Single nucleotide polymorphism rs13079080 is associated with differential regulation of the succinate receptor 1 (SUCNR1) gene by miRNA-4470.

Item does not contain fulltextOxidative stress is a feature of many common diseases. It leads to excessive formation and subsequent release of the mitochondrial metabolite succinate, which acts as a signalling molecule through binding the succinate receptor (SUCNR1). Recently, a potential role for SUCNR1 was proposed in age-related macular degeneration (AMD), a common cause of vision loss in the elderly associated with increased oxidative stress. Here, we evaluated the potential effect of genetic variants in SUCNR1 on its expression through differential micro-RNA (miRNA) binding to target mRNA, and investigated the relevance of altered SUCNR1 expression in AMD pathogenesis. We analysed common SUCNR1 SNPs for potential miRNA binding sites and identified rs13079080, located in the 3'-UTR and binding site for miRNA-4470. Both miRNA-4470 and SUCNR1 were found to be expressed in human retina. Moreover, using a luciferase reporter assay, a 60% decrease in activity was observed when miRNA-4470 was co-expressed with the C allele compared to the T allele of rs13079080. Finally, genotyping rs13079080 in an AMD case-control cohort revealed a protective effect of the TT genotype on AMD compared to the CC genotype (p = 0.007, odds ratio = 0.66). However, the association was not confirmed in the case-control study of the International AMD Genomics Consortium. Our study demonstrates that the T allele of rs13079080 in SUCNR1 disrupts a binding site for miRNA-4470, potentially increasing SUCNR1 expression and consequently increasing the capacity of sensing and dealing with oxidative stress. Therefore, it would be worthwhile assessing the relevance of rs13079080 in other oxidative stress-associated diseases in future studies.1 november 201

Whole-Exome Sequencing in Age-Related Macular Degeneration Identifies Rare Variants in COL8A1, a Component of Bruch's Membrane

Purpose: Genome-wide association studies and targeted sequencing studies of candidate genes have identified common and rare variants that are associated with age-related macular degeneration (AMD). Whole-exome sequencing (WES) studies allow a more comprehensive analysis of rare coding variants across all genes of the genome and will contribute to a better understanding of the underlying disease mechanisms. To date, the number of WES studies in AMD case-control cohorts remains scarce and sample sizes are limited. To scrutinize the role of rare protein-altering variants in AMD cause, we performed the largest WES study in AMD to date in a large European cohort consisting of 1125 AMD patients and 1361 control participants. Design: Genome-wide case-control association study of WES data. Participants: One thousand one hundred twenty-five AMD patients and 1361 control participants. Methods: A single variant association test of WES data was performed to detect variants that are associated individually with AMD. The cumulative effect of multiple rare variants with 1 gene was analyzed using a gene-based CMC burden test. Immunohistochemistry was performed to determine the localization of the Col8a1 protein in mouse eyes. Main Outcome Measures: Genetic variants associated with AMD. Results: We detected significantly more rare protein-altering variants in the COL8A1 gene in patients (22/2250 alleles [

Ophthalmology

OBJECTIVE: In the current study we aimed to identify metabolites associated with age-related macular degeneration (AMD) by performing the largest metabolome association analysis in AMD to date. In addition, we aimed to determine the effect of AMD-associated genetic variants on metabolite levels, and aimed to investigate associations between the identified metabolites and activity of the complement system, one of the main AMD-associated disease pathways. DESIGN: Case-control assocation analysis of metabolomics data. SUBJECTS: 2,267 AMD cases and 4,266 controls from five European cohorts. METHODS: Metabolomics was performed using a high-throughput H-NMR metabolomics platform, which allows the quantification of 146 metabolite measurements and 79 derivative values. Metabolome-AMD associations were studied using univariate logistic regression analyses. The effect of 52 AMD-associated genetic variants on the identified metabolites was investigated using linear regression. In addition, associations between the identified metabolites and activity of the complement pathway (defined by the C3d/C3 ratio) were investigated using linear regression. MAIN OUTCOME MEASURES: Metabolites associated with AMD RESULTS: We identified 60 metabolites that were significantly associated with AMD, including increased levels of large and extra-large HDL subclasses and decreased levels of VLDL, amino acids and citrate. Out of 52 AMD-associated genetic variants, seven variants were significantly associated with 34 of the identified metabolites. The strongest associations were identified for genetic variants located in or near genes involved in lipid metabolism (ABCA1, CETP, APOE, LIPC) with metabolites belonging to the large and extra-large HDL subclasses. In addition, 57 out of 60 metabolites were significantly associated with complement activation levels, and these associations were independent of AMD status. Increased large and extra-large HDL levels and decreased VLDL and amino acid levels were associated with increased complement activation. CONCLUSIONS: Lipoprotein levels were associated with AMD-associated genetic variants, while decreased essential amino acids may point to nutritional deficiencies in AMD. We observed strong associations between the vast majority of the AMD-associated metabolites and systemic complement activation levels, independent of AMD status. This may indicate biological interactions between the main AMD disease pathways, and suggests that multiple pathways may need to be targeted simultaneously for successful treatment of AMD

