Sowers__Meaghan_Honors_Project_paper.docx

24 

Full text

(1)

DNA Methylation and Neurodevelopmental Outcomes of Preterm Born Children:

A Systematic Review

By: Meaghan Sowers

Senior Honors Thesis

School of Nursing

University of North Carolina at Chapel Hill

April 28, 2020

Approved by:

(2)

Table of Contents

Abstract...iii

Introduction...1

Methods...3

Study Inclusion Criteria...3

Search Strategy...3

Study Selection and Data Extraction...3

Identification...5

Eligibility...5

Included...5

Screening...5

Results...6

Study characteristics...6

Neurodevelopmental outcomes and DNA methylation...6

Children born preterm < 30 weeks’ gestation...6

Children born extremely preterm at < 28 weeks’ gestation...8

Comparison between children born full-term vs preterm...9

Discussion...11

Clinical Implications...12

Limitations...13

Conclsions...14

(3)

ABSTRACT

Background: Preterm infants are at an increased risk of developing detrimental

neurodevelopmental outcomes. Although substantial research exists on DNA methylation related

to growth and development of newborns, there are currently no systematic reviews focusing on

how epigenetic dysregulation of DNA methylation is associated with neurodevelopmental

outcomes in preterm children.

Objectives: We sought to understand how DNA methylation and their associated genes play a role in the neurodevelopmental outcomes of preterm infants (<37 weeks gestational age).

Methods: We searched electronic databases PubMed, CINAHL, Embase, Scopus, and Web of Science in this systematic review. We identified 2,312 studies. Based on pre-determined criteria,

we reviewed full-text of 39 studies, and five were included in the final sample.

Results: Increased methylation of NR3C1, F10, PLA2G4E, TRIM9, GRIK3, ADCY7,CABLES,

GNAO1, PRKCZ, FDHI3, RHOF, SH3BP5, STX1A, HSP90AA1 and CRHBP and

hypomethylation of HSD11B2 are all associated with increased risk for cognitive impairment in preterm infants. Whereas, hypermethylation of FKBP5, CRHR2 and TH are associated with a decreased risk in cognitive impairment.

Conclusion: Future research should further examine these genes and their methylation patterns to be used as biomarkers for the early diagnosis of neurodevelopmental outcomes in children

(4)

INTRODUCTION

Preterm birth (PTB), defined as delivery at < 37 weeks of gestation, is a pressing public

health concern and the leading cause of infant morbidity and mortality worldwide (Mathews and

Driscoll 2017; Harrison and Goldenberg 2016; Purisch and Gyamfi-Bannerman 2017; Behnia et

al., 2015). In the United States, PTB accounts for approximately 11% of infants born

prematurely, with an annual cost of $26 billion (Purisch and Gyamfi-Bannerman 2017;

Fitzgerald, Boardman and Drake et al., 2018; Behnia et al., 2015). Approximately 30-40% of

children born prematurely will experience some level of neurodevelopmental impairment such as

cerebral palsy, autism spectrum disorder (ASD), epilepsy, intellectual disability and many other

learning, visual or motor disorders (Luu et al. 2017; Hirschberger et al. 2018; Serenius et al.

2016; Synnes and Hicks 2018; Joseph et al. 2016). Along with the financial costs, these

outcomes and complications can put emotional stress on preterm children and their families.

While a diagnosis at birth would be beneficial to these families, it is not currently possible.

Identification of molecular signatures predictive of neurodevelopmental impairment

related to prematurity is urgently needed. Identifying and locating molecular mechanisms and

biomarkers is essential for propelling research further to create early screening techniques to

detect neurodevelopmental outcomes before they become apparent. The impact of early

screening for neurodevelopmental disorders can assist in preparing parents, guardians, or

caregivers for a potential diagnosis. 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 (Mitchell, 2015; Cardosa et al., 2019; Blair, Pickler and Anderson,

(5)

Tyrosine Kinase, Neuregulin 3, and Solute Carrier Family 6 Member 4) have associations with

neurodevelopmental outcomes in multiple, high-quality studies (Burdick, Debrosse, Kane,

Lencz, and Malhotra, 2010; Lin et al., 2012; Kao et al., 2010; Meier et al., 2013; Tost et al.,

2014; Beevers, Wells, Ellis, and McGreary, 2009; Brummelte, Galea, Devlin, and Oberlander,

2013; Kobiella et al., 2011). It is understood that stressors early in life, such as PTB, can interact

with the genome and result in alterations in gene function (Wu et al., 2019; Burris, Baccarelli, Wright and Wright, 2015). DNA methylation can result from the interaction with stressors and the environment and has been associated with neurodevelopmental outcomes in children born

preterm (Aprón et al., 2017; Everson et al., 2019; Meakin et al., 2018; Lester et al., 2015; Tilley

et al., 2018; Sparrow et al., 2016; Bromer et al., 2012; Lee and Sawa, 2014). DNA methylation,

an important epigenetic mechanism that can regulate gene expression without changing DNA

sequence, is essential for cell identification and differentiation (Nugent and Bale, 2015; Bromer

et al., 2012; Conradt et al., 2013; Marsit, Maccani, Padbury and Lester, 2012). Although DNA

methylation is a needed mechanism for regulation of the genome, it can also be associated with

unthwarted neurodevelopmental disorders.

