1
|
Weaver JM, DiPiero M, Rodrigues PG, Cordash H, Davidson RJ, Planalp EM, Dean DC. Automated motion artifact detection in early pediatric diffusion MRI using a convolutional neural network. IMAGING NEUROSCIENCE (CAMBRIDGE, MASS.) 2023; 1:10.1162/imag_a_00023. [PMID: 38344118 PMCID: PMC10854394 DOI: 10.1162/imag_a_00023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/15/2024]
Abstract
Diffusion MRI (dMRI) is a widely used method to investigate the microstructure of the brain. Quality control (QC) of dMRI data is an important processing step that is performed prior to analysis using models such as diffusion tensor imaging (DTI) or neurite orientation dispersion and density imaging (NODDI). When processing dMRI data from infants and young children, where intra-scan motion is common, the identification and removal of motion artifacts is of the utmost importance. Manual QC of dMRI data is (1) time-consuming due to the large number of diffusion directions, (2) expensive, and (3) prone to subjective errors and observer variability. Prior techniques for automated dMRI QC have mostly been limited to adults or school-age children. Here, we propose a deep learning-based motion artifact detection tool for dMRI data acquired from infants and toddlers. The proposed framework uses a simple three-dimensional convolutional neural network (3DCNN) trained and tested on an early pediatric dataset of 2,276 dMRI volumes from 121 exams acquired at 1 month and 24 months of age. An average classification accuracy of 95% was achieved following four-fold cross-validation. A second dataset with different acquisition parameters and ages ranging from 2-36 months (consisting of 2,349 dMRI volumes from 26 exams) was used to test network generalizability, achieving 98% classification accuracy. Finally, to demonstrate the importance of motion artifact volume removal in a dMRI processing pipeline, the dMRI data were fit to the DTI and NODDI models and the parameter maps were compared with and without motion artifact removal.
Collapse
Affiliation(s)
- Jayse Merle Weaver
- Department of Medical Physics, University of Wisconsin–Madison, Madison, WI, United States
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
| | - Marissa DiPiero
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
- Neuroscience Training Program, University of Wisconsin–Madison, Madison, WI, United States
| | | | - Hassan Cordash
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
| | - Richard J. Davidson
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
- Department of Psychology, University of Wisconsin–Madison, Madison, WI, United States
- Center for Healthy Minds, University of Wisconsin–Madison, Madison WI, United States
- Department of Psychiatry, University of Wisconsin–Madison, Madison, WI, United States
| | - Elizabeth M. Planalp
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
- Department of Medicine, University of Wisconsin–Madison, Madison, WI, United States
| | - Douglas C. Dean
- Department of Medical Physics, University of Wisconsin–Madison, Madison, WI, United States
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
- Department of Pediatrics, University of Wisconsin–Madison, Madison, WI, United States
| |
Collapse
|
2
|
Banihashemi L, Schmithorst VJ, Bertocci MA, Samolyk A, Zhang Y, Lima Santos JP, Versace A, Taylor M, English G, Northrup JB, Lee VK, Stiffler R, Aslam H, Panigrahy A, Hipwell AE, Phillips ML. Neural Network Functional Interactions Mediate or Suppress White Matter-Emotional Behavior Relationships in Infants. Biol Psychiatry 2023; 94:57-67. [PMID: 36918062 PMCID: PMC10365319 DOI: 10.1016/j.biopsych.2023.03.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 02/28/2023] [Accepted: 03/02/2023] [Indexed: 03/16/2023]
Abstract
BACKGROUND Elucidating the neural basis of infant positive emotionality and negative emotionality can identify biomarkers of pathophysiological risk. Our goal was to determine how functional interactions among large-scale networks supporting emotional regulation influence white matter (WM) microstructural-emotional behavior relationships in 3-month-old infants. We hypothesized that microstructural-emotional behavior relationships would be differentially mediated or suppressed by underlying resting-state functional connectivity (rsFC), particularly between default mode network and central executive network structures. METHODS The analytic sample comprised primary caregiver-infant dyads (52 infants [42% female, mean age at scan = 15.10 weeks]), with infant neuroimaging and emotional behavior assessments conducted at 3 months. Infant WM and rsFC were assessed by diffusion-weighted imaging/tractography and resting-state magnetic resonance imaging during natural, nonsedated sleep. The Infant Behavior Questionnaire-Revised provided measures of infant positive emotionality and negative emotionality. RESULTS After significant WM-emotional behavior relationships were observed, multimodal analyses were performed using whole-brain voxelwise mediation. Results revealed that greater cingulum bundle volume was significantly associated with lower infant positive emotionality (β = -0.263, p = .031); however, a pattern of lower rsFC between central executive network and default mode network structures suppressed this otherwise negative relationship. Greater uncinate fasciculus volume was significantly associated with lower infant negative emotionality (β = -0.296, p = .022); however, lower orbitofrontal cortex-amygdala rsFC suppressed this otherwise negative relationship, while greater orbitofrontal cortex-central executive network rsFC mediated this relationship. CONCLUSIONS Functional interactions among neural networks have an important influence on WM microstructural-emotional behavior relationships in infancy. These relationships can elucidate neural mechanisms that contribute to future behavioral and emotional problems in childhood.
