Genetic Risk in Families with Age-Related Macular Degeneration

PURPOSE: To determine the contribution of common and rare genetic risk variants in families with age-related macular degeneration (AMD). DESIGN: Case-control study. PARTICIPANTS: A family cohort (355 affected and 342 unaffected family members from 144 families with AMD) and an unrelated case-control cohort (1078 patients, 952 controls), recruited from the European Genetic Database. METHODS: Genetic data of both cohorts were filtered for carriership of rare genetic variants in the coding and splice-site regions of the complement factor H (CFH) and complement factor I (CFI) genes, and 52 AMD-associated variants were extracted for calculation of genetic risk scores (GRS). To compare GRSs between familial and nonfamilial rare CFH and CFI variant carriers and noncarriers and between AMD disease stages, we performed a 2-way analysis of variance, with Bonferroni correction for multiple testing. Within families with AMD carrying rare CFH and CFI variants, we analyzed segregation patterns by calculating the proportion of affected among carriers. MAIN OUTCOME MEASURES: GRSs and segregation of rare CFH and CFI variants. RESULTS: We observed higher GRSs in familial versus nonfamilial individuals without rare CFH and CFI variants: mean GRS, 1.76 (standard error [SE], 0.08) versus 0.83 (SE, 0.03; P < 0.001). In 51 of 144 families (35.4%), rare CFH and CFI variants were identified. Within the AMD family cohort, carriers of rare CFH and CFI variants showed lower GRSs compared with noncarriers (mean GRS, 1.05 [SE, 0.23] vs. 1.76 [SE, 0.08]; P = 0.02). The proportion of affected family members with a high GRS was 57.3% (176/307). Of the affected family members with a low or intermediate GRS, 40.0% carried rare CFH or CFI variants. Among carriers of 11 rare CFH or CFI variants, the proportion affected by AMD was more than 75%. CONCLUSIONS: Genetic risk in families with AMD often is attributed to high GRSs based on common variants. However, in part of the families with a low or intermediate GRS, rare CFH and CFI variants contributed to disease development. We recommend computing GRSs and sequencing the CFH and CFI genes in families with AMD, in particular in the light of ongoing gene-specific clinical trials

Extinction times in the subcritical stochastic SIS logistic epidemic

Many real epidemics of an infectious disease are not straightforwardly super- or sub-critical, and the understanding of epidemic models that exhibit such complexity has been identified as a priority for theoretical work. We provide insights into the near-critical regime by considering the stochastic SIS logistic epidemic, a well-known birth-and-death chain used to model the spread of an epidemic within a population of a given size $N$. We study the behaviour of the process as the population size $N$ tends to infinity. Our results cover the entire subcritical regime, including the "barely subcritical" regime, where the recovery rate exceeds the infection rate by an amount that tends to 0 as $N \to \infty$ but more slowly than $N^{-1/2}$. We derive precise asymptotics for the distribution of the extinction time and the total number of cases throughout the subcritical regime, give a detailed description of the course of the epidemic, and compare to numerical results for a range of parameter values. We hypothesise that features of the course of the epidemic will be seen in a wide class of other epidemic models, and we use real data to provide some tentative and preliminary support for this theory.Comment: Revised; 34 pages; 6 figure

Key questions for modelling COVID-19 exit strategies

Combinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement lockdown exit strategies that allow restrictions to be relaxed while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, will allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. The roadmap requires a global collaborative effort from the scientific community and policy-makers, and is made up of three parts: i) improve estimation of key epidemiological parameters; ii) understand sources of heterogeneity in populations; iii) focus on requirements for data collection, particularly in Low-to-Middle-Income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health

