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Canli U, Aldhahi MI, Küçük H. Association of Physiological Performance, Physical Fitness, and Academic Achievement in Secondary School Students. CHILDREN (BASEL, SWITZERLAND) 2024; 11:396. [PMID: 38671613 PMCID: PMC11049434 DOI: 10.3390/children11040396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2024] [Revised: 03/23/2024] [Accepted: 03/23/2024] [Indexed: 04/28/2024]
Abstract
This study aimed to compare the physiological performance and physical fitness based on the academic achievement levels of secondary school students and to explore the effect of gender on the relationship between physiological performance, physical fitness, and academic achievement. In this cross-sectional study, 304 children aged 13-14 years were recruited. To assess physical fitness, students performed a 20 m sprint test, a pro-agility test, a one-mile endurance run/walk test, and a countermovement jump test. At the end of the one-mile endurance run/walk test, the estimated VO2peak value of the participants was calculated. The physiological performance of the students was determined by measuring their resting heart rate and blood pressure. Students were grouped into three categories based on their academic achievement levels. The assessment of academic achievement considered their scores from the previous academic year. The scores were divided into three levels: poor (average score of 69 points or less), average (scores ranging from 70 to 84 points), and good (scores of 85 points or higher). The study revealed a notable disparity among students' VO2Max measurements based on their academic achievement (F = 8.938, p < 0.001, η2 = 0.056). However, we observed that the group with poor academic achievement displayed lower diastolic blood pressure values than the groups with average and good performances. Finally, no significant gender differences were evident in the relationship between academic achievement and any of the physical and physiological parameters.
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Affiliation(s)
- Umut Canli
- Sports Science Faculty, Tekirdag Namik Kemal University, Suleymanpasa, Tekirdag 59010, Turkey;
| | - Monira I. Aldhahi
- Department of Rehabilitation Sciences, College of Health and Rehabilitation Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
| | - Hamza Küçük
- Yasar Dogu Faculty of Sport Sciences, Ondokuz Mayıs University, Samsun 55270, Turkey;
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Haddad E, Matloff W, Park G, Liu M, Jahanshad N, Kim HS. Subclinical variations on ECG and their associations with structural brain aging networks. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.18.24304486. [PMID: 38562784 PMCID: PMC10984068 DOI: 10.1101/2024.03.18.24304486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Impaired cardiac function is associated with cognitive impairment and brain imaging features of aging. Cardiac arrhythmias, including atrial fibrillation, are implicated in clinical and subclinical brain injuries. Even in the absence of a clinical diagnosis, subclinical or prodromal substrates of arrhythmias, including an abnormally long or short P-wave duration (PWD), a measure associated with atrial abnormalities, have been associated with stroke and cognitive decline. However, the extent to which PWD has subclinical influences on overall aging patterns of the brain is not clearly understood. Here, using neuroimaging and ECG data from the UK Biobank, we use a novel regional "brain age" method to identify the brain aging networks associated with abnormal PWD. We find that PWD is inversely associated with accelerated brain aging in the sensorimotor, frontoparietal, ventral attention, and dorsal attention networks, even in the absence of overt cardiac diseases. These findings suggest that detrimental aging outcomes may result from subclinically abnormal PWD.
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Affiliation(s)
- Elizabeth Haddad
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Imaging Genetics Center, University of Southern California, Marina Del Rey, CA, USA
| | - William Matloff
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Gilsoon Park
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Mengting Liu
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Neda Jahanshad
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Imaging Genetics Center, University of Southern California, Marina Del Rey, CA, USA
| | - Ho Sung Kim
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
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Rasser PE, Ehlkes T, Schall U. Fronto-temporal cortical grey matter thickness and surface area in the at-risk mental state and recent-onset schizophrenia: a magnetic resonance imaging study. BMC Psychiatry 2024; 24:33. [PMID: 38191320 PMCID: PMC10775434 DOI: 10.1186/s12888-024-05494-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Accepted: 01/02/2024] [Indexed: 01/10/2024] Open
Abstract
BACKGROUND Studies to date examining cortical thickness and surface area in young individuals At Risk Mental State (ARMS) of developing psychosis have revealed inconsistent findings, either reporting increased, decreased or no differences compared to mentally healthy individuals. The inconsistencies may be attributed to small sample sizes, varying age ranges, different ARMS identification criteria, lack of control for recreational substance use and antipsychotic pharmacotherapy, as well as different methods for deriving morphological brain measures. METHODS A surfaced-based approach was employed to calculate fronto-temporal cortical grey matter thickness and surface area derived from magnetic resonance imaging (MRI) data collected from 44 young antipsychotic-naïve ARMS individuals, 19 young people with recent onset schizophrenia, and 36 age-matched healthy volunteers. We conducted group comparisons of the morphological measures and explored their association with symptom severity, global and socio-occupational function levels, and the degree of alcohol and cannabis use in the ARMS group. RESULTS Grey matter thickness and surface areas in ARMS individuals did not significantly differ from their age-matched healthy counterparts. However, reduced left-frontal grey matter thickness was correlated with greater symptom severity and lower function levels; the latter being also correlated with smaller left-frontal surface areas. ARMS individuals with more severe symptoms showed greater similarities to the recent onset schizophrenia group. The morphological measures in ARMS did not correlate with the lifetime level of alcohol or cannabis use. CONCLUSIONS Our findings suggest that a decline in function levels and worsening mental state are associated with morphological changes in the left frontal cortex in ARMS but to a lesser extent than those seen in recent onset schizophrenia. Alcohol and cannabis use did not confound these findings. However, the cross-sectional nature of our study limits our ability to draw conclusions about the potential progressive nature of these morphological changes in ARMS.
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Affiliation(s)
- Paul E Rasser
- Centre for Brain & Mental Health Research, The University of Newcastle, Waratah, NSW, 2298, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, 2305, Australia
| | - Tim Ehlkes
- Centre for Brain & Mental Health Research, The University of Newcastle, Waratah, NSW, 2298, Australia
| | - Ulrich Schall
- Centre for Brain & Mental Health Research, The University of Newcastle, Waratah, NSW, 2298, Australia.
- Hunter Medical Research Institute, New Lambton Heights, NSW, 2305, Australia.
- Centre for Brain & Mental Health Research, McAuley Centre, Mater Hospital, Waratah, NSW, 2298, Australia.
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Gadde KM, Yin X, Goldberg RB, Orchard TJ, Schlögl M, Dabelea D, Ibebuogu UN, Watson KE, Pi‐Sunyer FX, Crandall JP, Temprosa M, Luchsinger JA. Coronary Artery Calcium and Cognitive Decline in the Diabetes Prevention Program Outcomes Study. J Am Heart Assoc 2023; 12:e029671. [PMID: 37929764 PMCID: PMC10727391 DOI: 10.1161/jaha.123.029671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 09/26/2023] [Indexed: 11/07/2023]
Abstract
Background Our aim was to investigate the association of coronary artery calcium (CAC) with cognitive function in adults with impaired glucose tolerance or type 2 diabetes. Methods and Results The Diabetes Prevention Program was a randomized controlled trial comparing an intensive lifestyle intervention, metformin, or placebo for prevention of type 2 diabetes among patients with prediabetes. After 3 years, intensive lifestyle intervention and placebo were stopped, the metformin arm was unmasked, and participants continued in the DPPOS (Diabetes Prevention Program Outcomes Study). Approximately 14 years after randomization (Y14), CAC (Agatston score) was assessed with computed tomography, and cognitive performance was assessed with the Spanish English Verbal Learning Test (SEVLT) and Digit Symbol Substitution Test. SEVLT and Digit Symbol Substitution Test were reassessed 5 years later (Y19) along with the Modified Mini-Mental State Exam. We examined cross-sectional and longitudinal associations between CAC and cognition among 1931 participants using linear and logistic regression. In unadjusted analyses, compared with no calcification, CAC score >300 was associated with decreased performance on all cognitive tests at Y14 in both sexes. Additionally, CAC >300 was associated with a greater 5-year decline in SEVLT Immediate Recall in both sexes and SEVLT Delayed Recall in women. After adjustment for demographic, genetic, metabolic, vascular, and behavioral covariates, CAC score >300 remained associated with greater decline in only SEVLT Delayed Recall in women. Conclusions In women with prediabetes or diabetes, CAC >300, compared with no calcification, was independently associated with greater decline in verbal memory. Registration information clinicaltrials.gov. Identifier: NCT00038727.
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Affiliation(s)
- Kishore M. Gadde
- Department of SurgeryUniversity of California, Irvine (UCI) Medical CenterOrangeCA
| | - Xiaoyan Yin
- Department of Biostatistics and BioinformaticsGeorge Washington University Biostatistics CenterRockvilleMD
| | - Ronald B. Goldberg
- Diabetes Research Institute, University of Miami Miller School of MedicineMiamiFL
| | | | - Mathias Schlögl
- Division of Geriatric Medicine, Clinic BarmelweidBarmelweidSwitzerland
| | - Dana Dabelea
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) CenterUniversity of Colorado Anschutz Medical CampusAuroraCO
| | - Uzoma N. Ibebuogu
- Department of MedicineUniversity of Tennessee Health Science CenterMemphisTN
| | - Karol E. Watson
- Department of Medicine, David Geffen School of Medicine at UCLALos AngelesCA
| | | | - Jill P. Crandall
- Department of Medicine, Albert Einstein College of MedicineBronxNY
| | - Marinella Temprosa
- Department of Biostatistics and BioinformaticsGeorge Washington University Biostatistics CenterRockvilleMD
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White KS, Walker JA, Wang J, Autissier P, Miller AD, Abuelezan NN, Burrack R, Li Q, Kim WK, Williams KC. Simian immunodeficiency virus-infected rhesus macaques with AIDS co-develop cardiovascular pathology and encephalitis. Front Immunol 2023; 14:1240946. [PMID: 37965349 PMCID: PMC10641955 DOI: 10.3389/fimmu.2023.1240946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 10/03/2023] [Indexed: 11/16/2023] Open
Abstract
Despite effective antiretroviral therapy, HIV co-morbidities remain where central nervous system (CNS) neurocognitive disorders and cardiovascular disease (CVD)-pathology that are linked with myeloid activation are most prevalent. Comorbidities such as neurocogntive dysfunction and cardiovascular disease (CVD) remain prevalent among people living with HIV. We sought to investigate if cardiac pathology (inflammation, fibrosis, cardiomyocyte damage) and CNS pathology (encephalitis) develop together during simian immunodeficiency virus (SIV) infection and if their co-development is linked with monocyte/macrophage activation. We used a cohort of SIV-infected rhesus macaques with rapid AIDS and demonstrated that SIV encephalitis (SIVE) and CVD pathology occur together more frequently than SIVE or CVD pathology alone. Their co-development correlated more strongly with activated myeloid cells, increased numbers of CD14+CD16+ monocytes, plasma CD163 and interleukin-18 (IL-18) than did SIVE or CVD pathology alone, or no pathology. Animals with both SIVE and CVD pathology had greater numbers of cardiac macrophages and increased collagen and monocyte/macrophage accumulation, which were better correlates of CVD-pathology than SIV-RNA. Animals with SIVE alone had higher levels of activated macrophage biomarkers and cardiac macrophage accumulation than SIVnoE animals. These observations were confirmed in HIV infected individuals with HIV encephalitis (HIVE) that had greater numbers of cardiac macrophages and fibrosis than HIV-infected controls without HIVE. These results underscore the notion that CNS and CVD pathologies frequently occur together in HIV and SIV infection, and demonstrate an unmet need for adjunctive therapies targeting macrophages.
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Affiliation(s)
- Kevin S. White
- Department of Biology, Boston College, Chestnut Hill, MA, United States
| | - Joshua A. Walker
- Department of Biology, Boston College, Chestnut Hill, MA, United States
| | - John Wang
- Department of Biology, Boston College, Chestnut Hill, MA, United States
| | - Patrick Autissier
- Department of Biology, Boston College, Chestnut Hill, MA, United States
| | - Andrew D. Miller
- Department of Biomedical Sciences, Section of Anatomic Physiology, Cornell University College of Veterinary Medicine, Ithaca, NY, United States
| | - Nadia N. Abuelezan
- Connel School of Nursing, Boston College, Chestnut Hill, MA, United States
| | - Rachel Burrack
- Nebraska Center for Virology, School of Biological Sciences, University of Nebraska-Lincoln, Lincoln, NE, United States
| | - Qingsheng Li
- Nebraska Center for Virology, School of Biological Sciences, University of Nebraska-Lincoln, Lincoln, NE, United States
| | - Woong-Ki Kim
- Division of Microbiology, Tulane National Primate Research Center, Covington, LA, United States
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Richter M, Widera S, Malz F, Goltermann J, Steinmann L, Kraus A, Enneking V, Meinert S, Repple J, Redlich R, Leehr EJ, Grotegerd D, Dohm K, Kugel H, Bauer J, Arolt V, Dannlowski U, Opel N. Higher body weight-dependent neural activation during reward processing. Brain Imaging Behav 2023; 17:414-424. [PMID: 37012575 PMCID: PMC10435630 DOI: 10.1007/s11682-023-00769-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/21/2023] [Indexed: 04/05/2023]
Abstract
Obesity is associated with alterations in brain structure and function, particularly in areas related to reward processing. Although brain structural investigations have demonstrated a continuous association between higher body weight and reduced gray matter in well-powered samples, functional neuroimaging studies have typically only contrasted individuals from the normal weight and obese body mass index (BMI) ranges with modest sample sizes. It remains unclear, whether the commonly found hyperresponsiveness of the reward circuit can (a) be replicated in well-powered studies and (b) be found as a function of higher body weight even below the threshold of clinical obesity. 383 adults across the weight spectrum underwent functional magnetic resonance imaging during a common card-guessing paradigm simulating monetary reward. Multiple regression was used to investigate the association of BMI and neural activation in the reward circuit. In addition, a one-way ANOVA model comparing three weight groups (normal weight, overweight, obese) was calculated. Higher BMI was associated with higher reward response in the bilateral insula. This association could no longer be found when participants with obesity were excluded from the analysis. The ANOVA revealed higher activation in obese vs. lean, but no difference between lean and overweight participants. The overactivation of reward-related brain areas in obesity is a consistent finding that can be replicated in large samples. In contrast to brain structural aberrations associated with higher body weight, the neurofunctional underpinnings of reward processing in the insula appear to be more pronounced in the higher body weight range.
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Affiliation(s)
- Maike Richter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry, Jena University Hospital/Friedrich-Schiller-University Jena, Jena, Germany
| | - Sophia Widera
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Franziska Malz
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Janik Goltermann
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Lavinia Steinmann
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Anna Kraus
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Verena Enneking
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department for Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| | - Ronny Redlich
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychology, Martin-Luther University of Halle, Halle, Germany
- German Center for Mental Health (DZPG), Jena-Magdeburg-Halle, Germany
- Center for Intervention and Research on Adaptive and Maladaptive Brain Circuits Underlying Mental Health (C-I-R-C), Jena-Magdeburg-Halle, Germany
| | - Elisabeth J Leehr
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Dohm
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Harald Kugel
- University Clinic for Radiology, University of Münster, Münster, Germany
| | - Jochen Bauer
- University Clinic for Radiology, University of Münster, Münster, Germany
| | - Volker Arolt
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Nils Opel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany.
- Department of Psychiatry, Jena University Hospital/Friedrich-Schiller-University Jena, Jena, Germany.
- German Center for Mental Health (DZPG), Jena-Magdeburg-Halle, Germany.
- Center for Intervention and Research on Adaptive and Maladaptive Brain Circuits Underlying Mental Health (C-I-R-C), Jena-Magdeburg-Halle, Germany.
