75 results on '"Tainta, M"'
Search Results
2. Test cognitivos breves como herramienta de decisión en Atención Primaria. Estudio poblacional y de validación
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Tainta, M., Iriondo, A., Ecay-Torres, M., Estanga, A., de Arriba, M., Barandiaran, M., Clerigue, M., Garcia-Sebastian, M., Villanua, J., Izagirre, A., Saldias, J., Aramburu, A., Taboada, J., Múgica, J., Barandiaran, A., Arrospide, A., Mar, J., and Martinez-Lage, P.
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- 2024
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3. Dementia-related neuropsychiatric symptoms: inequalities in pharmacological treatment and institutionalization
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Mar J, Arrospide A, Soto-Gordoa M, Iruin Á, Tainta M, Gabilondo A, Mar-Barrutia L, Calvo M, Mateos M, and Ibarrondo O
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Neuropsychiatric symptoms ,prevalence ,dementia ,antidepressant drugs ,antipsychotic drugs ,nursing home ,inequalities ,deprivation index ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Javier Mar,1–4 Arantzazu Arrospide,2–4 Myriam Soto-Gordoa,5 Álvaro Iruin,4,6 Mikel Tainta,7,8 Andrea Gabilondo,4,6 Lore Mar-Barrutia,9 Montserrat Calvo,10 Maider Mateos,10 Oliver Ibarrondo2,41Clinical Management Unit, OSI Alto Deba, Arrasate-Mondragón, España; 2AP-OSIs Gipuzkoa Research Unit, OSI Alto Deba, Arrasate-Mondragón, España; 3Economic Evaluation Department, Health Services Research on Chronic Patients Network (REDISSEC), Bilbao, Spain; 4Economic Evaluation Department, Biodonostia Health Research Institute, Donostia-San Sebastián, Spain; 5Departamento de Ingeniería de Organización, Mondragón Unibertsitatea, Arrasate-Mondragón, España; 6Psychiatry Service, Gipuzkoa Mental Health Network, Donostia-San Sebastián, España; 7Psychiatry Service, CITA Alzheimer Foundation, Donostia-San Sebastián, España; 8Neurology Service, OSI Goierri-Alto Urola, Zumárraga, España; 9Psychiatry Service, Hospital Bellvitge, Hospitalet de Llobregat, España; 10Health Department, Basque Government, Vitoria-Gasteiz, EspañaBackground: Dementia-related neuropsychiatric symptoms (NPS) are the main determinant of family stress and institutionalization of patients. This study aimed to identify inequalities by gender and socioeconomic status in the management of NPS in patients diagnosed with dementia.Methods: An observational study was carried out to study all the cases of dementia in the corporate database of the Basque Health Service (29,864 patients). The prescription of antipsychotics and antidepressants and admission to a nursing home were used to establish the presence of NPS. The socioeconomic status of individuals was classified by a deprivation index. Logistic regressions were used to identify drivers for drug prescriptions and institutionalization.Results: NPS are poorly recorded in the clinical databases (12%). Neuropsychiatric symptoms were severe enough in two thirds of patients with dementia to be treated with psychoactive medication. Institutionalization showed an increase from those who did not receive medication to those who had been prescribed antidepressants (OR: 1.546), antipsychotics (OR: 2.075) or both (OR: 2.741). The resulting inequalities were the increased prescription of antidepressant drugs in women and more nursing-home admissions for women who were the least socioeconomically deprived and men who were the most deprived.Conclusions: In large clinical databases, psychoactive drugs prescriptions can be useful to underscore the considerable burden of dementia-related NPS. Specific tools are needed to monitor social and health care programs targeted to dementia-related NPS from a population perspective. Programs aimed at reducing the family burden of care of dementia patients at home become the key elements in reducing inequalities in these patients’ care. Socioeconomic status is the most important driver of inequality, and gender inequality may simply be hidden within the social environment. Integrated programs boosting the continuity of care are an objective for which compliance could be measured according to the NPS coding in the electronic health record.Keywords: neuropsychiatric symptoms, prevalence, dementia, antidepressant drugs, antipsychotic drugs, nursing home, inequalities, deprivation index
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- 2019
4. Cerebellar and subcortical atrophy contribute to psychiatric symptoms in frontotemporal dementia
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Bussy, A., Levy, J., Best, T., Patel, R., Cupo, L., Van Langenhove, T., Nielsen, J., Pijnenburg, Y., Waldö, M., Remes, A., Schroeter, M., Santana, I., Pasquier, F., Otto, M., Danek, A., Levin, J., Le Ber, I., Vandenberghe, R., Synofzik, M., Moreno, F., de Mendonça, A., Sanchez‐Valle, R., Laforce, R., Langheinrich, T., Gerhard, A., Graff, C., Butler, C., Sorbi, S., Jiskoot, L., Seelaar, H., van Swieten, J., Finger, E., Tartaglia, M., Masellis, M., Tiraboschi, P., Galimberti, D., Borroni, B., Rowe, J., Bocchetta, M., Rohrer, J., Devenyi, G., Chakravarty, M., Ducharme, S., Esteve, A., Nelson, A., Bouzigues, A., Heller, C., Greaves, C., Cash, D., Thomas, D., Todd, E., Benotmane, H., Zetterberg, H., Swift, I., Nicholas, J., Samra, K., Russell, L., Shafei, R., Convery, R., Timberlake, C., Cope, T., Rittman, T., Benussi, A., Premi, E., Gasparotti, R., Archetti, S., Gazzina, S., Cantoni, V., Arighi, A., Fenoglio, C., Scarpini, E., Fumagalli, G., Borracci, V., Rossi, G., Giaccone, G., Di Fede, G., Caroppo, P., Prioni, S., Redaelli, V., Tang‐Wai, D., Rogaeva, E., Castelo‐Branco, M., Freedman, M., Keren, R., Black, S., Mitchell, S., Shoesmith, C., Bartha, R., Rademakers, R., Poos, J., Papma, J., Giannini, L., van Minkelen, R., Nacmias, B., Ferrari, C., Polito, C., Lombardi, G., Bessi, V., Veldsman, M., Andersson, C., Thonberg, H., Öijerstedt, L., Jelic, V., Thompson, P., Lladó, A., Antonell, A., Olives, J., Balasa, M., Bargalló, N., Borrego‐Ecija, S., Verdelho, A., Maruta, C., Ferreira, C., Miltenberger, G., do Couto, F., Gabilondo, A., Gorostidi, A., Villanua, J., Cañada, M., Tainta, M., Zulaica, M., Barandiaran, M., Alves, P., Bender, B., Wilke, C., Graf, L., Vogels, A., Vandenbulcke, M., Van Damme, P., Bruffaerts, R., Poesen, K., Rosa‐Neto, P., Gauthier, S., Camuzat, A., Brice, A., Bertrand, A., Funkiewiez, A., Rinaldi, D., Saracino, D., Colliot, O., Sayah, S., Prix, C., Wlasich, E., Wagemann, O., Loosli, S., Schönecker, S., Hoegen, T., Lombardi, J., Anderl‐Straub, S., Rollin, A., Kuchcinski, G., Bertoux, M., Lebouvier, T., Deramecourt, V., Santiago, B., Duro, D., Leitão, M., Almeida, M., Tábuas‐Pereira, M., Afonso, S., Engel, A., Polyakova, M., Erasmus MC other, Neurology, Radiology & Nuclear Medicine, Clinical Genetics, GENetic Frontotemporal dementia Initiative (GENFI), Lombardi, Gemma, Bessi, Valentina, Veldsman, Michele, Andersson, Christin, Thonberg, Hakan, Öijerstedt, Linn, Jelic, Vesna, Thompson, Paul, Langheinrich, Tobias, Lladó, Albert, Antonell, Anna, Olives, Jaume, Balasa, Mircea, Bargalló, Nuria, Borrego-Ecija, Sergi, Verdelho, Ana, Maruta, Carolina, Ferreira, Catarina B, Miltenberger, Gabriel, do Couto, Frederico Simões, Gabilondo, Alazne, Gorostidi, Ana, Villanua, Jorge, Cañada, Marta, Tainta, Mikel, Zulaica, Miren, Barandiaran, Myriam, Alves, Patricia, Bender, Benjamin, Wilke, Carlo, Graf, Lisa, Vogels, Annick, Vandenbulcke, Mathieu, Van Damme, Philip, Bruffaerts, Rose, Poesen, Koen, Rosa-Neto, Pedro, Gauthier, Serge, Camuzat, Agnès, Brice, Alexis, Bertrand, Anne, Funkiewiez, Aurélie, Rinaldi, Daisy, Saracino, Dario, Colliot, Olivier, Sayah, Sabrina, Prix, Catharina, Wlasich, Elisabeth, Wagemann, Olivia, Loosli, Sandra, Schönecker, Sonja, Hoegen, Tobias, Lombardi, Jolina, Anderl-Straub, Sarah, Rollin, Adeline, Kuchcinski, Gregory, Bertoux, Maxime, Lebouvier, Thibaud, Deramecourt, Vincent, Santiago, Beatriz, Duro, Diana, Leitão, Maria João, Almeida, Maria Rosario, Tábuas-Pereira, Miguel, Afonso, Sónia, Engel, Annerose, Polyakova, Maryna, Esteve, Aitana Sogorb, Nelson, Annabel, Bouzigues, Arabella, Heller, Carolin, Greaves, Caroline V, Cash, David, Thomas, David L, Todd, Emily, Benotmane, Hanya, Zetterberg, Henrik, Swift, Imogen J, Nicholas, Jennifer, Samra, Kiran, Russell, Lucy L, Bocchetta, Martina, Shafei, Rachelle, Convery, Rhian S, Timberlake, Carolyn, Cope, Thomas, Rittman, Timothy, Benussi, Alberto, Premi, Enrico, Gasparotti, Roberto, Archetti, Silvana, Gazzina, Stefano, Cantoni, Valentina, Arighi, Andrea, Fenoglio, Chiara, Scarpini, Elio, Fumagalli, Giorgio, Borracci, Vittoria, Rossi, Giacomina, Giaccone, Giorgio, Di Fede, Giuseppe, Caroppo, Paola, Tiraboschi, Pietro, Prioni, Sara, Redaelli, Veronica, Tang-Wai, David, Rogaeva, Ekaterina, Castelo-Branco, Miguel, Freedman, Morris, Keren, Ron, Black, Sandra, Mitchell, Sara, Shoesmith, Christen, Bartha, Robart, Rademakers, Rosa, Poos, Jackie, Papma, Janne M, Giannini, Lucia, van Minkelen, Rick, Pijnenburg, Yolande, Nacmias, Benedetta, Ferrari, Camilla, Polito, Cristina, Bussy, Aurélie [0000-0001-6695-9941], Nielsen, Jørgen E [0000-0003-0453-5582], Borroni, Barbara [0000-0001-9340-9814], Bocchetta, Martina [0000-0003-1814-5024], Devenyi, Gabriel A [0000-0002-7766-1187], Apollo - University of Cambridge Repository, and Amsterdam Neuroscience - Neurodegeneration
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C9orf72 Protein ,Radiological and Ultrasound Technology ,Medizin ,frontotemporal dementia ,Neurology ,Frontotemporal Dementia ,Cerebellum ,Humans ,magnetic resonance imaging ,genetics ,neuropsychiatry ,Radiology, Nuclear Medicine and imaging ,Human medicine ,ddc:610 ,Neurology (clinical) ,Atrophy ,Anatomy ,genetics [Frontotemporal Dementia] ,genetics [C9orf72 Protein] - Abstract
Funder: Alzheimer Society of Canada; Id: http://dx.doi.org/10.13039/501100000143, Funder: Weston Brain Institute; Id: http://dx.doi.org/10.13039/100012479, Funder: Fonds de Recherche du Québec ‐ Santé, Funder: Canadian Institutes of Health Research; Id: http://dx.doi.org/10.13039/501100000024, Funder: NIHR Rare Diseases Translational Research Collaboration, Funder: Deutsche Forschungsgemeinschaft; Id: http://dx.doi.org/10.13039/501100001659, Recent studies have reported early cerebellar and subcortical impact in the disease progression of genetic frontotemporal dementia (FTD) due to microtubule-associated protein tau (MAPT), progranulin (GRN) and chromosome 9 open reading frame 72 (C9orf72). However, the cerebello-subcortical circuitry in FTD has been understudied despite its essential role in cognition and behaviors related to FTD symptomatology. The present study aims to investigate the association between cerebellar and subcortical atrophy, and neuropsychiatric symptoms across genetic mutations. Our study included 983 participants from the Genetic Frontotemporal dementia Initiative including mutation carriers and noncarrier first-degree relatives of known symptomatic carriers. Voxel-wise analysis of the thalamus, striatum, globus pallidus, amygdala, and the cerebellum was performed, and partial least squares analyses (PLS) were used to link morphometry and behavior. In presymptomatic C9orf72 expansion carriers, thalamic atrophy was found compared to noncarriers, suggesting the importance of this structure in FTD prodromes. PLS analyses demonstrated that the cerebello-subcortical circuitry is related to neuropsychiatric symptoms, with significant overlap in brain/behavior patterns, but also specificity for each genetic mutation group. The largest differences were in the cerebellar atrophy (larger extent in C9orf72 expansion group) and more prominent amygdalar volume reduction in the MAPT group. Brain scores in the C9orf72 expansion carriers and MAPT carriers demonstrated covariation patterns concordant with atrophy patterns detectable up to 20 years before expected symptom onset. Overall, these results demonstrated the important role of the subcortical structures in genetic FTD symptom expression, particularly the cerebellum in C9orf72 and the amygdala in MAPT carriers.