Therefore, the purpose of this systematic review is to evaluate and understand how DNA

methylation, and associated genes, play a role in the neurodevelopmental outcome of preterm

infants (<37 weeks gestational age). In addition, this review will help identify consistent DNA

methylation markers across studies, inform next steps to guide identification of predictive

biomarkers of PTB-related neurodevelopmental outcomes and inform clinical practices in

genomics screening. This review will function to move research forward in identifying essential

(6)

METHODS

This systematic review follows the standards recommended in the Preferred Reporting

Items for Systematic Reviews and Meta-Analysis guideline (Moher et al. 2015). We focused on

studies that investigated the relationship between epigenetics and neurodevelopment outcomes

in preterm children.

Study Inclusion Criteria

Studies needed to investigate the relationships between DNA methylation and

neurodevelopmental outcomes of children born preterm in order to be considered for inclusion.

We defined preterm birth occurring at a gestational age of 37 weeks or less. Neurodevelopmental

outcomes considered for inclusion were cognitive impairment, cerebral palsy, autism and

epilepsy (Hirschberger et al., 2018). Studies with animal subjects were excluded.

Search Strategy

We identified studies through PubMed, CINAHL, Embase, Scopus, and Web of Science.

A comprehensive search string was applied to all five databases to collect studies: Premature

birth OR infant OR premature OR preterm OR prematurity AND epigenesis, genetic OR gene

expression OR DNA Methylation OR epigenetics OR epigenesis OR DNA methylation OR

DNA methylations OR gene expression OR gene expressions AND Neurodevelopmental

Disorders OR Cerebral Palsy OR Nervous System OR neurodevelopment OR

neurodevelopmental OR developmental disability OR developmental disabilities OR intellectual

disability OR intellectual disabilities OR cerebral palsy OR autism OR autistic OR nervous

system.

(7)

Studies were selected using the four-phase process for systematic reviews recommended

by the PRISMA guidelines (Figure 1) (Moher et al., 2015). After identifying 5,398 studies and

removing duplicates, 2,312 titles and abstracts from identified studies were screened for

eligibility and 2,272 studies were excluded. The full text of the remaining 40 studies was

retrieved and screened for eligibility. Reasons for exclusion for the 35 non-eligible studies were

recorded. In the final phase, four studies from the database search and one study from the manual

search met all eligibility criteria and were selected for data extraction. Data from included

literature was extracted into a template that included first author, publication year, sample size,

sample characteristics, graphic location, neurodevelopmental outcomes, neurodevelopmental

measure, time of measure, biological sample, DNA methylation method, p-values, multiple

testing, cell heterogeneity, main results, limitations and implications. For thoroughness, a second

(8)

Figure 1. Study Flow Diagram

Full-text articles excluded, with reasons

(n = 35)

16 Wrong study design 6 Wrong intervention

5 Wrong indication 3 Wrong patient

population 2 Wrong outcomes

1 Duplicate 1 Wrong setting 1 Article no longer

available Studies included in

quantitative synthesis (meta-analysis)

(n = 5) Studies included in qualitative synthesis

(n = 5)

Full-text articles assessed for eligibility

(n = 40)

Records excluded (n = 2272) Records screened

(n = 2312)

Records after duplicates removed (n = 2312)

Additional records identified through other sources

(n = 1) Id en tifi ca tio

El i gi b ili t y

In cl ud ed Sc re en in g

Records identified through database searching

(9)

RESULTS

Study characteristics

All five papers were published in the last five years. Gestational age of participants in the

studies ranged from 23-35 weeks. Two studies enrolled only extremely preterm infants (<28

weeks gestational age) (Meakin et al., 2018; Tilley et al., 2018). Cognitive function was the

primary neurodevelopmental outcome studied and was measured in all five studies. In two

studies, DNA methylation from a placental biopsy was used (Meakin et al., 2018; Tilley et al.,

2018). DNA methylation from buccal swabs was used in two studies (Everson et. al., 2019;

Lester et al., 2015), and the remaining study used blood (Aprón et al., 2017). Genome-wide

analysis were conducted for four studies and one conducted a study on candidate genes (Table

1).

