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Record W3037545866 · doi:10.1038/s41380-020-0822-5

The IMAGEN study: a decade of imaging genetics in adolescents

2020· review· en· W3037545866 on OpenAlexaff
Lea Mascarell-Maricic, Henrik Walter, Annika Rosenthal, Stephan Ripke, Erin Burke Quinlan, Tobias Banaschewski, Gareth J. Barker, Arun L.W. Bokde, Uli Bromberg, Christian Büchel, Sylvane Desrivières, Herta Flor, Vincent Frouin, Hugh Garavan, Bernd Itterman, Jean‐Luc Martinot, Marie‐Laure Paillère Martinot, Frauke Nees, Dimitri Papadopoulos Orfanos, Tomáš Paus, Luise Poustka, Sarah Hohmann, Michael N. Smolka, Juliane H. Fröhner, Robert Whelan, Jakob Kaminski, Andreas Heinz, Lisa Albrecht, Chris Andrew, Mercedes Arroyo, Éric Artiges, Semiha Aydın, Christine Bach, Alexis Barbot, Nathalie Boddaert, Zuleima Bricaud, Ruediger Bruehl, Arnaud Cachia, Anna Cattrell, Patricia Conrod, Patrick Constant, Jeffrey W. Dalley, Benjamin Decideur, Tahmine Fadai, Jürgen Gallinat, Fanny Gollier Briand, Penny Gowland, Bert Heinrichs, Nadja Heym, Thomas Hübner, James Ireland, Bernd Ittermann, Tianye Jia, Mark Lathrop, Dirk Lanzerath, Claire Lawrence, Hervé Lemaître, Katharina Lüdemann, Christine Macare, Catherine Mallik, Jean‐François Mangin, Karl Mann, Eva Mennigen, Fabiana Mesquita de Carvahlo, Xavier Mignon, Rubén Miranda, Kathrin Müller, Charlotte Nymberg, Marie-Laure Paillère, Zdenka Pausová, Jean‐Baptiste Poline, Michael A. Rapp, Guillaume Robert, J.H. Reuter, Marcella Rietschel, Trevor W. Robbins, Sarah Rodehacke, John Rogers, Alexander Romanowski, Barbara Ruggeri, Christine Schmäl, Dirk Schmidt, Sophia Schneider, MarkGunter Schumann, Yannick Schwartz, Wolfgang H. Sommer, Rainer Spanagel, Claudia Speiser, Tade Matthias Spranger, Alicia Stedman, Sabina Steiner, D.N. Stephens, Nicole Strache, Andreas Ströhle, Maren Struve, Naresh Subramaniam, Lauren Topper, Juliana Yacubian, Mônica Zilbovicius, Chi‐yan Wong, Steven Lubbe, Lourdes Martinez-Medina, Alinda R. Fernandes, Amir Tahmasebi

Bibliographic record

VenueMolecular Psychiatry · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsBaycrest HospitalUniversity of Toronto
FundersNational Institute of Biomedical Imaging and BioengineeringMedical Research CouncilNational Institutes of HealthNational Institute of Mental HealthVetenskapsrådetSvenska Forskningsrådet FormasEU Joint Programme – Neurodegenerative Disease ResearchInstitut National de la Santé et de la Recherche MédicaleAgence Nationale de la RechercheMission Interministérielle de Lutte Contre les Drogues et les Conduites AddictivesScience Foundation IrelandDeutsche ForschungsgemeinschaftKing's College LondonFondation de FranceBundesministerium für Bildung und ForschungNational Institute for Health and Care ResearchEuropean CommissionSouth London and Maudsley NHS Foundation Trust
KeywordsGeneralizability theoryImaging geneticsSample size determinationPsychologyLongitudinal sampleNeuroimagingBrain Structure and FunctionLongitudinal studyNeuroscienceAnticipation (artificial intelligence)NeurogeneticsCognitive psychologyDevelopmental psychologyBiologyGeneticsMedicineGeneArtificial intelligenceComputer scienceStatistics

Abstract

fetched live from OpenAlex

Imaging genetics offers the possibility of detecting associations between genotype and brain structure as well as function, with effect sizes potentially exceeding correlations between genotype and behavior. However, study results are often limited due to small sample sizes and methodological differences, thus reducing the reliability of findings. The IMAGEN cohort with 2000 young adolescents assessed from the age of 14 onwards tries to eliminate some of these limitations by offering a longitudinal approach and sufficient sample size for analyzing gene-environment interactions on brain structure and function. Here, we give a systematic review of IMAGEN publications since the start of the consortium. We then focus on the specific phenotype 'drug use' to illustrate the potential of the IMAGEN approach. We describe findings with respect to frontocortical, limbic and striatal brain volume, functional activation elicited by reward anticipation, behavioral inhibition, and affective faces, and their respective associations with drug intake. In addition to describing its strengths, we also discuss limitations of the IMAGEN study. Because of the longitudinal design and related attrition, analyses are underpowered for (epi-) genome-wide approaches due to the limited sample size. Estimating the generalizability of results requires replications in independent samples. However, such densely phenotyped longitudinal studies are still rare and alternative internal cross-validation methods (e.g., leave-one out, split-half) are also warranted. In conclusion, the IMAGEN cohort is a unique, very well characterized longitudinal sample, which helped to elucidate neurobiological mechanisms involved in complex behavior and offers the possibility to further disentangle genotype × phenotype interactions.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.324
Teacher spread0.310 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations93
Published2020
Admission routes1
Has abstractyes

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