1
|
Day TKM, Hermosillo R, Conan G, Randolph A, Perrone A, Earl E, Byington N, Hendrickson TJ, Elison JT, Fair DA, Feczko E. Multi-level fMRI analysis applied to hemispheric specialization in the language network, functional areas, and their behavioral correlations in the ABCD sample. Dev Cogn Neurosci 2024; 66:101355. [PMID: 38354531 PMCID: PMC10875197 DOI: 10.1016/j.dcn.2024.101355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 01/06/2024] [Accepted: 02/03/2024] [Indexed: 02/16/2024] Open
Abstract
Prior research suggests that the organization of the language network in the brain is left-dominant and becomes more lateralized with age and increasing language skill. The age at which specific components of the language network become adult-like varies depending on the abilities they subserve. So far, a large, developmental study has not included a language task paradigm, so we introduce a method to study resting-state laterality in the Adolescent Brain Cognitive Development (ABCD) study. Our approach mixes source timeseries between left and right homotopes of the (1) inferior frontal and (2) middle temporal gyri and (3) a region we term "Wernicke's area" near the supramarginal gyrus. Our large subset sample size of ABCD (n = 6153) allows improved reliability and validity compared to previous, smaller studies of brain-behavior associations. We show that behavioral metrics from the NIH Youth Toolbox and other resources are differentially related to tasks with a larger linguistic component over ones with less (e.g., executive function-dominant tasks). These baseline characteristics of hemispheric specialization in youth are critical for future work determining the correspondence of lateralization with language onset in earlier stages of development.
Collapse
Affiliation(s)
- Trevor K M Day
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA; Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA.
| | - Robert Hermosillo
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Gregory Conan
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Anita Randolph
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Anders Perrone
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Eric Earl
- Data Science & Sharing Team, National Institute of Mental Health, Bethesda, MD, USA
| | - Nora Byington
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Timothy J Hendrickson
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Informatics Institute, University of Minnesota, Minneapolis, MN, USA
| | - Jed T Elison
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA; Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Damien A Fair
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA; Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Eric Feczko
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA; Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| |
Collapse
|
2
|
Hermosillo RJM, Moore LA, Feczko E, Miranda-Domínguez Ó, Pines A, Dworetsky A, Conan G, Mooney MA, Randolph A, Graham A, Adeyemo B, Earl E, Perrone A, Carrasco CM, Uriarte-Lopez J, Snider K, Doyle O, Cordova M, Koirala S, Grimsrud GJ, Byington N, Nelson SM, Gratton C, Petersen S, Feldstein Ewing SW, Nagel BJ, Dosenbach NUF, Satterthwaite TD, Fair DA. A precision functional atlas of personalized network topography and probabilities. Nat Neurosci 2024:10.1038/s41593-024-01596-5. [PMID: 38532024 DOI: 10.1038/s41593-024-01596-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 02/08/2024] [Indexed: 03/28/2024]
Abstract
Although the general location of functional neural networks is similar across individuals, there is vast person-to-person topographic variability. To capture this, we implemented precision brain mapping functional magnetic resonance imaging methods to establish an open-source, method-flexible set of precision functional network atlases-the Masonic Institute for the Developing Brain (MIDB) Precision Brain Atlas. This atlas is an evolving resource comprising 53,273 individual-specific network maps, from more than 9,900 individuals, across ages and cohorts, including the Adolescent Brain Cognitive Development study, the Developmental Human Connectome Project and others. We also generated probabilistic network maps across multiple ages and integration zones (using a new overlapping mapping technique, Overlapping MultiNetwork Imaging). Using regions of high network invariance improved the reproducibility of executive function statistical maps in brain-wide associations compared to group average-based parcellations. Finally, we provide a potential use case for probabilistic maps for targeted neuromodulation. The atlas is expandable to alternative datasets with an online interface encouraging the scientific community to explore and contribute to understanding the human brain function more precisely.
Collapse
Affiliation(s)
- Robert J M Hermosillo
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA.
