Respiratory syncytial virus-related hospital stays in adults in France from 2012 to 2021: A national hospital database study

BACKGROUND

Respiratory syncytial virus (RSV) causes lower respiratory tract infections (LRTI) that may lead to hospitalization or death. The present study aimed to assess the burden of RSV infections in hospitalized adults.

METHODS

RSV-related hospitalizations were identified from the nationwide hospital claims database in France (PMSI) from 2012 to 2021 using ICD-10 codes J12.1, J20.5, J21.0 or B97.4, and outcomes assessment focused on 2016-2020. In-hospital outcomes included length of stay, need for intensive care (ICU) and in-hospital all-cause mortality. Post-discharge outcomes included 30-day readmission for decompensation, 90-day RSV-related readmission, and 30 and 60-day in-hospital mortality.

RESULTS

A cumulated number of 17 483 RSV-related stays were identified representing a rate of 72.0 cases per million stays. The outcomes assessment included 12,987 patients: 55.8 % were females and the mean age was 74.1 ± 16.4 years, with 57 % ≥ 75 years. Most of patients (78.6 %) had at least one comorbidity, mainly chronic respiratory (56.3 %) and cardiovascular diseases (41.3 %), or diabetes (23.5 %). A co-infection was found in 22.4 %, primarily bacterial (12 %). The mean length of stay was 12.3 ± 13.1 days. Overall, 10.9 % were admitted to an ICU and in-hospital mortality was 7.3 %. In-hospital outcomes were higher in cases of co-infection. Among 12 033 patients alive at discharge from the index stay, 6.5 % were readmitted with RSV within 90 days, 8.1 % for decompensation within 30 days, and 5.6 % died within 60-day.

CONCLUSION

This study demonstrated the high burden of RSV infections in older adults and those with chronic conditions, and the need for preventive strategies.

Associations between plasma levels of brominated flame retardants and methylation of DNA from peripheral blood: A cross-sectional study in a cohort of French women

BACKGROUND

Brominated flame retardants (BFRs) are organic compounds that are widespread in the environment. Because of their persistence, they are able to bioaccumulate with major impacts on human health. It has been hypothesized that the effect of BFRs on human health is mediated by alterations of DNA methylation.

OBJECTIVE

The aim of this study was to examine the association between methylation of DNA extracted from peripheral blood and circulating levels of BFRs measured in plasma.

METHODS

We conducted a methylation wide association study on 336 blood samples from a study within the E3N (Etude Epidémiologique auprès de femmes de l'Education Nationale) cohort, a long-term longitudinal cohort of French women. DNA methylation at more than 850 000 cytosine-guanine dinucleotide (CpG) sites was measured with the Illumina Infinium HumanMethylation - EPIC BeadChip. Circulating levels of seven BFRs (BDE-28, BDE-47, BDE-99, BDE-100, BDE-153, BDE-154 and PBB-153) were measured by gas chromatography coupled to high-resolution mass spectrometry in plasma samples. The association between DNA methylation and BFRs plasma levels was assessed through linear mixed-effects models followed by gene-set enrichment analyses (GSEA).

RESULTS

We identified 253 CpG sites whose methylation levels were significantly associated with exposure to BFRs after Bonferroni correction. For 50 of these CpGs the p-values were less than 2.2x10^-9 with the strongest association being between BDE-154 and cg23619365 (4.32x10^-13). GSEA of CpG sites associated with exposure to BFRs identified significant enrichment of genes involved in hypoxia, glycolysis and adipogenesis.

CONCLUSIONS

Exposure to BFRs appears to be related to numerous alterations in DNA methylation. These findings, if replicated in independent studies, provide insights into the biological and health effects of BFRs.

Coûts des hospitalisations et des soins de suite et de réadaptation liés au COVID-19 en France en 2020

Introduction

A l'origine d'une pandémie depuis 2020, la maladie liée au coronavirus SARS-CoV-2 (COVID-19) représente une surcharge importante pour les systèmes de santé. La surveillance nationale a dénombré un total de 261 123 cas d'infection ayant nécessité une hospitalisation en 2020 et 64 078 décès. Cette étude a pour objectif d'estimer la charge économique des hospitalisations, des soins de suite et de réadaptation (SSR) et des hospitalisations à domicile (HAD) liée au COVID-19 en France en 2020.

