Table 1 Human metagenomic studies of the gut microbiome and cardio-metabolic traits

Ley et al. (2006) [41]

To investigate the effect of either a carbohydrate- or fat-restricted diet on gut microbial ecology

14 adults; 12 obese, 2 lean

Randomized intervention

16S rRNA

• Increased abundance of Firmicutes and reduced abundance of Bacteroidetes in obese

• Increased abundance of Bacteroidetes and decreased abundance of Firmicutes following 1 year of either fat- or carbohydrate-restricted low-calorie diet

• Increase in Bacteroidetes correlated with body weight reduction regardless of diet

Zhang et al. (2009) [161]

To investigate microbiota composition in morbid obesity and following RYGB

9 adults; 3 lean, 3 morbidly obese, 3 post RYGB

Cross-sectional

16S rRNA, qPCR

• Firmicutes dominant in normal weight and obese, decreased in post RYGB

• Gamma-Proteobacteria increased whereas Clostridia decreased post-RYGB

• Prevotellaceae highly enriched in obese

• Methanobacteriales highly abundant in obese, while non-detectable in normal weight

Turnbaugh et al. (2009) [37]

To investigate the influence of host genotype, environmental exposure and host adiposity

154 adults; 31 MZ twin pairs, 23 DZ twin pairs, (concordant for obesity or leanness), 46 mothers

Cross-sectional

16S rRNA

• Lower proportion of Bacteroidetes and a higher proportion of Actinobacteria in obese

• Obesity associated with reduced diversity

• Obese microbiome enriched for genes involved in macronutrient metabolism

Larsen et al. (2010) [12]

To investigate differences in gut microbiota composition associated with T2D

20 adults; 10 T2D, 10 NGT

Cross-sectional

16S rRNA, qPCR

• Decreased diversity in T2D

• Firmicutes, including Clostridia, decreased in T2D

• The ratio of the phylogenetic groups Bacteroides-Prevotella to Clostridium coccoides-Eubacterium rectale and the Bacteroidetes to Firmicutes ratio correlated positively with 2 h p-glucose during an OGTT

• Beta-Proteobacteria highly enriched in T2D and correlated with 2 hour p-glucose during an OGTT

Jumpertz et al. (2011) [5]

To investigate the effect of caloric intake on microbiota composition in lean and obese

21 adults; 12 lean, 9 obese

Randomized cross-over intervention

16S rRNA

• High-calorie diet changes the relative abundance of microbiota on the phylum (Bacteroidetes versus Firmicutes), class (Bacteroidetes versus Clostridia), and order level (Bacteroidales versus Clostridiales)

• Phylum-, class-, and order-level changes in microbiota composition during intervention associated with fecal caloric content in lean but not in obese

Koren et al. (2011) [59]

To investigate the bacterial diversity of atherosclerotic plaque, oral cavity and gut in patients with CVD

30 adults; 15 CVD, 15 healthy

Cross-sectional

16S rRNA, qPCR

• No phylum- or genus level compositional difference between CVD patients and healthy controls

• Several shared OTUs between atherosclerotic plaque and fecal samples

Karlsson et al. (2012) [60]

To investigate the microbiota composition in patients with CVD

25 adults; 13 CVD, 12 healthy controls

Cross-sectional

Quantitative metagenomics

• Colinsella enriched in patients, Eubacterium and Roseburia enriched in controls

• Genera of Clostridiales, Clostridium and Peptostreptococcus negatively correlated with hsCRP

• Atherosclerosis associated with the Ruminococcus enterotype

Qin et al. (2012) [13]

To investigate differences in gut microbiota composition and function associated with T2D

368 adults; 183 T2D cases, 185 healthy controls

Cross-sectional

Quantitative metagenomics

• T2D associated with moderate dysbiosis with a decline in butyrate-producing bacteria

• Gut-microbiome-based T2D index accurately classifies T2D individuals

Le Chatelier et al. (2013) [55]

To investigate the bacterial abundance in lean and obese

292 adults; 123 lean, 169 obese

Cross-sectional/retrospective

Quantitative metagenomics and 16S rRNA

• Low bacterial richness associates with increased overall adiposity, insulin resistance, dyslipidemia, and a more pronounced inflammatory phenotype

• Discrimination between high versus low gene count and obesity status possible from a combination of only four species with ROC analysis AUC of 0.97

• Increased weight gain in individuals with low microbial gene count

Karlsson et al. (2013) [16]

To investigate differences in gut microbiota composition and function associated with T2D

145 adults; 53 T2D, 49 IGT, 43 NGT

Cross-sectional

Quantitative metagenomics

• Increased abundance of Lactobacillus spp. and abundance of Clostridium spp. decreased

• Clostridium spp. correlated with fasting glucose and HbA1c, whereas Lactobacillus spp. correlated negatively with fasting glucose, insulin, C-peptide and TAG, and positively with adiponectin and HDL

• Microbiota composition as determined by metagenomic clusters better correlated with T2D than known clinical risk factors (WC, WHR and BMI)

Zhang et al. (2013) [17]

To investigate differences in gut microbiota composition associated with T2D

121 adults; 44 NGT, 64 IGT, 13 T2D

Cross-sectional

16S rRNA

• Higher abundance of Clostridia in T2D

• Negative trend of abundance of Streptococcus from NGT to IGT to T2D

• Enterotype classification not associated with glucose tolerance status

• 28 OTUs associated with glucose tolerance status

• Fasting glucose associated with microbiota composition

• Fasting insulin inversely associated with alpha (intraindividual) diversity

Kong et al. (2013) [160]

To investigate the impact of RYGB on microbiota composition

30 adults; 7 T2D, 23 non-T2D obese

Non-randomized intervention

16S rRNA

• Increased bacterial richness following RYGB, mainly within the phylum Proteobacteria

• RYGB induced genus-level changes in microbiota composition correlated with changes in white adipose tissue gene expression

Graessler et al. (2013) [14]

To investigate the impact of RYGB on microbiota composition and function

6 adults; 5 T2D, 1 non-T2D obese

Non-randomized intervention

Quantitative metagenomics

• Relative abundance of 22 species an 11 genera affected 3 months after RYGB

• Overall, RYGB induced phylum-level changes characterized by reduction in Bacteroidetes and Firmicutes and an increase in Proteobacteria and Verrucomicrobia

• Species-level changes dominated by an increase in A. muciniphila, E. coli and K. pneumonia and a decrease in F. prausnitzii, E. rectale and D. invisus.