Evidence map›Paper›PMID 40506322›Full record

ArticleThe journal of prevention of Alzheimer's disease2025

Impact of cardiovascular risk factors on plasma biomarkers in prediction of Alzheimer's and cerebrovascular neuropathology.

Camilo Bermudez, Jeremy A Syrjanen, Nikki H Stricker, Alicia Algeciras-Schimnich, Naomi Kouri, Walter K Kremers, Ronald C Petersen, Clifford R Jack, David S Knopman, Dennis W Dickson and 9 more

Abstract read
In one paragraph

Article in The journal of prevention of Alzheimer's disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Association of plasma p-tau and p-tau/Aβ ratio with Alzheimer's pathology.The journal of prevention of Alzheimer's disease · 2026
    Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. 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

19 authors.

Camilo BermudezDepartment of Neurology, Mayo Clinic, Rochester, MN, USA.
Jeremy A SyrjanenDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Nikki H StrickerDepartment of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA.
Alicia Algeciras-SchimnichDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
Naomi KouriDepartment of Neuroscience, Mayo Clinic, Jacksonville, FL, USA.
Walter K KremersDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Ronald C PetersenDepartment of Neurology, Mayo Clinic, Rochester, MN, USA.
Clifford R JackDepartment of Radiology, Mayo Clinic, Rochester, MN, USA.
David S KnopmanDepartment of Neurology, Mayo Clinic, Rochester, MN, USA.
Dennis W DicksonDepartment of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
Darren M RothbergDepartment of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
Christina M MoloneyDepartment of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
Baayla D C BoonDepartment of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
Aivi T NguyenDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
R Ross ReichardDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
Melissa E MurrayDepartment of Neuroscience, Mayo Clinic, Jacksonville, FL, USA.
Michelle M MielkeDepartment of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
Prashanthi VemuriDepartment of Radiology, Mayo Clinic, Rochester, MN, USA.
Jonathan Graff-RadfordDepartment of Neurology, Mayo Clinic, Rochester, MN, USA. Electronic address: graff-radford.jonathan@mayo.edu.

Funding

Investigating Resistance and Resilience Mechanisms in Alzheimer’s DiseaseR01AG056366 · NIA · MAYO CLINIC ROCHESTER · PI PRASHANTHI VEMURI · 2017 to 2026
$7.0M
Disease pathways in the population determined by amyloid, tau, and neurodegeneration imaging biomarkersR37AG011378 · NIA · MAYO CLINIC ROCHESTER · PI CLIFFORD R. JACK · 2018 to 2026
$6.8M
NIA NIH HHS R01 AG056366NIA NIH HHS R37 AG011378
6 · The paper itself

Abstract

backgroundPlasma biomarkers for Alzheimer's disease and neurodegeneration have shown accurate prediction of underlying neuropathology. However, chronic cardiovascular risk factors such as diabetes and hypertension are associated with plasma biomarker levels and can influence the accurate prediction of underlying neuropathologic changes.

objectiveTo understand the interaction between plasma biomarkers of Alzheimer's disease and neurodegeneration with cardiovascular risk factors in relation to neuropathologic change in a heterogenous population to ascertain a more accurate utilization of these biomarkers.

designRetrospective, case-control study.

settingPopulation-based, Olmstead county, Minnesota, USA.

participantsThree-hundred and fifty-one participants (aged 87.4 ± 7.5 years) with brain autopsy and antemortem plasma biomarker testing. MEASUREMENTS: Plasma biomarker testing for Aβ42/40, p-tau181, GFAP, and NfL using Quanterix Simoa assays. Cardiovascular risk factors were quantified by a composite score of cardiovascular metabolic conditions (CMC) consisting of a binary history of diabetes, congestive heart failure, stroke, coronary artery disease, atrial fibrillation, hypertension, or dyslipidemia. Plasma biomarkers and cardiovascular metabolic conditions score were Z-scored and neuropathologic scales were binarized into high and low categories. Outcomes included elevated microvascular (Kalaria) and macrovascular (Strozyk) neuropathologic scales as well as Alzheimer's disease neuropathologic change (ADNC), Thal phase, Braak stage, and neuritic plaque score. Multivariate logistic regression models incorporated interaction terms between plasma biomarkers and CMC while controlling for age, sex, cognitive impairment, and BMI.

resultsWe observed that at higher cardiovascular metabolic conditions score, the association between GFAP and overall ADNC (OR = 0.61 [0.42, 0.89]), Thal phase (OR = 0.48 [0.33, 0.71]), and Braak Stage (OR = 0.56 [0.37, 0.84]), became weaker, while the association with Strozyk score (OR = 1.65 [1.11, 2.46]) was stronger with higher CMC. Meanwhile, at higher CMC Aβ42/40 became more strongly negative with high Braak stage (OR = 0.63 [0.47, 0.85]), neuritic plaque score (OR 0.70 [0.52, 0.95]), Kalaria score (OR = 0.71 [0.57, 0.88]), and Strozyk score (OR = 0.60 [0.43, 0.83]). The association between p-tau181 and Thal phase (OR = 1.43 [1.00, 2.04]) was stronger at higher CMC while the association between p-tau181 and Strozyk score (OR = 0.47 [0.31, 0.71]) was weaker at higher CMC. There was no interaction between NfL and CMC score for any metric of neuropathologic change.

conclusionUnderstanding how cardiovascular risk factors can modulate plasma biomarkers is important for their interpretation with respect to underlying pathology and their clinical application in screening, diagnosis, and prognosis of neurodegenerative diseases.

Indexed as

Alzheimer DiseaseBiomarkersBrainCardiovascular DiseasesCerebrovascular DisordersHeart Disease Risk FactorsAgedAged, 80 and overAmyloid beta-PeptidesCase-Control StudiesFemaleGlial Fibrillary Acidic ProteinHumansMaleMinnesotaNeurofilament ProteinsAmyloid beta-PeptidesBiomarkersGFAP protein, humanGlial Fibrillary Acidic Proteinneurofilament protein LNeurofilament ProteinsPeptide Fragmentstau ProteinsCardiovascular risk factorsNeuropathologyPlasma biomarkers

Identifiers

PMID40506322
PMCPMC12413713

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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.