Discovering pathways to autism spectrum disorder by using functional and integrative genomics approaches to assess monozygotic twin differences

Autism spectrum disorder (ASD) is a common developmental disorder typified by deficits in social communication and stereotyped behaviours. Despite evidence of a strong genetic basis to the disorder, molecular studies have thus far had little success in identifying risk variants or other biomarkers, and presently there is no unified pathomechanistic explanation. Monozygotic (MZ) twins show incomplete concordance in autistic traits, which suggests that alternative risk pathways involving non-shared environmental (NSE) factors could also have an important role to play in ASD. In this thesis, we describe microarray and RNA-seq studies characterising gene expression in a sample of 53 ASD MZ twin pairs from TEDS. The overall aims were to: 1) establish convergent evidence for genes and pathways involved in the etiology of ASD comparing affected and unaffected subjects across the sample 2) to identify those responsive to the environment by examining differences within the discordant pairs. We found a number of genes were differentially expressed including DEPDC1B - the most significant finding in cases vs controls, which also showed consistent down regulation within pairs. We further identified IGHG4, IGHG3, IGHV3-66, HSPA8P14, HSPA13, SLC15A2, and found that these results were enriched for transcriptional control, immune, and PI3K/AKT signalling pathways. We suggest that as these were found to be perturbed in the discordant twins, they could represent ASD risk pathways sensitive to the NSE. Next, we investigated integrative genomics methods for performing meta-dimensional analysis using the expression data along with methylation data on the same cohort. After applying regression-based joint analysis methods, and meta-analysis p-value combination methods to our datasets, a number of genes obtained nominal significance across the datasets, including potential genes of interest: NLGN2, UBE3A, OXTR. We suggest these represent genes with evidence for being functionally relevant to ASD

Discovering pathways to autism spectrum disorder by using functional and integrative genomics approaches to assess monozygotic twin differences

Autism spectrum disorder (ASD) is a common developmental disorder typified by deficits in social communication and stereotyped behaviours. Despite evidence of a strong genetic basis to the disorder, molecular studies have thus far had little success in identifying risk variants or other biomarkers, and presently there is no unified pathomechanistic explanation. Monozygotic (MZ) twins show incomplete concordance in autistic traits, which suggests that alternative risk pathways involving non-shared environmental (NSE) factors could also have an important role to play in ASD. In this thesis, we describe microarray and RNA-seq studies characterising gene expression in a sample of 53 ASD MZ twin pairs from TEDS. The overall aims were to: 1) establish convergent evidence for genes and pathways involved in the etiology of ASD comparing affected and unaffected subjects across the sample 2) to identify those responsive to the environment by examining differences within the discordant pairs. We found a number of genes were differentially expressed including DEPDC1B - the most significant finding in cases vs controls, which also showed consistent down regulation within pairs. We further identified IGHG4, IGHG3, IGHV3-66, HSPA8P14, HSPA13, SLC15A2, and found that these results were enriched for transcriptional control, immune, and PI3K/AKT signalling pathways. We suggest that as these were found to be perturbed in the discordant twins, they could represent ASD risk pathways sensitive to the NSE. Next, we investigated integrative genomics methods for performing meta-dimensional analysis using the expression data along with methylation data on the same cohort. After applying regression-based joint analysis methods, and meta-analysis p-value combination methods to our datasets, a number of genes obtained nominal significance across the datasets, including potential genes of interest: NLGN2, UBE3A, OXTR. We suggest these represent genes with evidence for being functionally relevant to ASD

Bigmelon:Tools for analysing large DNA methylation datasets

Motivation The datasets generated by DNA methylation analyses are getting bigger. With the release of the HumanMethylationEPIC micro-array and datasets containing thousands of samples, analyses of these large datasets using R are becoming impractical due to large memory requirements. As a result there is an increasing need for computationally efficient methodologies to perform meaningful analysis on high dimensional data. Results Here we introduce the bigmelon R package, which provides a memory efficient workflow that enables users to perform the complex, large scale analyses required in epigenome wide association studies (EWAS) without the need for large RAM. Building on top of the CoreArray Genomic Data Structure file format and libraries packaged in the gdsfmt package, we provide a practical workflow that facilitates the reading-in, preprocessing, quality control and statistical analysis of DNA methylation data. We demonstrate the capabilities of the bigmelon package using a large dataset consisting of 1193 human blood samples from the Understanding Society: UK Household Longitudinal Study, assayed on the EPIC micro-array platform. copy; 2018 The Author(s). Published by Oxford University Press.</p

Candidate genes linking maternal nutrient exposure to offspring health via DNA methylation: a review of existing evidence in humans with specific focus on one-carbon metabolism.

