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1,013 results on '"Hilal, Saima"'

1. Genetic variants for head size share genes and pathways with cancer

Author

Knol, Maria J, Poot, Raymond A, Evans, Tavia E, Satizabal, Claudia L, Mishra, Aniket, Sargurupremraj, Muralidharan, van der Auwera, Sandra, Duperron, Marie-Gabrielle, Jian, Xueqiu, Hostettler, Isabel C, van Dam-Nolen, Dianne HK, Lamballais, Sander, Pawlak, Mikolaj A, Lewis, Cora E, Carrion-Castillo, Amaia, van Erp, Theo GM, Reinbold, Céline S, Shin, Jean, Scholz, Markus, Håberg, Asta K, Kämpe, Anders, Li, Gloria HY, Avinun, Reut, Atkins, Joshua R, Hsu, Fang-Chi, Amod, Alyssa R, Lam, Max, Tsuchida, Ami, Teunissen, Mariël WA, Aygün, Nil, Patel, Yash, Liang, Dan, Beiser, Alexa S, Beyer, Frauke, Bis, Joshua C, Bos, Daniel, Bryan, R Nick, Bülow, Robin, Caspers, Svenja, Catheline, Gwenaëlle, Cecil, Charlotte AM, Dalvie, Shareefa, Dartigues, Jean-François, DeCarli, Charles, Enlund-Cerullo, Maria, Ford, Judith M, Franke, Barbara, Freedman, Barry I, Friedrich, Nele, Green, Melissa J, Haworth, Simon, Helmer, Catherine, Hoffmann, Per, Homuth, Georg, Ikram, M Kamran, Jack, Clifford R, Jahanshad, Neda, Jockwitz, Christiane, Kamatani, Yoichiro, Knodt, Annchen R, Li, Shuo, Lim, Keane, Longstreth, WT, Macciardi, Fabio, Consortium, The Cohorts for Heart and Aging Research in Genomic Epidemiology, Amouyel, Philippe, Arfanakis, Konstantinos, Aribisala, Benjamin S, Bastin, Mark E, Chauhan, Ganesh, Chen, Christopher, Cheng, Ching-Yu, de Jager, Philip L, Deary, Ian J, Fleischman, Debra A, Gottesman, Rebecca F, Gudnason, Vilmundur, Hilal, Saima, Hofer, Edith, Janowitz, Deborah, Jukema, J Wouter, Liewald, David CM, Lopez, Lorna M, Lopez, Oscar, Luciano, Michelle, Martinez, Oliver, Niessen, Wiro J, Nyquist, Paul, Rotter, Jerome I, Rundek, Tatjana, Sacco, Ralph L, Schmidt, Helena, Tiemeier, Henning, Trompet, Stella, van der Grond, Jeroen, Völzke, Henry, Wardlaw, Joanna M, Yanek, Lisa, Yang, Jingyun, and Consortium, The Enhancing NeuroImaging Genetics through Meta-Analysis

Subjects
Biomedical and Clinical Sciences, Human Genome, Genetics, Cancer, Stem Cell Research, Biotechnology, Neurosciences, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Neurological, Humans, Genome-Wide Association Study, Head, Neoplasms, Female, Male, Polymorphism, Single Nucleotide, Genetic Variation, Organ Size, Signal Transduction, Adult, Genetic Predisposition to Disease, Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium, cancer, genetics, genome-wide association study, head circumference, head size, intracranial volume, meta-analysis, Biomedical and clinical sciences
Abstract

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.

Published
2024

2. 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, Alzheimer's Disease, Prevention, Dementia, Clinical Research, Acquired Cognitive Impairment, Aging, Neurodegenerative, Brain Disorders, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), 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

4. Influence of Comorbidity of Cerebrovascular Disease and Amyloid-β on Alzheimer’s Disease

Author

Yassi, Nawaf, primary, Hilal, Saima, additional, Xia, Ying, additional, Lim, Yen Ying, additional, Watson, Rosie, additional, Kuijf, Hugo, additional, Fowler, Christopher, additional, Yates, Paul, additional, Maruff, Paul, additional, Martins, Ralph, additional, Ames, David, additional, Chen, Christopher, additional, Rowe, Christopher C., additional, Villemagne, Victor L., additional, Salvado, Olivier, additional, Desmond, Patricia M., additional, and Masters, Colin L., additional

Published
2024
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5. Deep Learning Based Detection of Enlarged Perivascular Spaces on Brain MRI

Author

Rashid, Tanweer, Liu, Hangfan, Ware, Jeffrey B., Li, Karl, Romero, Jose Rafael, Fadaee, Elyas, Nasrallah, Ilya M., Hilal, Saima, Bryan, R. Nick, Hughes, Timothy M., Davatzikos, Christos, Launer, Lenore, Seshadri, Sudha, Heckbert, Susan R., and Habes, Mohamad

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

BACKGROUND AND PURPOSE: Deep learning has been demonstrated effective in many neuroimaging applications. However, in many scenarios, the number of imaging sequences capturing information related to small vessel disease lesions is insufficient to support data-driven techniques. Additionally, cohort-based studies may not always have the optimal or essential imaging sequences for accurate lesion detection. Therefore, it is necessary to determine which imaging sequences are crucial for precise detection. This study introduces a novel deep learning framework to detect enlarged perivascular spaces (ePVS) and aims to find the optimal combination of MRI sequences for deep learning-based quantification. MATERIALS AND METHODS: We implemented an effective lightweight U-Net adapted for ePVS detection and comprehensively investigated different combinations of information from SWI, FLAIR, T1-weighted (T1w), and T2-weighted (T2w) MRI sequences. The training data included 21 participants, which were randomly selected from the MESA cohort. Participants had ePVS 683 lesions on average. For T1w, T2w, and FLAIR images, the MESA study collected 3D isotropic MRI scans at six different sites with Siemens scanners. Our training data included participants from all these sites and all the scanner models, and the proposed model was applied to the whole brain instead of selective regions. RESULTS: The experimental results showed that T2w MRI is the most important for accurate ePVS detection, and the incorporation of SWI, FLAIR and T1w MRI in the deep neural network had minor improvements in accuracy and resulted in the highest sensitivity and precision (sensitivity =0.82, precision =0.83). The proposed method achieved comparable accuracy at a minimal time cost compared to manual reading.

