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Jayaprakash HJ, Mizuno A, Snitz BE, Cohen AD, Klunk WE, Aizenstein HJ, Karim HT. Voxel-wise hemispheric Amyloid Asymmetry and its association with cerebral metabolism and grey matter density in cognitively normal older adults. medRxiv 2024:2024.03.05.24303808. [PMID: 38496561 PMCID: PMC10942537 DOI: 10.1101/2024.03.05.24303808] [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: 03/19/2024]
Abstract
Introduction Alzheimer's disease (AD) is a neurodegenerative disorder characterized by changes in beta amyloid (Aß) and tau as well as changes in cerebral glucose metabolism and gray matter volume. This has been categorized as three distinct stages of amyloid, tau, and neurodegeneration. Past studies have shown asymmetric Aβ accumulation and its association with asymmetric cerebral metabolism in preclinical AD. We analyzed data to replicate these findings and extend them to associations with gray matter volume and cognitive function. Methods We recruited 93 (mean age = 76.4±6.1 years) cognitively normal adults who underwent magnetic resonance imaging (MRI) and positron emission tomography (PET) with Pittsburgh compound B (PiB) and Fluorodeoxyglucose (FDG) tracers (to estimate Aβ and glucose metabolism, respectively). We conducted voxel-wise paired t-test on PiB (left vs. right hemispheres) to identify regions that differ in Aβ between the left and right cortex. We identified whether these regions showed asymmetry in FDG and gray matter volume using paired t-tests on each region. We then conducted correlations between asymmetry indices for each region that had significant asymmetry in PiB, FDG, and gray matter volume. We ran a group regression analysis on cognitive functions. Results We found 26 regions that had significant rightward asymmetry in PiB including prefrontal cortex, temporal cortex, insula, parahippocampus, caudate, and putamen. All these regions showed significant gray matter rightward asymmetry, and most of these regions showed significant FDG asymmetry except the caudate, orbital cortex, medial frontal gyrus, and superior temporal gyrus. Only in the superior frontal gyrus, we found that greater rightward asymmetry in PiB was associated with greater rightward asymmetry in FDG, r(82) =0.38, p<0.005 (FDR corrected) - no other regions showed significant Aß asymmetry correlation with either FDG or gray matter volume asymmetry. We found that greater rightward FDG asymmetry in the superior frontal gyrus was associated with greater visuospatial processing scores in our cognitive domain group regression analysis. Discussion AD has previously been modeled in three-stages: however, our results indicate that cerebral glucose metabolism may be dynamic throughout the disease progression and may serve as a compensatory pathway for maintaining cognitive functioning.
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Affiliation(s)
- Hunsica J. Jayaprakash
- Department of Bioengineering, University of Pittsburgh
- Department of Computer Science, University of Pittsburgh
- Center for Neural Basis of Cognition, Carnegie Mellon University and University of Pittsburgh
| | - Akiko Mizuno
- Department of Psychiatry, University of Pittsburgh
| | | | - Ann D. Cohen
- Department of Psychiatry, University of Pittsburgh
| | - Willian E. Klunk
- Department of Psychiatry, University of Pittsburgh
- Department of Neurology, University of Pittsburgh
| | - Howard J. Aizenstein
- Department of Bioengineering, University of Pittsburgh
- Department of Psychiatry, University of Pittsburgh
| | - Helmet T. Karim
- Department of Bioengineering, University of Pittsburgh
- Department of Psychiatry, University of Pittsburgh
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Thurston RC, Maki P, Chang Y, Wu M, Aizenstein HJ, Derby CA, Karikari TK. Menopausal vasomotor symptoms and plasma Alzheimer disease biomarkers. Am J Obstet Gynecol 2024; 230:342.e1-342.e8. [PMID: 37939982 PMCID: PMC10939914 DOI: 10.1016/j.ajog.2023.11.002] [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: 07/20/2023] [Revised: 10/30/2023] [Accepted: 11/01/2023] [Indexed: 11/10/2023]
Abstract
BACKGROUND Identifying risk factors for Alzheimer disease in women is important as women compose two-thirds of individuals with Alzheimer disease. Previous work links vasomotor symptoms, the cardinal menopausal symptom, with poor memory performance and alterations in brain structure, function, and connectivity. These associations are evident when vasomotor symptoms are monitored objectively with ambulatory skin conductance monitors. OBJECTIVE This study aimed to determine whether vasomotor symptoms are associated with Alzheimer disease biomarkers. STUDY DESIGN Between 2017 and 2020, the MsBrain study enrolled 274 community-dwelling women aged 45 to 67 years who had a uterus and at least 1 ovary and were late perimenopausal or postmenopausal status. The key exclusion criteria included neurologic disorder, surgical menopause, and recent use of hormonal or nonhormonal vasomotor symptom treatment. Women underwent 24 hours of ambulatory skin conductance monitoring to assess vasomotor symptoms. Plasma concentrations of Alzheimer disease biomarkers, including amyloid β 42-to-amyloid β 40 ratio, phosphorylated tau (181 and 231), glial fibrillary acidic protein, and neurofilament light, were measured using a single-molecule array (Simoa) technology. Associations between vasomotor symptoms and Alzheimer disease biomarkers were assessed via linear regression models adjusted for age, race and ethnicity, education, body mass index, and apolipoprotein E4 status. Additional models adjusted for estradiol and sleep. RESULTS A total of 248 (mean age, 59.06 years; 81% White; 99% postmenopausal status) of enrolled MsBrain participants contributed data. Objectively assessed vasomotor symptoms occurring during sleep were associated with significantly lower amyloid β 42/amyloid β 40, (beta, -.0010 [standard error, .0004]; P=.018; multivariable), suggestive of greater brain amyloid β pathology. The findings remained significant after additional adjustments for estradiol and sleep. CONCLUSION Nighttime vasomotor symptoms may be a marker of women at risk of Alzheimer disease. It is yet unknown if these associations are causal.
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Affiliation(s)
- Rebecca C Thurston
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA; Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA; Department of Psychology, University of Pittsburgh, Pittsburgh, PA.
| | - Pauline Maki
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL; Department of Psychology, University of Illinois at Chicago, Chicago, IL; Department of Obstetrics and Gynecology, University of Illinois at Chicago, Chicago, IL
| | - Yuefang Chang
- Department of Neurosurgery, University of Pittsburgh, Pittsburgh, PA
| | - Minjie Wu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA
| | | | - Carol A Derby
- Departments of Neurology and Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
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Lopez OL, Villemagne VL, Chang YF, Cohen AD, Klunk WE, Mathis CA, Pascoal T, Ikonomovic MD, Rowe C, Dore V, Snitz BE, Lopresti BJ, Kamboh MI, Aizenstein HJ, Kuller LH. Association Between β-Amyloid Accumulation and Incident Dementia in Individuals 80 Years or Older Without Dementia. Neurology 2024; 102:e207920. [PMID: 38165336 PMCID: PMC10870745 DOI: 10.1212/wnl.0000000000207920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 10/03/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND AND OBJECTIVES While the highest prevalence of dementia occurs in individuals older than 80 years, most imaging studies focused on younger populations. The rates of β-amyloid (Aβ) accumulation and the effect of Alzheimer disease (AD) pathology on progression to dementia in this age group remain unexplored. In this study, we examined the relationship between changes in Aβ deposition over time and incident dementia in nondemented individuals followed during a period of 11 years. METHODS We examined 94 participants (age 85.9 + 2.8 years) who had up to 5 measurements of Pittsburgh compound-B (PiB)-PET and clinical evaluations from 2009 to 2020. All 94 participants had 2 PiB-PET scans, 76 participants had 3 PiB-PET scans, 18 participants had 4 PiB-PET scans, and 10 participants had 5 PiB-PET scans. The rates of Aβ deposition were compared with 120 nondemented individuals younger than 80 years (69.3 ± 5.4 years) from the Australian Imaging, Biomarker, and Lifestyle (AIBL) study who had 3 or more annual PiB-PET assessments. RESULTS By 2020, 49% of the participants developed dementia and 63% were deceased. There was a gradual increase in Aβ deposition in all participants whether they were considered Aβ positive or negative at baseline. In a Cox model controlled for age, sex, education level, APOE-4 allele, baseline Mini-Mental State Examination, and mortality, short-term change in Aβ deposition was not significantly associated with incident dementia (HR 2.19 (0.41-11.73). However, baseline Aβ burden, cortical thickness, and white matter lesions volume were the predictors of incident dementia. Aβ accumulation was faster (p = 0.01) in the older cohort (5.6%/year) when compared with AIBL (4.1%/year). In addition, baseline Aβ deposition was a predictor of short-term change (mean time 1.88 years). DISCUSSION There was an accelerated Aβ accumulation in cognitively normal individuals older than 80 years. Baseline Aβ deposition was a determinant of incident dementia and short-term change in Aβ deposition suggesting that an active Aβ pathologic process was present when these participants were cognitively normal. Consequently, age may not be a limiting factor for the use of the emergent anti-Aβ therapies.
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Affiliation(s)
- Oscar L Lopez
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Victor L Villemagne
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Yue-Fang Chang
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Ann D Cohen
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - William E Klunk
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Chester A Mathis
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Tharick Pascoal
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Milos D Ikonomovic
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Christopher Rowe
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Vincent Dore
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Beth E Snitz
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Brian J Lopresti
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - M Ilyas Kamboh
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Howard J Aizenstein
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Lewis H Kuller
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
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Kim JE, Tamres LK, Orbell SL, Cheng RZ, Klunk WE, Aizenstein HJ, Butters MA, McDade E, Lingler JH. "And Does That Necessarily Mean Absolutely Alzheimer's?" An Analysis of Questions Raised Following Amyloid PET Results Disclosure. Am J Geriatr Psychiatry 2024; 32:45-54. [PMID: 37634955 PMCID: PMC10841154 DOI: 10.1016/j.jagp.2023.08.005] [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] [Received: 04/14/2023] [Revised: 08/03/2023] [Accepted: 08/07/2023] [Indexed: 08/29/2023]
Abstract
INTRODUCTION Amyloid PET scans provide individuals with mild cognitive impairment (MCI) information about their risk of progressing to Alzheimer's dementia (AD). Given the wide-ranging implications of this information, best practice guidelines are needed to support researchers and clinicians disclosing these high-stakes test results. To inform the development of such guidelines, this analysis aims to describe questions and concerns raised during the disclosure of amyloid PET results in the context of MCI. METHODS Qualitative description was performed to analyze (n = 34) transcripts of audio-recorded amyloid PET results disclosure sessions involving MCI care dyads. The analysis focused on characterizing the frequency and nature of questions raised during an open question-and-answer (Q&A) period following the return of scan results using a standardized protocol. RESULTS Nearly all (n = 32/34) dyads posed questions during Q&A. Questions fell within six main categories with the most common being requests for clarification regarding AD/MCI, and next steps given the result. Questions were interspersed with comments reflecting the need for emotional support. Independently administered assessments of comprehension of results showed that, following the disclosure and Q&A, 31/32 participants with MCI and 31/31 care partners scored ≥4 on a 5-point scale. The number of questions asked by care partners during Q&A positively correlated with their level of comprehension (n = 31, Spearman's r = 0.370, p = 0.040). DISCUSSION This analysis highlights the value of providing opportunities for patients and their family members to ask questions upon learning patients' brain amyloid status. Disclosing clinicians should be prepared to provide clarification, resources, and support to patients and families during the return of amyloid PET results.
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Affiliation(s)
- Jeong Eun Kim
- University of Pittsburgh School of Nursing (JEK, LKT, SLO, RZC, JHL), Pittsburgh, PA.
| | - Lisa K Tamres
- University of Pittsburgh School of Nursing (JEK, LKT, SLO, RZC, JHL), Pittsburgh, PA; University of Pittsburgh Alzheimer's Disease Research Center (LKT, WEK, HJA, MAB, EM, JHL), Pittsburgh, PA
| | - Staci L Orbell
- University of Pittsburgh School of Nursing (JEK, LKT, SLO, RZC, JHL), Pittsburgh, PA
| | - Rebekah Z Cheng
- University of Pittsburgh School of Nursing (JEK, LKT, SLO, RZC, JHL), Pittsburgh, PA
| | - William E Klunk
- University of Pittsburgh Alzheimer's Disease Research Center (LKT, WEK, HJA, MAB, EM, JHL), Pittsburgh, PA; Department of Psychiatry, School of Medicine, University of Pittsburgh (WEK, HJA, MAB, EM, JHL), Pittsburgh, PA
| | - Howard J Aizenstein
- University of Pittsburgh Alzheimer's Disease Research Center (LKT, WEK, HJA, MAB, EM, JHL), Pittsburgh, PA; Department of Psychiatry, School of Medicine, University of Pittsburgh (WEK, HJA, MAB, EM, JHL), Pittsburgh, PA
| | - Meryl A Butters
- University of Pittsburgh Alzheimer's Disease Research Center (LKT, WEK, HJA, MAB, EM, JHL), Pittsburgh, PA; Department of Psychiatry, School of Medicine, University of Pittsburgh (WEK, HJA, MAB, EM, JHL), Pittsburgh, PA
| | - Eric McDade
- University of Pittsburgh Alzheimer's Disease Research Center (LKT, WEK, HJA, MAB, EM, JHL), Pittsburgh, PA; Department of Psychiatry, School of Medicine, University of Pittsburgh (WEK, HJA, MAB, EM, JHL), Pittsburgh, PA
| | - Jennifer H Lingler
- University of Pittsburgh School of Nursing (JEK, LKT, SLO, RZC, JHL), Pittsburgh, PA; University of Pittsburgh Alzheimer's Disease Research Center (LKT, WEK, HJA, MAB, EM, JHL), Pittsburgh, PA; Department of Psychiatry, School of Medicine, University of Pittsburgh (WEK, HJA, MAB, EM, JHL), Pittsburgh, PA
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Martins T, Santini T, de Almeida B, Wu M, Wilckens KA, Minhas D, Ibinson JW, Aizenstein HJ, Ibrahim TS. Characterization of oscillations in the brain and cerebrospinal fluid using ultra-high field magnetic resonance imaging. medRxiv 2023:2023.12.05.23299452. [PMID: 38105931 PMCID: PMC10723515 DOI: 10.1101/2023.12.05.23299452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Development of innovative non-invasive neuroimaging methods and biomarkers are critical for studying brain disease. In this work, we have developed a methodology to characterize the frequency responses and spatial localization of oscillations and movements of cerebrospinal fluid (CSF) flow in the human brain. Using 7 Tesla human MRI and ultrafast echo-planar imaging (EPI), in-vivo images were obtained to capture CSF oscillations and movements. Physiological data was simultaneously collected and correlated with the 7T MR data. The primary components of CSF oscillations were identified using spectral analysis (with frequency bands identified around 0.3Hz, 1.2Hz and 2.4Hz) and were mapped spatially and temporally onto the MR image domain and temporally onto the physiological domain. The developed methodology shows a good consistency and repeatability (standard deviation of 0.052 and 0.078 for 0.3Hz and 1.2Hz bands respectively) in-vivo for potential brain dynamics and CSF flow and clearance studies.
