Citations 3
Genomic dimensions deconstruct the clinical heterogeneity of bipolar disorder
Veen, Tracey van der , Tesfaye, Markos , Yang, Jessica , Boltz, Toni , David, Friederike S. , Crinion, Shane , Koromina, Maria , Bigdeli, Tim B., Coombes, Brandon J., Panagiotaropoulou, Georgia, Parker, Nadine, Sung, Heejong , Bass, Nicholas, Coleman, Jonathan R. I., Guzman-Parra, José , Kálmán, János , McGrouther, Caroline C., Rangan, Aaditya V. , Scott, Katie , Vreeker, Annabel , Bauer, Michael , Brunkhorst-Kanaan, Nathalie, Byerley, William , Cervantes, Pablo , Chatzinakos, Chris , Claus, Isabelle , Cruceanu, Cristiana , Cuellar-Barboza, Alfredo, Dafnas, Konstantinos , Degenhardt, Franziska, Fanous, Ayman H. , Ferrier, I. Nicol , Forty, Liz , Frank, Josef , Freimer, Nelson B. , Hamshere, Marian L., Harder, Arvid , Hautzinger, Martin , Hellgren, Dennis, Hoffmann, Per, Jönsson, Lina , Kittel‐Schneider, Sarah , Knowles, James A. , Lavebratt, Catharina , Lawrence, Jacob , Leber, Markus , Lucae, Susanne , Lundberg, Martin , Maier, Wolfgang , Maihofer, Adam X. , Maratou, Eirini , McKay, James , Medeiros, Helena , Meyer‐Lindenberg, Andreas , Moutsatsou, Paraskevi , Mühleisen, Thomas W. , O’Connell, Kevin S. , Papiol, Sergi , Perry, Amy , Pisanu, Claudia , Potash, James B. , Rapaport, Mark Hyman , Regeer, Eline J. , Rice, John P. , Schulte, Eva C. , Senner, Fanny , Shilling, Paul D. , Sirignano, Lea , Slaney, Claire , Smeland, Olav B. , Sobell, Janet L. , Stein, Dan J. , Vawter, Marquis P. , Vedder, Helmut , Witt, Stephanie H. , Zandi, Peter P. , Investigators, Genomic Psychiatry Cohort (GPC), Psychiatry, HUNT All-In, Bengesser, Susanne , Berrettini, Wade H. , Blackwood, Douglas, Boehnke, Michael , Catts, Stanley V. , Craddock, Nicholas , Dikeos, Dimitris , Ferentinos, Panagiotis , Frye, Mark A. , Gawlik, Micha , Kahn, René S., Landén, Mikael , Lenger, Melanie , Loughland, Carmel , Melle, Ingrid , Myers, R , Müller‐Myhsok, Bertram , Neale, Benjamin M. , Øedegaard, Ketil J. , Paciga, Sara A. , Pato, Carlos N. , Pawlak, Joanna , Perlis, Roy H. , Reif, Andreas , Schalling, Martin , Scott, Laura J. , Scott, Rodney J., Stahl, Eli A. , Stordal, Eystein , Sullivan, Patrick F., Vaaler, Arne E. , Waldman, Irwin D. , Ophoff, Roel A. , Mullins, Niamh , Forstner, Andreas J. , van der Veen, Tracey , Yang, Jessica Mei Kay , Alda, Martin , Ophoff, Roel A , O'Connell, Kevin S , Mullins, Niamh , Forstner, Andreas J , Grigoroiu-Serbanescu, Maria , Edenberg, Howard J , McMahon, Francis , Andreassen, Ole A , Di Florio, Arianna , McQuillin, Andrew , Witt, Stephanie H , Meyer-Lindenberg, Andreas , Stein, Dan J , Papiol, Sergi , Cruceanu, Cristiana , Schulte, Eva , Kittel-Schneider, Sarah , Lavebratt, Catharina , Pisanu, Claudia , Reif, Andreas , Perlis, Roy H , Andlauer, Till F. 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No container title available | June 25, 2025 | Volume: No volume available | Issue: No issue available | Pages: No page available
ABSTRACT Bipolar disorder’s (BD) clinical heterogeneity has an unresolved genetic basis. We meta-analyzed genome-wide association studies (GWAS) of 16 BD subphenotypes in 226,032 individuals from 57 cohorts (38,022 cases); 10 advanced to multivariate and multi-trait analyses. Four factors (compulsive, psychotic, dysregulated, internalizing) explained 82.8% of shared genetic variance. BD1 and BD2 loaded on distinct factors despite a high genetic correlation; 87.0% of common-factor loci were significant in neither subtype. Unipolar mania aligned with psychosis over internalizing, and was distinguishable from BD1, and rapid cycling showed heritable cross-domain liability. We identified 356 risk loci, 158 novel, including the first univariate-GWAS associations for psychosis, unipolar mania, rapid cycling and schizoaffective disorder—and 249 credible genes (89 high-confidence), 12 with approved-drug or clinical-phase annotations. Cell-type association showed a midbrain dopaminergic–GABAergic gradient along the psychotic factor. BD’s genetic architecture appears hierarchical—a general liability resolving into dimensions of course and comorbidity beyond diagnostic subtypes.
