A detailed Hapmap of the Sitosterolemia locus spanning 69 kb; differences between Caucasians and African-Americans

BACKGROUND: Sitosterolemia is an autosomal recessive disorder that maps to the sitosterolemia locus, STSL, on human chromosome 2p21. Two genes, ABCG5 and ABCG8, comprise the STSL and mutations in either cause sitosterolemia. ABCG5 and ABCG8 are thought to have evolved by gene duplication event and are arranged in a head-to-head configuration. We report here a detailed characterization of the STSL in Caucasian and African-American cohorts. METHODS: Caucasian and African-American DNA samples were genotypes for polymorphisms at the STSL locus and haplotype structures determined for this locus RESULTS: In the Caucasian population, 13 variant single nucleotide polymorphisms (SNPs) were identified and resulting in 24 different haplotypes, compared to 11 SNPs in African-Americans resulting in 40 haplotypes. Three polymorphisms in ABCG8 were unique to the Caucasian population (E238L, INT10-50 and G575R), whereas one variant (A259V) was unique to the African-American population. Allele frequencies of SNPs varied also between these populations. CONCLUSION: We confirmed that despite their close proximity to each other, significantly more variations are present in ABCG8 compared to ABCG5. Pairwise D' values showed wide ranges of variation, indicating some of the SNPs were in strong linkage disequilibrium (LD) and some were not. LD was more prevalent in Caucasians than in African-Americans, as would be expected. These data will be useful in analyzing the proposed role of STSL in processes ranging from responsiveness to cholesterol-lowering drugs to selective sterol absorption

Trends in reported flooding in the UK: 1884–2013

A long term dataset of reported flooding based on reports from the UK Meteorological Office and the UK Centre for Ecology and Hydrology is described. This is possibly a unique dataset as the authors are unaware of any other 100+ year records of flood events and their consequences on a national scale. Flood events are classified by severity based upon qualitative descriptions. There is an increase in the number of reported flood events over time associated with an increased exposure to flooding as floodplain areas were developed. The data was de-trended for exposure, using population and dwelling house data. The adjusted record shows no trend in reported flooding over time, but there is significant decade to decade variability. This study opens a new approach considering flood occurrence over a long timescale using reported information (and thus likely effects on society) rather than just considering trends in extreme hydrological conditions.<br/

Characterization of long COVID temporal sub-phenotypes by distributed representation learning from electronic health record data: a cohort studyResearch in Context

Summary: Background: Characterizing Post-Acute Sequelae of COVID (SARS-CoV-2 Infection), or PASC has been challenging due to the multitude of sub-phenotypes, temporal attributes, and definitions. Scalable characterization of PASC sub-phenotypes can enhance screening capacities, disease management, and treatment planning. Methods: We conducted a retrospective multi-centre observational cohort study, leveraging longitudinal electronic health record (EHR) data of 30,422 patients from three healthcare systems in the Consortium for the Clinical Characterization of COVID-19 by EHR (4CE). From the total cohort, we applied a deductive approach on 12,424 individuals with follow-up data and developed a distributed representation learning process for providing augmented definitions for PASC sub-phenotypes. Findings: Our framework characterized seven PASC sub-phenotypes. We estimated that on average 15.7% of the hospitalized COVID-19 patients were likely to suffer from at least one PASC symptom and almost 5.98%, on average, had multiple symptoms. Joint pain and dyspnea had the highest prevalence, with an average prevalence of 5.45% and 4.53%, respectively. Interpretation: We provided a scalable framework to every participating healthcare system for estimating PASC sub-phenotypes prevalence and temporal attributes, thus developing a unified model that characterizes augmented sub-phenotypes across the different systems. Funding: Authors are supported by National Institute of Allergy and Infectious Diseases, National Institute on Aging, National Center for Advancing Translational Sciences, National Medical Research Council, National Institute of Neurological Disorders and Stroke, European Union, National Institutes of Health, National Center for Advancing Translational Sciences

Clinical phenotypes and outcomes in children with multisystem inflammatory syndrome across SARS-CoV-2 variant eras: a multinational study from the 4CE consortiumResearch in context

Summary: Background: Multisystem inflammatory syndrome in children (MIS-C) is a severe complication of SARS-CoV-2 infection. It remains unclear how MIS-C phenotypes vary across SARS-CoV-2 variants. We aimed to investigate clinical characteristics and outcomes of MIS-C across SARS-CoV-2 eras. Methods: We performed a multicentre observational retrospective study including seven paediatric hospitals in four countries (France, Spain, U.K., and U.S.). All consecutive confirmed patients with MIS-C hospitalised between February 1st, 2020, and May 31st, 2022, were included. Electronic Health Records (EHR) data were used to calculate pooled risk differences (RD) and effect sizes (ES) at site level, using Alpha as reference. Meta-analysis was used to pool data across sites. Findings: Of 598 patients with MIS-C (61% male, 39% female; mean age 9.7 years [SD 4.5]), 383 (64%) were admitted in the Alpha era, 111 (19%) in the Delta era, and 104 (17%) in the Omicron era. Compared with patients admitted in the Alpha era, those admitted in the Delta era were younger (ES −1.18 years [95% CI −2.05, −0.32]), had fewer respiratory symptoms (RD −0.15 [95% CI −0.33, −0.04]), less frequent non-cardiogenic shock or systemic inflammatory response syndrome (SIRS) (RD −0.35 [95% CI −0.64, −0.07]), lower lymphocyte count (ES −0.16 × 109/uL [95% CI −0.30, −0.01]), lower C-reactive protein (ES −28.5 mg/L [95% CI −46.3, −10.7]), and lower troponin (ES −0.14 ng/mL [95% CI −0.26, −0.03]). Patients admitted in the Omicron versus Alpha eras were younger (ES −1.6 years [95% CI −2.5, −0.8]), had less frequent SIRS (RD −0.18 [95% CI −0.30, −0.05]), lower lymphocyte count (ES −0.39 × 109/uL [95% CI −0.52, −0.25]), lower troponin (ES −0.16 ng/mL [95% CI −0.30, −0.01]) and less frequently received anticoagulation therapy (RD −0.19 [95% CI −0.37, −0.04]). Length of hospitalization was shorter in the Delta versus Alpha eras (−1.3 days [95% CI −2.3, −0.4]). Interpretation: Our study suggested that MIS-C clinical phenotypes varied across SARS-CoV-2 eras, with patients in Delta and Omicron eras being younger and less sick. EHR data can be effectively leveraged to identify rare complications of pandemic diseases and their variation over time. Funding: None