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Bell TR, Franz CE, Eyler LT, Fennema-Notestine C, Puckett OK, Dorros SM, Panizzon MS, Pearce RC, Hagler DJ, Lyons MJ, Beck A, Elman JA, Kremen WS. Probable chronic pain, brain structure, and Alzheimer's plasma biomarkers in older men. J Pain 2024:S1526-5900(24)00014-2. [PMID: 38199594 DOI: 10.1016/j.jpain.2024.01.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 12/06/2023] [Accepted: 01/03/2024] [Indexed: 01/12/2024]
Abstract
Chronic pain leads to tau accumulation and hippocampal atrophy in mice. In this study, we provide one of the first assessments in humans, examining the associations of probable chronic pain with hippocampal volume, integrity of the locus coeruleus (LC)-an upstream site of tau deposition-and Alzheimer's Disease-related plasma biomarkers. Participants were mostly cognitively unimpaired men. Probable chronic pain was defined as moderate-to-severe pain in 2+ study waves at average ages 56, 62, and 68. At age 68, 424 participants underwent structural magnestic resonance imaging (MRI) of hippocampal volume and LC-sensitive MRI providing an index of LC integrity (LC contrast-to-noise ratio). Analyses adjusted for confounders including major health conditions, depressive symptoms, and opioid use. Models showed that men with probable chronic pain had smaller hippocampal volume and lower rostral-middle-but not caudal-LC contrast-to-noise ratio compared to men without probable chronic pain. Men with probable chronic pain also had higher levels of plasma total tau, beta-amyloid-42, and beta-amyloid-40 compared to men without probable chronic pain. These findings suggest that probable chronic pain is associated with tau accumulation and reduced structural brain integrity in regions affected early in the development of Alzheimer's Disease. PERSPECTIVE: Probable chronic pain was associated with plasma biomarkers and brain regions that are affected early in Alzheimer's disease (AD). Reducing pain in midlife and elucidating biological mechanisms may help to reduce the risk of AD in older adults.
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Affiliation(s)
- Tyler R Bell
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, California
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, California
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, California
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, California; Department of Radiology, University of California San Diego, San Diego, La Jolla, California
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, California
| | - Stephen M Dorros
- Department of Radiology, University of California San Diego, San Diego, La Jolla, California
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, California
| | - Rahul C Pearce
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, California
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, San Diego, La Jolla, California; Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, California
| | - Michael J Lyons
- Department of Psychology, Boston University, Boston, Massachusetts
| | - Asad Beck
- Graduate Program in Neuroscience, University of Washington, Seattle, Washington
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, California
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, California
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Tang R, Elman JA, Dale AM, Dorros SM, Eyler LT, Fennema-Notestine C, Gustavson DE, Hagler DJ, Lyons MJ, Panizzon MS, Puckett OK, Reynolds CA, Franz CE, Kremen WS. Childhood Disadvantage Moderates Late Midlife Default Mode Network Cortical Microstructure and Visual Memory Association. J Gerontol A Biol Sci Med Sci 2024; 79:glad114. [PMID: 37096346 DOI: 10.1093/gerona/glad114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Indexed: 04/26/2023] Open
Abstract
BACKGROUND Childhood disadvantage is a prominent risk factor for cognitive and brain aging. Childhood disadvantage is associated with poorer episodic memory in late midlife and functional and structural brain abnormalities in the default mode network (DMN). Although age-related changes in DMN are associated with episodic memory declines in older adults, it remains unclear if childhood disadvantage has an enduring impact on this later-life brain-cognition relationship earlier in the aging process. Here, within the DMN, we examined whether its cortical microstructural integrity-an early marker of structural vulnerability that increases the risk for future cognitive decline and neurodegeneration-is associated with episodic memory in adults at ages 56-66, and whether childhood disadvantage moderates this association. METHODS Cortical mean diffusivity (MD) obtained from diffusion magnetic resonance imaging was used to measure microstructural integrity in 350 community-dwelling men. We examined both visual and verbal episodic memory in relation to DMN MD and divided participants into disadvantaged and nondisadvantaged groups based on parental education and occupation. RESULTS Higher DMN MD was associated with poorer visual memory but not verbal memory (β = -0.11, p = .040 vs β = -0.04, p = .535). This association was moderated by childhood disadvantage and was significant only in the disadvantaged group (β = -0.26, p = .002 vs β = -0.00, p = .957). CONCLUSIONS Lower DMN cortical microstructural integrity may reflect visual memory vulnerability in cognitively normal adults earlier in the aging process. Individuals who experienced childhood disadvantage manifested greater vulnerability to cortical microstructure-related visual memory dysfunction than their nondisadvantaged counterparts who exhibited resilience in the face of low cortical microstructural integrity.
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Affiliation(s)
- Rongxiang Tang
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, California, USA
- Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Stephen M Dorros
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, California, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Daniel E Gustavson
- Institute for Behavior Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, California, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
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Gillespie NA, Elman JA, McKenzie RE, Tu XM, Xian H, Reynolds CA, Panizzon MS, Lyons MJ, Eglit GML, Neale MC, Rissman RA, Franz C, Kremen WS. The heritability of blood-based biomarkers related to risk of Alzheimer's disease in a population-based sample of early old-age men. Alzheimers Dement 2024; 20:356-365. [PMID: 37622539 PMCID: PMC10843753 DOI: 10.1002/alz.13407] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 06/23/2023] [Accepted: 06/27/2023] [Indexed: 08/26/2023]
Abstract
INTRODUCTION Despite their increased application, the heritability of Alzheimer's disease (AD)-related blood-based biomarkers remains unexplored. METHODS Plasma amyloid beta 40 (Aβ40), Aβ42, the Aβ42/40 ratio, total tau (t-tau), and neurofilament light (NfL) data came from 1035 men 60 to 73 years of age (μ = 67.0, SD = 2.6). Twin models were used to calculate heritability and the genetic and environmental correlations between them. RESULTS Additive genetics explained 44% to 52% of Aβ42, Aβ40, t-tau, and NfL. The Aβ42/40 ratio was not heritable. Aβ40 and Aβ42 were genetically near identical (rg = 0.94). Both Aβ40 and Aβ42 were genetically correlated with NfL (rg = 0.35 to 0.38), but genetically unrelated to t-tau. DISCUSSION Except for Aβ42/40, plasma biomarkers are heritable. Aβ40 and Aβ42 share mostly the same genetic influences, whereas genetic influences on plasma t-tau and NfL are largely unique in early old-age men. The absence of genetic associations between the Aβs and t-tau is not consistent with the amyloid cascade hypothesis.
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Affiliation(s)
- Nathan A. Gillespie
- Virginia Institute for Psychiatric and Behaviour GeneticsDepartment of PsychiatryVirginia Commonwealth UniversityRichmondVirginiaUSA
- QIMR Berghofer Medical Research InstituteBrisbaneQueenslandAustralia
| | - Jeremy A. Elman
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - Ruth E. McKenzie
- Department of PsychologyBoston UniversityBostonMassachusettsUSA
- School of Education and Social PolicyMerrimack CollegeNorth AndoverMassachusettsUSA
| | - Xin M. Tu
- Center for Behavior Genetics of AgingUniversity of California, San DiegoLa JollaCaliforniaUSA
- Department of Family Medicine and Public HealthUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - Hong Xian
- Department of Epidemiology and BiostatisticsSaint. Louis UniversitySt. LouisMissouriUSA
- Research Service, VA St. Louis Healthcare SystemSt. LouisMissouriUSA
| | | | - Matthew S. Panizzon
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - Michael J. Lyons
- Department of Psychological and Brain SciencesBoston UniversityBostonMassachusettsUSA
| | - Graham M. L. Eglit
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
- Sam and Rose Stein Institute for Research on AgingUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Michael C. Neale
- Virginia Institute for Psychiatric and Behaviour GeneticsDepartment of PsychiatryVirginia Commonwealth UniversityRichmondVirginiaUSA
| | - Robert A. Rissman
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - Carol Franz
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - William S. Kremen
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of California, San DiegoLa JollaCaliforniaUSA
- Department of NeurosciencesUniversity of California, San DiegoLa JollaCaliforniaUSA
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Elman JA, Schork NJ, Rangan AV. Exploring the genetic heterogeneity of Alzheimer's disease: Evidence for genetic subtypes. medRxiv 2023:2023.05.02.23289347. [PMID: 37205553 PMCID: PMC10187457 DOI: 10.1101/2023.05.02.23289347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Background Alzheimer's disease (AD) exhibits heterogeneity in cognitive impairment, atrophy, and pathological accumulation, suggesting the potential existence of subtypes. AD is under substantial genetic influence, thus identifying systematic variation in genetic risk may provide insights into disease origins. Objective We investigated genetic heterogeneity in AD risk through a multi-step analysis. Methods We performed principal component analysis (PCA) on AD-associated variants in the UK Biobank (AD cases=2,739, controls=5,478) to assess the presence of structured genetic heterogeneity. Subsequently, a biclustering algorithm searched for distinct disease-specific genetic signatures among subsets of cases. Replication tests were conducted using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset (AD cases=500, controls=470). We categorized a separate set of ADNI individuals with mild cognitive impairment (MCI; n=399) into genetic subtypes and examined cognitive, amyloid, and tau trajectories. Results PCA revealed three distinct clusters ("constellations") within AD-associated variants containing a mixture of cases and controls, reflecting disease-relevant structure. We found two disease-specific biclusters among AD cases. Pathway analysis linked bicluster-associated variants to neuron morphogenesis and outgrowth, including genes related to cellular components and development-modulating factors. Both disease-relevant and disease-specific structure replicated in ADNI. Individuals with genetic signatures resembling bicluster 2 exhibited increased CSF p-tau and cognitive decline over time. Conclusions This study unveils a hierarchical structure of AD genetic risk. Disease-relevant constellations may represent differential biological vulnerability that is itself not sufficient to increase risk. Biclusters may represent distinct AD genetic subtypes. This structure replicates in an independent dataset and relates to differential pathological accumulation and cognitive decline over time.
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Affiliation(s)
- Jeremy A. Elman
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - Nicholas J. Schork
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- The Translational Genomics Research Institute, Quantitative Medicine and Systems Biology, Phoenix, AZ, USA
| | - Aaditya V. Rangan
- Department of Mathematics, New York University, New York, New York, USA
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Bell TR, Elman JA, Beck A, Fennema-Notestine C, Gustavson DE, Hagler DJ, Jak AJ, Lyons MJ, Puckett OK, Toomey R, Franz CE, Kremen WS. Rostral-middle locus coeruleus integrity and subjective cognitive decline in early old age. J Int Neuropsychol Soc 2023; 29:763-774. [PMID: 36524301 PMCID: PMC10272292 DOI: 10.1017/s1355617722000881] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
OBJECTIVES Abnormal tau, a hallmark Alzheimer's disease (AD) pathology, may appear in the locus coeruleus (LC) decades before AD symptom onset. Reports of subjective cognitive decline are also often present prior to formal diagnosis. Yet, the relationship between LC structural integrity and subjective cognitive decline has remained unexplored. Here, we aimed to explore these potential associations. METHODS We examined 381 community-dwelling men (mean age = 67.58; SD = 2.62) in the Vietnam Era Twin Study of Aging who underwent LC-sensitive magnetic resonance imaging and completed the Everyday Cognition scale to measure subjective cognitive decline along with their selected informants. Mixed models examined the associations between rostral-middle and caudal LC integrity and subjective cognitive decline after adjusting for depressive symptoms, physical morbidities, and family. Models also adjusted for current objective cognitive performance and objective cognitive decline to explore attenuation. RESULTS For participant ratings, lower rostral-middle LC contrast to noise ratio (LCCNR) was associated with significantly greater subjective decline in memory, executive function, and visuospatial abilities. For informant ratings, lower rostral-middle LCCNR was associated with significantly greater subjective decline in memory only. Associations remained after adjusting for current objective cognition and objective cognitive decline in respective domains. CONCLUSIONS Lower rostral-middle LC integrity is associated with greater subjective cognitive decline. Although not explained by objective cognitive performance, such a relationship may explain increased AD risk in people with subjective cognitive decline as the LC is an important neural substrate important for higher order cognitive processing, attention, and arousal and one of the first sites of AD pathology.
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Affiliation(s)
- Tyler R. Bell
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, CA, 92093
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, 92093
| | - Jeremy A. Elman
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, CA, 92093
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, 92093
| | - Asad Beck
- Center for Neurotechnology, University of Washington, Seattle, WA, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, CA, 92093
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, 92093
- Department of Radiology, University of California San Diego, San Diego, La Jolla, CA, 92093
| | - Daniel E. Gustavson
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO
| | - Donald J. Hagler
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, CA, 92093
- Department of Radiology, University of California San Diego, San Diego, La Jolla, CA, 92093
| | - Amy J. Jak
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, CA, 92093
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, 92093
| | - Michael J Lyons
- Department of Psychology, Boston University, Boston, MA, USA, 02215
| | - Olivia K. Puckett
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, CA, 92093
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, 92093
| | - Rosemary Toomey
- Department of Psychology, Boston University, Boston, MA, USA, 02215
| | - Carol E. Franz
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, CA, 92093
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, 92093
| | - William S. Kremen
- Department of Psychiatry, University of California San Diego, San Diego, La Jolla, CA, 92093
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, 92093
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Williams ME, Elman JA, Bell TR, Dale AM, Eyler LT, Fennema-Notestine C, Franz CE, Gillespie NA, Hagler DJ, Lyons MJ, McEvoy LK, Neale MC, Panizzon MS, Reynolds CA, Sanderson-Cimino M, Kremen WS. Higher cortical thickness/volume in Alzheimer's-related regions: protective factor or risk factor? Neurobiol Aging 2023; 129:185-194. [PMID: 37343448 PMCID: PMC10676195 DOI: 10.1016/j.neurobiolaging.2023.05.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 04/18/2023] [Accepted: 05/03/2023] [Indexed: 06/23/2023]
Abstract
Some evidence suggests a biphasic pattern of changes in cortical thickness wherein higher, rather than lower, thickness is associated with very early Alzheimer's disease (AD) pathology. We examined whether integrating information from AD brain signatures based on mean diffusivity (MD) can aid in the interpretation of cortical thickness/volume as a risk factor for future AD-related changes. Participants were 572 men in the Vietnam Era Twin Study of Aging who were cognitively unimpaired at baseline (mean age = 56 years; range = 51-60). Individuals with both high thickness/volume signatures and high MD signatures at baseline had lower cortical thickness/volume in AD signature regions and lower episodic memory performance 12 years later compared to those with high thickness/volume and low MD signatures at baseline. Groups did not differ in level of young adult cognitive reserve. Our findings are in line with a biphasic model in which increased cortical thickness may precede future decline and establish the value of examining cortical MD alongside cortical thickness to identify subgroups with differential risk for poorer brain and cognitive outcomes.
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Affiliation(s)
- McKenna E Williams
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.
| | - Jeremy A Elman
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Tyler R Bell
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, CA, USA; Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Carol E Franz
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Matthew S Panizzon
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, CA, USA
| | - Mark Sanderson-Cimino
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - William S Kremen
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
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Williams ME, Gillespie NA, Bell TR, Dale AM, Elman JA, Eyler LT, Fennema-Notestine C, Franz CE, Hagler DJ, Lyons MJ, McEvoy LK, Neale MC, Panizzon MS, Reynolds CA, Sanderson-Cimino M, Kremen WS. Genetic and Environmental Influences on Structural and Diffusion-Based Alzheimer's Disease Neuroimaging Signatures Across Midlife and Early Old Age. Biol Psychiatry Cogn Neurosci Neuroimaging 2023; 8:918-927. [PMID: 35738479 PMCID: PMC9827615 DOI: 10.1016/j.bpsc.2022.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 05/04/2022] [Accepted: 06/07/2022] [Indexed: 01/27/2023]
Abstract
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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Affiliation(s)
- McKenna E Williams
- 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 Diego, California.