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.
| | - Lucille A Moore
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Eric Feczko
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Óscar Miranda-Domínguez
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Adam Pines
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Ally Dworetsky
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Psychology, Northwestern University, Evanston, IL, USA
- Department of Psychology, Florida State University, Tallahassee, FL, USA
| | - Gregory Conan
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Michael A Mooney
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Center for Mental Health Innovation, Oregon Health and Science University, Portland, OR, USA
| | - Anita Randolph
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Alice Graham
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Eric Earl
- Data Science and Sharing Team, National Institute of Mental Health, Bethesda, MD, USA
| | - Anders Perrone
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Cristian Morales Carrasco
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | | | - Kathy Snider
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Olivia Doyle
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Michaela Cordova
- Joint Doctoral Program in Clinical Psychology, San Diego State University, San Diego, CA, USA
- Joint Doctoral Program in Clinical Psychology, University of California San Diego, San Diego, CA, USA
| | - Sanju Koirala
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
| | - Gracie J Grimsrud
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Nora Byington
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Steven M Nelson
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Caterina Gratton
- Department of Psychology, Northwestern University, Evanston, IL, USA
- Department of Psychology, Florida State University, Tallahassee, FL, USA
- Department of Psychological and Brain Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Steven Petersen
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
- Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Bonnie J Nagel
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
| |
Collapse
|
3
|
Mooney MA, Hermosillo RJM, Feczko E, Miranda-Dominguez O, Moore LA, Perrone A, Byington N, Grimsrud G, Rueter A, Nousen E, Antovich D, Feldstein Ewing SW, Nagel BJ, Nigg JT, Fair DA. Cumulative Effects of Resting-State Connectivity Across All Brain Networks Significantly Correlate with Attention-Deficit Hyperactivity Disorder Symptoms. J Neurosci 2024; 44:e1202232023. [PMID: 38286629 PMCID: PMC10919250 DOI: 10.1523/jneurosci.1202-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 11/30/2023] [Accepted: 12/18/2023] [Indexed: 01/31/2024] Open
Abstract
Identification of replicable neuroimaging correlates of attention-deficit hyperactivity disorder (ADHD) has been hindered by small sample sizes, small effects, and heterogeneity of methods. Given evidence that ADHD is associated with alterations in widely distributed brain networks and the small effects of individual brain features, a whole-brain perspective focusing on cumulative effects is warranted. The use of large, multisite samples is crucial for improving reproducibility and clinical utility of brain-wide MRI association studies. To address this, a polyneuro risk score (PNRS) representing cumulative, brain-wide, ADHD-associated resting-state functional connectivity was constructed and validated using data from the Adolescent Brain Cognitive Development (ABCD, N = 5,543, 51.5% female) study, and was further tested in the independent Oregon-ADHD-1000 case-control cohort (N = 553, 37.4% female). The ADHD PNRS was significantly associated with ADHD symptoms in both cohorts after accounting for relevant covariates (p < 0.001). The most predictive PNRS involved all brain networks, though the strongest effects were concentrated among the default mode and cingulo-opercular networks. In the longitudinal Oregon-ADHD-1000, non-ADHD youth had significantly lower PNRS (Cohen's d = -0.318, robust p = 5.5 × 10-4) than those with persistent ADHD (age 7-19). The PNRS, however, did not mediate polygenic risk for ADHD. Brain-wide connectivity was robustly associated with ADHD symptoms in two independent cohorts, providing further evidence of widespread dysconnectivity in ADHD. Evaluation in enriched samples demonstrates the promise of the PNRS approach for improving reproducibility in neuroimaging studies and unraveling the complex relationships between brain connectivity and behavioral disorders.
