Multi-omics analysis to decipher the molecular link between chronic exposure to pollution and human skin dysfunction

Chronic Exposure to Petroleum-Derived Hydrocarbons Alters Human Skin Microbiome and Metabolome Profiles: A Pilot Study

Petroleum-derived substances, like industrial oils and grease, are ubiquitous in our daily lives. Comprised of petroleum hydrocarbons (PH), these substances can come into contact with our skin, potentially causing molecular disruptions and contributing to the development of chronic disease. In this pilot study, we employed mass spectrometry-based untargeted metabolomics and 16S rRNA gene sequencing analyses to explore these effects. Superficial skin samples were collected from subjects with and without chronic dermal exposure to PH at two anatomical sites: the fingers (referred to as the hand) and arms (serving as an intersubject variability control). Exposed hands exhibited higher bacterial diversity (Shannon and Simpson indices) and an enrichment of oil-degrading bacteria (ODB), including Dietzia, Paracoccus, and Kocuria. Functional prediction suggested enriched pathways associated with PH degradation in exposed hands vs non-exposed hands, while no differences were observed when comparing the arms. Furthermore, carboxylic acids, glycerophospholipids, organooxygen compounds, phenol ethers, among others, were found to be more abundant in exposed hands. We observed positive correlations among multiple ODB and xenobiotics, suggesting a chemical remodeling of the skin favorable for ODB thriving. Overall, our study offers insights into the complex dysregulation of bacterial communities and the chemical milieu induced by chronic dermal exposure to PH.

Skin Surface Sebum Analysis by ESI-MS

The skin surface is an important sample source that the metabolomics community has only just begun to explore. Alterations in sebum, the lipid-rich mixture coating the skin surface, correlate with age, sex, ethnicity, diet, exercise, and disease state, making the skin surface an ideal sample source for future noninvasive biomarker exploration, disease diagnosis, and forensic investigation. The potential of sebum sampling has been realized primarily via electrospray ionization mass spectrometry (ESI-MS), an ideal approach to assess the skin surface lipidome. However, a better understanding of sebum collection and subsequent ESI-MS analysis is required before skin surface sampling can be implemented in routine analyses. Challenges include ambiguity in definitive lipid identification, inherent biological variability in sebum production, and methodological, technical variability in analyses. To overcome these obstacles, avoid common pitfalls, and achieve reproducible, robust outcomes, every portion of the workflow-from sample collection to data analysis-should be carefully considered with the specific application in mind. This review details current practices in sebum sampling, sample preparation, ESI-MS data acquisition, and data analysis, and it provides important considerations in acquiring meaningful lipidomic datasets from the skin surface. Forensic researchers investigating sebum as a means for suspect elimination in lieu of adequate fingerprint ridge detail or database matches, as well as clinical researchers interested in noninvasive biomarker exploration, disease diagnosis, and treatment monitoring, can use this review as a guide for developing methods of best-practice.

Facial Skin Microbiome Composition and Functional Shift with Aging

The change in the skin microbiome as individuals age is only partially known. To provide a better understanding of the impact of aging, whole-genome sequencing analysis was performed on facial skin swabs of 100 healthy female Caucasian volunteers grouped by age and wrinkle grade. Volunteers' metadata were collected through questionnaires and non-invasive biophysical measurements. A simple model and a biological statistical model were used to show the difference in skin microbiota composition between the two age groups. Taxonomic and non-metric multidimensional scaling analysis showed that the skin microbiome was more diverse in the older group (≥55 yo). There was also a significant decrease in Actinobacteria, namely in Cutibacterium acnes, and an increase in Corynebacterium kroppenstedtii. Some Streptococcus and Staphylococcus species belonging to the Firmicutes phylum and species belonging to the Proteobacteria phylum increased. In the 18-35 yo younger group, the microbiome was characterized by a significantly higher proportion of Cutibacterium acnes and Lactobacillus, most strikingly, Lactobacillus crispatus. The functional analysis using GO terms revealed that the young group has a higher significant expression of genes involved in biological and metabolic processes and in innate skin microbiome protection. The better comprehension of age-related impacts observed will later support the investigation of skin microbiome implications in antiaging protection.

