Evidence map›Paper›PMID 41677026›Full record

ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2026

From correlation to causation: cell-type-specific gene regulatory networks in Alzheimer's disease.

Danni Liu, Zhongli Jiang, Hyunjin Kim, Anke M Tukker, Ashish Dalvi, Junkai Xie, Yan Li, Chongli Yuan, Aaron B Bowman, Dabao Zhang and 1 more

Abstract read
In one paragraph

Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Integrative Transcriptomics and Mendelian Randomization IdentifyCurrent issues in molecular biology · 2026
    Article
  2. From correlation to causation: cell-type-specific gene regulatory networks in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Danni LiuDepartment of Epidemiology and Biostatistics, University of California, Irvine, California, USA.ORCID 0000-0002-2863-0288
Zhongli JiangDepartment of Epidemiology and Biostatistics, University of California, Irvine, California, USA.
Hyunjin KimSchool of Health Sciences, Purdue University, West Lafayette, Indiana, USA.
Anke M TukkerSchool of Health Sciences, Purdue University, West Lafayette, Indiana, USA.
Ashish DalviCenter for Complex Biological Systems, University of California, Irvine, California, USA.
Junkai XieDavidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana, USA.
Yan LiDepartment of Epidemiology and Biostatistics, University of California, Irvine, California, USA.
Chongli YuanDavidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana, USA.
Aaron B BowmanSchool of Health Sciences, Purdue University, West Lafayette, Indiana, USA.
Dabao ZhangDepartment of Epidemiology and Biostatistics, University of California, Irvine, California, USA.
Min ZhangDepartment of Epidemiology and Biostatistics, University of California, Irvine, California, USA.

Funding

Univ.of Calif., Irvine Cancer Center Support GrantP30CA062203 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI Melanie Funes · 1994 to 2026
$57.9M
Modeling functional genomics of susceptibility to the persistent effects of environmental toxins in an elderly rural Indiana neurodegenerative cohortR01AG080917 · NIA · PURDUE UNIVERSITY · PI Aaron B Bowman, Chongli Yuan · 2022 to 2026
$4.1M
Modeling Homeostasis of Human Blood MetabolitesR01GM131491 · NIGMS · UNIVERSITY OF WASHINGTON · PI RAFTERY, DANIEL, ZHANG, DABAO · 2020 to 2023
$2.2M
Human stem cell derived forebrain model to study persistent neurotoxic effects of trans-placental developmental exposures to environmental pollutantsK99ES036290 · NIEHS · PURDUE UNIVERSITY · PI TUKKER, ANKE MARIJE · 2024 to 2025
$251k
National Cancer Institute (NCI) of the National Institutes of Health (NIH) P30CA062203National Institute of Environmental Health Sciences (NIEHS) of the National Institutes of Health (NIH) K99ES036290National Institute of General Medical Sciences (NIGMS) of the National Institutes of Health (NIH) R01GM131491National Institute of General Medical Sciences (NIGMS) of the National Institutes of Health (NIH) R01GM131491-02S1National Institute on Aging (NIA) of the National Institutes of Health (NIH) R01AG080917National Institute on Aging (NIA) of the National Institutes of Health (NIH) R01AG080917-02S1NCI NIH HHS P30 CA062203NIA NIH HHS R01 AG080917NIEHS NIH HHS K99 ES036290NIGMS NIH HHS R01 GM131491The Anti-Cancer Challenge grant from the Chao Family Comprehensive Cancer Center of the University of California, Irvine
6 · The paper itself

Abstract

introductionAlzheimer's disease (AD) involves complex regulatory disruptions across multiple brain cell types, yet the comprehensive intracellular causal mechanisms remain poorly understood.

methodsWe present an integrative analysis framework using single-nucleus transcriptomics with matched subject-level genotype data from 272 AD patients in the Religious Orders Study and Rush Memory and Aging Project (ROSMAP) and construct causality-based, cell-type-specific gene regulatory networks (GRNs).

resultsOur method identifies regulatory genes among transcription factors (TFs) and non-TFs, generating a complete and accurate causal regulatory map across brain cell types. Our analyses reveal both established and novel regulations, pathways, and cell-type-specific hub genes in AD. Beyond constructing transcriptome-wide GRNs, we quantitatively evaluate hub genes and distinguish those with regulatory versus responsive roles. DISCUSSION: Our study provides a comprehensive map of cell-type-specific causal GRNs in AD, with a methodology applicable to other complex diseases such as cancer, enabling dynamic pathway exploration, hypothesis generation, and functional interpretation. HIGHLIGHTS: Comprehensive causal regulatory maps across six brain cell types revealed cell-type-specific regulatory mechanisms that move beyond traditional correlation-based and TF-centric model limitations. Novel and established hub genes and functional modules were compared across cell types, providing insights into cellular functions related to AD. Hub gene roles as regulators or targets were quantitatively evaluated within cell-type GRNs. The constructed GRNs show upstream non-TF genes regulating TFs and interconnected TF regulatory modules, highlighting the complexity of AD regulatory mechanisms beyond TF-centric assumptions.

Indexed as

Alzheimer DiseaseBrainGene Regulatory NetworksAgedFemaleGene Expression ProfilingHumansMaleTranscription FactorsTranscriptomeTranscription FactorsAlzheimer's diseasecausalitycell‐type‐specificgene regulatory network

Identifiers

PMID41677026
PMCPMC12895379

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.