Published
2022

6. 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, Clinical Research, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Cerebrovascular, Networking and Information Technology R&D (NITRD), Neurosciences, Neurodegenerative, Alzheimer's Disease Related Dementias (ADRD), Machine Learning and Artificial Intelligence, Vascular Cognitive Impairment/Dementia, Aging, Acquired Cognitive Impairment, Dementia, Brain Disorders, 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

11. Genomics of perivascular space burden unravels early mechanisms of cerebral small vessel disease

Author

Duperron, Marie-Gabrielle, Knol, Maria J., Le Grand, Quentin, Evans, Tavia E., Mishra, Aniket, Tsuchida, Ami, Roshchupkin, Gennady, Konuma, Takahiro, Trégouët, David-Alexandre, Romero, Jose Rafael, Frenzel, Stefan, Luciano, Michelle, Hofer, Edith, Bourgey, Mathieu, Dueker, Nicole D., Delgado, Pilar, Hilal, Saima, Tankard, Rick M., Dubost, Florian, Shin, Jean, Saba, Yasaman, Armstrong, Nicola J., Bordes, Constance, Bastin, Mark E., Beiser, Alexa, Brodaty, Henry, Bülow, Robin, Carrera, Caty, Chen, Christopher, Cheng, Ching-Yu, Deary, Ian J., Gampawar, Piyush G., Himali, Jayandra J., Jiang, Jiyang, Kawaguchi, Takahisa, Li, Shuo, Macalli, Melissa, Marquis, Pascale, Morris, Zoe, Muñoz Maniega, Susana, Miyamoto, Susumu, Okawa, Masakazu, Paradise, Matthew, Parva, Pedram, Rundek, Tatjana, Sargurupremraj, Muralidharan, Schilling, Sabrina, Setoh, Kazuya, Soukarieh, Omar, Tabara, Yasuharu, Teumer, Alexander, Thalamuthu, Anbupalam, Trollor, Julian N., Valdés Hernández, Maria C., Vernooij, Meike W., Völker, Uwe, Wittfeld, Katharina, Wong, Tien Yin, Wright, Margaret J., Zhang, Junyi, Zhao, Wanting, Zhu, Yi-Cheng, Schmidt, Helena, Sachdev, Perminder S., Wen, Wei, Yoshida, Kazumichi, Joutel, Anne, Satizabal, Claudia L., Sacco, Ralph L., Bourque, Guillaume, Lathrop, Mark, Paus, Tomas, Fernandez-Cadenas, Israel, Yang, Qiong, Mazoyer, Bernard, Boutinaud, Philippe, Okada, Yukinori, Grabe, Hans J., Mather, Karen A., Schmidt, Reinhold, Joliot, Marc, Ikram, M. Arfan, Matsuda, Fumihiko, Tzourio, Christophe, Wardlaw, Joanna M., Seshadri, Sudha, Adams, Hieab H. H., and Debette, Stéphanie

Published
2023
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12. White Matter Hyperintensity Volume and Poststroke Cognition: An Individual Patient Data Pooled Analysis of 9 Ischemic Stroke Cohort Studies

Author

de Kort, Floor A.S., Coenen, Mirthe, Weaver, Nick A., Kuijf, Hugo J., Aben, Hugo P., Bae, Hee-Joon, Bordet, Régis, Cammà, Guido, Chen, Christopher P.L.H., Dewenter, Anna, Duering, Marco, Fang, Rong, van der Giessen, Ruben S., Hamilton, Olivia K.L., Hilal, Saima, Huenges Wajer, Irene M.C., Kan, Cheuk Ni, Kim, Jonguk, Kim, Beom Joon, Köhler, Sebastian, de Kort, Paul L.M., Koudstaal, Peter J., Lim, Jae-Sung, Lopes, Renaud, Mok, Vincent C.T., Staals, Julie, Venketasubramanian, Narayanaswamy, Verhagen, Charlotte M., Verhey, Frans R.J., Wardlaw, Joanna M., Xu, Xin, Yu, Kyung-Ho, Biesbroek, J. Matthijs, and Biessels, Geert Jan

Published
2023
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17. Rate of brain aging associates with future executive function in Asian children and older adults

Author

Cheng, Susan F., primary, Yue, Wan Lin, additional, Ng, Kwun Kei, additional, Qian, Xing, additional, Liu, Siwei, additional, Tan, Trevor W.K., additional, Nguyen, Kim-Ngan, additional, Leong, Ruth L.F., additional, Hilal, Saima, additional, Cheng, Ching-Yu, additional, Tan, Ai Peng, additional, Law, Evelyn C., additional, Gluckman, Peter D., additional, Chen, Christopher Li-Hsian, additional, Chong, Yap Seng, additional, Meaney, Michael J., additional, Chee, Michael W.L., additional, Yeo, B.T. Thomas, additional, and Zhou, Juan Helen, additional

Published
2024
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18. Association of common genetic variants with brain microbleeds: A Genome-wide Association Study

