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Record W4311452644 · doi:10.1101/2022.12.13.22282475

Genome-wide association study of multiple neuropathology endophenotypes identifies novel risk loci and provides insights into known Alzheimer’s risk loci

2022· preprint· en· W4311452644 on OpenAlexfundno aff
Lincoln M. P. Shade, Yuriko Katsumata, Steven A. Claas, Mark Ebbert, Erin L. Abner, Timothy J. Hohman, Shubhabrata Mukherjee, Kwangsik Nho, Andrew J. Saykin, David A. Bennett, Julie A. Schneider, Peter T. Nelson, David W. Fardo

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsnot available
FundersNational Institute on AgingNational Institute of Biomedical Imaging and BioengineeringCanadian Institutes of Health ResearchNational Institutes of HealthGenentechIXICOH. Lundbeck A/SServierEisaiNorthern California Institute for Research and EducationPfizerBiogenBioClinicaF. Hoffmann-La RocheUniversity of PennsylvaniaUniversity of Southern CaliforniaIllinois Department of Public HealthNovartis Pharmaceuticals CorporationU.S. Department of DefenseEli Lilly and CompanyBristol-Myers SquibbAlzheimer's AssociationFoundation for the National Institutes of HealthAlzheimer's Disease Neuroimaging InitiativeMeso Scale Diagnostics
KeywordsNeuropathologyCerebral amyloid angiopathySenile plaquesGenome-wide association studyEndophenotypeAlzheimer's diseaseNeuroscienceApolipoprotein EPathologyBiologyDementiaDiseaseMedicineGeneticsSingle-nucleotide polymorphismGenotypeGeneCognition

Abstract

fetched live from OpenAlex

Abstract Background Alzheimer’s disease is highly heritable and exhibits neuropathological hallmarks of neurofibrillary tau tangles and neuritic amyloid plaques. Previous genome-wide association studies (GWAS) have identified over 70 genomic risk loci of clinically diagnosed Alzheimer’s disease. However, upon autopsy, many Alzheimer’s disease patients have multiple comorbid neuropathologies that may have independent or pleiotropic genomic risk factors. Autopsy data combined with GWAS provides the opportunity to study the genetic risk factors of individual neuropathologies. Methods We studied the genome-wide risk factors of eleven Alzheimer’s disease-related neuropathology endophenotypes. We used four sources of neuropathological data: National Alzheimer’s Coordinating Center, Religious Orders Study and Rush Memory and Aging Project, Adult Changes in Thought study, and Alzheimer’s Disease Neuroimaging Initiative. We used generalized linear mixed models to identify risk loci, followed by Bayesian colocalization analyses to identify potential functional mechanisms by which genetic loci influence neuropathology risk. Results We identified two novel loci associated with neuropathology: one PIK3R5 locus (lead variant rs72807981) with neurofibrillary pathology, and one COL4A1 locus (lead variant rs2000660) with cerebral atherosclerosis. We also confirmed associations between known Alzheimer’s genes and multiple neuropathology endophenotypes, including APOE (neurofibrillary tangles, neuritic plaques, diffuse plaques, cerebral amyloid angiopathy, and TDP-43 pathology); BIN1 (neurofibrillary tangles and neuritic plaques); and TMEM106B (TDP-43 pathology and hippocampal sclerosis). After adjusting for APOE genotype, we identified a locus near APOC2 (lead variant rs4803778) associated with cerebral amyloid angiopathy that influences DNA methylation at nearby CpG sites in the cerebral cortex. Conclusions rs2000660 is in strong linkage disequilibrium with a synonymous coding variant (rs650724) of COL4A1 , providing a candidate functional variant. Two CpG sites affected by the cerebral amyloid angiopathy-associated APOC2 locus were previously associated with dementia in an independent cohort, suggesting that the effect of this locus on disease may be mediated by DNA methylation. BIN1 is associated with neurofibrillary tangles and neuritic plaques but not with amyloid pathology. TMEM106B is associated with hippocampal sclerosis and TDP-43 pathology but not the canonical Alzheimer’s disease pathologies. These findings provide insights into known Alzheimer’s disease risk loci by refining the pathways affected by these risk genes.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.034
GPT teacher head0.302
Teacher spread0.267 · 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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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