Rowan Saloner, Adam M Staffaroni, Eric B Dammer, Erik C B Johnson, Emily W Paolillo, Amy Wise, Hilary W Heuer, Leah K Forsberg, Argentina Lario-Lago, Julia D Webb, Jacob W Vogel, Alexander F Santillo, Oskar Hansson, Joel H Kramer, Bruce L Miller, Jingyao Li, Joseph Loureiro, Rajeev Sivasankaran, Kathleen A Worringer, Nicholas T Seyfried, Jennifer S Yokoyama, Salvatore Spina, Lea T Grinberg, William W Seeley, Lawren VandeVrede, Peter A Ljubenkov, Ece Bayram, Andrea Bozoki, Danielle Brushaber, Ciaran M Considine, Gregory S Day, Bradford C Dickerson, Kimiko Domoto-Reilly, Kelley Faber, Douglas R Galasko, Tania Gendron, Daniel H Geschwind, Nupur Ghoshal, Neill Graff-Radford, Chadwick M Hales, Lawrence S Honig, Ging-Yuek R Hsiung, Edward D Huey, John Kornak, Walter Kremers, Maria I Lapid, Suzee E Lee, Irene Litvan, Corey T McMillan, Mario F Mendez, Toji Miyagawa, Alexander Pantelyat, Belen Pascual, Joseph Masdeu, Henry L Paulson, Leonard Petrucelli, Peter Pressman, Rosa Rademakers, Eliana Marisa Ramos, Katya Rascovsky, Erik D Roberson, Rodolfo Savica, Allison Snyder, Anna Campbell Sullivan, M Carmela Tartaglia, Marijne Vandebergh, Brad F Boeve, Howie J Rosen, Julio C Rojas, Adam L Boxer, Kaitlin B Casaletto
{"title":"脑脊液蛋白质组的大规模网络分析确定了额颞叶变性的分子特征。","authors":"Rowan Saloner, Adam M Staffaroni, Eric B Dammer, Erik C B Johnson, Emily W Paolillo, Amy Wise, Hilary W Heuer, Leah K Forsberg, Argentina Lario-Lago, Julia D Webb, Jacob W Vogel, Alexander F Santillo, Oskar Hansson, Joel H Kramer, Bruce L Miller, Jingyao Li, Joseph Loureiro, Rajeev Sivasankaran, Kathleen A Worringer, Nicholas T Seyfried, Jennifer S Yokoyama, Salvatore Spina, Lea T Grinberg, William W Seeley, Lawren VandeVrede, Peter A Ljubenkov, Ece Bayram, Andrea Bozoki, Danielle Brushaber, Ciaran M Considine, Gregory S Day, Bradford C Dickerson, Kimiko Domoto-Reilly, Kelley Faber, Douglas R Galasko, Tania Gendron, Daniel H Geschwind, Nupur Ghoshal, Neill Graff-Radford, Chadwick M Hales, Lawrence S Honig, Ging-Yuek R Hsiung, Edward D Huey, John Kornak, Walter Kremers, Maria I Lapid, Suzee E Lee, Irene Litvan, Corey T McMillan, Mario F Mendez, Toji Miyagawa, Alexander Pantelyat, Belen Pascual, Joseph Masdeu, Henry L Paulson, Leonard Petrucelli, Peter Pressman, Rosa Rademakers, Eliana Marisa Ramos, Katya Rascovsky, Erik D Roberson, Rodolfo Savica, Allison Snyder, Anna Campbell Sullivan, M Carmela Tartaglia, Marijne Vandebergh, Brad F Boeve, Howie J Rosen, Julio C Rojas, Adam L Boxer, Kaitlin B Casaletto","doi":"10.1038/s43587-025-00878-2","DOIUrl":null,"url":null,"abstract":"<p><p>The pathophysiological mechanisms driving disease progression of frontotemporal lobar degeneration (FTLD) and corresponding biomarkers are not fully understood. Here we leveraged aptamer-based proteomics (>4,000 proteins) to identify dysregulated communities of co-expressed cerebrospinal fluid proteins in 116 adults carrying autosomal dominant FTLD mutations (C9orf72, GRN and MAPT) compared with 39 non-carrier controls. Network analysis identified 31 protein co-expression modules. Proteomic signatures of genetic FTLD clinical severity included increased abundance of RNA splicing (particularly in C9orf72 and GRN) and extracellular matrix (particularly in MAPT) modules, as well as decreased abundance of synaptic/neuronal and autophagy modules. The generalizability of genetic FTLD proteomic signatures was tested and confirmed in independent cohorts of (1) sporadic progressive supranuclear palsy-Richardson syndrome and (2) frontotemporal dementia spectrum clinical syndromes. Network-based proteomics hold promise for identifying replicable molecular pathways in adults living with FTLD. 'Hub' proteins driving co-expression of affected modules warrant further attention as candidate biomarkers and therapeutic targets.</p>","PeriodicalId":94150,"journal":{"name":"Nature aging","volume":" ","pages":""},"PeriodicalIF":17.0000,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Large-scale network analysis of the cerebrospinal fluid proteome identifies molecular signatures of frontotemporal lobar degeneration.