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Affiliation(s)
- Tiago Martins
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Tales Santini
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Bruno de Almeida
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Minjie Wu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Kristine A. Wilckens
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Davneet Minhas
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, United States
| | - James W. Ibinson
- Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Howard J. Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Tamer S. Ibrahim
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
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Wilson JD, Gerlach AR, Karim HT, Aizenstein HJ, Andreescu C. Sex matters: acute functional connectivity changes as markers of remission in late-life depression differ by sex. Mol Psychiatry 2023; 28:5228-5236. [PMID: 37414928 PMCID: PMC10919097 DOI: 10.1038/s41380-023-02158-0] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 06/15/2023] [Accepted: 06/22/2023] [Indexed: 07/08/2023]
Abstract
The efficacy of antidepressant treatment in late-life is modest, a problem magnified by an aging population and increased prevalence of depression. Understanding the neurobiological mechanisms of treatment response in late-life depression (LLD) is imperative. Despite established sex differences in depression and neural circuits, sex differences associated with fMRI markers of antidepressant treatment response are underexplored. In this analysis, we assess the role of sex on the relationship of acute functional connectivity changes with treatment response in LLD. Resting state fMRI scans were collected at baseline and day one of SSRI/SNRI treatment for 80 LLD participants. One-day changes in functional connectivity (differential connectivity) were related to remission status after 12 weeks. Sex differences in differential connectivity profiles that distinguished remitters from non-remitters were assessed. A random forest classifier was used to predict the remission status with models containing various combinations of demographic, clinical, symptomatological, and connectivity measures. Model performance was assessed with area under the curve, and variable importance was assessed with permutation importance. The differential connectivity profile associated with remission status differed significantly by sex. We observed evidence for a difference in one-day connectivity changes between remitters and non-remitters in males but not females. Additionally, prediction of remission was significantly improved in male-only and female-only models over pooled models. Predictions of treatment outcome based on early changes in functional connectivity show marked differences between sexes and should be considered in future MR-based treatment decision-making algorithms.
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Affiliation(s)
- James D Wilson
- Department of Mathematics and Statistics, University of San Francisco, San Francisco, CA, USA
| | - Andrew R Gerlach
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Helmet T Karim
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Carmen Andreescu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
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Vogt KM, Ibinson JW, Burlew AC, Smith CT, Aizenstein HJ, Fiez JA. Brain connectivity under light sedation with midazolam and ketamine during task performance and the periodic experience of pain: Examining concordance between different approaches for seed-based connectivity analysis. Brain Imaging Behav 2023; 17:519-529. [PMID: 37166623 PMCID: PMC10543548 DOI: 10.1007/s11682-023-00782-6] [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] [Accepted: 04/29/2023] [Indexed: 05/12/2023]
Abstract
This work focused on functional connectivity changes under midazolam and ketamine sedation during performance of a memory task, with the periodic experience of pain. To maximize ability to compare to previous and future work, we performed secondary region of interest (ROI)-to-ROI functional connectivity analyses on these data, using two granularities of scale for ROIs. These findings are compared to the results of a previous seed-to-voxel analysis methodology, employed in the primary analysis. Healthy adult volunteers participated in this randomized crossover 3 T functional MRI study under no drug, followed by subanesthetic doses of midazolam or ketamine achieving minimal sedation. Periodic painful stimulation was delivered while subjects repeatedly performed a memory-encoding task. Atlas-based and network-level ROIs were used from within Conn Toolbox (ver 18). Timing of experimental task events was regressed from the data to assess drug-induced changes in background connectivity, using ROI-to-ROI methodology. Compared to saline, ROI-to-ROI connectivity changes under ketamine did not survive correction for multiple comparisons, thus data presented is from 16 subjects in a paired analysis between saline and midazolam. In both ROI-to-ROI analyses, the predominant direction of change was towards increased connectivity under midazolam, compared to saline. These connectivity increases occurred between functionally-distinct brain areas, with a posterior-predominant spatial distribution that included many long-range connectivity changes. During performance of an experimental task that involved periodic painful stimulation, compared to saline, low-dose midazolam was associated with robust increases in functional connectivity. This finding was concordant across different seed-based analyses for midazolam, but not ketamine. The neuroimaging drug trial from which this data was drawn was pre-registered (NCT-02515890) prior to enrollment of the first subject.
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Affiliation(s)
- Keith M Vogt
- Department of Anesthesiology and Perioperative Medicine, School of Medicine, University of Pittsburgh, 3459 Fifth Avenue, UPMC Montefiore - Suite 467, Pittsburgh, PA, 15213, USA.
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA.
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.
- Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, USA.
| | - James W Ibinson
- Department of Anesthesiology and Perioperative Medicine, School of Medicine, University of Pittsburgh, 3459 Fifth Avenue, UPMC Montefiore - Suite 467, Pittsburgh, PA, 15213, USA
- Department of Anesthesiology, Surgical Service Line, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
- Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alex C Burlew
- School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - C Tyler Smith
- Department of Anesthesiology and Perioperative Medicine, School of Medicine, University of Pittsburgh, 3459 Fifth Avenue, UPMC Montefiore - Suite 467, Pittsburgh, PA, 15213, USA
| | - Howard J Aizenstein
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Julie A Fiez
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
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Mizuno A, Karim HT, Ly MJ, Lopresti BJ, Cohen AD, Ali AA, Mathis CA, Klunk WE, Aizenstein HJ, Snitz BE. Low thalamic activity during a digit-symbol substitution task is associated with symptoms of subjective cognitive decline. Front Psychiatry 2023; 14:1242822. [PMID: 37743995 PMCID: PMC10511647 DOI: 10.3389/fpsyt.2023.1242822] [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] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 08/21/2023] [Indexed: 09/26/2023] Open
Abstract
Introduction Subjective cognitive decline (SCD) may represent the earliest preclinical stage of Alzheimer's Disease (AD) for some older adults. However, the underlying neurobiology of SCD is not completely understood. Since executive function may be affected earlier than memory function in the progression of AD, we aimed to characterize SCD symptoms in terms of fMRI brain activity during the computerized digit-symbol substitution task (DSST), an executive function task. We also explored associations of DSST task performance with brain activation, SCD severity, and amyloid-ß (Aß) load. Methods We analyzed data from 63 cognitively normal older individuals (mean age 73.6 ± 7.2) with varying degree of SCD symptoms. Participants completed a computerized version of DSST in the MR scanner and a Pittsburgh Compound-B (PiB)-PET scan to measure global cerebral Aß load. Results A voxel-wise analysis revealed that greater SCD severity was associated with lower dorsomedial thalamus activation. While task performance was not associated with brain activation nor Aß load, slower reaction time was associated with greater SCD severity. Discussion The observed lower dorsomedial thalamus activation may reflect declining familiarity-based working memory and the trans-thalamic executive function pathway in SCD. SCD symptoms may reflect altered neural function and subtle decline of executive function, while Aß load may have an indirect impact on neural function and performance. Self-perceived cognitive decline may serve as a psychological/subjective marker reflecting subtle brain changes.
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Affiliation(s)
- Akiko Mizuno
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Helmet Talib Karim
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Maria J. Ly
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, United States
| | - Brian J. Lopresti
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Ann D. Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Areej A. Ali
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Chester A. Mathis
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, United States
| | - William E. Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Howard J. Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Beth E. Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
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9
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Smagula SF, Hasler BP, Schulz R, Graves JL, Reynolds CF, Aizenstein HJ, Buysse DJ, Krafty RT, Hall MH. Activity patterns related to depression symptoms in stressed dementia caregivers. Int Psychogeriatr 2023; 35:373-380. [PMID: 31658928 PMCID: PMC7188574 DOI: 10.1017/s1041610219001601] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [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: 11/06/2022]
Abstract
OBJECTIVES Self-reported activity restriction is an established correlate of depression in dementia caregivers (dCGs). It is plausible that the daily distribution of objectively measured activity is also altered in dCGs with depression symptoms; if so, such activity characteristics could provide a passively measurable marker of depression or specific times to target preventive interventions. We therefore investigated how levels of activity throughout the day differed in dCGs with and without depression symptoms, then tested whether any such differences predicted changes in symptoms 6 months later. DESIGN, SETTING, PARTICIPANTS, AND MEASUREMENTS We examined 56 dCGs (mean age = 71, standard deviation (SD) = 6.7; 68% female) and used clustering to identify subgroups which had distinct depression symptom levels, leveraging baseline Center for Epidemiologic Studies of Depression Scale-Revised Edition and Patient Health Questionnaire-9 (PHQ-9) measures, as well as a PHQ-9 score from 6 months later. Using wrist activity (mean recording length = 12.9 days, minimum = 6 days), we calculated average hourly activity levels and then assessed when activity levels relate to depression symptoms and changes in symptoms 6 months later. RESULTS Clustering identified subgroups characterized by: (1) no/minimal symptoms (36%) and (2) depression symptoms (64%). After multiple comparison correction, the group of dCGs with depression symptoms was less active from 8 to 10 AM (Cohen's d ≤ -0.9). These morning activity levels predicted the degree of symptom change on the PHQ-9 6 months later (per SD unit β = -0.8, 95% confidence interval: -1.6, -0.1, p = 0.03) independent of self-reported activity restriction and other key factors. CONCLUSIONS These novel findings suggest that morning activity may protect dCGs from depression symptoms. Future studies should test whether helping dCGs get active in the morning influences the other features of depression in this population (i.e. insomnia, intrusive thoughts, and perceived activity restriction).
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Affiliation(s)
- Stephen F Smagula
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Brant P Hasler
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Richard Schulz
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jessica L Graves
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Charles F Reynolds
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Howard J Aizenstein
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Daniel J Buysse
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Robert T Krafty
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Martica H Hall
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
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10
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Bellaver B, Povala G, Ferreira PCL, Ferrari-Souza JP, Leffa DT, Lussier FZ, Benedet AL, Ashton NJ, Triana-Baltzer G, Kolb HC, Tissot C, Therriault J, Servaes S, Stevenson J, Rahmouni N, Lopez OL, Tudorascu DL, Villemagne VL, Ikonomovic MD, Gauthier S, Zimmer ER, Zetterberg H, Blennow K, Aizenstein HJ, Klunk WE, Snitz BE, Maki P, Thurston RC, Cohen AD, Ganguli M, Karikari TK, Rosa-Neto P, Pascoal TA. Astrocyte reactivity influences amyloid-β effects on tau pathology in preclinical Alzheimer's disease. Nat Med 2023:10.1038/s41591-023-02380-x. [PMID: 37248300 PMCID: PMC10353939 DOI: 10.1038/s41591-023-02380-x] [Citation(s) in RCA: 36] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 05/01/2023] [Indexed: 05/31/2023]
Abstract
An unresolved question for the understanding of Alzheimer's disease (AD) pathophysiology is why a significant percentage of amyloid-β (Aβ)-positive cognitively unimpaired (CU) individuals do not develop detectable downstream tau pathology and, consequently, clinical deterioration. In vitro evidence suggests that reactive astrocytes unleash Aβ effects in pathological tau phosphorylation. Here, in a biomarker study across three cohorts (n = 1,016), we tested whether astrocyte reactivity modulates the association of Aβ with tau phosphorylation in CU individuals. We found that Aβ was associated with increased plasma phosphorylated tau only in individuals positive for astrocyte reactivity (Ast+). Cross-sectional and longitudinal tau-positron emission tomography analyses revealed an AD-like pattern of tau tangle accumulation as a function of Aβ only in CU Ast+ individuals. Our findings suggest astrocyte reactivity as an important upstream event linking Aβ with initial tau pathology, which may have implications for the biological definition of preclinical AD and for selecting CU individuals for clinical trials.
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Affiliation(s)
- Bruna Bellaver
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Graduate Program in Biological Sciences-Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Guilherme Povala
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - João Pedro Ferrari-Souza
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Graduate Program in Biological Sciences-Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Douglas T Leffa
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Firoza Z Lussier
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andréa L Benedet
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | | | - Hartmuth C Kolb
- Neuroscience Biomarkers, Janssen Research and Development, La Jolla, CA, USA
| | - Cécile Tissot
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Jenna Stevenson
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Oscar L Lopez
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dana L Tudorascu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Biostatistics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Milos D Ikonomovic
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Geriatric Research Education and Clinical Center, VA Pittsburgh HS, Pittsburgh, PA, USA
| | - Serge Gauthier
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Eduardo R Zimmer
- Graduate Program in Biological Sciences-Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Department of Pharmacology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Graduate Program in Biological Sciences: Pharmacology and Therapeutics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Brain Institute, PUCRS, Porto Alegre, Brazil
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Pauline Maki
- Department of Psychiatry, University of Illinois, Chicago, IL, USA
| | - Rebecca C Thurston
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, PA, USA
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mary Ganguli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, PA, USA
| | - Thomas K Karikari
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
- Brain Imaging Centre, Montreal Neurological Institute-Hospital, Montreal, Quebec, Canada
| | - Tharick A Pascoal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
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11
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Smagula SF, Aizenstein HJ. Initial evidence regarding the neurobiological basis of psychological symptoms in dementia caregivers. Transl Psychiatry 2023; 13:169. [PMID: 37202392 DOI: 10.1038/s41398-023-02457-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 04/20/2023] [Accepted: 04/25/2023] [Indexed: 05/20/2023] Open
Abstract
Mood symptoms and disorders are common in dementia caregivers, who can be exposed to a myriad of potential stressors including their care recipient's neuropsychiatric symptoms. Existing evidence indicates that the effects of potentially stressful exposures on mental health depend on the caregiver's individual characteristics and responses. Specifically, prior studies indicate that risk factors measured on psychological (e.g., emotion-focused/behaviorally disengaged coping responses) and behavioral (e.g., sleep and activity restriction) levels of analysis may confer the effects of caregiving exposures on mental health. Theoretically, this process from caregiving stressors and other risk factors to mood symptoms is neurobiologically mediated. This article reviews recent studies that used brain imaging to identify neurobiological factors that are related to psychological outcomes in caregivers. Available observational data indicate that psychological outcomes in caregivers are related to differences in the structure/function of regions involved in socio-affective information processing (prefrontal), autobiographical memory (the posterior cingulate), and stress (amygdala). In addition, two small randomized controlled trials using repeated brain imaging showed that Mentalizing Imagery Therapy (a mindfulness program) increased prefrontal network connectivity and reduced mood symptoms. These studies raise the possibility that, in the future, brain imaging may be useful to detect the neurobiological basis of a given caregiver's mood vulnerability and guide the selection of interventions that are known to modify it. However, there remains a need for evidence on whether brain imaging improves on simpler/inexpensive measurement modalities like self-report for identifying vulnerable caregivers and matching them with efficacious interventions. In addition, to target interventions, more evidence is needed regarding the effects that both risk factors and interventions have on mood neurobiology (e.g., how persistent emotion-focused coping, sleep disruption, and mindfulness affect brain function).
