bo Rydins Stiftelse för Vetenskaplig Forskning (F0514)
  • Stiftelsen för Kunskaps- och Kompetensutveckling (20110225)

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.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.