Neurodevelopmental outcomes and DNA methylation

These results are organized by year of publication and preterm birth gestational weeks,

respectively. Each one is focused on their purpose, neurodevelopmental and DNA methylation

outcome measures and a summary of key findings.

Children born preterm < 30 weeks’ gestation

Lester et al.’s (2015) goal was to determine if methylation of certain candidate genes are

associated with neurobehavioral profiles in preterm infants. This article studied how DNA

methylation of Hydroxysteroid 11-Beta Dehydrogenase 2 (HSD11B2) and Nuclear Receptor

(10)

using the Neonatal Intensive Care Unit Network Neurobehavioral Scale (NNNS). This scale can

profile preterm infants into a high-risk and low-risk category which predicts long-term

developmental outcomes. Based on the NNNS scores, 38 out of 67 infants were categorized into

a low-risk group and the remaining 29 infants were put into the high-risk group for problematic

neurobehavior. For NR3C1 at CpG 3, the high-risk group showed double the amount of

methylation compared to the low-risk group. In contrast, DNA methylation for HSD11B2 at the CpG 3 site was lower for high-risk infants compared to the low-risk group. The DNA

methylation patterns of these genes and how they are reflected in the NNNS profile is an

indication that these genes and the CpG sites can be used as a biomarker for diagnostic testing on

preterm infants to determine cognitive function outcomes.

Everson et al. (2019) conducted a genome-wide study on the epigenetic differences

of infant neurobehavior based on the relationship between DNA methylation in the placenta of

preterm newborns (<30 weeks’ gestation) and NNNS scores. Based on the NNNS scores,

subjects were separated into an optimal profile group and an atypical profile group. Areas of

higher methylation was found among CpG sites in the newborns with atypical profile. The F10

gene had the strongest association with the NNNS scores, along with other genes that are linked

to neurobehavioral disorders, such as, phospholipase A2 group IVE (PLA2G4E), tripartite motif containing 9 (TRIM9), and glutamate ionotropic receptor kainate type subunit 3 (GRIK3). The authors highlight how their study illustrates the important link between DNA methylation of

(11)

Children born extremely preterm at < 28 weeks’ gestation

Meakin et al. (2018) studied how placental CpG methylation could predict cognitive

outcomes at the age of 10 for children born before 28 weeks’ gestation. A total of 14 genes were

found to play a key role in the functioning of the hypothalamic-pituitary-adrenal (HPA) axis.

These genes have many biological functions in the placenta that can influence fetal growth and

development as well as later-life cognition. In this study, the participants were from the

Extremely Low Gestational Age Newborn (ELGAN) study. They looked at cognitive

development at the age of 10 for children born prematurely. The School-Age Differential Ability

Scales-II (DAS-II) and NEPSY-II were used to assess for general cognitive ability. They

discovered CpG methylation 41 CpG probes within 10 HPA genes were associated with

moderate/severe cognitive impairment. Increased CpG methylation of the Nuclear Receptor

Subfamily Group 3C Member 1 (NR3C1), the Heat Shock Protein 90 Alpha Family Class A

Member 1 (HSP90AA1), and the Corticotropin Releasing Hormone Binding Protein (CRHBP)

were found to be associated with moderate/severe cognitive impairment. However, increased

CpG methylation of the FK506 Binding Protein 5 (FKBP5), the 3’ UTR region of Corticotropin

Releasing Hormone (CRH), the Corticotropin Releasing Hormone Receptor 2 (CRHR2), and

Tyrosine Hydroxylase (TH) showed a decreased risk of cognitive impairment. Overall, the authors were able to reveal that increases in placental CpG methylation of HPA-axis related

genes were associated with both a higher and lower risk of cognitive impairment at the age of

(12)

hypermethylation of CpG sites in the placenta predicts cognitive impairment at ten years of age

for children born before 28 weeks’ gestation. Out of 84 subjects, 18 had intellectual deficits, 18

had autism spectrum disorder without intellectual deficits and 48 had neither autism spectrum

disorder nor intellectual deficits. Cognitive assessment was assessed using School-Age

