SYSTEMATIC REVIEW AND META
–ANALYSIS
A systematic literature review of the human
skin microbiome as biomarker for
dermatological drug development
CorrespondenceRobert Rissmann, PhD, Centre for Human Drug Research, Zernikedreef 8, 2333CL Leiden, the Netherlands; Tel. +31 (0)71 5246400, Fax. +31 (0)715246499; E-mail: rrissmann@chdr.nl
Received24 January 2018;Revised9 May 2018;Accepted11 May 2018
T. Niemeyer - van der Kolk
1,2, H. E. C. van der Wall
1, C. Balmforth
1, M. B. A. Van Doorn
1,2and
R. Rissmann
1,3,41Centre for Human Drug Research, Leiden, the Netherlands,2Department of Dermatology Erasmus MC, University Medical Center Rotterdam, the Netherlands,3Leiden University Medical Center, Leiden, the Netherlands, and4Leiden Academic Center for Drug Research, Leiden, the Netherlands Keywordsbiomarkers, clinical drug development, microbiota, surrogate parameter
AIMS
To explore the potential of the skin microbiome as biomarker in six dermatological conditions: atopic dermatitis (AD), acne vulgaris (AV), psoriasis vulgaris (PV), hidradenitis suppurativa (HS), seborrhoeic dermatitis/pityriasis capitis (SD/PC) and ulcus cruris (UC).
METHODS
A systematic literature review was conducted according to the PRISMA guidelines. Two investigators independently reviewed the included studies and ranked the suitability microbiome implementation for early phase clinical studies in an adapted GRADE method.
RESULTS
In total, 841 papers were identified and after screening of titles and abstracts for eligibility we identified 42 manuscripts that could be included in the review. Eleven studies were included for AD,five for AV, 10 for PV, two for HS, four for SD and 10 for UC. For AD and AV, multiple studies report the relationship between the skin microbiome, disease severity and clinical response to treatment. This is currently lacking for the remaining conditions.
CONCLUSION
For two indications– AD and AV – there is preliminary evidence to support implementation of the skin microbiome as biomarkers in early phase clinical trials. For PV, UC, SD and HS there is insufficient evidence from the literature. More microbiome-directed prospective studies studying the effect of current treatments on the microbiome with special attention for patient meta-data, sampling methods and analysis methods are needed to draw more substantial conclusions.
© 2018 The Authors. British Journal of Clinical Pharmacology
published by John Wiley & Sons Ltd on behalf of British Pharmacological Society
Introduction
The escalating number of therapeutic candidates in drug de-velopment programs require strategies that optimize the pro-cess of clinical development. A common approach is the use of biomarkers in clinical trials. A biomarker is defined as a characteristic that can be objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmacological responses to a therapeutic in-tervention [1, 2]. Clinical biomarkers are thought to reflect disease activity and pathophysiology [3, 4]. A useful bio-marker in any class has to comply with the following general criteria: (i) there must be a consistent response of the bio-marker across studies (preferably from different research groups) and drugs from the same mechanistic class; (ii) the
biomarker must respond clearly to therapeutic (not
supratherapeutic) doses; (iii) there must be a clear dose- or concentration-response relationship; and (iv) there must a plausible relationship between the biomarker, pharmacology of the drug class and disease pathophysiology [4]. Validated biomarkers are often being used to guide drug development programmes from human pharmacology studies, i.e. phase 1 trials, to confirmatory trials, i.e. phase 3 studies [2]. For der-matological diseases the drug developers often rely on clinical efficacy scores, e.g. the Eczema Area and Severity Index (EASI) for atopic dermatitis (AD), Psoriasis Area and Severity Index for psoriasis vulgaris (PV) and inflammatory lesion count for acne vulgaris (AV) or investigator global assessments. How-ever, more objective outcome measures including validated
biomarkers would have great added value in thisfield. One
of these potential new biomarkers is the human skin microbiome, which has the potential to monitor disease ac-tivity and drug specific (mechanistic) effects.
The human microbiome refers to the combined genomic information of all microbial communities living on or in the human body. Collectively, this encompasses fungi (mycobiota), bacteria (microbiota), viruses, bacteriophage, archaea and protozoa. This, along with the human genome, completes what is now termed the human microbial superor-ganism [5]. The skin microbiome harbours vast microbial communities living in a range of both physiologically and to-pographically distinct niches and microenvironments [6, 7]. Actinobacteria (52%), Firmicutes (24%), Proteobacteria (17%) and Bacteroidetes (7%) are the four most abundant species identified on the skin [8]. Previous studies have shown that it is not only skin topography that influences mi-crobial colonization, but also a vast range of host-specific fac-tors including age and sex, and environmental facfac-tors such as occupation, clothing choice, antibiotic use, cosmetics, soaps, environmental temperature, humidity, and longitudinal and/or latitudinal variation in UV exposure, which can all
contribute to the variability seen in the microbial flora of
the skin [9–15]. Moreover, changes or aberrations in the skin microbiome have been implicated in the pathophysiology of numerous skin diseases such as AD and AV [16].
Several reviews have described the role and impact of skin microbiome on disease [17–22]. However, to date, no struc-tured review has been conducted to evaluate the feasibility, suitability and potential use of the skin microbiome as bio-marker for early phase clinical drug development. Therefore, we conducted a systemic literature review with predefined
search terms according to the PRISMA guidelines, with focus on six relevant disorders, i.e. AD, seborrhoeic dermatitis and
pityriasis capitis (dandruff; SD/PC), AV, hidradenitis
suppurativa (HS), PV and ulcus cruris/chronic wounds (UC). In addition, we evaluated and ranked the conditions regard-ing the potential as clinical biomarker. Lastly, we provided recommendations for prospective microbiome investigations in clinical drug development programmes.
Methods
We followed the Preferred Reporting Items for Systematic Re-views and Meta-analysis (PRISMA) [23]. In collaboration with a trained librarian from the Leiden University Medical Cen-tre, a structured electronic literature search was composed, using a combination of two main search criteria: microbiome and the targeted skin condition (i.e. AD, SD/PC, HS, AV, UC and PV). For each search term, all relevant keyword variations were used in conjunction with free text word variations. The search strategy was optimized for all consulted databases, tak-ing into account the differences of the various controlled vocabularies, as well as the differences of database-specific
technical variations (e.g. the use of quotation marks). The
fi-nal search was performed on 29 September 2017, using bib-liographic databases including PubMed (incl. MEDLINE), Embase (OVID-version), Web of Science, Cochrane Library, CENTRAL, Academic Search Premier and ScienceDirect. Animal-only studies, reviews without original data, non-English studies and case studies were excluded. Moreover, culture-based methods were excluded since the objective of this review was to explore the full microbiome profile and rel-ative abundances compared to other genus as biomarker. The remaining studies were fully reviewed. The overall quality of evidence was rated using pre-defined criteria (group size, type of control, method of sampling, serial sampling available, well defined metadata, analysis method). Grading of
Recom-mendations Assessment, Development and Evaluation (GRADE)
guidelines were used as guidance for rating the quality of ev-idence [24]. This was done by two investigators
indepen-dently and thefinal outcome was determined by discussion
once discrepancies occurred.
