SPECIFIC AIMS

This research proposal aims to identify mechanisms explaining why early adversity, namely child maltreatment, is consistently associated with an elevated risk for mental disorder 1-7. While there has been much emphasis on the long-term effects of adversity, including how genes and adversity jointly shape risk 8, there is limited research on how timing of adversity shapes trajectories of development and risk for internalizing symptoms.

The overarching concept we seek to test is that there are "sensitive periods" in development 9-11, or windows of time in the lifespan when the developing brain is particularly vulnerable or sensitive to experience, including adversity. Sensitive periods are characterized by phases of high plasticity and rapid brain development in a given domain 12; 13. First articulated by Hubel and Wiesel 14, a robust literature in animals 15; 16 and now in humans has identified sensitive periods in visual 17 and auditory system processes, including language development 18-22. Several genes (e.g., GAD1, GAD2, GABA1 alpha subunit, and BDNF) and environmental exposures (e.g., exercise, psychotropic medications) have been shown in animal studies to manipulate sensitive periods, either triggering their opening or closing 23. Importantly, recent literature also suggests sensitive periods are not fixed or limited solely to the early years of life and brain development. Instead, sensitive periods can be reopened throughout the lifecourse, even in adulthood, as a result of genetically-mediated factors and environments that "remove the brakes on plasticity" 24; 25.

Currently, we lack an in-depth understanding of the time-dependent effects of adversity on the Research Domain Criteria (RDoC) functional domains 26-29. This is especially true for social system processes, including attachment, social cognition, and social communication, which are likely precursors of internalizing symptoms. Although understudied, extant research suggests there are sensitive periods in attachment 30 and social cognition 31. Child abuse and neglect are known to affect social system processing, including perception of emotional expression32. However, it is unclear whether these effects are the same for all maltreated children or whether there is individual variation, depending on the age when children are first exposed. To that end, early evidence from epidemiological studies now suggests the effects of child maltreatment on internalizing symptoms differ depending on age at first exposure, which is suggestive of a sensitive period 33-35.

Based on prior research and our preliminary studies, the main hypothesis we are testing is that disruptions in social system processes explain the elevated risk of internalizing symptoms among children exposed to maltreatment and that the magnitude of this relationship will depend on the developmental timing of exposure to adversity and what sets of genes are expressed at that point in time.

HYPOTHESES

This proposal will test the following aims/hypotheses:

Aim 1: Explore the time-dependent effect of maltreatment on social domains/internalizing symptoms

Hypothesis 1: Children exposed to maltreatment during a sensitive period (age 3-5) will have lower functioning in social system domains and higher internalizing symptoms when compared to both non-exposed children and children exposed outside of the sensitive period, even after adjusting for maltreatment features (e.g., duration).

Aim 2: Examine the association between age at first onset of exposure to child maltreatment, social function, and internalizing symptoms in adolescents

Hypothesis 2: Social functioning will partially mediate or explain the association between age at first onset of exposure to child maltreatment and internalizing symptoms.

Aim 3: Investigate whether developmental genes modify the association between age at first exposure to child maltreatment and both social domain functioning and internalizing symptoms

Hypothesis 3: Variants in genes shown in animal studies to regulate sensitive periods, and sets of genes shown in humans to be differentially expressed across the lifespan, will modify the effect of adversity timing on domains of social functioning and internalizing symptoms.

The expected outcome of this proposal will be the development of a more nuanced approach to defining sensitive periods and the time-dependent effects of adversity on domains relevant to RDoC. This knowledge will have major impacts on the field, including greater insights into the biology of and mechanisms explaining susceptibility to internalizing symptoms and lead to the development of novel preventions and treatments.

EXPOSURE VARIABLES

Caregiver Reported Childhood Adversities: At yearly intervals between ages 1 and 8, caregivers provided information about whether the child was exposed to the different adversities in the past 12 to 18 months, including being taken into some form of foster care; physically hurt by someone else; sexually abused; separated from mother; and separated from father. This was included in the section entitled "Upsetting Events."

Child Reported Childhood Adversity: At age 16 children were asked to report whether they had been exposed to 23 different types of stressors since age 12.

Documented Reports of Child Maltreatment: We are also seeking information from the 329 children who were invested by social services for suspected maltreatment prior to age 6; this includes 162 children who were placed on local child protection registries as having confirmed cases of maltreatment.

MEDIATOR VARIABLES

Diagnostic Assessment of Non-Verbal Accuracy (DANVA): We are requesting data from the DANVA, which provides information about the offspring's ability to accurately detect facial displays of emotion. This task was administered at age 8.

Emotion Triangles Task: The child's ability to attribute emotional states to other individuals, a component of theory of mind, was assessed at age 13, using the emotion triangle task.

Separation Anxiety, as measured by the Development and Wellbeing Assessment (DAWBA), was asssessed at ages 7, 10, 13, 15.

Social and Communication Disorders Checklist: We are requesting data from this measure, which taps domains of social cognition. It appears this measure was administered to children at ages 7 and 15 (and possibly 10 and 13).

OUTCOME VARIABLES

We are proposing to examine the following outcome variables: (1) Rutter parent scale for preschool children; (2) Strengths and difficulties questionnaire; (3) Development and Wellbeing Assessment; (4) Short Mood and Feelings Questionnaire. For all of these outcomes, we will examine symptoms of mood and anxiety disorders (as a continuous measure) as well as extremes in the symptom distribution or diagnoses (from DAWBA).

EFFECT MODIFIERS

We are proposing to examine sets of genes as effect modifiers of the association between maltreatment and both social system processing and mood and anxiety disorders. Please see Appendix 1B for further details on the genetic information we are requesting.

