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Circulating Metabolome and White Matter Hyperintensities in Women and Men

2022· review· en· W4205510598 on OpenAlexafffund
Eeva Sliz, Jean Shin, Shahzad Ahmad, Dylan M. Williams, Stefan Frenzel, Karen Friederike Gauß, Sarah E. Harris, Ann‐Kristin Henning, María Valdés Hernández, Yi‐Han Hu, Beatriz Jiménez, Muralidharan Sargurupremraj, Carole H. Sudre, Ruiqi Wang, Katharina Wittfeld, Qiong Yang, Joanna M. Wardlaw, Henry Völzke, Meike W. Vernooij, Jonathan M. Schott, Marcus Richards, Petroula Proitsi, Matthias Nauck, Matthew R. Lewis, Lenore J. Launer, Norbert Hosten, Hans J. Grabe, Mohsen Ghanbari, Ian J. Deary, Simon R. Cox, Nish Chaturvedi, Josephine Barnes, Jerome I. Rotter, Stéphanie Debette, M. Arfan Ikram, Myriam Fornage, Tomáš Paus, Sudha Seshadri, Zdenka Pausová

Bibliographic record

VenueCirculation · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsUniversité de MontréalCégep de ChicoutimiCentre Hospitalier Universitaire Sainte-JustineUniversity of TorontoSickKids FoundationHospital for Sick ChildrenUniversité du Québec à Chicoutimi
FundersNational Center for Advancing Translational SciencesNational Institute on AgingMedical Research CouncilErasmus Medisch CentrumNational Institute of Diabetes and Digestive and Kidney DiseasesBiotechnology and Biological Sciences Research CouncilZonMwEuropean CommissionAge UKDementias Platform UKBritish Heart FoundationUniversity College LondonCanadian Institutes of Health ResearchNational Institute for Health and Care ResearchHospital for Sick ChildrenHeart and Stroke Foundation of Canada
KeywordsMedicineHyperintensityInternal medicineMetabolomeLinear regressionPopulationFalse discovery rateCardiologyMagnetic resonance imagingStatisticsMetaboliteRadiology

Abstract

fetched live from OpenAlex

Background: White matter hyperintensities (WMH), identified on T2-weighted magnetic resonance images of the human brain as areas of enhanced brightness, are a major risk factor of stroke, dementia, and death. There are no large-scale studies testing associations between WMH and circulating metabolites. Methods: We studied up to 9290 individuals (50.7% female, average age 61 years) from 15 populations of 8 community-based cohorts. WMH volume was quantified from T2-weighted or fluid-attenuated inversion recovery images or as hypointensities on T1-weighted images. Circulating metabolomic measures were assessed with mass spectrometry and nuclear magnetic resonance spectroscopy. Associations between WMH and metabolomic measures were tested by fitting linear regression models in the pooled sample and in sex-stratified and statin treatment–stratified subsamples. Our basic models were adjusted for age, sex, age×sex, and technical covariates, and our fully adjusted models were also adjusted for statin treatment, hypertension, type 2 diabetes, smoking, body mass index, and estimated glomerular filtration rate. Population-specific results were meta-analyzed using the fixed-effect inverse variance–weighted method. Associations with false discovery rate (FDR)–adjusted P values ( P FDR )<0.05 were considered significant. Results: In the meta-analysis of results from the basic models, we identified 30 metabolomic measures associated with WMH ( P FDR <0.05), 7 of which remained significant in the fully adjusted models. The most significant association was with higher level of hydroxyphenylpyruvate in men ( P FDR.full.adj =1.40×10 −7 ) and in both the pooled sample ( P FDR.full.adj =1.66×10 − 4 ) and statin-untreated ( P FDR.full.adj =1.65×10 − 6 ) subsample. In men, hydroxyphenylpyruvate explained 3% to 14% of variance in WMH. In men and the pooled sample, WMH were also associated with lower levels of lysophosphatidylcholines and hydroxysphingomyelins and a larger diameter of low-density lipoprotein particles, likely arising from higher triglyceride to total lipids and lower cholesteryl ester to total lipids ratios within these particles. In women, the only significant association was with higher level of glucuronate ( P FDR =0.047). Conclusions: Circulating metabolomic measures, including multiple lipid measures (eg, lysophosphatidylcholines, hydroxysphingomyelins, low-density lipoprotein size and composition) and nonlipid metabolites (eg, hydroxyphenylpyruvate, glucuronate), associate with WMH in a general population of middle-aged and older adults. Some metabolomic measures show marked sex specificities and explain a sizable proportion of WMH variance.

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 score0.975
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 science0.0000.000
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 head0.024
GPT teacher head0.267
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.

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

Citations40
Published2022
Admission routes2
Has abstractyes

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