In one paragraphArticle in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
5 · Who and what moneyAuthors and funding
19 authors.
Naz KaradagCentre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway.ORCID 0009-0009-8451-8096 Espen HagenCentre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway.ORCID 0000-0002-1321-5970 Alexey A ShadrinCentre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway.ORCID 0000-0002-7467-250X Dennis van der MeerCentre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway.ORCID 0000-0002-0466-386X Kevin S O'ConnellCentre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway.ORCID 0000-0002-6865-8795 Zillur RahmanCentre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway.
Gleda KutrolliCentre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway.ORCID 0000-0001-6602-2622 Nadine ParkerCentre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway.ORCID 0000-0002-8369-0152 Shahram BahramiCentre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway.ORCID 0000-0002-8179-2788 Vera FominykhCentre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway.ORCID 0000-0001-5490-2390 Nils Eiel SteenCentre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway.ORCID 0000-0001-6442-1179 Oleksandr FreiCentre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway.ORCID 0000-0002-6427-2625 Ole A AndreassenCentre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway.ORCID 0000-0002-4461-3568 Olav B SmelandCentre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital Oslo, Norway.ORCID 0000-0002-3761-5215 Funding
OTA-21-015A Post-Acute Sequelae of SARS-CoV-2 Infection Initiative: NYU Langone Health Clinical Science Core, Data Resource Core, and PASC Biorepository CoreOT2HL161847 · NHLBI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI GROSS, RACHEL SHARON, HORWITZ, LEORA · 2021 to 2025
$651.0MABCD-USA Consortium: Data Analysis, Informatics and Resource CenterU24DA041123 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANDERS M DALE · 2015 to 2026
$51.5MHealthy Brain and Child Development National Consortium Data Coordinating CenterU24DA055330 · NIDA · WASHINGTON UNIVERSITY · PI ANDERS M DALE, Damien A Fair · 2021 to 2026
$34.6MThe VETSA Longitudinal MRI Twin Study of Aging (VETSA MRI 4)R01AG076838 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANDERS M DALE, Jeremy A Elman · 2022 to 2026
$8.7MA Trans-Nordic Study of Extreme Major DepressionR01MH123724 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI PATRICK F SULLIVAN, Lu Yi · 2020 to 2026
$4.7M3/7 Psychiatric Genomics Consortium: Advancing Discovery and ImpactR01MH124839 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI ANDREASSEN, OLE A, HUCKINS, LAURA MARIANNE · 2021 to 2025
$2.0MNHLBI NIH HHS OT2 HL161847NIA NIH HHS R01 AG076838NIDA NIH HHS U24 DA041123NIDA NIH HHS U24 DA055330NIMH NIH HHS R01 MH123724NIMH NIH HHS R01 MH124839
6 · The paper itselfAbstract
Objective: Cognitive impairment is prevalent among individuals with epilepsy, and it is possible that genetic factors can underlie this relationship. Here, we investigated the potential shared genetic basis of common epilepsies and general cognitive ability (COG). Methods: We applied linkage disequilibrium score (LDSC) regression, MiXeR and conjunctional false discovery rate (conjFDR) to analyze different aspects of genetic overlap between COG and epilepsies. We used the largest available genome-wide association study data on COG ( Results: Using MiXeR, COG (11.2k variants) was estimated to be almost four times more polygenic than 'all epilepsy', GGE, juvenile myoclonic epilepsy (JME), and childhood absence epilepsy (CAE) (2.5k - 2.9k variants). The other epilepsy phenotypes were insufficiently powered for analysis. We show extensive genetic overlap between COG and epilepsies with significant negative genetic correlations (-0.23 to -0.04). COG was estimated to share 2.9k variants with both GGE and 'all epilepsy', and 2.3k variants with both JME and CAE. Using conjFDR, we identified 66 distinct loci shared between COG and epilepsies, including novel associations for GGE (27), 'all epilepsy' (5), JME (5) and CAE (5). The implicated genes were significantly expressed in multiple brain regions. The results were validated in independent samples (COG: Significance: Our study demonstrates a substantial genetic basis shared between epilepsies and COG and identifies novel overlapping genomic loci. Enhancing our understanding of the relationship between epilepsies and COG may lead to the development of novel comorbidity-targeted epilepsy treatments.
Identifiers
PMID38585944
PMCPMC10996742
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