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

Genetic biomarkers for precision medicine in age-related macular degeneration

Contains fulltext : 194335.pdf (publisher's version ) (Open Access)Age-related macular degeneration affects 1 in 10 elderly people. It is a progressive disease that leads to vision loss, severely impacting quality of life. Unfortunately, response to treatment is highly variable and in 10% of the patients treatment is not effective at all. A better understanding of the molecular players involved in treatment response would allow for highly personalized treatment strategies and could potentially benefit millions of patients worldwide. In this thesis, we identified several genetic variants associated with worse treatment response outcomes. Our results may therefore be used to improve patient care through personalized treatment.Radboud University, 17 september 2018Promotores : Hollander, A.I. den, Hoyng, C.B. Co-promotor : Jong, E.K. de208 p

Genetic biomarkers for precision medicine in age-related macular degeneration

Age-related macular degeneration affects 1 in 10 elderly people. It is a progressive disease that leads to vision loss, severely impacting quality of life. Unfortunately, response to treatment is highly variable and in 10% of the patients treatment is not effective at all. A better understanding of the molecular players involved in treatment response would allow for highly personalized treatment strategies and could potentially benefit millions of patients worldwide. In this thesis, we identified several genetic variants associated with worse treatment response outcomes. Our results may therefore be used to improve patient care through personalized treatment

Exploring the Use of Molecular Biomarkers for Precision Medicine in Age-Related Macular Degeneration

Precision medicine aims to improve patient care by adjusting medication to each patient's individual needs. Age-related macular degeneration (AMD) is a heterogeneous eye disease in which several pathways are involved, and the risk factors driving the disease differ per patient. As a consequence, precision medicine holds promise for improved management of this disease, which is nowadays a main cause of vision loss in the elderly. In this review, we provide an overview of the studies that have evaluated the use of molecular biomarkers to predict response to treatment in AMD. We predominantly focus on genetic biomarkers, but also include studies that examined circulating or eye fluid biomarkers in treatment response. This involves studies on treatment response to dietary supplements, response to anti-vascular endothelial growth factor, and response to complement inhibitors. In addition, we highlight promising new therapies that have been or are currently being tested in clinical trials and discuss the molecular studies that can help identify the most suitable patients for these upcoming therapeutic approaches

Risk factors for progression of age-related macular degeneration

Contains fulltext : 219118.pdf (Publisher’s version ) (Open Access)PURPOSE: Age-related macular degeneration (AMD) is a degenerative disease of the macula, often leading to progressive vision loss. The rate of disease progression can vary among individuals and has been associated with multiple risk factors. In this review, we provide an overview of the current literature investigating phenotypic, demographic, environmental, genetic, and molecular risk factors, and propose the most consistently identified risk factors for disease progression in AMD based on these studies. Finally, we describe the potential use of these risk factors for personalised healthcare. RECENT FINDINGS: While phenotypic risk factors such as drusen and pigment abnormalities become more important to predict disease progression during the course of the disease, demographic, environmental, genetic and molecular risk factors are more valuable at earlier disease stages. Demographic and environmental risk factors such as age and smoking are consistently reported to be related to disease progression, while other factors such as sex, body mass index (BMI) and education are less often associated. Of all known AMD variants, variants that are most consistently reported with disease progression are rs10922109 and rs570618 in CFH, rs116503776 in C2/CFB/SKIV2L, rs3750846 in ARMS2/HTRA1 and rs2230199 in C3. However, it seems likely that other AMD variants also contribute to disease progression but to a lesser extent. Rare variants have probably a large effect on disease progression in highly affected families. Furthermore, current prediction models do not include molecular risk factors, while these factors can be measured accurately in the blood. Possible promising molecular risk factors are High-Density Lipoprotein Cholesterol (HDL-C), Docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), zeaxanthin and lutein. SUMMARY: Phenotypic, demographic, environmental, genetic and molecular risk factors can be combined in prediction models to predict disease progression, but the selection of the proper risk factors for personalised risk prediction will differ among individuals and is dependent on their current disease stage. Future prediction models should include a wider set of genetic variants to determine the genetic risk more accurately, and rare variants should be taken into account in highly affected families. In addition, adding molecular factors in prediction models may lead to preventive strategies and personalised advice