. 2023 Apr 26;14(11):787–806. doi: 10.1093/procel/pwad023

Table 1.

Literature about diet-gut microbiome associations and their roles in the host health^*.

Study design	Dietary feature	Study	Sample size	Duration of follow-up	Country	Sequencing	Health outcome
Cross-sectional study	Vegan diet	Wu et al. (2016)	31	N/A	USA	16S rRNA	N/A
	Vegan diet	Wu et al. (2016)	Plasma metabolome of vegans differed markedly from omnivores but the gut microbiota was surprisingly similar. Higher consumption of fermentable substrate in vegans was not associated with higher levels of fecal SCFAs.
	Habitual diet (foods, food groups, nutrients, and dietary patterns)	Zhernakova et al. (2016)	1,135	N/A	Netherlands	Metagenomics	N/A
		Zhernakova et al. (2016)	Sixty dietary factors were associated with the gut microbiome, including energy (kcal), intake of carbohydrates, proteins and fats, and of specific food items such as bread and soft drinks.
	N-3 fatty acids	Menni et al. (2017)	876	N/A	UK	16S rRNA	N/A
	N-3 fatty acids	Menni et al. (2017)	Total omega-3 fatty acids and docosahexaenoic acid (DHA) were correlated with high microbial diversity. DHA was positively associated with operational taxonomic units from the Lachnospiraceae family.
	Vegetarian diet	Losasso et al. (2018)	101	N/A	Italy	16S rRNA	N/A
	Vegetarian diet	Losasso et al. (2018)	Vegetarians had a significantly greater microbial richness and a higher abundance of Bacteroidetes related operational taxonomic units compared to omnivorous.
	Dietary patterns identified using unsupervised hierarchical clustering and food groups	Bolte et al. (2021)	1,425	N/A	Netherlands	Metagenomics	Inflammation
		Bolte et al. (2021)	Diet-gut microbiome associations are consistent across patients with intestinal disease and the general population. Higher intake of animal foods, processed foods, alcohol, and sugar, is associated with higher levels of intestinal inflammatory markers. The opposite was found for plant foods and fish.
	Habitual diet (foods, food groups, nutrients, and dietary patterns)	Asnicar et al. (2021)	1,098	N/A	UK and USA	Metagenomics	Cardiometabolic blood markers
		Asnicar et al. (2021)	Habitual diet is linked to overall and feature-level composition of the gut microbiome. The panel of microbial species associated with healthy habitual diet overlapped with those associated with favorable cardiometabolic and postprandial markers.
	Habitual diet (foods, food groups, nutrients, and dietary patterns)	Breuninger et al. (2021)	1,992	N/A	German	16S rRNA	Metabolic diseases or risk factors
		Breuninger et al. (2021)	A panel of microbial species, including Faecalibacterium, Lachnospiracea incertae sedis, Gemmiger, and Roseburia, was associated with higher Alternate Healthy Eating Index and MedDiet Score and a higher intake of food items such as fruits, vegetables, legumes, and whole grains, and a lower prevalence of T2D.
	Ultra-processed food	Cuevas-Sierra A et al. (2021)	359	N/A	Spain	16S rRNA	N/A
	Ultra-processed food	Cuevas-Sierra A et al. (2021)	A consumption higher than five servings per day of ultra-processed food may affect gut microbiota composition differently in women and men
	Habitual diet (food groups)	Wang et al. (2022a)	2,772	N/A	China	16S rRNA	T2D
	Habitual diet (food groups)	Wang et al. (2022a)	Microbial genera that were favorable for the glycemic trait were consistently associated with healthy dietary habits (higher consumption of vegetable, fruit, fish, and nuts).
	Dietary diversity	Huang et al. (2022)	128	N/A	China	16S rRNA	Cardiometabolic disease biomarkers
	Dietary diversity	Huang et al. (2022)	Dietary variety was correlated with higher gut microbial diversity. The combination of Alistipes, Roseburia, and Barnesiella could moderately predict dietary variety level.
Prospective study	N-6 PUFAs	Miao et al. (2020)	1,591	A median follow-up of 6.2 years	China	16S rRNA	T2D
	N-6 PUFAs	Miao et al. (2020)	Gut microbial diversity acted as a potential mediator in the association between γ-linolenic acid and T2D risk. Seven genera were enriched in quartile 1 of gamma-linolenic acid and in participants without T2D.
	Fruit and vegetable	Jiang et al. (2020)	8,505	A median follow-up of 6.2 years	China	16S rRNA	T2D
	Fruit and vegetable	Jiang et al. (2020)	Fruit intake, but not vegetable, was associated with gut microbiota diversity and composition. The fruit-microbiota index (created from 31 fruit-related microbial features) was positively associated with fruit intake and inversely associated with T2D risk.
	Habitual diet (food groups)	Gou et al. (2021)	1,832	A median follow-up of 6.2 years	China	16S rRNA	T2D
	Habitual diet (food groups)	Gou et al. (2021)	Tea drinking was inversely associated with a microbiome risk score calculated based on 14 microbial features associated with T2D.
	Dairy	Shuai et al. (2021)	1,780	A median follow-up of 6.2 years	China	16S rRNA	Cardiometabolic health biomarkers