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Affiliation(s)
- Stephen F Smagula
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Howard J Aizenstein
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
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12
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Kolobaric A, Mizuno A, Yang X, George CJ, Seidman A, Aizenstein HJ, Kovacs M, Karim HT. History of major depressive disorder is associated with differences in implicit learning of emotional faces. J Psychiatr Res 2023; 161:324-332. [PMID: 36996725 PMCID: PMC10202097 DOI: 10.1016/j.jpsychires.2023.03.026] [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] [Received: 01/31/2023] [Revised: 03/13/2023] [Accepted: 03/15/2023] [Indexed: 04/01/2023]
Abstract
Major depressive disorder is often associated with worsened reward learning, with blunted reward response persisting after remission. In this study, we developed a probabilistic learning task with social rewards as a learning signal. We examined the impacts of depression on social rewards (facial affect displays) as an implicit learning signal. Fifty-seven participants without a history of depression and sixty-two participants with a history of depression (current or remitted) completed a structured clinical interview and an implicit learning task with social reward. Participants underwent an open-ended interview to evaluate whether they knew the rule consciously. Linear mixed effects models revealed that participants without a history of depression learned faster and showed a stronger preference towards the positive than the negative stimulus when compared to the participants with a history of depression. In contrast, those with a history depression learned slower on average and displayed greater variability in stimulus preference. We did not detect any differences in learning between those with current and remitted depression. The results indicate that on a probabilistic social reward task, people with a history of depression exhibit slower reward learning and greater variability in their learning behavior. Improving our understanding of alterations in social reward learning and their associations with depression and anhedonia may help to develop translatable psychotherapeutic approaches for modification of maladaptive emotion regulation.
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Affiliation(s)
| | - Akiko Mizuno
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Xiao Yang
- Department of Psychology, Old Dominion University, Norfolk, VA, USA
| | | | - Andrew Seidman
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Maria Kovacs
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
| | - Helmet T Karim
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
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13
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Kazan J, Gerlach AR, Mizuno A, Andreescu C, Aizenstein HJ, Ward S, Buente KJ, Stahl ST. Depressive symptoms anticipate behavioral and emotional factors among older adults: A prospective cross-lagged panel design. Psychiatry Research Communications 2023; 3. [PMID: 37009251 PMCID: PMC10062444 DOI: 10.1016/j.psycom.2022.100096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
This study examined the temporal relationship among depression, anxiety, insomnia, perceived stress, and physical activity in adults aged 60+ years with a history of major depressive disorder. We conducted a longitudinal study with 12 weeks of follow-up. Assessments consisted of phone or video interviews and included questionnaires evaluating depression, anxiety, insomnia, perceived stress, and physical activity. Our analytic approach consisted of a depression-focused cross-lagged panel model (CLPM) to examine week-to-week correlations among the five measures. The depression-focused CLPM identified statistically significant week-to-week self-predictive effects for each of the five measures. Higher depressive symptom burden was a strong predictor of increased stress, greater insomnia, and less physical activity the following week. No other cross-measure predictions were statistically significant. Our analytical approach clarifies the directional relationship among variables that typically co-occur with depression showing that higher depression symptom burden predisposes older adults to poor sleep, a reduced level of daytime activity, and a greater sense of stress. These findings support the need for longitudinal assessments and targeted interventions for reducing symptoms of depression in older adults.
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Affiliation(s)
- Joseph Kazan
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andrew R. Gerlach
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Akiko Mizuno
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Carmen Andreescu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Howard J. Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Scott Ward
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kara J. Buente
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Sarah T. Stahl
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Corresponding author. Department of Psychiatry, University of Pittsburgh, 3811 O’Hara Street, Pittsburgh, PA, 15213, USA., (S.T. Stahl)
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14
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Wu M, Schweitzer N, Iordanova BE, Halligan-Eddy E, Tudorascu DL, Mathis CA, Lopresti BJ, Kamboh MI, Cohen AD, Snitz BE, Klunk WE, Aizenstein HJ. In Pre-Clinical AD Small Vessel Disease is Associated With Altered Hippocampal Connectivity and Atrophy. Am J Geriatr Psychiatry 2023; 31:112-123. [PMID: 36274019 PMCID: PMC10768933 DOI: 10.1016/j.jagp.2022.09.011] [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] [Received: 04/08/2022] [Revised: 09/16/2022] [Accepted: 09/20/2022] [Indexed: 01/25/2023]
Abstract
OBJECTIVE Small Vessel Disease (SVD) is known to be associated with higher AD risk, but its relationship to amyloidosis in the progression of AD is unclear. In this cross-sectional study of cognitively normal older adults, we explored the interactive effects of SVD and amyloid-beta (Aβ) pathology on hippocampal functional connectivity during an associative encoding task and on hippocampal volume. METHODS This study included 61 cognitively normal older adults (age range: 65-93 years, age mean ± standard deviation: 75.8 ± 6.4, 41 [67.2%] female). PiB PET, T2-weighted FLAIR, T1-weighted and face-name fMRI images were acquired on each participant to evaluate brain Aβ, white matter hyperintensities (WMH+/- status), gray matter density, and hippocampal functional connectivity. RESULTS We found that, in WMH (+) older adults greater Aβ burden was associated with greater hippocampal local connectivity (i.e., hippocampal-parahippocampal connectivity) and lower gray matter density in medial temporal lobe (MTL), whereas in WMH (-) older adults greater Aβ burden was associated with greater hippocampal distal connectivity (i.e., hippocampal-prefrontal connectivity) and no changes in MTL gray matter density. Moreover, greater hippocampal local connectivity was associated with MTL atrophy. CONCLUSION These observations support a hippocampal excitotoxicity model linking SVD to neurodegeneration in preclinical AD. This may explain how SVD may accelerate the progression from Aβ positivity to neurodegeneration, and subsequent AD.
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Affiliation(s)
- Minjie Wu
- Department of Psychiatry (MW, EHE, DLT, ADC, WEK, HJA), University of Pittsburgh, Pittsburgh, PA.
| | - Noah Schweitzer
- Department of Bioengineering (NS, BEI, HJA), University of Pittsburgh, Pittsburgh, PA
| | - Bistra E Iordanova
- Department of Bioengineering (NS, BEI, HJA), University of Pittsburgh, Pittsburgh, PA
| | - Edythe Halligan-Eddy
- Department of Psychiatry (MW, EHE, DLT, ADC, WEK, HJA), University of Pittsburgh, Pittsburgh, PA
| | - Dana L Tudorascu
- Department of Psychiatry (MW, EHE, DLT, ADC, WEK, HJA), University of Pittsburgh, Pittsburgh, PA; Departments of Medicine and Biostatistics (DLT), University of Pittsburgh, Pittsburgh, PA
| | - Chester A Mathis
- Department of Radiology (CAM, BJL), University of Pittsburgh, Pittsburgh, PA
| | - Brian J Lopresti
- Department of Radiology (CAM, BJL), University of Pittsburgh, Pittsburgh, PA
| | - M Ilyas Kamboh
- Department of Human Genetics (MIK), University of Pittsburgh, Pittsburgh, PA
| | - Ann D Cohen
- Department of Psychiatry (MW, EHE, DLT, ADC, WEK, HJA), University of Pittsburgh, Pittsburgh, PA
| | - Beth E Snitz
- Department of Neurology (BES), University of Pittsburgh, Pittsburgh, PA
| | - William E Klunk
- Department of Psychiatry (MW, EHE, DLT, ADC, WEK, HJA), University of Pittsburgh, Pittsburgh, PA
| | - Howard J Aizenstein
- Department of Psychiatry (MW, EHE, DLT, ADC, WEK, HJA), University of Pittsburgh, Pittsburgh, PA; Department of Bioengineering (NS, BEI, HJA), University of Pittsburgh, Pittsburgh, PA
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15
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Thurston RC, Wu M, Chang YF, Aizenstein HJ, Derby CA, Barinas-Mitchell EA, Maki P. Menopausal Vasomotor Symptoms and White Matter Hyperintensities in Midlife Women. Neurology 2023; 100:e133-e141. [PMID: 36224031 PMCID: PMC9841446 DOI: 10.1212/wnl.0000000000201401] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 08/30/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND AND OBJECTIVES The menopause transition is increasingly recognized as a time of importance for women's brain health. A growing body of work indicates that the classic menopausal symptom, vasomotor symptom (VMS), may be associated with poorer cardiovascular health. Other work links VMS to poorer cognition. We investigate whether VMS, when rigorously assessed using physiologic measures, are associated with greater white matter hyperintensity volume (WMHV) among midlife women. We consider a range of potential explanatory factors in these associations and explore whether VMS are associated with the spatial distribution of WMHV. METHODS Women aged 45-67 years and free of hormone therapy underwent 24 hours of physiologic VMS monitoring (sternal skin conductance), actigraphy assessment of sleep, physical measures, phlebotomy, and 3 Tesla neuroimaging. Associations between VMS (24-hour, wake, and sleep VMS, with wake and sleep intervals defined by actigraphy) and whole brain WMHV were considered in linear regression models adjusted for age, race, education, smoking, body mass index, blood pressure, insulin resistance, and lipids. Secondary models considered WMHV in specific brain regions (deep, periventricular, frontal, temporal, parietal, and occipital) and additional covariates including sleep. RESULTS The study sample included 226 women. Physiologically assessed VMS were associated with greater whole brain WMHV in multivariable models, with the strongest associations observed for sleep VMS (24-hour VMS, B[SE] = 0.095 [0.045], p = 0.032; Wake VMS, B[SE] = 0.078 [0.046], p = 0.089, Sleep VMS, B[SE] = 0.173 [0.060], p = 0.004). Associations were not accounted for by additional covariates including actigraphy-assessed sleep (wake after sleep onset). When considering the spatial distribution of WMHV, sleep VMS were associated with both deep WMHV, periventricular WMHV, and frontal lobe WMHV. DISCUSSION VMS, particularly VMS occurring during sleep, were associated with greater WMHV. Identification of female-specific midlife markers of poor brain health later in life is critical to identify women who warrant early intervention and prevention. VMS have the potential to serve as female-specific midlife markers of brain health in women.
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Affiliation(s)
- Rebecca C Thurston
- From the Department of Psychiatry (R.C.T., M.W., H.J.A.), Epidemiology (R.C.T., E.A.B.-M.), Psychology (R.C.T.), and Neurosurgery (Y.-F.C.), University of Pittsburgh, PA; Department of Neurology and Epidemiology and Population Health (C.A.D.), Albert Einstein College of Medicine, Bronx, NY; and Department of Psychiatry (P.M.), University of Illinois at Chicago, IL.
| | - Minjie Wu
- From the Department of Psychiatry (R.C.T., M.W., H.J.A.), Epidemiology (R.C.T., E.A.B.-M.), Psychology (R.C.T.), and Neurosurgery (Y.-F.C.), University of Pittsburgh, PA; Department of Neurology and Epidemiology and Population Health (C.A.D.), Albert Einstein College of Medicine, Bronx, NY; and Department of Psychiatry (P.M.), University of Illinois at Chicago, IL
| | - Yue-Fang Chang
- From the Department of Psychiatry (R.C.T., M.W., H.J.A.), Epidemiology (R.C.T., E.A.B.-M.), Psychology (R.C.T.), and Neurosurgery (Y.-F.C.), University of Pittsburgh, PA; Department of Neurology and Epidemiology and Population Health (C.A.D.), Albert Einstein College of Medicine, Bronx, NY; and Department of Psychiatry (P.M.), University of Illinois at Chicago, IL
| | - Howard J Aizenstein
- From the Department of Psychiatry (R.C.T., M.W., H.J.A.), Epidemiology (R.C.T., E.A.B.-M.), Psychology (R.C.T.), and Neurosurgery (Y.-F.C.), University of Pittsburgh, PA; Department of Neurology and Epidemiology and Population Health (C.A.D.), Albert Einstein College of Medicine, Bronx, NY; and Department of Psychiatry (P.M.), University of Illinois at Chicago, IL
| | - Carol A Derby
- From the Department of Psychiatry (R.C.T., M.W., H.J.A.), Epidemiology (R.C.T., E.A.B.-M.), Psychology (R.C.T.), and Neurosurgery (Y.-F.C.), University of Pittsburgh, PA; Department of Neurology and Epidemiology and Population Health (C.A.D.), Albert Einstein College of Medicine, Bronx, NY; and Department of Psychiatry (P.M.), University of Illinois at Chicago, IL
| | - Emma A Barinas-Mitchell
- From the Department of Psychiatry (R.C.T., M.W., H.J.A.), Epidemiology (R.C.T., E.A.B.-M.), Psychology (R.C.T.), and Neurosurgery (Y.-F.C.), University of Pittsburgh, PA; Department of Neurology and Epidemiology and Population Health (C.A.D.), Albert Einstein College of Medicine, Bronx, NY; and Department of Psychiatry (P.M.), University of Illinois at Chicago, IL
| | - Pauline Maki
- From the Department of Psychiatry (R.C.T., M.W., H.J.A.), Epidemiology (R.C.T., E.A.B.-M.), Psychology (R.C.T.), and Neurosurgery (Y.-F.C.), University of Pittsburgh, PA; Department of Neurology and Epidemiology and Population Health (C.A.D.), Albert Einstein College of Medicine, Bronx, NY; and Department of Psychiatry (P.M.), University of Illinois at Chicago, IL
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16
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Li J, Mountz EJ, Mizuno A, Shah AM, Weinstein A, Cohen AD, Klunk WE, Snitz BE, Aizenstein HJ, Karim HT. Functional Asymmetry During Working Memory and Its Association with Markers of Alzheimer's Disease in Cognitively Normal Older Adults. J Alzheimers Dis 2023; 95:1077-1089. [PMID: 37638440 DOI: 10.3233/jad-230379] [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: 08/29/2023]
Abstract
BACKGROUND Amyloid-β (Aβ) deposits asymmetrically early in Alzheimer's disease (AD). This process is variable and has been associated with asymmetric hypometabolism. OBJECTIVE We investigated whether neural asymmetry during working memory and executive function processing was associated with AD genetic risk and markers of AD as well as other brain neuropathology biomarkers, cognitive function, and cognitive reserve in cognitively normal older adults. METHODS We analyzed data from 77 cognitively healthy, older adults who completed functional magnetic resonance imaging, positron emission tomography, and cognitive testing. We identified regions of significant activation and asymmetry during the Digital Symbol Substitution Task (DSST). We examined associations between regions with significant hemispheric asymmetry (directional and absolute) and global cerebral Aβ, cerebral glucose metabolism, white matter hyperintensities, APOE ɛ4 allele status, DSST reaction time, age, sex, education, and cognitive function. RESULTS Asymmetry was not associated with several factors including cognitive function, Aβ, and white matter hyperintensities. The presence of at least one ɛ4 APOE allele in participants was associated with less asymmetric activation in the angular gyrus (right dominant activation). Greater education was associated with less asymmetric activation in mediodorsal thalamus (left dominant activation). CONCLUSIONS Genetic risk of AD was associated with lower asymmetry in angular gyrus activation, while greater education was associated with lower asymmetry in mediodorsal thalamus activation. Changes in asymmetry may reflect components of compensation or cognitive reserve. Asymmetric neural recruitment during working memory may be related to maintenance of cognitive function in cognitively normal older adults.
