Self-reported dual sensory impairment and related factors: a European population-based cross-sectional survey.

BACKGROUND: Data on population-based self-reported dual vision and hearing impairment are sparse in Europe. We aimed to investigate self-reported dual sensory impairment (DSI) in European population. METHODS: A standardised questionnaire was used to collect medical and socio-economic data among individuals aged 15 years or more in 29 European countries. Individuals living in collective households or in institutions were excluded from the survey. RESULTS: Among 296 677 individuals, the survey included 153 866 respondents aged 50 years old or more. The crude prevalence of DSI was of 7.54% (7.36-7.72). Among individuals aged 60 or more, 9.23% of men and 10.94% of women had DSI. Eastern and southern countries had a higher prevalence of DSI. Multivariable analyses showed that social isolation and poor self-rated health status were associated with DSI with ORs of 2.01 (1.77-2.29) and 2.33 (2.15-2.52), while higher income was associated with lower risk of DSI (OR of 0.83 (0.78-0.89). Considering country-level socioeconomic factors, Human Development Index explained almost 38% of the variance of age-adjusted prevalence of DSI. CONCLUSION: There are important differences in terms of prevalence of DSI in Europe, depending on socioeconomic and medical factors. Prevention of DSI does represent an important challenge for maintaining quality of life in elderly population.

Progression of myopia in teenagers and adults: a nationwide longitudinal study of a prevalent cohort.

BACKGROUND: The prevalence of myopia is increasing worldwide. The purpose of this study was to evaluate the progression of myopia in teenagers and adults in France. METHODS: This nationwide prospective study followed 630 487 myopic adults and teenagers (mean age 43.4 years±18.2, 59.8% of women) between January 2013 and January 2019. Myopia and high myopia were defined as a spherical equivalent less than or equal to -0.50 and -6.00 diopters (D), respectively. Demographic data were collected at first visit and refractive characteristics were collected at each visit. Analysis of short-term progression (first 12 to 26 months postbaseline) was modelled using analysis of variance (ANOVA). Progression of myopia was stratified according to age, gender and spherical equivalent at first visit. RESULTS: Higher proportions of progressors were observed in the youngest age groups: 14-15 (18.2 %) and 16-17 years old (13.9 %). In multivariate analysis, after adjustment for over age, spherical equivalent and gender, the mean short-term progression decreased from -0.36 D in the 14-15 years age group to -0.13 D in the 28-29 years age group. Young age and higher myopia at baseline together were strongly associated with the risk of developing high myopia, the 5-year cumulative risk being 76% for youngest teenager with higher myopia status at baseline. CONCLUSION: In this large cohort of myopic teenagers and adults, myopia progression was reported in 18.2% and 13.9% of the 14-15 and 16-17 age groups, respectively. The risk to develop high myopia was higher for younger individuals with higher myopia at baseline examination.

Progression of myopia in children and teenagers: a nationwide longitudinal study.

BACKGROUND: Data on myopia prevalence and progression in European children are sparse. The aim of this work was to evaluate the progression of myopia in children and teenagers in a large prospective study. METHODS: A prospective study involving a nationwide cohort. Myopia was defined as a spherical equivalent (SE) of ≤ -0.50 diopters (D). Data on refractive error, gender and age were collected in 696 optical centres in France between 2013 and 2019, including 136 333 children (4-17 years old) in the analysis.Progression of myopia was assessed between the first visit and the last visit over up to 6.5 years. RESULTS: Mean age was 11.3±3.8 years (55.0% of female). The proportion of children progressing more than -0.50 D per year was higher in age groups 7-9 years and 10-12 years and in children with SE ≤ -4.00 D at first visit, representing 33.1%, 29.4% and 30.0% of these groups, respectively. In multivariate analysis, progression during the first 11-24 months was higher in the 7-9 and 10-12 age groups (-0.43 D and -0.42 D, respectively), for higher SE at baseline (at least -0.33 D for SE ≤ -1 D) and for girls (-0.35 D). CONCLUSION: This is the first French epidemiological study to investigate myopia progression in a large-scale cohort of children. Sex, age groups and myopia severity are associated with differing rates of progression.

Self-reported visual difficulties in Europe and related factors: a European population-based cross-sectional survey.

