METLiT: Quantitative Detection of Chronic Fatigue in Patients with Post-COVID Sequelae; Proposing the Possibility of Biomarker Discovery and Early Diagnosis of Neurological Disorders through Neuro-metabolite Analysis
METLiT: Quantitative Detection of Chronic Fatigue in Patients with Post-COVID Sequelae; Proposing the Possibility of Biomarker Discovery and Early Diagnosis of Neurological Disorders through Neuro-metabolite Analysis
Posted January. 14, 2025 15:10,
Updated January. 14, 2025 17:04
Medical AI startup METLiT Inc. (Co-CEOs: Suhyeok Song and Dr. Hyeong Hun Lee) announced the presentation of their latest research findings on Post-COVID Fatigue at the 2024 International Society for Magnetic Resonance in Medicine (ISMRM). This study suggests that the chronic fatigue symptoms persisting after recovery from COVID-19 may be associated with neuroinflammation and mitochondrial dysfunction and supports this hypothesis by analyzing changes in neuro-metabolites.
MRS-Based Metabolite Analysis: Potential for Early Detection of Neurological Damage
Dr.Jeong Hoon Lim and Dr.Hyeong Hun Lee (source=METLiT)
The METLiT research team in collaboration with Singapore National University Hospital (Dr. Jeong-Hoon Lim, Department of Rehabilitation Medicine – Head of the Post-COVID Sequelae Clinic), performed a precise analysis of changes in neuro-metabolites in the posterior cingulate gyrus using magnetic resonance spectroscopy (MRS). The analysis showed that, in the group of patients experiencing Post-COVID Fatigue, levels of antioxidants (such as glutathione) necessary for maintaining oxidative balance were decreased, and overall neural activity was reduced. These findings suggest the possibility of continued mitochondrial metabolic inefficiency and oxidative stress, potentially carrying a long-term risk of developing into neurodegenerative disorders.
(source=METLiT)
Strengthening Reliability with AI-Based Analytical Technology
In this study, METLiT’s proprietary deep learning-based MRS analytical technology was applied. This technology quantifies 17 major neuro-metabolites and accurately detected residual neuro-metabolite abnormalities even after recovery from COVID-19. METLiT’s AI technology has already garnered significant attention from medical institutions at home and abroad, and this study is regarded as a case that demonstrates the technology’s effectiveness on an international scale.
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Targeting the Global Healthcare Market through Biomarker Discovery
According to METLiT Co-CEO Dr. Hyeong Hun Lee, “This study marks an important achievement in identifying the root causes of symptoms in Post-COVID Fatigue patients at the metabolite level and demonstrates the feasibility of noninvasive brain disease diagnosis using MRS.” Furthermore, as a follow-up to this research, the team will present findings from a long-term follow-up study on patients with post-COVID sequelae at ISMRM 2025. The study investigates the correlation between the extent of chronic fatigue and brain metabolites, and two clinical research papers are planned for publication.
Currently, METLiT is conducting diverse research on neurological disorders with 12 leading global medical institutions in the United States, Singapore, Italy, and elsewhere to address unmet medical needs. Through these follow-up studies, the company aims to accelerate the productization of its technology and pioneer new markets in the precision medical diagnostics sector.
By Moon-kyoo Lee(munch@itdonga.com)
MRS-Based Metabolite Analysis: Potential for Early Detection of Neurological Damage
The METLiT research team in collaboration with Singapore National University Hospital (Dr. Jeong-Hoon Lim, Department of Rehabilitation Medicine – Head of the Post-COVID Sequelae Clinic), performed a precise analysis of changes in neuro-metabolites in the posterior cingulate gyrus using magnetic resonance spectroscopy (MRS). The analysis showed that, in the group of patients experiencing Post-COVID Fatigue, levels of antioxidants (such as glutathione) necessary for maintaining oxidative balance were decreased, and overall neural activity was reduced. These findings suggest the possibility of continued mitochondrial metabolic inefficiency and oxidative stress, potentially carrying a long-term risk of developing into neurodegenerative disorders.
Strengthening Reliability with AI-Based Analytical Technology
In this study, METLiT’s proprietary deep learning-based MRS analytical technology was applied. This technology quantifies 17 major neuro-metabolites and accurately detected residual neuro-metabolite abnormalities even after recovery from COVID-19. METLiT’s AI technology has already garnered significant attention from medical institutions at home and abroad, and this study is regarded as a case that demonstrates the technology’s effectiveness on an international scale.
________________________________________
Targeting the Global Healthcare Market through Biomarker Discovery
Currently, METLiT is conducting diverse research on neurological disorders with 12 leading global medical institutions in the United States, Singapore, Italy, and elsewhere to address unmet medical needs. Through these follow-up studies, the company aims to accelerate the productization of its technology and pioneer new markets in the precision medical diagnostics sector.
By Moon-kyoo Lee(munch@itdonga.com)
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