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1. Molecular landscape of the overlap between Alzheimer’s disease and somatic insulin-related diseases

Author: Ruisch, I. Hyun, Widomska, Joanna, De Witte, Ward, Mota, Nina R., Fanelli, Giuseppe, Van Gils, Veerle, Jansen, Willemijn J., Vos, Stephanie J. B., Fóthi, Abel, Barta, Csaba, Berkel, Simone, Alam, Kazi A., Martinez, Aurora, Haavik, Jan, O’Leary, Aet, Slattery, David, Sullivan, Mairéad, Glennon, Jeffrey, Buitelaar, Jan K., Bralten, Janita, Franke, Barbara, and Poelmans, Geert
Published: 2024
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2. Involvement of the choroid plexus in Alzheimer’s disease pathophysiology: findings from mouse and human proteomic studies

Author: Delvenne, Aurore, Vandendriessche, Charysse, Gobom, Johan, Burgelman, Marlies, Dujardin, Pieter, De Nolf, Clint, Tijms, Betty M., Teunissen, Charlotte E., Schindler, Suzanne E., Verhey, Frans, Ramakers, Inez, Martinez-Lage, Pablo, Tainta, Mikel, Vandenberghe, Rik, Schaeverbeke, Jolien, Engelborghs, Sebastiaan, De Roeck, Ellen, Popp, Julius, Peyratout, Gwendoline, Tsolaki, Magda, Freund-Levi, Yvonne, Lovestone, Simon, Streffer, Johannes, Bertram, Lars, Blennow, Kaj, Zetterberg, Henrik, Visser, Pieter Jelle, Vandenbroucke, Roosmarijn E., and Vos, Stephanie J. B.
Published: 2024
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3. The clinical importance of suspected non-Alzheimer disease pathophysiology

Author: Vos, Stephanie J. B., Delvenne, Aurore, Jack, Jr, Clifford R., Thal, Dietmar R., and Visser, Pieter Jelle
Published: 2024
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4. Synaptic protein CSF levels relate to memory scores in individuals without dementia.

Author: Wesenhagen, Kirsten E. J., de Leeuw, Diederick M., Tomassen, Jori, Gobom, Johan, Bos, Isabelle, Vos, Stephanie J. B., Martinez-Lage, Pablo, Tainta, Mikel, Popp, Julius, Peyratout, Gwendoline, Tsolaki, Magda, Vandenberghe, Rik, Freund-Levi, Yvonne, Verhey, Frans, Lovestone, Simon, Streffer, Johannes, Dobricic, Valerija, Blennow, Kaj, Scheltens, Philip, and Smit, August B.
Abstract: Background: We investigated how cerebrospinal fluid levels of synaptic proteins associate with memory function in normal cognition (CN) and mild cognitive impairment (MCI), and investigated the effect of amyloid positivity on these associations. Methods: We included 242 CN (105(43%) abnormal amyloid), and 278 MCI individuals (183(66%) abnormal amyloid) from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). For 181 (EMIF-AD MBD) and 36 (ADNI) proteins with a synaptic annotation in SynGO, associations with word learning recall were analysed with linear models. Results: Subsets of synaptic proteins showed lower levels with worse recall in preclinical AD (EMIF-AD MBD: 7, ADNI: 5 proteins, none overlapping), prodromal AD (EMIF-AD MBD only, 27 proteins) and non-AD MCI (EMIF-AD MBD: 1, ADNI: 7 proteins). The majority of these associations were specific to these clinical groups. Conclusions: Synaptic disturbance-related memory impairment occurred very early in AD, indicating it may be relevant to develop therapies targeting the synapse early in the disease. [ABSTRACT FROM AUTHOR]
Published: 2025
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5. Rare variants in IFFO1, DTNB, NLRC3 and SLC22A10 associate with Alzheimer’s disease CSF profile of neuronal injury and inflammation

Author: Neumann, Alexander, Küçükali, Fahri, Bos, Isabelle, Vos, Stephanie J. B., Engelborghs, Sebastiaan, De Pooter, Tim, Joris, Geert, De Rijk, Peter, De Roeck, Ellen, Tsolaki, Magda, Verhey, Frans, Martinez-Lage, Pablo, Tainta, Mikel, Frisoni, Giovanni, Blin, Oliver, Richardson, Jill, Bordet, Régis, Scheltens, Philip, Popp, Julius, Peyratout, Gwendoline, Johannsen, Peter, Frölich, Lutz, Vandenberghe, Rik, Freund-Levi, Yvonne, Streffer, Johannes, Lovestone, Simon, Legido-Quigley, Cristina, ten Kate, Mara, Barkhof, Frederik, Strazisar, Mojca, Zetterberg, Henrik, Bertram, Lars, Visser, Pieter Jelle, van Broeckhoven, Christine, and Sleegers, Kristel
Published: 2022
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6. Temporally ordered associations between type 2 diabetes and brain disorders – a Danish register-based cohort study

Author: Wimberley, Theresa, Horsdal, Henriette T., Brikell, Isabell, Laursen, Thomas M., Astrup, Aske, Fanelli, Giuseppe, Bralten, Janita, Poelmans, Geert, Gils, Veerle Van, Jansen, Willemijn J., Vos, Stephanie J. B., Bertaina-Anglade, Valérie, Camacho-Barcia, Lucia, Mora-Maltas, Bernat, Fernandez-Aranda, Fernando, Bonet, Mònica B., Salas-Salvadó, Jordi, Franke, Barbara, and Dalsgaard, Søren
Published: 2022
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7. Correction: Cerebrospinal fluid tau levels are associated with abnormal neuronal plasticity markers in Alzheimer’s disease

Author: Visser, Pieter Jelle, Reus, Lianne M., Gobom, Johan, Jansen, Iris, Dicks, Ellen, van der Lee, Sven J., Tsolaki, Magda, Verhey, Frans R. J., Popp, Julius, Martinez-Lage, Pablo, Vandenberghe, Rik, Lleó, Alberto, Molinuevo, José Luís, Engelborghs, Sebastiaan, Freund-Levi, Yvonne, Froelich, Lutz, Sleegers, Kristel, Dobricic, Valerija, Lovestone, Simon, Streffer, Johannes, Vos, Stephanie J. B., Bos, Isabelle, Smit, August B., Blennow, Kaj, Scheltens, Philip, Teunissen, Charlotte E., Bertram, Lars, Zetterberg, Henrik, and Tijms, Betty M.
Published: 2022
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8. Cerebrospinal fluid tau levels are associated with abnormal neuronal plasticity markers in Alzheimer’s disease

Author: Visser, Pieter Jelle, Reus, Lianne M., Gobom, Johan, Jansen, Iris, Dicks, Ellen, van der Lee, Sven J., Tsolaki, Magda, Verhey, Frans R. J., Popp, Julius, Martinez-Lage, Pablo, Vandenberghe, Rik, Lleó, Alberto, Molinuevo, José Luís, Engelborghs, Sebastiaan, Freund-Levi, Yvonne, Froelich, Lutz, Sleegers, Kristel, Dobricic, Valerija, Lovestone, Simon, Streffer, Johannes, Vos, Stephanie J. B., Bos, Isabelle, Smit, August B., Blennow, Kaj, Scheltens, Philip, Teunissen, Charlotte E., Bertram, Lars, Zetterberg, Henrik, and Tijms, Betty M.
Published: 2022
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9. Insulinopathies of the brain? Genetic overlap between somatic insulin-related and neuropsychiatric disorders

Author: Fanelli, Giuseppe, Franke, Barbara, De Witte, Ward, Ruisch, I. Hyun, Haavik, Jan, van Gils, Veerle, Jansen, Willemijn J., Vos, Stephanie J. B., Lind, Lars, Buitelaar, Jan K., Banaschewski, Tobias, Dalsgaard, Søren, Serretti, Alessandro, Mota, Nina Roth, Poelmans, Geert, and Bralten, Janita
Published: 2022
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10. Involvement of the choroid plexus in Alzheimer's disease pathophysiology: A mouse and human proteomic study.

Author: Delvenne, Aurore, Vandendriessche, Charysse, Gobom, Johan, Burgelman, Marlies, Dujardin, Pieter, De Nolf, Clint, Tijms, Betty M., Schindler, Suzanne E., Verhey, Frans R.J., Ramakers, Inez H.G.B., Zetterberg, Henrik, Visser, Pieter Jelle, Vandenbroucke, Roosmarijn E, and Vos, Stephanie J. B.
Abstract: Background: Structural and functional changes of the choroid plexus (ChP) have been reported in Alzheimer's disease (AD). Nonetheless, the role of the ChP in the pathogenesis of AD remains largely unknown. We aim to unravel the relationship between ChP functioning and core AD pathogenesis using a unique proteomic approach in mice and humans. Method: We used an App knock‐in mouse model, AppNL‐G‐F, with amyloid pathology to study the association between AD brain pathology and protein changes in mouse ChP tissue and CSF, using liquid chromatography mass spectrometry. Mouse proteomes were investigated at 7 weeks old (n = 5) and at 40 weeks old (n = 5). Results were compared to human AD CSF proteomic data (n = 496; from EMIF‐AD MBD, Knight ADRC, and Maastricht BB‐ACL studies) to identify key proteins and pathways associated with ChP changes in AD. Result: Compared to wild‐type (WT) mice, AppNL‐G‐F mice aged 7 or 40 weeks old had significant differences in some protein levels in ChP tissue (Figure 1 and 2). At both ages, ChP tissue proteomic changes were related to pathways associated with epithelial cells, mitochondrion, protein modification, extracellular matrix (ECM) and lipids. Pathways related to lysosomal function, endocytosis, protein formation, actin, and complement were uniquely dysregulated at 7 weeks, while pathways associated with nervous system, immune system, protein degradation and vascular system were uniquely dysregulated at 40 weeks. Mouse CSF proteomics showed changes in similar pathways as seen in ChP tissue proteomics (Figure 3). Proteomic analyses were also performed in non‐demented human participants with abnormal amyloid but normal tau levels. Among proteins that were up‐regulated in CSF of those participants compared to controls, a significant number were predominantly expressed in the ChP (38 to 56% of the up‐regulated proteins). The dysregulated proteins with a predominant expression in the ChP in those individuals were related to similar pathways as seen in AppNL‐G‐F mice ChP tissue and CSF proteomics (Figure 3). Conclusion: ChP changes are associated with amyloid pathology. Key pathways involved in ChP dysfunction in AD are associated with the ECM, lysosomal function, lipids, protein processing, complement, vascular system and mitochondrion. The ChP could become a novel promising target for AD treatment. [ABSTRACT FROM AUTHOR]
Published: 2024
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11. Paired plasma lipidomics and proteomics analysis in the conversion from mild cognitive impairment to Alzheimer's disease

