Evidence map›Paper›PMID 42507057›Full record

ArticleTranslational stroke research2026

Association Between Inflammatory Biomarkers And Carotid Ultrasound Parameters In The Northern Manhattan Stroke Study.

Farid Khasiyev, Minghua Liu, Mady Hornig, Mohammed Nafeli Shahrestani, Clinton B Wright, Mitchell Sv Elkind, Tatjana Rundek, Jose Gutierrez

Abstract read
PubMed Publisher
In one paragraph

Article in Translational stroke research, 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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

8 authors.

Farid KhasiyevDepartment of Neurology, University of Minnesota, Minneapolis, MN, USA.
Minghua LiuDepartment of Neurology, Columbia University, New York, NY, USA.
Mady HornigFeinstein Institutes for Medical Research, Northwell Health, New York, NY, USA.
Mohammed Nafeli ShahrestaniEvelyn F. McKnight Brain Institute, University of Miami Miller School of Medicine, Miami, FL, USA.
Clinton B WrightNational Institute of Neurological Disorders and Stroke, Bethesda, MD, USA.
Mitchell Sv ElkindDepartment of Neurology, Columbia University, New York, NY, USA.
Tatjana RundekEvelyn F. McKnight Brain Institute, University of Miami Miller School of Medicine, Miami, FL, USA.
Jose GutierrezDepartment of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA. Jdg319@miami.edu.

Funding

Cross-disciplinary research opportunity for training in AD/ADRD science (CROSSROADS)T32AG081170 · NIA · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI James E Galvin, Girardin Jean-Louis · 2024 to 2026
$1.4M
NIA NIH HHS T32 AG081170
6 · The paper itself

Abstract

Inflammation contributes to atherosclerosis and vascular remodeling, but the immune pathways associated with distinct carotid ultrasound phenotypes, including carotid intima-media thickness (cIMT), maximal plaque thickness (MPT), and arterial stiffness remain incompletely characterized. We investigated associations between circulating immune biomarkers and carotid ultrasound measures in a stroke-free, multi-ethnic cohort. We analyzed data from 1,134 stroke-free participants (mean age 70 ± 9 years, 59% women, 66% Hispanic) in the Northern Manhattan Study (NOMAS) who underwent high-resolution B-mode carotid ultrasound. cIMT and MPT were measured using automated edge-detection software, while arterial stiffness was assessed via systolic and diastolic diameter measurements, strain, and β-stiffness. Plasma levels of 60 immune biomarkers were quantified using a multiplex immunoassay. Biomarker selection was performed using LASSO, Random Forest, and XGBoost; markers selected by ≥ 2 methods were prioritized. Associations were tested using multivariable linear regression adjusted for age, sex, race/ethnicity, and cardiovascular risk factors (hypertension, hyperlipidemia, diabetes, and smoking). Machine-learning analyses identified partially distinct candidate biomarker profiles for cIMT, MPT, and arterial stiffness. In fully adjusted regression models, greater cIMT was associated with higher IL-4 and leptin levels and lower IL-10, VCAM-1, and SerpinE1 levels. None of the machine-learning-selected biomarkers was independently associated with MPT at the conventional p < 0.05 threshold. Greater arterial stiffness was associated with higher SCF levels, while CXCL10 demonstrated a nonsignificant inverse trend. Models incorporating the selected biomarkers had modestly higher adjusted R² values than models containing clinical covariates alone (cIMT, 0.072 versus 0.109; MPT, 0.134 versus 0.147; arterial stiffness, 0.063 versus 0.075). In a stroke-free, multiethnic cohort, machine-learning analyses identified distinct and overlapping candidate immune biomarker profiles across cIMT, plaque thickness, and arterial stiffness. However, only a subset of selected biomarkers demonstrated independent associations in fully adjusted regression models. These findings support a hypothesis-generating role for inflammatory and immunometabolic pathways in subclinical carotid disease and vascular aging and require validation in longitudinal studies.

Indexed as

Carotid ArteriesCarotid Intima-Media ThicknessInflammationStrokeUltrasonography, Carotid ArteriesAgedBiomarkersCohort StudiesFemaleHumansMaleMiddle AgedNew York CityVascular StiffnessBiomarkersArterial stiffnessCarotid atherosclerosisCarotid intima-media thicknessCarotid plaqueCarotid ultrasoundImmune pathwaysInflammatory biomarkersMachine learningSubclinical atherosclerosisVascular remodeling

Identifiers

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.