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2,379 results on '"Schott, A.‐M."'

1. Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities: A multicenter study in 3132 memory clinic patients

Author

Biesbroek, J Matthijs, Coenen, Mirthe, DeCarli, Charles, Fletcher, Evan M, Maillard, Pauline M, Initiative, Alzheimer's Disease Neuroimaging, Barkhof, Frederik, Barnes, Josephine, Benke, Thomas, Chen, Christopher PLH, Dal‐Bianco, Peter, Dewenter, Anna, Duering, Marco, Enzinger, Christian, Ewers, Michael, Exalto, Lieza G, Franzmeier, Nicolai, Hilal, Saima, Hofer, Edith, Koek, Huiberdina L, Maier, Andrea B, McCreary, Cheryl R, Papma, Janne M, Paterson, Ross W, Pijnenburg, Yolande AL, Rubinski, Anna, Schmidt, Reinhold, Schott, Jonathan M, Slattery, Catherine F, Smith, Eric E, Sudre, Carole H, Steketee, Rebecca ME, Teunissen, Charlotte E, van den Berg, Esther, van der Flier, Wiesje M, Venketasubramanian, Narayanaswamy, Venkatraghavan, Vikram, Vernooij, Meike W, Wolters, Frank J, Xin, Xu, Kuijf, Hugo J, and Biessels, Geert Jan

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Vascular Cognitive Impairment/Dementia, Brain Disorders, Clinical Research, Acquired Cognitive Impairment, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Alzheimer's Disease Related Dementias (ADRD), Aging, Dementia, Cerebrovascular, Alzheimer's Disease, Neurodegenerative, Neurological, Humans, Female, Middle Aged, Aged, Aged, 80 and over, Male, White Matter, Arteriolosclerosis, Amyloid beta-Peptides, Magnetic Resonance Imaging, amyloid pathology, arteriolosclerosis, dementia, lesion pattern, white matter hyperintensities, Alzheimer's Disease Neuroimaging Initiative, Geriatrics, Clinical sciences, Biological psychology
Abstract

IntroductionWhite matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-β1-42 (Aβ42)-positive status.MethodsIndividual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume.ResultsVRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p

Published
2024

3. Updating the study protocol: Insight 46 – a longitudinal neuroscience sub-study of the MRC National Survey of Health and Development – phases 2 and 3

Author

Murray-Smith, Heidi, Barker, Suzie, Barkhof, Frederik, Barnes, Josephine, Brown, Thomas M., Captur, Gabriella, R.E.Cartlidge, Molly, Cash, David M., Coath, William, Davis, Daniel, Dickson, John C., Groves, James, Hughes, Alun D., James, Sarah-Naomi, Keshavan, Ashvini, Keuss, Sarah E., King-Robson, Josh, Lu, Kirsty, Malone, Ian B., Nicholas, Jennifer M., Rapala, Alicja, Scott, Catherine J., Street, Rebecca, Sudre, Carole H., Thomas, David L., Wong, Andrew, Wray, Selina, Zetterberg, Henrik, Chaturvedi, Nishi, Fox, Nick C., Crutch, Sebastian J., Richards, Marcus, and Schott, Jonathan M.

Published
2024
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6. Previous fracture and subsequent fracture risk: a meta-analysis to update FRAX

Author

Kanis, J.A., Johansson, H., McCloskey, E.V., Liu, E., Åkesson, K.E., Anderson, F.A., Azagra, R., Bager, C.L., Beaudart, C., Bischoff-Ferrari, H.A., Biver, E., Bruyère, O., Cauley, J.A., Center, J.R., Chapurlat, R., Christiansen, C., Cooper, C., Crandall, C.J., Cummings, S.R., da Silva, J.A.P., Dawson-Hughes, B., Diez-Perez, A., Dufour, A.B., Eisman, J.A., Elders, P.J.M., Ferrari, S., Fujita, Y., Fujiwara, S., Glüer, C.-C., Goldshtein, I., Goltzman, D., Gudnason, V., Hall, J., Hans, D., Hoff, M., Hollick, R.J., Huisman, M., Iki, M., Ish-Shalom, S., Jones, G., Karlsson, M.K., Khosla, S., Kiel, D.P., Koh, W.-P., Koromani, F., Kotowicz, M.A., Kröger, H., Kwok, T., Lamy, O., Langhammer, A., Larijani, B., Lippuner, K., Mellström, D., Merlijn, T., Nordström, A., Nordström, P., O’Neill, T.W., Obermayer-Pietsch, B., Ohlsson, C., Orwoll, E.S., Pasco, J.A., Rivadeneira, F., Schott, A.-M., Shiroma, E.J., Siggeirsdottir, K., Simonsick, E.M., Sornay-Rendu, E., Sund, R., Swart, K.M.A., Szulc, P., Tamaki, J., Torgerson, D.J., van Schoor, N.M., van Staa, T.P., Vila, J., Wareham, N.J., Wright, N.C., Yoshimura, N., Zillikens, M.C., Zwart, M., Vandenput, L., Harvey, N.C., Lorentzon, M., and Leslie, W.D.

Published
2023
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7. Diagnosis and Management of Posterior Cortical Atrophy

Author

Yong, Keir XX, Graff-Radford, Jonathan, Ahmed, Samrah, Chapleau, Marianne, Ossenkoppele, Rik, Putcha, Deepti, Rabinovici, Gil D, Suarez-Gonzalez, Aida, Schott, Jonathan M, Crutch, Sebastian, and Harding, Emma

Subjects
Biomedical and Clinical Sciences, Ophthalmology and Optometry, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurodegenerative, Dementia, Brain Disorders, Neurosciences, Alzheimer's Disease, Acquired Cognitive Impairment, Aging, 4.2 Evaluation of markers and technologies, Detection, screening and diagnosis, 4.1 Discovery and preclinical testing of markers and technologies, Good Health and Well Being, Posterior cortical atrophy, Alzheimer's disease, Visual variant Alzheimer's disease, Visual processing, Atypical Alzheimer's disease, Treatment, Alzheimer’s disease, Atypical Alzheimer’s disease, Visual variant Alzheimer’s disease
Abstract

Purpose of reviewThe study aims to provide a summary of recent developments for diagnosing and managing posterior cortical atrophy (PCA). We present current efforts to improve PCA characterisation and recommendations regarding use of clinical, neuropsychological and biomarker methods in PCA diagnosis and management and highlight current knowledge gaps.Recent findingsRecent multi-centre consensus recommendations provide PCA criteria with implications for different management strategies (e.g. targeting clinical features and/or disease). Studies emphasise the preponderance of primary or co-existing Alzheimer's disease (AD) pathology underpinning PCA. Evidence of approaches to manage PCA symptoms is largely derived from small studies.SummaryPCA diagnosis is frequently delayed, and people are likely to receive misdiagnoses of ocular or psychological conditions. Current treatment of PCA is symptomatic - pharmacological and non-pharmacological - and the use of most treatment options is based on small studies or expert opinion. Recommendations for non-pharmacological approaches include interdisciplinary management tailored to the PCA clinical profile - visual-spatial - rather than memory-led, predominantly young onset - and psychosocial implications. Whilst emerging disease-modifying treatments have not been tested in PCA, an accurate and timely diagnosis of PCA and determining underlying pathology is of increasing importance in the advent of disease-modifying therapies for AD and other albeit rare causes of PCA.

Published
2023

8. Spatial distributions of white matter hyperintensities on brain MRI: A pooled analysis of individual participant data from 11 memory clinic cohorts

Author

Coenen, Mirthe, Biessels, Geert Jan, DeCarli, Charles, Fletcher, Evan F, Maillard, Pauline M, Initiative, Alzheimer's Disease Neuroimaging, Barkhof, Frederik, Barnes, Josephine, Benke, Thomas, Boomsma, Jooske MF, Chen, Christopher PLH, Dal-Bianco, Peter, Dewenter, Anna, Duering, Marco, Enzinger, Christian, Ewers, Michael, Exalto, Lieza G, Franzmeier, Nicolai, Groeneveld, Onno, Hilal, Saima, Hofer, Edith, Koek, Huiberdina L, Maier, Andrea B, McCreary, Cheryl R, Papma, Janne M, Paterson, Ross W, Pijnenburg, Yolande AL, Rubinski, Anna, Schmidt, Reinhold, Schott, Jonathan M, Slattery, Catherine F, Smith, Eric E, Sudre, Carole H, Steketee, Rebecca ME, van den Berg, Esther, van der Flier, Wiesje M, Venketasubramanian, Narayanaswamy, Vernooij, Meike W, Wolters, Frank J, Xin, Xu, Biesbroek, J Matthijs, and Kuijf, Hugo J

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Alzheimer's Disease Related Dementias (ADRD), Cerebrovascular, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Machine Learning and Artificial Intelligence, Clinical Research, Acquired Cognitive Impairment, Vascular Cognitive Impairment/Dementia, Aging, Neurodegenerative, Networking and Information Technology R&D (NITRD), Neurosciences, Brain Disorders, Dementia, Neurological, Humans, White Matter, Brain, Magnetic Resonance Imaging, Neuroimaging, Cognitive Dysfunction, Multicenter Studies as Topic, White matter hyperintensities, Brain MRI, Distribution frequencies, Lesion location, Alzheimer's Disease Neuroimaging Initiative, Biological psychology, Clinical and health psychology
Abstract

IntroductionThe spatial distribution of white matter hyperintensities (WMH) on MRI is often considered in the diagnostic evaluation of patients with cognitive problems. In some patients, clinicians may classify WMH patterns as "unusual", but this is largely based on expert opinion, because detailed quantitative information about WMH distribution frequencies in a memory clinic setting is lacking. Here we report voxel wise 3D WMH distribution frequencies in a large multicenter dataset and also aimed to identify individuals with unusual WMH patterns.MethodsIndividual participant data (N = 3525, including 777 participants with subjective cognitive decline, 1389 participants with mild cognitive impairment and 1359 patients with dementia) from eleven memory clinic cohorts, recruited through the Meta VCI Map Consortium, were used. WMH segmentations were provided by participating centers or performed in Utrecht and registered to the Montreal Neurological Institute (MNI)-152 brain template for spatial normalization. To determine WMH distribution frequencies, we calculated WMH probability maps at voxel level. To identify individuals with unusual WMH patterns, region-of-interest (ROI) based WMH probability maps, rule-based scores, and a machine learning method (Local Outlier Factor (LOF)), were implemented.ResultsWMH occurred in 82% of voxels from the white matter template with large variation between subjects. Only a small proportion of the white matter (1.7%), mainly in the periventricular areas, was affected by WMH in at least 20% of participants. A large portion of the total white matter was affected infrequently. Nevertheless, 93.8% of individual participants had lesions in voxels that were affected in less than 2% of the population, mainly located in subcortical areas. Only the machine learning method effectively identified individuals with unusual patterns, in particular subjects with asymmetric WMH distribution or with WMH at relatively rarely affected locations despite common locations not being affected.DiscussionAggregating data from several memory clinic cohorts, we provide a detailed 3D map of WMH lesion distribution frequencies, that informs on common as well as rare localizations. The use of data-driven analysis with LOF can be used to identify unusual patterns, which might serve as an alert that rare causes of WMH should be considered.