A multi-study analysis enables identification of potential microbial features associated with skin aging signs

Introduction: During adulthood, the skin microbiota can be relatively stable if environmental conditions are also stable, yet physiological changes of the skin with age may affect the skin microbiome and its function. The microbiome is an important factor to consider in aging since it constitutes most of the genes that are expressed on the human body. However, severity of specific aging signs (one of the parameters used to measure "apparent" age) and skin surface quality (e.g., texture, hydration, pH, sebum, etc.) may not be indicative of chronological age. For example, older individuals can have young looking skin (young apparent age) and young individuals can be of older apparent age. Methods: Here we aim to identify microbial taxa of interest associated to skin quality/aging signs using a multi-study analysis of 13 microbiome datasets consisting of 16S rRNA amplicon sequence data and paired skin clinical data from the face. Results: We show that there is a negative relationship between microbiome diversity and transepidermal water loss, and a positive association between microbiome diversity and age. Aligned with a tight link between age and wrinkles, we report a global positive association between microbiome diversity and Crow's feet wrinkles, but with this relationship varying significantly by sub-study. Finally, we identify taxa potentially associated with wrinkles, TEWL and corneometer measures. Discussion: These findings represent a key step towards understanding the implication of the skin microbiota in skin aging signs.

A cross-sectional epidemiological study conducted in Argentina to evaluate the impact of the exposome on skin aging

BACKGROUND

Skin aging is a gradual cumulative process that may be accelerated by various exposome factors.

AIMS

To investigate associations between exposome factors and facial skin aging in 11 locations in Argentina.

PATIENTS/METHODS

An observational, cross-sectional study with assessments by exposome questionnaire, Glogau photoaging classification from I to IV, AI-based algorithm analysis of 7 skin aging signs, and SCINEXA score.

RESULTS

Of 1346 participants, most were women (82%), aged 31-50 years (62%), of skin phototype III (52%), and living in urban areas (94%). The Glogau skin age was higher than the chronological age for 28% of overall participants, 36% of men, and 45% of participants from Ciudad de Buenos Aires versus 12% from Jujuy (p < 0.001). Being male (OR = 1.59; 95% CI 1.18-2.13), exposed to agrochemicals (OR = 1.59: 95% CI 1.01-2.51), of lower socioeconomic levels (OR = 2.06; 95% CI 1.32-3.21) and doing outdoor physical activity (OR = 1.33; 95% CI 1.00-1.76) increased the risk for premature aging. Odds decreased with high daily intake of water (OR = 0.76; 95% CI 0.59-0.97), daily dermocosmetic use (moisturizers [OR = 0.72; 95% CI 0.55-0.94], cleansers [OR = 0.53; CI 95% 0.42-0.67], retinoids [OR = 0.61; 95% CI 0.39-0.95]), and antiaging treatments (OR = 0.74; 95% CI 0.57-0.97).

CONCLUSIONS

Some exposome factors increased the risk for premature skin aging (physical outdoor activity, exposure to agrochemicals), while others were protective factors (high water intake, antiaging treatments, use of dermocosmetics). Locations with higher pollution levels had more premature skin aging.

A Catastrophic Biodiversity Loss in the Environment Is Being Replicated on the Skin Microbiome: Is This a Major Contributor to the Chronic Disease Epidemic?

There has been a catastrophic loss of biodiversity in ecosystems across the world. A similar crisis has been observed in the human gut microbiome, which has been linked to "all human diseases affecting westernized countries". This is of great importance because chronic diseases are the leading cause of death worldwide and make up 90% of America's healthcare costs. Disease development is complex and multifactorial, but there is one part of the body's interlinked ecosystem that is often overlooked in discussions about whole-body health, and that is the skin microbiome. This is despite it being a crucial part of the immune, endocrine, and nervous systems and being continuously exposed to environmental stressors. Here we show that a parallel biodiversity loss of 30-84% has occurred on the skin of people in the developed world compared to our ancestors. Research has shown that dysbiosis of the skin microbiome has been linked to many common skin diseases and, more recently, that it could even play an active role in the development of a growing number of whole-body health problems, such as food allergies, asthma, cardiovascular diseases, and Parkinson's, traditionally thought unrelated to the skin. Damaged skin is now known to induce systemic inflammation, which is involved in many chronic diseases. We highlight that biodiversity loss is not only a common finding in dysbiotic ecosystems but also a type of dysbiosis. As a result, we make the case that biodiversity loss in the skin microbiome is a major contributor to the chronic disease epidemic. The link between biodiversity loss and dysbiosis forms the basis of this paper's focus on the subject. The key to understanding why biodiversity loss creates an unhealthy system could be highlighted by complex physics. We introduce entropy to help understand why biodiversity has been linked with ecosystem health and stability. Meanwhile, we also introduce ecosystems as being governed by "non-linear physics" principles-including chaos theory-which suggests that every individual part of any system is intrinsically linked and implies any disruption to a small part of the system (skin) could have a significant and unknown effect on overall system health (whole-body health). Recognizing the link between ecosystem health and human health allows us to understand how crucial it could be to maintain biodiversity across systems everywhere, from the macro-environment we inhabit right down to our body's microbiome. Further, in-depth research is needed so we can aid in the treatment of chronic diseases and potentially change how we think about our health. With millions of people currently suffering, research to help mitigate the crisis is of vital importance.

