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1,309 results on '"Hillert, Jan"'

1. Big Multiple Sclerosis Data network: an international registry research network

Author

Glaser, Anna, Butzkueven, Helmut, van der Walt, Anneke, Gray, Orla, Spelman, Tim, Zhu, Chao, Trojano, Maria, Iaffaldano, Pietro, Battaglia, Mario A., Lucisano, Giuseppe, Vukusic, Sandra, Vukusic, Irena, Casey, Romain, Horakova, Dana, Drahota, Jiri, Magyari, Melinda, Joensen, Hanna, Pontieri, Luigi, Elberling, Frederik, Klyve, Pernilla, Mouresan, Elena Flavia, Forsberg, Lars, and Hillert, Jan

Published
2024
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4. COVID-19–Related Enhancement for the COMBAT-MS Study

Author

Piehl, Fredrik, primary, Fogdell-Hahn, Anna, additional, Englund, Simon, additional, Asplund Högelin, Klara, additional, Smith, Jessica, additional, Li, Bonnie, additional, Burman, Joachim, additional, Fink, Katharina, additional, Gunnarsson, Martin, additional, Hillert, Jan, additional, Lycke, Jan, additional, Nilsson, Petra, additional, Salzer, Jonatan, additional, Svenningsson, Anders, additional, Vrethem, Magnus, additional, Olsson, Tomas, additional, Kockum, Ingrid, additional, Al Nimer, Faiez, additional, Longinetti, Elisa, additional, and Frisell, Thomas, additional

Published
2023
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5. A genetic-epigenetic interplay at 1q21.1 locus underlies CHD1L-mediated vulnerability to primary progressive multiple sclerosis

Author

Pahlevan Kakhki, Majid, Giordano, Antonino, Starvaggi Cucuzza, Chiara, Venkata S. Badam, Tejaswi, Samudyata, Samudyata, Lemée, Marianne Victoria, Stridh, Pernilla, Gkogka, Asimenia, Shchetynsky, Klementy, Harroud, Adil, Gyllenberg, Alexandra, Liu, Yun, Boddul, Sanjaykumar, James, Tojo, Sorosina, Melissa, Filippi, Massimo, Esposito, Federica, Wermeling, Fredrik, Gustafsson, Mika, Casaccia, Patrizia, Hillert, Jan, Olsson, Tomas, Kockum, Ingrid, Sellgren, Carl M., Golzio, Christelle, Kular, Lara, and Jagodic, Maja

Published
2024
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7. Does initial high efficacy therapy in multiple sclerosis surpass escalation treatment strategy? A comparison of patients with relapsing-remitting multiple sclerosis in the Czech and Swedish national multiple sclerosis registries

Author

Hrnciarova, Tereza, Drahota, Jiri, Spelman, Tim, Hillert, Jan, Lycke, Jan, Kubala Havrdova, Eva, Recmanova, Eva, Adamkova, Jana, Mares, Jan, Libertinova, Jana, Pavelek, Zbysek, Hradilek, Pavel, Ampapa, Radek, Stetkarova, Ivana, Peterka, Marek, Martinkova, Alena, Stourac, Pavel, Grunermelova, Marketa, Vachova, Marta, Dufek, Michal, and Horakova, Dana

Published
2023
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8. A topological data analysis based classification method for multiple measurements

Author

Riihimäki, Henri, Chachólski, Wojciech, Theorell, Jakob, Hillert, Jan, and Ramanujam, Ryan

Subjects
Computer Science - Machine Learning, Mathematics - Algebraic Topology, Statistics - Machine Learning
Abstract

Machine learning models for repeated measurements are limited. Using topological data analysis (TDA), we present a classifier for repeated measurements which samples from the data space and builds a network graph based on the data topology. When applying this to two case studies, accuracy exceeds alternative models with additional benefits such as reporting data subsets with high purity along with feature values. For 300 examples of 3 tree species, the accuracy reached 80% after 30 datapoints, which was improved to 90% after increased sampling to 400 datapoints. Using data from 100 examples of each of 6 point processes, the classifier achieved 96.8% accuracy. In both datasets, the TDA classifier outperformed an alternative model. This algorithm and software can be beneficial for repeated measurement data common in biological sciences, as both an accurate classifier and a feature selection tool., Comment: 8 pages, 7 figures

Published
2019

9. Multiple sclerosis lesions in motor tracts from brain to cervical cord: spatial distribution and correlation with disability.

Author

Kerbrat, Anne, Gros, Charley, Badji, Atef, Bannier, Elise, Galassi, Francesca, Combès, Benoit, Chouteau, Raphaël, Labauge, Pierre, Ayrignac, Xavier, Carra-Dalliere, Clarisse, Maranzano, Josefina, Granberg, Tobias, Ouellette, Russell, Stawiarz, Leszek, Hillert, Jan, Talbott, Jason, Tachibana, Yasuhiko, Hori, Masaaki, Kamiya, Kouhei, Chougar, Lydia, Lefeuvre, Jennifer, Reich, Daniel, Nair, Govind, Valsasina, Paola, Rocca, Maria, Filippi, Massimo, Chu, Renxin, Bakshi, Rohit, Callot, Virginie, Pelletier, Jean, Audoin, Bertrand, Maarouf, Adil, Collongues, Nicolas, De Seze, Jérôme, Edan, Gilles, and Cohen-Adad, Julien

Subjects
MRI, corticospinal tract, disability, multiple sclerosis, Adult, Brain, Cervical Cord, Disability Evaluation, Disease Progression, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Multiple Sclerosis, Pyramidal Tracts, Retrospective Studies
Abstract

Despite important efforts to solve the clinico-radiological paradox, correlation between lesion load and physical disability in patients with multiple sclerosis remains modest. One hypothesis could be that lesion location in corticospinal tracts plays a key role in explaining motor impairment. In this study, we describe the distribution of lesions along the corticospinal tracts from the cortex to the cervical spinal cord in patients with various disease phenotypes and disability status. We also assess the link between lesion load and location within corticospinal tracts, and disability at baseline and 2-year follow-up. We retrospectively included 290 patients (22 clinically isolated syndrome, 198 relapsing remitting, 39 secondary progressive, 31 primary progressive multiple sclerosis) from eight sites. Lesions were segmented on both brain (T2-FLAIR or T2-weighted) and cervical (axial T2- or T2*-weighted) MRI scans. Data were processed using an automated and publicly available pipeline. Brain, brainstem and spinal cord portions of the corticospinal tracts were identified using probabilistic atlases to measure the lesion volume fraction. Lesion frequency maps were produced for each phenotype and disability scores assessed with Expanded Disability Status Scale score and pyramidal functional system score. Results show that lesions were not homogeneously distributed along the corticospinal tracts, with the highest lesion frequency in the corona radiata and between C2 and C4 vertebral levels. The lesion volume fraction in the corticospinal tracts was higher in secondary and primary progressive patients (mean = 3.6 ± 2.7% and 2.9 ± 2.4%), compared to relapsing-remitting patients (1.6 ± 2.1%, both P

