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Marceau K, Conradt E, Roubinov D. Prenatal influences across the life course: Biobehavioral mechanisms of development. Dev Psychol 2024; 60:1533-1543. [PMID: 39207388 DOI: 10.1037/dev0001794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
Despite the well-established importance of prenatal experiences for offspring health throughout the lifespan, our understanding of prenatal influences on psychological outcomes faces challenges due to a wide-ranging and somewhat fragmented literature. Here, we introduce the special issue of Developmental Psychology, "Prenatal Influences Across the Life Course: Biobehavioral Mechanisms of Development," which draws together a broad collection of 12 empirical studies and one review article. These studies illustrate the diversity in biobehavioral mechanisms and biopsychosocial processes that help explain the long-term impacts of prenatal experiences on human development. Collectively, these studies help to disentangle sources of influence across different life stages (e.g., prenatal from genetic, preconception, and/or postnatal influences) and fill key gaps in the literature, such as the inclusion of minoritized populations currently underrepresented in research, the role of fathers, and protective mechanisms. The research featured in this special issue underscores both the long reach of prenatal influences on child and adolescent development as well as the challenges in observing specific biological mediators given that prenatal risks are currently operationalized as specific or broad cumulative measures. In an effort to organize this complex literature, we propose a guiding framework for how to conceptualize the continued integration of the prenatal environment into the field of developmental psychology. This framework broadens the prevailing dichotomous view of prenatal mechanisms as cumulative or specific to articulate a dimensional approach focused on adaptation. We anticipate that such an approach may uncover meaningful and observable biobehavioral mechanisms of prenatal influence on offspring development in the future. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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Mangalam M, Isoyama Y, Ogata H, Nose-Ogura S, Kayaba M, Nagai N, Kiyono K. Multi-scaling allometry in human development, mammalian morphology, and tree growth. Sci Rep 2024; 14:19957. [PMID: 39198500 PMCID: PMC11358500 DOI: 10.1038/s41598-024-69199-5] [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: 02/14/2024] [Accepted: 08/01/2024] [Indexed: 09/01/2024] Open
Abstract
Various animal and plant species exhibit allometric relationships among their respective traits, wherein one trait undergoes expansion as a power-law function of another due to constraints acting on growth processes. For instance, the acknowledged consensus posits that tree height scales with the two-thirds power of stem diameter. In the context of human development, it is posited that body weight scales with the second power of height. This prevalent allometric relationship derives its nomenclature from fitting two variables linearly within a logarithmic framework, thus giving rise to the term "power-law relationship." Here, we challenge the conventional assumption that a singular power-law equation adequately encapsulates the allometric relationship between any two traits. We strategically leverage quantile regression analysis to demonstrate that the scaling exponent characterizing this power-law relationship is contingent upon the centile within these traits' distributions. This observation fundamentally underscores the proposition that individuals occupying disparate segments of the distribution may employ distinct growth strategies, as indicated by distinct power-law exponents. We introduce the innovative concept of "multi-scale allometry" to encapsulate this newfound insight. Through a comprehensive reevaluation of (i) the height-weight relationship within a cohort comprising 7, 863, 520 Japanese children aged 5-17 years for which the age, sex, height, and weight were recorded as part of a national study, (ii) the stem-diameter-height and crown-radius-height relationships within an expansive sample of 498, 838 georeferenced and taxonomically standardized records of individual trees spanning diverse geographical locations, and (iii) the brain-size-body-size relationship within an extensive dataset encompassing 1, 552 mammalian species, we resolutely substantiate the viability of multi-scale allometric analysis. This empirical substantiation advocates a paradigm shift from uni-scaling to multi-scaling allometric modeling, thereby affording greater prominence to the inherent growth processes that underlie the morphological diversity evident throughout the living world.
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Hopwood N. Species Choice and Model Use: Reviving Research on Human Development. JOURNAL OF THE HISTORY OF BIOLOGY 2024; 57:231-279. [PMID: 39075321 PMCID: PMC11341657 DOI: 10.1007/s10739-024-09775-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/13/2024] [Indexed: 07/31/2024]
Abstract
While model organisms have had many historians, this article places studies of humans, and particularly our development, in the politics of species choice. Human embryos, investigated directly rather than via animal surrogates, have gone through cycles of attention and neglect. In the past 60 years they moved from the sidelines to center stage. Research was resuscitated in anatomy, launched in reproductive biomedicine, molecular genetics, and stem-cell science, and made attractive in developmental biology. I explain this surge of interest in terms of rivalry with models and reliance on them. The greater involvement of medicine in human reproduction, especially through in vitro fertilization, gave access to fresh sources of material that fed critiques of extrapolation from mice and met demands for clinical relevance or "translation." Yet much of the revival depended on models. Supply infrastructures and digital standards, including biobanks and virtual atlases, emulated community resources for model organisms. Novel culture, imaging, molecular, and postgenomic methods were perfected on less precious samples. Toing and froing from the mouse affirmed the necessity of the exemplary mammal and its insufficiency justified inquiries into humans. Another kind of model-organoids and embryo-like structures derived from stem cells-enabled experiments that encouraged the organization of a new field, human developmental biology. Research on humans has competed with and counted on models.
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Vaisarova J, Lucca K. A developmental account of curiosity and creativity. Behav Brain Sci 2024; 47:e116. [PMID: 38770858 DOI: 10.1017/s0140525x23003485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Ivancovsky et al.'s Novelty-Seeking Model suggests several mechanisms that might underlie developmental change in creativity and curiosity. We discuss how these implications both do and do not align with extant developmental findings, suggest two further elements that can provide a more complete developmental account, and discuss current methodological barriers to formulating an integrated developmental model of curiosity and creativity.
