Exploring the Functional Basis of Epigenetic Aging in Relation to Body Fat Phenotypes in the Norfolk Island Cohort.

DNA methylation is an epigenetic factor that is modifiable and can change over a lifespan. While many studies have identified methylation sites (CpGs) related to aging, the relationship of these to gene function and age-related disease phenotypes remains unclear. This research explores this question by testing for the conjoint association of age-related CpGs with gene expression and the relation of these to body fat phenotypes. The study included blood-based gene transcripts and intragenic CpG methylation data from Illumina 450 K arrays in 74 healthy adults from the Norfolk Island population. First, a series of regression analyses were performed to detect associations between gene transcript level and intragenic CpGs and their conjoint relationship with age. Second, we explored how these age-related expression CpGs (eCpGs) correlated with obesity-related phenotypes, including body fat percentage, body mass index, and waist-to-hip ratio. We identified 35 age-related eCpGs associated with age. Of these, ten eCpGs were associated with at least one body fat phenotype. Collagen Type XI Alpha 2 Chain (COL11A2), Complement C1s (C1s), and four and a half LIM domains 2 (FHL2) genes were among the most significant genes with multiple eCpGs associated with both age and multiple body fat phenotypes. The COL11A2 gene contributes to the correct assembly of the extracellular matrix in maintaining the healthy structural arrangement of various components, with the C1s gene part of complement systems functioning in inflammation. Moreover, FHL2 expression was upregulated under hypermethylation in both blood and adipose tissue with aging. These results suggest new targets for future studies and require further validation to confirm the specific function of these genes on body fat regulation.

A genome-wide methylation study of body fat traits in the Norfolk Island isolate.

BACKGROUND AND AIMS: Natural variation in body fat is explained by both genetic and environmental effects. Epigenetic mechanisms such as DNA methylation can mediate these effects causing changes in gene expression leading to onset of obesity. Studies of genetic isolates have the potential to provide new epigenetic insights with advantages such as reduced genetic diversity and environmental exposures. METHODS AND RESULTS: This was an exploratory study of genome-wide DNA methylation in relation to body fat traits in 47 healthy adults from the genetic isolate of Norfolk Island. Quantitative body fat traits (body fat percentage, body mass index, hip circumference, waist circumference, waist-hip-ratio and weight) were carefully measured. DNA methylation data was obtained from peripheral blood using Illumina 450K arrays. Multi-trait analysis was performed using Principal Component Analysis (PCA). CpG by trait association testing was performed using stepwise linear regressions. Two components were identified that explained approximately 89% of the phenotypic variance. In total, 5 differential methylated positions (DMPs) were identified at genome-wide significance (P≤ 2.4 × 10-7), which mapped to GOT2-CDH8, LYSMD3, HIBADH, ADGRD1 and EBF4 genes. Gene set enrichment analysis of 848 genes containing suggestive DMPs (P≤ 1.0 × 10-4) implicated the Cadherin (28 genes, Padj = 6.76 × 10-7) and Wnt signaling pathways (38 genes, Padj = 7.78 × 10-6). CONCLUSION: This study provides new insights into the epigenetically influenced genes and pathways underlying body fat variation in a healthy cohort and provides targets for consideration in future studies of obesity risk.

Tiered analysis of whole-exome sequencing for epilepsy diagnosis.

It is thought that despite highly variable phenotypic expression, 70-80% of all epileptic cases are caused by one or more genetic mutations. Next generation sequencing technologies, such as whole exome sequencing (WES), can be used in a diagnostic or research setting to identify genetic mutations which may have significant prognostic implications for patients and their families. In this study, 398 genes associated with epilepsy or recurrent seizures were stratified into tiers based on genotype-phenotype concordance, tissue gene expression, frequency of affected individuals with mutations and evidence from functional and family studies. WES was completed on 14 DNA samples (2 with known mutations in SCN1A and 12 with no known mutations) from individuals diagnosed with epilepsy using an Ion AmpliSeq approach. WES confirmed positive SCN1A mutations in two samples. In n = 5/12 samples (S-3 to -14) we identified potentially causative mutations across five different genes. S-5 was identified to have a novel missense mutation in CCM2; S-6 a novel frameshift mutation identified in ADGRV1; S-10 had a previously reported pathogenic mutation in PCDH19, whilst a novel missense mutation in PCDH19 was shown in S-12; and S-13 identified to have separate missense mutations in KCNA2 and NPRL3. The application of WES followed by a targeted variant prioritization approach allowed for the discovery of potentially causative mutations in our cohort of previously undiagnosed epilepsy patients.