\",\"authors\":\"Rowan Saloner, Adam M Staffaroni, Eric B Dammer, Erik C B Johnson, Emily W Paolillo, Amy Wise, Hilary W Heuer, Leah K Forsberg, Argentina Lario-Lago, Julia D Webb, Jacob W Vogel, Alexander F Santillo, Oskar Hansson, Joel H Kramer, Bruce L Miller, Jingyao Li, Joseph Loureiro, Rajeev Sivasankaran, Kathleen A Worringer, Nicholas T Seyfried, Jennifer S Yokoyama, Salvatore Spina, Lea T Grinberg, William W Seeley, Lawren VandeVrede, Peter A Ljubenkov, Ece Bayram, Andrea Bozoki, Danielle Brushaber, Ciaran M Considine, Gregory S Day, Bradford C Dickerson, Kimiko Domoto-Reilly, Kelley Faber, Douglas R Galasko, Tania Gendron, Daniel H Geschwind, Nupur Ghoshal, Neill Graff-Radford, Chadwick M Hales, Lawrence S Honig, Ging-Yuek R Hsiung, Edward D Huey, John Kornak, Walter Kremers, Maria I Lapid, Suzee E Lee, Irene Litvan, Corey T McMillan, Mario F Mendez, Toji Miyagawa, Alexander Pantelyat, Belen Pascual, Joseph Masdeu, Henry L Paulson, Leonard Petrucelli, Peter Pressman, Rosa Rademakers, Eliana Marisa Ramos, Katya Rascovsky, Erik D Roberson, Rodolfo Savica, Allison Snyder, Anna Campbell Sullivan, M Carmela Tartaglia, Marijne Vandebergh, Brad F Boeve, Howie J Rosen, Julio C Rojas, Adam L Boxer, Kaitlin B Casaletto\",\"doi\":\"10.1038/s43587-025-00878-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The pathophysiological mechanisms driving disease progression of frontotemporal lobar degeneration (FTLD) and corresponding biomarkers are not fully understood. Here we leveraged aptamer-based proteomics (>4,000 proteins) to identify dysregulated communities of co-expressed cerebrospinal fluid proteins in 116 adults carrying autosomal dominant FTLD mutations (C9orf72, GRN and MAPT) compared with 39 non-carrier controls. Network analysis identified 31 protein co-expression modules. Proteomic signatures of genetic FTLD clinical severity included increased abundance of RNA splicing (particularly in C9orf72 and GRN) and extracellular matrix (particularly in MAPT) modules, as well as decreased abundance of synaptic/neuronal and autophagy modules. The generalizability of genetic FTLD proteomic signatures was tested and confirmed in independent cohorts of (1) sporadic progressive supranuclear palsy-Richardson syndrome and (2) frontotemporal dementia spectrum clinical syndromes. Network-based proteomics hold promise for identifying replicable molecular pathways in adults living with FTLD. 'Hub' proteins driving co-expression of affected modules warrant further attention as candidate biomarkers and therapeutic targets.</p>\",\"PeriodicalId\":94150,\"journal\":{\"name\":\"Nature aging\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":17.0000,\"publicationDate\":\"2025-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature aging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1038/s43587-025-00878-2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature aging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1038/s43587-025-00878-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
Large-scale network analysis of the cerebrospinal fluid proteome identifies molecular signatures of frontotemporal lobar degeneration.
The pathophysiological mechanisms driving disease progression of frontotemporal lobar degeneration (FTLD) and corresponding biomarkers are not fully understood. Here we leveraged aptamer-based proteomics (>4,000 proteins) to identify dysregulated communities of co-expressed cerebrospinal fluid proteins in 116 adults carrying autosomal dominant FTLD mutations (C9orf72, GRN and MAPT) compared with 39 non-carrier controls. Network analysis identified 31 protein co-expression modules. Proteomic signatures of genetic FTLD clinical severity included increased abundance of RNA splicing (particularly in C9orf72 and GRN) and extracellular matrix (particularly in MAPT) modules, as well as decreased abundance of synaptic/neuronal and autophagy modules. The generalizability of genetic FTLD proteomic signatures was tested and confirmed in independent cohorts of (1) sporadic progressive supranuclear palsy-Richardson syndrome and (2) frontotemporal dementia spectrum clinical syndromes. Network-based proteomics hold promise for identifying replicable molecular pathways in adults living with FTLD. 'Hub' proteins driving co-expression of affected modules warrant further attention as candidate biomarkers and therapeutic targets.