Host genetic factors related to innate immunity, environmental sensing and cellular functions are associated with human skin microbiota

Causal Relationship of Skin Microbiota on Psoriasis: A Mendelian Randomization Study

Objective

Epidemiological investigations have indicated an association between skin microbiota imbalance and psoriasis, however, the causal relationship has not been confirmed through Mendelian randomization (MR). MR employed genetic instrumental variables (IVs) to evaluate the causal relationship between skin microbiota and psoriasis, providing new insights for potential treatments.

Methods

Summary statistics for psoriasis and related traits were available from FinnGen R10 and United Kingdom Biobank (UKB) consortium. The genome-wide association studies (GWAS) on skin microbiota in three skin microenvironments came from two population-based German cohorts. Several selection processes were used to determine the optimal instrumental variables. Five MR methods were performed and different sensitivity analyses approaches yield robustness evidence under different assumptions.

Results

449 SNPs were employed as IVs for 53 bacterial genera, with F-statistics between 20.18 and 42.44, indicating no evidence of weak instrument bias. Bacteroides was associated with psoriasis from UKB in IVW (OR, 95% CI: 0.914, 0.869-0.961; P < 0.001, PB-H = 0.007). The taxon was also associated with psoriasis vulgaris (IVW: OR, 95% CI, 0.918, 0.872-0.967; P = 0.001, P B-H = 0.054) and psoriasis and related disorders (IVW: OR, 95% CI, 0.915, 0.875-0.957; P < 0.001, P B-H = 0.008). Consistent causal estimates were identified in terms of both magnitude and direction, indicating a protective effect of Bacteroides.

Conclusion

The MR study found that Bacteroides in the antecubital fossa may protect against psoriasis, offering genetic proof that skin microbiota helps prevent the condition.

Causal roles of skin and gut microbiota in skin appendage disorders suggested by genetic study

Objectives

There is evidence from observational studies that human microbiota is linked to skin appendage Disorders (SADs). Nevertheless, the causal association between microbiota and SADs is yet to be fully clarified.

Methods

A comprehensive two-sample Mendelian randomization (MR) was first performed to determine the causal effect of skin and gut microbiota on SADs. A total of 294 skin taxa and 211 gut taxa based on phylum, class, order, family, genus, and ASV level information were identified. Summary data of SADs and eight subtypes (acne vulgaris, hidradenitis suppurativa, alopecia areata, rogenic alopecia, rosacea, rhinophyma, seborrhoeic dermatitis, and pilonidal cyst) were obtained from the FinnGen consortium. We performed bidirectional MR to determine whether the skin and gut microbiota are causally associated with multiple SADs. Furthermore, sensitivity analysis was conducted to examine horizontal pleiotropy and heterogeneity.

Results

A total of 65 and 161 causal relationships between genetic liability in the skin and gut microbiota with SADs were identified, respectively. Among these, we separately found 5 and 11 strong causal associations that passed Bonferroni correction in the skin and gut microbiota with SADs. Several skin bacteria, such as Staphylococcus, Streptococcus, and Propionibacterium, were considered associated with multiple SADs. As gut probiotics, Bifidobacteria and Lactobacilli were associated with a protective effect on SAD risk. There was no significant heterogeneity in instrumental variables or horizontal pleiotropy.

Conclusions

Our MR analysis unveiled bidirectional causal relationships between SADs and the gut and skin microbiota, and had the potential to offer novel perspectives on the mechanistic of microbiota-facilitated dermatosis.

Causal effects of skin microbiota on intervertebral disk degeneration, low back pain and sciatica: a two-sample Mendelian randomization study

OBJECTIVE

The purpose of this study is to use two-sample Mendelian randomization (MR) to investigate the causal relationship between skin microbiota, especially Propionibacterium acnes, and intervertebral disc degeneration (IVDD), low back pain (LBP) and sciatica.

METHODS

We conducted a two-sample MR using the aggregated data from the whole genome-wide association studies (GWAS). 150 skin microbiota were derived from the GWAS catalog and IVDD, LBP and sciatica were obtained from the IEU Open GWAS project. Inverse-variance weighted (IVW) was the primary research method, with MR-Egger and Weighted median as supplementary methods. Perform sensitivity analysis and reverse MR analysis on all MR results and use multivariate MR to adjust for confounding factors.

RESULTS

MR revealed five skin microbiota associated with IVDD, four associated with LBP, and two with sciatica. Specifically, P.acnes in sebaceous skin environments were associated with reduced risk of IVDD; IVDD was found to increase the abundance of P.acnes in moist skin. Furthermore, ASV010 [Staphylococcus (unc.)] from dry skin was a risk factor for LBP and sciatica; ASV045 [Acinetobacter (unc.)] from dry skin and Genus Rothia from dry skin exhibited potential protective effects against LBP; ASV065 [Finegoldia (unc.)] from dry skin was a protective factor for IVDD and LBP. ASV054 [Enhydrobacter (unc.)] from moist skin, Genus Bacteroides from dry skin and Genus Kocuria from dry skin were identified as being associated with an increased risk of IVDD. Genus Streptococcus from moist skin was considered to be associated with an increased risk of sciatica.

