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This work was supported by the Strategic Action for Research in Health sciences [PI10/0082, PI13/01848, PI14/00874, PI16/01402, PI11/00726, PI16/609, PI16/1512, PI18/287, PI19/319 and PI20/00896], the GUTMOM Project (JPI-A Healthy Diet for a Healthy Life INTIMIC-085, State Secretary of R + D + I PCIN-2017-117), the Cátedra de Epidemiología y Control del Riesgo Cardiovascular at UAM (#820024), the State Agency for Research (PID2019-108973RB-C21 and C22), the Valencia Government (GRUPOS 03/101; PROMETEO/2009/029 and ACOMP/2013/039), the Castilla-Leon Government (GRS/279/A/08) and European Network of Excellence Ingenious Hypercare (EPSS- 037093) from the European Commission; CIBER Fisiopatología Obesidad y Nutrición (CIBEROBN) (CIBER-02-08-2009, CB06/03 and CB12/03/30016). MSP holds a Ramón y Cajal contract (RYC-2018-025069-I) from the Ministry of Science, Innovation and Universities. MDV holds a “Predoctoral Training in Health Research” contract (FI20/00162) from the Carlos III Health Institute. MGP and ADR received the support of a fellowship from “la Caixa” Foundation (ID 100010434, fellowship codes LCF/BQ/IN18/11660001, and LCF/BQ/DR19/11740016, respectively). PO received the support of a Sara Borrell contract from the Carlos III Health Institute (reference CD16/00255). The Strategic Action for Research in Health Sciences, CIBEROBN are initiatives from Carlos III Health Institute Madrid and co-funded by the European Social Fund “The ESF - investing in your future”. The State Agency for Research and Carlos III Health Institute belong to the Spanish Ministry of Science and Innovation. The funding bodies had no role in the study design, data collection and analysis, interpretation of results, manuscript preparation or in the decision to submit this manuscript for publication., Background: The contribution of metabolomic factors to the association of healthy lifestyle with type 2 diabetes risk is unknown. We assessed the association of a composite measure of lifestyle with plasma metabolite profiles and incident type 2 diabetes, and whether relevant metabolites can explain the prospective association between healthy lifestyle and incident type 2 diabetes. Methods: A Healthy Lifestyle Score (HLS) (5-point scale including diet, physical activity, smoking status, alcohol consumption and BMI) was estimated in 1016 Hortega Study participants, who had targeted plasma metabolomic determinations at baseline examination in 2001–2003, and were followed-up to 2015 to ascertain incident type 2 diabetes. Results: The HLS was cross-sectionally associated with 32 (out of 49) plasma metabolites (2.5% false discovery rate). In the subset of 830 participants without prevalent type 2 diabetes, the rate ratio (RR) and rate difference (RD) of incident type 2 diabetes (n cases = 51) per one-point increase in HLS was, respectively, 0.69 (95% CI, 0.51, 0.93), and − 8.23 (95% CI, − 16.34, − 0.13)/10,000 person-years. In single-metabolite models, most of the HLS-related metabolites were prospectively associated with incident type 2 diabetes. In probit Bayesian Kernel Machine Regression, these prospective associations were mostly driven by medium HDL particle concentration and phenylpropionate, followed by small LDL particle concentration, which jointly accounted for ~ 50% of the HLS-related decrease in incident type 2 diabetes. Conclusions: The HLS showed a strong inverse association with incident type 2 diabetes, which was largely explained by plasma metabolites measured years before the clinical diagnosis., CIBER Fisiopatología Obesidad y Nutrición, Castilla-Leon Government GRS/279/A/08, European Network of Excellence Ingenious Hypercare EPSS- 037093, State Agency for Research ACOMP/2013/039, GRUPOS 03/101, PROMETEO/2009/029, Strategic Action for Research in Health sciences INTIMIC-085, PCIN-2017-117, Ministerio de Ciencia, Innovación y Universidades RYC-2018-025069-I, European Commission EPSS-037093, Instituto de Salud Carlos III CB06/03, CB12/03/30016, CD16/00255, CIBER-02-08-2009, PI10/0082, PI11/00726, PI13/01848, PI14/00874, PI16/01402, PI16/1512, PI16/609, PI18/287, PI19/319, PI20/00896, Universidad Autónoma de Madrid 820024, Agencia Estatal de Investigación PID2019-108973RB-C21, “La Caixa” Foundation 100010434, LCF/BQ/DR19/11740016, LCF/BQ/IN18/11660001

To the Editor,A study of respiratory syncytial virus (RSV) infection in adult patients visiting an emergency department was recently published in this journal [1]. Among 227 cases, 34 (15%) were cl...

Osteoporosis and obesity are major public health problems that are closely correlated, as they share various features, including a genetic predisposition. A genetic correlation between obesity and osteoporosis due to the biological common pathways of bone and fat metabolism, which implies pleiotropic genes regulating has been described. The objective of our study was to analyse whether polymorphisms in obesity-related genes modify the risk of osteoporotic bone fracture.We studied 575 subjects from the Hortega Study. The subjects were followed-up for 12-14 years. 202 subjects were overweight, 143 obese and 221 had bone fractures. The distribution of 39 genetic variants in 22 obesity-related genes were studied.The results showed a relationship between polymorphisms in theIn conclusion, this study associates obesity-related polymorphisms in the