COVARIATES

We would also be interested in receiving basic demographic variables to use as covariates in our analysis. This includes information about: age, gender, race/ethnicity, socioeconomic status.

Aims: To determine whether sleeping position in the first 6 months is associated with long-term phenotypic changes.

Hypotheses:

1. That there is no adverse association of long-term physical health associated with sleeping on the back or side.

2. That a consequence of increased risk of chest infection associated with prone sleep position is a reduction in lung function in childhood.

3. That prone sleeping may be associated with improved motor ability and coordination.

4. That sleeping position has no long-term effect on cognitive abilities, behaviour or educational attainment.

Exposure variables:

Sleeping position, and other features of bedding and parenting up to 18 months

Outcome variables

All phenotypes on the database

Confounding variables

Gender; socio-economic features; housing; diet; parental education; child care; birthweight; gestation; etc.

Statistical approach will use a phenome scan, taking account of multiple testing. Regression analyses will be used to account for confounders as appropriate.

Background:

We have previously reported an association between prenatal paracetamol exposure and asthma in ALSPAC and shown that this relation is modified by maternal antioxidant gene polymorphisms [1,2]. It was recently reported that the analgesic properties of paracetamol may be mediated by the transient receptor potential ankyrin-1 (TRPA1) channel [3]. Furthermore, animal studies have suggested that TRPA1 plays a role in airway inflammation in asthma [4] and, of relevance to our epidemiological observations, there is evidence that paracetamol can cause neurogenic inflammation in the airways through stimulation of TRPA1 [5]. Cigarette smoke induced neurogenic inflammation is also thought to be mediated by TRPA1 [6].

Aims:

To analyse the relation between maternal and child TRPA1 variants and asthma and lung function in ALSPAC and to explore interactions between TRPA1 and prenatal paracetamol and tobacco smoke exposure on childhood asthma and lung function in order to potentially strengthen causal inference and shed light on mechanisms.

Hypotheses:

1) Maternal and child TRPA1 genotype is associated with asthma and lung function in the offspring.

2) TRPA1 modifies the effects of prenatal paracetamol exposure on childhood asthma and of maternal smoking in pregnancy on childhood small airway function.

Analyses:

It has been proposed that TRPA1 alleles in ALSPAC could be inferred using SNP imputation; a list of 129 imputed SNPs has been generated (all SNPs except one which have been mentioned in the literature associated with pain phenotypes are included in this list) and the plan is to work with Dave Evans to see how best to analyse the data.

A DTA covering analysis of genetic data is already in place with QMUL.

NB: We have all other variables (maternal exposures, confounders and childhood atopic and respiratory outcomes) needed to carry out these analyses.

References:

1) Shaheen SO, Newson RB, Henderson AJ, Headley JE, Stratton FD, Jones RW, Strachan DP, and the ALSPAC Study Team. Prenatal paracetamol exposure and risk of asthma and elevated IgE in childhood. Clin Exp Allergy 2005; 35:18-25.

2) Shaheen SO, Newson RB, Rose-Zerilli M, Ring SM, Holloway JW, Henderson AJ. Prenatal and infant acetaminophen exposure, antioxidant gene polymorphisms and childhood asthma. J Allergy Clin Immunol 2010; 126: 1141-1148.

3) Andersson DA et al. TRPA1 mediates spinal antinociception induced by acetaminophen and the cannabinoid delta9-tetrahydrocannabiorcol. Nature Communications 2011; 2:551.

4) Caceres AI et al. A sensory neuronal ion channel essential for airway inflammation and hyperreactivity in asthma. PNAS 2009; 106: 9099-9104.

5) Nassini R et al. Acetaminophen, via its reactive metabolite N-acetyl-p-benzo-quinoneimine and transient receptor potential ankyrin-1 stimulation, causes neurogenic inflammation in the airways and other tissues in rodents. FASEB J 2010; 24:4904-16.

6) Andre E et al. Cigarette smoke-induced neurogenic inflammation is mediated by alpha, beta-unsaturated adehydes and the TRPA1 receptor in rodents. J Clin Invest 2008; 118: 2574-82.

Aim: The exploration of heredibility of facial features: Fathers and offspring

Hypothesis: Fathers face shape has no influence on the face shape of his offspring

Twin, family and animal studies have suggested that inheritance plays a role in the determination of craniofacial morphology.1-4 Traditional two-dimensional measuring techniques on photographs or lateral skull radiographs tend to be imprecise as landmarks are subject to rotational, positional and magnification errors. However, recent advances in high resolution three-dimensional imaging technologies has provided the opportunity in detailing the spatial relationship of facial landmarks and investigating which genetic variants may be influencing these. However, the evidence for heritability of facial features is not robust and often poorly researched using small samples exhibiting weak associations between parental and offspring with mid father/mother estimates reported as a best predictor for offspring facial parameters.5,6 We will initially focus on facial parameters reported to be associated with known genes. 7,8

1. Kohn, LAP. The Role of Genetics in Craniofacial Morphology and Growth. Annual Review of Anthropology 20, 261-278(1991).

2. Saunders SR, Popovich F, Thompson GW, A family study of craniofacial dimensions in the Burlington Growth Centre sample, American Journal of Orthodontics, Volume 78, Issue 4, October 1980, Pages 394-403.

3. W. Stuart Hunter, Daniel R. Balbach, Donald E. Lamphiear, The heritability of attained growth in the human face, American Journal of Orthodontics, Volume 58, Issue 2, August 1970, Pages 128-134.