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Bherer L, Besnier F, Blanchette CA. Benefits of Cardiac Rehabilitation Programs, Physical Exercise, and Cognitive Training on Cognitive Deficits in Cardiovascular Diseases. Can J Cardiol 2023; 39:222-224. [PMID: 36336307 DOI: 10.1016/j.cjca.2022.10.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 10/24/2022] [Accepted: 10/29/2022] [Indexed: 11/06/2022] Open
Affiliation(s)
- Louis Bherer
- Research Center and Centre ÉPIC, Montreal Heart Institute, Montréal, Quebec, Canada; Department of Medicine, Faculty of Medicine, Université de Montréal, Montréal, Quebec, Canada; Research Center, Institut Universitaire de Gériatrie de Montréal, Montréal, Quebec, Canada.
| | - Florent Besnier
- Research Center and Centre ÉPIC, Montreal Heart Institute, Montréal, Quebec, Canada; Department of Medicine, Faculty of Medicine, Université de Montréal, Montréal, Quebec, Canada
| | - Caroll-Ann Blanchette
- Research Center and Centre ÉPIC, Montreal Heart Institute, Montréal, Quebec, Canada; Department of Medicine, Faculty of Medicine, Université de Montréal, Montréal, Quebec, Canada
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Lie IA, Wesnes K, Kvistad SS, Brouwer I, Wergeland S, Holmøy T, Midgard R, Bru A, Edland A, Eikeland R, Gosal S, Harbo HF, Kleveland G, Sørenes YS, Øksendal N, Barkhof F, Vrenken H, Myhr KM, Bø L, Torkildsen Ø. The Effect of Smoking on Long-term Gray Matter Atrophy and Clinical Disability in Patients with Relapsing-Remitting Multiple Sclerosis. NEUROLOGY - NEUROIMMUNOLOGY NEUROINFLAMMATION 2022; 9:9/5/e200008. [PMID: 35738901 PMCID: PMC9223432 DOI: 10.1212/nxi.0000000000200008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 05/06/2022] [Indexed: 11/15/2022]
Abstract
Background and Objectives The relationship between smoking, long-term brain atrophy, and clinical disability in patients with multiple sclerosis (MS) is unclear. Here, we assessed long-term effects of smoking by evaluating MRI and clinical outcome measures after 10 years in smoking and nonsmoking patients with relapsing-remitting MS (RRMS). Methods We included 85 treatment-naive patients with RRMS with recent inflammatory disease activity who participated in a 10-year follow-up visit after a multicenter clinical trial of 24 months. Smoking status was decided for each patient by 2 separate definitions: by serum cotinine levels measured regularly for the first 2 years of the follow-up (during the clinical trial) and by retrospective patient self-reporting. At the 10-year follow-up visit, clinical tests were repeated, and brain atrophy measures were obtained from MRI using FreeSurfer. Differences in clinical and MRI measurements at the 10-year follow-up between smokers and nonsmokers were investigated by 2-sample t tests or Mann-Whitney tests and linear mixed-effect regression models. All analyses were conducted separately for each definition of smoking status. Results After 10 years, smoking (defined by serum cotinine levels) was associated with lower total white matter volume (β = −21.74, p = 0.039) and higher logT2 lesion volume (β = 0.22, p = 0.011). When defining smoking status by patient self-reporting, the repeated analyses found an additional association with lower deep gray matter volume (β = −2.35, p = 0.049), and smoking was also associated with a higher score (higher walking impairment) on the log timed 25-foot walk test (β = 0.050, p = 0.039) after 10 years and a larger decrease in paced auditory serial addition test (attention) scores (β = −3.58, p = 0.029). Discussion Smoking was associated with brain atrophy and disability progression 10 years later in patients with RRMS. The findings imply that patients should be advised and offered aid in smoking cessation shortly after diagnosis, to prevent long-term disability progression.
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Affiliation(s)
- Ingrid Anne Lie
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway.
| | - Kristin Wesnes
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Silje S Kvistad
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Iman Brouwer
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Stig Wergeland
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Trygve Holmøy
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Rune Midgard
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Alla Bru
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Astrid Edland
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Randi Eikeland
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Sonia Gosal
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Hanne F Harbo
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Grethe Kleveland
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Yvonne S Sørenes
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Nina Øksendal
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Frederik Barkhof
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Hugo Vrenken
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Kjell-Morten Myhr
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Lars Bø
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Øivind Torkildsen
- From the Department of Clinical Medicine (I.A.L., K.-M.M., L.B., Ø.T.), University of Bergen; Neuro-SysMed, Department of Neurology, Haukeland University Hospital (I.A.L., K.W., S.S.K., S.W., K.-M.M., Ø.T.), Bergen; St. Olav's University Hospital (K.W.), Trondheim; Department of Immunology and Transfusion Medicine (S.S.K.), Haukeland University Hospital, Bergen, Norway; Department of Radiology and Nuclear Medicine (I.B., F.B., H.V.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, The Netherlands; Norwegian Multiple Sclerosis Registry and Biobank (S.W.), Department of Neurology, Haukeland University Hospital, Bergen; Institute of Clinical Medicine (T.H., H.F.H.), University of Oslo; Department of Neurology, Akershus University Hospital (T.H.), Lørenskog; Department of Neurology (R.M.), Molde Hospital; Department of Neurology (A.B.), Stavanger University Hospital; Department of Neurology (A.E.), Vestre Viken Hospital Trust, Drammen; Department of Research and Education (R.E.), Sørlandet Hospital Trust, Kristiansand; Faculty of Health and Sport Science (R.E.), University of Agder, Grimstad; Department of Neurology (S.G.), Østfold Hospital Kalnes, Grålum; Department of Neurology (H.F.H.), Oslo University Hospital; Department of Neurology (G.K.), Innlandet Hospital Lillehammer; Department of Neurology (Y.S.S.), Haugesund Hospital; Department of Neurology (N.Ø.), Nordland Hospital Trust, Bodø, Norway; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, Great Britain; and Norwegian Multiple Sclerosis Competence Centre (L.B.), Department of Neurology, Haukeland University Hospital, Bergen, Norway
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9
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Qin S, Basak C. Fitness and arterial stiffness in healthy aging: Modifiable cardiovascular risk factors contribute to altered default mode network patterns during executive function. Neuropsychologia 2022; 172:108269. [PMID: 35595064 DOI: 10.1016/j.neuropsychologia.2022.108269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 05/07/2022] [Accepted: 05/12/2022] [Indexed: 11/28/2022]
Abstract
Increases in cardiovascular risks such as high blood pressure and low physical fitness have been independently associated with altered default mode network (DMN) activation patterns in healthy aging. However, cardiovascular risk is a multidimensional health problem. Therefore, we need to investigate multiple cardiovascular risk factors and their contributions to cognition and DMN activations in older adults, which has not yet been done. The current fMRI study examined contributions of two common modifiable cardiovascular risk factors (arterial stiffness and physical fitness) on DMN activations involved during random n-back, a task of executive functioning and working memory, in older adults. The results how that high cardiovascular risk of either increased arterial stiffness or decreased fitness independently contributed to worse task performance and reduced deactivations in two DMN regions: the anterior and posterior cingulate cortices. We then examined not only the potential interaction between the two risk factors, but also their additive (i.e., combined) effect on performance and DMN deactivations. A significant interaction between the two cardiovascular risk factors was observed on performance, with arterial stiffness moderating the relationship between physical fitness and random n-back accuracy. The additive effect of the two factors on task performance was driven by arterial stiffness. Arterial stiffness was also found to be the driving factor when the additive effect of the two risk factors was examined on DMN deactivations. However, in posterior cingulate cortex, a hub region of the DMN, the additive effect on its deactivation was significantly higher than the effect of each risk factor alone. These results suggest that the effects of cardiovascular risks on the aging brain are complicated and multi-dimensional, with arterial stiffness moderating or driving the combined effects on performance and anterior DMN deactivations, but physical fitness contributing additional effect to posterior DMN deactivation during executive functioning.
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Affiliation(s)
- Shuo Qin
- Center for Vital Longevity, University of Texas at Dallas, United States
| | - Chandramallika Basak
- Center for Vital Longevity, University of Texas at Dallas, United States; Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, United States.
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10
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Ginty AT, Tyra AT, Young DA, Brindle RC, de Rooij SR, Williams SE. Cardiovascular reactions to acute psychological stress and academic achievement. Psychophysiology 2022; 59:e14064. [PMID: 35353904 PMCID: PMC9541813 DOI: 10.1111/psyp.14064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Revised: 01/12/2022] [Accepted: 03/09/2022] [Indexed: 11/30/2022]
Abstract
Cardiovascular reactions to acute psychological stress have been associated with cognitive function. However, previous work has assessed cardiovascular reactions and cognitive function in the laboratory at the same time. The present study examined the association between cardiovascular reactions to acute psychological stress in the laboratory and academic performance in final year high school students. Heart rate, blood pressure, stroke volume, and cardiac output reactions to an acute psychological stress task were measured in 131 participants during their final year of high school. Performance on high school A‐levels were obtained the following year. Higher heart rate and cardiac output reactivity were associated with better A‐level performance. These associations were still statistically significant after adjusting for a wide range of potentially confounding variables. The present results are consistent with a body of literature suggesting that higher heart rate reactions to acute psychological stress are associated with better cognitive performance across a variety of domains. The present study is the first to examine the associations between cardiovascular reactions to stress in the laboratory and academic achievement. Additionally, it is the first to examine a more comprehensive hemodynamic profile of cardiovascular reactivity (e.g., cardiac output) with cognitive function. The present results are consistent with a body of literature suggesting that higher heart rate reactions to acute psychological stress are associated with better cognitive performance across a variety of domains.
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Affiliation(s)
- Annie T Ginty
- Department of Psychology and Neuroscience, Baylor University, Waco, Texas, USA
| | - Alexandra T Tyra
- Department of Psychology and Neuroscience, Baylor University, Waco, Texas, USA
| | - Danielle A Young
- Department of Psychology and Neuroscience, Baylor University, Waco, Texas, USA
| | - Ryan C Brindle
- Department of Cognitive and Behavioral Science & Neuroscience Program, Washington and Lee University, Lexington, Virginia, USA
| | - Susanne R de Rooij
- Department of Epidemiology and Data Science, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Sarah E Williams
- School of Sport, Exercise, and Rehabilitation Sciences, University of Birmingham, Birmingham, UK
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11
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Melazzini L, Savoldi F, Chessa M, Vitali P, Zanardo M, Bertoldo EG, Fiolo V, Griffanti L, Carminati M, Frigiola A, Giamberti A, Secchi F, Callus E, Codari M, Sardanelli F. Adults with tetralogy of Fallot show specific features of cerebral small vessel disease: the BACH San Donato study. Brain Imaging Behav 2022; 16:1721-1731. [PMID: 35266099 PMCID: PMC8906830 DOI: 10.1007/s11682-022-00629-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/30/2021] [Indexed: 11/26/2022]
Abstract
Life expectancy in adults with congenital heart disease (ACHD) has increased. As these patients grow older, they experience aging-related diseases more than their healthy peers. To better characterize this field, we launched the multi-disciplinary BACH (Brain Aging in Congenital Heart disease) San Donato study, that aimed at investigating signs of brain injury in ACHD. Twenty-three adults with repaired tetralogy of Fallot and 23 age- and sex-matched healthy controls were prospectively recruited and underwent brain magnetic resonance imaging. White matter hyperintensities (WMHs) were segmented using a machine-learning approach and automatically split into periventricular and deep. Cerebral microbleeds were manually counted. A subset of 14 patients were also assessed with an extensive neuropsychological battery. Age was 41.78 ± 10.33 years (mean ± standard deviation) for patients and 41.48 ± 10.28 years for controls (p = 0.921). Albeit not significantly, total brain (p = 0.282) and brain tissue volumes (p = 0.539 for cerebrospinal fluid, p = 0.661 for grey matter, p = 0.793 for white matter) were lower in ACHD, while total volume (p = 0.283) and sub-classes of WMHs (p = 0.386 for periventricular WMHs and p = 0.138 for deep WMHs) were higher in ACHD than in controls. Deep WMHs were associated with poorer performance at the frontal assessment battery (r = -0.650, p = 0.012). Also, patients had a much larger number of microbleeds than controls (median and interquartile range 5 [3–11] and 0 [0–0] respectively; p < 0.001). In this study, adults with tetralogy of Fallot showed specific signs of brain injury, with some clinical implications. Eventually, accurate characterization of brain health using neuroimaging and neuropsychological data would aid in the identification of ACHD patients at risk of cognitive deterioration.
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Affiliation(s)
- Luca Melazzini
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milano, Italy
| | - Filippo Savoldi
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122, Milano, Italy
| | - Massimo Chessa
- ACHD Unit, Pediatric and Adult Congenital Heart Centre, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
- Vita-Salute San Raffaele University,, Via Olgettina 58, 20132, Milano, Italy
| | - Paolo Vitali
- Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy.
| | - Moreno Zanardo
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milano, Italy
| | - Enrico Giuseppe Bertoldo
- Clinical Psychology Service, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
| | - Valentina Fiolo
- Clinical Psychology Service, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
| | - Ludovica Griffanti
- Department of Psychiatry, Wellcome Centre for Integrative Neuroimaging (WIN), University of Oxford, Warneford Ln, Headington, OX3 7JX, Oxford, UK
| | - Mario Carminati
- Department of Pediatric Cardiology and Adult Congenital Heart Disease, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
| | - Alessandro Frigiola
- Department of Congenital Cardiac Surgery, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
| | - Alessandro Giamberti
- Department of Congenital Cardiac Surgery, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
| | - Francesco Secchi
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milano, Italy
- Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
| | - Edward Callus
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milano, Italy
- Clinical Psychology Service, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
| | - Marina Codari
- Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
- Department of Radiology, School of Medicine, Stanford University, 300 Pasteur Drive, Stanford, CA, 94305-5105, USA
| | - Francesco Sardanelli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milano, Italy
- Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
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12
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Jiménez-Balado J, Corlier F, Habeck C, Stern Y, Eich T. Effects of white matter hyperintensities distribution and clustering on late-life cognitive impairment. Sci Rep 2022; 12:1955. [PMID: 35121804 PMCID: PMC8816933 DOI: 10.1038/s41598-022-06019-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 01/20/2022] [Indexed: 11/29/2022] Open
Abstract
White matter hyperintensities (WMH) are a key hallmark of subclinical cerebrovascular disease and are known to impair cognition. Here, we parcellated WMH using a novel system that segments WMH based on both lobar regions and distance from the ventricles, dividing the brain into a coordinate system composed of 36 distinct parcels (‘bullseye’ parcellation), and then investigated the effect of distribution on cognition using two different analytic approaches. Data from a well characterized sample of healthy older adults (58 to 84 years) who were free of dementia were included. Cognition was evaluated using 12 computerized tasks, factored onto 4 indices representing episodic memory, speed of processing, fluid reasoning and vocabulary. We first assessed the distribution of WMH according to the bullseye parcellation and tested the relationship between WMH parcellations and performance across the four cognitive domains. Then, we used a data-driven approach to derive latent variables within the WMH distribution, and tested the relation between these latent components and cognitive function. We observed that different, well-defined cognitive constructs mapped to specific WMH distributions. Speed of processing was correlated with WMH in the frontal lobe, while in the case of episodic memory, the relationship was more ubiquitous, involving most of the parcellations. A principal components analysis revealed that the 36 bullseye regions factored onto 3 latent components representing the natural aggrupation of WMH: fronto-parietal periventricular (WMH principally in the frontal and parietal lobes and basal ganglia, especially in the periventricular region); occipital; and temporal and juxtacortical WMH (involving WMH in the temporal lobe, and at the juxtacortical region from frontal and parietal lobes). We found that fronto-parietal periventricular and temporal & juxtacortical WMH were independently associated with speed of processing and episodic memory, respectively. These results indicate that different cognitive impairment phenotypes might present with specific WMH distributions. Additionally, our study encourages future research to consider WMH classifications using parcellations systems other than periventricular and deep localizations.
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Affiliation(s)
- Joan Jiménez-Balado
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA
| | - Fabian Corlier
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA
| | - Christian Habeck
- Department of Neurology, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Yaakov Stern
- Department of Neurology, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Teal Eich
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA.
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13
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Adipose tissue distribution from body MRI is associated with cross-sectional and longitudinal brain age in adults. Neuroimage Clin 2022; 33:102949. [PMID: 35114636 PMCID: PMC8814666 DOI: 10.1016/j.nicl.2022.102949] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 01/20/2022] [Accepted: 01/21/2022] [Indexed: 12/12/2022]
Abstract
There is an intimate body-brain connection in ageing, and obesity is a key risk factor for poor cardiometabolic health and neurodegenerative conditions. We investigated adipose tissue distribution from body magnetic resonance imaging (MRI) in relation to brain structure using MRI-based morphometry and diffusion tensor imaging (DTI). The results indicated older-appearing brains in people with higher measures of adipose tissue, and accelerated ageing over the course of the study period in people with higher measures of adipose tissue.
There is an intimate body-brain connection in ageing, and obesity is a key risk factor for poor cardiometabolic health and neurodegenerative conditions. Although research has demonstrated deleterious effects of obesity on brain structure and function, the majority of studies have used conventional measures such as waist-to-hip ratio, waist circumference, and body mass index. While sensitive to gross features of body composition, such global anthropometric features fail to describe regional differences in body fat distribution and composition. The sample consisted of baseline brain magnetic resonance imaging (MRI) acquired from 790 healthy participants aged 18–94 years (mean ± standard deviation (SD) at baseline: 46.8 ± 16.3), and follow-up brain MRI collected from 272 of those individuals (two time-points with 19.7 months interval, on average (min = 9.8, max = 35.6). Of the 790 included participants, cross-sectional body MRI data was available from a subgroup of 286 participants, with age range 19–86 (mean = 57.6, SD = 15.6). Adopting a mixed cross-sectional and longitudinal design, we investigated cross-sectional body magnetic resonance imaging measures of adipose tissue distribution in relation to longitudinal brain structure using MRI-based morphometry (T1) and diffusion tensor imaging (DTI). We estimated tissue-specific brain age at two time points and performed Bayesian multilevel modelling to investigate the associations between adipose measures at follow-up and brain age gap (BAG) – the difference between actual age and the prediction of the brain’s biological age – at baseline and follow-up. We also tested for interactions between BAG and both time and age on each adipose measure. The results showed credible associations between T1-based BAG and liver fat, muscle fat infiltration (MFI), and weight-to-muscle ratio (WMR), indicating older-appearing brains in people with higher measures of adipose tissue. Longitudinal evidence supported interaction effects between time and MFI and WMR on T1-based BAG, indicating accelerated ageing over the course of the study period in people with higher measures of adipose tissue. The results show that specific measures of fat distribution are associated with brain ageing and that different compartments of adipose tissue may be differentially linked with increased brain ageing, with potential to identify key processes involved in age-related transdiagnostic disease processes.