Published
2020

10. Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility

Author

Patsopoulos, Nikolaos A, Baranzini, Sergio E, Santaniello, Adam, Shoostari, Parisa, Cotsapas, Chris, Wong, Garrett, Beecham, Ashley H, James, Tojo, Replogle, Joseph, Vlachos, Ioannis S, McCabe, Cristin, Pers, Tune H, Brandes, Aaron, White, Charles, Keenan, Brendan, Cimpean, Maria, Winn, Phoebe, Panteliadis, Ioannis-Pavlos, Robbins, Allison, Andlauer, Till FM, Zarzycki, Onigiusz, Dubois, Bénédicte, Goris, An, Søndergaard, Helle Bach, Sellebjerg, Finn, Sorensen, Per Soelberg, Ullum, Henrik, Thørner, Lise Wegner, Saarela, Janna, Cournu-Rebeix, Isabelle, Damotte, Vincent, Fontaine, Bertrand, Guillot-Noel, Lena, Lathrop, Mark, Vukusic, Sandra, Berthele, Achim, Pongratz, Viola, Buck, Dorothea, Gasperi, Christiane, Graetz, Christiane, Grummel, Verena, Hemmer, Bernhard, Hoshi, Muni, Knier, Benjamin, Korn, Thomas, Lill, Christina M, Luessi, Felix, Mühlau, Mark, Zipp, Frauke, Dardiotis, Efthimios, Agliardi, Cristina, Amoroso, Antonio, Barizzone, Nadia, Benedetti, Maria D, Bernardinelli, Luisa, Cavalla, Paola, Clarelli, Ferdinando, Comi, Giancarlo, Cusi, Daniele, Esposito, Federica, Ferrè, Laura, Galimberti, Daniela, Guaschino, Clara, Leone, Maurizio A, Martinelli, Vittorio, Moiola, Lucia, Salvetti, Marco, Sorosina, Melissa, Vecchio, Domizia, Zauli, Andrea, Santoro, Silvia, Mancini, Nicasio, Zuccalà, Miriam, Mescheriakova, Julia, van Duijn, Cornelia, Bos, Steffan D, Celius, Elisabeth G, Spurkland, Anne, Comabella, Manuel, Montalban, Xavier, Alfredsson, Lars, Bomfim, Izaura L, Gomez-Cabrero, David, Hillert, Jan, Jagodic, Maja, Lindén, Magdalena, Piehl, Fredrik, Jelčić, Ilijas, Martin, Roland, Sospedra, Mirela, Baker, Amie, Ban, Maria, Hawkins, Clive, Hysi, Pirro, Kalra, Seema, Karpe, Fredrik, Khadake, Jyoti, Lachance, Genevieve, Molyneux, Paul, and Neville, Matthew

Subjects
Neurosciences, Brain Disorders, Multiple Sclerosis, Human Genome, Autoimmune Disease, Clinical Research, Genetics, Neurodegenerative, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Neurological, Case-Control Studies, Cell Cycle Proteins, Chromosome Mapping, Chromosomes, Human, X, GTPase-Activating Proteins, Gene Frequency, Genetic Loci, Genome-Wide Association Study, Genomics, Humans, Inheritance Patterns, Major Histocompatibility Complex, Microglia, Polymorphism, Single Nucleotide, Quantitative Trait Loci, RNA-Seq, Transcriptome, International Multiple Sclerosis Genetics Consortium, General Science & Technology
Abstract

We analyzed genetic data of 47,429 multiple sclerosis (MS) and 68,374 control subjects and established a reference map of the genetic architecture of MS that includes 200 autosomal susceptibility variants outside the major histocompatibility complex (MHC), one chromosome X variant, and 32 variants within the extended MHC. We used an ensemble of methods to prioritize 551 putative susceptibility genes that implicate multiple innate and adaptive pathways distributed across the cellular components of the immune system. Using expression profiles from purified human microglia, we observed enrichment for MS genes in these brain-resident immune cells, suggesting that these may have a role in targeting an autoimmune process to the central nervous system, although MS is most likely initially triggered by perturbation of peripheral immune responses.

Published
2019

12. Genetics of immune response to Epstein-Barr virus: prospects for multiple sclerosis pathogenesis

Author

Huang, Jesse, primary, Tengvall, Katarina, additional, Bomfim Lima, Izaura, additional, Hedström, Anna Karin, additional, Butt, Julia, additional, Brenner, Nicole, additional, Gyllenberg, Alexandra, additional, Stridh, Pernilla, additional, Khademi, Mohsen, additional, Ernberg, Ingemar, additional, Al Nimer, Faiez, additional, Manouchehrinia, Ali, additional, Hillert, Jan, additional, Alfredsson, Lars, additional, Andersen, Oluf, additional, Sundström, Peter, additional, Waterboer, Tim, additional, Olsson, Tomas, additional, and Kockum, Ingrid, additional

Published
2024
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13. Treatment Persistence of Cladribine Tablets Versus Other Oral Disease-modifying Treatments for Multiple Sclerosis: Results from Danish, Norwegian, and Swedish Registries (P10-6.015)

Author

Spelman, Timothy, primary, Aarseth, Jan Harald, additional, Celius, Elisabeth, additional, Wergeland, Stig, additional, Magyari, Melinda, additional, Framke, Elisabeth, additional, Tundia, Namita, additional, Wong, Schiffon, additional, and Hillert, Jan, additional

Published
2024
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16. Genetic variation inHIF1Ais associated with smoldering inflammation and disease progression in Multiple Sclerosis

Author

Giordano, Antonino, primary, Stridh, Pernilla, additional, Preziosa, Paolo, additional, Pisa, Marco, additional, Sorosina, Melissa, additional, Mascia, Elisabetta, additional, Santoro, Silvia, additional, Misra, Kaalindi, additional, Clarelli, Ferdinando, additional, Ferrè, Laura, additional, Needhamsen, Maria, additional, Manouchehrinia, Ali, additional, Cannizzaro, Miryam, additional, Moridi, Thomas, additional, Shchetynsky, Klementy, additional, Ouellette, Russell, additional, Harroud, Adil, additional, Sandberg, Elisabeth, additional, Kuttikkatte, Subita Balaram, additional, Piehl, Fredrik, additional, Alfredsson, Lars, additional, Hillert, Jan, additional, Olsson, Tomas, additional, Fugger, Lars, additional, Attfield, Kate, additional, Granberg, Tobias, additional, Jagodic, Maja, additional, DeLuca, Gabriele Carmine, additional, Rocca, Mara, additional, Filippi, Massimo, additional, Kockum, Ingrid, additional, and Esposito, Federica, additional

Published
2024
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17. Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks

Author

Gros, Charley, De Leener, Benjamin, Badji, Atef, Maranzano, Josefina, Eden, Dominique, Dupont, Sara M., Talbott, Jason, Zhuoquiong, Ren, Liu, Yaou, Granberg, Tobias, Ouellette, Russell, Tachibana, Yasuhiko, Hori, Masaaki, Kamiya, Kouhei, Chougar, Lydia, Stawiarz, Leszek, Hillert, Jan, Bannier, Elise, Kerbrat, Anne, Edan, Gilles, Labauge, Pierre, Callot, Virginie, Pelletier, Jean, Audoin, Bertrand, Rasoanandrianina, Henitsoa, Brisset, Jean-Christophe, Valsasina, Paola, Rocca, Maria A., Filippi, Massimo, Bakshi, Rohit, Tauhid, Shahamat, Prados, Ferran, Yiannakas, Marios, Kearney, Hugh, Ciccarelli, Olga, Smith, Seth, Treaba, Constantina Andrada, Mainero, Caterina, Lefeuvre, Jennifer, Reich, Daniel S., Nair, Govind, Auclair, Vincent, McLaren, Donald G., Martin, Allan R., Fehlings, Michael G., Vahdat, Shahabeddin, Khatibi, Ali, Doyon, Julien, Shepherd, Timothy, Charlson, Erik, Narayanan, Sridar, and Cohen-Adad, Julien

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of damage, which are key criteria for the diagnosis, prognosis, and longitudinal monitoring in MS. Automating this operation eliminates inter-rater variability and increases the efficiency of large-throughput analysis pipelines. Robust and reliable segmentation across multi-site spinal cord data is challenging because of the large variability related to acquisition parameters and image artifacts. The goal of this study was to develop a fully-automatic framework, robust to variability in both image parameters and clinical condition, for segmentation of the spinal cord and intramedullary MS lesions from conventional MRI data. Scans of 1,042 subjects (459 healthy controls, 471 MS patients, and 112 with other spinal pathologies) were included in this multi-site study (n=30). Data spanned three contrasts (T1-, T2-, and T2*-weighted) for a total of 1,943 volumes. The proposed cord and lesion automatic segmentation approach is based on a sequence of two Convolutional Neural Networks (CNNs). To deal with the very small proportion of spinal cord and/or lesion voxels compared to the rest of the volume, a first CNN with 2D dilated convolutions detects the spinal cord centerline, followed by a second CNN with 3D convolutions that segments the spinal cord and/or lesions. When compared against manual segmentation, our CNN-based approach showed a median Dice of 95% vs. 88% for PropSeg, a state-of-the-art spinal cord segmentation method. Regarding lesion segmentation on MS data, our framework provided a Dice of 60%, a relative volume difference of -15%, and a lesion-wise detection sensitivity and precision of 83% and 77%, respectively. The proposed framework is open-source and readily available in the Spinal Cord Toolbox., Comment: 38 pages, 7 figures, 2 tables

