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ImportanceIndividuals who are amyloid-positive with subjective cognitive decline and clinical features increasing the likelihood of preclinical Alzheimer disease (SCD+) are at higher risk of developing dementia. Some individuals with SCD+ undergo amyloid-positron emission tomography (PET) as part of research studies and frequently wish to know their amyloid status; however, the disclosure of a positive amyloid-PET result might have psychological risks.ObjectiveTo assess the psychological outcomes of the amyloid-PET result disclosure in individuals with SCD+ and explore which variables are associated with a safer disclosure in individuals who are amyloid positive.Design, Setting, and ParticipantsThis prospective, multicenter study was conducted as part of The Amyloid Imaging to Prevent Alzheimer Disease Diagnostic and Patient Management Study (AMYPAD-DPMS) (recruitment period: from April 2018 to October 2020). The setting was 5 European memory clinics, and participants included patients with SCD+ who underwent amyloid-PET. Statistical analysis was performed from July to October 2022.ExposuresDisclosure of amyloid-PET result.Main Outcomes and MeasuresPsychological outcomes were defined as (1) disclosure related distress, assessed using the Impact of Event Scale–Revised (IES-R; scores of at least 33 indicate probable presence of posttraumatic stress disorder [PTSD]); and (2) anxiety and depression, assessed using the Hospital Anxiety and Depression scale (HADS; scores of at least 15 indicate probable presence of severe mood disorder symptoms).ResultsAfter disclosure, 27 patients with amyloid-positive SCD+ (median [IQR] age, 70 [66-74] years; gender: 14 men [52%]; median [IQR] education: 15 [13 to 17] years, median [IQR] Mini-Mental State Examination [MMSE] score, 29 [28 to 30]) had higher median (IQR) IES-R total score (10 [2 to 14] vs 0 [0 to 2]; P P P P P = .06) and Depression (–1.0 [–2.0 to 0.0] vs –1.0 [–3.0 to 0.0]; P = .46) deltas (score after disclosure – scores at baseline). In patients with amyloid-positive SCD+, despite the small sample size, higher education was associated with lower disclosure-related distress (ρ = –0.43; P = .02) whereas the presence of study partner was associated with higher disclosure-related distress (W = 7.5; P = .03). No participants with amyloid-positive SCD+ showed probable presence of PTSD or severe anxiety or depression symptoms at follow-up.Conclusions and RelevanceThe disclosure of a positive amyloid-PET result to patients with SCD+ was associated with a bigger psychological change, yet such change did not reach the threshold for clinical concern.

Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer's disease (AD), but its validation against markers of neurodegeneration and AD is lacking. Here, imaging-derived measures from the UK Biobank dataset (N=22,661) were used to predict brain-age in 2,314 cognitively unimpaired (CU) individuals at higher risk of AD and mild cognitive impaired (MCI) patients from four independent cohorts with available biomarker data: ALFA+, ADNI, EPAD and OASIS. Brain-age delta was associated with abnormal amyloid-b, more advanced stages (AT) of AD pathology and APOE-e4 status. Brain-age delta was positively associated with plasma neurofilament light, a marker of neurodegeneration, and sex differences in the brain effects of this marker were found. These results validate brain-age delta as a non-invasive marker of biological brain aging in non-demented individuals with abnormal levels of biomarkers of AD and axonal injury. Marc Suárez-Calvet: Horizon 2020 - Research and Innovation Framework Programme 948677, Instituto de Salud Carlos III PI19/00155, La Caixa Foundation 100010434, Horizon 2020 - Research and Innovation Framework Programme 847648 / Juan Domingo Gispert: EU/EFPIA Innovative Medicines Initiative Joint Undertaking