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Genetic and Environmental Influences on Structural and Diffusion-Based Alzheimer's Disease Neuroimaging Signatures Across Midlife and Early Old Age.
Williams, McKenna E; Gillespie, Nathan A; Bell, Tyler R; Dale, Anders M; Elman, Jeremy A; Eyler, Lisa T; Fennema-Notestine, Christine; Franz, Carol E; Hagler, Donald J; Lyons, Michael J; McEvoy, Linda K; Neale, Michael C; Panizzon, Matthew S; Reynolds, Chandra A; Sanderson-Cimino, Mark; Kremen, William S.
Afiliación
  • Williams ME; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California; Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California San Diego, San Die
  • Gillespie NA; Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, Virginia.
  • Bell TR; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California.
  • Dale AM; Department of Radiology, University of California San Diego, San Diego, California; Department of Neuroscience, University of California San Diego, San Diego, California.
  • Elman JA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California.
  • Eyler LT; Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, California.
  • Fennema-Notestine C; Department of Psychiatry, University of California San Diego, San Diego, California; Department of Radiology, University of California San Diego, San Diego, California.
  • Franz CE; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California.
  • Hagler DJ; Department of Radiology, University of California San Diego, San Diego, California.
  • Lyons MJ; Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts.
  • McEvoy LK; Department of Radiology, University of California San Diego, San Diego, California.
  • Neale MC; Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, Virginia.
  • Panizzon MS; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California.
  • Reynolds CA; Department of Psychology, University of California Riverside, Riverside, California.
  • Sanderson-Cimino M; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California; Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California San Diego, San Die
  • Kremen WS; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California.
Article en En | MEDLINE | ID: mdl-35738479
BACKGROUND: Composite scores of magnetic resonance imaging-derived metrics in brain regions associated with Alzheimer's disease (AD), commonly termed AD signatures, have been developed to distinguish early AD-related atrophy from normal age-associated changes. Diffusion-based gray matter signatures may be more sensitive to early AD-related changes compared with thickness/volume-based signatures, demonstrating their potential clinical utility. The timing of early (i.e., midlife) changes in AD signatures from different modalities and whether diffusion- and thickness/volume-based signatures each capture unique AD-related phenotypic or genetic information remains unknown. METHODS: Our validated thickness/volume signature, our novel mean diffusivity (MD) signature, and a magnetic resonance imaging-derived measure of brain age were used in biometrical analyses to examine genetic and environmental influences on the measures as well as phenotypic and genetic relationships between measures over 12 years. Participants were 736 men from 3 waves of the Vietnam Era Twin Study of Aging (VETSA) (baseline/wave 1: mean age [years] = 56.1, SD = 2.6, range = 51.1-60.2). Subsequent waves occurred at approximately 5.7-year intervals. RESULTS: MD and thickness/volume signatures were highly heritable (56%-72%). Baseline MD signatures predicted thickness/volume signatures over a decade later, but baseline thickness/volume signatures showed a significantly weaker relationship with future MD signatures. AD signatures and brain age were correlated, but each measure captured unique phenotypic and genetic variance. CONCLUSIONS: Cortical MD and thickness/volume AD signatures are heritable, and each signature captures unique variance that is also not explained by brain age. Moreover, results are in line with changes in MD emerging before changes in cortical thickness, underscoring the utility of MD as a very early predictor of AD risk.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedad de Alzheimer Tipo de estudio: Prognostic_studies Límite: Child / Humans / Male Idioma: En Revista: Biol Psychiatry Cogn Neurosci Neuroimaging Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedad de Alzheimer Tipo de estudio: Prognostic_studies Límite: Child / Humans / Male Idioma: En Revista: Biol Psychiatry Cogn Neurosci Neuroimaging Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos