Cross-sectional study observes advanced brain-age gaps linked to reduced frontal and temporal lobe volumes in military breachers, indicating region-specific structural vulnerability.
Objective: To determine whether military breachers show significant positive raw brain-age gap and to identify which intracranial-volume (ICV)-normalized lobar volumes best predict bias-corrected brain-age gap (BAGc). Setting and Participants: Eighty-five male (mean age 30.1 ± 4.5 years) Canadian Special Operations Forces (CANSOF) active breachers. Design: Cross-sectional. Main Measures: T1-weighted MRI was processed using the Brain Structure Ages (BSA) pipeline to derive global brain age and lobar volumes. Raw brain-age gap was calculated as estimated age minus chronological age. BAGc was obtained by residualizing raw BAG on chronological age and sex. Linear models tested associations between BAGc and ICV-normalized lobar volumes, adjusting for age. Multiple comparisons were controlled using Benjamini-Hochberg false discovery rate (FDR). Outlier robustness was assessed with Tukey IQR trimming. Results: Participants showed a significant positive raw brain-age gap (mean 8.81 ± 3.98 years; P < .001). After age-bias correction, smaller temporal (β = −0.41, q = 0.002) and frontal (β = −0.43, q = 0.006) lobe volumes were significantly associated with higher BAGc. Associations involving the limbic, parietal, and occipital lobes were not statistically significant after correction for multiple comparison. Findings were stable across outlier-trimming strategies. Conclusions: A positive raw brain-age gap was observed within this cohort of military breachers, with age-independent variation in brain-age deviation showing regionally patterned associations. After age-bias correction, higher BAGc was most strongly associated with relatively smaller frontal and temporal lobe volumes. These findings provide a foundation for future studies incorporating detailed exposure characterization, clinical measures, appropriate comparison groups, longitudinal follow-up, and multimodal imaging.
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Fernández-Ruíz et al. (2026) studied this question.
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