Exploration and detection of potential regulatory variants in refractive error GWAS

The Genetic Determinants of Axial Length: From Microphthalmia to High Myopia in Childhood

The axial length of the eye is critical for normal visual function by enabling light to precisely focus on the retina. The mean axial length of the adult human eye is 23.5 mm, but the molecular mechanisms regulating ocular axial length remain poorly understood. Underdevelopment can lead to microphthalmia (defined as a small eye with an axial length of less than 19 mm at 1 year of age or less than 21 mm in adulthood) within the first trimester of pregnancy. However, continued overgrowth can lead to axial high myopia (an enlarged eye with an axial length of 26.5 mm or more) at any age. Both conditions show high genetic and phenotypic heterogeneity associated with significant visual morbidity worldwide. More than 90 genes can contribute to microphthalmia, and several hundred genes are associated with myopia, yet diagnostic yields are low. Crucially, the genetic pathways underpinning the specification of eye size are only now being discovered, with evidence suggesting that shared molecular pathways regulate under- or overgrowth of the eye. Improving our mechanistic understanding of axial length determination will help better inform us of genotype-phenotype correlations in both microphthalmia and myopia, dissect gene-environment interactions in myopia, and develop postnatal therapies that may influence overall eye growth.

Education interacts with genetic variants near GJD2, RBFOX1, LAMA2, KCNQ5 and LRRC4C to confer susceptibility to myopia

Myopia most often develops during school age, with the highest incidence in countries with intensive education systems. Interactions between genetic variants and educational exposure are hypothesized to confer susceptibility to myopia, but few such interactions have been identified. Here, we aimed to identify genetic variants that interact with education level to confer susceptibility to myopia. Two groups of unrelated participants of European ancestry from UK Biobank were studied. A 'Stage-I' sample of 88,334 participants whose refractive error (avMSE) was measured by autorefraction and a 'Stage-II' sample of 252,838 participants who self-reported their age-of-onset of spectacle wear (AOSW) but who did not undergo autorefraction. Genetic variants were prioritized via a 2-step screening process in the Stage-I sample: Step 1 was a genome-wide association study for avMSE; Step 2 was a variance heterogeneity analysis for avMSE. Genotype-by-education interaction tests were performed in the Stage-II sample, with University education coded as a binary exposure. On average, participants were 58 years-old and left full-time education when they were 18 years-old; 35% reported University level education. The 2-step screening strategy in the Stage-I sample prioritized 25 genetic variants (GWAS P < 1e-04; variance heterogeneity P < 5e-05). In the Stage-II sample, 19 of the 25 (76%) genetic variants demonstrated evidence of variance heterogeneity, suggesting the majority were true positives. Five genetic variants located near GJD2, RBFOX1, LAMA2, KCNQ5 and LRRC4C had evidence of a genotype-by-education interaction in the Stage-II sample (P < 0.002) and consistent evidence of a genotype-by-education interaction in the Stage-I sample. For all 5 variants, University-level education was associated with an increased effect of the risk allele. In this cohort, additional years of education were associated with an enhanced effect of genetic variants that have roles including axon guidance and the development of neuronal synapses and neural circuits.

Genome-wide prioritization reveals novel gene signatures associated with cardiotoxic effects of tyrosine kinase inhibitors

Tyrosine kinase inhibitors (TKIs) are characterized as multi-targeted anticancer agents that lack specificity, leading to cardiovascular adverse effects. To date, there are no reliable means to predict the cardiotoxicity of TKIs under development. The present study assessed the usual variants of genes to determine the molecular targets of TKIs associated with heart failure (HF). Gene or gene products affected by TKIs were assessed using the Drug Gene Interaction Database. These genes were investigated in genome-wide association studies (GWAS) datasets associated with HF at a genome-wide significant level (P<1×10⁻⁵). Subsequently, single-nucleotide polymorphisms (SNPs) that reached the established GWAS threshold (P<5×10⁻⁸) were investigated for genome-wide significance. Based on a threshold score of 3, nine gene loci yielded associations according to their biological function using RegulomeDB. Finally, comprehensive functional analysis of SNPs was performed using bioinformatics databases to identify potential drug targets. Using rSNPBase, rs7115242, rs143160639 and rs870064 were found to interfere with proximal transcription regulation, while rs7115242, rs143160639 and rs117153772 were involved in distal regulation, and most SNPs participated in post-transcriptional RNA binding protein-mediated regulation. rs191188930 on platelet-derived growth factor receptor (PDGFR) α was associated with numerous TKI drugs, including sunitinib, pazopanib, sorafenib, dasatinib and nilotinib. Using RegulomeDB and HaploReg v4.1, rs191188930 was predicted to be located in enhancer histone markers. PhenoScanner GWAS analysis revealed that rs191188930 was associated with other diseases or phenotypes, in addition to HF. Genotype-Tissue Expression analysis indicated that the PDGFRα gene had the highest median expression in ‘Cells-Transformed fibroblasts’, and the Search Tool for the Retrieval of Interacting Genes/Proteins revealed the protein-protein interaction network of PDGFRα. The present findings demonstrated the overlap of TKI-induced genes and those mediating HF risk, suggesting molecular mechanisms potentially responsible for TKI-induced HF risk. Additionally, the present genetic study may be helpful to further investigate off-target drug effects.

