Table 1 Athlete/exercise-associated gut microbiota in comparison to other populations or across athletic classification: Characteristics of included articles (by publication date)
Authors, year, country | Subjects | Sex and age | Study design and gut microbiome analysis | Diet and/or exercise | Key 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 cyclists | 22 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. |