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- 2023
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5. Motor symptoms in genetic frontotemporal dementia: developing a new module for clinical rating scales
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Samra, K, MacDougall, AM, Peakman, G, Bouzigues, A, Bocchetta, M, Cash, DM, Greaves, CV, Convery, RS, van Swieten, JC, Jiskoot, L, Seelaar, H, Butler, CR, Fenoglio, C, Rohrer, JD, Gerhard, A, Ducharme, S, Le Ber, I, Tiraboschi, P, Santana, I, Pasquier, F, Levin, J, Shoesmith, C, Otto, M, Russell, LL, Nelson, A, Cash, D, Thomas, DL, Todd, E, Ferrari, C, Benotmane, H, Timberlake, C, Gabilondo, A, Cope, T, Rittman, T, Benussi, A, Premi, E, Gasparotti, R, Thompson, P, Archetti, S, Fumagalli, G, do Couto, FS, Borracci, V, Polito, C, Rossi, G, Giaccone, G, Di Fede, G, Caroppo, P, Ferreira, CB, Prioni, S, Langheinrich, T, Redaelli, V, Lladó, A, Bartha, R, Tang-Wai, D, Rogaeva, E, Castelo-Branco, M, Freedman, M, Keren, R, Black, S, Mitchell, S, Miltenberger, G, Rademakers, R, Poos, J, Papma, JM, Giannini, L, van Minkelen, R, Pijnenburg, Y, Gauthier, S, Nacmias, B, Lombardi, G, Bessi, V, Veldsman, M, Andersson, C, Thonberg, H, Öijerstedt, L, Prix, C, Jelic, V, Antonell, A, Graff, C, Olives, J, Balasa, M, Bargalló, N, Borrego-Ecija, S, Verdelho, A, Kuchcinski, G, Maruta, C, Gorostidi, A, Laforce, R, Villanua, J, Wlasich, E, Cañada, M, Tainta, M, Zulaica, M, Barandiaran, M, Moreno, F, Alves, P, Bender, B, Bertoux, M, Wilke, C, Lebouvier, T, Camuzat, A, Graf, L, Vogels, A, Vandenbulcke, M, Van Damme, P, Bruffaerts, R, Poesen, K, Rosa-Neto, P, Sanchez-Valle, R, Brice, A, Bertrand, A, Funkiewiez, A, Rinaldi, D, Saracino, D, Colliot, O, Sorbi, S, Sayah, S, Wagemann, O, Loosli, S, Schönecker, S, Hoegen, T, Lombardi, J, Anderl-Straub, S, Nicholas, J, Rollin, A, Deramecourt, V, Arighi, A, Santiago, B, Duro, D, Leitão, MJ, Almeida, MR, Tábuas-Pereira, M, Gazzina, S, Afonso, S, Masellis, M, Tartaglia, C, Shafei, R, Rowe, JB, Borroni, B, Finger, E, Synofzik, M, Galimberti, D, Vandenberghe, R, de Mendonça, A, Cantoni, V, Genetic FTD Initiative (GENFI), Samra, Kiran [0000-0002-3105-7099], Apollo - University of Cambridge Repository, Maruta, Carolina, Ferreira, Catarina B, Miltenberger, Gabriel, do Couto, Frederico Simões, Gabilondo, Alazne, Gorostidi, Ana, Villanua, Jorge, Cañada, Marta, Tainta, Mikel, Zulaica, Miren, Barandiaran, Myriam, Alves, Patricia, Bender, Benjamin, Wilke, Carlo, Graf, Lisa, Vogels, Annick, Vandenbulcke, Mathieu, Van Damme, Philip, Bruffaerts, Rose, Poesen, Koen, Rosa-Neto, Pedro, Gauthier, Serge, Camuzat, Agnès, Brice, Alexis, Bertrand, Anne, Funkiewiez, Aurélie, Rinaldi, Daisy, Saracino, Dario, Colliot, Olivier, Sayah, Sabrina, Prix, Catharina, Wlasich, Elisabeth, Wagemann, Olivia, Loosli, Sandra, Schönecker, Sonja, Hoegen, Tobias, Lombardi, Jolina, Anderl-Straub, Sarah, Rollin, Adeline, Kuchcinski, Gregory, Bertoux, Maxime, Lebouvier, Thibaud, Deramecourt, Vincent, Santiago, Beatriz, Duro, Diana, Leitão, Maria João, Almeida, Maria Rosario, Tábuas-Pereira, Miguel, Afonso, Sónia, Nelson, Annabel, Bocchetta, Martina, Cash, David, Thomas, David L, Todd, Emily, Benotmane, Hanya, Nicholas, Jennifer, Samra, Kiran, Shafei, Rachelle, Timberlake, Carolyn, Cope, Thomas, Rittman, Timothy, Benussi, Alberto, Premi, Enrico, Gasparotti, Roberto, Archetti, Silvana, Gazzina, Stefano, Cantoni, Valentina, Arighi, Andrea, Fenoglio, Chiara, Fumagalli, Giorgio, Borracci, Vittoria, Rossi, Giacomina, Giaccone, Giorgio, Di Fede, Giuseppe, Caroppo, Paola, Tiraboschi, Pietro, Prioni, Sara, Redaelli, Veronica, Tang-Wai, David, Rogaeva, Ekaterina, Castelo-Branco, Miguel, Freedman, Morris, Keren, Ron, Black, Sandra, Mitchell, Sara, Shoesmith, Christen, Bartha, Robart, Rademakers, Rosa, Poos, Jackie, Papma, Janne M, Giannini, Lucia, van Minkelen, Rick, Pijnenburg, Yolande, Nacmias, Benedetta, Ferrari, Camilla, Polito, Cristina, Lombardi, Gemma, Bessi, Valentina, Veldsman, Michele, Andersson, Christin, Thonberg, Hakan, Öijerstedt, Linn, Jelic, Vesna, Thompson, Paul, Langheinrich, Tobias, Lladó, Albert, Antonell, Anna, Olives, Jaume, Balasa, Mircea, Bargalló, Nuria, Borrego-Ecija, Sergi, and Verdelho, Ana
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Progranulin ,Clinical Neurology ,C9ORF72 ,tau Proteins ,AMYOTROPHIC-LATERAL-SCLEROSIS ,diagnosis [Frontotemporal Dementia] ,C9orf72 ,Tremor ,Genetics ,Humans ,ddc:610 ,genetics [Frontotemporal Dementia] ,genetics [C9orf72 Protein] ,MUTATION ,Science & Technology ,C9orf72 Protein ,HERITABILITY ,Amyotrophic Lateral Sclerosis ,PROGRESSIVE SUPRANUCLEAR PALSY ,COGNITIVE IMPAIRMENT ,REPEAT EXPANSION ,genetics [tau Proteins] ,Motor ,PATHOLOGICAL FEATURES ,Neurology ,FOS: Biological sciences ,Frontotemporal Dementia ,Mutation ,Human medicine ,Neurosciences & Neurology ,Neurology (clinical) ,Tau ,TAU ,Life Sciences & Biomedicine ,Frontotemporal dementia ,PARKINSONISM - Abstract
Funder: CIBERNED, Funder: Canadian Institutes of Health Research; doi: http://dx.doi.org/10.13039/501100000024, Funder: Lemaire Family Foundation, Funder: Swedish Frontotemporal Dementia Initiative, Funder: Italian Ministry of Health, Funder: Weston Brain Institute; doi: http://dx.doi.org/10.13039/100012479, Funder: Mady Browaaeys Fund, Funder: Miriam Marks Brain Research UK, Funder: Bluefield Project, OBJECTIVE: To investigate the optimal method of adding motor features to a clinical rating scale for frontotemporal dementia (FTD). METHODS: Eight hundred and thirty-two participants from the international multicentre Genetic FTD Initiative (GENFI) study were recruited: 522 mutation carriers (with C9orf72, GRN and MAPT mutations) and 310 mutation-negative controls. A standardised clinical questionnaire was used to assess eight motor symptoms (dysarthria, dysphagia, tremor, slowness, weakness, gait disorder, falls and functional difficulties using hands). Frequency and severity of each motor symptom was assessed, and a principal component analysis (PCA) was performed to identify how the different motor symptoms loaded together. Finally, addition of a motor component to the CDR® plus NACC FTLD was investigated (CDR® plus NACC FTLD-M). RESULTS: 24.3% of mutation carriers had motor symptoms (31.7% C9orf72, 18.8% GRN, 19.3% MAPT) compared to 6.8% of controls. Slowness and gait disorder were the commonest in all genetic groups while tremor and falls were the least frequent. Symptom severity scores were similar to equivalent physical motor examination scores. PCA revealed that all motor symptoms loaded together so a single additional motor component was added to the CDR® plus NACC FTLD to form the CDR® plus NACC FTLD-M. Individual global scores were more severe with the CDR® plus NACC FTLD-M, and no patients with a clinically diagnosed motor disorder (ALS/FTD-ALS or parkinsonism) were classified anymore as asymptomatic (unlike the CDR® plus NACC FTLD alone). CONCLUSIONS: Motor features are present in mutation carriers at all disease stages across all three genetic groups. Inclusion of motor symptoms in a rating scale that can be used in future clinical trials will not only ensure a more accurate severity measure is recorded but that a wider spectrum of FTD phenotypes can be included in the same trial.
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- 2022
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6. 20170. DISMINUCIÓN DE LOS EFECTOS DE LA PRÁCTICA EN LA ENFERMEDAD DE ALZHEIMER PRECLÍNICA: UN ESTUDIO MULTICÉNTRICO, LONGITUDINAL Y DE COHORTES
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Tort Merino, A., Pérez-Millán, A., Falgàs, N., Borrego-Écija, S., Guillén, N., Sarto, J., Esteller, D., Bosch, B., Castellví, M., Juncà- Parella, J., del Val, A., Fernández-Villullas, G., Antonell, A., Sánchez-Saudinós, M., Rubio-Guerra, S., Zhu, N., García-Martínez, M., Pozueta, A., Estanga, A., Ecay-Torres, M., López de Luis, C., Tainta, M., Altuna, M., Rodríguez-Rodríguez, E., Sánchez-Juan, P., Martínez-Lage, P., Lleó, A., Fortea, J., Illán-Gala, I., Balasa, M., Lladó, A., Rami, L., and Sánchez-Valle, R.
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- 2024
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7. Modelling the cascade of biomarker changes in GRN-related frontotemporal dementia
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Panman, J. L., Venkatraghavan, V., Van Der Ende, E. L., Steketee, R. M. E., Jiskoot, L. C., Poos, J. M., Dopper, E. G. P., Meeter, L. H. H., Kaat, L. D., Rombouts, S. A. R. B., Vernooij, M. W., Kievit, A. J. A., Premi, E., Cosseddu, M., Bonomi, E., Olives, J., Rohrer, J. D., Sanchez-Valle, R., Borroni, B., Bron, E. E., Van Swieten, J. C., Papma, J. M., Klein, S., Afonso, S., Almeida, M. R., Anderl-Straub, S., Andersson, C., Antonell, A., Archetti, S., Arighi, A., Balasa, M., Barandiaran, M., Bargallo, N., Bartha, R., Bender, B., Black, S., Butler, C., Bocchetta, M., Borrego-Ecija, S., Bras, J., Bruffaerts, R., Caroppo, P., Cash, D., Castelo-Branco, M., Convery, R., Cope, T., Danek, A., De Arriba, M., De Mendonca, A., Di Fede, G., Diaz, Z., Ducharme, S., Duro, D., Fenoglio, C., Ferreira, C. B., Finger, E., Flanagan, T., Fox, N., Freedman, M., Fumagalli, G., Gabilondo, A., Galimberti, D., Gasparotti, R., Gauthier, S., Gazzina, S., Gerhard, A., Giaccone, G., Gorostidi, A., Graff, C., Greaves, C., Guerreiro, R., Heller, C., Hoegen, T., Indakoetxea, B., Jelic, V., Karnath, H. -O., Keren, R., Laforce, R., Leitao, M. J., Levin, J., Llado, A., Loosli, S., Maruta, C., Masellis, M., Mead, S., Miltenberger, G., Van Minkelenm Sara Mitchell, R., Moore, K., Moreno, F., Nicholas, J., Oijerstedt, L., Otto, M., Ourselin, S., Padovani, A., Peakman, G., Pijnenburg, Y., Polito, C., Prioni, S., Prix, C., Rademakers, R., Redaelli, V., Rittman, T., Rogaeva, E., Rosa-Neto, P., Rossi, G., Rosser, M., Rowe, J., Santana, I., Santiago, B., Scarpini, E., Schonecker, S., Shafei, E. S. R., Shoesmith, C., Synofzik, M., Tabuas-Pereira, M., Tagliavini, F., Tartaglia, C., Tainta, M., Taipa, R., Tang-Wai, D., Thomas, D. L., Thonberg, H., Timberlake, C., Tiraboschi, P., Todd, E., Vandamme, P., Vandenberghe, R., Vandenbulcke, M., Veldsman, M., Verdelho, A., Villanua, J., Warren, J., Wilkeione, C., Elisabeth, W., Henrik, W., Zulaica, Z. M., Neurology, Physics and medical technology, Radiology & Nuclear Medicine, Clinical Genetics, and Medical Research Council
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Male ,Oncology ,Disease ,Neuropsychological Tests ,GENFI consortium investigators ,Primary progressive aphasia ,Cognition ,Progranulins ,0302 clinical medicine ,Neurofilament Proteins ,BEHAVIORAL VARIANT ,HETEROGENEITY ,Gray Matter ,11 Medical and Health Sciences ,Language ,Psychiatry ,0303 health sciences ,Brain ,Middle Aged ,Magnetic Resonance Imaging ,White Matter ,17 Psychology and Cognitive Sciences ,ALZHEIMERS-DISEASE ,Psychiatry and Mental health ,Phenotype ,medicine.anatomical_structure ,Frontotemporal Dementia ,Disease Progression ,Biomarker (medicine) ,Female ,Life Sciences & Biomedicine ,Frontotemporal dementia ,medicine.medical_specialty ,Clinical Neurology ,EVENT-BASED MODEL ,Grey matter ,Lateralization of brain function ,White matter ,03 medical and health sciences ,SDG 3 - Good Health and Well-being ,Internal medicine ,NEUROFILAMENT LIGHT-CHAIN ,medicine ,Humans ,LOBAR DEGENERATION ,PROGRANULIN ,Aged ,030304 developmental biology ,Science & Technology ,Neurology & Neurosurgery ,business.industry ,DISEASE PROGRESSION ,medicine.disease ,Mutation ,WHITE-MATTER INTEGRITY ,Surgery ,Neurosciences & Neurology ,Neurology (clinical) ,business ,GENFI ,Biomarkers ,030217 neurology & neurosurgery ,Progressive disease - Abstract
ObjectiveProgranulin-related frontotemporal dementia (FTD-GRN) is a fast progressive disease. Modelling the cascade of multimodal biomarker changes aids in understanding the aetiology of this disease and enables monitoring of individual mutation carriers. In this cross-sectional study, we estimated the temporal cascade of biomarker changes for FTD-GRN, in a data-driven way.MethodsWe included 56 presymptomatic and 35 symptomatic GRN mutation carriers, and 35 healthy non-carriers. Selected biomarkers were neurofilament light chain (NfL), grey matter volume, white matter microstructure and cognitive domains. We used discriminative event-based modelling to infer the cascade of biomarker changes in FTD-GRN and estimated individual disease severity through cross-validation. We derived the biomarker cascades in non-fluent variant primary progressive aphasia (nfvPPA) and behavioural variant FTD (bvFTD) to understand the differences between these phenotypes.ResultsLanguage functioning and NfL were the earliest abnormal biomarkers in FTD-GRN. White matter tracts were affected before grey matter volume, and the left hemisphere degenerated before the right. Based on individual disease severities, presymptomatic carriers could be delineated from symptomatic carriers with a sensitivity of 100% and specificity of 96.1%. The estimated disease severity strongly correlated with functional severity in nfvPPA, but not in bvFTD. In addition, the biomarker cascade in bvFTD showed more uncertainty than nfvPPA.ConclusionDegeneration of axons and language deficits are indicated to be the earliest biomarkers in FTD-GRN, with bvFTD being more heterogeneous in disease progression than nfvPPA. Our data-driven model could help identify presymptomatic GRN mutation carriers at risk of conversion to the clinical stage.
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- 2021
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8. Test cognitivos breves como herramienta de decisión en Atención Primaria. Estudio poblacional y de validación
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Tainta, M., primary, Iriondo, A., additional, Ecay-Torres, M., additional, Estanga, A., additional, de Arriba, M., additional, Barandiaran, M., additional, Clerigue, M., additional, Garcia-Sebastian, M., additional, Villanua, J., additional, Izagirre, A., additional, Saldias, J., additional, Aramburu, A., additional, Taboada, J., additional, Múgica, J., additional, Barandiaran, A., additional, Arrospide, A., additional, Mar, J., additional, and Martinez-Lage, P., additional
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- 2022
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9. Brief cognitive tests as a decision-making tool in primary care. A population and validation study
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Tainta, M., primary, Iriondo, A., additional, Ecay-Torres, M., additional, Estanga, A., additional, de Arriba, M., additional, Barandiaran, M., additional, Clerigue, M., additional, Garcia-Sebastian, M., additional, Villanua, J., additional, Izagirre, A., additional, Saldias, J., additional, Aramburu, A., additional, Taboada, J., additional, Múgica, J., additional, Barandiaran, A., additional, Arrospide, A., additional, Mar, J., additional, and Martinez-Lage, P., additional
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- 2022
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10. TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer's disease biomarker levels
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Hong, SJ, Dobricic, V, Ohlei, O, Bos, I, Vos, SJB, Prokopenko, D, Tijms, BM, Andreasson, U, Blennow, K, Vandenberghe, R, Gabel, S, Scheltens, P, Teunissen, CE, Engelborghs, S, Frisoni, G, Blin, O, Richardson, JC, Bordet, R, Lleo, A, Alcolea, D, Popp, J, Clark, C, Peyratout, G, Martinez-Lage, P, Tainta, M, Dobson, RJB, Legido-Quigley, C, Sleegers, K, Van Broeckhoven, C, Tanzi, RE, ten Kate, M, Wittig, M, Franke, A, Lill, CM, Barkhof, F, Lovestone, S, Streffer, J, Zetterberg, H, Visser, PJ, Bertram, L, and Neuroimaging Initiative
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s disease ,wide association study ,chitinase‐ ,like protein 1 ,neurogranin ,neurofilament light ,3‐ ,biomarker ,genome‐ ,Alzheimer&apos ,cerebrospinal fluid - Abstract
Introduction Neurofilament light (NfL), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are biomarkers for Alzheimer's disease (AD) to monitor axonal damage, astroglial activation, and synaptic degeneration, respectively. Methods We performed genome-wide association studies (GWAS) using DNA and cerebrospinal fluid (CSF) samples from the EMIF-AD Multimodal Biomarker Discovery study for discovery, and the Alzheimer's Disease Neuroimaging Initiative study for validation analyses. GWAS were performed for all three CSF biomarkers using linear regression models adjusting for relevant covariates. Results We identify novel genome-wide significant associations between DNA variants in TMEM106B and CSF levels of NfL, and between CPOX and YKL-40. We confirm previous work suggesting that YKL-40 levels are associated with DNA variants in CHI3L1. Discussion Our study provides important new insights into the genetic architecture underlying interindividual variation in three AD-related CSF biomarkers. In particular, our data shed light on the sequence of events regarding the initiation and progression of neuropathological processes relevant in AD.
