Evidence map›Paper›PMID 42142451›Full record

ArticleNeurobiology of aging2026

Predicted brain-regional gene expression patterns in individuals living with Alzheimer's disease.

Ali Razavi, Jiahui Hou, Shu-Ju Lin, Chunling Zhang, William S Kremen, Christine Fennema-Notestine, Jeremy Elman, Peter Holmans, Stephen V Faraone, Chris Gaiteri and 2 more

Abstract read
In one paragraph

Article in Neurobiology of aging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Ali RazaviDepartment of Neuroscience & Physiology, Norton College of Medicine, SUNY Upstate Medical University, Syracuse, NY, USA.
Jiahui HouDepartment of Psychiatry & Behavioral Sciences, Norton College of Medicine, SUNY Upstate Medical University, Syracuse, NY, USA.
Shu-Ju LinDepartment of Psychiatry, University of California San Diego, La Jolla, CA, USA.
Chunling ZhangDepartment of Neuroscience & Physiology, Norton College of Medicine, SUNY Upstate Medical University, Syracuse, NY, USA.
William S KremenDepartment of Psychiatry, University of California San Diego, La Jolla, CA, USA.
Christine Fennema-NotestineDepartment of Psychiatry, University of California San Diego, La Jolla, CA, USA; Department of Radiology, University of California San Diego, La Jolla, CA, USA.
Jeremy ElmanDepartment of Psychiatry, University of California San Diego, La Jolla, CA, USA.
Peter HolmansMRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK.
Stephen V FaraoneDepartment of Psychiatry & Behavioral Sciences, Norton College of Medicine, SUNY Upstate Medical University, Syracuse, NY, USA; Department of Neuroscience & Physiology, Norton College of Medicine, SUNY Upstate Medical University, Syracuse, NY, USA.
Chris GaiteriDepartment of Psychiatry & Behavioral Sciences, Norton College of Medicine, SUNY Upstate Medical University, Syracuse, NY, USA.
Jonathan L HessDepartment of Psychiatry & Behavioral Sciences, Norton College of Medicine, SUNY Upstate Medical University, Syracuse, NY, USA.
Stephen J GlattDepartment of Psychiatry & Behavioral Sciences, Norton College of Medicine, SUNY Upstate Medical University, Syracuse, NY, USA; Department of Public Health & Preventive Medicine, SUNY Upstate Medical University, Syracuse, NY, USA. Electronic address: GlattS@upstate.edu.

Funding

The VETSA Longitudinal Twin Study of Cognition and Aging (VETSA 4)R01AG050595 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ELMAN, JEREMY A, FRANZ, CAROL ELAINE · 2015 to 2024
$28.0M
The VETSA Longitudinal MRI Twin Study of Aging (VETSA MRI 4)R01AG076838 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANDERS M DALE, Jeremy A Elman · 2022 to 2026
$8.7M
Identifying therapeutic targets that confer synaptic resilience to Alzheimer's diseaseR01AG061800 · NIA · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Christopher A. Gaiteri, Jeremy H. Herskowitz · 2018 to 2026
$6.9M
Genetic Predictors, Transcriptomic Biomarkers, & Neurobiological Signatures of Resilience to Alzheimer's DiseaseR01AG064955 · NIA · UPSTATE MEDICAL UNIVERSITY · PI FENNEMA-NOTESTINE, CHRISTINE, GLATT, STEPHEN J · 2019 to 2023
$3.8M
Integrating Genetic, Neuroimaging, Transcriptomic, and Clinical Risk Factors as Multivariate Predictors of Cognitive Deterioration in Alzheimer's Disease.R01NS128535 · NINDS · UPSTATE MEDICAL UNIVERSITY · PI HESS, JONATHAN · 2022 to 2024
$1.2M
Linking genetic subtypes of Alzheimer's disease to biological and cognitive heterogeneityK01AG063805 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ELMAN, JEREMY A · 2021 to 2024
$516k
NIA NIH HHS K01 AG063805NIA NIH HHS R01 AG050595NIA NIH HHS R01 AG061800NIA NIH HHS R01 AG064955NIA NIH HHS R01 AG076838NINDS NIH HHS R01 NS128535
6 · The paper itself

Abstract

Studying brain gene expression in Alzheimer's Disease (AD) remains difficult as postmortem brain is difficult to access, cannot be used to guide donor treatment, may be confounded by environmental factors before and after death, and is difficult to link to early AD states or disease progression. To circumvent these limitations, several studies have tested blood transcriptome biomarkers for AD. However, gene-expression levels in the blood have limited correlation with those in the brain. To evaluate the potential of monitoring Alzheimer's progression with peripheral data, we used transcriptome-imputation to identify brain-region-specific AD-associated gene-expression differences in cohorts with blood-based transcriptome data. This approach provides a high-resolution image of AD-associated molecular differences in the brains of individuals actively living with disease. We analyzed eight AD studies (777 AD cases, 779 cognitively unimpaired controls), imputing transcriptomes in 10 brain regions via the Brain Gene Expression and Network Imputation Engine (BrainGENIE). Hundreds of differentially expressed genes (DEGs) associated with AD were identified in nine brain regions, with anterior cingulate cortex and amygdala showing the most differential expression. AD-associated genes were enriched in pathways such as proteostasis, mitochondrial dysfunction, and immune activation. We observed significant yet moderate concordance between imputed AD-associated changes and those directly measured in the dorsolateral prefrontal cortex and cerebellum. These transcriptomic changes can guide future in vitro studies focused on pathogenesis or be targets of novel therapeutic development. In conclusion, we demonstrated the scope and utility of brain expression imputation from the peripheral transcriptome, laying the groundwork for biomarker discovery and prospective AD studies.

Indexed as

Alzheimer DiseaseBrainGene ExpressionTranscriptomeAgedBiomarkersDisease ProgressionFemaleHumansMaleBiomarkersAlzheimer’s DiseaseBlood-based BiomarkersBrain Gene ExpressionGene ImputationNeurodegenerationTranscriptome ImputationTWAS

Identifiers

PMID42142451
PMCPMC13295099

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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 OpenQuestion graph.