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Maciocha F, Suchanecka A, Chmielowiec K, Chmielowiec J, Ciechanowicz A, Boroń A. Correlations of the CNR1 Gene with Personality Traits in Women with Alcohol Use Disorder. Int J Mol Sci 2024; 25:5174. [PMID: 38791212 PMCID: PMC11121729 DOI: 10.3390/ijms25105174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 05/02/2024] [Accepted: 05/07/2024] [Indexed: 05/26/2024] Open
Abstract
Alcohol use disorder (AUD) is a significant issue affecting women, with severe consequences for society, the economy, and most importantly, health. Both personality and alcohol use disorders are phenotypically very complex, and elucidating their shared heritability is a challenge for medical genetics. Therefore, our study investigated the correlations between the microsatellite polymorphism (AAT)n of the Cannabinoid Receptor 1 (CNR1) gene and personality traits in women with AUD. The study group included 187 female subjects. Of these, 93 were diagnosed with alcohol use disorder, and 94 were controls. Repeat length polymorphism of microsatellite regions (AAT)n in the CNR1 gene was identified with PCR. All participants were assessed with the Mini-International Neuropsychiatric Interview and completed the NEO Five-Factor and State-Trait Anxiety Inventories. In the group of AUD subjects, significantly fewer (AAT)n repeats were present when compared with controls (p = 0.0380). While comparing the alcohol use disorder subjects (AUD) and the controls, we observed significantly higher scores on the STAI trait (p < 0.00001) and state scales (p = 0.0001) and on the NEO Five-Factor Inventory Neuroticism (p < 0.00001) and Openness (p = 0.0237; insignificant after Bonferroni correction) scales. Significantly lower results were obtained on the NEO-FFI Extraversion (p = 0.00003), Agreeability (p < 0.00001) and Conscientiousness (p < 0.00001) scales by the AUD subjects when compared to controls. There was no statistically significant Pearson's linear correlation between the number of (AAT)n repeats in the CNR1 gene and the STAI and NEO Five-Factor Inventory scores in the group of AUD subjects. In contrast, Pearson's linear correlation analysis in controls showed a positive correlation between the number of the (AAT)n repeats and the STAI state scale (r = 0.184; p = 0.011; insignificant after Bonferroni correction) and a negative correlation with the NEO-FFI Openness scale (r = -0.241; p = 0.001). Interestingly, our study provided data on two separate complex issues, i.e., (1) the association of (AAT)n CNR1 repeats with the AUD in females; (2) the correlation of (AAT)n CNR1 repeats with anxiety as a state and Openness in non-alcohol dependent subjects. In conclusion, our study provided a plethora of valuable data for improving our understanding of alcohol use disorder and anxiety.
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Affiliation(s)
- Filip Maciocha
- Department of Clinical and Molecular Biochemistry, Pomeranian Medical University in Szczecin, Powstańców Wielkopolskich 72 St., 70-111 Szczecin, Poland; (F.M.); (A.C.)
| | - Aleksandra Suchanecka
- Independent Laboratory of Behavioral Genetics and Epigenetics, Pomeranian Medical University in Szczecin, Powstańców Wielkopolskich 72 St., 70-111 Szczecin, Poland;
| | - Krzysztof Chmielowiec
- Department of Hygiene and Epidemiology, Collegium Medicum, University of Zielona Góra, 28 Zyty St., 65-046 Zielona Góra, Poland; (K.C.); (J.C.)
| | - Jolanta Chmielowiec
- Department of Hygiene and Epidemiology, Collegium Medicum, University of Zielona Góra, 28 Zyty St., 65-046 Zielona Góra, Poland; (K.C.); (J.C.)
| | - Andrzej Ciechanowicz
- Department of Clinical and Molecular Biochemistry, Pomeranian Medical University in Szczecin, Powstańców Wielkopolskich 72 St., 70-111 Szczecin, Poland; (F.M.); (A.C.)
| | - Agnieszka Boroń
- Department of Clinical and Molecular Biochemistry, Pomeranian Medical University in Szczecin, Powstańców Wielkopolskich 72 St., 70-111 Szczecin, Poland; (F.M.); (A.C.)
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Fernández A, Cuesta P, Marcos A, Montenegro-Peña M, Yus M, Rodríguez-Rojo IC, Bruña R, Maestú F, López ME. Sex differences in the progression to Alzheimer's disease: a combination of functional and structural markers. GeroScience 2024; 46:2619-2640. [PMID: 38105400 PMCID: PMC10828170 DOI: 10.1007/s11357-023-01020-z] [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] [Received: 01/29/2023] [Accepted: 11/14/2023] [Indexed: 12/19/2023] Open
Abstract
Mild cognitive impairment (MCI) has been frequently interpreted as a transitional phase between healthy cognitive aging and dementia, particularly of the Alzheimer's disease (AD) type. Of note, few studies explored that transition from a multifactorial perspective, taking into consideration the effect of basic factors such as biological sex. In the present study 96 subjects with MCI (37 males and 59 females) were followed-up and divided into two subgroups according to their clinical outcome: "progressive" MCI (pMCI = 41), if they fulfilled the diagnostic criteria for AD at the end of follow-up; and "stable" MCI (sMCI = 55), if they remained with the initial diagnosis. Different markers were combined to characterize sex differences between groups, including magnetoencephalography recordings, cognitive performance, and brain volumes derived from magnetic resonance imaging. Results indicated that the pMCI group exhibited higher low-frequency activity, lower scores in neuropsychological tests and reduced brain volumes than the sMCI group, being these measures significantly correlated. When sex was considered, results revealed that this pattern was mainly due to the influence of the females' sample. Overall, females exhibited lower cognitive scores and reduced brain volumes. More interestingly, females in the pMCI group showed an increased theta activity that correlated with a more abrupt reduction of cognitive and volumetric scores as compared with females in the sMCI group and with males in the pMCI group. These findings suggest that females' brains might be more vulnerable to the effects of AD pathology, since regardless of age, they showed signs of more pronounced deterioration than males.
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Affiliation(s)
- Alberto Fernández
- Department of Legal Medicine, Psychiatry and Pathology, Universidad Complutense de Madrid, Madrid, Spain
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
| | - Pablo Cuesta
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
- Department of Radiology, Rehabilitation and Physiotherapy, Universidad Complutense de Madrid, Madrid, Spain
| | - Alberto Marcos
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
- Neurology Department, Hospital Clínico San Carlos, Madrid, Spain
| | - Mercedes Montenegro-Peña
- Centre for the Prevention of Cognitive Impairment, Madrid Salud, Madrid City Council, Madrid, Spain
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain
| | - Miguel Yus
- Radiology Department, Hospital Clínico San Carlos, Madrid, Spain
| | - Inmaculada Concepción Rodríguez-Rojo
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Nursing and Psysiotherapy, Universidad de Alcalá, Madrid, Spain
| | - Ricardo Bruña
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
- Department of Radiology, Rehabilitation and Physiotherapy, Universidad Complutense de Madrid, Madrid, Spain
| | - Fernando Maestú
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain
| | - María Eugenia López
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain.
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain.
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain.
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3
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Lafta MS, Mwinyi J, Affatato O, Rukh G, Dang J, Andersson G, Schiöth HB. Exploring sex differences: insights into gene expression, neuroanatomy, neurochemistry, cognition, and pathology. Front Neurosci 2024; 18:1340108. [PMID: 38449735 PMCID: PMC10915038 DOI: 10.3389/fnins.2024.1340108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 02/09/2024] [Indexed: 03/08/2024] Open
Abstract
Increased knowledge about sex differences is important for development of individualized treatments against many diseases as well as understanding behavioral and pathological differences. This review summarizes sex chromosome effects on gene expression, epigenetics, and hormones in relation to the brain. We explore neuroanatomy, neurochemistry, cognition, and brain pathology aiming to explain the current state of the art. While some domains exhibit strong differences, others reveal subtle differences whose overall significance warrants clarification. We hope that the current review increases awareness and serves as a basis for the planning of future studies that consider both sexes equally regarding similarities and differences.
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Affiliation(s)
- Muataz S. Lafta
- Department of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, Uppsala, Sweden
| | - Jessica Mwinyi
- Department of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, Uppsala, Sweden
- Centre for Women’s Mental Health, Uppsala University, Uppsala, Sweden
| | - Oreste Affatato
- Department of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, Uppsala, Sweden
- Centre for Women’s Mental Health, Uppsala University, Uppsala, Sweden
| | - Gull Rukh
- Department of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, Uppsala, Sweden
| | - Junhua Dang
- Department of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, Uppsala, Sweden
| | - Gerhard Andersson
- Department of Behavioural Sciences and Learning, Linköping University, Linköping, Sweden
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Helgi B. Schiöth
- Department of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, Uppsala, Sweden
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Hill AT, Bailey NW, Zomorrodi R, Hadas I, Kirkovski M, Das S, Lum JAG, Enticott PG. EEG microstates in early-to-middle childhood show associations with age, biological sex, and alpha power. Hum Brain Mapp 2023; 44:6484-6498. [PMID: 37873867 PMCID: PMC10681660 DOI: 10.1002/hbm.26525] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 10/04/2023] [Accepted: 10/06/2023] [Indexed: 10/25/2023] Open
Abstract
Electroencephalographic (EEG) microstates can provide a unique window into the temporal dynamics of large-scale brain networks across brief (millisecond) timescales. Here, we analysed fundamental temporal features of microstates extracted from the broadband EEG signal in a large (N = 139) cohort of children spanning early-to-middle childhood (4-12 years of age). Linear regression models were used to examine if participants' age and biological sex could predict the temporal parameters GEV, duration, coverage, and occurrence, for five microstate classes (A-E) across both eyes-closed and eyes-open resting-state recordings. We further explored associations between these microstate parameters and posterior alpha power after removal of the 1/f-like aperiodic signal. The microstates obtained from our neurodevelopmental EEG recordings broadly replicated the four canonical microstate classes (A to D) frequently reported in adults, with the addition of the more recently established microstate class E. Biological sex served as a significant predictor in the regression models for four of the five microstate classes (A, C, D, and E). In addition, duration and occurrence for microstate E were both found to be positively associated with age for the eyes-open recordings, while the temporal parameters of microstates C and E both exhibited associations with alpha band spectral power. Together, these findings highlight the influence of age and sex on large-scale functional brain networks during early-to-middle childhood, extending understanding of neural dynamics across this important period for brain development.
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Affiliation(s)
- Aron T. Hill
- Cognitive Neuroscience Unit, School of PsychologyDeakin UniversityGeelongAustralia
- Department of Psychiatry, Central Clinical SchoolMonash UniversityMelbourneAustralia
| | - Neil W. Bailey
- Monarch Research InstituteMonarch Mental Health GroupSydneyAustralia
- School of Medicine and PsychologyThe Australian National UniversityCanberraAustralia
| | - Reza Zomorrodi
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental HealthUniversity of TorontoTorontoCanada
| | - Itay Hadas
- Department of Psychiatry, School of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Melissa Kirkovski
- Cognitive Neuroscience Unit, School of PsychologyDeakin UniversityGeelongAustralia
- Institute for Health and SportVictoria UniversityMelbourneAustralia
| | - Sushmit Das
- Azrieli Adult Neurodevelopmental CentreCentre for Addiction and Mental HealthTorontoCanada
| | - Jarrad A. G. Lum
- Cognitive Neuroscience Unit, School of PsychologyDeakin UniversityGeelongAustralia
| | - Peter G. Enticott
- Cognitive Neuroscience Unit, School of PsychologyDeakin UniversityGeelongAustralia
- Department of Psychiatry, Central Clinical SchoolMonash UniversityMelbourneAustralia
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Spalek K, Coynel D, de Quervain D, Milnik A. Sex-dependent differences in connectivity patterns are related to episodic memory recall. Hum Brain Mapp 2023; 44:5612-5623. [PMID: 37647201 PMCID: PMC10619411 DOI: 10.1002/hbm.26465] [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] [Received: 04/03/2023] [Revised: 07/12/2023] [Accepted: 08/08/2023] [Indexed: 09/01/2023] Open
Abstract
Previous studies have shown that females typically outperform males on episodic memory tasks. In this study, we investigated if (1) there are differences between males and females in their connectome characteristics, (2) if these connectivity patterns are associated with memory performance, and (3) if these brain connectome characteristics contribute to the differences in episodic memory performance between sexes. In a sample of 655 healthy young subjects (n = 391 females; n = 264 males), we derived brain network characteristics from diffusion-weighted imaging (DWI) data using models of crossing fibers within each voxel of the brain and probabilistic tractography (graph strength, shortest path length, global efficiency, and weighted transitivity). Group differences were analysed with linear models and mediation analyses were used to explore how connectivity patterns might relate to sex-dependent differences in memory performance. Our results show significant sex-dependent differences in weighted transitivity (d = 0.42), with males showing higher values. Further, we observed a negative association between weighted transitivity and memory performance (r = -0.12). Finally, these distinct connectome characteristics partially mediated the observed differences in memory performance (effect size of the indirect effect r = 0.02). Our findings indicate a higher interconnectedness in females compared to males. Additionally, we demonstrate that the sex-dependent differences in episodic memory performance can be partially explained by the differences in this connectome measure. These results further underscore the importance of sex-dependent differences in brain connectivity and their impact on cognitive function.
