1
|
Ramirez JSB, Graham AM, Thompson JR, Zhu JY, Sturgeon D, Bagley JL, Thomas E, Papadakis S, Bah M, Perrone A, Earl E, Miranda-Dominguez O, Feczko E, Fombonne EJ, Amaral DG, Nigg JT, Sullivan EL, Fair DA. Maternal Interleukin-6 Is Associated With Macaque Offspring Amygdala Development and Behavior. Cereb Cortex 2021; 30:1573-1585. [PMID: 31665252 DOI: 10.1093/cercor/bhz188] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Revised: 07/11/2019] [Accepted: 07/16/2019] [Indexed: 12/20/2022] Open
Abstract
Human and animal cross-sectional studies have shown that maternal levels of the inflammatory cytokine interleukin-6 (IL-6) may compromise brain phenotypes assessed at single time points. However, how maternal IL-6 associates with the trajectory of brain development remains unclear. We investigated whether maternal IL-6 levels during pregnancy relate to offspring amygdala volume development and anxiety-like behavior in Japanese macaques. Magnetic resonance imaging (MRI) was administered to 39 Japanese macaque offspring (Female: 18), providing at least one or more time points at 4, 11, 21, and 36 months of age with a behavioral assessment at 11 months of age. Increased maternal third trimester plasma IL-6 levels were associated with offspring's smaller left amygdala volume at 4 months, but with more rapid amygdala growth from 4 to 36 months. Maternal IL-6 predicted offspring anxiety-like behavior at 11 months, which was mediated by reduced amygdala volumes in the model's intercept (i.e., 4 months). The results increase our understanding of the role of maternal inflammation in the development of neurobehavioral disorders by detailing the associations of a commonly examined inflammatory indicator, IL-6, on amygdala volume growth over time, and anxiety-like behavior.
Collapse
Affiliation(s)
- Julian S B Ramirez
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland OR, USA
| | - Alice M Graham
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland OR, USA
| | - Jacqueline R Thompson
- Divisions of Neuroscience and Cardiometabolic Health, Oregon National Primate Research Center, Beaverton OR, USA
| | - Jennifer Y Zhu
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland OR, USA
| | - Darrick Sturgeon
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland OR, USA
| | - Jennifer L Bagley
- Divisions of Neuroscience and Cardiometabolic Health, Oregon National Primate Research Center, Beaverton OR, USA
| | - Elina Thomas
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland OR, USA
| | - Samantha Papadakis
- Neuroscience Graduate Program, Oregon Health & Science University, Portland OR, USA
| | - Muhammed Bah
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland OR, USA
| | - Anders Perrone
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland OR, USA
| | - Eric Earl
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland OR, USA
| | | | - Eric Feczko
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland OR, USA.,Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland OR, USA
| | - Eric J Fombonne
- Department of Psychiatry, Oregon Health & Science University, Portland OR, USA.,Department of Pediatrics, Oregon Health & Science University, Portland OR, USA.,Institute for Development & Disability, Oregon Health & Science University, Portland OR, USA
| | - David G Amaral
- MIND Institute, University of California Davis, Davis CA, USA.,Department of Psychiatry and Behavioral Sciences, and Center for Neuroscience, University of California Davis, Davis CA, USA.,California National Primate Research Center, University of California Davis, Davis CA, USA
| | - Joel T Nigg
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland OR, USA.,Department of Psychiatry, Oregon Health & Science University, Portland OR, USA
| | - Elinor L Sullivan
- Divisions of Neuroscience and Cardiometabolic Health, Oregon National Primate Research Center, Beaverton OR, USA.,Department of Psychiatry, Oregon Health & Science University, Portland OR, USA.,Department of Human Physiology, University of Oregon, Eugene OR, USA
| | - Damien A Fair
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland OR, USA.,Neuroscience Graduate Program, Oregon Health & Science University, Portland OR, USA.,Department of Psychiatry, Oregon Health & Science University, Portland OR, USA.,Advance Imaging Research Center, Oregon Health & Science University, Portland OR, USA
| |
Collapse
|
2
|
Mary-Krause M, Herranz Bustamante JJ, Bolze C, Galéra C, Fombonne EJ, Melchior M. Cohort profile: The TEMPO cohort study. Int J Epidemiol 2021; 50:1067-1068k. [PMID: 34015132 DOI: 10.1093/ije/dyab026] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 02/05/2021] [Indexed: 11/14/2022] Open
Affiliation(s)
- Murielle Mary-Krause
- Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP), Equipe de Recherche en Epidémiologie Sociale (ERES), Paris, France
| | - Joel José Herranz Bustamante
- Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP), Equipe de Recherche en Epidémiologie Sociale (ERES), Paris, France
| | - Camille Bolze
- Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP), Equipe de Recherche en Epidémiologie Sociale (ERES), Paris, France
| | - Cédric Galéra
- University Hospital Unit for children and adolescents (UUHEA), CHU Bordeaux, Bordeaux, France.,Child Psychiatry Department, Charles Perrens Hospital, Bordeaux, France.,UMR1219, INSERM, Université de Bordeaux, Bordeaux, France
| | - Eric J Fombonne
- Departments of Psychiatry & Pediatrics, Oregon Health & Science University (OHSU), Portland, OR, USA
| | - Maria Melchior
- Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP), Equipe de Recherche en Epidémiologie Sociale (ERES), Paris, France
| |
Collapse
|
3
|
Feczko E, Balba NM, Miranda-Dominguez O, Cordova M, Karalunas SL, Irwin L, Demeter DV, Hill AP, Langhorst BH, Grieser Painter J, Van Santen J, Fombonne EJ, Nigg JT, Fair DA. Subtyping cognitive profiles in Autism Spectrum Disorder using a Functional Random Forest algorithm. Neuroimage 2017; 172:674-688. [PMID: 29274502 DOI: 10.1016/j.neuroimage.2017.12.044] [Citation(s) in RCA: 75] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Revised: 12/11/2017] [Accepted: 12/14/2017] [Indexed: 12/21/2022] Open
Abstract
DSM-5 Autism Spectrum Disorder (ASD) comprises a set of neurodevelopmental disorders characterized by deficits in social communication and interaction and repetitive behaviors or restricted interests, and may both affect and be affected by multiple cognitive mechanisms. This study attempts to identify and characterize cognitive subtypes within the ASD population using our Functional Random Forest (FRF) machine learning classification model. This model trained a traditional random forest model on measures from seven tasks that reflect multiple levels of information processing. 47 ASD diagnosed and 58 typically developing (TD) children between the ages of 9 and 13 participated in this study. Our RF model was 72.7% accurate, with 80.7% specificity and 63.1% sensitivity. Using the random forest model, the FRF then measures the proximity of each subject to every other subject, generating a distance matrix between participants. This matrix is then used in a community detection algorithm to identify subgroups within the ASD and TD groups, and revealed 3 ASD and 4 TD putative subgroups with unique behavioral profiles. We then examined differences in functional brain systems between diagnostic groups and putative subgroups using resting-state functional connectivity magnetic resonance imaging (rsfcMRI). Chi-square tests revealed a significantly greater number of between group differences (p < .05) within the cingulo-opercular, visual, and default systems as well as differences in inter-system connections in the somato-motor, dorsal attention, and subcortical systems. Many of these differences were primarily driven by specific subgroups suggesting that our method could potentially parse the variation in brain mechanisms affected by ASD.
Collapse
Affiliation(s)
- E Feczko
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA; Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland OR, 97239, USA.
| | - N M Balba
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA
| | - O Miranda-Dominguez
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA
| | - M Cordova
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA
| | - S L Karalunas
- Department of Psychiatry, Oregon Health & Science University, Portland, OR 97239, USA
| | - L Irwin
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA
| | - D V Demeter
- The University of Texas at Austin, Department of Psychology, Austin, TX 78713, USA
| | - A P Hill
- Department of Pediatrics, Oregon Health & Science University, Portland, OR 97239, USA; Center for Spoken Language Understanding, Institute on Development & Disability, Oregon Health & Science University, Portland, OR 97239, USA
| | - B H Langhorst
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA
| | - J Grieser Painter
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA
| | - J Van Santen
- Department of Pediatrics, Oregon Health & Science University, Portland, OR 97239, USA; Center for Spoken Language Understanding, Institute on Development & Disability, Oregon Health & Science University, Portland, OR 97239, USA
| | - E J Fombonne
- Department of Pediatrics, Oregon Health & Science University, Portland, OR 97239, USA; Department of Psychiatry, Oregon Health & Science University, Portland, OR 97239, USA
| | - J T Nigg
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA; Department of Psychiatry, Oregon Health & Science University, Portland, OR 97239, USA; Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - D A Fair
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, USA; Department of Psychiatry, Oregon Health & Science University, Portland, OR 97239, USA; Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR 97239, USA
| |
Collapse
|