4. Johannsdottir B, Thorarinsson F, Thordarson A, Magnusson TE, Heritability of craniofacial characteristics between parents and offspring estimated from lateral cephalograms, American Journal of Orthodontics and Dentofacial Orthopedics, Volume 127, Issue 2, February 2005, Pages 200-207.

5. Nakata M, Yu P, Davis B, Nance WE, The use of genetic data in the prediction of craniofacial dimensions, American Journal of Orthodontics, Volume 63, Issue 5, May 1973, Pages 471-480

6. Nakasima A, Ichinose M, Nakata S, Takahama Y, Hereditary factors in the craniofacial morphology of Angle's Class II and Class III malocclusions, American Journal of Orthodontics, Volume 82, Issue 2, August 1982, Pages 150-156

7. Paternoster L, Zhurov AI, Toma AM, Kemp JP, St Pourcain B, Timpson NJ, McMahon G, McArdle W, Ring SM, Smith GD, Richmond S, Evans DM. Genome-wide association study of three-dimensional facial morphology identifies a variant in PAX3 associated with nasion position. Am J Hum Genet. 2012 Mar 9;90(3):478-85.

8. Liu F, van der Lijn F, Schurmann C, Zhu G, Chakravarty MM, Hysi PG, Wollstein A, Lao O, de Bruijne M, Ikram MA, van der Lugt A, Rivadeneira F, Uitterlinden AG, Hofman A, Niessen WJ, Homuth G, de Zubicaray G, McMahon KL, Thompson PM, Daboul A, Puls R, Hegenscheid K, Bevan L, Pausova Z, Medland SE, Montgomery GW, Wright MJ, Wicking C, Boehringer S, Spector TD, Paus T, Martin NG, Biffar R, Kayser M. A genome-wide association study identifies five Loci influencing facial morphology in europeans. PLoS Genet. 2012 Sep;8(9):e1002932. doi:10.1371/journal.pgen.1002932.

BACKGROUND: Our primary measure of interest is relational complexity, a measure that encapsulates both an individuals's processing capacity and task complexity and is proposed to account for capacity limits found in both reasoning and working memory. At a variance components level, we show that a genetic factor influencing relational complexity accounts for most of the genetic covariation between measures of reasoning and working memory, and further, that there is a strong overlap with IQ. A criterion of our genetic variants of interest was that they must influence variation in all measures (i.e. relational complexity, IQ, reasoning, and working memory), while our genes of interest were the top results for relational complexity and for IQ.

AIM: To assess our most promising genetic variants and genes in independent samples. Two independent groups (the LBC1936 Scottish sample and the NCNG Norwegian sample) have shown some consistency with our findings, but results from a third group (the NTR Netherlands sample) were inconsistent.

HYPOTHESIS: Replicating genetic association and gene-based analyses in multiple independent samples increases the likelihood of avoiding Type 1 (and Type II) error and thereby increases the value of our manuscript.

INDEPENDENT VARIABLES: genotypes for 99 single nucleotide polymorphisms (SNPs) - 11 SNPs are specific genetic variants of interest and the remaining 88 SNPs represent the two genes of interest (list of 99 rs numbers to be provided if application is successful). Note that our genotyping was done using the Illumina HumanHap 610 quad chip (versus HumanHap 550 used by ALSPAC) and it is possible we may need to supply proxies for some SNPs.

DEPENDENT VARIABLES: Matrix Reasoning, WASI IQ (measures available for the other samples: LBC1936 and NCNG both had measures of Matrix Reasoning and IQ, while NTR had a measure of Raven's Progressive Matrices)

(possible) CONFOUNDING VARIABLES: Sex, Age, and Multidimensional Scaling (MDS) components as appropriate to the ALSPAC sample to adjust for population stratification

ANALYSES: Genetic association for 99 SNPs for the measures Matrix Reasoning and WASI IQ, with sex, age, and MDS components included as covariates. (NOTE: for a subset of these SNPs (i.e. 88 of 99) the association results will be used to run a gene-based analysis for 2 genes - this analysis to be conducted at QIMR)

Aims and Hypotheses

Learning disabilities are disorders characterized by unexpected difficulty with a specific mode of learning, generally with normal IQ and educational opportunity. The most common learning disabilities involve language; the NICHD estimates that 15-20% of Americans have a language-based learning disability. This high prevalence makes academic remediation of these disorders a costly burden to the educational system. The most common learning disabilities by far are dyslexia and language impairment (LI), which are specific deficits in processing and expressing written and spoken language, respectively. Both disorders are highly heritable, and genetic studies over the past three decades have identified a number of risk loci and genes. Because genetic methods have been used almost exclusively, however, nothing is known about how most risk variants exert their effects. Additionally, these risk variants account for little of the known heritability of these disorders; much of it is still 'missing,' which precludes development of a gene-based diagnosis. An effective gene-based diagnostic tool would be useful for early detection of affected individuals, as interventions are far more effective if administered earlier in life. In our current funding period, we reported compelling evidence that BV677278, a polymorphic tandem repeat within an intron of the dyslexia risk gene DCDC2, is a regulatory element that substantially influences reading and verbal language skills. We showed that this element can modulate expression from the DCDC2 promoter, that it binds specifically to the potent transcription factor ETV6, that at least two of its alleles significantly reduce mean reading or language performance, and that these alleles show a synergistic genetic interaction with a known risk allele of KIAA0319 (another known dyslexia risk gene in the same locus, DYX2). We also observed associations between other DYX2 regions, such as C6orf62 and THEM2, indicating that other DYX2 elements contribute to reading and language along with the risk variants in DCDC2 and KIAA0319. Based on these results, we hypothesize that BV677278 directly regulates KIAA0319 and other genes via a regulatory complex containing ETV6, and that the deleterious effects of specific BV677278 alleles are due to differences in target gene expression. We also hypothesize that BV677278 and KIAA0319 are not the only functional variants in the DYX2 locus that influence reading and language. To test these hypotheses, we will address the following specific aims:

