Yakeel T Quiroz1, Aaron P Schultz2, Kewei Chen3, Hillary D Protas4, Michael Brickhouse5, Adam S Fleisher6, Jessica B Langbaum4, Pradeep Thiyyagura4, Anne M Fagan7, Aarti R Shah7, Martha Muniz8, Joseph F Arboleda-Velasquez9, Claudia Munoz10, Gloria Garcia10, Natalia Acosta-Baena10, Margarita Giraldo10, Victoria Tirado10, Dora L Ramírez10, Pierre N Tariot11, Bradford C Dickerson5, Reisa A Sperling12, Francisco Lopera10, Eric M Reiman13. 1. Department of Neurology, Massachusetts General Hospital, Boston2Department of Psychiatry, Massachusetts General Hospital, Boston3Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston4Harvard Medical School, Boston, Ma. 2. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston4Harvard Medical School, Boston, Massachusetts. 3. Banner Alzheimer's Institute, Phoenix, Arizona7Arizona Alzheimer's Consortium, Phoenix8Department of Mathematics and Statistics, Arizona State University, Tempe. 4. Banner Alzheimer's Institute, Phoenix, Arizona7Arizona Alzheimer's Consortium, Phoenix. 5. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston4Harvard Medical School, Boston, Massachusetts9Frontotemporal Dementia Unit, Department of Neurology, Massachusetts General Hospital, Boston. 6. Banner Alzheimer's Institute, Phoenix, Arizona10Eli Lilly and Company, Indianapolis, Indiana11Department of Neurosciences, University of California, San Diego. 7. Department of Neurology, Washington University School of Medicine, St Louis, Missouri. 8. Psychology Department, Boston University, Boston, Massachusetts. 9. Schepens Eye Research Institute, Massachusetts Eye and Ear Infirmary, Boston15Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts. 10. Grupo de Neurociencias, Universidad de Antioquia, Medellín, Colombia. 11. Banner Alzheimer's Institute, Phoenix, Arizona7Arizona Alzheimer's Consortium, Phoenix16Department of Psychiatry, University of Arizona, Phoenix. 12. Department of Neurology, Massachusetts General Hospital, Boston3Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston4Harvard Medical School, Boston, Massachusetts17Center for Alzheimer Research and Treatment, Departm. 13. Banner Alzheimer's Institute, Phoenix, Arizona7Arizona Alzheimer's Consortium, Phoenix16Department of Psychiatry, University of Arizona, Phoenix18Division of Neurogenomics, Translational Genomics Research Institute, Phoenix, Arizona.
Abstract
IMPORTANCE: Brain imaging and fluid biomarkers are characterized in children at risk for autosomal dominant Alzheimer disease (ADAD). OBJECTIVE: To 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 PARTICIPANTS: Cross-sectional measures of structural and functional MRI and plasma Aβ assays were assessed in 18 PSEN1 E280A 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 MEASURES: All 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. RESULTS: Similar 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 RELEVANCE: Children 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.
IMPORTANCE: Brain imaging and fluid biomarkers are characterized in children at risk for autosomal dominant Alzheimer disease (ADAD). OBJECTIVE: To 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 PARTICIPANTS: Cross-sectional measures of structural and functional MRI and plasma Aβ assays were assessed in 18 PSEN1E280A 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 MEASURES: All 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. RESULTS: Similar 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 RELEVANCE: Children 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.
Authors: Natalia Acosta-Baena; Diego Sepulveda-Falla; Carlos Mario Lopera-Gómez; Mario César Jaramillo-Elorza; Sonia Moreno; Daniel Camilo Aguirre-Acevedo; Amanda Saldarriaga; Francisco Lopera Journal: Lancet Neurol Date: 2011-02-04 Impact factor: 44.182
Authors: Y T Quiroz; B A Ally; K Celone; J McKeever; A L Ruiz-Rizzo; F Lopera; C E Stern; A E Budson Journal: Neurology Date: 2011-07-20 Impact factor: 9.910
Authors: Eric M Reiman; Yakeel T Quiroz; Adam S Fleisher; Kewei Chen; Carlos Velez-Pardo; Marlene Jimenez-Del-Rio; Anne M Fagan; Aarti R Shah; Sergio Alvarez; Andrés Arbelaez; Margarita Giraldo; Natalia Acosta-Baena; Reisa A Sperling; Brad Dickerson; Chantal E Stern; Victoria Tirado; Claudia Munoz; Rebecca A Reiman; Matthew J Huentelman; Gene E Alexander; Jessica B S Langbaum; Kenneth S Kosik; Pierre N Tariot; Francisco Lopera Journal: Lancet Neurol Date: 2012-11-06 Impact factor: 44.182
Authors: Yakeel T Quiroz; Chantal E Stern; Eric M Reiman; Michael Brickhouse; Adriana Ruiz; Reisa A Sperling; Francisco Lopera; Bradford C Dickerson Journal: J Neurol Neurosurg Psychiatry Date: 2012-11-07 Impact factor: 10.154
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Authors: S Rios-Romenets; M Giraldo-Chica; H López; F Piedrahita; C Ramos; N Acosta-Baena; C Muñoz; P Ospina; C Tobón; W Cho; M Ward; J B Langbaum; P N Tariot; E M Reiman; F Lopera Journal: J Prev Alzheimers Dis Date: 2018
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