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14
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Beck D, de Lange AG, Pedersen ML, Alnæs D, Maximov II, Voldsbekk I, Richard G, Sanders A, Ulrichsen KM, Dørum ES, Kolskår KK, Høgestøl EA, Steen NE, Djurovic S, Andreassen OA, Nordvik JE, Kaufmann T, Westlye LT. Cardiometabolic risk factors associated with brain age and accelerate brain ageing. Hum Brain Mapp 2022; 43:700-720. [PMID: 34626047 PMCID: PMC8720200 DOI: 10.1002/hbm.25680] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Revised: 09/02/2021] [Accepted: 09/25/2021] [Indexed: 11/17/2022] Open
Abstract
The structure and integrity of the ageing brain is interchangeably linked to physical health, and cardiometabolic risk factors (CMRs) are associated with dementia and other brain disorders. In this mixed cross-sectional and longitudinal study (interval mean = 19.7 months), including 790 healthy individuals (mean age = 46.7 years, 53% women), we investigated CMRs and health indicators including anthropometric measures, lifestyle factors, and blood biomarkers in relation to brain structure using MRI-based morphometry and diffusion tensor imaging (DTI). We performed tissue specific brain age prediction using machine learning and performed Bayesian multilevel modeling to assess changes in each CMR over time, their respective association with brain age gap (BAG), and their interaction effects with time and age on the tissue-specific BAGs. The results showed credible associations between DTI-based BAG and blood levels of phosphate and mean cell volume (MCV), and between T1-based BAG and systolic blood pressure, smoking, pulse, and C-reactive protein (CRP), indicating older-appearing brains in people with higher cardiometabolic risk (smoking, higher blood pressure and pulse, low-grade inflammation). Longitudinal evidence supported interactions between both BAGs and waist-to-hip ratio (WHR), and between DTI-based BAG and systolic blood pressure and smoking, indicating accelerated ageing in people with higher cardiometabolic risk (smoking, higher blood pressure, and WHR). The results demonstrate that cardiometabolic risk factors are associated with brain ageing. While randomized controlled trials are needed to establish causality, our results indicate that public health initiatives and treatment strategies targeting modifiable cardiometabolic risk factors may also improve risk trajectories and delay brain ageing.
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Affiliation(s)
- Dani Beck
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
- Department of PsychologyUniversity of OsloOslo
- Sunnaas Rehabilitation Hospital HTNesodden
| | - Ann‐Marie G. de Lange
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
- LREN, Centre for Research in Neurosciences‐Department of Clinical NeurosciencesCHUV and University of LausanneLausanneSwitzerland
- Department of PsychiatryUniversity of OxfordOxfordUK
| | - Mads L. Pedersen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
- Department of PsychologyUniversity of OsloOslo
| | - Dag Alnæs
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
- Bjørknes CollegeOsloNorway
| | - Ivan I. Maximov
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
- Department of PsychologyUniversity of OsloOslo
- Department of Health and FunctioningWestern Norway University of Applied SciencesBergenNorway
| | - Irene Voldsbekk
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
- Department of PsychologyUniversity of OsloOslo
| | - Geneviève Richard
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
| | - Anne‐Marthe Sanders
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
- Department of PsychologyUniversity of OsloOslo
- Sunnaas Rehabilitation Hospital HTNesodden
| | - Kristine M. Ulrichsen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
- Department of PsychologyUniversity of OsloOslo
- Sunnaas Rehabilitation Hospital HTNesodden
| | - Erlend S. Dørum
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
- Department of PsychologyUniversity of OsloOslo
- Sunnaas Rehabilitation Hospital HTNesodden
| | - Knut K. Kolskår
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
- Department of PsychologyUniversity of OsloOslo
- Sunnaas Rehabilitation Hospital HTNesodden
| | - Einar A. Høgestøl
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
- Department of PsychologyUniversity of OsloOslo
| | - Nils Eiel Steen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
| | - Srdjan Djurovic
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
| | - Ole A. Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
- KG Jebsen Centre for Neurodevelopmental DisordersUniversity of OsloOsloNorway
| | | | - Tobias Kaufmann
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
- Department of Psychiatry and PsychotherapyUniversity of TübingenTubingenGermany
| | - Lars T. Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical MedicineUniversity of OsloOslo
- Department of PsychologyUniversity of OsloOslo
- KG Jebsen Centre for Neurodevelopmental DisordersUniversity of OsloOsloNorway
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15
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Taylor J. Exercise and the brain in cardiovascular disease: A narrative review. HEART AND MIND 2022. [DOI: 10.4103/hm.hm_50_22] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
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16
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Park S, Lee S, Kim Y, Cho S, Kim K, Kim YC, Han SS, Lee H, Lee JP, Lee S, Choi EK, Joo KW, Lim CS, Kim YS, Kim DK. Causal effects of atrial fibrillation on brain white and gray matter volume: a Mendelian randomization study. BMC Med 2021; 19:274. [PMID: 34814924 PMCID: PMC8611907 DOI: 10.1186/s12916-021-02152-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 10/04/2021] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Atrial fibrillation (AF) and brain volume loss are prevalent in older individuals. We aimed to assess the causal effect of atrial fibrillation on brain volume phenotypes by Mendelian randomization (MR) analysis. METHODS The genetic instrument for AF was constructed from a previous genome-wide association study (GWAS) meta-analysis (15,993 AF patients and 113,719 controls of European ancestry). The outcome summary statistics for head-size-normalized white or gray matter volume measured by magnetic resonance imaging were provided by a previous GWAS of 33,224 white British participants in the UK Biobank. Two-sample MR by the inverse variance-weighted method was performed, supported by pleiotropy-robust MR sensitivity analysis. The causal estimates for the effect of AF on ischemic stroke were also investigated in a dataset that included the findings from the MEGASTROKE study (34,217 stroke patients and 406,111 controls of European ancestry). The direct effects of AF on brain volume phenotypes adjusted for the mediating effect of ischemic stroke were studied by multivariable MR. RESULTS A higher genetic predisposition for AF was significantly associated with lower grey matter volume [beta -0.040, standard error (SE) 0.017, P=0.017], supported by pleiotropy-robust MR sensitivity analysis. Significant causal estimates were identified for the effect of AF on ischemic stroke (beta 0.188, SE 0.026, P=1.03E-12). The total effect of AF on lower brain grey matter volume was attenuated by adjusting for the effect of ischemic stroke (direct effects, beta -0.022, SE 0.033, P=0.528), suggesting that ischemic stroke is a mediator of the identified causal pathway. The causal estimates were nonsignificant for effects on brain white matter volume as an outcome. CONCLUSIONS This study identified that genetic predisposition for AF is significantly associated with lower gray matter volume but not white matter volume. The results indicated that the identified total effect of AF on gray matter volume may be mediated by ischemic stroke.
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Affiliation(s)
- Sehoon Park
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
- Department of Internal Medicine, Armed Forces Capital Hospital, Gyeonggi-do, Seongnam, Korea
| | - Soojin Lee
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Yaerim Kim
- Department of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea
| | - Semin Cho
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea
| | - Kwangsoo Kim
- Transdisciplinary Department of Medicine & Advanced Technology, Seoul National University Hospital, Seoul, Korea
| | - Yong Chul Kim
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
| | - Seung Seok Han
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Kidney Research Institute, Seoul National University, Seoul, Korea
| | - Hajeong Lee
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
| | - Jung Pyo Lee
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Kidney Research Institute, Seoul National University, Seoul, Korea
- Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, Korea
| | - Soryoung Lee
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea
| | - Eue-Keun Choi
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea
| | - Kwon Wook Joo
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea
- Kidney Research Institute, Seoul National University, Seoul, Korea
| | - Chun Soo Lim
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Kidney Research Institute, Seoul National University, Seoul, Korea
- Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, Korea
| | - Yon Su Kim
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea
- Kidney Research Institute, Seoul National University, Seoul, Korea
| | - Dong Ki Kim
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea.
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
- Kidney Research Institute, Seoul National University, Seoul, Korea.
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17
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Fitzgerald KC, Damian A, Conway D, Mowry EM. Vascular comorbidity is associated with lower brain volumes and lower neuroperformance in a large multiple sclerosis cohort. Mult Scler 2021; 27:1914-1923. [PMID: 33416436 PMCID: PMC8263795 DOI: 10.1177/1352458520984746] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
OBJECTIVE The objective of this study is to assess the association between vascular comorbidity burden with clinical and imaging features of disease burden in a large population of people with multiple sclerosis (MS). METHODS We included participants from the MS Partners Advancing Technology Health Solutions (MS PATHS) cohort. We evaluated if vascular comorbidities (diabetes, hypertension, and dyslipidemia) or a composite sum of comorbidities was associated with MS characteristics, including objective neurologic function assessments and quantitative brain magnetic resonance imaging (MRI) measurements in propensity score-weighted models. RESULTS In total, 11,506 participants (6409 (55%) with brain MRI) were included. Individuals with 2+ vascular comorbidities had slower walking speed (standard deviation (SD) = -0.49; 95% confidence interval (CI) = -0.78, -0.19; p = 0.001), slower manual dexterity (SD = -0.41; 95% CI = -0.57, -0.26; p < 0.0001), and fewer correct scores on cognitive processing speed (SD = -0.11; 95% CI = -0.20, -0.02; p = 0.02) versus those with no comorbidities. Those with 2+ had lower brain parenchymal (-0.41%, 95% CI = -0.64, -0.17) and gray matter fractions (-0.30%, 95% CI = -0.49, -0.10), including reduced cortical (-10.10 mL, 95% CI = -15.42, -4.78) and deep (-0.44 mL, 95% CI = -0.84, -0.04) gray matter volumes versus those with no comorbidity. CONCLUSION Increased vascular comorbidity burden was associated with clinical and imaging markers of neurologic dysfunction and neurodegeneration in MS. Strategies to optimize comorbidity management in people with MS are warranted.
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Affiliation(s)
- Kathryn C Fitzgerald
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA/Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Anne Damian
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Devon Conway
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH, USA
| | - Ellen M Mowry
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA/Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
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18
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Tiemeier H. Half the Body in One Model: How Obesity Impacts the Brain. J Clin Endocrinol Metab 2021; 106:e4284-e4286. [PMID: 33870437 PMCID: PMC8475194 DOI: 10.1210/clinem/dgab247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Indexed: 11/19/2022]
Affiliation(s)
- Henning Tiemeier
- Department of Social and Behavioral Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Correspondence: Henning Tiemeier, MD, PhD, Department of Social and Behavioral Science, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Kresge 619, Boston, MA 02115, USA.
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19
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Liu J, Li Y, Yang X, Xu H, Ren J, Zhou P. Regional Spontaneous Neural Activity Alterations in Type 2 Diabetes Mellitus: A Meta-Analysis of Resting-State Functional MRI Studies. Front Aging Neurosci 2021; 13:678359. [PMID: 34220486 PMCID: PMC8245688 DOI: 10.3389/fnagi.2021.678359] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 05/11/2021] [Indexed: 01/06/2023] Open
Abstract
Objective: Resting-state functional magnetic resonance imaging (rs-fMRI) studies have revealed inconsistent regional spontaneous neural activity alterations in patients with type 2 diabetes mellitus (T2DM). The aim of our meta-analysis was to identify concordant regional spontaneous neural activity abnormalities in patients with T2DM. Methods: A systematic search was conducted to identify voxel-based rs-fMRI studies comparing T2DM patients with healthy controls. The permutation of subject images seed-based d mapping (SDM) was used to quantitatively estimate the regional spontaneous neural activity abnormalities in patients with T2DM. Metaregression was conducted to examine the associations between clinical characteristics and functional alterations. Results: A total of 16 studies with 19 datasets including 434 patients with T2DM and 391 healthy controls were included. Patients with T2DM showed hypoactivity in the right medial superior frontal gyrus, right superior temporal gyrus, and left lingual gyrus, whereas hyperactivity in the right cerebellum. Metaregression analysis identified negative correlation between regional activity in the medial superior frontal and anterior cingulate gyri and illness duration of patients with T2DM. Conclusion: The patterns of regional spontaneous neural activity alterations, characterized by hypoactivity in the medial pre-frontal cortex, visual cortex, and superior temporal gyrus, whereas hyperactivity in the cerebellum, might represent the underlying neuropathological mechanisms of T2DM.
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Affiliation(s)
- Jieke Liu
- Department of Radiology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Yong Li
- Department of Radiology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Xi Yang
- Department of Radiology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Hao Xu
- Department of Radiology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jing Ren
- Department of Radiology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Peng Zhou
- Department of Radiology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
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20
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Bays HE, Khera A, Blaha MJ, Budoff MJ, Toth PP. Ten things to know about ten imaging studies: A preventive cardiology perspective ("ASPC top ten imaging"). Am J Prev Cardiol 2021; 6:100176. [PMID: 34327499 PMCID: PMC8315431 DOI: 10.1016/j.ajpc.2021.100176] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 03/16/2021] [Accepted: 03/19/2021] [Indexed: 02/07/2023] Open
Abstract
Knowing the patient's current cardiovascular disease (CVD) status, as well as the patient's current and future CVD risk, helps the clinician make more informed patient-centered management recommendations towards the goal of preventing future CVD events. Imaging tests that can assist the clinician with the diagnosis and prognosis of CVD include imaging studies of the heart and vascular system, as well as imaging studies of other body organs applicable to CVD risk. The American Society for Preventive Cardiology (ASPC) has published "Ten Things to Know About Ten Cardiovascular Disease Risk Factors." Similarly, this "ASPC Top Ten Imaging" summarizes ten things to know about ten imaging studies related to assessing CVD and CVD risk, listed in tabular form. The ten imaging studies herein include: (1) coronary artery calcium imaging (CAC), (2) coronary computed tomography angiography (CCTA), (3) cardiac ultrasound (echocardiography), (4) nuclear myocardial perfusion imaging (MPI), (5) cardiac magnetic resonance (CMR), (6) cardiac catheterization [with or without intravascular ultrasound (IVUS) or coronary optical coherence tomography (OCT)], (7) dual x-ray absorptiometry (DXA) body composition, (8) hepatic imaging [ultrasound of liver, vibration-controlled transient elastography (VCTE), CT, MRI proton density fat fraction (PDFF), magnetic resonance spectroscopy (MRS)], (9) peripheral artery / endothelial function imaging (e.g., carotid ultrasound, peripheral doppler imaging, ultrasound flow-mediated dilation, other tests of endothelial function and peripheral vascular imaging) and (10) images of other body organs applicable to preventive cardiology (brain, kidney, ovary). Many cardiologists perform cardiovascular-related imaging. Many non-cardiologists perform applicable non-cardiovascular imaging. Cardiologists and non-cardiologists alike may benefit from a working knowledge of imaging studies applicable to the diagnosis and prognosis of CVD and CVD risk - both important in preventive cardiology.
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Affiliation(s)
- Harold E. Bays
- Louisville Metabolic and Atherosclerosis Research Center, 3288 Illinois Avenue, Louisville KY 40213 USA
| | - Amit Khera
- UT Southwestern Medical Center, Dallas, TX USA
| | - Michael J. Blaha
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Baltimore MD USA
| | - Matthew J Budoff
- Department of Medicine, Lundquist Institute at Harbor-UCLA, Torrance CA USA
| | - Peter P. Toth
- CGH Medical Cener, Sterling, IL 61081 USA
- Cicarrone center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, MD USA
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21
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Gurholt TP, Kaufmann T, Frei O, Alnæs D, Haukvik UK, van der Meer D, Moberget T, O'Connell KS, Leinhard OD, Linge J, Simon R, Smeland OB, Sønderby IE, Winterton A, Steen NE, Westlye LT, Andreassen OA. Population-based body-brain mapping links brain morphology with anthropometrics and body composition. Transl Psychiatry 2021; 11:295. [PMID: 34006848 PMCID: PMC8131380 DOI: 10.1038/s41398-021-01414-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 04/12/2021] [Accepted: 04/19/2021] [Indexed: 12/13/2022] Open
Abstract
Understanding complex body-brain processes and the interplay between adipose tissue and brain health is important for understanding comorbidity between psychiatric and cardiometabolic disorders. We investigated associations between brain structure and anthropometric and body composition measures using brain magnetic resonance imaging (MRI; n = 24,728) and body MRI (n = 4973) of generally healthy participants in the UK Biobank. We derived regional and global measures of brain morphometry using FreeSurfer and tested their association with (i) anthropometric measures, and (ii) adipose and muscle tissue measured from body MRI. We identified several significant associations with small effect sizes. Anthropometric measures showed negative, nonlinear, associations with cerebellar/cortical gray matter, and brain stem structures, and positive associations with ventricular volumes. Subcortical structures exhibited mixed effect directionality, with strongest positive association for accumbens. Adipose tissue measures, including liver fat and muscle fat infiltration, were negatively associated with cortical/cerebellum structures, while total thigh muscle volume was positively associated with brain stem and accumbens. Regional investigations of cortical area, thickness, and volume indicated widespread and largely negative associations with anthropometric and adipose tissue measures, with an opposite pattern for thigh muscle volume. Self-reported diabetes, hypertension, or hypercholesterolemia were associated with brain structure. The findings provide new insight into physiological body-brain associations suggestive of shared mechanisms between cardiometabolic risk factors and brain health. Whereas the causality needs to be determined, the observed patterns of body-brain relationships provide a foundation for understanding the underlying mechanisms linking psychiatric disorders with obesity and cardiovascular disease, with potential for the development of new prevention strategies.