Results
The search resulted in 841 titles. After duplicates were re-moved, 443 papers were screened for inclusion. Four-hundred-and-one manuscripts were excluded based on the exclusion criteria with mostly culture-based studies that were not eligible. The remaining 42 studies were identified as using nonculture-based methods to analyse microbiome popula-tions in one of the targeted skin condipopula-tions and fully reviewed, Figure 1. All 42 were included in the review, the study characteristics can be found in Table 1.
Psoriasis vulgaris
In 10 studies, the cutaneous microbiome in PV patients was investigated, Table 1 [25–34]. In addition to microbiota, these studies have focused on the mycobiota. An increased
diversity in the fungal flora in psoriatic skin lesions, com-pared to healthy skin was reported by Paulino et al. [25] and Amaya et al. [26]. No differences in the abundance of specific species was observed. Controversially, a significant dichot-omy between the relative abundances of specific Malassezia species between healthy skin, and psoriatic skin lesions was
found by Takemoto et al. [32]. Similar inconsistencies in
find-ings were also observed in those studies assessing the micro-biota [28–31, 34].
Hidradenitis suppurativa
To date, only two studies have been published that investi-gated the skin microbiome in HS (Table 1) [35, 36]. Both
stud-ies report a significant dysbiosis in HS lesional skin with more
abundance of anaerobic genera. Five lesional microbiome
types were identified of which type 1 (Corynebacterium
spe-cies) and type IV (Porphyromonas and Peptoniphilus spespe-cies) were most prevalent [35]. Porphyromonas was also found as predominantly abundant on lesional skin by Guet-Revillet
et al. [36], together with Prevotella species. In addition, clinical
severity significantly correlated with Fusobacterium and
Parvimonas species variation in this study.
Ulcus cruris
The role of the skin microbiome in UC was explored in 10 dif-ferent studies, Table 1 [37–46]. Current research into UC microbiome, comprises larger, longitudinal studies, com-pared to those in PV and HS. The skin mycobiota of diabetic foot ulcers was longitudinally assessed and was observed to be highly heterogeneous over time and between subjects while the diversity increased upon antibiotic treatment [45]. There have been similar efforts to reveal correlations between
patient metadata, treatment and/or clinical outcomes and the cutaneous microbiome in studies investigating the micro-biota in UC [38, 42–44, 46]. Overall, the most common found genus in these studies was Staphylococcus, with Staphylococcus
aureus the most common species. Ulcer closing in diabetic
pa-tients was found to be positively correlated with higher mi-crobial diversity and relative abundance of Proteobacteria, while a relative abundance of Staphylococcus was correlated negatively in a study by Gardner et al. [42]. Although
Staphy-lococcus was consistently reported to be the most common
ge-nus, inconsistencies exist regarding other genus that are important in CU.
Seborrheic dermatitis/Pityriasis capitis
Four case–control studies investigated the microbiome in SD patients [47–50], Table 1. In general, Malassezia spp. were found to be more abundant on dandruff scalp compared to healthy scalp [47, 48, 50]. In addition to the mycobiota, a dysbiosis in Staphylococcus and Propionibacterium spp. was de-scribed in microbiota analysis [48, 50]. One of the four studies
did notfind a general association between Malassezia spp.
and SD but didfind a higher abundance of M. globate in severe
SD patients [49].
Acne vulgaris
Five studies investigated the skin microbiome in patients with AV, Table 1 [51–55]. Three (3) were case–control studies and two (2) were small single-centre, controlled studies, of whom one was a double-blind, randomized-controlled trial. In general, all case–control studies demonstrated similarly an increased microbial abundance of Propionibacterium acnes in the skin microbiome of patients with AV, compared to healthy [51–53]. In addition, an association between a spe-cific P. acnes strains and acne affected skin, and healthy skin respectively was demonstrated [51, 52]. Acne improved and
Propionibacterium abundance decreased after various
treat-ments, together with an increase of microbial diversity in the two controlled studies. Moreover, a positive correlation between Propionibacterium abundance and acne severity grade was found [54, 55].
Atopic dermatitis
The skin microbiome in patients with AD was assessed in 11 studies, Table 1 [56–66]. A greater proportion of longitu-dinal studies and 2 completed randomized controlled trials were performed in AD patients. There is general consensus across studies that skin affected by AD exhibits decreased bacterial diversity, as a result of an increased abundance of S. aureus [60–64, 66]. In particular, AD flare ups were as-sociated with an increased proportion of Staphyloccocus se-quences, and S. aureus abundance correlated with disease severity [60]. In line with these results, microbial diversity in AD lesions was inversely correlated with overall eczema severity as observed by the EASI [63], with several further studies also reporting taxonomic normalization and in-creased bacterial diversity in AD lesional skin, following various treatments [60, 61, 63, 66].
Figure 1