Matériels et méthodes

Une cohorte rétrospective incluant tous les patients hospitalisés avec un code diagnostic (CIM-10 ; principal, secondaire ou associé) relatif au COVID-19 entre le 1er janvier et le 31 décembre 2020 a été conduite à partir des données du PMSI (Programme de médicalisation des systèmes d'information : MCO, SSR et HAD). Les patients ont été divisés en 3 groupes selon les définitions de Santé Publique France : cas confirmés (virus identifié et symptômes typiques : code U07.10 ou U07.14), probables (symptômes cliniques U07.11) et possibles (autres symptômes U07.15). L'évaluation et la valorisation des coûts directs ont été effectuées selon la tarification à l'activité et les suppléments applicables de l'assurance maladie.

Résultats

Les données du PMSI ont permis d'identifier 271 728 séjours pour 210 635 patients hospitalisés avec un lien avec le COVID-19 dont 185 111 cas confirmés, 23 416 probables et 2 108 possibles. Les résultats suivants correspondent aux cas confirmés. La majorité des patients (85 %, N = 157 758) ont été pris en charge initialement par un séjour en MCO, 10 % (N = 18 375) en SSR et 5 % (N = 8 978) en HAD. La durée moyenne de séjour était de 17,8 ± 22 jours au total, 12,7 ± 13 jours en MCO, 26,4 ± 26 jours en SSR et 15,5 ± 19 jours en HAD. Parmi les séjours, 23 % ont impliqués les soins critiques (réanimation, unité de soins intensifs et/ou surveillance continue). La moitié des cas était des hommes, dont 56 % hospitalisés en MCO (N = 88 310), 39 % en SSR (N = 7 189) et 31 % en HAD (N = 2801). Au moins une comorbidité était enregistrée chez 79 % des patients (N = 146 457) : hypertension (54 %), diabète (27 %), troubles cardiovasculaires (24 %), insuffisance cardiaque (19 %), obésité (22 %), insuffisance rénale (16 %) et cancer (18 %).

Le coût total des hospitalisations et des SSR liés aux cas confirmés de COVID-19 est estimé à 1,672 milliards € représentant une moyenne de 7 044 €/séjour. Pour les passages en soins critiques, on estime à 339 millions € pour le passage en réanimation, 21,5 millions € en soins intensifs et 28,3 millions € en surveillance continue (respectivement 12 761 €, 2 356 € et 2 248 € en moyenne par séjour). Enfin, 11,5 millions € étaient attribuables à des traitements et/ou dispositifs inscrits sur la liste en sus.

Conclusion

Ces données quantifient le coût de la prise en charge hospitalière du COVID-19 en France en 2020, notamment à travers la durée de séjour et le recours aux soins intensifs pour un quart des patients. Cette surcharge économique devrait être réduite avec la mise en place de la couverture vaccinale en 2021.

Liens d'intérêts déclarés

Pr Sébastien Gallien : membre du comité scientifique de cette étude, qui est financée par Janssen-cilag France

Plasma concentration of brominated flame retardants and postmenopausal breast cancer risk: a nested case-control study in the French E3N cohort

BACKGROUND

Brominated flame retardants (BFRs) are lipophilic substances with endocrine-disrupting properties. To date, only few investigations, mainly retrospective case-control studies, have explored the link between internal levels of BFRs and the risk of breast cancer, leading to conflicting results. We investigated the associations between plasma concentrations of two main groups of BFRs, PBDEs (pentabromodiphenyl ethers) and PBBs (polybrominated biphenyls), and the risk of breast cancer in a nested case-control study.