Author: Gómez-Pascual, A, Naccache, T, Xu, J, Hooshmand, K, Wretlind, A, Gabrielli, M, Lombardo, M, Shi, L, Buckley, N, Tijms, B, Vos, S, Ten Kate, M, Engelborghs, S, Sleegers, K, Frisoni, G, Wallin, A, Lleó, A, Popp, J, Martinez-Lage, P, Streffer, J, Barkhof, F, Zetterberg, H, Visser, P, Lovestone, S, Bertram, L, Nevado-Holgado, A, Gualerzi, A, Picciolini, S, Proitsi, P, Verderio, C, Botía, J, Legido-Quigley, C, Gómez-Pascual, Alicia, Naccache, Talel, Xu, Jin, Hooshmand, Kourosh, Wretlind, Asger, Gabrielli, Martina, Lombardo, Marta Tiffany, Shi, Liu, Buckley, Noel J, Tijms, Betty M, Vos, Stephanie J B, Ten Kate, Mara, Engelborghs, Sebastiaan, Sleegers, Kristel, Frisoni, Giovanni B, Wallin, Anders, Lleó, Alberto, Popp, Julius, Martinez-Lage, Pablo, Streffer, Johannes, Barkhof, Frederik, Zetterberg, Henrik, Visser, Pieter Jelle, Lovestone, Simon, Bertram, Lars, Nevado-Holgado, Alejo J, Gualerzi, Alice, Picciolini, Silvia, Proitsi, Petroula, Verderio, Claudia, Botía, Juan A, Legido-Quigley, Cristina, Gómez-Pascual, A, Naccache, T, Xu, J, Hooshmand, K, Wretlind, A, Gabrielli, M, Lombardo, M, Shi, L, Buckley, N, Tijms, B, Vos, S, Ten Kate, M, Engelborghs, S, Sleegers, K, Frisoni, G, Wallin, A, Lleó, A, Popp, J, Martinez-Lage, P, Streffer, J, Barkhof, F, Zetterberg, H, Visser, P, Lovestone, S, Bertram, L, Nevado-Holgado, A, Gualerzi, A, Picciolini, S, Proitsi, P, Verderio, C, Botía, J, Legido-Quigley, C, Gómez-Pascual, Alicia, Naccache, Talel, Xu, Jin, Hooshmand, Kourosh, Wretlind, Asger, Gabrielli, Martina, Lombardo, Marta Tiffany, Shi, Liu, Buckley, Noel J, Tijms, Betty M, Vos, Stephanie J B, Ten Kate, Mara, Engelborghs, Sebastiaan, Sleegers, Kristel, Frisoni, Giovanni B, Wallin, Anders, Lleó, Alberto, Popp, Julius, Martinez-Lage, Pablo, Streffer, Johannes, Barkhof, Frederik, Zetterberg, Henrik, Visser, Pieter Jelle, Lovestone, Simon, Bertram, Lars, Nevado-Holgado, Alejo J, Gualerzi, Alice, Picciolini, Silvia, Proitsi, Petroula, Verderio, Claudia, Botía, Juan A, and Legido-Quigley, Cristina
Abstract: Background: Alzheimer's disease (AD) is a neurodegenerative condition for which there is currently no available medication that can stop its progression. Previous studies suggest that mild cognitive impairment (MCI) is a phase that precedes the disease. Therefore, a better understanding of the molecular mechanisms behind MCI conversion to AD is needed. Method: Here, we propose a machine learning-based approach to detect the key metabolites and proteins involved in MCI progression to AD using data from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Study. Proteins and metabolites were evaluated separately in multiclass models (controls, MCI and AD) and together in MCI conversion models (MCI stable vs converter). Only features selected as relevant by 3/4 algorithms proposed were kept for downstream analysis. Results: Multiclass models of metabolites highlighted nine features further validated in an independent cohort (0.726 mean balanced accuracy). Among these features, one metabolite, oleamide, was selected by all the algorithms. Further in-vitro experiments in rodents showed that disease-associated microglia excreted oleamide in vesicles. Multiclass models of proteins stood out with nine features, validated in an independent cohort (0.720 mean balanced accuracy). However, none of the proteins was selected by all the algorithms. Besides, to distinguish between MCI stable and converters, 14 key features were selected (0.872 AUC), including tTau, alpha-synuclein (SNCA), junctophilin-3 (JPH3), properdin (CFP) and peptidase inhibitor 15 (PI15) among others. Conclusions: This omics integration approach highlighted a set of molecules associated with MCI conversion important in neuronal and glia inflammation pathways.
Published: 2024

12. Blood DNA methylomic signatures associated with CSF biomarkers of Alzheimer's disease in the EMIF-AD study

Author: Smith, Rebecca G., Pishva, Ehsan, Kouhsar, Morteza, Imm, Jennifer, Dobricic, Valerija, Johannsen, Peter, Wittig, Michael, Franke, Andre, Vandenberghe, Rik, Schaeverbeke, Jolien, Freund-Levi, Yvonne, Frölich, Lutz, Scheltens, Philip, Teunissen, Charlotte E., Frisoni, Giovanni, Blin, Olivier, Richardson, Jill C., Bordet, Régis, Engelborghs, Sebastiaan, de Roeck, Ellen, Martinez-Lage, Pablo, Altuna, Miren, Tainta, Mikel, Lleó, Alberto, Sala, Isabel, Popp, Julius, Peyratout, Gwendoline, Winchester, Laura, Nevado-Holgado, Alejo, Verhey, Frans, Tsolaki, Magda, Andreasson, Ulf, Blennow, Kaj, Zetterberg, Henrik, Streffer, Johannes, Vos, Stephanie J. B., Lovestone, Simon, Visser, Pieter Jelle, Bertram, Lars, Lunnon, Katie, Smith, Rebecca G., Pishva, Ehsan, Kouhsar, Morteza, Imm, Jennifer, Dobricic, Valerija, Johannsen, Peter, Wittig, Michael, Franke, Andre, Vandenberghe, Rik, Schaeverbeke, Jolien, Freund-Levi, Yvonne, Frölich, Lutz, Scheltens, Philip, Teunissen, Charlotte E., Frisoni, Giovanni, Blin, Olivier, Richardson, Jill C., Bordet, Régis, Engelborghs, Sebastiaan, de Roeck, Ellen, Martinez-Lage, Pablo, Altuna, Miren, Tainta, Mikel, Lleó, Alberto, Sala, Isabel, Popp, Julius, Peyratout, Gwendoline, Winchester, Laura, Nevado-Holgado, Alejo, Verhey, Frans, Tsolaki, Magda, Andreasson, Ulf, Blennow, Kaj, Zetterberg, Henrik, Streffer, Johannes, Vos, Stephanie J. B., Lovestone, Simon, Visser, Pieter Jelle, Bertram, Lars, and Lunnon, Katie
Abstract: INTRODUCTION: We investigated blood DNA methylation patterns associated with 15 well-established cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) pathophysiology, neuroinflammation, and neurodegeneration. METHODS: We assessed DNA methylation in 885 blood samples from the European Medical Information Framework for Alzheimer's Disease (EMIF-AD) study using the EPIC array. RESULTS: We identified Bonferroni-significant differential methylation associated with CSF YKL-40 (five loci) and neurofilament light chain (NfL; seven loci) levels, with two of the loci associated with CSF YKL-40 levels correlating with plasma YKL-40 levels. A co-localization analysis showed shared genetic variants underlying YKL-40 DNA methylation and CSF protein levels, with evidence that DNA methylation mediates the association between genotype and protein levels. Weighted gene correlation network analysis identified two modules of co-methylated loci correlated with several amyloid measures and enriched in pathways associated with lipoproteins and development. DISCUSSION: We conducted the most comprehensive epigenome-wide association study (EWAS) of AD-relevant CSF biomarkers to date. Future work should explore the relationship between YKL-40 genotype, DNA methylation, and protein levels in the brain. HIGHLIGHTS: Blood DNA methylation was assessed in the EMIF-AD MBD study. Epigenome-wide association studies (EWASs) were performed for 15 Alzheimer's disease (AD)-relevant cerebrospinal fluid (CSF) biomarker measures. Five Bonferroni-significant loci were associated with YKL-40 levels and seven with neurofilament light chain (NfL). DNA methylation in YKL-40 co-localized with previously reported genetic variation. DNA methylation potentially mediates the effect of single-nucleotide polymorphisms (SNPs) in YKL-40 on CSF protein levels., Funding information: Innovative Medicines Initiative Joint Undertaking, Grant/Award Number: 115372; European Union’s Seventh Framework Program, Grant/Award Number: FP7/2007-2013; Alzheimer’s Society, Grant/Award Number: AS-PG-14-038; Medical Research Council (MRC), Grant/Award Number: MR/S011625/1; National Institute on Aging, Grant/Award Number: R01AG067015; ZonMw Memorabel/Alzheimer Nederland, Grant/Award Number: 733050516; Stichting Alzheimer Onderzoek, Grant/Award Numbers: #13007, #11020, #2017-032; Flemish Government, Grant/Award Number: VIND IWT 135043; Fonds Wetenschappelijk Onderzoek, Grant/Award Number: #12Y1620N; Department of Health of the Basque Government, Grant/Award Numbers: 2016111096, S-PR12CH001, S-PR13ZH001; Carlos III Institute Ministry of Health Government of Spain, Grant/Award Number: PI12/02262; Swiss National Science Foundation, Grant/Award Numbers: #320030_141179, 320030_204886; Synapsis Foundation—Dementia Research Switzerland, Grant/Award Number: #2017-PI01; Swedish Research Council, Grant/Award Numbers: #2022-01018, #2017-00915, #2019-02397; European Union’s Horizon Europe research and innovation programme, Grant/Award Number: 101053962; Swedish State Support for Clinical Research, Grant/Award Number: #ALFGBG-71320; Alzheimer Drug Discovery Foundation, Grant/Award Number: #201809-2016862; AD Strategic Fund and the Alzheimer’s Association, Grant/Award Numbers: #ADSF-21-831376-C, #ADSF-21-831381-C, #ADSF-21-831377-C; Bluefield Project; Olav Thon Foundation; Erling-Persson Family Foundation; Stiftelsen för Gamla Tjänarinnor; Hjärnfonden, Grant/Award Number: #FO2022-0270; European Union’s Horizon 2020 research and innovation programme, Grant/Award Number: 860197; European Union Joint Programme—Neurodegenerative Disease Research, Grant/Award Number: JPND2021-00694; National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre; UK Dementia Research Institute, Grant/Award Number: UKDRI-1003; Sw
Published: 2024
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13. Biomarkers voor de ziekte van Alzheimer: relaties met vasculaire factoren, neurodegeneratie en cognitie in de predementiële fasen

Author: Bos, Isabelle, Vos, Stephanie J. B., Verhey, Frans R. J., and Visser, Pieter Jelle
Published: 2019
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14. The potential cost‐effectiveness of roflumilast drug treatment in mild cognitive impairment

Author: Handels, Ron, primary, Grimm, Sabine, additional, Blokland, Arjan, additional, Possemis, Nina, additional, Ramakers, Inez H.G.B., additional, Sambeth, Anke, additional, Verhey, Frans R.J., additional, Vos, Stephanie J. B., additional, Joore, Manuela, additional, Prickaerts, Jos, additional, and Jönsson, Linus, additional
Published: 2023
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15. Blood DNA methylomic signatures associated with CSF biomarkers of Alzheimer’s disease in the EMIF‐AD Multimodal Biomarker Discovery study

Author: Smith, Rebecca G., primary, Imm, Jennifer L, additional, Dobricic, Valerija, additional, Sommerer, Yasmine, additional, Bos, Isabelle, additional, Vos, Stephanie J. B., additional, Verhey, Frans R.J., additional, Scheltens, Philip, additional, Engelborgs, Sebastiaan, additional, Frisoni, Giovanni B, additional, Blin, Olivier, additional, Richardson, Jill C, additional, Bordet, Régis, additional, Tsolaki, Magda, additional, Popp, Julius, additional, Martinez‐Lage, Pablo, additional, Lleo, Alberto, additional, Johannsen, Peter, additional, Freund‐Levi, Yvonne, additional, Lutz, Frölich, additional, Vandenberghe, Rik, additional, Wittig, Michael, additional, Frank, Andre, additional, Lovestone, Simon, additional, Streffer, Johannes, additional, Andreasson, Ulf, additional, Blennow, Kaj, additional, Visser, Pieter Jelle, additional, Zetterberg, Henrik, additional, Bertram, Lars, additional, and Lunnon, Katie, additional
Published: 2023
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16. Whole-exome rare-variant analysis of Alzheimer's disease and related biomarker traits