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- 2021
11. Abnormal pain perception is associated with thalamo-cortico-striatal atrophy in C9orf72 expansion carriers in the GENFI cohort
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Convery, Rhian S, Bocchetta, Martina, Masellis, Mario, Afonso, S., Taipa, R., Caroppo, P., Di Fede, G., Giaccone, G., Prioni, S., Redaelli, V., Rossi, G., Tiraboschi, P., Duro, D., Tartaglia, Maria Carmela, Almeida, M. R., Branco, M. C., Leitão, M. J., Tabuas-Pereira, M., Santiago, B., Gauthier, S., Rosa-Neto, P., Veldsman, M., Flanagan, T., Prix, C., Graff, Caroline, Hoegen, T., Wlasich, E., Loosli, S., Schonecker, S., Semler, E., Anderl-Straub, S., Galimberti, Daniela, Rowe, James B, Finger, Elizabeth, Synofzik, Matthis, Vandenberghe, Rik, de Mendonca, Alexandre, Tagliavini, Fabrizio, Greaves, Caroline V, Santana, Isabel, Ducharme, Simon, Butler, Christopher, Gerhard, Alex, Levin, Johannes, Danek, Adrian, Otto, Markus, Warren, Jason D, Rohrer, Jonathan D, Initiative, Genetic FTD, Moore, Katrina M, Rossor, M. N., Fox, N. C., Woollacott, I. O. C., Shafei, R., Heller, C., Peakman, G., Swift, I., Todd, E., Guerreiro, R., Bras, J., Cash, David M, Thomas, D. L., Nicholas, J., Mead, S., Jiskoot, L., Meeter, L., Panman, J., Papma, J., van Minkelen, R., Pijnenburg, Y., Barandiara, M., Van Swieten, John, Indakoetxea, B., Gabilondo, A., Tainta, M., de Arriba, M., Gorostidi, A., Zulaica, M., Villanua, J., Diaz, Z., Borrego-Ecija, S., Olives, J., Moreno, Fermin, Lladó, A., Balasa, M., Antonell, A., Bargallo, N., Premi, E., Cosseddu, M., Gazzina, S., Padovani, A., Gasparotti, R., Archetti, S., Sánchez-Valle, Raquel, Black, S., Mitchell, S., Rogaeva, E., Freedman, M., Keren, R., Tang-Wai, D., Öijerstedt, L., Andersson, C., Jelic, V., Thonberg, H., Borroni, Barbara, Arighi, A., Fenoglio, C., Scarpini, E., Fumagalli, G., Cope, T., Timberlake, C., Rittman, T., Shoesmith, C., Bartha, R., Rademakers, R., Laforce, Robert, Wilke, C., Karnarth, H-O, Bender, B., Bruffaerts, R., Vandamme, P., Vandenbulcke, M., Ferreira, C. B., Miltenberger, G., Maruta, C., Verdelho, A., Convery, Rhian S [0000-0002-9477-1812], Bocchetta, Martina [0000-0003-1814-5024], Greaves, Caroline V [0000-0002-6446-1960], Moore, Katrina M [0000-0002-4458-8390], Van Swieten, John [0000-0001-6278-6844], Borroni, Barbara [0000-0001-9340-9814], Rowe, James B [0000-0001-7216-8679], Finger, Elizabeth [0000-0003-4461-7427], Otto, Markus [0000-0002-6647-5944], Rohrer, Jonathan D [0000-0002-6155-8417], Apollo - University of Cambridge Repository, Neurology, and Repositório da Universidade de Lisboa
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Male ,diagnostic imaging [Corpus Striatum] ,Medizin ,Somatosensory system ,physiopathology [Frontotemporal Dementia] ,frontotemporal dementia ,Cohort Studies ,genetics [Progranulins] ,0302 clinical medicine ,Progranulins ,Thalamus ,C9orf72 ,Cerebellum ,diagnostic imaging [Cerebral Cortex] ,pathology [Cerebellum] ,Medicine ,pain ,genetics [Frontotemporal Dementia] ,Cerebral Cortex ,0303 health sciences ,DNA Repeat Expansion ,Pain Perception ,Middle Aged ,Magnetic Resonance Imaging ,Temporal Lobe ,Psychiatry and Mental health ,Cohort ,diagnostic imaging [Prefrontal Cortex] ,Female ,Frontotemporal dementia ,genetics [Atrophy] ,Adult ,medicine.medical_specialty ,pathology [Corpus Striatum] ,Pain ,Prefrontal Cortex ,genetics [Perceptual Disorders] ,MAPT protein, human ,tau Proteins ,diagnostic imaging [Frontotemporal Dementia] ,Temporal lobe ,Perceptual Disorders ,03 medical and health sciences ,Atrophy ,pathology [Thalamus] ,Internal medicine ,Humans ,ddc:610 ,genetics [C9orf72 Protein] ,030304 developmental biology ,diagnostic imaging [Perceptual Disorders] ,Aged ,diagnostic imaging [Thalamus] ,C9orf72 Protein ,business.industry ,pathology [Temporal Lobe] ,diagnostic imaging [Atrophy] ,physiopathology [Atrophy] ,medicine.disease ,diagnostic imaging [Cerebellum] ,pathology [Prefrontal Cortex] ,Corpus Striatum ,physiopathology [Perceptual Disorders] ,genetics [tau Proteins] ,diagnostic imaging [Temporal Lobe] ,Logistic Models ,Asymptomatic Diseases ,Mutation ,GRN protein, human ,Surgery ,Orbitofrontal cortex ,pathology [Cerebral Cortex] ,Neurology (clinical) ,C9orf72 protein, human ,business ,030217 neurology & neurosurgery - Abstract
© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. published by BMJ., Objective: Frontotemporal dementia (FTD) is typically associated with changes in behaviour, language and movement. However, recent studies have shown that patients can also develop an abnormal response to pain, either heightened or diminished. We aimed to investigate this symptom in mutation carriers within the Genetic FTD Initiative (GENFI). Methods: Abnormal responsiveness to pain was measured in 462 GENFI participants: 281 mutation carriers and 181 mutation-negative controls. Changes in responsiveness to pain were scored as absent (0), questionable or very mild (0.5), mild (1), moderate (2) or severe (3). Mutation carriers were classified into C9orf72 (104), GRN (128) and MAPT (49) groups, and into presymptomatic and symptomatic stages. An ordinal logistic regression model was used to compare groups, adjusting for age and sex. Voxel-based morphometry was performed to identify neuroanatomical correlates of abnormal pain perception. Results: Altered responsiveness to pain was present to a significantly greater extent in symptomatic C9orf72 expansion carriers than in controls: mean score 0.40 (SD 0.71) vs 0.00 (0.04), reported in 29% vs 1%. No significant differences were seen between the other symptomatic groups and controls, or any of the presymptomatic mutation carriers and controls. Neural correlates of altered pain perception in C9orf72 expansion carriers were the bilateral thalamus and striatum as well as a predominantly right-sided network of regions involving the orbitofrontal cortex, inferomedial temporal lobe and cerebellum. Conclusion: Changes in pain perception are a feature of C9orf72 expansion carriers, likely representing a disruption in somatosensory, homeostatic and semantic processing, underpinned by atrophy in a thalamo-cortico-striatal network.
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- 2020
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12. Genome-wide association study of Alzheimer's disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset
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Hong, SJ, Prokopenko, D, Dobricic, V, Kilpert, F, Bos, I, Vos, SJB, Tijms, BM, Andreasson, U, Blennow, K, Vandenberghe, R, Cleynen, I, Gabel, S, Schaeverbeke, J, Scheltens, P, Teunissen, CE, Niemantsverdriet, E, Engelborghs, S, Frisoni, G, Blin, O, Richardson, JC, Bordet, R, Molinuevo, JL, Rami, L, Kettunen, P, Wallin, A, Lleo, A, Sala, I, Popp, J, Peyratout, G, Martinez-Lage, P, Tainta, M, Dobson, RJB, Legido-Quigley, C, Sleegers, K, Van Broeckhoven, C, ten Kate, M, Barkhof, F, Zetterberg, H, Lovestone, S, Streffer, J, Wittig, M, Franke, A, Tanzi, RE, Visser, PJ, Bertram, L, and Alzheimers Dis Neuroimaging Initia
- Abstract
Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case-control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures derived from quantifications of five separate amyloid-beta (A beta) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to A beta 42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-A beta 38 and CSF-A beta 40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case-control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-A beta and -tau-related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.
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- 2020
13. Analysis of brain atrophy and local gene expression in genetic frontotemporal dementia
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Altmann, A., Cash, D. M., Bocchetta, M., Heller, C., Reynolds, R., Moore, K., Convery, R. S., Thomas, D. L., Van Swieten, J. C., Moreno, F., Sanchez-Valle, R., Borroni, B., Laforce, R., Masellis, M., Tartaglia, M. C., Graff, C., Galimberti, D., Rowe, J. B., Finger, E., Synofzik, M., Vandenberghe, R., De Mendonca, A., Tagliavini, F., Santana, I., Ducharme, S., Butler, C. R., Gerhard, A., Levin, J., Danek, A., Frisoni, G., Ghidoni, R., Sorbi, S., Otto, M., Ryten, M., Rohrer, J. D., Greaves, C., Peakman, G., Shafei, R., Todd, E., Rossor, M. N., Warren, J. D., Fox, N. C., Zetterberg, H., Guerreiro, R., Bras, J., Nicholas, J., Mead, S., Jiskoot, L., Meeter, L., Panman, J., Papma, J. M., Van Minkelen, R., Pijnenburg, Y., Barandiaran, M., Indakoetxea, B., Gabilondo, A., Tainta, M., De Arriba, M., Gorostidi, A., Zulaica, M., Villanua, J., Diaz, Z., Borrego-Ecija, S., Olives, J., Llado, A., Balasa, M., Antonell, A., Bargallo, N., Premi, E., Cosseddu, M., Gazzina, S., Padovani, A., Gasparotti, R., Archetti, S., Black, S., Mitchell, S., Rogaeva, E., Freedman, M., Keren, R., Tang-Wai, D., Oijerstedt, L., Andersson, C., Jelic, V., Thonberg, H., Arighi, A., Fenoglio, C., Scarpini, E., Fumagalli, G., Cope, T., Timberlake, C., Rittman, T., Shoesmith, C., Bartha, R., Rademakers, R., Wilke, C., Karnarth, H. -O., Bender, B., Bruffaerts, R., Van Damme, P., Vandenbulcke, M., Ferreira, C. B., Miltenberger, G., Maruta, C., Verdelho, A., Afonso, S., Taipa, R., Caroppo, P., Di Fede, G., Giaccone, G., Prioni, S., Redaelli, V., Rossi, G., Tiraboschi, P., Duro, D., Almeida, M. R., Castelo-Branco, M., Leitao, M. J., Tabuas-Pereira, M., Santiago, B., Gauthier, S., Rosa-Neto, P., Veldsman, M., Thompson, P., Langheinrich, T., Prix, C., Hoegen, T., Wlasich, E., Loosli, S., Schonecker, S., Semler, E., Anderl-Straub, S., Benussi, L., Binetti, G., Pievani, M., Lombardi, G., Nacmias, B., Ferrari, C., Bessi, V., Polito, C., Rowe, James [0000-0001-7216-8679], Apollo - University of Cambridge Repository, Medical Research Council, and Genetic FTD Initiative, GENFI
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0301 basic medicine ,Cell type ,Imaging genetics ,Clinical Neurology ,Medizin ,Biology ,Article ,DISEASE ,03 medical and health sciences ,0302 clinical medicine ,Atrophy ,atrophy ,C9orf72 ,Gene expression ,medicine ,Astrocytes ,Frontotemporal dementia ,ddc:610 ,10. No inequality ,Gene ,030304 developmental biology ,Genetics ,0303 health sciences ,Science & Technology ,TREM2 ,AcademicSubjects/SCI01870 ,Neurodegeneration ,General Engineering ,C9orf72 Gene ,Neurosciences ,astrocytes ,Genetic FTD Initiative, GENFI ,medicine.disease ,C9orf72 Protein ,030104 developmental biology ,gene expression ,imaging genetics ,Original Article ,AcademicSubjects/MED00310 ,Human medicine ,Neurosciences & Neurology ,Life Sciences & Biomedicine ,030217 neurology & neurosurgery - Abstract
Frontotemporal dementia is a heterogeneous neurodegenerative disorder characterized by neuronal loss in the frontal and temporal lobes. Despite progress in understanding which genes are associated with the aetiology of frontotemporal dementia, the biological basis of how mutations in these genes lead to cell loss in specific cortical regions remains unclear. In this work, we combined gene expression data for 16 772 genes from the Allen Institute for Brain Science atlas with brain maps of grey matter atrophy in symptomatic C9orf72, GRN and MAPT mutation carriers obtained from the Genetic Frontotemporal dementia Initiative study. No significant association was seen between C9orf72, GRN and MAPT expression and the atrophy patterns in the respective genetic groups. After adjusting for spatial autocorrelation, between 1000 and 5000 genes showed a negative or positive association with the atrophy pattern within each individual genetic group, with the most significantly associated genes being TREM2, SSBP3 and GPR158 (negative association in C9Orf72, GRN and MAPT respectively) and RELN, MXRA8 and LPA (positive association in C9Orf72, GRN and MAPT respectively). An overrepresentation analysis identified a negative association with genes involved in mitochondrial function, and a positive association with genes involved in vascular and glial cell function in each of the genetic groups. A set of 423 and 700 genes showed significant positive and negative association, respectively, with atrophy patterns in all three maps. The gene set with increased expression in spared cortical regions was enriched for neuronal and microglial genes, while the gene set with increased expression in atrophied regions was enriched for astrocyte and endothelial cell genes. Our analysis suggests that these cell types may play a more active role in the onset of neurodegeneration in frontotemporal dementia than previously assumed, and in the case of the positively associated cell marker genes, potentially through emergence of neurotoxic astrocytes and alteration in the blood–brain barrier, respectively., Altmann et al. investigated the concordance between spatial cortical gene expression in healthy subjects and atrophy patterns in genetic frontotemporal dementia. They found that elevated gene expression of endothelial cell and astrocyte-related genes in regions with atrophy, suggesting a role of these cell types in the aetiology of frontotemporal dementia., Graphical Abstract Graphical Abstract
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- 2020
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14. Age at symptom onset and death and disease duration in genetic frontotemporal dementia: an international retrospective cohort study
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Moore, K.M. Nicholas, J. Grossman, M. McMillan, C.T. Irwin, D.J. Massimo, L. Van Deerlin, V.M. Warren, J.D. Fox, N.C. Rossor, M.N. Mead, S. Bocchetta, M. Boeve, B.F. Knopman, D.S. Graff-Radford, N.R. Forsberg, L.K. Rademakers, R. Wszolek, Z.K. van Swieten, J.C. Jiskoot, L.C. Meeter, L.H. Dopper, E.G. Papma, J.M. Snowden, J.S. Saxon, J. Jones, M. Pickering-Brown, S. Le Ber, I. Camuzat, A. Brice, A. Caroppo, P. Ghidoni, R. Pievani, M. Benussi, L. Binetti, G. Dickerson, B.C. Lucente, D. Krivensky, S. Graff, C. Öijerstedt, L. Fallström, M. Thonberg, H. Ghoshal, N. Morris, J.C. Borroni, B. Benussi, A. Padovani, A. Galimberti, D. Scarpini, E. Fumagalli, G.G. Mackenzie, I.R. Hsiung, G.-Y.R. Sengdy, P. Boxer, A.L. Rosen, H. Taylor, J.B. Synofzik, M. Wilke, C. Sulzer, P. Hodges, J.R. Halliday, G. Kwok, J. Sanchez-Valle, R. Lladó, A. Borrego-Ecija, S. Santana, I. Almeida, M.R. Tábuas-Pereira, M. Moreno, F. Barandiaran, M. Indakoetxea, B. Levin, J. Danek, A. Rowe, J.B. Cope, T.E. Otto, M. Anderl-Straub, S. de Mendonça, A. Maruta, C. Masellis, M. Black, S.E. Couratier, P. Lautrette, G. Huey, E.D. Sorbi, S. Nacmias, B. Laforce, R., Jr Tremblay, M.-P.L. Vandenberghe, R. Damme, P.V. Rogalski, E.J. Weintraub, S. Gerhard, A. Onyike, C.U. Ducharme, S. Papageorgiou, S.G. Ng, A.S.L. Brodtmann, A. Finger, E. Guerreiro, R. Bras, J. Rohrer, J.D. Heller, C. Convery, R.S. Woollacott, I.O. Shafei, R.M. Graff-Radford, J. Jones, D.T. Dheel, C.M. Savica, R. Lapid, M.I. Baker, M. Fields, J.A. Gavrilova, R. Domoto-Reilly, K. Poos, J.M. Van der Ende, E.L. Panman, J.L. Donker Kaat, L. Seelaar, H. Richardson, A. Frisoni, G. Mega, A. Fostinelli, S. Chiang, H.-H. Alberici, A. Arighi, A. Fenoglio, C. Heuer, H. Miller, B. Karydas, A. Fong, J. João Leitão, M. Santiago, B. Duro, D. Ferreira, C. Gabilondo, A. De Arriba, M. Tainta, M. Zulaica, M. Ferreira, C. Semler, E. Ludolph, A. Landwehrmeyer, B. Volk, A.E. Miltenberger, G. Verdelho, A. Afonso, S. Tartaglia, M.C. Freedman, M. Rogaeva, E. Ferrari, C. Piaceri, I. Bessi, V. Lombardi, G. St-Onge, F. Doré, M.-C. Bruffaerts, R. Vandenbulcke, M. Van den Stock, J. Mesulam, M.M. Bigio, E. Koros, C. Papatriantafyllou, J. Kroupis, C. Stefanis, L. Shoesmith, C. Robertson, E. Coppola, G. Da Silva Ramos, E.M. Geschwind, D.