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Su mm ar y ta b le o f th e st u d ie s in cl ud e d in th e re vi e w So ur ce F ir st au th o r, y e a r [r e f] D is ea se St ud y d es ig n No . o f p at ie n ts Sa m p le co ll e c ti o n me th o d s A na ly si s K e y fi n d in g s W ea kn es se s Le ve l ev id e n c e Pa ul in o et al . 20 0 6 [1 8 ] PV Ca se co nt ro l 3P V /5H V St er ile sw a b s Le si o n a l an d n o n le si o n a l sk in M u lt ip le sa mp ling in on e P V a n d 2 H V 18S rR NA 5. 8 S rD N A ▪ Ma la ss ez ia my co b io ta su b sta nt ia lly d if fe re n t PV vs .H V ▪ Sm al l co h o rt Lo w A m ay a et al . 20 0 7 [1 9 ] PV Ca se co nt ro l 22 PV /3 6 A D /3 0 H V O p S ite ® tr a n spa re n t ad he si v e dr es si n g s Le si o n a l an d n o n le si o n a l sk in 5. 8 S rD NA ▪ Ma la ss ez ia sp e ci e s d e tec te d in ov er al l sit es hi gh er in PV an d A D co mp ar ed to HV ▪ Sm al l co h o rt ▪ P V p a ti en ts o n tr ea tm en t ▪ Li mi te d a n a ly si s ▪ Di ff er en t ski n si te co lle c ti on PV vs .A D a n d H V Lo w Pa ul in o et al . 20 0 8 [2 0 ] PV Ca se co nt ro l 1P V /1H V St er ile sw a b s Le si o n a l an d no nl es io na l ski n M u lt ip le ti me po in ts 5. 8 S rD NA ▪ M yc o bi o ta re la tiv el y sta bl e ov er ti me . ▪ No si g n ifi ca nt di c h o tom y be tw ee n P V a n d HV . ▪ Sm al l co h o rt ▪ Li mi te d a n a ly si s Lo w Ga o et al . 20 0 8 [2 1 ] PV Ca se co nt ro l 6P V /6H V St er ile sw a b s Le si o n a l an d n o n le si o n a l sk in 16S rR NA V1 -V 9 ▪ Fi rm u cu tes mo re ab un d a n t in le si o n a l sk in P V vs .n o n le si o n a l sk in a n d H V . ▪ A ct in o ba c te ri a le ss ab un da nt in le si on al sk in P V vs . no nl es io na l ski n a n d H V . ▪ Sm al l co h o rt ▪ N o se ri a l sa m p lin g Lo w Fa h le n et al . 20 1 1 [2 2 ] PV Ca se co nt ro l 10 PV /1 2 H V 2-m m sk in pu n ch bi op si es 16S rR NA V3 -V 4 ▪ M o st co mm on p h y la in PV an d H V : Fi rm ic ut is , Pr o te o ba ct er ia , A c ti n o b a ct e ri a . ▪ St ap hy lo c o c c i a n d Pr o p io ni ba c te ri a w e re le ss co mm on in ps o ri a ti c le sio ns ▪ Sm al l co h o rt ▪ N o se ri a l sa m p lin g ▪ Va ri at io n in sk in sam pl e sit es Lo w A le k se ye nk o et al .2 0 1 3 [2 3 ] PV Ca se co nt ro l & Pr o spe ct iv e lo n g it u d in a l co ho rt st ud y CC : 5 4 P V /3 7 HV PC : 1 7 P V /15 HV St er ile sw a b s Le si o n a l an d n o n le si o n a l sk in HV ma tc he d si tes M u lt ip le sa mp ling 16S rR NA V1 -V 3 ▪ M o st co mm on p h y la in P V an d H V : Fi rm ic ut is , P ro te o b a ct e ri a , A ct in o ba ct er ia . ▪ Co mb in e d re la ti v e ab un d a n ce of C o ry ne ba ct er iu m , St re pt o co cc u s an d St ap hy lo co cc u s wa s in cr e a se d in ps or ia ti c ski n, co mp ar ed to un af fe c te d sk in an d he al th y c on tr o l sk in ▪ So me p a ti e n ts on ac ti v e tr e a tm e n t ▪ Ma in ly se v e re pa ti e n ts Lo w to m o d e ra te St at n ik o v et al .2 0 1 3 [2 4 ] PV Ca se co nt ro l 54 PV /3 7 H V St er ile sw a b s Le si o n a l an d no nl es io na l ski n HV ma tc he d si tes 1 6 S rR N A V1 -V 3 an d V 3 -V5 ▪ M ic ro b io me si gn at ur es co ul d b e u se d to di ag no se ps o ri a si s ▪ No se ri a l sa m p lin g Lo w to m o d e ra te Ta k e m o to et al .2 0 1 5 [2 5 ] PV Ca se co nt ro l 12 PV /1 2 H V PV : p so ri at ic sc a les by tw ee ze r HV : O pS it e® tr an sp ar en t a d h e siv e dr es si ng s 26S rR NA D1 – D2 ▪ Ps o ri a ti c le sio ns ex hi bi te d si g n ifi c a n tl y g rea te r d iv er si ty co mp ar ed to HV ▪ Ma la ss ez ia re st ri ct a le v e ls w e re si g n ifi ca nt ly hi gh er in ps o ri a ti c le sio ns , c om p a re d to he al th y co n tr o ls ▪ Sm al l co h o rt ▪ N o se ri a l sa m p lin g ▪ On ly ma le p a ti e n ts ▪ Di ff er en t sam pl e me th o d P V an d H V Lo w (con ti n u esTa
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(C on ti nu ed ) So ur ce F ir st au th o r, y e a r [r e f] D is ea se St ud y d es ig n No . o f p at ie n ts Sa m p le co ll e c ti o n me th o d s A na ly si s K e y fi n d in g s W ea kn es se s Le ve l ev id e n c e Sa la va et al . 20 1 7 [2 6 ] PV Ca se co nt ro l 13 PV St er ile sw a b s Le si o n a l an d n on le si o n a l sk in 1 6 S rR N A V1 -V 3 ▪ No si g n ifi ca nt di ff e re n c e s mi cr o b ia l d iv er si ty be tw ee n le sio na l a n d no nl es io na l ski n ▪ Sm al l co h o rt ▪ N o se ri a l sa m p lin g ▪ Va ri at io n in sk in sa m p le si te s Lo w Te tt et al . 20 1 7 [2 7 ] PV Ca se co nt ro l 28 PV St er ile sw a b s Le si o n a l an d no nl es io na l ski n W M S seq u e n ci n g ▪ Pl aq ue s a t the ea r h a d a si g n ifi ca nt de c re a se in mi cr o b ia l d iv er si ty , a n d in cr ea se in St ap hy lo co cc us ab un d a n ce ▪ At sp e ci e s le ve l, n o di ff e re n c e s b e twe en le si o n a l an d n o n le si o n a l sk in w e re ob se rv e d ▪ Sm al l co h o rt ▪ N o se ri a l sa m p lin g ▪ So me p a ti e n ts on ac ti v e tr ea tm en t Lo w Ri n g et al . 20 1 7 [2 8 ] HS Ca se co nt ro l 30 HS 24 HV Bi o p si e s Le si o n a l an d no nl es io na l ski n 1 6 S rR N A V3 -V 4 1 8 S rD N A V3 -V 4 ▪ M ic ro b io me in H S si g n ifi c a n tly d if fe ren t fr o m HV in le si on al an d no nl es io na l ski n ▪ Fi v e mi cr o b io me ty pe s id en ti fied ▪ Le si o n a l sk in co ns is te d pr ed om in a n tl y o f Co ry n eb a ct er iu m sp e ci e s (t y pe I) an d P ep ton ip h ilu s sp e ci e s (t y pe IV ) ▪ Pr op io n ib a ct er iu m sh o w ed a si g n ifi c a n t hi gh er ab u n d a n ce in H V ▪ Sm al l co h o rt ▪ N o se ri a l sa m p lin g Lo w Gu e t-R e v il le t et al .2 0 1 7 [2 9 ] HS Pr o spe ct iv e co h o rt 65 HS St er ile sw a b s Le si o n a l an d no nl es io na l ski n 16S rR NA V1 -V 2 ▪ Le si o n a l sk in co ns is te d pr ed om in a n tl y o f a n a e ro b e s (Po rp hy ro mo na s an d Pr ev ot el la sp e c ie s) ▪ Cl in ic al se v e ri ty si g n ifi ca nt ly as so ci at ed wi th va ri at io ns in le si o n a l mi c ro b io ta ▪ Fu so ba ct er iu m a ss oc ia te d wi th se v e re H S ▪ Sm al l co h o rt Lo w Do w d et al . 