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, Virginia
| | - Tyler R Bell
- 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
| | - Anders M Dale
- Department of Radiology, University of California San Diego, San Diego, California; Department of Neuroscience, University of California San Diego, San Diego, California
| | - Jeremy A Elman
- 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
| | - Lisa T Eyler
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, California
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, San Diego, California; Department of Radiology, University of California San Diego, San Diego, California
| | - Carol E Franz
- 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
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, San Diego, California
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, San Diego, California
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, Virginia
| | - Matthew S Panizzon
- 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
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, California
| | - Mark Sanderson-Cimino
- 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 Diego, California
| | - William S Kremen
- 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
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Sanderson-Cimino M, Chen R, Tu XM, Elman JA, Jak AJ, Kremen WS. Misinterpreting cognitive change over multiple timepoints: When practice effects meet age-related decline. Neuropsychology 2023; 37:568-581. [PMID: 37079809 PMCID: PMC10313772 DOI: 10.1037/neu0000903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/22/2023] Open
Abstract
OBJECTIVE Practice effects (PE) on cognitive testing have been shown to delay detection of impairment and impede our ability to assess change. When decline over time is expected, as with older adults or progressive diseases, failure to adequately address PEs may lead to inaccurate conclusions because PEs artificially boost scores while pathology- or age-related decline reduces scores. Unlike most methods, a participant-replacement approach can separate pathology- or age-related decline from PEs; however, this approach has only been used across two timepoints. More than two timepoints make it possible to determine if PEs level out after the first follow-up, but it is analytically challenging because individuals may not be assessed at every timepoint. METHOD We examined 1,190 older adults who were cognitively unimpaired (n = 809) or had mild cognitive impairment (MCI; n = 381). Participants completed six neuropsychological measures at three timepoints (baseline, 12-month, 24-month). We implemented a participant-replacement method using generalized estimating equations in comparisons of matched returnees and replacements to calculate PEs. RESULTS Without accounting for PEs, cognitive function appeared to improve or stay the same. However, with the participant-replacement method, we observed significant PEs within both groups at all timepoints. PEs did not uniformly decrease across time; some-specifically on episodic memory measures-continued to increase beyond the first follow-up. CONCLUSION A replacement method of PE adjustment revealed significant PEs across two follow-ups. As expected in these older adults, accounting for PEs revealed cognitive decline. This, in turn, means earlier detection of cognitive deficits, including progression to MCI, and more accurate characterization of longitudinal change. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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Affiliation(s)
- Mark Sanderson-Cimino
- Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco
- Center for Behavior Genetics of Aging, University of California, San Diego
| | - Ruohui Chen
- Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego
| | - Xin M. Tu
- School of Medicine, University of California, San Diego
- Family Medicine and Public Health, University of California San Diego
- Sam and Rose Stein Institute for Research on Aging, University of California San Diego
| | - Jeremy A. Elman
- Center for Behavior Genetics of Aging, University of California, San Diego
- School of Medicine, University of California, San Diego
| | - Amy J. Jak
- Center for Behavior Genetics of Aging, University of California, San Diego
- Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System
| | - William S. Kremen
- Center for Behavior Genetics of Aging, University of California, San Diego
- School of Medicine, University of California, San Diego
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Bell TR, Beck A, Gillespie NA, Reynolds CA, Elman JA, Williams ME, Gustavson DE, Lyons MJ, Neale MC, Kremen WS, Franz CE. A Traitlike Dimension of Subjective Memory Concern Over 30 Years Among Adult Male Twins. JAMA Psychiatry 2023:2804641. [PMID: 37163244 PMCID: PMC10173101 DOI: 10.1001/jamapsychiatry.2023.1004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Importance Subjective memory concern has long been considered a state-related indicator of impending cognitive decline or dementia. The possibility that subjective memory concern may itself be a heritable trait is largely ignored, yet such an association would substantially confound its use in clinical or research settings. Objective To assess the heritability and traitlike dimensions of subjective memory concern and its clinical correlates. Design, Setting, and Participants This longitudinal twin cohort study was conducted from 1967 to 2019 among male adults with a mean (SD) age of 37.75 (2.52) years to follow-up at mean ages of 56.15 (2.72), 61.50 (2.43), and 67.35 (2.57) years (hereafter, 38, 56, 62, and 67 years, respectively) in the Vietnam Era Twin Study of Aging. The study included a national community-dwelling sample with health, education, and lifestyle characteristics comparable to a general sample of US men in this age cohort. Participants were monozygotic and dizygotic twins randomly recruited from the Vietnam Era Twin Registry. Data were analyzed from May 2021 to December 2022. Main Outcomes and Measures Measures included subjective memory concern at 4 time points; objective memory, depressive symptoms, and anxiety at the last 3 time points; negative emotionality (trait neuroticism) at age 56 years; polygenic risk scores (PRSs) for neuroticism, depression, and Alzheimer disease; APOE genotype; and parental history of dementia. Primary outcomes were heritability and correlations between subjective memory concern and other measures. Results The sample included 1555 male adults examined at age 38 years, 520 at age 56 years (due to late introduction of subjective memory concern questions), 1199 at age 62 years, and 1192 at age 67 years. Phenotypically, subjective memory concerns were relatively stable over time. At age 56 years, subjective memory concern had larger correlations with depressive symptoms (r, 0.32; 95% CI, 0.21 to 0.42), anxiety (r, 0.36; 95% CI, 0.18 to 0.51), and neuroticism (r, 0.34; 95% CI, 0.26 to 0.41) than with objective memory (r, -0.24; 95% CI, -0.33 to -0.13). Phenotypic results were similar at ages 62 and 67 years. A best-fitting autoregressive twin model indicated that genetic influences on subjective memory concern accumulated and persisted over time (h2 = 0.26-0.34 from age 38-67 years). At age 56 years, genetic influences for subjective memory concern were moderately correlated with genetic influences for anxiety (r, 0.36; 95% CI, 0.18 to 0.51), negative emotionality (r, 0.51; 95% CI, 0.44-0.57), and depressive symptoms (r, 0.20; 95% CI, 0.10 to 0.29) as well as objective memory (r, -0.22; 95% CI, -0.30 to -0.14). Similar genetic correlations were seen at ages 62 and 67 years. The neuroticism PRS was associated with subjective memory concern at age 38 years (r, 0.10; 95% CI, 0.03. to 0.18) and age 67 years (r, 0.09; 95% CI, 0.01 to 0.16). Subjective memory concern was not associated with any Alzheimer disease risk measures. Conclusions and Relevance This cohort study found stable genetic influences underlying subjective memory concern dating back to age 38 years. Subjective memory concern had larger correlations with affect-related measures than with memory-related measures. Improving the utility of subjective memory concern as an indicator of impending cognitive decline and dementia may depend on isolating its statelike component from its traitlike component.
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Affiliation(s)
- Tyler R Bell
- Center for Behavior Genetics of Aging, Department of Psychiatry, University of California, San Diego, La Jolla
| | - Asad Beck
- Graduate Program in Neuroscience, University of Washington, Seattle
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond
| | | | - Jeremy A Elman
- Center for Behavior Genetics of Aging, Department of Psychiatry, University of California, San Diego, La Jolla
| | - McKenna E Williams
- Center for Behavior Genetics of Aging, Department of Psychiatry, University of California, San Diego, La Jolla
- Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego
| | | | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond
| | - William S Kremen
- Center for Behavior Genetics of Aging, Department of Psychiatry, University of California, San Diego, La Jolla
| | - Carol E Franz
- Center for Behavior Genetics of Aging, Department of Psychiatry, University of California, San Diego, La Jolla
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10
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Schork NJ, Elman JA. Pathway-specific polygenic risk scores correlate with clinical status and Alzheimer's-related biomarkers. Res Sq 2023:rs.3.rs-2583037. [PMID: 36909609 PMCID: PMC10002839 DOI: 10.21203/rs.3.rs-2583037/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/05/2023]
Abstract
Background: APOE is the largest genetic risk factor for sporadic Alzheimer's disease (AD), but there is a substantial polygenic component as well. Polygenic risk scores (PRS) can summarize small effects across the genome but may obscure differential risk associated with different molecular processes and pathways. Variability at the genetic level may contribute to the extensive phenotypic heterogeneity of Alzheimer's disease (AD). Here, we examine polygenic risk impacting specific pathways associated with AD and examined its relationship with clinical status and AD biomarkers of amyloid, tau, and neurodegeneration (A/T/N). Methods: A total of 1,411 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) with genotyping data were included. Sets of variants identified from a pathway analysis of AD GWAS summary statistics were combined into clusters based on their assigned pathway. We constructed pathway-specific PRSs for each participant and tested their associations with diagnostic status (AD vs cognitively normal), abnormal levels of amyloid and ptau (positive vs negative), and hippocampal volume. The APOE region was excluded from all PRSs, and analyses controlled for APOE -ε4 carrier status. Results: Thirteen pathway clusters were identified relating to categories such as immune response, amyloid precursor processing, protein localization, lipid transport and binding, tyrosine kinase, and endocytosis. Eight pathway-specific PRSs were significantly associated with AD dementia diagnosis. Amyloid-positivity was associated with endocytosis and fibril formation, response misfolded protein, and regulation protein tyrosine PRSs. Ptau positivity and hippocampal volume were both related to protein localization and mitophagy PRS, and ptau positivity was additionally associated with an immune signaling PRS. A global AD PRS showed stronger associations with diagnosis and all biomarkers compared to pathway PRSs, suggesting a strong synergistic effect of all loci contributing to the global AD PRS. Conclusions: Pathway PRS may contribute to understanding separable disease processes, but do not appear to add significant power for predictive purposes. These findings demonstrate that, although genetic risk for AD is widely distributed, AD-phenotypes may be preferentially associated with risk in specific pathways. Defining genetic risk along multiple dimensions at the individual level may help clarify the etiological heterogeneity in AD.
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11
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Garduno AC, Laughlin GA, Bergstrom J, Tu XM, Cummins KM, Franz CE, Elman JA, Lyons MJ, Reynolds CA, Neale MC, Gillespie NA, Xian H, McKenzie RE, Toomey R, Kremen WS, Panizzon MS, McEvoy LK. Alcohol use and cognitive aging in middle-aged men: The Vietnam Era Twin Study of Aging. J Int Neuropsychol Soc 2023; 29:235-245. [PMID: 35465863 PMCID: PMC9592679 DOI: 10.1017/s1355617722000169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
OBJECTIVE To determine associations of alcohol use with cognitive aging among middle-aged men. METHOD 1,608 male twins (mean 57 years at baseline) participated in up to three visits over 12 years, from 2003-2007 to 2016-2019. Participants were classified into six groups based on current and past self-reported alcohol use: lifetime abstainers, former drinkers, very light (1-4 drinks in past 14 days), light (5-14 drinks), moderate (15-28 drinks), and at-risk drinkers (>28 drinks in past 14 days). Linear mixed-effects regressions modeled cognitive trajectories by alcohol group, with time-based models evaluating rate of decline as a function of baseline alcohol use, and age-based models evaluating age-related differences in performance by current alcohol use. Analyses used standardized cognitive domain factor scores and adjusted for sociodemographic and health-related factors. RESULTS Performance decreased over time in all domains. Relative to very light drinkers, former drinkers showed worse verbal fluency performance, by -0.21 SD (95% CI -0.35, -0.07), and at-risk drinkers showed faster working memory decline, by 0.14 SD (95% CI 0.02, -0.20) per decade. There was no evidence of protective associations of light/moderate drinking on rate of decline. In age-based models, light drinkers displayed better memory performance at advanced ages than very light drinkers (+0.14 SD; 95% CI 0.02, 0.20 per 10-years older age); likely attributable to residual confounding or reverse association. CONCLUSIONS Alcohol consumption showed minimal associations with cognitive aging among middle-aged men. Stronger associations of alcohol with cognitive aging may become apparent at older ages, when cognitive abilities decline more rapidly.
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Affiliation(s)
- Alexis C Garduno
- Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University, San Diego, CA, USA
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, USA
| | - Gail A Laughlin
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, USA
| | - Jaclyn Bergstrom
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, USA
| | - Xin M Tu
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, USA
| | - Kevin M Cummins
- Department of Public Health, California State University, Fullerton, CA, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, CA, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Hong Xian
- Department of Statistics, St Louis University, St Louis, MO, USA
- Research Service, VA St Louis Healthcare System, St Louis, MO, USA
| | - Ruth E McKenzie
- Department of Psychology, Boston University, Boston, MA, USA
- Department of Applied Human Development and Community Studies, Merrimack College, North Andover, MA, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Linda K McEvoy
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, USA
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Schork NJ, Elman JA. Pathway-Specific Polygenic Risk Scores Correlate with Clinical Status and Alzheimer's Disease-Related Biomarkers. J Alzheimers Dis 2023; 95:915-929. [PMID: 37661888 PMCID: PMC10697039 DOI: 10.3233/jad-230548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
BACKGROUND APOE is the largest genetic risk factor for Alzheimer's disease (AD), but there is a substantial polygenic component. Polygenic risk scores (PRS) can summarize small effects across the genome but may obscure differential risk across molecular processes and pathways that contribute to heterogeneity of disease presentation. OBJECTIVE We examined polygenic risk impacting specific AD-associated pathways and its relationship with clinical status and biomarkers of amyloid, tau, and neurodegeneration (A/T/N). METHODS We analyzed data from 1,411 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We applied pathway analysis and clustering to identify AD-associated "pathway clusters" and construct pathway-specific PRSs (excluding the APOE region). We tested associations with diagnostic status, abnormal levels of amyloid and ptau, and hippocampal volume. RESULTS Thirteen pathway clusters were identified, and eight pathway-specific PRSs were significantly associated with AD diagnosis. Amyloid-positivity was associated with endocytosis and fibril formation, response misfolded protein, and regulation protein tyrosine PRSs. Ptau positivity and hippocampal volume were both related to protein localization and mitophagy PRS, and ptau-positivity was also associated with an immune signaling PRS. A global AD PRS showed stronger associations with diagnosis and all biomarkers compared to pathway PRSs. CONCLUSIONS Pathway PRS may contribute to understanding separable disease processes, but do not add significant power for predictive purposes. These findings demonstrate that AD-phenotypes may be preferentially associated with risk in specific pathways, and defining genetic risk along multiple dimensions may clarify etiological heterogeneity in AD. This approach to delineate pathway-specific PRS can be used to study other complex diseases.
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Affiliation(s)
- Nicholas J. Schork
- The Translational Genomics Research Institute, Quantitative Medicine and Systems Biology, Phoenix, AZ, USA
- Department of Psychiatry University of California, San Diego, La Jolla, CA, USA
| | - Jeremy A. Elman
- Department of Psychiatry University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
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13
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Franz CE, Gustavson DE, Elman JA, Fennema-Notestine C, Hagler DJ, Baraff A, Tu XM, Wu TC, DeAnda J, Beck A, Kaufman JD, Whitsel N, Finch CE, Chen JC, Lyons MJ, Kremen WS. Associations Between Ambient Air Pollution and Cognitive Abilities from Midlife to Early Old Age: Modification by APOE Genotype. J Alzheimers Dis 2023; 93:193-209. [PMID: 36970897 PMCID: PMC10827529 DOI: 10.3233/jad-221054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
BACKGROUND Fine particulate matter (PM2.5) and nitrogen dioxide (NO2) measures of ambient air pollution are associated with accelerated age-related cognitive impairment, and Alzheimer's disease and related dementias (ADRD). OBJECTIVE We examined associations between air pollution, four cognitive factors, and the moderating role of apolipoprotein E (APOE) genotype in the understudied period of midlife. METHODS Participants were ∼1,100 men in the Vietnam Era Twin Study of Aging. Baseline cognitive assessments were from 2003 to 2007. Measures included past (1993-1999) and recent (3 years prior to baseline assessment) PM2.5 and NO2 exposure, in-person assessment of episodic memory, executive function, verbal fluency, and processing speed, and APOE genotype. Average baseline age was 56 years with a 12-year follow-up. Analyses adjusted for health and lifestyle covariates. RESULTS Performance in all cognitive domains declined from age 56 to 68. Higher PM2.5 exposures were associated with worse general verbal fluency. We found significant exposure-by-APOE genotype interactions for specific cognitive domains: PM2.5 with executive function and NO2 with episodic memory. Higher PM2.5 exposure was related to worse executive function in APOE ɛ4 carriers, but not in non-carriers. There were no associations with processing speed. CONCLUSION These results indicate negative effects of ambient air pollution exposure on fluency alongside intriguing differential modifications of cognitive performance by APOE genotype. APOE ɛ4 carriers appeared more sensitive to environmental differences. The process by which air pollution and its interaction with genetic risk for ADRD affects risk for later life cognitive decline or progression to dementia may begin in midlife.