Published
2023

9. Exome sequencing identifies rare damaging variants in ATP8B4 and ABCA1 as risk factors for Alzheimer’s disease

Author

Holstege, Henne, Hulsman, Marc, Charbonnier, Camille, Grenier-Boley, Benjamin, Quenez, Olivier, Grozeva, Detelina, van Rooij, Jeroen GJ, Sims, Rebecca, Ahmad, Shahzad, Amin, Najaf, Norsworthy, Penny J, Dols-Icardo, Oriol, Hummerich, Holger, Kawalia, Amit, Amouyel, Philippe, Beecham, Gary W, Berr, Claudine, Bis, Joshua C, Boland, Anne, Bossù, Paola, Bouwman, Femke, Bras, Jose, Campion, Dominique, Cochran, J Nicholas, Daniele, Antonio, Dartigues, Jean-François, Debette, Stéphanie, Deleuze, Jean-François, Denning, Nicola, DeStefano, Anita L, Farrer, Lindsay A, Fernández, Maria Victoria, Fox, Nick C, Galimberti, Daniela, Genin, Emmanuelle, Gille, Johan JP, Le Guen, Yann, Guerreiro, Rita, Haines, Jonathan L, Holmes, Clive, Ikram, M Arfan, Ikram, M Kamran, Jansen, Iris E, Kraaij, Robert, Lathrop, Marc, Lemstra, Afina W, Lleó, Alberto, Luckcuck, Lauren, Mannens, Marcel MAM, Marshall, Rachel, Martin, Eden R, Masullo, Carlo, Mayeux, Richard, Mecocci, Patrizia, Meggy, Alun, Mol, Merel O, Morgan, Kevin, Myers, Richard M, Nacmias, Benedetta, Naj, Adam C, Napolioni, Valerio, Pasquier, Florence, Pastor, Pau, Pericak-Vance, Margaret A, Raybould, Rachel, Redon, Richard, Reinders, Marcel JT, Richard, Anne-Claire, Riedel-Heller, Steffi G, Rivadeneira, Fernando, Rousseau, Stéphane, Ryan, Natalie S, Saad, Salha, Sanchez-Juan, Pascual, Schellenberg, Gerard D, Scheltens, Philip, Schott, Jonathan M, Seripa, Davide, Seshadri, Sudha, Sie, Daoud, Sistermans, Erik A, Sorbi, Sandro, van Spaendonk, Resie, Spalletta, Gianfranco, Tesi, Niccolo’, Tijms, Betty, Uitterlinden, André G, van der Lee, Sven J, Visser, Pieter Jelle, Wagner, Michael, Wallon, David, Wang, Li-San, Zarea, Aline, Clarimon, Jordi, van Swieten, John C, Greicius, Michael D, Yokoyama, Jennifer S, Cruchaga, Carlos, Hardy, John, and Ramirez, Alfredo

Subjects
Biological Sciences, Genetics, Dementia, Alzheimer's Disease, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Human Genome, Prevention, Acquired Cognitive Impairment, Neurodegenerative, Aging, Clinical Research, Biotechnology, Brain Disorders, 2.1 Biological and endogenous factors, Aetiology, Neurological, Humans, Adenosine Triphosphatases, Alzheimer Disease, ATP Binding Cassette Transporter 1, Genome-Wide Association Study, Risk Factors, Exosomes, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Alzheimer's disease (AD), the leading cause of dementia, has an estimated heritability of approximately 70%1. The genetic component of AD has been mainly assessed using genome-wide association studies, which do not capture the risk contributed by rare variants2. Here, we compared the gene-based burden of rare damaging variants in exome sequencing data from 32,558 individuals-16,036 AD cases and 16,522 controls. Next to variants in TREM2, SORL1 and ABCA7, we observed a significant association of rare, predicted damaging variants in ATP8B4 and ABCA1 with AD risk, and a suggestive signal in ADAM10. Additionally, the rare-variant burden in RIN3, CLU, ZCWPW1 and ACE highlighted these genes as potential drivers of respective AD-genome-wide association study loci. Variants associated with the strongest effect on AD risk, in particular loss-of-function variants, are enriched in early-onset AD cases. Our results provide additional evidence for a major role for amyloid-β precursor protein processing, amyloid-β aggregation, lipid metabolism and microglial function in AD.

Published
2022

10. Demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy: an international cohort study and individual participant data meta-analysis

Author

Abdi, Zeinab, Agosta, Federica, Ahmed, Samrah, Alcolea, Daniel, Allen, Isabel Elaine, Allinson, Kieren S.J., Apostolova, Liana G., Arighi, Andrea, Balasa, Mircea, Barkhof, Frederik, Best, John, Boon, Baayla D., Brandt, Katherine D., Brosch, Jared, Burrell, James, Butler, Christopher R., Calandri, Ismael, Caminiti, Silvia Paola, Canu, Elisa, Carrillo, Maria C., Caso, Francesca, Chapleau, Marianne, Chrem Mendez, Patricio, Chu, Min, Crutch, Sebastian, Cordato, Nicholas, Costa, Ana Sofia, Cui, Yue, Dickerson, Bradford, Dickson, Dennis W., Duara, Ranjan, Dubois, Bruno, Eldaief, Mark, Farlow, Martin, Fenoglio, Chiara, Filippi, Massimo, Fliessbach, Klaus, Formaglio, Maïté, Fortea, Juan, Fox, Nick, Foxe, David, Tilikete, Caroline Froment, Frosch, Matthew P., Fumagalli, Giorgio Giulio, Galasko, Douglas, Galimberti, Daniela, Garat, Oscar, Giardinieri, Giulia, Graff-Radford, Jonathan, Graff-Radford, Neill R., Grinberg, Lea, Groot, Colin, Hake, Ann Marie, Hansson, Oskar, Headley, Alison, Hernandez, Micaela, Hochberg, Daisy, Hodges, John R., Hof, Patrick R., Holton, Janice, Hromas, Gabrielle, Gala, Ignacio Illán, Irwin, David J., Jaunmuktane, Zane, Jing, Donglai, Josephs, Keith, Kagerer, Sonja M., Kasuga, Kensaku, Kong, Yu, Kövari, Enikö, Lacombe-Thibault, Mégane, Lleó, Alberto, Laforce, Robert, La Joie, Renaud, Lashley, Tammaryn, Leger, Gabriel, Levin, Netta, Levy, Richard, Liu, Yang, Liu, Li, Lladó Plarrumaní, Albert, Lucente, Diane E., Machulda, Mary M., Magnani, Giuseppe, Magnin, Eloi, Malpetti, Maura, Matthews, Brandy, McGinnis, Scott, Mendez, Mario F., Mesulam, Marsel, Migliaccio, Raffaella, Miklitz, Carolin, Miller, Zachary A., Montembeault, Maxime, Murray, Melissa E., Mundada, Nidhi, Nemes, Sara, Nestor, Peter J., Ocal, Dilek, Ossenkoppele, Rik, Paterson, Ross, Pelak, Victoria, Perani, Daniela, Phillips, Jeffrey, Piguet, Olivier, Pijnenburg, Yolande, Putcha, Deepti, Quimby, Megan, Rabinovici, Gil D., Reetz, Kathrin, Rein, Netaniel, Revesz, Tamas, Rezaii, Neguine, Rodriguez-Porcel, Federico, Rogalski, Emily, Rowe, James B., Ryan, Natalie, Sanchez-Valle, Raquel, Sacchi, Luca, Santos-Santos, Miguel Ángel, Schott, Jonathan M., Seeley, William, Sherman, Janet, Spina, Salvatore, Stomrud, Erik, Sullivan, A. Campbell, Tanner, Jeremy, Tideman, Pontus, Tokutake, Takayoshi, Tondo, Giacomo, Touroutoglou, Alexandra, Tousi, Babak, Vandenberghe, Rik, van der Flier, Wiesje, Walker, Jamie M., Weintraub, Sandra, Whitwell, Jennifer L., Wolk, David A., Wong, Bonnie, Wu, Liyong, Xie, Kexin, Yong, Keir, Apostolova, Liana, Boon, Baayla D C, Grinberg, Lea T, Irwin, David J, Josephs, Keith A, Mendez, Mario F, Mendez, Patricio Chrem, Miller, Zachary A, Murray, Melissa E, Nemes, Sára, Schott, Jonathan M, Sullivan, A Campbell, Walker, Jamie, Whitwell, Jennifer L, Wolk, David A, and Rabinovici, Gil D

Published
2024
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12. Investigating associations between blood metabolites, later life brain imaging measures, and genetic risk for Alzheimer’s disease

Author

Green, Rebecca E., Lord, Jodie, Scelsi, Marzia A., Xu, Jin, Wong, Andrew, Naomi-James, Sarah, Handy, Alex, Gilchrist, Lachlan, Williams, Dylan M., Parker, Thomas D., Lane, Christopher A., Malone, Ian B., Cash, David M., Sudre, Carole H., Coath, William, Thomas, David L., Keuss, Sarah, Dobson, Richard, Legido-Quigley, Cristina, Fox, Nick C., Schott, Jonathan M., Richards, Marcus, and Proitsi, Petroula

Published
2023
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13. Circulating Metabolome and White Matter Hyperintensities in Women and Men

Author

Sliz, Eeva, Shin, Jean, Ahmad, Shahzad, Williams, Dylan M, Frenzel, Stefan, Gauß, Friederike, Harris, Sarah E, Henning, Ann-Kristin, Hernandez, Maria Valdes, Hu, Yi-Han, Jiménez, Beatriz, Sargurupremraj, Muralidharan, Sudre, Carole, Wang, Ruiqi, Wittfeld, Katharina, Yang, Qiong, Wardlaw, Joanna M, Völzke, Henry, Vernooij, Meike W, Schott, Jonathan M, Richards, Marcus, Proitsi, Petroula, Nauck, Matthias, Lewis, Matthew R, Launer, Lenore, Hosten, Norbert, Grabe, Hans J, Ghanbari, Mohsen, Deary, Ian J, Cox, Simon R, Chaturvedi, Nishi, Barnes, Josephine, Rotter, Jerome I, Debette, Stephanie, Ikram, M Arfan, Fornage, Myriam, Paus, Tomas, Seshadri, Sudha, Pausova, Zdenka, and Group, for the NeuroCHARGE Working