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Affiliation(s)
- Klara Spalek
- Division of Cognitive NeuroscienceDepartment of BiomedicineUniversity of BaselBaselSwitzerland
- Division of Molecular NeuroscienceDepartment of BiomedicineUniversity of BaselBaselSwitzerland
- Hoekzema Lab, Adult PsychiatryUniversity Medical Centre AmsterdamAmsterdamNetherlands
| | - David Coynel
- Division of Cognitive NeuroscienceDepartment of BiomedicineUniversity of BaselBaselSwitzerland
- Research Cluster Molecular and Cognitive NeurosciencesUniversity of BaselBaselSwitzerland
| | - Dominique de Quervain
- Division of Cognitive NeuroscienceDepartment of BiomedicineUniversity of BaselBaselSwitzerland
- Research Cluster Molecular and Cognitive NeurosciencesUniversity of BaselBaselSwitzerland
- Psychiatric University Clinics, University of BaselBaselSwitzerland
| | - Annette Milnik
- Division of Cognitive NeuroscienceDepartment of BiomedicineUniversity of BaselBaselSwitzerland
- Division of Molecular NeuroscienceDepartment of BiomedicineUniversity of BaselBaselSwitzerland
- Psychiatric University Clinics, University of BaselBaselSwitzerland
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6
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Kabbej N, Ashby FJ, Riva A, Gamlin PD, Mandel RJ, Kunta A, Rouse CJ, Heldermon CD. Sex differences in brain transcriptomes of juvenile Cynomolgus macaques. RESEARCH SQUARE 2023:rs.3.rs-3422091. [PMID: 38045237 PMCID: PMC10690328 DOI: 10.21203/rs.3.rs-3422091/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Background: Behavioral, social, and physical characteristics are posited to distinguish the sexes, yet research on transcription-level sexual differences in the brain is limited. Here, we investigated sexually divergent brain transcriptomics in prepubertal cynomolgus macaques, a commonly used surrogate species to humans. Methods: A transcriptomic profile using RNA sequencing was generated for the temporal lobe, ventral midbrain, and cerebellum of 3 female and 3 male cynomolgus macaques previously treated with an Adeno-associated virus vector mix. Statistical analyses to determine differentially expressed protein-coding genes in all three lobes were conducted using DeSeq2 with a false discovery rate corrected P value of .05. Results: We identified target genes in the temporal lobe, ventral midbrain, and cerebellum with functions in translation, immunity, behavior, and neurological disorders that exhibited statistically significant sexually divergent expression. Conclusions: We provide potential mechanistic insights to the epidemiological differences observed between the sexes with regards to mental health and infectious diseases, such as COVID19. Our results provide pre-pubertal information on sexual differences in non-human primate brain transcriptomics and may provide insight to health disparities between the biological sexes in humans.
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VanderLaan DP, Skorska MN, Peragine DE, Coome LA. Carving the Biodevelopment of Same-Sex Sexual Orientation at Its Joints. ARCHIVES OF SEXUAL BEHAVIOR 2023; 52:2939-2962. [PMID: 35960401 DOI: 10.1007/s10508-022-02360-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 05/30/2022] [Accepted: 06/04/2022] [Indexed: 06/15/2023]
Abstract
Sexual orientation is a core aspect of human experience and understanding its development is fundamental to psychology as a scientific discipline. Biological perspectives have played an important role in uncovering the processes that contribute to sexual orientation development. Research in this field has relied on a variety of populations, including community, clinical, and cross-cultural samples, and has commonly focused on female gynephilia (i.e., female sexual attraction to adult females) and male androphilia (i.e., male sexual attraction to adult males). Genetic, hormonal, and immunological processes all appear to influence sexual orientation. Consistent with biological perspectives, there are sexual orientation differences in brain development and evidence indicates that similar biological influences apply across cultures. An outstanding question in the field is whether the hypothesized biological influences are all part of the same process or represent different developmental pathways leading to same-sex sexual orientation. Some studies indicate that same-sex sexually oriented people can be divided into subgroups who likely experienced different biological influences. Consideration of gender expression in addition to sexual orientation might help delineate such subgroups. Thus, future research on the possible existence of such subgroups could prove to be valuable for uncovering the biological development of sexual orientation. Recommendations for such future research are discussed.
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Affiliation(s)
- Doug P VanderLaan
- Department of Psychology, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON, L5L 1C6, Canada.
- Child and Youth Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada.
| | - Malvina N Skorska
- Child and Youth Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Diana E Peragine
- Department of Psychology, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON, L5L 1C6, Canada
| | - Lindsay A Coome
- Department of Psychology, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON, L5L 1C6, Canada
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Alahmadi AA, Alotaibi NO, Hakami NY, Almutairi RS, Darwesh AM, Abdeen R, Alghamdi J, Abdulaal OM, Alsharif W, Sultan SR, Kanbayti IH. Gender and cytoarchitecture differences: Functional connectivity of the hippocampal sub-regions. Heliyon 2023; 9:e20389. [PMID: 37780771 PMCID: PMC10539667 DOI: 10.1016/j.heliyon.2023.e20389] [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: 12/10/2022] [Revised: 07/27/2023] [Accepted: 09/20/2023] [Indexed: 10/03/2023] Open
Abstract
Introduction The hippocampus plays a significant role in learning, memory encoding, and spatial navigation. Typically, the hippocampus is investigated as a whole region of interest. However, recent work has developed fully detailed atlases based on cytoarchitecture properties of brain regions, and the hippocampus has been sub-divided into seven sub-areas that have structural differences in terms of distinct numbers of cells, neurons, and other structural and chemical properties. Moreover, gender differences are of increasing concern in neuroscience research. Several neuroscience studies have found structural and functional variations between the brain regions of females and males, and the hippocampus is one of these regions. Aim The aim of this study to explore whether the cytoarchitecturally distinct sub-regions of the hippocampus have varying patterns of functional connectivity with different networks of the brain and how these functional connections differ in terms of gender differences. Method This study investigated 200 healthy participants using seed-based resting-state functional magnetic resonance imaging (rsfMRI). The primary aim of this study was to explore the resting connectivity and gender distinctions associated with specific sub-regions of the hippocampus and their relationship with major functional brain networks. Results The findings revealed that the majority of the seven hippocampal sub-regions displayed functional connections with key brain networks, and distinct patterns of functional connectivity were observed between the hippocampal sub-regions and various functional networks within the brain. Notably, the default and visual networks exhibited the most consistent functional connections. Additionally, gender-based analysis highlighted evident functional resemblances and disparities, particularly concerning the anterior section of the hippocampus. Conclusion This study highlighted the functional connectivity patterns and involvement of the hippocampal sub-regions in major brain functional networks, indicating that the hippocampus should be investigated as a region of multiple distinct functions and should always be examined as sub-regions of interest. The results also revealed clear gender differences in functional connectivity.
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Affiliation(s)
- Adnan A.S. Alahmadi
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
- NMR Research Unit, Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Nada O. Alotaibi
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Norah Y. Hakami
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Raghad S. Almutairi
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Afnan M.F. Darwesh
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Rawan Abdeen
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Jamaan Alghamdi
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Osamah M. Abdulaal
- Diagnostic Radiology Technology, College of Applied Medical Sciences, Taibah University, Madina, Saudi Arabia
| | - Walaa Alsharif
- Diagnostic Radiology Technology, College of Applied Medical Sciences, Taibah University, Madina, Saudi Arabia
| | - Salahaden R. Sultan
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Ibrahem H. Kanbayti
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
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Kheloui S, Jacmin-Park S, Larocque O, Kerr P, Rossi M, Cartier L, Juster RP. Sex/gender differences in cognitive abilities. Neurosci Biobehav Rev 2023; 152:105333. [PMID: 37517542 DOI: 10.1016/j.neubiorev.2023.105333] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 07/09/2023] [Accepted: 07/27/2023] [Indexed: 08/01/2023]
Abstract
Sex/gender differences in cognitive sciences are riddled by conflicting perspectives. At the center of debates are clinical, social, and political perspectives. Front and center, evolutionary and biological perspectives have often focused on 'nature' arguments, while feminist and constructivist views have often focused on 'nurture arguments regarding cognitive sex differences. In the current narrative review, we provide a comprehensive overview regarding the origins and historical advancement of these debates while providing a summary of the results in the field of sexually polymorphic cognition. In so doing, we attempt to highlight the importance of using transdisciplinary perspectives which help bridge disciplines together to provide a refined understanding the specific factors that drive sex differences a gender diversity in cognitive abilities. To summarize, biological sex (e.g., birth-assigned sex, sex hormones), socio-cultural gender (gender identity, gender roles), and sexual orientation each uniquely shape the cognitive abilities reviewed. To date, however, few studies integrate these sex and gender factors together to better understand individual differences in cognitive functioning. This has potential benefits if a broader understanding of sex and gender factors are systematically measured when researching and treating numerous conditions where cognition is altered.
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Affiliation(s)
- Sarah Kheloui
- Department of Psychiatry and Addiction, University of Montreal, Montreal, Quebec, Canada; Department of Psychology, Université du Québec à Montréal, Montreal, Quebec, Canada; Centre de recherche de l'Institut universitaire en santé mentale de Montréal, Canada; Center on Sex⁎Gender, Allostasis and Resilience, Canada
| | - Silke Jacmin-Park
- Department of Psychology, University of Montreal, Montreal, Quebec, Canada; Department of Psychology, Université du Québec à Montréal, Montreal, Quebec, Canada; Centre de recherche de l'Institut universitaire en santé mentale de Montréal, Canada; Center on Sex⁎Gender, Allostasis and Resilience, Canada
| | - Ophélie Larocque
- Department of Psychology, University of Montreal, Montreal, Quebec, Canada; Department of Psychology, Université du Québec à Montréal, Montreal, Quebec, Canada; Centre de recherche de l'Institut universitaire en santé mentale de Montréal, Canada; Center on Sex⁎Gender, Allostasis and Resilience, Canada
| | - Philippe Kerr
- Department of Psychiatry and Addiction, University of Montreal, Montreal, Quebec, Canada; Department of Psychology, Université du Québec à Montréal, Montreal, Quebec, Canada; Centre de recherche de l'Institut universitaire en santé mentale de Montréal, Canada; Center on Sex⁎Gender, Allostasis and Resilience, Canada
| | - Mathias Rossi
- Department of Psychiatry and Addiction, University of Montreal, Montreal, Quebec, Canada; Department of Psychology, Université du Québec à Montréal, Montreal, Quebec, Canada; Centre de recherche de l'Institut universitaire en santé mentale de Montréal, Canada; Center on Sex⁎Gender, Allostasis and Resilience, Canada
| | - Louis Cartier
- Department of Psychiatry and Addiction, University of Montreal, Montreal, Quebec, Canada; Department of Psychology, Université du Québec à Montréal, Montreal, Quebec, Canada; Centre de recherche de l'Institut universitaire en santé mentale de Montréal, Canada; Center on Sex⁎Gender, Allostasis and Resilience, Canada
| | - Robert-Paul Juster
- Department of Psychiatry and Addiction, University of Montreal, Montreal, Quebec, Canada; Department of Psychology, Université du Québec à Montréal, Montreal, Quebec, Canada; Centre de recherche de l'Institut universitaire en santé mentale de Montréal, Canada; Center on Sex⁎Gender, Allostasis and Resilience, Canada.
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Castro-Fonseca E, Morais V, da Silva CG, Wollner J, Freitas J, Mello-Neto AF, Oliveira LE, de Oliveira VC, Leite REP, Alho AT, Rodriguez RD, Ferretti-Rebustini REL, Suemoto CK, Jacob-Filho W, Nitrini R, Pasqualucci CA, Grinberg LT, Tovar-Moll F, Lent R. The influence of age and sex on the absolute cell numbers of the human brain cerebral cortex. Cereb Cortex 2023; 33:8654-8666. [PMID: 37106573 PMCID: PMC10321098 DOI: 10.1093/cercor/bhad148] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 04/13/2023] [Accepted: 04/14/2023] [Indexed: 04/29/2023] Open
Abstract
The human cerebral cortex is one of the most evolved regions of the brain, responsible for most higher-order neural functions. Since nerve cells (together with synapses) are the processing units underlying cortical physiology and morphology, we studied how the human neocortex is composed regarding the number of cells as a function of sex and age. We used the isotropic fractionator for cell quantification of immunocytochemically labeled nuclei from the cerebral cortex donated by 43 cognitively healthy subjects aged 25-87 years old. In addition to previously reported sexual dimorphism in the medial temporal lobe, we found more neurons in the occipital lobe of men, higher neuronal density in women's frontal lobe, but no sex differences in the number and density of cells in the other lobes and the whole neocortex. On average, the neocortex has ~10.2 billion neurons, 34% in the frontal lobe and the remaining 66% uniformly distributed among the other 3 lobes. Along typical aging, there is a loss of non-neuronal cells in the frontal lobe and the preservation of the number of neurons in the cortex. Our study made possible to determine the different degrees of modulation that sex and age evoke on cortical cellularity.