Differential Ability Scales-II (DAS-II) and NEPSY-II. Normal cognitive function was identified

in 34% of the ELGAN cohort, 41% had low to normal cognition, 17% were moderately impaired

and 8% had severe cognitive impairment. Placental DNA methylation of 250 CpG sites of 217

unique genes were compared between two groups: spontaneous extremely preterm birth (EPTBs)

and indicated EPTBs. Seventeen of the 250 differentially methylated CpGs predicted moderate

to severe cognitive impairment at age ten for spontaneous EPTB. Higher amounts of methylation

were positively proportional to increased cognitive impairment. The genes that showed the most

significance in this study were Adenylate cyclase 7 (ADCY7), Cdk5 and Abl enzyme substrate 1 (CABLES1), G protein subunit alpha o1 (GNAO1), protein kinase C zeta (PRKCZ), retional

dehydrogenase 13 (RDH13), ras homolog family member F, filopodia associated (RHOF), SH3

domain binding protein 5 (SH3BP5), and syntaxin 1A (STX1A). Each of these genes predicted that a 1% increase in methylation at their probe sites increased the odds of developing moderate

or severe cognitive impairment at age ten by 4-7%. The 17 CpGs studied between spontaneous

and indicated EPTB could be used as clinical epigenomic biomarkers that can perinatally predict

late-life cognitive impairments.

(13)

Aprón et al., (2017) conducted a genome-wide study that compares methylation patterns

of full-term newborns (> 37 weeks’ gestation) versus preterm newborns (< 34 weeks’ gestation).

The authors identified CpG methylation patterns of 317 CpGs (corresponding to 232 genes) to be

associated with PTB. Out of all the CpG sites, the one found to be most significant and showed

the largest methylation difference between the preterm and full-term newborns was located in the

5’ UTR of the corresponding gene Solute Carrier Family 6 Member 3 (SLC6A3). Developmental

outcomes were assessed at 24 and 36 months of age using the Bayley Scale of Infant

Development (BSID) version II and III. This assessment tool is used to predict

neurodevelopmental outcomes in children. Overall, for each subset of the BSID, preterm infants

scored significantly lower compared to the full-term infants. The results of this study also found

that in preterm infants there is a relationship between increased SLC6A3 methylation and lower BSID scores which can predict later-life neurodevelopmental impairments, suggesting that this

gene has a potential epigenetic biomarker that could play a key role in the early diagnosis of

(14)

DISCUSSION

We set out to conduct a systematic review of the literature on how neurodevelopmental

outcomes of preterm infants are attributed to DNA methylation. DNA methylation is a biological

process by which methyl groups are added to the DNA molecule. Dysregulation of this process is

believed to be associated with detrimental health outcomes, such as neurodevelopmental

impairments. We found an array of protein coding genes that, when hypermethylated or

hypomethylated, cause an increased risk of cognitive impairment.

Lester et al. 2015 and Everson et al. 2019 both studied neurobehavioral profiles of

preterm infants using the NNNS scale to compare the DNA methylation patterns of genes and

their CpG sites. The hypermethylation of genes NR3C1, F10, PLA2G4E, TRIM9, GRIK3 were found to be most significantly correlated with infants at high-risk of developing a

neurobehavioral disorder based on NNNS scores (Lester et al., 2015; Everson et al., 2019). On

the other hand, the CpG site on the HSD11B2 gene was found to be hypomethylated in the high-risk group (Lester et al., 2015). Tilley et al. 2018 and Meakin et al. 2018 both studied placental

DNA methylation patterns in the ELGAN study group. The DAS-II and NEPSY-II scales were

used to assess cognitive function of their participants at age 10. In their studies, the

hypermethylated genes shown to have the most significant correlation to moderate/severe

cognitive impairment was ADCY7, CABLES1, GNAO1, PRKCZ, RDHI3, RHOF, SH3BP5,

NR3C1, HSP90AA1, and CRHBP (Tilley et al., 2018; Meakin et al., 2018).

Interestingly, Lester et al. 2015 and Meakin et al. 2018 both found the hypermethylation

(15)

Conradt et al. 2013 conducted a study on DNA methylation and neurodevelopmental outcomes

on children born full-term. One of their findings identified an increase in methylation of the

NR3C1 gene in mothers who were experiencing depression during pregnancy. The increase in the methylation of NR3C1 was affiliated with a lower NNNS score which indicates an increased risk in developing cognitive impairment. However, an increase in the methylation of genes does

not always correlate to an increased risk of cognitive impairment. On the contrary, Meakin et al.

(2018) discovered that hypermethylation of FKBP5, CRHR2, and TH CpG sites lead to a decreased risk in cognitive impairment at age 10.

Aprón et al. 2017 was the only study that used blood samples to study DNA methylation

patterns and the BSID II and III scales to assess for neurodevelopmental outcomes. In their

genome-wide study, they discovered that hypermethylation of SLC6A3 was more prevalent in preterm infants compared to full term infants and related to lower BSID scores. DNA

methylation are important regulators of tissue differentiation, contributing to processes of both

development and detrimental health outcomes. Considering the differences in tissues use by the

studies evaluated in this review (2 used placenta tissue, 2 used buccal swabs, 1 used blood

samples), we need to be cautious on comparing the results between studies derived from

different tissues. One cannot fully discard that similarities and/or differences observed in DNA

methylation patterns are not just due to differences in tissue/cell composition. Further studies

need to be conducted to explore how to interpret and compare findings from different tissues.