20 0 8 [3 0 ] U C Pr o spe ct iv e co h o rt 10 VL U /1 0 D FU / 10 PU De b ri d em en t sa m p le s 1 6 S rR N A V4 ▪ M a jo r p op ul at io ns in cl ud e o f al l w ou nd in c lu d e: St ap hy lo co cc us , Ps eu d o m o n a s, Pe pt on ip h ilu s, En te ro b a ct er , S tr eno tr op ho mo na s, Fi ne go ld ia an d Se rr a ti a sp ec ie s ▪ E a c h wo un d typ e d if fe re n t pr ofi le , d e p en de nt o n ox yg en to le ra n ce o f the ba ct er ia l p o p u lat io n ▪ Sm al l stu d y ▪ N o se ri a l sa m p lin g Lo w Pr ic e et al . 20 0 9 [3 1 ] U C Pr o spe ct iv e co h o rt 7 D F U /7 NU /3 VL U/ 3 PS U /4 O TH Wo un d b as e cu re tt e M u lt ip le ti me po in ts 1 6 S rR N A V3 ▪ Fa st id io us an ae ro b ic ba ct er ia of th e C lo st ri di al es fa mi ly XI we re th e m o st pr ev al en t b a c te ri a in w ou nd s ▪ Sm al l stu d y ▪ Sa mp ling ti me po in t va ri a b le Lo w (con ti n u es )Ta
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(C on ti nu ed ) So ur ce F ir st au th o r, y e a r [r e f] D is ea se St ud y d es ig n No . o f p at ie n ts Sa m p le co ll e c ti o n me th o d s A na ly si s K e y fi n d in g s W ea kn es se s Le ve l ev id e n c e ▪ Wo un d m ic ro b io ta fro m an ti b io tic tr ea te d p at ie nt s w e re si g n ifi ca nt ly di ff e re n t fr o m un tr ea te d p a tie nt s ▪ In di ab et ic p a ti e n ts , St re p toc o cc u s wa s mo re ab un da nt ▪ Pa ti en ts o n w id e va ri e ty o f tr e a tm e n ts Pr ic e et al . 20 1 1 [3 2 ] UC C ross-se c ti o n a l 4 D F U /3 NU /3 VL U/ 2 OT H Wo un d b as e cu re tt e M u lt ip le sa mp le s tak en 16S rR NA V3 -V 4 ▪ Th e 1 0 m o st co m m o n ge ne ra in cl ud ed St ap hy lo co cc us , Ps eu d o m o n a s, St re p toc oc cu s, An ae ro co cc us , Ra ls to n ia , M o rg a n ella , Po rp h yr o m o n a s, Pe pt o n ip h ilu s, Ja nt hi no ba ct er iu m an d C o ry ne b a ct er iu m ▪ Sa mp le s fro m d if fe re n t si te s w it hi n in d iv id ua l w o u n d s sh a re d si mi la ri ti es in ba ct er ia l co m m u ni ty co mp o si ti o ns ▪ Sa mp le s tak en fr om di ff e re n t w o u n d s w er e le ss si mi la r tha n tho se ta ke n fr o m di ff e re n t sit es w it h in th e sam e w o u n d ▪ Sm al l co h o rt ▪ Pa ti en ts o n ac ti v e tr ea tm en t ▪ N o se ri a l sa m p lin g Lo w Rh oa d s et al . 20 1 2 [3 3 ] UC C ross-se c ti o n a l 4D F U /3 N U /3 VL U /2 O T H Wo un d b as e cu re tt e 1 6 S rR N A V1 -V 3 ▪ Th e te n mo st co mm on ge ne ra in cl ud ed St ap hy lo co cc us , Ps eu d o m o n a s, St re p toc oc cu s, An ae ro co cc us , Ra ls to n ia , M o rg a n ella , Po rp h yr o m o n a s, Pe pt o n ip h ilu s, Ja n th ino b a ct er iu m an d C o ry ne b a ct er iu m ▪ Sa mp le s fro m d if fe re n t si te s w it hi n in d iv id ua l w o u n d s sh a re d si mi la ri ti es in ba ct er ia l co m m u ni ty co mp o si ti o ns ▪ Sa mp le s tak en fr om d if fe ren t w o u n d s w e re le ss si mi la r th a n th o se ta ke n fr om di ff e ren t si te s w it hi n th e sa m e w o u n d ▪ Sm al l co h o rt ▪ Pa ti en ts o n ac ti v e tr ea tm en t ▪ N o se ri a l sa m p lin g Lo w Gj o d sb o l et al .2 0 1 2 [3 4 ] U C Co mp ar at iv e 46 VL U Fi lt e r pa p e r p a d & pu nc h b io ps ie s 16S rR NA V1 -V 3 ▪ St ap hy lo co cc u s au re u s mo st fo u n d sp e c ie s ▪ M u lt ip le sa m p ling o ve r ti me le ad to id en ti fica ti o n of ad di ti o n a l sp e c ie s ▪ N o d if fe ren ce in o u tc o m e s di ff e re n t sam pl e tec hn iq ue s ▪ No co nt ro ls Lo w (con ti n u esTa
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(C on ti nu ed ) So ur ce F ir st au th o r, y e a r [r e f] D is ea se St ud y d es ig n No . o f p at ie n ts Sa m p le co ll e c ti o n me th o d s A na ly si s K e y fi n d in g s W ea kn es se s Le ve l ev id e n c e Ga rdne r et al .2 0 1 3 [3 5 ] UC C ross-se c ti o n a l 52 DF U St er ile sw a b s 1 6 S rR N A V1 -V 3 ▪ Th e m o st a b u nd an t O TU wa s St ap hy lo co cc us , w it h S. au re u s th e m o st co m m o n spe c ie s ▪ U lc e r cl o si n g w a s p os it iv el y co rr el at ed wi th nu mb er o f sp e ci e s le ve l O T U s, h ig he r mi cr o b ia l d iv er si ty , re lat iv e ab un d a n ce o f P ro te o b ac te ri a, an d n e g a ti ve ly co rre la te d w it h re la ti ve ab un d a n ce o f St ap hy lo co cc us ▪ U lc e r d e p th w a s n e g at iv el y as so ci at ed wi th St ap hy lo co cc us ab un d a n ce a n d po si ti v e ly as so ci at ed wi th an ae ro b ic ba ct er ia re la ti v e ab un d a n ce ▪ N o se ri a l sa m p lin g ▪ No co nt ro ls Lo w Wo lc o tt et al .2 0 1 6 [3 7 ] U C Co ho rt 29 6 3 91 0 D FU /9 1 6 VL U /6 7 6 D U /3 7 0 P S U Sh ar p d e b ri de me nt at su rf ac e w ou nd be d 16S rR NA V1 -V 3 ▪ N e it h e r p at ie nt de mo gr ap hi cs (a ge , g e n d e r, ra ce , d ia b e te s st a tu s) no r w o u n d ty p e in flu e n ce d th e ba ct er ia l co m p o si ti o n o f th e ch ro ni c w ou nd mi cr o b io m e ▪ St ap hy lo co cc u s an d Ps eu d o m o n a s co mp ri se th e mo st p re va len t g e n e ra p re se n t in th e m ic ro bi o ta o f ch ro n ic w o u n d s, w it h S. au re us an d S. ep id er m idi s th e m o st pr ed om in a n t sp e c ie s ▪ Ch ro n ic w o u n d s a re fr eq ue nt ly co lo ni ze d b y c om mu na lis tic an d an ae ro bi c b a c te ri a, in cl u d in g co ag ul at io n-ne ga ti ve St ap hy lo co cc u s, Co ry ne b a ct er iu m , an d Pr op io n iba ct er iu m sp e c ie s ▪ Un c le a r w he th er p a ti e n ts w e re on tr ea tm en t Lo w to m o d e ra te Sm it h et al . 