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Affiliation(s)
- Emily Castro-Fonseca
- Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
- D’Or Institute for Research and Education, Rio de Janeiro, Brazil
| | - Viviane Morais
- Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Camila G da Silva
- Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Juliana Wollner
- Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Jaqueline Freitas
- Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Arthur F Mello-Neto
- Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Luiz E Oliveira
- Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Vilson C de Oliveira
- Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Renata E P Leite
- Biobank for Aging Studies, LIM 22, University of São Paulo Medical School, São Paulo, Brazil
- Laboratory of Medical Research in Aging (LIM-66), University of São Paulo Medical School, São Paulo, Brazil
| | - Ana T Alho
- Biobank for Aging Studies, LIM 22, University of São Paulo Medical School, São Paulo, Brazil
| | - Roberta D Rodriguez
- Biobank for Aging Studies, LIM 22, University of São Paulo Medical School, São Paulo, Brazil
- Department of Pathology, University of São Paulo Medical School, São Paulo, Brazil
| | - Renata E L Ferretti-Rebustini
- Biobank for Aging Studies, LIM 22, University of São Paulo Medical School, São Paulo, Brazil
- Department of Medical Surgical Nursing, University of São Paulo School of Nursing, São Paulo, Brazil
| | - Claudia K Suemoto
- Biobank for Aging Studies, LIM 22, University of São Paulo Medical School, São Paulo, Brazil
- Laboratory of Medical Research in Aging (LIM-66), University of São Paulo Medical School, São Paulo, Brazil
| | - Wilson Jacob-Filho
- Biobank for Aging Studies, LIM 22, University of São Paulo Medical School, São Paulo, Brazil
- Laboratory of Medical Research in Aging (LIM-66), University of São Paulo Medical School, São Paulo, Brazil
| | - Ricardo Nitrini
- Biobank for Aging Studies, LIM 22, University of São Paulo Medical School, São Paulo, Brazil
- Department of Neurology, University of São Paulo Medical School, São Paulo, Brazil
| | - Carlos A Pasqualucci
- Biobank for Aging Studies, LIM 22, University of São Paulo Medical School, São Paulo, Brazil
- Department of Pathology, University of São Paulo Medical School, São Paulo, Brazil
| | - Lea T Grinberg
- Biobank for Aging Studies, LIM 22, University of São Paulo Medical School, São Paulo, Brazil
- Department of Pathology, University of São Paulo Medical School, São Paulo, Brazil
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, United States
| | - Fernanda Tovar-Moll
- Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
- D’Or Institute for Research and Education, Rio de Janeiro, Brazil
| | - Roberto Lent
- Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
- D’Or Institute for Research and Education, Rio de Janeiro, Brazil
- National Institute of Translational Neuroscience, Ministry of Science and Technology, São Paulo, Brazil
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11
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Evans TE, Knol MJ, Schwingenschuh P, Wittfeld K, Hilal S, Ikram MA, Dubost F, van Wijnen KMH, Katschnig P, Yilmaz P, de Bruijne M, Habes M, Chen C, Langer S, Völzke H, Ikram MK, Grabe HJ, Schmidt R, Adams HHH, Vernooij MW. Determinants of Perivascular Spaces in the General Population: A Pooled Cohort Analysis of Individual Participant Data. Neurology 2023; 100:e107-e122. [PMID: 36253103 PMCID: PMC9841448 DOI: 10.1212/wnl.0000000000201349] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 08/19/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Perivascular spaces (PVS) are emerging markers of cerebral small vessel disease (CSVD), but research on their determinants has been hampered by conflicting results from small single studies using heterogeneous rating methods. In this study, we therefore aimed to identify determinants of PVS burden in a pooled analysis of multiple cohort studies using 1 harmonized PVS rating method. METHODS Individuals from 10 population-based cohort studies with adult participants from the Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement consortium and the UK Biobank were included. On MRI scans, we counted PVS in 4 brain regions (mesencephalon, hippocampus, basal ganglia, and centrum semiovale) according to a uniform and validated rating protocol, both manually and automated using a deep learning algorithm. As potential determinants, we considered demographics, cardiovascular risk factors, APOE genotypes, and other imaging markers of CSVD. Negative binomial regression models were used to examine the association between these determinants and PVS counts. RESULTS In total, 39,976 individuals were included (age range 20-96 years). The average count of PVS in the 4 regions increased from the age 20 years (0-1 PVS) to 90 years (2-7 PVS). Men had more mesencephalic PVS (OR [95% CI] = 1.13 [1.08-1.18] compared with women), but less hippocampal PVS (0.82 [0.81-0.83]). Higher blood pressure, particularly diastolic pressure, was associated with more PVS in all regions (ORs between 1.04-1.05). Hippocampal PVS showed higher counts with higher high-density lipoprotein cholesterol levels (1.02 [1.01-1.02]), glucose levels (1.02 [1.01-1.03]), and APOE ε4-alleles (1.02 [1.01-1.04]). Furthermore, white matter hyperintensity volume and presence of lacunes were associated with PVS in multiple regions, but most strongly with the basal ganglia (1.13 [1.12-1.14] and 1.10 [1.09-1.12], respectively). DISCUSSION Various factors are associated with the burden of PVS, in part regionally specific, which points toward a multifactorial origin beyond what can be expected from PVS-related risk factor profiles. This study highlights the power of collaborative efforts in population neuroimaging research.
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Affiliation(s)
- Tavia E Evans
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Maria J Knol
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Petra Schwingenschuh
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Katharina Wittfeld
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Saima Hilal
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - M Arfan Ikram
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Florian Dubost
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Kimberlin M H van Wijnen
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Petra Katschnig
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Pinar Yilmaz
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Marleen de Bruijne
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Mohamad Habes
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Christopher Chen
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Sönke Langer
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Henry Völzke
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - M Kamran Ikram
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Hans J Grabe
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Reinhold Schmidt
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Hieab H H Adams
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile.
| | - Meike W Vernooij
- From the Departments of Clinical Genetics (T.E.E., M.J.K., H.H.H.A.), Radiology and Nuclear Medicine (T.E.E., F.D., K.M.H.W., P.Y., M.B., H.H.H.A., M.W.V.), Epidemiology (M.J.K., M.A.I., P.Y., M.K.I., M.W.V.), and Neurology (M.K.I.), Erasmus MC, Rotterdam, the Netherlands; Department of Neurology (P.S., P.K., R.S.), Medical University of Graz, Austria; German Center for Neurodegenerative Diseases (DZNE) (K.W., M.H., H.J.G.), Site Rostock/Greifswald; Department of Psychiatry and Psychotherapy (K.W., H.J.G.) and Institute of Diagnostic Radiology and Neuroradiology (S.L.), University Medicine Greifswald, Germany; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory Aging & Cognition Centre (MACC) (S.H., C.C., M.K.I.), National University Health System, Singapore; Saw Swee Hock School of Public Health (S.H.), National University of Singapore; Department of Biomedical Data Sciences (F.D.), Stanford University, CA; J. Philip Kistler Stroke Research Center (P.Y.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; The Machine Learning Section (M.B.), Department of Computer Science, University of Copenhagen, Denmark; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC) (M.H.), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), TX; and Latin American Brain Health (BrainLat) (H.H.H.A.), Universidad Adolfo Ibáñez, Santiago, Chile
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12
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Dark HE, Harnett NG, Hurst DR, Wheelock MD, Wood KH, Goodman AM, Mrug S, Elliott MN, Emery ST, Schuster MA, Knight DC. Sex-related differences in violence exposure, neural reactivity to threat, and mental health. Neuropsychopharmacology 2022; 47:2221-2229. [PMID: 36030316 PMCID: PMC9630543 DOI: 10.1038/s41386-022-01430-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 08/09/2022] [Accepted: 08/10/2022] [Indexed: 02/06/2023]
Abstract
The prefrontal cortex (PFC), hippocampus, and amygdala play an important role in emotional health. However, adverse life events (e.g., violence exposure) affect the function of these brain regions, which may lead to disorders such as depression and anxiety. Depression and anxiety disproportionately affect women compared to men, and this disparity may reflect sex differences in the neural processes that underlie emotion expression and regulation. The present study investigated sex differences in the relationship between violence exposure and the neural processes that underlie emotion regulation. In the present study, 200 participants completed a Pavlovian fear conditioning procedure in which cued and non-cued threats (i.e., unconditioned stimuli) were presented during functional magnetic resonance imaging. Violence exposure was previously assessed at four separate time points when participants were 11-19 years of age. Significant threat type (cued versus non-cued) × sex and sex × violence exposure interactions were observed. Specifically, women and men differed in amygdala and parahippocampal gyrus reactivity to cued versus non-cued threat. Further, dorsolateral PFC (dlPFC) and inferior parietal lobule (IPL) reactivity to threat varied positively with violence exposure among women, but not men. Similarly, threat-elicited skin conductance responses varied positively with violence exposure among women. Finally, women reported greater depression and anxiety symptoms than men. These findings suggest that sex differences in threat-related brain and psychophysiological activity may have implications for mental health.
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Affiliation(s)
- Heather E Dark
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA
- Laboratory of Behavioral Neuroscience, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Nathaniel G Harnett
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA
- Division of Depression and Anxiety, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Danielle R Hurst
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Muriah D Wheelock
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA
- Department of Radiology, Washington University in St. Louis, St Louis, MO, USA
| | - Kimberly H Wood
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA
- Department of Psychology, Samford University, Homewood, AL, USA
| | - Adam M Goodman
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA
- Department of Neurology, University of Alabama at Birmingham School of Medicine, Birmingham, AL, USA
| | - Sylvie Mrug
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Susan Tortolero Emery
- Texas Prevention Research Center, School of Public Health, University of Texas Health Science Center, Houston, TX, USA
| | - Mark A Schuster
- Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA, USA
| | - David C Knight
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA.
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13
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Chen Y, Zuo Y, Kang S, Pan L, Jiang S, Yan A, Li L. Using fractal dimension analysis to assess the effects of normal aging and sex on subregional cortex alterations across the lifespan from a Chinese dataset. Cereb Cortex 2022; 33:5289-5296. [PMID: 36300622 DOI: 10.1093/cercor/bhac417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 09/23/2022] [Accepted: 09/25/2022] [Indexed: 11/13/2022] Open
Abstract
Abstract
Fractal dimension (FD) is used to quantify brain structural complexity and is more sensitive to morphological variability than other cortical measures. However, the effects of normal aging and sex on FD are not fully understood. In this study, age- and sex-related differences in FD were investigated in a sample of 448 adults age of 19–80 years from a Chinese dataset. The FD was estimated with the surface-based morphometry (SBM) approach, sex differences were analyzed on a vertex level, and correlations between FD and age were examined. Generalized additive models (GAMs) were used to characterize the trajectories of age-related changes in 68 regions based on the Desikan–Killiany atlas. The SBM results showed sex differences in the entire sample and 3 subgroups defined by age. GAM results demonstrated that the FD values of 51 regions were significantly correlated with age. The trajectories of changes can be classified into 4 main patterns. Our results indicate that sex differences in FD are evident across developmental stages. Age-related trajectories in FD are not homogeneous across the cerebral cortex. Our results extend previous findings and provide a foundation for future investigation of the underlying mechanism.
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Affiliation(s)
- Yiyong Chen
- Ningbo University School of Medicine, , Ningbo, 315211, Zhejiang, PR China
| | - Yizhi Zuo
- Nanjing Medical University Human Anatomy Department, , Nanjing, 211166, Jiangsu, PR China
| | - Shaofang Kang
- Ningbo University College of Teacher Education, , Ningbo, 315211, Zhejiang, PR China
| | - Liliang Pan
- Ningbo University School of Medicine, , Ningbo, 315211, Zhejiang, PR China
| | - Siyu Jiang
- Ningbo University School of Medicine, , Ningbo, 315211, Zhejiang, PR China
| | - Aohui Yan
- Ningbo University School of Medicine, , Ningbo, 315211, Zhejiang, PR China
| | - Lin Li
- Nanjing Medical University Human Anatomy Department, , Nanjing, 211166, Jiangsu, PR China
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Yun HJ, Lee HJ, Lee JY, Tarui T, Rollins CK, Ortinau CM, Feldman HA, Grant PE, Im K. Quantification of sulcal emergence timing and its variability in early fetal life: Hemispheric asymmetry and sex difference. Neuroimage 2022; 263:119629. [PMID: 36115591 PMCID: PMC10011016 DOI: 10.1016/j.neuroimage.2022.119629] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 08/07/2022] [Accepted: 09/12/2022] [Indexed: 12/25/2022] Open
Abstract
Human fetal brains show regionally different temporal patterns of sulcal emergence following a regular timeline, which may be associated with spatiotemporal patterns of gene expression among cortical regions. This study aims to quantify the timing of sulcal emergence and its temporal variability across typically developing fetuses by fitting a logistic curve to presence or absence of sulcus. We found that the sulcal emergence started from the central to the temporo-parieto-occipital lobes and frontal lobe, and the temporal variability of emergence in most of the sulci was similar between 1 and 2 weeks. Small variability (< 1 week) was found in the left central and postcentral sulci and larger variability (>2 weeks) was shown in the bilateral occipitotemporal and left superior temporal sulci. The temporal variability showed a positive correlation with the emergence timing that may be associated with differential contributions between genetic and environmental factors. Our statistical analysis revealed that the right superior temporal sulcus emerged earlier than the left. Female fetuses showed a trend of earlier sulcal emergence in the right superior temporal sulcus, lower temporal variability in the right intraparietal sulcus, and higher variability in the right precentral sulcus compared to male fetuses. Our quantitative and statistical approach quantified the temporal patterns of sulcal emergence in detail that can be a reference for assessing the normality of developing fetal gyrification.
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Affiliation(s)
- Hyuk Jin Yun
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States; Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Hyun Ju Lee
- Department of Pediatrics, Hanyang University College of Medicine, Seoul 04763, Korea (the Republic of)
| | - Joo Young Lee
- Department of Pediatrics, Hanyang University College of Medicine, Seoul 04763, Korea (the Republic of)
| | - Tomo Tarui
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA 02115, United States
| | - Caitlin K Rollins
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Cynthia M Ortinau
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO 63130, United States
| | - Henry A Feldman
- Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States; Institutional Centers for Clinical and Translational Research, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - P Ellen Grant
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States; Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States; Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Kiho Im
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States; Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States.
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15
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Wen Z, Fried J, Pace-Schott EF, Lazar SW, Milad MR. Revisiting sex differences in the acquisition and extinction of threat conditioning in humans. Learn Mem 2022; 29:274-282. [PMID: 36206388 PMCID: PMC9488021 DOI: 10.1101/lm.053521.121] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Accepted: 06/21/2022] [Indexed: 11/25/2022]
Abstract
Findings pertaining to sex differences in the acquisition and extinction of threat conditioning, a paradigm widely used to study emotional homeostasis, remain inconsistent, particularly in humans. This inconsistency is likely due to multiple factors, one of which is sample size. Here, we pooled functional magnetic resonance imaging (fMRI) and skin conductance response (SCR) data from multiple studies in healthy humans to examine sex differences during threat conditioning, extinction learning, and extinction memory recall. We observed increased functional activation in males, relative to females, in multiple parietal and frontal (medial and lateral) cortical regions during acquisition of threat conditioning and extinction learning. Females mainly exhibited higher amygdala activation during extinction memory recall to the extinguished conditioned stimulus and also while responding to the unconditioned stimulus (presentation of the shock) during threat conditioning. Whole-brain functional connectivity analyses revealed that females showed increased connectivity across multiple networks including visual, ventral attention, and somatomotor networks during late extinction learning. At the psychophysiological level, a sex difference was only observed during shock delivery, with males exhibiting higher unconditioned responses relative to females. Our findings point to minimal to no sex differences in the expression of conditioned responses during acquisition and extinction of such responses. Functional MRI findings, however, show some distinct functional activations and connectivities between the sexes. These data suggest that males and females might use different neural mechanisms, mainly related to cognitive processing, to achieve comparable levels of acquired conditioned responses to threating cues.