CONCLUSIONS

This study identified a potential causal relationship between skin microbiota and IVDD, LBP, and sciatica. No evidence suggests skin-derived P.acnes is a risk factor for IVDD, LBP and sciatica. At the same time, IVDD can potentially cause an increase in P.acnes abundance, which supports the contamination theory.

Causal roles of skin microbiota in skin cancers suggested by genetic study

Background

There is evidence from observational studies that skin microbiota is linked to skin cancers. Nevertheless, the causal association between skin microbiota and skin cancers is yet to be fully clarified.

Methods

A bidirectional two-sample Mendelian randomization (MR) was performed to determine the causal relationship between skin microbiota and skin cancers. A total of 294 skin microbial taxa were identified from the first genome-wide association study across three skin microenvironments of two German population cohorts. Summary data of three skin cancers (malignant melanoma, squamous cell carcinoma, and basal cell carcinoma) were obtained from the FinnGen consortium. Moreover, sensitivity analysis examined horizontal pleiotropy and heterogeneity, and microenvironment-based meta-analysis confirmed the reliability of the results.

Results

We identified 65 nominal causalities and 5 strong causal associations between skin microbiota and skin cancers. Among them, the class Bacilli revealed a bidirectional positive relationship with malignant melanoma. The class Betaproteobacteria and class Gammaproteobacteria demonstrated a causal association with an elevated risk of malignant melanoma and basal cell carcinoma, respectively. In the reverse MR analysis, malignant melanoma was associated with a lower abundance of phylum Bacteroidetes. There were no indications of significant heterogeneity in instrumental variables or evidence of horizontal pleiotropy.

Conclusion

Our MR analysis indicated bidirectional causal associations between skin microbiota and skin cancers, and had the potential to offer novel perspectives on the mechanistic of microbiota-facilitated carcinogenesis.

A Mendelian randomization analysis reveals the multifaceted role of the skin microbiota in liver cancer

Background

Hepatocellular carcinoma (HCC, or hepatic cancer, HC) and cholangiocarcinoma (CCA, or hepatic bile duct cancer, HBDC) are two major types of primary liver cancer (PLC). Previous studies have suggested that microbiota can either act as risk factors or preventive factors in PLC. However, no study has reported the relationship between skin microbiota and PLC. Therefore, we conducted a two-sample Mendelian randomization (MR) study to assess the causality between skin microbiota and PLC.

Methods

Data from the genome-wide association study (GWAS) on skin microbiota were collected. The GWAS summary data of GCST90018803 (HBDC) and GCST90018858 (HC) were utilized in the discovery and verification phases, respectively. The inverse variance weighted (IVW) method was utilized as the principal method in our MR study. The MR-Egger intercept test, Cochran's Q-test, MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and leave-one-out analysis were conducted to identify the heterogeneity and pleiotropy.

Results

The results showed that Veillonella (unc.) plays a protective role in HBDC, while the family Neisseriaceae has a positive association with HBDC risk. The class Betaproteobacteria, Veillonella (unc.), and the phylum Bacillota (Firmicutes) play a protective role in HC. Staphylococcus epidermidis, Corynebacterium (unc.), the family Neisseriaceae, and Pasteurellaceae sp. were associated with an increased risk of HC.

Conclusion

This study provided new evidence regarding the association between skin microbiota and PLC, suggesting that skin microbiota plays a role in PLC progression. Skin microbiota could be a novel and effective way for PLC diagnosis and treatment.

The Causal Relationship Between Skin Microbiota and Facial Aging: A Mendelian Randomization Study

BACKGROUND

Facial aging is a complex process influenced by environmental factors, genetics, and lifestyle. The contribution of the skin microbiota to this process remains poorly understood.

METHODS

This two-sample Mendelian randomization (MR) study was performed using genome-wide genotype data from the UK Biobank and previously published studies on skin microbiota. The primary approach for MR analyses included inverse-variance weighting (IVW), MR-Egger regression, simple mode, weighted median, and weighted mode methods. Sensitivity analyses were performed to assess heterogeneity and pleiotropy, and reverse-direction MR analyses were performed to evaluate potential reverse causation.

