Brain Imaging and Blood Biomarker Abnormalities in Children With Autosomal Dominant Alzheimer Disease:A Cross-Sectional Study Yakeel T.Quiroz,PhD1,2,3,4,5; Aaron P.Schultz,PhD3,4; KeweiChen,PhD6,7,8
Yakeel T. Quiroz, PhD1,2,3,4,5; Aaron P. Schultz, PhD3,4; Kewei Chen, PhD6,7,8; Hillary D. Protas, PhD6,7; Michael Brickhouse, BS3,4,9; Adam S. Fleisher, MD6,10,11; Jessica B. Langbaum, PhD6,7; Pradeep Thiyyagura, MS6,7; Anne M. Fagan, PhD12; Aarti R. Shah, MS12; Martha Muniz, MA13; Joseph F. Arboleda-Velasquez, MD, PhD14,15; Claudia Munoz, BA5; Gloria Garcia, MS5; Natalia Acosta-Baena, MD5; Margarita Giraldo, MD5; Victoria Tirado, MS5; Dora L. Ramírez, MA5; Pierre N. Tariot, MD6,7,16; Bradford C. Dickerson, MD3,4,9; Reisa A. Sperling, MD, MMSc1,3,4,17; Francisco Lopera, MD5; Eric M. Reiman, MD6,7,16,18
ImportanceBrain imaging and fluid biomarkers are characterized in children at risk for autosomal dominant Alzheimer disease (ADAD).
ObjectiveTo characterize and compare structural magnetic resonance imaging (MRI), resting-state and task-dependent functional MRI, and plasma amyloid-β (Aβ) measurements in presenilin 1 (PSEN1) E280A mutation–carrying and noncarrying children with ADAD.
Design, Setting, and ParticipantsCross-sectional measures of structural and functional MRI and plasma Aβ assays were assessed in 18PSEN1E280A carriers and 19 noncarriers aged 9 to 17 years from a Colombian kindred with ADAD. Recruitment and data collection for this study were conducted at the University of Antioquia and the Hospital Pablo Tobon Uribe in Medellín, Colombia, between August 2011 and June 2012.
Main Outcomes and MeasuresAll participants had blood sampling, structural MRI, and functional MRI during associative memory encoding and resting-state and cognitive assessments. Outcome measures included plasma Aβ1-42 concentrations and Aβ1-42:Aβ1-40 ratios, memory encoding–dependent activation changes, resting-state connectivity, and regional gray matter volumes. Structural and functional MRI data were compared using automated brain mapping algorithms and search regions related to AD.ResultsSimilar to findings in adult mutation carriers, in the later preclinical and clinical stages of ADAD, mutation-carrying children were distinguished from control individuals by significantly higher plasma Aβ1-42 levels (mean [SD]: carriers, 18.8 [5.1] pg/mL and noncarriers, 13.1 [3.2] pg/mL;P < .001) and Aβ1-42:Aβ1-40 ratios (mean [SD]: carriers, 0.32 [0.06] and noncarriers, 0.21 [0.03];P < .001), as well as less memory encoding task–related deactivation in parietal regions (eg, mean [SD] parameter estimates for the right precuneus were −0.590 [0.50] for noncarriers and −0.087 [0.38] for carriers;P < .005 uncorrected). Unlike carriers in the later stages, mutation-carrying children demonstrated increased functional connectivity of the posterior cingulate cortex with medial temporal lobe regions (mean [SD] parameter estimates were 0.038 [0.070] for noncarriers and 0.190 [0.057] for carriers), as well as greater gray matter volumes in temporal regions (eg, left parahippocampus;P < . 049, corrected for multiple comparisons).
Conclusions and RelevanceChildren at genetic risk for ADAD have functional and structural brain changes and abnormal levels of plasma Aβ1-42. The extent to which the underlying brain changes are either neurodegenerative or developmental remains to be determined. This study provides additional information about the earliest known biomarker changes associated with ADAD.
JAMA Neurol.2015;72(8):912-919. doi:10.1001/jamaneurol.2015.1099.
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