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Altered Cerebral Curvature in Preterm Infants Is Associated with the Common Genetic Variation Related to Autism Spectrum Disorder and Lipid Metabolism. J Clin Med 2022; 11:jcm11113135. [PMID: 35683524 PMCID: PMC9181724 DOI: 10.3390/jcm11113135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 05/26/2022] [Accepted: 05/28/2022] [Indexed: 02/04/2023] Open
Abstract
Preterm births are often associated with neurodevelopmental impairment. In the critical developmental period of the fetal brain, preterm birth disrupts cortical maturation. Notably, preterm birth leads to alterations in the fronto-striatal and temporal lobes and the limbic region. Recent advances in MRI acquisition and analysis methods have revealed an integrated approach to the genetic influence on brain structure. Based on imaging studies, we hypothesized that the altered cortical structure observed after preterm birth is associated with common genetic variations. We found that the presence of the minor allele at rs1042778 in OXTR was associated with reduced curvature in the right medial orbitofrontal gyrus (p < 0.001). The presence of the minor allele at rs174576 in FADS2 (p < 0.001) or rs740603 in COMT (p < 0.001) was related to reduced curvature in the left posterior cingulate gyrus. This study provides biological insight into altered cortical curvature at term-equivalent age, suggesting that the common genetic variations related to autism spectrum disorder (ASD) and lipid metabolism may mediate vulnerability to early cortical dysmaturation in preterm infants.
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Liu W, Sun Q, Huang L, Bhattacharya A, Wang GW, Tan X, Kuban KCK, Joseph RM, O'Shea TM, Fry RC, Li Y, Santos HP. Innovative computational approaches shed light on genetic mechanisms underlying cognitive impairment among children born extremely preterm. J Neurodev Disord 2022; 14:16. [PMID: 35240980 PMCID: PMC8903548 DOI: 10.1186/s11689-022-09429-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 02/22/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Although survival rates for infants born extremely preterm (gestation < 28 weeks) have improved significantly in recent decades, neurodevelopmental impairment remains a major concern. Children born extremely preterm remain at high risk for cognitive impairment from early childhood to adulthood. However, there is limited evidence on genetic factors associated with cognitive impairment in this population. METHODS First, we used a latent profile analysis (LPA) approach to characterize neurocognitive function at age 10 for children born extremely preterm. Children were classified into two groups: (1) no or low cognitive impairment, and (2) moderate-to-severe cognitive impairment. Second, we performed TOPMed-based genotype imputation on samples with genotype array data (n = 528). Third, we then conducted a genome-wide association study (GWAS) for LPA-inferred cognitive impairment. Finally, computational analysis was conducted to explore potential mechanisms underlying the variant x LPA association. RESULTS We identified two loci reaching genome-wide significance (p value < 5e-8): TEA domain transcription factor 4 (TEAD4 at rs11829294, p value = 2.40e-8) and syntaxin 18 (STX18 at rs79453226, p value = 1.91e-8). Integrative analysis with brain expression quantitative trait loci (eQTL), chromatin conformation, and epigenomic annotations suggests tetraspanin 9 (TSPAN9) and protein arginine methyltransferase 8 (PRMT8) as potential functional genes underlying the GWAS signal at the TEAD4 locus. CONCLUSIONS We conducted a novel computational analysis by utilizing an LPA-inferred phenotype with genetics data for the first time. This study suggests that rs11829294 and its LD buddies have potential regulatory roles on genes that could impact neurocognitive impairment for extreme preterm born children.