Expression QTL analysis of glaucoma endophenotypes in the Norfolk Island isolate provides evidence that immune-related genes are associated with optic disc size.

Primary open-angle glaucoma (POAG) is influenced by both genetic and environmental factors. Despite significant progress in identifying genetic variants associated with POAG, there remains a substantial amount of unexplained heritability. Study design features that may enhance knowledge of the genetic architecture include focusing on multiple quantitative traits related to ocular disorders (i.e. endophenotypes), targeting genetic variants that directly influence gene expression (i.e. cis-eQTLs) and utilising genetically isolated populations to reduce genetic and environmental noise and thus enhance association signals. In this study we performed heritability and blood-based eQTL association analysis of five key POAG endophenotypes in 330 individuals from the Norfolk Island (NI) isolate. Results showed evidence of heritability for all five traits, with H2 estimates ranging from 0.35 for intraocular pressure (IOP) to 0.82 for central corneal thickness (CCT) (P < 0.05). The primary finding was for BTN3A2, whereby both cis-SNP and transcript were significantly associated with disc size within a conditional regression model. Specifically, this model included rs853676 (ß = 0.23,P = 0.008) and transcript (ß = 0.23, P = 0.03). We also observed a cis-SNP association between optic disc size and LPCAT2 independent of transcript (P = 0.0004). These genes have specific functions in immune system pathways and suggest a role for an inherited immune component of POAG risk. This study also demonstrates an alternate approach to understanding the functional genetic basis of POAG and ocular health more generally.

A Phenomic Scan of the Norfolk Island Genetic Isolate Identifies a Major Pleiotropic Effect Locus Associated with Metabolic and Renal Disorder Markers.

Multiphenotype genome-wide association studies (GWAS) may reveal pleiotropic genes, which would remain undetected using single phenotype analyses. Analysis of large pedigrees offers the added advantage of more accurately assessing trait heritability, which can help prioritise genetically influenced phenotypes for GWAS analysis. In this study we performed a principal component analysis (PCA), heritability (h2) estimation and pedigree-based GWAS of 37 cardiovascular disease -related phenotypes in 330 related individuals forming a large pedigree from the Norfolk Island genetic isolate. PCA revealed 13 components explaining >75% of the total variance. Nine components yielded statistically significant h2 values ranging from 0.22 to 0.54 (P<0.05). The most heritable component was loaded with 7 phenotypic measures reflecting metabolic and renal dysfunction. A GWAS of this composite phenotype revealed statistically significant associations for 3 adjacent SNPs on chromosome 1p22.2 (P<1x10-8). These SNPs form a 42kb haplotype block and explain 11% of the genetic variance for this renal function phenotype. Replication analysis of the tagging SNP (rs1396315) in an independent US cohort supports the association (P = 0.000011). Blood transcript analysis showed 35 genes were associated with rs1396315 (P<0.05). Gene set enrichment analysis of these genes revealed the most enriched pathway was purine metabolism (P = 0.0015). Overall, our findings provide convincing evidence for a major pleiotropic effect locus on chromosome 1p22.2 influencing risk of renal dysfunction via purine metabolism pathways in the Norfolk Island population. Further studies are now warranted to interrogate the functional relevance of this locus in terms of renal pathology and cardiovascular disease risk.

Genome-wide linkage and association analysis of primary open-angle glaucoma endophenotypes in the Norfolk Island isolate.