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Rivas-Sucari D, Rodríguez-Eguizabal JL, Rivas-Sucari HC. Diabetes mellitus type 2: associations with obesity, food addiction and, possibly, human development index. GAC MED MEX 2024; 160:227-228. [PMID: 39116864 DOI: 10.24875/gmm.m24000874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Accepted: 03/19/2024] [Indexed: 08/10/2024] Open
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Erb CD, Germine L, Hartshorne JK. Cognitive control across the lifespan: Congruency effects reveal divergent developmental trajectories. J Exp Psychol Gen 2023; 152:3285-3291. [PMID: 37289513 DOI: 10.1037/xge0001429] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The Simon, Stroop, and Eriksen flanker tasks are commonly used to assess cognitive control across the lifespan. However, it remains unclear whether these three tasks in fact measure the same cognitive abilities and in the same proportion. We take a developmental approach to this question: if the Simon, Stroop, and flanker tasks all roughly measure the same capacity, they should show similar patterns of age-related change. We present data from two massive online cross-sectional studies: Study 1 included 9,585 native English speakers between 10 and 80 years of age who completed the Simon and Stroop tasks, and Study 2 included 13,448 English speakers between 10 and 79 years of age who completed the flanker task. Of the three tasks, only the flanker task revealed an inverted U-shaped developmental trajectory, with performance improving until approximately 23 years of age and declining starting around 40 years of age. Performance on the Simon and Stroop tasks peaked around 34 and 26 years of age, respectively, and did not decline significantly in later life, though it is possible that age-related declines would be observed with more difficult versions of the tasks. Although the Simon and Stroop tasks are commonly interpreted to target similar underlying processes, we observed near zero correlations between the congruency effects observed in each task in terms of both accuracy and response time. We discuss these results in light of recent debates regarding the suitability of these tasks for assessing developmental and individual differences in cognitive control. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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Abstract
Historically, the immune system was believed to develop along a linear axis of maturity from fetal life to adulthood. Now, it is clear that distinct layers of immune cells are generated from unique waves of hematopoietic progenitors during different windows of development. This model, known as the layered immune model, has provided a useful framework for understanding why distinct lineages of B cells and γδ T cells arise in succession and display unique functions in adulthood. However, the layered immune model has not been applied to CD8+ T cells, which are still often viewed as a uniform population of cells belonging to the same lineage, with functional differences between cells arising from environmental factors encountered during infection. Recent studies have challenged this idea, demonstrating that not all CD8+ T cells are created equally and that the functions of individual CD8+ T cells in adults are linked to when they were created in the host. In this review, we discuss the accumulating evidence suggesting there are distinct ontogenetic subpopulations of CD8+ T cells and propose that the layered immune model be extended to the CD8+ T cell compartment.
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Wood DA, Kafiabadi S, Busaidi AA, Guilhem E, Montvila A, Lynch J, Townend M, Agarwal S, Mazumder A, Barker GJ, Ourselin S, Cole JH, Booth TC. Accurate brain-age models for routine clinical MRI examinations. Neuroimage 2022; 249:118871. [PMID: 34995797 DOI: 10.1016/j.neuroimage.2022.118871] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 11/26/2021] [Accepted: 01/03/2022] [Indexed: 01/08/2023] Open
Abstract
Convolutional neural networks (CNN) can accurately predict chronological age in healthy individuals from structural MRI brain scans. Potentially, these models could be applied during routine clinical examinations to detect deviations from healthy ageing, including early-stage neurodegeneration. This could have important implications for patient care, drug development, and optimising MRI data collection. However, existing brain-age models are typically optimised for scans which are not part of routine examinations (e.g., volumetric T1-weighted scans), generalise poorly (e.g., to data from different scanner vendors and hospitals etc.), or rely on computationally expensive pre-processing steps which limit real-time clinical utility. Here, we sought to develop a brain-age framework suitable for use during routine clinical head MRI examinations. Using a deep learning-based neuroradiology report classifier, we generated a dataset of 23,302 'radiologically normal for age' head MRI examinations from two large UK hospitals for model training and testing (age range = 18-95 years), and demonstrate fast (< 5 s), accurate (mean absolute error [MAE] < 4 years) age prediction from clinical-grade, minimally processed axial T2-weighted and axial diffusion-weighted scans, with generalisability between hospitals and scanner vendors (Δ MAE < 1 year). The clinical relevance of these brain-age predictions was tested using 228 patients whose MRIs were reported independently by neuroradiologists as showing atrophy 'excessive for age'. These patients had systematically higher brain-predicted age than chronological age (mean predicted age difference = +5.89 years, 'radiologically normal for age' mean predicted age difference = +0.05 years, p < 0.0001). Our brain-age framework demonstrates feasibility for use as a screening tool during routine hospital examinations to automatically detect older-appearing brains in real-time, with relevance for clinical decision-making and optimising patient pathways.
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Wierenga LM, Doucet GE, Dima D, Agartz I, Aghajani M, Akudjedu TN, Albajes‐Eizagirre A, Alnæs D, Alpert KI, Andreassen OA, Anticevic A, Asherson P, Banaschewski T, Bargallo N, Baumeister S, Baur‐Streubel R, Bertolino A, Bonvino A, Boomsma DI, Borgwardt S, Bourque J, den Braber A, Brandeis D, Breier A, Brodaty H, Brouwer RM, Buitelaar JK, Busatto GF, Calhoun VD, Canales‐Rodríguez EJ, Cannon DM, Caseras X, Castellanos FX, Chaim‐Avancini TM, Ching CRK, Clark VP, Conrod PJ, Conzelmann A, Crivello F, Davey CG, Dickie EW, Ehrlich S, van't Ent D, Fisher SE, Fouche J, Franke B, Fuentes‐Claramonte P, de Geus EJC, Di Giorgio A, Glahn DC, Gotlib IH, Grabe HJ, Gruber O, Gruner P, Gur RE, Gur RC, Gurholt TP, de Haan L, Haatveit B, Harrison BJ, Hartman CA, Hatton SN, Heslenfeld DJ, van den Heuvel OA, Hickie IB, Hoekstra PJ, Hohmann S, Holmes AJ, Hoogman M, Hosten N, Howells FM, Hulshoff Pol HE, Huyser C, Jahanshad N, James AC, Jiang J, Jönsson EG, Joska JA, Kalnin AJ, Klein M, Koenders L, Kolskår KK, Krämer B, Kuntsi J, Lagopoulos J, Lazaro L, Lebedeva IS, Lee PH, Lochner C, Machielsen MWJ, Maingault S, Martin NG, Martínez‐Zalacaín I, Mataix‐Cols D, Mazoyer B, McDonald BC, McDonald C, McIntosh AM, McMahon KL, McPhilemy G, van der Meer D, Menchón JM, Naaijen J, Nyberg L, Oosterlaan J, Paloyelis Y, Pauli P, Pergola G, Pomarol‐Clotet E, Portella MJ, Radua J, Reif A, Richard G, Roffman JL, Rosa PGP, Sacchet MD, Sachdev PS, Salvador R, Sarró S, Satterthwaite TD, Saykin AJ, Serpa MH, Sim K, Simmons A, Smoller JW, Sommer IE, Soriano‐Mas C, Stein DJ, Strike LT, Szeszko PR, Temmingh HS, Thomopoulos SI, Tomyshev AS, Trollor JN, Uhlmann A, Veer IM, Veltman DJ, Voineskos A, Völzke H, Walter H, Wang L, Wang Y, Weber B, Wen W, West JD, Westlye LT, Whalley HC, Williams SCR, Wittfeld K, Wolf DH, Wright MJ, Yoncheva YN, Zanetti MV, Ziegler GC, de Zubicaray GI, Thompson PM, Crone EA, Frangou S, Tamnes CK. Greater male than female variability in regional brain structure across the lifespan. Hum Brain Mapp 2022; 43:470-499. [PMID: 33044802 PMCID: PMC8675415 DOI: 10.1002/hbm.25204] [Citation(s) in RCA: 53] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 08/10/2020] [Accepted: 09/05/2020] [Indexed: 12/25/2022] Open
Abstract
For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.