Author: Küçükali, Fahri, Neumann, Alexander, Van Dongen, Jasper, De Pooter, Tim, Joris, Geert, De Rijk, Peter, Ohlei, Olena, Dobricic, Valerija, Bos, Isabelle, Vos, Stephanie J. B., Engelborghs, Sebastiaan, De Roeck, Ellen, Vandenberghe, Rik, Gabel, Silvy, Meersmans, Karen, Tsolaki, Magda, Verhey, Frans, Martinez-Lage, Pablo, Tainta, Mikel, Frisoni, Giovanni, Blin, Oliver, Richardson, Jill C., Bordet, Régis, Scheltens, Philip, Popp, Julius, Peyratout, Gwendoline, Johannsen, Peter, Frölich, Lutz, Freund-Levi, Yvonne, Streffer, Johannes, Lovestone, Simon, Legido-Quigley, Cristina, Kate, Mara Ten, Barkhof, Frederik, Zetterberg, Henrik, Bertram, Lars, Strazisar, Mojca, Visser, Pieter Jelle, Van Broeckhoven, Christine, Sleegers, Kristel, Küçükali, Fahri, Neumann, Alexander, Van Dongen, Jasper, De Pooter, Tim, Joris, Geert, De Rijk, Peter, Ohlei, Olena, Dobricic, Valerija, Bos, Isabelle, Vos, Stephanie J. B., Engelborghs, Sebastiaan, De Roeck, Ellen, Vandenberghe, Rik, Gabel, Silvy, Meersmans, Karen, Tsolaki, Magda, Verhey, Frans, Martinez-Lage, Pablo, Tainta, Mikel, Frisoni, Giovanni, Blin, Oliver, Richardson, Jill C., Bordet, Régis, Scheltens, Philip, Popp, Julius, Peyratout, Gwendoline, Johannsen, Peter, Frölich, Lutz, Freund-Levi, Yvonne, Streffer, Johannes, Lovestone, Simon, Legido-Quigley, Cristina, Kate, Mara Ten, Barkhof, Frederik, Zetterberg, Henrik, Bertram, Lars, Strazisar, Mojca, Visser, Pieter Jelle, Van Broeckhoven, Christine, and Sleegers, Kristel
Abstract: INTRODUCTION: Despite increasing evidence of a role of rare genetic variation in the risk of Alzheimer's disease (AD), limited attention has been paid to its contribution to AD-related biomarker traits indicative of AD-relevant pathophysiological processes. METHODS: We performed whole-exome gene-based rare-variant association studies (RVASs) of 17 AD-related traits on whole-exome sequencing (WES) data generated in the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) study (n = 450) and whole-genome sequencing (WGS) data from ADNI (n = 808). RESULTS: Mutation screening revealed a novel probably pathogenic mutation (PSEN1 p.Leu232Phe). Gene-based RVAS revealed the exome-wide significant contribution of rare coding variation in RBKS and OR7A10 to cognitive performance and protection against left hippocampal atrophy, respectively. DISCUSSION: The identification of these novel gene-trait associations offers new perspectives into the role of rare coding variation in the distinct pathophysiological processes culminating in AD, which may lead to identification of novel therapeutic and diagnostic targets., Funding agencies:European Medical Information Framework for Alzheimer's Disease (EMIF-AD)Innovative Medicines Initiative Joint Undertaking under the European Medical Information Framework (EMIF) 115372European Prevention of Alzheimer's Dementia (EPAD) 115736European Commission 860197 European Federation of Pharmaceutical Industries and Association (EFPIA) - European Commission within the fifth framework program QLRT-2001-2455European Commission within the fifth framework program 37670Department of Health of the Basque Government (allocation) 17.0.1.08.12.0000.2.454.01.41142.001Stichting voor Alzheimer Onderzoek 11020 13007 15005 Swiss National Science Foundation (SNSF) SNF 320030_141179 Synapsis Foundation - Alzheimer Research Switzerland 2017-PI01University of Antwerp Research FundEuropean Commission European Research Council (ERC) 681712 Swedish State Support for Clinical Research ALFGBG-720931Alzheimer Drug Discovery Foundation (ADDF), USA 201809-2016862AD Strategic FundAlzheimer's AssociationOlav Thon FoundationErling-Persson Family FoundationUK Dementia Research Institute at University College LondonNational Institute for Health and Care Research (NIHR) biomedical research centre at University College London Hospitals (UCLH)Instituto de Salud Carlos IIIDemensfonden, StockholmUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA U01 AG024904 DOD ADNI (Department of Defense) W81XWH-12-2-0012 United States Department of Health & Human ServicesNIH National Institute on Aging (NIA) United States Department of Health & Human ServicesNIH National Institute of Biomedical Imaging & Bioengineering (NIBIB)Alzheimer's Drug Discovery FoundationAraclon BiotechBiogenBristol-Myers SquibbCereSpir
Published: 2023
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17. Whole‐exome rare‐variant analysis of Alzheimer's disease and related biomarker traits

Author: Alzheimer's Disease Neuroimaging Initiative (ADNI), Küçükali, Fahri, Neumann, Alexander, Van Dongen, Jasper, De Pooter, Tim, Joris, Geert, De Rijk, Peter, Ohlei, Olena, Dobricic, Valerija, Bos, Isabelle, Vos, Stephanie J B, Engelborghs, Sebastiaan, De Roeck, Ellen, Vandenberghe, Rik, Gabel, Silvy, Meersmans, Karen, Tsolaki, Magda, Verhey, Frans, Martinez-Lage, Pablo, Tainta, Mikel, Frisoni, Giovanni, Blin, Oliver, Richardson, Jill C, Bordet, Régis, Scheltens, Philip, Popp, Julius, Peyratout, Gwendoline, Johannsen, Peter, Frölich, Lutz, Freund-Levi, Yvonne, Streffer, Johannes, Lovestone, Simon, Legido-Quigley, Cristina, Kate, Mara Ten, Barkhof, Frederik, Zetterberg, Henrik, Bertram, Lars, Strazisar, Mojca, Visser, Pieter Jelle, Van Broeckhoven, Christine, Sleegers, Kristel, Alzheimer’s Disease Neuroimaging Initiative (ADNI), EMIF-ADStudyGroup, Epidemiology, Psychiatrie & Neuropsychologie, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, Clinical sciences, Neuroprotection & Neuromodulation, Neurology, Amsterdam Neuroscience - Neurodegeneration, Radiology and nuclear medicine, Amsterdam Neuroscience - Brain Imaging, and Amsterdam Neuroscience - Neuroinfection & -inflammation
Subjects: D-RIBOSE, Epidemiology, Endophenotypes, Neuroscience(all), Clinical Neurology, ABCA7, Cellular and Molecular Neuroscience, Developmental Neuroscience, SDG 3 - Good Health and Well-being, GWAS, whole-exome sequencing, GENOME-WIDE ASSOCIATION, METAANALYSIS, Science & Technology, ENDOPHENOTYPES, MUTATIONS, Health Policy, neurology, biomarkers, rare coding variants, Alzheimer's disease, FRAMEWORK, Psychiatry and Mental health, Whole-exome sequencing, COGNITIVE DECLINE, Neurology (clinical), Neurosciences & Neurology, Human medicine, Geriatrics and Gerontology, Life Sciences & Biomedicine
Abstract: INTRODUCTION: Despite increasing evidence of a role of rare genetic variation in the risk of Alzheimer's disease (AD), limited attention has been paid to its contribution to AD-related biomarker traits indicative of AD-relevant pathophysiological processes. METHODS: We performed whole-exome gene-based rare-variant association studies (RVASs) of 17 AD-related traits on whole-exome sequencing (WES) data generated in the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) study (n = 450) and whole-genome sequencing (WGS) data from ADNI (n = 808). RESULTS: Mutation screening revealed a novel probably pathogenic mutation (PSEN1 p.Leu232Phe). Gene-based RVAS revealed the exome-wide significant contribution of rare coding variation in RBKS and OR7A10 to cognitive performance and protection against left hippocampal atrophy, respectively. DISCUSSION: The identification of these novel gene-trait associations offers new perspectives into the role of rare coding variation in the distinct pathophysiological processes culminating in AD, which may lead to identification of novel therapeutic and diagnostic targets. ispartof: ALZHEIMERS & DEMENTIA vol:19 issue:6 ispartof: location:United States status: Published online
Published: 2023
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18. Multiomics machine learning identifies inflammation molecular pathways in prodromal Alzheimer’s Disease

Author: Gómez-Pascual, Alicia, primary, Naccache, Talel, additional, Xu, Jin, additional, Hooshmand, Kourosh, additional, Wretlind, Asger, additional, Gabrielli, Martina, additional, Lombardo, Marta Tiffany, additional, Shi, Liu, additional, Buckley, Noel J., additional, Tijms, Betty M., additional, Vos, Stephanie J. B., additional, ten Kate, Mara, additional, Engelborghs, Sebastiaan, additional, Sleegers, Kristel, additional, Frisoni, Giovanni B., additional, Wallin, Anders, additional, Lleó, Alberto, additional, Popp, Julius, additional, Martinez-Lage, Pablo, additional, Streffer, Johannes, additional, Barkhof, Frederik, additional, Zetterberg, Henrik, additional, Visser, Pieter Jelle, additional, Lovestone, Simon, additional, Bertram, Lars, additional, Nevado-Holgado, Alejo J., additional, Gualerzi, Alice, additional, Picciolini, Silvia, additional, Proitsi, Petroula, additional, Verderio, Claudia, additional, Botía, Juan A., additional, and Legido-Quigley, Cristina, additional
Published: 2023
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19. Multiomics profiling of human plasma and cerebrospinal fluid reveals ATN‐derived networks and highlights causal links in Alzheimer's disease

Author: Shi, Liu, primary, Xu, Jin, additional, Green, Rebecca, additional, Wretlind, Asger, additional, Homann, Jan, additional, Buckley, Noel J., additional, Tijms, Betty M., additional, Vos, Stephanie J. B., additional, Lill, Christina M., additional, Kate, Mara ten, additional, Engelborghs, Sebastiaan, additional, Sleegers, Kristel, additional, Frisoni, Giovanni B., additional, Wallin, Anders, additional, Lleó, Alberto, additional, Popp, Julius, additional, Martinez‐Lage, Pablo, additional, Streffer, Johannes, additional, Barkhof, Frederik, additional, Zetterberg, Henrik, additional, Visser, Pieter Jelle, additional, Lovestone, Simon, additional, Bertram, Lars, additional, Nevado‐Holgado, Alejo J., additional, Proitsi, Petroula, additional, and Legido‐Quigley, Cristina, additional
Published: 2023
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20. Prediction of longitudinal cortical amyloid deposition based on cerebrospinal fluid biomarkers for Alzheimer's disease in cognitively unimpaired individuals: the role of APOE‐ε4.

Author: Rizzo, Marianna, Oomens, Julie Elisabeth, Jansen, Willemijn J., Gispert, Juan Domingo, Ritchie, Craig W, Jessen, Frank, Rovira, Mercè Boada, Marquié, Marta, Hanseeuw, Bernard J, Schmidt, Mark E, Stephens, Andrew W., Gismondi, Rossella, Frisoni, Giovanni B, Farrar, Gill, Barkhof, Frederik, García, David Vállez, Collij, Lyduine E., Alves, Isadora Lopes, Visser, Pieter Jelle, and Vos, Stephanie J. B.
Abstract: Background: The relationship between cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease (AD), APOE‐ε4 and longitudinal cortical amyloid deposition in preclinical AD is relevant for AD trial design but remains unclear. Thus, we aimed to investigate longitudinal cortical amyloid accumulation on PET as predicted by baseline CSF AD biomarker profiles and APOE‐ε4 carriership in cognitively unimpaired individuals. Method: We selected 330 cognitively unimpaired individuals from 6 cohorts of the AMYPAD study. All had available baseline data on CSF aß1‐42 (A), p‐tau181 (T), APOE‐ε4 carriership (yes/no), and baseline and follow‐up amyloid PET data. To evaluate different AD stages, individuals were classified as A‐T‐, A‐T+, A+T‐, or A+T+ based on CSF biomarker abnormality using center‐specific cut‐offs. We used a continuous outcome measure of global cortical amyloid deposition on PET expressed in centiloids. Analyses were performed in the total sample and stratified for APOE‐ε4, using generalized linear mixed models with random intercepts and slopes, adjusted for age and sex. Result: 58% were female, 49% APOE‐ε4 carriers, and mean age was 64+‐6.1 years, with an average follow‐up of 3 years. 170 individuals were A‐T‐, 70 A‐T+, 59 A+T‐, and 31 A+T+. Baseline cortical amyloid deposition was different between all groups, with A+T+ having the highest deposition, followed by A+T‐, A‐T+ and A‐T‐ (Figure 1, Table 1). Longitudinally, all groups showed increased amyloid deposition, except A‐T‐. Moreover, A+ groups showed greater increases in longitudinal amyloid deposition than A‐ groups. In APOE‐ε4 carriers, all AT groups showed increased longitudinal amyloid deposition, while in non‐carriers, A‐T+ and A‐T‐ did not (Figure 2, Table 1). Only in APOE‐ε4 carriers, A+T+ showed greater increases in longitudinal amyloid deposition than A+T‐, with A+T‐ showing a similar longitudinal deposition as A‐T+. Conclusion: APOE‐ε4 impacts the association between CSF AD biomarkers and longitudinal amyloid PET deposition in cognitively unimpaired persons. Amyloid‐negative APOE‐ε4 carriers could be at an early AD stage, as they showed increased cortical amyloid longitudinally, independent of baseline p‐tau status. In amyloid‐positive persons, p‐tau abnormality related to higher baseline cortical amyloid, but only in APOE‐ε4 carriers to steeper increases in cortical amyloid longitudinally. This has important implications for AD trial design. [ABSTRACT FROM AUTHOR]
Published: 2023
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21. The association between diabetes measures and Alzheimer's disease biomarkers in CSF – A meta‐analysis.