PURPOSE: Primary open-angle glaucoma (POAG) refers to a group of heterogeneous diseases involving optic nerve damage. Two well-established risk factors for POAG are elevated intraocular pressure (IOP) and a thinner central corneal thickness (CCT). These endophenotypes exhibit a high degree of heritability across populations. Large-scale genome-wide association studies (GWASs) of outbred populations have robustly implicated several susceptibility gene variants for both IOP and CCT. Despite this progress, a substantial amount of genetic variance remains unexplained. Population-specific variants that might be rare in outbred populations may also influence POAG endophenotypes. The Norfolk Island population is a founder-effect genetic isolate that has been well characterized for POAG endophenotypes. This population is therefore a suitable candidate for mapping new variants that influence these complex traits. METHODS: Three hundred and thirty participants from the Norfolk Island Eye Study (NIES) core pedigree provided DNA. Ocular measurements of CCT and IOP were also taken for analysis. Heritability analyses and genome-wide linkage analyses of short tandem repeats (STRs) were conducted using SOLAR. Pedigree-based GWASs of single-nucleotide polymorphisms (SNPs) were performed using the GenABEL software. RESULTS: CCT was the most heritable endophenotype in this cohort (h2 = 0.77, p = 6×10-6), while IOP showed a heritability of 0.39 (p = 0.008). A genome-wide linkage analysis of these POAG phenotypes identified a maximum logarithm of the odds (LOD) score of 1.9 for CCT on chromosome 20 (p = 0.0016) and 1.3 for IOP on chromosome 15 (p = 0.0072). The GWAS results revealed a study-wise significant association for IOP at rs790357, which is located within DLG2 on chr11q14.1 (p = 1.02×10-7). DLG2 is involved in neuronal signaling and development, and while it has not previously been associated with IOP, it has been associated with myopia. An analysis of 12 known SNPs for IOP showed that rs12419342 in RAPSN on chromosome 11 was nominally associated in Norfolk Island (NI; p = 0.0021). For CCT, an analysis of 26 known SNPs showed rs9938149 in BANP-ZNF469 on chromosome 16 was nominally associated in NI (p = 0.002). CONCLUSIONS: These study results indicate that CCT and IOP exhibit a substantial degree of heritability in the NI pedigree, indicating a genetic component. A genome-wide linkage analysis of POAG endophenotypes did not reveal any major effect loci, but the GWASs did implicate several known loci, as well as a potential new locus in DLG2, suggesting a role for neuronal signaling in development in IOP and perhaps POAG. These results also highlight the need to target rarer variants via whole genome sequencing in this genetic isolate.

Mapping eQTLs in the Norfolk Island genetic isolate identifies candidate genes for CVD risk traits.

Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable transcripts. eQTLs were identified by genome-wide association testing of these transcripts. Testing for association between CVD risk factors (i.e., blood lipids, blood pressure, and body fat indices) and eQTLs revealed 1,712 heritable transcripts (p < 0.05) with heritability values ranging from 0.18 to 0.84. From these, we identified 200 cis-acting and 70 trans-acting eQTLs (p < 1.84 × 10(-7)) An eQTL-centric analysis of CVD risk traits revealed multiple associations, including 12 previously associated with CVD-related traits. Trait versus eQTL regression modeling identified four CVD risk candidates (NAAA, PAPSS1, NME1, and PRDX1), all of which have known biological roles in disease. In addition, we implicated several genes previously associated with CVD risk traits, including MTHFR and FN3KRP. We have successfully identified a panel of eQTLs in the NI pedigree and used this to implicate several genes in CVD risk. Future studies are required for further assessing the functional importance of these eQTLs and whether the findings here also relate to outbred populations.

Common polygenic variation contributes to risk of migraine in the Norfolk Island population.

Migraine has been defined as a common disabling primary headache disorder. Epidemiology studies have provided with the undeniable evidence of genetic components as active players in the development of the disease under a polygenic model in which multiple risk alleles exert modest individual effects. Our objective was to test the contribution of a polygenic effect to migraine risk in the Norfolk Island population using a panel of SNPs reported to be disease associated in published migraine GWAS. We also investigated whether individual SNPs were associated with gene expression levels measured in whole blood. Polygenic scores were calculated in a total of 285 related individuals (74 cases, 211 controls) from the Norfolk Island using 51 SNPs previously reported to be associated with migraine in published GWAS. The association between polygenic score and migraine case-control status was tested using logistic regression. Results indicate that a migraine polygenic risk score was associated with migraine case-control status in this population (P = 0.016). This supports the hypothesis that multiple SNPs with weak effects collectively contribute to migraine risk in this population. Amongst the SNPs included in the polygenic model, four were associated with the expression of the USMG5 gene, including rs171251 (P = 0.012). Results from this study provide evidence for a polygenic contribution to migraine risk in an isolated population and highlight specific SNPs that regulate the expression of USMG5, a gene critical for mitochondrial function.

