Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 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.
Meri OkorieEdward and Pearl Fein Memory and Aging Center, University of California, San Francisco, San Francisco, California, USA.ORCID https://orcid.org/0000-0002-0487-3031
Xiaqing JiangDepartment of Psychiatry and Behavioural Sciences, University of California, San Francisco, San Francisco, California, USA.
Kristine YaffeEdward and Pearl Fein Memory and Aging Center, University of California, San Francisco, San Francisco, California, USA.
Jennifer S YokoyamaEdward and Pearl Fein Memory and Aging Center, University of California, San Francisco, San Francisco, California, USA.ORCID https://orcid.org/0000-0001-7274-2634
Shea J AndrewsEdward and Pearl Fein Memory and Aging Center, University of California, San Francisco, San Francisco, California, USA.ORCID https://orcid.org/0000-0002-1921-9470
Health and Aging Brain Study–Health Disparities
Funding
The Health & Aging Brain Study - Health Disparities (HABS-HD)U19AG078109 · NIA · UNIVERSITY OF NORTH TEXAS HLTH SCI CTR · PI LEIGH A JOHNSON · 2022 to 2026
$181.1M
TDP-43 Loss-of-Function: Biology to BiomarkersP01AG019724 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Jennifer Merrilees · 2002 to 2026
$67.2M
National Alzheimer's Coordinating CenterU24AG072122 · NIA · UNIVERSITY OF WASHINGTON · PI STEPHENS, KARI A · 2021 to 2025
$45.8M
Health and Aging Brain among Latino Elders (HABLE-AT(N)) StudyR01AG058533 · NIA · UNIVERSITY OF NORTH TEXAS HLTH SCI CTR · PI JOHNSON, LEIGH A, O'BRYANT, SID E · 2020 to 2025
$45.4M
Project 2: Biomarker Analysis, Non-Genetic Risk Factors, and Their Genetic InteractionsU19AG079774 · NIA · UNIVERSITY OF PENNSYLVANIA · PI HELENA Chang CHUI, Gyungah Jun · 2023 to 2026
$39.4M
Research Education ComponentP30AG062422 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Katherine P Rankin · 2019 to 2026
$36.9M
TR&D3: Intrinsic Surface MappingP41EB015922 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI TOGA, ARTHUR W · 2012 to 2022
$14.1M
Health Disparities in Alzheimer's Disease and Mild Cognitive Impairment among Mexican AmericansR01AG054073 · NIA · UNIVERSITY OF NORTH TEXAS HLTH SCI CTR · PI O'BRYANT, SID E, TOGA, ARTHUR W · 2017 to 2021
$12.6M
Tau Metabolism in FTD: From Gene Mutations to Molecular Chaperones and Lysosomal ProteasesU54NS123985 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KARCH, CELESTE MARIE · 2021 to 2025
$9.0M
US-South American Initiative for Genetic-Neural-Behavioral Interactions in Human Neurodegenerative ResearchR01AG057234 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Claudia Duran-Aniotz, Agustin M. Ibanez · 2019 to 2026
$6.1M
Elucidating clinical heterogeneity in early-onset AD via genomics, transcriptomics, and neuroimagingR01AG062588 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI YOKOYAMA, JENNIFER S · 2019 to 2023
$4.0M
Epigenetic Risk Factors for AD Age at Onset and Health Disparities: HABLE Epigenetics StudyR01AG070862 · NIA · UNIVERSITY OF NORTH TEXAS HLTH SCI CTR · PI BARBER, ROBERT CLINTON · 2021 to 2025
introductionDementia clinical risk scores (CRSs) provide accessible tools for identifying individuals at risk for Alzheimer's disease (AD) and related dementias, yet their performance across diverse populations and relationships to AD endophenotypes remains unclear.
methodsWe evaluated four CRSs, modified Cardiovascular Risk Factors, Aging, and Incidence of Dementia (mCAIDE), Washington Heights-Inwood Columbia Aging Project (WHICAP), Lifestyle for Brain Health (LIBRA), and Cognitive Dementia Risk (CogDRisk), in relation to cognitive impairment (CI) and AD endophenotypes, including tau phosphorylated at threonine 217 (pTau
resultsCogDRisk showed the strongest and most consistent performance across endophenotypes, pTau
conclusionsCRSs capture AD-related risk across diverse populations and modestly reflect underlying biological endophenotypes, supporting their utility in community-based risk assessment.
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.
Associations of dementia polyexposure scores to Alzheimer's disease endophenotypes in a diverse population. · full record | OpenQuestion