Author: van Gils, Veerle, Rizzo, Marianna, Côte, Jade, Viechtbauer, Wolfgang, Visser, Pieter Jelle, Jansen, Willemijn J., and Vos, Stephanie J. B.
Abstract: Background: Diabetes and blood glucose markers have previously been linked to cognitive decline. However, findings on the relation of diabetes with underlying Alzheimer's disease (AD) biomarkers are inconclusive. We aimed to explore whether diabetes and blood glucose markers are associated with AD biomarkers in cerebrospinal fluid (CSF) by performing a meta‐analysis of existing studies. Method: A systematic search in PubMed and Embase with abstract and full‐text screening resulted in the inclusion of 13 studies with 5,052 participants in our meta‐analysis. We included studies that provided results on the association between a diabetes measure and an AD biomarker in CSF (Table 1). Diabetes measures included diabetes diagnosis or glucose measures, i.e. fasting blood glucose, HbA1c, or insulin resistance index. AD biomarkers included CSF amyloid‐beta42, p‐tau and/or t‐tau. Where needed, results were converted to partial or biserial correlation coefficients. We performed a random effects meta‐analysis on the correlation coefficients per CSF biomarker, using the DerSimonian and Laird procedure and Knapp‐Hartung method. Meta‐regression was used to test potential moderating effects of age, sex, setting (memory clinic or population), % dementia cases, correlation type (Pearson, partial, or biserial), diabetes measure (diabetes diagnosis or glucose marker), MMSE score, and APOEe4 carriership (yes/no). All analyses were performed using the metafor package in R. Result: Our meta‐analysis showed small but significant associations of diabetes measures with increased (more normal) levels of amyloid‐beta42 (r = 0.08, p = 0.04, Figure 1) and increased (more abnormal) levels of p‐tau (r = 0.09, p = 0.04, Figure 2) and t‐tau (r = 0.10, p = 0.04, graph not shown as comparable to p‐tau). Heterogeneity was high for all outcomes (I2>60%, p<0.05 for Q‐test, wide prediction intervals). Meta‐regression analyses showed that heterogeneity in CSF amyloid could partly be explained by setting, as the association between diabetes measures and amyloid was only present in memory clinic studies as compared to population studies (difference estimate = 0.14, p = 0.03). Similarly, studies with more dementia cases showed a stronger association with amyloid (slope estimate = 0.0029, p = 0.001). No other moderating effects were found. Conclusion: Our findings suggest that diabetes measures are associated with tau‐related neurodegeneration that is independent from amyloid. This is valuable for improving diagnostics and treatment of patients with diabetes and AD. [ABSTRACT FROM AUTHOR]
Published: 2023
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22. Correction to: Cerebrovascular and amyloid pathology in predementia stages: the relationship with neurodegeneration and cognitive decline

Author: Bos, Isabelle, Verhey, Frans R., Ramakers, Inez H. G. B., Jacobs, Heidi I. L., Soininen, Hilkka, Freund-Levi, Yvonne, Hampel, Harald, Tsolaki, Magda, Wallin, Åsa K., van Buchem, Mark A., Oleksik, Ania, Verbeek, Marcel M., Rikkert, Marcel Olde, van der Flier, Wiesje M., Scheltens, Philip, Aalten, Pauline, Visser, Pieter Jelle, and Vos, Stephanie J. B.
Published: 2018
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23. A synergistic association of diabetes and AD biomarkers on cognitive decline in persons without dementia?

Author: van Gils, Veerle, primary, Jansen, Willemijn J., additional, Hort, Jakub, additional, Martinez‐Lage, Pablo, additional, Ramakers, Inez H.G.B., additional, Rouaud, Olivier, additional, Zetterberg, Henrik, additional, Dalsgaard, Søren, additional, Verhey, Frans R.J., additional, Visser, Pieter Jelle, additional, Vos, Stephanie J. B., additional, Consortium, EMIF‐AD MBD, additional, and Consortium, EPAD, additional
Published: 2022
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24. Prevalence of Suspected non‐Alzheimer’s disease pathophysiology across the Alzheimer’s disease clinical spectrum: a meta‐analysis

Author: Vos, Stephanie J. B., primary, Delvenne, Aurore, additional, and Visser, Pieter Jelle, additional
Published: 2022
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25. Association of Cerebral Amyloid-β Aggregation With Cognitive Functioning in Persons Without Dementia

Author: Jansen, Willemijn J., Ossenkoppele, Rik, Tijms, Betty M., Fagan, Anne M., Hansson, Oskar, Klunk, William E., van der Flier, Wiesje M., Villemagne, Victor L., Frisoni, Giovanni B., Fleisher, Adam S., Lleó, Alberto, Mintun, Mark A., Wallin, Anders, Engelborghs, Sebastiaan, Na, Duk L., Chételat, Gäel, Molinuevo, José Luis, Landau, Susan M., Mattsson, Niklas, Kornhuber, Johannes, Sabri, Osama, Rowe, Christopher C., Parnetti, Lucilla, Popp, Julius, Fladby, Tormod, Jagust, William J., Aalten, Pauline, Lee, Dong Young, Vandenberghe, Rik, Resende de Oliveira, Catarina, Kapaki, Elisabeth, Froelich, Lutz, Ivanoiu, Adrian, Gabryelewicz, Tomasz, Verbeek, Marcel M., Sanchez-Juan, Páscual, Hildebrandt, Helmut, Camus, Vincent, Zboch, Marzena, Brooks, David J., Drzezga, Alexander, Rinne, Juha O., Newberg, Andrew, de Mendonça, Alexandre, Sarazin, Marie, Rabinovici, Gil D., Madsen, Karine, Kramberger, Milica G., Nordberg, Agneta, Mok, Vincent, Mroczko, Barbara, Wolk, David A., Meyer, Philipp T., Tsolaki, Magda, Scheltens, Philip, Verhey, Frans R. J., Visser, Pieter Jelle, Aarsland, Dag, Alcolea, Daniel, Alexander, Myriam, Almdahl, Ina S., Arnold, Steven E., Baldeiras, Inês, Barthel, Henryk, van Berckel, Bart N.M., Blennow, Kaj, van Buchem, Mark A., Cavedo, Enrica, Chen, Kewei, Chipi, Elena, Cohen, Ann D., Förster, Stefan, Fortea, Juan, Frederiksen, Kristian S., Freund-Levi, Yvonne, Gkatzima, Olymbia, Gordon, Mark Forrest, Grimmer, Timo, Hampel, Harald, Hausner, Lucrezia, Hellwig, Sabine, Herukka, Sanna-Kaisa, Johannsen, Peter, Klimkowicz-Mrowiec, Aleksandra, Köhler, Sebastian, Koglin, Norman, van Laere, Koen, de Leon, Mony, Lisetti, Viviana, Maier, Wolfgang, Marcusson, Jan, Meulenbroek, Olga, Møllergård, Hanne M., Morris, John C., Nordlund, Arto, Novak, Gerald P., Paraskevas, George P., Perera, Gayan, Peters, Oliver, Ramakers, Inez H. G. B., Rami, Lorena, Rodríguez-Rodríguez, Eloy, Roe, Catherine M., Rot, Uros, Rüther, Eckart, Santana, Isabel, Schröder, Johannes, Seo, Sang W., Soininen, Hilkka, Spiru, Luiza, Stomrud, Erik, Struyfs, Hanne, Teunissen, Charlotte E., Vos, Stephanie J. B., van Waalwijk van Doorn, Linda J. C., Waldemar, Gunhild, Wallin, Åsa K., Wiltfang, Jens, and Zetterberg, Henrik
Published: 2018
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26. Multiomics profiling of human plasma and CSF reveals ATN derived networks and highlights causal links in Alzheimer’s disease

Author: Shi, Liu, primary, Xu, Jin, additional, Green, Rebecca, additional, Wretlind, Asger, additional, Homann, Jan, additional, Buckley, Noel J., additional, Tijms, Betty M., additional, Vos, Stephanie J. B., additional, Lill, Christina M., additional, Kate, Mara ten, additional, Engelborghs, Sebastiaan, additional, Sleegers, Kristel, additional, Frisoni, Giovanni B., additional, Wallin, Anders, additional, Lleó, Alberto, additional, Pop, Julius, additional, Martinez-Lage, Pablo, additional, Streffer, Johannes, additional, Barkhof, Frederik, additional, Zetterberg, Henrik, additional, Visser, Pieter Jelle, additional, Lovestone, Simon, additional, Bertram, Lars, additional, Nevado-Holgado, Alejo J., additional, Proitsi, Petroula, additional, and Legido-Quigley, Cristina, additional
Published: 2022
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27. Cerebrovascular and amyloid pathology in predementia stages: the relationship with neurodegeneration and cognitive decline

Author: Bos, Isabelle, Verhey, Frans R., Ramakers, Inez H.G.B., Jacobs, Heidi I. L., Soininen, Hilkka, Freund-Levi, Yvonne, Hampel, Harald, Tsolaki, Magda, Wallin, Åsa K., van Buchem, Mark A., Oleksik, Ania, Verbeek, Marcel M., Olde Rikkert, Marcel, van der Flier, Wiesje M., Scheltens, Philip, Aalten, Pauline, Visser, Pieter Jelle, and Vos, Stephanie J. B.
Published: 2017
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28. The Role of Vascular Risk Factors in Biomarker-Based AT(N) Groups: A German-Dutch Memory Clinic Study

Author: Kučikienė, Domantė, Costa, Ana Sofia, Banning, Leonie C P, van Gils, Veerle, Schulz, Jörg B, Ramakers, Inez H G B, Verhey, Frans R J, Vos, Stephanie J B, Reetz, Kathrin, Kučikienė, Domantė, Costa, Ana Sofia, Banning, Leonie C P, van Gils, Veerle, Schulz, Jörg B, Ramakers, Inez H G B, Verhey, Frans R J, Vos, Stephanie J B, and Reetz, Kathrin
Published: 2022

29. Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum

Author: Jansen, Willemijn J., Janssen, Olin, Tijms, Betty M., Vos, Stephanie J. B., Ossenkoppele, Rik, Visser, Pieter Jelle, Jansen, Willemijn J., Janssen, Olin, Tijms, Betty M., Vos, Stephanie J. B., Ossenkoppele, Rik, and Visser, Pieter Jelle
Abstract: Importance: One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design. Objective: To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates. Design, Setting, and Participants: This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria. Exposures: Alzheimer disease biomarkers detected on PET or in CSF. Main Outcomes and Measures: Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations. Results: Among the 19 097 participants (mean [SD] age, 69.1 [9.8] years; 10 148 women [53.1%]), Funding Agency:Biogen
Published: 2022
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30. Temporally ordered associations between type 2 diabetes and brain disorders - a Danish register-based cohort study

