Characterization of a Pan-Immunoglobulin Assay Quantifying Antibodies Directed against the Receptor Binding Domain of the SARS-CoV-2 S1-Subunit of the Spike Protein: A Population-Based Study.

Pan-immunoglobulin assays can simultaneously detect IgG, IgM and IgA directed against the receptor binding domain (RBD) of the S1 subunit of the spike protein (S) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 S1-RBD Ig). In this work, we aim to evaluate a quantitative SARS-CoV-2 S1-RBD Ig electrochemiluminescence immunoassay (ECLIA) regarding analytical, diagnostic, operational and clinical characteristics. Our work takes the form of a population-based study in the principality of Liechtenstein, including 125 cases with clinically well-described and laboratory confirmed SARS-CoV-2 infection and 1159 individuals without evidence of coronavirus disease 2019 (COVID-19). SARS-CoV-2 cases were tested for antibodies in sera taken with a median of 48 days (interquartile range, IQR, 43-52) and 139 days (IQR, 129-144) after symptom onset. Sera were also tested with other assays targeting antibodies against non-RBD-S1 and -S1/S2 epitopes. Sensitivity was 97.6% (95% confidence interval, CI, 93.2-99.1), whereas specificity was 99.8% (95% CI, 99.4-99.9). Antibody levels linearly decreased from hospitalized patients to symptomatic outpatients and SARS-CoV-2 infection without symptoms (p < 0.001). Among cases with SARS-CoV-2 infection, smokers had lower antibody levels than non-smokers (p = 0.04), and patients with fever had higher antibody levels than patients without fever (p = 0.001). Pan-SARS-CoV-2 S1-RBD Ig in SARS-CoV-2 infection cases significantly increased from first to second follow-up (p < 0.001). A substantial proportion of individuals without evidence of past SARS-CoV-2 infection displayed non-S1-RBD antibody reactivities (248/1159, i.e., 21.4%, 95% CI, 19.1-23.4). In conclusion, a quantitative SARS-CoV-2 S1-RBD Ig assay offers favorable and sustained assay characteristics allowing the determination of quantitative associations between clinical characteristics (e.g., disease severity, smoking or fever) and antibody levels. The assay could also help to identify individuals with antibodies of non-S1-RBD specificity with potential clinical cross-reactivity to SARS-CoV-2

Flattening the curve in 52 days: characterisation of the COVID-19 pandemic in the Principality of Liechtenstein - an observational study.

BACKGROUND The principality of Liechtenstein had its first COVID-19 case at the beginning of March 2020. After exponential growth, the pandemic&rsquo;s first wave was contained, with the last case being diagnosed 52 days after the initial occurrence. AIM To characterise the COVID-19 pandemic in Liechtenstein. METHODS All patients diagnosed in Liechtenstein were followed up until recovery and again 6&ndash;8 weeks after symptom onset. They were contacted every 2 days to record their clinical status until the resolution of their symptoms. The diagnosis of COVID-19 was based on clinical symptoms and molecular testing. Household and close workplace contacts were included in the follow-up, which also comprised antibody testing. In addition, public health measures installed during the pandemic in Liechtenstein are summarised. RESULTS During the first wave, 5% of the population obtained a reverse transcriptase polymerase chain reaction test. A total of 95 patients (median age 39 years) were diagnosed with COVID-19 (82 who resided in Liechtenstein), resulting in an incidence in Liechtenstein of 0.211%. One patient, aged 94, died (mortality rate 1%). Only 62% of patients could retrospectively identify a potential source of infection. Testing the patients&rsquo; household and close workplace contacts (n = 170) with antibody tests revealed that 25% of those tested were additional COVID-19 cases, a quarter of whom were asymptomatic. Those households which adhered to strict isolation measures had a significantly lower rate of affected household members than those who didn&rsquo;t follow such measures. The national public health measures never restricted free movement of residents. Masks were only mandatory in healthcare settings. The use of home working for the general workforce was promoted. Gatherings were prohibited. Schools, universities, certain public spaces (like sports facilities and playgrounds), childcare facilities, nonessential shops, restaurants and bars were closed. Social distancing, hygienic measures, solidarity and supporting individuals who were at risk were the main pillars of the public health campaigns. CONCLUSION The close collaboration of all relevant stakeholders allowed for the complete workup of all COVID-19 patients nationwide. A multitude of factors (e.g., young age of the patients, low-threshold access to testing, close monitoring of cases, high alertness and adherence to public health measures by the population) led to the early containment of the first wave of the pandemic, with a very low rate of serious outcomes. Antibody testing for SARS-CoV-2 revealed a substantial proportion of undiagnosed COVID-19 cases among close contacts of the patients