Specific Aim 1) Examine the effect of BV677278 on gene expression. Because a BV677278 deletion exists naturally in humans, we can examine the effect of having two, one, or zero copies of BV677278 on gene expression, as well as the effects of different BV677278 genotypes. To this end, we will correlate extant expression microarray data from ~1,000 lymphoblastoid cell lines from ALSPAC subjects with various BV677278 genotypes. Allele frequency of the deletion suggests that there will be at least 7 BV677278-null cell lines. We will also perform RNA-seq on ~100 of these cell lines selected for genotypes of interest, including all BV677278-nulls.

Specific Aim 2) Identify putative regulatory targets that interact with the ETV6-BV677278 complex. We will use chromatin interaction analysis with paired end tagging (ChIA-PET) to find putative regulatory targets that physically interact with the ETV6-BV677278 complex. ChIA-PET allows for an unbiased scan of the genome for physical interactions with this complex, and positive results can be confirmed by chromatin conformation capture (3C). 3C will be used as a backup if ChIA-PET fails, though it will require prior identification of candidate target sequences, informed by our expression study in Aim 1. These experiments will be performed in 20 ALSPAC lymphoblastoid cell lines selected for two, one, and zero BV677278 copies.

Specific Aim 3) Identify additional DYX2 variants independent of the BV677278 regulatory element and the KIAA0319 risk haplotype. Our data suggest that, although BV677278 and the KIAA0319 risk haplotype are important sources of the DYX2 linkage and association with dyslexia, there are other DYX2 variants that contribute risk. To identify these variants and to elucidate their functions, we will exploit the single-base resolution provided by next-generation sequencing, and deep sequence the entire DYX2 locus in 1,000 ALSPAC subjects. We will select these subjects using an extreme phenotypes approach: 250 each of the worst performers on reading and language tasks, respectively, and 250 each of the best performers on those same tasks, respectively. Risk variants will accumulate in specific regions in severely affected individuals and will be assessed for functional implications in gene expression, protein function, and histone modifications.

The overall goal of this proposal is to explore the molecular mechanisms by which genetic variants in the DYX2 locus influence written and verbal language skills and impart heritable risk to dyslexia and LI. Our proposed experiments will elucidate the mechanism of action of BV677278, characterize its synergistic interaction with KIAA0319, identify other regulatory and gene targets of BV677278 that may not have been captured by genetic approaches, and detect other variants in the DYX2 locus that influence reading and language. By expanding our understanding of the biological basis of complex reading and language processes, we hope to open future options for diagnosis and treatment of language-based learning disabilities.

Exposure Variables

RNA, DNA and lymphoblastoid cell lines from ALSPAC subjects will be chosen on the basis of their BV677278 genotype, expression data from the microarray analyses of ALSPAC cell lines, performance on verbal language and reading tasks, IQ, and ancestry.

BV677278 is a hypermutable compound short tandem repeat with more than 30 alleles. A 2,445bp deletion, encompassing BV677278 in its entirety, also exists naturally in humans-individuals heterozygous for this deletion are hemizygous (have only one copy) for BV677278, while individuals homozygous for the deletion are completely BV677278-null (no copies of BV677278 in their genome). Our analyses of the ALSPAC thus far have shown that BV677278 allele 5 is associated with dyslexia and lowered reading skills and that BV677278 allele 6 is associated with language impairment and lowered language skills. Not only did these alleles show association with their respective phenotypes, their effects were strong enough to significantly reduce mean performance on reading tasks in the case of allele 5, and language tasks in the case of allele 6, in carriers vs. non-carriers. Additionally, we found that BV677278 interacts synergistically with a known risk variant in the other dyslexia gene in DYX2, KIAA0319, to adversely affect several reading, language, and cognitive phenotypes [Powers et al., submitted]. We also showed that BV677278 specifically binds a nuclear protein and is capable of modulating expression from the DCDC2 promoter [Meng et al., 2011]. We identified this protein that binds to BV677278 as the potent transcription factor and proto-oncogene ETV6 [Powers et al., submitted]. In our aims, we propose to take advantage of the BV677278 microdeletion and the various BV677278 genotypes by comparing RNA-sequencing, deep sequencing of the DYX2 locus, and chromatin studies in lymphoblastoid cell lines with two, one, or no copies (control) of BV677278, and with various alleles that we have so far found to be deleterious to language and reading (alleles 5 and 6).

Outcome Variables

For Aim 1, the outcome of RNA-sequencing will show quantitative expression data (number of cDNA transcripts) from subjects with different BV677278 genotypes. We will be able to compare expression from subjects with two, one, or no copies of BV677278, as well as with BV677278 genotypes of interest, especially alleles 5 and 6. By sequencing 100 selected ALSPAC subjects, we will be able to adjust for intra-subject and inter-subject variation. We will also be able to compare RNA-sequence results with the extant ALSPAC microarray data. We intend to perform RNA-sequence at a high resolution (approximately two samples per flow-cell lane on the Illumina Hi-Seq platform), which should enable us to detect differences in splice variants as well.