20 1 6 [3 6 ] U C Co ho rt 20 DF U St er ile sw a b s 1 6 S rR N A V4 ▪ Th e m o st co m m o n ly d e tec te d ba ct er ia in al l u lc er s w er e Pe pt o n ip h ilu s, A n ae ro co cc us an d C o ry ne b a ct er iu m sp ec ie s ▪ In ne w u lc e rs , th e m o st co mm on ly de te c te d ba ct er ia w e re th e a b o ve an d St ap hy lo co cc u s sp e ci e s ▪ Th e m a jo rit y o f O TU s re sid in g in bo th ne w a n d re c u rr en t u lc e rs (> 67% ) w e re mo st ly Gr am -p o sit iv e co cc i (St ap hy lo co cc u s, St re pt o co cc u s, An ae ro co cc us , Pe pt on ip h ilu s an d Fi ne go ld ia ▪ Lo w e r H b A 1 c va lu es an d sh o rt e r d u rat io n o f d ia be te s co rr el at ed wi th hi gh er di v e rs it y w it h in th e ul ce r ▪ Sm al l co h o rt ▪ N o se ri a l sa m p lin g ▪ No co nt ro ls Lo w (con ti n u es )Ta
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(C on ti nu ed ) So ur ce F ir st au th o r, y e a r [r e f] D is ea se St ud y d es ig n No . o f p at ie n ts Sa m p le co ll e c ti o n me th o d s A na ly si s K e y fi n d in g s W ea kn es se s Le ve l ev id e n c e Ka la n et al . 20 1 6 [3 8 ] U C Pr o spe ct iv e lo n g it u d in a l co ho rt 10 0 D FU St er ile sw a b s M u lt ip le ti me po in t sa m p lin g IT S 1 rR NA ▪ Fu ng al mi cr o b io me w a s hi gh ly he te ro ge ne o u s o v e r ti me an d b e twe en su b je ct s ▪ Fu ng al di v e rs it y in cr e a sed w it h an ti bi ot ic ad mi ni st ra ti o n ▪ Th e p ro po rt io n o f th e ph y lu m A sc o m y co ta we re si g n ifi ca nt ly gr ea te r a t th e be gi nn in g o f the st u d y in w o u n d s tha t to ok > 8 w ee ks to he al ▪ No co nt ro ls ▪ Mo st pa ti en ts o n ac ti v e tr e a tm e n t Lo w to m o d e ra te Lo e sc h e et al . 20 1 7 [3 9 ] U C Pr o spe ct iv e lo n g it u d in a l co ho rt 10 0 D FU St er ile sw a b s M u lt ip le ti me po in t sa m p lin g 16S rR NA V1 -V 3 ▪ Th e m o st a b u nd an t g e n u s id en ti fied w a s St ap hy lo co cc u s, fo llo w e d by St re pt o co cc u s, C o ry ne b a ct er iu m an d An ae ro co cc us ▪ Th e m a jo r O T U a tt ri b u te d to St ap hy lo co cc u s wa s S . au re u s ▪ U lc e r m ic ro b io ta w as hi gh ly dy na mi c, w it h co mm un it y ty p e tr an si ti o n s o c cu rr in g ap p ro x im a te ly ev er y 3 .5 2 w e e k s ▪ M ic ro b io ta co mm un it y in st a b il it y w as as so ci at ed w it h fa st e r he al in g a n d im pr o v ed ou tc o m e s ▪ E x p o su re to sy st e m ic an ti b io ti cs de st a b iliz e w ou nd mi cr o b io ta , ra th er th a n al te ri n g o ve ral l di v e rs it y o r rel at iv e a b u n d a n c e of sp ec ifi ct a x a ▪ No co nt ro ls ▪ Mo st pa ti en ts o n ac ti v e tr ea tm en t Lo w to m o d e ra te Ku k P ar k et al .2 0 1 2 [4 0 ] SD /P C C a se con tr o l 4P C 3H V St er ile sw a b s 2 6 S rR N A D1 -D 2 ▪ P. me le a g ri nu m an d P. ch ru so g enu m d e te ct ed on d a n d ru ff sc a lp ▪ Ma la ss ez ia sp p . 2 ti m e s mo re ab un da nt o n da nd ru ff sc a lp ▪ Sm al l co h o rt ▪ N o se ri a l sa m p lin g Lo w Cl av au d et al . 20 1 3 . [4 1 ] SD /P C C a se –co nt ro l 29 PC 20 HV St er ile sw a b s In 2 0 PC p a ti e n ts le si o n a l an d n o n le si o n a l sa m p lin g 16S 28S -I T S ▪ M. re st ri ct a ma jo r fun ga l sp e ci e s o n sca lp PC an d H V ▪ M. re st ri ct a a nd s. ep id er m id is si g n ifi c a n tly mo re ab un d a n t on PC sc a lp ▪ Pr op io n ib a ct er iu m a cn es si g n ifi c a n tly le ss ab un d a n t on PC sc a lp ▪ M. re st ri ct a/ P. ac ne s ra ti o si g n ifi c a n tly hi g h e r in P C sc a lp ▪ Sm al l co h o rt ▪ N o se ri a l sa m p lin g Lo w So ar es et al . 20 1 5 [4 2 ] SD /P C C a se con tr o l 9 S D (5 m ild , 4 sev er e) 5H V St er ile sw a b s Sc al p, fo re he ad ch in , sh o u ld e r an d in ter fa c e sa m p le s 5. 8 S /I T S 2 rD N A ▪ In ge ne ra l, no as so ci at io n be tw ee n Ma la ss ez ia my co b io ta an d S D w as fo un d ▪ Sm al l co h o rt ▪ N o se ri a l sa m p lin g Lo w (con ti n u esTa
bl
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(C on ti nu ed ) So ur ce F ir st au th o r, y e a r [r e f] D is ea se St ud y d es ig n No . o f p at ie n ts Sa m p le co ll e c ti o n me th o d s A na ly si s K e y fi n d in g s W ea kn es se s Le ve l ev id e n c e ▪ Hi g h e r m. gl ob o sa ab un da nc e w a s fo u n d in no ns ca lp le si o n s of se v e re SD p a ti e n ts Pa rk et al . 