Controls of Initial Wood Decomposition on and in Forest Soils Using Standard Material

Forest ecosystems sequester approximately half of the world’s organic carbon (C), most of it in the soil. The amount of soil C stored depends on the input and decomposition rate of soil organic matter (OM), which is controlled by the abundance and composition of the microbial and invertebrate communities, soil physico-chemical properties, and (micro)-climatic conditions. Although many studies have assessed how these site-specific climatic and soil properties affect the decomposition of fresh OM, differences in the type and quality of the OM substrate used, make it difficult to compare and extrapolate results across larger scales. Here, we used standard wood stakes made from aspen (Populus tremuloides Michx.) and loblolly pine (Pinus taeda L.) to explore how climate and abiotic soil properties affect wood decomposition across 44 unharvested forest stands located across the northern hemisphere. Stakes were placed in three locations: (i) on top of the surface organic horizons (surface), (ii) at the interface between the surface organic horizons and mineral soil (interface), and (iii) into the mineral soil (mineral). Decomposition rates of both wood species was greatest for mineral stakes and lowest for stakes placed on the surface organic horizons, but aspen stakes decomposed faster than pine stakes. Our models explained 44 and 36% of the total variation in decomposition for aspen surface and interface stakes, but only 0.1% (surface), 12% (interface), 7% (mineral) for pine, and 7% for mineral aspen stakes. Generally, air temperature was positively, precipitation negatively related to wood stake decomposition. Climatic variables were stronger predictors of decomposition than soil properties (surface C:nitrogen ratio, mineral C concentration, and pH), regardless of stake location or wood species. However, climate-only models failed in explaining wood decomposition, pointing toward the importance of including local-site properties when predicting wood decomposition. The difficulties we had in explaining the variability in wood decomposition, especially for pine and mineral soil stakes, highlight the need to continue assessing drivers of decomposition across large global scales to better understand and estimate surface and belowground C cycling, and understand the drivers and mechanisms that affect C pools, CO2 emissions, and nutrient cycles

Frequency of serological non-responders and false-negative RT-PCR results in SARS-CoV-2 testing: a population-based study.

Objectives The sensitivity of molecular and serological methods for COVID-19 testing in an epidemiological setting is not well described. The aim of the study was to determine the frequency of negative RT-PCR results at first clinical presentation as well as negative serological results after a follow-up of at least 3 weeks. Methods Among all patients seen for suspected COVID-19 in Liechtenstein (n=1921), we included initially RT-PCR positive index patients (n=85) as well as initially RT-PCR negative (n=66) for follow-up with SARS-CoV-2 antibody testing. Antibodies were detected with seven different commercially available immunoassays. Frequencies of negative RT-PCR and serology results in individuals with COVID-19 were determined and compared to those observed in a validation cohort of Swiss patients (n=211). Results Among COVID-19 patients in Liechtenstein, false-negative RT-PCR at initial presentation was seen in 18% (12/66), whereas negative serology in COVID-19 patients was 4% (3/85). The validation cohort showed similar frequencies: 2/66 (3%) for negative serology, and 16/155 (10%) for false negative RT-PCR. COVID-19 patients with negative follow-up serology tended to have a longer disease duration (p=0.05) and more clinical symptoms than other patients with COVID-19 (p<0.05). The antibody titer from quantitative immunoassays was positively associated with the number of disease symptoms and disease duration (p<0.001). Conclusions RT-PCR at initial presentation in patients with suspected COVID-19 can miss infected patients. Antibody titers of SARS-CoV-2 assays are linked to the number of disease symptoms and the duration of disease. One in 25 patients with RT-PCR-positive COVID-19 does not develop antibodies detectable with frequently employed and commercially available immunoassays

Genome-wide analyses identify SCN5A as a susceptibility locus for premature atrial contraction frequency.

