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Record W4387139189 · doi:10.1038/s41525-023-00370-z

SLCO5A1 and synaptic assembly genes contribute to impulsivity in juvenile myoclonic epilepsy

2023· article· en· W4387139189 on OpenAlexafffund
Delnaz Roshandel, Eric J. Sanders, Amy Shakeshaft, Naim Panjwani, Lin Fan, Amber Collingwood, Anna Hall, Katherine Keenan, Celine Deneubourg, Filippo Mirabella, Simon Topp, Jana Zárubová, Rhys H. Thomas, Inga Talvik, Marte Syvertsen, Pasquale Striano, Anna Smith, Kaja Kristine Selmer, Guido Rubboli, Alessandro Orsini, Ching Ching Ng, Rikke S. Møller, Kheng Seang Lim, Khalid Hamandi, David A. Greenberg, Joanna Gesche, Elena Gardella, Choong Yi Fong, Christoph P. Beier, Danielle M. Andrade, Heinz Jungbluth, Mark P. Richardson, Annalisa Pastore, Manolis Fanto, Deb K. Pal, Lisa J. Strug, Zuzana Šobíšková, Cechovaz Pracoviste, Michaela Kajšová, M Miranda, Paulina Bala, Amy Kitching, Kate Irwin, Lorna Walding, Lynsey Adams, Uma Jegathasan, Rachel Swingler, Rachel Wane, Julia Aram, Nikil Sudarsan, Dee Mullan, Rebecca Ramsay, Vivien Richmond, M. Sargent, Paul Frattaroli, Matthew D. Taylor, Marie Home, Sal Uka, Susan Kilroy, Tonicha Nortcliffe, Kelly Holroyd, Alison McQueen, Dympna Mcaleer, Dina Jayachandran, Dawn Egginton, Bridget MacDonald, Michael Chang, David Deekollu, Alok Gaurav, Caroline Hamilton, Jaya Natarajan, Inyan Takon, Janet Cotta, Nick Moran, Jeremy D.P. Bland, Rosemary Belderbos, Heather Collier, Joanne Henry, Matthew J. Milner, Sam White, Michalis Koutroumanidis, William Stern, Jennifer M. Quirk, Javier Peña‐Ceballos, Anastasia Papathanasiou, Ioannis Stavropoulos, Dora A. Lozsádi, Andrew Swain, Charlotte Quamina, Jennifer Crooks, Tahir Majeed, Sonia Raj, Shakeelah Patel, Michael C. Young, Melissa Maguire, Munni Ray, Caroline Peacey, Linetty Makawa, Asyah Chhibda, Eve Sacre, Shanaz Begum, Martin O’ Malley, Lap Yeung, Claire Holliday, Louise Woodhead, Karen Helton Rhodes, Shan Ellawela, Joanne Glenton, Verity Calder, John M. Davis, Paul McAlinden, Sarah Francis, Lisa Robson, Karen Lanyon, Graham A. Mackay, Elma Stephen, Coleen Thow, Margaret Connon, Martin Kirkpatrick, Susan MacFarlane, Anne Scott MacLeod, Debbie Rice, Siva Kumar, Carolyn Campbell, Vicky Collins, William Whitehouse, Christina Giavasi, Boyanka Petrova, Thomas D. Brown, Catie Picton, Michael O’Donoghue, Charlotte West, Helen Navarra, Sean Slaght, Catherine Edwards, Andrew Gribbin, Liz Nelson, Stephen Warriner, Heather Angus‐Leppan, Loveth Ehiorobo, Bintou Camara, T Samakomva, Rajiv Mohanraj, Rajesh K. Pandey, Lisa Charles, Catherine Cotter, Archana Desurkar, Alison Hyde, Rachel Harrison, Markus Reuber, R. T. Clegg, J Sidebottom, Mayeth Recto, Patrick Easton, Charlotte Waite, Alice Howell, Jacqueline Smith, Shyam Mariguddi, Zena Haslam, Elizabeth Galizia, Hannah R. Cock, Mark Mencias, Samantha Truscott, Déirdre Daly, Hilda Mhandu, Nooria Said, Mark I. Rees, Seo‐Kyung Chung, Beata Fonferko‐Shadrach, Mark D. Baker, Fraser Scott, Naveed Ghaus, Gail Castle, Jacqui Bartholomew, Ann Needle, Julie Ball, Andrea Clough, Shashikiran Sastry, Charlotte Busby, Amit Agrawal, Debbie Dickerson, Almu Duran, Muhammad Shamim Khan, Laura Thrasyvoulou, Eve Irvine, Sarah Tittensor, Jacqueline Daglish, Sumant Kumar, Claire Backhouse, Claire Mewies, Denise Skinner, Rahul Bharat, Sarah-Jane Sharman, Arun Saraswatula, Helen Cockerill