Subjects
Epidemiology, Biomedical and Clinical Sciences, Health Sciences, Prevention, Clinical Research, Aging, Aged, Brain, Diabetes Mellitus, Type 2, Female, Humans, Magnetic Resonance Imaging, Male, Metabolome, Middle Aged, White Matter, NeuroCHARGE Working Group, brain, glucuronic acid, hydroxyphenylpyruvate, lipid ratios, lipidomics, lipids, lysophosphatidylcholines, metabolomics, sphingomyelins, white matter, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences, Sports science and exercise
Abstract

BackgroundWhite matter hyperintensities (WMH), identified on T2-weighted magnetic resonance images of the human brain as areas of enhanced brightness, are a major risk factor of stroke, dementia, and death. There are no large-scale studies testing associations between WMH and circulating metabolites.MethodsWe studied up to 9290 individuals (50.7% female, average age 61 years) from 15 populations of 8 community-based cohorts. WMH volume was quantified from T2-weighted or fluid-attenuated inversion recovery images or as hypointensities on T1-weighted images. Circulating metabolomic measures were assessed with mass spectrometry and nuclear magnetic resonance spectroscopy. Associations between WMH and metabolomic measures were tested by fitting linear regression models in the pooled sample and in sex-stratified and statin treatment-stratified subsamples. Our basic models were adjusted for age, sex, age×sex, and technical covariates, and our fully adjusted models were also adjusted for statin treatment, hypertension, type 2 diabetes, smoking, body mass index, and estimated glomerular filtration rate. Population-specific results were meta-analyzed using the fixed-effect inverse variance-weighted method. Associations with false discovery rate (FDR)-adjusted P values (PFDR)

Published
2022

15. New insights into atypical Alzheimer's disease in the era of biomarkers

Author

Graff-Radford, Jonathan, Yong, Keir XX, Apostolova, Liana G, Bouwman, Femke H, Carrillo, Maria, Dickerson, Bradford C, Rabinovici, Gil D, Schott, Jonathan M, Jones, David T, and Murray, Melissa E

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Aging, Brain Disorders, Dementia, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurodegenerative, Alzheimer's Disease, Acquired Cognitive Impairment, Detection, screening and diagnosis, 4.1 Discovery and preclinical testing of markers and technologies, 2.1 Biological and endogenous factors, Aetiology, Neurological, Good Health and Well Being, Age of Onset, Aged, Aged, 80 and over, Alzheimer Disease, Biomarkers, Female, Humans, Male, Middle Aged, Neuroimaging, Neurology & Neurosurgery, Clinical sciences
Abstract

Most patients with Alzheimer's disease present with amnestic problems; however, a substantial proportion, over-represented in young-onset cases, have atypical phenotypes including predominant visual, language, executive, behavioural, or motor dysfunction. In the past, these individuals often received a late diagnosis; however, availability of CSF and PET biomarkers of Alzheimer's disease pathologies and incorporation of atypical forms of Alzheimer's disease into new diagnostic criteria increasingly allows them to be more confidently diagnosed early in their illness. This early diagnosis in turn allows patients to be offered tailored information, appropriate care and support, and individualised treatment plans. These advances will provide improved access to clinical trials, which often exclude atypical phenotypes. Research into atypical Alzheimer's disease has revealed previously unrecognised neuropathological heterogeneity across the Alzheimer's disease spectrum. Neuroimaging, genetic, biomarker, and basic science studies are providing key insights into the factors that might drive selective vulnerability of differing brain networks, with potential mechanistic implications for understanding typical late-onset Alzheimer's disease.

Published
2021

18. Update of the fracture risk prediction tool FRAX: a systematic review of potential cohorts and analysis plan

Author

Vandenput, L., Johansson, H., McCloskey, E. V., Liu, E., Åkesson, K. E., Anderson, F. A., Azagra, R., Bager, C. L., Beaudart, C., Bischoff-Ferrari, H. A., Biver, E., Bruyère, O., Cauley, J. A., Center, J. R., Chapurlat, R., Christiansen, C., Cooper, C., Crandall, C. J., Cummings, S. R., da Silva, J. A. P., Dawson-Hughes, B., Diez-Perez, A., Dufour, A. B., Eisman, J. A., Elders, P. J. M., Ferrari, S., Fujita, Y., Fujiwara, S., Glüer, C.-C., Goldshtein, I., Goltzman, D., Gudnason, V., Hall, J., Hans, D., Hoff, M., Hollick, R. J., Huisman, M., Iki, M., Ish-Shalom, S., Jones, G., Karlsson, M. K., Khosla, S., Kiel, D. P., Koh, W.-P., Koromani, F., Kotowicz, M. A., Kröger, H., Kwok, T., Lamy, O., Langhammer, A., Larijani, B., Lippuner, K., Mellström, D., Merlijn, T., Nordström, A., Nordström, P., O’Neill, T. W., Obermayer-Pietsch, B., Ohlsson, C., Orwoll, E. S., Pasco, J. A., Rivadeneira, F., Schei, B., Schott, A.-M., Shiroma, E. J., Siggeirsdottir, K., Simonsick, E. M., Sornay-Rendu, E., Sund, R., Swart, K. M. A., Szulc, P., Tamaki, J., Torgerson, D. J., van Schoor, N. M., van Staa, T. P., Vila, J., Wareham, N. J., Wright, N. C., Yoshimura, N., Zillikens, M. C., Zwart, M., Harvey, N. C., Lorentzon, M., Leslie, W. D., and Kanis, J. A.

Published
2022
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19. Adulthood cognitive trajectories over 26 years and brain health at 70 years of age: findings from the 1946 British Birth Cohort

Author

James, Sarah-Naomi, Nicholas, Jennifer M., Lu, Kirsty, Keshavan, Ashvini, Lane, Christopher A., Parker, Thomas, Buchanan, Sarah M., Keuss, Sarah E., Murray-Smith, Heidi, Wong, Andrew, Cash, David M., Malone, Ian B., Barnes, Josephine, Sudre, Carole H., Coath, William, Modat, Marc, Ourselin, Sebastien, Crutch, Sebastian J., Kuh, Diana, Fox, Nick C., Schott, Jonathan M., and Richards, Marcus

Published
2023
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21. Longitudinal neuroanatomical and cognitive progression of posterior cortical atrophy.

Author

Firth, Nicholas C, Primativo, Silvia, Marinescu, Razvan-Valentin, Shakespeare, Timothy J, Suarez-Gonzalez, Aida, Lehmann, Manja, Carton, Amelia, Ocal, Dilek, Pavisic, Ivanna, Paterson, Ross W, Slattery, Catherine F, Foulkes, Alexander JM, Ridha, Basil H, Gil-Néciga, Eulogio, Oxtoby, Neil P, Young, Alexandra L, Modat, Marc, Cardoso, M Jorge, Ourselin, Sebastien, Ryan, Natalie S, Miller, Bruce L, Rabinovici, Gil D, Warrington, Elizabeth K, Rossor, Martin N, Fox, Nick C, Warren, Jason D, Alexander, Daniel C, Schott, Jonathan M, Yong, Keir XX, and Crutch, Sebastian J

Subjects
Cerebral Cortex, Humans, Alzheimer Disease, Disease Progression, Magnetic Resonance Imaging, Case-Control Studies, Longitudinal Studies, Neuropsychological Tests, Models, Neurological, Middle Aged, Female, Male, Cognitive Dysfunction, Alzheimer’s disease, brain atrophy, dementia, memory, structural MRI, Alzheimer's disease, Models, Neurological, Neurology & Neurosurgery, Medical and Health Sciences, Psychology and Cognitive Sciences
Abstract

Posterior cortical atrophy is a clinico-radiological syndrome characterized by progressive decline in visual processing and atrophy of posterior brain regions. With the majority of cases attributable to Alzheimer's disease and recent evidence for genetic risk factors specifically related to posterior cortical atrophy, the syndrome can provide important insights into selective vulnerability and phenotypic diversity. The present study describes the first major longitudinal investigation of posterior cortical atrophy disease progression. Three hundred and sixty-one individuals (117 posterior cortical atrophy, 106 typical Alzheimer's disease, 138 controls) fulfilling consensus criteria for posterior cortical atrophy-pure and typical Alzheimer's disease were recruited from three centres in the UK, Spain and USA. Participants underwent up to six annual assessments involving MRI scans and neuropsychological testing. We constructed longitudinal trajectories of regional brain volumes within posterior cortical atrophy and typical Alzheimer's disease using differential equation models. We compared and contrasted the order in which regional brain volumes become abnormal within posterior cortical atrophy and typical Alzheimer's disease using event-based models. We also examined trajectories of cognitive decline and the order in which different cognitive tests show abnormality using the same models. Temporally aligned trajectories for eight regions of interest revealed distinct (P < 0.002) patterns of progression in posterior cortical atrophy and typical Alzheimer's disease. Patients with posterior cortical atrophy showed early occipital and parietal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion leading to tissue loss of comparable extent later. Hippocampal, entorhinal and frontal regions underwent a lower rate of change and never approached the extent of posterior cortical involvement. Patients with typical Alzheimer's disease showed early hippocampal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion. Cognitive models showed tests sensitive to visuospatial dysfunction declined earlier in posterior cortical atrophy than typical Alzheimer's disease whilst tests sensitive to working memory impairment declined earlier in typical Alzheimer's disease than posterior cortical atrophy. These findings indicate that posterior cortical atrophy and typical Alzheimer's disease have distinct sites of onset and different profiles of spatial and temporal progression. The ordering of disease events both motivates investigation of biological factors underpinning phenotypic heterogeneity, and informs the selection of measures for clinical trials in posterior cortical atrophy.