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Affiliation(s)
- Weifang Liu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Le Huang
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Arjun Bhattacharya
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Geoffery W Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Xianming Tan
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Karl C K Kuban
- Department of Pediatrics, Boston University, Boston, MA, USA
| | - Robert M Joseph
- Department of Anatomy & Neurobiology, Boston University, Boston, MA, USA
| | - T Michael O'Shea
- Department of Pediatrics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Rebecca C Fry
- Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Hudson P Santos
- School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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Paquette N, Gajawelli N, Lepore N. Structural neuroimaging. HANDBOOK OF CLINICAL NEUROLOGY 2020; 174:251-264. [PMID: 32977882 DOI: 10.1016/b978-0-444-64148-9.00018-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Characterizing the neuroanatomical correlates of brain development is essential in understanding brain-behavior relationships and neurodevelopmental disorders. Advances in brain MRI acquisition protocols and image processing techniques have made it possible to detect and track with great precision anatomical brain development and pediatric neurologic disorders. In this chapter, we provide a brief overview of the modern neuroimaging techniques for pediatric brain development and review key normal brain development studies. Characteristic disorders affecting neurodevelopment in childhood, such as prematurity, attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), epilepsy, and brain cancer, and key neuroanatomical findings are described and then reviewed. Large datasets of typically developing children and children with various neurodevelopmental conditions are now being acquired to help provide the biomarkers of such impairments. While there are still several challenges in imaging brain structures specific to the pediatric populations, such as subject cooperation and tissues contrast variability, considerable imaging research is now being devoted to solving these problems and improving pediatric data analysis.
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Affiliation(s)
- Natacha Paquette
- CIBORG Lab, Department of Radiology, Children's Hospital of Los Angeles and University of Southern California, Los Angeles, CA, United States
| | - Niharika Gajawelli
- CIBORG Lab, Department of Radiology, Children's Hospital of Los Angeles and University of Southern California, Los Angeles, CA, United States
| | - Natasha Lepore
- CIBORG Lab, Department of Radiology, Children's Hospital of Los Angeles and University of Southern California, Los Angeles, CA, United States.
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Telford EJ, Cox SR, Fletcher-Watson S, Anblagan D, Sparrow S, Pataky R, Quigley A, Semple SI, Bastin ME, Boardman JP. A latent measure explains substantial variance in white matter microstructure across the newborn human brain. Brain Struct Funct 2017; 222:4023-4033. [PMID: 28589258 PMCID: PMC5686254 DOI: 10.1007/s00429-017-1455-6] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Accepted: 05/24/2017] [Indexed: 01/12/2023]
Abstract
A latent measure of white matter microstructure (g WM) provides a neural basis for information processing speed and intelligence in adults, but the temporal emergence of g WM during human development is unknown. We provide evidence that substantial variance in white matter microstructure is shared across a range of major tracts in the newborn brain. Based on diffusion MRI scans from 145 neonates [gestational age (GA) at birth range 23+2-41+5 weeks], the microstructural properties of eight major white matter tracts were calculated using probabilistic neighborhood tractography. Principal component analyses (PCAs) were carried out on the correlations between the eight tracts, separately for four tract-averaged water diffusion parameters: fractional anisotropy, and mean, radial and axial diffusivities. For all four parameters, PCAs revealed a single latent variable that explained around half of the variance across all eight tracts, and all tracts showed positive loadings. We considered the impact of early environment on general microstructural properties, by comparing term-born infants with preterm infants at term equivalent age. We found significant associations between GA at birth and the latent measure for each water diffusion measure; this effect was most apparent in projection and commissural fibers. These data show that a latent measure of white matter microstructure is present in very early life, well before myelination is widespread. Early exposure to extra-uterine life is associated with altered general properties of white matter microstructure, which could explain the high prevalence of cognitive impairment experienced by children born preterm.
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Affiliation(s)
- Emma J Telford
- MRC Centre for Reproductive Health, University of Edinburgh, 47 Little France Crescent, Edinburgh, EH16 4TJ, UK
| | - Simon R Cox
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Sue Fletcher-Watson
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - Devasuda Anblagan
- MRC Centre for Reproductive Health, University of Edinburgh, 47 Little France Crescent, Edinburgh, EH16 4TJ, UK
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - Sarah Sparrow
- MRC Centre for Reproductive Health, University of Edinburgh, 47 Little France Crescent, Edinburgh, EH16 4TJ, UK
| | - Rozalia Pataky
- MRC Centre for Reproductive Health, University of Edinburgh, 47 Little France Crescent, Edinburgh, EH16 4TJ, UK
| | - Alan Quigley
- Department of Radiology, Royal Hospital for Sick Children, 9 Sciennes Road, Edinburgh, EH9 1LF, UK
| | - Scott I Semple
- University/BHF Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, EH16 4TJ, UK
- Clinical Research Imaging Centre, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - James P Boardman
- MRC Centre for Reproductive Health, University of Edinburgh, 47 Little France Crescent, Edinburgh, EH16 4TJ, UK.