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Affiliation(s)
- Tiril P Gurholt
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway.
| | - Tobias Kaufmann
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Oleksandr Frei
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Unn K Haukvik
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Dennis van der Meer
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Torgeir Moberget
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Kevin S O'Connell
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Olof D Leinhard
- AMRA Medical, Linköping, Sweden
- Division of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | | | - Rozalyn Simon
- AMRA Medical, Linköping, Sweden
- Division of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Olav B Smeland
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Ida E Sønderby
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Adriano Winterton
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Nils Eiel Steen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Lars T Westlye
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
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22
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Hagi K, Nosaka T, Dickinson D, Lindenmayer JP, Lee J, Friedman J, Boyer L, Han M, Abdul-Rashid NA, Correll CU. Association Between Cardiovascular Risk Factors and Cognitive Impairment in People With Schizophrenia: A Systematic Review and Meta-analysis. JAMA Psychiatry 2021; 78:510-518. [PMID: 33656533 PMCID: PMC7931134 DOI: 10.1001/jamapsychiatry.2021.0015] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
IMPORTANCE Schizophrenia is associated with cognitive dysfunction and cardiovascular risk factors, including metabolic syndrome (MetS) and its constituent criteria. Cognitive dysfunction and cardiovascular risk factors can worsen cognition in the general population and may contribute to cognitive impairment in schizophrenia. OBJECTIVE To study the association between cognitive dysfunction and cardiovascular risk factors and cognitive impairment in individuals with schizophrenia. DATA SOURCES A search was conducted of Embase, Scopus, MEDLINE, PubMed, and Cochrane databases from inception to February 25, 2020, using terms that included synonyms of schizophrenia AND metabolic adversities AND cognitive function. Conference proceedings, clinical trial registries, and reference lists of relevant publications were also searched. STUDY SELECTION Studies were included that (1) examined cognitive functioning in patients with schizophrenia or schizoaffective disorder; (2) investigated the association of cardiovascular disease risk factors, including MetS, diabetes, obesity, overweight, obesity or overweight, hypertension, dyslipidemia, and insulin resistance with outcomes; and (3) compared cognitive performance of patients with schizophrenia/schizoaffective disorder between those with vs without cardiovascular disease risk factors. DATA EXTRACTION AND SYNTHESIS Extraction of data was conducted by 2 to 3 independent reviewers per article. Data were meta-analyzed using a random-effects model. MAIN OUTCOMES AND MEASURES The primary outcome was global cognition, defined as a test score using clinically validated measures of overall cognitive functioning. RESULTS Twenty-seven studies involving 10 174 individuals with schizophrenia were included. Significantly greater global cognitive deficits were present in patients with schizophrenia who had MetS (13 studies; n = 2800; effect size [ES] = 0.31; 95% CI, 0.13-0.50; P = .001), diabetes (8 studies; n = 2976; ES = 0.32; 95% CI, 0.23-0.42; P < .001), or hypertension (5 studies; n = 1899; ES = 0.21; 95% CI, 0.11-0.31; P < .001); nonsignificantly greater deficits were present in patients with obesity (8 studies; n = 2779; P = .20), overweight (8 studies; n = 2825; P = .41), and insulin resistance (1 study; n = 193; P = .18). Worse performance in specific cognitive domains was associated with cognitive dysfunction and cardiovascular risk factors regarding 5 domains in patients with diabetes (ES range, 0.23 [95% CI, 0.12-0.33] to 0.40 [95% CI, 0.20-0.61]) and 4 domains with MetS (ES range, 0.15 [95% CI, 0.03-0.28] to 0.40 [95% CI, 0.20-0.61]) and hypertension (ES range, 0.15 [95% CI, 0.04-0.26] to 0.27 [95% CI, 0.15-0.39]). CONCLUSIONS AND RELEVANCE In this systematic review and meta-analysis, MetS, diabetes, and hypertension were significantly associated with global cognitive impairment in people with schizophrenia.
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Affiliation(s)
- Katsuhiko Hagi
- Medical Affairs, Sumitomo Dainippon Pharma, Tokyo, Japan
| | - Tadashi Nosaka
- Medical Affairs, Sumitomo Dainippon Pharma, Tokyo, Japan
| | - Dwight Dickinson
- Clinical and Translational Neuroscience Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | | | - Jimmy Lee
- Research Division, Institute of Mental Health, Singapore,Department of Psychosis, Institute of Mental Health, Singapore,Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Joseph Friedman
- Department of Psychiatry, Mount Sinai School of Medicine, New York, New York
| | - Laurent Boyer
- Aix-Marseille University, Public Health, Chronic Diseases and Quality of Life, Research Unit, Marseille, France
| | - Mei Han
- School of Medicine, University of Wollongong, Wollongong, Australia,Illawarra Health and Medical Research Institute, Wollongong, Australia
| | | | - Christoph U. Correll
- Zucker Hillside Hospital, Psychiatry Research, Northwell Health, Glen Oaks, New York,Zucker School of Medicine at Hofstra/Northwell, Department of Psychiatry and Molecular Medicine, Hempstead, New York,Feinstein Institute for Medical Research, Center for Psychiatric Neuroscience, Manhasset, New York,Charité Universitätsmedizin, Department of Child and Adolescent Psychiatry, Berlin, Germany
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23
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González-Castañeda H, Pineda-García G, Serrano-Medina A, Martínez AL, Bonilla J, Ochoa-Ruíz E. Neuropsychology of metabolic syndrome: A systematic review and meta-analysis. COGENT PSYCHOLOGY 2021. [DOI: 10.1080/23311908.2021.1913878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
Affiliation(s)
- Hévila González-Castañeda
- Facultad De Medicina Y Psicología, Universidad Autónoma De Baja California, Tijuana B.C., Calzada Universidad 14418, Parque Industrial Internacional, Tijuana 22300, Mexico
| | | | | | | | - Julieta Bonilla
- Escuela de psicología, Universidad Xochicalco, Mexicali, 21376, Mexico
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24
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Banus J, Lorenzi M, Camara O, Sermesant M. Biophysics-based statistical learning: Application to heart and brain interactions. Med Image Anal 2021; 72:102089. [PMID: 34020082 DOI: 10.1016/j.media.2021.102089] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 03/01/2021] [Accepted: 04/18/2021] [Indexed: 11/18/2022]
Abstract
Initiatives such as the UK Biobank provide joint cardiac and brain imaging information for thousands of individuals, representing a unique opportunity to study the relationship between heart and brain. Most of research on large multimodal databases has been focusing on studying the associations among the available measurements by means of univariate and multivariate association models. However, these approaches do not provide insights about the underlying mechanisms and are often hampered by the lack of prior knowledge on the physiological relationships between measurements. For instance, important indices of the cardiovascular function, such as cardiac contractility, cannot be measured in-vivo. While these non-observable parameters can be estimated by means of biophysical models, their personalisation is generally an ill-posed problem, often lacking critical data and only applied to small datasets. Therefore, to jointly study brain and heart, we propose an approach in which the parameter personalisation of a lumped cardiovascular model is constrained by the statistical relationships observed between model parameters and brain-volumetric indices extracted from imaging, i.e. ventricles or white matter hyperintensities volumes, and clinical information such as age or body surface area. We explored the plausibility of the learnt relationships by inferring the model parameters conditioned on the absence of part of the target clinical features, applying this framework in a cohort of more than 3 000 subjects and in a pathological subgroup of 59 subjects diagnosed with atrial fibrillation. Our results demonstrate the impact of such external features in the cardiovascular model personalisation by learning more informative parameter-space constraints. Moreover, physiologically plausible mechanisms are captured through these personalised models as well as significant differences associated to specific clinical conditions.
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Affiliation(s)
- Jaume Banus
- Université Côte d'Azur, INRIA Sophia Antipolis, Epione Project-Team, France.
| | - Marco Lorenzi
- Université Côte d'Azur, INRIA Sophia Antipolis, Epione Project-Team, France
| | - Oscar Camara
- PhySense group, BCN-MedTech, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Maxime Sermesant
- Université Côte d'Azur, INRIA Sophia Antipolis, Epione Project-Team, France
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25
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Lu R, Aziz NA, Diers K, Stöcker T, Reuter M, Breteler MMB. Insulin resistance accounts for metabolic syndrome-related alterations in brain structure. Hum Brain Mapp 2021; 42:2434-2444. [PMID: 33769661 PMCID: PMC8090787 DOI: 10.1002/hbm.25377] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 01/22/2021] [Accepted: 01/28/2021] [Indexed: 12/26/2022] Open
Abstract
Metabolic syndrome (MetS) is a major public health burden worldwide and associated with brain abnormalities. Although insulin resistance is considered a pivotal feature of MetS, its role in the pathogenesis of MetS‐related brain alterations in the general population is unclear. Therefore, in 973 participants (mean age 52.5 years) of the population‐based Rhineland Study, we assessed brain morphology in relation to MetS and insulin resistance, and evaluated to what extent the pattern of structural brain changes seen in MetS overlap with those associated with insulin resistance. Cortical reconstruction and volumetric segmentation were obtained from high‐resolution brain images at 3 Tesla using FreeSurfer. The relations between metabolic measures and brain structure were assessed through (generalized) linear models. Both MetS and insulin resistance were associated with smaller cortical gray matter volume and thickness, but not with white matter or subcortical gray matter volume. Age‐ and sex‐adjusted vertex‐based brain morphometry demonstrated that MetS and insulin resistance were related to cortical thinning in a similar spatial pattern. Importantly, no independent effect of MetS on cortical gray matter was observed beyond the effect of insulin resistance. Our findings suggest that addressing insulin resistance is critical in the prevention of MetS‐related brain changes in later life.
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Affiliation(s)
- Ran Lu
- Population Health Sciences, German Center for Neurodegenerative diseases (DZNE), Bonn, Germany
| | - N Ahmad Aziz
- Population Health Sciences, German Center for Neurodegenerative diseases (DZNE), Bonn, Germany.,Department of Neurology, Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Kersten Diers
- Image Analysis, German Center for Neurodegenerative diseases (DZNE), Bonn, Germany
| | - Tony Stöcker
- MR Physics, German Center for Neurodegenerative diseases (DZNE), Bonn, Germany.,Department of Physics and Astronomy, University of Bonn, Bonn, Germany
| | - Martin Reuter
- Image Analysis, German Center for Neurodegenerative diseases (DZNE), Bonn, Germany.,A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Monique M B Breteler
- Population Health Sciences, German Center for Neurodegenerative diseases (DZNE), Bonn, Germany.,Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
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26
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Talamonti D, Vincent T, Fraser S, Nigam A, Lesage F, Bherer L. The Benefits of Physical Activity in Individuals with Cardiovascular Risk Factors: A Longitudinal Investigation Using fNIRS and Dual-Task Walking. J Clin Med 2021; 10:jcm10040579. [PMID: 33557109 PMCID: PMC7913805 DOI: 10.3390/jcm10040579] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 01/26/2021] [Accepted: 01/30/2021] [Indexed: 11/16/2022] Open
Abstract
Cardiovascular fitness is linked to better executive functions, preserved gait speed, and efficient cortical activity. Older adults with cardiovascular risk factors (CVRFs) typically show poor cognitive performance, low physical fitness, and altered brain functioning compared with healthy individuals. In the current study, the impact of regular physical activity on cognition, locomotion, and brain functions was explored in a cohort of older adults with low or high CVRFs. Cortical activation of the frontal areas was investigated using functional Near-Infrared Spectroscopy (fNIRS) at baseline, at 6 months and at 12 months. Evoked cortical response and behavioral performance were assessed using the dual-task walking paradigm, consisting of three conditions: single cognitive task (2-back task), single walking task (walking), and dual-task (2-back whilst walking). Results show greater task-related cortical response at baseline in individuals with high CVRFs compared to those with low CVRFs. Moreover, participants with high CVRFs benefitted the most from participating in regular physical activity, as their cortical response decreased at the 12-month follow-up and became comparable to that of participants with low CVRFs. These changes were observed in conjunction with improved cognitive performance and stable gait speed throughout the 12-month period in both groups. Our findings provide evidence that participation in regular physical activity may be especially beneficial in individuals with CVRFs by promoting brain and cognitive health, thus potentially contributing to prevention of cognitive decline. Future research may explore whether such effects are maintained in the long-term in order to design ad-hoc interventions in this specific population.
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Affiliation(s)
- Deborah Talamonti
- Montreal Heart Institute, Research Centre and Centre EPIC, Montreal, QC H1T 1N6, Canada; (T.V.); (A.N.); (F.L.); (L.B.)
- Correspondence:
| | - Thomas Vincent
- Montreal Heart Institute, Research Centre and Centre EPIC, Montreal, QC H1T 1N6, Canada; (T.V.); (A.N.); (F.L.); (L.B.)
| | - Sarah Fraser
- Interdisciplinary School of Health Sciences, University of Ottawa, Ottawa, ON K1N 6N5, Canada;
| | - Anil Nigam
- Montreal Heart Institute, Research Centre and Centre EPIC, Montreal, QC H1T 1N6, Canada; (T.V.); (A.N.); (F.L.); (L.B.)
- Department of Medicine, Université de Montreal, Montreal, QC H3T 1J4, Canada
| | - Frédéric Lesage
- Montreal Heart Institute, Research Centre and Centre EPIC, Montreal, QC H1T 1N6, Canada; (T.V.); (A.N.); (F.L.); (L.B.)
- École Polytechnique de Montreal, Montreal, QC H3T 1J4, Canada
| | - Louis Bherer
- Montreal Heart Institute, Research Centre and Centre EPIC, Montreal, QC H1T 1N6, Canada; (T.V.); (A.N.); (F.L.); (L.B.)
- Department of Medicine, Université de Montreal, Montreal, QC H3T 1J4, Canada
- Centre de Recherche, Institut Universitaire de Gériatrie de Montréal, Montréal, QC H3W 1W5, Canada
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27
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Chua SYL, Lascaratos G, Atan D, Zhang B, Reisman C, Khaw PT, Smith SM, Matthews PM, Petzold A, Strouthidis NG, Foster PJ, Khawaja AP, Patel PJ. Relationships between retinal layer thickness and brain volumes in the UK Biobank cohort. Eur J Neurol 2021; 28:1490-1498. [PMID: 33369822 PMCID: PMC8261460 DOI: 10.1111/ene.14706] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 11/12/2020] [Accepted: 12/10/2020] [Indexed: 12/29/2022]
Abstract
Background and purpose Current methods to diagnose neurodegenerative diseases are costly and invasive. Retinal neuroanatomy may be a biomarker for more neurodegenerative processes and can be quantified in vivo using optical coherence tomography (OCT), which is inexpensive and noninvasive. We examined the association of neuroretinal morphology with brain MRI image‐derived phenotypes (IDPs) in a large cohort of healthy older people. Methods UK Biobank participants aged 40 to 69 years old underwent comprehensive examinations including ophthalmic and brain imaging assessments. Macular retinal nerve fibre layer (mRNFL), macular ganglion cell‐inner plexiform layer (mGCIPL), macular ganglion cell complex (mGCC) and total macular thicknesses were obtained from OCT. Magnetic resonance imaging (MRI) IDPs assessed included total brain, grey matter, white matter and hippocampal volume. Multivariable linear regression models were used to evaluate associations between retinal layers thickness and brain MRI IDPs, adjusting for demographic factors and vascular risk factors. Results A total of 2131 participants (mean age 55 years; 51% women) with both gradable OCT images and brain imaging assessments were included. In multivariable regression analysis, thinner mGCIPL, mGCC and total macular thickness were all significantly associated with smaller total brain (p < 0.001), grey matter and white matter volume (p < 0.01), and grey matter volume in the occipital pole (p < 0.05). Thinner mGCC and total macular thicknesses were associated with smaller hippocampal volume (p < 0.02). No association was found between mRNFL and the MRI IDPs. Conclusions Markers of retinal neurodegeneration are associated with smaller brain volumes. Our findings suggest that retinal structure may be a biomarker providing information about important brain structure in healthy older adults.