RESULTS

The MR analysis identified ten skin microbiotas with potential causal relationships with facial aging. Protective skin microbiotas included Genus Finegoldia, ASV011 [Staphylococcus (unc.)], ASV008 [Staphylococcus (unc.)], phylum Firmicutes, Family Rhodobacteraceae, and ASV021 [Micrococcus (unc.)], which were negatively associated with facial aging. Conversely, Order Pseudomonadales, Family Moraxellaceae, ASV039 [Acinetobacter (unc.)], and phylum Bacteroidetes were positively associated with facial aging, indicating a risk factor for accelerated aging. Sensitivity analyses confirmed the robustness of these findings, and reverse-direction MR analyses did not suggest any reverse causation.

CONCLUSION

This study identified specific skin microbial that may influence facial aging and offered new insights into the rejuvenation strategies.

NO LEVEL ASSIGNED

This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Genome-wide association study identifies host genetic variants influencing oral microbiota diversity and metabolic health

The microbial communities of the oral cavity are important elements of oral and systemic health. With emerging evidence highlighting the heritability of oral bacterial microbiota, this study aimed to identify host genome variants that influence oral microbial traits. Using data from 16S rRNA gene amplicon sequencing, we performed genome-wide association studies with univariate and multivariate traits of the salivary microbiota from 610 unrelated adults from the Danish ADDITION-PRO cohort. We identified six single nucleotide polymorphisms (SNPs) in human genomes that showed associations with abundance of bacterial taxa at different taxonomical tiers (P < 5 × 10-8). Notably, SNP rs17793860 surpassed our study-wide significance threshold (P < 1.19 × 10-9). Additionally, rs4530093 was linked to bacterial beta diversity (P < 5 × 10-8). Out of these seven SNPs identified, six exerted effects on metabolic traits, including glycated hemoglobin A1c, triglyceride and high-density lipoprotein cholesterol levels, the risk of type 2 diabetes and stroke. Our findings highlight the impact of specific host SNPs on the composition and diversity of the oral bacterial community. Importantly, our results indicate an intricate interplay between host genetics, the oral microbiota, and metabolic health. We emphasize the need for integrative approaches considering genetic, microbial, and metabolic factors.

Genetic and Immunological Pathogenesis of Atopic Dermatitis

Type 2 immune-mediated diseases give a clear answer to the issue of nature (genetics) versus nurture (environment). Both genetics and environment play vital complementary roles in the development of atopic dermatitis (AD). As a key component of the atopic march, AD demonstrates the interactive nature of genetic and environmental contributions to atopy. From sequence variants in the epithelial barrier gene encoding FLG to the hygiene hypothesis, AD combines a broad array of contributions into a single syndrome. This review will focus on the genetic contribution to AD and where genetics facilitates the elicitation or enhancement of AD pathogenesis.

A genome-wide association study reveals the relationship between human genetic variation and the nasal microbiome

The nasal cavity harbors diverse microbiota that contributes to human health and respiratory diseases. However, whether and to what extent the host genome shapes the nasal microbiome remains largely unknown. Here, by dissecting the human genome and nasal metagenome data from 1401 healthy individuals, we demonstrated that the top three host genetic principal components strongly correlated with the nasal microbiota diversity and composition. The genetic association analyses identified 63 genome-wide significant loci affecting the nasal microbial taxa and functions, of which 2 loci reached study-wide significance (p < 1.7 × 10-10): rs73268759 within CAMK2A associated with genus Actinomyces and family Actinomycetaceae; and rs35211877 near POM121L12 with Gemella asaccharolytica. In addition to respiratory-related diseases, the associated loci are mainly implicated in cardiometabolic or neuropsychiatric diseases. Functional analysis showed the associated genes were most significantly expressed in the nasal airway epithelium tissue and enriched in the calcium signaling and hippo signaling pathway. Further observational correlation and Mendelian randomization analyses consistently suggested the causal effects of Serratia grimesii and Yokenella regensburgei on cardiometabolic biomarkers (cystine, glutamic acid, and creatine). This study suggested that the host genome plays an important role in shaping the nasal microbiome.

From hype to hope: Considerations in conducting robust microbiome science

Microbiome science has been one of the most exciting and rapidly evolving research fields in the past two decades. Breakthroughs in technologies including DNA sequencing have meant that the trillions of microbes (particularly bacteria) inhabiting human biological niches (particularly the gut) can be profiled and analysed in exquisite detail. This microbiome profiling has profound impacts across many fields of research, especially biomedical science, with implications for how we understand and ultimately treat a wide range of human disorders. However, like many great scientific frontiers in human history, the pioneering nature of microbiome research comes with a multitude of challenges and potential pitfalls. These include the reproducibility and robustness of microbiome science, especially in its applications to human health outcomes. In this article, we address the enormous promise of microbiome science and its many challenges, proposing constructive solutions to enhance the reproducibility and robustness of research in this nascent field. The optimisation of microbiome science spans research design, implementation and analysis, and we discuss specific aspects such as the importance of ecological principals and functionality, challenges with microbiome-modulating therapies and the consideration of confounding, alternative options for microbiome sequencing, and the potential of machine learning and computational science to advance the field. The power of microbiome science promises to revolutionise our understanding of many diseases and provide new approaches to prevention, early diagnosis, and treatment.