- Abstract
Background: Frontotemporal dementia is a heterogenous neurodegenerative disorder, with about a third of cases being genetic. Most of this genetic component is accounted for by mutations in GRN, MAPT, and C9orf72. In this study, we aimed to complement previous phenotypic studies by doing an international study of age at symptom onset, age at death, and disease duration in individuals with mutations in GRN, MAPT, and C9orf72. Methods: In this international, retrospective cohort study, we collected data on age at symptom onset, age at death, and disease duration for patients with pathogenic mutations in the GRN and MAPT genes and pathological expansions in the C9orf72 gene through the Frontotemporal Dementia Prevention Initiative and from published papers. We used mixed effects models to explore differences in age at onset, age at death, and disease duration between genetic groups and individual mutations. We also assessed correlations between the age at onset and at death of each individual and the age at onset and at death of their parents and the mean age at onset and at death of their family members. Lastly, we used mixed effects models to investigate the extent to which variability in age at onset and at death could be accounted for by family membership and the specific mutation carried. Findings: Data were available from 3403 individuals from 1492 families: 1433 with C9orf72 expansions (755 families), 1179 with GRN mutations (483 families, 130 different mutations), and 791 with MAPT mutations (254 families, 67 different mutations). Mean age at symptom onset and at death was 49·5 years (SD 10·0; onset) and 58·5 years (11·3; death) in the MAPT group, 58·2 years (9·8; onset) and 65·3 years (10·9; death) in the C9orf72 group, and 61·3 years (8·8; onset) and 68·8 years (9·7; death) in the GRN group. Mean disease duration was 6·4 years (SD 4·9) in the C9orf72 group, 7·1 years (3·9) in the GRN group, and 9·3 years (6·4) in the MAPT group. Individual age at onset and at death was significantly correlated with both parental age at onset and at death and with mean family age at onset and at death in all three groups, with a stronger correlation observed in the MAPT group (r=0·45 between individual and parental age at onset, r=0·63 between individual and mean family age at onset, r=0·58 between individual and parental age at death, and r=0·69 between individual and mean family age at death) than in either the C9orf72 group (r=0·32 individual and parental age at onset, r=0·36 individual and mean family age at onset, r=0·38 individual and parental age at death, and r=0·40 individual and mean family age at death) or the GRN group (r=0·22 individual and parental age at onset, r=0·18 individual and mean family age at onset, r=0·22 individual and parental age at death, and r=0·32 individual and mean family age at death). Modelling showed that the variability in age at onset and at death in the MAPT group was explained partly by the specific mutation (48%, 95% CI 35–62, for age at onset; 61%, 47–73, for age at death), and even more by family membership (66%, 56–75, for age at onset; 74%, 65–82, for age at death). In the GRN group, only 2% (0–10) of the variability of age at onset and 9% (3–21) of that of age of death was explained by the specific mutation, whereas 14% (9–22) of the variability of age at onset and 20% (12–30) of that of age at death was explained by family membership. In the C9orf72 group, family membership explained 17% (11–26) of the variability of age at onset and 19% (12–29) of that of age at death. Interpretation: Our study showed that age at symptom onset and at death of people with genetic frontotemporal dementia is influenced by genetic group and, particularly for MAPT mutations, by the specific mutation carried and by family membership. Although estimation of age at onset will be an important factor in future pre-symptomatic therapeutic trials for all three genetic groups, our study suggests that data from other members of the family will be particularly helpful only for individuals with MAPT mutations. Further work in identifying both genetic and environmental factors that modify phenotype in all groups will be important to improve such estimates. Funding: UK Medical Research Council, National Institute for Health Research, and Alzheimer's Society. © 2020 Elsevier Ltd
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- 2020
15. Social cognition impairment in genetic frontotemporal dementia within the GENFI cohort
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Russell, L.L. (Lucy L.), Greaves, C.V. (Caroline V.), Bocchetta, M. (Martina), Nicholas, J.M. (Jennifer), Convery, R.S. (Rhian S.), Moore, K. (Katrina), Cash, D.M. (David M.), Swieten, J.C. (John) van, Jiskoot, L.C. (Lize), Moreno, F. (Fermin), Sánchez-Valle, R. (Raquel), Borroni, B. (Barbara), Laforce, R. (Robert), Masellis, M. (Mario), Tartaglia, M.C. (Maria Carmela), Graff, C. (Caroline), Rotondo, E. (Emanuela), Galimberti, D. (Daniela), Rowe, J.B. (James), Finger, E. (Elizabeth), Synofzik, M. (Matthis), Vandenberghe, R. (Rik), De Mendonça, A. (Alexandre), Tagliavini, F. (Fabrizio), Santana, I. (Isabel), Ducharme, S. (Simon), Butler, C. (Chris), Gerhard, A. (Alex), Levin, J. (Johannes), Danek, A. (Adrian), Otto, M. (Markus), Warren, J.D. (Jason), Rohrer, J.D. (Jonathan), Rossor, M. (Martin), Fox, N.C. (Nick), Woollacott, I.O.C. (Ione O.C.), Shafei, R. (Rachelle), Heller, C. (Carolin), Guerreiro, R. (Rita), Bras, J. (Jose), Thomas, D.L. (David L), Mead, S. (Simon), Meeter, L.H.H. (Lieke), Panman, J.L. (Jessica), Papma, J.M. (Janne), Poos, J.M. (Jackie), Thornton, A.S. (Andrew), Pijnenburg, Y. (Yolanda), Barandiaran, M. (Myriam), Indakoetxea, B. (Begoña), Gabilondo, A. (Alazne), Tainta, M. (Mikel), de Arriba, M. (Maria), Gorostidi, A. (Ana), Zulaica, M. (Miren), Villanua, J. (Jorge), Diaz, Z. (Zigor), Borrego-Ecija, S. (Sergi), Olives, J. (Jaume), Lladó, A. (Albert), Balasa, M. (Mircea), Antonell, A. (Anna), Bargallo, N. (Nuria), Premi, E. (Enrico), Cosseddu MPsych, M. (Maura), Gazzina, S. (Stefano), Padovani, A. (Alessandro), Gasparotti, R. (Roberto), Archetti, S. (Silvana), Black, S.E. (Sandra), Mitchell, S. (Sara), Rogaeva, E. (Ekaterina), Freedman, M. (Morris), Keren, R. (Ron), Tang-Wai, D. (Daid), Öijerstedt, L. (Linn), Andersson, C. (Christin), Jelic, S. (Svetislav Svetislav), Thonberg, H. (Håkan), Arighi, A. (Andrea), Fenoglio, C. (Chiara), Scarpini, E. (Elio), Fumagalli, G. (Giorgio), Cope, T. (Thomas), Timberlake, C. (Carolyn), Rittman, T. (Timothy), Shoesmith, C. (Christen), Bartha, R. (Robart), Rademakers, S. (Suzanne), Wilke, C. (Carlo), Karnarth, H.-O. (Hans-Otto), Bender, B. (Benjamin), Bruffaerts, R. (Rose), Vandamme, P. (Philip), Vandenbulcke, M. (Mathieu), Ferreira, C.B. (Catarina B.), Miltenberger, G. (Gabriel), Maruta MPsych, C. (Carolina), Verdelho, A. (Ana), Afonso, S. (Sónia), Taipa, R. (Ricardo), Caroppo, P. (Paola), Di Fede, G. (Giuseppe), Giaccone, G. (Giuseppe), Muscio, C. (Cristina), Prioni, S. (Sara), Redaelli, V. (Veronica), Rossi, G. (Giacomina), Tiraboschi, P. (Pietro), Duro NPsych, D. (Diana), Almeida, M.R. (Maria R.), Castelo-Branco, M. (Miguel), Leitão, M.J. (Maria J.), Tabuas-Pereira, M. (Miguel), Santiago, B. (Beatriz), Gauthier, S. (Serge), Rosa-Neto, P. (Pedro), Veldsman, M. (Michele), Thompson, P.M. (Paul), Langheinrich, T. (Tobias), Prix, C. (Catharina), Hoegen, T. (Tobias), Wlasich, E. (Elisabeth), Loosli, S. (Sandra), Schonecker, S. (Sonja), Semler, E. (Elisa), Anderl-Straub, S. (Sarah), Russell, L.L. (Lucy L.), Greaves, C.V. (Caroline V.), Bocchetta, M. (Martina), Nicholas, J.M. (Jennifer), Convery, R.S. (Rhian S.), Moore, K. (Katrina), Cash, D.M. (David M.), Swieten, J.C. (John) van, Jiskoot, L.C. (Lize), Moreno, F. (Fermin), Sánchez-Valle, R. (Raquel), Borroni, B. (Barbara), Laforce, R. (Robert), Masellis, M. (Mario), Tartaglia, M.C. (Maria Carmela), Graff, C. (Caroline), Rotondo, E. (Emanuela), Galimberti, D. (Daniela), Rowe, J.B. (James), Finger, E. (Elizabeth), Synofzik, M. (Matthis), Vandenberghe, R. (Rik), De Mendonça, A. (Alexandre), Tagliavini, F. (Fabrizio), Santana, I. (Isabel), Ducharme, S. (Simon), Butler, C. (Chris), Gerhard, A. (Alex), Levin, J. (Johannes), Danek, A. (Adrian), Otto, M. (Markus), Warren, J.D. (Jason), Rohrer, J.D. (Jonathan), Rossor, M. (Martin), Fox, N.C. (Nick), Woollacott, I.O.C. (Ione O.C.), Shafei, R. (Rachelle), Heller, C. (Carolin), Guerreiro, R. (Rita), Bras, J. (Jose), Thomas, D.L. (David L), Mead, S. (Simon), Meeter, L.H.H. (Lieke), Panman, J.L. (Jessica), Papma, J.M. (Janne), Poos, J.M. (Jackie), Thornton, A.S. (Andrew), Pijnenburg, Y. (Yolanda), Barandiaran, M. (Myriam), Indakoetxea, B. (Begoña), Gabilondo, A. (Alazne), Tainta, M. (Mikel), de Arriba, M. (Maria), Gorostidi, A. (Ana), Zulaica, M. (Miren), Villanua, J. (Jorge), Diaz, Z. (Zigor), Borrego-Ecija, S. (Sergi), Olives, J. (Jaume), Lladó, A. (Albert), Balasa, M. (Mircea), Antonell, A. (Anna), Bargallo, N. (Nuria), Premi, E. (Enrico), Cosseddu MPsych, M. (Maura), Gazzina, S. (Stefano), Padovani, A. (Alessandro), Gasparotti, R. (Roberto), Archetti, S. (Silvana), Black, S.E. (Sandra), Mitchell, S. (Sara), Rogaeva, E. (Ekaterina), Freedman, M. (Morris), Keren, R. (Ron), Tang-Wai, D. (Daid), Öijerstedt, L. (Linn), Andersson, C. (Christin), Jelic, S. (Svetislav Svetislav), Thonberg, H. (Håkan), Arighi, A. (Andrea), Fenoglio, C. (Chiara), Scarpini, E. (Elio), Fumagalli, G. (Giorgio), Cope, T. (Thomas), Timberlake, C. (Carolyn), Rittman, T. (Timothy), Shoesmith, C. (Christen), Bartha, R. (Robart), Rademakers, S. (Suzanne), Wilke, C. (Carlo), Karnarth, H.-O. (Hans-Otto), Bender, B. (Benjamin), Bruffaerts, R. (Rose), Vandamme, P. (Philip), Vandenbulcke, M. (Mathieu), Ferreira, C.B. (Catarina B.), Miltenberger, G. (Gabriel), Maruta MPsych, C. (Carolina), Verdelho, A. (Ana), Afonso, S. (Sónia), Taipa, R. (Ricardo), Caroppo, P. (Paola), Di Fede, G. (Giuseppe), Giaccone, G. (Giuseppe), Muscio, C. (Cristina), Prioni, S. (Sara), Redaelli, V. (Veronica), Rossi, G. (Giacomina), Tiraboschi, P. (Pietro), Duro NPsych, D. (Diana), Almeida, M.R. (Maria R.), Castelo-Branco, M. (Miguel), Leitão, M.J. (Maria J.), Tabuas-Pereira, M. (Miguel), Santiago, B. (Beatriz), Gauthier, S. (Serge), Rosa-Neto, P. (Pedro), Veldsman, M. (Michele), Thompson, P.M. (Paul), Langheinrich, T. (Tobias), Prix, C. (Catharina), Hoegen, T. (Tobias), Wlasich, E. (Elisabeth), Loosli, S. (Sandra), Schonecker, S. (Sonja), Semler, E. (Elisa), and Anderl-Straub, S. (Sarah)
- Abstract
A key symptom of frontotemporal dementia (FTD) is difficulty interacting socially with others. Social cognition problems in FTD include impaired emotion processing and theory of mind difficulties, and whilst these have been studied extensively in sporadic FTD, few studies have investigated them in familial FTD. Facial Emotion Recognition (FER) and Faux Pas (FP) recognition tests were used to study social cognition within the Genetic Frontotemporal Dementia Initiative (GENFI), a large familial FTD cohort of C9orf72, GRN, and MAPT mutation carriers. 627 participants undertook at least one of the tasks, and were separated into mutation-negative healthy controls, presymptomatic mutation carriers (split into early and late groups) and symptomatic mutation carriers. Groups were compared using a linear regression model with bootstrapping, adjusting for age, sex, education, and for the FP recognition test, language. Neural correlates of social cognition deficits were explored using a voxel-based morphometry (VBM) study. All three of the symptomatic genetic groups were impaired on both tasks with no significant difference between them. However, prior to onset, only the late presymptomatic C9orf72 mutation carriers on the FER test were impaired compared to the control group, with a subanalysis showing differences particularly in fear and sadness. The VBM analysis revealed that impaired social cognition was mainly associated with a left hemisphere predominant network of regions involving particularly the striatum, orbitofrontal cortex and insula, and to a lesser extent the inferomedial temporal lobe and other areas of the frontal lobe. In conclusion, theory of mind and emotion processing abilities are impaired in familial FTD, with early changes occurring prior to symptom onset in C9orf72 presymptomatic mutation carriers. Future work should investigate how performance changes over time, in order to gain a clearer insight into social cognitive impairment over the course of the
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- 2020
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16. Age at symptom onset and death and disease duration in genetic frontotemporal dementia: an international retrospective cohort study
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Moore, KM, Nicholas, J, Grossman, M, McMillan, CT, Irwin, DJ, Massimo, L, Van Deerlin, VM, Warren, JD, Fox, NC, Rossor, MN, Mead, S, Bocchetta, M, Boeve, BF, Knopman, DS, Graff-Radford, NR, Forsberg, LK, Rademakers, R, Wszolek, ZK, van Swieten, JC, Jiskoot, LC, Meeter, LH, Dopper, EGP, Papma, JM, Snowden, JS, Saxon, J, Jones, M, Pickering-Brown, S, Le Ber, I, Camuzat, A, Brice, A, Caroppo, P, Ghidoni, R, Pievani, M, Benussi, L, Binetti, G, Dickerson, BC, Lucente, D, Krivensky, S, Graff, C, Oijerstedt, L, Fallstrom, M, Thonberg, H, Ghoshal, N, Morris, JC, Borroni, B, Benussi, A, Padovani, A, Galimberti, D, Scarpini, E, Fumagalli, GG, Mackenzie, IR, Hsiung, G-YR, Sengdy, P, Boxer, AL, Rosen, H, Taylor, JB, Synofzik, M, Wilke, C, Sulzer, P, Hodges, JR, Halliday, G, Kwok, J, Sanchez-Valle, R, Llado, A, Borrego-Ecija, S, Santana, I, Almeida, MR, Tabuas-Pereira, M, Moreno, F, Barandiaran, M, Indakoetxea, B, Levin, J, Danek, A, Rowe, JB, Cope, TE, Otto, M, Anderl-Straub, S, de Mendonca, A, Maruta, C, Masellis, M, Black, SE, Couratier, P, Lautrette, G, Huey, ED, Sorbi, S, Nacmias, B, Laforce, R, Tremblay, M-PL, Vandenberghe, R, Van Damme, P, Rogalski, EJ, Weintraub, S, Gerhard, A, Onyike, CU, Ducharme, S, Papageorgiou, SG, Ng, ASL, Brodtmann, A, Finger, E, Guerreiro, R, Bras, J, Rohrer, JD, Heller, C, Convery, R, Woollacott, IOC, Shafei, R, Graff-Radford, J, Jones, DT, Dheel, CM, Savica, R, Lapid, MI, Baker, M, Fields, JA, Gavrilova, R, Domoto-Reilly, K, Poos, JM, van der Ende, EL, Panman, JL, Kaat, LD, Seelaar, H, Richardson, A, Frisoni, G, Mega, A, Fostinelli, S, Chiang, H-H, Alberici, A, Arighi, A, Fenoglio, C, Heuer, H, Miller, B, Karydas, A, Fong, J, Leitao, MJ, Santiago, B, Duro, D, Ferreira, C, Gabilondo, A, de Arriba, M, Tainta, M, Zulaica, M, Ferreira, CB, Semler, E, Ludolph, A, Landwehrmeyer, B, Volk, AE, Miltenberger, G, Verdelho, A, Afonso, S, Tartaglia, MC, Freedman, M, Rogaeva, E, Ferrari, C, Piaceri, I, Bessi, V, Lombardi, G, St-Onge, F, Dore, M-C, Bruffaerts, R, Vandenbulcke, M, Van den Stock, J, Mesulam, MM, Bigio, E, Koros, C, Papatriantafyllou, J, Kroupis, C, Stefanis, L, Shoesmith, C, Roberson, E, Coppola, G, Ramos, EMDS, Geschwind, D, Moore, KM, Nicholas, J, Grossman, M, McMillan, CT, Irwin, DJ, Massimo, L, Van Deerlin, VM, Warren, JD, Fox, NC, Rossor, MN, Mead, S, Bocchetta, M, Boeve, BF, Knopman, DS, Graff-Radford, NR, Forsberg, LK, Rademakers, R, Wszolek, ZK, van Swieten, JC, Jiskoot, LC, Meeter, LH, Dopper, EGP, Papma, JM, Snowden, JS, Saxon, J, Jones, M, Pickering-Brown, S, Le Ber, I, Camuzat, A, Brice, A, Caroppo, P, Ghidoni, R, Pievani, M, Benussi, L, Binetti, G, Dickerson, BC, Lucente, D, Krivensky, S, Graff, C, Oijerstedt, L, Fallstrom, M, Thonberg, H, Ghoshal, N, Morris, JC, Borroni, B, Benussi, A, Padovani, A, Galimberti, D, Scarpini, E, Fumagalli, GG, Mackenzie, IR, Hsiung, G-YR, Sengdy, P, Boxer, AL, Rosen, H, Taylor, JB, Synofzik, M, Wilke, C, Sulzer, P, Hodges, JR, Halliday, G, Kwok, J, Sanchez-Valle, R, Llado, A, Borrego-Ecija, S, Santana, I, Almeida, MR, Tabuas-Pereira, M, Moreno, F, Barandiaran, M, Indakoetxea, B, Levin, J, Danek, A, Rowe, JB, Cope, TE, Otto, M, Anderl-Straub, S, de Mendonca, A, Maruta, C, Masellis, M, Black, SE, Couratier, P, Lautrette, G, Huey, ED, Sorbi, S, Nacmias, B, Laforce, R, Tremblay, M-PL, Vandenberghe, R, Van Damme, P, Rogalski, EJ, Weintraub, S, Gerhard, A, Onyike, CU, Ducharme, S, Papageorgiou, SG, Ng, ASL, Brodtmann, A, Finger, E, Guerreiro, R, Bras, J, Rohrer, JD, Heller, C, Convery, R, Woollacott, IOC, Shafei, R, Graff-Radford, J, Jones, DT, Dheel, CM, Savica, R, Lapid, MI, Baker, M, Fields, JA, Gavrilova, R, Domoto-Reilly, K, Poos, JM, van der Ende, EL, Panman, JL, Kaat, LD, Seelaar, H, Richardson, A, Frisoni, G, Mega, A, Fostinelli, S, Chiang, H-H, Alberici, A, Arighi, A, Fenoglio, C, Heuer, H, Miller, B, Karydas, A, Fong, J, Leitao, MJ, Santiago, B, Duro, D, Ferreira, C, Gabilondo, A, de Arriba, M, Tainta, M, Zulaica, M, Ferreira, CB, Semler, E, Ludolph, A, Landwehrmeyer, B, Volk, AE, Miltenberger, G, Verdelho, A, Afonso, S, Tartaglia, MC, Freedman, M, Rogaeva, E, Ferrari, C, Piaceri, I, Bessi, V, Lombardi, G, St-Onge, F, Dore, M-C, Bruffaerts, R, Vandenbulcke, M, Van den Stock, J, Mesulam, MM, Bigio, E, Koros, C, Papatriantafyllou, J, Kroupis, C, Stefanis, L, Shoesmith, C, Roberson, E, Coppola, G, Ramos, EMDS, and Geschwind, D