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Affiliation(s)
- Sharon Y L Chua
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
| | - Gerassimos Lascaratos
- Kings College Hospital, London, UK.,Department of Ophthalmology, School of Medicine, King's College London, London, UK
| | - Denize Atan
- Bristol Eye Hospital, University Hospitals Bristol NHS Foundation Trust, Bristol, UK.,Bristol Medical School, University of Bristol, Bristol, UK
| | - Bing Zhang
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Charles Reisman
- Topcon Healthcare Solutions, Research and Development, Oakland, NJ, USA
| | - Peng T Khaw
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
| | - Stephen M Smith
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Paul M Matthews
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Axel Petzold
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
| | - Nicholas G Strouthidis
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
| | - Paul J Foster
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
| | - Anthony P Khawaja
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
| | - Praveen J Patel
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
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28
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Veldsman M, Werden E, Egorova N, Khlif MS, Brodtmann A. Microstructural degeneration and cerebrovascular risk burden underlying executive dysfunction after stroke. Sci Rep 2020; 10:17911. [PMID: 33087782 PMCID: PMC7578057 DOI: 10.1038/s41598-020-75074-w] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 10/07/2020] [Indexed: 01/12/2023] Open
Abstract
Executive dysfunction affects 40% of stroke patients, but is poorly predicted by characteristics of the stroke itself. Stroke typically occurs on a background of cerebrovascular burden, which impacts cognition and brain network structural integrity. We used structural equation modelling to investigate whether measures of white matter microstructural integrity (fractional anisotropy and mean diffusivity) and cerebrovascular risk factors better explain executive dysfunction than markers of stroke severity. 126 stroke patients (mean age 68.4 years) were scanned three months post-stroke and compared to 40 age- and sex-matched control participants on neuropsychological measures of executive function. Executive function was below what would be expected for age and education level in stroke patients as measured by the organizational components of the Rey Complex Figure Test, F(3,155) = 17, R2 = 0.25, p < 0.001 (group significant predictor at p < 0.001) and the Trail-Making Test (B), F(3,157) = 3.70, R2 = 0.07, p < 0.01 (group significant predictor at p < 0.001). A multivariate structural equation model illustrated the complex relationship between executive function, white matter integrity, stroke characteristics and cerebrovascular risk (root mean square error of approximation = 0.02). Pearson's correlations confirmed a stronger relationship between executive dysfunction and white matter integrity (r = - 0.74, p < 0.001), than executive dysfunction and stroke severity (r = 0.22, p < 0.01). The relationship between executive function and white matter integrity is mediated by cerebrovascular burden. White matter microstructural degeneration of the superior longitudinal fasciculus in the executive control network better explains executive dysfunction than markers of stroke severity. Executive dysfunction and incident stroke can be both considered manifestations of cerebrovascular risk factors.
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Affiliation(s)
- Michele Veldsman
- Department of Experimental Psychology, University of Oxford, New Radcliffe House, Radcliffe Observatory Quarter, Oxford, OX2 6GG, UK.
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia.
| | - Emilio Werden
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
| | - Natalia Egorova
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
- Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, VIC, Australia
| | - Mohamed Salah Khlif
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
| | - Amy Brodtmann
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
- Austin Health, Heidelberg, Melbourne, VIC, Australia
- Eastern Clinical Research Unit, Box Hill Hospital, Melbourne, VIC, Australia
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29
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Common Brain Structural Alterations Associated with Cardiovascular Disease Risk Factors and Alzheimer's Dementia: Future Directions and Implications. Neuropsychol Rev 2020; 30:546-557. [PMID: 33011894 DOI: 10.1007/s11065-020-09460-6] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Accepted: 09/24/2020] [Indexed: 01/18/2023]
Abstract
Recent reports suggest declines in the age-specific risk of Alzheimer's dementia in higher income Western countries. At the same time, investigators believe that worldwide trends of increasing mid-life modifiable risk factors [e.g., cardiovascular disease (CVD) risk factors] coupled with the growth of the world's oldest age groups may nonetheless lead to an increase in Alzheimer's dementia. Thus, understanding the overlap in neuroanatomical profiles associated with CVD risk factors and AD may offer more relevant targets for investigating ways to reduce the growing dementia epidemic than current targets specific to isolated AD-related neuropathology. We hypothesized that a core group of common brain structural alterations exist between CVD risk factors and Alzheimer's dementia. Two co-authors conducted independent literature reviews in PubMed using search terms for CVD risk factor burden (separate searches for 'cardiovascular disease risk factors', 'hypertension', and 'Type 2 diabetes') and 'aging' or 'Alzheimer's dementia' with either 'grey matter volumes' or 'white matter'. Of studies that reported regionally localized results, we found support for our hypothesis, determining 23 regions commonly associated with both CVD risk factors and Alzheimer's dementia. Within this context, we outline future directions for research as well as larger cerebrovascular implications for these commonalities. Overall, this review supports previous as well as more recent calls for the consideration that both vascular and neurodegenerative factors contribute to the pathogenesis of dementia.
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30
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Jennings JR, Muldoon MF, Allen B, Ginty AT, Gianaros PJ. Cerebrovascular function in hypertension: Does high blood pressure make you old? Psychophysiology 2020; 58:e13654. [PMID: 32830869 DOI: 10.1111/psyp.13654] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2020] [Revised: 05/22/2020] [Accepted: 07/13/2020] [Indexed: 12/22/2022]
Abstract
The majority of individuals over an age of 60 have hypertension. Elevated blood pressure and older age are associated with very similar changes in brain structure and function. We review the parallel brain changes associated with increasing age and blood pressure. This review focuses on joint associations of aging and elevated blood pressure with neuropsychological function, regional cerebral blood flow responses to cognitive and metabolic challenges, white matter disruptions, grey matter volume, cortical thinning, and neurovascular coupling. Treatment of hypertension ameliorates many of these changes but fails to reverse them. Treatment of hypertension itself appears more successful with better initial brain function. We show evidence that sympathetic and renal influences known to increase blood pressure also impact brain integrity. Possible central mechanisms contributing to the course of hypertension and aging are then suggested. An emphasis is placed on psychologically relevant factors: stress, cardiovascular reactions to stress, and diet/obesity. The contribution of some of these factors to biological aging remains unclear and may provide a starting point for defining the independent and interacting effects of aging and increasing blood pressure on the brain.
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Affiliation(s)
- J Richard Jennings
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Matthew F Muldoon
- Department of Medicine, Heart and Vascular Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Ben Allen
- Department of Psychology, University of Tennessee, Knoxville, TN, USA
| | - Annie T Ginty
- Department of Psychology and Neuroscience, Baylor University, Waco, TX, USA
| | - Peter J Gianaros
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
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31
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Jennings JR, Muldoon MF, Sved AF. Is the Brain an Early or Late Component of Essential Hypertension? Am J Hypertens 2020; 33:482-490. [PMID: 32170317 DOI: 10.1093/ajh/hpaa038] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 02/17/2020] [Accepted: 03/11/2020] [Indexed: 11/13/2022] Open
Abstract
The brain's relationship to essential hypertension is primarily understood to be that of an end-organ, damaged late in life by stroke or dementia. Emerging evidence, however, shows that heightened blood pressure (BP) early in life and prior to traditionally defined hypertension, relates to altered brain structure, cerebrovascular function, and cognitive processing. Deficits in cognitive function, cerebral blood flow responsivity, volumes of brain areas, and white matter integrity all relate to increased but prehypertensive levels of BP. Such relationships may be observed as early as childhood. In this review, we consider the basis of these relationships by examining the emergence of putative causative factors for hypertension that would impact or involve brain function/structure, e.g., sympathetic nervous system activation and related endocrine and inflammatory activation. Currently, however, available evidence is not sufficient to fully explain the specific pattern of brain deficits related to heightened BP. Despite this uncertainty, the evidence reviewed suggests the value that early intervention may have, not only for reducing BP, but also for maintaining brain function.
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Affiliation(s)
- John Richard Jennings
- Department of Psychiatry and Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Matthew F Muldoon
- Division of Cardiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- Heart and Vascular Institute, Hypertension Center, UPMC Medical Center, Pittsburgh, Pennsylvania, USA
| | - Alan F Sved
- Center for Neuroscience, University of Pittsburgh, Pennsylvania, USA
- Department of Neuroscience, University of Pittsburgh, Pennsylvania, USA
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32
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Lebouvier T, Chen Y, Duriez P, Pasquier F, Bordet R. Antihypertensive agents in Alzheimer's disease: beyond vascular protection. Expert Rev Neurother 2019; 20:175-187. [PMID: 31869274 DOI: 10.1080/14737175.2020.1708195] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Introduction: Midlife hypertension has been consistently linked with increased risk of cognitive decline and Alzheimer's disease (AD). Observational studies and randomized trials show that the use of antihypertensive therapy is associated with a lesser incidence or prevalence of cognitive impairment and dementia. However, whether antihypertensive agents specifically target the pathological process of AD remains elusive.Areas covered: This review of literature provides an update on the clinical and preclinical arguments supporting anti-AD properties of antihypertensive drugs. The authors focused on validated all classes of antihypertensive treatments such as angiotensin-converting enzyme inhibitors (ACEi), angiotensin receptor blockers (ARB), calcium channel blockers (CCB), β-blockers, diuretics, neprilysin inhibitors, and other agents. Three main mechanisms can be advocated: action on the concurrent vascular pathology, action on the vascular component of Alzheimer's pathophysiology, and action on nonvascular targets.Expert opinion: In 2019, while there is no doubt that hypertension should be treated in primary prevention of vascular disease and in secondary prevention of stroke and mixed dementia, the place of antihypertensive agents in the secondary prevention of 'pure' AD remains an outstanding question.
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Affiliation(s)
- Thibaud Lebouvier
- Inserm URM_S1172, University of Lille, Lille, France.,DISTALZ, University of Lille, Lille, France
| | - Yaohua Chen
- DISTALZ, University of Lille, Lille, France.,Inserm, CHU Lille, University of Lille, Lille, France
| | | | - Florence Pasquier
- DISTALZ, University of Lille, Lille, France.,Inserm, CHU Lille, University of Lille, Lille, France
| | - Régis Bordet
- Inserm, CHU Lille, University of Lille, Lille, France
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33
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Rashid B, Dev SI, Esterman M, Schwarz NF, Ferland T, Fortenbaugh FC, Milberg WP, McGlinchey RE, Salat DH, Leritz EC. Aberrant patterns of default-mode network functional connectivity associated with metabolic syndrome: A resting-state study. Brain Behav 2019; 9:e01333. [PMID: 31568716 PMCID: PMC6908882 DOI: 10.1002/brb3.1333] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Revised: 03/13/2019] [Accepted: 03/29/2019] [Indexed: 12/14/2022] Open
Abstract
INTRODUCTION Metabolic syndrome (MetS) is a clustering of three or more cardiovascular risk factors (RF), including hypertension, obesity, high cholesterol, or hyperglycemia. MetS and its component RFs are more prevalent in older age, and can be accompanied by alterations in brain structure. Studies have shown altered functional connectivity (FC) in samples with individual RFs as well as in clinical populations that are at higher risk to develop MetS. These studies have indicated that the default mode network (DMN) may be particularly vulnerable, yet little is known about the overall impact of MetS on FC in this network. METHODS In this study, we evaluated the integrity of FC to the DMN in participants with MetS relative to non-MetS individuals. Using a seed-based connectivity analysis approach, resting-state functional MRI (fMRI) data were analyzed, and the FC measures among the DMN seed (isthmus of the cingulate) and rest of the brain voxels were estimated. RESULTS Participants with MetS demonstrated reduced positive connectivity between the DMN seed and left superior frontal regions, and reduced negative connectivity between the DMN seed and left superior parietal, left postcentral, right precentral, right superior temporal and right superior parietal regions, after accounting for age- and sex-effects. CONCLUSIONS Our results suggest that MetS is associated with alterations in FC between the DMN and other regions of the brain. Furthermore, these results indicate that the overall burden of vascular RFs associated with MetS may, in part, contribute to the pathophysiology underlying aberrant FC in the DMN.
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Affiliation(s)
- Barnaly Rashid
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Sheena I Dev
- Harvard Medical School, Boston, Massachusetts.,SDSU/UCSD Joint Doctoral Program in Clinical Psychology, San Diego, California
| | - Michael Esterman
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.,Department of Psychiatry, Boston University School of Medicine, Boston, Massachusetts
| | - Nicolette F Schwarz
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts.,McLean Imaging Center, McLean Hospital, Belmont, Massachusetts
| | - Tori Ferland
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Francesca C Fortenbaugh
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - William P Milberg
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Regina E McGlinchey
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - David H Salat
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts.,The Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts
| | - Elizabeth C Leritz
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
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34
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Elbejjani M, Auer R, Dolui S, Jacobs DR, Haight T, Goff DC, Detre JA, Davatzikos C, Bryan RN, Launer LJ. Cigarette smoking and cerebral blood flow in a cohort of middle-aged adults. J Cereb Blood Flow Metab 2019; 39:1247-1257. [PMID: 29355449 PMCID: PMC6668508 DOI: 10.1177/0271678x18754973] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Accepted: 12/06/2017] [Indexed: 11/15/2022]
Abstract
Cigarette smoking is often associated with dementia. This association is thought to be mediated by hypoperfusion; however, how smoking behavior relates to cerebral blood flow (CBF) remains unclear. Using data from the Coronary Artery Risk Development in Young Adults (CARDIA) cohort (mean age = 50; n = 522), we examined the association between smoking behavior (status, cumulative pack-years, age at smoking initiation, and years since cessation) and CBF (arterial spin labeling) in brain lobes and regions linked to dementia. We used adjusted linear regression models and tested whether associations differed between current and former-smokers. Compared to never-smokers, former-smokers had lower CBF in the parietal and occipital lobes, cuneus, precuneus, putamen, and insula; in contrast, current-smokers did not have lower CBF. The relationship between pack-years and CBF was different between current and former-smokers (p for interaction < 0.05): Among current-smokers, higher pack-years were associated with higher occipital, temporal, cuneus, putamen, insula, hippocampus, and caudate CBF; former-smokers had lower caudate CBF with increasing pack-years. Results show links between smoking and CBF at middle-age in regions implicated in cognitive and compulsive/addictive processes. Differences between current and former smoking suggest that distinct pathological and/or compensatory mechanisms may be involved depending on the timing and history of smoking exposure.
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Affiliation(s)
- Martine Elbejjani
- Laboratory of Epidemiology and
Population Sciences,
National
Institute on Aging, Bethesda, MD, USA
| | - Reto Auer
- Institute of Primary Health Care
(BIHAM), University of Bern, Bern, Switzerland
| | - Sudipto Dolui
- Department of Radiology, University of
Pennsylvania Health System, Philadelphia, PA, USA
| | - David R Jacobs
- Division of Epidemiology and Community
Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Thaddeus Haight
- Laboratory of Epidemiology and
Population Sciences,
National
Institute on Aging, Bethesda, MD, USA
| | - David C Goff
- National Heart, Lung, and Blood
Institute, Bethesda, MD, USA
| | - John A Detre
- Department of Neurology; University of
Pennsylvania Health System, Philadelphia, PA, USA
| | - Christos Davatzikos
- Department of Radiology, University of
Pennsylvania Health System, Philadelphia, PA, USA
| | - R Nick Bryan
- Department of Radiology, University of
Pennsylvania Health System, Philadelphia, PA, USA
| | - Lenore J Launer
- Laboratory of Epidemiology and
Population Sciences,
National
Institute on Aging, Bethesda, MD, USA
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35
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Shibata D, Suchy-Dicey A, Carty CL, Madhyastha T, Ali T, Best L, Grabowski TJ, Longstreth WT, Buchwald D. Lifestyle Risk Factors and Findings on Brain Magnetic Resonance Imaging of Older Adult American Indians: The Strong Heart Study. Neuroepidemiology 2019; 53:162-168. [PMID: 31163423 DOI: 10.1159/000501181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2018] [Accepted: 12/19/2019] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Clinical stroke is prevalent in American Indians, but the lifestyle risk factors for vascular brain injury have not been well-studied in this population. The purpose of this study was to correlate brain magnetic resonance imaging (MRI) findings with obesity, alcohol use, and smoking behaviors in elderly American Indians from the Strong Heart Study. METHODS Cranial MRI scans (n = 789) were analyzed for dichotomous measures of infarcts, hemorrhages, white matter hyperintensities (WMH), and cerebral atrophy and continuous measures of total brain, WMH, and hippocampal volume. Poisson regression was used to estimate prevalence ratios, and linear regression was used to estimate measures of association for continuous outcomes. Models were adjusted for the risk factors of interest as well as age, sex, study site, income, education, hypertension, diabetes, and low-density lipoprotein cholesterol. RESULTS Smoking was associated with increased hippocampal atrophy (p = 0.002) and increased prevalence of sulcal widening (p < 0.001). Relative to nonsmokers, smokers with more than 25 pack-years of smoking had a 27% (95% CI 7-47%) increased prevalence of high-grade sulci, p = 0.005. Body mass index was inversely associated with prevalence of nonlacunar infarcts and sulcal widening (all p = 0.004). Alcohol use was not significantly associated with any of the measured MRI findings. CONCLUSIONS This study found similar associations between smoking and vascular brain injury among American Indians, as seen in other populations. In particular, these findings support the role of smoking as a key correlate for cerebral atrophy.