Collapse
Affiliation(s)
- Layla Banihashemi
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
| | - Vanessa J Schmithorst
- Department of Pediatric Radiology, University of Pittsburgh Medical Center Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania
| | - Michele A Bertocci
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Alyssa Samolyk
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Yicheng Zhang
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - João Paulo Lima Santos
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Amelia Versace
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Megan Taylor
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Gabrielle English
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Jessie B Northrup
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Vincent K Lee
- Department of Pediatric Radiology, University of Pittsburgh Medical Center Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania
| | - Richelle Stiffler
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Haris Aslam
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Ashok Panigrahy
- Department of Pediatric Radiology, University of Pittsburgh Medical Center Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania
| | - Alison E Hipwell
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Mary L Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| |
Collapse
|
3
|
Posner MI, Rothbart MK. Fifty Years Integrating Neurobiology and Psychology to Study Attention. Biol Psychol 2023; 180:108574. [PMID: 37148960 DOI: 10.1016/j.biopsycho.2023.108574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 05/03/2023] [Accepted: 05/03/2023] [Indexed: 05/08/2023]
Abstract
At the time of the start of Biological Psychology cognitive studies had developed approaches to measuring cognitive processes. However, linking these to the underlying biology in the typical human brain had hardly begun. A critical step came in 1988 when methods for imaging the human brain in cognitive tasks began. By 1990 it was possible to describe three brain networks that carried out the hypothesized cognitive functions outlined 20 years before. Their development was traced in infancy, first using age-appropriate tasks and later through resting state imaging. Imaging was applied to both voluntary and involuntary cued shifts of visual orienting in humans and primates, and a summary was presented in 2002. By 2008 these new imaging findings were used to test hypotheses about the genes involved in each network. Recently, studies of mice using optogenetics to control populations of neurons have brought us closer to a synthesis of how attention and memory networks operate together in human learning. Perhaps the coming years will bring us to an integrated theory of aspects of attention using data from all the levels that can illuminate these issues, thus fulfilling a key goal of the Journal.
Collapse
|
4
|
Planalp EM, Dowe KN, Alexander AL, Goldsmith HH, Davidson RJ, Dean DC. White matter microstructure predicts individual differences in infant fear (But not anger and sadness). Dev Sci 2023; 26:e13340. [PMID: 36367143 PMCID: PMC10079554 DOI: 10.1111/desc.13340] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 08/19/2022] [Accepted: 10/18/2022] [Indexed: 11/13/2022]
Abstract
We examine neural correlates of discrete expressions of negative emotionality in infants to determine whether the microstructure of white matter tracts at 1 month of age foreshadows the expression of specific negative emotions later in infancy. Infants (n = 103) underwent neuroimaging at 1-month, and mothers reported on infant fear, sadness, and anger at 6, 12, and 18 months using the Infant Behavior Questionnaire-Revised. Levels and developmental change in fear, sadness, and anger were estimated from mother reports. Relations between MRI and infant emotion indicated that 1-month white matter microstructure was differentially associated with level and change in infant fear, but not anger or sadness, in the left stria terminalis (p < 0.05, corrected), a tract that connects frontal and tempo-parietal regions and has been implicated in emerging psychopathology in adults. More relaxed constraints on significance (p < 0.10, corrected) revealed that fear was associated with lower white matter microstructure bilaterally in the inferior portion of the stria terminalis and regions within the sagittal stratum. Results suggest the neurobehavioral uniqueness of fear as early as 1 month of age in regions that are associated with potential longer-term outcomes. This work highlights the early neural precursors of fearfulness, adding to literature explaining the psychobiological accounts of affective development. HIGHLIGHTS: Expressions of infant fear and anger, but not sadness, increase from 6 to 18 months of age. Early neural architecture in the stria terminalis is related to higher initial levels and increasing fear in infancy. After accounting for fear, anger and sadness do not appear to be associated with differences in early white matter microstructure. This work identifies early neural precursors of fearfulness as early as 1-month of age.
