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Purpose: Current prediction models for advanced age-related macular degeneration (AMD) are based on a restrictive set of risk factors. The objective of this study was to develop a comprehensive prediction model applying a machine learning algorithm allowing selection of the most predictive risk factors automatically., Design: Two population-based cohort studies., Participants: The Rotterdam Study I (RS-I; training set) included 3838 participants 55 years of age or older, with a median follow-up period of 10.8 years, and 108 incident cases of advanced AMD. The Antioxydants, Lipids Essentiels, Nutrition et Maladies Oculaires (ALIENOR) study (test set) included 362 participants 73 years of age or older, with a median follow-up period of 6.5 years, and 33 incident cases of advanced AMD., Methods: The prediction model used the bootstrap least absolute shrinkage and selection operator (LASSO) method for survival analysis to select the best predictors of incident advanced AMD in the training set. Predictive performance of the model was assessed using the area under the receiver operating characteristic curve (AUC)., Main Outcome Measures: Incident advanced AMD (atrophic, neovascular, or both), based on standardized interpretation of retinal photographs., Results: The prediction model retained (1) age, (2) a combination of phenotypic predictors (based on the presence of intermediate drusen, hyperpigmentation in one or both eyes, and Age-Related Eye Disease Study simplified score), (3) a summary genetic risk score based on 49 single nucleotide polymorphisms, (4) smoking, (5) diet quality, (6) education, and (7) pulse pressure. The cross-validated AUC estimation in RS-I was 0.92 (95% confidence interval [CI], 0.88-0.97) at 5 years, 0.92 (95% CI, 0.90-0.95) at 10 years, and 0.91 (95% CI, 0.88-0.94) at 15 years. In ALIENOR, the AUC reached 0.92 at 5 years (95% CI, 0.87-0.98). In terms of calibration, the model tended to underestimate the cumulative incidence of advanced AMD for the high-risk groups, especially in ALIENOR., Conclusions: This prediction model reached high discrimination abilities, paving the way toward making precision medicine for AMD patients a reality in the near future., (Copyright © 2020 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)

Purpose: The current study aimed to identify metabolites associated with age-related macular degeneration (AMD) by performing the largest metabolome association analysis in AMD to date, as well as aiming to determine the effect of AMD-associated genetic variants on metabolite levels and investigate associations between the identified metabolites and activity of the complement system, one of the main AMD-associated disease pathways., Design: Case-control association analysis of metabolomics data., Participants: Five European cohorts consisting of 2267 AMD patients and 4266 control participants., Methods: Metabolomics was performed using a high-throughput proton nuclear magnetic resonance metabolomics platform, which allows 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-to-C3 ratio) were investigated using linear regression., Main Outcome Measures: Metabolites associated with AMD., Results: We identified 60 metabolites that were associated significantly with AMD, including increased levels of large and extra-large high-density lipoprotein (HDL) subclasses and decreased levels of very low-density lipoprotein (VLDL), amino acids, and citrate. Of 52 AMD-associated genetic variants, 7 variants were associated significantly 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, and LIPC) with metabolites belonging to the large and extra-large HDL subclasses. Also, 57 of 60 metabolites were associated significantly with complement activation levels, 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, whereas 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., (Copyright © 2020 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)

Background & Aims: Mediterranean diet (MeDi) is considered as a key component for healthy aging, including prevention of age-related disability, while its association with frailty, independent of disability has never been assessed. Our objective was to investigate the relation between MeDi adherence and frailty incidence among persons aged ≥75 years participating at the prospective population-based French Three-City Study., Methods: The study sample consisted of 560 initially non-frail participants of the Three-City-Bordeaux center, seen at the 2009-2010 follow-up, and re-examined two years later. Adherence to MeDi was computed from a food frequency questionnaire (scored as 0-9). Frailty was defined as having at least three out of the following five slightly modified Fried frailty criteria: involuntary weight loss, exhaustion, slowness, weakness and low physical activity. Logistic regression models adjusted for sociodemographic and clinical covariates, including cognitive performance and depressive symptomatology, were used to assess the association between MeDi score and subsequent frailty risk., Results: Over the 2-year follow-up, 79 participants (14%) became frail. Older adults with the highest MeDi adherence (score 6-9) had a significantly 68% frailty risk reduction (95% CI: 28-86%, p = 0.006) compared to those in the lowest MeDi category (score 0-3). Regarding the frailty criterion separately, the highest MeDi adherence was associated with a significantly reduced risk of incident slowness (OR = 0.45; 95% CI: 0.20-0.99, p = 0.04), poor muscle strength (OR = 0.44; 95% CI: 0.20-0.98, p = 0.04) and low physical activity (OR = 0.39; 95% CI: 0.18-0.82, p = 0.01), compared to the lowest MeDi adherence., Conclusion: In addition to its well-documented beneficial effects on health, adherence to MeDi might contribute to prevent the onset of frailty, even at late stages of life., (Copyright © 2017 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.)

Background: In the era of personalized medicine, it's primordial to identify gene signatures for each event type in the context of competing risks in order to improve risk stratification and treatment strategy. Until recently, little attention was paid to the performance of high-dimensional selection in deriving molecular signatures in this context. In this paper, we investigate the performance of two selection methods developed in the framework of high-dimensional data and competing risks: Random survival forest and a boosting approach for fitting proportional subdistribution hazards models., Methods: Using data from bladder cancer patients (GSE5479) and simulated datasets, stability and prognosis performance of the two methods were evaluated using a resampling strategy. For each sample, the data set was split into 100 training and validation sets. Molecular signatures were developed in the training sets by the two selection methods and then applied on the corresponding validation sets., Results: Random survival forest and boosting approach have comparable performance for the prediction of survival data, with few selected genes in common. Nevertheless, many different sets of genes are identified by the resampling approach, with a very small frequency of genes occurrence among the signatures. Also, the smaller the training sample size, the lower is the stability of the signatures., Conclusion: Random survival forest and boosting approach give good predictive performance but gene signatures are very unstable. Further works are needed to propose adequate strategies for the analysis of high-dimensional data in the context of competing risks., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Objective: To analyze the association between dietary patterns and the 12-year risk of frailty and its components in community-dwelling elderly French adults., Design: A prospective cohort study., Setting: The Bordeaux sample of the Three-City Study., Participants: A total of 972 initially nonfrail nondemented participants (336 men and 636 women) aged 73 years on average, re-examined at least once over 12 years., Measurements: Five sex-specific dietary clusters were previously derived at baseline. Frailty incident to the baseline visit was defined as having at least three out of the following 5 criteria: unintentional weight loss, exhaustion, low energy expenditure, slowness, and muscle weakness. Multivariate Cox proportional hazard models were used to assess the association between dietary clusters and the risk of frailty and its components., Results: In total, 78 men for 3719 person-years and 221 women for 7027 person-years became frail over the follow-up. In multivariate analyses, men in the "pasta" pattern and women in the "biscuits and snacking" pattern had a significantly higher risk of frailty compared with those in the "healthy" pattern [hazard ratio (HR) 2.2; 95% confidence interval (CI) 1.1-4.4 and HR 1.8; 95% CI 1.2-2.8, respectively; P = .09 and P = .13 for the global test of significance of risk difference across clusters, respectively]. In men, "biscuits and snacking" and "pasta" patterns were significantly associated with higher risk for muscle weakness (HR 3.3; 95% CI 1.6-7.0 and HR 2.1; 95% CI 1.2-3.7, respectively; P = .003 for global test)., Conclusions: This 12-year prospective population-based study suggests that some particular unhealthy dietary patterns may increase the risk of frailty in older adults., (Copyright © 2016 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.)