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Affiliation(s)
- Zhenfu Wen
- Department of Psychiatry, New York University Grossman School of Medicine, New York, New York 10016, USA
| | - Jamie Fried
- Department of Psychiatry, New York University Grossman School of Medicine, New York, New York 10016, USA
| | - Edward F Pace-Schott
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts 02129, USA
| | - Sara W Lazar
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts 02129, USA
| | - Mohammed R Milad
- Department of Psychiatry, New York University Grossman School of Medicine, New York, New York 10016, USA
- The Neuroscience Institute, New York University Grossman School of Medicine, New York, New York 10016, USA
- Nathan Kline Institute for Psychiatric Research, Orangeburg, New York 10962, USA
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16
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Mental health and conspirasism in health care professionals during the spring 2020 COVID-19 lockdown in Greece. Acta Neuropsychiatr 2022; 34:132-147. [PMID: 34886920 PMCID: PMC8770848 DOI: 10.1017/neu.2021.38] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
INTRODUCTION The aim of the study was to investigate mental health and conspiracy theory beliefs concerning COVID-19 among health care professionals (HCPs). MATERIAL AND METHODS During lockdown, an online questionnaire gathered data from 507 HCPs (432 females aged 33.86 ± 8.63 and 75 males aged 39.09 ± 9.54). STATISTICAL ANALYSIS A post-stratification method to transform the study sample was used; descriptive statistics were calculated. RESULTS Anxiety and probable depression were increased 1.5-2-fold and were higher in females and nurses. Previous history of depression was the main risk factor. The rates of believing in conspiracy theories concerning the COVID-19 were alarming with the majority of individuals (especially females) following some theory to at least some extend. CONCLUSIONS The current paper reports high rates of depression, distress and suicidal thoughts in the HCPs during the lockdown, with a high prevalence of beliefs in conspiracy theories. Female gender and previous history of depression acted as risk factors, while the belief in conspiracy theories might act as a protective factor. The results should be considered with caution due to the nature of the data (online survey on a self-selected but stratified sample).
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Rokoff LB, Shoaff JR, Coull BA, Enlow MB, Bellinger DC, Korrick SA. Prenatal exposure to a mixture of organochlorines and metals and internalizing symptoms in childhood and adolescence. ENVIRONMENTAL RESEARCH 2022; 208:112701. [PMID: 35016863 PMCID: PMC8917058 DOI: 10.1016/j.envres.2022.112701] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 12/23/2021] [Accepted: 01/05/2022] [Indexed: 05/17/2023]
Abstract
BACKGROUND Although prenatal chemical exposures influence neurobehavior, joint exposures are not well explored as risk factors for internalizing disorders through adolescence. OBJECTIVE To evaluate associations of prenatal organochlorine and metal exposures, considered individually and as a mixture, with mid-childhood and adolescent internalizing symptoms. METHODS Participants were 468 children from a prospective cohort recruited at birth (1993-1998) in New Bedford, Massachusetts. Organochlorines (hexachlorobenzene, p,p'-dichlorodiphenyl dichloroethylene, polychlorinated biphenyls) and metals (lead, manganese) were analyzed in cord blood. Internalizing symptoms (anxiety, depressive, somatic) were assessed via multiple informants on the Conners' Rating Scale (CRS) at 8-years and Behavior Assessment System for Children, Second Edition (BASC-2) at 15-years; higher T-scores indicate greater symptoms. Overall and sex-specific covariate-adjusted associations were evaluated using Bayesian Kernel Machine Regression (BKMR) and five-chemical linear regression models. RESULTS The cohort was socioeconomically diverse (35% household income <$20,000; 55% maternal ≤ high school education at birth). Most chemical concentrations were consistent with background levels [e.g., median (range) cord blood lead: 1.1 (0-9.4) μg/dL]. BKMR suggested linear associations and no interactions between chemicals. The overall mixture was positively associated with Conners' Parent Rating Scale (CPRS) and BASC-2 Self Report of Personality (SRP) anxiety and depressive symptoms, and negatively with somatic symptoms. Prenatal lead was positively associated with adolescent anxiety symptoms [1.56 (95% CI: 0.50, 2.61) BASC-2 SRP Anxiety score increase per doubling lead]. For CRPS and BASC-2 SRP, a doubling of cord blood manganese was positively associated with internalizing symptoms for girls [e.g., 3.26 (95% CI: 0.27, 6.25) BASC-2 SRP Depression score increase], but not boys. Organochlorine exposures were not adversely associated with internalizing symptoms. DISCUSSION Low-level prenatal lead exposure was positively associated with adolescent anxiety symptoms, and prenatal manganese exposure was positively associated with internalizing symptoms for girls from mid-childhood through adolescence. In utero neurotoxicant metal exposures may contribute to the emergence of anxiety and depression.
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Affiliation(s)
- Lisa B Rokoff
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Population Health Sciences Program, Harvard University, Cambridge, MA, USA.
| | - Jessica R Shoaff
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Brent A Coull
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Michelle Bosquet Enlow
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - David C Bellinger
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Susan A Korrick
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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18
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Rahman F, Coull BA, Carroll KN, Wilson A, Just AC, Kloog I, Zhang X, Wright RJ, Chiu YHM. Prenatal PM 2.5 exposure and infant temperament at age 6 months: Sensitive windows and sex-specific associations. ENVIRONMENTAL RESEARCH 2022; 206:112583. [PMID: 34922978 PMCID: PMC8810739 DOI: 10.1016/j.envres.2021.112583] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Revised: 12/12/2021] [Accepted: 12/13/2021] [Indexed: 05/08/2023]
Abstract
BACKGROUND Prenatal exposure to fine particulate matter with a diameter of ≤2.5 μm (PM2.5) has been linked to adverse neurodevelopmental outcomes in later childhood, while research on early infant behavior remains sparse. OBJECTIVES We examined associations between prenatal PM2.5 exposure and infant negative affectivity, a stable temperamental trait associated with longer-term behavioral and mental health outcomes. We also examined sex-specific effects. METHODS Analyses included 559 mother-infant pairs enrolled in the PRogramming of Intergenerational Stress Mechanisms (PRISM) cohort. Daily PM2.5 exposure based on geocoded residential address during pregnancy was estimated using a satellite-based spatiotemporal model. Domains of negative affectivity (Sadness, Distress to Limitations, Fear, Falling Reactivity) were assessed using the Infant Behavior Questionnaire-Revised (IBQ-R) when infants were 6 months old. Subscale scores were calculated as the mean of item-specific responses; the global Negative Affectivity (NA) score was derived by averaging the mean of the four subscale scores. Bayesian distributed lag interaction models (BDLIMs) were used to identify sensitive windows for prenatal PM2.5 exposure on global NA and its subscales, and to examine effect modification by sex. RESULTS Mothers were primarily racial/ethnic minorities (38% Black, 37% Hispanic), 40% had ≤12 years of education; most did not smoke during pregnancy (87%). In the overall sample, BDLIMs revealed that increased PM2.5 at mid-pregnancy was associated with higher global NA, Sadness, and Fear scores, after adjusting for covariates (maternal age, education, race/ethnicity, sex). Among boys, increased PM2.5 at early pregnancy was associated with decreased Fear scores, while exposure during late pregnancy was associated with increased Fear scores (cumulative effect estimate = 0.57, 95% CI: 0.03-1.41). Among girls, increased PM2.5 during mid-pregnancy was associated with higher Fear scores (cumulative effect estimate = 0.82, 95% CI: 0.05-1.91). CONCLUSIONS Prenatal PM2.5 exposure was associated with negative affectivity at age 6 months, and the sensitive windows may vary by subdomains and infant sex.
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Affiliation(s)
- Fataha Rahman
- Kravis Children's Hospital, Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; The City College of New York, New York, NY, USA
| | - Brent A Coull
- Department of Biostatistics, Harvard TH Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Kecia N Carroll
- Kravis Children's Hospital, Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ander Wilson
- Department of Statistics, Colorado State University, Fort Collins, CO, USA
| | - Allan C Just
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Itai Kloog
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Xueying Zhang
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rosalind J Wright
- Kravis Children's Hospital, Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; The Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yueh-Hsiu Mathilda Chiu
- Kravis Children's Hospital, Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; The Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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19
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Lee JW, Profant M, Wang C. Metabolic Sex Dimorphism of the Brain at the Gene, Cell, and Tissue Level. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2022; 208:212-220. [PMID: 35017210 DOI: 10.4049/jimmunol.2100853] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 11/09/2021] [Indexed: 12/21/2022]
Abstract
The palpable observation in the sex bias of disease prevalence in the CNS has fascinated scientists for several generations. Brain sex dimorphism has been visualized by imaging and analytical tools at the tissue, cellular, and molecular levels. Recent work highlighted the specificity of such sex bias in the brain and its subregions, offering a unique lens through which disease pathogenesis can be investigated. The brain is the largest consumer of energy in the body and provides a unique metabolic environment for diverse lineages of cells. Immune cells are increasingly recognized as an integral part of brain physiology, and their function depends on metabolic homeostasis. This review focuses on metabolic sex dimorphism in brain tissue, resident, and infiltrating immune cells. In this context, we highlight the relevance of recent advances in metabolomics and RNA sequencing technologies at the single cell resolution and the development of novel computational approaches.
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Affiliation(s)
- Jun Won Lee
- Biological Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada; and
| | - Martin Profant
- Biological Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada; and.,Department of Immunology, University of Toronto, Toronto, Ontario, Canada
| | - Chao Wang
- Biological Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada; and .,Department of Immunology, University of Toronto, Toronto, Ontario, Canada
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20
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Mehta RK, Rhee J. Revealing Sex Differences During Upper and Lower Extremity Neuromuscular Fatigue in Older Adults Through a Neuroergonomics Approach. FRONTIERS IN NEUROERGONOMICS 2021; 2:663368. [PMID: 38235250 PMCID: PMC10790897 DOI: 10.3389/fnrgo.2021.663368] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 07/26/2021] [Indexed: 01/19/2024]
Abstract
Background: Sex differences in neuromuscular fatigue is well-documented, however the underlying mechanisms remain understudied, particularly for the aging population. Objective: This study investigated sex differences in fatigability of the upper and lower extremity of older adults using a neuroergonomics approach. Methods: Thirty community-dwelling older adults (65 years or older; 15 M, 15 F) performed intermittent submaximal fatiguing handgrip and knee extension exercises until voluntary exhaustion on separate days. Muscle activity from prime muscles of the hand/arm and knee extensors were monitored using electromyography, neural activity from the frontal, motor, and sensory areas were monitored using functional near infrared spectroscopy, and force output were obtained. Results: While older males were stronger than females across both muscle groups, they exhibited longer endurance times and greater strength loss during knee extension exercises. These lower extremity findings were associated with greater force complexity over time and concomitant increase in left motor and right sensory motor regions. While fatigability during handgrip exercises was comparable across sexes, older females exhibited concurrent increases in the activation of the ipsilateral motor regions over time. Discussion: We identified differences in the underlying central neural strategies adopted by males and females in maintaining downstream motor outputs during handgrip fatigue that were not evident with traditional ergonomics measures. Additionally, enhanced neural activation in males during knee exercises that accompanied longer time to exhaustion point to potential rehabilitation/exercise strategies to improve neuromotor outcomes in more fatigable older adults.
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Affiliation(s)
- Ranjana K. Mehta
- Wm. Michael Barnes '64 Department of Industrial & Systems Engineering, Texas A&M University, College Station, TX, United States
| | - Joohyun Rhee
- Department of Environmental and Occupational Health, Texas A&M University, College Station, TX, United States
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21
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Hidalgo-Lopez E, Zeidman P, Harris T, Razi A, Pletzer B. Spectral dynamic causal modelling in healthy women reveals brain connectivity changes along the menstrual cycle. Commun Biol 2021; 4:954. [PMID: 34376799 PMCID: PMC8355156 DOI: 10.1038/s42003-021-02447-w] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 07/01/2021] [Indexed: 01/01/2023] Open
Abstract
Longitudinal menstrual cycle studies allow to investigate the effects of ovarian hormones on brain organization. Here, we use spectral dynamic causal modelling (spDCM) in a triple network model to assess effective connectivity changes along the menstrual cycle within and between the default mode, salience and executive control networks (DMN, SN, and ECN). Sixty healthy young women were scanned three times along their menstrual cycle, during early follicular, pre-ovulatory and mid-luteal phase. Related to estradiol, right before ovulation the left insula recruits the ECN, while the right middle frontal gyrus decreases its connectivity to the precuneus and the DMN decouples into anterior/posterior parts. Related to progesterone during the mid-luteal phase, the insulae (SN) engage to each other, while decreasing their connectivity to parietal ECN, which in turn engages the posterior DMN. When including the most confident connections in a leave-one out cross-validation, we find an above-chance prediction of the left-out subjects' cycle phase. These findings corroborate the plasticity of the female brain in response to acute hormone fluctuations and may help to further understand the neuroendocrine interactions underlying cognitive changes along the menstrual cycle.
