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INTRODUCTION: The population of Taiwan has a long history of ethno-cultural evolution. The Taiwanese population was isolated from other large populations such as the European, Han Chinese, and Japanese population. The Taiwan Biobank (TWB) project has built a nationwide database, particularly for personal whole-genome sequence (WGS) to facilitate basic and clinical collaboration nationally and internationally, making it one of the most valuable public datasets of the East Asian population. OBJECTIVES: This study provides comprehensive medical genomic findings from TWB WGS data, for better characterization of disease susceptibility and the choice of ideal treatment regimens in Taiwanese population. METHODS: We reanalyzed 1496 WGS using a PrecisionFDA Truth challenge winner method Sentieon DNAscope. Single nucleotide variants (SNV) and small insertions/deletions (INDEL) were benchmarked. We also analyzed pharmacogenomic (PGx) drug-associated alleles, and copy number variants (CNV). Multiple practicing clinicians reviewed and curated the clinically significant variants. Variant annotations can be browsed at TaiwanGenomes (https://genomes.tw). RESULTS: We found that each participant had an average of 6,870.7 globally novel variants and 75.3% (831/1103) of the participants harbored at least one PharmGKB-selected high evidence level human leukocyte antigen (HLA) risk allele. 54 PharmGKB-reported high-level instances of evidence of Cytochrome P450 variant-drug pairs, with a population frequency of over 13.2%. We also identified 23 variants in the ACMG secondary finding V3 gene list from 25 participants, suggesting that 1.67% (25/1496) of the population is harboring at least one medical actionable variant. Our carrier status analyses suggest that one in 25 couples (3.94%) would risk having offspring with at least one pathogenic variant, which is in line with rates found in Japan and Singapore. For pathogenic CNV, we detected 6.88% and 2.02% carrier rates for alpha thalassemia and spinal muscular atrophy, respectively. CONCLUSION: Our study highlights the overall medical insights of a complete Taiwanese genomic profile.
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With the proliferation of genomic sequence data for biomedical research, the exploration of human genetic information by domain experts requires a comprehensive interrogation of large numbers of scientific publications in PubMed. However, a query in PubMed essentially provides search results sorted only by the date of publication. A search engine for retrieving and interpreting complex relations between biomedical concepts in scientific publications remains lacking. Here, we present pubmedKB, a web server designed to extract and visualize semantic relationships between four biomedical entity types: variants, genes, diseases, and chemicals. pubmedKB uses state-of-the-art natural language processing techniques to extract semantic relations from the large number of PubMed abstracts. Currently, over 2 million semantic relations between biomedical entity pairs are extracted from over 33 million PubMed abstracts in pubmedKB. pubmedKB has a user-friendly interface with an interactive semantic graph, enabling the user to easily query entities and explore entity relations. Supporting sentences with the highlighted snippets allow to easily navigate the publications. Combined with a new explorative approach to literature mining and an interactive interface for researchers, pubmedKB thus enables rapid, intelligent searching of the large biomedical literature to provide useful knowledge and insights. pubmedKB is available at https://www.pubmedkb.cc/.