Collapse
Affiliation(s)
- Michael A Mooney
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon 97239
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon 97239
- Center for Mental Health Innovation, Oregon Health & Science University, Portland, Oregon 97239
| | - Robert J M Hermosillo
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55454
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Eric Feczko
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55454
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Oscar Miranda-Dominguez
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55454
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455
| | - Lucille A Moore
- Department of Neurology, Oregon Health & Science University, Portland, Oregon 97239
| | - Anders Perrone
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Nora Byington
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Gracie Grimsrud
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Amanda Rueter
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Elizabeth Nousen
- Center for Mental Health Innovation, Oregon Health & Science University, Portland, Oregon 97239
- Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon 97239
| | - Dylan Antovich
- Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon 97239
| | | | - Bonnie J Nagel
- Center for Mental Health Innovation, Oregon Health & Science University, Portland, Oregon 97239
- Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon 97239
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon 97239
| | - Joel T Nigg
- Center for Mental Health Innovation, Oregon Health & Science University, Portland, Oregon 97239
- Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon 97239
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon 97239
| | - Damien A Fair
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55454
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
- Institute of Child Development, College of Education and Human Development, University of Minnesota, Minneapolis, Minnesota 55455
| |
Collapse
|
4
|
Holt-Gosselin B, Keding TJ, Poulin R, Brieant A, Rueter A, Hendrickson TJ, Perrone A, Byington N, Houghton A, Miranda-Dominguez O, Feczko E, Fair DA, Joormann J, Gee DG. Neural Circuit Markers of Familial Risk for Depression Among Healthy Youths in the Adolescent Brain Cognitive Development Study. Biol Psychiatry Cogn Neurosci Neuroimaging 2024; 9:185-195. [PMID: 37182734 PMCID: PMC10640659 DOI: 10.1016/j.bpsc.2023.05.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 05/01/2023] [Accepted: 05/02/2023] [Indexed: 05/16/2023]
Abstract
BACKGROUND Family history of depression is a robust predictor of early-onset depression, which may confer risk through alterations in neural circuits that have been implicated in reward and emotional processing. These alterations may be evident in youths who are at familial risk for depression but who do not currently have depression. However, the identification of robust and replicable findings has been hindered by few studies and small sample sizes. In the current study, we sought to identify functional connectivity (FC) patterns associated with familial risk for depression. METHODS Participants included healthy (i.e., no lifetime psychiatric diagnoses) youths at high familial risk for depression (HR) (n = 754; at least one parent with a history of depression) and healthy youths at low familial risk for psychiatric problems (LR) (n = 1745; no parental history of psychopathology) who were 9 to 10 years of age and from the Adolescent Brain Cognitive Development (ABCD) Study sample. We conducted whole-brain seed-to-voxel analyses to examine group differences in resting-state FC with the amygdala, caudate, nucleus accumbens, and putamen. We hypothesized that HR youths would exhibit global amygdala hyperconnectivity and striatal hypoconnectivity patterns primarily driven by maternal risk. RESULTS HR youths exhibited weaker caudate-angular gyrus FC than LR youths (α = 0.04, Cohen's d = 0.17). HR youths with a history of maternal depression specifically exhibited weaker caudate-angular gyrus FC (α = 0.03, Cohen's d = 0.19) as well as weaker caudate-dorsolateral prefrontal cortex FC (α = 0.04, Cohen's d = 0.21) than LR youths. CONCLUSIONS Weaker striatal connectivity may be related to heightened familial risk for depression, primarily driven by maternal history. Identifying brain-based markers of depression risk in youths can inform approaches to improving early detection, diagnosis, and treatment.
Collapse
Affiliation(s)
- Bailey Holt-Gosselin
- Department of Psychology, Yale University, New Haven, Connecticut; Interdepartmental Neuroscience Graduate Program, Yale University School of Medicine, New Haven, Connecticut
| | - Taylor J Keding
- Department of Psychology, Yale University, New Haven, Connecticut; Child Study Center, Yale School of Medicine, New Haven, Connecticut
| | - Rhayna Poulin
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Alexis Brieant
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Amanda Rueter
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Timothy J Hendrickson
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Anders Perrone
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Nora Byington
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Audrey Houghton
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota
| | | | - Eric Feczko
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Damien A Fair
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Jutta Joormann
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Dylan G Gee
- Department of Psychology, Yale University, New Haven, Connecticut.
