Human personal genome sequencing can be done with high efficiency by aligning a huge number of short reads derived from various next generation sequencing (NGS) technologies to the reference genome sequence. One of the major obstacles is the incompleteness of human reference genome. We tried to analyze the effect of hidden gene duplication on the NGS data using the known example of hydin gene. Hydin2 , a duplicated copy of hydin on chromosome 16q22, has been recently found to be localized to chromosome 1q21, and is not included in the current version of standard human genome reference. We found that all of eight personal genome data published so far do not contain hydin2, and there is large number of nsSNPs in hydin. The heterozygosity of those nsSNPs was significantly higher than expected. The sequence coverage depth in hydin gene was about two fold of average depth. We believe that these unique finding of hydin can be used as useful indicators to discover new hidden multiplication in human genome.
Coat Protein Complex I ; Gene Duplication ; Genome ; Genome, Human ; Humans

Purpose: In 2024, medical researchers in the Republic of Korea were invited to amend the health and medical data utilization guidelines (Government Publications Registration Number: 11-1352000-0052828-14). This study aimed to show the overall impact of the guideline revision, with a focus on clinical genomic data. Materials and Methods: This study amended the pseudonymization of genomic data defined in the previous version through a joint study led by the Ministry of Health and Welfare, the Korea Health Information Service, and the Korea Genome Organization. To develop the previous version, we held three conferences with four main medical research institutes and seven academic societies. We conducted two surveys targeting special genome experts in academia, industry, and institutes. Results: We found that cases of pseudonymization in the application of genome data were rare and that there was ambiguity in the terminology used in the previous version of the guidelines. Most experts (>~90%) agreed that the ‘reserved’ condition should be eliminated to make genomic data available after pseudonymization. In this study, the scope of genomic data was defined as clinical next-generation sequencing data, including FASTQ, BAM/SAM, VCF, and medical records. Pseudonymization targets genomic sequences and metadata, embedding specific elements, such as germline mutations, short tandem repeats, single-nucleotide polymorphisms, and identifiable data (for example, ID or environmental values). Expression data generated from multi-omics can be used without pseudonymization. Conclusion This amendment will not only enhance the safe use of healthcare data but also promote advancements in disease prevention, diagnosis, and treatment.

Purpose: In 2024, medical researchers in the Republic of Korea were invited to amend the health and medical data utilization guidelines (Government Publications Registration Number: 11-1352000-0052828-14). This study aimed to show the overall impact of the guideline revision, with a focus on clinical genomic data. Materials and Methods: This study amended the pseudonymization of genomic data defined in the previous version through a joint study led by the Ministry of Health and Welfare, the Korea Health Information Service, and the Korea Genome Organization. To develop the previous version, we held three conferences with four main medical research institutes and seven academic societies. We conducted two surveys targeting special genome experts in academia, industry, and institutes. Results: We found that cases of pseudonymization in the application of genome data were rare and that there was ambiguity in the terminology used in the previous version of the guidelines. Most experts (>~90%) agreed that the ‘reserved’ condition should be eliminated to make genomic data available after pseudonymization. In this study, the scope of genomic data was defined as clinical next-generation sequencing data, including FASTQ, BAM/SAM, VCF, and medical records. Pseudonymization targets genomic sequences and metadata, embedding specific elements, such as germline mutations, short tandem repeats, single-nucleotide polymorphisms, and identifiable data (for example, ID or environmental values). Expression data generated from multi-omics can be used without pseudonymization. Conclusion This amendment will not only enhance the safe use of healthcare data but also promote advancements in disease prevention, diagnosis, and treatment.

Purpose: In 2024, medical researchers in the Republic of Korea were invited to amend the health and medical data utilization guidelines (Government Publications Registration Number: 11-1352000-0052828-14). This study aimed to show the overall impact of the guideline revision, with a focus on clinical genomic data. Materials and Methods: This study amended the pseudonymization of genomic data defined in the previous version through a joint study led by the Ministry of Health and Welfare, the Korea Health Information Service, and the Korea Genome Organization. To develop the previous version, we held three conferences with four main medical research institutes and seven academic societies. We conducted two surveys targeting special genome experts in academia, industry, and institutes. Results: We found that cases of pseudonymization in the application of genome data were rare and that there was ambiguity in the terminology used in the previous version of the guidelines. Most experts (>~90%) agreed that the ‘reserved’ condition should be eliminated to make genomic data available after pseudonymization. In this study, the scope of genomic data was defined as clinical next-generation sequencing data, including FASTQ, BAM/SAM, VCF, and medical records. Pseudonymization targets genomic sequences and metadata, embedding specific elements, such as germline mutations, short tandem repeats, single-nucleotide polymorphisms, and identifiable data (for example, ID or environmental values). Expression data generated from multi-omics can be used without pseudonymization. Conclusion This amendment will not only enhance the safe use of healthcare data but also promote advancements in disease prevention, diagnosis, and treatment.

Purpose: In 2024, medical researchers in the Republic of Korea were invited to amend the health and medical data utilization guidelines (Government Publications Registration Number: 11-1352000-0052828-14). This study aimed to show the overall impact of the guideline revision, with a focus on clinical genomic data. Materials and Methods: This study amended the pseudonymization of genomic data defined in the previous version through a joint study led by the Ministry of Health and Welfare, the Korea Health Information Service, and the Korea Genome Organization. To develop the previous version, we held three conferences with four main medical research institutes and seven academic societies. We conducted two surveys targeting special genome experts in academia, industry, and institutes. Results: We found that cases of pseudonymization in the application of genome data were rare and that there was ambiguity in the terminology used in the previous version of the guidelines. Most experts (>~90%) agreed that the ‘reserved’ condition should be eliminated to make genomic data available after pseudonymization. In this study, the scope of genomic data was defined as clinical next-generation sequencing data, including FASTQ, BAM/SAM, VCF, and medical records. Pseudonymization targets genomic sequences and metadata, embedding specific elements, such as germline mutations, short tandem repeats, single-nucleotide polymorphisms, and identifiable data (for example, ID or environmental values). Expression data generated from multi-omics can be used without pseudonymization. Conclusion This amendment will not only enhance the safe use of healthcare data but also promote advancements in disease prevention, diagnosis, and treatment.

We found that non-small-cell lung cancer (NSCLC) cells express high levels of multiple aldehyde dehydrogenase (ALDH) isoforms via an informatics analysis of metabolic enzymes in NSCLC and immunohistochemical staining of NSCLC clinical tumor samples. Using a multiple reaction-monitoring mass spectrometry analysis, we found that multiple ALDH isozymes were generally abundant in NSCLC cells compared with their levels in normal IMR-90 human lung cells. As a result of the catalytic reaction mediated by ALDH, NADH is produced as a by-product from the conversion of aldehyde to carboxylic acid. We hypothesized that the NADH produced by ALDH may be a reliable energy source for ATP production in NSCLC. This study revealed that NADH production by ALDH contributes significantly to ATP production in NSCLC. Furthermore, gossypol, a pan-ALDH inhibitor, markedly reduced the level of ATP. Gossypol combined with phenformin synergistically reduced the ATP levels, which efficiently induced cell death following cell cycle arrest.
Adenosine Triphosphate ; Aldehyde Dehydrogenase* ; Cell Cycle Checkpoints ; Cell Death ; Energy Metabolism* ; Gossypol ; Humans ; Informatics ; Isoenzymes ; Lung ; Lung Neoplasms ; Mass Spectrometry ; NAD ; Phenformin ; Protein Isoforms