Author

Knol, Maria J, Lu, Dongwei, Traylor, Matthew, Adams, Hieab HH, Romero, José Rafael J, Smith, Albert V, Fornage, Myriam, Hofer, Edith, Liu, Junfeng, Hostettler, Isabel C, Luciano, Michelle, Trompet, Stella, Giese, Anne-Katrin, Hilal, Saima, van den Akker, Erik B, Vojinovic, Dina, Li, Shuo, Sigurdsson, Sigurdur, van der Lee, Sven J, Jack, Clifford R, Wilson, Duncan, Yilmaz, Pinar, Satizabal, Claudia L, Liewald, David CM, van der Grond, Jeroen, Chen, Christopher, Saba, Yasaman, van der Lugt, Aad, Bastin, Mark E, Windham, B Gwen, Cheng, Ching Yu, Pirpamer, Lukas, Kantarci, Kejal, Himali, Jayandra J, Yang, Qiong, Morris, Zoe, Beiser, Alexa S, Tozer, Daniel J, Vernooij, Meike W, Amin, Najaf, Beekman, Marian, Koh, Jia Yu, Stott, David J, Houlden, Henry, Schmidt, Reinhold, Gottesman, Rebecca F, MacKinnon, Andrew D, DeCarli, Charles, Gudnason, Vilmundur, Deary, Ian J, van Duijn, Cornelia M, Slagboom, P Eline, Wong, Tien Yin, Rost, Natalia S, Jukema, J Wouter, Mosley, Thomas H, Werring, David J, Schmidt, Helena, Wardlaw, Joanna M, Ikram, M Arfan, Seshadri, Sudha, Launer, Lenore J, Markus, Hugh S, and Initiative, for the Alzheimer’s Disease Neuroimaging

Subjects
Stroke, Human Genome, Neurosciences, Brain Disorders, Genetics, Prevention, Aetiology, 2.1 Biological and endogenous factors, Aged, Aged, 80 and over, Alleles, Apolipoprotein E2, Apolipoprotein E4, Apolipoproteins E, Case-Control Studies, Cerebral Hemorrhage, Cerebral Small Vessel Diseases, Cohort Studies, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Polymorphism, Single Nucleotide, Risk, White Matter, Alzheimer's Disease Neuroimaging Initiative, Clinical Sciences, Cognitive Sciences, Neurology & Neurosurgery
Abstract

ObjectiveTo identify common genetic variants associated with the presence of brain microbleeds (BMBs).MethodsWe performed genome-wide association studies in 11 population-based cohort studies and 3 case-control or case-only stroke cohorts. Genotypes were imputed to the Haplotype Reference Consortium or 1000 Genomes reference panel. BMBs were rated on susceptibility-weighted or T2*-weighted gradient echo MRI sequences, and further classified as lobar or mixed (including strictly deep and infratentorial, possibly with lobar BMB). In a subset, we assessed the effects of APOE ε2 and ε4 alleles on BMB counts. We also related previously identified cerebral small vessel disease variants to BMBs.ResultsBMBs were detected in 3,556 of the 25,862 participants, of which 2,179 were strictly lobar and 1,293 mixed. One locus in the APOE region reached genome-wide significance for its association with BMB (lead single nucleotide polymorphism rs769449; odds ratio [OR]any BMB [95% confidence interval (CI)] 1.33 [1.21-1.45]; p = 2.5 × 10-10). APOE ε4 alleles were associated with strictly lobar (OR [95% CI] 1.34 [1.19-1.50]; p = 1.0 × 10-6) but not with mixed BMB counts (OR [95% CI] 1.04 [0.86-1.25]; p = 0.68). APOE ε2 alleles did not show associations with BMB counts. Variants previously related to deep intracerebral hemorrhage and lacunar stroke, and a risk score of cerebral white matter hyperintensity variants, were associated with BMB.ConclusionsGenetic variants in the APOE region are associated with the presence of BMB, most likely due to the APOE ε4 allele count related to a higher number of strictly lobar BMBs. Genetic predisposition to small vessel disease confers risk of BMB, indicating genetic overlap with other cerebral small vessel disease markers.

Published
2020

19. Sex Differences in Poststroke Cognitive Impairment: A Multicenter Study in 2343 Patients With Acute Ischemic Stroke

Author

Exalto, Lieza G., Weaver, Nick A., Kuijf, Hugo J., Aben, Hugo P., Bae, Hee-Joon, Best, Jonathan G., Bordet, Régis, Chen, Christopher P.L.H., van der Giessen, Ruben S., Godefroy, Olivier, Gyanwali, Bibek, Hamilton, Olivia K.L., Hilal, Saima, Huenges Wajer, Irene M.C., Kim, Jonguk, Kappelle, L. Jaap, Kim, Beom Joon, Köhler, Sebastian, de Kort, Paul L.M., Koudstaal, Peter J., Lim, Jae-Sung, Makin, Stephen D.J., Mok, Vincent C.T., van Oostenbrugge, Robert J., Roussel, Martine, Staals, Julie, Valdés-Hernández, Maria del C., Venketasubramanian, Narayanaswamy, Verhey, Frans R.J., Wardlaw, Joanna M., Werring, David J., Xu, Xin, van Zandvoort, Martine J.E., Biesbroek, J. Matthijs, Chappell, Francesca M., and Biessels, Geert Jan

Published
2023
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20. Neuroimaging standards for research into small vessel disease—advances since 2013

