Risk factors and biomarkers of age-related macular degeneration.
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ABSTRACT:
SUBMITTER: Lambert NG
PROVIDER: S-EPMC4992630 | biostudies-literature | 2016 Sep
REPOSITORIES: biostudies-literature
Publications
Risk factors and biomarkers of age-related macular degeneration.
Lambert Nathan G NG ElShelmani Hanan H Singh Malkit K MK Mansergh Fiona C FC Wride Michael A MA Padilla Maximilian M Keegan David D Hogg Ruth E RE Ambati Balamurali K BK
Progress in retinal and eye research 20160506
A biomarker can be a substance or structure measured in body parts, fluids or products that can affect or predict disease incidence. As age-related macular degeneration (AMD) is the leading cause of blindness in the developed world, much research and effort has been invested in the identification of different biomarkers to predict disease incidence, identify at risk individuals, elucidate causative pathophysiological etiologies, guide screening, monitoring and treatment parameters, and predict d ...[more]
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Project description:Age related macular degeneration (AMD) is the leading cause of blindness in individuals older than 65 years of age. It is a multifactorial disorder and identification of risk factors enables individuals to make lifestyle choices that may reduce the risk of disease. Collaboration between geneticists, ophthalmologists, and optometrists suggests that genetic risk factors play a more significant role in AMD than previously thought. The most important genes are associated with immune system modulation and the complement system, e.g., complement factor H (CFH), factor B (CFB), factor C3, and serpin peptidase inhibitor (SERPING1). Genes associated with membrane transport, e.g., ATP-binding cassette protein (ABCR) and voltage-dependent calcium channel gamma 3 (CACNG3), the vascular system, e.g., fibroblast growth factor 2 (FGF2), fibulin-5, lysyl oxidase-like gene (LOXL1) and selectin-P (SELP), and with lipid metabolism, e.g., apolipoprotein E (APOE) and hepatic lipase (LIPC) have also been implicated. In addition, several other genes exhibit some statistical association with AMD, e.g., age-related maculopathy susceptibility protein 2 (ARMS2) and DNA excision repair protein gene (ERCC6) but more research is needed to establish their significance. Modifiable risk factors for AMD should be discussed with patients whose lifestyle and/or family history place them in an increased risk category. Furthermore, calculation of AMD risk using current models should be recommended as a tool for patient education. It is likely that AMD management in future will be increasingly influenced by assessment of genetic risk as such screening methods become more widely available.
| S-EPMC3880448 | biostudies-other
Project description: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.
| S-EPMC7155063 | biostudies-literature
Project description:In the age-related macular degeneration (AMD) 'inflammation model', local inflammation plus complement activation contributes to the pathogenesis and progression of the disease. Multiple genetic associations have now been established correlating the risk of development or progression of AMD. Stratifying patients by their AMD genetic profile may facilitate future AMD therapeutic trials resulting in meaningful clinical trial end points with smaller sample sizes and study duration.
| S-EPMC4709545 | biostudies-literature
Project description:ObjectiveAge-related macular degeneration (AMD) is a significant cause of blindness, initially characterized by the accumulation of sub-Retinal pigment epithelium (RPE) deposits, leading to progressive retinal degeneration and, eventually, irreversible vision loss. This study aimed to elucidate the differential expression of transcriptomic information in AMD and normal human RPE choroidal donor eyes and to investigate whether it could be used as a biomarker for AMD.MethodsRPE choroidal tissue samples (46 Normal samples, 38 AMD samples) were obtained from the GEO (GSE29801) database and screened for differentially expressed genes in normal and AMD patients using GEO2R and R to compare the degree of enrichment of differentially expressed genes in the GO, KEGG pathway. Firstly, we used machine learning models (LASSO, SVM algorithm) to screen disease signature genes and compare the differences between these signature genes in GSVA and immune cell infiltration. Secondly, we also performed a cluster analysis to classify AMD patients. We selected the best classification by weighted gene co-expression network analysis (WGCNA) to screen the key modules and modular genes with the strongest association with AMD. Based on the module genes, four machine models, RF, SVM, XGB, and GLM, were constructed to screen the predictive genes and further construct the AMD clinical prediction model. The accuracy of the column line graphs was evaluated using decision and calibration curves.ResultsFirstly, we identified 15 disease signature genes by lasso and SVM algorithms, which were associated with abnormal glucose metabolism and immune cell infiltration. Secondly, we identified 52 modular signature genes by WGCNA analysis. We found that SVM was the optimal machine learning model for AMD and constructed a clinical prediction model for AMD consisting of 5 predictive genes.ConclusionWe constructed a disease signature genome model and an AMD clinical prediction model by LASSO, WGCNA, and four machine models. The disease signature genes are of great reference significance for AMD etiology research. At the same time, the AMD clinical prediction model provides a reference for early clinical detection of AMD and even becomes a future census tool. In conclusion, our discovery of disease signature genes and AMD clinical prediction models may become promising new targets for the targeted treatment of AMD.