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Dima D, Modabbernia A, Papachristou E, Doucet GE, Agartz I, Aghajani M, Akudjedu TN, Albajes‐Eizagirre A, Alnæs D, Alpert KI, Andersson M, Andreasen NC, Andreassen OA, Asherson P, Banaschewski T, Bargallo N, Baumeister S, Baur‐Streubel R, Bertolino A, Bonvino A, Boomsma DI, Borgwardt S, Bourque J, Brandeis D, Breier A, Brodaty H, Brouwer RM, Buitelaar JK, Busatto GF, Buckner RL, Calhoun V, Canales‐Rodríguez EJ, Cannon DM, Caseras X, Castellanos FX, Cervenka S, Chaim‐Avancini TM, Ching CRK, Chubar V, Clark VP, Conrod P, Conzelmann A, Crespo‐Facorro B, Crivello F, Crone EA, Dannlowski U, Dale AM, Davey C, de Geus EJC, de Haan L, de Zubicaray GI, den Braber A, Dickie EW, Di Giorgio A, Doan NT, Dørum ES, Ehrlich S, Erk S, Espeseth T, Fatouros‐Bergman H, Fisher SE, Fouche J, Franke B, Frodl T, Fuentes‐Claramonte P, Glahn DC, Gotlib IH, Grabe H, Grimm O, Groenewold NA, Grotegerd D, Gruber O, Gruner P, Gur RE, Gur RC, Hahn T, Harrison BJ, Hartman CA, Hatton SN, Heinz A, Heslenfeld DJ, Hibar DP, Hickie IB, Ho B, Hoekstra PJ, Hohmann S, Holmes AJ, Hoogman M, Hosten N, Howells FM, Hulshoff Pol HE, Huyser C, Jahanshad N, James A, Jernigan TL, Jiang J, Jönsson EG, Joska JA, Kahn R, Kalnin A, Kanai R, Klein M, Klyushnik TP, Koenders L, Koops S, Krämer B, Kuntsi J, Lagopoulos J, Lázaro L, Lebedeva I, Lee WH, Lesch K, Lochner C, Machielsen MWJ, Maingault S, Martin NG, Martínez‐Zalacaín I, Mataix‐Cols D, Mazoyer B, McDonald C, McDonald BC, McIntosh AM, McMahon KL, McPhilemy G, Meinert S, Menchón JM, Medland SE, Meyer‐Lindenberg A, Naaijen J, Najt P, Nakao T, Nordvik JE, Nyberg L, Oosterlaan J, de la Foz VO, Paloyelis Y, Pauli P, Pergola G, Pomarol‐Clotet E, Portella MJ, Potkin SG, Radua J, Reif A, Rinker DA, Roffman JL, Rosa PGP, Sacchet MD, Sachdev PS, Salvador R, Sánchez‐Juan P, Sarró S, Satterthwaite TD, Saykin AJ, Serpa MH, Schmaal L, Schnell K, Schumann G, Sim K, Smoller JW, Sommer I, Soriano‐Mas C, Stein DJ, Strike LT, Swagerman SC, Tamnes CK, Temmingh HS, Thomopoulos SI, Tomyshev AS, Tordesillas‐Gutiérrez D, Trollor JN, Turner JA, Uhlmann A, van den Heuvel OA, van den Meer D, van der Wee NJA, van Haren NEM, van't Ent D, van Erp TGM, Veer IM, Veltman DJ, Voineskos A, Völzke H, Walter H, Walton E, Wang L, Wang Y, Wassink TH, Weber B, Wen W, West JD, Westlye LT, Whalley H, Wierenga LM, Williams SCR, Wittfeld K, Wolf DH, Worker A, Wright MJ, Yang K, Yoncheva Y, Zanetti MV, Ziegler GC, Thompson PM, Frangou S. Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years. Hum Brain Mapp 2022; 43:452-469. [PMID: 33570244 PMCID: PMC8675429 DOI: 10.1002/hbm.25320] [Citation(s) in RCA: 61] [Impact Index Per Article: 30.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 11/27/2020] [Accepted: 12/06/2020] [Indexed: 12/25/2022] Open
Abstract
Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.