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Affiliation(s)
- Jinghang Li
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Elizabeth J Mountz
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Akiko Mizuno
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ashti M Shah
- Physician Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Andrea Weinstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Howard J Aizenstein
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Helmet T Karim
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
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17
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Meehan E, Minhas DS, Gogola A, Ghodadra A, Cohen AD, Tudorascu DL, Lopresti BJ, Aizenstein HJ, Kendro S, Mason NS, Klunk WE, Laymon CM. Evaluation of A Direct Regional Reprojection Reconstruction Method to Improve Quantitation of Amyloid and Tau PET Images using 3D Printed Phantoms. Alzheimers Dement 2022. [DOI: 10.1002/alz.067917] [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]
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18
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Lopez OL, Villemagne VL, Cohen AD, Snitz BE, Aizenstein HJ, Klunk WE, Mathis C, Chang Y, Kuller LH. Relationship between longitudinal changes in amyloid deposition and incident dementia in non‐demented individuals age 80+. Alzheimers Dement 2022. [DOI: 10.1002/alz.065091] [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)
- Oscar L. Lopez
- Alzheimer's Disease Research Center Pittsburgh PA USA
- University of Pittsburgh Pittsburgh PA USA
| | - Victor L Villemagne
- University of Pittsburgh Pittsburgh PA USA
- The University of Pittsburgh Pittsburgh PA USA
| | - Ann D Cohen
- Alzheimer's Disease Research Center Pittsburgh PA USA
- University of Pittsburgh Pittsburgh PA USA
- University of Pittsburgh School of Medicine Pittsburgh PA USA
| | - Beth E Snitz
- Alzheimer's Disease Research Center Pittsburgh PA USA
- University of Pittsburgh Pittsburgh PA USA
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19
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Kuller LH, Snitz BE, Hughes TM, Chang Y, Cohen AD, Mathis CA, Aizenstein HJ, Lopez OL. Low untreated systolic blood pressure over 18 years is associated with survival free of dementia age 90. Alzheimers Dement 2022; 18:2176-2187. [PMID: 35089640 PMCID: PMC9787390 DOI: 10.1002/alz.12493] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 08/11/2021] [Indexed: 01/31/2023]
Abstract
INTRODUCTION We hypothesized that lower untreated systolic blood pressure (SBP) would be associated with a lower risk of dementia and death up to age 95. METHODS SBP measured between 2000 and 2006 was evaluated in relationship to dementia risk and brain biomarkers from 2009-2020 (n = 177) in the Gingko Evaluation of Memory Study (GEMS), mean age 95 in 2020. Participants had measurements of brain amyloid beta (Aβ) and repeat clinical-cognitive evaluations every 6 months. RESULTS By 2020, only 9 of 177 patients (5%) were alive and cognitively unimpaired (CU). Mean SBP from 2000 to 2006 was 120 mm Hg for nine alive/CU, 125 mm Hg for alive/mild cognitive impairment (MCI), and 130 mm Hg for alive/dementia (P = .03). The amount of Aβ was directly related to SBP levels. In multivariate analysis, Aβ+ in 2009 and thinner cortex were significant predictors of dementia. Excluding Aβ, SBP became a significant predictor of dementia. DISCUSSION Low SBP untreated by antihypertensive medications was associated with significant decreased risk of dementia and less Aβ.
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Affiliation(s)
- Lewis H. Kuller
- Department of EpidemiologyGraduate School of Public HealthUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Beth E. Snitz
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Timothy M. Hughes
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Yuefang Chang
- Department of NeurosurgeryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Ann D. Cohen
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Chester A. Mathis
- Department of RadiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | | | - Oscar L. Lopez
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
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20
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Kolobaric A, Karim HT, Banihashemi L, Mizuno A, Aizenstein HJ, Andreescu C. Are All Anxieties Created Equal? Stress-related Networks and Anxiety Phenotypes in Old Age. Am J Geriatr Psychiatry 2022; 30:801-812. [PMID: 35000866 PMCID: PMC9177511 DOI: 10.1016/j.jagp.2021.12.007] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 12/01/2021] [Accepted: 12/08/2021] [Indexed: 11/25/2022]
Abstract
OBJECTIVE The dysregulation of stress-related networks due to chronic symptoms such as severe worry and/or rumination is one of the putative pathways linking anxiety in late-life with cognitive decline and increased cardiovascular burden. Symptoms such as severe worry or rumination respond poorly to standard treatment and drive the morbidity associated with anxiety in older adults. We assessed if any of the neural networks anchored in the stress-related regions of interest (ROIs) are associated with distinct anxiety phenotypes (worry, rumination and global anxiety). METHODS We recruited older participants (over 50 years of age) with varying levels of worry (N = 91) to undergo resting state fMRI. We computed seed-based connectivity for each ROI: the bed nucleus of the stria terminalis, the paraventricular nucleus of the hypothalamus, habenula, and amygdala. We limited our connectivity analyses to extracted regions for each seeded ROI-based network based on their canonical networks in 1,000 participants (Neurosynth). Using connectivity and clinical factors, we fit cross-validated elastic net models to predict scores on Penn State Worry Questionnaire, Rumination Subscale Questionnaire, Hamilton Anxiety Rating Scale, and Perceived Stress Scale. RESULTS We identified several distinct connectivity patterns that predict anxiety phenotypes' severity. Greater worry was associated with greater paraventricular nucleus of the hypothalamus -subgenual anterior cingulate cortex, parahippocampal, and olfactory and amygdala-PHC connectivity. Greater global anxiety was associated with lower amygdala-superior temporal gyrus connectivity. Greater perceived stress was associated with lower amygdala-inferior temporal gyrus and amygdala-fusiform gyrus connectivity. CONCLUSION Our study suggests that various late-life anxiety phenotypes (worry, global anxiety, rumination) may be associated with varying functional connectivity related to stress and emotion regulation. This may aid in the development of future targeted interventions.
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Affiliation(s)
| | - Helmet T. Karim
- Department of Psychiatry, University of Pittsburgh, Pittsburgh PA,Department of Bioengineering, University of Pittsburgh, Pittsburgh PA
| | | | - Akiko Mizuno
- Department of Psychiatry, University of Pittsburgh, Pittsburgh PA
| | - Howard J. Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh PA,Department of Bioengineering, University of Pittsburgh, Pittsburgh PA
| | - Carmen Andreescu
- Department of Psychiatry (HTK, LB, AM, HJA, CA), University of Pittsburgh, Pittsburgh PA.
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21
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Shaaban CE, Fan E, Klatt BN, Cohen AD, Snitz BE, Yu Z, Lopresti BJ, Villemagne VL, Klunk WE, Aizenstein HJ, Rosso AL. Brain health correlates of mobility-related confidence. Exp Gerontol 2022; 163:111776. [PMID: 35339632 PMCID: PMC9109136 DOI: 10.1016/j.exger.2022.111776] [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: 10/16/2021] [Revised: 12/22/2021] [Accepted: 03/21/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND Mobility is important for independence in older age. While brain health correlates of objectively measured mobility-related features like gait and balance have been reported, we aimed to test neuroimaging and cognitive correlates of subjective measures of mobility-related confidence. METHODS We carried out a cross-sectional observational study comprised of N = 29 cognitively unimpaired older adult participants, mean age 75.8 ± 5.8, 52% female, 24% non-white. We measured cognition, hippocampal volume, white matter hyperintensities, cerebral amyloid-β (Aβ), and gait and balance confidence. We tested associations using unadjusted Spearman correlations and correlations partialling out covariates of interest one at a time. RESULTS Greater gait confidence was associated with better attention (unadjusted ρ = 0.37, p = 0.05; partially attenuated by adjustment for age, APOE4, anxiety, motivation, gait speed, or Aβ); executive performance (unadjusted ρ = 0.35, p = 0.06; partially attenuated by adjustment for age, APOE4, gait speed, or Aβ); and lower Aβ levels (unadjusted ρ = -0.40, p = 0.04; partially attenuated by adjustment for age, depressive symptoms, motivation, or gait speed). Greater balance confidence was associated with better global cognition (unadjusted ρ = 0.41, p = 0.03; partially attenuated by adjustment for APOE4, gait speed, or Aβ); attention (unadjusted ρ = 0.46, p = 0.01; robust to adjustment); and lower Aβ levels (unadjusted ρ = -0.35, p = 0.07; partially attenuated by adjustment for age, education, APOE4, depressive symptoms, anxiety, motivation, or gait speed). CONCLUSIONS Self-reported mobility-related confidence is associated with neuroimaging and cognitive measures and would be easy for providers to use in clinical evaluations. These associations should be further evaluated in larger samples, and longitudinal studies can help determine temporality of declines.
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Affiliation(s)
| | - Erica Fan
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Brooke N Klatt
- Department of Physical Therapy, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Zheming Yu
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Brian J Lopresti
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Andrea L Rosso
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
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22
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Thurston RC, Jakubowski KP, Wu M, Aizenstein HJ, Chang Y, Derby CA, Koenen KC, Barinas-Mitchell E, Maki PM. Sexual assault and white matter hyperintensities among midlife women. Brain Imaging Behav 2022; 16:773-780. [PMID: 34553332 PMCID: PMC8940746 DOI: 10.1007/s11682-021-00536-2] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/06/2021] [Indexed: 01/09/2023]
Abstract
Traumatic experiences have been linked to poor mental and physical health. However, there has been little examination of their relationship to neuroimaging markers of cerebrovascular risk. White matter hyperintensities (WMHs) are markers of brain small vessel disease. WMHs can be detected decades before the onset of dementia and other disorders and can serve as early markers for these brain disorders. We tested whether traumatic experiences were associated with brain WMH volume among midlife women. In the MsBrain study, 145 women (mean age = 59 years) without cardiovascular disease, stroke, or dementia were recruited. Women completed questionnaires [trauma checklist, depression, post-traumatic stress measures]; physical measures [body mass index (BMI), blood pressure (BP)]; phlebotomy; actigraphy sleep measurement, and 3 Tesla magnetic resonance brain imaging for WMHs. Cross-sectional associations between traumatic experiences and WMH volume were assessed in linear regression models. Covariates were age, race/ethnicity, education, BMI, BP, lipids, preeclampsia, sleep, and additionally depressive and post-traumatic stress disorder symptoms. 68% of women endorsed at least one of the traumas assessed. The most common trauma was sexual assault (23% of women). Women with trauma exposure had greater WMH volume than women without trauma [B(SE) = .24 (.09), p = .01, multivariable]. The single trauma most associated with WMH was sexual assault [B(SE) = .25 (.11), p = .02, multivariable]. Results persisted adjusting for depressive or post-traumatic stress symptoms. A trauma history, particularly sexual assault, was associated with greater WMH volume controlling for covariates, including depressive and post-traumatic symptoms. Sexual assault may place women at risk for poor brain health.
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Affiliation(s)
- Rebecca C Thurston
- Department of Psychiatry, University of Pittsburgh, 3811 O'Hara St, Pittsburgh, PA, 15213, USA.
