{'fraction_non_alphanumeric': 0.03157796101949026, 'fraction_numerical': 0.01686656671664168, 'mean_word_length': 5.379557680812911, 'pattern_counts': {'":': 0, '<': 1, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Alterations of the Human Gut Microbiome in Patients With Hidradenitis Suppurativa: A Case-control Study and Review of the Literature

Introduction Hidradenitis suppurativa (HS) is a chronic and systemic inflammatory disease that extends beyond the skin. The role of gut microbiome (GM) alterations in the pathogenesis of inflammatory and autoimmune disorders is remarkable. Objectives Based on the hypothesis that dysbiosis in the GM may trigger systemic inflammation in the pathogenesis of HS, this study aimed to investigate whether the GM is altered in HS patients compared with healthy subjects. Methods In the present case-control study, fecal samples from 15 patients with HS and 15 age- and sex-matched healthy individuals were collected and analyzed using 16S rRNA-based metagenomic analysis, New Generation Sequencing (NGS). The V3 and V4-hypervariable regions of the bacterial 16S rDNA gene were amplified from all samples and sequenced by the Illumina MiSeq platform. Bioinformatics analyses were performed in QIIME2. Results Shannon alpha diversity index showed significantly reduced diversity in HS patients (P = 0.048). Bray-Curtis Dissimilarity and Jaccard Distance revealed that the gut microbial composition of HS patients was significantly distinctive from that of controls (P = 0.01 and P = 0.007, respectively). The relative abundance of unclassified Clostridiales, unclassified Firmicutes, and Fusicatenibacter in HS was significantly lower than that in controls (P = 0.005, P = 0.029, and P = 0.046, respectively). Conclusions This study indicated that significant alterations in the GM of HS patients could play a critical role in the pathogenesis of HS and might be a trigger for systemic inflammation. Increased understanding of the pathogenesis of HS will shed light on the new potential therapeutic targets and novel treatment options.


Introduction
Hidradenitis suppurativa (HS) significantly impacts patients quality of life with its chronic and relapsing course and suboptimal response to therapy [1]. The etiopathogenesis of the disease has not been elucidated yet. However, it is clear that HS is not simply an inflammatory skin disorder, but a systemic inflammatory disorder [2]. Its associations with inflammatory and autoinflammatory disorders, increased levels of inflammatory cytokines in sera of patients, and γ-secretase complex mutations leading to impaired notch signaling pathway may suggest a systemic inflammation that distant skin sites might trigger [3].
Recently, a term called "gut-skin axis" has been introduced and highlighted a potential link between the gut microbiome and the skin through complex immune mechanisms [4]. The gut microbiome refers to the whole genome of the residential microbial community in the human intestine.
An altered gut microbiome is involved in the development of multiple immune-mediated and inflammatory disorders, especially of inflammatory bowel diseases (IBD), by disrupting the balance between pro-inflammatory and anti-inflammatory/regulatory immune cells [5,6]. Many studies have revealed dysbiosis, alterations in the gut microbiome, in inflammatory and autoimmune skin disorders such as acne, rosacea, atopic dermatitis, and psoriasis [7][8][9][10]. However, studies exploring the gut microbiome alterations in patients with HS are scarce in the literature [11][12][13][14].

Objectives
In the present study, we hypothesize that the gut microbiome of patients with HS is different from that of healthy people. Therefore, in this study, we aimed (1) to evaluate the gut microbiome of patients with HS, (2) to compare it with healthy subjects, and (3) to evaluate the relationship between fecal microbiome and obesity, smoking status, and treatment condition of HS patients.

Study Population
The study was conducted over the period from August 2018

Fecal Sample Collection
Fecal samples from all participants were collected in sterile containers. Then, all samples were transferred to a freezer within 60 minutes of collection and stored at −80°C until analyzed with New Generation Sequencing (NGS).

DNA Extraction
Total DNA extraction from 30 fecal samples was performed using The Biospeedy ® DNA Isolation Kit (Bioeksen R&D Technologies) according to the manufacturer instructions. to the next steps was tested. Next molecular processes were performed with DNA with OD260 / OD280 ratio of 1.8-2.0 and OD260 / OD230 ratio of 2.0-2 and at least 10 ng/ul (preferably 50-300 ng / µL) concentrations.

16S rRNA Amplification
The amplification of the V3 and V4-conserved regions of bacterial 16S rRNA were performed by polymerase chain reaction (PCR) using Illumina adapter overhang nucleotide 16S rRNA-specific sequences,

Bioinformatics and Statistical Analyses
The raw sequence data were processed using QIIME2 v2019.1 software. First, the barcode and the primers were trimmed, and unique sequences were identified. Pre-clustering prevented redundancy. UCHIME was used for the removal of chimeras. Next, the sequences were classified using a classifier within QIIME2. The references and taxonomy files were obtained from the QIIME2 database. After picking operational taxonomic units (OTU) at 97% sequence similarity and taxonomic assignments using the QIIME2 and SILVA rDNA database, the OTUs were binned into phylotypes.
Alpha diversity and beta diversity were calculated with QIIME2 v2019.1 software. The alpha diversity is defined as the diversity within a community and was calculated using One-sample t-test, Mann-Whitney U test, PERMANOVA, and Kruskal-Wallis test were used for statistical significance analysis. Statistical significance was set at P < 0.05.