| |
Collapse
|
5
|
Keller AS, Pines AR, Shanmugan S, Sydnor VJ, Cui Z, Bertolero MA, Barzilay R, Alexander-Bloch AF, Byington N, Chen A, Conan GM, Davatzikos C, Feczko E, Hendrickson TJ, Houghton A, Larsen B, Li H, Miranda-Dominguez O, Roalf DR, Perrone A, Shetty A, Shinohara RT, Fan Y, Fair DA, Satterthwaite TD. Personalized functional brain network topography is associated with individual differences in youth cognition. Nat Commun 2023; 14:8411. [PMID: 38110396 PMCID: PMC10728159 DOI: 10.1038/s41467-023-44087-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 11/29/2023] [Indexed: 12/20/2023] Open
Abstract
Individual differences in cognition during childhood are associated with important social, physical, and mental health outcomes in adolescence and adulthood. Given that cortical surface arealization during development reflects the brain's functional prioritization, quantifying variation in the topography of functional brain networks across the developing cortex may provide insight regarding individual differences in cognition. We test this idea by defining personalized functional networks (PFNs) that account for interindividual heterogeneity in functional brain network topography in 9-10 year olds from the Adolescent Brain Cognitive Development℠ Study. Across matched discovery (n = 3525) and replication (n = 3447) samples, the total cortical representation of fronto-parietal PFNs positively correlates with general cognition. Cross-validated ridge regressions trained on PFN topography predict cognition in unseen data across domains, with prediction accuracy increasing along the cortex's sensorimotor-association organizational axis. These results establish that functional network topography heterogeneity is associated with individual differences in cognition before the critical transition into adolescence.
Collapse
Affiliation(s)
- Arielle S Keller
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Adam R Pines
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Sheila Shanmugan
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing, China
| | - Maxwell A Bertolero
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Ran Barzilay
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Aaron F Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Nora Byington
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Andrew Chen
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Gregory M Conan
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Christos Davatzikos
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Eric Feczko
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Timothy J Hendrickson
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, 55414, USA
- University of Minnesota Informatics Institute, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Audrey Houghton
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Hongming Li
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Oscar Miranda-Dominguez
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, 55414, USA
| | - David R Roalf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Anders Perrone
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Alisha Shetty
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Yong Fan
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
| |
Collapse
|
6
|
Byington N, Grimsrud G, Mooney MA, Cordova M, Doyle O, Hermosillo RJM, Earl E, Houghton A, Conan G, Hendrickson TJ, Ragothaman A, Carrasco CM, Rueter A, Perrone A, Moore LA, Graham A, Nigg JT, Thompson WK, Nelson SM, Feczko E, Fair DA, Miranda-Dominguez O. Polyneuro risk scores capture widely distributed connectivity patterns of cognition. Dev Cogn Neurosci 2023; 60:101231. [PMID: 36934605 PMCID: PMC10031023 DOI: 10.1016/j.dcn.2023.101231] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 03/06/2023] [Accepted: 03/13/2023] [Indexed: 03/17/2023] Open
Abstract
Resting-state functional connectivity (RSFC) is a powerful tool for characterizing brain changes, but it has yet to reliably predict higher-order cognition. This may be attributed to small effect sizes of such brain-behavior relationships, which can lead to underpowered, variable results when utilizing typical sample sizes (N∼25). Inspired by techniques in genomics, we implement the polyneuro risk score (PNRS) framework - the application of multivariate techniques to RSFC data and validation in an independent sample. Utilizing the Adolescent Brain Cognitive Development® cohort split into two datasets, we explore the framework's ability to reliably capture brain-behavior relationships across 3 cognitive scores - general ability, executive function, learning & memory. The weight and significance of each connection is assessed in the first dataset, and a PNRS is calculated for each participant in the second. Results support the PNRS framework as a suitable methodology to inspect the distribution of connections contributing towards behavior, with explained variance ranging from 1.0 % to 21.4 %. For the outcomes assessed, the framework reveals globally distributed, rather than localized, patterns of predictive connections. Larger samples are likely necessary to systematically identify the specific connections contributing towards complex outcomes. The PNRS framework could be applied translationally to identify neurologically distinct subtypes of neurodevelopmental disorders.
