X-linked myopia 26 (Myopia 26, MIM #301010), which is caused by the variants of ARR3 (MIM *301770), is characterized by female-limited early-onset high myopia (eo-HM). Clinical characteristics include a tigroid appearance in the fundus and a temporal crescent of the optic nerve head. At present, the limited literature on eo-HM caused by ARR3 mutations shows that its inheritance mode is complex, which brings certain difficulties to pre-pregnancy genetic counseling, pre-implantation genetic diagnosis, and prenatal diagnosis. Here, we investigated the genetic underpinning of a Chinese family with eo-HM. Whole exome sequencing of the proband revealed a novel frameshift mutation in ARR3 (NM_004312, exon10, c.666delC, p. Asn222LysfsTer22). Although the mode of inheritance of the eo-HM family fits the X-linked pattern of ARR3, the phenotypes of three patients deviate from the typical early-onset high myopia. Through X-chromosome inactivation experiments, the patient’s different phenotypes can be precisely explained. In addition, this study not only enhanced the correlation between ARR3 and early-onset high myopia but also provided explanations for different phenotypes, which may inspire follow-up studies. Our results enrich the knowledge of the variant spectrum in ARR3 and provide critical information for preimplantation and prenatal genetic testing, diagnosis, and counseling.

Introduction: The overdiagnosing of papillary thyroid carcinoma (PTC) in China necessitates the development of an evidence-based diagnosis and prognosis strategy in line with precision medicine. A landscape of PTC in Chinese cohorts is needed to provide comprehensiveness.Methods: 6 paired PTC samples were employed for whole-exome sequencing, RNA sequencing, and data-dependent acquisition mass spectrum analysis. Weighted gene co-expression network analysis and protein-protein interactions networks were used to screen for hub genes. Moreover, we verified the hub genes' diagnostic and prognostic potential using online databases. Logistic regression was employed to construct a diagnostic model, and we evaluated its efficacy and specificity based on TCGA-THCA and GEO datasets.Results: The basic multiomics landscape of PTC among local patients were drawn. The similarities and differences were compared between the Chinese cohort and TCGA-THCA cohorts, including the identification of PNPLA5 as a driver gene in addition to BRAF mutation. Besides, we found 572 differentially expressed genes and 79 differentially expressed proteins. Through integrative analysis, we identified 17 hub genes for prognosis and diagnosis of PTC. Four of these genes, ABR, AHNAK2, GPX1, and TPO, were used to construct a diagnostic model with high accuracy, explicitly targeting PTC (AUC=0.969/0.959 in training/test sets).Discussion: Multiomics analysis of the Chinese cohort demonstrated significant distinctions compared to TCGA-THCA cohorts, highlighting the unique genetic characteristics of Chinese individuals with PTC. The novel biomarkers, holding potential for diagnosis and prognosis of PTC, were identified. Furthermore, these biomarkers provide a valuable tool for precise medicine, especially for immunotherapeutic or nanomedicine based cancer therapy.