(16)

used as biomarkers in identifying and diagnosing various neurodevelopmental outcomes. Our

current clinical approaches used to diagnose neurodevelopmental disorders are based on clinical

presentation rather than diagnosing from biological processes and are often limited and lack

precision (Mullin et al., 2013), because not only do symptoms for different types of

neurodevelopmental disorders overlap, but a diagnosis is often not made until middle or late

childhood (Reiss, 2009). Therefore, it is imperative that research steps forward into the

innovation of identifying these epigenetic processes as a diagnostic tool for neurodevelopmental

outcomes perinatally.

Limitations

We had a limited number of studies to include in our systematic review due to the scarce amount

of research on this topic. There was also not a wide variety of biological samples included in this

study, such as, cord blood or maternal tissue. Neurodevelopmental outcomes such as Autism,

Cerebral Palsy and Epilepsy were not studied due to the limited amount of research on the

methylation of their associated genes. There are many other genes that were not covered in this

study that are likely involved in the process of neurodevelopmental outcomes. The children’s

ages in these studies were limited to early infancy, from birth to 36 months old, and 10 years of

age. Due to the studies involving a highly specific population, some studies had a low or

(17)

CONCLUSIONS

This is the first systematic review to examine how DNA methylation correlates to

neurodevelopmental outcomes of preterm infants. There are several CpG sites on essential genes

found to be associated with later-life cognitive impairment. Both hypermethylated and some

hypomethylated CpG sites that were present in children born preterm were associated with

cognitive impairment outcomes. Overall, these epigenetic mechanisms have the potential to

recognize these genes as biomarkers in the early identification and diagnosis of possible

(18)

Study (DOI) Sample size (n) Sample

Characteristics GeographicLocation NeurodevelopmentalOutcome(s) Neurodevelopmental Assess measureTime of

Aprón et al., 2017 n = 46 (24 PT & 22 FT) PT Gestational age <34

weeks

FT Gestational age >37 weeks.

PT Birthweight <1500g

Madrid, Spain La Paz University Hospital

behavioral & learning disorders: ADHD, Cerebral palsy

Bayley scale of Infant Development version II and BSID III motor & mental

24 & 36 months

Everson et al., 2019 n = 709 infants (enrolled)

n = 679 (neurobehavioral assessment)

n = 624 (epigenomic screening)

Gestational age <30 weeks

9 university-affiliated NICUs: Providence, RI Grand Rapids, MI Kansas City, MO Honolulu, HI Winston-Salem, NC Torrance and Long Beach, CA

Neonatal neurobehavior Neonatal Intensive Care

Unit Network Neurobehavioral Scale (NNNS)

near term-equivalent age

Tilley et al., 2018 n=84 (59 spontaneous

EPTB & 25 indicated EPTB)

Gestational age 23-28 weeks

USA (multi-site) Cognitive function School-Age Differential Ability

Scales II (DAS-II) scales; NEPSY-II

10 years of age

Lester et al., 2015 n = 67 Gestational age 23-35

weeks

Birthweight, 480-1495 g.

NICU at Women & Infants Hospital of Rhode Island

Cerebral Palsy, Cognitive and Motor impairment

Neonatal Intensive Care

Unit Network Neurobehavioral Scale (NNNS)

3-4 days before discharge

Meakin et al., 2018 n = 228 Gestational age <28

weeks (average =25.7 weeks).

60.2% males, 39.8% females. 69.3% normal or low normal cognitive function. 30.7% moderate/severe cognitive impairment. 42% multigestation. 16% assisted reproductive technology (ART)

USA (multi-site) Cognitive function School-Age Differential Ability

Scales II (DAS-II) scales; NEPSY-II

(19)

Study (DOI) Biological Sample

DNA methylation measurement

DNAm scale Gene(s)

name(s)

p-value Multiple

testing

Cell heterogeneity

Aprón et al., 2017 Blood (12

months of age)

Bisulfite-treated genomic DNA was amplified and hybridized using the Infinium HumanMethylation450 BeadChip

Genome wide 317 CpGs were

identified. SLC6A3 was the main CpG

Yes Yes Yes

Everson et al., 2019 Buccal Swabs DNA was quantified using the Quibit

Fluorometer and aliquoted into a standardized concentration for subsequent analyses. DNA samples were plated randomly across 96-well plates and provided to the Emory University Integrated Genomics Core for bisulfite modification using the EZ DNA Methylation Kit subsequent assessment of genome-wide DNAm using the Illumina MethylationEPIC Beadarray

