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Table 1 Athlete/exercise-associated gut microbiota in comparison to other populations or across athletic classification: Characteristics of included articles (by publication date)

From: The athletic gut microbiota

Authors, year, countrySubjectsSex and ageStudy design and gut microbiome analysisDiet and/or exerciseKey outcome(s)
1. Clarke et al., 2014, Ireland [19]Professional male rugby athletes (n = 40) and healthy size, age and sex matched controls (n = 46)86 Males
23–35 years
Cross-sectional, observational
16S rRNA gene amplification of the V4 region
Diet recorded by a 187-food item FFQa.
Physical activity levels assessed by EPICb-Norfolk questionnaire.
• Athletes had a higher GMc diversity compared to controls.
• Athletes in low BMId (< 25 kg/m2) group had higher proportions of genus Akkermansia compared with high BMI (> 28 kg/m2) group.
2. Bressa et al., 2017, Spain [56]Healthy premenopausal women; active defined by WHOe (n = 19) and sedentary (n = 21)40 Females
18–40 years
Cross-sectional, observational
16S rRNA gene amplification of the V3 and V4 regions
Acceleration, energy expenditure, intensity of physical activity and body position measured by Acti -Sleep V.3.4.2 accelerometer.
Dietary pattern assessed by 97 food item FFQ.
• Physical activity associated with increased the abundance of health-promoting bacteria (Bifidobacterium species, Roseburia hominis, A. muciniphila and Faecalibacterium prausnitzii) in the microbiota.
• Inverse association between sedentary parameters and microbiota richness (number of species, and Shannon and Simpson indices).
3. Mörkl et al., 2017, Austria [57]Anorexia nervosa patients (n = 18), athletes (n = 20), normal weight (n = 26), overweight (n = 22), and obese women (n = 20).106 Females
18–40 years
Cross-sectional, observational
16S rRNA gene amplification of the V1 and V2 regions
24-h recall dietary intake
Activity level assessed by IPAQf score & METg/min
• Lower microbial richness in obese and anorexic individuals compared to athletes.
4. Petersen et al., 2017, USA [18]Professional (n = 22) and amateur (n = 11) level competitive cyclists22 Males/ 11 Females
19–49 years
Cross-sectional, observational
Metagenomic whole genome shotgun sequencing and RNA sequencing
Exercise load (hours/week): 6–10; 11–15; 16–20; and; 20 + .
Diet: equal protein, fat, carbohydrate; vegetarian; high complex carbohydrate; paleo; gluten-free.
• No significant correlations between taxonomic cluster and professional or amateur level cyclists.
• High relative abundance of Prevotella in cyclists training > 11 h/week.
• Increased abundance of Methanobrevibacter smithii transcripts in professional cyclists.
5. Barton et al., 2018, Ireland [13]Professional male rugby athletes (n = 40) and healthy size, age and gender matched controls (n = 46)86 Males
23–35 years
Cross-sectional, observational
Metagenomic whole genome shotgun sequencing and urine and fecal metabolomics
Diet recorded by a 187-food item FFQ.
Physical activity levels assessed by EPIC-Norfolk questionnaire. Serum creatine kinase levels were used as a proxy for level of physical activity.
• The microbiota of athletes was more diverse than both the low and high BMI control groups at the functional level.
• Athletes had an enriched profile of SCFAsh and higher levels of the metabolite TMAOi.
6. Jang et al., 2019, South Korea [11]Healthy sedentary men (as controls; n = 15), bodybuilders (n = 15), and elite distance runners (n = 15)45 Males
19–28 years
Cross-sectional, observational
16S rRNA gene amplification of the V3 and V4 regions
Physical activity level was assessed using the IPAQ.
Dietary intake was analyzed with the computerized nutritional evaluation program.
• Exercise type was associated with athlete diet patterns (bodybuilders: high-protein, high-fat, low-carbohydrate, and low-dietary fiber diet; distance runners: low-carbohydrate and low dietary fiber diet). Athlete type was significantly associated with the relative abundance of gut microbiota at the genus and species level.
• Increased abundance of Faecalibacterium, Sutterella, Clostridium, Haemophilus, and Eisenbergiella in bodybuilders.
• Athlete type did not differ in gut microbiota alpha and beta diversity.
7. O’Donovan et al., 2019, Ireland [58]Elite athletes from 16 different sports (n = 37)23 Males/ 14 Females
27 ± 5 years
Cross-sectional, observational
Metagenomic whole genome shotgun sequencing and urine and fecal metabolomics
Diet recorded by FFQ.• Microbial diversity did not differ between sport classification.
• Overall, samples dominated by species from one or a combination of five species: Eubacterium rectale, Polynucleobacter necessarius, Faecalibacterium prausnitzii, Bacteroides vulgatus and Gordonibacter massiliensis.
• Athletes with high dynamicj component were associated with greater abundance of Bifidobacterium animalis, Lactobacillus acidophilus, Prevotella intermedia and F. prausnitzii.
• Athletes with both a high dynamic and statick component were associated with greater abundance of Bacteroides caccae.
  1. aFFQ Food frequency questionnaire
  2. bEPIC European Prospective Investigation of Cancer
  3. cGM Gut microbiota
  4. dBMI Body mass index
  5. eWHO World Health Organization
  6. fIPAQ International Physical Activity Questionnaire
  7. gMET Metabolic equivalent
  8. hSCFA Short-chain fatty acid
  9. iTMAO Trimethylamine N-oxide
  10. jDynamic Classified by estimated VO2max
  11. kStatic Classified by maximal voluntary contraction