Author: Universitat Rovira i Virgili, Wimberley, Theresa; Horsdal, Henriette T.; Brikell, Isabell; Laursen, Thomas M.; Astrup, Aske; Fanelli, Giuseppe; Bralten, Janita; Poelmans, Geert; Van Gils, Veerle; Jansen, Willemijn J.; Vos, Stephanie J. B.; Bertaina-Anglade, Valerie; Camacho-Barcia, Lucia; Mora-Maltas, Bernat; Fernandez-Aranda, Fernando; Bonet, Monica B.; Salas-Salvado, Jordi; Franke, Barbara; Dalsgaard, Soren, Universitat Rovira i Virgili, and Wimberley, Theresa; Horsdal, Henriette T.; Brikell, Isabell; Laursen, Thomas M.; Astrup, Aske; Fanelli, Giuseppe; Bralten, Janita; Poelmans, Geert; Van Gils, Veerle; Jansen, Willemijn J.; Vos, Stephanie J. B.; Bertaina-Anglade, Valerie; Camacho-Barcia, Lucia; Mora-Maltas, Bernat; Fernandez-Aranda, Fernando; Bonet, Monica B.; Salas-Salvado, Jordi; Franke, Barbara; Dalsgaard, Soren
Abstract: Background Type 2 diabetes mellitus (T2DM) is linked with several neurodegenerative and psychiatric disorders, either as a comorbid condition or as a risk factor. We aimed to expand the evidence by examining associations with a broad range of brain disorders (psychiatric and neurological disorders, excluding late-onset neurodegenerative disorders), while also accounting for the temporal order of T2DM and these brain disorders. Methods In a population-based cohort-study of 1,883,198 Danish citizens, born 1955-1984 and followed until end of 2016, we estimated associations between T2DM and 16 brain disorders first diagnosed between childhood and mid-adulthood. We calculated odds ratios (OR) and hazard ratios (HR) with 95% confidence intervals (CI) in temporally ordered analyses (brain disorder diagnosis after T2DM and vice versa), adjusted for sex, age, follow-up, birth year, and parental factors. Results A total of 67,660 (3.6%) of the study population were identified as T2DM cases after age 30 and by a mean age of 45 years (SD of 8 years). T2DM was associated with most psychiatric disorders. Strongest associations were seen with other (i.e. non-anorectic) eating disorders (OR [95% CI]: 2.64 [2.36-2.94]) and schizophrenia spectrum disorder (2.73 [2.63-2.84]). Among neurological disorders especially inflammatory brain diseases (1.73 [1.57-1.91]) and epilepsy (1.67 [1.60-1.75]) were associated with T2DM. Most associations remained in both directions in the temporally ordered analyses. For most psychiatric disorders, associations were strongest in females. Conclusions T2DM was associated with several psychiatric and neurological disorders, and most associations were consistently found for both temporal order of disorders. This suggests a shared etiology of T2DM and those bra
Published: 2022

31. Cerebrospinal fluid proteomic profiling of individuals with mild cognitive impairment and suspected non‐Alzheimer's disease pathophysiology

Author: Delvenne, Aurore, primary, Gobom, Johan, additional, Tijms, Betty, additional, Bos, Isabelle, additional, Reus, Lianne M., additional, Dobricic, Valerija, additional, Kate, Mara ten, additional, Verhey, Frans, additional, Ramakers, Inez, additional, Scheltens, Philip, additional, Teunissen, Charlotte E., additional, Vandenberghe, Rik, additional, Schaeverbeke, Jolien, additional, Gabel, Silvy, additional, Popp, Julius, additional, Peyratout, Gwendoline, additional, Martinez‐Lage, Pablo, additional, Tainta, Mikel, additional, Tsolaki, Magda, additional, Freund‐Levi, Yvonne, additional, Lovestone, Simon, additional, Streffer, Johannes, additional, Barkhof, Frederik, additional, Bertram, Lars, additional, Blennow, Kaj, additional, Zetterberg, Henrik, additional, Visser, Pieter Jelle, additional, and Vos, Stephanie J. B., additional
Published: 2022
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32. Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum

Author: Jansen, Willemijn J, Janssen, Olin, von Arnim, Christine, Marquié, Marta, Martinez-Lage, Pablo, Maserejian, Nancy, Mattsson, Niklas, de Mendonça, Alexandre, Meyer, Philipp T, Miller, Bruce L, Minatani, Shinobu, Mintun, Mark A, Mok, Vincent C T, Baiardi, Simone, Molinuevo, Jose Luis, Morbelli, Silvia Daniela, Morris, John C, Mroczko, Barbara, Na, Duk L, Newberg, Andrew, Nobili, Flavio, Nordberg, Agneta, Olde Rikkert, Marcel G M, de Oliveira, Catarina Resende, Baldeiras, Ines, Olivieri, Pauline, Orellana, Adela, Paraskevas, George, Parchi, Piero, Pardini, Matteo, Parnetti, Lucilla, Peters, Oliver, Poirier, Judes, Popp, Julius, Prabhakar, Sudesh, Barthel, Henryk, Rabinovici, Gil D, Ramakers, Inez H, Rami, Lorena, Reiman, Eric M, Rinne, Juha O, Rodrigue, Karen M, Rodríguez-Rodriguez, Eloy, Roe, Catherine M, Rosa-Neto, Pedro, Rosen, Howard J, Bateman, Randall J, Rot, Uros, Rowe, Christopher C, Rüther, Eckart, Ruiz, Agustín, Sabri, Osama, Sakhardande, Jayant, Sánchez-Juan, Pascual, Sando, Sigrid Botne, Santana, Isabel, Sarazin, Marie, Van Berckel, Bart, Scheltens, Philip, Schröder, Johannes, Selnes, Per, Seo, Sang Won, Silva, Dina, Skoog, Ingmar, Snyder, Peter J, Soininen, Hilkka, Sollberger, Marc, Sperling, Reisa A, Binette, Alexa Pichet, Spiru, Luisa, Stern, Yaakov, Stomrud, Erik, Takeda, Akitoshi, Teichmann, Marc, Teunissen, Charlotte E, Thompson, Louisa I, Tomassen, Jori, Tsolaki, Magda, Vandenberghe, Rik, Blennow, Kaj, Verbeek, Marcel M, Verhey, Frans R J, Villemagne, Victor, Villeneuve, Sylvia, Vogelgsang, Jonathan, Waldemar, Gunhild, Wallin, Anders, Wallin, Åsa K, Wiltfang, Jens, Wolk, David A, Boada, Merce, Yen, Tzu-Chen, Zboch, Marzena, Zetterberg, Henrik, Boecker, Henning, Tijms, Betty M, Bottlaender, Michel, den Braber, Anouk, Brooks, David J, Van Buchem, Mark A, Camus, Vincent, Carill, Jose Manuel, Cerman, Jiri, Chen, Kewei, Chételat, Gaël, Chipi, Elena, Vos, Stephanie J B, Cohen, Ann D, Daniels, Alisha, Delarue, Marion, Didic, Mira, Drzezga, Alexander, Dubois, Bruno, Eckerström, Marie, Ekblad, Laura L, Engelborghs, Sebastiaan, Epelbaum, Stéphane, Ossenkoppele, Rik, Fagan, Anne M, Fan, Yong, Fladby, Tormod, Fleisher, Adam S, Van der Flier, Wiesje M, Förster, Stefan, Fortea, Juan, Frederiksen, Kristian Steen, Freund-Levi, Yvonne, Frings, Lars, Visser, Pieter Jelle, Frisoni, Giovanni B, Fröhlich, Lutz, Gabryelewicz, Tomasz, Gertz, Hermann-Josef, Gill, Kiran Dip, Gkatzima, Olymbia, Gómez-Tortosa, Estrella, Grimmer, Timo, Guedj, Eric, Habeck, Christian G, Group, Amyloid Biomarker Study, Hampel, Harald, Handels, Ron, Hansson, Oskar, Hausner, Lucrezia, Hellwig, Sabine, Heneka, Michael, Herukka, Sanna-Kaisa, Hildebrandt, Helmut, Hodges, John, Hort, Jakub, Aarsland, Dag, Huang, Chin-Chang, Iriondo, Ane Juaristi, Itoh, Yoshiaki, Ivanoiu, Adrian, Jagust, William J, Jessen, Frank, Johannsen, Peter, Johnson, Keith A, Kandimalla, Ramesh, Kapaki, Elisabeth N, Alcolea, Daniel, Kern, Silke, Kilander, Lena, Klimkowicz-Mrowiec, Aleksandra, Klunk, William E, Koglin, Norman, Kornhuber, Johannes, Kramberger, Milica G, Kuo, Hung-Chou, Van Laere, Koen, Landau, Susan M, Altomare, Daniele, Landeau, Brigitte, Lee, Dong Young, de Leon, Mony, Leyton, Cristian E, Lin, Kun-Ju, Lleó, Alberto, Löwenmark, Malin, Madsen, Karine, Maier, Wolfgang, Marcusson, Jan, Clinical sciences, Neuroprotection & Neuromodulation, Neurology, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Neurodegeneration, Radiology and nuclear medicine, Laboratory Medicine, Amsterdam Neuroscience - Neuroinfection & -inflammation, APH - Personalized Medicine, APH - Methodology, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, and Psychiatrie & Neuropsychologie
Subjects: Male, MILD COGNITIVE IMPAIRMENT, epidemiology [Cognitive Dysfunction], positron emission tomography, Alzheimer`s disease Donders Center for Medical Neuroscience [Radboudumc 1], epidemiology [Alzheimer Disease], Neuroscience(all), diagnostic imaging [Cognitive Dysfunction], Amyloidogenic Proteins, tau Proteins, cerebrospinal fluid [Amyloid beta-Peptides], DIAGNOSIS, cerebrospinal fluid, Apolipoproteins E, Alzheimer Disease, Prevalence, Humans, Amyloid, Alzheimer, PET, Cognitive Dysfunction, ddc:610, cerebrospinal fluid [Peptide Fragments], Aged, Amyloid beta-Peptides, neurology, DEMENTIA, Correction, ASSOCIATION, Amyloidosis, Middle Aged, Disorders of movement Donders Center for Medical Neuroscience [Radboudumc 3], health care planning, clinical trial design, Peptide Fragments, cerebrospinal fluid [Alzheimer Disease], PET, DRIFT, Cross-Sectional Studies, cerebrospinal fluid [Biomarkers], cerebrospinal fluid [tau Proteins], Radiology Nuclear Medicine and imaging, Positron-Emission Tomography, genetics [Apolipoproteins E], Female, Neurology (clinical), diagnostic imaging [Alzheimer Disease], cerebral amyloid aggregation, Biomarkers
Abstract: Importance: One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design.Objective: To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates.Design, Setting, and Participants: This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria.Exposures: Alzheimer disease biomarkers detected on PET or in CSF.Main Outcomes and Measures: Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations.Results: Among the 19 097 participants (mean [SD] age, 69.1 [9.8] years; 10 148 women [53.1%]) included, 10 139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P = .04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P = .004), subjective cognitive decline (9%; 95% CI, 3%-15%; P = .005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P = .004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P = .18).Conclusions and Relevance: This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies.
Published: 2022
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33. Additional file 2 of Cerebrospinal fluid tau levels are associated with abnormal neuronal plasticity markers in Alzheimer’s disease

Author: Visser, Pieter Jelle, Reus, Lianne M., Gobom, Johan, Jansen, Iris, Dicks, Ellen, van der Lee, Sven J., Tsolaki, Magda, Verhey, Frans R. J., Popp, Julius, Martinez-Lage, Pablo, Vandenberghe, Rik, Lleó, Alberto, Molinuevo, José Luís, Engelborghs, Sebastiaan, Freund-Levi, Yvonne, Froelich, Lutz, Sleegers, Kristel, Dobricic, Valerija, Lovestone, Simon, Streffer, Johannes, Vos, Stephanie J. B., Bos, Isabelle, Smit, August B., Blennow, Kaj, Scheltens, Philip, Teunissen, Charlotte E., Bertram, Lars, Zetterberg, Henrik, and Tijms, Betty M.
Subjects: mental disorders, sense organs
Abstract: Additional file 2: Figure S1. Longitudinal change in CSF total tau. Figure S2. Enrichment of synaptic processes in individuals with AD according to t-tau status. Figure S3. Enriched GO biological processes and SUZ12 and REST transcription factors associated with proteins that differed between AD individuals with increased t-tau and normal t-tau and proteins that changed with disease severity.
Published: 2022
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34. Characteristics of subjective cognitive decline associated with amyloid positivity