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Affiliation(s)
- Esmeralda Hidalgo-Lopez
- Department of Psychology and Centre for Cognitive Neuroscience, University of Salzburg, Salzburg, Austria.
| | - Peter Zeidman
- The Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - TiAnni Harris
- Department of Psychology and Centre for Cognitive Neuroscience, University of Salzburg, Salzburg, Austria
| | - Adeel Razi
- The Wellcome Centre for Human Neuroimaging, University College London, London, UK
- Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC, Australia
| | - Belinda Pletzer
- Department of Psychology and Centre for Cognitive Neuroscience, University of Salzburg, Salzburg, Austria.
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22
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Kurth F, Gaser C, Luders E. Development of sex differences in the human brain. Cogn Neurosci 2021; 12:155-162. [PMID: 32902364 PMCID: PMC8510853 DOI: 10.1080/17588928.2020.1800617] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Revised: 07/08/2020] [Indexed: 01/24/2023]
Abstract
Sex differences in brain anatomy have been described from early childhood through late adulthood, but without any clear consensus among studies. Here, we applied a machine learning approach to estimate 'Brain Sex' using a continuous (rather than binary) classifier in 162 boys and 185 girls aged between 5 and 18 years. Changes in the estimated sex differences over time at different age groups were subsequently calculated using a sliding window approach. We hypothesized that males and females would differ in brain structure already during childhood, but that these differences will become even more pronounced with increasing age, particularly during adolescence. Overall, the classifier achieved a good performance, with an accuracy of 80.4% and an AUC of 0.897 across all age groups. Assessing changes in the estimated sex with age revealed a growing difference between the sexes with increasing age. That is, the very large effect size of d = 1.2 which was already evident during childhood increased even further from age 11 onward, and eventually reached an effect size of d = 1.6 at age 17. Altogether these findings suggest a systematic sex difference in brain structure already during childhood, and a subsequent increase of this difference during adolescence.
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Affiliation(s)
- Florian Kurth
- School of Psychology, University of Auckland, Auckland, New Zealand
| | - Christian Gaser
- Departments of Psychiatry and Neurology, Jena University Hospital, Jena, Germany
| | - Eileen Luders
- School of Psychology, University of Auckland, Auckland, New Zealand
- Laboratory of Neuro Imaging, School of Medicine, University of Southern California, Los Angeles, USA
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23
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Androvičová R, Pfaus JG, Ovsepian SV. Estrogen pendulum in schizophrenia and Alzheimer's disease: Review of therapeutic benefits and outstanding questions. Neurosci Lett 2021; 759:136038. [PMID: 34116197 DOI: 10.1016/j.neulet.2021.136038] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 05/21/2021] [Accepted: 06/06/2021] [Indexed: 12/29/2022]
Abstract
Although produced largely in the periphery, gonadal steroids play a key role in regulating the development and functions of the central nervous system and have been implicated in several chronic neuropsychiatric disorders, with schizophrenia and Alzheimer's disease (AD) most prominent. Despite major differences in pathobiology and clinical manifestations, in both conditions, estrogen transpires primarily with protective effects, buffering the onset and progression of diseases at various levels. As a result, estrogen replacement therapy (ERT) emerges as one of the most widely discussed adjuvant interventions. In this review, we revisit evidence supporting the protective role of estrogen in schizophrenia and AD and consider putative cellular and molecular mechanisms. We explore the underlying functional processes relevant to the manifestation of these devastating conditions, with a focus on synaptic transmission and plasticity mechanisms. We discuss specific effects of estrogen deficit on neurotransmitter systems such as cholinergic, dopaminergic, serotoninergic, and glutamatergic. While the evidence from both, preclinical and clinical reports, in general, are supportive of the protective effects of estrogen from cognitive decline to synaptic pathology, numerous questions remain, calling for further research.
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Affiliation(s)
- Renáta Androvičová
- Department of Applied Neuroscience and Neuroimaging (RA) and Department of Experimental Neuroscience (SVO), National Institute of Mental Health, Topolová 748, 250 67 Klecany, Czech Republic.
| | - James G Pfaus
- Instituto de Investigaciones Cerebrales, Universidad Veracruzana, Xalapa, Mexico
| | - Saak V Ovsepian
- Department of Applied Neuroscience and Neuroimaging (RA) and Department of Experimental Neuroscience (SVO), National Institute of Mental Health, Topolová 748, 250 67 Klecany, Czech Republic
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24
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Prenatal metal mixtures and sex-specific infant negative affectivity. Environ Epidemiol 2021; 5:e147. [PMID: 33870019 PMCID: PMC8043734 DOI: 10.1097/ee9.0000000000000147] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 03/04/2021] [Indexed: 11/27/2022] Open
Abstract
Supplemental Digital Content is available in the text. Prenatal exposure to metals has been associated with a range of adverse neurocognitive outcomes; however, associations with early behavioral development are less well understood. We examined joint exposure to multiple co-occurring metals in relation to infant negative affect, a stable temperamental trait linked to psychopathology among children and adults.
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25
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Chowen JA, Garcia-Segura LM. Role of glial cells in the generation of sex differences in neurodegenerative diseases and brain aging. Mech Ageing Dev 2021; 196:111473. [PMID: 33766745 DOI: 10.1016/j.mad.2021.111473] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 03/14/2021] [Accepted: 03/16/2021] [Indexed: 12/11/2022]
Abstract
Diseases and aging-associated alterations of the nervous system often show sex-specific characteristics. Glial cells play a major role in the endogenous homeostatic response of neural tissue, and sex differences in the glial transcriptome and function have been described. Therefore, the possible role of these cells in the generation of sex differences in pathological alterations of the nervous system is reviewed here. Studies have shown that glia react to pathological insults with sex-specific neuroprotective and regenerative effects. At least three factors determine this sex-specific response of glia: sex chromosome genes, gonadal hormones and neuroactive steroid hormone metabolites. The sex chromosome complement determines differences in the transcriptional responses in glia after brain injury, while gonadal hormones and their metabolites activate sex-specific neuroprotective mechanisms in these cells. Since the sex-specific neuroprotective and regenerative activity of glial cells causes sex differences in the pathological alterations of the nervous system, glia may represent a relevant target for sex-specific therapeutic interventions.
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Affiliation(s)
- Julie A Chowen
- Department of Endocrinology, Hospital Infantil Universitario Niño Jesús, Instituto de Investigación la Princesa, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutriciόn (CIBEROBN), Instituto de Salud Carlos III, and IMDEA Food Institute, CEIUAM+CSIC, Madrid, Spain.
| | - Luis M Garcia-Segura
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC) and Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain.
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26
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Sex difference in cerebral blood flow and cerebral glucose metabolism: an activation-likelihood estimation meta-analysis. Nucl Med Commun 2021; 42:410-415. [PMID: 33306626 DOI: 10.1097/mnm.0000000000001343] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
OBJECTIVES Sex differences exist in a variety of aspects including neurochemicals as well as behavioral traits of cognition, language, and aggression. We performed a meta-analysis of studies using a coordinate-based technique of activation-likelihood estimation (ALE) to identify the pooled estimated effect of sex difference. METHODS We performed a systematic search of MEDLINE and EMBASE for English-language publications using the keywords of 'positron emission tomography (PET)', 'single-photon emission computed tomography (SPECT)', and 'sex'. A threshold of uncorrected P < 0.001 (minimum volume of 200 mm3) was applied to the resulting ALE map. RESULTS Cerebral blood flow (CBF) in right precuneus, left superior temporal gyrus, left inferior temporal, left inferior frontal gyrus, right cerebellar tonsil, and right middle temporal gyrus was higher in females than males. CBF in left anterior cingulate was higher in males than females. Whereas, the cerebral metabolic rate for glucose (CMRglu) in left thalamus, left cingulate gyrus, right inferior parietal lobule, left medial frontal gyrus, right middle frontal gyrus, right midbrain, and left inferior parietal lobule was higher in females than males. However, there was no brain region that showed higher CMRglu in males than females. CONCLUSION Regional CBF and CMRglu from PET and SPECT showed the difference between males and females.
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27
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Dump the "dimorphism": Comprehensive synthesis of human brain studies reveals few male-female differences beyond size. Neurosci Biobehav Rev 2021; 125:667-697. [PMID: 33621637 DOI: 10.1016/j.neubiorev.2021.02.026] [Citation(s) in RCA: 142] [Impact Index Per Article: 47.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 01/01/2021] [Accepted: 02/16/2021] [Indexed: 12/21/2022]
Abstract
With the explosion of neuroimaging, differences between male and female brains have been exhaustively analyzed. Here we synthesize three decades of human MRI and postmortem data, emphasizing meta-analyses and other large studies, which collectively reveal few reliable sex/gender differences and a history of unreplicated claims. Males' brains are larger than females' from birth, stabilizing around 11 % in adults. This size difference accounts for other reproducible findings: higher white/gray matter ratio, intra- versus interhemispheric connectivity, and regional cortical and subcortical volumes in males. But when structural and lateralization differences are present independent of size, sex/gender explains only about 1% of total variance. Connectome differences and multivariate sex/gender prediction are largely based on brain size, and perform poorly across diverse populations. Task-based fMRI has especially failed to find reproducible activation differences between men and women in verbal, spatial or emotion processing due to high rates of false discovery. Overall, male/female brain differences appear trivial and population-specific. The human brain is not "sexually dimorphic."
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28
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Gaillard A, Fehring DJ, Rossell SL. Sex differences in executive control: A systematic review of functional neuroimaging studies. Eur J Neurosci 2021; 53:2592-2611. [PMID: 33423339 DOI: 10.1111/ejn.15107] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 12/22/2020] [Accepted: 01/01/2021] [Indexed: 01/21/2023]
Abstract
The number of studies investigating sex differences in executive functions, particularly those using human functional neuroimaging techniques, has risen dramatically in the past decade. However, the influences of sex on executive function are still underexplored and poorly characterized. To address this, we conducted a systematic literature review of functional neuroimaging studies investigating sex differences in three prominent executive control domains of cognitive set-shifting, performance monitoring, and response inhibition. PubMed, Web of Science, and Scopus were systematically searched. Following the application of exclusion criteria, 21 studies were included, with a total of 677 females and 686 males. Ten of these studies were fMRI and PET, eight were EEG, and three were NIRS. At present, there is evidence for sex differences in the neural networks underlying all tasks of executive control included in this review suggesting males and females engage different strategies depending on task demands. There was one task exception, the 2-Back task, which showed no sex differences. Due to methodological variability and the involvement of multiple neural networks, a simple overarching statement with regard to gender differences during executive control cannot be provided. As such, we discuss limitations within the current literature and methodological considerations that should be employed in future research. Importantly, sex differences in neural mechanisms are present in the majority of tasks assessed, and thus should not be ignored in future research. PROSPERO registration information: CRD42019124772.
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Affiliation(s)
- Alexandra Gaillard
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University of Technology, Hawthorn, VIC., Australia
| | - Daniel J Fehring
- Cognitive Neuroscience Laboratory, Monash Biomedicine Discovery Institute, Department of Physiology, Monash University, Clayton, VIC., Australia.,ARC Centre of Excellence in Integrative Brain Function, Monash University, Clayton, VIC., Australia
| | - Susan L Rossell
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University of Technology, Hawthorn, VIC., Australia.,Psychiatry, St Vincent's Hospital, Melbourne, VIC., Australia
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Taylor CM, Pritschet L, Jacobs EG. The scientific body of knowledge - Whose body does it serve? A spotlight on oral contraceptives and women's health factors in neuroimaging. Front Neuroendocrinol 2021; 60:100874. [PMID: 33002517 PMCID: PMC7882021 DOI: 10.1016/j.yfrne.2020.100874] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Revised: 09/22/2020] [Accepted: 09/23/2020] [Indexed: 12/13/2022]
Abstract
Women constitute half of the world's population, yet neuroscience research does not serve the sexes equally. Fifty years of preclinical animal evidence documents the tightly-coupled relationship between our endocrine and nervous systems, yet human neuroimaging studies rarely consider how endocrine factors shape the structural and functional architecture of the human brain. Here, we quantify several blind spots in neuroimaging research, which overlooks aspects of the human condition that impact women's health (e.g. the menstrual cycle, hormonal contraceptives, pregnancy, menopause). Next, we illuminate potential consequences of this oversight: today over 100 million women use oral hormonal contraceptives, yet relatively few investigations have systematically examined whether disrupting endogenous hormone production impacts the brain. We close by presenting a roadmap for progress, highlighting the University of California Women's Brain Initiative which is addressing unmet needs in women's health research.
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Affiliation(s)
- Caitlin M Taylor
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, United States.
| | - Laura Pritschet
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, United States
| | - Emily G Jacobs
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, United States; Neuroscience Research Institute, University of California, Santa Barbara, United States.
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30
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Ambrase A, Lewis CA, Barth C, Derntl B. Influence of ovarian hormones on value-based decision-making systems: Contribution to sexual dimorphisms in mental disorders. Front Neuroendocrinol 2021; 60:100873. [PMID: 32987043 DOI: 10.1016/j.yfrne.2020.100873] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 07/28/2020] [Accepted: 09/15/2020] [Indexed: 12/22/2022]
Abstract
Women and men exhibit differences in behavior when making value-based decisions. Various hypotheses have been proposed to explain these findings, stressing differences in functional lateralization of the brain, functional activation, neurotransmitter involvement and more recently, sex hormones. While a significant interaction of neurotransmitter systems and sex hormones has been shown for both sexes, decision-making in women might be particularly affected by variations of ovarian hormones. In this review we have gathered information from animal and human studies on how ovarian hormones affect decision-making processes in females by interacting with neurotransmitter systems at functionally relevant brain locations and thus modify the computation of decision aspects. We also review previous findings on impaired decision-making in animals and clinical populations with substance use disorder and depression, emphasizing how little we know about the role of ovarian hormones in aberrant decision-making.