PURPOSE: There is a relative paucity of self-reported vision problems data in European countries. METHODS: In this context, we investigated self-reported vision problems through European Health Interview Survey 2, a cross-sectional European population survey based on a standardized questionnaire including 147 medical, demographic and socioeconomic variables applied to non-institutionalized individuals aged 15 years or more in 28 European countries, in addition to Iceland and Norway. RESULTS: The survey included 311 386 individuals (54.18% women), with overall crude prevalence of self-reported vision problems of 2.07% [95% CI; 2.01-2.14]. Among them, 1.70 % [1.61-1.78] of men, 2.41% [2.31-2.51] of women and 4.71% [4.53-4.89] of individuals aged 60 or more reported to have a lot of vision problems or to be not able to see. The frequency of self-reported vision problems was the highest in Eastern European countries with values of 2.43% [2.30-2.56]. In multivariate analyses, limiting long-standing illness, depression, daily smoking, lack of physical activity, lower educational level and social isolation were associated with self-reported vision problems with ORs of 2.66 [2.42-2.92], 2.16 [2.01-2.32], 1.11 [1.01-1.23], 1.31 [1.21-1.42], 1.29 [1.19-1.40] and 1.45 [1.26-1.67], respectively, while higher income was associated with less self-reported vision problems with OR of 0.80 [0.73-0.86]. CONCLUSIONS: This study demonstrated inequalities in terms of prevalence of self-reported vision problems in Europe, with higher prevalence in Eastern European countries and among women and older individuals.

Prevalence of macular complications related to myopia - Results of a multicenter evaluation of myopic patients in eye clinics in France.

PURPOSE: Uncorrected refractive errors are the first cause of vision impairment worldwide. High myopia is a frequent cause of sight-threatening chorioretinal complications. The aim of this study was to evaluate the prevalence of macular complications, visual impairment and blindness in patients with myopia. METHODS: A cross-sectional multicenter study carried out in French eye clinics mainly dedicated to refractive errors. Myopia severity was defined as mild (-0.5 to -3 D), moderate (-3 to -6 D), high (-6 to -10 D) and very high (more than -10 D). Macular complications related to myopia included lacquer cracks, myopic choroidal neovascularization, chorioretinal atrophy and retinoschisis. The prevalences of macular complications, blindness and vision impairment were estimated with respect to degree of myopia and age. Eligibility criteria were myopia on the left eye of -0.5 D or more. Exclusion criteria included any missing data related to subjective refractive error, age, gender and any history of cataract or refractive surgery. RESULTS: Data files from 198 641 myopic individuals with a mean age of 34 years (SD: 15 years) were analysed. The prevalence of mild, moderate, high and very high myopia was, respectively, 65.95%, 26.14%, 6.72% and 1.19%. The prevalence of macular complications in the high and very high myopia groups was 0.5% [0.39-0.64] and 4.27% [3.49-5.17]. The prevalence of blindness or vision impairment was observed in 10.10% [8.91-11.39%] of the very high myopic group. At 60 years old or over, the prevalences of blindness or vision impairment were, respectively, 9.75% [7.91-11.85%] and 25.71% [21.00-30.87%] in the high and very high myopia groups. CONCLUSIONS: This multicenter cross-sectional study provides new insights in terms of prevalence of macular complications related to myopia. To our knowledge, this is one of the largest European studies focusing on individuals with myopia, particularly on the macular complications and the functional consequences in relation to myopia.

Origin of Public Memory B Cell Clones in Fish After Antiviral Vaccination.

Vaccination induces "public" antibody clonotypes common to all individuals of a species, that may mediate universal protection against pathogens. Only few studies tried to trace back the origin of these public B-cell clones. Here we used Illumina sequencing and computational modeling to unveil the mechanisms shaping the structure of the fish memory antibody response against an attenuated Viral Hemorrhagic Septicemia rhabdovirus. After vaccination, a persistent memory response with a public VH5JH5 IgM component was composed of dominant antibodies shared among all individuals. The rearrangement model showed that these public junctions occurred with high probability indicating that they were already favored before vaccination due to the recombination process, as shown in mammals. In addition, these clonotypes were in the naïve repertoire associated with larger similarity classes, composed of junctions differing only at one or two positions by amino acids with comparable properties. The model showed that this property was due to selective processes exerted between the recombination and the naive repertoire. Finally, our results showed that public clonotypes greatly expanded after vaccination displayed several VDJ junctions differing only by one or two amino acids with similar properties, highlighting a convergent response. The fish public memory antibody response to a virus is therefore shaped at three levels: by recombination biases, by selection acting on the formation of the pre-vaccination repertoire, and by convergent selection of functionally similar clonotypes during the response. We also show that naive repertoires of IgM and IgT have different structures and sharing between individuals, due to selection biases. In sum, our comparative approach identifies three conserved features of the antibody repertoire associated with public memory responses. These features were already present in the last common ancestors of fish and mammals, while other characteristics may represent species-specific solutions.