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Karen P Jakubowski
- Department of Psychiatry, University of Pittsburgh, 3811 O'Hara St, Pittsburgh, PA, 15213, USA
| | - Minjie Wu
- Department of Psychiatry, University of Pittsburgh, 3811 O'Hara St, Pittsburgh, PA, 15213, USA
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh, 3811 O'Hara St, Pittsburgh, PA, 15213, USA
| | - Yuefang Chang
- Department of Neurosurgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Carol A Derby
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Karestan C Koenen
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Pauline M Maki
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
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23
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Banihashemi L, Peng CW, Rangarajan A, Karim HT, Wallace ML, Sibbach BM, Singh J, Stinley MM, Germain A, Aizenstein HJ. Childhood Threat Is Associated With Lower Resting-State Connectivity Within a Central Visceral Network. Front Psychol 2022; 13:805049. [PMID: 35310241 PMCID: PMC8927539 DOI: 10.3389/fpsyg.2022.805049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 02/09/2022] [Indexed: 11/25/2022] Open
Abstract
Childhood adversity is associated with altered or dysregulated stress reactivity; these altered patterns of physiological functioning persist into adulthood. Evidence from both preclinical animal models and human neuroimaging studies indicates that early life experience differentially influences stressor-evoked activity within central visceral neural circuits proximally involved in the control of stress responses, including the subgenual anterior cingulate cortex (sgACC), paraventricular nucleus of the hypothalamus (PVN), bed nucleus of the stria terminalis (BNST) and amygdala. However, the relationship between childhood adversity and the resting-state connectivity of this central visceral network remains unclear. To this end, we examined relationships between childhood threat and childhood socioeconomic deprivation, the resting-state connectivity between our regions of interest (ROIs), and affective symptom severity and diagnoses. We recruited a transdiagnostic sample of young adult males and females (n = 100; mean age = 27.28, SD = 3.99; 59 females) with a full distribution of maltreatment history and symptom severity across multiple affective disorders. Resting-state data were acquired using a 7.2-min functional magnetic resonance imaging (fMRI) sequence; noted ROIs were applied as masks to determine ROI-to-ROI connectivity. Threat was determined by measures of childhood traumatic events and abuse. Socioeconomic deprivation (SED) was determined by a measure of childhood socioeconomic status (parental education level). Covarying for age, race and sex, greater childhood threat was significantly associated with lower BNST-PVN, amygdala-sgACC and PVN-sgACC connectivity. No significant relationships were found between SED and resting-state connectivity. BNST-PVN connectivity was associated with the number of lifetime affective diagnoses. Exposure to threat during early development may entrain altered patterns of resting-state connectivity between these stress-related ROIs in ways that contribute to dysregulated neural and physiological responses to stress and subsequent affective psychopathology.
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Affiliation(s)
- Layla Banihashemi
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
- *Correspondence: Layla Banihashemi,
| | - Christine W. Peng
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Anusha Rangarajan
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Helmet T. Karim
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Meredith L. Wallace
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Statistics, University of Pittsburgh, Pittsburgh, PA, United States
| | - Brandon M. Sibbach
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Jaspreet Singh
- Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, United States
| | - Mark M. Stinley
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Anne Germain
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Howard J. Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
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24
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Kim T, Aizenstein HJ, Snitz BE, Cheng Y, Chang YF, Roush RE, Huppert TJ, Cohen A, Doman J, Becker JT. Tract Specific White Matter Lesion Load Affects White Matter Microstructure and Their Relationships With Functional Connectivity and Cognitive Decline. Front Aging Neurosci 2022; 13:760663. [PMID: 35185514 PMCID: PMC8848259 DOI: 10.3389/fnagi.2021.760663] [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] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 12/27/2021] [Indexed: 11/24/2022] Open
Abstract
White matter hyperintensities (WMHs) are associated with cognitive decline. Assessing the effect of WMH on WM microstructural changes and its relationships with structural and functional connectivity to multiple cognitive domains are helpful to better understand the pathophysiological processes of cognitive impairment. 65 participants (49 normal and 16 MCI subjects, age: 67.4 ± 8.3 years, 44 females) were studied at 3T. The WMHs and fifty fiber tracts were automatically segmented from the T1/T2-weighted images and diffusion-weighted images, respectively. Tract-profiles of WMH were compared with those of apparent fiber density (AFD). The relationship between AFD and tract connectivity (TC) was assessed. Functional connectivity (FC) between tract ends obtained from resting-state functional MRI was examined in relation to TC. Tract-specific relationships of WMH, TC and FC with a multi-domain neuropsychological test battery and Montreal Cognitive Assessment (MoCA) were also separately assessed by lasso linear regression. Indirect pathways of TC and FC between WMH and multiple cognitive measures were tested using the mediation analysis. Higher WMH loads in WM tracts were locally matched with the reduced AFD, which was related to decrease in TC. However, no direct relationship was found between TC and FC. Tract-specific changes on WMH, TC and FC for each cognitive performance may explain that macro- and microstructural and functional changes are associated differently with each cognitive domain in a fiber specific manner. In these identified tracts, the differences between normal and MCI for WMH and TC were increased, and the relationships of WMH, TC and FC with cognitive outcomes were more significant, compared to the results from all tracts. Indirect pathways of two-step (TC-FC) between WMH and all cognitive domains were significant (p < 0.0083 with Bonferroni correction), while the separated indirect pathways through TC and through FC were different depending on cognitive domain. Deterioration in specific cognitive domains may be affected by alterations in a set of different tracts that are differently associated with macrostructural, microstructural, and function changes. Thus, assessments of WMH and its associated changes on specific tracts help for better understanding of the interrelationships of multiple changes in cognitive impairment.
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Affiliation(s)
- Tae Kim
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
- *Correspondence: Tae Kim,
| | - Howard J. Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Beth E. Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Yu Cheng
- Departments of Statistics and Biostatistics, University of Pittsburgh, Pittsburgh, PA, United States
| | - Yue-Fang Chang
- Department of Neurosurgery, University of Pittsburgh, Pittsburgh, PA, United States
| | - Rebecca E. Roush
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Theodore J. Huppert
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
- Deparement of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Annie Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Jack Doman
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - James T. Becker
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
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25
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Minhas DS, Laymon CM, Lopresti BJ, Cohen AD, Tudorascu DL, Mason NS, Lopez OL, Villemagne VL, Aizenstein HJ, Mathis CA, Klunk WE. Semi‐quantitative [
11
C]PiB and [
15
O]H
2
O PET measures of cerebrospinal fluid dynamics discriminate amyloid load but not cognitive status. Alzheimers Dement 2021. [DOI: 10.1002/alz.055716] [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: 11/06/2022]
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26
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Torbati ME, Minhas DS, Ahmad GE, O'Connor EE, John M, Laymon CM, Zixi Y, Cohen AD, Aizenstein HJ, Klunk WE, Christian BT, Crainiceanu C, Hwang SJ, Tudorascu DL. An MRI multi‐scanner neuroimaging data harmonization study using RAVEL and ComBat. Alzheimers Dement 2021. [DOI: 10.1002/alz.053928] [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: 11/09/2022]
Affiliation(s)
| | | | | | | | | | | | - Yang Zixi
- University of Pittsburgh Pittsburgh PA USA
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27
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Shaaban CE, Snitz BE, Tudorascu DL, Lopresti BJ, Royse SK, Yu Z, Aizenstein HJ, Klunk WE, Cohen AD. Sex and cerebral small vessel disease‐specific longitudinal trajectories of amyloid, tau, and neurodegeneration. Alzheimers Dement 2021. [DOI: 10.1002/alz.056291] [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)
| | - Beth E Snitz
- University of Pittsburgh Pittsburgh PA USA
- Alzheimer's Disease Research Center Pittsburgh PA USA
| | | | | | - Sarah K Royse
- University of Pittsburgh School of Medicine Pittsburgh PA USA
| | - Zheming Yu
- University of Pittsburgh Pittsburgh PA USA
| | - Howard J Aizenstein
- University of Pittsburgh Pittsburgh PA USA
- Alzheimer's Disease Research Center Pittsburgh PA USA
| | - William E Klunk
- University of Pittsburgh Pittsburgh PA USA
- Alzheimer's Disease Research Center Pittsburgh PA USA
| | - Ann D Cohen
- University of Pittsburgh Pittsburgh PA USA
- Alzheimer's Disease Research Center Pittsburgh PA USA
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28
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Schweitzer N, Farhat N, Wu M, Kofler J, Berardinelli J, Ibrahim T, Iordanova B, Aizenstein HJ. A novel method for tracking the progression of WMHs through the alignment of premortem in‐vivo to postmortem ex‐vivo MRI and histopathology. Alzheimers Dement 2021. [DOI: 10.1002/alz.053167] [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: 11/10/2022]
Affiliation(s)
| | | | - Minjie Wu
- University of Pittsburgh School of Medicine Pittsburgh PA USA
| | - Julia Kofler
- University of Pittsburgh School of Medicine Pittsburgh PA USA
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29
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Eshaghzadeh Torbati M, Minhas DS, Ahmad G, O'Connor EE, Muschelli J, Laymon CM, Yang Z, Cohen AD, Aizenstein HJ, Klunk WE, Christian BT, Hwang SJ, Crainiceanu CM, Tudorascu DL. A multi-scanner neuroimaging data harmonization using RAVEL and ComBat. Neuroimage 2021; 245:118703. [PMID: 34736996 PMCID: PMC8820090 DOI: 10.1016/j.neuroimage.2021.118703] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [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: 05/14/2021] [Revised: 10/07/2021] [Accepted: 10/28/2021] [Indexed: 11/27/2022] Open
Abstract
Modern neuroimaging studies frequently combine data collected from multiple scanners and experimental conditions. Such data often contain substantial technical variability associated with image intensity scale (image intensity scales are not the same in different images) and scanner effects (images obtained from different scanners contain substantial technical biases). Here we evaluate and compare results of data analysis methods without any data transformation (RAW), with intensity normalization using RAVEL, with regional harmonization methods using ComBat, and a combination of RAVEL and ComBat. Methods are evaluated on a unique sample of 16 study participants who were scanned on both 1.5T and 3T scanners a few months apart. Neuroradiological evaluation was conducted for 7 different regions of interest (ROI’s) pertinent to Alzheimer’s disease (AD). Cortical measures and results indicate that: (1) RAVEL substantially improved the reproducibility of image intensities; (2) ComBat is preferred over RAVEL and the RAVEL-ComBat combination in terms of regional level harmonization due to more consistent harmonization across subjects and image-derived measures; (3) RAVEL and ComBat substantially reduced bias compared to analysis of RAW images, but RAVEL also resulted in larger variance; and (4) the larger root mean square deviation (RMSD) of RAVEL compared to ComBat is due mainly to its larger variance.
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Affiliation(s)
- Mahbaneh Eshaghzadeh Torbati
- Intelligent System Program, University of Pittsburgh School of Computing and Information, Pittsburgh, PA 15213, USA
| | - Davneet S Minhas
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Ghasan Ahmad
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Erin E O'Connor
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - John Muschelli
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Charles M Laymon
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Zixi Yang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Bradley T Christian
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Seong Jae Hwang
- Intelligent System Program, University of Pittsburgh School of Computing and Information, Pittsburgh, PA 15213, USA; Department of Computer Science, University of Pittsburgh School of Computing and Information, Pittsburgh, PA 15213, USA
| | - Ciprian M Crainiceanu
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Dana L Tudorascu
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA; Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15213, USA.
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30
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Gerlach AR, Karim HT, Kazan J, Aizenstein HJ, Krafty RT, Andreescu C. Networks of worry-towards a connectivity-based signature of late-life worry using higher criticism. Transl Psychiatry 2021; 11:550. [PMID: 34711810 PMCID: PMC8553743 DOI: 10.1038/s41398-021-01648-5] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 09/16/2021] [Accepted: 09/27/2021] [Indexed: 01/14/2023] Open
Abstract
Severe worry is a complex transdiagnostic phenotype independently associated with increased morbidity, including cognitive impairment and cardiovascular diseases. We investigated the neurobiological basis of worry in older adults by analyzing resting state fMRI using a large-scale network-based approach. We collected resting fMRI on 77 participants (>50 years old) with varying worry severity. We computed region-wise connectivity across the default mode network (DMN), anterior salience network, and left executive control network. All 22,366 correlations were regressed on worry severity and adjusted for age, sex, race, education, disease burden, depression, anxiety, rumination, and neuroticism. We employed higher criticism, a second-level method of significance testing for rare and weak features, to reveal the functional connectivity patterns associated with worry. The analysis suggests that worry has a complex, yet distinct signature associated with resting state functional connectivity. Intra-connectivities and inter-connectivities of the DMN comprise the dominant contribution. The anterior cingulate, temporal lobe, and thalamus are heavily represented with overwhelmingly negative association with worry. The prefrontal regions are also strongly represented with a mix of positive and negative associations with worry. Identifying the most salient connections may be useful for targeted interventions for reducing morbidity associated with severe worry in older adults.
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Affiliation(s)
- Andrew R. Gerlach
- grid.21925.3d0000 0004 1936 9000Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
| | - Helmet T. Karim
- grid.21925.3d0000 0004 1936 9000Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA ,grid.21925.3d0000 0004 1936 9000Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA USA
| | - Joseph Kazan
- grid.21925.3d0000 0004 1936 9000Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
| | - Howard J. Aizenstein
- grid.21925.3d0000 0004 1936 9000Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA ,grid.21925.3d0000 0004 1936 9000Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA USA
| | - Robert T. Krafty
- grid.189967.80000 0001 0941 6502Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA USA
| | - Carmen Andreescu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
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31
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Cui C, Higashiyama A, Lopresti BJ, Ihara M, Aizenstein HJ, Watanabe M, Chang Y, Kakuta C, Yu Z, Mathis CA, Kokubo Y, Fukuda T, Villemagne VL, Klunk WE, Lopez OL, Kuller LH, Miyamoto Y, Sekikawa A. Comparing Pathological Risk Factors for Dementia between Cognitively Normal Japanese and Americans. Brain Sci 2021; 11:1180. [PMID: 34573201 PMCID: PMC8469296 DOI: 10.3390/brainsci11091180] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 08/28/2021] [Accepted: 08/30/2021] [Indexed: 11/16/2022] Open
Abstract
The Alzheimer's Disease Neuroimaging Initiative showed that Japanese had significantly lower brain Aβ burden than Americans among a cognitively normal population. This cross-sectional study aimed to compare vascular disease burden, Aβ burden, and neurodegeneration between cognitively normal elderly Japanese and Americans. Japanese and American participants were matched for age (±4-year-old), sex, and Apolipoprotein E (APOE) genotype. Brain vascular disease burden and brain Aβ burden were measured using white matter lesions (WMLs) and 11C-labeled Pittsburgh Compound B (PiB) retention, respectively. Neurodegeneration was measured using hippocampal volumes and cortical thickness. A total of 95 Japanese and 95 Americans were recruited (50.5% men, mean age = 82). Compared to Americans, Japanese participants had larger WMLs, and a similar global Aβ standardized uptake value ratio (SUVR), cortical thickness and hippocampal volumes. Japanese had significantly lower regional Aβ SUVR in the anterior ventral striatum, posterior cingulate cortex, and precuneus. Cognitively normal elderly Japanese and Americans had different profiles regarding vascular disease and Aβ burden. This suggests that multiple risk factors are likely to be involved in the development of dementia. Additionally, Japanese might have a lower risk of dementia due to lower Aβ burden than Americans. Longitudinal follow-up of these cohorts is warranted to ascertain the predictive accuracy of these findings.
