Evidence map›Paper›PMID 42845523›Full record

ArticlebioRxiv : the preprint server for biology2026

Sex-Specific Regional Brain Morphometric Correlates of Neighborhood Socioeconomic Disadvantage in Clinical Neuroimaging.

Ethan H Willbrand, Luis A Vazquez, Michael B Fromandi, Paloma C Frautschi, Troy B Powell, John-Paul J Yu

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Ethan H WillbrandMedical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States.ORCID 0000-0003-4625-5642
Luis A VazquezDepartment of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States.
Michael B FromandiMedical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States.
Paloma C FrautschiDepartment of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States.
Troy B PowellMedical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States.
John-Paul J YuMedical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States.

Funding

University of Wisconsin Institute for Clinical and Translational ResearchUL1TR002373 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI ELIZABETH S BURNSIDE, Allan R. Brasier · 2017 to 2026
$75.9M
Research Training for Computation and Informatics in Biology and MedicineT15LM007359 · NLM · UNIVERSITY OF WISCONSIN-MADISON · PI Mark W. Craven, Colin Noel Dewey · 2002 to 2026
$22.6M
NRSA Training CoreTL1TR002375 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI Vivek Prabhakaran · 2017 to 2026
$8.4M
Integrated Training For Physician-ScientistsT32GM140935 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI Anna Huttenlocher, Jeniel E Nett · 2021 to 2026
$6.5M
NCATS NIH HHS TL1 TR002375NCATS NIH HHS UL1 TR002373NIGMS NIH HHS T32 GM140935NLM NIH HHS T15 LM007359
6 · The paper itself

Abstract

background and purposeNeighborhood-level socioeconomic disadvantage is associated with adverse brain morphometry, yet whether these associations differ by biological sex remain opaque. Here, we investigated sex-specific associations between the area deprivation index and brain morphometry derived from routine clinical MRI in a real-world clinical population. MATERIALS AND

methodsIntracranial volume-normalized regional brain volumes were extracted from T1-weighted MRI examinations performed in 2,863 consecutive clinical patients (median age 54 years [IQR 38-68]; 61.2% female) at a single academic medical center and associated community partners using an automated atlas-based segmentation pipeline. Exploratory factor analysis was applied to 131 regional brain volumes to identify latent neuroanatomical morphometric networks. Sex-stratified linear regression models examined associations between area deprivation index national percentile rank and each factor score, adjusting for age, with correction for multiple comparisons.

resultsFactor analysis identified five neuroanatomical morphometric networks: cerebellar (ML1), frontal/executive (ML2), subcortical-ventricular (ML3), medial temporal/limbic (ML4), and posterior cortical/visual (ML5). In male patients (

conclusionsIn a real-world clinical population, neighborhood-level socioeconomic disadvantage was associated with lower regional brain volumes across cerebellar, frontal/executive, and medial temporal/limbic neuroanatomical morphometric networks in male but not female patients. These findings suggest that the neuroanatomical correlates of neighborhood disadvantage may be sex-specific, and that sex-stratified analyses may be necessary to fully characterize the relationship between the social exposome and brain morphometry in clinical neuroimaging research.

Identifiers

PMID42845523
PMCPMC13640686

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