Genome wide F10, PLA2G4E,

TRIM9 & GRIK3

Yes Yes Yes

Tilley et al., 2018

Placenta

Isolated DNA was first bisulfite-converted using the EZ DNA methylation kit. Converted DNA was then hybridized onto the Illumina HumanMethylation450 BeadChip

Genome wide ADCY7,

CABLES1, GNAO1, PRKCZ, RDHI3, RHOF, SH3BP5, STX1A

Yes Yes Yes

Lester et al., 2015 Buccal Swabs Genomic DNA was extracted from oral

swab samples of each infant collected using Oragene Discover for assisted collection using the prepIT kit and subjected to bisulfite modification using the EZ DNA methylation

Candidate gene HSD11B2 &

NR3C1

Yes Yes N/A

Meakin et al., 2018 Placenta Isolated DNA was first

bisulfite-converted using the EZ DNA methylation kit. Converted DNA was then hybridized onto the Illumina HumanMethylation450 BeadChip

Genome wide CRHBP, NR3C1,

HSP90AA1, FKBP5, CRH, CRHR2, & TH

Yes Yes Yes

(20)

identify susceptible individuals and develop preventive and therapeutic measures. Further studies are necessary to confirm the interaction between gestational age as a cause of the changes or a causal role for SLC6A3 and genes related with this pathologic pathway.

BSID-II mental and motor scores showed that methylation and gestational age were significantly associated with this score in simple linear regressions

Peripheral white blood cells were used, which are not part of a tissue related to

neurodevelopment.

Everson et al.,

2019 Differentially methylated CpGs at multiple genes linked to neural structure, function, or different neurobehavioral or

neurodegenerative conditions were found in infants with poorly regulated neurobehavioral profiles

A 10% false discovery rate was used to identify significantly differentially methylated CpG sites. Only one of the models yielded an FDR < 5%.

It is probable that some of identified epigenetic loci are false-positives.

Neonatal epigenetic variation may be informative for predicting infant neurobehavior and neurodevelopmental outcomes in order to maximize the potential benefits of interventions aimed at ameliorating long term deficits.

Methylation of F10, PLA2G4E, TRIM9, and GRIK3 are associated with NNNS scores that put infants at high risk for neurobehavioral disorders.

The combination of epigenomics and neurobehavior has potential for a personalized medicine approach for early detection of poor developmental outcomes.

Tilley et al., 2018

Methylation of genes in placental tissue predicts children's cognitive function at ten years of age

This study is focused on CpG methylation in the placenta only and would not have similar results to a study that focuses on CpG methylation in the fetal brain due to the fact that CpG methylation is tissue-specific.

CpG hypermethylation in placental tissue from spontaneous EPTB could mediate the relationship seen between PTB and adverse neurodevelopmental outcomes Hypermethylation in genes is associated with neuronal development

and function

Hypermethylation of DMPs predicts cognitive function at ten years

of age. 5 of the 17 sites failed to reach significance in the sensitivity analysis due to the lowered

power of the analysis caused by the restricted sample size

DMPs identified between spontaneous and indicated EPTB can be further investigated and used as perinatal clinical

epigenomic biomarkers of later-life neurodevelopmental outcomes.

For each of these genes, a one percent increase in methylation at their respective probe sites predicted a 4-7% increase in the odds of moderate or severe cognitive impairment at age 10

Current standard practice relies on childhood cognitive tests to identify cognitive impairment. But, identification of neonates at highest risk for adverse neurodevelopmental outcomes could present opportunities for earlier interventions which can improve the outcomes of these children

Lester et al., 2015

Preterm infants are more prone to have increased cortisol levels and are at higher risk for more DNA methylation at CpG3 for NR3C1 and less methylation of CpG3 for HSD11B2--which can later lead to adverse neurodevelopmental outcomes.

Causal relations cannot be established because it is an associational study. This study does not indicate epigenetic mechanisms in the brain. Only 2 genes were studied, but more genes are likely involved in these processes.

A genome-wide study of DNA methylation would competent this study of candidate genes and further our understanding o neurobehavioral development.

Meakin et al., 2018

Of the 237 tested probes, 41 probes representing 10 HPA genes were identified to have CpG methylation that was significantly associated with moderate/severe cognitive impairment.

Study focused on CpG methylation of placenta only and not brain tissue. Environmental exposure data was not available for this study.

