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Chun MY, Jang H, Kim SJ, Park YH, Yun J, Lockhart SN, Weiner M, De Carli C, Moon SH, Choi JY, Nam KR, Byun BH, Lim SM, Kim JP, Choe YS, Kim YJ, Na DL, Kim HJ, Seo SW. Emerging role of vascular burden in AT(N) classification in individuals with Alzheimer's and concomitant cerebrovascular burdens. J Neurol Neurosurg Psychiatry 2023; 95:44-51. [PMID: 37558399 PMCID: PMC10803958 DOI: 10.1136/jnnp-2023-331603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 07/22/2023] [Indexed: 08/11/2023]
Abstract
OBJECTIVES Alzheimer's disease (AD) is characterised by amyloid-beta accumulation (A), tau aggregation (T) and neurodegeneration (N). Vascular (V) burden has been found concomitantly with AD pathology and has synergistic effects on cognitive decline with AD biomarkers. We determined whether cognitive trajectories of AT(N) categories differed according to vascular (V) burden. METHODS We prospectively recruited 205 participants and classified them into groups based on the AT(N) system using neuroimaging markers. Abnormal V markers were identified based on the presence of severe white matter hyperintensities. RESULTS In A+ category, compared with the frequency of Alzheimer's pathological change category (A+T-), the frequency of AD category (A+T+) was significantly lower in V+ group (31.8%) than in V- group (64.4%) (p=0.004). Each AT(N) biomarker was predictive of cognitive decline in the V+ group as well as in the V- group (p<0.001). Additionally, the V+ group showed more severe cognitive trajectories than the V- group in the non-Alzheimer's pathological changes (A-T+, A-N+; p=0.002) and Alzheimer's pathological changes (p<0.001) categories. CONCLUSION The distribution and longitudinal outcomes of AT(N) system differed according to vascular burdens, suggesting the importance of incorporating a V biomarker into the AT(N) system.
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Affiliation(s)
- Min Young Chun
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
- Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, South Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Samsung Alzheimer's Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Soo-Jong Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
| | - Yu Hyun Park
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
| | - Jihwan Yun
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
| | - Samuel N Lockhart
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Michael Weiner
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Charles De Carli
- Department of Neurology, University of California-Davis, Davis, California, USA
| | - Seung Hwan Moon
- Departmentof Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Jae Yong Choi
- Division of Applied RI, Korea Institute of Radiological and Medical Sciences, Seoul, South Korea
| | - Kyung Rok Nam
- Division of Applied RI, Korea Institute of Radiological and Medical Sciences, Seoul, South Korea
| | - Byung-Hyun Byun
- Department of Nuclear Medicine, Korea Cancer Center Hospital, Korea Institute of Radiological and Medical Sciences, Seoul, South Korea
| | - Sang-Moo Lim
- Department of Nuclear Medicine, Korea Cancer Center Hospital, Korea Institute of Radiological and Medical Sciences, Seoul, South Korea
| | - Jun Pyo Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Samsung Alzheimer's Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Center for Neuroimaging, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Yeong Sim Choe
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
| | - Young Ju Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Samsung Alzheimer's Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Cell and Gene Therapy Institute (CGTI), Research Institute for Future Medicine, Samsung Medical Center, Seoul, South Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Samsung Alzheimer's Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Samsung Alzheimer's Convergence Research Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea
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Kang M, Jeong E, Kim JY, Yun SA, Jang MA, Jang JH, Kim TY, Huh HJ, Lee NY. Optimization of extraction-free protocols for SARS-CoV-2 detection using a commercial rRT-PCR assay. Sci Rep 2023; 13:20364. [PMID: 37990045 PMCID: PMC10663557 DOI: 10.1038/s41598-023-47645-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 11/16/2023] [Indexed: 11/23/2023] Open
Abstract
In the ongoing global fight against coronavirus disease 2019 (COVID-19), the sample preparation process for real-time reverse transcription polymerase chain reaction (rRT-PCR) faces challenges due to time-consuming steps, labor-intensive procedures, contamination risks, resource demands, and environmental implications. However, optimized strategies for sample preparation have been poorly investigated, and the combination of RNase inhibitors and Proteinase K has been rarely considered. Hence, we investigated combinations of several extraction-free protocols incorporating heat treatment, sample dilution, and Proteinase K and RNase inhibitors, and validated the effectiveness using 120 SARS-CoV-2 positive and 62 negative clinical samples. Combining sample dilution and heat treatment with Proteinase K and RNase inhibitors addition exhibited the highest sensitivity (84.26%) with a mean increase in cycle threshold (Ct) value of + 3.8. Meanwhile, combined sample dilution and heat treatment exhibited a sensitivity of 79.63%, accounting for a 38% increase compared to heat treatment alone. Our findings highlight that the incorporation of Proteinase K and RNase inhibitors with sample dilution and heat treatment contributed only marginally to the improvement without yielding statistically significant differences. Sample dilution significantly impacts SARS-CoV-2 detection, and sample conditions play a crucial role in the efficiency of extraction-free methods. Our findings may provide insights for streamlining diagnostic testing, enhancing its accessibility, cost-effectiveness, and sustainability.