For Aim 2, the outcome of the CHiA-PET chromatin studies will be next-generation sequence data of fusion fragments. If successful, one half of the fragment should contain sequence from BV677278, and the other half from putative target genes (under BV677278 transcriptional control) located elsewhere in the DYX2 locus (cis) and beyond (trans). Bioinformatics analysis will be able to differentiate cis from trans elements. Within the DYX2 locus we will be especially looking for fusion fragments containing sequence from the KIAA0319 risk haplotype or promoter region, as well as other possible regulatory elements in the region. Outside DYX2, we will use existing annotation from publically available resources such as JASPAC, ENCODE, and ENSEMBL and in vitro transcriptional reporter assays to inform us whether we have hit transcriptional control elements and target genes that may be relevant to language and reading.

For Aim 3, the outcome of deep sequencing of the 1.5MB DYX2 locus will be variants, known and unknown, distributed throughout the locus. Here we will be looking for clusters of variants in putative regulatory regions such as the DCDC2 promoter, the KIAA0319 promoter, and promoters from other genes that appear to influence reading and language. Analysis for this outcome will be somewhat empirical in terms of setting cluster boundaries and significance, and will depend on the frequency of variants that we see, and whether hits are in areas of LD with SNPs previously shown to be associated with reading, language, or cognition, or that have putative functional roles or show evolutionary conservation.

Confounding Variables

A significant confounder for these experiments will be the heterogeneous genetic background of the subjects, and consequently the lymphoblastoid cell lines, we will use. We will try to minimize the effects of genetic background by restricting studies to subjects of European ancestry, by comparing outcomes from subjects that have the same BV677278 genotypes, and by utilizing population structure metrics already calculated in genome-wide association studies completed at ALSPAC.

There are inherent biases in the techniques we have selected to use in our studies. Therefore,we intend to confirm all novel variants identified by next-generation sequencing results with Sanger sequencing, and all putative physical interactions identified via CHiA-PETwith chromatin conformation capture (3C). We will also use luciferase-reporter experiments to confirm function of novel putative regulatory elements identified by sequencing or the chromatin studies

Materials Requested and Selection Criteria:

1) RNA: We request 5 micrograms (concentration ~50 nanogram/microliter) of RNA from 100 selected subjects for RNA-sequencing. Subject selection will be informed by the results of our genotyping of the BV677278 element and the analysis of the microarray expression data (pending). The goal in subject selection is to identify subjects with BV677278 genotypes of interest, specifically alleles previously related to reading and language performance and the presence/absence of the BV677278 element (del/del and del/+), and to correlate their relationship with global gene expression.

2) Lymphoblastoid Cell Lines: We request 20 lymphoblastoid cell lines from selected subjects for in vivo chromatin studies. Subject selection will be informed by BV677278 genotype, particularly the presence/absence of the BV677278 element and risk alleles (e.g. alleles 5 and 6).

3) DNA: Depending on availability, we request 1-3 micrograms (concentration ~100 nanogram/microliter) of cell line-derived DNA from 1,000 selected subjects for deep sequencing of the 1.5MB of the DYX2 locus. Subject selection will be contingent on past performance on selected language and reading tasks in the ALSPAC at ages 7, 8 and 9 years. We will select subjects using an extreme phenotypes approach: 250 each of the worst performers on reading and language tasks, respectively, and 250 each of the best performers on those same tasks, respectively.

Performance Sites

All non-sequencing experiments will be performed in Dr. Gruen's lab at the Yale Child Health Research Center. This includes all the chromatin studies (CHiA-PET and 3C) and any cell culture that will be required, DNA extraction, and PCR.

All sequencing, next-generation and conventional Sanger sequencing, sequence alignment and annotation, will be performed at the Yale Center for Genome Analysis and The W.M. Keck Foundation Biotechnology Resource Laboratory at Yale. Analysis of aligned and annotated sequence results will be performed in Dr. Gruen's lab at the Yale Child Health Research Center.

Security and Storage of Information and Materials

ALSPAC phenotype, genotype, and sequence information are stored on Yale networked/secured desktop computers only. No ALSPAC data are downloaded to computers that are not connected to the Yale network. No ALSPAC data are downloaded onto thumb drives, peripheral drives, or laptop computers that are not directly connected to the Yale network. No ALSPAC data may be shared with collaborators other than those that have been approved by ALSPAC. In addition, there is no identifying information with phenotype, genotype or sequence information that could link them with a specific ALSPAC subject.

RNA and DNA are stored in -70degree freezers in Dr. Gruen's lab in the Yale Child Health Research Center (464 Congress Avenue). Doors to the lab are locked and accessible by key entry only. Access to the Yale Child Health Research Center is restricted to Yale employees, students, and post-docs who work in the Center. In addition there is no identifying information recorded on the RNA/DNA tubes that could link the material with a specific ALSPAC subject.

Lymphoblastoid cell lines (LCL's) are stored in liquid nitrogen freezers in the Yale Child Health Research Center. Active cultures are stored in CO2 incubators in dedicated facilities in the Center. Access to the Yale Child Health Research Center is restricted to Yale employees, students, and post-docs who work in the Center. In addition there is no identifying information recorded on the cell culture flasks or storage vials that could link the material with a specific ALSPAC subject.

Data Sharing

Per ALSPAC protocol, all data generated in the course of this research will be returned to the ALSPAC within 12 months of its generation.

Ethical Considerations

The main ethical concerns of this proposed research are 1) protection of subject privacy, 2) security and storage of information and materials, 3) serendipitous identification of potentially important health information, and 4) subject withdrawal from the study.

1) Protection of Subject Privacy

Per ALSPAC protocol, all materials and information from ALSPAC is stripped of any identifiers that could possibly link them with a specific subject prior to being sent to collaborators. There is a theoretical possibility that whole genome sequencing or whole exome sequencing could identify an exceedingly rare phenotype that could be traced to a specific subject in the ALSPAC. However, we will not be performing either whole genome or whole exome sequencing on any subject DNA in this proposal. Furthermore, there are no known syndromes, rare or common, that could become known to us by deep sequencing the DYX2 locus. Therefore the risk of violating subject privacy through this research is minimal.