Future studies should integrate mRNA and protein expression with CpG methylation and environmental exposure data as it relates to epigenetic modification to provide more information on biomarkers for exposure and later-life cognitive

impairments. Increased CpG methylation of NR3C1, HSP90AA1 & CRHBP

(21)

BIBLIOGRAPHY

Arpón, A., Milagro, F. I., Laja, A., Segura, V., Pipaón, M. S. D., Riezu-Boj, J.-I., & Martínez, J. A. (2018). Methylation changes and pathways affected in preterm birth: a role for

SLC6A3 in neurodevelopment. Epigenomics, 10(1), 91–103. doi: 10.2217/epi-2017-0082 Beevers, C. G., Wells, T. T., Ellis, A. J., & Mcgeary, J. E. (2009). Association of the serotonin

transporter gene promoter region (5-HTTLPR) polymorphism with biased attention for emotional stimuli. Journal of Abnormal Psychology, 118(3), 670–681. doi:

10.1037/a0016198

Behnia, F., Parets, S. E., Kechichian, T., Yin, H., Dutta, E. H., Saade, G. R., … Menon, R. (2015). Fetal DNA methylation of autism spectrum disorders candidate genes: association with spontaneous preterm birth. American Journal of Obstetrics and Gynecology, 212(4). doi: 10.1016/j.ajog.2015.02.011

Blair, L. M., Pickler, R. H., & Anderson, C. (2016). Integrative Review of Genetic Factors Influencing Neurodevelopmental Outcomes in Preterm Infants. Biological research for nursing, 18(2), 127–137. https://doi.org/10.1177/1099800415605379

Bromer, C., Marsit, C. J., Armstrong, D. A., Padbury, J. F., & Lester, B. (2012). Genetic and epigenetic variation of the glucocorticoid receptor (NR3C1) in placenta and infant

neurobehavior. Developmental Psychobiology. doi: 10.1002/dev.21061

Brummelte, S., Galea, L., Devlin, A., & Oberlander, T. (2012). Antidepressant use during pregnancy and serotonin transporter genotype (SLC6A4) Affect newborn serum reelin levels. Developmental Psychobiology, 55(5), 518–529. doi: 10.1002/dev.21056

Burdick, K. E., Derosse, P., Kane, J. M., Lencz, T., & Malhotra, A. K. (2010). Association of Genetic Variation in theMETProto-Oncogene With Schizophrenia and General Cognitive Ability. American Journal of Psychiatry, 167(4), 436–443. doi:

10.1176/appi.ajp.2009.09050615

Burris, H. H., Baccarelli, A. A., Wright, R. O., & Wright, R. J. (2015). Epigenetics: linking social and environmental exposures to preterm birth. Pediatric Research, 79(1-2), 136– 140. doi: 10.1038/pr.2015.191

Cardosa, A. R., Lopes-Marques, M., Silva, R. M., Serrano, C., Amorim, A., Prata, M. J., & Azevedo, L. (2019). Essential genetic findings in neurodevelopmental disorders. Human Genomics, 13(31), 1–7. doi: https://doi.org/10.1186/s40246-019-0216-4

(22)

M. (2019). Epigenome-wide Analysis Identifies Genes and Pathways Linked to Neurobehavioral Variation in Preterm Infants. Scientific Reports, 9(1). doi: 10.1038/s41598-019-42654-4

Fitzgerald, E., Boardman, J. P., & Drake, A. J. (2018). Preterm Birth and the Risk of

Neurodevelopmental Disorders - Is There a Role for Epigenetic Dysregulation? Current Genomics, 19(7), 507–521. doi: 10.2174/1389202919666171229144807

Harrison, M.S. and Goldenberg, R.L. 2016. Global burden of prematurity. Seminars in Fetal & Neonatal Medicine 21(2), pp. 74–79.

Hirschberger, R.G., Kuban, K.C.K., O’Shea, T.M., et al. 2018. Co-occurrence and Severity of Neurodevelopmental Burden (Cognitive Impairment, Cerebral Palsy, Autism Spectrum Disorder, and Epilepsy) at Age Ten Years in Children Born Extremely Preterm. Pediatric Neurology 79, pp. 45–52.

Joseph, R.M., O’Shea, T.M., Allred, E.N., et al. 2016. Neurocognitive and academic outcomes at age 10 years of extremely preterm newborns. Pediatrics 137(4).

Kao, W.-T., Wang, Y., Kleinman, J. E., Lipska, B. K., Hyde, T. M., Weinberger, D. R., & Law, A. J. (2010). Common genetic variation in Neuregulin 3 (NRG3) influences risk for schizophrenia and impacts NRG3 expression in human brain. Proceedings of the National Academy of Sciences, 107(35), 15619–15624. doi: 10.1073/pnas.1005410107 Kobiella, A., Reimold, M., Ulshöfer, D. E., Ikonomidou, V. N., Vollmert, C., Vollstädt-Klein, S.,

… Smolka, M. N. (2011). How the serotonin transporter 5-HTTLPR polymorphism influences amygdala function: the roles of in vivo serotonin transporter expression and amygdala structure. Translational Psychiatry, 1(8). doi: 10.1038/tp.2011.29

