PubMed HealthSearch

Biomedical subjects

Cheng-Yu Tsai

Publications and source records attributed to Cheng-Yu Tsai.

2 recordsLinked to original sources

A lipid-immune network signature defines susceptibility to asparaginase-associated pancreatitis.

BACKGROUNDAsparaginase is essential for curing acute lymphoblastic leukemia (ALL), but its use is limited by asparaginase-associated pancreatitis (AAP), a severe and unpredictable toxicity lacking validated prospective biomarkers. We sought to define early systemic molecular features of susceptibility to AAP.METHODSWe performed longitudinal lipidomic and proteomic profiling in two independent pediatric ALL cohorts (n = 161; 79 AAP cases, 82 controls) using paired blood samples collected before asparaginase exposure and at the end of induction therapy (including a single dose of asparaginase), thereby capturing pre-injury biology rather than consequences of pancreatitis. We applied differential abundance and network-based analyses and integrated lipid-cytokine associations using proteomics.RESULTSAcross cohorts, we identified a reproducible lysophosphatidylcholine-centered (LPC-centered) signature characterized by attenuated induction therapy-associated LPC responses and disruption of LPC coregulation at the network level. Proteomic profiling revealed enrichment of cytokine signaling pathways, and integrative analyses demonstrated altered lipid-cytokine coupling, including a flip in association direction for LPC species and IL-18 between cases and controls. Although IL-18/LPC ratios did not differ globally, elevated postinduction IL-18/LPC ratios identified AAP risk within a protocol-defined very high-risk ALL subgroup (AUC = 0.81).CONCLUSIONThese findings support a systems-level model in which failure of coordinated lipid-immune responses under therapeutic stress confers vulnerability to AAP, providing a framework for validation and mitigation strategies.TRIAL REGISTRATIONNCT00400946; NCT01574274; NCT03020030 (parent trials).FUNDINGServier Pharmaceuticals (IIT-95014-027-USA); SDRC (P30DK116074); Stanford SPARK; Fonds de Recherche du Québec - Santé; Fondation Charles-Bruneau; Leukemia & Lymphoma Society of Canada.

Adolescent

Unraveling the complex genetic landscape of OTOF-related hearing loss: a deep dive into cryptic variants and haplotype phasing.

BACKGROUND: Pathogenic variants in OTOF are a major cause of auditory synaptopathy. However, challenges remain in interpreting OTOF variants, including difficulties in confirming haplotype phasing using traditional short-read sequencing (SRS) due to the large gene size, the potential incomplete penetrance of certain variants, and difficulties in assessing variants at non-canonical splice sites. This study aims to revisit the genetic landscape of OTOF variants in a Taiwanese non-syndromic auditory neuropathy spectrum disorder (ANSD) cohort using a combination of sequencing technologies, predictive tools, and experimental validations. METHODS: We performed SRS to analyze OTOF variants in 65 unrelated Taiwanese patients diagnosed with non-syndromic ANSD, complemented by long-read sequencing (LRS) for haplotype phasing. A prediction-to-validation pipeline was implemented to assess the pathogenicity of cryptic variants using SpliceAI software and minigene assays. RESULTS: Biallelic pathogenic OTOF variants were identified in 33 patients (50.8%), while monoallelic variants were found in five patients. Three novel variants, c.3864G > A (p.Ala1288 =), c.4501G > A (p.Ala1501Thr), and c.5813 + 2T > C, were detected. The pathogenicity of two non-canonical mis-splicing variants, c.3894 + 5G > C and c.3864G > A (p.Ala1288 =), was confirmed by minigene assays. LRS-based haplotype phasing revealed that the common missense variant c.5098G > C (p.Glu1700Gln) and the novel variant c.5975A > G (p.Lys1992Arg) are in cis and form a founder pathogenic allele in the Taiwanese population. CONCLUSIONS: Our study highlights the genetic heterogeneity of DFNB9 and emphasizes the importance of population-specific variant interpretation. The integration of advanced sequencing technologies, predictive algorithms, and functional validation assays will improve the accuracy of molecular diagnosis and inform personalized treatment strategies for individuals with DFNB9.

Humans