Author

Duering, Marco, Biessels, Geert Jan, Brodtmann, Amy, Chen, Christopher, Cordonnier, Charlotte, de Leeuw, Frank-Erik, Debette, Stéphanie, Frayne, Richard, Jouvent, Eric, Rost, Natalia S, ter Telgte, Annemieke, Al-Shahi Salman, Rustam, Backes, Walter H, Bae, Hee-Joon, Brown, Rosalind, Chabriat, Hugues, De Luca, Alberto, deCarli, Charles, Dewenter, Anna, Doubal, Fergus N, Ewers, Michael, Field, Thalia S, Ganesh, Aravind, Greenberg, Steven, Helmer, Karl G, Hilal, Saima, Jochems, Angela C C, Jokinen, Hanna, Kuijf, Hugo, Lam, Bonnie Y K, Lebenberg, Jessica, MacIntosh, Bradley J, Maillard, Pauline, Mok, Vincent C T, Pantoni, Leonardo, Rudilosso, Salvatore, Satizabal, Claudia L, Schirmer, Markus D, Schmidt, Reinhold, Smith, Colin, Staals, Julie, Thrippleton, Michael J, van Veluw, Susanne J, Vemuri, Prashanthi, Wang, Yilong, Werring, David, Zedde, Marialuisa, Akinyemi, Rufus O, Del Brutto, Oscar H, Markus, Hugh S, Zhu, Yi-Cheng, Smith, Eric E, Dichgans, Martin, and Wardlaw, Joanna M

Published
2023
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21. The Meta VCI Map consortium for meta‐analyses on strategic lesion locations for vascular cognitive impairment using lesion‐symptom mapping: Design and multicenter pilot study

Author

Weaver, Nick A, Zhao, Lei, Biesbroek, J Matthijs, Kuijf, Hugo J, Aben, Hugo P, Bae, Hee‐Joon, Caballero, Miguel ÁA, Chappell, Francesca M, Chen, Christopher PLH, Dichgans, Martin, Duering, Marco, Georgakis, Marios K, van der Giessen, Ruben S, Gyanwali, Bibek, Hamilton, Olivia KL, Hilal, Saima, Hofe, Elise M vom, de Kort, Paul LM, Koudstaal, Peter J, Lam, Bonnie YK, Lim, Jae‐Sung, Makin, Stephen DJ, Mok, Vincent CT, Shi, Lin, Hernández, Maria C Valdés, Venketasubramanian, Narayanaswamy, Wardlaw, Joanna M, Wollenweber, Frank A, Wong, Adrian, Xin, Xu, consortium, Meta VCI Map, DeCarli, C, Fletcher, EA, Maillard, P, Barnes, J, Sudre, CH, Schott, JM, Ikram, MA, Papma, JM, Steketee, RME, Vernooij, MW, Bordet, R, Lopes, R, Huang, C‐W, Frayne, R, McCreary, CR, Smith, EE, group, Calgary Normative Study, Backes, W, Köhler, S, van Oostenbrugge, RJ, Staals, J, Verhey, F, Cheng, CY, Kalaria, RN, Werring, D, Hsu, JL, Huang, K‐L, van der Grond, J, Jukema, JW, van der Mast, RC, Nijboer, TCW, group, Framingham Heart Study, Yu, K‐H, group, The Dutch Parelsnoer Institute–Neurodegenerative diseases, Schmidt, R, Pirpamer, L, MacIntosh, BJ, Robertson, AD, de Leeuw, F‐E, Tuladhar, AM, Chaturvedi, N, Tillin, T, Brodaty, H, Sachdev, P, group, TABASCO, Barkhof, F, van der Flier, WM, Kappelle, LJ, and Biessels, Geert Jan

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Biomedical Imaging, Atherosclerosis, Clinical Research, Brain Disorders, Acquired Cognitive Impairment, Stroke, Neurosciences, Meta VCI Map consortium, Cerebrovascular disease, Consortium, Data harmonization, Lesion location, Lesion-symptom mapping, Small vessel disease, Support vector regression, Vascular cognitive impairment, Genetics, Biological psychology
Abstract

IntroductionThe Meta VCI Map consortium performs meta-analyses on strategic lesion locations for vascular cognitive impairment using lesion-symptom mapping. Integration of data from different cohorts will increase sample sizes, to improve brain lesion coverage and support comprehensive lesion-symptom mapping studies.MethodsCohorts with available imaging on white matter hyperintensities or infarcts and cognitive testing were invited. We performed a pilot study to test the feasibility of multicenter data processing and analysis and determine the benefits to lesion coverage.ResultsForty-seven groups have joined Meta VCI Map (stroke n = 7800 patients; memory clinic n = 4900; population-based n = 14,400). The pilot study (six ischemic stroke cohorts, n = 878) demonstrated feasibility of multicenter data integration (computed tomography/magnetic resonance imaging) and achieved marked improvement of lesion coverage.DiscussionMeta VCI Map will provide new insights into the relevance of vascular lesion location for cognitive dysfunction. After the successful pilot study, further projects are being prepared. Other investigators are welcome to join.