20 1 7 [4 3 ] SD /P C C a se con tr o l 29 SD 28 PC 45 HV St er ile sw a b s Sc al p sam pl es 16 s rR N A V4 -V 5 IT S 1 rD N A ▪ Hi g h e r ab un d a n ce o f St ap hy lo co cc u s sp . a n d m. re st ri ct a ,a n d lo w e r a b u n d a n c e of P ro p io n iba ct er iu m as so ci at ed wi th sc al p d is ea se ▪ No se ri a l sa m p lin g Lo w Be k -T h o m se n et al .2 0 0 8 [4 4 ] A V Ca se co nt ro l 5A V /3H V C ya n o a c ry la te b io ps y A V ac ne le si o n fa ce HV no se ar ea 16S rR NA V1 -V 9 ▪ A cn e sk in hi g h e r di v e rs it y , P. a cn es an d S. ep id er m idi s mo st co mm o n sp ec ie s ▪ Sm al l co h o rt ▪ On ly mo d e ra te to se ve re pa ti e n ts ▪ N o se ri a l sa m p lin g ▪ No no nl es io na l p a ti e n t sam pl in g Lo w Fi tz -G ib bo n et al .2 0 1 3 [4 5 ] A V Ca se co nt ro l 49 AV /5 2 H V B io ré® De ep C le a n si n g P o re str ip s N o se ar ea 16S rR NA V1 -V 9 ▪ N o d if fe ren ce re la ti v e ab un d a n ce P. ac ne s A V in HV . ▪ A sso ci at io n spe ci fic P. ac ne s st ra in an d a c n e . ▪ So me p a ti e n ts on ac ti v e tr ea tm en t ▪ N o se ri a l sa m p lin g ▪ No no nl es io na l p a tie nt sa m p ling Lo w Ba rn a rd et al .2 0 1 6 [4 6 ] A V Ca se co nt ro l 38 AV /3 4 H V B io ré® De ep Cl ea ns in g Po re st ri p s N o se ar ea W M S seq u e n ci n g ▪ A sso ci at io n spe ci fic P. a cn es st ra in a n d a c n e . ▪ So me p a ti e n ts on ac ti v e tr ea tm en t ▪ N o se ri a l sa m p lin g ▪ No no nl es io na l p a tie nt sa m p ling Lo w Dr eno et al . 20 1 7 [4 7 ] A V Si ng le -c en te r, ra nd o m iz e d -c o n tr o lle d , do ub le -b li nd Er yt hr om y ci n 4 % OR De rm at oc o sme ti c 26 AV St er ile sw a b s Le si o n a l an d n o n le si o n a l sk in M u lt ip le ti me po in ts 1 6 S rR N A V4 ▪ Di ff e re n t m ic ro bi o ta pr ofi le s o n d if fe re n t si te s. ▪ E ry thr o m y c in tr e a tm e n t re du ce d th e nu mb er of A ct in o ba ct er ia , a n d de rm o co sme ti c re d uc ed A ct in o ba ct er ia an d St ap hy lo co cc u s sp p. ▪ Sm al l co h o rt ▪ M u lt ip le sa mp le s ex cl ud ed du e to in suf fici e n t b a c te ria l m a ter ia l Mo de ra te Ke lh al a et al . 20 1 7 [4 8 ] A V Si ng le -c en tr e , co nt ro lled st u d y is ot re ti no in 0. 4– 0. 6 m g kg – 1 or lyme c yc lin e 3 0 0 mg tw ic e d a ily 17 is ot re ti n o in 11 ly me c yc lin e 16 HV St er ile sw a b s Pr ed os e a n d af te r 6 w ee ks C h e e k , ba c k an d a rm p it 16S rR NA V1 -V 3 ▪ Po si ti v e c o rr el at io n Pr op io n iba ct er iu m ab un d a n ce a n d ac ne se v e ri ty gr ad e ▪ B o th tr ea tm en ts re du ce d cl in ica l ac ne gr ad es ▪ Pr op io n ib a ct er iu m de cr ea se d in ch e e k sa m p le s a ft e r bo th tr ea tm e n ts ▪ Pr op io n ib a ct er iu m de cr ea se d in b ac k sam p le s ▪ Sm al l co h o rt ▪ No no nl es io na l p a ti e n t sam pl in g Mo de ra te (c on ti n u es )Ta
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(C on ti nu ed ) So ur ce F ir st au th o r, y e a r [r e f] D is ea se St ud y d es ig n No . o f p at ie n ts Sa m p le co ll e c ti o n me th o d s A na ly si s K e y fi n d in g s W ea kn es se s Le ve l ev id e n c e af te r ly m e cy cl in e , b u t no t iso tr et in o in tre at me nt ▪ Di v e rs it y in cr e a sed af te r tre at me nt Su g it a et al . 20 0 4 [5 8 ] A D Ca se co nt ro l 13 AD /1 2 H V O p S ite ® tr a n spa re n t ad he si v e dr es si n g s Le si o n a l sk in HV ma tc he d si tes 26S a n d 5 S rR N A in te rg e n ic sp ac er re g io n 1 ▪ M. re st ri ct a c o lo ni ze s bo th A D an d H V ▪ Sm al l co h o rt ▪ N o se ri a l sa m p lin g ▪ Li mi te d a n a ly si s ▪ Pa ti en ts o n ac ti v e tr ea tm en t Lo w De ki o et al . 20 0 7 [4 9 ] A D Ca se co nt ro l 13 AD /1 0 H V St er ile sw a b s Fo re he ad sk in 16S rR NA ▪ In bo th A D an d H V th er e w as a h ig h rat e o f St re p toc o cc u s sp e ci e s ▪ In A D St re n o tr op ho m o n a s ma lt op hi lia wa s sign ifi ca nt ly mo re c o m m o n ▪ Sm al l co h o rt ▪ N o se ri a l sa m p lin g ▪ Pa ti en ts o n ac ti v e tr ea tm en t Lo w Ka g a et al . 20 0 9 [5 0 ] A D Ca se co nt ro l 56 AD /3 2 H V O p S ite ® tr a n spa re n t ad he si v e dr es si n g s Le si o n a l sk in A D Fa ce HV 26S a n d 5 S rR N A in te rg e n ic sp ac er re g io n 1 ▪ In mi ld an d m o d e rat e AD , M. re st ri ct a wa s pr ed om in a n t o v e r M. gl o b o se ▪ In pa ti e n ts wi th se v e re A D , p ro po rt io n s of M. re st ri ct a an d M. gl ob os e w e re al mo st id en ti ca l ▪ Li mi te d a n a ly si s ▪ N o se ri a l sa m p lin g ▪ Va ri at io n in sk in sam pl e sit es ▪ Pa ti en ts po ss ib ly o n a c ti v e tr ea tm en t Lo w to m o d e ra te Yi m et al . 20 1 0 [5 1 ] A D Pr o spe ct iv e co h o rt 60 St er ile sw a b s 5 b od y sit es 26S ▪ Th er e w er e n o sig ni fica n t di ff e re n c e s b e twe en po si ti v e Ma las sez ia cu lt u re , Ma la ss ez ia sp e ci e s, an d se v e ri ty of AD ▪ Li mi te d a n a ly si s ▪ Pa ti en ts o n em o lli e n t tr ea tm en t Lo w to m o d e ra te Ak a z a et al . 20 1 0 [5 2 ] A D Ca se co nt ro l 67 St er ile sw a b s Le si o n a l an d n o n le si o n a l sk in Fa ce an d tru nk 26S ▪ Fo r th e to ta l n u m b e r o f Ma la ss ez ia sp e ci e s, th er e w e re no si g n ifi c a n t di ff er en ce s be tw ee n le sio na l a n d no nl es io na l a re a s ▪ N o se ri a l sa m p lin g ▪ Pa ti en ts o n ac ti v e tr ea tm en t Lo w to m o d e ra te Ko ng et al . 20 1 2 [6 0 ] A D Pr o spe ct iv e co h o rt 12 AD /1 1 H V St er ile sw a b s M u lt ip le ti me po in ts Ba se lin e ,fl ar e, p o st -fl ar e 16S rR NA V1 -V 9 ▪ Fl ar e u ps w e re as so c ia te d w it h an in c re a se d p ro p o rt io n of St ap hy lo co cc us se q u en ce s, pa rt ic ul ar ly S. au re us ,a n d co rr el at ed wi th di se a se sev er it y ▪ In cr ea se s in St re p toc o cc u s, Pr op io n b ac te ri um ,a n d C o ry ne b a ct er iu m sp ec ie s w e re ob se rv e d fo llo w in g th e ra p y ▪ Sm al l co h o rt ▪ On ly mo d e ra te to se v e re pa ti e n ts ▪ Di ff er en t tr e a tm e n ts re g im e n s d u ri n g flar e Lo w to m o d e ra te Se it e et al . 20 1 4 [5 4 ] A D Pr o spe ct iv e co h o rt Em o lli e n s tr e a tme nt 46 St er ile sw a b s Le si o n a l an d n o n le si o n a l sk in M u lt ip le ti me po in ts 16S rR NA V1 -V 2 ▪ A ff e c te d sk in ha rb o u re d a g re at er re la ti v e ab un da nc e of St ap hy lo co cc us ,a n d in pa rt ic ul ar ▪ La rg e ti m e b et w e e n fi rs t a n d se c o n d sa m p le ▪ On ly mo d e ra te pa ti e n ts Lo w to m o d e ra te (c on ti n u esTa
