. 2020 Sep 10;21(Suppl 1):25–35. doi: 10.1007/s40257-020-00546-8

Table 1.

Recent comparative studies using 16S rRNA gene sequencing to analyze microbiota in rosacea

Title (author, year of publication)	Number of subjects/study comparison	Race	Age (years) mean ± SD (range)	16S rRNA gene sequencing and analysis	Outcome
Skin microbiota
Characterization of the facial microbiome in twins discordant for rosacea (Zaidi et al. 2018) [18]	60 subjects (42 healthy subjects, 18 patients with rosacea) Rosacea vs control	White (82.5%) Black (6.3%) Other (11.2%)	Rosacea: 31.3 ± 10.2 Healthy: 36.4 ± 17.3	V3–V4 region of the 16S rRNA gene Greengenes database	Top four most abundant phyla: Firmicutes (43%), Proteobacteria (39%), Actinobacteria (16%), and Bacteroidetes (1%) No significant difference in mean abundance for all phyla between left vs right cheek nor between healthy subjects and rosacea patients Comparable alpha diversity between monozygotic twin pairs with and without rosacea Two genera (Gordonia and Geobacillus) and an age of 30–60 years (vs 0–30 years) were significantly predictive of NRS score
Characterization and analysis of the skin microbiota in rosacea: a case–control study (Rainer et al. 2019) [19]	19 subjects with rosacea (ETR, PPR, or both); 19 rosacea-free controls Rosacea vs control	All Caucasian	Rosacea: age-matched to control Control: (23–65)	V3–V4 hypervariable region of the 16S rRNA gene Greengenes database	Weak negative correlation between the relative abundance of Cutibacterium acnes and NRS scores (R²=0.0378, P = 0.124). Significantly enriched and depleted species in ETR: (enriched) none; (depleted) Actinomyces europaeus, Prevotella tannerae, Prevotella intermedia, Campylobacter ureolyticus, Corynebacterium kroppenstedtii Significantly enriched and depleted species in PPR: (enriched) Porphyromonas endodontalis, Ruminococcus gnavus, Azorhizobium doebereinerae, Shewanella algae, Providencia stuartii, Roseomonas mucosa; (depleted) Dysgonomonas gadei, Azorhizobium doebereinerae, Shewanella algae, Providencia stuartii, Cutibacterium granulosum, Anoxybacillus kestanbolensis
Characterization and analysis of the skin microbiota in rosacea: impact of systemic antibiotics (Woo et al. 2020) [22]	12 subjects with rosacea Rosacea before vs after 6 weeks of oral doxycycline	Asian (Korean)	49.2 ± 18.6 (20–79) Median: 51	V3–V4 hypervariable region of the 16S rRNA gene NCBI taxonomy	3.43-fold increase in Weissella confusa relative abundance after oral doxycycline treatment (P = 0.008) Higher relative abundance of Cutibacterium acnes in patients aged 60 and under vs those aged over 60 (P = 0.018) Lower mean relative abundance of Cutibacterium acnes (P = 0.081) and higher relative abundance of Snodgrassella alvi (P = 0.087) in IGA4 vs IGA3 skin Comparable alpha diversity between the before-treatment and the after-treatment groups
Gut microbiota
Rosacea and its association with enteral microbiota in Korean females (Nam et al. 2018) [37]	12 rosacea patients; 251 control subjects Rosacea vs control	Asian (Korean)	Rosacea: 42.6 Control: 43.0	V3–V4 region of the 16S rRNA gene Greengenes database	Reduced abundance of Peptococcaceae family and Methanobrevibacter genus, but increased abundance of Acidaminococcus and Megasphaera genera in patients with rosacea vs control subjects, with significance retained after adjustment
An altered fecal microbial profiling in rosacea patients compared to matched controls (Chen et al. 2020) [38]	11 rosacea patients; 110 control subjects Rosacea vs control	Asian (Taiwanese)	Rosacea: 49.9 ± 11.3 Control: 50.6 ± 10.2	V3–V4 hypervariable region of the 16S rRNA gene Greengenes database	Significant reduction of fecal microbial richness in rosacea patients Enriched Rhabdochlamydia, CF231, Bifidobacterium, Sarcina, and Ruminococcus genera in rosacea patients. Reduced abundance of Lactobacillus, Megasphaerae, Acidaminococcus, Hemophilus, Roseburia, and Clostridium genera in rosacea patients

Title (author, year of publication)