2) Security and Storage of Information and Materials

All information and data obtained during the proposed studies will be stored on Yale-maintained servers with security maintained by Yale University networks. Please see details in the above security section.

3) Serendipitous Identification of Potentially Important Health Information

In the course of deep sequencing the 1.5 megabases (MB) of the DYX2 dyslexia locus on 6p22, it is theoretically possible that we could identify a translocation that could suggest risk of malignancy. The 1.5MB we propose to sequence has been well defined in terms of coding regions and genes. It does not contain any oncogenes or proto-oncogenes or sequences previously described as causing malignancies. However, a recent report by Longoni et al. (2012) suggests that DCDC2 could be a novel oncogenic target of the ETS transcription factor ESE3/EHF. In this study the authors found that DCDC2 was aberrantly expressed in 53 malignant prostate tumors, but absent in 10 normal control prostates. They conclude that the ETS transcription factor ESE3/EHF, which is expressed in normal prostate and frequently lost in prostate tumors, maintained DCDC2 repressed by binding to a novel identified ETS binding site in the DCDC2 gene promoter. The authors do not report that genomic rearrangements, mutations, or RNA splice variants involving DCDC2 were the cause of prostatic malignancies or contributed to drug resistance, but a translocation could theoretically remove DCDC2 repression by separating DCDC2 from its regulatory element.

The risk of serendipitously finding a genomic rearrangement or mutation in the DYX2 locus that could increase the risk of malignancy is extremely small. However, should we find any genomic rearrangement, mutation, or splice variant, in the course of deep sequencing DYX2 that could suggest even a small increased risk of malignancy, we will report it to the ALSPAC within 6 months of identifying it. It will then be ALSPAC's responsibility to decide whether to share the information with a subject or for any further action.

4) Subject Withdrawal from the Study

In the event that we are notified by the ALSPAC that a donor-subject has withdrawn from the study, we will destroy any biomaterials we have received, including DNA, RNA, or lymphoblastoid cell lines. Since all information, genotypes, and variables are de-identified we don't expect that these would need to be deleted. However, we will delete any data if directed to do so by the ALSPAC. The Yale Human Investigation Committee will oversee this procedure.

Oversight of Protection of Human Subjects

All human subject research at Yale is under the oversight of the Yale Human Investigation Committee (HIC). Protocols describing protection of human subjects in detail must be reviewed and approved by the Yale HIC prior to applying for any funding, federal or private, or submission of results for publication. All prior research with the ALSPAC, including this proposal, has been submitted for review by the Yale HIC.

References:

Cho K, Frijters JC, Zhang H, Miller LL, Gruen JR. Prenatal exposure to nicotine and impaired reading performance. The Journal of Pediatrics, in press.

Eicher JD, Powers NR, Cho K, Miller LL, Mueller K, Ring SM, Tomblin JB, Gruen JR. Associations of prenatal nicotine exposure and the dopamine related genes ANKK1/DRD2 to verbal language, manuscript in preparation.

Longoni N, Kunderfranco P, Pellini S, Albino D, Mello-Grand M, Pinton S, D'Ambrosio G, Sarti M, Sessa F, Chiorino G, Catapano CV, Carbone, GM. (2012) Aberrant expression of the neuronal-specific protein DCDC2 promotes malignant phenotypes and is associated with prostate cancer progression. Oncogene doi: 10.1038/onc.2012.245 (epub ahead of print)

Meng H, Smith SD, Hager K, Held M, Liu J, Olson RK, Pennington B, DeFries JC, Gelernter J, O'Reilly-Pol T, Somlo S, Skudlarski P, Shaywitz SE, Shaywitz BA, Marchione K, Wang Y, Paramasivam M, LoTurco JJ, Page GP, Gruen JR. DCDC2 is associated with reading disability and modulates neuronal development in the brain, Proc Natl Acad Sci USA, 102: 17053-17058, 2005. PMID 16278297

Meng H, Powers NR, Tang L, Cope NA, Zhang P-X, Fuleihan R, Gibson C, Page GP, Gruen JR. A dyslexia-associated variant in DCDC2 changes gene expression. Behavior Genetics 2011 Jan;41(1):58-66.

Powers NR, Eicher JD, Butter F, Kong Y, Miller LL, Ring SM, Mann M, Gruen JR. Alleles of a Rapidly-Evolving ETV6 Binding Site in DCDC2 Confer Risk of Reading and Language Impairment, submitted.

Background

Television Exposure

A systematic review in 2006 reported that young people watched on average 1.8-2.8 hours of TV per day, however 28% watched more than 4 hours and these were more likely to remain in the high viewing category at older ages.(1) Despite the development of various media technologies over the past 10 years, television content remains at the forefront of total media exposure in young people. It is now accessible through live and scheduled broadcasting, 'On Demand', recorded time shifted programming, online content via computers, mobile phones or other portable devices. More recent statistics have shown that television content exposure accounts for a daily average of 4 hours and 39 minutes across all these platforms. (2)

In the UK there are an average of 2.4 televisions per household,(3) which has risen over the last 10 years, with over 96% of homes having access to digital television.(4) In 2002 58% of UK children aged between 4-9 years had a television set in their bedroom, which rose to 79% of those aged 10-15 years old.(5)