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Affiliation(s)
- Minhee Kang
- Smart Healthcare Research Institute, Biomedical Engineering Research Center, Samsung Medical Center, Seoul, South Korea
- Department of Medical Device Management and Research, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, South Korea
| | - Eunjung Jeong
- Smart Healthcare Research Institute, Biomedical Engineering Research Center, Samsung Medical Center, Seoul, South Korea
- Department of Medical Device Management and Research, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, South Korea
| | - Ji-Yeon Kim
- Samsung Biomedical Research Institute, Center for Clinical Medicine, Samsung Medical Center, Seoul, South Korea
| | - Sun Ae Yun
- Samsung Biomedical Research Institute, Center for Clinical Medicine, Samsung Medical Center, Seoul, South Korea
| | - Mi-Ae Jang
- Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Ja-Hyun Jang
- Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Tae Yeul Kim
- Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
| | - Hee Jae Huh
- Department of Medical Device Management and Research, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, South Korea.
- Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
| | - Nam Yong Lee
- Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
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Park H, Kim DR, Shin A, Jeong E, Son S, Ahn JH, Ahn SY, Choi SJ, Oh SY, Chang YS, Kim YJ, Kang M. Loop-mediated isothermal amplification assay for screening congenital cytomegalovirus infection in newborns. Appl Microbiol Biotechnol 2023; 107:6789-6798. [PMID: 37725139 PMCID: PMC10589182 DOI: 10.1007/s00253-023-12771-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 08/17/2023] [Accepted: 09/02/2023] [Indexed: 09/21/2023]
Abstract
Congenital cytomegalovirus (CMV) infection is a common cause of sensorineural hearing loss and neurodevelopmental impairment in newborns. However, congenital CMV infection cannot be diagnosed using samples collected more than 3 weeks after birth because testing after this time cannot distinguish between congenital infection and postnatal infection. Herein, we developed a robust loop-mediated isothermal amplification (LAMP) assay for the large-scale screening of newborns for congenital CMV infection. In contrast to conventional quantitative polymerase chain reaction (qPCR), which detects CMV within a dynamic range of 1.0 × 106 to 1.0 × 102 copies/μL, our quantitative LAMP assay (qLAMP) detects CMV within a dynamic range of 1.1 × 108 to 1.1 × 103 copies/μL. Moreover, the turnaround time for obtaining results following DNA extraction is 90 min in qPCR but only 15 min in qLamp. The colorimetric LAMP assay can also detect CMV down to 1.1 × 103 copies/μL within 30 min, irrespective of the type of heat source. Our LAMP assay can be utilized in central laboratories as an alternative to conventional qPCR for quantitative CMV detection, or for point-of-care testing in low-resource environments, such as developing countries, via colorimetric naked-eye detection. KEY POINTS: • LAMP assay enables large-scale screening of newborns for congenital CMV infection. • LAMP allows colorimetric or quantitative detection of congenital CMV infection. • LAMP assay can be used as a point-of-care testing tool in low-resource environments.
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Affiliation(s)
- Hyeonseek Park
- Biomedical Engineering Research Center, Smart Healthcare Research Institute, Samsung Medical Center, Seoul, Republic of Korea
- Department of Medical Device Management and Research, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Republic of Korea
| | - Doo Ri Kim
- Department of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Areum Shin
- Department of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Eunjung Jeong
- Biomedical Engineering Research Center, Smart Healthcare Research Institute, Samsung Medical Center, Seoul, Republic of Korea
- Department of Medical Device Management and Research, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Republic of Korea
| | - Sohee Son
- Department of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jin-Hyun Ahn
- Department of Microbiology, Sungkyunkwan University School of Medicine, Suwon, Republic of Korea
| | - So Yoon Ahn
- Department of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Suk-Joo Choi
- Department of Gynecology and Obstetrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Soo-Young Oh
- Department of Gynecology and Obstetrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Yun Sil Chang
- Department of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Yae-Jean Kim
- Department of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
- Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Republic of Korea.
| | - Minhee Kang
- Biomedical Engineering Research Center, Smart Healthcare Research Institute, Samsung Medical Center, Seoul, Republic of Korea.
- Department of Medical Device Management and Research, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Republic of Korea.
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