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(C on ti nu ed ) So ur ce F ir st au th o r, y e a r [r e f] D is ea se St ud y d es ig n No . o f p at ie n ts Sa m p le co ll e c ti o n me th o d s A na ly si s K e y fi n d in g s W ea kn es se s Le ve l ev id e n c e S. ep id er m is , c om p a re d to he al th y ski n ▪ Re sp o n d e rs ha d in cr e a sed mi cr o b ia l d iv er si ty an d de cr ea se in St ap hy lo co cc u s sp ec ie s Ch ng et al . 20 1 6 [5 5 ] A D Ca se co nt ro l 19 me di ca l h is to ry AD /1 5 H V /5 p o sit iv e sk in p ri ck Ta pe st ri p p in g an ti -c u b it al fo ss a 16S rR NA V3 -V 6 WM S ▪ No n fl ar e, ba se lin e sk in mi cr o b io m e si g n a tu re s en ri ch ed fo r St re pt oc oc cu s an d Ge m ell a in A D pr o n e sk in v e rs us no rm a l sk in ▪ In cr ea se d p e rc e n tag e of S. au re u s ca rr ie rs no te d in AD c o h o rt o ve r co nt ro l su b je c ts ▪ Sm al l co h o rt ▪ N o se ri a l sa m p lin g ▪ No le si o n a l sa m p le s Lo w Go n z a le z et al .2 0 1 6 [5 6 ] A D Ra nd o m iz e d , p la c e b o -co nt ro lled , sin gl e-bl in d e d To p ic a l st e ro id or To p ic a l st e ro id + d ilut e bl ea ch ba th 21 AD /1 4 H V St er ile sw a b s Le si o n a l an d n o n le si o n a l sk in M u lt ip le ti me po in ts 1 6 S rR N A V4 ▪ A ff e c te d sk in ha rb o u re d a g re at er re la ti v e ab un da nc e of S. au re u s ▪ M ic ro b ia l d iv e rs it y at al l le si o n a l si te s in v er se ly co rr el at ed w it h ov er al l E AS I In d e x sc o re ▪ Ta xo no mi c n o rm a li za ti o n oc cu rr ed on le si o n a l fo llow in g tr ea tm e n ts ▪ B a c te ri a l co m m u n iti es o n le si o n a l sk in re se m b le no nl es io n a l sk in bu t re m a in d is ti n ct fr o m he al th y c on tr o l sk in ▪ Sm al l stu d y Mo de ra te Se it e et al . 20 1 7 [5 7 ] A D Do ub le -b lin d , Ra nd o m iz e d , co mp ar at iv e Em o lli e n t A or Em o lli e n t B 53 St er ile sw a b s Le si o n a l an d no nl es io na l ski n M u lt ip le ti me po in ts 16S rR NA V1 -V 2 ▪ Si g n ifi ca nt in c re a se d le ve ls of X a n tho m o n a s ge nu s in pa ti en ts tr e a te d w it h e m o llie nt A ▪ Le v e ls o f St ap hy lo co cc u s ge nu s in cr e a sed b e tw ee n Da y 1 an d D a y 2 8 in p a ti e n ts tr ea te d w it h e m o lli e n t B ▪ On ly mo d e ra te pa ti e n ts ▪ No w a sh -o ut o th e r tre at me nt s Mo de ra te Ki m et al . 20 1 7 [5 9 ] A D Pr o spe ct iv e co h o rt We t d re ss in g s To p ic a l st e ro id s An ti h is ta m in e s An ti b io ti c s 27 AD 6H V Sa lin e so ak ed ga uz es 1 6 S rR N A V1 -V 3 ▪ P rop o rt io n of St ap hy lo co cc u s si g n ifi c a n tly d e c re a se d a ft er tr ea tm e n t ▪ Di v e rs it y (S h a n n o n In d e x ) si g n ifi c a n tly in c re a se d af te r tre at me nt ▪ Sm al l stu d y ▪ Pa ti en ts o n w id e v a ri e ty o f tr ea tm en ts ▪ No no nl es io na l ski n a n a ly si s Lo w to m o d e ra te A D , a to pi c d er ma ti ti s; A V , a c n e vu lg a ri s; DF U , di ab et ic fo o t ul ce r; H S , h id ra d e n it is sup p u ra ti v a ; N U, ne ur op at hi c u lc er ; O T H , o th e r; O T U , o p e ra ti o na l ta x o n o m ic un it ; P S U , p o st-su rg ic a l ul ce r; PU , p re ss u re ul ce r; PV , p so ri as is vu lg ar is ; S D /P C , se b or rh o e ic de rm at it is /p it yr ia si s ca p it is ; U C , u lc u s cr u ri s; VL U, v e n o u s le g u lc erDiscussion
This systematic review provides an overview of the clinical studies that have investigated nonculture skin microbiome associated outcomes in AD, SD, AV, HS, PV and UC with the goal to explore its potential as biomarker in early phase clin-ical drug development with drug specific or disease specific application, as also referred to as type 3 or type 6 biomarker according to the classic definition of Danhof et al. [67].
Potential for microbiome as biomarker: AD and
AV
From our analysis, there is some preliminary evidence that the skin microbiota may be a suitable disease specific bio-marker for clinical trials of AD. This is due to the correlation between Staphylococcus abundance, microbiome diversity profile and disease severity that seems to exist in multiple tri-als, therewith complying with most of the criteria for a useful biomarker, Table 2 [4]. Objective data on the change of the microbiota may be valuable to support subjective AD efficacy scores in early phase clinical trials. However, it must be noted that the cause and effect relationship between skin microbi-ota dysbiosis and AD remains incompletely elucidated [68]. Currently, no evidence of benefit of antimicrobial interven-tions directed at reduction of Staphylococcus in patients with AD exists, only in secondarily impetiginized AD [69–71]. As multiple studies included in this review indicate that the skin microbiota within an individual patient varies over time [60, 61, 63, 64], there is need for longitudinal, frequent sampling and standard analysis studies. Nevertheless, it has proven its potential value and is recommended to apply in AD clinical trials, in particular when microbiota can serve also as drug-specific biomarker, i.e. for drugs with antimicrobial activity such as antimicrobial peptides that are currently in clinical trials for AD.