Published
2019

22. Genetic architecture of subcortical brain structures in 38,851 individuals

Author

Satizabal, Claudia L, Adams, Hieab HH, Hibar, Derrek P, White, Charles C, Knol, Maria J, Stein, Jason L, Scholz, Markus, Sargurupremraj, Muralidharan, Jahanshad, Neda, Roshchupkin, Gennady V, Smith, Albert V, Bis, Joshua C, Jian, Xueqiu, Luciano, Michelle, Hofer, Edith, Teumer, Alexander, van der Lee, Sven J, Yang, Jingyun, Yanek, Lisa R, Lee, Tom V, Li, Shuo, Hu, Yanhui, Koh, Jia Yu, Eicher, John D, Desrivières, Sylvane, Arias-Vasquez, Alejandro, Chauhan, Ganesh, Athanasiu, Lavinia, Rentería, Miguel E, Kim, Sungeun, Hoehn, David, Armstrong, Nicola J, Chen, Qiang, Holmes, Avram J, den Braber, Anouk, Kloszewska, Iwona, Andersson, Micael, Espeseth, Thomas, Grimm, Oliver, Abramovic, Lucija, Alhusaini, Saud, Milaneschi, Yuri, Papmeyer, Martina, Axelsson, Tomas, Ehrlich, Stefan, Roiz-Santiañez, Roberto, Kraemer, Bernd, Håberg, Asta K, Jones, Hannah J, Pike, G Bruce, Stein, Dan J, Stevens, Allison, Bralten, Janita, Vernooij, Meike W, Harris, Tamara B, Filippi, Irina, Witte, A Veronica, Guadalupe, Tulio, Wittfeld, Katharina, Mosley, Thomas H, Becker, James T, Doan, Nhat Trung, Hagenaars, Saskia P, Saba, Yasaman, Cuellar-Partida, Gabriel, Amin, Najaf, Hilal, Saima, Nho, Kwangsik, Mirza-Schreiber, Nazanin, Arfanakis, Konstantinos, Becker, Diane M, Ames, David, Goldman, Aaron L, Lee, Phil H, Boomsma, Dorret I, Lovestone, Simon, Giddaluru, Sudheer, Le Hellard, Stephanie, Mattheisen, Manuel, Bohlken, Marc M, Kasperaviciute, Dalia, Schmaal, Lianne, Lawrie, Stephen M, Agartz, Ingrid, Walton, Esther, Tordesillas-Gutierrez, Diana, Davies, Gareth E, Shin, Jean, Ipser, Jonathan C, Vinke, Louis N, Hoogman, Martine, Jia, Tianye, Burkhardt, Ralph, Klein, Marieke, Crivello, Fabrice, Janowitz, Deborah, Carmichael, Owen, Haukvik, Unn K, Aribisala, Benjamin S, and Schmidt, Helena

Subjects
Biological Sciences, Genetics, Neurosciences, Biotechnology, Mental Health, Human Genome, Brain Disorders, Aetiology, 2.1 Biological and endogenous factors, Neurological, Adult, Aged, Animals, Brain, Cohort Studies, Drosophila melanogaster, Genetic Variation, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Middle Aged, Neurodevelopmental Disorders, Organ Size, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.

Published
2019

26. Extracellular Vesicle-Enriched miRNA-Biomarkers Show Improved Utility for Detecting Alzheimer’s Disease Dementia and Medial Temporal Atrophy

Author

Chai, Yuek Ling, primary, Strohm, Lea, additional, Zhu, Yanan, additional, Chia, Rachel S.L., additional, Chong, Joyce Ruifen, additional, Suresh, Danesha Devini, additional, Zhou, Li Han, additional, Too, Heng Phon, additional, Hilal, Saima, additional, Radivoyevitch, Tomas, additional, Koo, Edward H., additional, Chen, Christopher P., additional, and Poplawski, Gunnar Heiko Dirk, additional

Published
2024
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29. Association of plasma GFAP with elevated brain amyloid is dependent on severity of white matter lesions in an Asian cognitively impaired cohort

Author

Chong, Joyce R., primary, Chai, Yuek Ling, additional, Yam, Amelia T. Y., additional, Hilal, Saima, additional, Vrooman, Henri, additional, Venketasubramanian, Narayanaswamy, additional, Blennow, Kaj, additional, Zetterberg, Henrik, additional, Ashton, Nicholas J., additional, Chen, Christopher P., additional, and Lai, Mitchell K. P., additional

Published
2024
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31. Developing blood-brain barrier arterial spin labelling as a non-invasive early biomarker of Alzheimer’s disease (DEBBIE-AD): a prospective observational multicohort study protocol

Author

Padrela, Beatriz, primary, Mahroo, Amnah, additional, Tee, Mervin, additional, Sneve, Markus H, additional, Moyaert, Paulien, additional, Geier, Oliver, additional, Kuijer, Joost P A, additional, Beun, Soetkin, additional, Nordhøy, Wibeke, additional, Zhu, Yufei David, additional, Buck, Mareike A, additional, Hoinkiss, Daniel C, additional, Konstandin, Simon, additional, Huber, Jörn, additional, Wiersinga, Julia, additional, Rikken, Roos, additional, de Leeuw, Diederick, additional, Grydeland, Håkon, additional, Tippett, Lynette, additional, Cawston, Erin E, additional, Ozturk-Isik, Esin, additional, Linn, Jennifer, additional, Brandt, Moritz, additional, Tijms, Betty M, additional, van de Giessen, Elsmarieke M, additional, Muller, Majon, additional, Fjell, Anders, additional, Walhovd, Kristine, additional, Bjørnerud, Atle, additional, Pålhaugen, Lene, additional, Selnes, Per, additional, Clement, Patricia, additional, Achten, Eric, additional, Anazodo, Udunna, additional, Barkhof, Frederik, additional, Hilal, Saima, additional, Fladby, Tormod, additional, Eickel, Klaus, additional, Morgan, Catherine, additional, Thomas, David L, additional, Petr, Jan, additional, Günther, Matthias, additional, and Mutsaerts, Henk J M M, additional

Published
2024
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32. A multi-regression framework to improve diagnostic ability of optical coherence tomography retinal biomarkers to discriminate mild cognitive impairment and Alzheimer’s disease

Author

Chua, Jacqueline, Li, Chi, Ho, Lucius Kang Hua, Wong, Damon, Tan, Bingyao, Yao, Xinwen, Gan, Alfred, Schwarzhans, Florian, Garhöfer, Gerhard, Sng, Chelvin C. A., Hilal, Saima, Venketasubramanian, Narayanaswamy, Cheung, Carol Y., Fischer, Georg, Vass, Clemens, Wong, Tien Yin, Chen, Christopher Li-Hsian, and Schmetterer, Leopold

Published
2022
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33. A deep learning model for detection of Alzheimer's disease based on retinal photographs: a retrospective, multicentre case-control study