| S-EPMC10320320 | biostudies-literature
Project description:BACKGROUND/AIMS:There are limited data from India on genetic variants influencing late age-related macular degeneration (AMD). We have previously reported associations from a population-based study in India (the India age-related eye disease study (INDEYE)) of early AMD and single nucleotide polymorphisms (SNPs) in ARMS2/HTRA1 and no association with CFH, C2 or CFB. Late AMD cases were too few for meaningful analyses. We aimed to investigate SNPs for late AMD through case enrichment and extend the loci for early AMD. METHODS:Fundus images of late AMD hospital cases were independently graded by the modified Wisconsin AMD grading scheme. In total 510 cases with late AMD (14 geographic atrophy and 496 neovascular AMD (nvAMD)), 1876 with early AMD and 1176 with no signs of AMD underwent genotyping for selected SNPs. We investigated genotype and per-allele additive associations (OR and 95% CIs) with nvAMD or early AMD. Bonferroni adjusted P values are presented. RESULTS:We found associations with nvAMD for CFHY402H variant (rs1061170) (OR=1.99, 95%?CI 1.67 to 2.37, P=10-6), ARMS2 (rs10490924) (OR=2.94, 95% CI 2.45 to 3.52, P=10-9), C2 (rs547154) (OR=0.67, 95% CI 0.53 to 0.85, P=0.01), ABCA1 (rs1883025) (OR=0.77, 95% CI 0.65 to 0.92, P=0.04)?and an SNP near VEGFA (rs4711751) (OR=0.64, 95% CI 0.54 to 0.77, P=10-3). We found no associations of TLR3 (rs3775291), CFD (rs3826945), FRK (rs1999930) or LIPC (rs10468017) or APOE ?4 alleles with nvAMD or early AMD, nor between early AMD and rs1883025 or rs4711751. CONCLUSIONS:The major genetic determinants of nvAMD risk in India are similar to those in other ancestries, while findings for early AMD suggest potential differences in the pathophysiology of AMD development.
| S-EPMC6104670 | biostudies-literature
Project description:Age-related macular degeneration (AMD) is a leading cause of blindness in the United States and developed countries. Although the etiology and pathogenesis of AMD remain unknown, a complex interaction of genetic and environmental factors is thought to exist. The incidence and progression of all of the features of AMD are known to increase significantly with age. The tendency for familial aggregation and the findings of gene variation association studies implicate a significant genetic component in the development of AMD. This review summarizes in detail the AMD-related genes identified by studies on genetically engineered and spontaneously gene-mutated (naturally mutated) animals, AMD chromosomal loci identified by linkage studies, AMD-related genes identified through studies of monogenic degenerative retinal diseases, and AMD-related gene variation identified by association studies.
| S-EPMC1950336 | biostudies-literature
Project description:Age-Related Macular Degeneration (AMD) is a bilateral ocular condition resulting in irreversible vision impairment caused by the progressive loss of photoreceptors in the macula, a region at the center of the retina. The progressive loss of photoreceptor is a key feature of dry AMD but not always wet AMD, though both forms of AMD can lead to loss of vision. Regression-based biological age clocks are one of the most promising biomarkers of aging but have not yet been used in AMD. Here we conducted analyses to identify regression-based biological age clocks for the retina and explored their use in AMD using transcriptomic data consisting of a total of 453 retina samples including 105 Minnesota Grading System (MGS) level 1 samples, 175 MGS level 2, 112 MGS level 3 and 61 MGS level 4 samples, as well as 167 fibroblast samples. The clocks yielded good separation among AMD samples with increasing severity score viz., MGS1-4, regardless of whether clocks were trained in retina tissue, dermal fibroblasts, or in combined datasets. Clock application to cultured fibroblasts, embryonic stem cells, and induced Pluripotent Stem Cells (iPSCs) were consistent with age reprograming in iPSCs. Moreover, clock application to in vitro neuronal differentiation suggests broader applications. Interesting, many of the age clock genes identified include known targets mechanistically linked to AMD and aging, such as GDF11, C16ORF72, and FBN2. This study provides new observations for retina age clocks and suggests new applications for monitoring in vitro neuronal differentiation. These clocks could provide useful markers for AMD monitoring and possible intervention, as well as potential targets for in vitro screens.