Published
2019

23. New insights into the genetic etiology of Alzheimer’s disease and related dementias

Author

Bellenguez, Céline, Küçükali, Fahri, Jansen, Iris E., Kleineidam, Luca, Moreno-Grau, Sonia, Amin, Najaf, Naj, Adam C., Campos-Martin, Rafael, Grenier-Boley, Benjamin, Andrade, Victor, Holmans, Peter A., Boland, Anne, Damotte, Vincent, van der Lee, Sven J., Costa, Marcos R., Kuulasmaa, Teemu, Yang, Qiong, de Rojas, Itziar, Bis, Joshua C., Yaqub, Amber, Prokic, Ivana, Chapuis, Julien, Ahmad, Shahzad, Giedraitis, Vilmantas, Aarsland, Dag, Garcia-Gonzalez, Pablo, Abdelnour, Carla, Alarcón-Martín, Emilio, Alcolea, Daniel, Alegret, Montserrat, Alvarez, Ignacio, Álvarez, Victoria, Armstrong, Nicola J., Tsolaki, Anthoula, Antúnez, Carmen, Appollonio, Ildebrando, Arcaro, Marina, Archetti, Silvana, Pastor, Alfonso Arias, Arosio, Beatrice, Athanasiu, Lavinia, Bailly, Henri, Banaj, Nerisa, Baquero, Miquel, Barral, Sandra, Beiser, Alexa, Pastor, Ana Belén, Below, Jennifer E., Benchek, Penelope, Benussi, Luisa, Berr, Claudine, Besse, Céline, Bessi, Valentina, Binetti, Giuliano, Bizarro, Alessandra, Blesa, Rafael, Boada, Mercè, Boerwinkle, Eric, Borroni, Barbara, Boschi, Silvia, Bossù, Paola, Bråthen, Geir, Bressler, Jan, Bresner, Catherine, Brodaty, Henry, Brookes, Keeley J., Brusco, Luis Ignacio, Buiza-Rueda, Dolores, Bûrger, Katharina, Burholt, Vanessa, Bush, William S., Calero, Miguel, Cantwell, Laura B., Chene, Geneviève, Chung, Jaeyoon, Cuccaro, Michael L., Carracedo, Ángel, Cecchetti, Roberta, Cervera-Carles, Laura, Charbonnier, Camille, Chen, Hung-Hsin, Chillotti, Caterina, Ciccone, Simona, Claassen, Jurgen A. H. R., Clark, Christopher, Conti, Elisa, Corma-Gómez, Anaïs, Costantini, Emanuele, Custodero, Carlo, Daian, Delphine, Dalmasso, Maria Carolina, Daniele, Antonio, Dardiotis, Efthimios, Dartigues, Jean-François, de Deyn, Peter Paul, de Paiva Lopes, Katia, de Witte, Lot D., Debette, Stéphanie, Deckert, Jürgen, del Ser, Teodoro, Denning, Nicola, DeStefano, Anita, Dichgans, Martin, Diehl-Schmid, Janine, Diez-Fairen, Mónica, Rossi, Paolo Dionigi, Djurovic, Srdjan, Duron, Emmanuelle, Düzel, Emrah, Dufouil, Carole, Eiriksdottir, Gudny, Engelborghs, Sebastiaan, Escott-Price, Valentina, Espinosa, Ana, Ewers, Michael, Faber, Kelley M., Fabrizio, Tagliavini, Nielsen, Sune Fallgaard, Fardo, David W., Farotti, Lucia, Fenoglio, Chiara, Fernández-Fuertes, Marta, Ferrari, Raffaele, Ferreira, Catarina B., Ferri, Evelyn, Fin, Bertrand, Fischer, Peter, Fladby, Tormod, Fließbach, Klaus, Fongang, Bernard, Fornage, Myriam, Fortea, Juan, Foroud, Tatiana M., Fostinelli, Silvia, Fox, Nick C., Franco-Macías, Emlio, Bullido, María J., Frank-García, Ana, Froelich, Lutz, Fulton-Howard, Brian, Galimberti, Daniela, García-Alberca, Jose Maria, García-González, Pablo, Garcia-Madrona, Sebastian, Garcia-Ribas, Guillermo, Ghidoni, Roberta, Giegling, Ina, Giorgio, Giaccone, Goate, Alison M., Goldhardt, Oliver, Gomez-Fonseca, Duber, González-Pérez, Antonio, Graff, Caroline, Grande, Giulia, Green, Emma, Grimmer, Timo, Grünblatt, Edna, Grunin, Michelle, Gudnason, Vilmundur, Guetta-Baranes, Tamar, Haapasalo, Annakaisa, Hadjigeorgiou, Georgios, Haines, Jonathan L., Hamilton-Nelson, Kara L., Hampel, Harald, Hanon, Olivier, Hardy, John, Hartmann, Annette M., Hausner, Lucrezia, Harwood, Janet, Heilmann-Heimbach, Stefanie, Helisalmi, Seppo, Heneka, Michael T., Hernández, Isabel, Herrmann, Martin J., Hoffmann, Per, Holmes, Clive, Holstege, Henne, Vilas, Raquel Huerto, Hulsman, Marc, Humphrey, Jack, Biessels, Geert Jan, Jian, Xueqiu, Johansson, Charlotte, Jun, Gyungah R., Kastumata, Yuriko, Kauwe, John, Kehoe, Patrick G., Kilander, Lena, Ståhlbom, Anne Kinhult, Kivipelto, Miia, Koivisto, Anne, Kornhuber, Johannes, Kosmidis, Mary H., Kukull, Walter A., Kuksa, Pavel P., Kunkle, Brian W., Kuzma, Amanda B., Lage, Carmen, Laukka, Erika J., Launer, Lenore, Lauria, Alessandra, Lee, Chien-Yueh, Lehtisalo, Jenni, Lerch, Ondrej, Lleó, Alberto, Longstreth, Jr, William, Lopez, Oscar, de Munain, Adolfo Lopez, Love, Seth, Löwemark, Malin, Luckcuck, Lauren, Lunetta, Kathryn L., Ma, Yiyi, Macías, Juan, MacLeod, Catherine A., Maier, Wolfgang, Mangialasche, Francesca, Spallazzi, Marco, Marquié, Marta, Marshall, Rachel, Martin, Eden R., Montes, Angel Martín, Rodríguez, Carmen Martínez, Masullo, Carlo, Mayeux, Richard, Mead, Simon, Mecocci, Patrizia, Medina, Miguel, Meggy, Alun, Mehrabian, Shima, Mendoza, Silvia, Menéndez-González, Manuel, Mir, Pablo, Moebus, Susanne, Mol, Merel, Molina-Porcel, Laura, Montrreal, Laura, Morelli, Laura, Moreno, Fermin, Morgan, Kevin, Mosley, Thomas, Nöthen, Markus M., Muchnik, Carolina, Mukherjee, Shubhabrata, Nacmias, Benedetta, Ngandu, Tiia, Nicolas, Gael, Nordestgaard, Børge G., Olaso, Robert, Orellana, Adelina, Orsini, Michela, Ortega, Gemma, Padovani, Alessandro, Paolo, Caffarra, Papenberg, Goran, Parnetti, Lucilla, Pasquier, Florence, Pastor, Pau, Peloso, Gina, Pérez-Cordón, Alba, Pérez-Tur, Jordi, Pericard, Pierre, Peters, Oliver, Pijnenburg, Yolande A. L., Pineda, Juan A., Piñol-Ripoll, Gerard, Pisanu, Claudia, Polak, Thomas, Popp, Julius, Posthuma, Danielle, Priller, Josef, Puerta, Raquel, Quenez, Olivier, Quintela, Inés, Thomassen, Jesper Qvist, Rábano, Alberto, Rainero, Innocenzo, Rajabli, Farid, Ramakers, Inez, Real, Luis M., Reinders, Marcel J. T., Reitz, Christiane, Reyes-Dumeyer, Dolly, Ridge, Perry, Riedel-Heller, Steffi, Riederer, Peter, Roberto, Natalia, Rodriguez-Rodriguez, Eloy, Rongve, Arvid, Allende, Irene Rosas, Rosende-Roca, Maitée, Royo, Jose Luis, Rubino, Elisa, Rujescu, Dan, Sáez, María Eugenia, Sakka, Paraskevi, Saltvedt, Ingvild, Sanabria, Ángela, Sánchez-Arjona, María Bernal, Sanchez-Garcia, Florentino, Juan, Pascual Sánchez, Sánchez-Valle, Raquel, Sando, Sigrid B., Sarnowski, Chloé, Satizabal, Claudia L., Scamosci, Michela, Scarmeas, Nikolaos, Scarpini, Elio, Scheltens, Philip, Scherbaum, Norbert, Scherer, Martin, Schmid, Matthias, Schneider, Anja, Schott, Jonathan M., Selbæk, Geir, Seripa, Davide, Serrano, Manuel, Sha, Jin, Shadrin, Alexey A., Skrobot, Olivia, Slifer, Susan, Snijders, Gijsje J. L., Soininen, Hilkka, Solfrizzi, Vincenzo, Solomon, Alina, Song, Yeunjoo, Sorbi, Sandro, Sotolongo-Grau, Oscar, Spalletta, Gianfranco, Spottke, Annika, Squassina, Alessio, Stordal, Eystein, Tartan, Juan Pablo, Tárraga, Lluís, Tesí, Niccolo, Thalamuthu, Anbupalam, Thomas, Tegos, Tosto, Giuseppe, Traykov, Latchezar, Tremolizzo, Lucio, Tybjærg-Hansen, Anne, Uitterlinden, Andre, Ullgren, Abbe, Ulstein, Ingun, Valero, Sergi, Valladares, Otto, Broeckhoven, Christine Van, Vance, Jeffery, Vardarajan, Badri N., van der Lugt, Aad, Dongen, Jasper Van, van Rooij, Jeroen, van Swieten, John, Vandenberghe, Rik, Verhey, Frans, Vidal, Jean-Sébastien, Vogelgsang, Jonathan, Vyhnalek, Martin, Wagner, Michael, Wallon, David, Wang, Li-San, Wang, Ruiqi, Weinhold, Leonie, Wiltfang, Jens, Windle, Gill, Woods, Bob, Yannakoulia, Mary, Zare, Habil, Zhao, Yi, Zhang, Xiaoling, Zhu, Congcong, Zulaica, Miren, Farrer, Lindsay A., Psaty, Bruce M., Ghanbari, Mohsen, Raj, Towfique, Sachdev, Perminder, Mather, Karen, Jessen, Frank, Ikram, M. Arfan, de Mendonça, Alexandre, Hort, Jakub, Tsolaki, Magda, Pericak-Vance, Margaret A., Amouyel, Philippe, Williams, Julie, Frikke-Schmidt, Ruth, Clarimon, Jordi, Deleuze, Jean-François, Rossi, Giacomina, Seshadri, Sudha, Andreassen, Ole A., Ingelsson, Martin, Hiltunen, Mikko, Sleegers, Kristel, Schellenberg, Gerard D., van Duijn, Cornelia M., Sims, Rebecca, van der Flier, Wiesje M., Ruiz, Agustín, Ramirez, Alfredo, and Lambert, Jean-Charles