Collapse
Affiliation(s)
- Nora Byington
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States.
| | - Gracie Grimsrud
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | - Michael A Mooney
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, United States; Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, United States
| | - Michaela Cordova
- Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California San Diego, San Diego, CA 92120, United States
| | - Olivia Doyle
- Department of Psychiatry, Oregon Health & Science University, Portland, OR 97239, United States
| | - Robert J M Hermosillo
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | - Eric Earl
- Data Science and Sharing Team, National Institute of Mental Health, Bethesda, MD 20892, United States
| | - Audrey Houghton
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | - Gregory Conan
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | - Timothy J Hendrickson
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | | | - Cristian Morales Carrasco
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | - Amanda Rueter
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | - Anders Perrone
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | - Lucille A Moore
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | - Alice Graham
- Department of Psychiatry, Oregon Health & Science University, Portland, OR 97239, United States
| | - Joel T Nigg
- Department of Psychiatry, Oregon Health & Science University, Portland, OR 97239, United States; Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, United States
| | - Wesley K Thompson
- Center for Population Neuroscience and Genetics, Laureate Institute for Brain Research, Tulsa, OK 74136, United States
| | - Steven M Nelson
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States; Department of Pediatrics, University of Minnesota, Minneapolis, MN 55414, United States
| | - Eric Feczko
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States; Department of Pediatrics, University of Minnesota, Minneapolis, MN 55414, United States
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States; Department of Pediatrics, University of Minnesota, Minneapolis, MN 55414, United States; Institute of Child Development, University of Minnesota, Minneapolis, MN 55414, United States
| | - Oscar Miranda-Dominguez
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States; Department of Pediatrics, University of Minnesota, Minneapolis, MN 55414, United States
| |
Collapse
|
7
|
LeWinn KZ, Karr CJ, Hazlehurst M, Carroll K, Loftus C, Nguyen R, Barrett E, Swan SH, Szpiro AA, Paquette A, Moore P, Spalt E, Younglove L, Sullivan A, Colburn T, Byington N, Sims Taylor L, Moe S, Wang S, Cordeiro A, Mattias A, Powell J, Johnson T, Norona-Zhou A, Mason A, Bush NR, Sathyanarayana S. Cohort profile: the ECHO prenatal and early childhood pathways to health consortium (ECHO-PATHWAYS). BMJ Open 2022; 12:e064288. [PMID: 36270755 PMCID: PMC9594508 DOI: 10.1136/bmjopen-2022-064288] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
PURPOSE Exposures early in life, beginning in utero, have long-term impacts on mental and physical health. The ECHO prenatal and early childhood pathways to health consortium (ECHO-PATHWAYS) was established to examine the independent and combined impact of pregnancy and childhood chemical exposures and psychosocial stressors on child neurodevelopment and airway health, as well as the placental mechanisms underlying these associations. PARTICIPANTS The ECHO-PATHWAYS consortium harmonises extant data from 2684 mother-child dyads in three pregnancy cohort studies (CANDLE [Conditions Affecting Neurocognitive Development and Learning in Early Childhood], TIDES [The Infant Development and Environment Study] and GAPPS [Global Alliance to Prevent Prematurity and Stillbirth]) and collects prospective data under a unified protocol. Study participants are socioeconomically diverse and include a large proportion of Black families (38% Black and 51% White), often under-represented in research. Children are currently 5-15 years old. New data collection includes multimodal assessments of primary outcomes (airway health and neurodevelopment) and exposures (air pollution, phthalates and psychosocial stress) as well as rich covariate characterisation. ECHO-PATHWAYS is compiling extant and new biospecimens in a central biorepository and generating the largest placental transcriptomics data set to date (N=1083). FINDINGS TO DATE Early analyses demonstrate adverse associations of prenatal exposure to air pollution, phthalates and maternal stress with early childhood airway outcomes and neurodevelopment. Placental transcriptomics work suggests that phthalate exposure alters placental gene expression, pointing to mechanistic pathways for the developmental toxicity of phthalates. We also observe associations between prenatal maternal stress and placental corticotropin releasing hormone, a marker of hormonal activation during pregnancy relevant for child health. Other publications describe novel methods for examining exposure mixtures and the development of a national spatiotemporal model of ambient outdoor air pollution. FUTURE PLANS The first wave of data from the unified protocol (child age 8-9) is nearly complete. Future work will leverage these data to examine the combined impact of early life social and chemical exposures on middle childhood health outcomes and underlying placental mechanisms.