Protocol for assessing maternal, environmental and epigenetic risk factors for dental caries in children.

BACKGROUND: Expenditure on dental and oral health services in Australia is $3.4 billion AUD annually. This is the sixth highest health cost and accounts for 7 % of total national health expenditure. Approximately 49 % of Australian children aged 6 years have caries experience in their deciduous teeth and this is rising. The aetiology of dental caries involves a complex interplay of individual, behavioural, social, economic, political and environmental conditions, and there is increasing interest in genetic predisposition and epigenetic modification. METHODS: The Oral Health Sub-study; a cross sectional study of a birth cohort began in November 2012 by examining mothers and their children who were six years old by the time of initiation of the study, which is ongoing. Data from detailed questionnaires of families from birth onwards and data on mothers' knowledge, attitudes and practices towards oral health collected at the time of clinical examination are used. Subjects' height, weight and mid-waist circumference are taken and Body Mass Index (BMI) computed, using an electronic Bio-Impedance balance. Dental caries experience is scored using the International Caries Detection and Assessment System (ICDAS). Saliva is collected for physiological measures. Salivary Deoxyribose Nucleic Acid (DNA) is extracted for genetic studies including epigenetics using the SeqCap Epi Enrichment Kit. Targets of interest are being confirmed by pyrosequencing to identify potential epigenetic markers of caries risk. DISCUSSION: This study will examine a wide range of potential determinants for childhood dental caries and evaluate inter-relationships amongst them. The findings will provide an evidence base to plan and implement improved preventive strategies.

Clinical application of targeted long read sequencing in prenatal beta-thalassemia testing and genetic counseling.

BACKGROUND: Beta thalassemia, related to HBB mutation and associated with elevated hemoglobin A2 (HbA2), is an important genetic hemoglobinopathy with high incidences of disease and carrier rates in Singapore. Carrier screening is essential to facilitate prenatal counseling and testing. However, when individuals with elevated HbA2 do not have an identifiable HBB disease-associated variant, there is ambiguity on risk to their offspring. METHODS: We describe a case report of a proband with elevated HbA2, no identifiable HBB disease-associated variant, whose partner was a beta thalassemia carrier. Through clinical HBB gene sequencing, multiplex ligation-dependent probe amplification (MLPA) analysis, as well as targeted Nanopore long read sequencing of selected genes, we performed a complete analysis of HBB including the promoter region, 5'UTR and coding gene sequence, as well as evaluation for potential modifier variants and other rare structural variants. RESULTS: This process identified that the proband was heterozygous for KLF1:c.544T>C (p.Phe182Leu), a potential functional polymorphism previously known to be associated with benign elevated HbA2 levels. The presence of disease variants in the HBB locus was excluded. CONCLUSION: This finding provided clarity and enabled family planning for the proband and her family.

Evaluating the suitability of current mitochondrial DNA interpretation guidelines for multigenerational whole mitochondrial genome comparisons.