PLoS One

Age-related macular degeneration (AMD) is a common, progressive multifactorial vision-threatening disease and many genetic and environmental risk factors have been identified. The risk of AMD is influenced by lifestyle and diet, which may be reflected by an altered metabolic profile. Therefore, measurements of metabolites could identify biomarkers for AMD, and could aid in identifying high-risk individuals. Hypothesis-free technologies such as metabolomics have a great potential to uncover biomarkers or pathways that contribute to disease pathophysiology. To date, only a limited number of metabolomic studies have been performed in AMD. Here, we aim to contribute to the discovery of novel biomarkers and metabolic pathways for AMD using a targeted metabolomics approach of 188 metabolites. This study focuses on non-advanced AMD, since there is a need for biomarkers for the early stages of disease before severe visual loss has occurred. Targeted metabolomics was performed in 72 patients with early or intermediate AMD and 72 control individuals, and metabolites predictive for AMD were identified by a sparse partial least squares discriminant analysis. In our cohort, we identified four metabolite variables that were most predictive for early and intermediate stages of AMD. Increased glutamine and phosphatidylcholine diacyl C28:1 levels were detected in non-advanced AMD cases compared to controls, while the rate of glutaminolysis and the glutamine to glutamate ratio were reduced in non-advanced AMD. The association of glutamine with non-advanced AMD corroborates a recent report demonstrating an elevated glutamine level in early AMD using a different metabolomics technique. In conclusion, this study indicates that metabolomics is a suitable method for the discovery of biomarker candidates for AMD. In the future, larger metabolomics studies could add to the discovery of novel biomarkers in yet unknown AMD pathways and expand our insights in AMD pathophysiology

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

Statistical physics of vaccination

Historically, infectious diseases caused considerable damage to human societies, and they continue to do so today. To help reduce their impact, mathematical models of disease transmission have been studied to help understand disease dynamics and inform prevention strategies. Vaccination–one of the most important preventive measures of modern times–is of great interest both theoretically and empirically. And in contrast to traditional approaches, recent research increasingly explores the pivotal implications of individual behavior and heterogeneous contact patterns in populations. Our report reviews the developmental arc of theoretical epidemiology with emphasis on vaccination, as it led from classical models assuming homogeneously mixing (mean-field) populations and ignoring human behavior, to recent models that account for behavioral feedback and/or population spatial/social structure. Many of the methods used originated in statistical physics, such as lattice and network models, and their associated analytical frameworks. Similarly, the feedback loop between vaccinating behavior and disease propagation forms a coupled nonlinear system with analogs in physics. We also review the new paradigm of digital epidemiology, wherein sources of digital data such as online social media are mined for high-resolution information on epidemiologically relevant individual behavior. Armed with the tools and concepts of statistical physics, and further assisted by new sources of digital data, models that capture nonlinear interactions between behavior and disease dynamics offer a novel way of modeling real-world phenomena, and can help improve health outcomes. We conclude the review by discussing open problems in the field and promising directions for future research

Prevalence of Age-Related Macular Degeneration in Europe: The Past and the Future

Purpose Age-related macular degeneration (AMD) is a frequent, complex disorder in elderly of European ancestry. Risk profiles and treatment options have changed considerably over the years, which may have affected disease prevalence and outcome. We determined the prevalence of early and late AMD in Europe from 1990 to 2013 using the European Eye Epidemiology (E3) consortium, and made projections for the future. Design Meta-analysis of prevalence data. Participants A total of 42 080 individuals 40 years of age and older participating in 14 population-based cohorts from 10 countries in Europe. Methods AMD was diagnosed based on fundus photographs using the Rotterdam Classification. Prevalence of early and late AMD was calculated using random-effects meta-analysis stratified for age, birth cohort, gender, geographic region, and time period of the study. Best-corrected visual acuity (BCVA) was compared between late AMD subtypes; geographic atrophy (GA) and choroidal neovascularization (CNV). Main Outcome Measures Prevalence of early and late AMD, BCVA, and number of AMD cases. Results Prevalence of early AMD increased from 3.5% (95% confidence interval [CI] 2.1%–5.0%) in those aged 55–59 years to 17.6% (95%

The incidence and predictors of depressive and anxiety symptoms in older adults with vision impairment: a longitudinal prospective cohort study