AMYPAD 115952 / Marc Suárez-Calvet: La Caixa Foundation 100010434; LCF/PR/ GN17/50300004 / Irene Cumplido-Mayoral: TriBEKa Imaging Platform project TriBEKa-17-519007, Universities and Research Secretariat, Ministry of Business and Knowledge of the Catalan Government 2017-SGR-892 / Juan Domingo Gispert: EIT Digital Grant 2021, Spanish Ministry of Science and Innovation (MCIN)/Spanish Research Agency (AEI) MCIN/AEI /10.13039/501100011033 RTI2018-102261, cofunded by the European Regional Development Fund (FEDER) / Marc Suárez-Calvet: NIHR biomedical research center at UCLH Frederik Barkhof Instituto de Salud Carlos III PI22/00456 / Raffaele Cacciaglia: Spanish Ministry of Science and Innovation (MCIN)/Spanish Research Agency (AEI) MCIN/ AEI/10.13039/501100011033 PID2021-125433OA-100 / Verónica Vilaplana: Spanish Research Agency (AEI) PID2020-116907RB-I00 of the call MCIN/ AEI /10.13039/501100011033 Peer Reviewed Article signat per 27 autors/es: Irene Cumplido-Mayoral, Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; Marina García-Prat, Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; Grégory Operto, Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; Carles Falcon, Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; Mahnaz Shekari, Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; Raffaele Cacciaglia, Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; Marta Milà-Alomà, Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; Luigi Lorenzini, Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands; Silvia Ingala, Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands; Alle Meije Wink, Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands; Henk JMM Mutsaerts, Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands; Carolina Minguillón, Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; Karine Fauria, Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; José Luis Molinuevo, Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; Sven Haller, CIRD Centre d'Imagerie Rive Droite, Geneva, Switzerland; Gael Chetelat, Normandie Univ, UNICAEN, INSERM, U1237, Caen, France; Adam Waldman, Centre for Dementia Prevention, University of Edinburgh, Edinburgh, United Kingdom; Adam J Schwarz, Takeda Pharmaceutical Company Ltd, Cambridge, United States; Frederik Barkhof, Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands; Ivonne Suridjan, Roche Diagnostics International Ltd, Rotkreuz, Switzerland; Gwendlyn Kollmorgen, Roche Diagnostics GmbH, Penzberg, Germany; Anna Bayfield, Roche Diagnostics GmbH, Penzberg, Germany; Henrik Zetterberg, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden; Kaj Blennow, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden; Marc Suárez-Calvet, Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; Verónica Vilaplana, Department of Signal Theory and Communications, Universitat Politècnica de Catalunya, Barcelona, Spain; Juan Domingo Gispert López, Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain

Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer's disease (AD), but its validation against markers of neurodegeneration and AD is lacking. Here, imaging-derived measures from the UK Biobank dataset (N=22,661) were used to predict brain-age in 2,314 cognitively unimpaired (CU) individuals at higher risk of AD and mild cognitive impaired (MCI) patients from four independent cohorts with available biomarker data: ALFA+, ADNI, EPAD, and OASIS. Brain-age delta was associated with abnormal amyloid-β, more advanced stages (AT) of AD pathology and APOE-ε4 status. Brain-age delta was positively associated with plasma neurofilament light, a marker of neurodegeneration, and sex differences in the brain effects of this marker were found. These results validate brain-age delta as a non-invasive marker of biological brain aging in non-demented individuals with abnormal levels of biomarkers of AD and axonal injury.