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Affiliation(s)
- Dean Shibata
- Department of Radiology, University of Washington, Seattle, Washington, USA,
| | - Astrid Suchy-Dicey
- Partnerships for Native Health, Washington State University, Pullman, Washington, USA
| | - Cara L Carty
- Partnerships for Native Health, Washington State University, Pullman, Washington, USA.,Elson S Floyd College of Medicine, Washington State University, Seattle, Washington, USA
| | - Tara Madhyastha
- Department of Radiology, University of Washington, Seattle, Washington, USA.,Integrated Brain Imaging Center, University of Washington, Seattle, Washington, USA
| | - Tauqeer Ali
- Center for American Indian Health Research, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Lyle Best
- Strong Heart Study-Dakota Center, Eagle Butte, South Dakota, USA
| | - Thomas J Grabowski
- Integrated Brain Imaging Center, University of Washington, Seattle, Washington, USA.,Department of Neurology, University of Washington, Seattle, Washington, USA
| | - W T Longstreth
- Department of Neurology, University of Washington, Seattle, Washington, USA.,Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Dedra Buchwald
- Partnerships for Native Health, Washington State University, Pullman, Washington, USA.,Elson S Floyd College of Medicine, Washington State University, Seattle, Washington, USA
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36
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van de Kreeke JA, Nguyen HT, Konijnenberg E, Tomassen J, den Braber A, Ten Kate M, Sudre CH, Barkhof F, Boomsma DI, Tan HS, Verbraak FD, Visser PJ. Retinal and Cerebral Microvasculopathy: Relationships and Their Genetic Contributions. Invest Ophthalmol Vis Sci 2019; 59:5025-5031. [PMID: 30326071 DOI: 10.1167/iovs.18-25341] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Purpose Retinal microvasculopathy may reflect small vessel disease in the brain. Here we test the relationships between retinal vascular parameters and small vessel disease, the influence of cardiovascular risk factors on these relationships, and their common genetic background in a monozygotic twin cohort. Methods We selected 134 cognitively healthy individuals (67 monozygotic twin pairs) aged ≥60 years from the Netherlands Twin Register for the EMIF-AD PreclinAD study. We measured seven retinal vascular parameters averaged over both eyes using fundus images analyzed with Singapore I Vessel Assessment. Small vessel disease was assessed on MRI by a volumetric measurement of periventricular and deep white matter hyperintensities. We calculated associations between RVPs and WMH, estimated intratwin pair correlations, and performed twin-specific analyses on relationships of interest. Results Deep white matter hyperintensities volume was positively associated with retinal tortuosity in veins (P = 0.004) and fractal dimension in arteries (P = 0.001) and veins (P = 0.032), periventricular white matter hyperintensities volume was positively associated with retinal venous width (P = 0.028). Intratwin pair correlations were moderate to high for all small vessel disease/retinal vascular parameter variables (r = 0.49-0.87, P < 0.001). Cross-twin cross-trait analyses showed that retinal venous tortuosity of twin 1 could predict deep white matter hyperintensities volume of the co-twin (r = 0.23, P = 0.030). Within twin-pair differences for retinal venous tortuosity were associated with within twin-pair differences in deep white matter hyperintensities volume (r = 0.39, P = 0.001). Conclusions Retinal arterial fractal dimension and venous tortuosity have associations with deep white matter hyperintensities volume. Twin-specific analyses suggest that retinal venous tortuosity and deep white matter hyperintensities volume have a common etiology driven by both shared genetic factors and unique environmental factors, supporting the robustness of this relationship.
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Affiliation(s)
- Jacoba A van de Kreeke
- Ophthalmology Department, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - H Ton Nguyen
- Ophthalmology Department, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Elles Konijnenberg
- Alzheimer Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Jori Tomassen
- Alzheimer Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Anouk den Braber
- Alzheimer Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Mara Ten Kate
- Alzheimer Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Carole H Sudre
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,Dementia Research Centre, Institute of Neurology, University College London, London, United Kingdom
| | - Frederik Barkhof
- Radiology Department, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Netherlands Twin Register, Amsterdam, Netherlands
| | - H Stevie Tan
- Ophthalmology Department, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Frank D Verbraak
- Ophthalmology Department, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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Gray matter reduction related to decreased serum creatinine and increased triglyceride, Hemoglobin A1C, and low-density lipoprotein in subjects with obesity. Neuroradiology 2019; 61:703-710. [PMID: 31011773 DOI: 10.1007/s00234-019-02202-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Accepted: 03/21/2019] [Indexed: 12/19/2022]
Abstract
PURPOSE Altered brain volume and metabolic variables have been found in subjects with obesity. However, the role of metabolic parameters in gray matter volume (GMV) has been poorly investigated. This study aimed to investigate the relationship between the metabolic parameters and brain volume in subjects with obesity. METHODS Thirty-seven subjects with obesity and 39 age and sex matched normal-weight controls were included in this study. Eighteen of the 37 participants who underwent sleeve gastrectomy were included in the longitudinal analysis. Blood samples and high-resolution 3T T1-weighted magnetic resonance images were collected. Metabolic parameters in plasma and GMV were measured. RESULTS Multiple linear regression analysis showed that gray matter reduction in several cognition-related cortices including right angular gyrus, superior occipital cortex, superior parietal cortex, and cerebellum was related to decreased creatinine, as well as increased triglyceride, HbA1c, and low-density lipoprotein in plasma in subjects with obesity. Weight loss after the surgery induced significant recovery of altered metabolic parameters and decreased gray matter volume. Furthermore, changes in the four metabolic parameters before and after the surgery were associated with changes in gray matter volume. CONCLUSION Our results suggest that the gray matter reduction is related to decreased creatinine as well as increased triglyceride, HbA1c, and low-density lipoprotein in plasma in subjects with obesity.
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Boots EA, Zhan L, Dion C, Karstens AJ, Peven JC, Ajilore O, Lamar M. Cardiovascular disease risk factors, tract-based structural connectomics, and cognition in older adults. Neuroimage 2019; 196:152-160. [PMID: 30980900 DOI: 10.1016/j.neuroimage.2019.04.024] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 03/29/2019] [Accepted: 04/05/2019] [Indexed: 01/01/2023] Open
Abstract
Cardiovascular disease risk factors (CVD-RFs) are associated with decreased gray and white matter integrity and cognitive impairment in older adults. Less is known regarding the interplay between CVD-RFs, brain structural connectome integrity, and cognition. We examined whether CVD-RFs were associated with measures of tract-based structural connectivity in 94 non-demented/non-depressed older adults and if alterations in connectivity mediated associations between CVD-RFs and cognition. Participants (age = 68.2 years; 52.1% female; 46.8% Black) underwent CVD-RF assessment, MRI, and cognitive evaluation. Framingham 10-year stroke risk (FSRP-10) quantified CVD-RFs. Graph theory analysis integrated T1-derived gray matter regions of interest (ROIs; 23 a-priori ROIs associated with CVD-RFs and dementia), and diffusion MRI-derived white matter tractography into connectivity matrices analyzed for local efficiency and nodal strength. A principal component analysis resulted in three rotated factor scores reflecting executive function (EF; FAS, Trail Making Test (TMT) B-A, Letter-Number Sequencing, Matrix Reasoning); attention/information processing (AIP; TMT-A, TMT-Motor, Digit Symbol); and memory (CVLT-II Trials 1-5 Total, Delayed Free Recall, Recognition Discriminability). Linear regressions between FSRP-10 and connectome ROIs adjusting for word reading, intracranial volume, and white matter hyperintensities revealed negative associations with nodal strength in eight ROIs (p-values<.05) and negative associations with efficiency in two ROIs, and a positive association in one ROI (p-values<.05). There was mediation of bilateral hippocampal strength on FSRP-10 and AIP, and left rostral middle frontal gyrus strength on FSRP-10 and AIP and EF. Stroke risk plays differential roles in connectivity and cognition, suggesting the importance of multi-modal neuroimaging biomarkers in understanding age-related CVD-RF burden and brain-behavior.
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Affiliation(s)
- Elizabeth A Boots
- Department of Psychology, University of Illinois at Chicago, Chicago, IL, 60607, USA; Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Liang Zhan
- Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - Catherine Dion
- Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, 32603, USA
| | - Aimee J Karstens
- Department of Psychology, University of Illinois at Chicago, Chicago, IL, 60607, USA
| | - Jamie C Peven
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - Olusola Ajilore
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, 60612, USA
| | - Melissa Lamar
- Department of Psychology, University of Illinois at Chicago, Chicago, IL, 60607, USA; Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA; Department of Behavioral Sciences, Rush University Medical Center, Chicago, IL, 60612, USA.
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Bora E, McIntyre RS, Ozerdem A. Neurococognitive and neuroimaging correlates of obesity and components of metabolic syndrome in bipolar disorder: a systematic review. Psychol Med 2019; 49:738-749. [PMID: 30326979 DOI: 10.1017/s0033291718003008] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND Individuals with bipolar disorder (BD) have a higher prevalence of obesity and metabolic syndrome (MetS) compared with the general population. Obesity and MetS are associated with cognitive deficits and brain imaging abnormalities in the general population. Obesity and components of MetS might potentially associate with neuroimaging and neurocognitive findings in BD. METHODS A literature search of studies investigating the association between obesity (and other components of MetS) and neurocognitive and neuroimaging findings in BD was conducted. In addition to a systematic review, a random-effects meta-analysis was conducted when sufficient data were available. RESULTS Twenty-three studies were included in the current systematic review. Overweight/obese patients were significantly associated with impaired neurocognition compared normal weight individuals with BD (d = 0.37). The most robust association between obesity and cognitive deficits in BD was observed in the cognitive subdomain of executive functions (d = 0.61). There was also evidence for a significant relationship between cognitive impairment in BD and other components of MetS including hypertension, dyslipidemia, and diabetes. Overweight/obese individuals with BD had more pronounced brain imaging abnormalities than normal weight individuals with BD. CONCLUSIONS Obesity and related cardiovascular risk factors significantly are associated with more severe cognitive and brain imaging abnormalities in BD. Medical co-morbidities can potentially contribute to functional decline observed in some patients throughout the course of BD.
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Affiliation(s)
- Emre Bora
- Department of Psychiatry,Dokuz Eylul University School of Medicine,Izmir,Turkey
| | - Roger S McIntyre
- Department of Psychiatry,University of Toronto,Toronto, ON,Canada
| | - Aysegul Ozerdem
- Department of Psychiatry,Dokuz Eylul University School of Medicine,Izmir,Turkey
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From Heart to Head, Thrombi to Emboli, and Inferences to Extrapolation. J Am Coll Cardiol 2019; 73:1000-1003. [DOI: 10.1016/j.jacc.2019.01.025] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2019] [Accepted: 01/22/2019] [Indexed: 11/24/2022]
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Cigarette smoking and gray matter brain volumes in middle age adults: the CARDIA Brain MRI sub-study. Transl Psychiatry 2019; 9:78. [PMID: 30741945 PMCID: PMC6370765 DOI: 10.1038/s41398-019-0401-1] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Revised: 01/18/2018] [Accepted: 03/26/2018] [Indexed: 12/24/2022] Open
Abstract
Cigarette smoking has been associated with dementia and dementia-related brain changes, notably gray matter (GM) volume atrophy. These associations are thought to reflect the co-morbidity of smoking and vascular, respiratory, and substance use/psychological conditions. However, the extent and localization of the smoking-GM relationship and the degree to which vascular, respiratory, and substance use/psychological factors influence this relationship remain unclear. In the Coronary Artery Risk Development in Young Adults CARDIA cohort (n = 698; 52% women; 40% black participants; age = 50.3 (SD = 3.5)), we examined the associations of smoking status with total GM volume and GM volume of brain regions linked to neurocognitive and addiction disorders. Linear regression models were used to adjust for vascular, respiratory, and substance use/psychological factors and to examine whether they modify the smoking-GM relationship. Compared to never-smokers, current smokers had smaller total GM volume (-8.86 cm3 (95%CI = -13.44, -4.29). Adjustment for substance use/psychological - but not vascular or respiratory - factors substantially attenuated this association (coefficients = -5.54 (95% CI = -10.32, -0.76); -8.33 (95% CI = -12.94, -3.72); -7.69 (95% CI = -6.95, -4.21), respectively). There was an interaction between smoking and alcohol use such that among alcohol non-users, smoking was not related to GM volumes and among alcohol users, those who currently smoked had -12 cm3 smaller total GM, specifically in the frontal and temporal lobes, amygdala, cingulate, and insula. Results suggest a large-magnitude association between smoking and smaller GM volume at middle age, accounting for vascular, respiratory, and substance use/psychological factors, and that the association was strongest in alcohol users. Regions suggested to be most vulnerable are those where cognition and addiction processes overlap.
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42
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Shibata D, Suchy-Dicey A, Carty CL, Madhyastha T, Ali T, Best L, Grabowski TJ, Longstreth WT, Buchwald D. Vascular Risk Factors and Findings on Brain MRI of Elderly Adult American Indians: The Strong Heart Study. Neuroepidemiology 2019; 52:173-180. [PMID: 30677776 PMCID: PMC6986809 DOI: 10.1159/000496343] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2018] [Accepted: 12/17/2018] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Clinical stroke is prevalent in American Indians, but the risk factors for cerebrovascular pathology have not been well-studied in this population. The purpose of this study was to correlate abnormalities on brain magnetic resonance imaging (MRI) with clinical risk factors in a cohort of elderly American Indians. METHODS Brain MRI scans from 789 participants of the Strong Heart Study were analyzed for infarcts, hemorrhage, white matter disease, and measures of cerebral atrophy including ventricular and sulcal grade and total brain volume. Clinical risk factors included measures of hypertension, diabetes, and high levels of low-density lipoprotein (LDL) cholesterol. Regression models adjusted for potential confounders were used to estimate associations between risk factors and brain MRI outcomes. RESULTS -Hypertension was associated with the presence of infarcts (p = 0.001), ventricle enlargement (p = 0.01), and increased white matter hyperintensity volume (p = 0.01). Diabetes was associated with increased prevalence of cerebral atrophy (p < 0.001), ventricular enlargement (p = 0.001), and sulcal widening (p = 0.001). High LDL was not significantly associated with any of the measured cranial imaging outcomes. CONCLUSIONS This study found risk factors for cerebrovascular disease in American Indians similar to those seen in other populations and provides additional evidence for the important roles of hypertension and diabetes in promoting cerebral infarcts and brain atrophy, respectively.
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Affiliation(s)
- Dean Shibata
- Department of Radiology, University of Washington, Seattle, Washington, USA,
| | - Astrid Suchy-Dicey
- Partnerships for Native Health, Washington State University, Seattle, Washington, USA
| | - Cara L Carty
- Partnerships for Native Health, Washington State University, Seattle, Washington, USA.,Elson S Floyd College of Medicine, Washington State University, Seattle, Washington, USA
| | - Tara Madhyastha
- Department of Radiology, University of Washington, Seattle, Washington, USA.,Integrated Brain Imaging Center, University of Washington, Seattle, Washington, USA
| | - Tauqeer Ali
- Center for American Indian Health Research, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma, Oklahoma, USA
| | - Lyle Best
- Strong Heart Study-Dakota Center, Eagle Butte, South Dakota, USA
| | - Thomas J Grabowski
- Integrated Brain Imaging Center, University of Washington, Seattle, Washington, USA.,Department of Neurology, University of Washington, Seattle, Washington, USA
| | - W T Longstreth
- Department of Neurology, University of Washington, Seattle, Washington, USA.,Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Dedra Buchwald
- Partnerships for Native Health, Washington State University, Seattle, Washington, USA.,Elson S Floyd College of Medicine, Washington State University, Seattle, Washington, USA
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Kolenic M, Franke K, Hlinka J, Matejka M, Capkova J, Pausova Z, Uher R, Alda M, Spaniel F, Hajek T. Obesity, dyslipidemia and brain age in first-episode psychosis. J Psychiatr Res 2018; 99:151-158. [PMID: 29454222 DOI: 10.1016/j.jpsychires.2018.02.012] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 02/06/2018] [Accepted: 02/09/2018] [Indexed: 12/31/2022]
Abstract
INTRODUCTION Obesity and dyslipidemia may negatively affect brain health and are frequent medical comorbidities of schizophrenia and related disorders. Despite the high burden of metabolic disorders, little is known about their effects on brain structure in psychosis. We investigated, whether obesity or dyslipidemia contributed to brain alterations in first-episode psychosis (FEP). METHODS 120 participants with FEP, who were undergoing their first psychiatric hospitalization, had <24 months of untreated psychosis and were 18-35 years old and 114 controls within the same age range participated in the study. We acquired 3T brain structural MRI, fasting lipids and body mass index. We used machine learning trained on an independent sample of 504 controls to estimate the individual brain age of study participants and calculated the BrainAGE score by subtracting the chronological from the estimated brain age. RESULTS In a multiple regression model, the diagnosis of FEP (B = 1.15, SE B = 0.31, p < 0.001) and obesity/overweight (B = 0.92, SE B = 0.35, p = 0.008) were each additively associated with BrainAGE scores (R2 = 0.22, F(3, 230) = 21.92, p < 0.001). BrainAGE scores were highest in participants with FEP and obesity/overweight (3.83 years, 95%CI = 2.35-5.31) and lowest in normal weight controls (-0.27 years, 95%CI = -1.22-0.69). LDL-cholesterol, HDL-cholesterol or triglycerides were not associated with BrainAGE scores. CONCLUSIONS Overweight/obesity may be an independent risk factor for diffuse brain alterations manifesting as advanced brain age already early in the course of psychosis. These findings raise the possibility that targeting metabolic health and intervening already at the level of overweight/obesity could slow brain ageing in FEP.
