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      Patient genetics is linked to chronic wound microbiome composition and healing

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          Abstract

          The clinical importance of microbiomes to the chronicity of wounds is widely appreciated, yet little is understood about patient-specific processes shaping wound microbiome composition. Here, a two-cohort microbiome-genome wide association study is presented through which patient genomic loci associated with chronic wound microbiome diversity were identified. Further investigation revealed that alternative TLN2 and ZNF521 genotypes explained significant inter-patient variation in relative abundance of two key pathogens, Pseudomonas aeruginosa and Staphylococcus epidermidis. Wound diversity was lowest in Pseudomonas aeruginosa infected wounds, and decreasing wound diversity had a significant negative linear relationship with healing rate. In addition to microbiome characteristics, age, diabetic status, and genetic ancestry all significantly influenced healing. Using structural equation modeling to identify common variance among SNPs, six loci were sufficient to explain 53% of variation in wound microbiome diversity, which was a 10% increase over traditional multiple regression. Focusing on TLN2, genotype at rs8031916 explained expression differences of alternative transcripts that differ in inclusion of important focal adhesion binding domains. Such differences are hypothesized to relate to wound microbiomes and healing through effects on bacterial exploitation of focal adhesions and/or cellular migration. Related, other associated loci were functionally enriched, often with roles in cytoskeletal dynamics. This study, being the first to identify patient genetic determinants for wound microbiomes and healing, implicates genetic variation determining cellular adhesion phenotypes as important drivers of infection type. The identification of predictive biomarkers for chronic wound microbiomes may serve as risk factors and guide treatment by informing patient-specific tendencies of infection.

          Author summary

          Chronic, or non-healing, wounds represent a costly burden to patients, and bacterial infection of wounds is an important driver of chronicity. A variety of bacterial species often occur in chronic wounds, but it is unknown why certain species are observed in some wound infections and not others. In this study, genetic variation of wound clinic patients was compared to the bacteria observed in their infected wounds. Through these comparisons, genetic variation in the TLN2 and ZNF521 genes was found to be associated with both the number of bacteria observed in wounds and the abundance of common pathogens (primarily Pseudomonas aeruginosa and Staphylococcus epidermidis). Moreover, Pseudomonas infected wounds were found to have fewer species present and wounds with fewer species were slower to heal. Furthermore, patient genes associated with microbiomes commonly encode proteins known to be important for cellular structures important to healing and to which bacteria directly interact. Experimental investigation of one such gene, TLN2, identified genotype-dependent differences in the expression of functionally different versions of TLN2 that is hypothesized to shape differences in cellular adhesion structures. Finally, a new statistical approach is presented in which patient biomarkers are used to predict the number of species observed during infection. Overall, our results describe how patient genetic variation influence the types of bacteria likely to infect an individual as well as influence healing.

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          qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots

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            An Economic Evaluation of the Impact, Cost, and Medicare Policy Implications of Chronic Nonhealing Wounds

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              Opportunities and challenges for transcriptome-wide association studies