Supplemental material, sj-pdf-1-jcb-10.1177_0271678X231178993 for Genetic, vascular, and amyloid components of cerebral blood flow in a preclinical population by Beatriz E Padrela, Luigi Lorenzini, Lyduine E Collij, David Vállez García, Emma Coomans, Silvia Ingala, Jori Tomassen, Quinten Deckers, Mahnaz Shekari, Eco JC de Geus, Elsmarieke van de Giessen, Mara ten Kate, Pieter Jelle Visser, Frederik Barkhof, Jan Petr, Anouk den Braber and Henk JMM Mutsaerts in Journal of Cerebral Blood Flow & Metabolism

Purpose: To determine whether the APOE-ε4 allele modulates the relationship between regional β-amyloid (Aβ) accumulation and cognitive change in middle-aged cognitively unimpaired (CU) participants. Methods: The 352 CU participants (mean aged 61.1 [4.7] years) included completed two cognitive assessments (average interval 3.34 years), underwent [18F]flutemetamol Aβ positron emission tomography (PET), T1w magnetic resonance imaging (MRI), as well as APOE genotyping. Global and regional Aβ PET positivity was assessed across five regions-of-interest by visual reading (VR) and regional Centiloids. Linear regression models were developed to examine the interaction between regional and global Aβ PET positivity and APOE-ε4 status on longitudinal cognitive change assessed with the Preclinical Alzheimer's Cognitive Composite (PACC), episodic memory, and executive function, after controlling for age, sex, education, cognitive baseline scores, and hippocampal volume. Results: In total, 57 participants (16.2%) were VR+ of whom 41 (71.9%) were APOE-ε4 carriers. No significant APOE-ε4*global Aβ PET interactions were associated with cognitive change for any cognitive test. However, APOE-ε4 carriers who were VR+ in temporal areas (n = 19 [9.81%], p = 0.04) and in the striatum (n = 8 [4.14%], p = 0.01) exhibited a higher decline in the PACC. The temporal areas findings were replicated when regional PET positivity was determined with Centiloid values. Regionally, VR+ in the striatum was associated with higher memory decline. As for executive function, interactions between APOE-ε4 and regional VR+ were found in temporal and parietal regions, and in the striatum. Conclusion: CU APOE-ε4 carriers with a positive Aβ PET VR in regions known to accumulate amyloid at later stages of the Alzheimer's disease (AD) continuum exhibited a steeper cognitive decline. This work supports the contention that regional VR of Aβ PET might convey prognostic information about future cognitive decline in individuals at higher risk of developing AD. Clinicaltrials: gov Identifier: NCT02485730. Registered 20 June 2015 https://clinicaltrials.gov/ct2/show/NCT02485730 and ClinicalTrials.gov Identifier:NCT02685969. Registered 19 February 2016 https://clinicaltrials.gov/ct2/show/NCT02685969 . The research leading to these results has received funding from “la Caixa” Foundation (LCF/PR/GN17/10300004) and the Alzheimer’s Association and an international anonymous charity foundation through the TriBEKa Imaging Platform project (TriBEKa-17-519007). Additional support has been received from the Universities and Research Secretariat, Ministry of Business and Knowledge of the Catalan Government under grant 2021 SGR 00913. NV-T is funded by a postdoctoral grant, Juan de la Cierva Programme (FJC2018-038085-I), Ministry of Science and Innovation-Spanish State Research Agency. Her research has received additional support of “la Caixa” Foundation (LCF/PR/GN17/10300004) and the Health Department of the Catalan Government (Health Research and Innovation Strategic Plan 2016–2020 Grant SLT002/16/00201). OG-R is supported by the Spanish Ministry of Science, Innovation and Universities (IJC2020-043417-I) and receives funding from the Alzheimer’s Association Research Fellowship Program (2019-AARF-644568). EA-U is supported by Alzheimer’s Association research grants (AARG 2019-AARG-644641, AARG 2019-AARG-644641-RAPID), a “Ramón y Cajal” fellowship (RYC2018-026053-I) and by a grant of the Ministry of Science and Innovation (PID2019-111514RA-I00). MS-C receives funding from the European Research Council under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 948677), the Instituto de Salud Carlos III (PI19/00155), and from a fellowship from “la Caixa” Foundation (ID 100010434) and from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 847648 (LCF/BQ/PR21/11840004). JD-G holds a “Ramón y Cajal” fellowship (RYC-2013-13054).