Author

Cheung, Carol Y, Ran, An Ran, Wang, Shujun, Chan, Victor T T, Sham, Kaiser, Hilal, Saima, Venketasubramanian, Narayanaswamy, Cheng, Ching-Yu, Sabanayagam, Charumathi, Tham, Yih Chung, Schmetterer, Leopold, McKay, Gareth J, Williams, Michael A, Wong, Adrian, Au, Lisa W C, Lu, Zhihui, Yam, Jason C, Tham, Clement C, Chen, John J, Dumitrascu, Oana M, Heng, Pheng-Ann, Kwok, Timothy C Y, Mok, Vincent C T, Milea, Dan, Chen, Christopher Li-Hsian, and Wong, Tien Yin

Published
2022
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34. A genome-wide association study identifies genetic loci associated with specific lobar brain volumes

Author

van der Lee, Sven J, Knol, Maria J, Chauhan, Ganesh, Satizabal, Claudia L, Smith, Albert Vernon, Hofer, Edith, Bis, Joshua C, Hibar, Derrek P, Hilal, Saima, van den Akker, Erik B, Arfanakis, Konstantinos, Bernard, Manon, Yanek, Lisa R, Amin, Najaf, Crivello, Fabrice, Cheung, Josh W, Harris, Tamara B, Saba, Yasaman, Lopez, Oscar L, Li, Shuo, van der Grond, Jeroen, Yu, Lei, Paus, Tomas, Roshchupkin, Gennady V, Amouyel, Philippe, Jahanshad, Neda, Taylor, Kent D, Yang, Qiong, Mathias, Rasika A, Boehringer, Stefan, Mazoyer, Bernard, Rice, Ken, Cheng, Ching Yu, Maillard, Pauline, van Heemst, Diana, Wong, Tien Yin, Niessen, Wiro J, Beiser, Alexa S, Beekman, Marian, Zhao, Wanting, Nyquist, Paul A, Chen, Christopher, Launer, Lenore J, Psaty, Bruce M, Ikram, M Kamran, Vernooij, Meike W, Schmidt, Helena, Pausova, Zdenka, Becker, Diane M, De Jager, Philip L, Thompson, Paul M, van Duijn, Cornelia M, Bennett, David A, Slagboom, P Eline, Schmidt, Reinhold, Longstreth, WT, Ikram, M Arfan, Seshadri, Sudha, Debette, Stéphanie, Gudnason, Vilmundur, Adams, Hieab HH, and DeCarli, Charles

Subjects
Biological Sciences, Genetics, Neurosciences, Mental Health, Brain Disorders, Human Genome, Underpinning research, 1.1 Normal biological development and functioning, Aetiology, 2.1 Biological and endogenous factors, Neurological, Frontal Lobe, Gene Expression Regulation, Developmental, Genetic Loci, Genetic Variation, Genome-Wide Association Study, Genotype, Heredity, Humans, Magnetic Resonance Imaging, Occipital Lobe, Organ Size, Parietal Lobe, Phenotype, Temporal Lobe, United Kingdom, Biomarkers, Genome-wide association studies, Neurology, Biological sciences, Biomedical and clinical sciences
Abstract

Brain lobar volumes are heritable but genetic studies are limited. We performed genome-wide association studies of frontal, occipital, parietal and temporal lobe volumes in 16,016 individuals, and replicated our findings in 8,789 individuals. We identified six genetic loci associated with specific lobar volumes independent of intracranial volume. Two loci, associated with occipital (6q22.32) and temporal lobe volume (12q14.3), were previously reported to associate with intracranial and hippocampal volume, respectively. We identified four loci previously unknown to affect brain volumes: 3q24 for parietal lobe volume, and 1q22, 4p16.3 and 14q23.1 for occipital lobe volume. The associated variants were located in regions enriched for histone modifications (DAAM1 and THBS3), or close to genes causing Mendelian brain-related diseases (ZIC4 and FGFRL1). No genetic overlap between lobar volumes and neurological or psychiatric diseases was observed. Our findings reveal part of the complex genetics underlying brain development and suggest a role for regulatory regions in determining brain volumes.

Published
2019

35. Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting

Author

Chauhan, Ganesh, Adams, Hieab HH, Satizabal, Claudia L, Bis, Joshua C, Teumer, Alexander, Sargurupremraj, Muralidharan, Hofer, Edith, Trompet, Stella, Hilal, Saima, Smith, Albert Vernon, Jian, Xueqiu, Malik, Rainer, Traylor, Matthew, Pulit, Sara L, Amouyel, Philippe, Mazoyer, Bernard, Zhu, Yi-Cheng, Kaffashian, Sara, Schilling, Sabrina, Beecham, Gary W, Montine, Thomas J, Schellenberg, Gerard D, Kjartansson, Olafur, Guðnason, Vilmundur, Knopman, David S, Griswold, Michael E, Windham, B Gwen, Gottesman, Rebecca F, Mosley, Thomas H, Schmidt, Reinhold, Saba, Yasaman, Schmidt, Helena, Takeuchi, Fumihiko, Yamaguchi, Shuhei, Nabika, Toru, Kato, Norihiro, Rajan, Kumar B, Aggarwal, Neelum T, De Jager, Philip L, Evans, Denis A, Psaty, Bruce M, Rotter, Jerome I, Rice, Kenneth, Lopez, Oscar L, Liao, Jiemin, Chen, Christopher, Cheng, Ching-Yu, Wong, Tien Y, Ikram, Mohammad K, van der Lee, Sven J, Amin, Najaf, Chouraki, Vincent, DeStefano, Anita L, Aparicio, Hugo J, Romero, Jose R, Maillard, Pauline, DeCarli, Charles, Wardlaw, Joanna M, del C. Valdés Hernández, Maria, Luciano, Michelle, Liewald, David, Deary, Ian J, Starr, John M, Bastin, Mark E, Maniega, Susana Muñoz, Slagboom, P Eline, Beekman, Marian, Deelen, Joris, Uh, Hae-Won, Lemmens, Robin, Brodaty, Henry, Wright, Margaret J, Ames, David, Boncoraglio, Giorgio B, Hopewell, Jemma C, Beecham, Ashley H, Blanton, Susan H, Wright, Clinton B, Sacco, Ralph L, Wen, Wei, Thalamuthu, Anbupalam, Armstrong, Nicola J, Chong, Elizabeth, Schofield, Peter R, Kwok, John B, van der Grond, Jeroen, Stott, David J, Ford, Ian, Jukema, J Wouter, Vernooij, Meike W, Hofman, Albert, Uitterlinden, André G, van der Lugt, Aad, Wittfeld, Katharina, Grabe, Hans J, Hosten, Norbert, von Sarnowski, Bettina, Völker, Uwe, Levi, Christopher, and Jimenez-Conde, Jordi

