BACKGROUND: The pathological mechanism of chronic thromboembolic pulmonary hypertension (CTEPH) is not fully understood, and inflammation has been reported to be one of its etiological factors. IgG regulates systemic inflammatory homeostasis, primarily through its N -glycans. Little is known about IgG N -glycosylation in CTEPH. We aimed to map the IgG N -glycome of CTEPH to provide new insights into its pathogenesis and discover novel markers and therapies. METHODS: We characterized the plasma IgG N -glycome of patients with CTEPH in a discovery cohort and validated our results in an independent validation cohort using matrix-assisted laser desorption/ionization time of flight mass spectrometry. Thereafter, we correlated IgG N -glycans with clinical parameters and circulating inflammatory cytokines in patients with CTEPH. Furthermore, we determined IgG N -glycan quantitative trait loci in CTEPH to reveal partial mechanisms underlying glycan changes. RESULTS: Decreased IgG galactosylation representing a proinflammatory phenotype was found in CTEPH. The distribution of IgG galactosylation showed a strong association with NT-proBNP (N-terminal pro-B-type natriuretic peptide) in CTEPH. In line with the glycomic findings, IgG pro-/anti-inflammatory N -glycans correlated well with a series of inflammatory markers and gene loci that have been reported to be involved in the regulation of these glycans or inflammatory immune responses. CONCLUSIONS: This is the first study to reveal the full signature of the IgG N -glycome of a proinflammatory phenotype and the genes involved in its regulation in CTEPH. Plasma IgG galactosylation may be useful for evaluating the inflammatory state in patients with CTEPH; however, this requires further validation. This study improves our understanding of the mechanisms underlying CTEPH inflammation from the perspective of glycomics.

BACKGROUND: The pathogenesis of chronic thromboembolic pulmonary hypertension (CTEPH) is multifactorial and growing evidence has indicated that hematological disorders are involved. Clonal hematopoiesis of indeterminate potential (CHIP) has recently been associated with an increased risk of both hematological malignancies and cardiovascular diseases. However, the prevalence and clinical relevance of CHIP in patients with CTEPH remains unclear. METHODS: Using stepwise calling on next-generation sequencing data from 499 patients with CTEPH referred to 3 centers between October 2006 and December 2021, CHIP mutations were identified. We associated CHIP with all-cause mortality in patients with CTEPH. To provide insights into potential mechanisms, the associations between CHIP and inflammatory markers were also determined. RESULTS: In total, 47 (9.4%) patients with CTEPH carried at least 1 CHIP mutation at a variant allele frequency of ≥2%. The most common mutations were in DNMT3A , TET2 , RUNX1 , and ASXL1 . During follow-up (mean, 55 months), deaths occurred in 22 (46.8%) and 104 (23.0%) patients in the CHIP and non-CHIP groups, respectively ( P <0.001, log-rank test). The association of CHIP with mortality remained robust in the fully adjusted model (hazard ratio, 2.190 [95% CI, 1.257–3.816]; P =0.006). Moreover, patients with CHIP mutations showed higher circulating interleukin-1β and interleukin-6 and lower interleukin-4 and IgG galactosylation levels. CONCLUSIONS: This is the first study to show that CHIP mutations occurred in 9.4% of patients with CTEPH are associated with a severe inflammatory state and confer a poorer prognosis in long-term follow-up.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by poor prognosis and high mortality. Transforming growth factor-β (TGF-β) plays a key role in PDAC tumor progression, which is often associated with aberrant glycosylation. However, how PDAC cells respond to TGF-β and the role of glycosylation therein is not well known. Here, we investigated the TGF-β-mediated response and glycosylation changes in the PaTu-8955S (PaTu-S) cell line deficient in SMA-related and MAD-related protein 4 (SMAD4), a signal transducer of the TGF-β signaling. PaTu-S cells responded to TGF-β by upregulating SMAD2 phosphorylation and target gene expression. We found that TGF-β induced expression of the mesenchymal marker N-cadherin but did not significantly affect epithelial marker E-cadherin expression. We also examined differences in N-glycans, O-glycans, and glycosphingolipid-linked glycans in PaTu-S cells upon TGF-β stimulation. TGF-β treatment primarily induced N-glycome aberrations involving elevated levels of branching, core fucosylation, and sialylation in PaTu-S cells, in agreement with TGF-β-induced changes in the expression of glycosylation-associated genes. In addition, we observed differences in O glycosylation and glycosphingolipid glycosylation profiles after TGF-β treatment, including lower levels of sialylated Tn antigen and neoexpression of globosides. Furthermore, the expression of transcription factor sex-determining region Y-related high-mobility group box 4 was upregulated upon TGF-β stimulation, and its depletion blocked TGF-β-induced N-glycomic changes. Thus, TGF-β-induced N-glycosylation changes can occur in a sex-determining region Y-related high-mobility group box 4–dependent and SMAD4-independent manner in the pancreatic PaTu-S cancer cell line. Our results open up avenues to study the relevance of glycosylation in TGF-β signaling in SMAD4-inactivated PDAC.

Background: Hereditary angioedema (HAE) is a rare disease with heterogeneous clinical symptoms. It is vitally important to predict whether an HAE patient will develop severe symptoms in clinical practice, but there are currently no predictive biomarkers for HAE stratification. Plasma N‐glycomes are disease‐specific and have great potential for the discovery of non‐invasive biomarkers. In this study, we profiled the plasma N‐glycome of HAE patients from two independent cohorts to identify candidate biomarkers.Methods: Linkage‐specific sialylation derivatization combined with matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry detection and automated data processing was employed to analyze the plasma N‐glycome of two independent type‐1 HAE cohorts.Results: HAE patients had abnormal glycan complexity, galactosylation, and α2,3‐ and α2,6‐linked sialylation compared to healthy controls (HC). The classification models based on dysregulated glycan traits could successfully discriminate between HAE and HC with area under the curves (AUCs) being greater than 0.9. Some of the aberrant glycans showed response to therapy. Moreover, we identified a series of glycan traits with strong associations with the occurrence of laryngeal or gastrointestinal angioedema or disease severity score. Predictive models based on these traits could be used to predict disease severity (AUC > 0.9). These results were replicated in an independent cohort.Conclusions: We reported the full plasma N‐glycomic signature of HAE for the first time, and identified potential biomarkers. These findings may play a critical role in predicting disease severity and guide the treatment of HAE in clinical practice. Further protein‐specific and prospective studies are needed to validate our findings.

Patients with lateral lymph node metastasis (LLNM) may experience higher locoregional recurrence rates and poorer prognoses compared to those without LLNM, highlighting the need for effective preoperative stratification to reliably assess risk LLNM. In this study, we collected PTMC samples from Peking Union Medical College Hospital and employed data-independent acquisition mass spectrometry proteomics technique to identify protein profiles in PTMC tissues with and without LLNM. Pseudo temporal analysis and single sample gene set enrichment analysis were conducted in combination with The Cancer Genome Atlas Thyroid Carcinoma for functional coordination analysis and the construction of a prediction model based on random forest. Non-negative matrix factorization (NMF) clustering was utilized to classify molecular subtypes of PTMC. Our findings revealed that the differential activation of pathways such as MAPK and PI3K was critical in enhancing the lateral lymph node metastatic potential of PTMC. We successfully screened biomarkers via machine learning and public databases, creating an effective prediction model for metastasis. Additionally, we explored the mechanism of metastasis-associated PTMC subtypes via NMF clustering. These insights into LLNM mechanisms in PTMC may contribute to future biomarker screening and the identification of therapeutic targets.