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Affiliation(s)
- Chendi Cui
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA; (C.C.); (L.H.K.)
| | - Aya Higashiyama
- Department of Preventive Cardiology, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan; (A.H.); (M.W.); (Y.K.); (Y.M.)
- Department of Hygiene, Wakayama Medical University, Wakayama 641-0011, Japan
| | - Brian J. Lopresti
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA; (B.J.L.); (Z.Y.); (C.A.M.)
| | - Masafumi Ihara
- Department of Neurology, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan; (M.I.); (C.K.)
| | - Howard J. Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA; (H.J.A.); (V.L.V.); (W.E.K.)
| | - Makoto Watanabe
- Department of Preventive Cardiology, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan; (A.H.); (M.W.); (Y.K.); (Y.M.)
| | - Yuefang Chang
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA;
| | - Chikage Kakuta
- Department of Neurology, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan; (M.I.); (C.K.)
| | - Zheming Yu
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA; (B.J.L.); (Z.Y.); (C.A.M.)
| | - Chester A. Mathis
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA; (B.J.L.); (Z.Y.); (C.A.M.)
| | - Yoshihiro Kokubo
- Department of Preventive Cardiology, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan; (A.H.); (M.W.); (Y.K.); (Y.M.)
| | - Tetsuya Fukuda
- Department of Radiology, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan;
| | - Victor L. Villemagne
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA; (H.J.A.); (V.L.V.); (W.E.K.)
| | - William E. Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA; (H.J.A.); (V.L.V.); (W.E.K.)
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15213, USA;
| | - Oscar L. Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15213, USA;
| | - Lewis H. Kuller
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA; (C.C.); (L.H.K.)
| | - Yoshihiro Miyamoto
- Department of Preventive Cardiology, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan; (A.H.); (M.W.); (Y.K.); (Y.M.)
- Open Innovation Center, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan
| | - Akira Sekikawa
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA; (C.C.); (L.H.K.)
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32
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Laymon CM, Minhas DS, Royse SK, Aizenstein HJ, Cohen AD, Tudorascu DL, Klunk WE. Characterization of point-spread function specification error on Geometric Transfer Matrix partial volume correction in [ 11C]PiB amyloid imaging. EJNMMI Phys 2021; 8:54. [PMID: 34283320 PMCID: PMC8292473 DOI: 10.1186/s40658-021-00403-5] [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] [Received: 03/08/2021] [Accepted: 07/05/2021] [Indexed: 11/29/2022] Open
Abstract
Purpose Partial-volume correction (PVC) using the Geometric Transfer Matrix (GTM) method is used in positron emission tomography (PET) to compensate for the effects of spatial resolution on quantitation. We evaluate the effect of misspecification of scanner point-spread function (PSF) on GTM results in amyloid imaging, including the effect on amyloid status classification (positive or negative). Methods Twenty-nine subjects with Pittsburgh Compound B ([11C]PiB) PET and structural T1 MR imaging were analyzed. FreeSurfer 5.3 (FS) was used to parcellate MR images into regions-of-interest (ROIs) that were used to extract radioactivity concentration values from the PET images. GTM PVC was performed using our “standard” PSF parameterization [3D Gaussian, full-width at half-maximum (w) of approximately 5 mm]. Additional GTM PVC was performed with “incorrect” parameterizations, taken around the correct value. The result is a set of regional activity values for each of the GTM applications. For each case, activity values from various ROIs were combined and normalized to produce standardized uptake value ratios (SUVRs) for nine standard [11C]PiB quantitation ROIs and a global region. GTM operating-point characteristics were determined from the slope of apparent SUVR versus w curves. Results Errors in specification of w on the order of 1 mm (3D) mainly produce only modest errors of up to a few percent. An exception was the anterior ventral striatum in which fractional errors of up to 0.29 per millimeter (3D) of error in w were observed. Conclusion While this study does not address all the issues regarding the quantitative strengths and weakness of GTM PVC, we find that with reasonable caution, the unavoidable inaccuracies associated with PSF specification do not preclude its use in amyloid quantitation. Supplementary Information The online version contains supplementary material available at 10.1186/s40658-021-00403-5.
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Affiliation(s)
- Charles M Laymon
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA. .,Department of Bioengineering, University of Pittsburgh, PET Center, PUH B930, 200 Lothrop St, Pittsburgh, PA, 15213, USA.
| | - Davneet S Minhas
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Sarah K Royse
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Bioengineering, University of Pittsburgh, PET Center, PUH B930, 200 Lothrop St, Pittsburgh, PA, 15213, USA
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dana L Tudorascu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
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33
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Mizuno A, Karim HT, Ly MJ, Cohen AD, Lopresti BJ, Mathis CA, Klunk WE, Aizenstein HJ, Snitz BE. An Effect of Education on Memory-Encoding Activation in Subjective Cognitive Decline. J Alzheimers Dis 2021; 81:1065-1078. [PMID: 33843669 DOI: 10.3233/jad-201087] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Subjective cognitive decline (SCD) may be an early manifestation of pre-clinical Alzheimer's disease. Elevated amyloid-β (Aβ) is a correlate of SCD symptoms in some individuals. The underlying neural correlates of SCD symptoms and their association with Aβ is unknown. SCD is a heterogeneous condition, and cognitive reserve may explain individual differences in its neural correlates. OBJECTIVE We investigated the association between brain activation during memory encoding and SCD symptoms, as well as with Aβ, among older individuals. We also tested the moderating role of education (an index of cognitive reserve) on the associations. METHODS We measured brain activation during the "face-name" memory-encoding fMRI task and Aβ deposition with Pittsburgh Compound-B (PiB)-PET among cognitively normal older individuals (n = 63, mean age 73.1 ± 7.4 years). We tested associations between activation and SCD symptoms by self-report measures, Aβ, and interactions with education. RESULTS Activation was not directly associated with SCD symptoms or Aβ. However, education moderated the association between activation and SCD symptoms in the executive control network, salience network, and subcortical regions. Greater SCD symptoms were associated with greater activation in those with higher education, but with lower activation in those with lower education. CONCLUSION SCD symptoms were associated with different patterns of brain activation in the extended memory system depending on level of cognitive reserve. Greater SCD symptoms may represent a saturation of neural compensation in individuals with greater cognitive reserve, while it may reflect diminishing neural resources in individuals with lower cognitive reserve.
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Affiliation(s)
- Akiko Mizuno
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Helmet T Karim
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Maria J Ly
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Brian J Lopresti
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Chester A Mathis
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
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34
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Karim HT, Ly M, Yu G, Krafty R, Tudorascu DL, Aizenstein HJ, Andreescu C. Aging faster: worry and rumination in late life are associated with greater brain age. Neurobiol Aging 2021; 101:13-21. [PMID: 33561786 PMCID: PMC8122027 DOI: 10.1016/j.neurobiolaging.2021.01.009] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [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] [Received: 08/11/2020] [Revised: 01/05/2021] [Accepted: 01/09/2021] [Indexed: 01/07/2023]
Abstract
Older adults with anxiety have lower gray matter brain volume-a component of accelerated aging. We have previously validated a machine learning model to predict brain age, an estimate of an individual's age based on voxel-wise gray matter images. We investigated associations between brain age and anxiety, depression, stress, and emotion regulation. We recruited 78 participants (≥50 years) along a wide range of worry severity. We collected imaging data and computed voxel-wise gray matter images, which were input into an existing machine learning model to estimate brain age. We conducted a multivariable linear regression between brain age and age, sex, race, education, worry, anxiety, depression, rumination, neuroticism, stress, reappraisal, and suppression. We found that greater brain age was significantly associated with greater age, male sex, greater worry, greater rumination, and lower suppression. Male sex, worry, and rumination are associated with accelerated aging in late life and expressive suppression may have a protective effect. These results provide evidence for the transdiagnostic model of negative repetitive thoughts, which are associated with cognitive decline, amyloid, and tau.
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Affiliation(s)
- Helmet T Karim
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Maria Ly
- Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
| | - Gary Yu
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Robert Krafty
- Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dana L Tudorascu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA; Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Carmen Andreescu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
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Thurston RC, Wu M, Aizenstein HJ, Chang Y, Barinas Mitchell E, Derby CA, Maki PM. Sleep characteristics and white matter hyperintensities among midlife women. Sleep 2021; 43:5682717. [PMID: 31863110 DOI: 10.1093/sleep/zsz298] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [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: 10/11/2019] [Revised: 11/26/2019] [Indexed: 01/08/2023] Open
Abstract
STUDY OBJECTIVES Sleep disturbance is common among midlife women. Poor self-reported sleep characteristics have been linked to cerebrovascular disease and dementia risk. However, little work has considered the relation of objectively assessed sleep characteristics and white matter hyperintensities (WMHs), a marker of small vessel disease in the brain. Among 122 midlife women, we tested whether women with short or disrupted sleep would have greater WMH, adjusting for cardiovascular disease (CVD) risk factors, estradiol, and physiologically assessed sleep hot flashes. METHODS We recruited 122 women (mean age = 58 years) without a history of stroke or dementia who underwent 72 h of actigraphy to quantify sleep, 24 h of physiologic monitoring to quantify hot flashes; magnetic resonance imaging to assess WMH; phlebotomy, questionnaires, and physical measures (blood pressure, height, and weight). Associations between actigraphy-assessed sleep (wake after sleep onset and total sleep time) and WMH were tested in linear regression models. Covariates included demographics, CVD risk factors (blood pressure, lipids, and diabetes), estradiol, mood, and sleep hot flashes. RESULTS Greater actigraphy-assessed waking after sleep onset was associated with more WMH [B(SE) = .008 (.002), p = 0.002], adjusting for demographics, CVD risk factors, and sleep hot flashes. Findings persisted adjusting for estradiol and mood. Neither total sleep time nor subjective sleep quality was related to WMH. CONCLUSIONS Greater actigraphy-assessed waking after sleep onset but not subjective sleep was related to greater brain WMH among midlife women. Poor sleep may be associated with brain small vessel disease at midlife, which can increase the risk for brain disorders.
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Affiliation(s)
- Rebecca C Thurston
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA.,Department of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA.,Department of Psychology, University of Pittsburgh, Pittsburgh, PA
| | - Minjie Wu
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Yuefang Chang
- Department of Neurosurgery, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Emma Barinas Mitchell
- Department of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA
| | - Carol A Derby
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY
| | - Pauline M Maki
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL
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36
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Santini T, Koo M, Farhat N, Campos VP, Alkhateeb S, Vieira MAC, Butters MA, Rosano C, Aizenstein HJ, Mettenburg J, Novelli EM, Ibrahim TS. Analysis of hippocampal subfields in sickle cell disease using ultrahigh field MRI. Neuroimage Clin 2021; 30:102655. [PMID: 34215139 PMCID: PMC8102634 DOI: 10.1016/j.nicl.2021.102655] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 03/28/2021] [Accepted: 03/29/2021] [Indexed: 12/05/2022]
Abstract
Sickle cell disease (SCD) is an inherited hemoglobinopathy that causes organ dysfunction, including cerebral vasculopathy and neurological complications. Hippocampal segmentation with newer and advanced 7 Tesla (7T) MRI protocols has revealed atrophy in specific subregions in other neurodegenerative and neuroinflammatory diseases, however, there is limited evidence of hippocampal involvement in SCD. Thus, we explored whether SCD may be also associated with abnormalities in hippocampal subregions. We conducted 7T MRI imaging in individuals with SCD, including the HbSS, HbSC and HbS/beta thalassemia genotypes (n = 53), and healthy race and age-matched controls (n = 47), using a customized head coil. Both T1- and T2-weighted images were used for automatic segmentation of the hippocampal subfields. Individuals with SCD had, on average, significantly smaller volume of the region including the Dentate Gyrus and Cornu Ammonis (CA) 2 and 3 as compared to the control group. Other hippocampal subregions also showed a trend towards smaller volumes in the SCD group. These findings support and extend previous reports of reduced volume in the temporal lobe in SCD patients. Further studies are necessary to investigate the mechanisms that lead to structural changes in the hippocampus subfields and their relationship with cognitive performance in SCD patients.
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Affiliation(s)
- Tales Santini
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Minseok Koo
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Nadim Farhat
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Vinicius P Campos
- Department of Electrical and Computer Engineering, University of São Paulo, São Carlos, SP, Brazil
| | - Salem Alkhateeb
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Marcelo A C Vieira
- Department of Electrical and Computer Engineering, University of São Paulo, São Carlos, SP, Brazil
| | - Meryl A Butters
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Caterina Rosano
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Howard J Aizenstein
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Joseph Mettenburg
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Enrico M Novelli
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States; Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, PA, United States.
| | - Tamer S Ibrahim
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States; Department of Radiology, University of Pittsburgh, Pittsburgh, PA, United States.
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37
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Zhao X, Sicilia A, Minhas DS, O'Connor EE, Aizenstein HJ, Klunk WE, Tudorascu DL, Hwang SJ. ROBUST WHITE MATTER HYPERINTENSITY SEGMENTATION ON UNSEEN DOMAIN. Proc IEEE Int Symp Biomed Imaging 2021; 2021:1047-1051. [PMID: 34909113 PMCID: PMC8668404 DOI: 10.1109/isbi48211.2021.9434034] [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] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Typical machine learning frameworks heavily rely on an underlying assumption that training and test data follow the same distribution. In medical imaging which increasingly begun acquiring datasets from multiple sites or scanners, this identical distribution assumption often fails to hold due to systematic variability induced by site or scanner dependent factors. Therefore, we cannot simply expect a model trained on a given dataset to consistently work well, or generalize, on a dataset from another distribution. In this work, we address this problem, investigating the application of machine learning models to unseen medical imaging data. Specifically, we consider the challenging case of Domain Generalization (DG) where we train a model without any knowledge about the testing distribution. That is, we train on samples from a set of distributions (sources) and test on samples from a new, unseen distribution (target). We focus on the task of white matter hyperintensity (WMH) prediction using the multi-site WMH Segmentation Challenge dataset and our local in-house dataset. We identify how two mechanically distinct DG approaches, namely domain adversarial learning and mix-up, have theoretical synergy. Then, we show drastic improvements of WMH prediction on an unseen target domain.
