001048933 001__ 1048933
001048933 005__ 20251211202155.0
001048933 037__ $$aFZJ-2025-05030
001048933 1001_ $$0P:(DE-Juel1)181023$$aMiller, Tatiana$$b0$$ufzj
001048933 1112_ $$aAging and Cognition Conference$$cPavia$$d2025-05-07 - 2025-05-10$$wItaly
001048933 245__ $$aWhite Matter Lesions spatial distribution patterns related to cardiovascular aging follow arterial supply territories
001048933 260__ $$c2025
001048933 3367_ $$0PUB:(DE-HGF)1$$2PUB:(DE-HGF)$$aAbstract$$babstract$$mabstract$$s1765445659_15760
001048933 3367_ $$033$$2EndNote$$aConference Paper
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001048933 3367_ $$2DRIVER$$aconferenceObject
001048933 3367_ $$2DataCite$$aOutput Types/Conference Abstract
001048933 3367_ $$2ORCID$$aOTHER
001048933 520__ $$aWhite matter lesions (WML) in brain MRI scans are common in older adults and are linked to cognitive, mood, and motor disorders, as well as increased risks of dementia and stroke. These lesions are influenced by lifestyle and cardiovascular factors. To explore the relationship between cardiovascular health and WML spatial distribution, we analysed the similarity between participants using k-means clustering, based on WML center location, WML burden, and cardiovascular health status, in two population-based cohorts: 1000BRAINS (n=1,040, ages 18-85) and NAKO (n=27,559, ages 19-74). Cardiovascular health status was summarized using a ‘cardiovascular age’ score, which included age, sex, blood pressure, hypertension medication, smoking status, diabetes diagnosis, and cholesterol levels. We mapped the affected brain areas on the Digital 3D Brain MRI Arterial Territories Atlas and tested each cluster’s mean WML distribution, surpassing 95% bootstrap confidence.Our findings revealed five distinct WML spatial distribution patterns in each cohort, four of which were common across both. These patterns highlighted specific arterial territories with varying degrees of WML presence, providing evidence that WML spatial distributions are influenced by cardiovascular aging. Additionally, the medial lenticulostriate territory emerged as the first arterial region affected in normal aging.
001048933 536__ $$0G:(DE-HGF)POF4-5251$$a5251 - Multilevel Brain Organization and Variability (POF4-525)$$cPOF4-525$$fPOF IV$$x0
001048933 536__ $$0G:(EU-Grant)945539$$aHBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539)$$c945539$$fH2020-SGA-FETFLAG-HBP-2019$$x1
001048933 7001_ $$0P:(DE-Juel1)166110$$aBittner, Nora$$b1$$eCorresponding author$$ufzj
001048933 7001_ $$0P:(DE-Juel1)180197$$aDellani, Paulo R.$$b2$$ufzj
001048933 7001_ $$0P:(DE-Juel1)203396$$aQuabs, Julian$$b3$$ufzj
001048933 7001_ $$0P:(DE-Juel1)131675$$aCaspers, Svenja$$b4$$ufzj
001048933 909CO $$ooai:juser.fz-juelich.de:1048933$$popenaire$$pVDB$$pec_fundedresources
001048933 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)181023$$aForschungszentrum Jülich$$b0$$kFZJ
001048933 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)166110$$aForschungszentrum Jülich$$b1$$kFZJ
001048933 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)180197$$aForschungszentrum Jülich$$b2$$kFZJ
001048933 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)203396$$aForschungszentrum Jülich$$b3$$kFZJ
001048933 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131675$$aForschungszentrum Jülich$$b4$$kFZJ
001048933 9131_ $$0G:(DE-HGF)POF4-525$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5251$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vDecoding Brain Organization and Dysfunction$$x0
001048933 9141_ $$y2025
001048933 9201_ $$0I:(DE-Juel1)INM-1-20090406$$kINM-1$$lStrukturelle und funktionelle Organisation des Gehirns$$x0
001048933 980__ $$aabstract
001048933 980__ $$aVDB
001048933 980__ $$aI:(DE-Juel1)INM-1-20090406
001048933 980__ $$aUNRESTRICTED