Background: Mounting evidence suggests that nutritional exposures during pregnancy influence the fetal epigenome, and that these epigenetic changes can persist postnatally, with implications for disease risk across the life course. Methods: We review human intergenerational studies using a three-part search strategy. Search 1 investigates associations between preconceptional or pregnancy nutritional exposures, focusing on one-carbon metabolism, and offspring DNA methylation. Search 2 considers associations between offspring DNA methylation at genes found in the first search and growth-related, cardiometabolic and cognitive outcomes. Search 3 isolates those studies explicitly linking maternal nutritional exposure to offspring phenotype via DNA methylation. Finally, we compile all candidate genes and regions of interest identified in the searches and describe their genomic locations, annotations and coverage on the Illumina Infinium Methylation beadchip arrays. Results: We summarize findings from the 34 studies found in the first search, the 31 studies found in the second search and the eight studies found in the third search. We provide details of all regions of interest within 45 genes captured by this review. Conclusions: Many studies have investigated imprinted genes as priority loci, but with the adoption of microarray-based platforms other candidate genes and gene classes are now emerging. Despite a wealth of information, the current literature is characterized by heterogeneous exposures and outcomes, and mostly comprise observational associations that are frequently underpowered. The synthesis of current knowledge provided by this review identifies research needs on the pathway to developing possible early life interventions to optimize lifelong health

Environmentally sensitive hotspots in the methylome of the early human embryo

In humans, DNA methylation marks inherited from gametes are largely erased following fertilisation, prior to construction of the embryonic methylome. Exploiting a natural experiment of seasonal variation including changes in diet and nutritional status in rural Gambia, we analysed three datasets covering two independent child cohorts and identified 259 CpGs showing consistent associations between season of conception (SoC) and DNA methylation. SoC effects were most apparent in early infancy, with evidence of attenuation by mid-childhood. SoC-associated CpGs were enriched for metastable epialleles, parent-of-origin-specific methylation and germline differentially methylated regions, supporting a periconceptional environmental influence. Many SoC-associated CpGs overlapped enhancers or sites of active transcription in H1 embryonic stem cells and fetal tissues. Half were influenced but not determined by measured genetic variants that were independent of SoC. Environmental 'hotspots' providing a record of environmental influence at periconception constitute a valuable resource for investigating epigenetic mechanisms linking early exposures to lifelong health and disease

DNA methylation signatures associated with cardiometabolic risk factors in children from India and The Gambia: results from the EMPHASIS study.

BACKGROUND: The prevalence of cardiometabolic disease (CMD) is rising globally, with environmentally induced epigenetic changes suggested to play a role. Few studies have investigated epigenetic associations with CMD risk factors in children from low- and middle-income countries. We sought to identify associations between DNA methylation (DNAm) and CMD risk factors in children from India and The Gambia. RESULTS: Using the Illumina Infinium HumanMethylation 850 K Beadchip array, we interrogated DNAm in 293 Gambian (7-9 years) and 698 Indian (5-7 years) children. We identified differentially methylated CpGs (dmCpGs) associated with systolic blood pressure, fasting insulin, triglycerides and LDL-Cholesterol in the Gambian children; and with insulin sensitivity, insulinogenic index and HDL-Cholesterol in the Indian children. There was no overlap of the dmCpGs between the cohorts. Meta-analysis identified dmCpGs associated with insulin secretion and pulse pressure that were different from cohort-specific dmCpGs. Several differentially methylated regions were associated with diastolic blood pressure, insulin sensitivity and fasting glucose, but these did not overlap with the dmCpGs. We identified significant cis-methQTLs at three LDL-Cholesterol-associated dmCpGs in Gambians; however, methylation did not mediate genotype effects on the CMD outcomes. CONCLUSION: This study identified cardiometabolic biomarkers associated with differential DNAm in Indian and Gambian children. Most associations were cohort specific, potentially reflecting environmental and ethnic differences

Protocol for the EMPHASIS study; epigenetic mechanisms linking maternal pre-conceptional nutrition and children's health in India and Sub-Saharan Africa.

