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Broce IJ, Sirkis DW, Nillo RM, Bonham LW, Lee SE, Miller BL, Castruita PA, Sturm VE, Sugrue LS, Desikan RS, Yokoyama JS. C9orf72 gene networks in the human brain correlate with cortical thickness in C9-FTD and implicate vulnerable cell types. Front Neurosci 2024; 18:1258996. [PMID: 38469573 PMCID: PMC10925697 DOI: 10.3389/fnins.2024.1258996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 01/15/2024] [Indexed: 03/13/2024] Open
Abstract
Introduction A hexanucleotide repeat expansion (HRE) intronic to chromosome 9 open reading frame 72 (C9orf72) is recognized as the most common genetic cause of amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and ALS-FTD. Identifying genes that show similar regional co-expression patterns to C9orf72 may help identify novel gene targets and biological mechanisms that mediate selective vulnerability to ALS and FTD pathogenesis. Methods We leveraged mRNA expression data in healthy brain from the Allen Human Brain Atlas to evaluate C9orf72 co-expression patterns. To do this, we correlated average C9orf72 expression values in 51 regions across different anatomical divisions (cortex, subcortex, and cerebellum) with average gene expression values for 15,633 protein-coding genes, including 54 genes known to be associated with ALS, FTD, or ALS-FTD. We then performed imaging transcriptomic analyses to evaluate whether the identified C9orf72 co-expressed genes correlated with patterns of cortical thickness in symptomatic C9orf72 pathogenic HRE carriers (n = 19) compared to controls (n = 23). Lastly, we explored whether genes with significant C9orf72 imaging transcriptomic correlations (i.e., "C9orf72 imaging transcriptomic network") were enriched in specific cell populations in the brain and enriched for specific biological and molecular pathways. Results A total of 2,120 genes showed an anatomical distribution of gene expression in the brain similar to C9orf72 and significantly correlated with patterns of cortical thickness in C9orf72 HRE carriers. This C9orf72 imaging transcriptomic network was differentially expressed in cell populations previously implicated in ALS and FTD, including layer 5b cells, cholinergic neurons in the spinal cord and brainstem and medium spiny neurons of the striatum, and was enriched for biological and molecular pathways associated with protein ubiquitination, autophagy, cellular response to DNA damage, endoplasmic reticulum to Golgi vesicle-mediated transport, among others. Conclusion Considered together, we identified a network of C9orf72 associated genes that may influence selective regional and cell-type-specific vulnerabilities in ALS/FTD.
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Affiliation(s)
- Iris J. Broce
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
- Department of Neurosciences, University of California San Diego, San Diego, CA, United States
| | - Daniel W. Sirkis
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Ryan M. Nillo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Luke W. Bonham
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Suzee E. Lee
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Bruce L. Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Patricia A. Castruita
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Virginia E. Sturm
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
- Global Brain Health Institute, University of California San Francisco, San Francisco, CA, United States
| | - Leo S. Sugrue
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Rahul S. Desikan
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Jennifer S. Yokoyama
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
- Global Brain Health Institute, University of California San Francisco, San Francisco, CA, United States
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Broce IJ, Sirkis DW, Nillo RM, Bonham LW, Lee SE, Miller B, Castruita P, Sturm VE, Sugrue LS, Desikan RS, Yokoyama JS. C9orf72 gene networks in the human brain correlate with cortical thickness in C9-FTD and implicate vulnerable cell types. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.17.549377. [PMID: 37503230 PMCID: PMC10370095 DOI: 10.1101/2023.07.17.549377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Introduction A hexanucleotide repeat expansion (HRE) intronic to chromosome 9 open reading frame 72 (C9orf72) is recognized as the most common genetic cause of amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and ALS-FTD. Identifying genes that show similar regional co-expression patterns to C9orf72 may help identify novel gene targets and biological mechanisms that mediate selective vulnerability to ALS and FTD pathogenesis. Methods We leveraged mRNA expression data in healthy brain from the Allen Human Brain Atlas to evaluate C9orf72 co-expression patterns. To do this, we correlated average C9orf72 expression values in 51 regions across different anatomical divisions (cortex, subcortex, cerebellum) with average gene expression values for 15,633 protein-coding genes, including 50 genes known to be associated with ALS, FTD, or ALS-FTD. We then evaluated whether the identified C9orf72 co-expressed genes correlated with patterns of cortical thickness in symptomatic C9orf72 pathogenic HRE carriers (n=19). Lastly, we explored whether genes with significant C9orf72 radiogenomic correlations (i.e., 'C9orf72 gene network') were enriched in specific cell populations in the brain and enriched for specific biological and molecular pathways. Results A total of 1,748 genes showed an anatomical distribution of gene expression in the brain similar to C9orf72 and significantly correlated with patterns of cortical thickness in C9orf72 HRE carriers. This C9orf72 gene network was differentially expressed in cell populations previously implicated in ALS and FTD, including layer 5b cells, cholinergic motor neurons in the spinal cord, and medium spiny neurons of the striatum, and was enriched for biological and molecular pathways associated with multiple neurotransmitter systems, protein ubiquitination, autophagy, and MAPK signaling, among others. Conclusions Considered together, we identified a network of C9orf72-associated genes that may influence selective regional and cell-type-specific vulnerabilities in ALS/FTD.