The nanophthalmos protein TMEM98 inhibits MYRF self-cleavage and is required for eye size specification

The precise control of eye size is essential for normal vision. TMEM98 is a highly conserved and widely expressed gene which appears to be involved in eye size regulation. Mutations in human TMEM98 are found in patients with nanophthalmos (very small eyes) and variants near the gene are associated in population studies with myopia and increased eye size. As complete loss of function mutations in mouse Tmem98 result in perinatal lethality, we produced mice deficient for Tmem98 in the retinal pigment epithelium (RPE), where Tmem98 is highly expressed. These mice have greatly enlarged eyes that are very fragile with very thin retinas, compressed choroid and thin sclera. To gain insight into the mechanism of action we used a proximity labelling approach to discover interacting proteins and identified MYRF as an interacting partner. Mutations of MYRF are also associated with nanophthalmos. The protein is an endoplasmic reticulum-tethered transcription factor which undergoes autoproteolytic cleavage to liberate the N-terminal part which then translocates to the nucleus where it acts as a transcription factor. We find that TMEM98 inhibits the self-cleavage of MYRF, in a novel regulatory mechanism. In RPE lacking TMEM98, MYRF is ectopically activated and abnormally localised to the nuclei. Our findings highlight the importance of the interplay between TMEM98 and MYRF in determining the size of the eye.

Regulatory variants: from detection to predicting impact

Variants within non-coding genomic regions can greatly affect disease. In recent years, increasing focus has been given to these variants, and how they can alter regulatory elements, such as enhancers, transcription factor binding sites and DNA methylation regions. Such variants can be considered regulatory variants. Concurrently, much effort has been put into establishing international consortia to undertake large projects aimed at discovering regulatory elements in different tissues, cell lines and organisms, and probing the effects of genetic variants on regulation by measuring gene expression. Here, we describe methods and techniques for discovering disease-associated non-coding variants using sequencing technologies. We then explain the computational procedures that can be used for annotating these variants using the information from the aforementioned projects, and prediction of their putative effects, including potential pathogenicity, based on rule-based and machine learning approaches. We provide the details of techniques to validate these predictions, by mapping chromatin-chromatin and chromatin-protein interactions, and introduce Clustered Regularly Interspaced Short Palindromic Repeats-Associated Protein 9 (CRISPR-Cas9) technology, which has already been used in this field and is likely to have a big impact on its future evolution. We also give examples of regulatory variants associated with multiple complex diseases. This review is aimed at bioinformaticians interested in the characterization of regulatory variants, molecular biologists and geneticists interested in understanding more about the nature and potential role of such variants from a functional point of views, and clinicians who may wish to learn about variants in non-coding genomic regions associated with a given disease and find out what to do next to uncover how they impact on the underlying mechanisms.

Myopia genetics in genome-wide association and post-genome-wide association study era

Genome-wide association studies (GWAS) of myopia and refractive error have generated exciting results and identified novel risk-associated loci. However, the interpretation of the findings of GWAS of complex diseases is not straightforward and has remained challenging. This review provides a brief summary of the main focus on the advantages and limitations of GWAS of myopia, with potential strategies that may contribute to further insight into the genetics of myopia in the post-GWAS or omics era.

Genome-Wide SNP Discovery in Indigenous Cattle Breeds of South Africa

Single nucleotide polymorphism arrays have created new possibilities for performing genome-wide studies to detect genomic regions harboring sequence variants that affect complex traits. However, the majority of validated SNPs for which allele frequencies have been estimated are limited primarily to European breeds. The objective of this study was to perform SNP discovery in three South African indigenous breeds (Afrikaner, Drakensberger, and Nguni) using whole genome sequencing. DNA was extracted from blood and hair samples, quantified and prepared at 50 ng/μl concentration for sequencing at the Agricultural Research Council Biotechnology Platform using an Illumina HiSeq 2500. The fastq files were used to call the variants using the Genome Analysis Tool Kit. A total of 1,678,360 were identified as novel using Run 6 of 1000 Bull Genomes Project. Annotation of the identified variants classified them into functional categories. Within the coding regions, about 30% of the SNPs were non-synonymous substitutions that encode for alternate amino acids. The study of distribution of SNP across the genome identified regions showing notable differences in the densities of SNPs among the breeds and highlighted many regions of functional significance. Gene ontology terms identified genes such as MLANA, SYT10, and CDC42EP5 that have been associated with coat color in mouse, and ADAMS3, DNAJC3, and PAG5 genes have been associated with fertility in cattle. Further analysis of the variants detected 688 candidate selective sweeps (ZHp Z-scores ≤ -4) across all three breeds, of which 223 regions were assigned as being putative selective sweeps (ZHp scores ≤-5). We also identified 96 regions with extremely low ZHp Z-scores (≤-6) in Afrikaner and Nguni. Genes such as KIT and MITF that have been associated with skin pigmentation in cattle and CACNA1C, which has been associated with biopolar disorder in human, were identified in these regions. This study provides the first analysis of sequence data to discover SNPs in indigenous South African cattle breeds. The information will play an important role in our efforts to understand the genetic history of our cattle and in designing appropriate breed improvement programmes.