Published
2022
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26. Whole genome sequencing for the diagnosis of neurological repeat expansion disorders in the UK: a retrospective diagnostic accuracy and prospective clinical validation study

Author

McDonagh, Ellen M, Rueda, Antonio, Polychronopoulos, Dimitris, Chan, Georgia, Angus-Leppan, Heather, Bhatia, Kailash P, Davison, James E, Festenstein, Richard, Fratta, Pietro, Giunti, Paola, Howard, Robin, Venkata, Laxmi, Laurá, Matilde, McEntagart, Meriel, Menzies, Lara, Morris, Huw, Reilly, Mary M, Robinson, Robert, Rosser, Elisabeth, Faravelli, Francesca, Schrag, Anette, Schott, Jonathan M, Warner, Thomas T, Wood, Nicholas W, Bourn, David, Eggleton, Kelly, Labrum, Robyn, Twiss, Philip, Abbs, Stephen, Santos, Liana, Almheiri, Ghareesa, Sheikh, Isabella, Vandrovcova, Jana, Patch, Christine, Taylor Tavares, Ana Lisa, Hyder, Zerin, Need, Anna, Brittain, Helen, Baple, Emma, Moutsianas, Loukas, Deshpande, Viraj, Perry, Denise L, Ajay, Subramanian S., Chawla, Aditi, Rajan, Vani, Oprych, Kathryn, Chinnery, Patrick F, Douglas, Angela, Wilson, Gill, Ellard, Sian, Temple, I Karen, Mumford, Andrew, McMullan, Dom, Naresh, Kikkeri, Flinter, Frances A, Taylor, Jenny C, Greenhalgh, Lynn, Newman, William, Brennan, Paul, Sayer, John A, Raymond, F Lucy, Chitty, Lyn S, Ambrose, John C., Arumugam, Prabhu, Bleda, Marta, Boardman-Pretty, Freya, Boissiere, Jeanne M., Boustred, Christopher R., Craig, Clare E.H., de Burca, Anna, Devereau, Andrew, Elgar, Greg, Foulger, Rebecca E., Furió-Tarí, Pedro, Hackett, Joanne, Halai, Dina, Hamblin, Angela, Henderson, Shirley, Holman, James, Hubbard, Tim J.P., Jackson, Rob, Jones, Louise J., Kayikci, Melis, Lahnstein, Lea, Lawson, Kay, Leigh, Sarah E.A., Leong, Ivonne U.S., Lopez, Javier F., Maleady-Crowe, Fiona, Mason, Joanne, Mueller, Michael, Murugaesu, Nirupa, Odhams, Chris A., Perez-Gil, Daniel, Pullinger, John, Rahim, Tahrima, Riesgo-Ferreiro, Pablo, Rogers, Tim, Ryten, Mina, Savage, Kevin, Sawant, Kushmita, Siddiq, Afshan, Sieghart, Alexander, Smedley, Damian, Sosinsky, Alona, Spooner, William, Stevens, Helen E., Stuckey, Alexander, Sultana, Razvan, Thompson, Simon R., Tregidgo, Carolyn, Walsh, Emma, Watters, Sarah A., Welland, Matthew J., Williams, Eleanor, Witkowska, Katarzyna, Wood, Suzanne M., Zarowiecki, Magdalena, Ibañez, Kristina, Polke, James, Hagelstrom, R Tanner, Dolzhenko, Egor, Pasko, Dorota, Thomas, Ellen Rachel Amy, Daugherty, Louise C, Kasperaviciute, Dalia, Smith, Katherine R, Deans, Zandra C, Hill, Sue, Fowler, Tom, Scott, Richard H, Hardy, John, Houlden, Henry, Rendon, Augusto, Caulfield, Mark J, Eberle, Michael A, Taft, Ryan J, and Tucci, Arianna

Published
2022
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28. Study of $\eta$ and $\eta'$ photoproduction at MAMI

Author

Kashevarov, V. L., Ott, P., Prakhov, S., Adlarson, P., Afzal, F., Ahmed, Z., Akondi, C. S., Annand, J. R. M., Arends, H. J., Beck, R., Braghieri, A., Briscoe, W. J., Cividini, F., Codling, R., Collicott, C., Costanza, S., Denig, A., Downie, E. J., Dieterle, M., Bondy, M. I. Ferretti, Filkov, L. V., Fix, A., Gardner, S., Garni, S., Glazier, D. I., Glowa, D., Gradl, W., Gurevich, G., Hamilton, D. J., Hornidge, D., Howdle, D., Huber, G. M., Kaeser, A., Kay, S., Keshelashvili, I., Kondratiev, R., Korolija, M., Krusche, B., Linturi, J., Lisin, V., Livingston, K., MacGregor, I. J. D., MacRae, R., Mancell, J., Manley, D. M., Martel, P. P., McGeorge, J. C., McNicol, E., Middleton, D. G., Miskimen, R., Mornacchi, E., Mullen, C., Mushkarenkov, A., Neiser, A., Oberle, M., Ostrick, M., Otte, P. B., Oussena, B., Paudyal, D., Pedroni, P., Polyanski, V. V., Rajabi, A., Robinson, J., Rosner, G., Rostomyan, T., Sarty, A., Schott, D. M., Schumann, S., Sfienti, C., Sokhoyan, V., Spieker, K., Steffen, O., Strandberg, B., Strakovsky, I. I., Strub, Th., Supek, I., Taragin, M. F., Thiel, A., Thiel, M., Tiator, L., Thomas, A., Unverzagt, M., Wagner, S., Watts, D. P., Werthmueller, D., Wettig, J., Witthauer, L., Wolfes, M., Workman, R. L., and Zana, L.

Subjects
Nuclear Experiment, High Energy Physics - Experiment, High Energy Physics - Phenomenology
Abstract

The reactions $\gamma p\to \eta p$ and $\gamma p\to \eta' p$ have been measured from their thresholds up to the center-of-mass energy $W=1.96$GeV with the tagged-photon facilities at the Mainz Microtron, MAMI. Differential cross sections were obtained with unprecedented accuracy, providing fine energy binning and full production-angle coverage. A strong cusp is observed in the total cross section and excitation functions for $\eta$ photoproduction at the energies in vicinity of the $\eta'$ threshold, $W=1896$MeV ($E_\gamma=1447$MeV). This behavior is explained in a revised $\eta$MAID isobar model by a significant branching of the $N(1895)1/2^-$ nucleon resonance to both, $\eta p$ and $\eta' p$, confirming the existence and constraining the properties of this poorly known state.

Published
2017
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29. Personalizing progressive changes to brain structure in Alzheimer's disease using normative modeling.

Author

Verdi, Serena, Rutherford, Saige, Fraza, Charlotte, Tosun, Duygu, Altmann, Andre, Raket, Lars Lau, Schott, Jonathan M., Marquand, Andre F., and Cole, James H.

Abstract

INTRODUCTION: Neuroanatomical normative modeling captures individual variability in Alzheimer's disease (AD). Here we used normative modeling to track individuals' disease progression in people with mild cognitive impairment (MCI) and patients with AD. METHODS: Cortical and subcortical normative models were generated using healthy controls (n ≈ 58k). These models were used to calculate regional z scores in 3233 T1‐weighted magnetic resonance imaging time‐series scans from 1181 participants. Regions with z scores < –1.96 were classified as outliers mapped on the brain and summarized by total outlier count (tOC). RESULTS: tOC increased in AD and in people with MCI who converted to AD and also correlated with multiple non‐imaging markers. Moreover, a higher annual rate of change in tOC increased the risk of progression from MCI to AD. Brain outlier maps identified the hippocampus as having the highest rate of change. DISCUSSION: Individual patients' atrophy rates can be tracked by using regional outlier maps and tOC. Highlights: Neuroanatomical normative modeling was applied to serial Alzheimer's disease (AD) magnetic resonance imaging (MRI) data for the first time.Deviation from the norm (outliers) of cortical thickness or brain volume was computed in 3233 scans.The number of brain‐structure outliers increased over time in people with AD.Patterns of change in outliers varied markedly between individual patients with AD.People with mild cognitive impairment whose outliers increased over time had a higher risk of progression from AD. [ABSTRACT FROM AUTHOR]

Published
2024
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30. Peripheral hearing loss at age 70 predicts brain atrophy and associated cognitive change.

Author

Parker, Thomas D., Hardy, Chris, Keuss, Sarah, Coath, William, Cash, David M., Lu, Kirsty, Nicholas, Jennifer M., James, Sarah-Naomi, Sudre, Carole, Crutch, Sebastian, Bamiou, Doris-Eva, Warren, Jason D., Fox, Nick C., Richards, Marcus, and Schott, Jonathan M.

Subjects
ALZHEIMER'S disease, AUDIOMETRY, SCHOLARSHIPS, CEREBRAL atrophy, RESEARCH institutes, HEARING levels, HEARING
Published
2024
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31. Prevalence of amyloid‐β pathology in distinct variants of primary progressive aphasia

Author

Bergeron, David, Gorno‐Tempini, Maria L, Rabinovici, Gil D, Santos‐Santos, Miguel A, Seeley, William, Miller, Bruce L, Pijnenburg, Yolande, Keulen, M Antoinette, Groot, Colin, van Berckel, Bart NM, van der Flier, Wiesje M, Scheltens, Philip, Rohrer, Jonathan D, Warren, Jason D, Schott, Jonathan M, Fox, Nick C, Sanchez‐Valle, Raquel, Grau‐Rivera, Oriol, Gelpi, Ellen, Seelaar, Harro, Papma, Janne M, van Swieten, John C, Hodges, John R, Leyton, Cristian E, Piguet, Olivier, Rogalski, Emily J, Mesulam, Marsel M, Koric, Lejla, Kristensen, Nora, Pariente, Jeéreémie, Dickerson, Bradford, Mackenzie, Ian R, Hsiung, Ging‐Yuek R, Belliard, Serge, Irwin, David J, Wolk, David A, Grossman, Murray, Jones, Matthew, Harris, Jennifer, Mann, David, Snowden, Julie S, Chrem‐Mendez, Patricio, Calandri, Ismael L, Amengual, Alejandra A, Miguet‐Alfonsi, Carole, Magnin, Eloi, Magnani, Giuseppe, Santangelo, Roberto, Deramecourt, Vincent, Pasquier, Florence, Mattsson, Niklas, Nilsson, Christer, Hansson, Oskar, Keith, Julia, Masellis, Mario, Black, Sandra E, Matías‐Guiu, Jordi A, Cabrera‐Martin, María‐Nieves, Paquet, Claire, Dumurgier, Julien, Teichmann, Marc, Sarazin, Marie, Bottlaender, Michel, Dubois, Bruno, Rowe, Christopher C, Villemagne, Victor L, Vandenberghe, Rik, Granadillo, Elias, Teng, Edmond, Mendez, Mario, Meyer, Philipp T, Frings, Lars, Lleó, Alberto, Blesa, Rafael, Fortea, Juan, Seo, Sang Won, Diehl‐Schmid, Janine, Grimmer, Timo, Frederiksen, Kristian Steen, Sánchez‐Juan, Pascual, Chételat, Gaël, Jansen, Willemijn, Bouchard, Rémi W, Laforce, Robert Jr, Visser, Pieter Jelle, and Ossenkoppele, Rik

