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We applied network control theory to diffusion magnetic resonance imaging-derived connectomes in 25,697 adults aged 40\u201370 years to quantify the energetic cost of engaging 8 large-scale brain networks. Metabolic syndrome was defined according to established criteria, with a composite score (0\u20135) based on the presence of central obesity, elevated triglycerides, reduced high-density lipoprotein cholesterol, hypertension, and impaired glycemic control. Normative modeling provided age-adjusted network deviations and brain age gap estimates. Associations with metabolic indicators and behavioral cognitive performance (7 tasks in UK Biobank) were tested, and meta-analytic mapping (123 cognitive states in Neurosynth) was used to identify at-risk domains. Severity of metabolic syndrome was associated with distinct, network-specific energetic alterations, including progressively increased subcortical control energy cost, decreased visual, and threshold changes in attentional and executive networks. The control energy profiles of the subcortical and visual networks exhibited accelerated brain age gap trajectories, reflecting significant departures from normative age-matched expectations. Waist circumference was the strongest metabolic predictor, with effects amplified in older age. Partial least squares correlation analysis revealed associations of metabolic profile (central obesity and dyslipidemia) with higher subcortical\/dorsal attention\/control and lower visual network energy. Vulnerability mapping indicated that episodic memory, spatial navigation, and processing speed were the domains at most at risk in relation to higher metabolic syndrome severity scores. Behavioral testing confirmed lower memory and processing speed scores in participants with metabolic syndrome. Overall, metabolic syndrome reshapes the brain\u2019s energetic landscape, accelerates functional brain aging, and selectively impairs memory-related networks. Network control theory-derived metrics offer a mechanistic and sensitive biomarker linking metabolic health to cognitive function. Central adiposity was the primary modifiable driver, underscoring the importance of early, targeted metabolic interventions to preserve network efficiency and cognitive resilience.<\/jats:p>","DOI":"10.1162\/imag.a.1282","type":"journal-article","created":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T20:01:24Z","timestamp":1780516884000},"update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":1,"title":["Metabolic syndrome severity and the energetic cost of brain network transitions: A normative modeling study of accelerated brain aging"],"prefix":"10.1162","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8315-7200","authenticated-orcid":false,"given":"Hyun Soo","family":"Park","sequence":"first","affiliation":[{"name":"Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Yuseong-gu, Daejeon, Republic of 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