Published
2018

18. Spatial distribution of multiple sclerosis lesions in the cervical spinal cord.

Author

Eden, Dominique, Gros, Charley, Badji, Atef, Dupont, Sara, De Leener, Benjamin, Maranzano, Josefina, Zhuoquiong, Ren, Liu, Yaou, Granberg, Tobias, Ouellette, Russell, Stawiarz, Leszek, Hillert, Jan, Talbott, Jason, Bannier, Elise, Kerbrat, Anne, Edan, Gilles, Labauge, Pierre, Callot, Virginie, Pelletier, Jean, Audoin, Bertrand, Rasoanandrianina, Henitsoa, Brisset, Jean-Christophe, Valsasina, Paola, Rocca, Maria, Filippi, Massimo, Bakshi, Rohit, Tauhid, Shahamat, Prados, Ferran, Yiannakas, Marios, Kearney, Hugh, Ciccarelli, Olga, Smith, Seth, Andrada Treaba, Constantina, Mainero, Caterina, Lefeuvre, Jennifer, Reich, Daniel, Nair, Govind, Shepherd, Timothy, Charlson, Erik, Tachibana, Yasuhiko, Hori, Masaaki, Kamiya, Kouhei, Chougar, Lydia, Narayanan, Sridar, and Cohen-Adad, Julien

Subjects
MRI, lesions, multicentre, multiple sclerosis, spinal cord, Adult, Brain, Cervical Cord, Disability Evaluation, Disease Progression, Female, Gray Matter, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Multiple Sclerosis, Multiple Sclerosis, Chronic Progressive, Multiple Sclerosis, Relapsing-Remitting, Spatial Analysis, Spinal Cord, Spinal Cord Diseases, White Matter
Abstract

Spinal cord lesions detected on MRI hold important diagnostic and prognostic value for multiple sclerosis. Previous attempts to correlate lesion burden with clinical status have had limited success, however, suggesting that lesion location may be a contributor. Our aim was to explore the spatial distribution of multiple sclerosis lesions in the cervical spinal cord, with respect to clinical status. We included 642 suspected or confirmed multiple sclerosis patients (31 clinically isolated syndrome, and 416 relapsing-remitting, 84 secondary progressive, and 73 primary progressive multiple sclerosis) from 13 clinical sites. Cervical spine lesions were manually delineated on T2- and T2*-weighted axial and sagittal MRI scans acquired at 3 or 7 T. With an automatic publicly-available analysis pipeline we produced voxelwise lesion frequency maps to identify predilection sites in various patient groups characterized by clinical subtype, Expanded Disability Status Scale score and disease duration. We also measured absolute and normalized lesion volumes in several regions of interest using an atlas-based approach, and evaluated differences within and between groups. The lateral funiculi were more frequently affected by lesions in progressive subtypes than in relapsing in voxelwise analysis (P < 0.001), which was further confirmed by absolute and normalized lesion volumes (P < 0.01). The central cord area was more often affected by lesions in primary progressive than relapse-remitting patients (P < 0.001). Between white and grey matter, the absolute lesion volume in the white matter was greater than in the grey matter in all phenotypes (P < 0.001); however when normalizing by each region, normalized lesion volumes were comparable between white and grey matter in primary progressive patients. Lesions appearing in the lateral funiculi and central cord area were significantly correlated with Expanded Disability Status Scale score (P < 0.001). High lesion frequencies were observed in patients with a more aggressive disease course, rather than long disease duration. Lesions located in the lateral funiculi and central cord area of the cervical spine may influence clinical status in multiple sclerosis. This work shows the added value of cervical spine lesions, and provides an avenue for evaluating the distribution of spinal cord lesions in various patient groups.

Published
2019

19. Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks

Author

Gros, Charley, De Leener, Benjamin, Badji, Atef, Maranzano, Josefina, Eden, Dominique, Dupont, Sara M, Talbott, Jason, Zhuoquiong, Ren, Liu, Yaou, Granberg, Tobias, Ouellette, Russell, Tachibana, Yasuhiko, Hori, Masaaki, Kamiya, Kouhei, Chougar, Lydia, Stawiarz, Leszek, Hillert, Jan, Bannier, Elise, Kerbrat, Anne, Edan, Gilles, Labauge, Pierre, Callot, Virginie, Pelletier, Jean, Audoin, Bertrand, Rasoanandrianina, Henitsoa, Brisset, Jean-Christophe, Valsasina, Paola, Rocca, Maria A, Filippi, Massimo, Bakshi, Rohit, Tauhid, Shahamat, Prados, Ferran, Yiannakas, Marios, Kearney, Hugh, Ciccarelli, Olga, Smith, Seth, Treaba, Constantina Andrada, Mainero, Caterina, Lefeuvre, Jennifer, Reich, Daniel S, Nair, Govind, Auclair, Vincent, McLaren, Donald G, Martin, Allan R, Fehlings, Michael G, Vahdat, Shahabeddin, Khatibi, Ali, Doyon, Julien, Shepherd, Timothy, Charlson, Erik, Narayanan, Sridar, and Cohen-Adad, Julien

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Spinal Cord Injury, Neurodegenerative, Bioengineering, Autoimmune Disease, Traumatic Head and Spine Injury, Physical Injury - Accidents and Adverse Effects, Brain Disorders, Biomedical Imaging, Multiple Sclerosis, Neurosciences, Neurological, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Neural Networks, Computer, Observer Variation, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity, Spinal Cord, MRI, Segmentation, Spinal cord, Multiple sclerosis, Convolutional neural networks, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences
Abstract

The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of damage, which are key criteria for the diagnosis, prognosis, and longitudinal monitoring in MS. Automating this operation eliminates inter-rater variability and increases the efficiency of large-throughput analysis pipelines. Robust and reliable segmentation across multi-site spinal cord data is challenging because of the large variability related to acquisition parameters and image artifacts. In particular, a precise delineation of lesions is hindered by a broad heterogeneity of lesion contrast, size, location, and shape. The goal of this study was to develop a fully-automatic framework - robust to variability in both image parameters and clinical condition - for segmentation of the spinal cord and intramedullary MS lesions from conventional MRI data of MS and non-MS cases. Scans of 1042 subjects (459 healthy controls, 471 MS patients, and 112 with other spinal pathologies) were included in this multi-site study (n = 30). Data spanned three contrasts (T1-, T2-, and T2∗-weighted) for a total of 1943 vol and featured large heterogeneity in terms of resolution, orientation, coverage, and clinical conditions. The proposed cord and lesion automatic segmentation approach is based on a sequence of two Convolutional Neural Networks (CNNs). To deal with the very small proportion of spinal cord and/or lesion voxels compared to the rest of the volume, a first CNN with 2D dilated convolutions detects the spinal cord centerline, followed by a second CNN with 3D convolutions that segments the spinal cord and/or lesions. CNNs were trained independently with the Dice loss. When compared against manual segmentation, our CNN-based approach showed a median Dice of 95% vs. 88% for PropSeg (p ≤ 0.05), a state-of-the-art spinal cord segmentation method. Regarding lesion segmentation on MS data, our framework provided a Dice of 60%, a relative volume difference of -15%, and a lesion-wise detection sensitivity and precision of 83% and 77%, respectively. In this study, we introduce a robust method to segment the spinal cord and intramedullary MS lesions on a variety of MRI contrasts. The proposed framework is open-source and readily available in the Spinal Cord Toolbox.

Published
2019

20. Comparing the Safety of Medicines to Treat MS during the COVID-19 Pandemic

Author

Piehl, Fredrick, primary, Fogdell-Hahn, Anna, additional, Englund, Simon, additional, Asplund Högelin, Klara, additional, Smith, Jessica, additional, Li, Bonnie, additional, Burman, Joachim, additional, Fink, Katharina, additional, Gunnarsson, Martin, additional, Hillert, Jan, additional, Lycke, Jan, additional, Nilsson, Petra, additional, Salzer, Jonatan, additional, Svenningsson, Anders, additional, Vrethem, Magnus, additional, Olsson, Tomas, additional, Kockum, Ingrid, additional, Al Nimer, Faiez, additional, Longinetti, Elisa, additional, Frisell, Thomas, additional, and Langer-Gould, Annette, additional

Published
2023
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21. Genetic risk factors for pediatric-onset multiple sclerosis.