	Dairy	Shuai et al. (2021)	Dairy consumption is associated with the gut microbial composition and a higher alpha-diversity, which were inversely associated with blood triglycerides, while positively associated with high-density lipoprotein cholesterol.
	Healthy diet score and food groups	Yu et al. (2021)	1,920	5.2–20.5 years of follow-up	China	16S rRNA	N/A
	Healthy diet score and food groups	Yu et al. (2021)	Among healthy Chinese adults, long-term diet quality is positively associated with fecal microbiome diversity and abundance of fiber-fermenting bacteria.
	MedDiet and food groups	Wang et al. (2021)	307	2 pairs of fecal samples collected 6 months apart	USA	Metagenomics	Cardiometabolic disease risk
	MedDiet and food groups	Wang et al. (2021)	A healthy Mediterranean-style dietary pattern is associated with specific functional and taxonomic components of the gut microbiome, and that its protective associations with cardiometabolic health vary depending on microbial composition (e.g., the relative abundance of Prevotella copri).
	Dietary diversity	Xiao et al. (2022)	3,236	Over 3 years of follow-up	China	16S rRNA	Glycemic and inflammatory phenotypes
	Dietary diversity	Xiao et al. (2022)	High dietary diversity is associated with the gut microbial diversity and composition. Both the dietary diversity and diversity-related microbial features were correlated with host circulating secondary bile acids.
	Plant-based dietary pattern and food groups	Miao et al. (2022)	3,096	3 years	China	16S rRNA	Cardiometabolic biomarkers
	Plant-based dietary pattern and food groups	Miao et al. (2022)	Long-term and short-term plant-based dietary pattern were differently associated with gut microbial diversity and composition. Microbes related to long-term plant-based dietary pattern showed association with future cardiometabolic biomarkers.
Intervention study	Red wine	Queipo-Ortuño et al. (2012)	10 healthy volunteers	4 weeks	Spain	PCR	Cardiometabolic blood markers
		Queipo-Ortuño et al. (2012)	The daily consumption of red wine polyphenol for 4 weeks significantly increased the abundance of Bifidobacterium. Changes in cholesterol and C-reactive protein concentrations were linked to changes in the bifidobacteria number.
		Moreno-Indias et al. (2016)	10 obese individuals	30 days	Spain	PCR	Metabolic syndrome markers
		Moreno-Indias et al. (2016)	In the metabolic syndrome patients, red wine polyphenols significantly increased the number of butyrate-producing bacteria. The changes in gut microbiota in these patients contributed to the improvement in the metabolic syndrome markers.
	Whole grains	Vanegas et al. (2017)	81 healthy adults	6 weeks	USA	16S rRNA	Inflammatory makers
	Whole grains	Vanegas et al. (2017)	Substituting whole grains for refined grains for 6 weeks increased Lachnospira and decreased proinflammatory Enterobacteriaceae, and had modest positive effects on acute innate immune response.
	Omega-3 fatty acids	Watson et al. (2017)	22 healthy volunteers	8 weeks	UK	16S rRNA	N/A
	Omega-3 fatty acids	Watson et al. (2017)	There were no significant changes in alpha- or beta-diversity, or phyla composition, associated with omega-3 fatty acid supplementation. However, a reversible increased abundance of several genera, including Bifidobacterium, Roseburia, and Lactobacillus was observed with omega-3 fatty acid intervention.
	Dietary fat	Wan et al. (2019)	217 young adults	6 months	China	16S rRNA	Blood lipids and Inflammatory factors
	Dietary fat	Wan et al. (2019)	The low-fat diet was associated with increased microbial alpha-diversity and abundance of Blautia and Faecalibacterium. Change in relative abundance of Blautia was negatively associated with the changes in serum total cholesterol, low-density lipoprotein cholesterol, and non-high-density lipoprotein cholesterol.
	MedDiet	Ghosh et al. (2020)	612 non-frail or pre-frail participants	6 months	Italy, UK, Netherlands, Poland, and France	16S rRNA	Frailty
		Ghosh et al. (2020)	Adherence to the MedDiet led to increased abundance of specific taxa that were positively associated with several markers of lower frailty and improved cognitive function.
		Rinott et al. (2022)	286 participants with abdominal obesity/dyslipidemia were	1 year	Israel	16S rRNA and metagenomics	Cardiometabolic disease biomarkers
		Rinott et al. (2022)	The level of adherence to the Green-MedDiet was associated with the changes in microbiome composition, and changes in gut microbial features mediated the association between adherence to the Green-MedDiet and body weight and cardiometabolic risk reduction.
	Non-nutritive sweeteners	Suez et al. (2022)	120 healthy participants	14 days	Israel	Metagenomics	Glucose tolerance
	Non-nutritive sweeteners	Suez et al. (2022)	Administered saccharin, sucralose, aspartame, and stevia sachets for 2 weeks in doses lower than the acceptable daily intake distinctly altered stool and oral microbiome, whereas saccharin and sucralose significantly impaired glycemic responses.

^*Except for a few pioneer and intervention studies, most of the studies listed in the table were published within past 5 years, and with sample size larger than 1,000.