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Differences in Microbiomes Between Intact Diabetic Skin, Diabetic Foot

Ulcers, and Non-Diabetic Skin Katie Springer, BS

Dr. William M. Scholl College of Podiatric Medicine

July 13, 2019

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Disclosure

• Grant support – NIH grant T35DK074390 from the National Institute

of Diabetes and Digestive and Kidney Diseases. – American Podiatric Medical Students’ Association.

• The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIDDK, NIH or APMSA.

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Introduction • Individuals with diabetes are more prone to infection. • Shifts in the bioburden can increase a person’s risk of

infection. • 3 Dimensions of bioburden

– Microbial load – Microbial diversity – Microbial shift toward pathogenicity

• The purpose of this study was to evaluate differences in the microbiome between DFU, DS, and NDS.

1. Dewilde, S., Harris, T., Hosking, F. J., & Cook, D. G. (2018). Risk of Infection in Type 1 and Type 2 Diabetes Compared With the General Population: A Matched Cohort Study. Diabetes Care, 41(3), 513–521.

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Methods • 40 subjects participated in this

study • 20 with diabetes and a single

UTSA Grade 1A plantar ulcer • 20 age (+/-4 years) and

gender match controls

• Wound/skin cultures via Levine technique • Subjects with diabetes

• Wound • Equivalent ulcer location contralateral

foot • Controls

• Plantar aspect of bilateral feet

• Quantitative cultures • 16S ribosomal RNA (rRNA) gene amplicon sequencing

• Statistical Analysis

• Analysis of Similarity (ANOSIM) • Alpha-diversity measurements

• Richness, evenness, diversity, and variation in taxonomic distinctness

1. Copeland-Halperin, L. R., Kaminsky, A. J., Bluefeld, N., & Miraliakbari, R. (2016). Sample procurement for cultures of infected wounds: a systematic review. Journal of Wound Care, 25(Sup4), S4–S10.

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Results: Characteristics Controls Subjects with Diabetes p-value

Mean HbA1c 5.53+/- 0.9 7.38 +/- 1.5 <0.001

Mean Glucose 103.3 +/- 16.4 162.4 +/- 74.4 0.0013

Mean BMI 30.0 +/- 6.8 31.1 +/- 6.2 0.604

Mean Age 59.4 +/- 12.9 58.6 +/- 12.4

Gender ratio (M:F)

14:6 14:6

Wound duration (months)

N/A 11.5 +/- 18.5

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Microbial Load

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Alpha Diversity Indices • Number of genera detected (S),

richness (d), evenness (J’), Shannon Index (H’) and Simpson Index (1-Lambda’).

• Kruskal-Wallis used to determine if populations of microbiome are significantly different.

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Microbial Community Ordination Non-metric MDS

Standardise Samples by TotalTransform: Square rootResemblance: S17 Bray-Curtis similarity

ConditionDFUDSNDS

2D Stress: 0.15

• Analysis of similarity o The difference in microbial community

structure between the three groups o Diabetic skin and diabetic foot ulcer

microbiomes were most similar to each other (low R) and ANOSIM results were not significant t p<0.05.

o Both diabetic skin and diabetic skin ulcer microbiomes were significantly different from non-diabetic skin

Analysis of Similarity (ANOSIM)

Comparison R value p-value

DFU, DS 0.07 0.074

DFU, NDS 0.424 0.001

DS, NDS 0.152 0.006

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Dominant Taxa

Klebsiella

Enhydrobacter

Stenotrophomonas

Micrococcus

Staphylococcus

Corynebacterium 1

Finegoldia

Peptoniphilus

Anaerococcus

Ezakiella

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Discussion • Diversity is commonly used as an indicator of ecosystem health • Decreased microbiome diversity in individuals with diabetes

– Potentiate microbiome shift towards pathogenicity infection

• Decreased diversity in the skin microbiome in DS vs. NDS – Skin barrier compromised – Microbiome migration and shift towards pathogenicity

• Potential changes in individuals with diabetes leading to decreased diversity: – Increased skin pH – Advanced glycation end (AGE) products in the skin matrix – Increased levels of skin inflammation – Inadequate immunological response

1. Gardiner, M., Vicaretti, M., Sparks, J., Bansal, S., Bush, S., Liu, M., … Burke, C. M. (2017). A longitudinal study of the diabetic skin and wound microbiome, 2035, 1–23. 2. Yosipovitch G, Tur E, Cohen O, Rusecki Y. 1993. Skin surface pH in intertriginous areas in NIDDM patients. Possible correlation to candidal intertrigo. Diabetes Care 16:560–563 3. Gkogkolou P, Bohm M. 2012. Advanced glycation end products: key players in skin aging? Dermato-Endocrinology 4:259-270 4. Tellechea A, Kafanas A, Leal EC, Tecilazich F, Kuchibhotla S, Auster ME, Kontoes I, Paolino J, Carvalho E, Nabzdyk LP, Veves A. 2013. Increased skin inflammation and blood vessel density in human and experimental diabetes. International Journal of Lower Extremity Wounds 12:4–11 5. Mor A, Berencsi K, Nielsen JS, Rungby J, Friborg S, Brandslund I, Christiansen JS, Vaag A, Beck-Nielsen H, Sorensen HT, Thomsen RW. 2016. Rates of communitybased antibiotic prescriptions and hospital-treated infections in individuals with and without type 2 diabetes: a Danish nationwide

cohort study, 2004–2012. Clinical Infectious Diseases 63:501–511

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Discussion cont. • Current focus on treatment of diabetic foot infections

– Better culture techniques, antibiotics

• Shift in research focus – Explore factors that drive microbial colonization in people

with diabetes – Gut-skin axis – Develop new promicrobia and antimicrobial therapeutics

• Shifting the microbiome of the DS towards the NDS as a preventative treatment of the diabetic foot

Kurečič, M., Rijavec, T., Hribernik, S., Lapanje, A., Kleinschek, K. S., & Maver, U. (2018). Novel electrospun fibers with incorporated commensal bacteria for potential preventive treatment of the diabetic foot. Nanomedicine, 13(13), 1583–1594. https://doi.org/10.2217/nnm-2018-0014

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Limitations and Future Studies

• Limitations: – Pilot study – Small sample size

• Future Studies: – Association/stratification

with other patient parameters

• HbA1c • Glucose levels

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Conclusion

• Diabetes doesn’t appear to affect microbial load of intact skin

• Dysbiosis in the DS is marked by significantly reduced microbial diversity – Potential instigator of diabetic foot infection

• Targeting research to focus on the pathogenic shift – Microbiomes role in diabetic foot infection

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Acknowledgments • Stephanie Wu, DPM, MS, FACFAS • Stefan Green, PhD • Sasha Shafikhani, PhD • Chalen Yang, MS • Jacqueline Ortiz, CCRP