The choroid plexus (CP) plays a central role in maintaining brain homeostasis through cerebrospinal fluid production and formation of the blood–cerebrospinal fluid barrier. Dysfunction of the CP has been linked with normative aging and a range of neurological diseases. CP pathology may present as enlargement or as tissue calcification; these represent potentially distinct biological processes with different clinical implications.
Population neuroimaging studies to date have largely focused on lateral ventricle CP volumetry. Volume measures cannot selectively identify calcified tissue, limiting understanding of CP calcific changes. The authors frame the need for an imaging phenotype that detects calcific CP tissue to complement volumetry and to investigate associations with aging, brain structure, and disease risk.
To quantify CP calcification (CPcal) across multiple ventricles, the study used quantitative susceptibility mapping (QSM) applied to imaging from 30,012 participants in the UK Biobank. CPcal was measured in the lateral (LV), third (3rdV), and fourth (4thV) ventricles. The analysis examined associations of CPcal with demographic variables (age, sex), diagnostic categories across endocrine/metabolic, psychiatric, nervous system, and circulatory systems, family history of Alzheimer’s disease and related dementias (ADRD), cardiometabolic traits, and brain structural measures including cortical and subcortical volumes, white matter microstructure, and subcortical susceptibility.
CPcal increased with age across ventricular compartments. The largest reported association with age was observed in the lateral ventricle (correlation r = 0.191). Male sex was associated with greater CPcal in the lateral and third ventricles, with reported effect sizes in the range d = 0.249–0.359. In the fourth ventricle, calcification prevalence was higher in males (odds ratio = 1.274). These findings indicate sex and age differences in CP calcific burden across ventricular regions.
Greater CPcal was associated with a range of clinical diagnostic categories, including endocrine and metabolic disorders, psychiatric and behavioral diagnoses, nervous system conditions, and circulatory disorders. The third ventricle demonstrated the strongest and most consistent associations with these diagnostic groups, with reported effect sizes in the range d = 0.097–0.125. This regional specificity suggests that CPcalcification in the 3rdV may be particularly informative in relation to systemic and neurological disease.
Some of the strongest associations were observed for cardiometabolic-related conditions. After adjusting for ventricular volume, associations persisted—most notably for diabetes (d = 0.303) and tobacco use disorder (d = 0.314). These findings indicate that CPcal associations with cardiometabolic health are not fully explained by overall ventricular enlargement and may reflect specific calcific tissue changes detectable with QSM.
A reported association was observed between a maternal family history of Alzheimer’s disease and related dementias and greater lateral ventricle CPcal (d = 0.063). The authors note this link but do not provide mechanistic detail in the source text.
CPcal was associated with measures of brain macrostructure and microstructure. Small correlations were reported between CPcal and cortical and subcortical volumes (r = 0.033–0.046), white matter microstructure (r = 0.017–0.042), and subcortical susceptibility (r = -0.064–0.131). These associations suggest relationships between CP calcific burden and broader brain structural properties measured in this cohort.
Quantitative susceptibility mapping–derived CPcal is presented as a scalable, radiation-free imaging phenotype that complements traditional volumetry by specifically characterizing calcific CP tissue. In this large sample, CPcal tracked with aging, sex, cardiometabolic disease, psychiatric and nervous system diagnoses, and structural brain measures, with particularly notable associations in the third ventricle. The authors position QSM-derived CPcal as a potential marker relevant to cardiometabolic health, brain aging, and neurodegenerative risk.
The source text is a preprint abstract and reports key associations, effect sizes, and sample size (n = 30,012) but does not include methodological detail beyond the use of QSM and the ventricular targets assessed. Details such as imaging parameters, statistical models, covariates beyond ventricular volume, selection criteria, or full diagnostic definitions were not reported in the provided source text. The authors declared no competing interests and listed NIH grant support in the funding statement.