Multi-omics approaches in psychoneuroimmunology and health research: Conceptual considerations and methodological recommendations

The field of psychoneuroimmunology (PNI) has grown substantially in both relevance and prominence over the past 40 years. Notwithstanding its impressive trajectory, a majority of PNI studies are still based on a relatively small number of analytes. To advance this work, we suggest that PNI, and health research in general, can benefit greatly from adopting a multi-omics approach, which involves integrating data across multiple biological levels (e.g., the genome, proteome, transcriptome, metabolome, lipidome, and microbiome/metagenome) to more comprehensively profile biological functions and relate these profiles to clinical and behavioral outcomes. To assist investigators in this endeavor, we provide an overview of multi-omics research, highlight recent landmark multi-omics studies investigating human health and disease risk, and discuss how multi-omics can be applied to better elucidate links between psychological, nervous system, and immune system activity. In doing so, we describe how to design high-quality multi-omics studies, decide which biological samples (e.g., blood, stool, urine, saliva, solid tissue) are most relevant, incorporate behavioral and wearable sensing data into multi-omics research, and understand key data quality, integration, analysis, and interpretation issues. PNI researchers are addressing some of the most interesting and important questions at the intersection of psychology, neuroscience, and immunology. Applying a multi-omics approach to this work will greatly expand the horizon of what is possible in PNI and has the potential to revolutionize our understanding of mind-body medicine.

Does mask wearing affect skin health? An untargeted skin metabolomics study

Wearing masks is used as an effective way to prevent the spread of viruses. However, the effect of wearing masks on skin health requires further assessment. In this study, a non-invasive D-squame sampling method coupled with an untargeted metabolomics analysis by liquid chromatography high-resolution mass spectrometry was developed to identify the changes in the skin metabolome caused by wearing masks. D-squame method was found to have advantages over the commonly used sterile gauze method, especially for the lipids and lipid-like molecules. A total of 356 skin metabolites were putatively identified from the stratum corneum of 10 volunteers, and 17 differential metabolites were significantly downregulated after wearing surgical masks or N95 respirators. The downregulation of metabolites such as phosphatidylethanolamine and sphingomyelin might be related to hypoxia or increased skin moisture caused by wearing masks. Changes in skin metabolomics indicated a potential risk of skin barrier disruption and skin inflammation. Intermittent removal of the masks can effectively alleviate changes in the skin metabolome.

Skin microbiome differentiates into distinct cutotypes with unique metabolic functions upon exposure to polycyclic aromatic hydrocarbons

BACKGROUND

The effects of air pollutants, particularly polycyclic aromatic hydrocarbons (PAHs), on the skin microbiome remain poorly understood. Thus, to better understand the interplay between air pollutants, microbiomes, and skin conditions, we applied metagenomics and metabolomics to analyze the effects of PAHs in air pollution on the skin microbiomes of over 120 subjects residing in two cities in China with different levels of air pollution.

RESULTS

The skin microbiomes differentiated into two cutotypes (termed 1 and 2) with distinct taxonomic, functional, resistome, and metabolite compositions as well as skin phenotypes that transcended geography and host factors. High PAH exposure was linked to dry skin and cutotype 2, which was enriched with species with potential biodegradation functions and had reduced correlation network structure integrity. The positive correlations identified between dominant taxa, key functional genes, and metabolites in the arginine biosynthesis pathway in cutotype 1 suggest that arginine from bacteria contributes to the synthesis of filaggrin-derived natural moisturizing factors (NMFs), which provide hydration for the skin, and could explain the normal skin phenotype observed. In contrast, no correlation with the arginine biosynthesis pathway was observed in cutotype 2, which indicates the limited hydration functions of NMFs and explains the observed dry skin phenotype. In addition to dryness, skin associated with cutotype 2 appeared prone to other adverse conditions such as inflammation.