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Dementia, Rare Diseases, Aging, Neurodegenerative, Brain Disorders, Frontotemporal Dementia (FTD), Clinical Research, Aphasia, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Acquired Cognitive Impairment, Alzheimer's Disease Related Dementias (ADRD), Genetics, Alzheimer's Disease, 4.2 Evaluation of markers and technologies, Aetiology, Detection, screening and diagnosis, 2.1 Biological and endogenous factors, Neurological, Age Factors, Aged, Aged, 80 and over, Amyloid beta-Peptides, Aphasia, Primary Progressive, Apolipoproteins E, Brain, Female, Genotype, Humans, Male, Middle Aged, Prevalence, Neurology & Neurosurgery, Clinical sciences
Abstract

ObjectiveTo estimate the prevalence of amyloid positivity, defined by positron emission tomography (PET)/cerebrospinal fluid (CSF) biomarkers and/or neuropathological examination, in primary progressive aphasia (PPA) variants.MethodsWe conducted a meta-analysis with individual participant data from 1,251 patients diagnosed with PPA (including logopenic [lvPPA, n = 443], nonfluent [nfvPPA, n = 333], semantic [svPPA, n = 401], and mixed/unclassifiable [n = 74] variants of PPA) from 36 centers, with a measure of amyloid-β pathology (CSF [n = 600], PET [n = 366], and/or autopsy [n = 378]) available. The estimated prevalence of amyloid positivity according to PPA variant, age, and apolipoprotein E (ApoE) ε4 status was determined using generalized estimating equation models.ResultsAmyloid-β positivity was more prevalent in lvPPA (86%) than in nfvPPA (20%) or svPPA (16%; p

Published
2018

32. Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference.

Author

Young, Alexandra L, Marinescu, Razvan V, Oxtoby, Neil P, Bocchetta, Martina, Yong, Keir, Firth, Nicholas C, Cash, David M, Thomas, David L, Dick, Katrina M, Cardoso, Jorge, van Swieten, John, Borroni, Barbara, Galimberti, Daniela, Masellis, Mario, Tartaglia, Maria Carmela, Rowe, James B, Graff, Caroline, Tagliavini, Fabrizio, Frisoni, Giovanni B, Laforce, Robert, Finger, Elizabeth, de Mendonça, Alexandre, Sorbi, Sandro, Warren, Jason D, Crutch, Sebastian, Fox, Nick C, Ourselin, Sebastien, Schott, Jonathan M, Rohrer, Jonathan D, Alexander, Daniel C, Genetic FTD Initiative (GENFI), and Alzheimer’s Disease Neuroimaging Initiative (ADNI)

Subjects
Genetic FTD Initiative, Alzheimer’s Disease Neuroimaging Initiative, Humans, Alzheimer Disease, Neurodegenerative Diseases, Reproducibility of Results, Genotype, Phenotype, Models, Neurological, Time Factors, Frontotemporal Dementia, Models, Neurological, Alzheimer's Disease, Brain Disorders, Genetics, Aging, Neurodegenerative, Acquired Cognitive Impairment, Dementia, Alzheimer's Disease including Alzheimer's Disease Related Dementias, Neurosciences, Rare Diseases, 2.1 Biological and endogenous factors, MD Multidisciplinary
Abstract

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique-Subtype and Stage Inference (SuStaIn)-able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer's disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 × 10-4) or temporal stage (p = 3.96 × 10-5). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine.

Published
2018

33. Analysis of shared heritability in common disorders of the brain

Author

Consortium, The Brainstorm, Anttila, Verneri, Bulik-Sullivan, Brendan, Finucane, Hilary K, Walters, Raymond K, Bras, Jose, Duncan, Laramie, Escott-Price, Valentina, Falcone, Guido J, Gormley, Padhraig, Malik, Rainer, Patsopoulos, Nikolaos A, Ripke, Stephan, Wei, Zhi, Yu, Dongmei, Lee, Phil H, Turley, Patrick, Grenier-Boley, Benjamin, Chouraki, Vincent, Kamatani, Yoichiro, Berr, Claudine, Letenneur, Luc, Hannequin, Didier, Amouyel, Philippe, Boland, Anne, Deleuze, Jean-François, Duron, Emmanuelle, Vardarajan, Badri N, Reitz, Christiane, Goate, Alison M, Huentelman, Matthew J, Kamboh, M Ilyas, Larson, Eric B, Rogaeva, Ekaterina, St George-Hyslop, Peter, Hakonarson, Hakon, Kukull, Walter A, Farrer, Lindsay A, Barnes, Lisa L, Beach, Thomas G, Demirci, F Yesim, Head, Elizabeth, Hulette, Christine M, Jicha, Gregory A, Kauwe, John SK, Kaye, Jeffrey A, Leverenz, James B, Levey, Allan I, Lieberman, Andrew P, Pankratz, Vernon S, Poon, Wayne W, Quinn, Joseph F, Saykin, Andrew J, Schneider, Lon S, Smith, Amanda G, Sonnen, Joshua A, Stern, Robert A, Van Deerlin, Vivianna M, Van Eldik, Linda J, Harold, Denise, Russo, Giancarlo, Rubinsztein, David C, Bayer, Anthony, Tsolaki, Magda, Proitsi, Petra, Fox, Nick C, Hampel, Harald, Owen, Michael J, Mead, Simon, Passmore, Peter, Morgan, Kevin, Nöthen, Markus M, Schott, Jonathan M, Rossor, Martin, Lupton, Michelle K, Hoffmann, Per, Kornhuber, Johannes, Lawlor, Brian, McQuillin, Andrew, Al-Chalabi, Ammar, Bis, Joshua C, Ruiz, Agustin, Boada, Mercè, Seshadri, Sudha, Beiser, Alexa, Rice, Kenneth, van der Lee, Sven J, De Jager, Philip L, Geschwind, Daniel H, Riemenschneider, Matthias, Riedel-Heller, Steffi, Rotter, Jerome I, Ransmayr, Gerhard, Hyman, Bradley T, Cruchaga, Carlos, Alegret, Montserrat, Winsvold, Bendik, Palta, Priit, Farh, Kai-How, and Cuenca-Leon, Ester

Subjects
Biological Sciences, Genetics, Biological Psychology, Health Sciences, Psychology, Clinical Research, Mental Health, Human Genome, Brain Disorders, Neurosciences, Mental Illness, 2.1 Biological and endogenous factors, Neurological, Mental health, Brain Diseases, Genetic Variation, Genome-Wide Association Study, Humans, Mental Disorders, Phenotype, Quantitative Trait, Heritable, Risk Factors, Brainstorm Consortium, General Science & Technology
Abstract

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Published
2018

35. Cerebrospinal fluid neurofilament light chain profiling and quantitation in neurological diseases

Author

Leckey, Claire A, primary, Coulton, John B, additional, Giovannucci, Tatiana A, additional, He, Yingxin, additional, Aslanyan, Aram, additional, Laban, Rhiannon, additional, Heslegrave, Amanda, additional, Doykov, Ivan, additional, Ammoscato, Francesca, additional, Chataway, Jeremy, additional, De Angelis, Floriana, additional, Gnanapavan, Sharmilee, additional, Byrne, Lauren M, additional, Schott, Jonathan M, additional, Wild, Edward J, additional, Barthelémy, Nicolas R, additional, Zetterberg, Henrik, additional, Wray, Selina, additional, Bateman, Randall J, additional, Mills, Kevin, additional, and Paterson, Ross W, additional

Published
2024
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38. Antiphospholipid antibodies and neurological manifestations in acute COVID-19: A single-centre cross-sectional study

Author

Benjamin, Laura A., Paterson, Ross W., Moll, Rachel, Pericleous, Charis, Brown, Rachel, Mehta, Puja R., Athauda, Dilan, Ziff, Oliver J., Heaney, Judith, Checkley, Anna M., Houlihan, Catherine F., Chou, Michael, Heslegrave, Amanda J., Chandratheva, Arvind, Michael, Benedict D., Blennow, Kaj, Vivekanandam, Vinojini, Foulkes, Alexander, Mummery, Catherine J., Lunn, Michael P., Keddie, Stephen, Spyer, Moira J., Mckinnon, Tom, Hart, Melanie, Carletti, Francesco, Jäger, Hans Rolf, Manji, Hadi, Zandi, Michael S., Werring, David J., Nastouli, Eleni, Simister, Robert, Solomon, Tom, Zetterberg, Henrik, Schott, Jonathan M., Cohen, Hannah, and Efthymiou, Maria

Published
2021
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39. The Dementias Platform UK (DPUK) Data Portal

Author

Bauermeister, Sarah, Orton, Christopher, Thompson, Simon, Barker, Roger A., Bauermeister, Joshua R., Ben-Shlomo, Yoav, Brayne, Carol, Burn, David, Campbell, Archie, Calvin, Catherine, Chandran, Siddharthan, Chaturvedi, Nishi, Chêne, Geneviève, Chessell, Iain P., Corbett, Anne, Davis, Daniel H. J., Denis, Mike, Dufouil, Carole, Elliott, Paul, Fox, Nick, Hill, Derek, Hofer, Scott M., Hu, Michele T., Jindra, Christoph, Kee, Frank, Kim, Chi-Hun, Kim, Changsoo, Kivimaki, Mika, Koychev, Ivan, Lawson, Rachael A., Linden, Gerry J., Lyons, Ronan A., Mackay, Clare, Matthews, Paul M., McGuiness, Bernadette, Middleton, Lefkos, Moody, Catherine, Moore, Katrina, Na, Duk L., O’Brien, John T., Ourselin, Sebastien, Paranjothy, Shantini, Park, Ki-Soo, Porteous, David J., Richards, Marcus, Ritchie, Craig W., Rohrer, Jonathan D., Rossor, Martin N., Rowe, James B., Scahill, Rachael, Schnier, Christian, Schott, Jonathan M., Seo, Sang W., South, Matthew, Steptoe, Matthew, Tabrizi, Sarah J., Tales, Andrea, Tillin, Therese, Timpson, Nicholas J., Toga, Arthur W., Visser, Pieter-Jelle, Wade-Martins, Richard, Wilkinson, Tim, Williams, Julie, Wong, Andrew, and Gallacher, John E. J.

