With the recent development of sequencing technology and the rapid reduction of sequencing costs, high-throughput sequencing (including second and third-generation sequencing) is revolutionizing basic life science research and clinical research from various aspects. High-throughput sequencing often produces millions of sequencing reads at a time, and the alignment or assembly of these reads allows the determination of various mutations (e.g., SNV and Indels) at the genomic level, accurate gene expression quantification at the transcriptomic level, and identification of histone or DNA modification at the epigenomic level. The resulting accumulation of enormous multi-omics information has opened up a new era of finding effective disease markers and studying their roles in disease occurrence and development. Using high-throughput sequencing, various markers of chronic diseases (such as cancer, heart disease, diabetes, and arthritis) have been developed at all omics levels, which have been used for diagnosis and classification of diseases, prediction of treatment effects, and prevention of diseases. The quickly and massively acquired multi-omics data, together with newly developed algorithms, provide an excellent chance for the identification of more reliable biomarkers. This research topic aims at (1) developing new chronic disease markers at four levels (i.e., genome, epigenome, transcriptome, and translatome) with the help of high-throughput sequencing, and (2) delineating potential marker-related mechanisms for chronic disease occurrence or development. This research topic covers a broad spectrum of interests, and studies including both wet lab and dry lab results are more welcomed. More specifically, this research topic welcomes contributions including but not limited to the following areas: 1. Identification of novel biomarkers for chronic disease detection (especially in early-stage) or prognosis prediction using high-throughp