Lee, R. S., & Sawa, A. (2014). Environmental Stressors and Epigenetic Control of the Hypothalamic-Pituitary-Adrenal Axis. Neuroendocrinology, 100(4), 278–287. doi: 10.1159/000369585

Lester, B. M., Marsit, C. J., Giarraputo, J., Hawes, K., Lagasse, L. L., & Padbury, J. F. (2015). Neurobehavior related to epigenetic differences in preterm infants. Epigenomics, 7(7), 1123–1136. doi: 10.2217/epi.15.63

Lester B, Tronick E. The Neonatal Intensive Care Unit Network Neurobehavioral Scale (NNNS). Pediatrics 113(3), 631–699 (2004).

(23)

Luu, T.M., Rehman Mian, M.O. and Nuyt, A.M. 2017. Long-Term Impact of Preterm Birth: Neurodevelopmental and Physical Health Outcomes. Clinics in Perinatology 44(2), pp. 305–314.

Marsit, C. J., Maccani, M. A., Padbury, J. F., & Lester, B. M. (2012). Placental 11-Beta

Hydroxysteroid Dehydrogenase Methylation Is Associated with Newborn Growth and a Measure of Neurobehavioral Outcome. PLoS ONE, 7(3). doi:

10.1371/journal.pone.0033794

Mathews, T.J. and Driscoll, A.K. 2017. Trends in Infant Mortality in the United States, 2005-2014. NCHS data brief (279), pp. 1–8.

Meakin, C. J., Martin, E. M., Santos, H. P., Mokrova, I., Kuban, K., Oshea, T. M., … Fry, R. C. (2018). Placental CpG methylation of HPA-axis genes is associated with cognitive

impairment at age 10 among children born extremely preterm. Hormones and

Behavior, 101, 29–35. doi: 10.1016/j.yhbeh.2018.02.007

Meier, S., Strohmaier, J., Breuer, R., Mattheisen, M., Degenhardt, F., Mühleisen, T. W., … Wüst, S. (2013). Neuregulin 3 is associated with attention deficits in schizophrenia and bipolar disorder. International Journal of Neuropsychopharmacology, 16(3), 549–556. doi: 10.1017/s1461145712000697

Mitchell, K. J. (2015). The Genetic Architecture of Neurodevelopmental Disorders. The Genetics of Neurodevelopmental Disorders, 1–28. doi: 10.1002/9781118524947.ch1

Moher, D., Shamseer, L., Clarke, M., et al. 2015. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic reviews 4(1), p. 1. Mullin, A. P., Gokhale, A., Moreno-De-Luca, A., Sanyal, S., Waddington, J. L., & Faundez, V.

(2013). Neurodevelopmental disorders: mechanisms and boundary definitions from genomes, interactomes and proteomes. Translational Psychiatry, 3(12). doi:

10.1038/tp.2013.108

Nugent, B. M., & Bale, T. L. (2015). The omniscient placenta: Metabolic and epigenetic regulation of fetal programming. Frontiers in Neuroendocrinology, 39, 28–37. doi: 10.1016/j.yfrne.2015.09.001

Purisch, S.E. and Gyamfi-Bannerman, C. 2017. Epidemiology of preterm birth. Seminars in

Perinatology 41(7), pp. 387–391.

(24)

extremely preterm infants 6.5 years after active perinatal care in sweden. JAMA pediatrics 170(10), pp. 954–963.

Sparrow, S., Manning, J. R., Cartier, J., Anblagan, D., Bastin, M. E., Piyasena, C., … Boardman, J. P. (2016). Epigenomic profiling of preterm infants reveals DNA methylation

differences at sites associated with neural function. Translational Psychiatry, 6(1). doi: 10.1038/tp.2015.210

Synnes, A. and Hicks, M. 2018. Neurodevelopmental outcomes of preterm children at school age and beyond. Clinics in Perinatology 45(3), pp. 393–408.

Tilley, S. K., Martin, E. M., Smeester, L., Joseph, R. M., Kuban, K. C. K., Heeren, T. C., … Fry, R. C. (2018). Placental CpG methylation of infants born extremely preterm predicts cognitive impairment later in life. Plos One, 13(3). doi: 10.1371/journal.pone.0193271 Tost, H., Callicott, J. H., Rasetti, R., Vakkalanka, R., Mattay, V. S., Weinberger, D. R., & Law,

A. J. (2014). Effects of Neuregulin 3 Genotype on Human Prefrontal Cortex Physiology. The Journal of Neuroscience, 34(3), 1051–1056. doi:

10.1523/jneurosci.3496-13.2014

Figure

Updating...

Download now (24 Page)
Related subjects :