Collapse
Affiliation(s)
| | - Kristin N Dowe
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Psychology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Andrew L Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - H Hill Goldsmith
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Psychology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Richard J Davidson
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Psychology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Douglas C Dean
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Pediatrics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| |
Collapse
|
5
|
DiPiero M, Rodrigues PG, Gromala A, Dean DC. Applications of advanced diffusion MRI in early brain development: a comprehensive review. Brain Struct Funct 2023; 228:367-392. [PMID: 36585970 PMCID: PMC9974794 DOI: 10.1007/s00429-022-02605-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 12/21/2022] [Indexed: 01/01/2023]
Abstract
Brain development follows a protracted developmental timeline with foundational processes of neurodevelopment occurring from the third trimester of gestation into the first decade of life. Defining structural maturational patterns of early brain development is a critical step in detecting divergent developmental trajectories associated with neurodevelopmental and psychiatric disorders that arise later in life. While considerable advancements have already been made in diffusion magnetic resonance imaging (dMRI) for pediatric research over the past three decades, the field of neurodevelopment is still in its infancy with remarkable scientific and clinical potential. This comprehensive review evaluates the application, findings, and limitations of advanced dMRI methods beyond diffusion tensor imaging, including diffusion kurtosis imaging (DKI), constrained spherical deconvolution (CSD), neurite orientation dispersion and density imaging (NODDI) and composite hindered and restricted model of diffusion (CHARMED) to quantify the rapid and dynamic changes supporting the underlying microstructural architectural foundations of the brain in early life.
Collapse
Affiliation(s)
- Marissa DiPiero
- Department of Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | | | - Alyssa Gromala
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Douglas C Dean
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA.
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, 53705, USA.
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, 53705, USA.
| |
Collapse
|
6
|
Visual tracking at 4 months in preterm infants predicts 6.5-year cognition and attention. Pediatr Res 2022; 92:1082-1089. [PMID: 34949760 DOI: 10.1038/s41390-021-01895-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 11/19/2021] [Accepted: 11/24/2021] [Indexed: 11/08/2022]
Abstract
BACKGROUND Visual tracking of moving objects requires sustained attention and prediction of the object's trajectory. We tested the hypothesis that measures of eye-head tracking of moving objects are associated to long-term neurodevelopment in very preterm infants. METHODS Visual tracking performance was assessed at 4 month's corrected age in 57 infants with gestational age <32 weeks. An object moved in front of the infant with sinusoidal or triangular (i.e. abrupt) turns of the direction. Gaze gain, smooth pursuit gain, and timing of gaze to object motion were analyzed. At 6.5 years the Wechsler Intelligence Scale for Children (WISC-IV), the Brown Attention Deficit Disorder (Brown ADD), and visual examination were performed. RESULTS Gaze gain and smooth pursuit gain at 4 months were strongly related to all WISC-IV parameters at 6.5 years. Gaze gain for the triangular and sinusoidal motion patterns related similarly to the cognitive scores. For the sinusoidal motion pattern, timing related to most Brown ADD parameters. There were no statistically significant differences in associations dependent on motion pattern. Visual function did not influence the results. CONCLUSION The ability to attend to and smoothly track a moving object in infancy is an early marker of cognition and attention at 6.5 years. IMPACT Potential long-term implications of infant visual tracking of moving objects for school-age neurodevelopment has not been previously studied in very preterm infants. Early coordination of eye and head movements in gaze gain, smooth pursuit, and timing of gaze to object motion are closely associated with cognition and attention at 6.5 years. As related functions at 6.5 years include perceptual and verbal skills, working memory, processing speed and attention, predictive elements in gaze tracking of moving objects might be a suitable target for future intervention studies.
Collapse
|
7
|
Kokkinaki T, Markodimitraki M, Vasdekis VG. Maternal speech to singleton and first-born dizygotic twin infants: a four-month longitudinal and naturalistic study. EUROPEAN JOURNAL OF DEVELOPMENTAL PSYCHOLOGY 2022. [DOI: 10.1080/17405629.2022.2092092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- Theano Kokkinaki
- Laboratory of Applied Psychology, Department of Psychology, University of Crete, Rethymnon, Greece
| | | | | |
Collapse
|
8
|
|
9
|
Copeland A, Silver E, Korja R, Lehtola SJ, Merisaari H, Saukko E, Sinisalo S, Saunavaara J, Lähdesmäki T, Parkkola R, Nolvi S, Karlsson L, Karlsson H, Tuulari JJ. Infant and Child MRI: A Review of Scanning Procedures. Front Neurosci 2021; 15:666020. [PMID: 34321992 PMCID: PMC8311184 DOI: 10.3389/fnins.2021.666020] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 05/04/2021] [Indexed: 12/13/2022] Open
Abstract
Magnetic resonance imaging (MRI) is a safe method to examine human brain. However, a typical MR scan is very sensitive to motion, and it requires the subject to lie still during the acquisition, which is a major challenge for pediatric scans. Consequently, in a clinical setting, sedation or general anesthesia is often used. In the research setting including healthy subjects anesthetics are not recommended for ethical reasons and potential longer-term harm. Here we review the methods used to prepare a child for an MRI scan, but also on the techniques and tools used during the scanning to enable a successful scan. Additionally, we critically evaluate how studies have reported the scanning procedure and success of scanning. We searched articles based on special subject headings from PubMed and identified 86 studies using brain MRI in healthy subjects between 0 and 6 years of age. Scan preparations expectedly depended on subject's age; infants and young children were scanned asleep after feeding and swaddling and older children were scanned awake. Comparing the efficiency of different procedures was difficult because of the heterogeneous reporting of the used methods and the success rates. Based on this review, we recommend more detailed reporting of scanning procedure to help find out which are the factors affecting the success of scanning. In the long term, this could help the research field to get high quality data, but also the clinical field to reduce the use of anesthetics. Finally, we introduce the protocol used in scanning 2 to 5-week-old infants in the FinnBrain Birth Cohort Study, and tips for calming neonates during the scans.