Published
2020

40. Dissociable effects of APOE ε4 and β-amyloid pathology on visual working memory

Author

Lu, Kirsty, Nicholas, Jennifer M., Pertzov, Yoni, Grogan, John, Husain, Masud, Pavisic, Ivanna M., James, Sarah-Naomi, Parker, Thomas D., Lane, Christopher A., Keshavan, Ashvini, Keuss, Sarah E., Buchanan, Sarah M., Murray-Smith, Heidi, Cash, David M., Malone, Ian B., Sudre, Carole H., Coath, William, Wong, Andrew, Henley, Susie M. D., Fox, Nick C., Richards, Marcus, Schott, Jonathan M., and Crutch, Sebastian J.

Published
2021
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42. Consensus classification of posterior cortical atrophy

Author

Crutch, Sebastian J, Schott, Jonathan M, Rabinovici, Gil D, Murray, Melissa, Snowden, Julie S, van der Flier, Wiesje M, Dickerson, Bradford C, Vandenberghe, Rik, Ahmed, Samrah, Bak, Thomas H, Boeve, Bradley F, Butler, Christopher, Cappa, Stefano F, Ceccaldi, Mathieu, de Souza, Leonardo Cruz, Dubois, Bruno, Felician, Olivier, Galasko, Douglas, Graff‐Radford, Jonathan, Graff‐Radford, Neill R, Hof, Patrick R, Krolak‐Salmon, Pierre, Lehmann, Manja, Magnin, Eloi, Mendez, Mario F, Nestor, Peter J, Onyike, Chiadi U, Pelak, Victoria S, Pijnenburg, Yolande, Primativo, Silvia, Rossor, Martin N, Ryan, Natalie S, Scheltens, Philip, Shakespeare, Timothy J, González, Aida Suárez, Tang‐Wai, David F, Yong, Keir XX, Carrillo, Maria, Fox, Nick C, and Area, Alzheimer's Association ISTAART Atypical Alzheimer's Disease and Associated Syndromes Professional Interest

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Aging, Rare Diseases, Neurosciences, Neurodegenerative, Neurological, Brain, Brain Diseases, Humans, Posterior cortical atrophy, Alzheimer's disease, Clinico-radiological syndrome, Pathophysiology, Biomarker, Alzheimer's Association ISTAART Atypical Alzheimer's Disease and Associated Syndromes Professional Interest Area, Geriatrics, Clinical sciences, Biological psychology
Abstract

IntroductionA classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings.MethodsConsensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA.ResultsA three-level classification framework for PCA is described comprising both syndrome- and disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum.DiscussionThere was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work.

Published
2017

43. A meta-analysis of previous falls and subsequent fracture risk in cohort studies.

Author

Vandenput, L, Johansson, H, McCloskey, EV, Liu, E, Schini, M, Åkesson, KE, Anderson, FA, Azagra, R, Bager, CL, Beaudart, C, Bischoff-Ferrari, HA, Biver, E, Bruyère, O, Cauley, JA, Center, JR, Chapurlat, R, Christiansen, C, Cooper, C, Crandall, CJ, Cummings, SR, da Silva, JAP, Dawson-Hughes, B, Diez-Perez, A, Dufour, AB, Eisman, JA, Elders, PJM, Ferrari, S, Fujita, Y, Fujiwara, S, Glüer, C-C, Goldshtein, I, Goltzman, D, Gudnason, V, Hall, J, Hans, D, Hoff, M, Hollick, RJ, Huisman, M, Iki, M, Ish-Shalom, S, Jones, G, Karlsson, MK, Khosla, S, Kiel, DP, Koh, W-P, Koromani, F, Kotowicz, MA, Kröger, H, Kwok, T, Lamy, O, Langhammer, A, Larijani, B, Lippuner, K, McGuigan, FEA, Mellström, D, Merlijn, T, Nguyen, TV, Nordström, A, Nordström, P, O'Neill, TW, Obermayer-Pietsch, B, Ohlsson, C, Orwoll, ES, Pasco, JA, Rivadeneira, F, Schott, A-M, Shiroma, EJ, Siggeirsdottir, K, Simonsick, EM, Sornay-Rendu, E, Sund, R, Swart, KMA, Szulc, P, Tamaki, J, Torgerson, DJ, van Schoor, NM, van Staa, TP, Vila, J, Wareham, NJ, Wright, NC, Yoshimura, N, Zillikens, M, Zwart, M, Harvey, NC, Lorentzon, M, Leslie, WD, Kanis, JA, Vandenput, L, Johansson, H, McCloskey, EV, Liu, E, Schini, M, Åkesson, KE, Anderson, FA, Azagra, R, Bager, CL, Beaudart, C, Bischoff-Ferrari, HA, Biver, E, Bruyère, O, Cauley, JA, Center, JR, Chapurlat, R, Christiansen, C, Cooper, C, Crandall, CJ, Cummings, SR, da Silva, JAP, Dawson-Hughes, B, Diez-Perez, A, Dufour, AB, Eisman, JA, Elders, PJM, Ferrari, S, Fujita, Y, Fujiwara, S, Glüer, C-C, Goldshtein, I, Goltzman, D, Gudnason, V, Hall, J, Hans, D, Hoff, M, Hollick, RJ, Huisman, M, Iki, M, Ish-Shalom, S, Jones, G, Karlsson, MK, Khosla, S, Kiel, DP, Koh, W-P, Koromani, F, Kotowicz, MA, Kröger, H, Kwok, T, Lamy, O, Langhammer, A, Larijani, B, Lippuner, K, McGuigan, FEA, Mellström, D, Merlijn, T, Nguyen, TV, Nordström, A, Nordström, P, O'Neill, TW, Obermayer-Pietsch, B, Ohlsson, C, Orwoll, ES, Pasco, JA, Rivadeneira, F, Schott, A-M, Shiroma, EJ, Siggeirsdottir, K, Simonsick, EM, Sornay-Rendu, E, Sund, R, Swart, KMA, Szulc, P, Tamaki, J, Torgerson, DJ, van Schoor, NM, van Staa, TP, Vila, J, Wareham, NJ, Wright, NC, Yoshimura, N, Zillikens, M, Zwart, M, Harvey, NC, Lorentzon, M, Leslie, WD, and Kanis, JA

Abstract

UNLABELLED: The relationship between self-reported falls and fracture risk was estimated in an international meta-analysis of individual-level data from 46 prospective cohorts. Previous falls were associated with an increased fracture risk in women and men and should be considered as an additional risk factor in the FRAX® algorithm. INTRODUCTION: Previous falls are a well-documented risk factor for subsequent fracture but have not yet been incorporated into the FRAX algorithm. The aim of this study was to evaluate, in an international meta-analysis, the association between previous falls and subsequent fracture risk and its relation to sex, age, duration of follow-up, and bone mineral density (BMD). METHODS: The resource comprised 906,359 women and men (66.9% female) from 46 prospective cohorts. Previous falls were uniformly defined as any fall occurring during the previous year in 43 cohorts; the remaining three cohorts had a different question construct. The association between previous falls and fracture risk (any clinical fracture, osteoporotic fracture, major osteoporotic fracture, and hip fracture) was examined using an extension of the Poisson regression model in each cohort and each sex, followed by random-effects meta-analyses of the weighted beta coefficients. RESULTS: Falls in the past year were reported in 21.4% of individuals. During a follow-up of 9,102,207 person-years, 87,352 fractures occurred of which 19,509 were hip fractures. A previous fall was associated with a significantly increased risk of any clinical fracture both in women (hazard ratio (HR) 1.42, 95% confidence interval (CI) 1.33-1.51) and men (HR 1.53, 95% CI 1.41-1.67). The HRs were of similar magnitude for osteoporotic, major osteoporotic fracture, and hip fracture. Sex significantly modified the association between previous fall and fracture risk, with predictive values being higher in men than in women (e.g., for major osteoporotic fracture, HR 1.53 (95% CI 1.27-1.84) in men vs. HR 1

Published
2024

44. A meta-analysis of previous falls and subsequent fracture risk in cohort studies

Author

Vandenput, L., Johansson, H., McCloskey, E. V., Liu, E., Schini, M., Åkesson, K.E., Anderson, F. A., Azagra, R., Bager, C. L., Beaudart, C., Bischoff-Ferrari, H. A., Biver, E., Bruyère, O., Cauley, J. A., Center, J. R., Chapurlat, R., Christiansen, C., Cooper, C., Crandall, C. J., Cummings, S. R., da Silva, J. A. P., Dawson-Hughes, B., Diez-Perez, A., Dufour, A. B., Eisman, J. A., Elders, P. J. M., Ferrari, S., Fujita, Y., Fujiwara, S., Glüer, C. -C, Goldshtein, I., Goltzman, D., Gudnason, V., Hall, J., Hans, D., Hoff, M., Hollick, R. J., Huisman, M., Iki, M., Ish-Shalom, S., Jones, G., Karlsson, M. K., Khosla, S., Kiel, D. P., Koh, W. -P, Koromani, F., Kotowicz, M. A., Kröger, H., Kwok, T., Lamy, O., Langhammer, A., Larijani, B., Lippuner, K., McGuigan, F. E. A., Mellström, D., Merlijn, T., Nguyen, T. V., Nordström, Anna, Nordström, P., O’Neill, T. W., Obermayer-Pietsch, B., Ohlsson, C., Orwoll, E. S., Pasco, J. A., Rivadeneira, F., Schott, A. -M, Shiroma, E. J., Siggeirsdottir, K., Simonsick, E. M., Sornay-Rendu, E., Sund, R., Swart, K. M. A., Szulc, P., Tamaki, J., Torgerson, D. J., van Schoor, N. M., van Staa, T. P., Vila, J., Wareham, N. J., Wright, N. C., Yoshimura, N., Zillikens, M. C., Zwart, M., Harvey, N. C., Lorentzon, M., Leslie, W. D., Kanis, J. A., Vandenput, L., Johansson, H., McCloskey, E. V., Liu, E., Schini, M., Åkesson, K.E., Anderson, F. A., Azagra, R., Bager, C. L., Beaudart, C., Bischoff-Ferrari, H. A., Biver, E., Bruyère, O., Cauley, J. A., Center, J. R., Chapurlat, R., Christiansen, C., Cooper, C., Crandall, C. J., Cummings, S. R., da Silva, J. A. P., Dawson-Hughes, B., Diez-Perez, A., Dufour, A. B., Eisman, J. A., Elders, P. J. M., Ferrari, S., Fujita, Y., Fujiwara, S., Glüer, C. -C, Goldshtein, I., Goltzman, D., Gudnason, V., Hall, J., Hans, D., Hoff, M., Hollick, R. J., Huisman, M., Iki, M., Ish-Shalom, S., Jones, G., Karlsson, M. K., Khosla, S., Kiel, D. P., Koh, W. -P, Koromani, F., Kotowicz, M. A., Kröger, H., Kwok, T., Lamy, O., Langhammer, A., Larijani, B., Lippuner, K., McGuigan, F. E. A., Mellström, D., Merlijn, T., Nguyen, T. V., Nordström, Anna, Nordström, P., O’Neill, T. W., Obermayer-Pietsch, B., Ohlsson, C., Orwoll, E. S., Pasco, J. A., Rivadeneira, F., Schott, A. -M, Shiroma, E. J., Siggeirsdottir, K., Simonsick, E. M., Sornay-Rendu, E., Sund, R., Swart, K. M. A., Szulc, P., Tamaki, J., Torgerson, D. J., van Schoor, N. M., van Staa, T. P., Vila, J., Wareham, N. J., Wright, N. C., Yoshimura, N., Zillikens, M. C., Zwart, M., Harvey, N. C., Lorentzon, M., Leslie, W. D., and Kanis, J. A.