Collapse
Affiliation(s)
- Kaja Z LeWinn
- Department of Psychiatry and Behavioral Sciences, School of Medicine, University of California San Francisco, San Francisco, California, USA
| | - Catherine J Karr
- Department of Environmental and Occupational Health Sciences and Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington, USA
- Department of Pediatrics, School of Medicine, University of Washington, Seattle, Washington, USA
| | - Marnie Hazlehurst
- Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, Washington, USA
| | - Kecia Carroll
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Christine Loftus
- Department of Environmental Health and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, Washington, USA
| | - Ruby Nguyen
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota System, Minneapolis, Minnesota, USA
| | - Emily Barrett
- Department of Biostatistics and Epidemiology, Environmental and Occupational Health Sciences Institute (EOHSI), Rutgers School of Public Health, Rutgers University, Piscataway, New Jersey, USA
| | - Shanna H Swan
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Adam A Szpiro
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, Washington, USA
| | - Alison Paquette
- Department of Pediatrics, School of Medicine, University of Washington, Seattle, Washington, USA
- Center for Developmental Biology and Regenerative Medicine, Seattle Children's Research Institute, Seattle, Washington, USA
| | - Paul Moore
- Division of Allergy, Immunology, and Pulmonology and the Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Elizabeth Spalt
- Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, Washington, USA
| | - Lisa Younglove
- Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, Washington, USA
| | - Alexis Sullivan
- Center for Health and Community, School of Medicine, University of California San Francisco, San Francisco, California, USA
| | - Trina Colburn
- Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, Seattle, Washington, USA
| | - Nora Byington
- Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, Seattle, Washington, USA
| | - Lauren Sims Taylor
- Department of Preventive Medicine, College of Medicine, The University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Stacey Moe
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota System, Minneapolis, Minnesota, USA
| | - Sarah Wang
- Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, Seattle, Washington, USA
| | - Alana Cordeiro
- Center for Health and Community, School of Medicine, University of California San Francisco, San Francisco, California, USA
| | - Aria Mattias
- Department of Envrionmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Jennifer Powell
- Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, Seattle, Washington, USA
| | - Tye Johnson
- Department of Obstetrics and Gynecology, University of Rochester Medical Center, Rochester, New York, USA
| | - Amanda Norona-Zhou
- Center for Health and Community, School of Medicine, University of California San Francisco, San Francisco, California, USA
| | - Alex Mason
- Department of Preventive Medicine, College of Medicine, The University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Nicole R Bush
- Department of Psychiatry and Behavioral Sciences and the Department of Pediatrics, School of Medicine, University of California San Francisco, San Francisco, California, USA
| | - Sheela Sathyanarayana
- Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, Seattle, Washington, USA
- Department of Environmental and Occupational Health Sciences, School of Public Health; Department of Pediatrics, School of Medicine, University of Washington, Seattle, Washington, USA
| |
Collapse
|
8
|
Wilson K, Gebretsadik T, Adgent MA, Loftus C, Karr C, Moore PE, Sathyanarayana S, Byington N, Barrett E, Bush N, Nguyen R, Hartman TJ, LeWinn KZ, Calvert A, Mason WA, Carroll KN. The association between duration of breastfeeding and childhood asthma outcomes. Ann Allergy Asthma Immunol 2022; 129:205-211. [PMID: 35552008 PMCID: PMC9442497 DOI: 10.1016/j.anai.2022.04.034] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 04/27/2022] [Accepted: 04/29/2022] [Indexed: 11/19/2022]