- Abstract
BACKGROUND: Frontotemporal dementia is a heterogenous neurodegenerative disorder, with about a third of cases being genetic. Most of this genetic component is accounted for by mutations in GRN, MAPT, and C9orf72. In this study, we aimed to complement previous phenotypic studies by doing an international study of age at symptom onset, age at death, and disease duration in individuals with mutations in GRN, MAPT, and C9orf72. METHODS: In this international, retrospective cohort study, we collected data on age at symptom onset, age at death, and disease duration for patients with pathogenic mutations in the GRN and MAPT genes and pathological expansions in the C9orf72 gene through the Frontotemporal Dementia Prevention Initiative and from published papers. We used mixed effects models to explore differences in age at onset, age at death, and disease duration between genetic groups and individual mutations. We also assessed correlations between the age at onset and at death of each individual and the age at onset and at death of their parents and the mean age at onset and at death of their family members. Lastly, we used mixed effects models to investigate the extent to which variability in age at onset and at death could be accounted for by family membership and the specific mutation carried. FINDINGS: Data were available from 3403 individuals from 1492 families: 1433 with C9orf72 expansions (755 families), 1179 with GRN mutations (483 families, 130 different mutations), and 791 with MAPT mutations (254 families, 67 different mutations). Mean age at symptom onset and at death was 49·5 years (SD 10·0; onset) and 58·5 years (11·3; death) in the MAPT group, 58·2 years (9·8; onset) and 65·3 years (10·9; death) in the C9orf72 group, and 61·3 years (8·8; onset) and 68·8 years (9·7; death) in the GRN group. Mean disease duration was 6·4 years (SD 4·9) in the C9orf72 group, 7·1 years (3·9) in the GRN group, and 9·3 years (6·4) in the MAPT group. Individual age at onset and at
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- 2020
17. Social cognition impairment in genetic frontotemporal dementia within the GENFI cohort
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Russell, LL, Greaves, CV, Bocchetta, M, Nicholas, J, Convery, RS, Moore, K, Cash, DM, van Swieten, J.C., Jiskoot, Lize, Moreno, F, Sanchez-Valle, R, Borroni, B, Laforce, R, Jr, Masellis, M, Tartaglia, MC, Graff, C, Rotondo, E, Galimberti, D, Rowe, JB, Finger, E, Synofzik, M, Vandenberghe, R, Mendonça, A, Tagliavini, F, Santana, I, Ducharme, S, Butler, C, Gerhard, A, Levin, J, Danek, A, Otto, M, Warren, JD, Rohrer, JD, Rossor, MN, Fox, NC, Woollacott, IOC, Shafei, R, Heller, C, Guerreiro, R, Bras, J, Thomas, DL, Mead, S, Meeter, Lieke, Panman, J, Papma, J, Poos, J, van Minkelen, Rick, Al Pijnenburg, Y, Barandiaran, M, Indakoetxea, B, Gabilondo, A, Tainta, M, de Arriba, M, Gorostidi, A, Zulaica, M, Villanua, J, Diaz, Z, Borrego-Ecija, S, Olives, J, Lladó, A, Balasa, M, Antonell, A, Bargallo, N, Premi, E, Cosseddu Mpsych, M, Gazzina, S, Padovani, A, Gasparotti, R, Archetti, S, Black, S, Mitchell, S, Rogaeva, E, Freedman, M, Keren, R, Tang-Wai, D, Öijerstedt, L, Andersson, C, Jelic, V, Thonberg, H, Arighi, A, Fenoglio, C, Scarpini, E, Fumagalli, G, Cope, T, Timberlake, C, Rittman, T, Shoesmith, C, Bartha, R, Rademakers, R, Wilke, C, Karnarth, HO, Bender, B, Bruffaerts, R, Vandamme, P, Vandenbulcke, M, Ferreira, CB, Miltenberger, G, Maruta Mpsych, C, Verdelho, A, Afonso, S, Taipa, R, Caroppo, P, Di Fede, G, Giaccone, G, Muscio, C, Prioni, S, Redaelli, V, Rossi, G, Tiraboschi, P, Duro Npsych, D, Almeida, M R, Castelo-Branco, M, Leitão, MJ, Tabuas-Pereira, M, Santiago, B, Gauthier, S, Rosa-Neto, P, Veldsman, M, Thompson, P, Langheinrich, T, Prix, C, Hoegen, T, Wlasich, E, Loosli, S, Schonecker, S, Semler, E, Anderl-Straub, S, Russell, LL, Greaves, CV, Bocchetta, M, Nicholas, J, Convery, RS, Moore, K, Cash, DM, van Swieten, J.C., Jiskoot, Lize, Moreno, F, Sanchez-Valle, R, Borroni, B, Laforce, R, Jr, Masellis, M, Tartaglia, MC, Graff, C, Rotondo, E, Galimberti, D, Rowe, JB, Finger, E, Synofzik, M, Vandenberghe, R, Mendonça, A, Tagliavini, F, Santana, I, Ducharme, S, Butler, C, Gerhard, A, Levin, J, Danek, A, Otto, M, Warren, JD, Rohrer, JD, Rossor, MN, Fox, NC, Woollacott, IOC, Shafei, R, Heller, C, Guerreiro, R, Bras, J, Thomas, DL, Mead, S, Meeter, Lieke, Panman, J, Papma, J, Poos, J, van Minkelen, Rick, Al Pijnenburg, Y, Barandiaran, M, Indakoetxea, B, Gabilondo, A, Tainta, M, de Arriba, M, Gorostidi, A, Zulaica, M, Villanua, J, Diaz, Z, Borrego-Ecija, S, Olives, J, Lladó, A, Balasa, M, Antonell, A, Bargallo, N, Premi, E, Cosseddu Mpsych, M, Gazzina, S, Padovani, A, Gasparotti, R, Archetti, S, Black, S, Mitchell, S, Rogaeva, E, Freedman, M, Keren, R, Tang-Wai, D, Öijerstedt, L, Andersson, C, Jelic, V, Thonberg, H, Arighi, A, Fenoglio, C, Scarpini, E, Fumagalli, G, Cope, T, Timberlake, C, Rittman, T, Shoesmith, C, Bartha, R, Rademakers, R, Wilke, C, Karnarth, HO, Bender, B, Bruffaerts, R, Vandamme, P, Vandenbulcke, M, Ferreira, CB, Miltenberger, G, Maruta Mpsych, C, Verdelho, A, Afonso, S, Taipa, R, Caroppo, P, Di Fede, G, Giaccone, G, Muscio, C, Prioni, S, Redaelli, V, Rossi, G, Tiraboschi, P, Duro Npsych, D, Almeida, M R, Castelo-Branco, M, Leitão, MJ, Tabuas-Pereira, M, Santiago, B, Gauthier, S, Rosa-Neto, P, Veldsman, M, Thompson, P, Langheinrich, T, Prix, C, Hoegen, T, Wlasich, E, Loosli, S, Schonecker, S, Semler, E, and Anderl-Straub, S
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- 2020
18. Reversible delayed post-hypoxic leukoencephalopathy
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Tainta, M., de la Riva, P., Urtasun, M.Á., and Martí-Massó, J.F.
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- 2018
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19. Leucoencefalopatía posthipóxica diferida reversible
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Tainta, M., de la Riva, P., Urtasun, M.Á., and Martí-Massó, J.F.
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- 2018
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20. Leucoencefalopatía posthipóxica diferida reversible
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Tainta, M., de la Riva, P., Urtasun, M.Á., and Martí-Massó, J.F.
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- 2024
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21. P5-25 Coupling between beta and high-frequency activity in the human subthalamic nucleus may be a pathophysiological mechanism in Parkinson disease
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Alegre, M., primary, Lopez-Azcarate, J., additional, Tainta, M., additional, Rodriguez-Oroz, M.C., additional, Valencia, M., additional, Gonzalez, R., additional, Guridi, J., additional, Iriarte, J., additional, Obeso, J.A., additional, and Artieda, J., additional
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- 2010
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22. Coupling between Beta and High-Frequency Activity in the Human Subthalamic Nucleus May Be a Pathophysiological Mechanism in Parkinson's Disease
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Lopez-Azcarate, J., primary, Tainta, M., additional, Rodriguez-Oroz, M. C., additional, Valencia, M., additional, Gonzalez, R., additional, Guridi, J., additional, Iriarte, J., additional, Obeso, J. A., additional, Artieda, J., additional, and Alegre, M., additional
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- 2010
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23. [Rhomboencephalitis and endocarditis caused by Listeria monocytogenes: an unreported association]
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Tainta M, Patricia de la Riva, Gonzalez F, Jf, Marti-Masso, and Ma, Goenaga
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Rhombencephalon ,Endocarditis ,Humans ,Listeria monocytogenes
24. Blood DNA methylomic signatures associated with CSF biomarkers of Alzheimer's disease in the EMIF-AD study.
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Smith RG, Pishva E, Kouhsar M, Imm J, Dobricic V, Johannsen P, Wittig M, Franke A, Vandenberghe R, Schaeverbeke J, Freund-Levi Y, Frölich L, Scheltens P, Teunissen CE, Frisoni G, Blin O, Richardson JC, Bordet R, Engelborghs S, de Roeck E, Martinez-Lage P, Altuna M, Tainta M, Lleó A, Sala I, Popp J, Peyratout G, Winchester L, Nevado-Holgado A, Verhey F, Tsolaki M, Andreasson U, Blennow K, Zetterberg H, Streffer J, Vos SJB, Lovestone S, Visser PJ, Bertram L, and Lunnon K
- Subjects
- Humans, Female, Male, Aged, Middle Aged, Genome-Wide Association Study, Alzheimer Disease genetics, Alzheimer Disease blood, Alzheimer Disease cerebrospinal fluid, DNA Methylation genetics, Chitinase-3-Like Protein 1 cerebrospinal fluid, Chitinase-3-Like Protein 1 genetics, Chitinase-3-Like Protein 1 blood, Biomarkers cerebrospinal fluid, Biomarkers blood, Neurofilament Proteins cerebrospinal fluid, Neurofilament Proteins blood
- 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., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)
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- 2024
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25. Blood-based multivariate methylation risk score for cognitive impairment and dementia.
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Koetsier J, Cavill R, Reijnders R, Harvey J, Homann J, Kouhsar M, Deckers K, Köhler S, Eijssen LMT, van den Hove DLA, Demuth I, Düzel S, Smith RG, Smith AR, Burrage J, Walker EM, Shireby G, Hannon E, Dempster E, Frayling T, Mill J, Dobricic V, Johannsen P, Wittig M, Franke A, Vandenberghe R, Schaeverbeke J, Freund-Levi Y, Frölich L, Scheltens P, Teunissen CE, Frisoni G, Blin O, Richardson JC, Bordet R, Engelborghs S, de Roeck E, Martinez-Lage P, Tainta M, Lleó A, Sala I, Popp J, Peyratout G, Verhey F, Tsolaki M, Andreasson U, Blennow K, Zetterberg H, Streffer J, Vos SJB, Lovestone S, Visser PJ, Lill CM, Bertram L, Lunnon K, and Pishva E
- Subjects
- Humans, Male, Female, Aged, Risk Factors, Machine Learning, Cross-Sectional Studies, Alzheimer Disease genetics, Alzheimer Disease blood, Alzheimer Disease diagnosis, Prospective Studies, Risk Assessment, Aged, 80 and over, DNA Methylation genetics, Cognitive Dysfunction genetics, Cognitive Dysfunction blood, Cognitive Dysfunction diagnosis, Dementia genetics, Dementia blood, Dementia diagnosis
- Abstract
Introduction: The established link between DNA methylation and pathophysiology of dementia, along with its potential role as a molecular mediator of lifestyle and environmental influences, positions blood-derived DNA methylation as a promising tool for early dementia risk detection., Methods: In conjunction with an extensive array of machine learning techniques, we employed whole blood genome-wide DNA methylation data as a surrogate for 14 modifiable and non-modifiable factors in the assessment of dementia risk in independent dementia cohorts., Results: We established a multivariate methylation risk score (MMRS) for identifying mild cognitive impairment cross-sectionally, independent of age and sex (P = 2.0 × 10
-3 ). This score significantly predicted the prospective development of cognitive impairments in independent studies of Alzheimer's disease (hazard ratio for Rey's Auditory Verbal Learning Test (RAVLT)-Learning = 2.47) and Parkinson's disease (hazard ratio for MCI/dementia- Published
- 2024
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26. CSF proteomic profiles of neurodegeneration biomarkers in Alzheimer's disease.
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Delvenne A, Gobom J, Schindler SE, Kate MT, Reus LM, Dobricic V, Tijms BM, Benzinger TLS, Cruchaga C, Teunissen CE, Ramakers I, Martinez-Lage P, Tainta M, Vandenberghe R, Schaeverbeke J, Engelborghs S, Roeck E, Popp J, Peyratout G, Tsolaki M, Freund-Levi Y, Lovestone S, Streffer J, Barkhof F, Bertram L, Blennow K, Zetterberg H, Visser PJ, and Vos SJB
- Subjects
- Humans, Female, Male, Aged, Middle Aged, Peptide Fragments cerebrospinal fluid, Alzheimer Disease cerebrospinal fluid, Alzheimer Disease pathology, Biomarkers cerebrospinal fluid, Neurogranin cerebrospinal fluid, Neurofilament Proteins cerebrospinal fluid, tau Proteins cerebrospinal fluid, Proteomics, Hippocampus pathology, Amyloid beta-Peptides cerebrospinal fluid
- Abstract
Introduction: We aimed to unravel the underlying pathophysiology of the neurodegeneration (N) markers neurogranin (Ng), neurofilament light (NfL), and hippocampal volume (HCV), in Alzheimer's disease (AD) using cerebrospinal fluid (CSF) proteomics., Methods: Individuals without dementia were classified as A+ (CSF amyloid beta [Aβ]42), T+ (CSF phosphorylated tau181), and N+ or N- based on Ng, NfL, or HCV separately. CSF proteomics were generated and compared between groups using analysis of covariance., Results: Only a few individuals were A+T+Ng-. A+T+Ng+ and A+T+NfL+ showed different proteomic profiles compared to A+T+Ng- and A+T+NfL-, respectively. Both Ng+ and NfL+ were associated with neuroplasticity, though in opposite directions. Compared to A+T+HCV-, A+T+HCV+ showed few proteomic changes, associated with oxidative stress., Discussion: Different N markers are associated with distinct neurodegenerative processes and should not be equated. N markers may differentially complement disease staging beyond amyloid and tau. Our findings suggest that Ng may not be an optimal N marker, given its low incongruency with tau pathophysiology., Highlights: In Alzheimer's disease, neurogranin (Ng)+, neurofilament light (NfL)+, and hippocampal volume (HCV)+ showed differential protein expression in cerebrospinal fluid. Ng+ and NfL+ were associated with neuroplasticity, although in opposite directions. HCV+ showed few proteomic changes, related to oxidative stress. Neurodegeneration (N) markers may differentially refine disease staging beyond amyloid and tau. Ng might not be an optimal N marker, as it relates more closely to tau., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)
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- 2024
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27. Synaptic protein CSF levels relate to memory scores in individuals without dementia.
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Wesenhagen KEJ, de Leeuw DM, Tomassen J, Gobom J, Bos I, Vos SJB, Martinez-Lage P, Tainta M, Popp J, Peyratout G, Tsolaki M, Vandenberghe R, Freund-Levi Y, Verhey F, Lovestone S, Streffer J, Dobricic V, Blennow K, Scheltens P, Smit AB, Bertram L, Teunissen CE, Zetterberg H, and Tijms BM
- Abstract
Introduction: 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 EMIF-AD MBD and 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 groups., Discussion: 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., Competing Interests: Declarations Competing Interests KB has served as a consultant, at advisory boards, or at data monitoring committees for Abcam, Axon, BioArctic, Biogen, JOMDD/Shimadzu. Julius Clinical, Lilly, MagQu, Novartis, Pharmatrophix, Prothena, Roche Diagnostics, and Siemens Healthineers, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program, outside the work presented in this paper. HZ has served at scientific advisory boards and/or as a consultant for Abbvie, Alector, Annexon, Artery Therapeutics, AZTherapies, CogRx, Denali, Eisai, Nervgen, Pinteon Therapeutics, Red Abbey Labs, Passage Bio, Roche, Samumed, Siemens Healthineers, Triplet Therapeutics, and Wave, has given lectures in symposia sponsored by Cellectricon, Fujirebio, Alzecure, Biogen, and Roche, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program. PS has acquired grants for the institution from GE Healthcare and Piramal and received consultancy/speaker fees paid to the institution from Novartis, Probiodrug, Biogen, Roche, and EIP Pharma, LLC in the past 2 years. CT received grants from the European Commission, the Dutch Research Council (ZonMW), Association of Frontotemporal Dementia/Alzheimer’s Drug Discovery Foundation, The Weston Brain Institute, Alzheimer Netherlands. Prof. dr. Teunissen has functioned in advisory boards of Roche, received non-financial support in the form of research consumables from ADxNeurosciences and Euroimmun, performed contract research or received grants from Probiodrug, Biogen, Esai, Toyama, Janssen Prevention Center, Boehringer, AxonNeurosciences, EIP farma, PeopleBio, Roche. The other authors report no conflict of interest.
