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Janssen LM, Lemaire F, Sanchez-Calero CL, Huaux F, Ronsmans S, Hoet PH, Ghosh M. External and internal exposome as triggers of biological signalling in systemic sclerosis - A narrative synthesis. J Autoimmun 2025; 150:103342. [PMID: 39643962 DOI: 10.1016/j.jaut.2024.103342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2024] [Revised: 11/20/2024] [Accepted: 11/25/2024] [Indexed: 12/09/2024]
Abstract
Systemic sclerosis (SSc) is an autoimmune chronic connective tissue disorder with a complex pathogenesis and a strong gene-environment interaction. Despite the low prevalence of SSc, with around 100-250 cases per million, the morbidity and mortality are high and disproportionately affecting women. In this context, we review the influence of the external and internal exposome on the "immunome" in SSc. While several studies have addressed aspects of exposure-induced autoimmunity in general, very few have focused on SSc-specific phenotypes. In epidemiological studies, targeted characterization of the external exposome component in relation to SSc has often been limited to a single exposure. Despite the selective characterization of exposure, such studies play an important role in providing evidence that can be used towards reduction of exposure of modifiable factors, and can lead to proper management and prevention of SSc. Additionally, there is an effort towards integration of external exposome data with health data (health records, medical imaging, diagnostic results, etc.), to significantly improve our understanding of the environmental and occupational causes of SSc. A limited number of studies have identified biological processes related to the vascular homeostasis, fibrotic processes and the immune system. The key findings of the current review show advances in our understanding of the SSc disease phenotype and associated biomarkers in relation to specific pathophysiological features, however most often such studies are not supplemented with external exposome data.
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Affiliation(s)
- Lisa Mf Janssen
- Environment and Health, Department of Public Health and Primary Care, KU Leuven, Herestraat 49, 3000 Leuven, Belgium
| | - Frauke Lemaire
- Environment and Health, Department of Public Health and Primary Care, KU Leuven, Herestraat 49, 3000 Leuven, Belgium
| | | | - François Huaux
- Louvain Center for Toxicology and Applied Pharmacology, UCLouvain, Brussels, Belgium
| | - Steven Ronsmans
- Environment and Health, Department of Public Health and Primary Care, KU Leuven, Herestraat 49, 3000 Leuven, Belgium
| | - Peter Hm Hoet
- Environment and Health, Department of Public Health and Primary Care, KU Leuven, Herestraat 49, 3000 Leuven, Belgium.
| | - Manosij Ghosh
- Environment and Health, Department of Public Health and Primary Care, KU Leuven, Herestraat 49, 3000 Leuven, Belgium.
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McGinniss JE, Whiteside SA, Simon-Soro A, Diamond JM, Christie JD, Bushman FD, Collman RG. The lung microbiome in lung transplantation. J Heart Lung Transplant 2021; 40:733-744. [PMID: 34120840 PMCID: PMC8335643 DOI: 10.1016/j.healun.2021.04.014] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 04/13/2021] [Accepted: 04/19/2021] [Indexed: 12/21/2022] Open
Abstract
Culture-independent study of the lower respiratory tract after lung transplantation has enabled an understanding of the microbiome - that is, the collection of bacteria, fungi, and viruses, and their respective gene complement - in this niche. The lung has unique features as a microbial environment, with balanced entry from the upper respiratory tract, clearance, and local replication. There are many pressures impacting the microbiome after transplantation, including donor allograft factors, recipient host factors such as underlying disease and ongoing exposure to the microbe-rich upper respiratory tract, and transplantation-related immunosuppression, antimicrobials, and postsurgical changes. To date, we understand that the lung microbiome after transplant is dysbiotic; that is, it has higher biomass and altered composition compared to a healthy lung. Emerging data suggest that specific microbiome features may be linked to host responses, both immune and non-immune, and clinical outcomes such as chronic lung allograft dysfunction (CLAD), but many questions remain. The goal of this review is to put into context our burgeoning understanding of the lung microbiome in the postlung transplant patient, the interactions between microbiome and host, the role the microbiome may play in post-transplant complications, and critical outstanding research questions.
