Evidence map›Paper›PMID 40156243›Full record

ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2025

Unraveling temporal patterns of diagnostic markers and comorbidities in Alzheimer's disease: Insights from large-scale data.

Bayard Rogers

Abstract read
In one paragraph

Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

1 author.

Bayard RogersUniversity College London, London, UK.

Funding

National Alzheimer's Coordinating CenterU24AG072122 · NIA · UNIVERSITY OF WASHINGTON · PI STEPHENS, KARI A · 2021 to 2025
$45.8M
Research Education ComponentP30AG062422 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Katherine P Rankin · 2019 to 2026
$36.9M
Research Education ComponentP30AG062421 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI BRADFORD C DICKERSON · 2019 to 2026
$36.5M
UCSD Shiley-Marcos Alzheimer's Disease Research Center P30P30AG062429 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DOUGLAS R GALASKO · 2019 to 2026
$34.9M
Wisconsin Alzheimer's Disease Research CenterP30AG062715 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Sanjay Asthana · 2019 to 2026
$34.5M
Research Education ComponentP30AG062677 · NIA · MAYO CLINIC ROCHESTER · PI KEJAL KANTARCI · 2019 to 2026
$33.5M
Research Education ComponentP30AG066514 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Margaret Sewell · 2020 to 2026
$31.0M
Yale Alzheimer Disease Research CenterP30AG066508 · NIA · YALE UNIVERSITY · PI STEPHEN M STRITTMATTER · 2020 to 2026
$30.2M
Research Education CoreP30AG066462 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PHILIP L DE JAGER · 2020 to 2026
$30.1M
Research Education ComponentP30AG066468 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI C. Elizabeth Shaaban · 2020 to 2026
$29.4M
Research Education ComponentP30AG066507 · NIA · JOHNS HOPKINS UNIVERSITY · PI Corinne Pettigrew · 2020 to 2026
$29.3M
University of Washington Alzheimer's Disease Research CenterP30AG066509 · NIA · UNIVERSITY OF WASHINGTON · PI Amanda D. Boyd · 2020 to 2026
$29.0M
NIA NIH HHS P20 AG068024NIA NIH HHS P20 AG068053NIA NIH HHS P20 AG068077NIA NIH HHS P20 AG068082NIA NIH HHS P30 AG062421NIA NIH HHS P30 AG062422NIA NIH HHS P30 AG062429NIA NIH HHS P30 AG062677NIA NIH HHS P30 AG062715NIA NIH HHS P30 AG066444NIA NIH HHS P30 AG066462NIA NIH HHS P30 AG066468NIA NIH HHS P30 AG066506NIA NIH HHS P30 AG066507NIA NIH HHS P30 AG066508NIA NIH HHS P30 AG066509NIA NIH HHS P30 AG066511NIA NIH HHS P30 AG066512NIA NIH HHS P30 AG066514NIA NIH HHS P30 AG066515NIA NIH HHS P30 AG066518NIA NIH HHS P30 AG066519NIA NIH HHS P30 AG066530NIA NIH HHS P30 AG066546NIA NIH HHS P30 AG072931NIA NIH HHS P30 AG072946NIA NIH HHS P30 AG072947NIA NIH HHS P30 AG072958NIA NIH HHS P30 AG072959NIA NIH HHS P30 AG072972NIA NIH HHS P30 AG072973NIA NIH HHS P30 AG072975NIA NIH HHS P30 AG072976NIA NIH HHS P30 AG072977NIA NIH HHS P30 AG072978NIA NIH HHS P30 AG072979NIA NIH HHS R01 AG079280NIA NIH HHS U24 AG072122
6 · The paper itself

Abstract

introductionComorbid conditions associated with Alzheimer's disease (AD) are poorly understood regarding timing and potential impact on disease onset and progression.

methodsMedical Information Mart for Intensive Care-IV electronic health records from 2008 to 2019 were examined. The study identified 2527 AD patients (34.9% male, mean age 80.27 years) among 299,712 patients. We examined the timing of 12 cardiovascular and metabolic diseases relative to AD diagnosis. Data from the National Alzheimer's Coordinating Center validated the findings.

resultsHypertension was the most common comorbidity, diagnosed 1.09 years before AD. Depression was the only comorbidity diagnosed after AD start, 0.16 years on average. AD patients had greater rates of hypertension, hypercholesterolemia, and depression compared to the general population. DISCUSSION: The findings emphasize early detection and therapy of AD-related comorbidities, notably cardiovascular and metabolic diseases. The temporal link between these diseases and AD suggests opportunities for preventive strategies and improved care pathways. HIGHLIGHTS: Temporal analysis of comorbidities: The study reveals hypertension and hyperlipidemia as leading precursors to AD, typically diagnosed 1 to 1.3 years prior to AD onset, while depression emerges predominantly after diagnosis. Unique data integration: Large-scale datasets from MIMIC-IV (n = 299,712) and NACC (n = 51,836) were leveraged to identify chronological patterns in 12 key comorbid conditions relative to AD diagnosis. Sex- and age-specific insights: AD prevalence peaks at 80 to 86 years, with females exhibiting higher rates of LOAD compared to males. Depression as a post-diagnostic marker: Unlike other comorbidities, depression's post-diagnostic mean onset (0.16 years after AD diagnosis) highlights the need for targeted mental health interventions in AD patients. Implications for early detection: Findings suggest that managing hypertension, hyperlipidemia, and other modifiable conditions in midlife may delay or reduce the risk of AD development. Comorbidity variability across cohorts: Hypertension and hypercholesterolemia showed significantly higher prevalence in the NACC cohort compared to MIMIC-IV, reflecting potential dataset-specific biases or regional healthcare differences. Future research directions: Advocates for longitudinal, multiethnic, and global studies to refine early diagnostic criteria and explore preventive strategies tailored to comorbid conditions.

Indexed as

Alzheimer DiseaseHypertensionAgedAged, 80 and overBiomarkersComorbidityDepressionElectronic Health RecordsFemaleHumansMaleTime FactorsBiomarkersAlzheimer's disease (AD)comorbiditiesdisease progressionelectronic health record (EHR)hypertension

Identifiers

PMID40156243
PMCPMC11953563

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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.