Genetic risk factors for pediatric-onset multiple sclerosis
Stridh, Pernilla , Shao, Xiaorong, Rhead, Brooke , Lotze, Timothy , Schreiner, Teri , Belman, Anita , Greenberg, Benjamin , Aaen, Gregory , Tillema, Jan Mendelt, Hart, Janace, Caillier, Stacy J. , Ness, Jayne , Harris, Yolanda, Rubin, Jennifer , Candee, Meghan , Gorman, Mark , Benson, Lina , Rodriguez, Moses , Mar, Soe , Kahn, Ilana , Rose, John , Roalstad, Shelly, Casper, T. Charles , Shen, Ling, Quach, Hong , Quach, Diana , Hedström, Anna Karin , Olsson, Tomas , Kockum, Ingrid , Alfredsson, Lars , Schaefer, Catherine , Barcellos, Lisa F. , Tillema, Jan M, Rodriguez, Moses , Greenberg, Benjamin M , Gianfrancesco, Milena A , Graves, Jennifer , Chitnis, Tanuja , Waldman, Amy , Schreiner, Teri , Weinstock‐Guttman, Bianca , Krupp, Lauren , Hillert, Jan A. , Waubant, Emmanuelle L. , Rubin, Jennifer P
Multiple Sclerosis Journal | October 5, 2017 | Volume: 24 | Issue: 14 | Pages: 1825-1834
Background: Strong evidence supports the role of both genetic and environmental factors in pediatric-onset multiple sclerosis (POMS) etiology. Objective: We comprehensively investigated the association between established major histocompatibility complex (MHC) and non-MHC adult multiple sclerosis (MS)-associated variants and susceptibility to POMS. Methods: Cases with onset <18 years ( n = 569) and controls ( n = 16,251) were included from the United States and Sweden. Adjusted logistic regression and meta-analyses were performed for individual risk variants and a weighted genetic risk score (wGRS) for non-MHC variants. Results were compared to adult MS cases ( n = 7588). Results: HLA–DRB1*15:01 was strongly associated with POMS (odds ratio (OR) meta = 2.95, p < 2.0 × 10 −16 ). Furthermore, 28 of 104 non-MHC variants studied (23%) were associated ( p < 0.05); POMS cases carried, on average, a higher burden of these 28 variants compared to adults (OR avg = 1.24 vs 1.13, respectively), though the difference was not significant. The wGRS was strongly associated with POMS (OR meta = 2.77, 95% confidence interval: 2.33, 3.32, p < 2.0 × 10 −16 ) and higher, on average, when compared to adult cases. Additional class III risk variants in the MHC region associated with POMS were revealed after accounting for HLA–DRB1*15:01 and HLA–A*02. Conclusion: Pediatric and adult MS share many genetic variants suggesting similar biological processes are present. MHC variants beyond HLA–DRB1*15:01 and HLA–A*02 are also associated with POMS.
The Immunoregulator Soluble TACI Is Released by ADAM10 and Reflects B Cell Activation in Autoimmunity
Kuhn, Peer‐Hendrik , Laurent, Sarah , Hauck, Stefanie M. , Berer, Kerstin, Wendlinger, Simone A., Krumbholz, Markus , Khademi, Mohsen , Olsson, Tomas , Dreyling, Martin , Pfister, H.-W., Alexander, Tobias , Hiepe, Falk , Kümpfel, Tania , Wekerle, Hartmut , Hohlfeld, Reinhard , Meinl, Edgar , Crawford, Howard C, Hoffmann, Franziska S. , Crawford, Howard C. , Lichtenthaler, Stefan F.
The Journal of Immunology | December 11, 2014 | Volume: 194 | Issue: 2 | Pages: 542-552
Abstract BAFF and a proliferation-inducing ligand (APRIL), which control B cell homeostasis, are therapeutic targets in autoimmune diseases. TACI-Fc (atacicept), a soluble fusion protein containing the extracellular domain of the BAFF–APRIL receptor TACI, was applied in clinical trials. However, disease activity in multiple sclerosis unexpectedly increased, whereas in systemic lupus erythematosus, atacicept was beneficial. In this study, we show that an endogenous soluble TACI (sTACI) exists in vivo. TACI proteolysis involved shedding by a disintegrin and metalloproteinase 10 releasing sTACI from activated B cells. The membrane-bound stub was subsequently cleaved by γ-secretase reducing ligand-independent signaling of the remaining C-terminal fragment. The shed ectodomain assembled ligand independently in a homotypic way. It functioned as a decoy receptor inhibiting BAFF- and APRIL-mediated B cell survival and NF-κB activation. We determined sTACI levels in autoimmune diseases with established hyperactivation of the BAFF–APRIL system. sTACI levels were elevated both in the cerebrospinal fluid of the brain-restricted autoimmune disease multiple sclerosis correlating with intrathecal IgG production, as well as in the serum of the systemic autoimmune disease systemic lupus erythematosus correlating with disease activity. Together, we show that TACI is sequentially processed by a disintegrin and metalloproteinase 10 and γ-secretase. The released sTACI is an immunoregulator that shares decoy functions with atacicept. It reflects systemic and compartmentalized B cell accumulation and activation.