Abstract

Summary: The relationship between self-reported falls and fracture risk was estimated in an international meta-analysis of individual-level data from 46 prospective cohorts. Previous falls were associated with an increased fracture risk in women and men and should be considered as an additional risk factor in the FRAX® algorithm. Introduction: Previous falls are a well-documented risk factor for subsequent fracture but have not yet been incorporated into the FRAX algorithm. The aim of this study was to evaluate, in an international meta-analysis, the association between previous falls and subsequent fracture risk and its relation to sex, age, duration of follow-up, and bone mineral density (BMD). Methods: The resource comprised 906,359 women and men (66.9% female) from 46 prospective cohorts. Previous falls were uniformly defined as any fall occurring during the previous year in 43 cohorts; the remaining three cohorts had a different question construct. The association between previous falls and fracture risk (any clinical fracture, osteoporotic fracture, major osteoporotic fracture, and hip fracture) was examined using an extension of the Poisson regression model in each cohort and each sex, followed by random-effects meta-analyses of the weighted beta coefficients. Results: Falls in the past year were reported in 21.4% of individuals. During a follow-up of 9,102,207 person-years, 87,352 fractures occurred of which 19,509 were hip fractures. A previous fall was associated with a significantly increased risk of any clinical fracture both in women (hazard ratio (HR) 1.42, 95% confidence interval (CI) 1.33–1.51) and men (HR 1.53, 95% CI 1.41–1.67). The HRs were of similar magnitude for osteoporotic, major osteoporotic fracture, and hip fracture. Sex significantly modified the association between previous fall and fracture risk, with predictive values being higher in men than in women (e.g., for major osteoporotic fracture, HR 1.53 (95% CI 1.27–1.84) in men vs. HR 1.32

Published
2024
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45. Measurement of pi^0 photoproduction on the proton at MAMI C

Author

Adlarson, P., Afzal, F., Akondi, C. S., Annand, J. R. M., Arends, H. J., Azimov, Ya. I., Beck, R., Borisov, N., Braghieri, A., Briscoe, W. J., Cherepnya, S., Cividini, F., Collicott, C., Costanza, S., Denig, A., Downie, E. J., Dieterle, M., Bondy, M. I. Ferretti, Fil'kov, L. V., Fix, A., Gardner, S., Garni, S., Glazier, D. I., Glowa, D., Gradl, W., Gurevich, G., Hamilton, D. J., Hornidge, D., Huber, G. M., Käser, A., Kashevarov, V. L., Kay, S., Keshelashvili, I., Kondratiev, R., Korolija, M., Krusche, B., Kulikov, V. V., Lazarev, A., Linturi, J., Lisin, V., Livingston, K., MacGregor, I. J. D., Manley, D. M., Martel, P. P., Martemianov, M., McGeorge, J. C., Meyer, W., Middleton, D. G., Miskimen, R., Mushkarenkov, A., Neganov, A., Neiser, A., Oberle, M., Ostrick, M., Ott, P., Otte, P. B., Oussena, B., Paudyal, D., Pedroni, P., Polonski, A., Polyanski, V. V., Prakhov, S., Rajabi, A., Reicherz, G., Ron, G., Rostomyan, T., Sarty, A., Schott, D. M., Schumann, S., Sfienti, C., Sokhoyan, V., Spieker, K., Steffen, O., Strakovsky, I. I., Strub, Th., Supek, I., Taragin, M. F., Thiel, A., Thiel, M., Tiator, L., Thomas, A., Unverzagt, M., Usov, Yu. A., Wagner, S., Watts, D. P., Werthmüller, D., Wettig, J., Witthauer, L., Wolfes, M., Workman, R. L., and Zana, L. A.

Subjects
High Energy Physics - Experiment, Nuclear Experiment
Abstract

Differential cross sections for the gamma p -> pi^0 p reaction have been measured with the A2 tagged-photon facilities at the Mainz Microtron, MAMI C, up to the center-of-mass energy W=1.9 GeV. The new results, obtained with a fine energy and angular binning, increase the existing quantity of pi^0 photoproduction data by ~47%. Owing to the unprecedented statistical accuracy and the full angular coverage, the results are sensitive to high partial-wave amplitudes. This is demonstrated by the decomposition of the differential cross sections in terms of Legendre polynomials and by further comparison to model predictions. A new solution of the SAID partial-wave analysis obtained after adding the new data into the fit is presented., Comment: 13 pages, 12 figures, 1 table

Published
2015
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46. A new measurement of the neutron detection efficiency for the NaI Crystal Ball detector

Author

Martemianov, M., Kulikov, V., Demissie, B. T., Marinides, Z., Akondi, C. S., Annand, J. R. M., Arends, H. J., Beck, R., Borisov, N., Braghieri, A., Briscoe, W. J., Cherepnya, S., Collicott, C., Costanza, S., Downie, E. J., Dieterle, M., Bondy, M. I. Ferretti, Filkov, L. V., Garni, S., Glazier, D. I., Glowa, D., Gradl, W., Gurevich, G., Hornidge, D., Huber, G. M., Kaeser, A., Kashevarov, V. L., Keshelashvili, I., Kondratiev, R., Korolija, M., Krusche, B., Lazarev, A., Linturi, J. M., Lisin, V., Livingston, K., MacGregor, I. J. D., Manley, D. M., Martel, P. P., Middleton, D. G., Miskimen, R., Mushkarenkov, A., Neganov, A., Neiser, A., Oberle, M., Ostrick, M., Ott, P., Otte, P. B., Oussena, B., Pedroni, P., Polonski, A., Prakhov, S., Ron, G., Rostomyan, T., Sarty, A., Schott, D. M., Schumann, S., Sokhoyan, V., Steffen, O., Strakovsky, I. I., Strub, Th., Supek, I., Thiel, M., Thomas, A., Unverzagt, M., Usov, Yu. A., Wagner, S., Watts, D. P., Wettig, J., Werthmuller, D., Witthauer, L., and Wolfes, M.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment, Nuclear Experiment
Abstract

We report on a measurement of the neutron detection efficiency in NaI crystals in the Crystal Ball detector obtained from a study of single p0 photoproduction on deuterium using the tagged photon beam at the Mainz Microtron. The results were obtained up to a neutron energy of 400 MeV. They are compared to previous measurements made more than 15 years ago at the pion beam at the BNL AGS.

Published
2015
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47. Towards cascading genetic risk in Alzheimer's disease.

Author

Altmann, Andre, Aksman, Leon M, Oxtoby, Neil P, Young, Alexandra L, Alexander, Daniel C, Barkhof, Frederik, Shoai, Maryam, Hardy, John, and Schott, Jonathan M

Subjects
DISEASE risk factors, ALZHEIMER'S disease, PROPORTIONAL hazards models, GENOME-wide association studies, MONOGENIC & polygenic inheritance (Genetics)
Abstract

Alzheimer's disease typically progresses in stages, which have been defined by the presence of disease-specific biomarkers: amyloid (A), tau (T) and neurodegeneration (N). This progression of biomarkers has been condensed into the ATN framework, in which each of the biomarkers can be either positive (+) or negative (−). Over the past decades, genome-wide association studies have implicated ∼90 different loci involved with the development of late-onset Alzheimer's disease. Here, we investigate whether genetic risk for Alzheimer's disease contributes equally to the progression in different disease stages or whether it exhibits a stage-dependent effect. Amyloid (A) and tau (T) status was defined using a combination of available PET and CSF biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort. In 312 participants with biomarker-confirmed A−T− status, we used Cox proportional hazards models to estimate the contribution of APOE and polygenic risk scores (beyond APOE) to convert to A+T− status (65 conversions). Furthermore, we repeated the analysis in 290 participants with A+T− status and investigated the genetic contribution to conversion to A+T+ (45 conversions). Both survival analyses were adjusted for age, sex and years of education. For progression from A−T− to A+T−, APOE-e4 burden showed a significant effect [hazard ratio (HR) = 2.88; 95% confidence interval (CI): 1.70–4.89; P < 0.001], whereas polygenic risk did not (HR = 1.09; 95% CI: 0.84–1.42; P = 0.53). Conversely, for the transition from A+T− to A+T+, the contribution of APOE-e4 burden was reduced (HR = 1.62; 95% CI: 1.05–2.51; P = 0.031), whereas the polygenic risk showed an increased contribution (HR = 1.73; 95% CI: 1.27–2.36; P < 0.001). The marginal APOE effect was driven by e4 homozygotes (HR = 2.58; 95% CI: 1.05–6.35; P = 0.039) as opposed to e4 heterozygotes (HR = 1.74; 95% CI: 0.87–3.49; P = 0.12). The genetic risk for late-onset Alzheimer's disease unfolds in a disease stage-dependent fashion. A better understanding of the interplay between disease stage and genetic risk can lead to a more mechanistic understanding of the transition between ATN stages and a better understanding of the molecular processes leading to Alzheimer's disease, in addition to opening therapeutic windows for targeted interventions. [ABSTRACT FROM AUTHOR]

Published
2024
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