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Affiliation(s)
- Carol E. Franz
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA
| | - Daniel E. Gustavson
- Institute for Behavior Genetics, University of Colorado Boulder, Boulder, CO
| | - Jeremy A. Elman
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA
| | - Christine Fennema-Notestine
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA
- Department of Radiology, University of California, San Diego, La Jolla, CA
| | - Donald J. Hagler
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA
- Department of Radiology, University of California, San Diego, La Jolla, CA
- Department of Neurosciences, University of California, San Diego, La Jolla, CA
| | - Aaron Baraff
- Vietnam Era Twin Registry, VA Puget Sound Health Care, Seattle, WA
| | - Xin M. Tu
- Herbert Wertheim School of Public Health & Human Longevity Science, University of California San Diego, CA
| | - Tsung-Chin Wu
- Herbert Wertheim School of Public Health & Human Longevity Science, University of California San Diego, CA
| | - Jaden DeAnda
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA
- Department of Psychology, San Diego State University, San Diego, CA
| | - Asad Beck
- Graduate Program in Neuroscience, University of Washington, Seattle, WA
| | - Joel D. Kaufman
- Epidemiology, Environmental and Occupational Health Sciences, and General Internal Medicine, University of Washington, Seattle, WA
| | - Nathan Whitsel
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA
| | - Caleb E. Finch
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA
| | - Jiu-Chiuan Chen
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - William S. Kremen
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA
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Tang R, Panizzon MS, Elman JA, Gillespie NA, Hauger RL, Rissman RA, Lyons MJ, Neale MC, Reynolds CA, Franz CE, Kremen WS. Association of neurofilament light chain with renal function: mechanisms and clinical implications. Alzheimers Res Ther 2022; 14:189. [PMID: 36527130 PMCID: PMC9756450 DOI: 10.1186/s13195-022-01134-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 12/03/2022] [Indexed: 12/23/2022]
Abstract
BACKGROUND Blood-based neurofilament light chain (NfL) is a promising biomarker of neurodegeneration across multiple neurodegenerative diseases. However, blood-based NfL is highly associated with renal function in older adults, which leads to the concern that blood-based NfL levels may be influenced by renal function, rather than neurodegeneration alone. Despite growing interest in using blood-based NfL as a biomarker of neurodegeneration in research and clinical practices, whether renal function should always be accounted for in these settings remains unclear. Moreover, the mechanisms underlying this association between blood-based measures of NfL and renal function remain elusive. In this study, we first evaluated the effect of renal function on the associations of plasma NfL with other measures of neurodegeneration. We then examined the extent of genetic and environmental contributions to the association between plasma NfL and renal function. METHODS In a sample of 393 adults (mean age=75.22 years, range=54-90), we examined the associations of plasma NfL with cerebrospinal fluid (CSF) NfL and brain volumetric measures before and after adjusting for levels of serum creatinine (an index of renal function). In an independent sample of 969 men (mean age=67.57 years, range=61-73) that include monozygotic and dizygotic twin pairs, we replicated the same analyses and leveraged biometrical twin modeling to examine the genetic and environmental influences on the plasma NfL and creatinine association. RESULTS Plasma NfL's associations with cerebrospinal fluid NfL and brain volumetric measures did not meaningfully change after adjusting for creatinine levels. Both plasma NfL and creatinine were significantly heritable (h2=0.54 and 0.60, respectively). Their phenotypic correlation (r=0.38) was moderately explained by shared genetic influences (genetic correlation=0.46) and unique environmental influences (unique environmental correlation=0.27). CONCLUSIONS Adjusting for renal function is unnecessary when assessing associations between plasma NfL and other measures of neurodegeneration but is necessary if plasma NfL is compared to a cutoff for classifying neurodegeneration-positive versus neurodegeneration-negative individuals. Blood-based measures of NfL and renal function are heritable and share common genetic influences.
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Affiliation(s)
- Rongxiang Tang
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA.
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, 92093, USA.
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, 92093, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, 92093, USA
| | - Nathan A Gillespie
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, 23284, USA
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Richard L Hauger
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, 92093, USA
- Center of Excellence for Stress and Mental Health (CESAMH), VA San Diego Healthcare System, San Diego, CA, 92093, USA
| | - Robert A Rissman
- Department of Neurosciences, University of California San Diego, CA, 92093, La Jolla, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, 02212, USA
| | - Michael C Neale
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, 23284, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, CA, 92521, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, 92093, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, 92093, USA
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15
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Gillespie NA, Rissman RA, Elman JA, Reynolds CA, Panizzon MS, Lyons MJ, Neale MC, Franz CE, Kremen WS. The etiology of blood‐based biomarkers for Alzheimer’s Disease in a population‐based sample of mid to late‐age males. Alzheimers Dement 2022. [DOI: 10.1002/alz.060480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
| | - Robert A. Rissman
- Department of Neurosciences, University of California San Diego CA USA
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16
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Tang R, Elman JA, Franz CE, Hagler DJ, Puckett OK, Kremen WS. Brain Controllability of Cognitive Control Networks is Associated with Executive Functions in Older Adults. Alzheimers Dement 2022. [DOI: 10.1002/alz.060583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
| | | | | | | | | | - William S. Kremen
- University of California, San Diego La Jolla CA USA
- VA San Diego Healthcare System San Diego CA USA
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17
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Franz CE, Elman JA, Fennema‐Notestine C, Whitsell N, Wu T, Tu XM, Qin YA, Kremen WS. APOE‐e4 Status Moderates Associations between Executive Function and Air Pollution Exposure in Older Men. Alzheimers Dement 2022. [DOI: 10.1002/alz.069339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
| | | | | | | | - Tsung‐Chin Wu
- University of California, San Diego San Diego CA USA
| | - Xin M Tu
- University of California, San Diego La Jolla CA USA
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Gustavson DE, Archer DB, Elman JA, Fennema‐Notestine C, Hagler DJ, Panizzon MS, Shashikumar N, Hohman TJ, Jefferson AL, Lyons MJ, Franz CE, Kremen WS. Executive Functions and Episodic Memory are Associated with Extracellular White Matter Microstructure in Early Old Age. Alzheimers Dement 2022. [DOI: 10.1002/alz.062268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Daniel E. Gustavson
- Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center Nashville TN USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center Nashville TN USA
| | - Derek B Archer
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center Nashville TN USA
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center Nashville TN USA
| | | | | | | | | | - Niranjana Shashikumar
- Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center Nashville TN USA
| | - Timothy J. Hohman
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center Nashville TN USA
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center Nashville TN USA
- Vanderbilt University Nashville TN USA
| | - Angela L. Jefferson
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center Nashville TN USA
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center Nashville TN USA
- Vanderbilt University Nashville TN USA
| | | | | | - William S. Kremen
- University of California, San Diego La Jolla CA USA
- VA San Diego Healthcare System San Diego CA USA
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Gustavson DE, Archer DB, Elman JA, Puckett OK, Fennema-Notestine C, Panizzon MS, Shashikumar N, Hohman TJ, Jefferson AL, Eyler LT, McEvoy LK, Lyons MJ, Franz CE, Kremen WS. Associations among executive function Abilities, free Water, and white matter microstructure in early old age. Neuroimage Clin 2022; 37:103279. [PMID: 36493704 PMCID: PMC9731853 DOI: 10.1016/j.nicl.2022.103279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 10/26/2022] [Accepted: 11/30/2022] [Indexed: 12/04/2022]
Abstract
BACKGROUND Studies have investigated white matter microstructure in relation to late-life cognitive impairments, with fractional anisotropy (FA) and mean diffusivity (MD) measures thought to capture demyelination and axonal degradation. However, new post-processing methods allow isolation of free water (FW), which captures extracellular fluid contributions such as atrophy and neuroinflammation, from tissue components. FW also appears to be highly relevant to late-life cognitive impairment. Here, we evaluated whether executive functions are associated with FW, and FA and MD corrected for FW (FAFWcorr and MDFWcorr). METHOD We examined 489 non-demented men in the Vietnam Era Twin Study of Aging (VETSA) at mean age 68. Two latent factors capturing 'common executive function' and 'working-memory specific' processes were estimated based on 6 tasks. Analyses focused on 11 cortical white matter tracts across three metrics: FW, FAFWcorr, and MDFWcorr. RESULTS Better 'common executive function' was associated with lower FW across 9 of the 11 tracts. There were no significant associations with intracellular metrics after false discovery rate correction. Effects also appeared driven by individuals with MCI (13.7% of the sample). Working memory-specific tasks showed some associations with FAFWcorr, including the triangularis portion of the inferior frontal gyrus. There was no evidence that cognitive reserve (i.e., general cognitive ability assessed in early adulthood) moderated these associations between executive function and FW or FA. DISCUSSION Executive function abilities in early old age are associated primarily with extracellular fluid (FW) as opposed to white matter (FAFWcorr or MDFWcorr). Moderation analyses suggested cognitive reserve does not play a strong role in these associations, at least in this sample of non-demented men.
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Affiliation(s)
- Daniel E Gustavson
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Derek B Archer
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - Christine Fennema-Notestine
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - Niranjana Shashikumar
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Timothy J Hohman
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Angela L Jefferson
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, La Jolla, CA, USA; Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
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20
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Beam CR, Luczak SE, Panizzon MS, Reynolds CA, Christensen K, Dahl Aslan AK, Elman JA, Franz CE, Kremen WS, Lee T, Nygaard M, Sachdev PS, Whitfield KE, Pedersen NL, Gatz M. Estimating Likelihood of Dementia in the Absence of Diagnostic Data: A Latent Dementia Index in 10 Genetically Informed Studies. J Alzheimers Dis 2022; 90:1187-1201. [PMID: 36213997 PMCID: PMC9741742 DOI: 10.3233/jad-220472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
BACKGROUND Epidemiological research on dementia is hampered by differences across studies in how dementia is classified, especially where clinical diagnoses of dementia may not be available. OBJECTIVE We apply structural equation modeling to estimate dementia likelihood across heterogeneous samples within a multi-study consortium and use the twin design of the sample to validate the results. METHODS Using 10 twin studies, we implement a latent variable approach that aligns different tests available in each study to assess cognitive, memory, and functional ability. The model separates general cognitive ability from components indicative of dementia. We examine the validity of this continuous latent dementia index (LDI). We then identify cut-off points along the LDI distributions in each study and align them across studies to distinguish individuals with and without probable dementia. Finally, we validate the LDI by determining its heritability and estimating genetic and environmental correlations between the LDI and clinically diagnosed dementia where available. RESULTS Results indicate that coordinated estimation of LDI across 10 studies has validity against clinically diagnosed dementia. The LDI can be fit to heterogeneous sets of memory, other cognitive, and functional ability variables to extract a score reflective of likelihood of dementia that can be interpreted similarly across studies despite diverse study designs and sampling characteristics. Finally, the same genetic sources of variance strongly contribute to both the LDI and clinical diagnosis. CONCLUSION This latent dementia indicator approach may serve as a model for other research consortia confronted with similar data integration challenges.
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Affiliation(s)
- Christopher R. Beam
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Susan E. Luczak
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Matthew S. Panizzon
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Chandra A. Reynolds
- Department of Psychology, University of California Riverside, Riverside, CA, USA
| | - Kaare Christensen
- The Danish Twin Registry, University of Southern Denmark, Odense, Denmark
| | - Anna K. Dahl Aslan
- School of Health Sciences, University of Skövde, Skövde, Sweden,
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Jeremy A. Elman
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Carol E. Franz
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - William S. Kremen
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Teresa Lee
- Centre for Healthy Brain Ageing (CHeBA), University of New South Wales, Sydney, Australia
| | - Marianne Nygaard
- The Danish Twin Registry, University of Southern Denmark, Odense, Denmark
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing (CHeBA), University of New South Wales, Sydney, Australia
| | - Keith E. Whitfield
- Department of Psychology, University of Nevada LasVegas, Las Vegas, Nevada
| | - Nancy L. Pedersen
- Department of Psychology, University of Southern California, Los Angeles, CA, USA,
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Margaret Gatz
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden,
Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA,Correspondence to: Margaret Gatz, Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA. Tel.: +1 213 740 2212; E-mail:
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21
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Tang R, Elman JA, Franz CE, Dale AM, Eyler LT, Fennema-Notestine C, Hagler DJ, Lyons MJ, Panizzon MS, Puckett OK, Kremen WS. Longitudinal association of executive function and structural network controllability in the aging brain. GeroScience 2022; 45:837-849. [PMID: 36269506 PMCID: PMC9886719 DOI: 10.1007/s11357-022-00676-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 10/12/2022] [Indexed: 02/03/2023] Open
Abstract
Executive function encompasses effortful cognitive processes that are particularly susceptible to aging. Functional brain networks supporting executive function-such as the frontoparietal control network and the multiple demand system-have been extensively investigated. However, it remains unclear how structural networks facilitate and constrain the dynamics of functional networks to contribute to aging-related executive function declines. We examined whether changes in structural network modal controllability-a network's ability to facilitate effortful brain state transitions that support cognitive functions-are associated with changes in executive function cross-sectionally and longitudinally. Diffusion-weighted imaging and neuropsychological testing were conducted at two time points (Time 1: ages 56 to 66, N = 172; Time 2: ages 61 to 70, N = 267) in community-dwelling men from the Vietnam Era Twin Study of Aging. An executive function factor score was computed from six neuropsychological tasks. Structural networks constructed from white matter connectivity were used to estimate modal controllability in control network and multiple demand system. We showed that higher modal controllability in control network and multiple demand system was associated with better executive function at Time 2, after controlling for age, young adult general cognitive ability, and physical health status. Moreover, changes in executive function over a period of 5 to 6 years (Time 1-Time 2, N = 105) were associated with changes in modal controllability of the multiple demand system and weakly in the control network over the same time period. These findings suggest that changes in the ability of structural brain networks in facilitating effortful brain state transitions may be a key neural mechanism underlying aging-related executive function declines and cognitive aging.
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Affiliation(s)
- Rongxiang Tang
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA. .,Center for Behavior Genetics of Aging, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA.
| | - Jeremy A. Elman
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093 USA ,Center for Behavior Genetics of Aging, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA
| | - Carol E. Franz
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093 USA ,Center for Behavior Genetics of Aging, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA
| | - Anders M. Dale
- Department of Radiology, University of California San Diego, La Jolla, CA 92093 USA ,Department of Neurosciences, University of California San Diego, La Jolla, CA 92093 USA
| | - Lisa T. Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093 USA ,Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA 92093 USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093 USA ,Department of Radiology, University of California San Diego, La Jolla, CA 92093 USA
| | - Donald J. Hagler
- Department of Radiology, University of California San Diego, La Jolla, CA 92093 USA
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02212 USA
| | - Matthew S. Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093 USA ,Center for Behavior Genetics of Aging, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA
| | - Olivia K. Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093 USA ,Center for Behavior Genetics of Aging, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA
| | - William S. Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093 USA ,Center for Behavior Genetics of Aging, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA
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22
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Ditmars HL, Logue MW, Toomey R, McKenzie RE, Franz CE, Panizzon MS, Reynolds CA, Cuthbert KN, Vandiver R, Gustavson DE, Eglit GML, Elman JA, Sanderson-Cimino M, Williams ME, Andreassen OA, Dale AM, Eyler LT, Fennema-Notestine C, Gillespie NA, Hauger RL, Jak AJ, Neale MC, Tu XM, Whitsel N, Xian H, Kremen WS, Lyons MJ. Associations Between Depression and Cardiometabolic Health: A 27-Year Longitudinal Study - Corrigendum. Psychol Med 2022; 52:3018. [PMID: 36177891 DOI: 10.1017/s0033291722003105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Affiliation(s)
- Hillary L Ditmars
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Mark W Logue
- Research Service, VA Boston Healthcare System, Boston, MA, USA
- Biomedical Genetics Program, Boston University School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Ruth E McKenzie
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
- School of Education and Social Policy, Merrimack College, North Andover, MA, USA
| | - Carol E Franz
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Matthew S Panizzon
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA, USA
| | - Kristy N Cuthbert
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Richard Vandiver
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Daniel E Gustavson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Graham M L Eglit
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
- VA San Diego Healthcare System, San Diego, CA, USA
| | - Jeremy A Elman
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Mark Sanderson-Cimino
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- San Diego State University/UC San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - McKenna E Williams
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- San Diego State University/UC San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Ole A Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital Oslo, Oslo, Norway
| | - Anders M Dale
- Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Lisa T Eyler
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Nathan A Gillespie
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Richard L Hauger
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Amy J Jak
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Michael C Neale
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Xin M Tu
- Department of Family Medicine and Public Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Nathan Whitsel
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Hong Xian
- Department of Epidemiology & Biostatistics, Saint Louis University College for Public Health & Social Justice, Saint Louis, MO, USA
| | - William S Kremen
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
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23
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Ditmars HL, Logue MW, Toomey R, McKenzie RE, Franz CE, Panizzon MS, Reynolds CA, Cuthbert KN, Vandiver R, Gustavson DE, Eglit GML, Elman JA, Sanderson-Cimino M, Williams ME, Andreassen OA, Dale AM, Eyler LT, Fennema-Notestine C, Gillespie NA, Hauger RL, Jak AJ, Neale MC, Tu XM, Whitsel N, Xian H, Kremen WS, Lyons MJ. Associations between depression and cardiometabolic health: A 27-year longitudinal study. Psychol Med 2022; 52:3007-3017. [PMID: 33431106 PMCID: PMC8547283 DOI: 10.1017/s003329172000505x] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND Clarifying the relationship between depression symptoms and cardiometabolic and related health could clarify risk factors and treatment targets. The objective of this study was to assess whether depression symptoms in midlife are associated with the subsequent onset of cardiometabolic health problems. METHODS The study sample comprised 787 male twin veterans with polygenic risk score data who participated in the Harvard Twin Study of Substance Abuse ('baseline') and the longitudinal Vietnam Era Twin Study of Aging ('follow-up'). Depression symptoms were assessed at baseline [mean age 41.42 years (s.d. = 2.34)] using the Diagnostic Interview Schedule, Version III, Revised. The onset of eight cardiometabolic conditions (atrial fibrillation, diabetes, erectile dysfunction, hypercholesterolemia, hypertension, myocardial infarction, sleep apnea, and stroke) was assessed via self-reported doctor diagnosis at follow-up [mean age 67.59 years (s.d. = 2.41)]. RESULTS Total depression symptoms were longitudinally associated with incident diabetes (OR 1.29, 95% CI 1.07-1.57), erectile dysfunction (OR 1.32, 95% CI 1.10-1.59), hypercholesterolemia (OR 1.26, 95% CI 1.04-1.53), and sleep apnea (OR 1.40, 95% CI 1.13-1.74) over 27 years after controlling for age, alcohol consumption, smoking, body mass index, C-reactive protein, and polygenic risk for specific health conditions. In sensitivity analyses that excluded somatic depression symptoms, only the association with sleep apnea remained significant (OR 1.32, 95% CI 1.09-1.60). CONCLUSIONS A history of depression symptoms by early midlife is associated with an elevated risk for subsequent development of several self-reported health conditions. When isolated, non-somatic depression symptoms are associated with incident self-reported sleep apnea. Depression symptom history may be a predictor or marker of cardiometabolic risk over decades.