Author: Janssen, Olin, Jansen, Willemijn J, Epelbaum, Stéphane, Lleó, Alberto, Engelborghs, Sebastiaan, van der Flier, Wiesje M, Landau, Susan, Popp, Julius, Wallin, Anders, Scheltens, Philip, Rikkert, Marcel Olde, Snyder, Peter J, Vos, Stephanie J B, Rowe, Chris, Chételat, Gaël, Ruíz, Agustin, Marquié, Marta, Chipi, Elena, Wolfsgruber, Steffen, Heneka, Michael, Boecker, Henning, Peters, Oliver, Jarholm, Jonas, Boada, Merce, Rami, Lorena, Tort-Merino, Adrià, Binette, Alexa Pichet, Poirier, Judes, Rosa-Neto, Pedro, Cerman, Jiri, Dubois, Bruno, Teichmann, Marc, Alcolea, Daniel, Fortea, Juan, Parnetti, Lucilla, Sánchez-Saudinós, M Belén, Ebenau, Jarith, Pocnet, Cornelia, Eckerström, Marie, Thompson, Louisa, Villemagne, Victor, Buckley, Rachel, Burnham, Samantha, Delarue, Marion, Freund-Levi, Yvonne, Gabryelewicz, Tomasz, Wallin, Åsa K, Ramakers, Inez, Tsolaki, Magda, Soininen, Hilkka, Hampel, Harald, Spiru, Luiza, Initiative, Alzheimer's Disease Neuroimaging, group, FACEHBI study, group, PREVENT-AD research, Tijms, Betty, Fladby, Tormod, Ossenkoppele, Rik, Verhey, Frans R J, Jessen, Frank, Visser, Pieter Jelle, Molinuevo, José Luis, Villeneuve, Sylvia, Hort, Jakub, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, Psychiatrie & Neuropsychologie, Neurology, Amsterdam Neuroscience - Neurodegeneration, Amsterdam Neuroscience - Brain Imaging, Alzheimers Dis Neuroimaging Initia, Facehbi Study Grp, PREVENT-AD Res Grp, Clinical sciences, and Neuroprotection & Neuromodulation
Subjects: PRECLINICAL ALZHEIMERS-DISEASE, Amyloid, SYMPTOMS, positron emission tomography, Epidemiology, Neuroscience(all), Apolipoprotein E4, Amyloidogenic Proteins, cerebrospinal fluid, Cellular and Molecular Neuroscience, Developmental Neuroscience, mental disorders, Humans, Cognitive Dysfunction, ddc:610, DEPOSITION, OLDER-ADULTS, genetics [Apolipoprotein E4], POPULATION, RISK, neurology, Health Policy, DEMENTIA, genetics [Cognitive Dysfunction], Brain, amyloid, Amyloidosis, Alzheimer's disease, PREVALENCE, COMMUNITY, Psychiatry and Mental health, metabolism [Brain], Positron-Emission Tomography, Neurology (clinical), Human medicine, psychology [Cognitive Dysfunction], Geriatrics and Gerontology, subjective cognitive decline, MEMORY COMPLAINTS, Biomarkers
Abstract: Introduction The evidence for characteristics of persons with subjective cognitive decline (SCD) associated with amyloid positivity is limited. Methods In 1640 persons with SCD from 20 Amyloid Biomarker Study cohort, we investigated the associations of SCD-specific characteristics (informant confirmation, domain-specific complaints, concerns, feelings of worse performance) demographics, setting, apolipoprotein E gene (APOE) epsilon 4 carriership, and neuropsychiatric symptoms with amyloid positivity. Results Between cohorts, amyloid positivity in 70-year-olds varied from 10% to 76%. Only older age, clinical setting, and APOE epsilon 4 carriership showed univariate associations with increased amyloid positivity. After adjusting for these, lower education was also associated with increased amyloid positivity. Only within a research setting, informant-confirmed complaints, memory complaints, attention/concentration complaints, and no depressive symptoms were associated with increased amyloid positivity. Feelings of worse performance were associated with less amyloid positivity at younger ages and more at older ages. Discussion Next to age, setting, and APOE epsilon 4 carriership, SCD-specific characteristics may facilitate the identification of amyloid-positive individuals.
Published: 2022
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35. Additional file 1 of Temporally ordered associations between type 2 diabetes and brain disorders – a Danish register-based cohort study

Author: Wimberley, Theresa, Horsdal, Henriette T., Brikell, Isabell, Laursen, Thomas M., Astrup, Aske, Fanelli, Giuseppe, Bralten, Janita, Poelmans, Geert, Gils, Veerle Van, Jansen, Willemijn J., Vos, Stephanie J. B., Bertaina-Anglade, Valérie, Camacho-Barcia, Lucia, Mora-Maltas, Bernat, Fernandez-Aranda, Fernando, Bonet, Mònica B., Salas-Salvadó, Jordi, Franke, Barbara, and Dalsgaard, Søren
Abstract: Additional file 1: Supplementary Table 1. Diagnostic classifications for definition of type 2 diabetes and selected brain disorders. Supplementary Table 2. Crude and adjusted estimates based on logistic regression analyses and temporally ordered Cox regression analyses. Supplementary Table 3. Temporally ordered analyses of sex-specific associations between diagnoses of brain disorders and type 2 diabetes. Supplementary Table 4. Adjusted estimates based on logistic regression analyses and temporally ordered Cox regression analyses without and with adjustment for highest attained level of education. Supplementary Table 5. Adjusted estimates based on logistic regression analysis applying the main and two alternative register-based T2DM definitions.
Published: 2022
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36. Cerebral Microbleeds and Amyloid Pathology Estimates From the Amyloid Biomarker Study.

Author: Oomens, Julie E., van Gils, Veerle, Vos, Stephanie J. B., Freeze, Whitney M., Maserejian, Nancy N., Curiale, Gioacchino, Gillis, Cai, Boada, Mercè, van der Flier, Wiesje M., Hort, Jakub, Johnson, Sterling C., Lleó, Alberto, Ramakers, Inez H., Rodrigue, Karen M., Sánchez-Juan, Pascual, Sarazin, Marie, Scarmeas, Nikolaos, Zetterberg, Henrik, Alcolea, Daniel, and Barkhof, Frederik
Published: 2025
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37. Genome-Wide Association Study of Alzheimer’s Disease Brain Imaging Biomarkers and Neuropsychological Phenotypes in the European Medical Information Framework for Alzheimer’s Disease Multimodal Biomarker Discovery Dataset

Author: Homann, Jan, primary, Osburg, Tim, additional, Ohlei, Olena, additional, Dobricic, Valerija, additional, Deecke, Laura, additional, Bos, Isabelle, additional, Vandenberghe, Rik, additional, Gabel, Silvy, additional, Scheltens, Philip, additional, Teunissen, Charlotte E., additional, Engelborghs, Sebastiaan, additional, Frisoni, Giovanni, additional, Blin, Olivier, additional, Richardson, Jill C., additional, Bordet, Regis, additional, Lleó, Alberto, additional, Alcolea, Daniel, additional, Popp, Julius, additional, Clark, Christopher, additional, Peyratout, Gwendoline, additional, Martinez-Lage, Pablo, additional, Tainta, Mikel, additional, Dobson, Richard J. B., additional, Legido-Quigley, Cristina, additional, Sleegers, Kristel, additional, Van Broeckhoven, Christine, additional, Wittig, Michael, additional, Franke, Andre, additional, Lill, Christina M., additional, Blennow, Kaj, additional, Zetterberg, Henrik, additional, Lovestone, Simon, additional, Streffer, Johannes, additional, ten Kate, Mara, additional, Vos, Stephanie J. B., additional, Barkhof, Frederik, additional, Visser, Pieter Jelle, additional, and Bertram, Lars, additional
Published: 2022
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38. Immune protein levels in cerebrospinal fluid:Associations with memory scores across the AD spectrum

Author: Wesenhagen, Kirsten E. J., Teunissen, Charlotte E., Gobom, Johan, Vos, Stephanie J. B., Blennow, Kaj, Zetterberg, Henrik, Scheltens, Philip, Tijms, Betty M., Visser, Pieter Jelle, Neurology, Amsterdam Neuroscience - Neurodegeneration, Clinical chemistry, Amsterdam Neuroscience - Neuroinfection & -inflammation, and Amsterdam Neuroscience - Brain Imaging
Abstract: BACKGROUND: Alzheimer's disease (AD) is characterized by amyloid and tau aggregation. In addition, immune alterations are involved, perhaps with clinical stage-dependent effects. How cerebrospinal fluid (CSF) levels of immune system-related proteins associate with memory function in AD remains unknown. We studied this question across the AD clinical spectrum. METHOD: We selected from ADNI and EMIF-AD MBD, 425 amyloid-positive (A+) individuals across clinical stages (preclinical, prodromal and dementia) and 102 amyloid-negative (A-) CN controls, with available CSF proteomics and memory scores. Memory test scores of word lists were Z-transformed based on controls (ADNI), or published norms (EMIF-AD). Proteins were measured in EMIF-AD with mass spectrometry (MS) (2537 proteins) and in ADNI by MS (142 proteins) and RBM (83 proteins). Of 165 proteins assessed in both cohorts, we selected 53 proteins associated with 'immune system process' in Gene Ontology (GOv2.1). We Z-transformed levels relative to controls in each cohort and pooled the datasets. For proteins showing an interaction with diagnosis on memory with p-value < 0.1, we analysed group-stratified associations in linear models (predictor: protein levels; outcome: memory scores; covariates: sex, age, years of education, diagnosis; p-value threshold: 0.05). We annotated memory-associated proteins for subcategories of the immune system process. RESULT: We included 102 A- controls and 425 A+ individuals (preclinical AD: 105, prodromal AD: 183, and AD dementia: 137, Table 1). Eighteen proteins (34%) showed diagnosis-dependent memory associations, for which we performed stratified analyses. In the control group, higher levels of 4 proteins (22%) associated with worse memory (Figure 1-2). In preclinical AD, lower concentrations of 11 proteins associated with worse memory (Figure 1). These proteins were enriched for neutrophil degranulation. Of the 11 proteins, 2 were associated with memory in controls, but in an opposite direction. In prodromal AD, lower concentrations of 4 proteins associated with worse memory. No associations occurred in individuals with AD-type dementia, probably due to the low memory scores in this group (Figure 2). CONCLUSION: Our results suggest immune alterations affect memory function very early in AD. Further research is needed to clarify why in controls higher levels of immune proteins associate with lower memory function.
Published: 2021
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39. Alzheimer's disease genetic risk variants show brain cell type-specific associations with protein levels in cerebrospinal fluid

Author: Reus, Lianne M., van der Lee, Sven J., Teunissen, Charlotte E., Gobom, Johan, Vos, Stephanie J. B., Blennow, Kaj, Zetterberg, Henrik, Bertram, Lars, Visser, Pieter Jelle, Tijms, Betty M., Neurology, Clinical genetics, Clinical chemistry, Amsterdam Neuroscience - Neurodegeneration, Amsterdam Neuroscience - Neuroinfection & -inflammation, and Amsterdam Neuroscience - Brain Imaging
Abstract: BACKGROUND: Neuronal dysfunction is central to the clinical manifestation of Alzheimer's disease (AD). However, genome-wide studies also suggest important roles for non-neuronal brain cell-types such as microglia and astrocytes. Our objective was to study whether brain cell type-specific polygenic risk scores (PGRS) for AD, including single nucleotide polymorphisms (SNPs) of genes expressed in one brain cell type, showed relationships with levels of cerebrospinal fluid (CSF) AD markers in individuals across the clinical spectrum of AD. METHOD: We selected 1,535 subjects (552 controls/709 mild cognitive impairment/274 AD-dementia, age 71±8 years, 48%female) from the ADNI (N=617) and EMIF-AD MBD (N=918) study, who had genetic data available. We labelled AD risk genes as specific for neurons, astrocytes, microglia, oligodendrocytes or endothelial cells when more than 50% of the gene expression was produced by one cell type (otherwise as 'non-specific') according to the BRAIN RNASeq database (Zhang et al., 2014). We calculated cell type-specific-PGRS with cell type-corresponding SNPs (P
Published: 2021
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40. OPINION: Suspected non-Alzheimer disease pathophysiology — concept and controversy

