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Record W2989223418 · doi:10.1101/683367

Common genetic variation indicates separate etiologies for periventricular and deep white matter hyperintensities

2019· preprint· en· W2989223418 on OpenAlexaff
Nicola J. Armstrong, Karen A. Mather, Muralidharan Sargurupremraj, Maria J. Knol, Rainer Malik, Claudia L. Satizábal, Lisa R. Yanek, Wen Wei, Vilmundur Guðnason, Nicole D Deuker, Lloyd T. Elliott, Edith Hofer, Neda Jahanshad, Shuo Li, Mark Logue, Michelle Luciano, Markus Scholz, Albert V. Smith, Stella Trompet, Dina Vojinović, Rui Xia, Fidel Alfaro‐Almagro, David Ames, Najaf Amin, Philippe Amouyel, Alexa Beiser, Henry Brodaty, Ian J. Deary, Christine Fennema‐Notestine, Piyush G Gampwar, Rebecca F. Gottesman, Ludovica Griffanti, Clifford R. Jack, Mark Jenkinson, Jiyang Jain, Brian G. Kral, John B. Kwok, Leonie Lampe, David C. Liewald, Pauline Maillard, Jonathan Marchini, Mark E. Bastin, Bernard Mazoyer, Lukas Pirpamer, José R. Romero, Gennady V. Roshchupkin, Peter R. Schofield, Matthias L. Schroeter, David J. Stott, Anbupalam Thalamuth, Julian N. Trollor, Christophe Tzourio, Jeroen van der Grond, Meike W. Vernooij, A. Veronica Witte, Maragret J Wright, Qiong Yang, Moris Zoe, Siggi Siggurdsson, Arno Villringer, Helena Schmidt, Asta Håberg, Cornelia M. van Duijn, J. Wouter Jukema, Martin Dichigans, Ralph L. Sacco, Clinton B. Wright, William S. Kremen, Lewis C. Becker, Paul M. Thompson, Lenore J. Launer, Thomas H. Mosley, Joanna M. Wardlaw, Mohammad Ikram, Hieab H.H. Adams, Reinhold Schmidt, Stephen M. Smith, Charles DeCarli, Perminder S. Sachdev, Myriam Fornage, Stephanie Debbette, Sudha Seshadri, Paul Nyquist

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA regulation and disease
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHyperintensityLocus (genetics)Genome-wide association studyWhite matterGenetic associationEtiologyGenetic architectureBiologyCandidate genePhenotypeDiseaseIschemic strokeGeneticsMedicinePathologyGeneMagnetic resonance imagingCardiologyGenotypeSingle-nucleotide polymorphismIschemia

Abstract

fetched live from OpenAlex

Abstract We conducted a genome-wide association meta-analysis of two ischemic white matter disease subtypes in the brain, periventricular and deep white matter hyperintensities (PVWMH and DWMH). In 26,654 participants, we found 10 independent genome-wide significant loci only associated with PVWMH, four of which have not been described previously for total WMH burden (16q24.2, 17q21.31, 10q23.1, 7q36.1). Additionally, in both PVWMH and DWMH we observed the previous association of the 17q25.1 locus with total WMH. We found that both phenotypes have shared but also distinct genetic architectures, consistent with both different underlying and related pathophysiology. PVWMH had more extensive genetic overlap with small vessel ischemic stroke, and unique associations with several loci implicated in ischemic stroke. DWMH were characterized by associations with loci previously implicated in vascular as well as astrocytic and neuronal function. Our study confirms the utility of these phenotypes and identifies new candidate genes associated only with PVWMH.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.608
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.008
GPT teacher head0.215
Teacher spread0.207 · 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 designObservational
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

Citations1
Published2019
Admission routes1
Has abstractyes

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