Collapse
Affiliation(s)
- Anni Copeland
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
| | - Eero Silver
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
| | - Riikka Korja
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychology, University of Turku, Turku, Finland
| | - Satu J. Lehtola
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Harri Merisaari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Radiology, Turku University Hospital, University of Turku, Turku, Finland
| | - Ekaterina Saukko
- Department of Radiology, Turku University Hospital, University of Turku, Turku, Finland
| | - Susanne Sinisalo
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Jani Saunavaara
- Department of Medical Physics, Turku University Hospital, Turku, Finland
| | - Tuire Lähdesmäki
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Pediatric Neurology, Turku University Hospital, University of Turku, Turku, Finland
| | - Riitta Parkkola
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Radiology, Turku University Hospital, University of Turku, Turku, Finland
| | - Saara Nolvi
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychology and Speech-Language Pathology, Turku Institute for Advanced Studies, University of Turku, Turku, Finland
| | - Linnea Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
- Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland
| | - Hasse Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
| | - Jetro J. Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
- Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| |
Collapse
|
10
|
Dean DC, Madrid A, Planalp EM, Moody JF, Papale LA, Knobel KM, Wood EK, McAdams RM, Coe CL, Hill Goldsmith H, Davidson RJ, Alisch RS, Kling PJ. Cord blood DNA methylation modifications in infants are associated with white matter microstructure in the context of prenatal maternal depression and anxiety. Sci Rep 2021; 11:12181. [PMID: 34108589 PMCID: PMC8190282 DOI: 10.1038/s41598-021-91642-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 05/17/2021] [Indexed: 12/12/2022] Open
Abstract
Maternal and environmental factors influence brain networks and architecture via both physiological pathways and epigenetic modifications. In particular, prenatal maternal depression and anxiety symptoms appear to impact infant white matter (WM) microstructure, leading us to investigate whether epigenetic modifications (i.e., DNA methylation) contribute to these WM differences. To determine if infants of women with depression and anxiety symptoms exhibit epigenetic modifications linked to neurodevelopmental changes, 52 umbilical cord bloods (CBs) were profiled. We observed 219 differentially methylated genomic positions (DMPs; FDR p < 0.05) in CB that were associated with magnetic resonance imaging measures of WM microstructure at 1 month of age and in regions previously described to be related to maternal depression and anxiety symptoms. Genomic characterization of these associated DMPs revealed 143 unique genes with significant relationships to processes involved in neurodevelopment, GTPase activity, or the canonical Wnt signaling pathway. Separate regression models for female (n = 24) and male (n = 28) infants found 142 associated DMPs in females and 116 associated DMPs in males (nominal p value < 0.001, R > 0.5), which were annotated to 98 and 81 genes, respectively. Together, these findings suggest that umbilical CB DNA methylation levels at birth are associated with 1-month WM microstructure.
Collapse
Affiliation(s)
- Douglas C Dean
- Department of Pediatrics, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, USA.,Department of Medical Physics, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.,Waisman Center, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Andy Madrid
- Department of Neurosurgery, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Elizabeth M Planalp
- Waisman Center, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.,Department of Psychology, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Jason F Moody
- Department of Medical Physics, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Ligia A Papale
- Department of Neurosurgery, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Karla M Knobel
- Waisman Center, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Elizabeth K Wood
- Harlow Center for Biological Psychology, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Ryan M McAdams
- Department of Pediatrics, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, USA
| | - Christopher L Coe
- Waisman Center, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.,Department of Psychology, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.,Harlow Center for Biological Psychology, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - H Hill Goldsmith
- Waisman Center, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.,Department of Psychology, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Richard J Davidson
- Waisman Center, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.,Department of Psychology, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.,Center for Healthy Minds, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.,Department of Psychiatry, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Reid S Alisch
- Department of Neurosurgery, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.
| | - Pamela J Kling
- Department of Pediatrics, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, USA
| |
Collapse
|