Evidence map›Paper›PMID 38848574›Full record

ReviewAnnual review of biomedical data science2024

Employing Informatics Strategies in Alzheimer's Disease Research: A Review from Genetics, Multiomics, and Biomarkers to Clinical Outcomes.

Jingxuan Bao, Brian N Lee, Junhao Wen, Mansu Kim, Shizhuo Mu, Shu Yang, Christos Davatzikos, Qi Long, Marylyn D Ritchie, Li Shen

Abstract readReview
In one paragraph

Review in Annual review of biomedical data science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Leveraging Social Determinants of Health in Alzheimer's Research Using LLM-Augmented Literature Mining and Knowledge Graphs.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2025
    Article
  5. Enabling Few-Shot Alzheimer's Disease Diagnosis on Biomarker Data with Tabular LLMs.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2025
    Article
  6. 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

10 authors.

Jingxuan BaoDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA; email: Li.Shen@pennmedicine.upenn.edu.
Brian N LeeDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA; email: Li.Shen@pennmedicine.upenn.edu.
Junhao WenLaboratory of AI and Biomedical Science (LABS), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, California, USA.
Mansu KimAI Graduate School, Gwangju Institute of Science and Technology, Gwangju, South Korea.
Shizhuo MuDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA; email: Li.Shen@pennmedicine.upenn.edu.
Shu YangDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA; email: Li.Shen@pennmedicine.upenn.edu.
Christos DavatzikosCenter for Biomedical Image Computing and Analytics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Qi LongDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA; email: Li.Shen@pennmedicine.upenn.edu.
Marylyn D RitchieDepartment of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Li ShenDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA; email: Li.Shen@pennmedicine.upenn.edu.

Funding

Technology Identification and Training CoreP30AG073105 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DEMIRIS, GEORGE, KARLAWISH, JASON H · 2021 to 2025
$21.2M
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
Artificial Intelligence Strategies for Alzheimer's Disease ResearchU01AG066833 · NIA · CEDARS-SINAI MEDICAL CENTER · PI MOORE, JASON H., RITCHIE, MARYLYN D · 2022 to 2025
$6.7M
Translational big data analytic approaches to advance drug repurposing for Alzheimer's diseaseR01AG071470 · NIA · UNIVERSITY OF PENNSYLVANIA · PI KIM, DOKYOON, NING, XIA · 2021 to 2025
$3.8M
Advancing Analysis of Multi-omics Data in Alzheimer's Disease ResearchRF1AG063481 · NIA · UNIVERSITY OF PENNSYLVANIA · PI LONG, QI · 2019 to 2020
$3.8M
Statistical Modeling of Alzheimer's Disease Progression Integrating Brain Imaging and -Omics DataR01AG071174 · NIA · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI KUNDU, SUPRATEEK, LONG, QI · 2021 to 2025
$3.3M
ENIGMA World Aging CenterR01AG058854 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMPSON, PAUL M · 2021 to 2025
$3.3M
An integrative Bayesian approach for linking brain to behavioral phenotypeR01EB034720 · NIBIB · YALE UNIVERSITY · PI R Todd Constable, Yize Zhao · 2023 to 2026
$2.4M
Novel integrative imaging genetics analysis for Alzheimer's disease riskand progressionRF1AG068191 · NIA · YALE UNIVERSITY · PI ZHAO, YIZE · 2021 to 2021
$1.9M
Artificial Intelligence Strategies for Alzheimer's Disease ResearchR01AG066833 · NIA · UNIVERSITY OF PENNSYLVANIA · PI MOORE, JASON H., RITCHIE, MARYLYN D · 2021 to 2021
$1.6M
Informatics Algorithms for Genomic Analysis of Brain Imaging DataR01LM013463 · NLM · UNIVERSITY OF PENNSYLVANIA · PI MOORE, JASON H., SAYKIN, ANDREW J · 2020 to 2023
$1.4M
Novel integrative imaging genetics analysis for Alzheimer's disease riskand progressionR01AG068191 · NIA · YALE UNIVERSITY · PI ZHAO, YIZE · 2024 to 2025
$1.2M
NIA NIH HHS P30 AG073105NIA NIH HHS R01 AG058854NIA NIH HHS R01 AG066833NIA NIH HHS R01 AG068191NIA NIH HHS R01 AG071174NIA NIH HHS R01 AG071470NIA NIH HHS RF1 AG063481NIA NIH HHS RF1 AG068191NIA NIH HHS U01 AG066833NIA NIH HHS U01 AG068057NIBIB NIH HHS R01 EB034720NLM NIH HHS R01 LM013463
6 · The paper itself

Abstract

Alzheimer's disease (AD) is a critical national concern, affecting 5.8 million people and costing more than $250 billion annually. However, there is no available cure. Thus, effective strategies are in urgent need to discover AD biomarkers for disease early detection and drug development. In this review, we study AD from a biomedical data scientist perspective to discuss the four fundamental components in AD research: genetics (G), molecular multiomics (M), multimodal imaging biomarkers (B), and clinical outcomes (O) (collectively referred to as the GMBO framework). We provide a comprehensive review of common statistical and informatics methodologies for each component within the GMBO framework, accompanied by the major findings from landmark AD studies. Our review highlights the potential of multimodal biobank data in addressing key challenges in AD, such as early diagnosis, disease heterogeneity, and therapeutic development. We identify major hurdles in AD research, including data scarcity and complexity, and advocate for enhanced collaboration, data harmonization, and advanced modeling techniques. This review aims to be an essential guide for understanding current biomedical data science strategies in AD research, emphasizing the need for integrated, multidisciplinary approaches to advance our understanding and management of AD.

Indexed as

Alzheimer DiseaseBiomarkersBiomedical ResearchGenomicsHumansMultiomicsBiomarkersAlzheimer's diseaseclinical outcomesgeneticsimagingmolecular multiomics

Identifiers

PMID38848574
PMCPMC11525791

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.