EpiDiP/NanoDiP: a versatile unsupervised machine learning edge computing platform for epigenomic tumour diagnostics.

DNA methylation analysis based on supervised machine learning algorithms with static reference data, allowing diagnostic tumour typing with unprecedented precision, has quickly become a new standard of care. Whereas genome-wide diagnostic methylation profiling is mostly performed on microarrays, an increasing number of institutions additionally employ nanopore sequencing as a faster alternative. In addition, methylation-specific parallel sequencing can generate methylation and genomic copy number data. Given these diverse approaches to methylation profiling, to date, there is no single tool that allows (1) classification and interpretation of microarray, nanopore and parallel sequencing data, (2) direct control of nanopore sequencers, and (3) the integration of microarray-based methylation reference data. Furthermore, no software capable of entirely running in routine diagnostic laboratory environments lacking high-performance computing and network infrastructure exists. To overcome these shortcomings, we present EpiDiP/NanoDiP as an open-source DNA methylation and copy number profiling suite, which has been benchmarked against an established supervised machine learning approach using in-house routine diagnostics data obtained between 2019 and 2021. Running locally on portable, cost- and energy-saving system-on-chip as well as gpGPU-augmented edge computing devices, NanoDiP works in offline mode, ensuring data privacy. It does not require the rigid training data annotation of supervised approaches. Furthermore, NanoDiP is the core of our public, free-of-charge EpiDiP web service which enables comparative methylation data analysis against an extensive reference data collection. We envision this versatile platform as a useful resource not only for neuropathologists and surgical pathologists but also for the tumour epigenetics research community. In daily diagnostic routine, analysis of native, unfixed biopsies by NanoDiP delivers molecular tumour classification in an intraoperative time frame.

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.

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.

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.

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.

Capturing SNP Association across the NK Receptor and HLA Gene Regions in Multiple Sclerosis by Targeted Penalised Regression Models.

Conventional genome-wide association studies (GWASs) of complex traits, such as Multiple Sclerosis (MS), are reliant on per-SNP p-values and are therefore heavily burdened by multiple testing correction. Thus, in order to detect more subtle alterations, ever increasing sample sizes are required, while ignoring potentially valuable information that is readily available in existing datasets. To overcome this, we used penalised regression incorporating elastic net with a stability selection method by iterative subsampling to detect the potential interaction of loci with MS risk. Through re-analysis of the ANZgene dataset (1617 cases and 1988 controls) and an IMSGC dataset as a replication cohort (1313 cases and 1458 controls), we identified new association signals for MS predisposition, including SNPs above and below conventional significance thresholds while targeting two natural killer receptor loci and the well-established HLA loci. For example, rs2844482 (98.1% iterations), otherwise ignored by conventional statistics (p = 0.673) in the same dataset, was independently strongly associated with MS in another GWAS that required more than 40 times the number of cases (~45 K). Further comparison of our hits to those present in a large-scale meta-analysis, confirmed that the majority of SNPs identified by the elastic net model reached conventional statistical GWAS thresholds (p < 5 × 10-8) in this much larger dataset. Moreover, we found that gene variants involved in oxidative stress, in addition to innate immunity, were associated with MS. Overall, this study highlights the benefit of using more advanced statistical methods to (re-)analyse subtle genetic variation among loci that have a biological basis for their contribution to disease risk.

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.

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.

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.

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.

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.

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.

Genome-wide DNA methylation changes in CD19+ B cells from relapsing-remitting multiple sclerosis patients.

Multiple Sclerosis (MS) is an inflammatory and neurodegenerative disease of the central nervous system. The inflammatory process in MS is driven by both T and B cells and current therapies are targeted to each of these cell types. Epigenetic mechanisms may provide a valuable link between genes and environment. DNA methylation is the best studied epigenetic mechanism and is recognized as a potential contributor to MS risk. The objective of this study was to identify DNA methylation changes associated with MS in CD19+ B-cells. We performed an epigenome-wide association analysis of DNA methylation in the CD19+ B-cells from 24 patients with relapsing-remitting MS on various treatments and 24 healthy controls using Illumina 450 K arrays. A large differentially methylated region (DMR) was observed at the lymphotoxin alpha (LTA) locus. This region was hypermethylated and contains 19 differentially methylated positions (DMPs) spanning 860 bp, all of which are located within the transcriptional start site. We also observed smaller DMRs at 4 MS-associated genes: SLC44A2, LTBR, CARD11 and CXCR5. These preliminary findings suggest that B-cell specific DNA-methylation may be associated with MS risk or response to therapy, specifically at the LTA locus. Development of B-cell specific epigenetic therapies is an attractive new avenue of research in MS treatment. Further studies are now required to validate these findings and understand their functional significance.

Exome Sequencing Diagnoses X-Linked Moesin-Associated Immunodeficiency in a Primary Immunodeficiency Case.

Background: We investigated the molecular etiology of a young male proband with confirmed immunodeficiency of unknown cause, presenting with recurrent bacterial and Varicella zoster viral infections in childhood and persistent lymphopenia into early adulthood. Aim: To identify causative functional genetic variants related to an undiagnosed primary immunodeficiency. Method: Whole genome microarray copy number variant (CNV) analysis was performed on the proband followed by whole exome sequencing (WES) and trio analysis of the proband and family members. A >4 kbp deletion identified by repeated CNV analysis of exome sequencing data along with three damaging missense single nucleotide variants were validated by Sanger sequencing in all family members. Confirmation of the causative role of the candidate gene was performed by qPCR and Western Blot analyses on the proband, family members and a healthy control. Results: CNV identified our previously reported interleukin 25 amplification in the proband; however, the variant was not validated to be a candidate gene for immunodeficiency. WES trio analysis, data filtering and in silico prediction identified a novel, damaging (SIFT: 0; Polyphen 1; Grantham score: 101) and disease-causing (MutationTaster) single base mutation in the X chromosome (c.511C > T p.Arg171Trp) MSN gene not identified in the UCSC Genome Browser database. The mutation was validated by Sanger sequencing, confirming the proband was hemizygous X-linked recessive (-/T) at this locus and inherited the affected T allele from his non-symptomatic carrier mother (C/T), with other family members (father, sister) confirmed to be wild type (C/C). Western Blot analysis demonstrated an absence of moesin protein in lymphocytes derived from the proband, compared with normal expression in lymphocytes derived from the healthy control, father and mother. qPCR identified significantly lower MSN mRNA transcript expression in the proband compared to an age- and sex-matched healthy control subject in whole blood (p = 0.02), and lymphocytes (p = 0.01). These results confirmed moesin deficiency in the proband, directly causative of his immunodeficient phenotype. Conclusion: These findings confirm X-linked moesin-associated immunodeficiency in a proband previously undiagnosed up to 24 years of age. This study also highlights the utility of WES for the diagnosis of rare or novel forms of primary immunodeficiency disease.

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.

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.