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Frangou S, Modabbernia A, Williams SCR, Papachristou E, Doucet GE, Agartz I, Aghajani M, Akudjedu TN, Albajes‐Eizagirre A, Alnæs D, Alpert KI, Andersson M, Andreasen NC, Andreassen OA, Asherson P, Banaschewski T, Bargallo N, Baumeister S, Baur‐Streubel R, Bertolino A, Bonvino A, Boomsma DI, Borgwardt S, Bourque J, Brandeis D, Breier A, Brodaty H, Brouwer RM, Buitelaar JK, Busatto GF, Buckner RL, Calhoun V, Canales‐Rodríguez EJ, Cannon DM, Caseras X, Castellanos FX, Cervenka S, Chaim‐Avancini TM, Ching CRK, Chubar V, Clark VP, Conrod P, Conzelmann A, Crespo‐Facorro B, Crivello F, Crone EA, Dale AM, Dannlowski U, Davey C, de Geus EJC, de Haan L, de Zubicaray GI, den Braber A, Dickie EW, Di Giorgio A, Doan NT, Dørum ES, Ehrlich S, Erk S, Espeseth T, Fatouros‐Bergman H, Fisher SE, Fouche J, Franke B, Frodl T, Fuentes‐Claramonte P, Glahn DC, Gotlib IH, Grabe H, Grimm O, Groenewold NA, Grotegerd D, Gruber O, Gruner P, Gur RE, Gur RC, Hahn T, Harrison BJ, Hartman CA, Hatton SN, Heinz A, Heslenfeld DJ, Hibar DP, Hickie IB, Ho B, Hoekstra PJ, Hohmann S, Holmes AJ, Hoogman M, Hosten N, Howells FM, Hulshoff Pol HE, Huyser C, Jahanshad N, James A, Jernigan TL, Jiang J, Jönsson EG, Joska JA, Kahn R, Kalnin A, Kanai R, Klein M, Klyushnik TP, Koenders L, Koops S, Krämer B, Kuntsi J, Lagopoulos J, Lázaro L, Lebedeva I, Lee WH, Lesch K, Lochner C, Machielsen MWJ, Maingault S, Martin NG, Martínez‐Zalacaín I, Mataix‐Cols D, Mazoyer B, McDonald C, McDonald BC, McIntosh AM, McMahon KL, McPhilemy G, Meinert S, Menchón JM, Medland SE, Meyer‐Lindenberg A, Naaijen J, Najt P, Nakao T, Nordvik JE, Nyberg L, Oosterlaan J, de la Foz VO, Paloyelis Y, Pauli P, Pergola G, Pomarol‐Clotet E, Portella MJ, Potkin SG, Radua J, Reif A, Rinker DA, Roffman JL, Rosa PGP, Sacchet MD, Sachdev PS, Salvador R, Sánchez‐Juan P, Sarró S, Satterthwaite TD, Saykin AJ, Serpa MH, Schmaal L, Schnell K, Schumann G, Sim K, Smoller JW, Sommer I, Soriano‐Mas C, Stein DJ, Strike LT, Swagerman SC, Tamnes CK, Temmingh HS, Thomopoulos SI, Tomyshev AS, Tordesillas‐Gutiérrez D, Trollor JN, Turner JA, Uhlmann A, van den Heuvel OA, van den Meer D, van der Wee NJA, van Haren NEM, van 't Ent D, van Erp TGM, Veer IM, Veltman DJ, Voineskos A, Völzke H, Walter H, Walton E, Wang L, Wang Y, Wassink TH, Weber B, Wen W, West JD, Westlye LT, Whalley H, Wierenga LM, Wittfeld K, Wolf DH, Worker A, Wright MJ, Yang K, Yoncheva Y, Zanetti MV, Ziegler GC, Thompson PM, Dima D. Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years. Hum Brain Mapp 2022; 43:431-451. [PMID: 33595143 PMCID: PMC8675431 DOI: 10.1002/hbm.25364] [Citation(s) in RCA: 113] [Impact Index Per Article: 56.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 01/02/2021] [Accepted: 01/21/2021] [Indexed: 12/25/2022] Open
Abstract
Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
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van Noordt S, Heffer T, Willoughby T. A developmental examination of medial frontal theta dynamics and inhibitory control. Neuroimage 2021; 246:118765. [PMID: 34875380 DOI: 10.1016/j.neuroimage.2021.118765] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 11/19/2021] [Accepted: 11/24/2021] [Indexed: 12/11/2022] Open
Abstract
Medial frontal theta-band oscillations are a robust marker of action-outcome monitoring. In a large developmental sample (n = 432, 9-16 years), we examined whether phase and non-phase locked medial frontal theta power were related to inhibitory control among children and adolescents. Our results showed that the well-established increase in medial frontal theta power during inhibitory control was captured largely by non-phase locked dynamics, which partially mediated the positive effect of age on task performance. A person-centered approach also revealed latent classes of individuals based on their multivariate theta power dynamics (phase locked/non-phase locked, GO/NOGO). The class of individuals showing low phase locked and high non-phase locked medial frontal theta were significantly older, had better inhibitory control, scored higher on measures of general cognitive function, and were more efficient in their behavioural responses. The functional significance of phase and non-phase locked theta dynamics, and their potential changes, could have important implications for action-outcome monitoring and cognitive function in both typical and atypical development, as well as related psychopathology .
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Tan SC, Gamaldo AA, Brick T, Thorpe RJ, Allaire JC, Whitfield KE. The Effects of Selective Survival on Black Adults' Cognitive Development. J Gerontol B Psychol Sci Soc Sci 2021; 76:1489-1498. [PMID: 33406264 PMCID: PMC8436692 DOI: 10.1093/geronb/gbab003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVES The theory of selective survival suggests that possibly around 70-75 years of age, Blacks may display substantive changes in their pattern of cognitive decline. This study examined the age-graded pattern of cognitive decline within older Blacks by describing a trend that characterizes differences in the change of cognitive decline from ages 51.5 to 95.5, and hypothesized that this age-graded pattern is nonlinear. METHOD Utilizing 2 waves of longitudinal data from the Baltimore Study of Black Aging, this study used multilevel modeling to test whether the interaction between age and the 3-year study period (time between waves) had a positive effect on changes in inductive reasoning, declarative memory, working memory, and perceptual speed. RESULTS A significant positive interaction between age and wave was found for inductive reasoning, demonstrating an age-grade pattern of change/decline in cognitive pattern for Blacks aged 51.5-95.4. Simple slope probing via the Johnson-Neyman Technique suggested that Black adults ~64 years and younger experienced significant decline in inductive reasoning across study time, whereas for those older than 63.71, the decline was nonsignificant. No significant age-wave interactions were found for declarative memory, working memory, or perceptual speed. DISCUSSION Findings suggest a selective survival effect for inductive reasoning ability among Blacks. With decline evident so early, common cognitive intervention programs targeting adults 65+ may come too late for Blacks, signifying the importance and urgency for early health interventions and public policy designed to promote cognitive reserve.