METHODS

A total of 197 incident breast cancer cases and 197 controls with a blood sample collected in 1994-1999 were included. Plasma levels of PBDE congeners (BDE-28, BDE-47, BDE-99, BDE-100, BDE153, BDE-154) and of PBB-153 were measured by gas chromatography coupled to high-resolution mass spectrometry. Conditional logistic regression models, adjusted for potential confounders, were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

Women were aged 56 years on average at blood draw. All cases, except for one, were diagnosed after menopause, with an average age at diagnosis of 68 years. Overall, we found no evidence of an association between plasma levels of PBDEs and PBB-153 and postmenopausal breast cancer risk (log-concentrations of BFRs yielding non-statistically significant ORs of 0.87 to 1.07). The analysis showed a non-linear inverse association for BDE-100 and BDE-153 and postmenopausal breast cancer risk; nevertheless, these findings were statistically significant only when the exposure was modeled as ng/L plasma (third vs. first quintile: OR = 0.42, 95%CI = 0.19-0.93 and OR = 0.42, 95%CI = 0.18-0.98, respectively) and not when modeled as ng/gr of lipids (OR = 0.58, 95%CI = 0.27-1.25 and OR = 0.53, 95%CI = 0.25-1.17). These results were unchanged in stratified analyses by tumor hormone receptor expression or body mass index.

CONCLUSIONS

Our results suggest no clear association between internal levels of PBDEs and PBB-153 and the risk of breast cancer in postmenopausal women. However, these findings need to be carefully interpreted, taking into account limitations due to the limited number of women included in the study, the lack of information concerning genetic susceptibility of cases, and the unavailability of exposure assessment during critical windows of susceptibility for breast cancer. More studies are warranted to further investigate the relationships between PBDE and PBB exposure and breast cancer risk.

Computational tools to detect signatures of mutational processes in DNA from tumours: A review and empirical comparison of performance

Mutational signatures refer to patterns in the occurrence of somatic mutations that might be uniquely ascribed to particular mutational process. Tumour mutation catalogues can reveal mutational signatures but are often consistent with the mutation spectra produced by a variety of mutagens. To date, after the analysis of tens of thousands of exomes and genomes from about 40 different cancer types, tens of mutational signatures characterized by a unique probability profile across the 96 trinucleotide-based mutation types have been identified, validated and catalogued. At the same time, several concurrent methods have been developed for either the quantification of the contribution of catalogued signatures in a given cancer sequence or the identification of new signatures from a sample of cancer sequences. A review of existing computational tools has been recently published to guide researchers and practitioners through their mutational signature analyses, but other tools have been introduced since its publication and, a systematic evaluation and comparison of the performance of such tools is still lacking. In order to fill this gap, we have carried out an empirical evaluation of the main packages available to date, using both real and simulated data. Among other results, our empirical study shows that the identification of signatures is more difficult for cancers characterized by multiple signatures each having a small contribution. This work suggests that detection methods based on probabilistic models, especially EMu and bayesNMF, have in general better performance than NMF-based methods.

Stem cell replication, somatic mutations and role of randomness in the development of cancer

An intense scientific debate has recently taken place relating to the "bad luck" hypothesis in cancer development, namely that intrinsic random, and therefore unavoidable, mutagenic events would have a predominant role in tumorigenesis. In this article we review the main contributions to this debate and explain the reasons why the claim that cancer is mostly explained by intrinsic random factors is unsupported by data and theoretical models. In support of this, we present an analysis showing that smoking-induced mutations are more predictive of cancer risk than the lifetime number of stem cell cellular divisions.

Association of Selenoprotein and Selenium Pathway Genotypes with Risk of Colorectal Cancer and Interaction with Selenium Status

Selenoprotein genetic variations and suboptimal selenium (Se) levels may contribute to the risk of colorectal cancer (CRC) development. We examined the association between CRC risk and genotype for single nucleotide polymorphisms (SNPs) in selenoprotein and Se metabolic pathway genes. Illumina Goldengate assays were designed and resulted in the genotyping of 1040 variants in 154 genes from 1420 cases and 1421 controls within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Multivariable logistic regression revealed an association of 144 individual SNPs from 63 Se pathway genes with CRC risk. However, regarding the selenoprotein genes, only TXNRD1 rs11111979 retained borderline statistical significance after adjustment for correlated tests (PACT = 0.10; PACT significance threshold was P < 0.1). SNPs in Wingless/Integrated (Wnt) and Transforming growth factor (TGF) beta-signaling genes (FRZB, SMAD3, SMAD7) from pathways affected by Se intake were also associated with CRC risk after multiple testing adjustments. Interactions with Se status (using existing serum Se and Selenoprotein P data) were tested at the SNP, gene, and pathway levels. Pathway analyses using the modified Adaptive Rank Truncated Product method suggested that genes and gene x Se status interactions in antioxidant, apoptosis, and TGF-beta signaling pathways may be associated with CRC risk. This study suggests that SNPs in the Se pathway alone or in combination with suboptimal Se status may contribute to CRC development.