Potential Mutations in Chinese Pathologic Myopic Patients and Contributions to Phenotype

Purpose

Pathologic myopia is a leading cause of visual impairment in East Asia. The aim of this study was to investigate the potential mutations in Chinese pathologic myopic patients and to analyze the correlations between genotype and clinical phenotype.

Method

One hundred and three patients with pathologic myopia and one hundred and nine unrelated healthy controls were recruited from Zhongshan Ophthalmic Center. Detailed clinical data, including ultra-widefield retinal images, measurements of best-corrected visual acuity, axial length, refractive error and ophthalmic examination results, were obtained. Blood samples were collected for high-throughput DNA targeted sequencing. Based on the screening results, phenotype-genotype correlations were analyzed.

Results

The study included 196 eyes of 103 patients (36 men and 67 women) with an average age of 52.19 (38.92 – 65.46) years, an average refractive error of -11.80 D (-16.38 – -7.22) and a mean axial length of 28.26 mm (25.79 – 30.73). The patients were subdivided into three groups: myopic chorioretinal atrophy (190 eyes of 101 patients), myopic choroidal neovascularization (17 eyes of 15 patients), and myopic traction retinopathy (71 eyes of 61 patients). Systematic analysis of variants in the 255 genes revealed six potential pathogenic mutations: PEX7, OCA2, LRP5 (rs545382, c.1647T>C), TSPAN12 (rs41623, c.765G>T), RDH5 (rs3138142, c.423C>T) and TTC21B (rs80225158, c.2385G>C). OCA2 mutations were primarily observed in patients with myopic traction maculopathy.

Conclusion

Genetic alterations contribute to various clinical characteristics in Chinese pathologic myopic patients. The study may provide new insights into the etiology of pathologic myopia and potential targets for therapeutic interventions.

Replication and validation of genetic polymorphisms associated with survival after allogeneic blood or marrow transplant

Multiple candidate gene-association studies of non-HLA single-nucleotide polymorphisms (SNPs) and outcomes after blood or marrow transplant (BMT) have been conducted. We identified 70 publications reporting 45 SNPs in 36 genes significantly associated with disease-related mortality, progression-free survival, transplant-related mortality, and/or overall survival after BMT. Replication and validation of these SNP associations were performed using DISCOVeRY-BMT (Determining the Influence of Susceptibility COnveying Variants Related to one-Year mortality after BMT), a well-powered genome-wide association study consisting of 2 cohorts, totaling 2888 BMT recipients with acute myeloid leukemia, acute lymphoblastic leukemia, or myelodysplastic syndrome, and their HLA-matched unrelated donors, reported to the Center for International Blood and Marrow Transplant Research. Gene-based tests were used to assess the aggregate effect of SNPs on outcome. None of the previously reported significant SNPs replicated at P < .05 in DISCOVeRY-BMT. Validation analyses showed association with one previously reported donor SNP at P < .05 and survival; more associations would be anticipated by chance alone. No gene-based tests were significant at P < .05. Functional annotation with publicly available data shows these candidate SNPs most likely do not have biochemical function; only 13% of candidate SNPs correlate with gene expression or are predicted to impact transcription factor binding. Of these, half do not impact the candidate gene of interest; the other half correlate with expression of multiple genes. These findings emphasize the peril of pursing candidate approaches and the importance of adequately powered tests of unbiased genome-wide associations with BMT clinical outcomes given the ultimate goal of improving patient outcomes.

Prioritizing single-nucleotide polymorphisms and variants associated with clinical mastitis

Next-generation sequencing technology has provided resources to easily explore and identify candidate single-nucleotide polymorphisms (SNPs) and variants. However, there remains a challenge in identifying and inferring the causal SNPs from sequence data. A problem with different methods that predict the effect of mutations is that they produce false positives. In this hypothesis, we provide an overview of methods known for identifying causal variants and discuss the challenges, fallacies, and prospects in discerning candidate SNPs. We then propose a three-point classification strategy, which could be an additional annotation method in identifying causalities.