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Genetic Associations Between Modifiable Risk Factors and Alzheimer Disease

2023· article· en· W4376871489 on OpenAlexaff
Jiao Luo, Jesper Qvist Thomassen, Céline Bellenguez, Benjamin Grenier‐Boley, Itziar de Rojas, Atahualpa Castillo-Morales, Kayenat Parveen, Fahri Küçükali, Aude Nicolas, Oliver Peters, Anja Schneider, Martin Dichgans, Dan Rujescu, Norbert Scherbaum, Jürgen Deckert, Steffi G. Riedel‐Heller, Lucrezia Hausner, Laura Molina‐Porcel, Emrah Düzel, Timo Grimmer, Jens Wiltfang, Stefanie Heilmann‐Heimbach, Susanne Moebus, Thomas Tegos, Nikolaos Scarmeas, Jordi Clarimón, Fermín Moreno, Jordi Pérez‐Tur, María J. Bullido, Pau Pástor, Raquel Sánchez‐Valle, Victoria Álvarez, Merçé Boada, Pablo García‐González, Raquel Puerta, Pablo Mir, Luís Miguel Real, Gerard Piñol‐Ripoll, José María García‐Alberca, José Luís Royo, Eloy Rodríguez‐Rodríguez, Hilkka Soininen, Teemu Kuulasmaa, Alexandre de Mendonça, Shima Mehrabian, Jakub Hort, Martin Vyhnálek, Sven J. van der Lee, Caroline Graff, Goran Papenberg, Vilmantas Giedraitis, Anne Boland, Delphine Bacq‐Daian, Jean‐François Deleuze, Gaël Nicolas, Carole Dufouil, Florence Pasquier, Olivier Hanon, Stéphanie Debette, Edna Grünblatt, Julius Popp, Luisa Benussi, Daniela Galimberti, Beatrice Arosio, Patrizia Mecocci, Vincenzo Solfrizzi, Lucilla Parnetti, Alessio Squassina, Lucio Tremolizzo, Barbara Borroni, Benedetta Nacmias, Sandro Sorbi, Paolo Caffarra, Davide Seripa, Innocenzo Rainero, Antonio Daniele, Carlo Masullo, Gianfranco Spalletta, Julie Williams, Philippe Amouyel, Frank Jessen, Patrick G. Kehoe, Magda Tsolaki, Giacomina Rossi, Pascual Sánchez‐Juan, Kristel Sleegers, Martin Ingelsson, Ole A. Andreassen, Mikko Hiltunen, Cornelia M. van Duijn, Rebecca Sims, Wiesje M. van der Flier, Agustı́n Ruiz, Alfredo Ramı́rez, Jean‐Charles Lambert, Ruth Frikke‐Schmidt

Bibliographic record

VenueJAMA Network Open · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsOntario Brain InstituteUniversity of TorontoUniversity Health Network
FundersVogel StiftungMedical Research CouncilHersenstichtingDemensfondenGrifolsSunovionH. Lundbeck A/SNorges ForskningsrådEisaiServierBiogenPfizerAlzheimer NederlandZonMwKarolinska InstitutetEli Lilly and CompanyLundbeckfondenMinistero della SaluteAlzheimer's AssociationFONDATION ALZHEIMERInstituto de Salud Carlos IIINational Research FoundationAmgenNovo NordiskBundesministerium für Bildung und ForschungEuropean Commission
KeywordsMendelian randomizationMedicineDementiaOdds ratioDiseaseAlzheimer's diseaseBiobankCase-control studyGerontologyInternal medicineBioinformaticsGeneticsGenotypeBiologyGenetic variants

Abstract

fetched live from OpenAlex

Importance: An estimated 40% of dementia is potentially preventable by modifying 12 risk factors throughout the life course. However, robust evidence for most of these risk factors is lacking. Effective interventions should target risk factors in the causal pathway to dementia. Objective: To comprehensively disentangle potentially causal aspects of modifiable risk factors for Alzheimer disease (AD) to inspire new drug targeting and improved prevention. Design, Setting, and Participants: This genetic association study was conducted using 2-sample univariable and multivariable mendelian randomization. Independent genetic variants associated with modifiable risk factors were selected as instrumental variables from genomic consortia. Outcome data for AD were obtained from the European Alzheimer & Dementia Biobank (EADB), generated on August 31, 2021. Main analyses were conducted using the EADB clinically diagnosed end point data. All analyses were performed between April 12 and October 27, 2022. Exposures: Genetically determined modifiable risk factors. Main Outcomes and Measures: Odds ratios (ORs) and 95% CIs for AD were calculated per 1-unit change of genetically determined risk factors. Results: The EADB-diagnosed cohort included 39 106 participants with clinically diagnosed AD and 401 577 control participants without AD. The mean age ranged from 72 to 83 years for participants with AD and 51 to 80 years for control participants. Among participants with AD, 54% to 75% were female, and among control participants, 48% to 60% were female. Genetically determined high-density lipoprotein (HDL) cholesterol concentrations were associated with increased odds of AD (OR per 1-SD increase, 1.10 [95% CI, 1.05-1.16]). Genetically determined high systolic blood pressure was associated with increased risk of AD after adjusting for diastolic blood pressure (OR per 10-mm Hg increase, 1.22 [95% CI, 1.02-1.46]). In a second analysis to minimize bias due to sample overlap, the entire UK Biobank was excluded from the EADB consortium; odds for AD were similar for HDL cholesterol (OR per 1-SD unit increase, 1.08 [95% CI, 1.02-1.15]) and systolic blood pressure after adjusting for diastolic blood pressure (OR per 10-mm Hg increase, 1.23 [95% CI, 1.01-1.50]). Conclusions and Relevance: This genetic association study found novel genetic associations between high HDL cholesterol concentrations and high systolic blood pressure with higher risk of AD. These findings may inspire new drug targeting and improved prevention implementation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.040
GPT teacher head0.303
Teacher spread0.263 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations93
Published2023
Admission routes1
Has abstractyes

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