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Lidstone DE, Mostofsky SH. Moving Toward Understanding Autism: Visual-Motor Integration, Imitation, and Social Skill Development. Pediatr Neurol 2021; 122:98-105. [PMID: 34330613 PMCID: PMC8372541 DOI: 10.1016/j.pediatrneurol.2021.06.010] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 06/19/2021] [Accepted: 06/22/2021] [Indexed: 11/25/2022]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a behavioral phenotype characterized by impaired development of social-communicative skills and excessive repetitive and stereotyped behaviors. Despite high phenotypic heterogeneity in ASD, a meaningful subpopulation of children with ASD (∼90%) show significant general motor impairment. More focused studies on the nature of motor impairment in ASD reveal that children with ASD are particularly impaired on tasks such as ball catching and motor imitation that require efficient visual-motor integration (VMI). Motor computational approaches also provide evidence for VMI impairment showing that children with ASD form internal sensorimotor representations that bias proprioceptive over visual feedback. Impaired integration of visual information to form internal representations of others' and the external world may explain observed impairments on VMI tasks and motor imitation of others. Motor imitation is crucial for acquiring both social and motor skills, and impaired imitation skill may contribute to the observed core behavioral phenotype of ASD. The current review examines evidence supporting VMI impairment as a core feature of ASD that may contribute to both impaired motor imitation and social-communicative skill development. We propose that understanding the neurobiological mechanisms underlying VMI impairment in ASD may be key to discovery of therapeutics to address disability in children and adults with ASD.
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Drakulich S, Thiffault AC, Olafson E, Parent O, Labbe A, Albaugh MD, Khundrakpam B, Ducharme S, Evans A, Chakravarty MM, Karama S. Maturational trajectories of pericortical contrast in typical brain development. Neuroimage 2021; 235:117974. [PMID: 33766753 PMCID: PMC8278832 DOI: 10.1016/j.neuroimage.2021.117974] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 02/27/2021] [Accepted: 03/17/2021] [Indexed: 11/16/2022] Open
Abstract
In the last few years, a significant amount of work has aimed to characterize maturational trajectories of cortical development. The role of pericortical microstructure putatively characterized as the gray-white matter contrast (GWC) at the pericortical gray-white matter boundary and its relationship to more traditional morphological measures of cortical morphometry has emerged as a means to examine finer grained neuroanatomical underpinnings of cortical changes. In this work, we characterize the GWC developmental trajectories in a representative sample (n = 394) of children and adolescents (~4 to ~22 years of age), with repeated scans (1-3 scans per subject, total scans n = 819). We tested whether linear, quadratic, or cubic trajectories of contrast development best described changes in GWC. A best-fit model was identified vertex-wise across the whole cortex via the Akaike Information Criterion (AIC). GWC across nearly the whole brain was found to significantly change with age. Cubic trajectories were likeliest for 63% of vertices, quadratic trajectories were likeliest for 20% of vertices, and linear trajectories were likeliest for 16% of vertices. A main effect of sex was observed in some regions, where males had a higher GWC than females. However, no sex by age interactions were found on GWC. In summary, our results suggest a progressive decrease in GWC at the pericortical boundary throughout childhood and adolescence. This work contributes to efforts seeking to characterize typical, healthy brain development and, by extension, can help elucidate aberrant developmental trajectories.
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Grasser LR, Jovanovic T. Safety learning during development: Implications for development of psychopathology. Behav Brain Res 2021; 408:113297. [PMID: 33862062 PMCID: PMC8102395 DOI: 10.1016/j.bbr.2021.113297] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 03/23/2021] [Accepted: 04/11/2021] [Indexed: 12/13/2022]
Abstract
Fear and safety learning are necessary adaptive behaviors that develop over the course of maturation. While there is a large body of literature regarding the neurobiology of fear and safety learning in adults, less is known regarding safety learning during development. Given developmental changes in the brain, there are corresponding changes in safety learning that are quantifiable; these may serve to predict risk and point to treatment targets for fear and anxiety-related disorders in children and adolescents. For healthy, typically developing youth, the main developmental variation observed is reduced discrimination between threat and safety cues in children compared to adolescents and adults, while lower expression of extinction learning is exhibited in adolescents compared to adults. Such distinctions may be related to faster maturation of the amygdala relative to the prefrontal cortex, as well as incompletely developed functional circuits between the two. Fear and anxiety-related disorders, childhood maltreatment, and behavioral problems are all associated with alterations in safety learning for youth, and this dysfunction may proceed into adulthood with corresponding abnormalities in brain structure and function-including amygdala hypertrophy and hyperreactivity. As impaired inhibition of fear to safety may reflect abnormalities in the developing brain and subsequent psychopathology, impaired safety learning may be considered as both a predictor of risk and a treatment target. Longitudinal neuroimaging studies over the course of development, and studies that query change with interventions are needed in order to improve outcomes for individuals and reduce long-term impact of developmental psychopathology.
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Zacharopoulos G, Emir U, Cohen Kadosh R. The cross-sectional interplay between neurochemical profile and brain connectivity. Hum Brain Mapp 2021; 42:2722-2733. [PMID: 33835605 PMCID: PMC8127145 DOI: 10.1002/hbm.25396] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 02/11/2021] [Accepted: 02/21/2021] [Indexed: 01/05/2023] Open
Abstract
Neurochemical profile and brain connectivity are both critical aspects of brain function. However, our knowledge of their interplay across development is currently poor. We combined single-voxel magnetic resonance spectroscopy and resting functional magnetic resonance imaging in a cross-sectional sample spanning from childhood to adulthood which was reassessed in ~1.5 years (N = 293). We revealed the developmental trajectories of 20 neurochemicals in two key developmental brain regions (the intraparietal sulcus, IPS, and the middle frontal gyrus, MFG). We found that certain neurochemicals exhibited similar developmental trajectories across the two regions, while other trajectories were region-specific. Crucially, we mapped the connectivity of the brain regions IPS and MFG to the rest of the brain across development as a function of regional glutamate and GABA concentration. We demonstrated that glutamate concentration within the IPS is modulated by age in explaining IPS connectivity with frontal, temporal and parietal regions. In mature participants, higher glutamate within the IPS was related to more negative connectivity while the opposite pattern was found for younger participants. Our findings offer specific developmental insights on the interplay between the brain's resting activity and the glutamatergic system both of which are crucial for regulating normal functioning and are dysregulated in several clinical conditions.