Sanger sequencing of the mitochondrial DNA (mtDNA) control region was previously the only method available for forensic casework involving degraded samples from skeletal remains. The introduction of Next Generation Sequencing (NGS) has transformed genetic data generation and human identification using mtDNA. Whole mitochondrial genome (mtGenome) analysis is now being introduced into forensic laboratories around the world to analyze historical remains. Research into large pedigrees using the mtGenome is critical to evaluate currently available interpretation guidelines for mtDNA analysis, which were developed for comparisons using the control region. This study included mtGenomes from 225 individuals from the last four generations of the Norfolk Island (NI) genetic isolate pedigree consisting of 49 distinct maternal lineages. The data from these individuals were arranged into 2339 maternally related pairs separated by up to 18 meioses. Our results show that 97.3% of maternally related pairs were concordant at all nucleotide positions, resulting in the correct interpretation of "Cannot Exclude"; 2.7% of pairs produced an "Inconclusive" result, and there were no instances of false exclusion. While these results indicate that existing guidelines are suitable for multigenerational whole mtGenome analysis, we recommend caution be taken when classifying heteroplasmic changes as differences for human identification. Our data showed the classification of heteroplasmic changes as differences increases the prevalence of inconclusive identification by 6%, with false exclusions observed in 0.34% of pairs examined. Further studies of multigenerational pedigrees, however, are needed to validate mtGenome interpretation guidelines for historical case work to more fully utilize emerging advancements.

Multi-phenotype genome-wide association studies of the Norfolk Island isolate implicate pleiotropic loci involved in chronic kidney disease.

Chronic kidney disease (CKD) is a persistent impairment of kidney function. Genome-wide association studies (GWAS) have revealed multiple genetic loci associated with CKD susceptibility but the complete genetic basis is not yet clear. Since CKD shares risk factors with cardiovascular diseases and diabetes, there may be pleiotropic loci at play but may go undetected when using single phenotype GWAS. Here, we used multi-phenotype GWAS in the Norfolk Island isolate (n = 380) to identify new loci associated with CKD. We performed a principal components analysis on different combinations of 29 quantitative traits to extract principal components (PCs) representative of multiple correlated phenotypes. GWAS of a PC derived from glomerular filtration rate, serum creatinine, and serum urea identified a suggestive peak (pmin = 1.67 × 10-7) that mapped to KCNIP4. Inclusion of other secondary CKD measurements with these three kidney function traits identified the KCNIP4 locus with GWAS significance (pmin = 1.59 × 10-9). Finally, we identified a group of two SNPs with increased minor allele frequencies as potential functional variants. With the use of genetic isolate and the PCA-based multi-phenotype GWAS approach, we have revealed a potential pleotropic effect locus for CKD. Further studies are required to assess functional relevance of this locus.

DNA methylation in blood-Potential to provide new insights into cell biology.

Epigenetics plays a fundamental role in cellular development and differentiation; epigenetic mechanisms, such as DNA methylation, are involved in gene regulation and the exquisite nuance of expression changes seen in the journey from pluripotency to final differentiation. Thus, DNA methylation as a marker of cell identify has the potential to reveal new insights into cell biology. We mined publicly available DNA methylation data with a machine-learning approach to identify differentially methylated loci between different white blood cell types. We then interrogated the DNA methylation and mRNA expression of candidate loci in CD4+, CD8+, CD14+, CD19+ and CD56+ fractions from 12 additional, independent healthy individuals (6 male, 6 female). 'Classic' immune cell markers such as CD8 and CD19 showed expected methylation/expression associations fitting with established dogma that hypermethylation is associated with the repression of gene expression. We also observed large differential methylation at loci which are not established immune cell markers; some of these loci showed inverse correlations between methylation and mRNA expression (such as PARK2, DCP2). Furthermore, we validated these observations further in publicly available DNA methylation and RNA sequencing datasets. Our results highlight the value of mining publicly available data, the utility of DNA methylation as a discriminatory marker and the potential value of DNA methylation to provide additional insights into cell biology and developmental processes.

Genome-wide DNA methylation analysis of heavy cannabis exposure in a New Zealand longitudinal cohort.