Abstract
BACKGROUND Postnatal exposures, including breastfeeding, may influence asthma development. OBJECTIVE To investigate the association between breastfeeding duration and child asthma. METHODS We studied 2021 mother-child dyads in the ECHO PATHWAYS consortium of prospective pregnancy cohorts (GAPPS, CANDLE, TIDES). Women reported the duration of any and exclusive breastfeeding and child asthma outcomes during follow-up at child age 4 to 6 years. Outcomes included current wheeze (previous 12 months), ever asthma, current asthma (having ≥2 of current wheeze, ever asthma, medication use in past 12-24 months), and strict current asthma (ever asthma with either or both current wheeze and medication use in past 12-24 months). We used multivariable logistic regression to assess associations (odds ratios and 95% confidence intervals) between breastfeeding and asthma outcomes adjusting for potential confounders. We assessed effect modification by mode of delivery, infant sex, and maternal asthma. RESULTS Among women, 33%, 13%, 9%, and 45% reported 0 to less than 2, 2 to 4, 5 to 6, and more than 6 months of any breastfeeding, respectively. The duration of any breastfeeding had a protective linear trend with ever asthma but no other outcomes. There was a duration-dependent protective association of exclusive breastfeeding and child asthma outcomes (eg, current asthma adjusted odds ratio [95% confidence interval], 0.64 [0.41-1.02], 0.61 [0.38-0.98], and 0.52 (0.31-0.87) for 2to 4 months, 5 to 6 months, and more than 6 months, respectively, compared with <2 months). For exclusive breastfeeding, protective associations were stronger in dyads with children born by vaginal vs cesarean delivery although interactions did not reach statistical significance (Pinteractions 0.12-0.40). CONCLUSION Longer duration of exclusive breastfeeding had a protective association with child asthma.
Collapse
Affiliation(s)
- Keadrea Wilson
- Division of Neonatology, Department of Pediatrics, University of Tennessee Health Science Center, Memphis, Tennessee
| | - Tebeb Gebretsadik
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Margaret A Adgent
- Department of Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Christine Loftus
- Departments of Environmental and Occupational Health Sciences and Pediatrics, University of Washington, Seattle, Washington
| | - Catherine Karr
- Seattle Children's Research Institute, Seattle, Washington
| | - Paul E Moore
- Division of Allergy, Immunology and Pulmonary Medicine, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Sheela Sathyanarayana
- Departments of Environmental and Occupational Health Sciences and Pediatrics, University of Washington, Seattle, Washington
| | - Nora Byington
- Seattle Children's Research Institute, Seattle, Washington
| | - Emily Barrett
- Department of Biostatistics and Epidemiology, Rutgers University, Piscataway, New Jersey
| | - Nicole Bush
- Department of Pediatrics, University of California San Francisco, San Francisco, California; Weill Institute for Neurosciences, Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, California
| | - Ruby Nguyen
- Department of Epidemiology & Community Health, University of Minnesota, Minneapolis, Minnesota
| | - Terry J Hartman
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Kaja Z LeWinn
- Weill Institute for Neurosciences, Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, California
| | - Alexis Calvert
- Division of General Pediatrics, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - W Alex Mason
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, Tennessee
| | - Kecia N Carroll
- Division of General Pediatrics, Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, New York.