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
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Smits A, van den Anker JN, Allegaert K. Clinical pharmacology of analgosedatives in neonates: ways to improve their safe and effective use. ACTA ACUST UNITED AC 2016; 69:350-360. [PMID: 27364566 DOI: 10.1111/jphp.12599] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2016] [Accepted: 06/11/2016] [Indexed: 12/19/2022]
Abstract
OBJECTIVES To propose approaches tailored to the specific needs of neonates, such as structured product development programmes, with the ultimate goal to improve the safe and effective use of analgosedatives in these fragile patients. KEY FINDINGS The feasibility and relevance of a structured product development programme in neonates (optimal study design based on preliminary data; model development; internal, external and prospective evaluation; an individualized dosing regimen; long-term safety; pharmacogenetics) are illustrated for the use of morphine. Based on changes in clinical practices, similar development plans are in progress for short-acting analgosedatives such as propofol, but are in need of tailored pharmacodynamic tools to assess and quantify effects. Furthermore, for drugs like paracetamol where there is already sufficient clinical pharmacology knowledge, attention needs to be given to long-term safety aspects. Finally, new covariates such as pharmacogenetics might further improve neonatal pain management, but clearly need to be integrated with other well-established covariates like age or weight. SUMMARY Product development programmes for analgosedatives in neonates are needed. These programmes should be tailored to their specific needs (short-acting sedation, pain relief), should include long-term safety and should incorporate the exploration of newer covariates like pharmacogenetics.
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Affiliation(s)
- Anne Smits
- Neonatal Intensive Care Unit, VU Medical Center, Amsterdam, The Netherlands.,Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium
| | - John N van den Anker
- Intensive Care and Department of Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands.,Division of Paediatric Pharmacology and Pharmacometrics, University Children's Hospital Basel, Basel, Switzerland.,Division of Pediatric Clinical Pharmacology, Children's National Medical Center, Washington, DC, USA.,Departments of Pediatrics, Integrative Systems Biology, Pharmacology & Physiology, George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Karel Allegaert
- Intensive Care and Department of Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands.,Department of Development and Regeneration, KU Leuven, Leuven, Belgium
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Blair LM, Pickler RH, Anderson C. Integrative Review of Genetic Factors Influencing Neurodevelopmental Outcomes in Preterm Infants. Biol Res Nurs 2015; 18:127-37. [PMID: 26374169 DOI: 10.1177/1099800415605379] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Preterm infants are at elevated risk for a host of neurodevelopmental problems, including disorders that appear later in life. Gene-environment interactions and prematurity may combine to increase the risk for poor neurodevelopmental outcomes. Increasing evidence supports a genetic link to risk for atypical development; however, no genomic risk profiles are currently used for infants without apparent genetic disorders. The purpose of this review was to synthesize recent evidence of genetic associations with atypical neurodevelopmental outcomes that may affect preterm infants who do not have a rare genetic disease. Electronic and hand-search strategies were used to find relevant articles that were English-language, peer-reviewed primary research or meta-analysis reports published between July 2009 and July 2014, involving human participants. Articles included in the analysis (N = 29) used a wide range of study designs and methodologies, complicating the analysis. An integrative-review design was used to synthesize the data. Numerous genes (n = 43) and additional large deletion copy number variants were associated with neurodevelopmental outcomes, including cognition, attention, perception, psychiatric disease, autism spectrum disorder, cerebral palsy, infant behavior, and alterations in brain architecture. The creation of genetic risk profiles for complex disorders of neurodevelopment is presently hindered by inconsistent genetic-association evidence, methodological considerations, reporting problems, and lack of replication. However, several avenues of investigation offer promise, including large (>100 kb) copy number variants and the candidate genes MET, NRG3, and SLC6A4, each of which were reported to have associations with neurodevelopmental outcomes in multiple, high-quality studies.
