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The microbiome can affect skin health from the gut-skin axis, from environmental exposure, and topical treatments. Decreasing biodiversity of skin microbiota has been linked to inflammatory conditions, allergies, and skin health.
This cross sectional study will be used to survey healthy volunteers and measure the density and diversity of skin flora of varying skin types. The aim of this study is to identify associations between the skin flora and characteristics of healthy skin types.
The microbiome can affect skin health from the gut-skin axis, from environmental exposure, and topical treatments. Decreasing biodiversity of skin microbiota has been linked to inflammatory conditions, allergies and skin health.
Therefore, this cross sectional study will be used to survey healthy volunteers and measure the density and diversity of skin flora of varying skin types.
This study will aim to determine if there are associations between the diversity and/or density of normal bacterial flora and (1) the different skin types (i.e. normal, dry, oily, combination, sensitive); (2) the different Fitzpatrick skin types (i.e. ivory; fair or pale; fair to beige with golden undertones; olive or light brown; dark brown; deeply pigmented dark brown to darkest brown): (3) the number of skin products used daily representing time spent on skin health (i.e. low:0-1, mid:2-4, high:5+). Participants will complete a survey in which they will identify their skin conditions and the number and type of skin products they use on their face as a part of their daily routine.
In addition, this study will evaluate the potential of an autofluorescence image-guided device to capture differences in healthy human skin flora through autofluorescence. The MolecuLight i:X™ is used to detect bacteria in chronic wounds. Based on extensive preclinical and clinical studies, the i:X has demonstrated its capability at collecting autofluorescent images of wounds and detecting the presence and relative changes in connective tissue (e.g. collagen) content and bio-distribution involved in wound healing. It can also detect the presence and relative amounts of commensal and pathogenic bacteria within the wound based on autofluorescence alone (these bacteria are invisible to standard visualization with the naked eye using white light), thus providing a measure of infection status.
The imaging device will be used to image skin from the cheek and forehead of healthy volunteers to compare the fluorescent characteristics of normal skin flora. The fluorescent images captured with the i:X™ will be compared against 16S RNA analysis of the skin microbiome and traditional microbiology techniques with selective and differential tests. In addition, non-selective agars will be used to grow bacteria according to the spatial topography of the skin, using a tape stripping method, with lightly adhesive 3M™Tegaderm wound dressings. This will serve as a "map" for fluorescent images by which to compare fluorescent features to bacterial species.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Normal skin |
| ||
| Oily skin |
| ||
| Dry skin |
| ||
| Combination skin |
| ||
| Sensitive skin |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| fluorescence imaging with 405nm light | Other | Each group will have images taken with an Health Canada approved device to capture images under white light and 405nm fluorescence with an mCherry filter. These images will not be used for diagnostics and will be analyzed for features which correlate to identified microbes from 16S RNA analysis and traditional microbiological technique. Groups are self identified by participants in order to capture a diverse population. |
| Measure | Description | Time Frame |
|---|---|---|
| Bacterial diversity between individuals of each skin condition (i.e. normal, dry, oily, combination, sensitive). (Number of CFU) | Frequency of unique colonies identified from microbiological and microbiome techniques between individuals of each skin condition (i.e. normal, dry, oily, combination, sensitive). | February 2020 |
| Bacterial density (CFU/cm2) between individuals of each skin condition | Abundance of bacterial colonies per cm2 of sampled area identified from microbiological and microbiome techniques between individuals of each skin condition (i.e. normal, dry, oily, combination, sensitive). | February 2020 |
| MolecuLight i:X detection of density and diversity (green or red fluroescence/cm2) | Abundance of green and/or red fluorescent detection with MolecuLight i:X per cm2 of sampled area between individuals of each skin condition. Frequency of green or red fluorescence per sample. | February 2020 |
| Measure | Description | Time Frame |
|---|---|---|
| Identification of spatial distribution of bacterial species (CFU/cm2 of individual species) | Abundance of unique species and bacterial families identified from microbiological and microbiome techniques between individuals of each skin condition (i.e. normal, dry, oily, combination, sensitive) and Fitzpatrick skin type per. Distribution of unique species and bacterial families across the area of sampling of individuals on Tegaderm "map". |
| Measure | Description | Time Frame |
|---|---|---|
| Imapact of cosmetic use on diversity of bacterial species across individuals with different cosmetic use (high, mid, low). (Number of CFU) | Compare the frequency of specific bacterial species and bacterial families identified with microbiology and microbiome techniques between individuals with different skin care routines. | February 2020 |
Inclusion Criteria:
Exclusion Criteria:
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The study population will consist of healthy volunteers with no existing or recent skin conditions.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Princess Margaret Cancer Research Tower | Toronto | Ontario | M5G1L7 | Canada |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 20203603 | Background | Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, Manichanh C, Nielsen T, Pons N, Levenez F, Yamada T, Mende DR, Li J, Xu J, Li S, Li D, Cao J, Wang B, Liang H, Zheng H, Xie Y, Tap J, Lepage P, Bertalan M, Batto JM, Hansen T, Le Paslier D, Linneberg A, Nielsen HB, Pelletier E, Renault P, Sicheritz-Ponten T, Turner K, Zhu H, Yu C, Li S, Jian M, Zhou Y, Li Y, Zhang X, Li S, Qin N, Yang H, Wang J, Brunak S, Dore J, Guarner F, Kristiansen K, Pedersen O, Parkhill J, Weissenbach J; MetaHIT Consortium; Bork P, Ehrlich SD, Wang J. A human gut microbial gene catalogue established by metagenomic sequencing. Nature. 2010 Mar 4;464(7285):59-65. doi: 10.1038/nature08821. | |
| 4639749 |
| Label | URL |
|---|---|
| Understanding Your Skin. Different skin conditions as defined by cosmetic industry | View source |
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IPD which underlie results may be shared in an academic publication. It is undecided if these results may yield a publication.