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Affiliation(s)
- Xingchen Zhao
- Department of Computer Science, University of Pittsburgh
| | | | | | - Erin E O'Connor
- Department of Diagnostic Radiology & Nuclear Medicine - University of Maryland, Baltimore
| | | | | | | | - Seong Jae Hwang
- Intelligent Systems Program - University of Pittsburgh
- Department of Computer Science, University of Pittsburgh
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38
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Sicilia A, Zhao X, Minhas DS, O'Connor EE, Aizenstein HJ, Klunk WE, Tudorascu DL, Hwang SJ. MULTI-DOMAIN LEARNING BY META-LEARNING: TAKING OPTIMAL STEPS IN MULTI-DOMAIN LOSS LANDSCAPES BY INNER-LOOP LEARNING. Proc IEEE Int Symp Biomed Imaging 2021; 2021:650-654. [PMID: 34909112 PMCID: PMC8668019 DOI: 10.1109/isbi48211.2021.9433977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
We consider a model-agnostic solution to the problem of Multi-Domain Learning (MDL) for multi-modal applications. Many existing MDL techniques are model-dependent solutions which explicitly require nontrivial architectural changes to construct domain-specific modules. Thus, properly applying these MDL techniques for new problems with well-established models, e.g. U-Net for semantic segmentation, may demand various low-level implementation efforts. In this paper, given emerging multi-modal data (e.g., various structural neuroimaging modalities), we aim to enable MDL purely algorithmically so that widely used neural networks can trivially achieve MDL in a model-independent manner. To this end, we consider a weighted loss function and extend it to an effective procedure by employing techniques from the recently active area of learning-to-learn (meta-learning). Specifically, we take inner-loop gradient steps to dynamically estimate posterior distributions over the hyperparameters of our loss function. Thus, our method is model-agnostic, requiring no additional model parameters and no network architecture changes; instead, only a few efficient algorithmic modifications are needed to improve performance in MDL. We demonstrate our solution to a fitting problem in medical imaging, specifically, in the automatic segmentation of white matter hyperintensity (WMH). We look at two neuroimaging modalities (T1-MR and FLAIR) with complementary information fitting for our problem.
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Affiliation(s)
| | - Xingchen Zhao
- Department of Computer Science, University of Pittsburgh
| | | | - Erin E O'Connor
- Department of Diagnostic Radiology & Nuclear Medicine - University of Maryland, Baltimore
| | | | | | | | - Seong Jae Hwang
- Intelligent Systems Program - University of Pittsburgh
- Department of Computer Science, University of Pittsburgh
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39
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Banihashemi L, Peng CW, Verstynen T, Wallace ML, Lamont DN, Alkhars HM, Yeh FC, Beeney JE, Aizenstein HJ, Germain A. Opposing relationships of childhood threat and deprivation with stria terminalis white matter. Hum Brain Mapp 2021; 42:2445-2460. [PMID: 33739544 PMCID: PMC8090789 DOI: 10.1002/hbm.25378] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [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: 06/18/2020] [Revised: 01/27/2021] [Accepted: 02/04/2021] [Indexed: 12/12/2022] Open
Abstract
While stress may be a potential mechanism by which childhood threat and deprivation influence mental health, few studies have considered specific stress‐related white matter pathways, such as the stria terminalis (ST) and medial forebrain bundle (MFB). Our goal was to examine the relationships between childhood adversity and ST and MFB structural integrity and whether these pathways may provide a link between childhood adversity and affective symptoms and disorders. Participants were young adults (n = 100) with a full distribution of maltreatment history and affective symptom severity. Threat was determined by measures of childhood abuse and repeated traumatic events. Socioeconomic deprivation (SED) was determined by a measure of childhood socioeconomic status (parental education). Participants underwent diffusion spectrum imaging. Human Connectome Project data was used to perform ST and MFB tractography; these tracts were used as ROIs to extract generalized fractional anisotropy (gFA) from each participant. Childhood threat was associated with ST gFA, such that greater threat was associated with less ST gFA. SED was also associated with ST gFA, however, conversely to threat, greater SED was associated with greater ST gFA. Additionally, threat was negatively associated with MFB gFA, and MFB gFA was negatively associated with post‐traumatic stress symptoms. Our results suggest that childhood threat and deprivation have opposing influences on ST structural integrity, providing new evidence that the context of childhood adversity may have an important influence on its neurobiological effects, even on the same structure. Further, the MFB may provide a novel link between childhood threat and affective symptoms.
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Affiliation(s)
- Layla Banihashemi
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Christine W Peng
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Timothy Verstynen
- Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Meredith L Wallace
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Statistics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Daniel N Lamont
- Petersen Institute of NanoScience and Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Hussain M Alkhars
- Department of Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Fang-Cheng Yeh
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Joseph E Beeney
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Anne Germain
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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40
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Jedema HP, Song X, Aizenstein HJ, Bonner AR, Stein EA, Yang Y, Bradberry CW. Long-Term Cocaine Self-administration Produces Structural Brain Changes That Correlate With Altered Cognition. Biol Psychiatry 2021; 89:376-385. [PMID: 33012519 PMCID: PMC7855373 DOI: 10.1016/j.biopsych.2020.08.008] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 08/12/2020] [Accepted: 08/13/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND An enduring question from cross-sectional clinical studies is whether the structural and functional differences often observed between cocaine users and healthy control subjects result from a history of drug use or instead reflect preexisting differences. To assess causality from drug exposure, true predrug baseline imaging and neurocognitive assessments are needed. METHODS We addressed this fundamental question of causality using longitudinal anatomical magnetic resonance imaging and neurocognitive assessments in rhesus macaques. Cognitive tasks employed were stimulus reversal learning as a measure of cognitive flexibility/inhibitory control and delayed match to sample as a measure of visual working memory. Time points examined were before and following 12 months of chronic cocaine (n = 8) or water (n = 6) self-administration. A magnetic resonance imaging-only time point was also obtained following 2 years of forced abstinence. RESULTS We identified localized patterns of gray matter density (GMD) changes that were largely concordant with cross-sectional clinical studies. These included decreases in orbitofrontal cortex, insula, amygdala, and temporal cortex. There was also a prominent increase in GMD in the caudate putamen. GMD decreases were significantly correlated with cognitive impairments across individuals only in select cortical regions. Following abstinence, changes in GMD in some regions, including the orbitofrontal cortex, insula, and amygdala, were persistent and thus may play an important role in risk of relapse following extended abstinence. CONCLUSIONS Cocaine use is causal in producing regional changes in GMD, and those changes appear to drive cognitive impairments.
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Affiliation(s)
- Hank P. Jedema
- Dept of Psychiatry, University of Pittsburgh, Pittsburgh PA, USA,Intramural Research Program, National Institute on Drug Abuse, Baltimore MD, USA
| | - Xiaowei Song
- Intramural Research Program, National Institute on Drug Abuse, Baltimore MD, USA
| | | | - Alexandra R. Bonner
- Dept of Psychiatry, University of Pittsburgh, Pittsburgh PA, USA,Current address, Cleveland Clinic Children’s Hospital
| | - Elliot A. Stein
- Intramural Research Program, National Institute on Drug Abuse, Baltimore MD, USA
| | - Yihong Yang
- Intramural Research Program, National Institute on Drug Abuse, Baltimore MD, USA
| | - Charles W. Bradberry
- Dept of Psychiatry, University of Pittsburgh, Pittsburgh PA, USA,Intramural Research Program, National Institute on Drug Abuse, Baltimore MD, USA,VA Pittsburgh Healthcare System, Pittsburgh PA, USA,corresponding author: 251 Bayview Blvd, Suite 200, Baltimore, MD 21224; ; ph: 443-740-2519
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41
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Yu GZ, Ly M, Karim HT, Muppidi N, Aizenstein HJ, Ibinson JW. Accelerated brain aging in chronic low back pain. Brain Res 2021; 1755:147263. [PMID: 33422525 DOI: 10.1016/j.brainres.2020.147263] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [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: 09/24/2020] [Revised: 11/20/2020] [Accepted: 12/20/2020] [Indexed: 12/15/2022]
Abstract
Chronic low back pain (CLBP) is a leading cause of disability and is associated with neurodegenerative changes in brain structure. These changes lead to impairments in cognitive function and are consistent with those seen in aging, suggesting an accelerated aging pattern. In this study we assessed this using machine-learning estimated brain age (BA) as a holistic metric of morphometric changes associated with aging. Structural imaging data from 31 non-depressed CLBP patients and 32 healthy controls from the Pain and Interoception Imaging Network were included. Using our previously developed algorithm, we estimated BA per individual based on grey matter density. We then conducted multivariable linear modeling for effects of group, chronological age, and their interaction on BA. We also performed two voxel-wise analyses comparing grey matter density between CLBP and control individuals and the association between gray matter density and BA. There was an interaction between CLBP and greater chronological age on BA such that the discrepancy in BA between healthy and CLBP individuals was greater for older individuals. In CLBP individuals, BA was not associated with sex, current level of pain, duration of CLBP, or mild to moderate depressive symptoms. CLBP individuals had lower cerebellar grey matter density compared to healthy individuals. Brain age was associated with lower gray matter density in numerous brain regions. CLBP was associated with greater BA, which was more profound in later life. BA as a holistic metric was sensitive to differences in gray matter density in numerous regions which eluded direct comparison between groups.
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Affiliation(s)
- Gary Z Yu
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Maria Ly
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
| | - Helmet T Karim
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nishita Muppidi
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Howard J Aizenstein
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - James W Ibinson
- Department of Anesthesiology, University of Pittsburgh, Pittsburgh, PA, USA.
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42
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Godina SL, Rosano C, Gianaros P, Aizenstein HJ, Carlson MC, Rosso AL. What factors explain racial differences in memory‐related gray matter volume regions of interest among cognitively normal older adults? Alzheimers Dement 2020. [DOI: 10.1002/alz.047637] [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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43
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Minhas DS, Ghodadra A, Yu Z, Royse SK, Aizenstein HJ, Cohen A, Tudorascu DL, Lopresti BJ, Mathis C, Klunk WE, Laymon CM. Evaluation of amyloid and tau PET quantitation methods using a 3D‐printed anatomically accurate brain phantom. Alzheimers Dement 2020. [DOI: 10.1002/alz.045455] [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: 11/09/2022]
Affiliation(s)
| | - Anish Ghodadra
- University of Pittsburgh School of Medicine Pittsburgh PA USA
| | - Zheming Yu
- University of Pittsburgh School of Medicine Pittsburgh PA USA
| | - Sarah K Royse
- University of Pittsburgh School of Medicine Pittsburgh PA USA
| | | | - Ann Cohen
- University of Pittsburgh School of Medicine Pittsburgh PA USA
| | | | | | - Chester Mathis
- University of Pittsburgh School of Medicine Pittsburgh PA USA
| | - William E Klunk
- University of Pittsburgh School of Medicine Pittsburgh PA USA
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44
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Schroeder RA, Thurston RC, Wu M, Aizenstein HJ, Derby CA, Maki PM. Distinctive roles of estrone and estradiol in shaping verbal memory circuitry in postmenopausal women. Alzheimers Dement 2020. [DOI: 10.1002/alz.043110] [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: 11/09/2022]
Affiliation(s)
| | | | - Minjie Wu
- University of Pittsburgh School of Medicine Pittsburgh PA USA
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45
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Karim HT, Rosso A, Aizenstein HJ, Bohnen NI, Studenski S, Rosano C. Resting state connectivity within the basal ganglia and gait speed in older adults with cerebral small vessel disease and locomotor risk factors. Neuroimage Clin 2020; 28:102401. [PMID: 32932053 PMCID: PMC7495101 DOI: 10.1016/j.nicl.2020.102401] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [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: 01/22/2020] [Revised: 07/31/2020] [Accepted: 08/25/2020] [Indexed: 12/19/2022]
Abstract
BACKGROUND AND AIM The basal ganglia are critical for planned locomotion, but their role in age-related gait slowing is not well known. Spontaneous regional co-activation of brain activity at rest, known as resting state connectivity, is emerging as a biomarker of functional neural specialization of varying human processes, including gait. We hypothesized that greater connectivity amongst regions of the basal ganglia would be associated with faster gait speed in the elderly. We further investigated whether this association was similar in strength to that of other risk factors for gait slowing, specifically white matter hyperintensities (WMH). METHODS A cohort of 269 adults (79-90 years, 146 females, 164 White) were assessed for gait speed (m/sec) via stopwatch; brain activation during resting state functional magnetic resonance imaging, WMH, and gray matter volume (GMV) normalized by intracranial volume via 3T neuroimaging; and risk factors of poorer locomotion via clinical exams (body mass index (BMI), muscle strength, vision, musculoskeletal pain, cardiometabolic conditions, depressive symptoms, and cognitive function). To understand whether basal ganglia connectivity shows distinct clusters of connectivity, we conducted a k-means clustering analysis of regional co-activation among the substantia nigra, nucleus accumbens, subthalamic nucleus, putamen, pallidum, and caudate. We conducted two multivariable linear regression models: (1) with gait speed as the dependent variable and connectivity, demographics, WMH, GMV, and locomotor risk factors as independent variables and (2) with basal ganglia connectivity as the dependent variable and demographics, WMH, GMV, and locomotor risk factors as independent variables. RESULTS We identified two clusters of basal ganglia connectivity: high and low without a distinct spatial distribution allowing us to compute an average connectivity index of the entire basal ganglia regional connectivity (representing a continuous measure). Lower connectivity was associated with slower gait, independent of other locomotor risk factors, including WMH; the coefficient of this association was similar to those of other locomotor risk factors. Lower connectivity was significantly associated with lower BMI and greater WMH. CONCLUSIONS Lower resting state basal ganglia connectivity is associated with slower gait speed. Its contribution appears comparable to WMH and other locomotor risk factors. Future studies should assess whether promoting higher basal ganglia connectivity in older adults may reduce age-related gait slowing.