Novel Common Genetic Susceptibility Loci for Colorectal Cancer

BACKGROUND

Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10-8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk.

METHODS

We conducted a GWAS in European descent CRC cases and control subjects using a discovery-replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10-8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided.

RESULTS

The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10-8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0.

CONCLUSIONS

This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screening.

Mitochondrial DNA copy number variation, leukocyte telomere length, and breast cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) study

BACKGROUND

Leukocyte telomere length (LTL) and mitochondrial genome (mtDNA) copy number and deletions have been proposed as risk markers for various cancer types, including breast cancer (BC).

METHODS

To gain a more comprehensive picture on how these markers can modulate BC risk, alone or in conjunction, we performed simultaneous measurements of LTL and mtDNA copy number in up to 570 BC cases and 538 controls from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. As a first step, we measured LTL and mtDNA copy number in 96 individuals for which a blood sample had been collected twice with an interval of 15 years.

RESULTS

According to the intraclass correlation (ICC), we found very good stability over the time period for both measurements, with ICCs of 0.63 for LTL and 0.60 for mtDNA copy number. In the analysis of the entire study sample, we observed that longer LTL was strongly associated with increased risk of BC (OR 2.71, 95% CI 1.58-4.65, p = 3.07 × 10- 4 for highest vs. lowest quartile; OR 3.20, 95% CI 1.57-6.55, p = 1.41 × 10- 3 as a continuous variable). We did not find any association between mtDNA copy number and BC risk; however, when considering only the functional copies, we observed an increased risk of developing estrogen receptor-positive BC (OR 2.47, 95% CI 1.05-5.80, p = 0.04 for highest vs. lowest quartile).

CONCLUSIONS

We observed a very good correlation between the markers over a period of 15 years. We confirm a role of LTL in BC carcinogenesis and suggest an effect of mtDNA copy number on BC risk.

Identifying and correcting epigenetics measurements for systematic sources of variation

Background

Methylation measures quantified by microarray techniques can be affected by systematic variation due to the technical processing of samples, which may compromise the accuracy of the measurement process and contribute to bias the estimate of the association under investigation. The quantification of the contribution of the systematic source of variation is challenging in datasets characterized by hundreds of thousands of features.

In this study, we introduce a method previously developed for the analysis of metabolomics data to evaluate the performance of existing normalizing techniques to correct for unwanted variation. Illumina Infinium HumanMethylation450K was used to acquire methylation levels in over 421,000 CpG sites for 902 study participants of a case-control study on breast cancer nested within the EPIC cohort. The principal component partial R-square (PC-PR2) analysis was used to identify and quantify the variability attributable to potential systematic sources of variation. Three correcting techniques, namely ComBat, surrogate variables analysis (SVA) and a linear regression model to compute residuals were applied. The impact of each correcting method on the association between smoking status and DNA methylation levels was evaluated, and results were compared with findings from a large meta-analysis.

Results

A sizeable proportion of systematic variability due to variables expressing ‘batch’ and ‘sample position’ within ‘chip’ was identified, with values of the partial R² statistics equal to 9.5 and 11.4% of total variation, respectively. After application of ComBat or the residuals’ methods, the contribution was 1.3 and 0.2%, respectively. The SVA technique resulted in a reduced variability due to ‘batch’ (1.3%) and ‘sample position’ (0.6%), and in a diminished variability attributable to ‘chip’ within a batch (0.9%). After ComBat or the residuals’ corrections, a larger number of significant sites (k = 600 and k = 427, respectively) were associated to smoking status than the SVA correction (k = 96).

Conclusions

The three correction methods removed systematic variation in DNA methylation data, as assessed by the PC-PR2, which lent itself as a useful tool to explore variability in large dimension data. SVA produced more conservative findings than ComBat in the association between smoking and DNA methylation.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0471-6) contains supplementary material, which is available to authorized users.