Novel Structural Parameters of Ig-Ag Complexes Yield a Quantitative Description of Interaction Specificity and Binding Affinity.

Antibody-antigen complexes challenge our understanding, as analyses to date failed to unveil the key determinants of binding affinity and interaction specificity. We partially fill this gap based on novel quantitative analyses using two standardized databases, the IMGT/3Dstructure-DB and the structure affinity benchmark. First, we introduce a statistical analysis of interfaces which enables the classification of ligand types (protein, peptide, and chemical; cross-validated classification error of 9.6%) and yield binding affinity predictions of unprecedented accuracy (median absolute error of 0.878 kcal/mol). Second, we exploit the contributions made by CDRs in terms of position at the interface and atomic packing properties to show that in general, VH CDR3 and VL CDR3 make dominant contributions to the binding affinity, a fact also shown to be consistent with the enthalpy-entropy compensation associated with preconfiguration of CDR3. Our work suggests that the affinity prediction problem could be partially solved from databases of high resolution crystal structures of complexes with known affinity.

Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation.

The 2015 D3R Grand Challenge provided an opportunity to test our new model for the binding free energy of small molecules, as well as to assess our protocol to predict binding poses for protein-ligand complexes. Our pose predictions were ranked 3-9 for the HSP90 dataset, depending on the assessment metric. For the MAP4K dataset the ranks are very dispersed and equal to 2-35, depending on the assessment metric, which does not provide any insight into the accuracy of the method. The main success of our pose prediction protocol was the re-scoring stage using the recently developed Convex-PL potential. We make a thorough analysis of our docking predictions made with AutoDock Vina and discuss the effect of the choice of rigid receptor templates, the number of flexible residues in the binding pocket, the binding pocket size, and the benefits of re-scoring. However, the main challenge was to predict experimentally determined binding affinities for two blind test sets. Our affinity prediction model consisted of two terms, a pairwise-additive enthalpy, and a non pairwise-additive entropy. We trained the free parameters of the model with a regularized regression using affinity and structural data from the PDBBind database. Our model performed very well on the training set, however, failed on the two test sets. We explain the drawback and pitfalls of our model, in particular in terms of relative coverage of the test set by the training set and missed dynamical properties from crystal structures, and discuss different routes to improve it.

High-resolution crystal structures leverage protein binding affinity predictions.

Predicting protein binding affinities from structural data has remained elusive, a difficulty owing to the variety of protein binding modes. Using the structure-affinity-benchmark (SAB, 144 cases with bound/unbound crystal structures and experimental affinity measurements), prediction has been undertaken either by fitting a model using a handfull of predefined variables, or by training a complex model from a large pool of parameters (typically hundreds). The former route unnecessarily restricts the model space, while the latter is prone to overfitting. We design models in a third tier, using 12 variables describing enthalpic and entropic variations upon binding, and a model selection procedure identifying the best sparse model built from a subset of these variables. Using these models, we report three main results. First, we present models yielding a marked improvement of affinity predictions. For the whole dataset, we present a model predicting Kd within 1 and 2 orders of magnitude for 48% and 79% of cases, respectively. These statistics jump to 62% and 89% respectively, for the subset of the SAB consisting of high resolution structures. Second, we show that these performances owe to a new parameter encoding interface morphology and packing properties of interface atoms. Third, we argue that interface flexibility and prediction hardness do not correlate, and that for flexible cases, a performance matching that of the whole SAB can be achieved. Overall, our work suggests that the affinity prediction problem could be partly solved using databases of high resolution complexes whose affinity is known.

Ciruvis: a web-based tool for rule networks and interaction detection using rule-based classifiers.

BACKGROUND: The use of classification algorithms is becoming increasingly important for the field of computational biology. However, not only the quality of the classification, but also its biological interpretation is important. This interpretation may be eased if interacting elements can be identified and visualized, something that requires appropriate tools and methods. RESULTS: We developed a new approach to detecting interactions in complex systems based on classification. Using rule-based classifiers, we previously proposed a rule network visualization strategy that may be applied as a heuristic for finding interactions. We now complement this work with Ciruvis, a web-based tool for the construction of rule networks from classifiers made of IF-THEN rules. Simulated and biological data served as an illustration of how the tool may be used to visualize and interpret classifiers. Furthermore, we used the rule networks to identify feature interactions, compared them to alternative methods, and computationally validated the findings. CONCLUSIONS: Rule networks enable a fast method for model visualization and provide an exploratory heuristic to interaction detection. The tool is made freely available on the web and may thus be used to aid and improve rule-based classification.