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Genetics, Stroke, Human Genome, Brain Disorders, Prevention, Aging, Cardiovascular, Cerebrovascular, 2.1 Biological and endogenous factors, Good Health and Well Being, Stroke Genetics Network (SiGN), the International Stroke Genetics Consortium (ISGC), METASTROKE, Alzheimer's Disease Genetics Consortium (ADGC), and the Neurology Working Group of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract

ObjectiveTo explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts.MethodsWe performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI.ResultsThe mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10-8; and LINC00539/ZDHHC20, p = 5.82 × 10-9. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p [BI] = 9.38 × 10-25; p [SSBI] = 5.23 × 10-14 for hypertension), smoking (p [BI] = 4.4 × 10-10; p [SSBI] = 1.2 × 10-4), diabetes (p [BI] = 1.7 × 10-8; p [SSBI] = 2.8 × 10-3), previous cardiovascular disease (p [BI] = 1.0 × 10-18; p [SSBI] = 2.3 × 10-7), stroke (p [BI] = 3.9 × 10-69; p [SSBI] = 3.2 × 10-24), and MRI-defined white matter hyperintensity burden (p [BI] = 1.43 × 10-157; p [SSBI] = 3.16 × 10-106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy.ConclusionIn this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI.

Published
2019

37. Association Between Domain-Specific Physical Activity and Cardiometabolic Factors in a Multiethnic Asian Population: A Longitudinal Study.

Author

Ge, Lixia, Hilal, Saima, Müller-Riemenschneider, Falk, and Tan, Chuen Seng

Subjects
DIASTOLIC blood pressure, LDL cholesterol, HDL cholesterol, ASIANS, PHYSICAL activity
Abstract

Aims: To examine the association between domain-specific physical activity (PA) and cardiometabolic factors with longitudinal data, which is limited in current literature. Methods: Participants who attended the Singapore Multi-Ethnic Cohort and follow-up surveys were included in this study (N = 3950, mean age: 44.7 y, female: 57.9%). Self-reported moderate- to vigorous-intensity PA (MVPA) for each domain (leisure-time, transportation, occupation, and household) was categorized into 4 levels: no, low, middle, and high MVPA. The longitudinal associations of domain-specific MVPA with cardiometabolic factors including systolic and diastolic blood pressures, low-density and high-density lipoprotein cholesterols, triglycerides, and body mass index were examined using Generalized Estimating Equations, accounting for confounding factors and repeated measurements. Results: There were 5.2% participants who had no MVPA. For each domain, this rate ranged from 22.6% (household) to 83.3% (occupation). Leisure-time and occupation MVPAs had positive and linear associations with high-density lipoprotein cholesterols, corresponding to 0.030 (95% confidence interval, 0.015 to 0.045) mmol/L (leisure-time) and 0.063 (95% confidence interval, 0.043 to 0.083) mmol/L (occupation), when compared high with no respective MVPA. Occupation and household MVPAs were associated with low-density lipoprotein cholesterol. Transportation and occupation exhibited a positive and linear relationship with diastolic blood pressure. None of the domains were associated with body mass index, systolic blood pressures, or triglycerides. Conclusions: This study showed that each domain had differential association with individual cardiometabolic risk factors. As occupation, transportation, or household PA had unfavorable associations with low-density lipoprotein cholesterol or diastolic blood pressure, the overall beneficial impact of higher PA levels may not necessarily hold in the context of domain-specific PA and cardiovascular health. Further investigation is needed to corroborate our findings. [ABSTRACT FROM AUTHOR]

Published
2023
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41. Marital History and Cognition in a Chinese Longevity Cohort.

Author

Huang, Xiangyuan and Hilal, Saima

Subjects
*ALZHEIMER'S disease, *DISEASE risk factors, *MARRIAGE, *LONGEVITY, *ADULTERY, CHINESE history
Abstract

Background: Marital factor has been associated with dementia and Alzheimer's disease, but there is limited evidence on the impact of holistic marital history over time. Objective: This study aimed to examine association of marital history with cognition. Methods: The study included 24,596 dementia-free participants from the Chinese Longitudinal Healthy Longevity Study (CLHLS). Holistic marital history was collected at baseline, categorizing participants into five groups: widow-single, widow-remarried, divorce-single, divorce-remarried and married based on the first two marriages. Dementia was collected at follow-up through self-report or from a delegate if the participant was deceased. For 15,355 participants, the Chinese Mini-Mental Status Examination (CMMSE) was administered at both baseline and follow-ups. Cognitive impairment was defined as a follow-up CMMSE score below 18, and rate of cognitive change was calculated as the change in CMMSE score between consecutive visits divided by the duration. Results: Compared with married older adults, widow-single group had significantly higher risk of dementia (HR 1.28, 95% CI 1.05, 1.54), cognitive impairment (HR 1.31, 95% CI 1.17, 1.47) and significantly faster decline of MMSE score (β –0.09, 95% CI –0.17, –0.01). Meanwhile, widow-remarried group had significantly lower risk of dementia, cognitive impairment and slower MMSE score decline than widow-single group, although the differences were only significant among female but not male. Conclusions: In this prospective cohort, married older adults and those widowed but with a second marriage had significantly better cognition than widowed individuals who did not remarry. [ABSTRACT FROM AUTHOR]