Author

Gianfrancesco, Milena A, Stridh, Pernilla, Shao, Xiaorong, Rhead, Brooke, Graves, Jennifer S, Chitnis, Tanuja, Waldman, Amy, Lotze, Timothy, Schreiner, Teri, Belman, Anita, Greenberg, Benjamin, Weinstock-Guttman, Bianca, Aaen, Gregory, Tillema, Jan M, Hart, Janace, Caillier, Stacy, Ness, Jayne, Harris, Yolanda, Rubin, Jennifer, Candee, Meghan, Krupp, Lauren, Gorman, Mark, Benson, Leslie, Rodriguez, Moses, Mar, Soe, Kahn, Ilana, Rose, John, Roalstad, Shelly, Casper, T Charles, Shen, Ling, Quach, Hong, Quach, Diana, Hillert, Jan, Hedstrom, Anna, Olsson, Tomas, Kockum, Ingrid, Alfredsson, Lars, Schaefer, Catherine, Barcellos, Lisa F, Waubant, Emmanuelle, and Network of Pediatric Multiple Sclerosis Centers

Subjects
Network of Pediatric Multiple Sclerosis Centers, Humans, Multiple Sclerosis, Genetic Predisposition to Disease, Logistic Models, Risk Factors, Polymorphism, Single Nucleotide, Sweden, Female, Male, Genetic Testing, HLA-DRB1 Chains, Multiple sclerosis, epidemiology, genetics, pediatrics, Brain Disorders, Human Genome, Autoimmune Disease, Genetics, Prevention, Neurosciences, Neurodegenerative, Aetiology, 2.1 Biological and endogenous factors, Clinical Sciences, Neurology & Neurosurgery
Abstract

BackgroundStrong evidence supports the role of both genetic and environmental factors in pediatric-onset multiple sclerosis (POMS) etiology.ObjectiveWe comprehensively investigated the association between established major histocompatibility complex (MHC) and non-MHC adult multiple sclerosis (MS)-associated variants and susceptibility to POMS.MethodsCases with onset

Published
2018

22. Fine-mapping genomic loci refines bipolar disorder risk genes

Author

Koromina, Maria, primary, Ravi, Ashvin, additional, Panagiotaropoulou, Georgia, additional, Schilder, Brian M., additional, Humphrey, Jack, additional, Braun, Alice, additional, Bidgeli, Tim, additional, Chatzinakos, Chris, additional, Coombes, Brandon, additional, Kim, Jaeyoung, additional, Liu, Xiaoxi, additional, Terao, Chikashi, additional, O'Connell, Kevin S., additional, Adams, Mark, additional, Adolfsson, Rolf, additional, Alda, Martin, additional, Alfredsson, Lars, additional, Andlauer, Till F.M., additional, Andreassen, Ole A., additional, Antoniou, Anastasia, additional, Baune, Bernhard T., additional, Bengesser, Susanne, additional, Biernacka, Joanna, additional, Boehnke, Michael, additional, Bosch, Rosa, additional, Cairns, Murray, additional, Carr, Vaughan J., additional, Casas, Miquel, additional, Catts, Stanley, additional, Cichon, Sven, additional, Corvin, Aiden, additional, Craddock, Nicholas, additional, Dafnas, Konstantinos, additional, Dalkner, Nina, additional, Dannlowski, Udo, additional, Degenhardt, Franziska, additional, Di Florio, Arianna, additional, Dikeos, Dimitris, additional, Fellendorf, Frederike Tabea, additional, Ferentinos, Panagiotis, additional, Forstner, Andreas J., additional, Forty, Liz, additional, Frye, Mark, additional, Fullerton, Janice M., additional, Gawlik, Micha, additional, Gizer, Ian R., additional, Gordon-Smith, Katherine, additional, Green, Melissa J., additional, Grigoroiu-Serbanescu, Maria, additional, Guzman-Parra, Josep, additional, Hahn, Tim, additional, Henskens, Frans, additional, Hillert, Jan, additional, Jablensky, Assen V., additional, Jones, Lisa, additional, Jones, Ian, additional, Jonsson, Lina, additional, Kelsoe, John R., additional, Kircher, Tilo, additional, Kirov, George, additional, Kittel-Schneider, Sarah, additional, Kogevinas, Manolis, additional, Landen, Mikael, additional, Leboyer, Marion, additional, Lenger, Melanie, additional, Lissowska, Jolanta, additional, Lochner, Christine, additional, Loughland, Carmel, additional, MacIntyre, Donald, additional, Martin, Nicholas G., additional, Maratou, Eirini, additional, Mathews, Carol A., additional, Mayoral, Fermin, additional, McElroy, Susan L., additional, McGregor, Nathaniel W., additional, McIntosh, Andrew, additional, McQuillin, Andrew, additional, Michie, Patricia, additional, Mitchell, Philip B., additional, Moutsatsou, Paraskevi, additional, Mowry, Bryan, additional, Mueller-Myhsok, Bertram, additional, Myers, Richard, additional, Nenadic, Igor, additional, Noethen, Markus M., additional, O'Donovan, Michael, additional, O'Donovan, Claire, additional, Ophoff, Roel A., additional, Owen, Michael J., additional, Pantelis, Chris, additional, Pato, Carlos, additional, Pato, Michele T., additional, Patrinos, George P., additional, Pawlak, Joanna M., additional, Perlis, Roy H., additional, Porichi, Evgenia, additional, Posthuma, Danielle, additional, Ramos-Quiroga, Josep Antoni, additional, Reif, Andreas, additional, Reininghaus, Eva Z., additional, Ribases, Marta, additional, Rietschel, Marcella, additional, Schall, Ulrich, additional, Schulze, Thomas G., additional, Scott, Laura, additional, Scott, Rodney J., additional, Serretti, Alessandro, additional, Shannon Weickert, Cynthia, additional, Smoller, Jordan W., additional, Soler Artigas, Maria Soler, additional, Stein, Dan J., additional, Streit, Fabian, additional, Toma, Claudio, additional, Tooney, Paul, additional, Vieta, Eduard, additional, Vincent, John B., additional, Waldman, Irwin D., additional, Weickert, Thomas, additional, Witt, Stephanie H., additional, Swiatkowska, Beata, additional, Hong, Kyung Sue Sue, additional, Ikeda, Masashi, additional, Iwata, Nakao, additional, Won, Hong-Hee, additional, Edenberg, Howard J., additional, Ripke, Stephan, additional, Raj, Towfique, additional, Coleman, Jonathan R. I., additional, and Mullins, Niamh, additional

Published
2024
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24. Introducing a core dataset for real-world data in multiple sclerosis registries and cohorts: Recommendations from a global task force

Author

Parciak, Tina, primary, Geys, Lotte, additional, Helme, Anne, additional, van der Mei, Ingrid, additional, Hillert, Jan, additional, Schmidt, Hollie, additional, Salter, Amber, additional, Zakaria, Magd, additional, Middleton, Rodden, additional, Stahmann, Alexander, additional, Dobay, Pamela, additional, Hernandez Martinez-Lapiscina, Elena, additional, Iaffaldano, Pietro, additional, Plueschke, Kelly, additional, Rojas, Juan I, additional, Sabidó, Meritxell, additional, Magyari, Melinda, additional, van der Walt, Anneke, additional, Arickx, Francis, additional, Comi, Giancarlo, additional, and Peeters, Liesbet M, additional

Published
2023
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27. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology

Author

Mullins, Niamh, Forstner, Andreas J., O’Connell, Kevin S., Coombes, Brandon, Coleman, Jonathan R. I., Qiao, Zhen, Als, Thomas D., Bigdeli, Tim B., Børte, Sigrid, Bryois, Julien, Charney, Alexander W., Drange, Ole Kristian, Gandal, Michael J., Hagenaars, Saskia P., Ikeda, Masashi, Kamitaki, Nolan, Kim, Minsoo, Krebs, Kristi, Panagiotaropoulou, Georgia, Schilder, Brian M., Sloofman, Laura G., Steinberg, Stacy, Trubetskoy, Vassily, Winsvold, Bendik S., Won, Hong-Hee, Abramova, Liliya, Adorjan, Kristina, Agerbo, Esben, Al Eissa, Mariam, Albani, Diego, Alliey-Rodriguez, Ney, Anjorin, Adebayo, Antilla, Verneri, Antoniou, Anastasia, Awasthi, Swapnil, Baek, Ji Hyun, Bækvad-Hansen, Marie, Bass, Nicholas, Bauer, Michael, Beins, Eva C., Bergen, Sarah E., Birner, Armin, Bøcker Pedersen, Carsten, Bøen, Erlend, Boks, Marco P., Bosch, Rosa, Brum, Murielle, Brumpton, Ben M., Brunkhorst-Kanaan, Nathalie, Budde, Monika, Bybjerg-Grauholm, Jonas, Byerley, William, Cairns, Murray, Casas, Miquel, Cervantes, Pablo, Clarke, Toni-Kim, Cruceanu, Cristiana, Cuellar-Barboza, Alfredo, Cunningham, Julie, Curtis, David, Czerski, Piotr M., Dale, Anders M., Dalkner, Nina, David, Friederike S., Degenhardt, Franziska, Djurovic, Srdjan, Dobbyn, Amanda L., Douzenis, Athanassios, Elvsåshagen, Torbjørn, Escott-Price, Valentina, Ferrier, I. Nicol, Fiorentino, Alessia, Foroud, Tatiana M., Forty, Liz, Frank, Josef, Frei, Oleksandr, Freimer, Nelson B., Frisén, Louise, Gade, Katrin, Garnham, Julie, Gelernter, Joel, Giørtz Pedersen, Marianne, Gizer, Ian R., Gordon, Scott D., Gordon-Smith, Katherine, Greenwood, Tiffany A., Grove, Jakob, Guzman-Parra, José, Ha, Kyooseob, Haraldsson, Magnus, Hautzinger, Martin, Heilbronner, Urs, Hellgren, Dennis, Herms, Stefan, Hoffmann, Per, Holmans, Peter A., Huckins, Laura, Jamain, Stéphane, Johnson, Jessica S., Kalman, Janos L., Kamatani, Yoichiro, Kennedy, James L., Kittel-Schneider, Sarah, Knowles, James A., Kogevinas, Manolis, Koromina, Maria, Kranz, Thorsten M., Kranzler, Henry R., Kubo, Michiaki, Kupka, Ralph, Kushner, Steven A., Lavebratt, Catharina, Lawrence, Jacob, Leber, Markus, Lee, Heon-Jeong, Lee, Phil H., Levy, Shawn E., Lewis, Catrin, Liao, Calwing, Lucae, Susanne, Lundberg, Martin, MacIntyre, Donald J., Magnusson, Sigurdur H., Maier, Wolfgang, Maihofer, Adam, Malaspina, Dolores, Maratou, Eirini, Martinsson, Lina, Mattheisen, Manuel, McCarroll, Steven A., McGregor, Nathaniel W., McGuffin, Peter, McKay, James D., Medeiros, Helena, Medland, Sarah E., Millischer, Vincent, Montgomery, Grant W., Moran, Jennifer L., Morris, Derek W., Mühleisen, Thomas W., O’Brien, Niamh, O’Donovan, Claire, Olde Loohuis, Loes M., Oruc, Lilijana, Papiol, Sergi, Pardiñas, Antonio F., Perry, Amy, Pfennig, Andrea, Porichi, Evgenia, Potash, James B., Quested, Digby, Raj, Towfique, Rapaport, Mark H., DePaulo, J. Raymond, Regeer, Eline J., Rice, John P., Rivas, Fabio, Rivera, Margarita, Roth, Julian, Roussos, Panos, Ruderfer, Douglas M., Sánchez-Mora, Cristina, Schulte, Eva C., Senner, Fanny, Sharp, Sally, Shilling, Paul D., Sigurdsson, Engilbert, Sirignano, Lea, Slaney, Claire, Smeland, Olav B., Smith, Daniel J., Sobell, Janet L., Søholm Hansen, Christine, Soler Artigas, Maria, Spijker, Anne T., Stein, Dan J., Strauss, John S., Świątkowska, Beata, Terao, Chikashi, Thorgeirsson, Thorgeir E., Toma, Claudio, Tooney, Paul, Tsermpini, Evangelia-Eirini, Vawter, Marquis P., Vedder, Helmut, Walters, James T. R., Witt, Stephanie H., Xi, Simon, Xu, Wei, Yang, Jessica Mei Kay, Young, Allan H., Young, Hannah, Zandi, Peter P., Zhou, Hang, Zillich, Lea, Adolfsson, Rolf, Agartz, Ingrid, Alda, Martin, Alfredsson, Lars, Babadjanova, Gulja, Backlund, Lena, Baune, Bernhard T., Bellivier, Frank, Bengesser, Susanne, Berrettini, Wade H., Blackwood, Douglas H. R., Boehnke, Michael, Børglum, Anders D., Breen, Gerome, Carr, Vaughan J., Catts, Stanley, Corvin, Aiden, Craddock, Nicholas, Dannlowski, Udo, Dikeos, Dimitris, Esko, Tõnu, Etain, Bruno, Ferentinos, Panagiotis, Frye, Mark, Fullerton, Janice M., Gawlik, Micha, Gershon, Elliot S., Goes, Fernando S., Green, Melissa J., Grigoroiu-Serbanescu, Maria, Hauser, Joanna, Henskens, Frans, Hillert, Jan, Hong, Kyung Sue, Hougaard, David M., Hultman, Christina M., Hveem, Kristian, Iwata, Nakao, Jablensky, Assen V., Jones, Ian, Jones, Lisa A., Kahn, René S., Kelsoe, John R., Kirov, George, Landén, Mikael, Leboyer, Marion, Lewis, Cathryn M., Li, Qingqin S., Lissowska, Jolanta, Lochner, Christine, Loughland, Carmel, Martin, Nicholas G., Mathews, Carol A., Mayoral, Fermin, McElroy, Susan L., McIntosh, Andrew M., McMahon, Francis J., Melle, Ingrid, Michie, Patricia, Milani, Lili, Mitchell, Philip B., Morken, Gunnar, Mors, Ole, Mortensen, Preben Bo, Mowry, Bryan, Müller-Myhsok, Bertram, Myers, Richard M., Neale, Benjamin M., Nievergelt, Caroline M., Nordentoft, Merete, Nöthen, Markus M., O’Donovan, Michael C., Oedegaard, Ketil J., Olsson, Tomas, Owen, Michael J., Paciga, Sara A., Pantelis, Chris, Pato, Carlos, Pato, Michele T., Patrinos, George P., Perlis, Roy H., Posthuma, Danielle, Ramos-Quiroga, Josep Antoni, Reif, Andreas, Reininghaus, Eva Z., Ribasés, Marta, Rietschel, Marcella, Ripke, Stephan, Rouleau, Guy A., Saito, Takeo, Schall, Ulrich, Schalling, Martin, Schofield, Peter R., Schulze, Thomas G., Scott, Laura J., Scott, Rodney J., Serretti, Alessandro, Shannon Weickert, Cynthia, Smoller, Jordan W., Stefansson, Hreinn, Stefansson, Kari, Stordal, Eystein, Streit, Fabian, Sullivan, Patrick F., Turecki, Gustavo, Vaaler, Arne E., Vieta, Eduard, Vincent, John B., Waldman, Irwin D., Weickert, Thomas W., Werge, Thomas, Wray, Naomi R., Zwart, John-Anker, Biernacka, Joanna M., Nurnberger, John I., Cichon, Sven, Edenberg, Howard J., Stahl, Eli A., McQuillin, Andrew, Di Florio, Arianna, Ophoff, Roel A., and Andreassen, Ole A.