Cannabis use is of increasing public health interest globally. Here we examined the effect of heavy cannabis use, with and without tobacco, on genome-wide DNA methylation in a longitudinal birth cohort (Christchurch Health and Development Study, CHDS). A total of 48 heavy cannabis users were selected from the CHDS cohort, on the basis of their adult exposure to cannabis and tobacco, and DNA methylation assessed from whole blood samples, collected at approximately age 28. Methylation in heavy cannabis users was assessed, relative to non-users (n = 48 controls) via the Illumina Infinium® MethylationEPIC BeadChip. We found the most differentially methylated sites in cannabis with tobacco users were in the AHRR and F2RL3 genes, replicating previous studies on the effects of tobacco. Cannabis-only users had no evidence of differential methylation in these genes, or at any other loci at the epigenome-wide significance level (P < 10-7). However, there were 521 sites differentially methylated at P < 0.001 which were enriched for genes involved in neuronal signalling (glutamatergic synapse and long-term potentiation) and cardiomyopathy. Further, the most differentially methylated loci were associated with genes with reported roles in brain function (e.g. TMEM190, MUC3L, CDC20 and SP9). We conclude that the effects of cannabis use on the mature human blood methylome differ from, and are less pronounced than, the effects of tobacco use, and that larger sample sizes are required to investigate this further.

MicroRNA Profiling in Adipose Before and After Weight Loss Highlights the Role of miR-223-3p and the NLRP3 Inflammasome.

OBJECTIVE: Adipose tissue plays a key role in obesity-related metabolic dysfunction. MicroRNA (miRNA) are gene regulatory molecules involved in intercellular and inter-organ communication. It was hypothesized that miRNA levels in adipose tissue would change after gastric bypass surgery and that this would provide insights into their role in obesity-induced metabolic dysregulation. METHODS: miRNA profiling (Affymetrix GeneChip miRNA 2.0 Array) of omental and subcutaneous adipose (n = 15 females) before and after gastric bypass surgery was performed. RESULTS: One omental and thirteen subcutaneous adipose miRNAs were significantly differentially expressed after gastric bypass, including downregulation of miR-223-3p and its antisense relative miR-223-5p in both adipose tissues. mRNA levels of miR-223-3p targets NLRP3 and GLUT4 were decreased and increased, respectively, following gastric bypass in both adipose tissues. Significantly more NLRP3 protein was observed in omental adipose after gastric bypass (P = 0.02). Significant hypomethlyation of NLRP3 and hypermethylation of miR-223 were observed in both adipose tissues after gastric bypass. In subcutaneous adipose, significant correlations were observed between both miR-223-3p and miR-223-5p and glucose and between NLRP3 mRNA and protein levels and blood lipids. CONCLUSIONS: This is the first report detailing genome-wide miRNA profiling of omental adipose before and after gastric bypass, and it further highlights the association of miR-223-3p and the NLRP3 inflammasome with obesity.

Variant Call Format-Diagnostic Annotation and Reporting Tool: A Customizable Analysis Pipeline for Identification of Clinically Relevant Genetic Variants in Next-Generation Sequencing Data.

In this article, we introduce the variant call format-diagnostic annotation and reporting tool (VCF-DART), a customized analysis pipeline tool for the rapid annotation of variants from exome or genome sequencing and the generation of reports for genetic diagnostics. VCF-DART uses custom gene lists to categorize variants into specific analysis tiers and to subcategorize them on the basis of standard parameters to facilitate the rapid interrogation of potentially pathogenic variants by human operators. The tool uses publicly available databases to identify a range of data to assist with variant classification and curation processes and includes robust logging of parameters and database versions to allow comparison of analyses performed at different times. VCF-DART-an online analysis pipeline for next-generation sequencing data-is a platform agnostic tool that leverages the use of publicly available databases to improve a laboratory's calling ability and reduce analysis times long-term. It also runs highly efficiently and scales from desk and laptop machines to servers. Overall, VCF-DART provides a simple, customizable, and entirely open-source method to identify genetic variants that may be of clinical importance in a variety of genetically important conditions.

Genome-wide allele-specific methylation is enriched at gene regulatory regions in a multi-generation pedigree from the Norfolk Island isolate.