Effects of television

Studies have shown that television viewing in adolescence can provide information on safe health practices, encourage social connections and behaviours. However there are concerns about its effects on aggression, sexual behaviour, substance use, self-image, social behaviour, physical health, life satisfaction and academic attainment. It has been recognised that television viewing does not require any special physical or cognitive abilities and does not require coordination with other people, therefore has a low or non-existent entry barrier compared to other leisure activities. It provides entertainment which is seen as an immediate benefit and the immediate costs appear negligible or are not predicted at all. Many of the associated costs do not result immediately, rather they take longer to appear for example the effects on sleep, material aspirations and consequences of a lack of investment in social contacts, education or career.(6)

Much of the knowledge we obtain about the world is indirect, through fictional or true accounts and experiences of others on television rather than our own experiences.(7) It has been suggested through Cultivation theory that messages obtained through television exposure on a frequent basis, whether accurate or not, makes up an individual's knowledge and affects their perceptions and behaviours.(7-9) Children and adolescents are particularly vulnerable to these messages, which can comprise of violence, sexuality, body image distortion, objectification and adverse health messages including alcohol, tobacco and illicit substance use, and it is more difficult for them to discriminate between what they see and reality.(10-13) However, children and adolescents are also able to learn pro-social content from television viewing and then generalise that learning to real-life situation, to produce helping behaviour, friendliness, imagination, racial and ethnic tolerance and respect for elders.(14-16)

A high amount of television viewing also displaces time spent in important developmental activities such as reading, problem-solving, homework, hobbies and interactions with parents, siblings and friends, and shown to be associated with attachment problems, social ability issues and attention issues.(17) In adults, it is suggested that excessive television viewing promotes social isolation and therefore hinders the development of social support networks and coping abilities, affecting mental health of individuals.(18)

Effects on mental health and behaviour

One longitudinal study has shown an association between television exposure in adolescence and increased depressive symptoms in young adulthood.(19) Television was most closely linked to depression compared to other media content such as videocassettes, computer games or radio, however this study did not adjust for physical activity.(19) Depressive symptoms have been associated with increased television viewing in other studies, although data shows that physical activity can be unrelated to depressive symptoms,(20) whereas it has also shown to be a protective factor.(21) In children, one study has shown that a greater amount of television viewing was associated with psychological difficulties irrespective of physical activity or sedentary time.(22)

Adolescents with a television set in their bedroom were shown to have fewer family meals, poorer school performance and had higher screen time exposure.(23) This exposure is negatively associated with health-promoting behaviours such as life appreciation, health responsibility, social support and exercise behaviour(24) and a risk factor for school life dissatisfaction and anxiety.(21) Anxiety and symptoms of psychological trauma has also been seen in children with greater television exposure.(25) A greater percentage of nightmares and separation anxiety was experienced in children witnessing distressing content on television, with 38% of them experiencing an increase in distress symptoms.(26) Several studies have shown that an increase in television viewing and in particular before going to bed affected sleep times, disturbances and sleepiness in children,(10, 27-30) which may contribute to mental and cognitive dysfunction.(31)

It is proposed that unrealistic ideals of attractiveness are transmitted through the media resulting in body dissatisfaction; a study concluded that idealised commercials led to an immediate impact on negative mood and appearance comparison for both sexes, with an increased body dissatisfaction for girls.(32) These recurrent episodes of dissatisfaction may accumulate over time leading to a longer-term body image dissatisfaction.(33) Music videos in particular have a high content of visual and auditory messages and have shown to bring about body dissatisfaction.(12) A meta-analysis by Groesz showed that body image was more strongly negative for female adolescents after viewing slender ideals in the media.(34) Another study showed that those who watched television content about cosmetic surgery wanted to alter their own appearance using the similar methods more than those not exposed to this content.(35)

High levels of television viewing leads to crowding out of activities which have a positive effect on happiness, such as time spent with friends and collegues.(36) In adults, it has been associated higher levels of loneliness, hopelessness, shyness, feelings of failure and guilt, depression and eating disorders; in addition to lower levels of self-esteem, weight satisfaction, perceived attractiveness and life satisfaction.(30,37) Particular television content also appears to directly affect mental health, especially news content which individuals are exposed to frequently,(38) which have shown to intensify depressed moods.(39) Heavy television viewers tended to overestimate crime rates, show more anxiety,(40) have less trust in others,(41,42) overestimate the affluence of others,(43) have higher material aspirations(44) and rate their own relative income lower,(46) leading to a lower subjective well-being.(47)

In adults who are experiencing stress, mood management theory predicts television is used to ameliorate moods or block anxious thoughts.(39,48) Stress is associated with an increase in self-reported television viewing in and adults(48) and in adolescents as a coping strategy.(49) In children, stress has been associated with an increased amount of television viewing in children who usually watched a greater amount of television.(50)

Effects on physical health

Television viewing in children and adolescents has shown to be associated with poor fitness, being overweight, smoking and raised cholesterol in adulthood, thus having long-term adverse effects on health.(51) Those adolescents with a television set in their bedroom undertook less physical activity, and had poorer dietary habits including higher consumption of foods containing sugar on a daily basis while watching television or as a result of advertisements.(23,52) The act of sitting itself had been studied and has been shown to lead to changes in resting glucose levels, blood pressure and biomarkers of cardiovascular disease and cancer.(53)

Anti-social behaviour

It has been shown that media exposure is associated with increased violence and aggressive behaviour, more high-risk behaviours such as substance use and earlier onset of sexual activity.(54) In children as young as three years of age, television exposure has shown an increased tendency to exhibit aggressive behaviour.(25,55) A television violence study has shown that nearly two-thirds of all programmes contained violence, with children's shows containing the most.(56) A longitudinal study found that watching violent television content as a young child was also associated with antisocial behaviour several years later in boys 7-10 years old.(57) One RCT showed that an intervention to reduce television viewing decreased aggressive behaviour in school children, supporting the causal influences of television content on aggression.(58) In adolescents the time spent viewing television content increased the likelihood of subsequent aggressive acts against others.(59) Nearly a quarter of music videos portrayed violence and weapon carrying,(60) and higher alcohol consumption and violent behaviour has been observed in teens from the effect of music videos, particularly from violent lyrics.(61,62) However, studies are not entirely consistent and some show no association between television violence and youth violence and aggression.(63,64)

Aims:

1. To examine the association between amount of television viewing in childhood/adolescence and depression in adolescents.