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- 2024
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28. Involvement of the choroid plexus in Alzheimer's disease pathophysiology: findings from mouse and human proteomic studies.
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Delvenne A, Vandendriessche C, Gobom J, Burgelman M, Dujardin P, De Nolf C, Tijms BM, Teunissen CE, Schindler SE, Verhey F, Ramakers I, Martinez-Lage P, Tainta M, Vandenberghe R, Schaeverbeke J, Engelborghs S, De Roeck E, Popp J, Peyratout G, Tsolaki M, Freund-Levi Y, Lovestone S, Streffer J, Bertram L, Blennow K, Zetterberg H, Visser PJ, Vandenbroucke RE, and Vos SJB
- Subjects
- Animals, Humans, Mice, Amyloid beta-Protein Precursor metabolism, Amyloid beta-Protein Precursor genetics, Proteome metabolism, Male, Female, Mice, Inbred C57BL, Choroid Plexus metabolism, Alzheimer Disease metabolism, Alzheimer Disease cerebrospinal fluid, Proteomics, Mice, Transgenic, Disease Models, Animal
- 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 relation between ChP functioning and core AD pathogenesis using a unique proteomic approach in mice and humans., Methods: We used an APP knock-in mouse model, APP
NL-G-F , exhibiting 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 the age of 7 weeks (n = 5) and 40 weeks (n = 5). Results were compared with previously published human AD CSF proteomic data (n = 496) to identify key proteins and pathways associated with ChP changes in AD., Results: ChP tissue proteome was dysregulated in APPNL-G-F mice relative to wild-type mice at both 7 and 40 weeks. At both ages, ChP tissue proteomic changes were associated with epithelial cells, mitochondria, protein modification, extracellular matrix and lipids. Nonetheless, some ChP tissue proteomic changes were different across the disease trajectory; 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. CSF proteomics in both mice and humans showed similar ChP-related dysregulated pathways., Conclusions: Together, our findings support the hypothesis of ChP dysfunction in AD. These ChP changes were related to amyloid pathology. Therefore, the ChP could become a novel promising therapeutic target for AD., (© 2024. The Author(s).)- Published
- 2024
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29. Unlocking Preclinical Alzheimer's: A Multi-Year Label-Free In Vitro Raman Spectroscopy Study Empowered by Chemometrics.
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Lopez E, Etxebarria-Elezgarai J, García-Sebastián M, Altuna M, Ecay-Torres M, Estanga A, Tainta M, López C, Martínez-Lage P, Amigo JM, and Seifert A
- Subjects
- Humans, Machine Learning, Male, Female, Biomarkers cerebrospinal fluid, Aged, Early Diagnosis, Spectrum Analysis, Raman methods, Alzheimer Disease diagnosis, Alzheimer Disease cerebrospinal fluid
- Abstract
Alzheimer's disease is a progressive neurodegenerative disorder, the early detection of which is crucial for timely intervention and enrollment in clinical trials. However, the preclinical diagnosis of Alzheimer's encounters difficulties with gold-standard methods. The current definitive diagnosis of Alzheimer's still relies on expensive instrumentation and post-mortem histological examinations. Here, we explore label-free Raman spectroscopy with machine learning as an alternative to preclinical Alzheimer's diagnosis. A special feature of this study is the inclusion of patient samples from different cohorts, sampled and measured in different years. To develop reliable classification models, partial least squares discriminant analysis in combination with variable selection methods identified discriminative molecules, including nucleic acids, amino acids, proteins, and carbohydrates such as taurine/hypotaurine and guanine, when applied to Raman spectra taken from dried samples of cerebrospinal fluid. The robustness of the model is remarkable, as the discriminative molecules could be identified in different cohorts and years. A unified model notably classifies preclinical Alzheimer's, which is particularly surprising because of Raman spectroscopy's high sensitivity regarding different measurement conditions. The presented results demonstrate the capability of Raman spectroscopy to detect preclinical Alzheimer's disease for the first time and offer invaluable opportunities for future clinical applications and diagnostic methods.
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- 2024
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30. GOIZ ZAINDU study: a FINGER-like multidomain lifestyle intervention feasibility randomized trial to prevent dementia in Southern Europe.
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Tainta M, Ecay-Torres M, de Arriba M, Barandiaran M, Otaegui-Arrazola A, Iriondo A, Garcia-Sebastian M, Estanga A, Saldias J, Clerigue M, Gabilondo A, Ros N, Mugica J, Barandiaran A, Mangialasche F, Kivipelto M, Arrospide A, Mar J, and Martinez-Lage P
- Subjects
- Aged, Female, Humans, Male, Cognition, Europe, Feasibility Studies, Life Style, Pilot Projects, Aged, 80 and over, Cognitive Dysfunction prevention & control, Cognitive Dysfunction epidemiology, Dementia epidemiology, Dementia prevention & control
- Abstract
Background: GOIZ ZAINDU ("caring early" in Basque) is a pilot study to adapt the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) methodology to the Basque population and evaluate the feasibility and adherence to a FINGER-like multidomain intervention program. Additional aims included the assessment of efficacy on cognition and data collection to design a large efficacy trial., Method: GOIZ ZAINDU is a 1-year, randomized, controlled trial of a multidomain intervention in persons aged 60+ years, with Cardiovascular Risk Factors, Aging and Dementia (CAIDE) risk score ≥ 6, no diagnosis of dementia, and below-than-expected performance in at least one of three cognitive screening tests. Randomization to a multidomain intervention (MD-Int) or regular health advice (RHA) was stratified by sex, age (>/≤ 75), and cognitive status (mild cognitive impairment (MCI)/normal cognition). MD-Int included cardiovascular risk factor control, nutritional counseling, physical activity, and cognitive training. The primary outcomes were retention rate and adherence to the intervention program. Exploratory cognitive outcomes included changes in the Neuropsychological Test Battery z-scores. Analyses were performed according to the intention to treat., Results: One hundred twenty-five participants were recruited (mean age: 75.64 (± 6.46); 58% women). The MD-Int (n = 61) and RHA (n = 64) groups were balanced in terms of their demographics and cognition. Fifty-two (85%) participants from the RHA group and 56 (88%) from the MD-Int group completed the study. More than 70% of the participants had high overall adherence to the intervention activities. The risk of cognitive decline was higher in the RHA group than in the MD-Int group in terms of executive function (p =.019) and processing speed scores (p =.026)., Conclusions: The GOIZ-ZAINDU study proved that the FINGER methodology is adaptable and feasible in a different socio-cultural environment. The exploratory efficacy results showed a lower risk of decline in executive function and processing speed in the intervention group. These results support the design of a large-scale efficacy trial., Trial Registration: GOIZ ZAINDU feasibility trial was approved and registered by the Euskadi Drug Research Ethics Committee (ID: PI2017134) on 23 January 2018. Retrospectively registered in ClinicalTrials.gov (NCT06163716) on 8 December 2023., (© 2024. The Author(s).)
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- 2024
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31. Multivariate GWAS of Alzheimer's disease CSF biomarker profiles implies GRIN2D in synaptic functioning.
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Neumann A, Ohlei O, Küçükali F, Bos IJ, Timsina J, Vos S, Prokopenko D, Tijms BM, Andreasson U, Blennow K, Vandenberghe R, Scheltens P, Teunissen CE, Engelborghs S, Frisoni GB, Blin O, Richardson JC, Bordet R, Lleó A, Alcolea D, Popp J, Marsh TW, Gorijala P, Clark C, Peyratout G, Martinez-Lage P, Tainta M, Dobson RJB, Legido-Quigley C, Van Broeckhoven C, Tanzi RE, Ten Kate M, Lill CM, Barkhof F, Cruchaga C, Lovestone S, Streffer J, Zetterberg H, Visser PJ, Sleegers K, and Bertram L
- Subjects
- Humans, Female, Male, Genome-Wide Association Study, tau Proteins genetics, Biomarkers, Inflammation, Apolipoproteins E genetics, Membrane Proteins genetics, Nerve Tissue Proteins genetics, Receptors, N-Methyl-D-Aspartate genetics, Alzheimer Disease genetics, Alzheimer Disease pathology
- Abstract
Background: Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified several risk loci, but many remain unknown. Cerebrospinal fluid (CSF) biomarkers may aid in gene discovery and we previously demonstrated that six CSF biomarkers (β-amyloid, total/phosphorylated tau, NfL, YKL-40, and neurogranin) cluster into five principal components (PC), each representing statistically independent biological processes. Here, we aimed to (1) identify common genetic variants associated with these CSF profiles, (2) assess the role of associated variants in AD pathophysiology, and (3) explore potential sex differences., Methods: We performed GWAS for each of the five biomarker PCs in two multi-center studies (EMIF-AD and ADNI). In total, 973 participants (n = 205 controls, n = 546 mild cognitive impairment, n = 222 AD) were analyzed for 7,433,949 common SNPs and 19,511 protein-coding genes. Structural equation models tested whether biomarker PCs mediate genetic risk effects on AD, and stratified and interaction models probed for sex-specific effects., Results: Five loci showed genome-wide significant association with CSF profiles, two were novel (rs145791381 [inflammation] and GRIN2D [synaptic functioning]) and three were previously described (APOE, TMEM106B, and CHI3L1). Follow-up analyses of the two novel signals in independent datasets only supported the GRIN2D locus, which contains several functionally interesting candidate genes. Mediation tests indicated that variants in APOE are associated with AD status via processes related to amyloid and tau pathology, while markers in TMEM106B and CHI3L1 are associated with AD only via neuronal injury/inflammation. Additionally, seven loci showed sex-specific associations with AD biomarkers., Conclusions: These results suggest that pathway and sex-specific analyses can improve our understanding of AD genetics and may contribute to precision medicine., (© 2023. BioMed Central Ltd., part of Springer Nature.)
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- 2023
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32. Whole-exome rare-variant analysis of Alzheimer's disease and related biomarker traits.
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Küçükali F, Neumann A, Van Dongen J, De Pooter T, Joris G, De Rijk P, Ohlei O, Dobricic V, Bos I, Vos SJB, Engelborghs S, De Roeck E, Vandenberghe R, Gabel S, Meersmans K, Tsolaki M, Verhey F, Martinez-Lage P, Tainta M, Frisoni G, Blin O, Richardson JC, Bordet R, Scheltens P, Popp J, Peyratout G, Johannsen P, Frölich L, Freund-Levi Y, Streffer J, Lovestone S, Legido-Quigley C, Kate MT, Barkhof F, Zetterberg H, Bertram L, Strazisar M, Visser PJ, Van Broeckhoven C, and Sleegers K
- Subjects
- Humans, Exome genetics, Genetic Association Studies, Phenotype, Biomarkers, Alzheimer Disease genetics, Alzheimer Disease diagnosis
- 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., (© 2022 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)
- Published
- 2023
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33. Cerebrospinal fluid proteomic profiling of individuals with mild cognitive impairment and suspected non-Alzheimer's disease pathophysiology.
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Delvenne A, Gobom J, Tijms B, Bos I, Reus LM, Dobricic V, Kate MT, Verhey F, Ramakers I, Scheltens P, Teunissen CE, Vandenberghe R, Schaeverbeke J, Gabel S, Popp J, Peyratout G, Martinez-Lage P, Tainta M, Tsolaki M, Freund-Levi Y, Lovestone S, Streffer J, Barkhof F, Bertram L, Blennow K, Zetterberg H, Visser PJ, and Vos SJB
- Subjects
- Humans, Male, Female, Aged, Peptide Fragments cerebrospinal fluid, Alzheimer Disease cerebrospinal fluid, Middle Aged, Cognitive Dysfunction cerebrospinal fluid, Proteomics, Biomarkers cerebrospinal fluid, Amyloid beta-Peptides cerebrospinal fluid, tau Proteins cerebrospinal fluid
- Abstract
Background: Suspected non-Alzheimer's disease pathophysiology (SNAP) is a biomarker concept that encompasses individuals with neuronal injury but without amyloidosis. We aim to investigate the pathophysiology of SNAP, defined as abnormal tau without amyloidosis, in individuals with mild cognitive impairment (MCI) by cerebrospinal fluid (CSF) proteomics., Methods: Individuals were classified based on CSF amyloid beta (Aβ)1-42 (A) and phosphorylated tau (T), as cognitively normal A-T- (CN), MCI A-T+ (MCI-SNAP), and MCI A+T+ (MCI-AD). Proteomics analyses, Gene Ontology (GO), brain cell expression, and gene expression analyses in brain regions of interest were performed., Results: A total of 96 proteins were decreased in MCI-SNAP compared to CN and MCI-AD. These proteins were enriched for extracellular matrix (ECM), hemostasis, immune system, protein processing/degradation, lipids, and synapse. Fifty-one percent were enriched for expression in the choroid plexus., Conclusion: The pathophysiology of MCI-SNAP (A-T+) is distinct from that of MCI-AD. Our findings highlight the need for a different treatment in MCI-SNAP compared to MCI-AD., (© 2022 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)
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- 2023
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34. Estimation of the epidemiology of dementia and associated neuropsychiatric symptoms by applying machine learning to real-world data.
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Mar J, Gorostiza A, Arrospide A, Larrañaga I, Alberdi A, Cernuda C, Iruin Á, Tainta M, Mar-Barrutia L, and Ibarrondo O
- Subjects
- Humans, Male, Female, Retrospective Studies, Nursing Homes, Machine Learning, Dementia diagnosis, Dementia epidemiology, Dementia etiology, Psychotic Disorders diagnosis, Psychotic Disorders epidemiology, Psychotic Disorders etiology
- Abstract
Introduction: Incidence rates of dementia-related neuropsychiatric symptoms (NPS) are not known and this hampers the assessment of their population burden. The objective of this study was to obtain an approximate estimate of the population incidence and prevalence of both dementia and NPS., Methods: Given the dynamic nature of the population with dementia, a retrospective study was conducted within the database of the Basque Health Service (real-world data) at the beginning and end of 2019. Validated random forest models were used to identify separately depressive and psychotic clusters according to their presence in the electronic health records of all patients diagnosed with dementia., Results: Among the 631,949 individuals over 60 years registered, 28,563 were diagnosed with dementia, of whom 15,828 (55.4%) showed psychotic symptoms and 19,461 (68.1%) depressive symptoms. The incidence of dementia in 2019 was 6.8/1000 person-years. Most incident cases of depressive (72.3%) and psychotic (51.9%) NPS occurred in cases of incident dementia. The risk of depressive-type NPS grows with years since dementia diagnosis, living in a nursing home, and female sex, but falls with older age. In the psychotic cluster model, the effects of male sex, and older age are inverted, both increasing the probability of this type of symptoms., Conclusions: The stigmatization factor conditions the social and attitudinal environment, delaying the diagnosis of dementia, preventing patients from receiving adequate care and exacerbating families' suffering. This study evidences the synergy between big data and real-world data for psychiatric epidemiological research., (Copyright © 2021 SEP y SEPB. Published by Elsevier España, S.L.U. All rights reserved.)
- Published
- 2022
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35. Rare variants in IFFO1, DTNB, NLRC3 and SLC22A10 associate with Alzheimer's disease CSF profile of neuronal injury and inflammation.
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Neumann A, Küçükali F, Bos I, Vos SJB, Engelborghs S, De Pooter T, Joris G, De Rijk P, De Roeck E, Tsolaki M, Verhey F, Martinez-Lage P, Tainta M, Frisoni G, Blin O, Richardson J, Bordet R, Scheltens P, Popp J, Peyratout G, Johannsen P, Frölich L, Vandenberghe R, Freund-Levi Y, Streffer J, Lovestone S, Legido-Quigley C, Ten Kate M, Barkhof F, Strazisar M, Zetterberg H, Bertram L, Visser PJ, van Broeckhoven C, and Sleegers K
- Subjects
- Amyloid beta-Peptides genetics, Biomarkers, Chitinase-3-Like Protein 1 genetics, DNA-Binding Proteins, Dithionitrobenzoic Acid, Humans, Inflammation genetics, Intercellular Signaling Peptides and Proteins, Neurogranin genetics, Transcription Factors, tau Proteins, Alzheimer Disease diagnosis
- Abstract
Alzheimer's disease (AD) biomarkers represent several neurodegenerative processes, such as synaptic dysfunction, neuronal inflammation and injury, as well as amyloid pathology. We performed an exome-wide rare variant analysis of six AD biomarkers (β-amyloid, total/phosphorylated tau, NfL, YKL-40, and Neurogranin) to discover genes associated with these markers. Genetic and biomarker information was available for 480 participants from two studies: EMIF-AD and ADNI. We applied a principal component (PC) analysis to derive biomarkers combinations, which represent statistically independent biological processes. We then tested whether rare variants in 9576 protein-coding genes associate with these PCs using a Meta-SKAT test. We also tested whether the PCs are intermediary to gene effects on AD symptoms with a SMUT test. One PC loaded on NfL and YKL-40, indicators of neuronal injury and inflammation. Four genes were associated with this PC: IFFO1, DTNB, NLRC3, and SLC22A10. Mediation tests suggest, that these genes also affect dementia symptoms via inflammation/injury. We also observed an association between a PC loading on Neurogranin, a marker for synaptic functioning, with GABBR2 and CASZ1, but no mediation effects. The results suggest that rare variants in IFFO1, DTNB, NLRC3, and SLC22A10 heighten susceptibility to neuronal injury and inflammation, potentially by altering cytoskeleton structure and immune activity disinhibition, resulting in an elevated dementia risk. GABBR2 and CASZ1 were associated with synaptic functioning, but mediation analyses suggest that the effect of these two genes on synaptic functioning is not consequential for AD development., (© 2022. The Author(s).)
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- 2022
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36. 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.