Author: Jack, Clifford R., Jr, Knopman, David S., Chételat, Gaël, Dickson, Dennis, Fagan, Anne M., Frisoni, Giovanni B., Jagust, William, Mormino, Elizabeth C., Petersen, Ronald C., Sperling, Reisa A., van der Flier, Wiesje M., Villemagne, Victor L., Visser, Pieter J., and Vos, Stephanie J. B.
Published: 2016
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41. Prevalence of Cerebral Amyloid Pathology in Persons Without Dementia: A Meta-analysis

Author: Jansen, Willemijn J., Ossenkoppele, Rik, Knol, Dirk L., Tijms, Betty M., Scheltens, Philip, Verhey, Frans R. J., Visser, Pieter Jelle, Aalten, Pauline, Aarsland, Dag, Alcolea, Daniel, Alexander, Myriam, Almdahl, Ina S., Arnold, Steven E., Baldeiras, Inês, Barthel, Henryk, van Berckel, Bart N. M., Bibeau, Kristen, Blennow, Kaj, Brooks, David J., van Buchem, Mark A., Camus, Vincent, Cavedo, Enrica, Chen, Kewei, Chetelat, Gael, Cohen, Ann D., Drzezga, Alexander, Engelborghs, Sebastiaan, Fagan, Anne M., Fladby, Tormod, Fleisher, Adam S., van der Flier, Wiesje M., Ford, Lisa, Förster, Stefan, Fortea, Juan, Foskett, Nadia, Frederiksen, Kristian S., Freund-Levi, Yvonne, Frisoni, Giovanni B., Froelich, Lutz, Gabryelewicz, Tomasz, Gill, Kiran Dip, Gkatzima, Olymbia, Gómez-Tortosa, Estrella, Gordon, Mark Forrest, Grimmer, Timo, Hampel, Harald, Hausner, Lucrezia, Hellwig, Sabine, Herukka, Sanna-Kaisa, Hildebrandt, Helmut, Ishihara, Lianna, Ivanoiu, Adrian, Jagust, William J., Johannsen, Peter, Kandimalla, Ramesh, Kapaki, Elisabeth, Klimkowicz-Mrowiec, Aleksandra, Klunk, William E., Köhler, Sebastian, Koglin, Norman, Kornhuber, Johannes, Kramberger, Milica G., Van Laere, Koen, Landau, Susan M., Lee, Dong Young, de Leon, Mony, Lisetti, Viviana, Lleó, Alberto, Madsen, Karine, Maier, Wolfgang, Marcusson, Jan, Mattsson, Niklas, de Mendonça, Alexandre, Meulenbroek, Olga, Meyer, Philipp T., Mintun, Mark A., Mok, Vincent, Molinuevo, José Luis, Møllergård, Hanne M., Morris, John C., Mroczko, Barbara, Van der Mussele, Stefan, Na, Duk L., Newberg, Andrew, Nordberg, Agneta, Nordlund, Arto, Novak, Gerald P., Paraskevas, George P., Parnetti, Lucilla, Perera, Gayan, Peters, Oliver, Popp, Julius, Prabhakar, Sudesh, Rabinovici, Gil D., Ramakers, Inez H. G. B., Rami, Lorena, Resende de Oliveira, Catarina, Rinne, Juha O., Rodrigue, Karen M., Rodríguez-Rodríguez, Eloy, Roe, Catherine M., Rot, Uros, Rowe, Christopher C., Rüther, Eckart, Sabri, Osama, Sanchez-Juan, Páscual, Santana, Isabel, Sarazin, Marie, Schröder, Johannes, Schütte, Christin, Seo, Sang W., Soetewey, Femke, Soininen, Hilkka, Spiru, Luiza, Struyfs, Hanne, Teunissen, Charlotte E., Tsolaki, Magda, Vandenberghe, Rik, Verbeek, Marcel M., Villemagne, Victor L., Vos, Stephanie J. B., van Waalwijk van Doorn, Linda J. C., Waldemar, Gunhild, Wallin, Anders, Wallin, Åsa K., Wiltfang, Jens, Wolk, David A., Zboch, Marzena, and Zetterberg, Henrik
Published: 2015
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42. Prevalence and prognosis of Alzheimer’s disease at the mild cognitive impairment stage

Author: Vos, Stephanie J. B., Verhey, Frans, Frölich, Lutz, Kornhuber, Johannes, Wiltfang, Jens, Maier, Wolfgang, Peters, Oliver, Rüther, Eckart, Nobili, Flavio, Morbelli, Silvia, Frisoni, Giovanni B., Drzezga, Alexander, Didic, Mira, van Berckel, Bart N. M., Simmons, Andrew, Soininen, Hilkka, Kłoszewska, Iwona, Mecocci, Patrizia, Tsolaki, Magda, Vellas, Bruno, Lovestone, Simon, Muscio, Cristina, Herukka, Sanna-Kaisa, Salmon, Eric, Bastin, Christine, Wallin, Anders, Nordlund, Arto, de Mendonça, Alexandre, Silva, Dina, Santana, Isabel, Lemos, Raquel, Engelborghs, Sebastiaan, Van der Mussele, Stefan, Freund-Levi, Yvonne, Wallin, Åsa K., Hampel, Harald, van der Flier, Wiesje, Scheltens, Philip, and Visser, Pieter Jelle
Published: 2015
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43. Investigation of the choroid plexus implication in Alzheimer's disease pathophysiology using human proteomics and mouse transcriptomics.

Author: Delvenne, Aurore, Vandendriessche, Charysse, Gobom, Johan, Fagan, Anne M., Verhey, Frans R.J., Zetterberg, Henrik, Visser, Pieter Jelle, Vandenbroucke, Roosmarijn E, and Vos, Stephanie J. B.
Abstract: Background: The choroid plexus (CP) is responsible for the production of cerebrospinal fluid (CSF), transport of proteins to the CSF and clearance of proteins from the CSF. The CP becomes compromised during aging, which is exacerbated in AD. Nonetheless, the relation between CP and AD pathophysiology remains unclear. We aim to investigate the pathophysiology underlying the CP involvement in AD, utilizing human CSF proteomics and mouse CP transcriptomics. Method: We included 526 individuals from EMIF‐AD MBD, St Louis Knight ADRC and Maastricht BB‐ACL studies. Based on CSF Aβ1‐42 (A, data‐driven cut‐offs), individuals were classified as controls (cognitively normal (CN) A‐, n = 171) or as amyloid‐positive (CN A+, n = 120; mild cognitive impairment (MCI) A+, n = 154; AD A+, n = 81). CSF proteomic data were generated using TMT spectrometry and protein concentrations were compared using ANOVA adjusted for age and sex. Transcriptomic was performed in CP tissue of APPNL‐G‐F (n = 17) and wild‐type C57BL/6J (n = 17) mice using Illumina RNA‐Seq and differential expression analysis was conducted. Next, Gene Ontology and Ingenuity Pathway analyses were performed. For proteomics, high expression of proteins in the CP was identified based on Allen Brain Atlas and the R package ABAEnrichment. Result: In CN A+, 51 proteins were increased and 21 decreased relative to controls. Out of those increased proteins, 57% were enriched for expression in the CP (ABAEnrichment P<0.001, Figure 1) and were associated with lysosomes and the CLEAR pathway, extracellular matrix and coagulation. A similar pattern was observed for both MCI A+ and AD A+ compared to controls, with a significant percentage of increased proteins enriched for expression in the CP (22 to 30%), which are related to lysosomes and the CLEAR pathway, extracellular matrix and coagulation. In APPNL‐G‐F compared to wild‐type mice, CP transcriptomics revealed 313 upregulated and 198 downregulated genes (Figure 2). The upregulated genes were also associated with the lysosomes and the CLEAR pathway, as well as energy metabolism and lipids. Conclusion: Human proteomics and mice transcriptomics studies suggest an association between amyloid pathology, CP functioning and lysosomes. Dysfunction of lysosomes in AD could relate to compromised clearing events. This is important for future research and AD treatment development. [ABSTRACT FROM AUTHOR]
Published: 2023
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44. Genome-wide association study of Alzheimer's disease brain imaging biomarkers and neuropsychological phenotypes in the EMIF-AD Multimodal Biomarker Discovery dataset

Author: Homann, Jan, primary, Osburg, Tim, additional, Ohlei, Olena, additional, Dobricic, Valerija, additional, Deecke, Laura, additional, Bos, Isabelle, additional, Vandenberghe, Rik, additional, Gabel, Silvy, additional, Scheltens, Philip, additional, Teunissen, Charlotte E., additional, Engelborghs, Sebastiaan, additional, Frisoni, Giovanni, additional, Blin, Olivier, additional, Richardson, Jill C., additional, Bordet, Regis, additional, Lleo, Alberto, additional, Alcolea, Daniel, additional, Popp, Julius, additional, Clark, Christopher, additional, Peyratout, Gwendoline, additional, Martinez-Lage, Pablo, additional, Tainta, Mikel, additional, Dobson, Richard J. B., additional, Legido-Quigley, Cristina, additional, Sleegers, Kristel, additional, Van Broeckhoven, Christine, additional, Wittig, Michael, additional, Franke, Andre, additional, Lill, Christina M., additional, Blennow, Kaj, additional, Zetterberg, Henrik, additional, Lovestone, Simon, additional, Streffer, Johannes, additional, ten Kate, Mara, additional, Vos, Stephanie J. B., additional, Barkhof, Frederik, additional, Visser, Pieter Jelle, additional, and Bertram, Lars, additional
Published: 2021
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45. Subjective cognitive decline and rates of incident Alzheimer's disease and non–Alzheimer's disease dementia