| |
Collapse
|
9
|
Enquobahrie DA, MacDonald J, Hussey M, Bammler TK, Loftus CT, Paquette AG, Byington N, Marsit CJ, Szpiro A, Kaufman JD, LeWinn KZ, Bush NR, Tylavsky F, Karr CJ, Sathyanarayana S. Prenatal exposure to particulate matter and placental gene expression. Environ Int 2022; 165:107310. [PMID: 35653832 PMCID: PMC9235522 DOI: 10.1016/j.envint.2022.107310] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 04/13/2022] [Accepted: 05/16/2022] [Indexed: 05/30/2023]
Abstract
BACKGROUND While strong evidence supports adverse maternal and offspring consequences of air pollution, mechanisms that involve the placenta, a key part of the intrauterine environment, are largely unknown. Previous studies of air pollution and placental gene expression were small candidate gene studies that rarely considered prenatal windows of exposure or the potential role of offspring sex. We examined overall and sex-specific associations of prenatal exposure to fine particulate matter (PM2.5) with genome-wide placental gene expression. METHODS Participants with placenta samples, collected at birth, and childhood health outcomes from CANDLE (Memphis, TN) (n = 776) and GAPPS (Seattle, WA) (n = 205) cohorts of the ECHO-PATHWAYS Consortium were included in this study. PM2.5 exposures during trimesters 1, 2, 3, and the first and last months of pregnancy, were estimated using a spatiotemporal model. Cohort-specific linear adjusted models were fit for each exposure window and expression of >11,000 protein coding genes from paired end RNA sequencing data. Models with interaction terms were used to examine PM2.5-offspring sex interactions. False discovery rate (FDR < 0.10) was used to correct for multiple testing. RESULTS Mean PM2.5 estimate was 10.5-10.7 μg/m3 for CANDLE and 6.0-6.3 μg/m3 for GAPPS participants. In CANDLE, expression of 13 (11 upregulated and 2 downregulated), 20 (11 upregulated and 9 downregulated) and 3 (2 upregulated and 1 downregulated) genes was associated with PM2.5 in the first trimester, second trimester, and first month, respectively. While we did not find any statistically significant association, overall, between PM2.5 and gene expression in GAPPS, we found offspring sex and first month PM2.5 interaction for DDHD1 expression (positive association among males and inverse association among females). We did not observe PM2.5 and offspring sex interactions in CANDLE. CONCLUSION In CANDLE, but not GAPPS, we found that prenatal PM2.5 exposure during the first half of pregnancy is associated with placental gene expression.
Collapse
Affiliation(s)
- Daniel A Enquobahrie
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, United States; Department of Health Systems and Population Health, School of Public Health, University of Washington, Seattle, WA, United States.
| | - James MacDonald
- Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA, United States
| | - Michael Hussey
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, United States
| | - Theo K Bammler
- Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA, United States
| | - Christine T Loftus
- Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA, United States
| | - Alison G Paquette
- Department of Pediatrics, School of Medicine, University of Washington, Seattle, WA, United States; Seattle Children's Research Institute, Seattle, WA, United States
| | - Nora Byington
- Seattle Children's Research Institute, Seattle, WA, United States
| | - Carmen J Marsit
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Adam Szpiro
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, United States
| | - Joel D Kaufman
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, United States; Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA, United States
| | - Kaja Z LeWinn
- Department of Psychiatry and Behavioral Sciences, School of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Nicole R Bush
- Department of Psychiatry and Behavioral Sciences, School of Medicine, University of California, San Francisco, San Francisco, CA, United States; Department of Pediatrics, School of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Frances Tylavsky
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Catherine J Karr
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, United States; Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA, United States; Department of Pediatrics, School of Medicine, University of Washington, Seattle, WA, United States
| | - Sheela Sathyanarayana
- Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA, United States; Department of Pediatrics, School of Medicine, University of Washington, Seattle, WA, United States; Seattle Children's Research Institute, Seattle, WA, United States
| |
Collapse
|
10
|
Aaden A, Morales-Carrasco C, Hermosillo R, Byington N, Feczko E, Chen M, Conelea C, Fair D, Miranda-Dominguez O. Target identification for Transcranial Magnetic Stimulation (TMS) using precision mapping. Brain Stimul 2021. [DOI: 10.1016/j.brs.2021.10.248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
|