ArticleStem cell reports2025
Modeling common Alzheimer's disease with high and low polygenic risk in human iPSC: A large-scale research resource.
Article in Stem cell reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- From polygenic risk to functional genomics: a framework for precision gynecological disease modeling.Nature communications · 2026Review
- The Impact of the Exposome on Epithelial Barriers: New Approach Methodologies for Translational Research.Thoracic research and practice · 2026Article
- Are we fully exploiting genetic discoveries to understand and treat Alzheimer's disease?Mammalian genome : official journal of the International Mammalian Genome Society · 2026Article
Corrections and comments
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Authors and funding
24 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Common forms of Alzheimer's disease (AD) are complex and polygenic. We have created a research resource that seeks to capture the extremes of polygenic risk in a collection of human induced pluripotent stem cell (iPSC) lines from over 100 donors: the IPMAR Resource (iPSC Platform to Model Alzheimer's Disease Risk). Donors were selected from a large UK cohort of 6,000+ research-diagnosed early or late-onset AD cases and elderly cognitively healthy controls, many of whom have lived through the age of risk for disease development (>85 years). We include iPSC with extremes of global AD polygenic risk (high-risk late-onset AD: 34; high-risk early-onset AD: 29; low-risk control: 27) as well as those reflecting complement pathway-specific genetic risk (high-risk AD: 9; low-risk controls: 10). All iPSC have associated clinical, longitudinal, and genetic datasets and will be available through collaboration or from cell (EBiSC) and data (DPUK) repositories.
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Registered trials
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.