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Multi-Omics Profiling Reveals Sex-Stratified Biomarkers Predicting Chronicity in Pediatric Primary Immune Thrombocytopenia

ABSTRACT:

Primary immune thrombocytopenia (ITP) is recognized as an acquired autoimmune hemorrhagic disorder distinguished by diminished platelet counts. The efficacy of a sex-stratified multi-omics integrative analytical strategy for forecasting pediatric ITP chronicity was proposed and validated in this study. This investigation was designed as a non-interventional, prospective observational cohort. Plasma samples were collected from 67 children initially diagnosed with ITP along with 40 healthy controls. After a minimum of one year of regular follow-up, participants were classified according to sex and disease progression. Male cohorts consisted of chronic ITP, non-chronic ITP, and healthy control; female cohorts comprised chronic ITP, non-chronic ITP, and healthy control. From each subgroup, three peripheral blood samples were randomly chosen for proteomic and metabolomic profiling. The biomarkers exhibiting differential expression in both ITP vs. healthy control and chronic vs. non-chronic comparisons within each sex group were identified, while demonstrating sex-specific differential expression model. Integrative omics were analyzed for correlations using Pearson’s coefficient (threshold: |r| > 0.8, p< 0.05). Subsequently, candidate biomarkers were validated within a verification cohort through enzyme-linked immunosorbent assay. Independent predictive variables were further established utilizing multivariate logistic regression analysis. Additionally, the robustness of the predictive model was assessed by receiver operating characteristic curve analysis, calibration curves, and decision curve analysis.The sex-associated biomarkers related to chronicity progression were as follows: in males, intercellular adhesion molecule-1(ICAM-1) and biopterin; in females, actin, alpha 2, smooth muscle (ACTA-2) and N6-acetyl-L-lysine. ICAM-1 and N6-acetyl-L-lysine were identified as statistically significant factors associated with disease chronicity in males and females, respectively. Cross-gender applications of these biomarkers revealed limited predictive value. Furthermore, the receiver operating characteristics curves, calibration curves, and clinical decision curve analysis demonstrated good predictive efﬁcacy of these validated biomarkers.This study has provided novel objective biological indicators for the early prediction of ITP chronicity in patients of different sexes, establishing new evidence for early personalized diagnosis and treatment. The underlying mechanisms of interaction between these biomarkers, sex differences, and ITP chronicity progression warrant further investigation.

INSTRUMENT(S): Liquid Chromatography MS - positive - HILIC, Liquid Chromatography MS - negative - HILIC

PROVIDER: MTBLS12920 | MetaboLights | 2025-09-01

REPOSITORIES: MetaboLights

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			Action	DRS
	a_MTBLS12920_LC-MS_negative_hilic_metabolite_profiling.txt	Txt
	a_MTBLS12920_LC-MS_positive_hilic_metabolite_profiling.txt	Txt
	i_Investigation.txt	Txt
	m_MTBLS12920_LC-MS_negative_hilic_metabolite_profiling_v2_maf.tsv	Tabular
	m_MTBLS12920_LC-MS_positive_hilic_metabolite_profiling_v2_maf.tsv	Tabular

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Project description:Bound amino compounds (amino acid and amino sugar polymers) comprise a significant proportion (~40%) of soil organic nitrogen and therefore represent an essential source of nitrogen for plant and microbial nutrition. The analysis of their content and isotope enrichment still represents a significant challenge due to the low isotope enrichment levels reached under near-native soil conditions and the lack of isotopically labeled standards for some key amino compounds. In this study, we used both a 13C-labeled and an unlabeled amino acid mixture to establish isotope calibration curves for 16 amino compounds, using the 6-Aminoquinolyl-N-hydroxysccinimidyl carbamate (AQC) derivatization method and ultra-high-performance liquid chromatography with high-resolution Orbitrap mass spectrometry (UPLC-Orbitrap MS). Molecular ions of AQC-derivatives for all standard amino compounds were identified at the expected m/z values of the respective isotopologues. The isotope calibration curves exhibited excellent linear fits across the whole 13C enrichment range and polynomial fits in the low 13C enrichment range (R2 > 0.990). However, the polynomial fitting terms differed between individual amino acids. Subsequently, we developed equations to relate the calibrated regression terms to the physicochemical properties of the respective amino acids, here mainly the ratio of amino compound-C atoms to total C atoms in AQC-amino compound derivatives. Based on these regressions, we could ultimately predict isotope calibration curves for those amino compounds unavailable as 13C labeled standards, for example muramic acid, hydroxyproline and diaminopimelic acid. To test the model accuracy, we compared the outcomes of measured calibrations with predicted calibrations for amino acids where we had isotopically enriched standards. The results of linear regression between measured and predicted data were excellent, where R2 was >0.97, and mean absolute (percentage) deviation, MAD and MAPD, were 0.334 and 15.8%. Finally, we applied both standard and predicted calibration curves to low 13C amended soil samples and unlabeled controls to test the applicability of our model. The limit of detection (LOD) as the minimum detectable atom % 13C incorporation of amino compounds ranged from 0.0003 to 0.14 atom % among different amino compounds. This general predictive model can be used to comprehensively quantify isotope enrichments across the entire soil amino compound profile, including amino sugars and proteinogenic and non-proteinogenic amino acids, providing valuable insights for a better understanding of the overall fate of different amino compounds in soils or broader environmental samples.

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Multi-Omics Profiling Reveals Sex-Stratified Biomarkers Predicting Chronicity in Pediatric Primary Immune Thrombocytopenia

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