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Rehbein E, Hornung J, Sundström Poromaa I, Derntl B. Shaping of the Female Human Brain by Sex Hormones: A Review. Neuroendocrinology 2021; 111:183-206. [PMID: 32155633 DOI: 10.1159/000507083] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Accepted: 03/09/2020] [Indexed: 12/26/2022]
Abstract
Traditionally sex hormones have been associated with reproductive and developmental processes only. Since the 1950s we know that hormones can have organizational effects on the developing brain and initiate hormonal transition periods such as puberty. However, recent evidence shows that sex hormones additionally structure the brain during important hormonal transition periods across a woman's life including short-term fluctuations during the menstrual cycle. However, a comprehensive review focusing on structural changes during all hormonal transition phases of women is still missing. Therefore, in this review structural changes across hormonal transition periods (i.e., puberty, menstrual cycle, oral contraceptive intake, pregnancy and menopause) were investigated in a structured way and correlations with sex hormones evaluated. Results show an overall reduction in grey matter and region-specific decreases in prefrontal, parietal and middle temporal areas during puberty. Across the menstrual cycle grey matter plasticity in the hippocampus, the amygdala as well as temporal and parietal regions were most consistently reported. Studies reporting on pre- and post-pregnancy measurements revealed volume reductions in midline structures as well as prefrontal and temporal cortices. During perimenopause, the decline in sex hormones was paralleled with a reduction in hippocampal and parietal cortex volume. Brain volume changes were significantly correlated with estradiol, testosterone and progesterone levels in some studies, but directionality remains inconclusive between studies. These results indicate that sex hormones play an important role in shaping women's brain structure during different transition periods and are not restricted to specific developmental periods.
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Haran JP, McCormick BA. Aging, Frailty, and the Microbiome-How Dysbiosis Influences Human Aging and Disease. Gastroenterology 2021; 160:507-523. [PMID: 33307030 PMCID: PMC7856216 DOI: 10.1053/j.gastro.2020.09.060] [Citation(s) in RCA: 71] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Revised: 09/08/2020] [Accepted: 09/16/2020] [Indexed: 02/07/2023]
Abstract
The human gut microbiome is a collection of bacteria, protozoa, fungi, and viruses that coexist in our bodies and are essential in protective, metabolic, and physiologic functions of human health. Gut dysbiosis has traditionally been linked to increased risk of infection, but imbalances within the intestinal microbial community structure that correlate with untoward inflammatory responses are increasingly recognized as being involved in disease processes that affect many organ systems in the body. Furthermore, it is becoming more apparent that the connection between gut dysbiosis and age-related diseases may lie in how the gut microbiome communicates with both the intestinal mucosa and the systemic immune system, given that these networks have a common interconnection to frailty. We therefore discuss recent advances in our understanding of the important role the microbiome plays in aging and how this knowledge opens the door for potential novel therapeutics aimed at shaping a less dysbiotic microbiome to prevent or treat age-related diseases.
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Patel Y, Parker N, Shin J, Howard D, French L, Thomopoulos SI, Pozzi E, Abe Y, Abé C, Anticevic A, Alda M, Aleman A, Alloza C, Alonso-Lana S, Ameis SH, Anagnostou E, McIntosh AA, Arango C, Arnold PD, Asherson P, Assogna F, Auzias G, Ayesa-Arriola R, Bakker G, Banaj N, Banaschewski T, Bandeira CE, Baranov A, Bargalló N, Bau CHD, Baumeister S, Baune BT, Bellgrove MA, Benedetti F, Bertolino A, Boedhoe PSW, Boks M, Bollettini I, Del Mar Bonnin C, Borgers T, Borgwardt S, Brandeis D, Brennan BP, Bruggemann JM, Bülow R, Busatto GF, Calderoni S, Calhoun VD, Calvo R, Canales-Rodríguez EJ, Cannon DM, Carr VJ, Cascella N, Cercignani M, Chaim-Avancini TM, Christakou A, Coghill D, Conzelmann A, Crespo-Facorro B, Cubillo AI, Cullen KR, Cupertino RB, Daly E, Dannlowski U, Davey CG, Denys D, Deruelle C, Di Giorgio A, Dickie EW, Dima D, Dohm K, Ehrlich S, Ely BA, Erwin-Grabner T, Ethofer T, Fair DA, Fallgatter AJ, Faraone SV, Fatjó-Vilas M, Fedor JM, Fitzgerald KD, Ford JM, Frodl T, Fu CHY, Fullerton JM, Gabel MC, Glahn DC, Roberts G, Gogberashvili T, Goikolea JM, Gotlib IH, Goya-Maldonado R, Grabe HJ, Green MJ, Grevet EH, Groenewold NA, Grotegerd D, Gruber O, Gruner P, Guerrero-Pedraza A, Gur RE, Gur RC, Haar S, Haarman BCM, Haavik J, Hahn T, Hajek T, Harrison BJ, Harrison NA, Hartman CA, Whalley HC, Heslenfeld DJ, Hibar DP, Hilland E, Hirano Y, Ho TC, Hoekstra PJ, Hoekstra L, Hohmann S, Hong LE, Höschl C, Høvik MF, Howells FM, Nenadic I, Jalbrzikowski M, James AC, Janssen J, Jaspers-Fayer F, Xu J, Jonassen R, Karkashadze G, King JA, Kircher T, Kirschner M, Koch K, Kochunov P, Kohls G, Konrad K, Krämer B, Krug A, Kuntsi J, Kwon JS, Landén M, Landrø NI, Lazaro L, Lebedeva IS, Leehr EJ, Lera-Miguel S, Lesch KP, Lochner C, Louza MR, Luna B, Lundervold AJ, MacMaster FP, Maglanoc LA, Malpas CB, Portella MJ, Marsh R, Martyn FM, Mataix-Cols D, Mathalon DH, McCarthy H, McDonald C, McPhilemy G, Meinert S, Menchón JM, Minuzzi L, Mitchell PB, Moreno C, Morgado P, Muratori F, Murphy CM, Murphy D, Mwangi B, Nabulsi L, Nakagawa A, Nakamae T, Namazova L, Narayanaswamy J, Jahanshad N, Nguyen DD, Nicolau R, O'Gorman Tuura RL, O'Hearn K, Oosterlaan J, Opel N, Ophoff RA, Oranje B, García de la Foz VO, Overs BJ, Paloyelis Y, Pantelis C, Parellada M, Pauli P, Picó-Pérez M, Picon FA, Piras F, Piras F, Plessen KJ, Pomarol-Clotet E, Preda A, Puig O, Quidé Y, Radua J, Ramos-Quiroga JA, Rasser PE, Rauer L, Reddy J, Redlich R, Reif A, Reneman L, Repple J, Retico A, Richarte V, Richter A, Rosa PGP, Rubia KK, Hashimoto R, Sacchet MD, Salvador R, Santonja J, Sarink K, Sarró S, Satterthwaite TD, Sawa A, Schall U, Schofield PR, Schrantee A, Seitz J, Serpa MH, Setién-Suero E, Shaw P, Shook D, Silk TJ, Sim K, Simon S, Simpson HB, Singh A, Skoch A, Skokauskas N, Soares JC, Soreni N, Soriano-Mas C, Spalletta G, Spaniel F, Lawrie SM, Stern ER, Stewart SE, Takayanagi Y, Temmingh HS, Tolin DF, Tomecek D, Tordesillas-Gutiérrez D, Tosetti M, Uhlmann A, van Amelsvoort T, van der Wee NJA, van der Werff SJA, van Haren NEM, van Wingen GA, Vance A, Vázquez-Bourgon J, Vecchio D, Venkatasubramanian G, Vieta E, Vilarroya O, Vives-Gilabert Y, Voineskos AN, Völzke H, von Polier GG, Walton E, Weickert TW, Weickert CS, Weideman AS, Wittfeld K, Wolf DH, Wu MJ, Yang TT, Yang K, Yoncheva Y, Yun JY, Cheng Y, Zanetti MV, Ziegler GC, Franke B, Hoogman M, Buitelaar JK, van Rooij D, Andreassen OA, Ching CRK, Veltman DJ, Schmaal L, Stein DJ, van den Heuvel OA, Turner JA, van Erp TGM, Pausova Z, Thompson PM, Paus T. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders. JAMA Psychiatry 2021; 78:47-63. [PMID: 32857118 PMCID: PMC7450410 DOI: 10.1001/jamapsychiatry.2020.2694] [Citation(s) in RCA: 106] [Impact Index Per Article: 35.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 06/12/2020] [Indexed: 01/01/2023]
