Evidence map›Paper›PMID 38728189›Full record

ArticleJournal of Alzheimer's disease : JAD2024

Deep Trans-Omic Network Fusion for Molecular Mechanism of Alzheimer's Disease.

Linhui Xie, Yash Raj, Pradeep Varathan, Bing He, Meichen Yu, Kwangsik Nho, Paul Salama, Andrew J Saykin, Jingwen Yan

Abstract read
In one paragraph

Article in Journal of Alzheimer's disease : JAD, 2024. 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. Review
  2. Review
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

9 authors.

Linhui XieDepartment of Electrical and Computer Engineering, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA.
Yash RajDepartment of BioHealth Informatics, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA.
Pradeep VarathanDepartment of BioHealth Informatics, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA.
Bing HeDepartment of BioHealth Informatics, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA.
Meichen YuDepartment of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
Kwangsik NhoDepartment of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
Paul SalamaDepartment of Electrical and Computer Engineering, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA.
Andrew J SaykinDepartment of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
Jingwen YanDepartment of BioHealth Informatics, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA.

Funding

Alzheimer's Disease Genetics ConsortiumU01AG032984 · NIA · UNIVERSITY OF PENNSYLVANIA · PI SCHELLENBERG, GERARD DAVID · 2009 to 2024
$60.4M
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
Peripheral and Central Biomarkers of Alzheimer's Disease in Diverse CohortsU19AG074879 · NIA · MAYO CLINIC JACKSONVILLE · PI Minerva Maria Carrasquillo · 2023 to 2026
$42.0M
RISK FACTORS, PATHOLOGY, AND CLINICAL EXPRESSIONS OF ADR01AG015819 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 1998 to 2024
$21.4M
Ultrascale Machine Learning to Empower Discovery in Alzheimers Disease BiobanksU01AG068057 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Christos Davatzikos, Heng Huang · 2020 to 2026
$20.7M
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
Genetic Epidemiology of Cognitive Decline in an Aging Population SampleR01AG030146 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI EVANS, DENIS A · 2007 to 2018
$6.2M
Exploring the Role of the Brain Transcriptome in Cognitive DeclineR01AG036836 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI DE JAGER, PHILIP L · 2011 to 2014
$2.9M
Integrative Predictive Modeling of Alzheimer's DiseaseR21AG072101 · NIA · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI PATANIA, ALICE, YAN, XIAORAN · 2021 to 2021
$446k
Gene co-expression underlying the connectomic alterations in Alzheimer's diseaseR21AG066135 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI YAN, JINGWEN · 2019 to 2020
$428k
NIA NIH HHS P30 AG010161NIA NIH HHS R01 AG015819NIA NIH HHS R01 AG017917NIA NIH HHS R01 AG030146NIA NIH HHS R01 AG036836NIA NIH HHS R21 AG066135NIA NIH HHS R21 AG072101NIA NIH HHS U01 AG032984NIA NIH HHS U01 AG046152NIA NIH HHS U01 AG068057NIA NIH HHS U19 AG074879
6 · The paper itself

Abstract

Background: There are various molecular hypotheses regarding Alzheimer's disease (AD) like amyloid deposition, tau propagation, neuroinflammation, and synaptic dysfunction. However, detailed molecular mechanism underlying AD remains elusive. In addition, genetic contribution of these molecular hypothesis is not yet established despite the high heritability of AD. Objective: The study aims to enable the discovery of functionally connected multi-omic features through novel integration of multi-omic data and prior functional interactions. Methods: We propose a new deep learning model MoFNet with improved interpretability to investigate the AD molecular mechanism and its upstream genetic contributors. MoFNet integrates multi-omic data with prior functional interactions between SNPs, genes, and proteins, and for the first time models the dynamic information flow from DNA to RNA and proteins. Results: When evaluated using the ROS/MAP cohort, MoFNet outperformed other competing methods in prediction performance. It identified SNPs, genes, and proteins with significantly more prior functional interactions, resulting in three multi-omic subnetworks. SNP-gene pairs identified by MoFNet were mostly eQTLs specific to frontal cortex tissue where gene/protein data was collected. These molecular subnetworks are enriched in innate immune system, clearance of misfolded proteins, and neurotransmitter release respectively. We validated most findings in an independent dataset. One multi-omic subnetwork consists exclusively of core members of SNARE complex, a key mediator of synaptic vesicle fusion and neurotransmitter transportation. Conclusions: Our results suggest that MoFNet is effective in improving classification accuracy and in identifying multi-omic markers for AD with improved interpretability. Multi-omic subnetworks identified by MoFNet provided insights of AD molecular mechanism with improved details.

Indexed as

Alzheimer DiseaseDeep LearningPolymorphism, Single NucleotideGene Regulatory NetworksHumansAlzheimer’s diseasedeep learningmulti-omicsneural networksystems biology

Identifiers

PMID38728189
PMCPMC12090225

What OpenQuestion holds

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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.