Evidence mapPaperPMID 40096060Full record

ArticlePLoS genetics2025

Local genetic covariance analysis with lipid traits identifies novel loci for early-onset Alzheimer's Disease.

Nicholas R Ray, Joseph Bradley, Elanur Yilmaz, Caghan Kizil, Jiji T Kurup, Eden R Martin, Hans-Ulrich Klein, Brian W Kunkle, David A Bennett, Philip L De Jager and 4 more

Abstract read
In one paragraph

Article in PLoS genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Nicholas R RayTaub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, United States of America.ORCID https://orcid.org/0009-0009-4931-3239
Joseph BradleyNeuroGenomics and Informatics Center, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States of America.ORCID https://orcid.org/0000-0003-0217-4808
Elanur YilmazTaub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, United States of America.ORCID https://orcid.org/0000-0001-7045-5068
Caghan KizilTaub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, United States of America.ORCID https://orcid.org/0000-0002-8164-9762
Jiji T KurupTaub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, United States of America.
Eden R MartinThe John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, United States of America.
Hans-Ulrich KleinTaub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, United States of America.ORCID https://orcid.org/0000-0002-6382-9428
Brian W KunkleThe John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, United States of America.ORCID https://orcid.org/0000-0002-9515-5157
David A BennettRUSH Alzheimer's Disease Center, RUSH University, Chicago, Illinois, United States of America.
Philip L De JagerTaub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, United States of America.ORCID https://orcid.org/0000-0002-8057-2505
Alzheimer’s Disease Genetics Consortium
Gary W BeechamThe John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, United States of America.
Carlos CruchagaNeuroGenomics and Informatics Center, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States of America.ORCID https://orcid.org/0000-0002-0276-2899
Christiane ReitzTaub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, United States of America.ORCID https://orcid.org/0000-0001-8757-7889

Funding

PREDICTING COGNITIVE DECLINE IN NONDEMENTED ELDER SUBJECTSP01AG003991 · NIA · WASHINGTON UNIVERSITY · PI JOHN MORRIS · 1985 to 2023
$14.7M
EPIDEMIOLOGY OF NEURAL RESERVE AND NEUROBIOLOGY IN AGINGR01AG017917 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI DAVID ALAN BENNETT · 2001 to 2023
$11.9M
SUPPLEMENT TO RUSH ALZHEIMERS DISEASE CENTER COREP30AG010161 · RUSH UNIVERSITY MEDICAL CENTER · 1991 to 2005
$10.7M
RISK FACTORS, PATHOLOGY, AND CLINICAL EXPRESSIONS OF ADR01AG015819 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI DAVID ALAN BENNETT · 1998 to 2024
$6.0M
Research Education CoreP30AG066462 · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2025 to 2025
$4.8M
Genome Center for Alzheimer's Disease (GCAD)U54AG052427 · UNIVERSITY OF PENNSYLVANIA · 2025 to 2025
$3.9M
Rush Alzheimer's Disease Research CenterP30AG072975 · RUSH UNIVERSITY MEDICAL CENTER · 2025 to 2025
$3.1M
Genetic and neuroanatomical basis of neuropsychiatric symptoms in Alzheimer's disease in populations of diverse ancestryU01AG079850 · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2025 to 2025
$737k
NIA NIH HHS P01 AG003991NIA NIH HHS P30 AG010161NIA NIH HHS P30 AG066462NIA NIH HHS P30 AG072975NIA NIH HHS R01 AG015819NIA NIH HHS R01 AG017917NIA NIH HHS R01 AG062268NIA NIH HHS R01 AG064614NIA NIH HHS U01 AG032984NIA NIH HHS U01 AG046152NIA NIH HHS U01 AG061356NIA NIH HHS U01 AG079850NIA NIH HHS U54 AG052427NIMH NIH HHS R01 MH120794
6 · The paper itself

Abstract

The genetic component of early-onset Alzheimer disease (EOAD), accounting for ~10% of all Alzheimer's disease (AD) cases, is largely unexplained. Recent studies suggest that EOAD may be enriched for variants acting in the lipid pathway. The current study examines the shared genetic heritability between EOAD and the lipid pathway using genome-wide multi-trait genetic covariance analyses. Summary statistics were obtained from the GWAS meta-analyses of EOAD by the Alzheimer's Disease Genetics Consortium (n=19,668) and five blood lipid traits by the Global Lipids Genetics Consortium (n=1,320,016). The significant results were compared between the EOAD and lipids GWAS and genetic covariance analyses were performed via SUPERGNOVA. Genes in linkage disequilibrium (LD) with top EOAD hits in identified regions of covariance with lipid traits were scored and ranked for causality by combining evidence from gene-based analysis, AD-risk scores incorporating transcriptomic and proteomic evidence, eQTL data, eQTL colocalization analyses, DNA methylation data, and single-cell RNA sequencing analyses. Direct comparison of GWAS results showed 5 loci overlapping between EOAD and at least one lipid trait harboring APOE, TREM2, MS4A4E, LILRA5, and LRRC25. Local genetic covariance analyses identified 3 regions of covariance between EOAD and at least one lipid trait. Gene prioritization nominated 3 likely causative genes at these loci: ANKDD1B, CUZD1, and MS4A64.The current study identified genetic covariance between EOAD and lipids, providing further evidence of shared genetic architecture and mechanistic pathways between the two traits.

Indexed as

Alzheimer DiseaseLipid MetabolismLipidsAge of OnsetDNA MethylationFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansLinkage DisequilibriumMalePolymorphism, Single NucleotideQuantitative Trait LociReceptors, ImmunologicLipidsReceptors, Immunologic

Identifiers

PMID40096060
PMCPMC11984970

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.