Published
2021
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28. Updated Results of the COVID-19 in MS Global Data Sharing Initiative: Anti-CD20 and Other Risk Factors Associated With COVID-19 Severity

Author

Simpson-Yap, Steve, Pirmani, Ashkan, Kalincik, Tomas, De Brouwer, Edward, Geys, Lotte, Parciak, Tina, Helme, Anne, Rijke, Nick, Hillert, Jan A., Moreau, Yves, Edan, Gilles, Sharmin, Sifat, Spelman, Tim, McBurney, Robert, Schmidt, Hollie, Bergmann, Arnfin B., Braune, Stefan, Stahmann, Alexander, Middleton, Rod M., Salter, Amber, Bebo, Bruce, Van der Walt, Anneke, Butzkueven, Helmut, Ozakbas, Serkan, Boz, Cavit, Karabudak, Rana, Alroughani, Raed, Rojas, Juan I., van der Mei, Ingrid A., Sciascia do Olival, Guilherme, Magyari, Melinda, Alonso, Ricardo N., Nicholas, Richard S., Chertcoff, Anibal S., de Torres, Ana Zabalza, Arrambide, Georgina, Nag, Nupur, Descamps, Annabel, Costers, Lars, Dobson, Ruth, Miller, Aleisha, Rodrigues, Paulo, Prčkovska, Vesna, Comi, Giancarlo, and Peeters, Liesbet M.

Published
2022
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29. Evidence for a causal relationship between low vitamin D, high BMI, and pediatric-onset MS

Author

Gianfrancesco, Milena A, Stridh, Pernilla, Rhead, Brooke, Shao, Xiaorong, Xu, Edison, Graves, Jennifer S, Chitnis, Tanuja, Waldman, Amy, Lotze, Timothy, Schreiner, Teri, Belman, Anita, Greenberg, Benjamin, Weinstock-Guttman, Bianca, Aaen, Gregory, Tillema, Jan M, Hart, Janace, Caillier, Stacy, Ness, Jayne, Harris, Yolanda, Rubin, Jennifer, Candee, Meghan, Krupp, Lauren, Gorman, Mark, Benson, Leslie, Rodriguez, Moses, Mar, Soe, Kahn, Ilana, Rose, John, Roalstad, Shelly, Casper, T Charles, Shen, Ling, Quach, Hong, Quach, Diana, Hillert, Jan, Bäärnhielm, Maria, Hedstrom, Anna, Olsson, Tomas, Kockum, Ingrid, Alfredsson, Lars, Metayer, Catherine, Schaefer, Catherine, Barcellos, Lisa F, and Waubant, Emmanuelle

Subjects
Neurosciences, Pediatric, Multiple Sclerosis, Brain Disorders, Prevention, Clinical Research, Nutrition, Genetics, Neurodegenerative, Autoimmune Disease, 2.1 Biological and endogenous factors, Aetiology, Adolescent, Age of Onset, Biomarkers, Body Mass Index, Female, Genetic Predisposition to Disease, HLA-DRB1 Chains, Humans, Male, Mendelian Randomization Analysis, Risk, Sweden, United States, Vitamin D, White People, Network of Pediatric Multiple Sclerosis Centers, Clinical Sciences, Cognitive Sciences, Neurology & Neurosurgery
Abstract

ObjectiveTo utilize Mendelian randomization to estimate the causal association between low serum vitamin D concentrations, increased body mass index (BMI), and pediatric-onset multiple sclerosis (MS) using genetic risk scores (GRS).MethodsWe constructed an instrumental variable for vitamin D (vitD GRS) by computing a GRS for 3 genetic variants associated with levels of 25(OH)D in serum using the estimated effect of each risk variant. A BMI GRS was also created that incorporates the cumulative effect of 97 variants associated with BMI. Participants included non-Hispanic white individuals recruited from over 15 sites across the United States (n = 394 cases, 10,875 controls) and Sweden (n = 175 cases, 5,376 controls; total n = 16,820).ResultsMeta-analysis findings demonstrated that a vitD GRS associated with increasing levels of 25(OH)D in serum decreased the odds of pediatric-onset MS (odds ratio [OR] 0.72, 95% confidence interval [CI] 0.55, 0.94; p = 0.02) after controlling for sex, genetic ancestry, HLA-DRB1*15:01, and over 100 non-human leukocyte antigen MS risk variants. A significant association between BMI GRS and pediatric disease onset was also demonstrated (OR 1.17, 95% CI 1.05, 1.30; p = 0.01) after adjusting for covariates. Estimates for each GRS were unchanged when considered together in a multivariable model.ConclusionsWe provide evidence supporting independent and causal effects of decreased vitamin D levels and increased BMI on susceptibility to pediatric-onset MS.

Published
2017

30. Causal Effect of Genetic Variants Associated With Body Mass Index on Multiple Sclerosis Susceptibility.

Author

Gianfrancesco, Milena, Glymour, M, Walter, Stefan, Rhead, Brooke, Shao, Xiaorong, Shen, Ling, Quach, Hong, Hubbard, Alan, Jónsdóttir, Ingileif, Stefánsson, Kári, Strid, Pernilla, Hillert, Jan, Hedström, Anna, Olsson, Tomas, Kockum, Ingrid, Schaefer, Catherine, Alfredsson, Lars, and Barcellos, Lisa

Subjects
Mendelian randomization, body mass index, genetic instrumental variables, multiple sclerosis, obesity, Adult, Body Mass Index, Case-Control Studies, Female, Genetic Predisposition to Disease, Genetic Variation, Humans, Male, Mendelian Randomization Analysis, Middle Aged, Multiple Sclerosis
Abstract

Multiple sclerosis (MS) is an autoimmune disease with both genetic and environmental risk factors. Recent studies indicate that childhood and adolescent obesity double the risk of MS, but this association may reflect unmeasured confounders rather than causal effects of obesity. We used separate-sample Mendelian randomization to estimate the causal effect of body mass index (BMI) on susceptibility to MS. Using data from non-Hispanic white members of the Kaiser Permanente Medical Care Plan of Northern California (KPNC) (2006-2014; 1,104 cases of MS and 10,536 controls) and a replication data set from Sweden (the Epidemiological Investigation of MS (EIMS) and the Genes and Environment in MS (GEMS) studies, 2005-2013; 5,133 MS cases and 4,718 controls), we constructed a weighted genetic risk score using 97 variants previously established to predict BMI. Results were adjusted for birth year, sex, education, smoking status, ancestry, and genetic predictors of MS. Estimates in KPNC and Swedish data sets suggested that higher genetically induced BMI predicted greater susceptibility to MS (odds ratio = 1.13, 95% confidence interval: 1.04, 1.22 for the KPNC sample; odds ratio = 1.09, 95% confidence interval: 1.03, 1.15 for the Swedish sample). Although the mechanism remains unclear, to our knowledge, these findings support a causal effect of increased BMI on susceptibility to MS for the first time, and they suggest a role for inflammatory pathways that characterize both obesity and the MS disease process.

Published
2017

31. Mendelian randomization shows a causal effect of low vitamin D on multiple sclerosis risk

Author

Rhead, Brooke, Bäärnhielm, Maria, Gianfrancesco, Milena, Mok, Amanda, Shao, Xiaorong, Quach, Hong, Shen, Ling, Schaefer, Catherine, Link, Jenny, Gyllenberg, Alexandra, Hedström, Anna Karin, Olsson, Tomas, Hillert, Jan, Kockum, Ingrid, Glymour, M Maria, Alfredsson, Lars, and Barcellos, Lisa F

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Human Genome, Brain Disorders, Neurosciences, Clinical Research, Prevention, Multiple Sclerosis, Neurodegenerative, Autoimmune Disease, Aetiology, 2.1 Biological and endogenous factors, Neurological, Clinical sciences
Abstract

ObjectiveWe sought to estimate the causal effect of low serum 25(OH)D on multiple sclerosis (MS) susceptibility that is not confounded by environmental or lifestyle factors or subject to reverse causality.MethodsWe conducted mendelian randomization (MR) analyses using an instrumental variable (IV) comprising 3 single nucleotide polymorphisms found to be associated with serum 25(OH)D levels at genome-wide significance. We analyzed the effect of the IV on MS risk and both age at onset and disease severity in 2 separate populations using logistic regression models that controlled for sex, year of birth, smoking, education, genetic ancestry, body mass index at age 18-20 years or in 20s, a weighted genetic risk score for 110 known MS-associated variants, and the presence of one or more HLA-DRB1*15:01 alleles.ResultsFindings from MR analyses using the IV showed increasing levels of 25(OH)D are associated with a decreased risk of MS in both populations. In white, non-Hispanic members of Kaiser Permanente Northern California (1,056 MS cases and 9,015 controls), the odds ratio (OR) was 0.79 (p = 0.04, 95% confidence interval (CI): 0.64-0.99). In members of a Swedish population from the Epidemiological Investigation of Multiple Sclerosis and Genes and Environment in Multiple Sclerosis MS case-control studies (6,335 cases and 5,762 controls), the OR was 0.86 (p = 0.03, 95% CI: 0.76-0.98). A meta-analysis of the 2 populations gave a combined OR of 0.85 (p = 0.003, 95% CI: 0.76-0.94). No association was observed for age at onset or disease severity.ConclusionsThese results provide strong evidence that low serum 25(OH)D concentration is a cause of MS, independent of established risk factors.