BACKGROUND: Animal studies have shown that nutritional exposures during pregnancy can modify epigenetic marks regulating fetal development and susceptibility to later disease, providing a plausible mechanism to explain the developmental origins of health and disease. Human observational studies have shown that maternal peri-conceptional diet predicts DNA methylation in offspring. However, a causal pathway from maternal diet, through changes in DNA methylation, to later health outcomes has yet to be established. The EMPHASIS study (Epigenetic Mechanisms linking Pre-conceptional nutrition and Health Assessed in India and Sub-Saharan Africa, ISRCTN14266771) will investigate epigenetically mediated links between peri-conceptional nutrition and health-related outcomes in children whose mothers participated in two randomized controlled trials of micronutrient supplementation before and during pregnancy. METHODS: The original trials were the Mumbai Maternal Nutrition Project (MMNP, ISRCTN62811278) in which Indian women were offered a daily snack made from micronutrient-rich foods or low-micronutrient foods (controls), and the Peri-conceptional Multiple Micronutrient Supplementation Trial (PMMST, ISRCTN13687662) in rural Gambia, in which women were offered a daily multiple micronutrient (UNIMMAP) tablet or placebo. In the EMPHASIS study, DNA methylation will be analysed in the children of these women (~1,100 children aged 5-7 y in MMNP and 298 children aged 7-9 y in PMMST). Cohort-specific and cross-cohort effects will be explored. Differences in DNA methylation between allocation groups will be identified using the Illumina Infinium MethylationEPIC array, and by pyrosequencing top hits and selected candidate loci. Associations will be analysed between DNA methylation and health-related phenotypic outcomes, including size at birth, and children's post-natal growth, body composition, skeletal development, cardio-metabolic risk markers (blood pressure, serum lipids, plasma glucose and insulin) and cognitive function. Pathways analysis will be used to test for enrichment of nutrition-sensitive loci in biological pathways. Causal mechanisms for nutrition-methylation-phenotype associations will be explored using Mendelian Randomization. Associations between methylation unrelated to supplementation and phenotypes will also be analysed. CONCLUSION: The study will increase understanding of the epigenetic mechanisms underpinning the long-term impact of maternal nutrition on offspring health. It will potentially lead to better nutritional interventions for mothers preparing for pregnancy, and to identification of early life biomarkers of later disease risk

RNA sequencing of identical twins discordant for autism reveals blood-based signatures implicating immune and transcriptional dysregulation

Background: A gap exists in our mechanistic understanding of how genetic and environmental risk factors converge at the molecular level to result in the emergence of autism symptoms. We compared blood-based gene expression signatures in identical twins concordant and discordant for autism spectrum condition (ASC) to differentiate genetic and environmentally driven transcription differences, and establish convergent evidence for biological mechanisms involved in ASC. Methods: Genome-wide gene expression data were generated using RNA-seq on whole blood samples taken from 16 pairs of monozygotic (MZ) twins and seven twin pair members (39 individuals in total), who had been assessed for ASC and autism traits at age 12. Differential expression (DE) analyses were performed between (a) affected and unaffected subjects (N = 36) and (b) within discordant ASC MZ twin pairs (total N = 11) to identify environmental-driven DE. Gene set enrichment and pathway testing was performed on DE gene lists. Finally, an integrative analysis using DNA methylation data aimed to identify genes with consistent evidence for altered regulation in cis. Results: In the discordant twin analysis, three genes showed evidence for DE at FDR < 10%: IGHG4, EVI2A and SNORD15B. In the case-control analysis, four DE genes were identified at FDR<10% including IGHG4, PRR13P5, DEPDC1B, and ZNF501. We find enrichment for DE of genes curated in the SFARI human gene database. Pathways showing evidence of enrichment included those related to immune cell signalling and immune response, transcriptional control and cell cycle/proliferation. Integrative methylomic and transcriptomic analysis identified a number of genes showing suggestive evidence for cis dysregulation. Limitations: Identical twins stably discordant for ASC are rare, and as such the sample size was limited and constrained to the use of peripheral blood tissue for transcriptomic and methylomic profiling. Given these primary limitations, we focused on transcript-level analysis. Conclusions: Using a cohort of ASC discordant and concordant MZ twins, we add to the growing body of transcriptomic-based evidence for an immune-based component in the molecular aetiology of ASC. Whilst the sample size was limited, the study demonstrates the utility of the discordant MZ twin design combined with multi-omics integration for maximising the potential to identify disease-associated molecular signals

DNA methylation in children from The Gambia

Genome-wide DNA methylation profiling of 251 whole-blood samples from children aged 2 years from the ENID mother-child cohort in The Gambia. Bisulphite converted DNA from the 251 samples were hybridised to the Illumina Infinium HumanMethylation 450k Beadchip. An additional 6 samples were included as technical replicates

Estimation of a significance threshold for epigenome-wide association studies.

Epigenome-wide association studies (EWAS) are designed to characterise population-level epigenetic differences across the genome and link them to disease. Most commonly, they assess DNA-methylation status at cytosine-guanine dinucleotide (CpG) sites, using platforms such as the Illumina 450k array that profile a subset of CpGs genome wide. An important challenge in the context of EWAS is determining a significance threshold for declaring a CpG site as differentially methylated, taking multiple testing into account. We used a permutation method to estimate a significance threshold specifically for the 450k array and a simulation extrapolation approach to estimate a genome-wide threshold. These methods were applied to five different EWAS datasets derived from a variety of populations and tissue types. We obtained an estimate of α=2.4×10-7 for the 450k array, and a genome-wide estimate of α=3.6×10-8. We further demonstrate the importance of these results by showing that previously recommended sample sizes for EWAS should be adjusted upwards, requiring samples between ∼10% and ∼20% larger in order to maintain type-1 errors at the desired level