Incidence and Risk Factors of Recurrent Clostridioides difficile Infection in Patients With Cirrhosis

INTRODUCTION: Clostridioides difficile infection (CDI) is common in patients with cirrhosis and is associated with poor outcomes. CDI risk factors in this population have been well characterized; however, risk factors of recurrent CDI (R-CDI) after treatment have not been explored. We sought to estimate the incidence of R-CDI and its associated risk factors in patients with cirrhosis. METHODS: We performed a cohort study of patients with cirrhosis hospitalized with CDI between 2012 and 2016. We collected patient characteristics, including detailed information on the CDI, features of the underlying liver disease, and outcomes including R-CDI, hospital readmission, and mortality. R-CDI was defined as CDI occurring 2–8 weeks after the initial episode. Cox proportional hazards model was used to identify variables independently associated with the outcomes. RESULTS: A total of 257 hospitalized patients with cirrhosis and CDI were included. CDI was community associated in 22.6%. The incidence of R-CDI was 11.9%. R-CDI was not significantly associated with medications at hospital admission or discharge. Independent risk factors of R-CDI included increased Charlson Comorbidity Index (hazard ratio [HR] 1.30; 95% confidence interval [CI]: 1.09–1.55) and use of lactulose (HR 2.58; 95% CI: 1.09–6.09). The 30-day readmission rate was 37%, and readmission was associated with increased Charlson Comorbidity Index (HR 1.12; 95% CI: 1.03–1.23) and Model for End-Stage Liver Disease score (HR 1.04; 95% CI: 1.01–1.07). The 90-day mortality was 22.8%. DISCUSSION: In patients with cirrhosis, R-CDI is associated with comorbidity burden and lactulose use. Attention to these factors might aid clinicians in efforts to prevent R-CDI and improve outcomes in this population

Author Correction: Discovery of 42 genome-wide significant loci associated with dyslexia

Correction to: Nature Genetics https://doi.org/10.1038/s41588-022-01192-y. Published online 20 October 2022. In the version of this article originally published, a paragraph was omitted in the Methods section, reading “Genomic control. Top SNPs are reported from the more conservative GWAS results adjusted for genomic control (Fig. 1, Extended Data Figs. 1–4, and Supplementary Tables 1, 2, 9 and 10), whereas downstream analyses (including gene-set analysis, enrichment and heritability partitioning, genetic correlations, polygenic prediction, candidate gene replication) are based on GWAS results without genomic control.” The paragraph has now been included in the HTML and PDF versions of the article

Multi-Trait Genetic Analysis Identifies Autoimmune Loci Associated with Cutaneous Melanoma

Genome-wide association studies (GWAS) have identified a number of risk loci for cutaneous melanoma. Cutaneous melanoma shares overlapping genetic risk (genetic correlation) with a number of other traits, including its risk factors such as sunburn propensity. This genetic correlation can be exploited to identify additional cutaneous melanoma risk loci by multitrait analysis of GWAS (MTAG). We used bivariate linkage disequilibrium–score regression score regression to identify traits that are genetically correlated with clinically confirmed cutaneous melanoma and then used publicly available GWAS for these traits in a multitrait analysis of GWAS. Multitrait analysis of GWAS allows GWAS to be combined while accounting for sample overlap and incomplete genetic correlation. We identified a total of 74 genome-wide independent loci, 19 of them were not previously reported in the input cutaneous melanoma GWAS meta-analysis. Of these loci, 55 were replicated (P < 0.05/74, Bonferroni-corrected P-value in two independent cutaneous melanoma replication cohorts from Melanoma Institute Australia and 23andMe, Inc. Among the, to our knowledge, previously unreported cutaneous melanoma loci are ones that have also been associated with autoimmune traits including rs715199 near LPP and rs10858023 near AP4B1. Our analysis indicates genetic correlation between traits can be leveraged to identify new risk genes for cutaneous melanoma.</p