| S-EPMC9244395 | biostudies-literature
Project description:Age-related macular degeneration (AMD) is the leading cause of visual impairment and blindness in the USA. Although the treatment of AMD has evolved to include laser photocoagulation, photodynamic therapy, surgical macular translocation and antiangiogenesis agents, treatment options for advanced AMD are limited. Furthermore, the dry form of AMD, albeit less devastating than the wet form, has even fewer viable treatment options. This review summarizes the various biomarkers of AMD and analyzes whether or not they may one day be exploited to determine risks of disease onset, measure progression of disease or even assess the effects of treatment of AMD. Potential biomarkers are important to identify since some might be utilized to reflect the disease state of a particular patient and to individualize therapy. Although studies have yielded promising results for nutrient and inflammatory biomarkers, these results have been inconsistent. At present, the best available markers of AMD risk are single nucleotide polymorphisms (SNPs). SNPs in complement factor H (CFH) and PLEKHA1/ARMS2/HtrA1 capture a substantial fraction of AMD risk and permit the identification of individuals at high risk of developing AMD.
| S-EPMC2000850 | biostudies-literature
Project description:PurposeAge-related macular degeneration (AMD) can result in severe vision loss and blurriness in the older population. The early and intermediate stages of AMD typically start without noticeable symptoms and can only be detected with a comprehensive eye exam. Because of the quiet onset of the disease, it is necessary to identify potential biomarkers to aid in the diagnosis, staging, and association with disease onset. Inflammasome signaling proteins are prominent biomarkers in the central nervous system, and the inflammasome has been shown to play a role in the innate inflammatory response in aging and AMD.MethodsSerum from healthy controls and AMD patients were analyzed for the protein levels of Apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC), interleukin (IL)-18 and C-reactive protein (CRP) to determine cutoff points, positive and negative predictive values, and receiver operator characteristic curves, as well as univariate and multivariate linear and logistic regression models.ResultsASC, IL-18, and CRP were elevated in the serum of AMD patients when compared to healthy controls. The area under the curve (AUC) for ASC was 0.98 with a cutoff point of 365.6 pg/mL, whereas IL-18 had an AUC of 0.73 and a cutoff point of 242.4 pg/mL, and the AUC for CRP was 0.67 with a cutoff point of 8,684,152 pg/mL. Levels of IL-18 had a statistically significant linear correlation with that of ASC with an adjusted R 2 of 0.1906, indicating that 19% of IL-18 could be explained by ASC protein levels in serum. Moreover, a logistic regression model for the diagnosis of AMD consists of ASC and having a diagnosis of hypertension, indicating that these two factors (elevated levels of ASC and a diagnosis of hypertension [HTN]) are associated with the diagnosis of AMD.ConclusionsASC, IL-18, and CRP are elevated in patients with AMD, and the protein levels of IL-18 are partially the result of ASC protein expression. Moreover, elevated protein levels of ASC in serum and a diagnosis of HTN increase the odds of patients having a diagnosis of AMD.Translational relevanceBiomarkers of AMD may be used to monitor disease risk, response to treatment and disease progression.
| S-EPMC7746957 | biostudies-literature
Project description:Age-related macular degeneration (AMD) is a leading cause of severe vision loss worldwide, with a global prevalence that is predicted to substantially increase. Identifying early biomarkers indicative of progression risk will improve our ability to assess which patients are at greatest risk of progressing from intermediate AMD (iAMD) to vision-threatening late-stage AMD. This is key to ensuring individualized management and timely intervention before substantial structural damage. Some structural biomarkers suggestive of AMD progression risk are well established, such as changes seen on color fundus photography and more recently optical coherence tomography (drusen volume, pigmentary abnormalities). Emerging biomarkers identified through multimodal imaging, including reticular pseudodrusen, hyperreflective foci, and drusen sub-phenotypes, are being intensively explored as risk factors for progression towards late-stage disease. Other structural biomarkers merit further research, such as ellipsoid zone reflectivity and choriocapillaris flow features. The measures of visual function that best detect change in iAMD and correlate with risk of progression remain under intense investigation, with tests such as dark adaptometry and cone-specific contrast tests being explored. Evidence on blood and plasma markers is preliminary, but there are indications that changes in levels of C-reactive protein and high-density lipoprotein cholesterol may be used to stratify patients and predict risk. With further research, some of these biomarkers may be used to monitor progression. Emerging artificial intelligence methods may help evaluate and validate these biomarkers; however, until we have large and well-curated longitudinal data sets, using artificial intelligence effectively to inform clinical trial design and detect outcomes will remain challenging. This is an exciting area of intense research, and further work is needed to establish the most promising biomarkers for disease progression and their use in clinical care and future trials. Ultimately, a multimodal approach may yield the most accurate means of monitoring and predicting future progression towards vision-threatening, late-stage AMD.
| S-EPMC10640447 | biostudies-literature