Background: Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta), as a marker of accelerated/decelerated biological brain aging. Accelerated biological aging has been found in Alzheimer’s disease (AD), but validation against biomarkers of AD and neurodegeneration is lacking. We studied the association between brain-age delta vs biomarkers and risk factors for AD, neurodegeneration, and cerebrovascular disease in non-demented individuals. Furthermore, between-sex differences in the brain areas that better predicted age were sought. Method: We trained XGBoost regressor models to predict brain-age separately for females and males using volumes and cortical thickness in regions of the Desikan-Kiliany atlas (obtained with Freesurfer 6.0) from the UKBioBank cohort (n=22,661). Using this trained model, we estimated brain-age delta in cognitively unimpaired (CU) and mild cognitive impaired (MCI) individuals four independent cohorts: ALFA+ (nCU=380), ADNI (nCU=253, nMCI=498), EPAD (nCU=653, nMCI=155) and OASIS (nCU=407). Chronological age, sex, MMSE and APOE categories were available for all subjects. ALFA+, ADNI and EPAD cohorts included data for AD CSF biomarkers (Aß42 and p-tau) and amyloid-b/tau (AT) staging was performed using pre-established cut-off values, whereas for OASIS amyloid-b was determined by PET. White Matter Hyperintensities (WMH) were available as a marker of small vessel disease and plasma (ALFA+ and ADNI) neurofilament light (NfL) as of neurodegeneration. Linear regression models, including chronological age and sex as covariates were used to identify associations between brain-age delta and biomarkers. We identified the individuals at the 10th and 90th deciles to select those with higher (accelerated) and lower (decelerated) brain-age delta and tested for interactions between age and all the variables on brain-age delta. Result: Between-sex differences were found in the most predictive brain regions (Figure 1). Brain-age delta was positively associated with abnormal amyloid-ß status, advanced AT stages and APOE-e4 carriership. Furthermore, brain-age delta was positively associated with plasma NfL in MCI patients and an interaction between age and plasma NfL was found on brain-age delta of CU individuals (Figure 2). Conclusion: Biological brain-age can be estimated from structural neuroimaging and is associated with biomarkers and risk factors of AD pathology and neurodegeneration in non-demented individuals. This project has received support from European Prevention of Alzheimer’s Dementia (EPAD) grant no. 115736, Edinburgh, United Kingdom. Peer Reviewed La publicació està signada per 27 autors/autores: Irene Cumplido-Mayoral 1,2; Marina Garcia 1; Grégory Operto 1,3,4; Carles Falcon 1,3,5; Mahnaz Shekari 1,2,6; Raffaele Cacciaglia 1,3,4; Marta Milà-Alomà 1,2,3,4; Luigi Lorenzini 7; Silvia Ingala 7; Alle Meije Wink 7; Henk-Jan Mutsaerts 7; Carolina Minguillón 1,3,4; Karine Fauria 1,4; Jose Luis Molinuevo 1,3,4,8; Sven Haller 9; Gael Chetelat 10; Adam Waldman 11; Adam J. Schwarz 12; Frederik Barkhof 7,13; Gwendlyn Kollmorgen 14; Ivonne Suridjan 14; Norbert Wild 14; Henrik Zetterberg 15,16,17,18,19; Kaj Blennow 15,19; Marc Suárez-Calvet 1,3,4,20; Verónica Vilaplana 21; Juan Domingo Gispert 1,3,5; ALFA study 22; ADNI study 23 on Behalf Of The EPAD Consortium 24 // 1 Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain; 2 Universitat Pompeu Fabra, Barcelona, Spain; 3 IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain; 4 Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain; 5 Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain; 6 Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; 7 Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands; 8 Lundbeck A/S, Copenhagen, Denmark; 9 CIRD Centre d’Imagerie Rive Droite, Geneva, Switzerland; 10 Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France; 11 Centre for Dementia Prevention, Edinburgh Imaging, and UK Dementia Research Institute at The University of Edinburgh, Edinburgh, United Kingdom; 12 Takeda Pharmaceutical Company Ltd, Cambridge, MA, USA; 13 Institutes of Neurology and Healthcare Engineering, University College London, London, United Kingdom; 14 Roche Diagnostics International Ltd, Rotkreuz, Switzerland; 15 Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; 16 UK Dementia Research Institute at UCL, London, United Kingdom; 17 Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong; 18 Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; 19 Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden; 20 Servei de Neurologia, Hospital del Mar, Barcelona, Spain; 21 Department of Signal Theory and Communications, Universitat Politècnica de Catalunya, Barcelona, Spain; 22 BarcelonaBeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain; 23 Laboratory of Neuroimaging (LONI), University of Southern California, Los Angeles, CA, USA.