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| ID | Term |
|---|---|
| D003141 | Communicable Diseases |
| ID | Term |
|---|---|
| D007239 | Infections |
| D020969 | Disease Attributes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| ID | Term |
|---|---|
| D061848 | Optical Imaging |
| D008027 | Light |
| ID | Term |
|---|---|
| D003952 | Diagnostic Imaging |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
| D008919 | Investigative Techniques |
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| February 2020 |
| Identification of spatial distribution of red/green fluorescence detected with MolecuLight i:X™ (red and green fluroescence/cm2) | Abundance of unique fluorescent (green and red) detection with MolecuLight i:X™ between individuals of each skin condition (i.e. normal, dry, oily, combination, sensitive) and Fitzpatrick skin type. Distribution of red and green fluorescent signals across the area of sampling of individuals on Tegaderm "map". | February 2020 |
| Imapact of cosmetic use on density of bacterial species across individuals with different cosmetic use (high, mid, low). (CFU/cm2) |
Compare the abundance of specific bacterial species and bacterial families identified with microbiology and microbiome techniques between individuals with different skin care routines per cm2 of area sampled. |
| February 2020 |
| Background |
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| 29193830 | Background | Lee HJ, Jeong SE, Lee S, Kim S, Han H, Jeon CO. Effects of cosmetics on the skin microbiome of facial cheeks with different hydration levels. Microbiologyopen. 2018 Apr;7(2):e00557. doi: 10.1002/mbo3.557. Epub 2017 Nov 29. |
| 30464283 | Background | Sohn E. Skin microbiota's community effort. Nature. 2018 Nov;563(7732):S91-S93. doi: 10.1038/d41586-018-07432-8. No abstract available. |
| 3377516 | Background | Fitzpatrick TB. The validity and practicality of sun-reactive skin types I through VI. Arch Dermatol. 1988 Jun;124(6):869-71. doi: 10.1001/archderm.124.6.869. No abstract available. |
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| 17558006 | Background | Agren MS, Werthen M. The extracellular matrix in wound healing: a closer look at therapeutics for chronic wounds. Int J Low Extrem Wounds. 2007 Jun;6(2):82-97. doi: 10.1177/1534734607301394. |
| 25790480 | Background | DaCosta RS, Kulbatski I, Lindvere-Teene L, Starr D, Blackmore K, Silver JI, Opoku J, Wu YC, Medeiros PJ, Xu W, Xu L, Wilson BC, Rosen C, Linden R. Point-of-care autofluorescence imaging for real-time sampling and treatment guidance of bioburden in chronic wounds: first-in-human results. PLoS One. 2015 Mar 19;10(3):e0116623. doi: 10.1371/journal.pone.0116623. eCollection 2015. |
| 25089944 | Background | Wu YC, Kulbatski I, Medeiros PJ, Maeda A, Bu J, Xu L, Chen Y, DaCosta RS. Autofluorescence imaging device for real-time detection and tracking of pathogenic bacteria in a mouse skin wound model: preclinical feasibility studies. J Biomed Opt. 2014 Aug;19(8):085002. doi: 10.1117/1.JBO.19.8.085002. |
| 24928709 | Background | He SY, McCulloch CE, Boscardin WJ, Chren MM, Linos E, Arron ST. Self-reported pigmentary phenotypes and race are significant but incomplete predictors of Fitzpatrick skin phototype in an ethnically diverse population. J Am Acad Dermatol. 2014 Oct;71(4):731-7. doi: 10.1016/j.jaad.2014.05.023. Epub 2014 Jun 11. |
| 18555952 | Background | Baumann L. Understanding and treating various skin types: the Baumann Skin Type Indicator. Dermatol Clin. 2008 Jul;26(3):359-73, vi. doi: 10.1016/j.det.2008.03.007. |
| 28244218 | Background | Ottolino-Perry K, Chamma E, Blackmore KM, Lindvere-Teene L, Starr D, Tapang K, Rosen CF, Pitcher B, Panzarella T, Linden R, DaCosta RS. Improved detection of clinically relevant wound bacteria using autofluorescence image-guided sampling in diabetic foot ulcers. Int Wound J. 2017 Oct;14(5):833-841. doi: 10.1111/iwj.12717. Epub 2017 Feb 28. |
| 26214616 | Background | Chamma E, Qiu J, Lindvere-Teene L, Blackmore KM, Majeed S, Weersink R, Dickie CI, Griffin AM, Wunder JS, Ferguson PC, DaCosta RS. Optically-tracked handheld fluorescence imaging platform for monitoring skin response in the management of soft tissue sarcoma. J Biomed Opt. 2015 Jul;20(7):076011. doi: 10.1117/1.JBO.20.7.076011. |
| 25907362 | Background | Wu YC, Smith M, Chu A, Lindvere-Teene L, Starr D, Tapang K, Shekhman R, Wong O, Linden R, DaCosta RS. Handheld fluorescence imaging device detects subclinical wound infection in an asymptomatic patient with chronic diabetic foot ulcer: a case report. Int Wound J. 2016 Aug;13(4):449-53. doi: 10.1111/iwj.12451. Epub 2015 Apr 22. |
| D060733 | Electromagnetic Radiation |
| D055590 | Electromagnetic Phenomena |
| D060328 | Magnetic Phenomena |
| D055585 | Physical Phenomena |
| D055620 | Optical Phenomena |
| D011827 | Radiation |
| D011840 | Radiation, Nonionizing |