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Kaller CP, Reisert M, Katzev M, Umarova R, Mader I, Hennig J, Weiller C, Köstering L. Predicting planning performance from structural connectivity between left and right mid-dorsolateral prefrontal cortex: moderating effects of age during postadolescence and midadulthood. Cereb Cortex 2013; 25:869-83. [PMID: 24108808 DOI: 10.1093/cercor/bht276] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Complex cognitive abilities such as planning are known to critically rely on activity of bilateral mid-dorsolateral prefrontal cortex (mid-dlPFC). However, the functional relevance of the structural connectivity between left and right mid-dlPFC is yet unknown. Here, we applied global tractography to derive streamline counts as estimates of the structural connectivity between mid-dlPFC homologs and related it to planning performance in the Tower of London task across early to midadulthood, assuming a moderating effect of age. Multiple regression analyses with interaction effects revealed that streamline counts between left and right mid-dlPFC were negatively associated with planning performance specifically in early postadolescence. From the fourth life decade on, there was a trend for a reversed, positive association. These differential findings were corroborated by converging results from fractional anisotropy and white-matter density estimates in the genu of the corpus callosum where fibers connecting mid-dlPFC homologs traversed. Moreover, the results for streamline counts were regionally specific, marking the strength of mid-dlPFC connectivity as critical in predicting interindividual differences in planning performance across different stages of adulthood. Taken together, present findings provide first evidence for nonadditive effects of age on the relation between complex cognitive abilities and the structural connectivity of mid-dlPFC homologs.
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Affiliation(s)
- Christoph P Kaller
- Department of Neurology, University Medical Center Freiburg Brain Imaging Center BrainLinks-BrainTools Cluster of Excellence
| | - Marco Reisert
- Freiburg Brain Imaging Center Medical Physics, Department of Radiology, University Medical Center Freiburg
| | - Michael Katzev
- Department of Neurology, University Medical Center Freiburg Brain Imaging Center
| | - Roza Umarova
- Department of Neurology, University Medical Center Freiburg Brain Imaging Center
| | - Irina Mader
- Freiburg Brain Imaging Center Department of Neuroradiology, University Medical Center, University of Freiburg, 79106 Freiburg, Germany
| | - Jürgen Hennig
- Freiburg Brain Imaging Center BrainLinks-BrainTools Cluster of Excellence Medical Physics, Department of Radiology, University Medical Center Freiburg
| | - Cornelius Weiller
- Department of Neurology, University Medical Center Freiburg Brain Imaging Center BrainLinks-BrainTools Cluster of Excellence
| | - Lena Köstering
- Department of Neurology, University Medical Center Freiburg Brain Imaging Center
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Joshi SH, Narr KL, Philips OR, Nuechterlein KH, Asarnow RF, Toga AW, Woods RP. Statistical shape analysis of the corpus callosum in Schizophrenia. Neuroimage 2012; 64:547-59. [PMID: 23000788 DOI: 10.1016/j.neuroimage.2012.09.024] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2012] [Revised: 08/13/2012] [Accepted: 09/05/2012] [Indexed: 11/27/2022] Open
Abstract
We present a statistical shape-analysis framework for characterizing and comparing morphological variation of the corpus callosum. The midsagittal boundary of the corpus callosum is represented by a closed curve and analyzed using an invariant shape representation. The shape space of callosal curves is endowed with a Riemannian metric. Shape distances are given by the length of shortest paths (geodesics) that are invariant to shape-confounding transformations. The statistical framework enables computation of shape averages and covariances on the shape space in an intrinsic manner (unique to the shape space). The statistical framework makes use of the tangent principal component approach to achieve dimension reduction on the space of corpus callosum shapes. The advantages of this approach are - it is fully automatic, invariant, and avoids the use of landmarks to define shapes. We applied our method to determine the effects of sex, age, schizophrenia and schizophrenia-related genetic liability on callosal shape in a large sample of patients and controls and their first-degree relatives (N=218). Results showed significant age, sex, and schizophrenia effects on both global and local callosal shape structure.
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Affiliation(s)
- Shantanu H Joshi
- Laboratory of Neuro Imaging, University of California, Los Angeles, CA 90095-7334, USA.
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