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Homann J, Osburg T, Ohlei O, Dobricic V, Deecke L, Bos I, Vandenberghe R, Gabel S, Scheltens P, Teunissen CE, Engelborghs S, Frisoni G, Blin O, Richardson JC, Bordet R, Lleó A, Alcolea D, Popp J, Clark C, Peyratout G, Martinez-Lage P, Tainta M, Dobson RJB, Legido-Quigley C, Sleegers K, Van Broeckhoven C, Wittig M, Franke A, Lill CM, Blennow K, Zetterberg H, Lovestone S, Streffer J, Ten Kate M, Vos SJB, Barkhof F, Visser PJ, and Bertram L
- Abstract
Alzheimer's disease (AD) is the most frequent neurodegenerative disease with an increasing prevalence in industrialized, aging populations. AD susceptibility has an established genetic basis which has been the focus of a large number of genome-wide association studies (GWAS) published over the last decade. Most of these GWAS used dichotomized clinical diagnostic status, i.e., case vs. control classification, as outcome phenotypes, without the use of biomarkers. An alternative and potentially more powerful study design is afforded by using quantitative AD-related phenotypes as GWAS outcome traits, an analysis paradigm that we followed in this work. Specifically, we utilized genotype and phenotype data from n = 931 individuals collected under the auspices of the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) study to perform a total of 19 separate GWAS analyses. As outcomes we used five magnetic resonance imaging (MRI) traits and seven cognitive performance traits. For the latter, longitudinal data from at least two timepoints were available in addition to cross-sectional assessments at baseline. Our GWAS analyses revealed several genome-wide significant associations for the neuropsychological performance measures, in particular those assayed longitudinally. Among the most noteworthy signals were associations in or near EHBP1 (EH domain binding protein 1; on chromosome 2p15) and CEP112 (centrosomal protein 112; 17q24.1) with delayed recall as well as SMOC2 (SPARC related modular calcium binding 2; 6p27) with immediate recall in a memory performance test. On the X chromosome, which is often excluded in other GWAS, we identified a genome-wide significant signal near IL1RAPL1 (interleukin 1 receptor accessory protein like 1; Xp21.3). While polygenic score (PGS) analyses showed the expected strong associations with SNPs highlighted in relevant previous GWAS on hippocampal volume and cognitive function, they did not show noteworthy associations with recent AD risk GWAS findings. In summary, our study highlights the power of using quantitative endophenotypes as outcome traits in AD-related GWAS analyses and nominates several new loci not previously implicated in cognitive decline., Competing Interests: HZ has served at scientific advisory boards and/or as a consultant for Abbvie, Alector, Annexon, Artery Therapeutics, AZTherapies, CogRx, Denali, Eisai, Nervgen, Pinteon Therapeutics, Red Abbey Labs, Passage Bio, Roche, Samumed, Siemens Healthineers, Triplet Therapeutics, and Wave, has given lectures in symposia sponsored by Cellectricon, Fujirebio, Alzecure, Biogen, and Roche, and was a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which was a part of the GU Ventures Incubator Program. FB is supported by the NIHR biomedical research centre at UCLH. JP received consultation honoraria from Nestle Institute of Health Sciences, Ono Pharma, OM Pharma, and Fujirebio, unrelated to the submitted work. CT has a collaboration contract with ADx Neurosciences, Quanterix and Eli Lilly, performed contract research or received grants from AC-Immune, Axon Neurosciences, Biogen, Brainstorm Therapeutics, Celgene, EIP Pharma, Eisai, PeopleBio, Roche, Toyama, Vivoryon. She serves on editorial boards of Medidact Neurologie/Springer, Alzheimer Research and Therapy, Neurology: Neuroimmunology and Neuroinflammation, and was editor of a Neuromethods book Springer. CT also holds a speaker’s contract with Roche, Inc. KB has served as a consultant, at advisory boards, or at data monitoring committees for Abcam, Axon, BioArctic, Biogen, JOMDD/Shimadzu. Julius Clinical, Lilly, MagQu, Novartis, Pharmatrophix, Prothena, Roche Diagnostics, and Siemens Healthineers, and was a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which was a part of the GU Ventures Incubator Program, outside the work presented in this paper. SL is currently an employee at Janssen Medical UK. JS was an employee of Janssen R&D, LLC., and is currently an employee and chief medical officer of AC Immune SA. JR was an employee of Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Stevenage, UK., (Copyright © 2022 Homann, Osburg, Ohlei, Dobricic, Deecke, Bos, Vandenberghe, Gabel, Scheltens, Teunissen, Engelborghs, Frisoni, Blin, Richardson, Bordet, Lleó, Alcolea, Popp, Clark, Peyratout, Martinez-Lage, Tainta, Dobson, Legido-Quigley, Sleegers, Van Broeckhoven, Wittig, Franke, Lill, Blennow, Zetterberg, Lovestone, Streffer, ten Kate, Vos, Barkhof, Visser and Bertram.)
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- 2022
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37. Sex-Specific Metabolic Pathways Were Associated with Alzheimer's Disease (AD) Endophenotypes in the European Medical Information Framework for AD Multimodal Biomarker Discovery Cohort.
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Xu J, Green R, Kim M, Lord J, Ebshiana A, Westwood S, Baird AL, Nevado-Holgado AJ, Shi L, Hye A, Snowden SG, Bos I, Vos SJB, Vandenberghe R, Teunissen CE, Kate MT, Scheltens P, Gabel S, Meersmans K, Blin O, Richardson J, De Roeck EE, Engelborghs S, Sleegers K, Bordet R, Rami L, Kettunen P, Tsolaki M, Verhey FRJ, Alcolea D, Lleó A, Peyratout G, Tainta M, Johannsen P, Freund-Levi Y, Frölich L, Dobricic V, Frisoni GB, Molinuevo JL, Wallin A, Popp J, Martinez-Lage P, Bertram L, Blennow K, Zetterberg H, Streffer J, Visser PJ, Lovestone S, Proitsi P, Legido-Quigley C, and On Behalf Of The European Medical Information Framework Consortium
- Abstract
Background: physiological differences between males and females could contribute to the development of Alzheimer's Disease (AD). Here, we examined metabolic pathways that may lead to precision medicine initiatives., Methods: We explored whether sex modifies the association of 540 plasma metabolites with AD endophenotypes including diagnosis, cerebrospinal fluid (CSF) biomarkers, brain imaging, and cognition using regression analyses for 695 participants (377 females), followed by sex-specific pathway overrepresentation analyses, APOE ε4 stratification and assessment of metabolites' discriminatory performance in AD., Results: In females with AD, vanillylmandelate (tyrosine pathway) was increased and tryptophan betaine (tryptophan pathway) was decreased. The inclusion of these two metabolites (area under curve (AUC) = 0.83, standard error (SE) = 0.029) to a baseline model (covariates + CSF biomarkers, AUC = 0.92, SE = 0.019) resulted in a significantly higher AUC of 0.96 (SE = 0.012). Kynurenate was decreased in males with AD (AUC = 0.679, SE = 0.046)., Conclusions: metabolic sex-specific differences were reported, covering neurotransmission and inflammation pathways with AD endophenotypes. Two metabolites, in pathways related to dopamine and serotonin, were associated to females, paving the way to personalised treatment.
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- 2021
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38. TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer's disease biomarker levels.
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Hong S, Dobricic V, Ohlei O, Bos I, Vos SJB, Prokopenko D, Tijms BM, Andreasson U, Blennow K, Vandenberghe R, Gabel S, Scheltens P, Teunissen CE, Engelborghs S, Frisoni G, Blin O, Richardson JC, Bordet R, Lleó A, Alcolea D, Popp J, Clark C, Peyratout G, Martinez-Lage P, Tainta M, Dobson RJB, Legido-Quigley C, Sleegers K, Van Broeckhoven C, Tanzi RE, Ten Kate M, Wittig M, Franke A, Lill CM, Barkhof F, Lovestone S, Streffer J, Zetterberg H, Visser PJ, and Bertram L
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- Aged, Chitinase-3-Like Protein 1 genetics, Female, Humans, Male, Neurofilament Proteins genetics, Neurogranin cerebrospinal fluid, Alzheimer Disease genetics, Biomarkers cerebrospinal fluid, Genome-Wide Association Study, Membrane Proteins genetics, Nerve Tissue Proteins genetics
- Abstract
Introduction: Neurofilament light (NfL), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are biomarkers for Alzheimer's disease (AD) to monitor axonal damage, astroglial activation, and synaptic degeneration, respectively., Methods: We performed genome-wide association studies (GWAS) using DNA and cerebrospinal fluid (CSF) samples from the EMIF-AD Multimodal Biomarker Discovery study for discovery, and the Alzheimer's Disease Neuroimaging Initiative study for validation analyses. GWAS were performed for all three CSF biomarkers using linear regression models adjusting for relevant covariates., Results: We identify novel genome-wide significant associations between DNA variants in TMEM106B and CSF levels of NfL, and between CPOX and YKL-40. We confirm previous work suggesting that YKL-40 levels are associated with DNA variants in CHI3L1., Discussion: Our study provides important new insights into the genetic architecture underlying interindividual variation in three AD-related CSF biomarkers. In particular, our data shed light on the sequence of events regarding the initiation and progression of neuropathological processes relevant in AD., (© 2021 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)
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- 2021
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39. Replication study of plasma proteins relating to Alzheimer's pathology.
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Shi L, Winchester LM, Westwood S, Baird AL, Anand SN, Buckley NJ, Hye A, Ashton NJ, Bos I, Vos SJB, Kate MT, Scheltens P, Teunissen CE, Vandenberghe R, Gabel S, Meersmans K, Engelborghs S, De Roeck EE, Sleegers K, Frisoni GB, Blin O, Richardson JC, Bordet R, Molinuevo JL, Rami L, Wallin A, Kettunen P, Tsolaki M, Verhey F, Lléo A, Sala I, Popp J, Peyratout G, Martinez-Lage P, Tainta M, Johannsen P, Freund-Levi Y, Frölich L, Dobricic V, Legido-Quigley C, Barkhof F, Andreasson U, Blennow K, Zetterberg H, Streffer J, Lill CM, Bertram L, Visser PJ, Kolb HC, Narayan VA, Lovestone S, and Nevado-Holgado AJ
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- Aged, Apolipoprotein E4 blood, Apolipoprotein E4 genetics, Cognitive Dysfunction blood, Cognitive Dysfunction pathology, Europe, Female, Humans, Male, Middle Aged, Alzheimer Disease blood, Alzheimer Disease pathology, Amyloid beta-Peptides blood, Biomarkers blood, Blood Proteins, Proteomics, tau Proteins blood
- Abstract
Introduction: This study sought to discover and replicate plasma proteomic biomarkers relating to Alzheimer's disease (AD) including both the "ATN" (amyloid/tau/neurodegeneration) diagnostic framework and clinical diagnosis., Methods: Plasma proteins from 972 subjects (372 controls, 409 mild cognitive impairment [MCI], and 191 AD) were measured using both SOMAscan and targeted assays, including 4001 and 25 proteins, respectively., Results: Protein co-expression network analysis of SOMAscan data revealed the relation between proteins and "N" varied across different neurodegeneration markers, indicating that the ATN variants are not interchangeable. Using hub proteins, age, and apolipoprotein E ε4 genotype discriminated AD from controls with an area under the curve (AUC) of 0.81 and MCI convertors from non-convertors with an AUC of 0.74. Targeted assays replicated the relation of four proteins with the ATN framework and clinical diagnosis., Discussion: Our study suggests that blood proteins can predict the presence of AD pathology as measured in the ATN framework as well as clinical diagnosis., (© 2021 the Alzheimer's Association.)
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- 2021
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40. Plasma lipids are associated with white matter microstructural changes and axonal degeneration.
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Iriondo A, García-Sebastian M, Arrospide A, Arriba M, Aurtenetxe S, Barandiaran M, Clerigue M, Ecay-Torres M, Estanga A, Gabilondo A, Izagirre A, Saldias J, Tainta M, Villanua J, Mar J, Goñi FM, and Martínez-Lage P
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- Brain, Humans, Lipids, Magnetic Resonance Imaging, Plasma, Diffusion Tensor Imaging, White Matter diagnostic imaging
- Abstract
Dislipidemia is a risk factor for cognitive impairment. We studied the association between interindividual variability of plasma lipids and white matter (WM) microstructure, using diffusion tensor imaging (DTI) in 273 healthy adults. Special focus was placed on 7 regions of interest (ROI) which are structural components of cognitive neurocircuitry. We also investigated the effect of plasma lipids on cerebrospinal fluid (CSF) neurofilament light chain (NfL), an axonal degeneration marker. Low density lipoprotein (LDL) and triglyceride (TG) levels showed a negative association with axial diffusivity (AxD) in multiple regions. High density lipoproteins (HDL) showed a positive correlation. The association was independent of Apolipoprotein E (APOE) genotype, blood pressure or use of statins. LDL moderated the relation between NfL and AxD in the body of the corpus callosum (p = 0.041), right cingulum gyrus (p = 0.041), right fornix/stria terminalis (p = 0.025) and right superior longitudinal fasciculus (p = 0.020) and TG in the right inferior longitudinal fasciculus (p = 0.004) and left fornix/stria terminalis (p = 0.001). We conclude that plasma lipids are associated to WM microstructural changes and axonal degeneration and might represent a risk factor in the transition from healthy aging to disease.
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- 2021
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41. Estimation of the epidemiology of dementia and associated neuropsychiatric symptoms by applying machine learning to real-world data.
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Mar J, Gorostiza A, Arrospide A, Larrañaga I, Alberdi A, Cernuda C, Iruin Á, Tainta M, Mar-Barrutia L, and Ibarrondo O
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Introduction: Incidence rates of dementia-related neuropsychiatric symptoms (NPS) are not known and this hampers the assessment of their population burden. The objective of this study was to obtain an approximate estimate of the population incidence and prevalence of both dementia and NPS., Methods: Given the dynamic nature of the population with dementia, a retrospective study was conducted within the database of the Basque Health Service (real-world data) at the beginning and end of 2019. Validated random forest models were used to identify separately depressive and psychotic clusters according to their presence in the electronic health records of all patients diagnosed with dementia., Results: Among the 631,949 individuals over 60 years registered, 28,563 were diagnosed with dementia, of whom 15,828 (55.4%) showed psychotic symptoms and 19,461 (68.1%) depressive symptoms. The incidence of dementia in 2019 was 6.8/1000 person-years. Most incident cases of depressive (72.3%) and psychotic (51.9%) NPS occurred in cases of incident dementia. The risk of depressive-type NPS grows with years since dementia diagnosis, living in a nursing home, and female sex, but falls with older age. In the psychotic cluster model, the effects of male sex, and older age are inverted, both increasing the probability of this type of symptoms., Conclusions: The stigmatization factor conditions the social and attitudinal environment, delaying the diagnosis of dementia, preventing patients from receiving adequate care and exacerbating families' suffering. This study evidences the synergy between big data and real-world data for psychiatric epidemiological research., (Copyright © 2021 SEP y SEPB. Publicado por Elsevier España, S.L.U. All rights reserved.)
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- 2021
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42. Mediterranean Diet and Risk of Dementia and Alzheimer's Disease in the EPIC-Spain Dementia Cohort Study.
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Andreu-Reinón ME, Chirlaque MD, Gavrila D, Amiano P, Mar J, Tainta M, Ardanaz E, Larumbe R, Colorado-Yohar SM, Navarro-Mateu F, Navarro C, and Huerta JM
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- Adult, Aged, Alzheimer Disease epidemiology, Case-Control Studies, Cohort Studies, Dementia epidemiology, Female, Humans, Male, Middle Aged, Risk Factors, Spain epidemiology, Alzheimer Disease prevention & control, Dementia prevention & control, Diet, Mediterranean
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The Mediterranean diet (MD) has shown to reduce the occurrence of several chronic diseases. To evaluate its potential protective role on dementia incidence we studied 16,160 healthy participants from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Spain Dementia Cohort study recruited between 1992-1996 and followed up for a mean (±SD) of 21.6 (±3.4) years. A total of 459 incident cases of dementia were ascertained through expert revision of medical records. Data on habitual diet was collected through a validated diet history method to assess adherence to the relative Mediterranean Diet (rMED) score. Hazard ratios (HR) of dementia by rMED levels (low, medium and high adherence levels: ≤6, 7-10 and ≥11 points, respectively) were estimated using multivariable Cox models, whereas time-dependent effects were evaluated using flexible parametric Royston-Parmar (RP) models. Results of the fully adjusted model showed that high versus low adherence to the categorical rMED score was associated with a 20% (HR = 0.80, 95%CI: 0.60-1.06) lower risk of dementia overall and HR of dementia was 8% (HR = 0.92, 0.85-0.99, p = 0.021) lower for each 2-point increment of the continuous rMED score. By sub-types, a favorable association was also found in women for non-AD (HR per 2-points = 0.74, 95%CI: 0.62-0.89), while not statistically significant in men for AD (HR per 2-points = 0.88, 0.76-1.01). The association was stronger in participants with lower education. In conclusion, in this large prospective cohort study MD was inversely associated with dementia incidence after accounting for major cardiovascular risk factors. The results differed by dementia sub-type, sex, and education but there was no significant evidence of effect modification.
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- 2021
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43. Genome-wide association study of Alzheimer's disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset.
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Hong S, Prokopenko D, Dobricic V, Kilpert F, Bos I, Vos SJB, Tijms BM, Andreasson U, Blennow K, Vandenberghe R, Cleynen I, Gabel S, Schaeverbeke J, Scheltens P, Teunissen CE, Niemantsverdriet E, Engelborghs S, Frisoni G, Blin O, Richardson JC, Bordet R, Molinuevo JL, Rami L, Kettunen P, Wallin A, Lleó A, Sala I, Popp J, Peyratout G, Martinez-Lage P, Tainta M, Dobson RJB, Legido-Quigley C, Sleegers K, Van Broeckhoven C, Ten Kate M, Barkhof F, Zetterberg H, Lovestone S, Streffer J, Wittig M, Franke A, Tanzi RE, Visser PJ, and Bertram L
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- Aged, Amyloid beta-Peptides genetics, Biomarkers, Female, Genome-Wide Association Study, Humans, Male, Peptide Fragments, tau Proteins genetics, Alzheimer Disease genetics
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Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case-control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures derived from quantifications of five separate amyloid-beta (Aβ) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to Aβ42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-Aβ38 and CSF-Aβ40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case-control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-Aβ and -tau-related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.