CONCLUSIONS

This study revealed the roles of PAHs in driving skin microbiome differentiation into cutotypes that vary extensively in taxonomy and metabolic functions and may subsequently lead to variations in skin-microbe interactions that affect host skin health. An improved understanding of the roles of microbiomes on skin exposed to air pollutants can aid the development of strategies that harness microbes to prevent undesirable skin conditions. Video Abstract.

A State-of-the-Science Review on High-Resolution Metabolomics Application in Air Pollution Health Research: Current Progress, Analytical Challenges, and Recommendations for Future Direction

BACKGROUND

Understanding the mechanistic basis of air pollution toxicity is dependent on accurately characterizing both exposure and biological responses. Untargeted metabolomics, an analysis of small-molecule metabolic phenotypes, may offer improved estimation of exposures and corresponding health responses to complex environmental mixtures such as air pollution. The field remains nascent, however, with questions concerning the coherence and generalizability of findings across studies, study designs and analytical platforms.

OBJECTIVES

We aimed to review the state of air pollution research from studies using untargeted high-resolution metabolomics (HRM), highlight the areas of concordance and dissimilarity in methodological approaches and reported findings, and discuss a path forward for future use of this analytical platform in air pollution research.

METHODS

We conducted a state-of-the-science review to a) summarize recent research of air pollution studies using untargeted metabolomics and b) identify gaps in the peer-reviewed literature and opportunities for addressing these gaps in future designs. We screened articles published within Pubmed and Web of Science between 1 January 2005 and 31 March 2022. Two reviewers independently screened 2,065 abstracts, with discrepancies resolved by a third reviewer.

RESULTS

We identified 47 articles that applied untargeted metabolomics on serum, plasma, whole blood, urine, saliva, or other biospecimens to investigate the impact of air pollution exposures on the human metabolome. Eight hundred sixteen unique features confirmed with level-1 or -2 evidence were reported to be associated with at least one or more air pollutants. Hypoxanthine, histidine, serine, aspartate, and glutamate were among the 35 metabolites consistently exhibiting associations with multiple air pollutants in at least 5 independent studies. Oxidative stress and inflammation-related pathways-including glycerophospholipid metabolism, pyrimidine metabolism, methionine and cysteine metabolism, tyrosine metabolism, and tryptophan metabolism-were the most commonly perturbed pathways reported in > 70 % of studies. More than 80% of the reported features were not chemically annotated, limiting the interpretability and generalizability of the findings.

CONCLUSIONS

Numerous investigations have demonstrated the feasibility of using untargeted metabolomics as a platform linking exposure to internal dose and biological response. Our review of the 47 existing untargeted HRM-air pollution studies points to an underlying coherence and consistency across a range of sample analytical quantitation methods, extraction algorithms, and statistical modeling approaches. Future directions should focus on validation of these findings via hypothesis-driven protocols and technical advances in metabolic annotation and quantification. https://doi.org/10.1289/EHP11851.

Characterization of different contaminants and current knowledge for defining chemical mixtures in human milk: A review

Hundreds of xenobiotics, with very diverse origins, have been detected in human milk, including contaminants of emerging concern, personal care products and other current-use substances reflecting lifestyle. The routes of exposure to these chemicals include dermal absorption, ingestion and inhalation. Specific families of chemicals are dominant among human milk monitoring studies (e.g., organochlorine pesticides, bisphenol A, dioxins), even though other understudied families may be equally toxicologically relevant (e.g., food-processing chemicals, current-use plasticizers and flame retardants, mycotoxins). Importantly, the lack of reliable human milk monitoring data for some individual chemicals and, especially, for complex mixtures, is a major factor hindering risk assessment. Non-targeted screening can be used as an effective tool to identify unknown contaminants of concern in human milk. This approach, in combination with novel methods to conduct risk assessments on the chemical mixtures detected in human milk, will assist in elucidating exposures that may have adverse effects on the development of breastfeeding infants.