              Transcriptome-wide association studies (TWAS) integrate genome-wide association studies (GWAS) and gene expression datasets to identify gene-trait associations. In this Perspective, we explore properties of TWAS as a potential approach to prioritize causal genes at GWAS loci, by using simulations and case studies of literature-curated candidate causal genes for schizophrenia, low-density-lipoprotein cholesterol and Crohn’s disease. We explore risk loci where TWAS accurately prioritizes the likely causal gene as well as loci where TWAS prioritizes multiple genes, some likely to be non-causal, owing to sharing of expression quantitative trait loci (eQTL). TWAS is especially prone to spurious prioritization with expression data from non-trait-related tissues or cell types, owing to substantial cross-cell-type variation in expression levels and eQTL strengths. Nonetheless, TWAS prioritizes candidate causal genes more accurately than simple baselines. We suggest best practices for causal-gene prioritization with TWAS and discuss future opportunities for improvement. Our results showcase the strengths and limitations of using eQTL datasets to determine causal genes at GWAS loci.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: Writing – review & editing
                Role: Data curationRole: ResourcesRole: Writing – review & editing
                Role: Formal analysisRole: ValidationRole: Writing – review & editing
                Role: InvestigationRole: Writing – review & editing
                Role: InvestigationRole: Writing – review & editing
                Role: InvestigationRole: VisualizationRole: Writing – review & editing
                Role: MethodologyRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Pathog
                PLoS Pathog
                plos
                plospath
                PLoS Pathogens
                Public Library of Science (San Francisco, CA USA )
                1553-7366
                1553-7374
                18 June 2020
                June 2020
                : 16
                : 6
                : e1008511
                Affiliations
                [1 ] Department of Biological Sciences, Texas Tech University, Lubbock, Texas, United States of America
                [2 ] RTL Genomics, Lubbock, Texas, United States of America
                [3 ] Southwest Regional Wound Care Center, Lubbock, Texas, United States of America
                [4 ] Microbiology, Immunology & Genetics, University of North Texas Health Science Center, Fort Worth, Texas, United States of America
                [5 ] Department of Surgery, Texas Tech University Health Sciences Center, Lubbock, Texas, United States of America
                [6 ] Burn Center of Excellence, Texas Tech University Health Sciences Center, Lubbock, Texas, United States of America
                [7 ] Department of Educational Psychology, Texas Tech University, Lubbock, Texas, United States of America
                [8 ] Optentia Research Focus Area, North West University, Vanderbijlpark, South Africa
                [9 ] Natural Science Research Laboratory, Texas Tech University, Lubbock, Texas, United States of America
                University of North Carolina at Chapel Hil, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-0405-9371
                http://orcid.org/0000-0002-7451-8684
                http://orcid.org/0000-0002-4146-4712
                Article
                PPATHOGENS-D-19-01578
                10.1371/journal.ppat.1008511
                7302439
                32555671
                063af7d5-2c0f-477b-9409-d2f11da6015e
                © 2020 Tipton et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 23 August 2019
                : 1 April 2020
                Page count
                Figures: 5, Tables: 0, Pages: 22
                Funding
                This work was supported by Texas Tech University Office Research and Innovation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbiome
                Biology and Life Sciences
                Genetics
                Genomics
                Microbial Genomics
                Microbiome
                Biology and Life Sciences
                Microbiology
                Microbial Genomics
                Microbiome
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Tissue Repair
                Medicine and Health Sciences
                Physiology
                Physiological Processes
                Tissue Repair
                Biology and Life Sciences
                Ecology
                Ecological Metrics
                Species Diversity
                Ecology and Environmental Sciences
                Ecology
                Ecological Metrics
                Species Diversity
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbial Pathogens
                Bacterial Pathogens
                Pseudomonas Aeruginosa
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Microbial Pathogens
                Bacterial Pathogens
                Pseudomonas Aeruginosa
                Biology and Life Sciences
                Organisms
                Bacteria
                Pseudomonas
                Pseudomonas Aeruginosa
                Biology and Life Sciences
                Genetics
                Genetic Loci
                Biology and Life Sciences
                Organisms
                Bacteria
                Staphylococcus
                Staphylococcus Epidermidis
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbial Pathogens
                Bacterial Pathogens
                Staphylococcus
                Staphylococcus Epidermidis
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Microbial Pathogens
                Bacterial Pathogens
                Staphylococcus
                Staphylococcus Epidermidis
                Biology and Life Sciences
                Genetics
                Molecular Genetics
                Biology and Life Sciences
                Molecular Biology
                Molecular Genetics
                Biology and Life Sciences
                Genetics
                Heredity
                Genetic Mapping
                Variant Genotypes
                Custom metadata
                The scripts used for all statistical analysis are available at https://github.com/genotyper/mbGWAS_wounds. Genotype data are available at GEO study GSE149314.

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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