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Affiliation(s)
- Aiste Ambrase
- Department of Psychiatry and Psychotherapy, University of Tuebingen, Tübingen, Germany; International Max Planck Research School for Cognitive and Systems Neuroscience, University of Tübingen, Tuebingen, Germany
| | - Carolin A Lewis
- Department of Psychiatry and Psychotherapy, University of Tuebingen, Tübingen, Germany; Emotion Neuroimaging Lab, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany
| | - Claudia Barth
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Birgit Derntl
- Department of Psychiatry and Psychotherapy, University of Tuebingen, Tübingen, Germany; International Max Planck Research School for Cognitive and Systems Neuroscience, University of Tübingen, Tuebingen, Germany; TübingenNeuroCampus, University of Tübingen, Tübingen, Germany; LEAD Research School and Graduate Network, University of Tübingen, Tübingen, Germany.
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31
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Compère L, Charron S, Gallarda T, Rari E, Lion S, Nys M, Anssens A, Coussinoux S, Machefaux S, Oppenheim C, Piolino P. Gender identity better than sex explains individual differences in episodic and semantic components of autobiographical memory: An fMRI study. Neuroimage 2020; 225:117507. [PMID: 33127480 DOI: 10.1016/j.neuroimage.2020.117507] [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: 02/19/2020] [Revised: 10/02/2020] [Accepted: 10/21/2020] [Indexed: 12/22/2022] Open
Abstract
Advances in the literature of sex-related differences in autobiographical memory increasingly tend to highlight the importance of psychosocial factors such as gender identity, which may explain these differences better than sex as a biological factor. To date, however, none of these behavioral studies have investigated this hypothesis using neuroimaging. The purpose of this fMRI study is to examine for the first time sex and gender identity-related differences in episodic and semantic autobiographical memory in healthy participants (M=19, W=18). No sex-related differences were found; however, sex-related effects of masculine and feminine gender identity were identified in men and women independently. These results confirm the hypothesis that differences in episodic and semantic autobiographical memory are best explained by gender but are an interaction between biological sex and gender identity and extend these findings to the field of neuroimaging. We discuss the importance of hormonal factors to be taken into consideration in the future.
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Affiliation(s)
- Laurie Compère
- Université de Paris, MC(2)Lab, F-92100 Boulogne-Billancourt, Ile de France, France; Department of Psychiatry, University of Pittsburgh School of Medicine, United States.
| | | | - Thierry Gallarda
- «Consultation dysphorie de genre», hôpital Sainte-Anne, groupe hospitalier universitaire (GHU) Paris Psychiatrie et Neuroscience, France
| | - Eirini Rari
- «Consultation dysphorie de genre», hôpital Sainte-Anne, groupe hospitalier universitaire (GHU) Paris Psychiatrie et Neuroscience, France
| | - Stéphanie Lion
- Université de Paris, IPNP, INSERM, F-75005 Paris, France
| | - Marion Nys
- Université de Paris, MC(2)Lab, F-92100 Boulogne-Billancourt, Ile de France, France
| | - Adèle Anssens
- Université de Paris, MC(2)Lab, F-92100 Boulogne-Billancourt, Ile de France, France
| | - Sandrine Coussinoux
- «Consultation dysphorie de genre», hôpital Sainte-Anne, groupe hospitalier universitaire (GHU) Paris Psychiatrie et Neuroscience, France
| | - Sébastien Machefaux
- «Consultation dysphorie de genre», hôpital Sainte-Anne, groupe hospitalier universitaire (GHU) Paris Psychiatrie et Neuroscience, France
| | | | - Pascale Piolino
- Université de Paris, MC(2)Lab, F-92100 Boulogne-Billancourt, Ile de France, France; Institut Universitaire de France (IUF), Paris, France.
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32
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Nephew BC, Febo M, Cali R, Workman KP, Payne L, Moore CM, King JA, Lacreuse A. Robustness of sex-differences in functional connectivity over time in middle-aged marmosets. Sci Rep 2020; 10:16647. [PMID: 33024242 PMCID: PMC7538565 DOI: 10.1038/s41598-020-73811-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Accepted: 09/14/2020] [Indexed: 02/07/2023] Open
Abstract
Nonhuman primates (NHPs) are an essential research model for gaining a comprehensive understanding of the neural mechanisms of neurocognitive aging in our own species. In the present study, we used resting state functional connectivity (rsFC) to investigate the relationship between prefrontal cortical and striatal neural interactions, and cognitive flexibility, in unanaesthetized common marmosets (Callithrix jacchus) at two time points during late middle age (8 months apart, similar to a span of 5-6 years in humans). Based on our previous findings, we also determine the reproducibility of connectivity measures over the course of 8 months, particularly previously observed sex differences in rsFC. Male marmosets exhibited remarkably similar patterns of stronger functional connectivity relative to females and greater cognitive flexibility between the two imaging time points. Network analysis revealed that the consistent sex differences in connectivity and related cognitive associations were characterized by greater node strength and/or degree values in several prefrontal, premotor and temporal regions, as well as stronger intra PFC connectivity, in males compared to females. The current study supports the existence of robust sex differences in prefrontal and striatal resting state networks that may contribute to differences in cognitive function and offers insight on the neural systems that may be compromised in cognitive aging and age-related conditions such as mild cognitive impairment and Alzheimer's disease.
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Affiliation(s)
- Benjamin C Nephew
- Department of Biology and Biotechnology, Worcester Polytechnic Institute, Worcester, MA, 01609, USA.
- Center for Comparative Neuroimaging, University of Massachusetts Medical School, Worcester, MA, 01655, USA.
| | - Marcelo Febo
- Department of Psychiatry, University of Florida, Gainesville, FL, 32610, USA
| | - Ryan Cali
- Department of Psychiatry, University of Massachusetts Medical School, Worcester, MA, 01655, USA
| | - Kathryn P Workman
- Psychological and Brain Sciences, University of Massachusetts, Amherst, MA, 01003, USA
| | - Laurellee Payne
- Center for Comparative Neuroimaging, University of Massachusetts Medical School, Worcester, MA, 01655, USA
| | - Constance M Moore
- Center for Comparative Neuroimaging, University of Massachusetts Medical School, Worcester, MA, 01655, USA
- Department of Psychiatry, University of Massachusetts Medical School, Worcester, MA, 01655, USA
| | - Jean A King
- Department of Biology and Biotechnology, Worcester Polytechnic Institute, Worcester, MA, 01609, USA
- Center for Comparative Neuroimaging, University of Massachusetts Medical School, Worcester, MA, 01655, USA
- Department of Psychiatry, University of Massachusetts Medical School, Worcester, MA, 01655, USA
| | - Agnès Lacreuse
- Psychological and Brain Sciences, University of Massachusetts, Amherst, MA, 01003, USA
- Neuroscience and Behavior Program, University of Massachusetts, Amherst, MA, 01003, USA
- Center for Neuroendocrine Studies, University of Massachusetts, Amherst, MA, 01003, USA
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33
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Gaillard A, Fehring DJ, Rossell SL. A systematic review and meta-analysis of behavioural sex differences in executive control. Eur J Neurosci 2020; 53:519-542. [PMID: 32844505 DOI: 10.1111/ejn.14946] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 07/28/2020] [Accepted: 08/14/2020] [Indexed: 12/24/2022]
Abstract
Literature investigating whether an individuals' sex affects their executive control abilities and performance on cognitive tasks in a normative population has been contradictory and inconclusive. Using meta-analytic procedures (abiding by PRISMA guidelines), this study attempts to identify the magnitude of behavioural sex differences in three prominent executive control domains of cognitive set-shifting, performance monitoring, and response inhibition. PubMed, Web of Science, and Scopus were systematically searched. Across 46 included studies, a total of 1988 females and 1884 males were included in the analysis. Overall, males and females did not differ on performance in any of the three domains of performance monitoring, response inhibition, or cognitive set-shifting. Task-specific sex differences were observed in the domains of performance monitoring, in the CANTAB Spatial Working Memory task-males scored statistically higher than females (Hedges' g = -0.60), and response inhibition, in the Delay Discounting task-females scored statistically higher than males (Hedges' g = 0.64). While the meta-analysis did not detect overall behavioural sex differences in executive control, significant heterogeneity and task-specific sex differences were found. To further understand sex differences within these specific tasks and domains, future research must better control for age and sex hormone levels.
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Affiliation(s)
- Alexandra Gaillard
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University of Technology, Hawthorn, VIC, Australia
| | - Daniel J Fehring
- Cognitive Neuroscience Laboratory, Monash Biomedicine Discovery Institute, Department of Physiology, Monash University, Clayton, VIC, Australia.,ARC Centre of Excellence in Integrative Brain Function, Monash University, Clayton, VIC, Australia
| | - Susan L Rossell
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University of Technology, Hawthorn, VIC, Australia.,Psychiatry, St Vincent's Hospital, Melbourne, VIC, Australia
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34
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Gonzalez A, Frey BN. Understanding the complex interplay between violence, depression and suicidal ideation in women: Time for a comprehensive sex- and gender-based approach. REVISTA BRASILEIRA DE PSIQUIATRIA 2020; 42:467-468. [PMID: 32876137 PMCID: PMC7524419 DOI: 10.1590/1516-4446-2020-1336] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 07/16/2020] [Indexed: 11/24/2022]
Affiliation(s)
- Andrea Gonzalez
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.,Offord Centre for Child Studies, Hamilton, ON, Canada
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.,Women's Health Concerns Clinic and Mood Disorders Program, St. Joseph's Healthcare Hamilton, ON, Canada
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35
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Adeli E, Zhao Q, Zahr NM, Goldstone A, Pfefferbaum A, Sullivan EV, Pohl KM. Deep learning identifies morphological determinants of sex differences in the pre-adolescent brain. Neuroimage 2020; 223:117293. [PMID: 32841716 PMCID: PMC7780846 DOI: 10.1016/j.neuroimage.2020.117293] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 07/06/2020] [Accepted: 08/17/2020] [Indexed: 12/11/2022] Open
Abstract
The application of data-driven deep learning to identify sex differences in developing brain structures of pre-adolescents has heretofore not been accomplished. Here, the approach identifies sex differences by analyzing the minimally processed MRIs of the first 8144 participants (age 9 and 10 years) recruited by the Adolescent Brain Cognitive Development (ABCD) study. The identified pattern accounted for confounding factors (i.e., head size, age, puberty development, socioeconomic status) and comprised cerebellar (corpus medullare, lobules III, IV/V, and VI) and subcortical (pallidum, amygdala, hippocampus, parahippocampus, insula, putamen) structures. While these have been individually linked to expressing sex differences, a novel discovery was that their grouping accurately predicted the sex in individual pre-adolescents. Another novelty was relating differences specific to the cerebellum to pubertal development. Finally, we found that reducing the pattern to a single score not only accurately predicted sex but also correlated with cognitive behavior linked to working memory. The predictive power of this score and the constellation of identified brain structures provide evidence for sex differences in pre-adolescent neurodevelopment and may augment understanding of sex-specific vulnerability or resilience to psychiatric disorders and presage sex-linked learning disabilities.
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Affiliation(s)
- Ehsan Adeli
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Qingyu Zhao
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Natalie M Zahr
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Center for Biomedical Sciences, SRI International, Menlo Park, CA 94025, USA
| | - Aimee Goldstone
- Center for Biomedical Sciences, SRI International, Menlo Park, CA 94025, USA
| | - Adolf Pfefferbaum
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Center for Biomedical Sciences, SRI International, Menlo Park, CA 94025, USA
| | - Edith V Sullivan
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Kilian M Pohl
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Center for Biomedical Sciences, SRI International, Menlo Park, CA 94025, USA.
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36
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Zhang X, Liang M, Qin W, Wan B, Yu C, Ming D. Gender Differences Are Encoded Differently in the Structure and Function of the Human Brain Revealed by Multimodal MRI. Front Hum Neurosci 2020; 14:244. [PMID: 32792927 PMCID: PMC7385398 DOI: 10.3389/fnhum.2020.00244] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 06/02/2020] [Indexed: 12/30/2022] Open
Abstract
Despite widely reported gender differences in both brain structure and brain function, very few studies have examined the relationship between the structural differences and the functional differences between genders. Here, different imaging measures including both structural [i.e., gray matter volume (GMV)] and functional [i.e., regional homogeneity (ReHo) and functional connectivity (FC)] measures were employed to detect the gender differences in the human brain based on univariate and multivariate approaches with a sample of 290 healthy adults (155 females). The univariate analyses revealed that gender differences were detected in both structural (i.e., GMV) and functional (ReHo or FC) imaging measures, mainly manifested as greater values in females than in males in regions of the frontal, parietal, occipital lobes and cerebellum. Importantly, there was little overlap between the differences detected in GMV and those detected in ReHo and FC, and their differences between genders were not correlated with each other. The multivariate pattern analyses revealed that each of these measures had discriminative power to successfully distinguish between genders (classification accuracy: 94.3%, 90.73%, and 83.89% for GMV, ReHo, and FC, respectively) and their combination further improved the classification performance (96.6%). Our results suggest that gender differences are encoded in both brain structure and brain function, but in different manners. The finding of different and complementary information contained in structural and functional differences between genders highlights the complex relationship between brain structure and function, which may underlie the complex nature of gender differences in behavior.