Published
2016

32. Introducing a core dataset for real-world data in multiple sclerosis registries and cohorts: Recommendations from a global task force.

Author

Parciak, Tina, Geys, Lotte, Helme, Anne, van der Mei, Ingrid, Hillert, Jan, Schmidt, Hollie, Salter, Amber, Zakaria, Magd, Middleton, Rodden, Stahmann, Alexander, Dobay, Pamela, Hernandez Martinez-Lapiscina, Elena, Iaffaldano, Pietro, Plueschke, Kelly, Rojas, Juan I, Sabidó, Meritxell, Magyari, Melinda, van der Walt, Anneke, Arickx, Francis, and Comi, Giancarlo

Subjects
TASK forces, MULTIPLE sclerosis, MAGNETIC resonance imaging, DATA dictionaries
Abstract

Background: As of September 2022, there was no globally recommended set of core data elements for use in multiple sclerosis (MS) healthcare and research. As a result, data harmonisation across observational data sources and scientific collaboration is limited. Objectives: To define and agree upon a core dataset for real-world data (RWD) in MS from observational registries and cohorts. Methods: A three-phase process approach was conducted combining a landscaping exercise with dedicated discussions within a global multi-stakeholder task force consisting of 20 experts in the field of MS and its RWD to define the Core Dataset. Results: A core dataset for MS consisting of 44 variables in eight categories was translated into a data dictionary that has been published and disseminated for emerging and existing registries and cohorts to use. Categories include variables on demographics and comorbidities (patient-specific data), disease history, disease status, relapses, magnetic resonance imaging (MRI) and treatment data (disease-specific data). Conclusion: The MS Data Alliance Core Dataset guides emerging registries in their dataset definitions and speeds up and supports harmonisation across registries and initiatives. The straight-forward, time-efficient process using a dedicated global multi-stakeholder task force has proven to be effective to define a concise core dataset. [ABSTRACT FROM AUTHOR]

Published
2024
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33. Risk of Multiple Sclerosis in People Living with HIV: An International Cohort Study.

Author

McKay, Kyla A., Wijnands, José M. A., Manouchehrinia, Ali, Zhu, Feng, Sereda, Paul, Li, Jenny, Ye, Monica, Trigg, Jason, Kooij, Katherine, Ekström, Anna Mia, Gisslén, Magnus, Hillert, Jan, Hogg, Robert S., Tremlett, Helen, and Kingwell, Elaine

Subjects
HIV-positive persons, MULTIPLE sclerosis, EXPOSURE therapy, COHORT analysis, ANTIRETROVIRAL agents
Abstract

Objective: There has been interest in a possible negative association between HIV and multiple sclerosis (MS). We aimed to compare the risk of MS in a cohort of individuals living with HIV to that in the general population. Methods: Population‐based health data were accessed for 2 cohorts of HIV‐positive persons from Sweden and British Columbia, Canada. Incident MS was identified using MS registries or a validated algorithm applied to administrative data. Individuals with HIV were followed from 1 year after the first clinical evidence of HIV or the first date of complete administrative health data (Canada = April 1, 1992 and Sweden = January 1, 2001) until the earliest of incident MS, emigration, death, or study end (Canada = March 31, 2020 and Sweden = December 31, 2018). The observed MS incidence rate in the HIV‐positive cohort was compared to the expected age‐, sex‐, calendar year‐, income‐specific, and region of birth‐specific rates in a randomly selected sample of >20% of each general population. The standardized incidence ratio (SIR) for MS following the first antiretroviral therapy exposure ("ART‐exposed") was also calculated. Results: The combined Sweden‐Canada cohort included 29,163 (75% men) HIV‐positive persons. During 242,248 person‐years of follow‐up, 14 incident MS cases were observed in the HIV‐positive cohort, whereas 26.19 cases were expected. The SIR for MS in the HIV‐positive population was 0.53 (95% confidence interval [CI] = 0.32–0.90). The SIR for MS following the first ART exposure was 0.55 (95% CI = 0.31–0.96). Interpretation: This international population‐based study demonstrated a lower risk of MS among HIV‐positive individuals, and HIV‐positive ART‐exposed individuals. These findings provide support for further exploration into the relationship among HIV, ART, and MS. ANN NEUROL 2024;95:487–494 [ABSTRACT FROM AUTHOR]

Published
2024
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34. State of the Art and Future Challenges in Multiple Sclerosis Research and Medical Management: An Insight into the 5th International Porto Congress of Multiple Sclerosis

Author

Sá, María José, Soares dos Reis, Ricardo, Altintas, Ayse, Celius, Elisabeth Gulowsen, Chien, Claudia, Comi, Giancarlo, Graus, Francesc, Hillert, Jan, Hobart, Jeremy, Khan, Gulfaraz, Kissani, Najib, Langdon, Dawn, Leite, Maria Isabel, Okuda, Darin T., Palace, Jacqueline, Papais-Alvarenga, Regina María, Mendes-Pinto, Inês, and Shi, Fu-Dong

Published
2020
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37. Timing of high-efficacy therapy for multiple sclerosis: a retrospective observational cohort study

Author

He, Anna, Merkel, Bernd, Brown, James William L, Zhovits Ryerson, Lana, Kister, Ilya, Malpas, Charles B, Sharmin, Sifat, Horakova, Dana, Kubala Havrdova, Eva, Spelman, Tim, Izquierdo, Guillermo, Eichau, Sara, Trojano, Maria, Lugaresi, Alessandra, Hupperts, Raymond, Sola, Patrizia, Ferraro, Diana, Lycke, Jan, Grand'Maison, Francois, Prat, Alexandre, Girard, Marc, Duquette, Pierre, Larochelle, Catherine, Svenningsson, Anders, Petersen, Thor, Grammond, Pierre, Granella, Franco, Van Pesch, Vincent, Bergamaschi, Roberto, McGuigan, Christopher, Coles, Alasdair, Hillert, Jan, Piehl, Fredrik, Butzkueven, Helmut, and Kalincik, Tomas

Published
2020
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39. Associations of Disease-Modifying Therapies With COVID-19 Severity in Multiple Sclerosis

Author

Simpson-Yap, Steve, De Brouwer, Edward, Kalincik, Tomas, Rijke, Nick, Hillert, Jan A, Walton, Clare, Edan, Gilles, Moreau, Yves, Spelman, Tim, Geys, Lotte, Parciak, Tina, Gautrais, Clement, Lazovski, Nikola, Pirmani, Ashkan, Ardeshirdavanai, Amin, Forsberg, Lars, Glaser, Anna, McBurney, Robert, Schmidt, Hollie, Bergmann, Arnfin B, Braune, Stefan, Stahmann, Alexander, Middleton, Rodden, Salter, Amber, Fox, Robert J., van der Walt, Anneke, Butzkueven, Helmut, Alroughani, Raed, Ozakbas, Serkan, Rojas, Juan I, van der Mei, Ingrid, Nag, Nupur, Ivanov, Rumen, Sciascia do Olival, Guilherme, Dias, Alice Estavo, Magyari, Melinda, Brum, Doralina, Mendes, Maria Fernanda, Alonso, Ricardo N, Nicholas, Richard S, Bauer, Johana, Chertcoff, Aníbal Sebastián, Zabalza, Anna, Arrambide, Georgina, Fidao, Alex, Comi, Giancarlo, and Peeters, Liesbet

Published
2021
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40. Multiple sclerosis risk loci and disease severity in 7,125 individuals from 10 studies.