Abstract
IMPORTANCE Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood. OBJECTIVE To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia. DESIGN, SETTING, AND PARTICIPANTS Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244. MAIN OUTCOMES AND MEASURES Interregional profiles of group difference in cortical thickness between cases and controls. RESULTS A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders. CONCLUSIONS AND RELEVANCE In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.
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Khundrakpam B, Choudhury S, Vainik U, Al‐Sharif N, Bhutani N, Jeon S, Gold I, Evans A. Distinct influence of parental occupation on cortical thickness and surface area in children and adolescents: Relation to self-esteem. Hum Brain Mapp 2020; 41:5097-5113. [PMID: 33058416 PMCID: PMC7670644 DOI: 10.1002/hbm.25169] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Revised: 07/23/2020] [Accepted: 07/31/2020] [Indexed: 12/13/2022] Open
Abstract
Studies of socioeconomic disparities have largely focused on correlating brain measures with either composite measure of socioeconomic status (SES), or its components-family income or parental education, giving little attention to the component of parental occupation. Emerging evidence suggests that parental occupation may be an important and neglected indicator of childhood and adolescent SES compared to absolute measures of material resources or academic attainment because, while related, it may more precisely capture position in social hierarchy and related health outcomes. On the other hand, although cortical thickness and surface area are brain measures with distinct genetic and developmental origins, large-scale neuroimaging studies investigating regional differences in interaction of the composite measure of SES or its components with cortical thickness and surface area are missing. We set out to fill this gap, focusing specifically on the role of parental occupation on cortical thickness and surface area by analyzing magnetic resonance imaging scans from 704 healthy individuals (age = 3-21 years). We observed spatially distributed patterns of (parental occupation × age2 ) interaction with cortical thickness (localized at the left caudal middle frontal, the left inferior parietal and the right superior parietal) and surface area (localized at the left orbitofrontal cortex), indicating independent sources of variability. Further, with decreased cortical thickness, children from families with lower parental occupation exhibited lower self-esteem. Our findings demonstrate distinct influence of parental occupation on cortical thickness and surface area in children and adolescents, potentially reflecting different neurobiological mechanisms by which parental occupation may impact brain development.
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Reh R, Williams LJ, Todd RM, Ward LM. Warped rhythms: Epileptic activity during critical periods disrupts the development of neural networks for human communication. Behav Brain Res 2020; 399:113016. [PMID: 33212087 DOI: 10.1016/j.bbr.2020.113016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 11/06/2020] [Accepted: 11/09/2020] [Indexed: 12/27/2022]
Abstract
It is well established that temporal lobe epilepsy-the most common and well-studied form of epilepsy-can impair communication by disrupting social-emotional and language functions. In pediatric epilepsy, where seizures co-occur with the development of critical brain networks, age of onset matters: The earlier in life seizures begin, the worse the disruption in network establishment, resulting in academic hardship and social isolation. Yet, little is known about the processes by which epileptic activity disrupts developing human brain networks. Here we take a synthetic perspective-reviewing a range of research spanning studies on molecular and oscillatory processes to those on the development of large-scale functional networks-in support of a novel model of how such networks can be disrupted by epilepsy. We seek to bridge the gap between research on molecular processes, on the development of human brain circuitry, and on clinical outcomes to propose a model of how epileptic activity disrupts brain development.
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Munsell BC, Gleichgerrcht E, Hofesmann E, Delgaizo J, McDonald CR, Marebwa B, Styner MA, Fridriksson J, Rorden C, Focke NK, Gilmore JH, Bonilha L. Personalized connectome fingerprints: Their importance in cognition from childhood to adult years. Neuroimage 2020; 221:117122. [PMID: 32634596 PMCID: PMC11316952 DOI: 10.1016/j.neuroimage.2020.117122] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 06/27/2020] [Indexed: 12/31/2022] Open
Abstract
Structural neural network architecture patterns in the human brain could be related to individual differences in phenotype, behavior, genetic determinants, and clinical outcomes from neuropsychiatric disorders. Recent studies have indicated that a personalized neural (brain) fingerprint can be identified from structural brain connectomes. However, the accuracy, reproducibility and translational potential of personalized fingerprints in terms of cognition is not yet fully determined. In this study, we introduce a dynamic connectome modeling approach to identify a critical set of white matter subnetworks that can be used as a personalized fingerprint. Several individual variable assessments were performed that demonstrate the accuracy and practicality of personalized fingerprint, specifically predicting the identity and IQ of middle age adults, and the developmental quotient in toddlers. Our findings suggest the fingerprint found by our dynamic modeling approach is sufficient for differentiation between individuals, and is also capable of predicting general intellectual ability across human development.