Number of subjects/study comparison

Race

Age (years) mean ± SD (range)

16S rRNA gene sequencing and analysis

Outcome

Skin microbiota

Characterization of the facial microbiome in twins discordant for rosacea (Zaidi et al. 2018) [18]

60 subjects (42 healthy subjects, 18 patients with rosacea)

Rosacea vs control

White (82.5%)

Black (6.3%)

Other (11.2%)

Rosacea: 31.3 ± 10.2

Healthy: 36.4 ± 17.3

V3–V4 region of the 16S rRNA gene

Greengenes database

Top four most abundant phyla: Firmicutes (43%), Proteobacteria (39%), Actinobacteria (16%), and Bacteroidetes (1%)

No significant difference in mean abundance for all phyla between left vs right cheek nor between healthy subjects and rosacea patients

Comparable alpha diversity between monozygotic twin pairs with and without rosacea

Two genera (Gordonia and Geobacillus) and an age of 30–60 years (vs 0–30 years) were significantly predictive of NRS score

Characterization and analysis of the skin microbiota in rosacea: a case–control study (Rainer et al. 2019) [19]

19 subjects with rosacea (ETR, PPR, or both); 19 rosacea-free controls

Rosacea vs control

All Caucasian

Rosacea: age-matched to control

Control: (23–65)

V3–V4 hypervariable region of the 16S rRNA gene

Greengenes database

Weak negative correlation between the relative abundance of Cutibacterium acnes and NRS scores (R²=0.0378, P = 0.124).

Significantly enriched and depleted species in ETR: (enriched) none; (depleted) Actinomyces europaeus, Prevotella tannerae, Prevotella intermedia, Campylobacter ureolyticus, Corynebacterium kroppenstedtii

Significantly enriched and depleted species in PPR: (enriched) Porphyromonas endodontalis, Ruminococcus gnavus, Azorhizobium doebereinerae, Shewanella algae, Providencia stuartii, Roseomonas mucosa; (depleted) Dysgonomonas gadei, Azorhizobium doebereinerae, Shewanella algae, Providencia stuartii, Cutibacterium granulosum, Anoxybacillus kestanbolensis

Characterization and analysis of the skin microbiota in rosacea: impact of systemic antibiotics (Woo et al. 2020) [22]

12 subjects with rosacea

Rosacea before vs after 6 weeks of oral doxycycline

Asian (Korean)

49.2 ± 18.6

(20–79)

Median: 51

V3–V4 hypervariable region of the 16S rRNA gene

NCBI taxonomy

3.43-fold increase in Weissella confusa relative abundance after oral doxycycline treatment (P = 0.008)

Higher relative abundance of Cutibacterium acnes in patients aged 60 and under vs those aged over 60 (P = 0.018)

Lower mean relative abundance of Cutibacterium acnes (P = 0.081) and higher relative abundance of Snodgrassella alvi (P = 0.087) in IGA4 vs IGA3 skin

Comparable alpha diversity between the before-treatment and the after-treatment groups

Gut microbiota

Rosacea and its association with enteral microbiota in Korean females (Nam et al. 2018) [37]

12 rosacea patients; 251 control subjects

Rosacea vs control

Asian (Korean)

Rosacea: 42.6

Control: 43.0

V3–V4 region of the 16S rRNA gene

Greengenes database

Reduced abundance of Peptococcaceae family and Methanobrevibacter genus, but increased abundance of Acidaminococcus and Megasphaera genera in patients with rosacea vs control subjects, with significance retained after adjustment

An altered fecal microbial profiling in rosacea patients compared to matched controls (Chen et al. 2020) [38]

11 rosacea patients; 110 control subjects

Rosacea vs control

Asian (Taiwanese)

Rosacea: 49.9 ± 11.3

Control: 50.6 ± 10.2

V3–V4 hypervariable region of the 16S rRNA gene

Greengenes database

Significant reduction of fecal microbial richness in rosacea patients

Enriched Rhabdochlamydia, CF231, Bifidobacterium, Sarcina, and Ruminococcus genera in rosacea patients.

Reduced abundance of Lactobacillus, Megasphaerae, Acidaminococcus, Hemophilus, Roseburia, and Clostridium genera in rosacea patients

16S rRNA bacteria-specific small subunit ribosomal RNA, ETR erythematotelangiectatic rosacea, IGA Investigator’s Global Assessment, NCBI National Center for Biotechnology Information, NRS National Rosacea Society, PPR papulopustular rosacea, SD standard deviation