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- 2020
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44. Incidence of Dementia and Associated Factors in the EPIC-Spain Dementia Cohort.
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Andreu-Reinón ME, Huerta JM, Gavrila D, Amiano P, Mar J, Tainta M, Ardanaz E, Larumbe R, Navarro C, Colorado-Yohar SM, Navarro-Mateu F, and Chirlaque MD
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- Adult, Aged, Aged, 80 and over, Alcohol Drinking epidemiology, Alcohol Drinking psychology, Alcohol Drinking trends, Cohort Studies, Dementia psychology, Diabetes Mellitus diagnosis, Diabetes Mellitus epidemiology, Diabetes Mellitus psychology, Educational Status, Female, Follow-Up Studies, Humans, Hyperlipidemias diagnosis, Hyperlipidemias epidemiology, Hyperlipidemias psychology, Incidence, Male, Middle Aged, Prospective Studies, Spain epidemiology, Dementia diagnosis, Dementia epidemiology
- Abstract
Background: Dementia has become a public health priority as the number of cases continues to grow worldwide., Objective: To assess dementia incidence and determinants in the EPIC-Spain Dementia Cohort., Methods: 25,015 participants (57% women) were recruited from three Spanish regions between 1992-1996 and followed-up for over 20 years. Incident cases were ascertained through individual revision of medical records of potential cases. Crude and age-adjusted incidence rates (IR) of dementia and sub-types (Alzheimer's disease (AD), and non-AD) were calculated by sex. Neelson-Aalen cumulative incidence estimates at 10, 15, and 20 years were obtained for each sex and age group. Multivariate Royston-Parmar models were used to assess independent determinants., Results: Global IR were higher in women for dementia and AD, and similar by sex for non-AD. IR ranged from 0.09 cases of dementia (95% confidence interval: 0.06-0.13) and 0.05 (0.03-0.09) of AD per 1000 person-years (py) in participants below 60 years, to 23.2 (15.9-33.8) cases of dementia and 14.6 (9.1-33.5) of AD (per 1000 py) in those ≥85 years. Adjusted IR were consistently higher in women than men for overall dementia and AD. Up to 12.5% of women and 9.1% of men 60-65 years-old developed dementia within 20 years. Low education, diabetes, and hyperlipidemia were the main independent predictors of dementia risk, whereas alcohol showed an inverse association., Conclusion: Dementia incidence increased with age and was higher among women, but showed no geographical pattern. Dementia risk was higher among subjects with lower education, not drinking alcohol, and presenting cardiovascular risk factors.
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- 2020
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45. Validation of Plasma Proteomic Biomarkers Relating to Brain Amyloid Burden in the EMIF-Alzheimer's Disease Multimodal Biomarker Discovery Cohort.
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Westwood S, Baird AL, Anand SN, Nevado-Holgado AJ, Kormilitzin A, Shi L, Hye A, Ashton NJ, Morgan AR, Bos I, Vos SJB, Baker S, Buckley NJ, Ten Kate M, Scheltens P, Teunissen CE, Vandenberghe R, Gabel S, Meersmans K, Engelborghs S, De Roeck EE, Sleegers K, Frisoni GB, Blin O, Richardson JC, Bordet R, Molinuevo JL, Rami L, Wallin A, Kettunen P, Tsolaki M, Verhey F, Lléo A, Sala I, Popp J, Peyratout G, Martinez-Lage P, Tainta M, Johannsen P, Freund-Levi Y, Frölich L, Dobricic V, Legido-Quigley C, Bertram L, Barkhof F, Zetterberg H, Morgan BP, Streffer J, Visser PJ, and Lovestone S
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- Aged, Alzheimer Disease diagnostic imaging, Apolipoprotein E4 genetics, Body Burden, Cerebral Amyloid Angiopathy diagnostic imaging, Cognitive Dysfunction blood, Cognitive Dysfunction diagnostic imaging, Cohort Studies, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Positron-Emission Tomography, ROC Curve, tau Proteins cerebrospinal fluid, Alzheimer Disease blood, Biomarkers blood, Blood Proteins analysis, Cerebral Amyloid Angiopathy blood, Proteomics
- Abstract
We have previously investigated, discovered, and replicated plasma protein biomarkers for use to triage potential trials participants for PET or cerebrospinal fluid measures of Alzheimer's disease (AD) pathology. This study sought to undertake validation of these candidate plasma biomarkers in a large, multi-center sample collection. Targeted plasma analyses of 34 proteins with prior evidence for prediction of in vivo pathology were conducted in up to 1,000 samples from cognitively healthy elderly individuals, people with mild cognitive impairment, and in patients with AD-type dementia, selected from the EMIF-AD catalogue. Proteins were measured using Luminex xMAP, ELISA, and Meso Scale Discovery assays. Seven proteins replicated in their ability to predict in vivo amyloid pathology. These proteins form a biomarker panel that, along with age, could significantly discriminate between individuals with high and low amyloid pathology with an area under the curve of 0.74. The performance of this biomarker panel remained consistent when tested in apolipoprotein E ɛ4 non-carrier individuals only. This blood-based panel is biologically relevant, measurable using practical immunocapture arrays, and could significantly reduce the cost incurred to clinical trials through screen failure.
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- 2020
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46. Cerebrospinal Fluid 7-Ketocholesterol Level is Associated with Amyloid-β42 and White Matter Microstructure in Cognitively Healthy Adults.
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Iriondo A, García-Sebastian M, Arrospide A, Arriba M, Aurtenetxe S, Barandiaran M, Clerigue M, Ecay-Torres M, Estanga A, Gabilondo A, Izagirre A, Saldias J, Tainta M, Villanua J, Blennow K, Zetterberg H, Mar J, Abad-García B, Dias IHK, Goñi FM, and Martínez-Lage P
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- Adult, Aged, Aged, 80 and over, Biomarkers cerebrospinal fluid, Cohort Studies, Cross-Sectional Studies, Female, Humans, Longitudinal Studies, Magnetic Resonance Imaging methods, Male, Middle Aged, White Matter metabolism, Amyloid beta-Peptides cerebrospinal fluid, Cognition physiology, Ketocholesterols cerebrospinal fluid, Peptide Fragments cerebrospinal fluid, White Matter diagnostic imaging
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Background: Abnormal cholesterol metabolism changes the neuronal membrane and may promote amyloidogenesis. Oxysterols in cerebrospinal fluid (CSF) are related to Alzheimer's disease (AD) biomarkers in mild cognitive impairment and dementia. Cholesterol turnover is important for axonal and white matter (WM) microstructure maintenance., Objective: We aim to demonstrate that the association of oxysterols, AD biomarkers, and WM microstructure occurs early in asymptomatic individuals., Methods: We studied the association of inter-individual variability of CSF 24-hydroxycholesterol (24-OHC), 27-hydroxycholesterol (27-OHC), 7-ketocholesterol (7-KC), 7β-hydroxycholesterol (7β-OHC), amyloid-β42 (Aβ42), total-tau (t-tau), phosphorylated-tau (p-tau), neurofilament (NfL), and WM microstructure using diffusion tensor imaging, generalized linear models and moderation/mediation analyses in 153 healthy adults., Results: Higher 7-KC levels were related to lower Aβ42, indicative of greater AD pathology (p = 0.041) . Higher 7-KC levels were related to lower fractional anisotropy (FA) and higher mean (MD), axial (AxD), and radial (RD) diffusivity. 7-KC modulated the association between AxD and NfL in the corpus callosum splenium (B = 39.39, p = 0.017), genu (B = 68.64, p = 0.000), and fornix (B = 10.97, p = 0.000). Lower Aβ42 levels were associated to lower FA and higher MD, AxD, and RD in the fornix, corpus callosum, inferior longitudinal fasciculus, and hippocampus. The association between AxD and Aβ42 was moderated by 7K-C (p = 0.048)., Conclusion: This study adds clinical evidence to support the role of 7K-C on axonal integrity and the involvement of cholesterol metabolism in the Aβ42 generation process.
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- 2020
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47. Validation of Random Forest Machine Learning Models to Predict Dementia-Related Neuropsychiatric Symptoms in Real-World Data.
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Mar J, Gorostiza A, Ibarrondo O, Cernuda C, Arrospide A, Iruin Á, Larrañaga I, Tainta M, Ezpeleta E, and Alberdi A
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- Aged, Aged, 80 and over, Databases, Factual statistics & numerical data, Dementia diagnosis, Dementia epidemiology, Female, Forecasting, Humans, Male, Mental Disorders epidemiology, Reproducibility of Results, Retrospective Studies, Data Analysis, Databases, Factual standards, Electronic Health Records standards, Machine Learning standards, Mental Disorders diagnosis
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Background: Neuropsychiatric symptoms (NPS) are the leading cause of the social burden of dementia but their role is underestimated., Objective: The objective of the study was to validate predictive models to separately identify psychotic and depressive symptoms in patients diagnosed with dementia using clinical databases representing the whole population to inform decision-makers., Methods: First, we searched the electronic health records of 4,003 patients with dementia to identify NPS. Second, machine learning (random forest) algorithms were applied to build separate predictive models for psychotic and depressive symptom clusters in the training set (N = 3,003). Third, calibration and discrimination were assessed in the test set (N = 1,000) to assess the performance of the models., Results: Neuropsychiatric symptoms were noted in the electronic health record of 58% of patients. The area under the receiver operating curve reached 0.80 for the psychotic cluster model and 0.74 for the depressive cluster model. The Kappa index and accuracy also showed better discrimination in the psychotic model. Calibration plots indicated that both types of model had less predictive accuracy when the probability of neuropsychiatric symptoms was <25%. The most important variables in the psychotic cluster model were use of risperidone, level of sedation, use of quetiapine and haloperidol and the number of antipsychotics prescribed. In the depressive cluster model, the most important variables were number of antidepressants prescribed, escitalopram use, level of sedation, and age., Conclusion: Given their relatively good performance, the predictive models can be used to estimate prevalence of NPS in population databases.
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- 2020
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48. Dickkopf-1 Overexpression in vitro Nominates Candidate Blood Biomarkers Relating to Alzheimer's Disease Pathology.
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Shi L, Winchester LM, Liu BY, Killick R, Ribe EM, Westwood S, Baird AL, Buckley NJ, Hong S, Dobricic V, Kilpert F, Franke A, Kiddle S, Sattlecker M, Dobson R, Cuadrado A, Hye A, Ashton NJ, Morgan AR, Bos I, Vos SJB, Ten Kate M, Scheltens P, Vandenberghe R, Gabel S, Meersmans K, Engelborghs S, De Roeck EE, Sleegers K, Frisoni GB, Blin O, Richardson JC, Bordet R, Molinuevo JL, Rami L, Wallin A, Kettunen P, Tsolaki M, Verhey F, Lleó A, Alcolea D, Popp J, Peyratout G, Martinez-Lage P, Tainta M, Johannsen P, Teunissen CE, Freund-Levi Y, Frölich L, Legido-Quigley C, Barkhof F, Blennow K, Rasmussen KL, Nordestgaard BG, Frikke-Schmidt R, Nielsen SF, Soininen H, Vellas B, Kloszewska I, Mecocci P, Zetterberg H, Morgan BP, Streffer J, Visser PJ, Bertram L, Nevado-Holgado AJ, and Lovestone S
- Subjects
- Aged, Alzheimer Disease genetics, Biomarkers blood, Female, Gene Expression, HEK293 Cells, Humans, Intercellular Signaling Peptides and Proteins biosynthesis, Intercellular Signaling Peptides and Proteins genetics, Male, Middle Aged, Alzheimer Disease blood, Alzheimer Disease pathology, Intercellular Signaling Peptides and Proteins blood
- Abstract
Background: Previous studies suggest that Dickkopf-1 (DKK1), an inhibitor of Wnt signaling, plays a role in amyloid-induced toxicity and hence Alzheimer's disease (AD). However, the effect of DKK1 expression on protein expression, and whether such proteins are altered in disease, is unknown., Objective: We aim to test whether DKK1 induced protein signature obtained in vitro were associated with markers of AD pathology as used in the amyloid/tau/neurodegeneration (ATN) framework as well as with clinical outcomes., Methods: We first overexpressed DKK1 in HEK293A cells and quantified 1,128 proteins in cell lysates using aptamer capture arrays (SomaScan) to obtain a protein signature induced by DKK1. We then used the same assay to measure the DKK1-signature proteins in human plasma in two large cohorts, EMIF (n = 785) and ANM (n = 677)., Results: We identified a 100-protein signature induced by DKK1 in vitro. Subsets of proteins, along with age and apolipoprotein E ɛ4 genotype distinguished amyloid pathology (A + T-N-, A+T+N-, A+T-N+, and A+T+N+) from no AD pathology (A-T-N-) with an area under the curve of 0.72, 0.81, 0.88, and 0.85, respectively. Furthermore, we found that some signature proteins (e.g., Complement C3 and albumin) were associated with cognitive score and AD diagnosis in both cohorts., Conclusions: Our results add further evidence for a role of DKK regulation of Wnt signaling in AD and suggest that DKK1 induced signature proteins obtained in vitro could reflect theATNframework as well as predict disease severity and progression in vivo.
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- 2020
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49. A metabolite-based machine learning approach to diagnose Alzheimer-type dementia in blood: Results from the European Medical Information Framework for Alzheimer disease biomarker discovery cohort.
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Stamate D, Kim M, Proitsi P, Westwood S, Baird A, Nevado-Holgado A, Hye A, Bos I, Vos SJB, Vandenberghe R, Teunissen CE, Kate MT, Scheltens P, Gabel S, Meersmans K, Blin O, Richardson J, De Roeck E, Engelborghs S, Sleegers K, Bordet R, Ramit L, Kettunen P, Tsolaki M, Verhey F, Alcolea D, Lléo A, Peyratout G, Tainta M, Johannsen P, Freund-Levi Y, Frölich L, Dobricic V, Frisoni GB, Molinuevo JL, Wallin A, Popp J, Martinez-Lage P, Bertram L, Blennow K, Zetterberg H, Streffer J, Visser PJ, Lovestone S, and Legido-Quigley C
- Abstract
Introduction: Machine learning (ML) may harbor the potential to capture the metabolic complexity in Alzheimer Disease (AD). Here we set out to test the performance of metabolites in blood to categorize AD when compared to CSF biomarkers., Methods: This study analyzed samples from 242 cognitively normal (CN) people and 115 with AD-type dementia utilizing plasma metabolites (n = 883). Deep Learning (DL), Extreme Gradient Boosting (XGBoost) and Random Forest (RF) were used to differentiate AD from CN. These models were internally validated using Nested Cross Validation (NCV)., Results: On the test data, DL produced the AUC of 0.85 (0.80-0.89), XGBoost produced 0.88 (0.86-0.89) and RF produced 0.85 (0.83-0.87). By comparison, CSF measures of amyloid, p-tau and t-tau (together with age and gender) produced with XGBoost the AUC values of 0.78, 0.83 and 0.87, respectively., Discussion: This study showed that plasma metabolites have the potential to match the AUC of well-established AD CSF biomarkers in a relatively small cohort. Further studies in independent cohorts are needed to validate whether this specific panel of blood metabolites can separate AD from controls, and how specific it is for AD as compared with other neurodegenerative disorders., (© 2019 The Authors.)
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- 2019
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50. Discovery and validation of plasma proteomic biomarkers relating to brain amyloid burden by SOMAscan assay.
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Shi L, Westwood S, Baird AL, Winchester L, Dobricic V, Kilpert F, Hong S, Franke A, Hye A, Ashton NJ, Morgan AR, Bos I, Vos SJB, Buckley NJ, Kate MT, Scheltens P, Vandenberghe R, Gabel S, Meersmans K, Engelborghs S, De Roeck EE, Sleegers K, Frisoni GB, Blin O, Richardson JC, Bordet R, Molinuevo JL, Rami L, Wallin A, Kettunen P, Tsolaki M, Verhey F, Lleó A, Alcolea D, Popp J, Peyratout G, Martinez-Lage P, Tainta M, Johannsen P, Teunissen CE, Freund-Levi Y, Frölich L, Legido-Quigley C, Barkhof F, Blennow K, Zetterberg H, Baker S, Morgan BP, Streffer J, Visser PJ, Bertram L, Lovestone S, and Nevado-Holgado AJ
- Subjects
- Age Factors, Aged, Apolipoprotein E4 genetics, Apolipoprotein E4 metabolism, Europe, Female, Humans, Male, Middle Aged, Alzheimer Disease genetics, Alzheimer Disease metabolism, Amyloid metabolism, Biomarkers blood, Brain metabolism, Proteomics
- Abstract
Introduction: Plasma proteins have been widely studied as candidate biomarkers to predict brain amyloid deposition to increase recruitment efficiency in secondary prevention clinical trials for Alzheimer's disease. Most such biomarker studies are targeted to specific proteins or are biased toward high abundant proteins., Methods: 4001 plasma proteins were measured in two groups of participants (discovery group = 516, replication group = 365) selected from the European Medical Information Framework for Alzheimer's disease Multimodal Biomarker Discovery study, all of whom had measures of amyloid., Results: A panel of proteins (n = 44), along with age and apolipoprotein E (APOE) ε4, predicted brain amyloid deposition with good performance in both the discovery group (area under the curve = 0.78) and the replication group (area under the curve = 0.68). Furthermore, a causal relationship between amyloid and tau was confirmed by Mendelian randomization., Discussion: The results suggest that high-dimensional plasma protein testing could be a useful and reproducible approach for measuring brain amyloid deposition., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)
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- 2019
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