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Boedhoe PSW, van Rooij D, Hoogman M, Twisk JWR, Schmaal L, Abe Y, Alonso P, Ameis SH, Anikin A, Anticevic A, Arango C, Arnold PD, Asherson P, Assogna F, Auzias G, Banaschewski T, Baranov A, Batistuzzo MC, Baumeister S, Baur-Streubel R, Behrmann M, Bellgrove MA, Benedetti F, Beucke JC, Biederman J, Bollettini I, Bose A, Bralten J, Bramati IE, Brandeis D, Brem S, Brennan BP, Busatto GF, Calderoni S, Calvo A, Calvo R, Castellanos FX, Cercignani M, Chaim-Avancini TM, Chantiluke KC, Cheng Y, Cho KIK, Christakou A, Coghill D, Conzelmann A, Cubillo AI, Dale AM, Dallaspezia S, Daly E, Denys D, Deruelle C, Di Martino A, Dinstein I, Doyle AE, Durston S, Earl EA, Ecker C, Ehrlich S, Ely BA, Epstein JN, Ethofer T, Fair DA, Fallgatter AJ, Faraone SV, Fedor J, Feng X, Feusner JD, Fitzgerald J, Fitzgerald KD, Fouche JP, Freitag CM, Fridgeirsson EA, Frodl T, Gabel MC, Gallagher L, Gogberashvili T, Gori I, Gruner P, Gürsel DA, Haar S, Haavik J, Hall GB, Harrison NA, Hartman CA, Heslenfeld DJ, Hirano Y, Hoekstra PJ, Hoexter MQ, Hohmann S, Høvik MF, Hu H, Huyser C, Jahanshad N, Jalbrzikowski M, James A, Janssen J, Jaspers-Fayer F, Jernigan TL, Kapilushniy D, Kardatzki B, Karkashadze G, Kathmann N, Kaufmann C, Kelly C, Khadka S, King JA, Koch K, Kohls G, Konrad K, Kuno M, Kuntsi J, Kvale G, Kwon JS, Lázaro L, Lera-Miguel S, Lesch KP, Hoekstra L, Liu Y, Lochner C, Louza MR, Luna B, Lundervold AJ, Malpas CB, Marques P, Marsh R, Martínez-Zalacaín I, Mataix-Cols D, Mattos P, McCarthy H, McGrath J, Mehta MA, Menchón JM, Mennes M, Martinho MM, Moreira PS, Morer A, Morgado P, Muratori F, Murphy CM, Murphy DGM, Nakagawa A, Nakamae T, Nakao T, Namazova-Baranova L, Narayanaswamy JC, Nicolau R, Nigg JT, Novotny SE, Nurmi EL, Weiss EO, O'Gorman Tuura RL, O'Hearn K, O'Neill J, Oosterlaan J, Oranje B, Paloyelis Y, Parellada M, Pauli P, Perriello C, Piacentini J, Piras F, Piras F, Plessen KJ, Puig O, Ramos-Quiroga JA, Reddy YCJ, Reif A, Reneman L, Retico A, Rosa PGP, Rubia K, Rus OG, Sakai Y, Schrantee A, Schwarz L, Schweren LJS, Seitz J, Shaw P, Shook D, Silk TJ, Simpson HB, Skokauskas N, Soliva Vila JC, Solovieva A, Soreni N, Soriano-Mas C, Spalletta G, Stern ER, Stevens MC, Stewart SE, Sudre G, Szeszko PR, Tamm L, Taylor MJ, Tolin DF, Tosetti M, Tovar-Moll F, Tsuchiyagaito A, van Erp TGM, van Wingen GA, Vance A, Venkatasubramanian G, Vilarroya O, Vives-Gilabert Y, von Polier GG, Walitza S, Wallace GL, Wang Z, Wolfers T, Yoncheva YN, Yun JY, Zanetti MV, Zhou F, Ziegler GC, Zierhut KC, Zwiers MP, Thompson PM, Stein DJ, Buitelaar J, Franke B, van den Heuvel OA. Subcortical Brain Volume, Regional Cortical Thickness, and Cortical Surface Area Across Disorders: Findings From the ENIGMA ADHD, ASD, and OCD Working Groups. Am J Psychiatry 2020; 177:834-843. [PMID: 32539527 PMCID: PMC8296070 DOI: 10.1176/appi.ajp.2020.19030331] [Citation(s) in RCA: 105] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
OBJECTIVE Attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data. METHODS Structural T1-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures). RESULTS No shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood. CONCLUSIONS The study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.
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Wetzel E, Grijalva E, Robins RW, Roberts BW. You're still so vain: Changes in narcissism from young adulthood to middle age. J Pers Soc Psychol 2020; 119:479-496. [PMID: 31670564 PMCID: PMC7190428 DOI: 10.1037/pspp0000266] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
To date, there have been no long-term longitudinal studies of continuity and change in narcissism. This study investigated rank-order consistency and mean-level changes in overall narcissism and 3 of its facets (leadership, vanity, and entitlement) over a 23-year period spanning young adulthood (Mage = 18, N = 486) to midlife (Mage = 41, N = 237). We also investigated whether life experiences predicted changes in narcissism from young adulthood to midlife, and whether young adult narcissism predicted life experiences assessed in midlife. Narcissism and its facets showed strong rank-order consistency from age 18 to 41, with latent correlations ranging from .61 to .85. We found mean-level decreases in overall narcissism (d = -0.79) and all 3 facets, namely leadership (d = -0.67), vanity (d = -0.46), and entitlement (d = -0.82). Participants who were in supervisory positions showed smaller decreases in leadership, and participants who experienced more unstable relationships and who were physically healthier showed smaller decreases in vanity from young adulthood to middle age. Analyses of the long-term correlates of narcissism showed that young adults with higher narcissism and leadership levels were more likely to be in supervisory positions in middle age. Young adults with higher vanity levels had fewer children and were more likely to divorce by middle age. Together, the findings suggest that people tend to become less narcissistic from young adulthood to middle age, and the magnitude of this decline is related to the particular career and family pathways a person pursues during this stage of life. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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