Bibliographic record

Venuenpj Genomic Medicine · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsSickKids FoundationKrembil FoundationPublic Health OntarioUniversity of TorontoHospital for Sick Children
FundersEngineering and Physical Sciences Research CouncilMedical Research CouncilCanadian Institutes of Health ResearchHorizon 2020 Framework ProgrammeSheffield Children's NHS Foundation TrustSt George's University Hospitals NHS Foundation TrustOdense UniversitetshospitalEisaiMinistero dell’Istruzione, dell’Università e della RicercaNorges ForskningsrådNational Centre for the Replacement, Refinement and Reduction of Animals in ResearchEuropean CommissionAction Medical ResearchSheffield Teaching Hospitals NHS Foundation TrustUniversity of NottinghamSyddansk UniversitetCanada Research ChairsSwansea UniversityNationwide Children's HospitalEpilepsy Research UKNational Institute for Health and Care ResearchNottingham University Hospitals NHS TrustHealth and Care Research WalesRoyal Free London NHS Foundation TrustMedical Research Council Centre for Neurodevelopmental DisordersGW PharmaceuticalsUniversity Hospitals Birmingham NHS Foundation TrustParc Geneteg Cymru
KeywordsJuvenile myoclonic epilepsyImpulsivityEpilepsyJuvenileMyoclonic epilepsyNeurosciencePsychologyBiologyPsychiatryGenetics

Abstract

fetched live from OpenAlex

Abstract Elevated impulsivity is a key component of attention-deficit hyperactivity disorder (ADHD), bipolar disorder and juvenile myoclonic epilepsy (JME). We performed a genome-wide association, colocalization, polygenic risk score, and pathway analysis of impulsivity in JME ( n = 381). Results were followed up with functional characterisation using a drosophila model. We identified genome-wide associated SNPs at 8q13.3 ( P = 7.5 × 10 −9 ) and 10p11.21 ( P = 3.6 × 10 −8 ). The 8q13.3 locus colocalizes with SLCO5A1 expression quantitative trait loci in cerebral cortex ( P = 9.5 × 10 −3 ). SLCO5A1 codes for an organic anion transporter and upregulates synapse assembly/organisation genes. Pathway analysis demonstrates 12.7-fold enrichment for presynaptic membrane assembly genes ( P = 0.0005) and 14.3-fold enrichment for presynaptic organisation genes ( P = 0.0005) including NLGN1 and PTPRD . RNAi knockdown of Oatp30B , the Drosophila polypeptide with the highest homology to SLCO5A1 , causes over-reactive startling behaviour ( P = 8.7 × 10 −3 ) and increased seizure-like events ( P = 6.8 × 10 −7 ). Polygenic risk score for ADHD genetically correlates with impulsivity scores in JME ( P = 1.60 × 10 −3 ). SLCO5A1 loss-of-function represents an impulsivity and seizure mechanism. Synaptic assembly genes may inform the aetiology of impulsivity in health and disease.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.936
Threshold uncertainty score0.678

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.254
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2023
Admission routes2
Has abstractyes

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