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Affiliation(s)
- Hillary L. Ditmars
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - Mark W. Logue
- Research Service, VA Boston Healthcare System, Boston, MA
- Biomedical Genetics Program, Boston University School of Medicine, Boston, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - Ruth E. McKenzie
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
- School of Education and Social Policy, Merrimack College, North Andover, MA, USA
| | - Carol E. Franz
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Matthew S. Panizzon
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Chandra A. Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA
| | - Kristy N. Cuthbert
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - Richard Vandiver
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | | | - Graham M. L. Eglit
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
- VA San Diego Healthcare System, San Diego, CA
| | - Jeremy A. Elman
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Mark Sanderson-Cimino
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- San Diego State University/UC San Diego Joint Doctoral Program in Clinical Psychology
| | - McKenna E. Williams
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- San Diego State University/UC San Diego Joint Doctoral Program in Clinical Psychology
| | - Ole A. Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine University of Oslo Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital Oslo, Oslo, Norway
| | - Anders M. Dale
- Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA
- Department of Neurosciences, University of California, San Diego, La Jolla, CA
| | - Lisa T. Eyler
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
| | - Christine Fennema-Notestine
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA
| | - Nathan A. Gillespie
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA
| | - Richard L. Hauger
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA
| | - Amy J. Jak
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA
| | - Michael C. Neale
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA
- Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA
| | - Xin M. Tu
- Department of Family Medicine and Public Health, VA San Diego Healthcare System, San Diego, CA
| | - Nathan Whitsel
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
| | - Hong Xian
- Department of Epidemiology & Biostatistics, Saint Louis University College for Public Health & Social Justice
| | - William S. Kremen
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
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Elman JA, Puckett OK, Hagler DJ, Pearce RC, Fennema-Notestine C, Hatton SN, Lyons MJ, McEvoy LK, Panizzon MS, Reas ET, Dale AM, Franz CE, Kremen WS. Associations between MRI-assessed locus coeruleus integrity and cortical gray matter microstructure. Cereb Cortex 2022; 32:4191-4203. [PMID: 34969072 PMCID: PMC9528780 DOI: 10.1093/cercor/bhab475] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 11/17/2021] [Accepted: 11/22/2021] [Indexed: 01/27/2023] Open
Abstract
The locus coeruleus (LC) is one of the earliest sites of tau pathology, making it a key structure in early Alzheimer's disease (AD) progression. As the primary source of norepinephrine for the brain, reduced LC integrity may have negative consequences for brain health, yet macrostructural brain measures (e.g. cortical thickness) may not be sensitive to early stages of neurodegeneration. We therefore examined whether LC integrity was associated with differences in cortical gray matter microstructure among 435 men (mean age = 67.5; range = 62-71.7). LC structural integrity was indexed by contrast-to-noise ratio (LCCNR) from a neuromelanin-sensitive MRI scan. Restriction spectrum imaging (RSI), an advanced multi-shell diffusion technique, was used to characterize cortical microstructure, modeling total diffusion in restricted, hindered, and free water compartments. Higher LCCNR (greater integrity) was associated with higher hindered and lower free water diffusion in multiple cortical regions. In contrast, no associations between LCCNR and cortical thickness survived correction. Results suggest lower LC integrity is associated with patterns of cortical microstructure that may reflect a reduction in cytoarchitectural barriers due to broader neurodegenerative processes. These findings highlight the potential utility for LC imaging and advanced diffusion measures of cortical microstructure in assessing brain health and early identification of neurodegenerative processes.
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Affiliation(s)
- Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Rahul C Pearce
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Sean N Hatton
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA 92093, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - Emilie T Reas
- Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Center of Excellence for Stress and Mental Health, VA San Diego Health Care System, La Jolla, CA 92161, USA
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Elman JA, Vogel JW, Bocancea DI, Ossenkoppele R, van Loenhoud AC, Tu XM, Kremen WS. Issues and recommendations for the residual approach to quantifying cognitive resilience and reserve. Alzheimers Res Ther 2022; 14:102. [PMID: 35879736 PMCID: PMC9310423 DOI: 10.1186/s13195-022-01049-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 07/14/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND Cognitive reserve and resilience are terms used to explain interindividual variability in maintenance of cognitive health in response to adverse factors, such as brain pathology in the context of aging or neurodegenerative disorders. There is substantial interest in identifying tractable substrates of resilience to potentially leverage this phenomenon into intervention strategies. One way of operationalizing cognitive resilience that has gained popularity is the residual method: regressing cognition on an adverse factor and using the residual as a measure of resilience. This method is attractive because it provides a statistical approach that is an intuitive match to the reserve/resilience conceptual framework. However, due to statistical properties of the regression equation, the residual approach has qualities that complicate its interpretation as an index of resilience and make it statistically inappropriate in certain circumstances. METHODS AND RESULTS We describe statistical properties of the regression equation to illustrate why the residual is highly correlated with the cognitive score from which it was derived. Using both simulations and real data, we model common applications of the approach by creating a residual score (global cognition residualized for hippocampal volume) in individuals along the AD spectrum. We demonstrate that in most real-life scenarios, the residual measure of cognitive resilience is highly correlated with cognition, and the degree of this correlation depends on the initial relationship between the adverse factor and cognition. Subsequently, any association between this resilience metric and an external variable may actually be driven by cognition, rather than by an operationalized measure of resilience. We then assess several strategies proposed as potential solutions to this problem, such as including both the residual and original cognitive measure in a model. However, we conclude these solutions may be insufficient, and we instead recommend against "pre-regression" strategies altogether in favor of using statistical moderation (e.g., interactions) to quantify resilience. CONCLUSIONS Caution should be taken in the use and interpretation of the residual-based method of cognitive resilience. Rather than identifying resilient individuals, we encourage building more complete models of cognition to better identify the specific adverse and protective factors that influence cognitive decline.
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Affiliation(s)
- Jeremy A. Elman
- grid.266100.30000 0001 2107 4242Department of Psychiatry, University of California San Diego, 9500 Gilman Dr. (MC0738), La Jolla, CA 92093 USA ,grid.266100.30000 0001 2107 4242Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA USA
| | - Jacob W. Vogel
- grid.25879.310000 0004 1936 8972Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA USA ,grid.25879.310000 0004 1936 8972Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104 USA
| | - Diana I. Bocancea
- grid.12380.380000 0004 1754 9227Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Rik Ossenkoppele
- grid.12380.380000 0004 1754 9227Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands ,grid.16872.3a0000 0004 0435 165XVU University Medical Center, Amsterdam, the Netherlands ,grid.4514.40000 0001 0930 2361Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Anna C. van Loenhoud
- grid.12380.380000 0004 1754 9227Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands ,grid.16872.3a0000 0004 0435 165XVU University Medical Center, Amsterdam, the Netherlands
| | - Xin M. Tu
- grid.266100.30000 0001 2107 4242Family Medicine and Public Health, University of California San Diego, La Jolla, CA USA
| | - William S. Kremen
- grid.266100.30000 0001 2107 4242Department of Psychiatry, University of California San Diego, 9500 Gilman Dr. (MC0738), La Jolla, CA 92093 USA ,grid.266100.30000 0001 2107 4242Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA USA
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Kremen WS, Elman JA, Panizzon MS, Eglit GML, Sanderson-Cimino M, Williams ME, Lyons MJ, Franz CE. Cognitive Reserve and Related Constructs: A Unified Framework Across Cognitive and Brain Dimensions of Aging. Front Aging Neurosci 2022; 14:834765. [PMID: 35711905 PMCID: PMC9196190 DOI: 10.3389/fnagi.2022.834765] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 05/03/2022] [Indexed: 01/27/2023] Open
Abstract
Cognitive reserve and related constructs are valuable for aging-related research, but consistency and clarification of terms is needed as there is still no universally agreed upon nomenclature. We propose a new set of definitions for the concepts of reserve, maintenance, and resilience, and we invoke parallel concepts for each that are applicable to cognition and to brain. Our definitions of reserve and resilience correspond reasonably well to dictionary definitions of these terms. We demonstrate logical/methodological problems that arise from incongruence between commonly used conceptual and operational definitions. In our view, cognitive reserve should be defined conceptually as one's total cognitive resources at a given point in time. IQ and education are examples of common operational definitions (often referred to as proxies) of cognitive reserve. Many researchers define cognitive reserve conceptually as a property that allows for performing better than expected cognitively in the face of aging or pathology. Performing better than expected is demonstrated statistically by interactions in which the moderator is typically IQ or education. The result is an irreconcilable situation in which cognitive reserve is both the moderator and the moderation effect itself. Our proposed nomenclature resolves this logical inconsistency by defining performing better than expected as cognitive resilience. Thus, in our usage, we would test the hypothesis that high cognitive reserve confers greater cognitive resilience. Operational definitions (so-called proxies) should not conflate factors that may influence reserve-such as occupational complexity or engagement in cognitive activities-with cognitive reserve itself. Because resources may be depleted with aging or pathology, one's level of cognitive reserve may change over time and will be dependent on when assessment takes place. Therefore, in addition to cognitive reserve and cognitive resilience, we introduce maintenance of cognitive reserve as a parallel to brain maintenance. If, however, education is the measure of reserve in older adults, it precludes assessing change or maintenance of reserve. Finally, we discuss consideration of resistance as a subcategory of resilience, reverse causation, use of residual scores to assess performing better than expected given some adverse factor, and what constitutes high vs. low cognitive reserve across different studies.
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Affiliation(s)
- William S. Kremen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, United States
| | - Jeremy A. Elman
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
| | - Matthew S. Panizzon
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
| | - Graham M. L. Eglit
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
| | - Mark Sanderson-Cimino
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
- Department of Psychology, San Diego State University, San Diego, CA, United States
| | - McKenna E. Williams
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
- Department of Psychology, San Diego State University, San Diego, CA, United States
| | - Michael J. Lyons
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, United States
| | - Carol E. Franz
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
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27
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Sanderson-Cimino M, Elman JA, Tu XM, Gross AL, Panizzon MS, Gustavson DE, Bondi MW, Edmonds EC, Eppig JS, Franz CE, Jak AJ, Lyons MJ, Thomas KR, Williams ME, Kremen WS. Practice Effects in Mild Cognitive Impairment Increase Reversion Rates and Delay Detection of New Impairments. Front Aging Neurosci 2022; 14:847315. [PMID: 35547623 PMCID: PMC9083463 DOI: 10.3389/fnagi.2022.847315] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Accepted: 03/21/2022] [Indexed: 01/27/2023] Open
Abstract
Objective Cognitive practice effects (PEs) can delay detection of progression from cognitively unimpaired to mild cognitive impairment (MCI). They also reduce diagnostic accuracy as suggested by biomarker positivity data. Even among those who decline, PEs can mask steeper declines by inflating cognitive scores. Within MCI samples, PEs may increase reversion rates and thus impede detection of further impairment. Within an MCI sample at baseline, we evaluated how PEs impact prevalence, reversion rates, and dementia progression after 1 year. Methods We examined 329 baseline Alzheimer's Disease Neuroimaging Initiative MCI participants (mean age = 73.1; SD = 7.4). We identified test-naïve participants who were demographically matched to returnees at their 1-year follow-up. Since the only major difference between groups was that one completed testing once and the other twice, comparison of scores in each group yielded PEs. PEs were subtracted from each test to yield PE-adjusted scores. Biomarkers included cerebrospinal fluid phosphorylated tau and amyloid beta. Cox proportional models predicted time until first dementia diagnosis using PE-unadjusted and PE-adjusted diagnoses. Results Accounting for PEs increased MCI prevalence at follow-up by 9.2% (272 vs. 249 MCI), and reduced reversion to normal by 28.8% (57 vs. 80 reverters). PEs also increased stability of single-domain MCI by 12.0% (164 vs. 147). Compared to PE-unadjusted diagnoses, use of PE-adjusted follow-up diagnoses led to a twofold increase in hazard ratios for incident dementia. We classified individuals as false reverters if they reverted to cognitively unimpaired status based on PE-unadjusted scores, but remained classified as MCI cases after accounting for PEs. When amyloid and tau positivity were examined together, 72.2% of these false reverters were positive for at least one biomarker. Interpretation Even when PEs are small, they can meaningfully change whether some individuals with MCI retain the diagnosis at a 1-year follow-up. Accounting for PEs resulted in increased MCI prevalence and altered stability/reversion rates. This improved diagnostic accuracy also increased the dementia-predicting ability of MCI diagnoses.
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Affiliation(s)
- Mark Sanderson-Cimino
- University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego State University, San Diego, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, San Diego, CA, United States,*Correspondence: Mark Sanderson-Cimino,
| | - Jeremy A. Elman
- Center for Behavior Genetics of Aging, University of California, San Diego, San Diego, CA, United States,Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, United States
| | - Xin M. Tu
- Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, United States,Department of Family Medicine and Public Health, University of California, San Diego, San Diego, CA, United States,Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, San Diego, CA, United States
| | - Alden L. Gross
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MA, United States
| | - Matthew S. Panizzon
- Center for Behavior Genetics of Aging, University of California, San Diego, San Diego, CA, United States,Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, United States
| | - Daniel E. Gustavson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Mark W. Bondi
- Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, United States,Psychology Service, VA San Diego Healthcare System, San Diego, CA, United States
| | - Emily C. Edmonds
- Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, United States,Research Service, VA San Diego Healthcare System, San Diego, CA, United States
| | - Joel S. Eppig
- Rehabilitation Institute of Washington, Seattle, WA, United States
| | - Carol E. Franz
- Center for Behavior Genetics of Aging, University of California, San Diego, San Diego, CA, United States,Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, United States
| | - Amy J. Jak
- Center for Behavior Genetics of Aging, University of California, San Diego, San Diego, CA, United States,Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, CA, United States
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, United States
| | - Kelsey R. Thomas
- Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, United States,Research Service, VA San Diego Healthcare System, San Diego, CA, United States
| | - McKenna E. Williams
- University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego State University, San Diego, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, San Diego, CA, United States
| | - William S. Kremen
- Center for Behavior Genetics of Aging, University of California, San Diego, San Diego, CA, United States,Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, CA, United States,Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, CA, United States
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28
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Gillespie NA, Hatton SN, Hagler DJ, Dale AM, Elman JA, McEvoy LK, Eyler LT, Fennema-Notestine C, Logue MW, McKenzie RE, Puckett OK, Tu XM, Whitsel N, Xian H, Reynolds CA, Panizzon MS, Lyons MJ, Neale MC, Kremen WS, Franz C. The Impact of Genes and Environment on Brain Ageing in Males Aged 51 to 72 Years. Front Aging Neurosci 2022; 14:831002. [PMID: 35493948 PMCID: PMC9051484 DOI: 10.3389/fnagi.2022.831002] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 03/15/2022] [Indexed: 01/27/2023] Open
Abstract
Magnetic resonance imaging data are being used in statistical models to predicted brain ageing (PBA) and as biomarkers for neurodegenerative diseases such as Alzheimer's Disease. Despite their increasing application, the genetic and environmental etiology of global PBA indices is unknown. Likewise, the degree to which genetic influences in PBA are longitudinally stable and how PBA changes over time are also unknown. We analyzed data from 734 men from the Vietnam Era Twin Study of Aging with repeated MRI assessments between the ages 51-72 years. Biometrical genetic analyses "twin models" revealed significant and highly correlated estimates of additive genetic heritability ranging from 59 to 75%. Multivariate longitudinal modeling revealed that covariation between PBA at different timepoints could be explained by a single latent factor with 73% heritability. Our results suggest that genetic influences on PBA are detectable in midlife or earlier, are longitudinally very stable, and are largely explained by common genetic influences.
