Using artificial intelligence and promoter-level transcriptome analysis to identify a biomarker as a possible prognostic predictor of cardiac complications in male patients with Fabry disease

Fabry disease is the most frequently occurring form of lysosomal disease in Japan, and is characterized by a wide variety of conditions. Primarily, the three major types of concerns associated with Fabry disease observed during adulthood that must be prevented are central nervous system, renal, and cardiac complications. Cardiac complications, such as cardiomyopathy, cardiac muscle fibrosis, and severe arrhythmia, are the most common mortality causes in patients with Fabry disease. To predict cardiac complications of Fabry disease, we extracted RNA from the venous blood of patients for cap analysis of gene expression (CAGE), performed likelihood ratio tests for each RNA expression dataset obtained from individuals with and without cardiac complications, and analyzed the correlation between cardiac functional factors observed using magnetic resonance imaging data extracted using artificial intelligence algorithms and RNA expression. Our findings showed that CHN1 expression was significantly higher in male Fabry disease patients with cardiac complications and that it could be associated with many cardiac functional factors. <i>CHN1</i> encodes a GTPase-activating protein, chimerin 1, which is specific to the GTP-binding protein Rac (involved in oxidative stress generation and the promotion of myocardial fibrosis). Thus, CHN1 is a potential predictive biomarker of cardiac complications in Fabry disease; however, further studies are required to confirm this observation.

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Publication Details

Journal
Molecular Genetics and Metabolism Reports
Published
2024-10-13
DOI
https://doi.org/10.1016/j.ymgmr.2024.101152
Citations
6
Primary Topic
Protein Tyrosine Phosphatases
Type
article
Field-Weighted Citation Impact
1.40

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article

Using artificial intelligence and promoter-level transcriptome analysis to identify a biomarker as a possible prognostic predictor of cardiac complications in male patients with Fabry disease

Hiroshi Kobayashi, Sayoko Izuka, Norio Nakata, Masako Nishikawa et al.
6 citations
Molecular Genetics and Metabolism Reports
Protein Tyrosine Phosphatases
1.40
article

Using artificial intelligence and promoter-level transcriptome analysis to identify a biomarker as a possible prognostic predictor of cardiac complications in male patients with Fabry disease

Hiroshi Kobayashi, Sayoko Izuka, Norio Nakata, Masako Nishikawa, Kenichi Hongo
article en
6 citations

Abstract

Fabry disease is the most frequently occurring form of lysosomal disease in Japan, and is characterized by a wide variety of conditions. Primarily, the three major types of concerns associated with Fabry disease observed during adulthood that must be prevented are central nervous system, renal, and cardiac complications. Cardiac complications, such as cardiomyopathy, cardiac muscle fibrosis, and severe arrhythmia, are the most common mortality causes in patients with Fabry disease. To predict cardiac complications of Fabry disease, we extracted RNA from the venous blood of patients for cap analysis of gene expression (CAGE), performed likelihood ratio tests for each RNA expression dataset obtained from individuals with and without cardiac complications, and analyzed the correlation between cardiac functional factors observed using magnetic resonance imaging data extracted using artificial intelligence algorithms and RNA expression. Our findings showed that CHN1 expression was significantly higher in male Fabry disease patients with cardiac complications and that it could be associated with many cardiac functional factors. <i>CHN1</i> encodes a GTPase-activating protein, chimerin 1, which is specific to the GTP-binding protein Rac (involved in oxidative stress generation and the promotion of myocardial fibrosis). Thus, CHN1 is a potential predictive biomarker of cardiac complications in Fabry disease; however, further studies are required to confirm this observation.

Molecular Genetics and Metabolism ReportsVol. 41
Jikei University School of Medicine (JP)
Ministry of Education, Culture, Sports, Science and Technology, Japan Society for the Promotion of Science
Openalex Percentile: Top 19%
Protein Tyrosine Phosphatases
1.40
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Using artificial intelligence and promoter-level transcriptome analysis to identify a biomarker as a possible prognostic predictor of cardiac complications in male patients with Fabry disease — Hiroshi Kobayashi, Sayoko Izuka, et al. · Molecular Genetics and Metabolism Reports (2024) | TGRS Research Map | TGRS