A cross-sectional study of Chinese women facial skin status with environmental factors and individual lifestyles

Geographical, environmental and pollution conditions affect facial skin health, but their effects on skin appearance have not been elucidated. This study aimed to describe the skin barrier and skin tone characteristics of Chinese subjects according to lifestyle and environmental conditions using in vitro measurements. In total, 1092 women aged 22-42 years were recruited from 7 representative Chinese cities. Eight skin parameters (hydration, sebum, pH, transdermal water loss, individual type angle, melanin index, erythema index, yellowness) were measured using noninvasive instruments; individual lifestyle data were also collected. Data on four meteorological factors (air temperature, relative humidity, sunshine duration, wind speed) and seven air pollution indicators (air quality index, fine particulate matter, breathable particulate matter, sulfur dioxide, nitrogen dioxide, carbon monoxide and ozone) were collected in each city from the China Meteorological Administration. Facial skin characteristics differed significantly between cities. Facial skin barrier characteristics and skin tones showed regional differences, with a better skin barrier associated with the western region, as indicated by high skin hydration and sebum secretion and a low pH value. According to the value of transdermal water loss, lighter and darker skin tones were found in the western and southern regions, respectively. Environmental conditions affected facial skin status. Air pollution induced facial skin issues, with fine particulate matter and nitrogen dioxide contributing the most. Individual lifestyles affected the facial skin barrier and skin tone.

An Overview of the Latest Metabolomics Studies on Atopic Eczema with New Directions for Study

Atopic eczema (AE) is an inflammatory skin disorder affecting approximately 20% of children worldwide and early onset can lead to asthma and allergies. Currently, the mechanisms of the disease are not fully understood. Metabolomics, the analysis of small molecules in the skin produced by the host and microbes, opens a window to observe the mechanisms of the disease which then may lead to new drug targets for AE treatment. Here, we review the latest advances in AE metabolomics, highlighting both the lipid and non-lipid molecules, along with reviewing the metabolites currently known to reside in the skin.

Current Knowledge in Skin Metabolomics: Updates from Literature Review

Metabolomic profiling is an emerging field consisting of the measurement of metabolites in a biological system. Since metabolites can vary in relation to different stimuli, specific metabolic patterns can be closely related to a pathological process. In the dermatological setting, skin metabolomics can provide useful biomarkers for the diagnosis, prognosis, and therapy of cutaneous disorders. The main goal of the present review is to present a comprehensive overview of the published studies in skin metabolomics. A search for journal articles focused on skin metabolomics was conducted on the MEDLINE, EMBASE, Cochrane, and Scopus electronic databases. Only research articles with electronically available English full text were taken into consideration. Studies specifically focused on cutaneous microbiomes were also excluded from the present search. A total of 97 papers matched all the research criteria and were therefore considered for the present work. Most of the publications were focused on inflammatory dermatoses and immune-mediated cutaneous disorders. Skin oncology also turned out to be a relevant field in metabolomic research. Only a few papers were focused on infectious diseases and rarer genetic disorders. All the major metabolomic alterations published so far in the dermatological setting are described extensively in this review.

Advances in Microbiome-Derived Solutions and Methodologies Are Founding a New Era in Skin Health and Care

The microbiome, as a community of microorganisms and their structural elements, genomes, metabolites/signal molecules, has been shown to play an important role in human health, with significant beneficial applications for gut health. Skin microbiome has emerged as a new field with high potential to develop disruptive solutions to manage skin health and disease. Despite an incomplete toolbox for skin microbiome analyses, much progress has been made towards functional dissection of microbiomes and host-microbiome interactions. A standardized and robust investigation of the skin microbiome is necessary to provide accurate microbial information and set the base for a successful translation of innovations in the dermo-cosmetic field. This review provides an overview of how the landscape of skin microbiome research has evolved from method development (multi-omics/data-based analytical approaches) to the discovery and development of novel microbiome-derived ingredients. Moreover, it provides a summary of the latest findings on interactions between the microbiomes (gut and skin) and skin health/disease. Solutions derived from these two paths are used to develop novel microbiome-based ingredients or solutions acting on skin homeostasis are proposed. The most promising skin and gut-derived microbiome interventional strategies are presented, along with regulatory, safety, industrial, and technical challenges related to a successful translation of these microbiome-based concepts/technologies in the dermo-cosmetic industry.