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Affiliation(s)
- Nathan A. Gillespie
- Virginia Institute for Psychiatric and Behaviour Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, United States,QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia,*Correspondence: Nathan A. Gillespie,
| | - Sean N. Hatton
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States,Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
| | - Donald J. Hagler
- Department of Radiology, University of California, San Diego, La Jolla, CA, United States
| | - Anders M. Dale
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States,Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, United States,Halıcıoğlu Data Science Institute, University of California, San Diego, La Jolla, CA, United States
| | - Jeremy A. Elman
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
| | - Linda K. McEvoy
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, United States
| | - Lisa T. Eyler
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, United States
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Department of Radiology, University of California, San Diego, La Jolla, CA, United States
| | - Mark W. Logue
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, United States,Department of Psychiatry and Biomedical Genetics Section, Boston University School of Medicine, Boston, MA, United States,Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Ruth E. McKenzie
- Department of Psychology, Boston University, Boston, MA, United States,School of Education and Social Policy, Merrimack College, North Andover, MA, United States
| | - Olivia K. Puckett
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
| | - Xin M. Tu
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States,Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, United States
| | - Nathan Whitsel
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
| | - Hong Xian
- Department of Epidemiology and Biostatistics, Saint. Louis University, St. Louis, MO, United States,Research Service, VA St. Louis Healthcare System, St. Louis, MO, United States
| | - Chandra A. Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA, United States
| | - Matthew S. Panizzon
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, United States
| | - Michael C. Neale
- Virginia Institute for Psychiatric and Behaviour Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, United States,Department of Biological Psychology, Free University of Amsterdam, Amsterdam, Netherlands
| | - William S. Kremen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States,Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, La Jolla, CA, United States,William S. Kremen,
| | - Carol Franz
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States,Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States,Carol Franz,
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29
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Bethlehem RAI, Seidlitz J, White SR, Vogel JW, Anderson KM, Adamson C, Adler S, Alexopoulos GS, Anagnostou E, Areces-Gonzalez A, Astle DE, Auyeung B, Ayub M, Bae J, Ball G, Baron-Cohen S, Beare R, Bedford SA, Benegal V, Beyer F, Blangero J, Blesa Cábez M, Boardman JP, Borzage M, Bosch-Bayard JF, Bourke N, Calhoun VD, Chakravarty MM, Chen C, Chertavian C, Chetelat G, Chong YS, Cole JH, Corvin A, Costantino M, Courchesne E, Crivello F, Cropley VL, Crosbie J, Crossley N, Delarue M, Delorme R, Desrivieres S, Devenyi GA, Di Biase MA, Dolan R, Donald KA, Donohoe G, Dunlop K, Edwards AD, Elison JT, Ellis CT, Elman JA, Eyler L, Fair DA, Feczko E, Fletcher PC, Fonagy P, Franz CE, Galan-Garcia L, Gholipour A, Giedd J, Gilmore JH, Glahn DC, Goodyer IM, Grant PE, Groenewold NA, Gunning FM, Gur RE, Gur RC, Hammill CF, Hansson O, Hedden T, Heinz A, Henson RN, Heuer K, Hoare J, Holla B, Holmes AJ, Holt R, Huang H, Im K, Ipser J, Jack CR, Jackowski AP, Jia T, Johnson KA, Jones PB, Jones DT, Kahn RS, Karlsson H, Karlsson L, Kawashima R, Kelley EA, Kern S, Kim KW, Kitzbichler MG, Kremen WS, Lalonde F, Landeau B, Lee S, Lerch J, Lewis JD, Li J, Liao W, Liston C, Lombardo MV, Lv J, Lynch C, Mallard TT, Marcelis M, Markello RD, Mathias SR, Mazoyer B, McGuire P, Meaney MJ, Mechelli A, Medic N, Misic B, Morgan SE, Mothersill D, Nigg J, Ong MQW, Ortinau C, Ossenkoppele R, Ouyang M, Palaniyappan L, Paly L, Pan PM, Pantelis C, Park MM, Paus T, Pausova Z, Paz-Linares D, Pichet Binette A, Pierce K, Qian X, Qiu J, Qiu A, Raznahan A, Rittman T, Rodrigue A, Rollins CK, Romero-Garcia R, Ronan L, Rosenberg MD, Rowitch DH, Salum GA, Satterthwaite TD, Schaare HL, Schachar RJ, Schultz AP, Schumann G, Schöll M, Sharp D, Shinohara RT, Skoog I, Smyser CD, Sperling RA, Stein DJ, Stolicyn A, Suckling J, Sullivan G, Taki Y, Thyreau B, Toro R, Traut N, Tsvetanov KA, Turk-Browne NB, Tuulari JJ, Tzourio C, Vachon-Presseau É, Valdes-Sosa MJ, Valdes-Sosa PA, Valk SL, van Amelsvoort T, Vandekar SN, Vasung L, Victoria LW, Villeneuve S, Villringer A, Vértes PE, Wagstyl K, Wang YS, Warfield SK, Warrier V, Westman E, Westwater ML, Whalley HC, Witte AV, Yang N, Yeo B, Yun H, Zalesky A, Zar HJ, Zettergren A, Zhou JH, Ziauddeen H, Zugman A, Zuo XN, Bullmore ET, Alexander-Bloch AF. Brain charts for the human lifespan. Nature 2022; 604:525-533. [PMID: 35388223 PMCID: PMC9021021 DOI: 10.1038/s41586-022-04554-y] [Citation(s) in RCA: 372] [Impact Index Per Article: 186.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 02/16/2022] [Indexed: 02/02/2023]
Abstract
Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.
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Affiliation(s)
- R A I Bethlehem
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.
| | - J Seidlitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA.
| | - S R White
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - J W Vogel
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Informatics & Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - K M Anderson
- Department of Psychology, Yale University, New Haven, CT, USA
| | - C Adamson
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Medicine, Monash University, Melbourne, Victoria, Australia
| | - S Adler
- UCL Great Ormond Street Institute for Child Health, London, UK
| | - G S Alexopoulos
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, USA
| | - E Anagnostou
- Department of Pediatrics University of Toronto, Toronto, Canada
- Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada
| | - A Areces-Gonzalez
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China
- University of Pinar del Río "Hermanos Saiz Montes de Oca", Pinar del Río, Cuba
| | - D E Astle
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - B Auyeung
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - M Ayub
- Queen's University, Department of Psychiatry, Centre for Neuroscience Studies, Kingston, Ontario, Canada
- University College London, Mental Health Neuroscience Research Department, Division of Psychiatry, London, UK
| | - J Bae
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea
| | - G Ball
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia
| | - S Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridge Lifetime Asperger Syndrome Service (CLASS), Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - R Beare
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Medicine, Monash University, Melbourne, Victoria, Australia
| | - S A Bedford
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - V Benegal
- Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India
| | - F Beyer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - J Blangero
- Department of Human Genetics, South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Edinburg, TX, USA
| | - M Blesa Cábez
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - J P Boardman
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - M Borzage
- Fetal and Neonatal Institute, Division of Neonatology, Children's Hospital Los Angeles, Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - J F Bosch-Bayard
- McGill Centre for Integrative Neuroscience, Ludmer Centre for Neuroinformatics and Mental Health, Montreal Neurological Institute, Montreal, Quebec, Canada
- McGill University, Montreal, Quebec, Canada
| | - N Bourke
- Department of Brain Sciences, Imperial College London, London, UK
- Care Research and Technology Centre, Dementia Research Institute, London, UK
| | - V D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - M M Chakravarty
- McGill University, Montreal, Quebec, Canada
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - C Chen
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - C Chertavian
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - G Chetelat
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Y S Chong
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - J H Cole
- Centre for Medical Image Computing (CMIC), University College London, London, UK
- Dementia Research Centre (DRC), University College London, London, UK
| | - A Corvin
- Department of Psychiatry, Trinity College, Dublin, Ireland
| | - M Costantino
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Quebec, Canada
- Undergraduate program in Neuroscience, McGill University, Montreal, Quebec, Canada
| | - E Courchesne
- Department of Neuroscience, University of California, San Diego, San Diego, CA, USA
- Autism Center of Excellence, University of California, San Diego, San Diego, CA, USA
| | - F Crivello
- Institute of Neurodegenerative Disorders, CNRS UMR5293, CEA, University of Bordeaux, Bordeaux, France
| | - V L Cropley
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
| | - J Crosbie
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - N Crossley
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Instituto Milenio Intelligent Healthcare Engineering, Santiago, Chile
| | - M Delarue
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - R Delorme
- Child and Adolescent Psychiatry Department, Robert Debré University Hospital, AP-HP, Paris, France
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
| | - S Desrivieres
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - G A Devenyi
- Cerebral Imaging Centre, McGill Department of Psychiatry, Douglas Mental Health University Institute, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - M A Di Biase
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - R Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, London, UK
| | - K A Donald
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - G Donohoe
- Center for Neuroimaging, Cognition & Genomics (NICOG), School of Psychology, National University of Ireland Galway, Galway, Ireland
| | - K Dunlop
- Weil Family Brain and Mind Research Institute, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - A D Edwards
- Centre for the Developing Brain, King's College London, London, UK
- Evelina London Children's Hospital, London, UK
- MRC Centre for Neurodevelopmental Disorders, London, UK
| | - J T Elison
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - C T Ellis
- Department of Psychology, Yale University, New Haven, CT, USA
- Haskins Laboratories, New Haven, CT, USA
| | - J A Elman
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - L Eyler
- Desert-Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, Los Angeles, CA, USA
| | - D A Fair
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - E Feczko
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - P C Fletcher
- Department of Psychiatry, University of Cambridge, and Wellcome Trust MRC Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - P Fonagy
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
- Anna Freud National Centre for Children and Families, London, UK
| | - C E Franz
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | | | - A Gholipour
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
| | - J Giedd
- Department of Child and Adolescent Psychiatry, University of California, San Diego, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - J H Gilmore
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - D C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - I M Goodyer
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - P E Grant
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - N A Groenewold
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, SA-MRC Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - F M Gunning
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - R E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - R C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - C F Hammill
- The Hospital for Sick Children, Toronto, Ontario, Canada
- Mouse Imaging Centre, Toronto, Ontario, Canada
| | - O Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - T Hedden
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - A Heinz
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Berlin, Germany
| | - R N Henson
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - K Heuer
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Université de Paris, Paris, France
| | - J Hoare
- Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - B Holla
- Department of Integrative Medicine, NIMHANS, Bengaluru, India
- Accelerator Program for Discovery in Brain disorders using Stem cells (ADBS), Department of Psychiatry, NIMHANS, Bengaluru, India
| | - A J Holmes
- Departments of Psychology and Psychiatry, Yale University, New Haven, CT, USA
| | - R Holt
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - H Huang
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- The Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - K Im
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - J Ipser
- Department of Psychiatry and Mental Health, Clinical Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - C R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - A P Jackowski
- Department of Psychiatry, Universidade Federal de São Paulo, São Paulo, Brazil
- National Institute of Developmental Psychiatry, Beijing, China
| | - T Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and BrainInspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London, UK
| | - K A Johnson
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - P B Jones
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - D T Jones
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - R S Kahn
- Department of Psychiatry, Icahn School of Medicine, Mount Sinai, NY, USA
| | - H Karlsson
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - L Karlsson
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - R Kawashima
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - E A Kelley
- Queen's University, Departments of Psychology and Psychiatry, Centre for Neuroscience Studies, Kingston, Ontario, Canada
| | - S Kern
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - K W Kim
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
- Institute of Human Behavioral Medicine, SNU-MRC, Seoul, South Korea
| | - M G Kitzbichler
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - W S Kremen
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - F Lalonde
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - B Landeau
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - S Lee
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - J Lerch
- Mouse Imaging Centre, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
| | - J D Lewis
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - J Li
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - W Liao
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - C Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - M V Lombardo
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - J Lv
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- School of Biomedical Engineering and Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - C Lynch
- Weil Family Brain and Mind Research Institute, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - T T Mallard
- Department of Psychology, University of Texas, Austin, TX, USA
| | - M Marcelis
- Department of Psychiatry and Neuropsychology, School of Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, Maastricht, The Netherlands
- Institute for Mental Health Care Eindhoven (GGzE), Eindhoven, The Netherlands
| | - R D Markello
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - S R Mathias
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - B Mazoyer
- Institute of Neurodegenerative Disorders, CNRS UMR5293, CEA, University of Bordeaux, Bordeaux, France
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - P McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - M J Meaney
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - A Mechelli
- Bordeaux University Hospital, Bordeaux, France
| | - N Medic
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - B Misic
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - S E Morgan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Computer Science and Technology, University of Cambridge, Cambridge, UK
- The Alan Turing Institute, London, UK
| | - D Mothersill
- Department of Psychology, School of Business, National College of Ireland, Dublin, Ireland
- School of Psychology and Center for Neuroimaging and Cognitive Genomics, National University of Ireland Galway, Galway, Ireland
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - J Nigg
- Department of Psychiatry, School of Medicine, Oregon Health and Science University, Portland, OR, USA
| | - M Q W Ong
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - C Ortinau
- Department of Pediatrics, Washington University in St Louis, St Louis, MO, USA
| | - R Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Lund University, Clinical Memory Research Unit, Lund, Sweden
| | - M Ouyang
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - L Palaniyappan
- Robarts Research Institute and The Brain and Mind Institute, University of Western Ontario, London, Ontario, Canada
| | - L Paly
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - P M Pan
- Department of Psychiatry, Federal University of Sao Poalo (UNIFESP), Sao Poalo, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), Sao Poalo, Brazil
| | - C Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
- Melbourne School of Engineering, The University of Melbourne, Parkville, Victoria, Australia
- Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - M M Park
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - T Paus
- Department of Psychiatry, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, Quebec, Canada
- Departments of Psychiatry and Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Z Pausova
- The Hospital for Sick Children, Toronto, Ontario, Canada
- Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
| | - D Paz-Linares
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China
- Cuban Neuroscience Center, Havana, Cuba
| | - A Pichet Binette
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - K Pierce
- Department of Neuroscience, University of California, San Diego, San Diego, CA, USA
| | - X Qian
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - J Qiu
- School of Psychology, Southwest University, Chongqing, China
| | - A Qiu
- Department of Biomedical Engineering, The N.1 Institute for Health, National University of Singapore, Singapore, Singapore
| | - A Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - T Rittman
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - A Rodrigue
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - C K Rollins
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - R Romero-Garcia
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Instituto de Biomedicina de Sevilla (IBiS) HUVR/CSIC/Universidad de Sevilla, Dpto. de Fisiología Médica y Biofísica, Seville, Spain
| | - L Ronan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - M D Rosenberg
- Department of Psychology and Neuroscience Institute, University of Chicago, Chicago, IL, USA
| | - D H Rowitch
- Department of Paediatrics and Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - G A Salum
- Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Hospital de Clinicas de Porto Alegre, Porto Alegre, Brazil
- National Institute of Developmental Psychiatry (INPD), São Paulo, Brazil
| | - T D Satterthwaite
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Informatics & Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - H L Schaare
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Juelich, Juelich, Germany
| | - R J Schachar
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - A P Schultz
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
| | - G Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Institute for Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
- PONS-Centre, Charite Mental Health, Dept of Psychiatry and Psychotherapy, Charite Campus Mitte, Berlin, Germany
| | - M Schöll
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Dementia Research Centre, Queen's Square Institute of Neurology, University College London, London, UK
| | - D Sharp
- Department of Brain Sciences, Imperial College London, London, UK
- Care Research and Technology Centre, UK Dementia Research Institute, London, UK
| | - R T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - I Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - C D Smyser
- Departments of Neurology, Pediatrics, and Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - R A Sperling
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - D J Stein
- SA MRC Unit on Risk and Resilience in Mental Disorders, Dept of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - A Stolicyn
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - J Suckling
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - G Sullivan
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - Y Taki
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - B Thyreau
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - R Toro
- Université de Paris, Paris, France
- Department of Neuroscience, Institut Pasteur, Paris, France
| | - N Traut
- Department of Neuroscience, Institut Pasteur, Paris, France
- Center for Research and Interdisciplinarity (CRI), Université Paris Descartes, Paris, France
| | - K A Tsvetanov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - N B Turk-Browne
- Department of Psychology, Yale University, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
| | - J J Tuulari
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Medicine, University of Turku, Turku, Finland
- Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
| | - C Tzourio
- Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, U1219, CHU Bordeaux, Bordeaux, France
| | - É Vachon-Presseau