The Characteristics of Participants
We enrolled 15 patients with HS and 15 age-and sex-matched healthy controls in this study. All subjects were Turkish in origin and coming from exact geographical locations. The characteristics of study groups are shown in Table 1.

Community Richness and Diversity
The alpha-diversity of the gut microbiome was significantly lower in HS patients than healthy individuals (Shannon index, P = 0.048). The Simpson, ACE, Chao, and Faith phylodiversity indices of HS patients were lower than those of controls; however, the differences were not statistically sig-

Overall Taxonomic Analysis of HS Patients and Controls, Distribution at the Phylum Level
The gut microbiome of both HS patients and healthy controls was

Overall Taxonomic Analysis of HS Patients and Controls, Distribution at the Genus Level
Lachnospiraceae_unclassified, Ruminococcaceae_unclassified, Clostridiales_unclassified, Roseburia, Gemmiger,  genus level showed no significant taxa alterations among non-obese and obese, non-smokers and smokers, and treatment naïve and under treatment groups.

Conclusions
Based on our hypothesis that the gut microbiome of patients  Figure 4).   These studies have found an association between smoking status and gut microbiome composition, which is that the composition of the gut microbiome of smokers is different from that of non-smokers [33][34][35]. In our study, there were no significant differences neither in diversity nor taxa distribution between the gut microbiome of obese and healthy subjects or the gut microbiome of smokers and non-smokers.

Analysis of Fecal Microbiome When Stratified by BMI, Smoking Status, and Treatment of HS Patients
Several limitations of this study should be noted. First, we could not perform a power analysis, and the sample size was small in study subgroups. Larger sample size should be concluded with more significant results in future studies.
Second, although we excluded participants using antibiotics, probiotics, prebiotics, and on a specific diet, not following genus Faecalibacterium was not different between HS and healthy subjects in our study.
The gut microbiome plays a critical role in human health through the development of immune responses mediated by metabolic products and inflammatory signaling pathways [18]. It has been shown that commensal bacteria produce immunomodulatory metabolites, particularly short-chain fatty acids (SCFAs) like butyrate, propionate, and acetate.
These metabolites have anti-inflammatory actions mediated by G-protein coupled receptors and contribute to the epithelial barrier integrity [19]. Short-chain fatty acids producing bacteria induce peripheral T-regulatory cells (Tregs), eliminate the Th17/Th1 response and provide a balance between pro-inflammatory and anti-inflammatory immune cells [6,[20][21][22][23]. Some bacterial taxa are well-characterized with their anti-inflammatory properties. For example, Firmicutes phylum is known for its anti-inflammatory actions via producing SCFAs [18]. Three genera, unclassified Clostridiales, Fusicatenibacter, and unclassified Firmicutes that were shown to be decreased in our study, belong to Firmicutes phylum. Faecalibacterium prausnitzii and Roseburia species are other well-known anti-inflammatory bacteria and play a critical role in IBD [24,25]. The relative abundance of Faecalibacterium and Roseburia was not different between the gut microbiome of patients with HS and healthy controls.
However, decreased abundance of Fusicatenibacter was remarkable in HS patients. Fusicatenibacter saccharivorans is a recently isolated and cultured bacterium and a strain of Clostridium subcluster XIVa that induces Tregs and produces butyrate and other SCFAs [26,27]. A recent study has reported that F .saccharivorans decreased in patients with active ulcerative colitis (UC), and there is a negative correlation between the abundance of Fusicatenibacter saccharivorans and UC activity [28]. Therefore, a lower abundance of unclassified Clostridiales, Fusicatenibacter, and unclassified Firmicutes in the gut microbiome of patients with HS may be a triggering factor for systemic inflammation through decreased SCFA production and dysregulation of inflammatory mechanisms, which lead to a shift toward a pro-inflammatory state.
Seven of 15 HS patients included in our study were obese, and 13 out of 15 patients with HS were current smokers.
Obesity is a common comorbidity in patients with HS and is considered a risk factor in the development of HS along with smoking and aberrant regulation of innate immunity [15,29].
Gut microbiome alterations may underlie a common pathophysiological process for HS, obesity, smoking, and aberrant immune response by producing various microbial metabolites and consequent inflammation. Recently, several studies in humans and animal models have shown the gut microbiome impact on obesity, and dysbiosis of the gut microbiota is closely associated with obesity [30][31][32]. A few studies in the