2. To examine the association between amount of television viewing in childhood/adolescence and antisocial behaviour in adolescents.

Hypotheses:

We hypothesise that adolescents who watched a greater amount of television in childhood or adolescence are more likely to show depressive symptoms and exhibit antisocial behaviour in adolescence. There are likely to be multiple reasons for the association of depression with television viewing including the displacement of time from more important developmental and social activities, certain television content causing distress/anxiety and poor sleep, unreal ideals of attractiveness and life dissatisfaction. Television viewing may also be used to ameliorate mood, block anxious thoughts or as a coping mechanism for stress. Regarding antisocial behaviour, the Cultivation theory predicts that through television content, frequent exposure to messages of violence can affect perceptions and behaviour in children and adolescents.

Exposure and outcome variables:

Exp: Self-reported television viewing at age 16

Out: Depressive symptoms and anti-social behaviour at age 18

Exp: Self-reported television viewing at ages 14 and 16

Out: Depressive symptoms and antisocial behaviour at ages 16 and 18

Exp: Depressive symptoms and antisocial behaviour at ages 14 and 16

Out: Self-reported television viewing at age 16

Exp: Parent-reported television viewing at ages 4, 5, 6, and 9 - Weekday, weekend, school day and holidays to create daily average

Out: Depressive symptoms and antisocial behaviour at ages 14, 16 and 18

Confounding variables:

Physical activity, BMI, previous depression, socio-economic indicators, major life events, substance misuse, gender, maternal depression, completion of school and educational achievement, parental education, neglect, parental abuse, early violence, neighbourhood violence, early antisocial behaviour.

Analysis

The main outcomes could be treated either as a binary or continuous variable. However, both depressive symptom scores and antisocial behaviour do not have normally distributed frequencies so our primary analysis will use logistic regression with binary outcomes. We will use the logistic regression model to adjust for confounding variables.

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AIMS

Various different asthma definitions are used in research and clinic. It is important to identify specific underlying mechanisms for the associations of early life exposures with different asthma related outcomes, which might reflect different specific structural and functional adaptations. Major potential early life risk factors are a low birth weight, and change in infant's growth. In a large population-based cohort study followed from birth until the age of 17 years, our aim is to identify potential risk factors for the different asthma phenotypes in young adulthood.

HYPOTHESIS

A recent paper on fetal and infant growth and asthma symptoms in preschool children showed an association between infant weight gain and asthma symptoms, independent of fetal growth, suggesting that early infancy might be critical for the development of asthma. The effect of infant growth on asthma phenotypes and lung function measurements at older ages needs to be explored. If adverse infant growth is also associated with respiratory outcomes in young adulthood, a valuable and modifiable risk factor is identified which could be potentially used for new preventive, diagnostic and therapeutic approaches.

Low birth weight is associated with increased risks of asthma, chronic obstructive lung disease, and impaired lung function in adults and with increased risks of respiratory symptoms in the first 7 years. Low birth weight per se is not likely to be the causal factor for asthma. The same birth weight might be the result of various growth patterns. The developmental plasticity hypothesis suggests that the associations between low birth weight and diseases in later life are explained by early adaptation mechanisms in response to various adverse exposures, including smoke exposure. Previous studies showed inconclusive results about fetal growth patterns and fetal smoke exposure and the risk of wheezing in childhood. The associations of longitudinally measured fetal and early childhood growth patterns, and their interactions with wheezing phenotypes, asthma, bronchial hyperresponsiveness and lung function in later life need to be studied in detail.

EXPOSURE VARIABLES

Birth weight and infant growth.

POTENTIAL CONFOUNDER VARIABLES

parental age, body mass index, education and occupation, history of asthma or atopy, smoking during pregancy, gestational age at birth, children's gender, crowding, siblings, breastfeeding status, ethnicity, tobacco smoke exposure, housing, pet keeping and body mass index at time of outcome.

OUTCOME VARIABLES

(1) recently identified asthma phenotypes: never/infrequent wheeze, transient early wheeze, prolonged early wheeze, intermediate onset wheeze, late onset wheeze, persistent wheeze; (2) doctor diagnosed asthma; at ages 8 and 15 years (2) Lung function (spirometry, bronchial responsiveness to methacholine, exhaled nitric oxide; at ages 8 and 15 years).

The iScan technology housed within the ALSPAC laboratories provides an opportunity to collect valuable genetic data on specific samples in small scale projects. However, where dealing with small sample sizes and potentially valuable,limited, DNA sources, one needs to be confident in the efficiency and reliability of the lab based pipelines for data collection. This proposal simply seeks permission to use a small number (likely sample number for each test being 16 samples, though this may vary by platform) of DNA samples from the ALSPAC immortalised cell lines (which have a theoretically infinite supply of DNA) to test new arrays. Data generated from this testing will then be used to verify the performance of particular arrays before use on samples with a finite reserve.