Author: Slot, Rosalinde E R, Sikkes, Sietske A M, Lista, Simone, Luck, Tobias, Maruff, Paul, Molinuevo, José Luis, Kornhuber, Johannes, Reisberg, Barry, Riedel-Heller, Steffi G, Risacher, Shannon L, Roehr, Susanne, Sachdev, Perminder S, Berkhof, Johannes, Scarmeas, Nikolaos, Scheltens, Philip, Shulman, Melanie B, Saykin, Andrew J, Verfaillie, Sander C J, Visser, Pieter Jelle, Vos, Stephanie J B, Wagner, Michael, Wolfsgruber, Steffen, Jessen, Frank, Brodaty, Henry, Initiative, Alzheimer's Disease Neuroimaging, group, DESCRIPA working, group, INSIGHT-preAD study, group, SCD-I working, van der Flier, Wiesje M, Boada, Mercè, de Deyn, Peter Paul, Jones, Roy, Frisoni, Giovanni, Spiru, Luiza, Buckley, Rachel, Nobili, Flavio, Freund-Levi, Yvonne, Soininen, Hilkka, Verhey, Frans, Wallin, Åsa K, Touchon, Jacques, Rikkert, Marcel Olde, Rigaud, Anne-Sophie, Bullock, Roger, Tsolaki, Magda, Cavedo, Enrica, Vellas, Bruno, Wilcock, Gordon, Hampel, Harald, Froelich, Lutz, Bakardjian, Hovagim, Benali, Habib, Bertin, Hugo, Bonheur, Joel, Boukadida, Laurie, Boukerrou, Nadia, Dardiotis, Efthimios, Chiesa, Patrizia, Colliot, Olivier, Dubois, Bruno, Dubois, Marion, Epelbaum, Stéphane, Gagliardi, Geoffroy, Genthon, Remy, Habert, Marie-Odile, Guillo-Benarous, Francoise, Houot, Marion, Kas, Aurélie, Lamari, Foudil, Levy, Marcel, Metzinger, Christiane, Mochel, Fanny, Nyasse, Francis, Poisson, Catherine, Potier, Marie-Claude, Revillon, Marie, Santos, Antonio, Andrade, Katia Santos, Sole, Marine, Surtee, Mohmed, Thiebaud de Schotten, Michel, Vergallo, Andrea, Younsi, Nadjia, Kochan, Nicole A, Psychiatrie & Neuropsychologie, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, DESCRIPA working group, INSIGHT-preAD study group, SCD-I working group, Neurology, Amsterdam Neuroscience - Neurodegeneration, Epidemiology and Data Science, APH - Methodology, APH - Personalized Medicine, and Clinical Neuropsychology
Subjects: 0301 basic medicine, Male, NATIONAL INSTITUTE, Pediatrics, epidemiology [Cognitive Dysfunction], Epidemiology, Dementia incidence, Preclinical Alzheimer's disease, Vascular dementia, Cohort Studies, 0302 clinical medicine, RECRUITMENT METHODS, Risk Factors, Cognitive decline, Aged, 80 and over, Health Policy, Incidence, Hazard ratio, Middle Aged, Alzheimer's disease, IMPAIRMENT, 3. Good health, Psychiatry and Mental health, Disease Progression, Female, psychology [Cognitive Dysfunction], ASSOCIATION WORKGROUPS, Alzheimer’s disease, Frontotemporal dementia, Alzheimer's Disease Neuroimaging Initiative, MAJOR SUBTYPES, medicine.medical_specialty, psychology [Dementia], epidemiology [Dementia], Dementia Lewy bodies, Article, APOLIPOPROTEIN-E, 03 medical and health sciences, Cellular and Molecular Neuroscience, Diagnostic Self Evaluation, Developmental Neuroscience, SDG 3 - Good Health and Well-being, BASE-LINE CHARACTERISTICS, Subjective cognitive decline, Neurology (clinical), Geriatrics and Gerontology, Psychiatry and Mental Health, medicine, Dementia, Humans, Cognitive Dysfunction, ddc:610, OLDER-ADULTS, Preclinical Alzheimer’s disease, Aged, Proportional hazards model, business.industry, Memory clinic, medicine.disease, Self Concept, 030104 developmental biology, DIAGNOSTIC GUIDELINES, Human medicine, business, MEMORY COMPLAINTS, 030217 neurology & neurosurgery
Abstract: Introduction: In this multicenter study on subjective cognitive decline (SCD) in community-based and memory clinic settings, we assessed the (1) incidence of Alzheimer's disease (AD) and non-AD dementia and (2) determinants of progression to dementia.Methods: Eleven cohorts provided 2978 participants with SCD and 1391 controls. We estimated dementia incidence and identified risk factors using Cox proportional hazards models.Results: In SCD, incidence of dementia was 17.7 (95% Poisson confidence interval 15.2-20.3)/1000 person-years (AD: 11.5 [9.6-13.7], non-AD: 6.1 [4.7-7.7]), compared with 14.2 (11.3-17.6) in controls (AD: 10.1 [7.7-13.0], non-AD: 4.1 [2.6-6.0]). The risk of dementia was strongly increased in SCD in a memory clinic setting but less so in a community-based setting. In addition, higher age (hazard ratio 1.1 [95% confidence interval 1.1-1.1]), lower Mini-Mental State Examination (0.7 [0.66-0.8]), and apolipoprotein E epsilon 4 (1.8 [1.3-2.5]) increased the risk of dementia.Discussion: SCD can precede both AD and non-AD dementia. Despite their younger age, individuals with SCD in a memory clinic setting have a higher risk of dementia than those in community-based cohorts. (C) 2018 The Authors. Published by Elsevier Inc.
Published: 2019
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46. Insulinopathies of the brain? Genetic overlap between somatic insulin-related and neuropsychiatric disorders

Author: Fanelli, Giuseppe, primary, Franke, Barbara, additional, De Witte, Ward, additional, Ruisch, I. Hyun, additional, Haavik, Jan, additional, van Gils, Veerle, additional, Jansen, Willemijn J., additional, Vos, Stephanie J. B., additional, Lind, Lars, additional, Buitelaar, Jan K., additional, Banaschewski, Tobias, additional, Dalsgaard, Søren, additional, Serretti, Alessandro, additional, Mota, Nina Roth, additional, Poelmans, Geert, additional, and Bralten, Janita, additional
Published: 2021
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47. Sex-specific metabolic pathways associate with Alzheimer’s Disease (AD) endophenotypes in the European Medical Information Framework for AD Multimodal Biomarker Discovery cohort

Author: Xu, Jin, primary, Green, Rebecca, additional, Kim, Min, additional, Lord, Jodie, additional, Ebshiana, Amera, additional, Westwood, Sarah, additional, Baird, Alison L, additional, Nevado-Holgado, Alejo J, additional, Shi, Liu, additional, Hye, Abdul, additional, Snowden, Stuart G., additional, Bos, Isabelle, additional, Vos, Stephanie J. B., additional, Vandenberghe, Rik, additional, Teunissen, Charlotte E., additional, Kate, Mara Ten, additional, Scheltens, Philip, additional, Gabel, Silvy, additional, Meersmans, Karen, additional, Blin, Olivier, additional, Richardson, Jill, additional, De Roeck, Ellen Elisa, additional, Engelborghs, Sebastiaan, additional, Sleegers, Kristel, additional, Bordet, Régis, additional, Rami, Lorena, additional, Kettunen, Petronella, additional, Tsolaki, Magda, additional, Verhey, Frans R.J., additional, Alcolea, Daniel, additional, Lleó, Alberto, additional, Peyratout, Gwendoline, additional, Tainta, Mikel, additional, Johannsen, Peter, additional, Freund-Levi, Yvonne, additional, Frölich, Lutz, additional, Dobricic, Valerija, additional, Frisoni, Giovanni B., additional, Molinuevo, José Luis, additional, Wallin, Anders, additional, Popp, Julius, additional, Martinez-Lage, Pablo, additional, Bertram, Lars, additional, Blennow, Kaj, additional, Zetterberg, Henrik, additional, Streffer, Johannes, additional, Visser, Pieter Jelle, additional, Lovestone, Simon, additional, Proitsi, Petroula, additional, and Legido-Quigley, Cristina, additional
Published: 2021
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48. Replication study of plasma proteins relating to Alzheimer's pathology

Author: Shi, Liu, primary, Winchester, Laura M., additional, Westwood, Sarah, additional, Baird, Alison L., additional, Anand, Sneha N., additional, Buckley, Noel J, additional, Hye, Abdul, additional, Ashton, Nicholas J., additional, Bos, Isabelle, additional, Vos, Stephanie J. B., additional, Kate, Mara ten, additional, Scheltens, Philip, additional, Teunissen, Charlotte E., additional, Vandenberghe, Rik, additional, Gabel, Silvy, additional, Meersmans, Karen, additional, Engelborghs, Sebastiaan, additional, De Roeck, Ellen E., additional, Sleegers, Kristel, additional, Frisoni, Giovanni B., additional, Blin, Olivier, additional, Richardson, Jill C., additional, Bordet, Régis, additional, Molinuevo, José L., additional, Rami, Lorena, additional, Wallin, Anders, additional, Kettunen, Petronella, additional, Tsolaki, Magda, additional, Verhey, Frans, additional, Lléo, Alberto, additional, Sala, Isabel, additional, Popp, Julius, additional, Peyratout, Gwendoline, additional, Martinez‐Lage, Pablo, additional, Tainta, Mikel, additional, Johannsen, Peter, additional, Freund‐Levi, Yvonne, additional, Frölich, Lutz, additional, Dobricic, Valerija, additional, Legido‐Quigley, Cristina, additional, Barkhof, Frederik, additional, Andreasson, Ulf, additional, Blennow, Kaj, additional, Zetterberg, Henrik, additional, Streffer, Johannes, additional, Lill, Christina M., additional, Bertram, Lars, additional, Visser, Pieter Jelle, additional, Kolb, Hartmuth C., additional, Narayan, Vaibhav A., additional, Lovestone, Simon, additional, and Nevado‐Holgado, Alejo J., additional
Published: 2021
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49. TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer’s disease biomarker levels

Author: Hong, Shengjun, primary, Dobricic, Valerija, additional, Bos, Isabelle, additional, Vos, Stephanie J. B., additional, Prokopenko, Dmitry, additional, Tijms, Betty M., additional, Andreasson, Ulf, additional, Blennow, Kaj, additional, Vandenberghe, Rik, additional, Gabel, Silvy, additional, Scheltens, Philip, additional, Teunissen, Charlotte E., additional, Engelborghs, Sebastiaan, additional, Frisoni, Giovanni, additional, Blin, Olivier, additional, Richardson, Jill C., additional, Bordet, Regis, additional, Lleó, Alberto, additional, Alcolea, Daniel, additional, Popp, Julius, additional, Clark, Christopher, additional, Peyratout, Gwendoline, additional, Martinez-Lage, Pablo, additional, Tainta, Mikel, additional, Dobson, Richard J. B., additional, Legido-Quigley, Cristina, additional, Sleegers, Kristel, additional, Van Broeckhoven, Christine, additional, Tanzi, Rudolph E, additional, ten Kate, Mara, additional, Wittig, Michael, additional, Franke, Andre, additional, Barkhof, Frederik, additional, Lovestone, Simon, additional, Streffer, Johannes, additional, Zetterberg, Henrik, additional, Visser, Pieter Jelle, additional, and Bertram, Lars, additional
Published: 2020
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50. Identifying Protein Quantitative Trait Loci in the Cerebrospinal Fluid Proteome.

Author: Reus, Lianne M., Teunissen, Charlotte E., Gobom, Johan, Vos, Stephanie J. B., Blennow, Kaj, Zetterberg, Henrik, Bertram, Lars, Visser, Pieter Jelle, and Tijms, Betty M.
Abstract: Background: Genome‐wide association studies (GWAS) on dementia have successfully identified variants conferring risk to disease. Still, how such variants impact exact biological mechanisms underlying disease remains largely unclear. Protein quantitative trait loci (pQTLs) measured in cerebrospinal fluid (CSF) may provide insight into these neurobiological mechanisms, since CSF protein levels can reflect ongoing processes in the brain and have been related to genetic variants. We used a CSF pQTL approach in individuals along the Alzheimer's disease (AD) spectrum to reveal intermediate molecular pathways by which genetic variance influences neurobiological processes. Improving the functional interpretation of genetic variants in a matrix relevant to neurological disease helps deciphering biological mechanisms underlying neurological traits. Method: We selected 243 subjects (106 controls/67 mild cognitive impairment/70 AD‐dementia, age 66.8±8.1 years, 53.9%female) from the EMIF‐AD MBD study, who had genetic data and CSF data (n = 1,351 proteins, tandem mass tag (TMT) mass spectrometry) available. Association signals between genetic variants and CSF proteins were tested using linear regression, adjusted for principal components (PC1‐3), age and sex using the genome‐wide significance threshold (P<5.0e−8). CSF pQTLs were identified as novel if the association has not been previously reported in Yang et al., (2021), Sasayama et al., (2017) or Kauwe et al., (2014). Results: Twenty‐four out of 1,351 CSF proteins (1.78%) showed genome‐wide significant associations with in total 147 SNPs (Table 1; Figure 1). We identified 25 CSF pQTLs, representing three cis‐acting (IGH, LTF and ADAMTS8) and 22 trans‐acting pQTLs. Results included mostly novel CSF pQTL associations, exception for the cis association of LTF with LTF protein levels. Two novel cis‐acting pQTLs were previously reported in a study on human lymphocytes (IGH on IGHV2‐70D) (Theusch et al., 2020) and prefrontal cortex brain data (ADAMTS8 on ADAMTS8) (Ng et al., 2017). Conclusions: These results contribute to the functional interpretation of genetic variance on neurobiological processes, by pinpointing inflammation and tissue remodeling as potential contributing mechanisms in AD. [ABSTRACT FROM AUTHOR]
Published: 2023
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