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Affiliation(s)
- Marian Kolenic
- National Institute of Mental Health, Topolová 748, 250 67, Klecany, Czech Republic; 3rd School of Medicine, Charles University, Ruská 87, 100 00, Prague, Czech Republic
| | - Katja Franke
- Structural Brain Mapping Group, Department of Neurology, Jena University Hospital, Erlanger Alle 101, D - 07747, Jena, Germany
| | - Jaroslav Hlinka
- National Institute of Mental Health, Topolová 748, 250 67, Klecany, Czech Republic; Institute of Computer Science, Czech Academy of Sciences, Pod Vodarenskou Vezi 271/2, 182 07, Prague, Czech Republic
| | - Martin Matejka
- 3rd School of Medicine, Charles University, Ruská 87, 100 00, Prague, Czech Republic; Psychiatric Hospital Bohnice, Ústavní 91, 181 00, Prague, Czech Republic; Psychiatric Hospital Kosmonosy, Lípy 15, 293 06, Kosmonosy, Czech Republic
| | - Jana Capkova
- National Institute of Mental Health, Topolová 748, 250 67, Klecany, Czech Republic; 3rd School of Medicine, Charles University, Ruská 87, 100 00, Prague, Czech Republic
| | - Zdenka Pausova
- The Hospital for Sick Children, University of Toronto, 686 Bay Street, 10-9705, Toronto, ON M5G 0A4, Canada
| | - Rudolf Uher
- Dalhousie University, Department of Psychiatry, 5909, Veteran's Memorial Lane, Halifax, NS B3H 2E2, Canada
| | - Martin Alda
- National Institute of Mental Health, Topolová 748, 250 67, Klecany, Czech Republic; Dalhousie University, Department of Psychiatry, 5909, Veteran's Memorial Lane, Halifax, NS B3H 2E2, Canada
| | - Filip Spaniel
- National Institute of Mental Health, Topolová 748, 250 67, Klecany, Czech Republic
| | - Tomas Hajek
- National Institute of Mental Health, Topolová 748, 250 67, Klecany, Czech Republic; Dalhousie University, Department of Psychiatry, 5909, Veteran's Memorial Lane, Halifax, NS B3H 2E2, Canada.
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Kharabian Masouleh S, Beyer F, Lampe L, Loeffler M, Luck T, Riedel-Heller SG, Schroeter ML, Stumvoll M, Villringer A, Witte AV. Gray matter structural networks are associated with cardiovascular risk factors in healthy older adults. J Cereb Blood Flow Metab 2018; 38:360-372. [PMID: 28857651 PMCID: PMC5951018 DOI: 10.1177/0271678x17729111] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
While recent 'big data' analyses discovered structural brain networks that alter with age and relate to cognitive decline, identifying modifiable factors that prevent these changes remains a major challenge. We therefore aimed to determine the effects of common cardiovascular risk factors on vulnerable gray matter (GM) networks in a large and well-characterized population-based cohort. In 616 healthy elderly (258 women, 60-80 years) of the LIFE-Adult-Study, we assessed the effects of obesity, smoking, blood pressure, markers of glucose and lipid metabolism as well as physical activity on major GM-networks derived using linked independent component analysis. Age, sex, hypertension, diabetes, white matter hyperintensities, education and depression were considered as confounders. Results showed that smoking, higher blood pressure, and higher glycated hemoglobin (HbA1c) were independently associated with lower GM volume and thickness in GM-networks that covered most areas of the neocortex. Higher waist-to-hip ratio was independently associated with lower GM volume in a network of multimodal regions that correlated negatively with age and memory performance. In this large cross-sectional study, we found selective negative associations of smoking, higher blood pressure, higher glucose, and visceral obesity with structural covariance networks, suggesting that reducing these factors could help to delay late-life trajectories of GM aging.
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Affiliation(s)
| | - Frauke Beyer
- 1 Department of Neurology, Max Planck Institute for Cognitive and Brain Sciences, Leipzig, Germany
| | - Leonie Lampe
- 1 Department of Neurology, Max Planck Institute for Cognitive and Brain Sciences, Leipzig, Germany.,2 LIFE - Leipzig Research Center for Civilization Diseases, 9180 University of Leipzig , Leipzig, Germany
| | - Markus Loeffler
- 2 LIFE - Leipzig Research Center for Civilization Diseases, 9180 University of Leipzig , Leipzig, Germany.,3 Institute for Medical Informatics, Statistics, and Epidemiology (IMISE), 9180 University of Leipzig , Leipzig, Germany
| | - Tobias Luck
- 2 LIFE - Leipzig Research Center for Civilization Diseases, 9180 University of Leipzig , Leipzig, Germany.,4 Institute of Social Medicine, Occupational Health and Public Health (ISAP), Medical Faculty, 9180 University of Leipzig , Leipzig, Germany
| | - Steffi G Riedel-Heller
- 4 Institute of Social Medicine, Occupational Health and Public Health (ISAP), Medical Faculty, 9180 University of Leipzig , Leipzig, Germany
| | - Matthias L Schroeter
- 1 Department of Neurology, Max Planck Institute for Cognitive and Brain Sciences, Leipzig, Germany.,2 LIFE - Leipzig Research Center for Civilization Diseases, 9180 University of Leipzig , Leipzig, Germany.,5 Clinic for Cognitive Neurology, 9180 University of Leipzig , Leipzig, Germany
| | - Michael Stumvoll
- 6 IFB Adiposity Diseases Faculty of Medicine, 9180 University of Leipzig , Leipzig, Germany
| | - Arno Villringer
- 1 Department of Neurology, Max Planck Institute for Cognitive and Brain Sciences, Leipzig, Germany.,5 Clinic for Cognitive Neurology, 9180 University of Leipzig , Leipzig, Germany
| | - A Veronica Witte
- 1 Department of Neurology, Max Planck Institute for Cognitive and Brain Sciences, Leipzig, Germany
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Tuulari JJ, Karlsson HK, Antikainen O, Hirvonen J, Pham T, Salminen P, Helmiö M, Parkkola R, Nuutila P, Nummenmaa L. Bariatric Surgery Induces White and Grey Matter Density Recovery in the Morbidly Obese: A Voxel-Based Morphometric Study. Hum Brain Mapp 2018; 37:3745-3756. [PMID: 27400738 DOI: 10.1002/hbm.23272] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2015] [Revised: 05/02/2016] [Accepted: 05/17/2016] [Indexed: 01/21/2023] Open
Abstract
Obesity is associated with lowered brain's grey (GM) and white matter (WM) density as measured by voxel-based morphometry (VBM). Nevertheless, it remains unknown whether obesity has a causal influence on cerebral atrophy. We recruited 47 morbidly obese subjects (mean BMI = 42.2, SD = 4.0, 42 females and five males) eligible for bariatric surgery and 29 non-obese subjects (mean BMI = 23.2, SD = 2.8, 23 females and six males) served as controls. Baseline scans were acquired with T1-weighted magnetic resonance imaging (MRI) at 1.5 Tesla; obese participants were scanned again six months after the surgery. Local GM and WM densities were quantified using VBM. Full-volume analyses were used for comparing baseline between-group differences as well as the effects of surgery-induced weight loss in the morbidly obese. Metabolic variables were used in linear models to predict WM and GM densities. Obese subjects had initially lower GM densities in widespread cortical areas including frontal, parietal, and temporal regions as well as insulae. Lower WM densities were observed throughout the WM. Bariatric surgery and concomitant weight loss resulted in global increase in WM density. Grey matter increase was limited to occipital and inferior temporal regions. Metabolic variables were associated with brain densities. We conclude that weight loss results in global recovery of WM as well as local recovery of grey matter densities. These changes likely reflect improved brain tissue integrity. Hum Brain Mapp 37:3745-3756, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
| | | | | | - Jussi Hirvonen
- Turku PET Centre, University of Turku, Turku, Finland.,Department of Radiology, University of Turku, and Turku University Hospital, Turku, Finland
| | - Tam Pham
- Turku PET Centre, University of Turku, Turku, Finland
| | - Paulina Salminen
- Department of Digestive Surgery and Urology, Turku University Hospital, Turku, Finland
| | - Mika Helmiö
- Department of Digestive Surgery and Urology, Turku University Hospital, Turku, Finland
| | - Riitta Parkkola
- Department of Radiology, University of Turku, and Turku University Hospital, Turku, Finland
| | - Pirjo Nuutila
- Turku PET Centre, University of Turku, Turku, Finland.,Department of Endocrinology, Turku University Hospital, Turku, Finland
| | - Lauri Nummenmaa
- Turku PET Centre, University of Turku, Turku, Finland.,Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, Finland.,Department of Psychology, University of Turku, Finland
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King KS, Sheng M, Liu P, Maroules CD, Rubin CD, Peshock RM, McColl RW, Lu H. Detrimental effect of systemic vascular risk factors on brain hemodynamic function assessed with MRI. Neuroradiol J 2018; 31:253-261. [PMID: 29319396 DOI: 10.1177/1971400917750375] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
Background and purpose Vascular risk factors have been associated with decreased cerebral blood flow (CBF) but this is etiologically nonspecific and may result from vascular insufficiency or a response to decreased brain metabolic activity. We apply new MRI techniques to measure oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen consumption (CMRO2), hypothesizing that decreased CBF related to these vascular risk factors will be associated with increased OEF, confirming a primary vascular insufficiency. Methods 3T MRI was obtained on 70 community-based participants in this IRB-approved study with informed consent, with previous assessment of systolic blood pressure, hypertension medication, elevated serum triglycerides, low serum HDL, and diabetes mellitus. CBF was measured using phase contrast adjusted for brain volume (ml/100 g/min), OEF (%) was obtained from T2-Relaxation-Under-Spin-Tagging (TRUST), and CMRO2 (μmol/100 g/min) was derived using the Fick principle. Stepwise linear regression identified optimal predictors of CBF with age, sex, and hematocrit included for adjustment. This predictive model was then evaluated against OEF and CMRO2. Results Hypertriglyceridemia was associated with low CBF and high OEF. High systolic blood pressure was associated with high CBF and low OEF, which was primarily attributable to those with pressures above 160 mmHg. Neither risk factor was associated with significant differences in cerebral metabolic rate. Conclusion Low CBF related to hypertriglyceridemia was accompanied by high OEF with no significant difference in CMRO2, confirming subclinical vascular insufficiency. High CBF related to high systolic blood pressure likely reflected limitations of autoregulation at higher blood pressures.
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Affiliation(s)
- Kevin S King
- 1 Huntington Medical Research Institutes, USA.,2 Department of Radiology, University of Texas Southwestern Medical Center, USA
| | - Min Sheng
- 3 Advanced Imaging Research Center, University of Texas Southwestern Medical Center, USA
| | - Peiying Liu
- 3 Advanced Imaging Research Center, University of Texas Southwestern Medical Center, USA.,4 Department of Radiology, 1501 Johns Hopkins University , USA
| | | | - Craig D Rubin
- 5 Department of Internal Medicine, University of Texas Southwestern Medical Center, USA
| | - Ron M Peshock
- 2 Department of Radiology, University of Texas Southwestern Medical Center, USA.,5 Department of Internal Medicine, University of Texas Southwestern Medical Center, USA
| | - Roderick W McColl
- 2 Department of Radiology, University of Texas Southwestern Medical Center, USA
| | - Hanzhang Lu
- 3 Advanced Imaging Research Center, University of Texas Southwestern Medical Center, USA.,4 Department of Radiology, 1501 Johns Hopkins University , USA
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Yano Y, Reis JP, Levine DA, Bryan RN, Viera AJ, Shimbo D, Tedla YG, Allen NB, Schreiner PJ, Bancks MP, Sidney S, Pletcher MJ, Liu K, Greenland P, Lloyd-Jones DM, Launer LJ. Visit-to-Visit Blood Pressure Variability in Young Adulthood and Hippocampal Volume and Integrity at Middle Age: The CARDIA Study (Coronary Artery Risk Development in Young Adults). Hypertension 2017; 70:1091-1098. [PMID: 28993449 PMCID: PMC5680098 DOI: 10.1161/hypertensionaha.117.10144] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2017] [Revised: 09/15/2017] [Accepted: 09/16/2017] [Indexed: 01/15/2023]
Abstract
The aims of this study are to assess the relationships of visit-to-visit blood pressure (BP) variability in young adulthood to hippocampal volume and integrity at middle age. We used data over 8 examinations spanning 25 years collected in the CARDIA study (Coronary Artery Risk Development in Young Adults) of black and white adults (age, 18-30 years) started in 1985 to 1986. Visit-to-visit BP variability was defined as by SDBP and average real variability (ARVBP, defined as the absolute differences of BP between successive BP measurements). Hippocampal tissue volume standardized by intracranial volume (%) and integrity assessed by fractional anisotropy were measured by 3-Tesla magnetic resonance imaging at the year-25 examination (n=545; mean age, 51 years; 54% women and 34% African Americans). Mean systolic BP (SBP)/diastolic BP levels were 110/69 mm Hg at year 0 (baseline), 117/73 mm Hg at year 25, and ARVSBP and SDSBP were 7.7 and 7.9 mm Hg, respectively. In multivariable-adjusted linear models, higher ARVSBP was associated with lower hippocampal volume (unstandardized regression coefficient [standard error] with 1-SD higher ARVSBP: -0.006 [0.003]), and higher SDSBP with lower hippocampal fractional anisotropy (-0.02 [0.01]; all P<0.05), independent of cumulative exposure to SBP during follow-up. Conversely, cumulative exposure to SBP and diastolic BP was not associated with hippocampal volume. There was no interaction by sex or race between ARVSBP or SDSBP with hippocampal volume or integrity. In conclusion, visit-to-visit BP variability during young adulthood may be useful in assessing the potential risk for reductions in hippocampal volume and integrity in midlife.
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Affiliation(s)
- Yuichiro Yano
- From the Department of Preventive Medicine, University of Mississippi Medical Center, Jackson (Y.Y.); Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Y., Y.G.T., N.B.A., M.P.B., K.L., P.G., D.M.L.-J.); Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (J.P.R.); Division of General Medicine, University of Michigan, Ann Arbor (D.A.L.); Department of Radiology, University of Pennsylvania Health System, Philadelphia (R.N.B.); Department of Family Medicine, Hypertension Research Program, University of North Carolina at Chapel Hill (A.J.V.); Department of Medicine, Columbia University Medical Center, New York, NY (D.S.); Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (P.J.S.); Division of Research, Kaiser Permanente of Northern California, Oakland (S.S.); Department of Epidemiology and Biostatistics, University of California, San Francisco (M.J.P.); and Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD (L.J.L.).
| | - Jared P Reis
- From the Department of Preventive Medicine, University of Mississippi Medical Center, Jackson (Y.Y.); Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Y., Y.G.T., N.B.A., M.P.B., K.L., P.G., D.M.L.-J.); Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (J.P.R.); Division of General Medicine, University of Michigan, Ann Arbor (D.A.L.); Department of Radiology, University of Pennsylvania Health System, Philadelphia (R.N.B.); Department of Family Medicine, Hypertension Research Program, University of North Carolina at Chapel Hill (A.J.V.); Department of Medicine, Columbia University Medical Center, New York, NY (D.S.); Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (P.J.S.); Division of Research, Kaiser Permanente of Northern California, Oakland (S.S.); Department of Epidemiology and Biostatistics, University of California, San Francisco (M.J.P.); and Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD (L.J.L.)
| | - Deborah A Levine
- From the Department of Preventive Medicine, University of Mississippi Medical Center, Jackson (Y.Y.); Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Y., Y.G.T., N.B.A., M.P.B., K.L., P.G., D.M.L.-J.); Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (J.P.R.); Division of General Medicine, University of Michigan, Ann Arbor (D.A.L.); Department of Radiology, University of Pennsylvania Health System, Philadelphia (R.N.B.); Department of Family Medicine, Hypertension Research Program, University of North Carolina at Chapel Hill (A.J.V.); Department of Medicine, Columbia University Medical Center, New York, NY (D.S.); Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (P.J.S.); Division of Research, Kaiser Permanente of Northern California, Oakland (S.S.); Department of Epidemiology and Biostatistics, University of California, San Francisco (M.J.P.); and Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD (L.J.L.)