BACKGROUND: Allele-specific methylation (ASM) occurs when DNA methylation patterns exhibit asymmetry among alleles. ASM occurs at imprinted loci, but its presence elsewhere across the human genome is indicative of wider importance in terms of gene regulation and disease risk. Here, we studied ASM by focusing on blood-based DNA collected from 24 subjects comprising a 3-generation pedigree from the Norfolk Island genetic isolate. We applied a genome-wide bisulphite sequencing approach with a genotype-independent ASM calling method to map ASM across the genome. Regions of ASM were then tested for enrichment at gene regulatory regions using Genomic Association Test (GAT) tool. RESULTS: In total, we identified 1.12 M CpGs of which 147,170 (13%) exhibited ASM (P ≤ 0.05). When including contiguous ASM signal spanning ≥ 2 CpGs, this condensed to 12,761 ASM regions (AMRs). These AMRs tagged 79% of known imprinting regions and most (98.1%) co-localised with known single nucleotide variants. Notably, miRNA and lncRNA showed a 3.3- and 1.8-fold enrichment of AMRs, respectively (P < 0.005). Also, the 5' UTR and start codons each showed a 3.5-fold enrichment of AMRs (P < 0.005). There was also enrichment of AMRs observed at subtelomeric regions of many chromosomes. Five out of 11 large AMRs localised to the protocadherin cluster on chromosome 5. CONCLUSIONS: This study shows ASM extends far beyond genomic imprinting in humans and that gene regulatory regions are hotspots for ASM. Future studies of ASM in pedigrees should help to clarify transgenerational inheritance patterns in relation to genotype and disease phenotypes.

Next Generation Sequencing Methods for Diagnosis of Epilepsy Syndromes.

Epilepsy is a neurological disorder characterized by an increased predisposition for seizures. Although this definition suggests that it is a single disorder, epilepsy encompasses a group of disorders with diverse aetiologies and outcomes. A genetic basis for epilepsy syndromes has been postulated for several decades, with several mutations in specific genes identified that have increased our understanding of the genetic influence on epilepsies. With 70-80% of epilepsy cases identified to have a genetic cause, there are now hundreds of genes identified to be associated with epilepsy syndromes which can be analyzed using next generation sequencing (NGS) techniques such as targeted gene panels, whole exome sequencing (WES) and whole genome sequencing (WGS). For effective use of these methodologies, diagnostic laboratories and clinicians require information on the relevant workflows including analysis and sequencing depth to understand the specific clinical application and diagnostic capabilities of these gene sequencing techniques. As epilepsy is a complex disorder, the differences associated with each technique influence the ability to form a diagnosis along with an accurate detection of the genetic etiology of the disorder. In addition, for diagnostic testing, an important parameter is the cost-effectiveness and the specific diagnostic outcome of each technique. Here, we review these commonly used NGS techniques to determine their suitability for application to epilepsy genetic diagnostic testing.

Critical evaluation of linear regression models for cell-subtype specific methylation signal from mixed blood cell DNA.

Epigenome-wide association studies seek to identify DNA methylation sites associated with clinical outcomes. Difference in observed methylation between specific cell-subtypes is often of interest; however, available samples often comprise a mixture of cells. To date, cell-subtype estimates have been obtained from mixed-cell DNA data using linear regression models, but the accuracy of such estimates has not been critically assessed. We evaluated linear regression performance for cell-subtype specific methylation estimation using a 450K methylation array dataset of both mixed-cell and cell-subtype sorted samples from six healthy males. CpGs associated with each cell-subtype were first identified using t-tests between groups of cell-subtype sorted samples. Subsequent reduced panels of reliably accurate CpGs were identified from mixed-cell samples using an accuracy heuristic (D). Performance was assessed by comparing cell-subtype specific estimates from mixed-cells with corresponding cell-sorted mean using the mean absolute error (MAE) and the Coefficient of Determination (R2). At the cell-subtype level, methylation levels at 3272 CpGs could be estimated to within a MAE of 5% of the expected value. The cell-subtypes with the highest accuracy were CD56+ NK (R2 = 0.56) and CD8+T (R2 = 0.48), where 23% of sites were accurately estimated. Hierarchical clustering and pathways enrichment analysis confirmed the biological relevance of the panels. Our results suggest that linear regression for cell-subtype specific methylation estimation is accurate only for some cell-subtypes at a small fraction of cell-associated sites but may be applicable to EWASs of disease traits with a blood-based pathology. Although sample size was a limitation in this study, we suggest that alternative statistical methods will provide the greatest performance improvements.