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Quebec, Canada
| | | | - P A Valdes-Sosa
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
- Alan Edwards Centre for Research on Pain (AECRP), McGill University, Montreal, Quebec, Canada
| | - S L Valk
- Institute for Neuroscience and Medicine 7, Forschungszentrum Jülich, Jülich, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - T van Amelsvoort
- Department of Psychiatry and Neurosychology, Maastricht University, Maastricht, The Netherlands
| | - S N Vandekar
- Department of Biostatistics, Vanderbilt University, Nashville, TN, USA
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - L Vasung
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - L W Victoria
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - S Villeneuve
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - A Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany
| | - P E Vértes
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- The Alan Turing Institute, London, UK
| | - K Wagstyl
- Wellcome Centre for Human Neuroimaging, London, UK
| | - Y S Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - S K Warfield
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
| | - V Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - E Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - M L Westwater
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - H C Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - A V Witte
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany
- Faculty of Medicine, CRC 1052 'Obesity Mechanisms', University of Leipzig, Leipzig, Germany
| | - N Yang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - B Yeo
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Centre for Sleep and Cognition and Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- N.1 Institute for Health & Institute for Digital Medicine, National University of Singapore, Singapore, Singapore
- Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, Singapore
| | - H Yun
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - A Zalesky
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - H J Zar
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, SA-MRC Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - A Zettergren
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
| | - J H Zhou
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Center for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - H Ziauddeen
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - A Zugman
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), Sao Poalo, Brazil
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH), Bethesda, MD, USA
- Department of Psychiatry, Escola Paulista de Medicina, São Paulo, Brazil
| | - X N Zuo
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Brain and Education, School of Education Science, Nanning Normal University, Nanning, China
| | - E T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - A F Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
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Whitsel N, Reynolds CA, Buchholz EJ, Pahlen S, Pearce RC, Hatton SN, Elman JA, Gillespie NA, Gustavson DE, Puckett OK, Dale AM, Eyler LT, Fennema-Notestine C, Hagler DJ, Hauger RL, McEvoy LK, McKenzie R, Neale MC, Panizzon MS, Sanderson-Cimino M, Toomey R, Tu XM, Williams MKE, Bell T, Xian H, Lyons MJ, Kremen WS, Franz CE. Long-term associations of cigarette smoking in early mid-life with predicted brain aging from mid- to late life. Addiction 2022; 117:1049-1059. [PMID: 34605095 PMCID: PMC8904283 DOI: 10.1111/add.15710] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 09/03/2021] [Accepted: 09/15/2021] [Indexed: 11/27/2022]
Abstract
BACKGROUND AND AIMS Smoking is associated with increased risk for brain aging/atrophy and dementia. Few studies have examined early associations with brain aging. This study aimed to measure whether adult men with a history of heavier smoking in early mid-life would have older than predicted brain age 16-28 years later. DESIGN Prospective cohort observational study, utilizing smoking pack years data from average age 40 (early mid-life) predicting predicted brain age difference scores (PBAD) at average ages 56, 62 (later mid-life) and 68 years (early old age). Early mid-life alcohol use was also evaluated. SETTING Population-based United States sample. PARTICIPANTS/CASES Participants were male twins of predominantly European ancestry who served in the United States military between 1965 and 1975. Structural magnetic resonance imaging (MRI) began at average age 56. Subsequent study waves included most baseline participants; attrition replacement subjects were added at later waves. MEASUREMENTS Self-reported smoking information was used to calculate pack years smoked at ages 40, 56, 62, and 68. MRIs were processed with the Brain-Age Regression Analysis and Computation Utility software (BARACUS) program to create PBAD scores (chronological age-predicted brain age) acquired at average ages 56 (n = 493; 2002-08), 62 (n = 408; 2009-14) and 68 (n = 499; 2016-19). FINDINGS In structural equation modeling, age 40 pack years predicted more advanced age 56 PBAD [β = -0.144, P = 0.012, 95% confidence interval (CI) = -0.257, -0.032]. Age 40 pack years did not additionally predict PBAD at later ages. Age 40 alcohol consumption, but not a smoking × alcohol interaction, predicted more advanced PBAD at age 56 (β = -0.166, P = 0.001, 95% CI = -0.261, -0.070) with additional influences at age 62 (β = -0.115, P = 0.005, 95% CI = -0.195, -0.036). Age 40 alcohol did not predict age 68 PBAD. Within-twin-pair analyses suggested some genetic mechanism partially underlying effects of alcohol, but not smoking, on PBAD. CONCLUSIONS Heavier smoking and alcohol consumption by age 40 appears to predict advanced brain aging by age 56 in men.
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Affiliation(s)
- Nathan Whitsel
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA, USA
| | - Erik J Buchholz
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Shandell Pahlen
- Department of Psychology, University of California, Riverside, Riverside, CA, USA
| | - Rahul C Pearce
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Sean N Hatton
- Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Daniel E Gustavson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Anders M Dale
- Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
- Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Donald J Hagler
- Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Richard L Hauger
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Linda K McEvoy
- Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Ruth McKenzie
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Mark Sanderson-Cimino
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, La Jolla, CA, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Xin M Tu
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Mc Kenna E Williams
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, La Jolla, CA, USA
| | - Tyler Bell
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Hong Xian
- Department of Epidemiology and Biostatistics, St Louis University, St Louis, MO, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
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Sanderson‐Cimino M, Elman JA, Tu XM, Gross AL, Panizzon MS, Gustavson DE, Bondi MW, Edmonds EC, Eglit GM, Eppig JS, Franz CE, Jak AJ, Lyons MJ, Thomas KR, Williams ME, Kremen WS. Cognitive practice effects delay diagnosis of MCI: Implications for clinical trials. Alzheimers Dement (N Y) 2022; 8:e12228. [PMID: 35128027 PMCID: PMC8804942 DOI: 10.1002/trc2.12228] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 07/12/2021] [Accepted: 11/15/2021] [Indexed: 02/03/2023]
Abstract
INTRODUCTION Practice effects (PEs) on cognitive tests obscure decline, thereby delaying detection of mild cognitive impairment (MCI). Importantly, PEs may be present even when there are performance declines, if scores would have been even lower without prior test exposure. We assessed how accounting for PEs using a replacement-participants method impacts incident MCI diagnosis. METHODS Of 889 baseline cognitively normal (CN) Alzheimer's Disease Neuroimaging Initiative (ADNI) participants, 722 returned 1 year later (mean age = 74.9 ± 6.8 at baseline). The scores of test-naïve demographically matched "replacement" participants who took tests for the first time were compared to returnee scores at follow-up. PEs-calculated as the difference between returnee follow-up scores and replacement participants scores-were subtracted from follow-up scores of returnees. PE-adjusted cognitive scores were then used to determine if individuals were below the impairment threshold for MCI. Cerebrospinal fluid amyloid beta, phosphorylated tau, and total tau were used for criterion validation. In addition, based on screening and recruitment numbers from a clinical trial of amyloid-positive individuals, we estimated the effect of earlier detection of MCI by accounting for cognitive PEs on a hypothetical clinical trial in which the key outcome was progression to MCI. RESULTS In the ADNI sample, PE-adjusted scores increased MCI incidence by 19% (P < .001), increased proportion of amyloid-positive MCI cases (+12%), and reduced proportion of amyloid-positive CNs (-5%; P's < .04). Additional calculations showed that the earlier detection and increased MCI incidence would also substantially reduce necessary sample size and study duration for a clinical trial of progression to MCI. Cost savings were estimated at ≈$5.41 million. DISCUSSION Detecting MCI as early as possible is of obvious importance. Accounting for cognitive PEs with the replacement-participants method leads to earlier detection of MCI, improved diagnostic accuracy, and can lead to multi-million-dollar cost reductions for clinical trials.
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Affiliation(s)
- Mark Sanderson‐Cimino
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical PsychologySan DiegoCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
| | - Jeremy A. Elman
- Center for Behavior Genetics of AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
| | - Xin M. Tu
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Family Medicine and Public HealthUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Sam and Rose Stein Institute for Research on AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
| | - Alden L. Gross
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Matthew S. Panizzon
- Center for Behavior Genetics of AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
| | - Daniel E. Gustavson
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Mark W. Bondi
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Psychology ServiceVA San Diego Healthcare SystemSan DiegoCaliforniaUSA
| | - Emily C. Edmonds
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Research ServiceVA San Diego Healthcare SystemSan DiegoCaliforniaUSA
| | - Graham M.L. Eglit
- Center for Behavior Genetics of AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Sam and Rose Stein Institute for Research on AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
| | | | - Carol E. Franz
- Center for Behavior Genetics of AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
| | - Amy J. Jak
- Center for Behavior Genetics of AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Center of Excellence for Stress and Mental HealthVeterans Affairs San Diego Healthcare SystemSan DiegoCaliforniaUSA
| | - Michael J. Lyons
- Department of Psychological and Brain SciencesBoston UniversityBostonMassachusettsUSA
| | - Kelsey R. Thomas
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Research ServiceVA San Diego Healthcare SystemSan DiegoCaliforniaUSA
| | - McKenna E. Williams
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical PsychologySan DiegoCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
| | - William S. Kremen
- Center for Behavior Genetics of AgingUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
- Department of PsychiatrySchool of MedicineUniversity of CaliforniaSan DiegoLa JollaCaliforniaUSA
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Kremen WS, Elman JA, Panizzon MS, Eglit GML, Sanderson-Cimino M, Williams ME, Lyons MJ, Franz CE. Cognitive Reserve and Related Constructs: A Unified Framework Across Cognitive and Brain Dimensions of Aging. Front Aging Neurosci 2022. [PMID: 35711905 DOI: 10.3389/fnagi.2022.834765fda] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2023] Open
Abstract
Cognitive reserve and related constructs are valuable for aging-related research, but consistency and clarification of terms is needed as there is still no universally agreed upon nomenclature. We propose a new set of definitions for the concepts of reserve, maintenance, and resilience, and we invoke parallel concepts for each that are applicable to cognition and to brain. Our definitions of reserve and resilience correspond reasonably well to dictionary definitions of these terms. We demonstrate logical/methodological problems that arise from incongruence between commonly used conceptual and operational definitions. In our view, cognitive reserve should be defined conceptually as one's total cognitive resources at a given point in time. IQ and education are examples of common operational definitions (often referred to as proxies) of cognitive reserve. Many researchers define cognitive reserve conceptually as a property that allows for performing better than expected cognitively in the face of aging or pathology. Performing better than expected is demonstrated statistically by interactions in which the moderator is typically IQ or education. The result is an irreconcilable situation in which cognitive reserve is both the moderator and the moderation effect itself. Our proposed nomenclature resolves this logical inconsistency by defining performing better than expected as cognitive resilience. Thus, in our usage, we would test the hypothesis that high cognitive reserve confers greater cognitive resilience. Operational definitions (so-called proxies) should not conflate factors that may influence reserve-such as occupational complexity or engagement in cognitive activities-with cognitive reserve itself. Because resources may be depleted with aging or pathology, one's level of cognitive reserve may change over time and will be dependent on when assessment takes place. Therefore, in addition to cognitive reserve and cognitive resilience, we introduce maintenance of cognitive reserve as a parallel to brain maintenance. If, however, education is the measure of reserve in older adults, it precludes assessing change or maintenance of reserve. Finally, we discuss consideration of resistance as a subcategory of resilience, reverse causation, use of residual scores to assess performing better than expected given some adverse factor, and what constitutes high vs. low cognitive reserve across different studies.
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Affiliation(s)
- William S Kremen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, United States
| | - Jeremy A Elman
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
| | - Matthew S Panizzon
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
| | - Graham M L Eglit
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
| | - Mark Sanderson-Cimino
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
- Department of Psychology, San Diego State University, San Diego, CA, United States
| | - McKenna E Williams
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
- Department of Psychology, San Diego State University, San Diego, CA, United States
| | - Michael J Lyons
- Department of Psychological & Brain Sciences, Boston University, Boston, MA, United States
| | - Carol E Franz
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, United States
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33
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Eglit GML, Elman JA, Panizzon MS, Sanderson-Cimino M, Williams ME, Dale AM, Eyler LT, Fennema-Notestine C, Gillespie NA, Gustavson DE, Hatton SN, Hagler DJ, Hauger RL, Jak AJ, Logue MW, McEvoy LK, McKenzie RE, Neale MC, Puckett O, Reynolds CA, Toomey R, Tu XM, Whitsel N, Xian H, Lyons MJ, Franz CE, Kremen WS. Paradoxical cognitive trajectories in men from earlier to later adulthood. Neurobiol Aging 2022; 109:229-238. [PMID: 34785406 PMCID: PMC8715388 DOI: 10.1016/j.neurobiolaging.2021.10.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 10/07/2021] [Accepted: 10/07/2021] [Indexed: 01/03/2023]
Abstract
Because longitudinal studies of aging typically lack cognitive data from earlier ages, it is unclear how general cognitive ability (GCA) changes throughout the life course. In 1173 Vietnam Era Twin Study of Aging (VETSA) participants, we assessed young adult GCA at average age 20 and current GCA at 3 VETSA assessments beginning at average age 56. The same GCA index was used throughout. Higher young adult GCA and better GCA maintenance were associated with stronger specific cognitive abilities from age 51 to 73. Given equivalent GCA at age 56, individuals who had higher age 20 GCA outperformed those whose GCA remained stable in terms of memory, executive function, and working memory abilities from age 51 to 73. Thus, paradoxically, despite poorer maintenance of GCA, high young adult GCA still conferred benefits. Advanced predicted brain age and the combination of elevated vascular burden and APOE-ε4 status were associated with poorer maintenance of GCA. These findings highlight the importance of distinguishing between peak and current GCA for greater understanding of cognitive aging.
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Affiliation(s)
- Graham M L Eglit
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA.
| | - Jeremy A Elman
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Mathew S Panizzon
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Mark Sanderson-Cimino
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA; San Diego State University/University of California, San Diego Joint Doctoral Program, San Diego, CA, USA
| | - McKenna E Williams
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA; San Diego State University/University of California, San Diego Joint Doctoral Program, San Diego, CA, USA
| | - Anders M Dale
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Department of Radiology, University of California, San Diego, La Jolla, CA, USA; Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA; Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Daniel E Gustavson
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Sean N Hatton
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Donald J Hagler
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Richard L Hauger
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Amy J Jak
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Mark W Logue
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA, USA; Psychiatry and Biomedical Genetics, Boston University School of Medicine, Boston, MA, USA; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Linda K McEvoy
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Ruth E McKenzie
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA; School of Education and Social Policy, Merrimack College, North Andover, MA, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Olivia Puckett
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, CA, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Xin M Tu
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Nathan Whitsel
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Hong Xian
- Department of Epidemiology and Biostatistics, St. Louis University, St. Louis, MO, USA
| | - Michael J Lyons
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Carol E Franz
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - William S Kremen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
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Zheng Y, Garrett ME, Sun D, Clarke-Rubright EK, Haswell CC, Maihofer AX, Elman JA, Franz CE, Lyons MJ, Kremen WS, Peverill M, Sambrook K, McLaughlin KA, Davenport ND, Disner S, Sponheim SR, Andrew E, Korgaonkar M, Bryant R, Varkevisser T, Geuze E, Coleman J, Beckham JC, Kimbrel NA, Sullivan D, Miller M, Hayes J, Verfaellie M, Wolf E, Salat D, Spielberg JM, Milberg W, McGlinchey R, Dennis EL, Thompson PM, Medland S, Jahanshad N, Nievergelt CM, Ashley-Koch AE, Logue MW, Morey RA. Trauma and posttraumatic stress disorder modulate polygenic predictors of hippocampal and amygdala volume. Transl Psychiatry 2021; 11:637. [PMID: 34916497 PMCID: PMC8677780 DOI: 10.1038/s41398-021-01707-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 10/05/2021] [Accepted: 10/20/2021] [Indexed: 11/08/2022] Open
Abstract
The volume of subcortical structures represents a reliable, quantitative, and objective phenotype that captures genetic effects, environmental effects such as trauma, and disease effects such as posttraumatic stress disorder (PTSD). Trauma and PTSD represent potent exposures that may interact with genetic markers to influence brain structure and function. Genetic variants, associated with subcortical volumes in two large normative discovery samples, were used to compute polygenic scores (PGS) for the volume of seven subcortical structures. These were applied to a target sample enriched for childhood trauma and PTSD. Subcortical volume PGS from the discovery sample were strongly associated in our trauma/PTSD enriched sample (n = 7580) with respective subcortical volumes of the hippocampus (p = 1.10 × 10-20), thalamus (p = 7.46 × 10-10), caudate (p = 1.97 × 10-18), putamen (p = 1.7 × 10-12), and nucleus accumbens (p = 1.99 × 10-7). We found a significant association between the hippocampal volume PGS and hippocampal volume in control subjects from our sample, but was absent in individuals with PTSD (GxE; (beta = -0.10, p = 0.027)). This significant GxE (PGS × PTSD) relationship persisted (p < 1 × 10-19) in four out of five threshold peaks (0.024, 0.133, 0.487, 0.730, and 0.889) used to calculate hippocampal volume PGSs. We detected similar GxE (G × ChildTrauma) relationships in the amygdala for exposure to childhood trauma (rs4702973; p = 2.16 × 10-7) or PTSD (rs10861272; p = 1.78 × 10-6) in the CHST11 gene. The hippocampus and amygdala are pivotal brain structures in mediating PTSD symptomatology. Trauma exposure and PTSD modulate the effect of polygenic markers on hippocampal volume (GxE) and the amygdala volume PGS is associated with PTSD risk, which supports the role of amygdala volume as a risk factor for PTSD.