In AV, a strong, positive correlation between
Propionibacterium and acne severity grade is reported [55].
Moreover, acne improved and Propionibacterium decreased after treatment, while the microbial diversity increased [54, 55]. Taking into account that a clear pathophysiological
role of P. acnes exists and antimicrobial interventions are ef-fective in AV [72, 73], the adoption of the skin microbiome as biomarker in acne drug development programmes is, al-though still in its infancy, suggested by our review (Table 2). Lesion clearance often takes a long time; therefore, the in-clusion of microbiota is a valid option to monitor subclini-cal treatment effects and restoration of normal bacterial profile, i.e. rebiosis. Although a small uncertainty remains regarding the exact relationship between aberrations in the skin microbiome and acne [74], we conclude that there is definitely a potential for the microbiota as biomarker in clinical trials (Table 2). Another option would be to culture
P. acnes instead of profiling the whole skin microbiota in
clinical trials; however, with this approach a comprehensive overview and insight in the diversity will be missed.
PV, UC, hidradenitis and SD are lacking
evidence
Although dysbiosis in psoriasis seems to exist in the micro- as
well as the mycobiota, study findings are heterogeneous.
Wide variability in study design, sampling methods, control-lable factors and sequencing techniques between groups, in conjunction with small sample populations, could provide a possible explanation for this. Therefore, no clear recommen-dations can be made at this time. Future work focusing on se-rial sampling and longitudinal studying of skin microbiome populations it PV patients, may provide information on its potential applicability as biomarker, Table 2. From a clinical perspective, we know that antimicrobial and antifungal agents are not successful in the treatment of psoriasis, which suggests that it is less attractive to explore [75, 76]. However, since immune dysregulation is the key of psoriasis and recent investigations describe the extensive cross talk between the immune system and the microbiome, there may still be po-tential that should be explored [77]. For UC inconsistencies in study design, sampling methods and the heterogeneity of
the disease group also limit the comparability of study
find-ings. There appears to be a relationship between certain spe-cies, types of ulcers and ulcer duration [42, 46]. However, longitudinal studies with frequent standard sampling and
Table 2
Evaluation of the microbiome as clinical biomarker for each dermatological disease included in the review based on the criteria of a useful bio-marker as defined by de Visser et al. [4]
Indication
Manuscripts (N)
Evidence
level overall Consistency
Therapeutic response Dose– response relation Relationship with disease Recommendation for trial implementation
PV 10 Low – 0 0 0 Negative, more evidence needed
HS 2 Low + 0 0 + Negative, more evidence needed
UC 10 Low + 0 0 + Negative, more evidence needed
SD 4 Low – 0 0 + Negative, more evidence needed
AV 5 Moderate + + 0 + Positive
AD 11 Moderate + + 0 + Positive
AD, atopic dermatitis; AV, acne vulgaris; HS, hidradenitis suppurativa; PV, psoriasis vulgaris; SD/PC, seborrhoeic dermatitis/pityriasis capitis; UC, ulcus cruris Scoring system indicated as follows: +, studies in general report a positive outcome; 0, no studies available;–, studies in general report a negative outcome
standard analysis procedures are necessary to make a
recom-mendation. Thefinding of dysbiosis in HS skin microbiome
mostly regarding anaerobic species that is mostly consistent in two different studies opens up opportunities for the skin
microbiome as biomarker in thisfield, Table 2 [35, 36].
How-ever, future studies will have to confirm this potential. In SD, three different sequencing methods were used in the three different studies [47, 49, 50]. This, together with the small sample populations, single time point sampling and poor
study designs, might explain the heterogeneity infindings.
Since there is a clear evidence that antifungal agents such as ketoconazole are effective in SD [78], it is recommended to further explore the skin microbiome’s potential in this dis-ease in future clinical trials.
Limitations and considerations
It is important to note that in all included studies, there was a high variability in study design and sampling methods be-tween groups, which makes comparisons of specific findings difficult. Case–control studies (25/42, 60%) dominate re-search into the skin microbiome and skin disease. Patients are compared with healthy controls, capturing microbial pro-files at a particular time, but have little predictive value in de-termining functionality, looking more at associations, and not causation. The small patient sample sizes across all stud-ies may fail to account for interindividual differences within the study population. The poorly defined inclusion and ex-clusion criteria, with certain studies including actively treated patients in their sample population, could also
con-found potentialfindings. The standardization of controllable
factors to reduce confounders was not well documented or maybe not performed in most of the included studies. As sim-ple factors including but not limiting of age, ethnicity, envi-ronmental factors, soap use, hand-washing and the use of topical (antimicrobial) agents before sampling have been shown to alter microbial skin communities; documentation of these metadata is essential to draw valid conclusions [5, 8, 12, 60, 61, 79–81]. Multiple methods were used for skin microbiome sampling across the studies (i.e. swabs, biop-sies, tape strips, wound curettes). Interestingly, all have been shown to exhibit a wide variation in biomass yield, micro-bial profile, human DNA contribution/contamination, sampling depth and discomfort level for the test subject [19, 62, 82–87]. In addition to the sampling method, the se-lection of sampling sites and sampling frequency are impor-tant factors that were not always considered in the included studies. Consistent sampling of the same anatomi-cal area of skin in all individuals in study cohorts is essential in order to limit confounders, and allow for the accurate comparison of skin microbiome populations. Moreover, re-garding analysis, only consistent use of specific primers to target specific hypervariable V regions, will allow for colla-tion of data and comparison between multiple studies. It is clear that broadly used analysis methods in this review as shown in Table 1 count as a limitation for comparison. Taken all the above together, based on the level of evidence it is clear that our recommendations should be made with some caution. A standard approach for skin microbiome study design, collection, storage, processing and analysis as proposed by Kong et al. should be followed in future studies
[17]. However, although the list of limitations and some-times poor evidence might be assessed as a weak recommen dation for the inclusion of cutaneous microbiome in
der-matological trials, the recent finding that the gut
microbiome partially explains the response/nonresponse to PD-1 immunotherapy in different cancer patients will foster research into microbiome in general [88, 89]. In ad-dition, the relation between the gut microbiome in inflam-matory bowel disease and response to infliximab was also recently highlighted [90]. In particular, when considering the reports about the role of the gut-skin axis that might influence many diseases including the here investigated skin disorders [91–93].
Conclusion
Only a small number of studies have consistently reported the cutaneous microbiome for skin diseases and chronic
wounds. Ourfindings reveal that for two indications – AD
and AV– there is preliminary evidence to support
implemen-tation of the skin microbiome as biomarker in early phase clinical trials. For PV, UC, SD and HS, there is insufficient ev-idence. More standardized microbiome-directed studies studying the effect of current treatments on the microbiome are needed to draw conclusions.
Competing Interests
There are no competing interests to declare.
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