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Affiliation(s)
- Xi Zhang
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.,School of Medical Imaging, Tianjin Medical University, Tianjin, China.,Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China
| | - Meng Liang
- School of Medical Imaging, Tianjin Medical University, Tianjin, China.,Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China
| | - Wen Qin
- Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China.,Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Baikun Wan
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Chunshui Yu
- School of Medical Imaging, Tianjin Medical University, Tianjin, China.,Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China.,Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Dong Ming
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.,Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
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37
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Gender differences in anxiety: The mediating role of sensitivity to unpredictable threat. Int J Psychophysiol 2020; 153:127-134. [PMID: 32417225 DOI: 10.1016/j.ijpsycho.2020.05.001] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 03/02/2020] [Accepted: 05/01/2020] [Indexed: 12/19/2022]
Abstract
Anxiety disorders and symptoms disproportionately impact women relative to men, but it is unclear what mechanism(s) contribute to this phenomenon. The present study examined sensitivity to unpredictable threat as a potential mechanism of gender differences in panic symptoms. The sample included 67 participants (35 women) who completed the no, predictable, and unpredictable threat (NPU-threat) startle paradigm with electric shocks as the aversive stimulus. Participants also completed the self-report Inventory of Depression and Anxiety Symptoms to assess current panic and depression symptoms. Results indicated that women, relative to men, reported greater panic symptoms and demonstrated increased startle potentiation in anticipation of predictable and unpredictable threat. Furthermore, across all participants increased startle potentiation in anticipation of unpredictable (but not predictable) threat was associated with greater panic symptoms, but there was no relationship with depression symptoms. Finally, the gender difference in panic symptoms was mediated by startle potentiation in anticipation of unpredictable (but not predictable) threat. The present study suggests that a heightened sensitivity to unpredictable threat might be a mechanism that contributes to increased anxiety in women.
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38
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Angelopoulou G, Meier EL, Kasselimis D, Pan Y, Tsolakopoulos D, Velonakis G, Karavasilis E, Kelekis NL, Goutsos D, Potagas C, Kiran S. Investigating Gray and White Matter Structural Substrates of Sex Differences in the Narrative Abilities of Healthy Adults. Front Neurosci 2020; 13:1424. [PMID: 32063823 PMCID: PMC7000661 DOI: 10.3389/fnins.2019.01424] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 12/16/2019] [Indexed: 12/12/2022] Open
Abstract
Linguistic aspects of narration have been investigated in healthy populations, in a wide variety of languages and speech genres with very different results. There is some evidence indicating that linguistic elements, such as speech rate (i.e., the measure indicating the amount of speech produced in a certain time period), mean length of utterance (MLU) (i.e., the index reflecting sentence grammatical structure), frequency of nouns and verbs, might be affected by non-linguistic factors such as sex. On the other hand, despite the existence of neuroimaging evidence of structural differences between males and females, it is yet unknown how such differences could explain between-sex disparities in linguistic abilities in natural speech contexts. To date, no study has evaluated discourse production elements in relation to sex differences and their neural correlates in terms of brain structure, a topic that could provide unique insights on the relationship between language and the brain. The aim of the present study was to determine sex differences in narrative skills in healthy adults and to investigate white and gray matter structural correlates of linguistic skills in each group. Twenty-seven male and 30 female (N = 57) right-handed, neurologically intact, monolingual Greek speakers, matched for age and years of education, participated. Narrations of a personal medical event were elicited. Linguistic elements of speech rate (words per minute), MLUs, frequency of nouns and verbs were calculated for each speech sample, by two independent raters. Structural 3D T1 images were segmented and parcellated using FreeSurfer and whole-brain between-sex differences in cortical thickness, cortical volume and surface area, were obtained. Between-group differences in white matter diffusion tensor scalars were examined via Tract-Based Spatial-Statistics and whole-brain tractography and automated tract delineation using Automated Fiber Quantification. Speech rate and noun frequency were significantly lower for men, while verb frequency was significantly higher for women, but no differences were identified for MLU. Regarding cortical measures, males demonstrated increased volume, surface area and cortical thickness in several bilateral regions, while no voxel-wise or tractography-based between-group differences in white matter metrics were observed. Regarding the relationship between sex and speech variables, hierarchical regression analyses showed that the superior/middle frontal cluster in surface area may serve as a significant predictor of speech rate variance, but only in females. We discuss several possible interpretations of how sex-related speech abilities could be represented differently in men and women in gray matter structures within the broad language network.
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Affiliation(s)
- Georgia Angelopoulou
- Neuropsychology and Language Disorders Unit, 1st Department of Neurology, Eginition Hospital, National and Kapodistrian University of Athens, Athens, Greece
- Sargent College of Health & Rehabilitation Sciences, Boston University, Boston, MA, United States
| | - Erin L. Meier
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Dimitrios Kasselimis
- Neuropsychology and Language Disorders Unit, 1st Department of Neurology, Eginition Hospital, National and Kapodistrian University of Athens, Athens, Greece
- Division of Psychiatry and Behavioral Sciences, School of Medicine, University of Crete, Heraklion, Greece
| | - Yue Pan
- Sargent College of Health & Rehabilitation Sciences, Boston University, Boston, MA, United States
| | - Dimitrios Tsolakopoulos
- Neuropsychology and Language Disorders Unit, 1st Department of Neurology, Eginition Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - George Velonakis
- 2nd Department of Radiology, General University Hospital “Attikon”, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Efstratios Karavasilis
- 2nd Department of Radiology, General University Hospital “Attikon”, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Nikolaos L. Kelekis
- 2nd Department of Radiology, General University Hospital “Attikon”, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Dionysios Goutsos
- Department of Linguistics, School of Philosophy, National and Kapodistrian University of Athens, Athens, Greece
| | - Constantin Potagas
- Neuropsychology and Language Disorders Unit, 1st Department of Neurology, Eginition Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Swathi Kiran
- Sargent College of Health & Rehabilitation Sciences, Boston University, Boston, MA, United States
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39
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Luders E, Kurth F. Structural differences between male and female brains. HANDBOOK OF CLINICAL NEUROLOGY 2020; 175:3-11. [PMID: 33008534 DOI: 10.1016/b978-0-444-64123-6.00001-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Research based on structural magnetic resonance imaging (MRI) has revealed a number of sex differences in the anatomy of the human brain. The first part of this chapter presents an excerpt of these findings discriminating among effects on a global, regional, and local level. While findings are far from consistent and conclusive, there is general consensus with respect to sex-specific brain size, with male brains being bigger on average than female brains. So, the question arises as to whether any of the observed sex differences are merely driven by brain size. The second part of this chapter thus sheds light on a unique scientific attempt to discriminate between brain size effects and sex effects. The overarching goal of this chapter is to exemplify the variety of findings and to demonstrate that the presence, magnitude, and direction of significant sex differences strongly depend on the measurement applied. The assumption that sex differences are simply a by-product of brain size, rather than pure (size independent) sex effects has proven to be true for some but certainly not all findings. Therefore, when examining the possible sexual dimorphism of the brain, it is imperative to avoid oversimplification and generalization.
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Affiliation(s)
- Eileen Luders
- School of Psychology, University of Auckland, Auckland, New Zealand; Laboratory of Neuro Imaging, School of Medicine, University of Southern California, Los Angeles, CA, United States.
| | - Florian Kurth
- School of Psychology, University of Auckland, Auckland, New Zealand
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40
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Birner A, Bengesser SA, Seiler S, Dalkner N, Queissner R, Platzer M, Fellendorf FT, Hamm C, Maget A, Pilz R, Lenger M, Reininghaus B, Pirpamer L, Ropele S, Hinteregger N, Magyar M, Deutschmann H, Enzinger C, Kapfhammer HP, Reininghaus EZ. Total gray matter volume is reduced in individuals with bipolar disorder currently treated with atypical antipsychotics. J Affect Disord 2020; 260:722-727. [PMID: 31563071 DOI: 10.1016/j.jad.2019.09.068] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Revised: 09/13/2019] [Accepted: 09/18/2019] [Indexed: 12/01/2022]
Abstract
BACKGROUND/AIMS Recent evidence indicates that the intake of atypical antipsychotics (AAP) is associated with gray matter abnormalities in patients with psychiatric disorders. We explored if patients with bipolar disorder (BD) who are medicated with AAP exhibit total gray matter volume (TGV) reduction compared to BD individuals not medicated with AAP and healthy controls (HC). METHODS In a cross-sectional design, 124 individuals with BD and 86 HC underwent 3T-MRI of the brain and clinical assessment as part of our BIPFAT-study. The TGV was estimated using Freesurfer. We used univariate covariance analysis (ANCOVA) to test for normalized TGV differences and controlled for covariates. RESULTS ANCOVA results indicated that 75 BD individuals taking AAP had significantly reduced normalized TGV as compared to 49 BD not taking AAP (F = 9.995, p = .002., Eta = 0.084) and 86 HC (F = 7.577, p = .007, Eta = 0.046). LIMITATIONS Our cross-sectional results are not suited to draw conclusions about causality. We have no clear information on treatment time and baseline volumes before drug treatment in the studied subjects. We cannot exclude that patients received different psychopharmacologic medications prior to the study point. We did not included dosages into the calculation. Many BD individuals received combinations of psychopharmacotherapy across drug classes. We did not have records displaying quantitative alcohol consumption and drug abuse in our sample. CONCLUSIONS Our data provide further evidence for the impact of AAP on brain structure in BD. Longitudinal studies are needed to investigate the causal directions of the proposed relationships.
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Affiliation(s)
- Armin Birner
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Auenbruggerplatz 31, A-8036, Graz, Austria
| | - Susanne A Bengesser
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Auenbruggerplatz 31, A-8036, Graz, Austria.
| | - Stephan Seiler
- Imaging of Dementia and Aging (IDeA), Laboratory Department of Neurology and Center for Neuroscience, University of California, Davis, USA
| | - Nina Dalkner
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Auenbruggerplatz 31, A-8036, Graz, Austria
| | - Robert Queissner
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Auenbruggerplatz 31, A-8036, Graz, Austria
| | - Martina Platzer
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Auenbruggerplatz 31, A-8036, Graz, Austria
| | - Frederike T Fellendorf
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Auenbruggerplatz 31, A-8036, Graz, Austria
| | - Carlo Hamm
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Auenbruggerplatz 31, A-8036, Graz, Austria
| | - Alexander Maget
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Auenbruggerplatz 31, A-8036, Graz, Austria
| | - Rene Pilz
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Auenbruggerplatz 31, A-8036, Graz, Austria
| | - Melanie Lenger
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Auenbruggerplatz 31, A-8036, Graz, Austria
| | - Bernd Reininghaus
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Auenbruggerplatz 31, A-8036, Graz, Austria
| | - Lukas Pirpamer
- Department of Neurology, Medical University of Graz, Austria
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Austria; Division of Neuroradiology, Department of Radiology, Medical University of Graz, Austria
| | - Nicole Hinteregger
- Division of Neuroradiology, Department of Radiology, Medical University of Graz, Austria
| | - Marton Magyar
- Division of Neuroradiology, Department of Radiology, Medical University of Graz, Austria
| | - Hannes Deutschmann
- Division of Neuroradiology, Department of Radiology, Medical University of Graz, Austria
| | - Christian Enzinger
- Department of Neurology, Medical University of Graz, Austria; Division of Neuroradiology, Department of Radiology, Medical University of Graz, Austria
| | - Hans-Peter Kapfhammer
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Auenbruggerplatz 31, A-8036, Graz, Austria
| | - Eva Z Reininghaus
- Department of Psychiatry and Psychotherapy, Medical University of Graz, Auenbruggerplatz 31, A-8036, Graz, Austria
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41
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Kumral D, Şansal F, Cesnaite E, Mahjoory K, Al E, Gaebler M, Nikulin VV, Villringer A. BOLD and EEG signal variability at rest differently relate to aging in the human brain. Neuroimage 2019; 207:116373. [PMID: 31759114 DOI: 10.1016/j.neuroimage.2019.116373] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Revised: 10/17/2019] [Accepted: 11/17/2019] [Indexed: 01/22/2023] Open
Abstract
Variability of neural activity is regarded as a crucial feature of healthy brain function, and several neuroimaging approaches have been employed to assess it noninvasively. Studies on the variability of both evoked brain response and spontaneous brain signals have shown remarkable changes with aging but it is unclear if the different measures of brain signal variability - identified with either hemodynamic or electrophysiological methods - reflect the same underlying physiology. In this study, we aimed to explore age differences of spontaneous brain signal variability with two different imaging modalities (EEG, fMRI) in healthy younger (25 ± 3 years, N = 135) and older (67 ± 4 years, N = 54) adults. Consistent with the previous studies, we found lower blood oxygenation level dependent (BOLD) variability in the older subjects as well as less signal variability in the amplitude of low-frequency oscillations (1-12 Hz), measured in source space. These age-related reductions were mostly observed in the areas that overlap with the default mode network. Moreover, age-related increases of variability in the amplitude of beta-band frequency EEG oscillations (15-25 Hz) were seen predominantly in temporal brain regions. There were significant sex differences in EEG signal variability in various brain regions while no significant sex differences were observed in BOLD signal variability. Bivariate and multivariate correlation analyses revealed no significant associations between EEG- and fMRI-based variability measures. In summary, we show that both BOLD and EEG signal variability reflect aging-related processes but are likely to be dominated by different physiological origins, which relate differentially to age and sex.