| | - R Nick Bryan
- From the Department of Preventive Medicine, University of Mississippi Medical Center, Jackson (Y.Y.); Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Y., Y.G.T., N.B.A., M.P.B., K.L., P.G., D.M.L.-J.); Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (J.P.R.); Division of General Medicine, University of Michigan, Ann Arbor (D.A.L.); Department of Radiology, University of Pennsylvania Health System, Philadelphia (R.N.B.); Department of Family Medicine, Hypertension Research Program, University of North Carolina at Chapel Hill (A.J.V.); Department of Medicine, Columbia University Medical Center, New York, NY (D.S.); Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (P.J.S.); Division of Research, Kaiser Permanente of Northern California, Oakland (S.S.); Department of Epidemiology and Biostatistics, University of California, San Francisco (M.J.P.); and Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD (L.J.L.)
| | - Anthony J Viera
- From the Department of Preventive Medicine, University of Mississippi Medical Center, Jackson (Y.Y.); Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Y., Y.G.T., N.B.A., M.P.B., K.L., P.G., D.M.L.-J.); Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (J.P.R.); Division of General Medicine, University of Michigan, Ann Arbor (D.A.L.); Department of Radiology, University of Pennsylvania Health System, Philadelphia (R.N.B.); Department of Family Medicine, Hypertension Research Program, University of North Carolina at Chapel Hill (A.J.V.); Department of Medicine, Columbia University Medical Center, New York, NY (D.S.); Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (P.J.S.); Division of Research, Kaiser Permanente of Northern California, Oakland (S.S.); Department of Epidemiology and Biostatistics, University of California, San Francisco (M.J.P.); and Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD (L.J.L.)
| | - Daichi Shimbo
- From the Department of Preventive Medicine, University of Mississippi Medical Center, Jackson (Y.Y.); Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Y., Y.G.T., N.B.A., M.P.B., K.L., P.G., D.M.L.-J.); Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (J.P.R.); Division of General Medicine, University of Michigan, Ann Arbor (D.A.L.); Department of Radiology, University of Pennsylvania Health System, Philadelphia (R.N.B.); Department of Family Medicine, Hypertension Research Program, University of North Carolina at Chapel Hill (A.J.V.); Department of Medicine, Columbia University Medical Center, New York, NY (D.S.); Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (P.J.S.); Division of Research, Kaiser Permanente of Northern California, Oakland (S.S.); Department of Epidemiology and Biostatistics, University of California, San Francisco (M.J.P.); and Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD (L.J.L.)
| | - Yacob G Tedla
- From the Department of Preventive Medicine, University of Mississippi Medical Center, Jackson (Y.Y.); Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Y., Y.G.T., N.B.A., M.P.B., K.L., P.G., D.M.L.-J.); Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (J.P.R.); Division of General Medicine, University of Michigan, Ann Arbor (D.A.L.); Department of Radiology, University of Pennsylvania Health System, Philadelphia (R.N.B.); Department of Family Medicine, Hypertension Research Program, University of North Carolina at Chapel Hill (A.J.V.); Department of Medicine, Columbia University Medical Center, New York, NY (D.S.); Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (P.J.S.); Division of Research, Kaiser Permanente of Northern California, Oakland (S.S.); Department of Epidemiology and Biostatistics, University of California, San Francisco (M.J.P.); and Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD (L.J.L.)
| | - Norrina B Allen
- From the Department of Preventive Medicine, University of Mississippi Medical Center, Jackson (Y.Y.); Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Y., Y.G.T., N.B.A., M.P.B., K.L., P.G., D.M.L.-J.); Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (J.P.R.); Division of General Medicine, University of Michigan, Ann Arbor (D.A.L.); Department of Radiology, University of Pennsylvania Health System, Philadelphia (R.N.B.); Department of Family Medicine, Hypertension Research Program, University of North Carolina at Chapel Hill (A.J.V.); Department of Medicine, Columbia University Medical Center, New York, NY (D.S.); Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (P.J.S.); Division of Research, Kaiser Permanente of Northern California, Oakland (S.S.); Department of Epidemiology and Biostatistics, University of California, San Francisco (M.J.P.); and Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD (L.J.L.)
| | - Pamela J Schreiner
- From the Department of Preventive Medicine, University of Mississippi Medical Center, Jackson (Y.Y.); Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Y., Y.G.T., N.B.A., M.P.B., K.L., P.G., D.M.L.-J.); Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (J.P.R.); Division of General Medicine, University of Michigan, Ann Arbor (D.A.L.); Department of Radiology, University of Pennsylvania Health System, Philadelphia (R.N.B.); Department of Family Medicine, Hypertension Research Program, University of North Carolina at Chapel Hill (A.J.V.); Department of Medicine, Columbia University Medical Center, New York, NY (D.S.); Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (P.J.S.); Division of Research, Kaiser Permanente of Northern California, Oakland (S.S.); Department of Epidemiology and Biostatistics, University of California, San Francisco (M.J.P.); and Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD (L.J.L.)
| | - Michael P Bancks
- From the Department of Preventive Medicine, University of Mississippi Medical Center, Jackson (Y.Y.); Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Y., Y.G.T., N.B.A., M.P.B., K.L., P.G., D.M.L.-J.); Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (J.P.R.); Division of General Medicine, University of Michigan, Ann Arbor (D.A.L.); Department of Radiology, University of Pennsylvania Health System, Philadelphia (R.N.B.); Department of Family Medicine, Hypertension Research Program, University of North Carolina at Chapel Hill (A.J.V.); Department of Medicine, Columbia University Medical Center, New York, NY (D.S.); Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (P.J.S.); Division of Research, Kaiser Permanente of Northern California, Oakland (S.S.); Department of Epidemiology and Biostatistics, University of California, San Francisco (M.J.P.); and Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD (L.J.L.)
| | - Stephen Sidney
- From the Department of Preventive Medicine, University of Mississippi Medical Center, Jackson (Y.Y.); Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Y., Y.G.T., N.B.A., M.P.B., K.L., P.G., D.M.L.-J.); Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (J.P.R.); Division of General Medicine, University of Michigan, Ann Arbor (D.A.L.); Department of Radiology, University of Pennsylvania Health System, Philadelphia (R.N.B.); Department of Family Medicine, Hypertension Research Program, University of North Carolina at Chapel Hill (A.J.V.); Department of Medicine, Columbia University Medical Center, New York, NY (D.S.); Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (P.J.S.); Division of Research, Kaiser Permanente of Northern California, Oakland (S.S.); Department of Epidemiology and Biostatistics, University of California, San Francisco (M.J.P.); and Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD (L.J.L.)
| | - Mark J Pletcher
- From the Department of Preventive Medicine, University of Mississippi Medical Center, Jackson (Y.Y.); Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Y., Y.G.T., N.B.A., M.P.B., K.L., P.G., D.M.L.-J.); Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (J.P.R.); Division of General Medicine, University of Michigan, Ann Arbor (D.A.L.); Department of Radiology, University of Pennsylvania Health System, Philadelphia (R.N.B.); Department of Family Medicine, Hypertension Research Program, University of North Carolina at Chapel Hill (A.J.V.); Department of Medicine, Columbia University Medical Center, New York, NY (D.S.); Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (P.J.S.); Division of Research, Kaiser Permanente of Northern California, Oakland (S.S.); Department of Epidemiology and Biostatistics, University of California, San Francisco (M.J.P.); and Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD (L.J.L.)
| | - Kiang Liu
- From the Department of Preventive Medicine, University of Mississippi Medical Center, Jackson (Y.Y.); Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Y., Y.G.T., N.B.A., M.P.B., K.L., P.G., D.M.L.-J.); Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (J.P.R.); Division of General Medicine, University of Michigan, Ann Arbor (D.A.L.); Department of Radiology, University of Pennsylvania Health System, Philadelphia (R.N.B.); Department of Family Medicine, Hypertension Research Program, University of North Carolina at Chapel Hill (A.J.V.); Department of Medicine, Columbia University Medical Center, New York, NY (D.S.); Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (P.J.S.); Division of Research, Kaiser Permanente of Northern California, Oakland (S.S.); Department of Epidemiology and Biostatistics, University of California, San Francisco (M.J.P.); and Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD (L.J.L.)
| | - Philip Greenland
- From the Department of Preventive Medicine, University of Mississippi Medical Center, Jackson (Y.Y.); Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Y., Y.G.T., N.B.A., M.P.B., K.L., P.G., D.M.L.-J.); Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (J.P.R.); Division of General Medicine, University of Michigan, Ann Arbor (D.A.L.); Department of Radiology, University of Pennsylvania Health System, Philadelphia (R.N.B.); Department of Family Medicine, Hypertension Research Program, University of North Carolina at Chapel Hill (A.J.V.); Department of Medicine, Columbia University Medical Center, New York, NY (D.S.); Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (P.J.S.); Division of Research, Kaiser Permanente of Northern California, Oakland (S.S.); Department of Epidemiology and Biostatistics, University of California, San Francisco (M.J.P.); and Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD (L.J.L.)
| | - Donald M Lloyd-Jones
- From the Department of Preventive Medicine, University of Mississippi Medical Center, Jackson (Y.Y.); Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Y., Y.G.T., N.B.A., M.P.B., K.L., P.G., D.M.L.-J.); Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (J.P.R.); Division of General Medicine, University of Michigan, Ann Arbor (D.A.L.); Department of Radiology, University of Pennsylvania Health System, Philadelphia (R.N.B.); Department of Family Medicine, Hypertension Research Program, University of North Carolina at Chapel Hill (A.J.V.); Department of Medicine, Columbia University Medical Center, New York, NY (D.S.); Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (P.J.S.); Division of Research, Kaiser Permanente of Northern California, Oakland (S.S.); Department of Epidemiology and Biostatistics, University of California, San Francisco (M.J.P.); and Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD (L.J.L.)
| | - Lenore J Launer
- From the Department of Preventive Medicine, University of Mississippi Medical Center, Jackson (Y.Y.); Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Y., Y.G.T., N.B.A., M.P.B., K.L., P.G., D.M.L.-J.); Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (J.P.R.); Division of General Medicine, University of Michigan, Ann Arbor (D.A.L.); Department of Radiology, University of Pennsylvania Health System, Philadelphia (R.N.B.); Department of Family Medicine, Hypertension Research Program, University of North Carolina at Chapel Hill (A.J.V.); Department of Medicine, Columbia University Medical Center, New York, NY (D.S.); Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (P.J.S.); Division of Research, Kaiser Permanente of Northern California, Oakland (S.S.); Department of Epidemiology and Biostatistics, University of California, San Francisco (M.J.P.); and Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD (L.J.L.)
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Elbejjani M, Schreiner PJ, Siscovick DS, Sidney S, Lewis CE, Bryan NR, Launer LJ. Sex hormones and brain volumes in a longitudinal study of middle-aged men in the CARDIA study. Brain Behav 2017; 7:e00765. [PMID: 29075555 PMCID: PMC5651379 DOI: 10.1002/brb3.765] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Revised: 05/02/2017] [Accepted: 06/03/2017] [Indexed: 01/31/2023] Open
Abstract
INTRODUCTION Several findings suggest that testosterone (T) is neuroprotective and that declining T levels during aging are associated with cognitive and brain pathologies; however, little is known on T and brain health in middle-age. We examined the relationships of total T, bioavailable T, and sex hormone binding globulin (SHBG) levels with total and regional gray matter (GM) and white matter (WM) volumes in middle-aged men. We also evaluated the association of sex hormone levels with cognitive function. METHODS Analysis included 267 community-dwelling men participating in the Coronary Artery Risk Development in Young Adults (CARDIA) brain magnetic resonance imaging (MRI) substudy. Total T, bioavailable T, and SHBG levels were measured at three times from the 2nd to 4th decade of life; brain volumes were measured at the ages of 42-56. Associations were estimated using linear regression models, adjusted for several potential confounders. RESULTS Higher SHBG levels were associated with greater total WM volume (+3.15 cm3 [95% confidence interval [CI] = 0.01, 6.28] per one standard deviation higher SHBG). Higher SHBG levels were associated with lower total and regional GM volumes overall and significantly with smaller parietal GM volume (-0.96 cm3 [95%CI = -1.71, -0.21]). T levels were not related to brain volumes. Neither T nor SHBG levels were associated with cognitive function. CONCLUSION Results suggest a role for SHBG in structural brain outcomes in men and emphasize the value of investigating SHBG levels as modulators of sex hormone and metabolic pathways regulating brain and behavioral characteristics in men.
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Affiliation(s)
- Martine Elbejjani
- Laboratory of Epidemiology and Population ScienceNational Institute on AgingBethesdaMDUSA
| | - Pamela J. Schreiner
- Division of Epidemiology and Community HealthUniversity of MinnesotaMinneapolisMNUSA
| | - David S. Siscovick
- School of Public HealthUniversity of WashingtonSeattleWAUSA
- The New York Academy of MedicineNew York, NYUSA
| | - Stephen Sidney
- Division of ResearchKaiser Permanente Northern CaliforniaOaklandCAUSA
| | - Cora E. Lewis
- Division of Preventive MedicineUniversity of Alabama at BirminghamBirmingham, ALUSA
| | - Nick R. Bryan
- Department of RadiologyUniversity of Pennsylvania Health SystemPhiladelphiaPAUSA
| | - Lenore J. Launer
- Laboratory of Epidemiology and Population ScienceNational Institute on AgingBethesdaMDUSA
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Schwarz NF, Nordstrom LK, Pagen LHG, Palombo DJ, Salat DH, Milberg WP, McGlinchey RE, Leritz EC. Differential associations of metabolic risk factors on cortical thickness in metabolic syndrome. NEUROIMAGE-CLINICAL 2017; 17:98-108. [PMID: 29062686 PMCID: PMC5641920 DOI: 10.1016/j.nicl.2017.09.022] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Revised: 08/31/2017] [Accepted: 09/26/2017] [Indexed: 12/31/2022]
Abstract
Objective Metabolic syndrome (MetS) refers to a cluster of risk factors for cardiovascular disease, including obesity, hypertension, dyslipidemia, and hyperglycemia. While sizable prior literature has examined associations between individual risk factors and quantitative measures of cortical thickness (CT), only very limited research has investigated such measures in MetS. Furthermore, the relative contributions of these risk factors to MetS-related effects on brain morphology have not yet been studied. The primary goal of this investigation was to examine how MetS may affect CT. A secondary goal was to explore the relative contributions of individual risk factors to regional alterations in CT, with the potential to identify risk factor combinations that may underlie structural changes. Methods Eighteen participants with MetS (mean age = 59.78 years) were age-matched with 18 healthy control participants (mean age = 60.50 years). CT measures were generated from T1-weighted images and groups were contrasted using whole-brain general linear modeling. A follow-up multivariate partial least squares correlation (PLS) analysis, including the full study sample with complete risk factor measurements (N = 53), was employed to examine which risk factors account for variance in group structural differences. Results Participants with MetS demonstrated significantly reduced CT in left hemisphere inferior parietal, rostral middle frontal, and lateral occipital clusters and in a right hemisphere precentral cluster. The PLS analysis revealed that waist circumference, high-density lipoprotein cholesterol (HDL-C), triglycerides, and glucose were significant contributors to reduced CT in these clusters. In contrast, diastolic blood pressure showed a significantly positive association with CT while systolic blood pressure did not emerge as a significant contributor. Age was not associated with CT. Conclusion These results indicate that MetS can be associated with regionally specific reductions in CT. Importantly, a novel link between a risk factor profile comprising indices of obesity, hyperglycemia, dyslipidemia and diastolic BP and localized alterations in CT emerged. While the pathophysiological mechanisms underlying these associations remain incompletely understood, these findings may be relevant for future investigations of MetS and might have implications for treatment approaches that focus on specific risk factor profiles with the aim to reduce negative consequences on the structural integrity of the brain. Cortical thickness is reduced bilaterally in metabolic syndrome. Five out of six risk factor components contribute to altered cortical thickness. Particular risk factor combination may be an important target for intervention.
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Affiliation(s)
- Nicolette F Schwarz
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), Veterans Administration Boston Healthcare System, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Leslie K Nordstrom
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), Veterans Administration Boston Healthcare System, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Linda H G Pagen
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), Veterans Administration Boston Healthcare System, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Daniela J Palombo
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), Veterans Administration Boston Healthcare System, Boston, MA, USA; Boston University School of Medicine, Boston, MA, USA
| | - David H Salat
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), Veterans Administration Boston Healthcare System, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; The Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA, USA
| | - William P Milberg
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), Veterans Administration Boston Healthcare System, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Regina E McGlinchey
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), Veterans Administration Boston Healthcare System, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Elizabeth C Leritz
- Neuroimaging Research for Veterans Center (NeRVe), Geriatric Research Education and Clinical Center (GRECC), Veterans Administration Boston Healthcare System, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
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Abstract
Purpose of Review In this review, we summarise the evidence on the association between cardiovascular disease (CVD) and cognitive impairment and explore the role of the nitric oxide (NO) pathway as a causal mechanism. Recent Findings Evidence from epidemiological studies suggests that the presence of CVD and its risk factors in midlife is associated with an increased risk of later life cognitive impairment and dementia. It is unclear what is driving this association but risk may be conveyed via an increase in neurodegeneration (e.g. amyloid deposition), vascular changes (e.g. small vessel disease) and mechanistically due to increased levels of oxidative stress and inflammation as well as changes in NO bioavailability. Summary CVDs and dementia are major challenges to global health worldwide. The NO pathway may be a promising biological candidate for future studies focused on reducing not only CVD but also risk of cognitive decline and dementia.
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