Purpose: Depression and anxiety are highly prevalent in older adults with vision impairment. Because symptoms of depression and anxiety appear to fluctuate, it is important to identify patients who are at risk of developing these symptoms for early diagnosis and treatment. Therefore, the aim of this study was to determine the incidence of subthreshold depression and anxiety, and to investigate predictors of developing symptoms of depression and anxiety in older adults with vision impairment who had no subthreshold depression or anxiety at baseline. Methods: A longitudinal prospective cohort study with a follow-up of 24 months in 540 older adults with vision impairment (mean age 75 years, 56% female, 48% macular degeneration, 15% glaucoma) from outpatient low-vision rehabilitation organisations was performed. The cumulative incidences of subthreshold depression and anxiety were calculated and linear mixed models with maximum likelihood estimation were used to determine two prediction models. Main outcome measures were: fluctuations in (i) depressive symptoms (Center for Epidemiologic Studies Depression Scale, CES-D) and (ii) anxiety symptoms (Hospital Anxiety and Depression Scale-Anxiety subscale, HADS-A). Results: The annual cumulative incidences of subthreshold depression and anxiety were 21.3% (95% Confidence Interval (CI) 18.7–23.9%) and 9.5% (95% CI 7.4–11.6%), respectively. Risk factors for developing depressive symptoms were: living alone, having just enough money to cover expenses, having macular degeneration, having problems with adaptation to vision loss, reduced health related quality of life, and experiencing symptoms of anxiety. For developing anxiety symptoms, a relatively younger age, experiencing symptoms of depression, not living alone and experiencing hindrance at work proved to be risk factors. Conclusions: This study shows that the incidence of subthreshold depression and anxiety in older adults with vision impairment is twice as high compared with older adults in general and confirms that depression and anxiety symptoms fluctuate over time. It is of great importance that low vision rehabilitation staff monitor older adults with vision impairment who are most vulnerable for developing these symptoms, based on the risk factors that were found in this study, to be able to offer early interventions to prevent and treat mental health problems in this population

Evaluating the Occurrence of Rare Variants in the Complement Factor H Gene in Patients with Early-Onset Drusen Maculopathy

Importance: Early-onset drusen maculopathy (EODM) is a severe disease and can lead to advanced macular degeneration early in life; however, genetic and phenotypic characteristics of individuals with EODM are not well studied. Objective: To identify genotypic and phenotypic characteristics of individuals with EODM. Design, Setting, and Participants: This case-control study collected data from the European Genetic Database from September 2004 to October 2019. A total of 89 patients with EODM diagnosed at 55 years or younger and 91 patients with age-related macular degeneration (AMD) diagnosed at 65 years or older were included. Exposures: Coding regions of CFH, CFI, C3, C9, CFB, ABCA4, PRPH2, TIMP3, and CTNNA1 genes were sequenced, genetic risk scores (GRS) were calculated based on 52 AMD-associated variants, and phenotypic characteristics on color fundus photographs were analyzed comparing patients with EODM and AMD. Main Outcomes and Measures: GRS, frequency of rare genetic complement variants, and phenotypic characteristics. Results: This case-control study included 89 patients with EODM (mean [SD] age, 51.8 [8.7] years; 58 [65.2%] were female) and 91 patients with AMD (mean [SD] age, 77.6 [6.1] years; 45 [49.5%] female). At a mean (SD) age of 56.4 (7.3) years, 40 of 89 patients with EODM (44.9%) were affected by geographic atrophy or choroidal neovascularization. A lower GRS was observed in patients with EODM compared with patients with AMD (1.03 vs 1.60; P =.002), and 27 of 89 patients with EODM (30.3%) carried rare variants in the CFH gene compared with 7 of 91 patients with AMD (7.7%). Carriership of a rare CFH variant was associated with EODM (odds ratio, 7.2; 95% CI, 2.7-19.6; P <.001). A large macular drusen area (more than 50% covered with drusen) was observed in patients with EODM (24 of 162 eyes [14.8%]) compared with patients with AMD (9 of 164 eyes [5.5%]) (odds ratio, 4.57; 95% CI, 1.5-14.1; P =.008). Conclusions and Relevance: A large proportion of patients with EODM in this study carried rare CFH variants, with most of the identified CFH variants clustered in the first 7 complement control protein domains affecting factor H and factor H-like 1. Because EODM frequently leads to advanced macular degeneration at an early age and can result in many years of vision loss, this study supports targeting the complement system and sequencing the CFH gene in patients with EODM to improve genetic counseling and future treatments for AMD.

IN VITRO KINEMATICS OF HUMAN NATIVE KNEES: A DATABASE OF 60 SPECIMENS

info:eu-repo/semantics/publishe