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Affiliation(s)
- John E McGinniss
- Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Samantha A Whiteside
- Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Aurea Simon-Soro
- Department of Orthodontics and Divisions of Community Oral Health and Pediatric Dentistry, School of Dental Medicine at the University of Pennsylvania
| | - Joshua M Diamond
- Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Jason D Christie
- Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania; Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Fredrick D Bushman
- Department of Microbiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Ronald G Collman
- Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania; Department of Microbiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
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Meier C, Freiburghaus K, Bovet C, Schniering J, Allanore Y, Distler O, Nakas C, Maurer B. Serum metabolites as biomarkers in systemic sclerosis-associated interstitial lung disease. Sci Rep 2020; 10:21912. [PMID: 33318574 PMCID: PMC7736572 DOI: 10.1038/s41598-020-78951-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 12/02/2020] [Indexed: 01/21/2023] Open
Abstract
Systemic sclerosis (SSc) is a severe multi-organ disease with interstitial lung disease (ILD) being the major cause of death. While targeted therapies are emerging, biomarkers for sub-stratifying patients based on individual profiles are lacking. Herein, we investigated how levels of serum metabolites correlated with different stages of SSc and SSc-ILD. Serum samples of patients with SSc without ILD, stable and progressive SSc-ILD as well as of healthy controls (HC) were analysed using liquid targeted tandem mass spectrometry. The best discriminating profile consisted of 4 amino acids (AA) and 3 purine metabolites. L-tyrosine, L-tryptophan, and 1-methyl-adenosine distinguished HC from SSc patients. L-leucine, L-isoleucine, xanthosine, and adenosine monophosphate differentiated between progressing and stable SSc-ILD. In SSc-ILD, both, L-leucine and xanthosine negatively correlated with changes in FVC% predicted. Additionally, xanthosine was negatively correlated with changes in DLco% predicted and positively with the prognostic GAP index. Validation of L-leucine and L-isoleucine by an enzymatic assay confirmed both the sub-stratification of SSc-ILD patients and correlation with lung function and prognosis score. Serum metabolites may have potential as biomarkers for discriminating SSc patients based on the presence and severity of ILD. Confirmation in larger cohorts will be needed to appreciate their value for routine clinical care.
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Affiliation(s)
- C Meier
- Department of Rheumatology, Center of Experimental Rheumatology, University Hospital Zurich, Zurich, Switzerland
| | - K Freiburghaus
- University Institute of Clinical Chemistry, Bern University Hospital, University of Bern, Bern, Switzerland
| | - C Bovet
- University Institute of Clinical Chemistry, Bern University Hospital, University of Bern, Bern, Switzerland
| | - J Schniering
- Department of Rheumatology, Center of Experimental Rheumatology, University Hospital Zurich, Zurich, Switzerland
| | - Y Allanore
- Department of Rheumatology A, Descartes University, APHP, Cochin Hospital, Paris, France
| | - O Distler
- Department of Rheumatology, Center of Experimental Rheumatology, University Hospital Zurich, Zurich, Switzerland
| | - C Nakas
- University Institute of Clinical Chemistry, Bern University Hospital, University of Bern, Bern, Switzerland
- Laboratory of Biometry, University of Thessaly, Volos, Greece
| | - B Maurer
- Department of Rheumatology, Center of Experimental Rheumatology, University Hospital Zurich, Zurich, Switzerland.
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Depner CM, Cogswell DT, Bisesi PJ, Markwald RR, Cruickshank-Quinn C, Quinn K, Melanson EL, Reisdorph N, Wright KP. Developing preliminary blood metabolomics-based biomarkers of insufficient sleep in humans. Sleep 2020; 43:zsz321. [PMID: 31894238 PMCID: PMC7355401 DOI: 10.1093/sleep/zsz321] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Revised: 12/27/2019] [Indexed: 01/20/2023] Open
Abstract
STUDY OBJECTIVE Identify small molecule biomarkers of insufficient sleep using untargeted plasma metabolomics in humans undergoing experimental insufficient sleep. METHODS We conducted a crossover laboratory study where 16 normal-weight participants (eight men; age 22 ± 5 years; body mass index < 25 kg/m2) completed three baseline days (9 hours sleep opportunity per night) followed by 5-day insufficient (5 hours sleep opportunity per night) and adequate (9 hours sleep opportunity per night) sleep conditions. Energy balanced diets were provided during baseline, with ad libitum energy intake provided during the insufficient and adequate sleep conditions. Untargeted plasma metabolomics analyses were performed using blood samples collected every 4 hours across the final 24 hours of each condition. Biomarker models were developed using logistic regression and linear support vector machine (SVM) algorithms. RESULTS The top-performing biomarker model was developed by linear SVM modeling, consisted of 65 compounds, and discriminated insufficient versus adequate sleep with 74% overall accuracy and a Matthew's Correlation Coefficient of 0.39. The compounds in the top-performing biomarker model were associated with ATP Binding Cassette Transporters in Lipid Homeostasis, Phospholipid Metabolic Process, Plasma Lipoprotein Remodeling, and sphingolipid metabolism. CONCLUSION We identified potential metabolomics-based biomarkers of insufficient sleep in humans. Although our current biomarkers require further development and validation using independent cohorts, they have potential to advance our understanding of the negative consequences of insufficient sleep, improve diagnosis of poor sleep health, and could eventually help identify targets for countermeasures designed to mitigate the negative health consequences of insufficient sleep.
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Affiliation(s)
- Christopher M Depner
- Sleep and Chronobiology Laboratory, Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO
| | - Dasha T Cogswell
- Sleep and Chronobiology Laboratory, Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO
| | - Paul J Bisesi
- Sleep and Chronobiology Laboratory, Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO
| | - Rachel R Markwald
- Sleep and Chronobiology Laboratory, Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO
| | | | - Kevin Quinn
- Skaggs School of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Edward L Melanson
- Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO
- Division of Geriatric Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
- Eastern Colorado Veterans Affairs Geriatric Research, Education, and Clinical Center, Denver, CO
| | - Nichole Reisdorph
- Skaggs School of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Kenneth P Wright
- Sleep and Chronobiology Laboratory, Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO
- Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO
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