Author

George, Michaela F, Briggs, Farren BS, Shao, Xiaorong, Gianfrancesco, Milena A, Kockum, Ingrid, Harbo, Hanne F, Celius, Elisabeth G, Bos, Steffan D, Hedström, Anna, Shen, Ling, Bernstein, Allan, Alfredsson, Lars, Hillert, Jan, Olsson, Tomas, Patsopoulos, Nikolaos A, De Jager, Philip L, Oturai, Annette B, Søndergaard, Helle B, Sellebjerg, Finn, Sorensen, Per S, Gomez, Refujia, Caillier, Stacy J, Cree, Bruce AC, Oksenberg, Jorge R, Hauser, Stephen L, D'Alfonso, Sandra, Leone, Maurizio A, Martinelli Boneschi, Filippo, Sorosina, Melissa, van der Mei, Ingrid, Taylor, Bruce V, Zhou, Yuan, Schaefer, Catherine, and Barcellos, Lisa F

Subjects
Genetics, Neurosciences
Abstract

ObjectiveWe investigated the association between 52 risk variants identified through genome-wide association studies and disease severity in multiple sclerosis (MS).MethodsTen unique MS case data sets were analyzed. The Multiple Sclerosis Severity Score (MSSS) was calculated using the Expanded Disability Status Scale at study entry and disease duration. MSSS was considered as a continuous variable and as 2 dichotomous variables (median and extreme ends; MSSS of ≤5 vs >5 and MSSS of

Published
2016

42. The CLARION study: first report on safety findings in patients newly initiating treatment with cladribine tablets or fingolimod for multiple sclerosis

Author

Butzkueven, Helmut, primary, Hillert, Jan, additional, Soilu-Hänninen, Merja, additional, Ziemssen, Tjalf, additional, Kuhle, Jens, additional, Wergeland, Stig, additional, Magyari, Melinda, additional, Berger, Joseph R., additional, Moore, Nicholas, additional, Aydemir, Aida, additional, Bezemer, Irene, additional, and Sabidó, Meritxell, additional

Published
2023
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43. Molecular mimicry between Anoctamin 2 and Epstein-Barr virus nuclear antigen 1 associates with multiple sclerosis risk

Author

Tengvall, Katarina, Huang, Jesse, Hellström, Cecilia, Kammer, Patrick, Biström, Martin, Ayoglu, Burcu, Bomfim, Izaura Lima, Stridh, Pernilla, Butt, Julia, Brenner, Nicole, Michel, Angelika, Lundberg, Karin, Padyukov, Leonid, Lundberg, Ingrid E., Svenungsson, Elisabet, Ernberg, Ingemar, Olafsson, Sigurgeir, Dilthey, Alexander T., Hillert, Jan, Alfredsson, Lars, Sundström, Peter, Nilsson, Peter, Waterboer, Tim, Olsson, Tomas, and Kockum, Ingrid

Published
2019

45. Class II HLA interactions modulate genetic risk for multiple sclerosis.

Author

Moutsianas, Loukas, Jostins, Luke, Beecham, Ashley, Dilthey, Alexander, Xifara, Dionysia, Ban, Maria, Shah, Tejas, Patsopoulos, Nikolaos, Alfredsson, Lars, Anderson, Carl, Attfield, Katherine, Barrett, Jeffrey, Binder, Thomas, Booth, David, Buck, Dorothea, Celius, Elisabeth, Cotsapas, Chris, DAlfonso, Sandra, Dendrou, Calliope, Donnelly, Peter, Dubois, Bénédicte, Fontaine, Bertrand, Fugger, Lars, Goris, An, Graetz, Christiane, Hemmer, Bernhard, Hillert, Jan, Kockum, Ingrid, Leslie, Stephen, Lill, Christina, Martinelli-Boneschi, Filippo, Olsson, Tomas, Oturai, Annette, Saarela, Janna, Søndergaard, Helle, Spurkland, Anne, Taylor, Bruce, Winkelmann, Juliane, Zipp, Frauke, Haines, Jonathan, Pericak-Vance, Margaret, Spencer, Chris, Stewart, Graeme, Hafler, David, Ivinson, Adrian, Harbo, Hanne, De Jager, Philip, Compston, Alastair, McCauley, Jacob, Sawcer, Stephen, McVean, Gil, Hauser, Stephen, Oksenberg, Jorge, Baranzini, Sergio, and Gourraud, Pierre-Antoine

Subjects
Alleles, Epistasis, Genetic, Genetic Predisposition to Disease, Histocompatibility Antigens Class II, Humans, Multiple Sclerosis, Polymorphism, Single Nucleotide
Abstract

Association studies have greatly refined the understanding of how variation within the human leukocyte antigen (HLA) genes influences risk of multiple sclerosis. However, the extent to which major effects are modulated by interactions is poorly characterized. We analyzed high-density SNP data on 17,465 cases and 30,385 controls from 11 cohorts of European ancestry, in combination with imputation of classical HLA alleles, to build a high-resolution map of HLA genetic risk and assess the evidence for interactions involving classical HLA alleles. Among new and previously identified class II risk alleles (HLA-DRB1*15:01, HLA-DRB1*13:03, HLA-DRB1*03:01, HLA-DRB1*08:01 and HLA-DQB1*03:02) and class I protective alleles (HLA-A*02:01, HLA-B*44:02, HLA-B*38:01 and HLA-B*55:01), we find evidence for two interactions involving pairs of class II alleles: HLA-DQA1*01:01-HLA-DRB1*15:01 and HLA-DQB1*03:01-HLA-DQB1*03:02. We find no evidence for interactions between classical HLA alleles and non-HLA risk-associated variants and estimate a minimal effect of polygenic epistasis in modulating major risk alleles.

Published
2015

50. JC polyomavirus infection is strongly controlled by human leucocyte antigen class II variants.

Author

Sundqvist, Emilie, Buck, Dorothea, Warnke, Clemens, Albrecht, Eva, Gieger, Christian, Khademi, Mohsen, Lima Bomfim, Izaura, Fogdell-Hahn, Anna, Link, Jenny, Alfredsson, Lars, Søndergaard, Helle Bach, Hillert, Jan, International Multiple Sclerosis Genetics Consortium, Oturai, Annette B, Hemmer, Bernhard, Kockum, Ingrid, and Olsson, Tomas

Subjects
International Multiple Sclerosis Genetics Consortium, CD4-Positive T-Lymphocytes, Humans, JC Virus, Polyomavirus Infections, Haplotypes, Alleles, Female, Male, HLA-DQ beta-Chains, HLA-DRB1 Chains, Scandinavian and Nordic Countries, Virology, Microbiology, Immunology, Medical Microbiology
Abstract

JC polyomavirus (JCV) carriers with a compromised immune system, such as in HIV, or subjects on immune-modulating therapies, such as anti VLA-4 therapy may develop progressive multifocal leukoencephalopathy (PML) which is a lytic infection of oligodendrocytes in the brain. Serum antibodies to JCV mark infection occur only in 50-60% of infected individuals, and high JCV-antibody titers seem to increase the risk of developing PML. We here investigated the role of human leukocyte antigen (HLA), instrumental in immune defense in JCV antibody response. Anti-JCV antibody status, as a surrogate for JCV infection, were compared to HLA class I and II alleles in 1621 Scandinavian persons with MS and 1064 population-based Swedish controls and associations were replicated in 718 German persons with MS. HLA-alleles were determined by SNP imputation, sequence specific (SSP) kits and a reverse PCR sequence-specific oligonucleotide (PCR-SSO) method. An initial GWAS screen displayed a strong HLA class II region signal. The HLA-DRB1*15 haplotype was strongly negatively associated to JCV sero-status in Scandinavian MS cases (OR = 0.42, p = 7×10(-15)) and controls (OR = 0.53, p = 2×10(-5)). In contrast, the DQB1*06:03 haplotype was positively associated with JCV sero-status, in Scandinavian MS cases (OR = 1.63, p = 0.006), and controls (OR = 2.69, p = 1×10(-5)). The German dataset confirmed these findings (OR = 0.54, p = 1×10(-4) and OR = 1.58, p = 0.03 respectively for these haplotypes). HLA class II restricted immune responses, and hence CD4+ T cell immunity is pivotal for JCV infection control. Alleles within the HLA-DR1*15 haplotype are associated with a protective effect on JCV infection. Alleles within the DQB1*06:03 haplotype show an opposite association. These associations between JC virus antibody response and human leucocyte antigens supports the notion that CD4+ T cells are crucial in the immune defence to JCV and lays the ground for risk stratification for PML and development of therapy and prevention.

Published
2014

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