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Hou, M.-C.

Publications and source records attributed to Hou, M.-C..

2 recordsLinked to original sources

Integrated microbiome and metabolomic profiling reveals alterations across the adenoma-colorectal cancer sequence

The incidence of colorectal cancer (CRC) has been increasing in Taiwan and is associated with multiple risk factors, including aging, obesity, and dietary habits. Increasing evidence suggests that gut microbiota dysbiosis contributes to CRC development. This study aimed to characterize microbial and metabolic alterations across premalignant and malignant colorectal lesions and to identify potential microbiome-associated biomarkers. Individuals undergoing colonoscopy for screening or surveillance at Taipei Veterans General Hospital were enrolled. Gut microbial composition was analyzed using full-length 16S rRNA gene sequencing to achieve high-resolution taxonomic profiling. Predicted functional pathways were inferred from microbial communities, and targeted metabolomic profiling was performed to evaluate microbial metabolic outputs. A total of 122 individuals were included, comprising 62 healthy controls, 15 adenoma cases, and 45 CRC cases. Progressive shifts in microbial composition and predicted functional pathways were observed along the adenoma-carcinoma sequence. Several bacterial taxa, including Phocaeicola dorei, Anaerotignum faecicola, Negativibacillus massiliensis, and Dysosmobacter segnis, were enriched in CRC. At the functional level, CRC samples showed enrichment of pathways associated with energy metabolism and bacterial stress responses. Metabolomic analysis further revealed increased levels of tauro-ursocholanic acid in CRC samples, whereas short-chain fatty acids (SCFAs) were reduced compared with controls. Integrative analysis combining full-length 16S sequencing, functional pathway prediction, and metabolomic profiling revealed coordinated microbial and metabolic alterations across the adenoma-carcinoma sequence. These findings provide insight into microbiome-associated processes in colorectal tumorigenesis and suggest potential microbial and metabolic biomarkers for CRC. ImportanceColorectal cancer (CRC) develops through a adenoma-carcinoma sequence, yet the microbial and metabolic alterations accompanying this progression remain incompletely understood. In this study, we integrated full-length 16S rRNA gene sequencing with metabolomic profiling to characterize taxonomic, functional, and metabolic changes across healthy controls, adenoma, and CRC. Our results reveal synchronized shifts in specific microbial taxa, predicted metabolic pathways, and fecal metabolites along the adenoma-carcinoma sequence. Several bacterial species, including Phocaeicola dorei, Anaerotignum faecicola, and Dysosmobacter segnis, increased in CRC, whereas short-chain fatty acids decreased progressively from controls to adenoma and CRC. Functional pathway analysis further indicated alterations in microbial fermentation, amino acid metabolism, and energy-related pathways. Together, these findings highlight the potential role of microbiome-associated metabolic changes in colorectal tumorigenesis and suggest candidate microbial and metabolic markers that may aid in understanding disease development and improving risk stratification.

microbiology↗

The Taiwan Precision Medicine Initiative: A Cohort for Large-Scale Studies

The Taiwan Precision Medicine Initiative (TPMI), a project initiated by the Academia Sinica in collaboration with 16 major medical centers around Taiwan, has recruited 565,390 participants who consented to provide DNA samples for genetic profiling and grant access to their electronic medical records (EMR) for studies to develop precision medicine. Access to the EMR is both retrospective and prospective, allowing researchers to conduct prospective studies over time. Genetic profiling is done with population-optimized SNP arrays for the Han Chinese populations that enable genetic analyses such as genome-wide association, phenome-wide association, and polygenic risk score studies to evaluate common disease risk and pharmacogenetic response. Furthermore, the TPMI participants agree to be contacted for future research opportunities related to their genetic risks and receive personalized genetic risk profiles with health management recommendations. TPMI has established the TPMI Data Access Platform (TDAP), a central database and analysis platform that both safeguards the security of the data and facilitates academic research. The TPMI is the largest non-European cohort that merges genetic profiles with EMR in the world. With a cohort that can be followed over time, it can be utilized to validate genetic risk prediction models, conduct clinical trials to show the efficacy of risk-based health management, and optimize health policies based on genetic risks. In this report, we describe the TPMI study design, the population and genetic characteristics of the TPMI cohort, and the power it provides to conduct crucial studies in developing precision medicine on a population and personal level. As Han Chinese represent almost 20% of the worlds population, the results of TPMI studies will benefit >1.4 billion people around the world and serve as a model for developing population-based precision medicine.

genetics↗