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Affiliation(s)
- Yuanchao Zheng
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Melanie E Garrett
- Department of Medicine, Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA
- VISN 6 MIRECC, Durham VA Health Care System, Durham, NC, USA
| | - Delin Sun
- VISN 6 MIRECC, Durham VA Health Care System, Durham, NC, USA
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA
| | - Emily K Clarke-Rubright
- VISN 6 MIRECC, Durham VA Health Care System, Durham, NC, USA
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA
| | - Courtney C Haswell
- VISN 6 MIRECC, Durham VA Health Care System, Durham, NC, USA
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA
| | - Adam X Maihofer
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Jeremy A Elman
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Carol E Franz
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - William S Kremen
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
- Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, La Jolla, CA, USA
| | - Matthew Peverill
- Department of Psychology, University of Washington, Seattle, WA, USA
| | - Kelly Sambrook
- Department of Psychology, Harvard University, Boston, MA, USA
| | | | - Nicholas D Davenport
- Minneapolis VA Health Care System, Minneapolis, MN, USA
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Seth Disner
- Minneapolis VA Health Care System, Minneapolis, MN, USA
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Scott R Sponheim
- Minneapolis VA Health Care System, Minneapolis, MN, USA
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | | | - Mayuresh Korgaonkar
- Brain Dynamics Centre, Westmead Institute of Medical Research, University of Sydney, Westmead, NSW, Australia
| | - Richard Bryant
- School of Psychology, University of New South Wales, Sydney, NSW, Australia
| | - Tim Varkevisser
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
- Brain Research and Innovation Centre, Ministry of Defence, Utrecht, The Netherlands
| | - Elbert Geuze
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
- Brain Research and Innovation Centre, Ministry of Defence, Utrecht, The Netherlands
| | - Jonathan Coleman
- King's College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, London, UK
- King's College London, NIHR Maudsley BRC, London, UK
| | - Jean C Beckham
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Nathan A Kimbrel
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Danielle Sullivan
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Mark Miller
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- VA Boston Healthcare System, Jamaica Plain, MA, USA
| | - Jasmeet Hayes
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Mieke Verfaellie
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Erika Wolf
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - David Salat
- VA Boston Healthcare System, Jamaica Plain, MA, USA
- Department of Radiology, Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Jeffrey M Spielberg
- VA Boston Healthcare System, Jamaica Plain, MA, USA
- Department of Psychological and Brain Sciences, University of Delaware, Newark, DE, USA
| | - William Milberg
- Translational Research Center for TBI and Stress Disorders, VA Boston Healthcare System, Boston, MA, USA
- Geriatric Research, Educational and Clinical Center, VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Regina McGlinchey
- Translational Research Center for TBI and Stress Disorders, VA Boston Healthcare System, Boston, MA, USA
- Geriatric Research, Educational and Clinical Center, VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Emily L Dennis
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Sarah Medland
- Queensland Institute for Medical Research, Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Caroline M Nievergelt
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, La Jolla, CA, USA
| | - Allison E Ashley-Koch
- Department of Medicine, Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA
- VISN 6 MIRECC, Durham VA Health Care System, Durham, NC, USA
| | - Mark W Logue
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Departments of Psychiatry and Biomedical Genetics, Boston University School of Medicine, Boston, MA, USA
| | - Rajendra A Morey
- VISN 6 MIRECC, Durham VA Health Care System, Durham, NC, USA.
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA.
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA.
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Williams ME, Gillespie NA, Dale AM, Elman JA, Eyler LT, Fennema‐Notestine C, Hagler DJ, McEvoy LK, Neale MC, Panizzon MS, Sanderson‐Cimino ME, Franz CE, Kremen WS. Genetic and environmental influences on Alzheimer’s disease neuroimaging signatures. Alzheimers Dement 2021. [DOI: 10.1002/alz.054708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Gustavson DE, Reynolds CA, Hohman TJ, Jefferson AL, Elman JA, Panizzon MS, Lyons MJ, Franz CE, Kremen WS. Alzheimer’s disease polygenic scores predict changes in executive function across 12 years in late middle age. Alzheimers Dement 2021. [DOI: 10.1002/alz.056045] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Daniel E. Gustavson
- Vanderbilt Memory & Alzheimer's Center Vanderbilt University Medical Center Nashville TN USA
| | | | - Timothy J. Hohman
- Vanderbilt Genetics Institute Vanderbilt University Medical Center Nashville TN USA
| | - Angela L. Jefferson
- Vanderbilt Genetics Institute Vanderbilt University Medical Center Nashville TN USA
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Granholm EL, Elman JA, Galasko DR, Kremen WS, Salmon DP, Holden J, Delay C, Macomber A, Link P, Bondi MW. Pupillary responses as a biomarker of early risk for Alzheimer’s disease: Association with tau not beta‐amyloid. Alzheimers Dement 2021. [DOI: 10.1002/alz.056511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Eric L. Granholm
- VA San Diego Healthcare System San Diego CA USA
- University of California San Diego San Diego CA USA
| | | | - Doug R. Galasko
- VA San Diego Healthcare System San Diego CA USA
- University of California San Diego La Jolla CA USA
- Shiley‐Marcos Alzheimer's Disease Research Center La Jolla CA USA
| | - William S. Kremen
- VA San Diego Healthcare System San Diego CA USA
- University of California San Diego La Jolla CA USA
| | - David P. Salmon
- University of California San Diego La Jolla CA USA
- Shiley‐Marcos Alzheimer's Disease Research Center La Jolla CA USA
| | - Jason Holden
- University of California San Diego La Jolla CA USA
| | | | | | | | - Mark W. Bondi
- VA San Diego Healthcare System San Diego CA USA
- University of California San Diego La Jolla CA USA
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Sanderson‐Cimino ME, Elman JA, Tu XM, Panizzon MS, Jak AJ, Franz CE, Kremen WS. Accounting for practice effects improves stability of MCI diagnosis and uncovers new impairments. Alzheimers Dement 2021. [DOI: 10.1002/alz.056630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
| | | | - Xin M Tu
- University of California, San Diego La Jolla CA USA
| | | | - Amy J. Jak
- University of California San Diego La Jolla CA USA
- VA San Diego Healthcare System San Diego CA USA
| | - Carol E. Franz
- University of California, San Diego La Jolla CA USA
- Vietnam Era Twin Study of Aging La Jolla CA USA
| | - William S. Kremen
- University of California, San Diego La Jolla CA USA
- VA San Diego Healthcare System San Diego CA USA
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Elman JA, Puckett OK, Hagler DJ, Pearce RC, Fennema‐Notestine C, Hatton SN, Dale AM, Panizzon MS, Lyons MJ, Franz CE, Kremen WS. Associations between MRI‐assessed locus coeruleus integrity and restriction spectrum imaging of cortical gray matter microstructure. Alzheimers Dement 2021. [DOI: 10.1002/alz.056266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - William S. Kremen
- University of California San Diego La Jolla CA USA
- VA San Diego Healthcare System San Diego CA USA
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Bell TR, Elman JA, Puckett OK, Franz CE, Kremen WS. Persistent pain is associated with lower locus coeruleus integrity in older adults. Alzheimers Dement 2021. [DOI: 10.1002/alz.054438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Franz CE, Hatton SN, Elman JA, Warren T, Gillespie NA, Whitsel NA, Puckett OK, Dale AM, Eyler LT, Fennema-Notestine C, Hagler DJ, Hauger RL, McKenzie R, Neale MC, Panizzon MS, Pearce RC, Reynolds CA, Sanderson-Cimino M, Toomey R, Tu XM, Williams M, Xian H, Lyons MJ, Kremen WS. Lifestyle and the aging brain: interactive effects of modifiable lifestyle behaviors and cognitive ability in men from midlife to old age. Neurobiol Aging 2021; 108:80-89. [PMID: 34547718 PMCID: PMC8862767 DOI: 10.1016/j.neurobiolaging.2021.08.007] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Revised: 07/23/2021] [Accepted: 08/12/2021] [Indexed: 01/18/2023]
Abstract
We examined the influence of lifestyle on brain aging after nearly 30 years, and tested the hypothesis that young adult general cognitive ability (GCA) would moderate these effects. In the community-dwelling Vietnam Era Twin Study of Aging (VETSA), 431 largely non-Hispanic white men completed a test of GCA at mean age 20. We created a modifiable lifestyle behavior composite from data collected at mean age 40. During VETSA, MRI-based measures at mean age 68 included predicted brain age difference (PBAD), Alzheimer's disease (AD) brain signature, and abnormal white matter scores. There were significant main effects of young adult GCA and lifestyle on PBAD and the AD signature (ps ≤ 0.012), and a GCA-by-lifestyle interaction on both (ps ≤ 0.006). Regardless of GCA level, having more favorable lifestyle behaviors predicted less advanced brain age and less AD-like brain aging. Unfavorable lifestyles predicted advanced brain aging in those with lower age 20 GCA, but did not affect brain aging in those with higher age 20 GCA. Targeting early lifestyle modification may promote dementia risk reduction, especially among lower reserve individuals.
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Affiliation(s)
- Carol E Franz
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA.
| | - Sean N Hatton
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Teresa Warren
- Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA; QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Nathan A Whitsel
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA; Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Richard L Hauger
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Ruth McKenzie
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Rahul C Pearce
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, CA, USA
| | - Mark Sanderson-Cimino
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Xin M Tu
- Department of Family Medicine, University of California San Diego, San Diego, CA, USA
| | - McKenna Williams
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA; San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Hong Xian
- Department of Epidemiology & Biostatistics, St. Louis University, St. Louis, MO, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
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Williams ME, Elman JA, McEvoy LK, Andreassen OA, Dale AM, Eglit GML, Eyler LT, Fennema-Notestine C, Franz CE, Gillespie NA, Hagler DJ, Hatton SN, Hauger RL, Jak AJ, Logue MW, Lyons MJ, McKenzie RE, Neale MC, Panizzon MS, Puckett OK, Reynolds CA, Sanderson-Cimino M, Toomey R, Tu XM, Whitsel N, Xian H, Kremen WS. 12-year prediction of mild cognitive impairment aided by Alzheimer's brain signatures at mean age 56. Brain Commun 2021; 3:fcab167. [PMID: 34396116 PMCID: PMC8361427 DOI: 10.1093/braincomms/fcab167] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 04/26/2021] [Accepted: 05/10/2021] [Indexed: 01/22/2023] Open
Abstract
Neuroimaging signatures based on composite scores of cortical thickness and hippocampal volume predict progression from mild cognitive impairment to Alzheimer's disease. However, little is known about the ability of these signatures among cognitively normal adults to predict progression to mild cognitive impairment. Towards that end, a signature sensitive to microstructural changes that may predate macrostructural atrophy should be useful. We hypothesized that: (i) a validated MRI-derived Alzheimer's disease signature based on cortical thickness and hippocampal volume in cognitively normal middle-aged adults would predict progression to mild cognitive impairment; and (ii) a novel grey matter mean diffusivity signature would be a better predictor than the thickness/volume signature. This cohort study was part of the Vietnam Era Twin Study of Aging. Concurrent analyses compared cognitively normal and mild cognitive impairment groups at each of three study waves (ns = 246-367). Predictive analyses included 169 cognitively normal men at baseline (age = 56.1, range = 51-60). Our previously published thickness/volume signature derived from independent data, a novel mean diffusivity signature using the same regions and weights as the thickness/volume signature, age, and an Alzheimer's disease polygenic risk score were used to predict incident mild cognitive impairment an average of 12 years after baseline (follow-up age = 67.2, range = 61-71). Additional analyses adjusted for predicted brain age difference scores (chronological age minus predicted brain age) to determine if signatures were Alzheimer-related and not simply ageing-related. In concurrent analyses, individuals with mild cognitive impairment had higher (worse) mean diffusivity signature scores than cognitively normal participants, but thickness/volume signature scores did not differ between groups. In predictive analyses, age and polygenic risk score yielded an area under the curve of 0.74 (sensitivity = 80.00%; specificity = 65.10%). Prediction was significantly improved with addition of the mean diffusivity signature (area under the curve = 0.83; sensitivity = 85.00%; specificity = 77.85%; P = 0.007), but not with addition of the thickness/volume signature. A model including both signatures did not improve prediction over a model with only the mean diffusivity signature. Results held up after adjusting for predicted brain age difference scores. The novel mean diffusivity signature was limited by being yoked to the thickness/volume signature weightings. An independently derived mean diffusivity signature may thus provide even stronger prediction. The young age of the sample at baseline is particularly notable. Given that the brain signatures were examined when participants were only in their 50 s, our results suggest a promising step towards improving very early identification of Alzheimer's disease risk and the potential value of mean diffusivity and/or multimodal brain signatures.