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Affiliation(s)
- D Kumral
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; MindBrainBody Institute at the Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany.
| | - F Şansal
- International Graduate Program Medical Neurosciences, Charité-Universitätsmedizin, Berlin, Germany; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - E Cesnaite
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - K Mahjoory
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institute for Biomagnetism and Biosignalanalysis, University of Muenster, Muenster, Germany
| | - E Al
- MindBrainBody Institute at the Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - M Gaebler
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; MindBrainBody Institute at the Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - V V Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Neurophysics Group, Department of Neurology, Campus Benjamin Franklin, Charité Universitätsmedizin Berlin, Berlin, Germany; Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
| | - A Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; MindBrainBody Institute at the Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany; Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany; Department of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
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42
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de Lacy N, McCauley E, Kutz JN, Calhoun VD. Sex-related differences in intrinsic brain dynamism and their neurocognitive correlates. Neuroimage 2019; 202:116116. [DOI: 10.1016/j.neuroimage.2019.116116] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 08/20/2019] [Indexed: 01/13/2023] Open
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43
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Tahira AC, Barbosa AR, Feltrin AS, Gastaldi VD, de Toledo VHC, de Carvalho Pereira JG, Lisboa BCG, de Souza Reis VN, dos Santos ACF, Maschietto M, Brentani H. Putative contributions of the sex chromosome proteins SOX3 and SRY to neurodevelopmental disorders. Am J Med Genet B Neuropsychiatr Genet 2019; 180:390-414. [PMID: 30537354 PMCID: PMC6767407 DOI: 10.1002/ajmg.b.32704] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Revised: 11/08/2018] [Accepted: 11/12/2018] [Indexed: 12/12/2022]
Abstract
The male-biased prevalence of certain neurodevelopmental disorders and the sex-biased outcomes associated with stress exposure during gestation have been previously described. Here, we hypothesized that genes distinctively targeted by only one or both homologous proteins highly conserved across therian mammals, SOX3 and SRY, could induce sexual adaptive changes that result in a differential risk for neurodevelopmental disorders. ChIP-seq/chip data showed that SOX3/SRY gene targets were expressed in different brain cell types in mice. We used orthologous human genes in rodent genomes to extend the number of SOX3/SRY set (1,721). These genes were later found to be enriched in five modules of coexpressed genes during the early and mid-gestation periods (FDR < 0.05), independent of sexual hormones. Genes with differential expression (24, p < 0.0001) and methylation (40, p < 0.047) between sexes were overrepresented in this set. Exclusive SOX3 or SRY target genes were more associated with the late gestational and postnatal periods. Using autism as a model sex-biased disorder, the SOX3/SRY set was enriched in autism gene databases (FDR ≤ 0.05), and there were more de novo variations from the male autism spectrum disorder (ASD) samples under the SRY peaks compared to the random peaks (p < 0.024). The comparison of coexpressed networks of SOX3/SRY target genes between male autism and control samples revealed low preservation in gene modules related to stress response (99 genes) and neurogenesis (78 genes). This study provides evidence that while SOX3 is a regulatory mechanism for both sexes, the male-exclusive SRY also plays a role in gene regulation, suggesting a potential mechanism for sex bias in ASD.
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Affiliation(s)
- Ana Carolina Tahira
- LIM23, Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | - André Rocha Barbosa
- LIM23, Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
- Inter‐institutional Grad Program on BioinformaticsUniversity of São PauloSão PauloSPBrazil
| | | | - Vinicius Daguano Gastaldi
- LIM23, Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | - Victor Hugo Calegari de Toledo
- LIM23, Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | | | - Bianca Cristina Garcia Lisboa
- LIM23, Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | - Viviane Neri de Souza Reis
- LIM23, Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | - Ana Cecília Feio dos Santos
- LIM23, Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
- Laboratório de Pesquisas Básicas em Malária – EntomologiaSeção de Parasitologia – Instituto Evandro Chagas/SVS/MSAnanindeuaPABrazil
| | - Mariana Maschietto
- Brazilian Biosciences National Laboratory (LNBio)Brazilian Center for Research in Energy and Materials (CNPEM)CampinasSPBrazil
| | - Helena Brentani
- LIM23, Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
- Inter‐institutional Grad Program on BioinformaticsUniversity of São PauloSão PauloSPBrazil
- Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSPBrazil
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD)Sao PauloSPBrazil
- Faculdade de Medicina FMUSPUniversidade de Sao PauloSao PauloSPBrazil
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Genetic and environmental influences on functional connectivity within and between canonical cortical resting-state networks throughout adolescent development in boys and girls. Neuroimage 2019; 202:116073. [PMID: 31386921 DOI: 10.1016/j.neuroimage.2019.116073] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Revised: 06/27/2019] [Accepted: 08/02/2019] [Indexed: 12/11/2022] Open
Abstract
The human brain is active during rest and hierarchically organized into intrinsic functional networks. These functional networks are largely established early in development, with reports of a shift from a local to more distributed organization during childhood and adolescence. It remains unknown to what extent genetic and environmental influences on functional connectivity change throughout adolescent development. We measured functional connectivity within and between eight cortical networks in a longitudinal resting-state fMRI study of adolescent twins and their older siblings on two occasions (mean ages 13 and 18 years). We modelled the reliability for these inherently noisy and head-motion sensitive measurements by analyzing data from split-half sessions. Functional connectivity between resting-state networks decreased with age whereas functional connectivity within resting-state networks generally increased with age, independent of general cognitive functioning. Sex effects were sparse, with stronger functional connectivity in the default mode network for girls compared to boys, and stronger functional connectivity in the salience network for boys compared to girls. Heritability explained up to 53% of the variation in functional connectivity within and between resting-state networks, and common environment explained up to 33%. Genetic influences on functional connectivity remained stable during adolescent development. In conclusion, longitudinal age-related changes in functional connectivity within and between cortical resting-state networks are subtle but wide-spread throughout adolescence. Genes play a considerable role in explaining individual variation in functional connectivity with mostly stable influences throughout adolescence.
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Individual differences in the effect of menstrual cycle on basal ganglia inhibitory control. Sci Rep 2019; 9:11063. [PMID: 31363112 PMCID: PMC6667495 DOI: 10.1038/s41598-019-47426-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Accepted: 07/17/2019] [Indexed: 12/22/2022] Open
Abstract
Basal ganglia (BG) are involved in inhibitory control (IC) and known to change in structure and activation along the menstrual cycle. Therefore, we investigated BG activation and connectivity patterns related to IC during different cycle phases. Thirty-six naturally cycling women were scanned three times performing a Stop Signal Task and hormonal levels analysed from saliva samples. We found an impaired Stop signal reaction time (SSRT) during pre-ovulatory compared to menses the higher the baseline IC of women. Blood oxygen level dependent (BOLD)-response in bilateral putamen significantly decreased during the luteal phase. Connectivity strength from the left putamen displayed an interactive effect of cycle and IC. During pre-ovulatory the connectivity with anterior cingulate cortex and left inferior parietal lobe was significantly stronger the higher the IC, and during luteal with left supplementary motor area. Right putamen's activation and left hemisphere's connectivity predicted the SSRT across participants. Therefore, we propose a compensatory mechanism for the hormonal changes across the menstrual cycle based on a lateralized pattern.
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Pallayova M, Brandeburova A, Tokarova D. Update on Sexual Dimorphism in Brain Structure–Function Interrelationships: A Literature Review. Appl Psychophysiol Biofeedback 2019; 44:271-284. [DOI: 10.1007/s10484-019-09443-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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47
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Adolescent sex differences in cortico-subcortical functional connectivity during response inhibition. COGNITIVE AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2019; 20:1-18. [PMID: 31111341 DOI: 10.3758/s13415-019-00718-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Numerous lines of evidence have shown that cognitive processes engaged during response inhibition tasks are associated with structure and functional integration of regions within fronto-parietal networks. However, while prior studies have started to characterize how intrinsic connectivity during resting state differs between boys and girls, comparatively less is known about how functional connectivity differs between males and females when brain function is exogenously driven by the processing demands of typical Go/No-Go tasks that assess both response inhibition and error processing. The purpose of this study was to characterize adolescent sex differences and possible changes in sexually dimorphic regional functional connectivity across adolescent development in both cortical and subcortical brain connectivity elicited during a visual Go/No-Go task. A total of 130 healthy adolescents (ages 12-25 years) performed a Go/No-Go task during functional magnetic resonance imaging. High model-order group independent component analysis was used to characterize whole-brain network functional connectivity during response inhibition and then a univariate technique used to evaluate differences related to sex and age. As predicted and similar to previously described findings from non-task-driven resting state connectivity studies, functional connectivity sex differences were observed in several subcortical regions, including the amygdala, caudate, thalamus, and cortical regions, including inferior frontal gyrus engaged most strongly during successful response inhibition and/or error processing. Importantly, adolescent boys and girls exhibited different normative profiles of age-related changes in several default mode networks of regions and anterior cingulate cortex. These results suggest that cortical-subcortical functional networks supporting response inhibition operate differently between sexes during adolescence.
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48
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de Lacy N, McCauley E, Kutz JN, Calhoun VD. Multilevel Mapping of Sexual Dimorphism in Intrinsic Functional Brain Networks. Front Neurosci 2019; 13:332. [PMID: 31024243 PMCID: PMC6460937 DOI: 10.3389/fnins.2019.00332] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2018] [Accepted: 03/21/2019] [Indexed: 12/17/2022] Open
Abstract
Differences in cognitive performance between males and females are well-described, most commonly in certain spatial and language tasks. Sex-related differences in cognition are relevant to the study of the neurotypical brain and to neuropsychiatric disorders, which exhibit prominent disparities in the incidence, prevalence and severity of symptoms between men and women. While structural dimorphism in the human brain is well-described, controversy exists regarding the existence and degree of sex-related differences in brain function. We analyzed resting-state functional MRI from 650 neurotypical young adults matched for age and sex to determine the degree of sexual dimorphism present in intrinsic functional networks. Multilevel modeling was pursued to create 8-, 24-, and 51-network models of whole-brain data to quantify sex-related effects in network activity with increasing resolution. We determined that sexual dimorphism is present in the majority of intrinsic brain networks and affects ∼0.5-2% of brain locations surveyed in the three whole-brain network models. It is particularly common in task-positive control networks and is pervasive among default mode networks. The size of sex-related effects varied by network but can be moderate or even large in size. Female > male effects were on average larger, but male > female effects spread across greater network territory. Using a novel methodology, we mapped dimorphic locations to meta-analytic association test maps derived from task fMRI, demonstrating that the neurocognitive footprint of intrinsic neural correlates is much larger in males. All results were replicated in a motion-matched sub-sample. Our findings argue that sex is an important biological variable in human brain function and suggest that observed differences in neurocognitive performance have identifiable intrinsic neural correlates.
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Affiliation(s)
- Nina de Lacy
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States
| | - Elizabeth McCauley
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States
| | - J. Nathan Kutz
- Department of Applied Mathematics, University of Washington, Seattle, WA, United States
| | - Vince D. Calhoun
- Mind Research Network, Albuquerque, NM, United States
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, United States
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49
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Mukaibo T, Gao X, Yang NY, Oei MS, Nakamoto T, Melvin JE. Sexual dimorphisms in the transcriptomes of murine salivary glands. FEBS Open Bio 2019; 9:947-958. [PMID: 30998297 PMCID: PMC6487692 DOI: 10.1002/2211-5463.12625] [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] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 03/05/2019] [Accepted: 03/17/2019] [Indexed: 12/25/2022] Open
Abstract
Transcriptional profiling identified 933 sexually dimorphic genes out of the 14 371 protein‐coding genes expressed in the three major murine salivary glands: parotid, sublingual, and submandibular. Most (89%) sex‐specific genes were enriched in a single gland, while only 0.5% of the sexually dimorphic genes were enriched in all glands. The sublingual gland displayed a strong male sex bias (94% of sex‐enriched genes), while a sex preference was not obvious in the parotid or submandibular glands. A subset of transcription factor genes was correlated with the expression of gland‐specific, sex‐enriched genes. Higher expression of Cftr chloride and Scnn1 sodium channels in the male submandibular correlated with greater NaCl reabsorption. In conclusion, adult salivary glands display sex‐ and gland‐specific differences in gene expression that reflect their unique functional properties.
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Affiliation(s)
- Taro Mukaibo
- Secretory Mechanisms and Dysfunctions Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA.,Division of Oral Reconstruction and Rehabilitation, Kyushu Dental University, Kitakyushu, Fukuoka, Japan
| | - Xin Gao
- Secretory Mechanisms and Dysfunctions Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA.,Joint Institute for Food Safety and Applied Nutrition, University of Maryland, College Park, MD, USA
| | - Ning-Yan Yang
- Secretory Mechanisms and Dysfunctions Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA.,Department of Pediatric Dentistry, Beijing Stomatological Hospital & School of Stomatology, Capital Medical University, Beijing, China
| | - Maria S Oei
- Secretory Mechanisms and Dysfunctions Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA
| | - Tetsuji Nakamoto
- Department of Prosthodontics, Matsumoto Dental University, Shiojiri, Japan
| | - James E Melvin
- Secretory Mechanisms and Dysfunctions Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA
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50
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Yagi S, Galea LAM. Sex differences in hippocampal cognition and neurogenesis. Neuropsychopharmacology 2019; 44:200-213. [PMID: 30214058 PMCID: PMC6235970 DOI: 10.1038/s41386-018-0208-4] [Citation(s) in RCA: 191] [Impact Index Per Article: 38.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2018] [Revised: 08/29/2018] [Accepted: 08/30/2018] [Indexed: 12/27/2022]
Abstract
Sex differences are reported in hippocampal plasticity, cognition, and in a number of disorders that target the integrity of the hippocampus. For example, meta-analyses reveal that males outperform females on hippocampus-dependent tasks in rodents and in humans, furthermore women are more likely to experience greater cognitive decline in Alzheimer's disease and depression, both diseases characterized by hippocampal dysfunction. The hippocampus is a highly plastic structure, important for processing higher order information and is sensitive to the environmental factors such as stress. The structure retains the ability to produce new neurons and this process plays an important role in pattern separation, proactive interference, and cognitive flexibility. Intriguingly, there are prominent sex differences in the level of neurogenesis and the activation of new neurons in response to hippocampus-dependent cognitive tasks in rodents. However, sex differences in spatial performance can be nuanced as animal studies have demonstrated that there are task, and strategy choice dependent sex differences in performance, as well as sex differences in the subregions of the hippocampus influenced by learning. This review discusses sex differences in pattern separation, pattern completion, spatial learning, and links between adult neurogenesis and these cognitive functions of the hippocampus. We emphasize the importance of including both sexes when studying genomic, cellular, and structural mechanisms of the hippocampal function.
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Affiliation(s)
- Shunya Yagi
- Department of Psychology, Graduate Program in Neuroscience, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Liisa A M Galea
- Department of Psychology, Graduate Program in Neuroscience, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada.
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