Trial reportScientific reports2020
Serum metabolites as biomarkers in systemic sclerosis-associated interstitial lung disease.
Trial report in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- Pooled it
- Clinical characteristics and factors associated with progressive pulmonary fibrosis in patients with systemic sclerosis-associated interstitial lung disease.Clinical rheumatology · 2026Article
- On the correlation of tryptophan and its kynurenine pathway metabolites level in blood, saliva and urine in systemic sclerosis patients.Rheumatology international · 2026Article
- Serum acylcarnitine to amide ratio as a predictive biomarker for the progression of pulmonary disease caused byERJ open research · 2026Article
- Multi-omics to study chronic respiratory diseases and viral infections.European respiratory review : an official journal of the European Respiratory Society · 2026Review
- Altered Metabolism in Idiopathic Pulmonary Fibrosis.Journal of cellular physiology · 2025Review
- Diagnostics, Efficacy, and Safety of Immunomodulatory and Anti-Fibrotic Treatment for Interstitial Lung Disease Associated with Systemic Scleroderma (SSc-ILD).Diagnostics (Basel, Switzerland) · 2025Review
- NMR based clinical metabolomics revealed altered lipid and sugar metabolism in systemic sclerosis with implications for diagnosis and therapeutic strategies.Scientific reports · 2025Article
- Metabolomics in systemic sclerosis.Rheumatology international · 2024Review
- The interplay between rheumatic diseases and pulmonary health.Rheumatology international · 2024Review
- Different Kynurenine Pathway Dysregulation in Systemic Sclerosis in Men and Women.International journal of molecular sciences · 2024Article
- Fine mapping-based multi-omics analysis interprets the gut-lung axis function of SGLT2 inhibitors.Frontiers in cellular and infection microbiology · 2024Article
- Gut microbiome and metabolomics in systemic sclerosis: feature, link and mechanisms.Frontiers in immunology · 2024Review
- Metabolic fingerprinting of systemic sclerosis: a systematic review.Frontiers in molecular biosciences · 2023Review
- Plasma Metabolomic Profiling Reveals Four Possibly Disrupted Mechanisms in Systemic Sclerosis.Biomedicines · 2022Article
- Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.