Genetically predicted levels of circulating cytokines and the risk of six immune skin diseases: a two-sample Mendelian randomization study

Background

Circulating cytokines play a crucial role in the onset and progression of immune skin diseases. However, the causal relationships and the direction of causal effects require further investigation.

Methods

Two-sample Mendelian randomization (MR) analyses were conducted to assess the causal relationships between 41 circulating cytokines and six immune skin diseases including alopecia areata, chloasma, hidradenitis suppurativa (HS), lichen planus (LP), seborrheic dermatitis, and urticaria, using summary statistics from genome-wide association studies. Reverse MR analyses was performed to test for the reverse causation. Pleiotropy and heterogeneity tests were conducted to assess the robustness of the findings.

Results

Twelve unique cytokines showed a suggestive causal relationship with the risk of six immune skin diseases. Among them, the causal effects between 9 unique cytokines and immune skin diseases have strong statistical power. Additionally, the concentrations of six cytokines might be influenced by LP and urticaria. After Bonferroni correction, the following associations remained significant: the causal effect of beta-nerve growth factor on HS (odds ratio [OR] = 1.634, 95% confidence interval [CI] = 1.226-2.177, p = 7.97e-04), interleukin (IL)-6 on LP (OR = 0.615, 95% CI = 0.481-0.786, p = 1.04e-04), IL-4 on LP (OR = 1.099. 95% CI = 1.020-1.184, p = 1.26e-02), and IL-2 on urticaria (OR = 0.712, 95% CI = 0.531-0.955, p = 2.33e-02).

Conclusion

This study provides novel perspectives on the relationship between circulating cytokines and immune skin diseases, potentially providing valuable insights into their etiology, diagnostic approaches, and treatment.

Disease modification in inflammatory skin disorders: opportunities and challenges

Progress in understanding of the mechanisms underlying chronic inflammatory skin disorders, such as atopic dermatitis and psoriasis vulgaris, has led to new treatment options with the primary goal of alleviating symptoms. In addition, this knowledge has the potential to inform on new strategies aimed at inducing deep and therapy-free remission, that is, disease modification, potentially impacting on associated comorbidities. However, to reach this goal, key areas require further exploration, including the definitions of disease modification and disease activity index, further understanding of disease mechanisms and systemic spillover effects, potential windows of opportunity, biomarkers for patient stratification and successful intervention, as well as appropriate study design. This Perspective article assesses the opportunities and challenges in the discovery and development of disease-modifying therapies for chronic inflammatory skin disorders.

Dupilumab but not cyclosporine treatment shifts the microbiome toward a healthy skin flora in patients with moderate-to-severe atopic dermatitis

BACKGROUND

Atopic dermatitis (AD) patients display an altered skin microbiome which may not only be an indicator but also a driver of inflammation. We aimed to investigate associations among AD patients' skin microbiome, clinical data, and response to systemic therapy in patients of the TREATgermany registry.

METHODS

Skin swabs of 157 patients were profiled with 16S rRNA gene amplicon sequencing before and after 3 months of treatment with dupilumab or cyclosporine. For comparison, 16s microbiome data from 258 population-based healthy controls were used. Disease severity was assessed using established instruments such as the Eczema Area and Severity Index (EASI).

RESULTS

We confirmed the previously shown correlation of Staphylococcus aureus abundance and bacterial alpha diversity with AD severity as measured by EASI. Therapy with Dupilumab shifted the bacterial community toward the pattern seen in healthy controls. The relative abundance of Staphylococci and in particular S. aureus significantly decreased on both lesional and non-lesional skin, whereas the abundance of Staphylococcus hominis increased. These changes were largely independent from the degree of clinical improvement and were not observed for cyclosporine.

CONCLUSIONS

Systemic treatment with dupilumab but not cyclosporine tends to restore a healthy skin microbiome largely independent of the clinical response indicating potential effects of IL-4RA blockade on the microbiome.

How longitudinal data can contribute to our understanding of host genetic effects on the gut microbiome

A key component of microbiome research is understanding the role of host genetic influence on gut microbial composition. However, it can be difficult to link host genetics with gut microbial composition because host genetic similarity and environmental similarity are often correlated. Longitudinal microbiome data can supplement our understanding of the relative role of genetic processes in the microbiome. These data can reveal environmentally contingent host genetic effects, both in terms of controlling for environmental differences and in comparing how genetic effects differ by environment. Here, we explore four research areas where longitudinal data could lend new insights into host genetic effects on the microbiome: microbial heritability, microbial plasticity, microbial stability, and host and microbiome population genetics. We conclude with a discussion of methodological considerations for future studies.