Published
2024
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42. Abstract WP239: Apolipoprotein E4 Allele Effect on the Prevalence of Intracranial Large Artery Stenosis

Author

Lopez-Navarro, Edgar R, primary, Khasiyev, Farid, additional, Spagnolo-Allende, Antonio J, additional, Guzman, Vanessa A, additional, Strobino, Kevin, additional, Liu, Minghua, additional, Del Brutto, Oscar, additional, Sanchez, Danurys, additional, Hilal, Saima, additional, Elkind, Mitchell, additional, Rundek, Tatjana, additional, Del, Victor J, additional, Brickman, Adam, additional, Manly, Jennifer, additional, Andrews, Howard, additional, Seshadri, Sudha, additional, Romero, Jose R, additional, Chen, Christopher, additional, and Gutierrez, Jose, additional

Published
2024
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45. Association of brain arterial diameters with demographic and anatomical factors in a multi-national pooled analysis of cohort studies

Author

Del Brutto, Victor J, primary, Khasiyev, Farid, additional, Liu, Minghua, additional, Spagnolo-Allende, Antonio, additional, Qiao, Ye, additional, Melgarejo Arias, Jesus D, additional, Guzman, Vanessa A, additional, Igwe, Kay C, additional, Sanchez, Danurys L., additional, Andrews, Howard, additional, Morales, Clarissa D, additional, Farrell, Meagan T, additional, Bassil, Darina T, additional, Seshadri, Sudha, additional, Wagner, Ryan G, additional, Mngomezulu, Victor, additional, Manly, Jennifer, additional, Elkind, Mitchell SV, additional, Berkman, Lisa, additional, Romero, Jose R, additional, Maestre, Gladys E, additional, Del Brutto, Oscar H, additional, Brickman, Adam M, additional, Venketasubramanian, Narayanaswamy, additional, Chen, Christopher, additional, Robert, Caroline, additional, Hilal, Saima, additional, Rundek, Tatjana, additional, Wasserman, Bruce A, additional, and Gutierrez, Jose, additional

Published
2023
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46. Blood‐brain barrier permeability measured with arterial spin labeling as potential cerebrovascular biomarker over the lifespan

Author

Padrela, Beatriz E., primary, Tee, Mervin, additional, Markus, Sneve H, additional, Geier, Oliver, additional, Mahroo, Amnah, additional, Grydeland, Håkon, additional, Fladby, Tormod, additional, Eickel, Klaus, additional, Günther, Matthias, additional, Barkhof, Frederik, additional, Hilal, Saima, additional, Mutsaerts, Henk‐Jan, additional, and Petr, Jan, additional

Published
2023
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48. Enlarged Perivascular Spaces in a Diverse Community‐based Sample. The Multi‐Ethnic Study of Atherosclerosis

Author

Charisis, Sokratis, primary, Rashid, Tanweer, additional, Liu, Hangfan, additional, Ware, Jeffrey B., additional, Jensen, Paul N., additional, Austin, Thomas R., additional, Li, Karl, additional, Fadaee, Elyas, additional, Hilal, Saima, additional, Chen, Christopher Li‐Hsian, additional, Hughes, Tim M., additional, Romero, Jose Rafael, additional, Toledo, Jon B., additional, Longstreth, William T, additional, Hohman, Timothy J., additional, Nasrallah, Ilya M., additional, Bryan, Nick, additional, Launer, Lenore J J., additional, Davatzikos, Christos, additional, Seshadri, Sudha, additional, Heckbert, Susan R., additional, and Habes, Mohamad, additional

Published
2023
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49. Strategic infarct locations for post-stroke cognitive impairment: a pooled analysis of individual patient data from 12 acute ischaemic stroke cohorts

Author

Weaver, Nick A, Kuijf, Hugo J, Aben, Hugo P, Abrigo, Jill, Bae, Hee-Joon, Barbay, Mélanie, Best, Jonathan G, Bordet, Régis, Chappell, Francesca M, Chen, Christopher P L H, Dondaine, Thibaut, van der Giessen, Ruben S, Godefroy, Olivier, Gyanwali, Bibek, Hamilton, Olivia K L, Hilal, Saima, Huenges Wajer, Irene M C, Kang, Yeonwook, Kappelle, L Jaap, Kim, Beom Joon, Köhler, Sebastian, de Kort, Paul L M, Koudstaal, Peter J, Kuchcinski, Gregory, Lam, Bonnie Y K, Lee, Byung-Chul, Lee, Keon-Joo, Lim, Jae-Sung, Lopes, Renaud, Makin, Stephen D J, Mendyk, Anne-Marie, Mok, Vincent C T, Oh, Mi Sun, van Oostenbrugge, Robert J, Roussel, Martine, Shi, Lin, Staals, Julie, del C Valdés-Hernández, Maria, Venketasubramanian, Narayanaswamy, Verhey, Frans R J, Wardlaw, Joanna M, Werring, David J, Xin, Xu, Yu, Kyung-Ho, van Zandvoort, Martine J E, Zhao, Lei, Biesbroek, J Matthijs, and Biessels, Geert Jan

Published
2021
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