Telomere length (TL) is associated with biological aging, consequently influencing the risk of age-related diseases such as Alzheimer’s disease (AD). We aimed to evaluate the potential causal role of TL in AD endophenotypes (i.e., cognitive performance, N = 2233; brain age and AD-related signatures, N = 1134; and cerebrospinal fluid biomarkers (CSF) of AD and neurodegeneration, N = 304) through a Mendelian randomization (MR) analysis. Our analysis was conducted in the context of the ALFA (ALzheimer and FAmilies) study, a population of cognitively healthy individuals at risk of AD. A total of 20 single nucleotide polymorphisms associated with TL were used to determine the effect of TL on AD endophenotypes. Analyses were adjusted by age, sex, and years of education. Stratified analyses by APOE-ɛ4 status and polygenic risk score of AD were conducted. MR analysis revealed significant associations between genetically predicted longer TL and lower levels of CSF Aβ and higher levels of CSF NfL only in APOE-ɛ4 non-carriers. Moreover, inheriting longer TL was associated with greater cortical thickness in age and AD-related brain signatures and lower levels of CSF p-tau among individuals at a high genetic predisposition to AD. Further observational analyses are warranted to better understand these associations., The project leading to these results has received funding from the Alzheimer’s Association (Grant AARG-19-618265). This project has received funding from Instituto de Salud Carlos III (PI19/00119). Additional support has been received from “la Caixa” Foundation (ID 100010434), under agreement LCF/PR/GN17/50300004, the Alzheimer’s Association and an international anonymous charity foundation through the TriBEKa Imaging Platform project (TriBEKa-17-519007), the Health Department of the Catalan Government (Health Research and Innovation Strategic Plan (PERIS) 2016-2020 grant# SLT002/16/00201), and the Universities and Research Secretariat, Ministry of Business and Knowledge of the Catalan Government under the grant no. 2017-SGR-892. All CRG authors acknowledge the support of the Spanish Ministry of Science, Innovation and Universities to the EMBL partnership, the Centro de Excelencia Severo Ochoa, and the CERCA Programme/Generalitat de Catalunya. NV-T is funded by a post-doctoral grant, Juan de la Cierva Incorporación Programme (IJC2020-043216-I), Ministry of Science and Innovation–Spanish State Research Agency. EMAU is supported by the Spanish Ministry of Science, Innovation and Universities - Spanish State Research Agency (RYC2018-026053-I). MS-C receives funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement no. 948677). MS-C also receives funding from the Instituto de Salud Carlos III (PI19/00155) and from the Spanish Ministry of Science, Innovation and Universities (Juan de la Cierva Programme grant IJC2018-037478-I). HZ is a Wallenberg Scholar supported by grants from the Swedish Research Council (#2018-02532); the European Research Council (#681712); Swedish State Support for Clinical Research (#ALFGBG-720931); the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862); the AD Strategic Fund and the Alzheimer’s Association (#ADSF-21-831376-C, #ADSF-21-831381-C, and #ADSF-21-831377-C); the Olav Thon Foundation; the Erling-Persson Family Foundation, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden (#FO2019-0228); the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860197 (MIRIADE); and the UK Dementia Research Institute at UCL. KB is supported by the Swedish Research Council (#2017-00915); the Alzheimer Drug Discovery Foundation (ADDF), USA (#RDAPB-201809-2016615); the Swedish Alzheimer Foundation (#AF-742881); Hjärnfonden, Sweden (#FO2017-0243); the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-715986); the European Union Joint Program for Neurodegenerative Disorders (JPND2019-466-236); and the National Institute of Health (NIH), USA, (grant #1R01AG068398-01). JDG is supported by the Spanish Ministry of Science and Innovation (RYC-2013-13054). AS-V. is the recipient of an Instituto de Salud Carlos III Miguel Servet II fellowship (CP II 17/00029).