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Affiliation(s)
- H T Karim
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States.
| | - A Rosso
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, United States
| | - H J Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - N I Bohnen
- Departments of Radiology & Neurology, University of Michigan, Ann Arbor, MI, United States; Neurology Service & Geriatric Research Education and Clinical Center, VA Ann Arbor Healthcare System, Ann Arbor, MI, United States
| | - S Studenski
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - C Rosano
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, United States
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46
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Snitz BE, Chang Y, Tudorascu DL, Lopez OL, Lopresti BJ, DeKosky ST, Carlson MC, Cohen AD, Kamboh MI, Aizenstein HJ, Klunk WE, Kuller LH. Predicting resistance to amyloid-beta deposition and cognitive resilience in the oldest-old. Neurology 2020; 95:e984-e994. [PMID: 32699143 PMCID: PMC7668550 DOI: 10.1212/wnl.0000000000010239] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Accepted: 02/20/2020] [Indexed: 01/05/2023] Open
Abstract
OBJECTIVE To explore long-term predictors of avoiding β-amyloid (Aβ) deposition and maintaining unimpaired cognition as outcomes in the oldest old. METHODS In a longitudinal observational cohort study, 100 former participants of the Ginkgo Evaluation of Memory Study (GEMS; 2000-2008) completed biannual Pittsburgh compound B-PET imaging and annual clinical-cognitive evaluations beginning in 2010. Most recent Aβ status and cognitive status were selected for each participant. Longitudinal outcomes included change in serial Aβ and cognitive tests. Baseline predictors from GEMS included neuropsychological tests, daily functioning, APOE genotype, lifestyle variables, occupational measures, health history, sleep, subjective memory, physical and cognitive activities, depressive symptoms, and physical performance and health indices, among others. RESULTS Mean age at the last cognitive evaluation was 92.0 (range 86-100) years. Mean follow-up time from baseline to last measured Aβ status was 12.3 (SD 1.9) years and to last cognitive evaluation was 14.1 (SD 1.9) years. The APOE*2 allele predicted last Aβ status (n = 34 Aβ negative vs n = 66 Aβ positive). Baseline cognition predicted cognitive status (n = 30 unimpaired vs n = 70 impaired). Predictors of cognitive status among Aβ-positive participants only (n = 14 normal cognition vs n = 52 impaired) were baseline cognitive test scores and smoking history. Baseline pulse pressure predicted longitudinal Aβ increase; paid work engagement and life satisfaction predicted less cognitive decline. CONCLUSIONS The APOE*2 allele and lower pulse pressure predict resistance to Aβ deposition in advanced aging. Cognitive test scores 14 years prior, likely reflecting premorbid abilities, predict cognitive status and maintenance of unimpaired cognition in the presence of Aβ. Several lifestyle factors appear protective.
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Affiliation(s)
- Beth E Snitz
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
| | - Yuefang Chang
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Dana L Tudorascu
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Oscar L Lopez
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Brian J Lopresti
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Steven T DeKosky
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Michelle C Carlson
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Ann D Cohen
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - M Ilyas Kamboh
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Howard J Aizenstein
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - William E Klunk
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Lewis H Kuller
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
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Smagula SF, Karim HT, Ibrahim TS, Krafty RT, Stahl ST, Rodakowski J, Reynolds CF, Hall MH, Aizenstein HJ. Resting-State Function Connectivity Associated With Being a "Morning-Type" Dementia Caregiver and Having Lower Depression Symptom Severity. J Gerontol B Psychol Sci Soc Sci 2020; 76:1071-1076. [PMID: 32750139 DOI: 10.1093/geronb/gbaa115] [Citation(s) in RCA: 4] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Indexed: 01/22/2023] Open
Abstract
OBJECTIVES A lack of "morningness" predicts greater depression symptom severity over time, including in a vulnerable group of older adults: family dementia caregivers (dCGs). Evidence regarding the neurobiological basis of these correlations is needed to guide future research towards biomarker-informed detection and prevention approaches. We therefore primarily aimed to identify simple resting-state biomarkers that correlated with a lack of "morningness" in dCGs. METHOD We examined 54 dCGs (mean age = 70, range: 61-84; 70% female) of whom 40% were definite "morning types" according to Composite Scale of Morningness (CSM). Using a 7 Tesla resting-state sequence, we compared the functional connectivity of nodes in networks previously implicated in depression (fronto-parietal, default mode, limbic, and salience) between caregivers who were and were not "morning types." RESULTS Correcting for voxel-wise comparisons, "morning-type" dCGs had less amygdala-posterior cingulate connectivity (Cohen's d = -1.3), which statistically mediated ~32% of the association between the degree of "morningness" and lower depression severity. Post hoc analyses of CSM items found significant correlations, with both amygdala-posterior cingulate FC and depression severity, for 4/6 items pertaining to difficulty, 2/5 items pertaining to preference, and 0/2 items pertaining to typical patterns. DISCUSSION Prior research shows that amygdala-posterior cingulate connectivity increases when allocating attention to peripheral aspects of negative emotional stimuli. As such, difficulty with morning activation may relate to the ongoing direction of focus around distressing content; in contrast, morning activity participation may serve to limit focus on distress. Replication and experimental studies are required to confirm these associations and their modifiability.
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Affiliation(s)
- Stephen F Smagula
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pennsylvania
| | - Helmet T Karim
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pennsylvania
| | - Tamer S Ibrahim
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pennsylvania
| | - Robert T Krafty
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pennsylvania
| | - Sarah T Stahl
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pennsylvania
| | - Juleen Rodakowski
- Department of Occupational Therapy, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pennsylvania
| | - Charles F Reynolds
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pennsylvania
| | - Martica H Hall
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pennsylvania
| | - Howard J Aizenstein
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pennsylvania
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48
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Nadkarni NK, Tudorascu D, Campbell E, Snitz BE, Cohen AD, Halligan E, Mathis CA, Aizenstein HJ, Klunk WE. Association Between Amyloid-β, Small-vessel Disease, and Neurodegeneration Biomarker Positivity, and Progression to Mild Cognitive Impairment in Cognitively Normal Individuals. J Gerontol A Biol Sci Med Sci 2020; 74:1753-1760. [PMID: 30957843 DOI: 10.1093/gerona/glz088] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [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: 08/27/2018] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND We estimated the prevalence and incidence of amyloid-β deposition (A), small-vessel disease (V), and neurodegeneration (N) biomarker positivity in community-dwelling cognitively normal individuals (CN). We determined the longitudinal association between the respective biomarker indices with progression to all-cause mild cognitive impairment (MCI) and its amnestic and nonamnestic subtypes. METHODS CN participants, recruited by advertising, underwent brain [C-11]Pittsburgh Compound-B (PiB)-positron emission tomography (PET), magnetic resonance imaging, and [F-18]fluoro-2-deoxy-glucose (FDG)-PET, and were designated as having high or low amyloid-β (A+/A-), greater or lower white matter hyperintensities burden (V+/V-) and diminished or normal cortical glucose metabolism (N+/N-). MCI was adjudicated using clinical assessments. We examined the association between A, V, and N biomarker positivity at study baseline and endpoint, with progression to MCI using linear regression, Cox proportional hazards and Kaplan-Meier analyses adjusted for age and APOE-ε4 carrier status. RESULTS In 98 CN individuals (average age 74 years, 65% female), A+, V+, and N+ prevalence was 26%, 33%, and 8%, respectively. At study endpoint (median: 5.5 years), an A+, but not a V+ or N+ scan, was associated with higher odds of all-cause MCI (Chi-square = 3.9, p = .048, odds ratio, 95% confidence interval = 2.6 [1.01-6.8]). Baseline A+, V+, or N+ were not associated with all-cause MCI, however, baseline A+ (p = .018) and A+N+ (p = .049), and endpoint A+N+ (p = .025) were associated with time to progression to amnestic, not nonamnestic, MCI. CONCLUSION Longitudinal assessments clarify the association between amyloid-β and progression to all-cause MCI in CN individuals. The association between biomarker positivity indices of amyloid-β and neurodegeneration, and amnestic MCI reflects the underlying pathology involved in the progression to prodromal Alzheimer's disease.
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Affiliation(s)
- Neelesh K Nadkarni
- Division of Geriatric Medicine, Department of Medicine, University of Pittsburgh, Pennsylvania.,Department of Neurology, University of Pittsburgh, Pennsylvania
| | - Dana Tudorascu
- Division of General Internal Medicine, Department of Medicine, University of Pittsburgh, Pennsylvania.,Department of Biostatistics, University of Pittsburgh, Pennsylvania.,Department of Psychiatry, University of Pittsburgh, Pennsylvania
| | | | - Beth E Snitz
- Department of Neurology, University of Pittsburgh, Pennsylvania
| | - Annie D Cohen
- Department of Psychiatry, University of Pittsburgh, Pennsylvania
| | - Edye Halligan
- Department of Psychiatry, University of Pittsburgh, Pennsylvania
| | | | | | - William E Klunk
- Department of Neurology, University of Pittsburgh, Pennsylvania.,Department of Psychiatry, University of Pittsburgh, Pennsylvania
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49
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Snitz BE, Tudorascu DL, Yu Z, Campbell E, Lopresti BJ, Laymon CM, Minhas DS, Nadkarni NK, Aizenstein HJ, Klunk WE, Weintraub S, Gershon RC, Cohen AD. Associations between NIH Toolbox Cognition Battery and in vivo brain amyloid and tau pathology in non-demented older adults. Alzheimers Dement (Amst) 2020; 12:e12018. [PMID: 32426450 PMCID: PMC7228102 DOI: 10.1002/dad2.12018] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [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: 09/19/2019] [Revised: 01/13/2020] [Accepted: 01/23/2020] [Indexed: 12/04/2022]
Abstract
INTRODUCTION The National Institutes of Health (NIH) Toolbox Cognition Battery (NIHTB-CB) was developed to be a common assessment metric across a broad array of research studies. We investigated associations between NIHTB-CB and brain amyloid and tau deposition in cognitively unimpaired older adults. METHODS One hundred eighteen community-based volunteers completed magnetic resonance imaging (MRI), Pittsburgh compound B (PiB)-PET (positron emission tomography) and AV-1451-PET neuroimaging, a neuropsychological evaluation, NIHTB-CB, and the Clinical Dementia Rating (CDR) scale. Demographically adjusted regression models evaluated cognition-biomarker associations; standardized effect sizes allowed comparison of association strength across measures. RESULTS No NIHTB-CB measures were associated with amyloid deposition. NIHTB-CB measures of fluid cognition, including Pattern Comparison Processing Speed, Dimensional Change Card Sort, and Fluid Cognition Composite, were associated with tau deposition in higher Braak regions. Pattern Comparison Processing Speed was the most robust association with sensitivity analyses. DISCUSSION NIHTB-CB tasks of processing speed and executive functions may be sensitive to pathologic tau deposition on imaging in normal aging.
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Affiliation(s)
- Beth E. Snitz
- Department of NeurologyUniversity of PittsburghSchool of MedicinePittsburghPennsylvania
| | - Dana L. Tudorascu
- Department of MedicineUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
| | - Zheming Yu
- Department of RadiologyUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
| | - Elizabeth Campbell
- Department of RadiologyUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
| | - Brian J. Lopresti
- Department of RadiologyUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
| | - Charles M. Laymon
- Department of RadiologyUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
- Department of BioengineeringUniversity of Pittsburgh School of EngineeringPittsburghPennsylvania
| | - Davneet S. Minhas
- Department of RadiologyUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
| | - Neelesh K. Nadkarni
- Department of MedicineUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
| | - Howard J. Aizenstein
- Department of BioengineeringUniversity of Pittsburgh School of EngineeringPittsburghPennsylvania
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
| | - William E. Klunk
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
| | - Sandra Weintraub
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinois
| | - Richard C. Gershon
- Department of Medical Social SciencesNorthwestern University Feinberg School of MedicineChicagoIllinois
| | - Ann D. Cohen
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
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50
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Cui C, Birru RL, Snitz BE, Ihara M, Kakuta C, Lopresti BJ, Aizenstein HJ, Lopez OL, Mathis CA, Miyamoto Y, Kuller LH, Sekikawa A. Effects of soy isoflavones on cognitive function: a systematic review and meta-analysis of randomized controlled trials. Nutr Rev 2020; 78:134-144. [PMID: 31504836 PMCID: PMC7808187 DOI: 10.1093/nutrit/nuz050] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [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: 01/10/2023] Open
Abstract
CONTEXT The results of preclinical and observational studies support the beneficial effect of soy isoflavones on cognition. OBJECTIVE This review aimed to evaluate the effects of soy isoflavones on cognition in adults. DATA SOURCES The PUBMED, EMBASE, Ovid Medline, Cochrane Library, and clinicaltrials.gov databases were searched. STUDY SELECTION Two researchers independently screened 1955 records, using the PICOS criteria: participants were adults; intervention was dietary sources with soy isoflavones or isolated soy isoflavones; comparator was any comparator; outcome was cognitive function; study type was randomized controlled trials (RCTs). A third researcher was consulted to resolve any discrepancies. Sixteen RCTs were included and their quality assessed. DATA EXTRACTION Information on study design, characteristics of participants, and outcomes was extracted. PRISMA guidelines were followed. DATA ANALYSIS A random-effects meta-analysis was used to pool estimates across studies. In the 16 RCTs (1386 participants, mean age = 60 y), soy isoflavones were found to improve overall cognitive function (standardized mean difference [SMD], 0.19; 95% confidence interval [CI], 0.07-0.32) and memory (SMD, 0.15; 95%CI, 0.03-0.26). CONCLUSION The results showed that soy isoflavones may improve cognitive function in adults. SYSTEMATIC REVIEW REGISTRATION PROSPERO registration no. CRD42018082070.
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Affiliation(s)
- Chendi Cui
- C. Cui, L. Kuller, and A. Sekikawa are with the Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Rahel L Birru
- R. Birru is with the Department of Environmental and Occupational Health, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Beth E Snitz
- B. Snitz and O. Lopez are with the Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Masafumi Ihara
- M. Ihara, A. Higashiyama, C. Kakuta, and Y. Miyamoto are with the National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Chikage Kakuta
- M. Ihara, A. Higashiyama, C. Kakuta, and Y. Miyamoto are with the National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Brian J Lopresti
- B. Lopresti and C. Mathis are with the Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Howard J Aizenstein
- H. Aizenstein is with the Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Oscar L Lopez
- B. Snitz and O. Lopez are with the Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Chester A Mathis
- B. Lopresti and C. Mathis are with the Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Yoshihiro Miyamoto
- M. Ihara, A. Higashiyama, C. Kakuta, and Y. Miyamoto are with the National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Lewis H Kuller
- C. Cui, L. Kuller, and A. Sekikawa are with the Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Akira Sekikawa
- C. Cui, L. Kuller, and A. Sekikawa are with the Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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