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Affiliation(s)
- McKenna E Williams
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Jeremy A Elman
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Ole A Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo 0316, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo 0372, Norway
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
- Department of Neuroscience, University of California San Diego, La Jolla, CA 92093, USA
| | - Graham M L Eglit
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, CA 92093, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Carol E Franz
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA 23284, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Sean N Hatton
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Neuroscience, University of California San Diego, La Jolla, CA 92093, USA
| | - Richard L Hauger
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center of Excellence for Stress and Mental Health (CESAMH), VA San Diego Healthcare System, San Diego, CA 92093, USA
| | - Amy J Jak
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- VA San Diego Healthcare System, San Diego, CA 92093, USA
| | - Mark W Logue
- National Center for PTSD: Behavioral Science Division, VA Boston Healthcare System, Boston, MA 02130, USA
- Department of Psychiatry and the Biomedical Genetics Section, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02212, USA
| | - Ruth E McKenzie
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- School of Education and Social Policy, Merrimack College, North Andover, MA 01845, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA 23284, USA
| | - Matthew S Panizzon
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Olivia K Puckett
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, CA 92521, USA
| | - Mark Sanderson-Cimino
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02212, USA
| | - Xin M Tu
- Family Medicine and Public Health, University of California San Diego, La Jolla, CA 92093, USA
| | - Nathan Whitsel
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
| | - Hong Xian
- Department of Biostatistics, St. Louis University, St. Louis, MO 63103, USA
| | - William S Kremen
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center of Excellence for Stress and Mental Health (CESAMH), VA San Diego Healthcare System, San Diego, CA 92093, USA
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Sanderson-Cimino M, Panizzon MS, Elman JA, Tu X, Gustavson DE, Puckett O, Cross K, Notestine R, Hatton SN, Eyler LT, McEvoy LK, Hagler DJ, Neale MC, Gillespie NA, Lyons MJ, Franz CE, Fennema-Notestine C, Kremen WS. Periventricular and deep abnormal white matter differ in associations with cognitive performance at midlife. Neuropsychology 2021; 35:252-264. [PMID: 33970659 PMCID: PMC8500190 DOI: 10.1037/neu0000718] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Objective: Abnormal white matter (AWM) on magnetic resonance imaging is associated with cognitive performance in older adults. We explored cognitive associations with AWM during late-midlife. Method: Participants were community-dwelling men (n = 242; M = 61.90 years; range = 56-66). Linear-mixed effects regression models examined associations of total, periventricular, and deep AWM with cognitive performance, controlling for multiple comparisons. Models considering specific cognitive domains controlled for current general cognitive ability (GCA). We hypothesized that total AWM would be associated with worse processing speed, executive function, and current GCA; deep AWM would correlate with GCA and periventricular AWM would relate to specific cognitive abilities. We also assessed the potential influence of cognitive reserve by examining a moderation effect of early life (mean age of 20) cognition. Results: Greater total and deep AWM were associated with poorer current GCA. Periventricular AWM was associated with worse executive function, working memory, and episodic memory. When periventricular and deep AWM were modeled simultaneously, both retained their respective significant associations with cognitive performance. Cognitive reserve did not moderate associations. Conclusions: Our findings suggest that AWM contributes to poorer cognitive function in late-midlife. Examining only total AWM may obscure the potential differential impact of regional AWM. Separating total AWM into subtypes while controlling for current GCA revealed a dissociation in relationships with cognitive performance; deep AWM was associated with nonspecific cognitive ability whereas periventricular AWM was associated with specific frontal-related abilities and memory. Management of vascular or other risk factors that may increase the risk of AWM should begin during or before early late-midlife. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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Affiliation(s)
- Mark Sanderson-Cimino
- Joint Doctoral Program in Clinical Psychology, San Diego State/University of California
- Center for Behavior Genetics of Aging, University of California
| | - Matthew S. Panizzon
- Center for Behavior Genetics of Aging, University of California
- Department of Psychiatry University of California
| | - Jeremy A. Elman
- Center for Behavior Genetics of Aging, University of California
- Department of Psychiatry University of California
| | - Xin Tu
- Family Medicine and Public Health, University of California
| | - Daniel E. Gustavson
- Center for Behavior Genetics of Aging, University of California
- Department of Psychiatry University of California
- Department of Medicine, Vanderbilt University Medical Center
| | - Olivia Puckett
- Center for Behavior Genetics of Aging, University of California
- Department of Psychiatry University of California
| | | | - Randy Notestine
- Department of Psychiatry University of California
- Computational and Applied Statistics Laboratory (CASL) at the San Diego Supercomputer Center
| | - Sean N Hatton
- Center for Behavior Genetics of Aging, University of California
- Department of Psychiatry University of California
- Department of Neurosciences, University of California
| | - Lisa T. Eyler
- Department of Psychiatry University of California
- Mental Illness Research, Education, And Clinical Center, Veterans Affairs San Diego Healthcare System
| | - Linda K. McEvoy
- Department of Radiology, University of California, San Diego
| | | | - Michael C. Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University
| | - Nathan A. Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University
| | - Carol E. Franz
- Center for Behavior Genetics of Aging, University of California
- Department of Psychiatry University of California
| | - Christine Fennema-Notestine
- Center for Behavior Genetics of Aging, University of California
- Department of Psychiatry University of California
- Department of Radiology, University of California, San Diego
| | - William S. Kremen
- Center for Behavior Genetics of Aging, University of California
- Department of Psychiatry University of California
- Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System
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Elman JA, Puckett OK, Beck A, Fennema-Notestine C, Cross LK, Dale AM, Eglit GML, Eyler LT, Gillespie NA, Granholm EL, Gustavson DE, Hagler DJ, Hatton SN, Hauger R, Jak AJ, Logue MW, McEvoy LK, McKenzie RE, Neale MC, Panizzon MS, Reynolds CA, Sanderson-Cimino M, Toomey R, Tu XM, Whitsel N, Williams ME, Xian H, Lyons MJ, Franz CE, Kremen WS. MRI-assessed locus coeruleus integrity is heritable and associated with multiple cognitive domains, mild cognitive impairment, and daytime dysfunction. Alzheimers Dement 2021; 17:1017-1025. [PMID: 33580733 PMCID: PMC8248066 DOI: 10.1002/alz.12261] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 10/12/2020] [Accepted: 11/10/2020] [Indexed: 12/22/2022]
Abstract
Introduction The locus coeruleus (LC) undergoes extensive neurodegeneration in early Alzheimer's disease (AD). The LC is implicated in regulating the sleep–wake cycle, modulating cognitive function, and AD progression. Methods Participants were 481 men (ages 62 to 71.7) from the Vietnam Era Twin Study of Aging. LC structural integrity was indexed by neuromelanin‐sensitive magnetic resonance imaging (MRI) contrast‐to‐noise ratio (LCCNR). We examined LCCNR, cognition, amnestic mild cognitive impairment (aMCI), and daytime dysfunction. Results Heritability of LCCNR was .48. Participants with aMCI showed greater daytime dysfunction. Lower LCCNR was associated with poorer episodic memory, general verbal fluency, semantic fluency, and processing speed, as well as increased odds of aMCI and greater daytime dysfunction. Discussion Reduced LC integrity is associated with widespread differences across cognitive domains, daytime sleep‐related dysfunction, and risk for aMCI. These findings in late‐middle‐aged adults highlight the potential of MRI‐based measures of LC integrity in early identification of AD risk.
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Affiliation(s)
- Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Asad Beck
- Graduate Program in Neuroscience, University of Washington, Seattle, Washington, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Latonya K Cross
- Department of Psychology, University of Hawaii Hilo, Hilo, Hawaii, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, California, USA.,Department of Neuroscience, University of California San Diego, La Jolla, California, USA
| | - Graham M L Eglit
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, California, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Eric L Granholm
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,VA San Diego Healthcare System, San Diego, California, USA
| | - Daniel E Gustavson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Sean N Hatton
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA.,Department of Neuroscience, University of California San Diego, La Jolla, California, USA
| | - Richard Hauger
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,VA San Diego Healthcare System, San Diego, California, USA
| | - Amy J Jak
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,VA San Diego Healthcare System, San Diego, California, USA
| | - Mark W Logue
- National Center for PTSD: Behavioral Science Division, VA Boston Healthcare System, Boston, Massachusetts, USA.,Department of Psychiatry and the Biomedical Genetics Section, Boston University School of Medicine, Boston, Massachusetts, USA.,Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Ruth E McKenzie
- School of Education and Public Policy, Merrimack College, Andover, Massachusetts, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, California, USA
| | - Mark Sanderson-Cimino
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA.,Joint Doctoral Program in Clinical Psychology, San Diego State/University of California, San Diego, California, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, USA
| | - Xin M Tu
- Family Medicine and Public Health, University of California San Diego, La Jolla, California, USA
| | - Nathan Whitsel
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - McKenna E Williams
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA.,Joint Doctoral Program in Clinical Psychology, San Diego State/University of California, San Diego, California, USA
| | - Hong Xian
- Department of Epidemiology & Biostatistics, St. Louis University, St. Louis, Missouri, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA.,VA San Diego Healthcare System, San Diego, California, USA
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Gustavson DE, Jak AJ, Elman JA, Panizzon MS, Franz CE, Gifford KA, Reynolds CA, Toomey R, Lyons MJ, Kremen WS. How Well Does Subjective Cognitive Decline Correspond to Objectively Measured Cognitive Decline? Assessment of 10-12 Year Change. J Alzheimers Dis 2021; 83:291-304. [PMID: 34308902 PMCID: PMC8482061 DOI: 10.3233/jad-210123] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Although not strongly correlated with current objective cognitive ability, subjective cognitive decline (SCD) is a risk factor for Alzheimer's disease. Most studies focus on SCD in relation to future decline rather than objective prior decline that it purportedly measures. OBJECTIVE We evaluated whether self-report of cognitive decline-as a continuous measure-corresponds to objectively-assessed episodic memory and executive function decline across the same period. METHODS 1,170 men completed the Everyday Cognition Questionnaire (ECog) at mean age 68 assessing subjective changes in cognitive ability relative to 10 years prior. A subset had mild cognitive impairment (MCI), but MCI was diagnosed without regard to subjective decline. Participants completed up to 3 objective assessments of memory and executive function (M = 56, 62, and 68 years). Informant-reported ECogs were completed for 1,045 individuals. Analyses controlled for depression and anxiety symptoms assessed at mean age 68. RESULTS Participant-reported ECog scores were modestly associated with objective decline for memory (β= -0.23, 95%CI [-0.37, -0.10]) and executive function (β= -0.19, 95%CI [-0.33, -0.05]) over the same time period. However, these associations were nonsignificant after excluding MCI cases. Results were similar for informant ratings. Participant-rated ECog scores were more strongly associated with concurrent depression and anxiety symptoms, (β= 0.44, 95%CI [0.36, 0.53]). CONCLUSION Continuous SCD scores are correlated with prior objective cognitive changes in non-demented individuals, though this association appears driven by individuals with current MCI. However, participants' current depression and anxiety ratings tend to be strongly associated with their SCD ratings. Thus, what primarily drives SCD ratings remains unclear.
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Affiliation(s)
- Daniel E. Gustavson
- Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN
| | - Amy J. Jak
- Department of Psychiatry, University of California, San Diego, La Jolla, CA
- Psychology Service, Veterans Affairs San Diego Healthcare system, La Jolla, CA
| | - Jeremy A. Elman
- Department of Psychiatry, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Matthew S. Panizzon
- Department of Psychiatry, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Carol E. Franz
- Department of Psychiatry, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Katherine A. Gifford
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN
| | - Chandra A. Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - William S. Kremen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
- Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, La Jolla, CA
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Slayday RE, Gustavson DE, Elman JA, Beck A, McEvoy LK, Tu XM, Fang B, Hauger RL, Lyons MJ, McKenzie RE, Sanderson-Cimino ME, Xian H, Kremen WS, Franz CE. Interaction between Alcohol Consumption and Apolipoprotein E (ApoE) Genotype with Cognition in Middle-Aged Men. J Int Neuropsychol Soc 2021; 27:56-68. [PMID: 32662384 PMCID: PMC7856052 DOI: 10.1017/s1355617720000570] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Heavy alcohol consumption is associated with poorer cognitive function in older adults. Although understudied in middle-aged adults, the relationship between alcohol and cognition may also be influenced by genetics such as the apolipoprotein (ApoE) ε4 allele, a risk factor for Alzheimer's disease. We examined the relationship between alcohol consumption, ApoE genotype, and cognition in middle-aged adults and hypothesized that light and/or moderate drinkers (≤2 drinks per day) would show better cognitive performance than heavy drinkers or non-drinkers. Additionally, we hypothesized that the association between alcohol use and cognitive function would differ by ApoE genotype (ε4+ vs. ε4-). METHOD Participants were 1266 men from the Vietnam Era Twin Study of Aging (VETSA; M age = 56; range 51-60) who completed a neuropsychological battery assessing seven cognitive abilities: general cognitive ability (GCA), episodic memory, processing speed, executive function, abstract reasoning, verbal fluency, and visuospatial ability. Alcohol consumption was categorized into five groups: never, former, light, moderate, and heavy. RESULTS In fully adjusted models, there was no significant main effect of alcohol consumption on cognitive functions. However, there was a significant interaction between alcohol consumption and ApoE ε4 status for GCA and episodic memory, such that the relationship of alcohol consumption and cognition was stronger in ε4 carriers. The ε4+ heavy drinking subgroup had the poorest GCA and episodic memory. CONCLUSIONS Presence of the ε4 allele may increase vulnerability to the deleterious effects of heavy alcohol consumption. Beneficial effects of light or moderate alcohol consumption were not observed.
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Affiliation(s)
- Riki E. Slayday
- Department of Psychology, San Diego State University, San
Diego, CA, USA
| | - Daniel E. Gustavson
- Department of Psychiatry, University of California San
Diego, La Jolla CA, USA
| | - Jeremy A. Elman
- Department of Psychiatry, University of California San
Diego, La Jolla CA, USA
| | - Asad Beck
- University of Washington, Graduate Program in Neuroscience,
Seattle, WA, USA
| | - Linda K. McEvoy
- Department of Radiology, University of California San
Diego, La Jolla, CA, USA
| | - Xin M. Tu
- Department of Family Medicine, University of California San
Diego, La Jolla, CA, USA
| | - Bin Fang
- Department of Psychiatry, University of California San
Diego, La Jolla CA, USA
| | - Richard L. Hauger
- Department of Psychiatry, University of California San
Diego, La Jolla CA, USA
- Center of Excellence for Stress and Mental Health, VA San
Diego Healthcare System, San Diego, CA, USA
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston
University, Boston, MA, USA
| | - Ruth E. McKenzie
- Department of Psychological and Brain Sciences, Boston
University, Boston, MA, USA
| | - Mark E. Sanderson-Cimino
- Department of Psychology, San Diego State University, San
Diego, CA, USA
- Department of Psychiatry, University of California San
Diego, La Jolla CA, USA
| | - Hong Xian
- Department of Biostatistics, St Louis University, St.
Louis, MO, USA
| | - William S. Kremen
- Department of Psychiatry, University of California San
Diego, La Jolla CA, USA
- Center of Excellence for Stress and Mental Health, VA San
Diego Healthcare System, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of
California San Diego, La Jolla CA, USA
| | - Carol E. Franz
- Department of Psychiatry, University of California San
Diego, La Jolla CA, USA
- Center for Behavior Genetics of Aging, University of
California San Diego, La Jolla CA, USA
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47
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Eglit GM, Elman JA, Panizzon MS, Sanderson‐Cimino ME, Williams ME, Dale AM, Eyler LT, Fennema‐Notestine C, Gillespie NA, Gustavson DE, Hatton SN, Hauger RL, Jak AJ, Logue MW, McEvoy LK, McKenzie R, Neale MC, Puckett OK, Reynolds CA, Toomey R, Tu XM, Whitsell N, Xian H, Lyons MJ, Franz CE, Kremen WS. Paradoxical cognitive reserve: Cognitive trajectories from earlier to later adulthood. Alzheimers Dement 2020. [DOI: 10.1002/alz.047686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Graham M.L. Eglit
- Center for Behavior Genetics of Aging University of California San Diego La Jolla CA USA
- Department of Psychiatry University of California San Diego La Jolla CA USA
- Veterans Affairs San Diego Healthcare System San Diego CA USA
| | | | | | | | - McKenna E. Williams
- SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology San Diego CA USA
| | | | | | | | | | | | | | | | - Amy J. Jak
- University of California San Diego La Jolla CA USA
| | | | | | | | | | | | | | | | - Xin M. Tu
- University of California San Diego La Jolla CA USA
| | | | - Hong Xian
- St. Louis University St. Louis MO USA
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48
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Elman JA, Puckett OK, Beck A, Panizzon MS, Sanderson‐Cimino ME, Gustavson DE, Lyons MJ, Franz CE, Kremen WS. MRI‐assessed locus coeruleus integrity is heritable and associated with cognition, Alzheimer’s risk, and sleep‐wake disturbance. Alzheimers Dement 2020. [DOI: 10.1002/alz.044862] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
| | | | - Asad Beck
- University of Washington Seattle WA USA
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49
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Williams ME, Elman JA, McEvoy LK, Dale AM, Fennema‐Notestine C, Franz CE, Gillespie NA, Hagler DJ, Lyons MJ, Neale MC, Panizzon MS, Puckett OK, Kremen WS. Cortical thickness and mean diffusivity AD signatures at average age 56 predict 12‐year progression to mild cognitive impairment. Alzheimers Dement 2020. [DOI: 10.1002/alz.043486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- McKenna E. Williams
- SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology San Diego CA USA
| | | | | | | | | | | | | | | | | | | | | | | | - William S. Kremen
- University of California, San Diego La Jolla CA USA
- VA San Diego Healthcare System San Diego CA USA
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50
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Kremen WS, Sanderson‐Cimino ME, Elman JA, Tu XM, Gross AL, Panizzon MS, Eglit GM, Jak AJ, Edmonds EC, Thomas KR, Eppig JS, Williams ME, Bondi MW, Lyons MJ, Franz CE. Accounting for cognitive practice effects results in earlier detection and more accurate diagnosis of MCI: Biomarker confirmation. Alzheimers Dement 2020. [DOI: 10.1002/alz.044883] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- William S. Kremen
- VA San Diego Healthcare System San Diego CA USA
- University of California San Diego La Jolla CA USA
| | | | | | - Xin M. Tu
- University of California San Diego La Jolla CA USA
| | - Alden L. Gross
- Department of Epidemiology Johns Hopkins Bloomberg School of Public Health Baltimore MD USA
| | | | | | - Amy J. Jak
- University of California San Diego La Jolla CA USA
| | | | | | - Joel S. Eppig
- University of California San Diego La Jolla CA USA
- San Diego State University San Diego CA USA
| | - McKenna E. Williams
- SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology San Diego CA USA
| | - Mark W. Bondi
- University of California, San Diego, School of Medicine San Diego CA USA
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