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Affiliation(s)
- Iris J. Broce
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
- Department of Neurosciences, University of California, San Diego, San Diego, CA, United States
| | - Daniel W. Sirkis
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Ryan M. Nillo
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Luke W. Bonham
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Suzee E. Lee
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Bruce Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Patricia Castruita
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Virginia E. Sturm
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
- Global Brain Health Institute, University of California, San Francisco, San Francisco, CA, and Trinity College Dublin, Dublin, Ireland
| | - Leo S. Sugrue
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Rahul S. Desikan
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Jennifer S. Yokoyama
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
- Global Brain Health Institute, University of California, San Francisco, San Francisco, CA, and Trinity College Dublin, Dublin, Ireland
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Ryu J, Komoto Y, Ohshiro T, Taniguchi M. Direct biomolecule discrimination in mixed samples using nanogap-based single-molecule electrical measurement. Sci Rep 2023; 13:9103. [PMID: 37277540 DOI: 10.1038/s41598-023-35724-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 05/23/2023] [Indexed: 06/07/2023] Open
Abstract
In single-molecule measurements, metal nanogap electrodes directly measure the current of a single molecule. This technique has been actively investigated as a new detection method for a variety of samples. Machine learning has been applied to analyze signals derived from single molecules to improve the identification accuracy. However, conventional identification methods have drawbacks, such as the requirement of data to be measured for each target molecule and the electronic structure variation of the nanogap electrode. In this study, we report a technique for identifying molecules based on single-molecule measurement data measured only in mixed sample solutions. Compared with conventional methods that require training classifiers on measurement data from individual samples, our proposed method successfully predicts the mixing ratio from the measurement data in mixed solutions. This demonstrates the possibility of identifying single molecules using only data from mixed solutions, without prior training. This method is anticipated to be particularly useful for the analysis of biological samples in which chemical separation methods are not applicable, thereby increasing the potential for single-molecule measurements to be widely adopted as an analytical technique.
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Affiliation(s)
- Jiho Ryu
- SANKEN, Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka, 567-0047, Japan
| | - Yuki Komoto
- SANKEN, Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka, 567-0047, Japan
- Artificial Intelligence Research Center, Osaka University, Ibaraki, Osaka, 567-0047, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiative (OTRI), Osaka University, Ibaraki, Osaka, 567-0047, Japan
| | - Takahito Ohshiro
- SANKEN, Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka, 567-0047, Japan
| | - Masateru Taniguchi
- SANKEN, Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka, 567-0047, Japan.
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Yang Z, Zhang S, Xia T, Fan Y, Shan Y, Zhang K, Xiong J, Gu M, You B. RNA Modifications Meet Tumors. Cancer Manag Res 2022; 14:3223-3243. [PMID: 36444355 PMCID: PMC9700476 DOI: 10.2147/cmar.s391067] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Accepted: 11/11/2022] [Indexed: 09/14/2023] Open
Abstract
RNA modifications occur through the whole process of gene expression regulation, including transcription, translation, and post-translational processes. They are closely associated with gene expression, RNA stability, and cell cycle. RNA modifications in tumor cells play a vital role in tumor development and metastasis, changes in the tumor microenvironment, drug resistance in tumors, construction of tumor cell-cell "internet", etc. Several types of RNA modifications have been identified to date and have various effects on the biological characteristics of different tumors. In this review, we discussed the function of RNA modifications, including N 6-methyladenine (m6A), 5-methylcytosine (m5C), N 7-methyladenosine (m7G), N 1-methyladenosine (m1A), pseudouridine (Ψ), and adenosine-to-inosine (A-to-I), in the microenvironment and therapy of solid and liquid tumors.
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Affiliation(s)
- Zhiyuan Yang
- Department of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
- Institute of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
| | - Siyu Zhang
- Department of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
- Institute of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
| | - Tian Xia
- Department of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
- Institute of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
| | - Yue Fan
- Department of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
- Institute of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
| | - Ying Shan
- Department of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
- Institute of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
| | - Kaiwen Zhang
- Department of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
- Institute of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
| | - Jiayan Xiong
- Department of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
- Institute of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
| | - Miao Gu
- Department of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
- Institute of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
| | - Bo You
- Department of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
- Institute of Otolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, People’s Republic of China
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