Article in Science (New York, N.Y.), 2026. 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.
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
18 authors.
Yang Zhang *Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.ORCID 0000-0002-1483-9195
Xinyue Lu *Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.ORCID 0000-0001-7521-9128
Alexander K Kunisky *Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA.ORCID 0000-0002-6974-7474
Shahul Alam *Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.ORCID 0000-0002-4821-7079
Junjie Tang *Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
Ruochi Zhang *Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Shike WangRay and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
Han ZhangComputer Science Department, University of California, Los Angeles, Los Angeles, CA, USA.
Jude BaroudiDepartment of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA.ORCID 0009-0007-1335-5272
Walid IchchoDivision of Hematology and Oncology, Department of Medicine, University of Washington, Seattle, WA, USA.
Deyong JiaDepartment of Urology, University of Washington, Seattle, WA, USA.ORCID 0000-0003-2034-0363
Sahar GhorbanikalatehDepartment of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA.ORCID 0009-0000-8442-7439
Sahel GhorbanikalatehDepartment of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA.ORCID 0009-0006-3555-1496
Shihan WangDepartment of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA.ORCID 0009-0003-2143-4705
Hansruedi MathysDepartment of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA.ORCID 0000-0003-0186-2115
Zhijun DuanDivision of Hematology and Oncology, Department of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0002-8147-793X
Jian MaRay and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.ORCID 0000-0002-4202-5834
Funding
SUPPLEMENT TO RUSH ALZHEIMERS DISEASE CENTER COREP30AG010161 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 1991 to 2020
$49.1M
EPIDEMIOLOGY OF NEURAL RESERVE AND NEUROBIOLOGY IN AGINGR01AG017917 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 2001 to 2023
$43.3M
Rush Alzheimer's Disease Research CenterP30AG072975 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI Lisa L Barnes, Julie A. Schneider · 2021 to 2026
$24.7M
RISK FACTORS, PATHOLOGY, AND CLINICAL EXPRESSIONS OF ADR01AG015819 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 1998 to 2024
$21.4M
Pathway discovery, validation and compound identification for Alzheimer's disease - SupplementU01AG046152 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BENNETT, DAVID ALAN, DE JAGER, PHILIP L · 2013 to 2017
$13.6M
Multiscale Analyses of 4D Nucleome Structure and Function by Comprehensive Multimodal Data IntegrationUM1HG011593 · NHGRI · CARNEGIE-MELLON UNIVERSITY · PI ALBER, FRANK, BELMONT, ANDREW STEVEN · 2020 to 2024
$10.4M
UW 4-Dimensional Genomic Organization of Mammalian Embryogenesis CenterUM1HG011586 · NHGRI · UNIVERSITY OF WASHINGTON · PI DISTECHE, CHRISTINE M., NOBLE, WILLIAM STAFFORD · 2020 to 2024
$10.3M
Alzheimer variants: Propagation of shared functional changes across cellular networksU01AG072572 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI DE JAGER, PHILIP L, ST GEORGE-HYSLOP, PETER HENRY · 2021 to 2025
$8.5M
Impact of Methamphetamine Use on the HIV Nucleome in Individuals on Antiretroviral TherapyR61DA047010 · NIDA · UNIVERSITY OF WASHINGTON · PI DUAN, ZHIJUN, MULLINS, JAMES IVAN · 2018 to 2020
$3.1M
Computational Methods for Next-Generation Comparative GenomicsR01HG007352 · NHGRI · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI MA, JIAN · 2014 to 2023
$2.8M
Computational methods for studying single-cell 3D genomeR01HG012303 · NHGRI · CARNEGIE-MELLON UNIVERSITY · PI DUAN, ZHIJUN, MA, JIAN · 2022 to 2025
$2.2M
Spatial omics technologies to map the senescent cell microenvironmentUH3CA268202 · NCI · BROWN UNIVERSITY · PI MA, JIAN, NERETTI, NICOLA · 2023 to 2025
Alzheimer's disease (AD) disrupts brain function through cell type-specific transcriptomic and epigenomic alterations, yet the contribution of three-dimensional (3D) genome organization to AD remains poorly understood. We applied GAGE-seq (genome architecture and gene expression by sequencing) to jointly profile gene expression and 3D chromatin structure in single cells from postmortem brain tissue from AD patients and age-matched individuals without AD, revealing chromatin reorganization linked to cell type-specific dysregulation. Integrations with spatial transcriptomics and chromatin accessibility data uncovered altered niches reflecting genome compartment remodeling and regulatory element reorganization. Hicformer, a deep learning framework, showed that 3D genome features are essential for predicting disease-relevant, cell type-specific gene expression changes. Our results establish higher-order chromatin alterations as a component of AD-associated molecular pathology, providing a multiscale view of transcriptional regulation and 3D genome organization in neurodegeneration.
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.
Single-cell multiomics connects 3D genome and transcriptome alterations in Alzheimer's disease. · full record | OpenQuestion