Premature atrial contractions (PACs) are frequently observed on electrocardiograms and are associated with increased risks of atrial fibrillation (AF), stroke, and mortality. In this study, we aimed to identify genetic susceptibility loci for PAC frequency. We performed a genome-wide association study meta-analysis with PAC frequency obtained from ambulatory cardiac monitoring in 4,831 individuals of European ancestry. We identified a genome-wide significant locus at the SCN5A gene. The lead variant, rs7373862, located in an intron of SCN5A, was associated with an increase of 0.12 [95% CI 0.08-0.16] standard deviations of the normalized PAC frequency per risk allele. Among genetic variants previously associated with AF, there was a significant enrichment in concordance of effect for PAC frequency (n = 73/106, p = 5.1 × 10-5). However, several AF risk loci, including PITX2, were not associated with PAC frequency. These findings suggest the existence of both shared and distinct genetic mechanisms for PAC frequency and AF

An Extremes of outcome strategy provides evidence that multiple sclerosis severity is determined by alleles at the <i>HLA-DRB1</i> locus

Multiple sclerosis (MS) is a common inflammatory disease of the central nervous system unsurpassed for variability in disease outcome. A cohort of sporadic MS cases (n=63), taken from opposite extremes of the distribution of long-term outcome, was used to determine the role of the HLA-DRB1 locus on MS disease severity. Genotyping sets of benign and malignant MS patients showed that HLA-DRB1*01 was significantly underrepresented in malignant compared with benign cases. This allele appears to attenuate the progressive disability that characterizes MS in the long term. The observation was doubly replicated in (i) Sardinian benign and malignant patients and (ii) a cohort of affected sibling pairs discordant for HLA-DRB1*01. Among the latter, mean disability progression indices were significantly lower in those carrying the HLA-DRB1*01 allele compared with their disease-concordant siblings who did not. The findings were additionally supported by similar transmission distortion of HLA-DRB1*04 subtypes closely related to HLA-DRB1*01. The protective effect of HLA-DRB1*01 in sibling pairs may result from a specific epistatic interaction with the susceptibility allele HLA-DRB1*1501. A high-density (&gt;700) SNP examination of the MHC region in the benign and malignant patients could not identify variants differing significantly between the two groups, suggesting that HLA-DRB1 may itself be the disease-modifying locus. We conclude that HLA-DRB1*01, previously implicated in disease resistance, acts as an independent modifier of disease progression. These results closely link susceptibility to long-term outcome in MS, suggesting that shared quantitative MHC-based mechanisms are common to both, emphasizing the central role of this region in pathogenesis

A random forest approach to the detection of epistatic interactions in case-control studies

<p>Abstract</p> <p>Background</p> <p>The key roles of epistatic interactions between multiple genetic variants in the pathogenesis of complex diseases notwithstanding, the detection of such interactions remains a great challenge in genome-wide association studies. Although some existing multi-locus approaches have shown their successes in small-scale case-control data, the "combination explosion" course prohibits their applications to genome-wide analysis. It is therefore indispensable to develop new methods that are able to reduce the search space for epistatic interactions from an astronomic number of all possible combinations of genetic variants to a manageable set of candidates.</p> <p>Results</p> <p>We studied case-control data from the viewpoint of binary classification. More precisely, we treated single nucleotide polymorphism (SNP) markers as categorical features and adopted the random forest to discriminate cases against controls. On the basis of the gini importance given by the random forest, we designed a sliding window sequential forward feature selection (SWSFS) algorithm to select a small set of candidate SNPs that could minimize the classification error and then statistically tested up to three-way interactions of the candidates. We compared this approach with three existing methods on three simulated disease models and showed that our approach is comparable to, sometimes more powerful than, the other methods. We applied our approach to a genome-wide case-control dataset for Age-related Macular Degeneration (AMD) and successfully identified two SNPs that were reported to be associated with this disease.</p> <p>Conclusion</p> <p>Besides existing pure statistical approaches, we demonstrated the feasibility of incorporating machine learning methods into genome-wide case-control studies. The gini importance offers yet another measure for the associations between SNPs and complex diseases, thereby complementing existing statistical measures to facilitate the identification of epistatic interactions and the understanding of epistasis in the pathogenesis of complex diseases.</p

Nitrogen Increases Early-Stage and Slows Late-Stage Decomposition Across Diverse Grasslands

To evaluate how increased anthropogenic nutrient inputs alter carbon cycling in grasslands, we conducted a litter decomposition study across 20 temperate grasslands on three continents within the Nutrient Network, a globally distributed nutrient enrichment experiment We determined the effects of addition of experimental nitrogen (N), phosphorus (P) and potassium plus micronutrient (Kμ) on decomposition of a common tree leaf litter in a long-term study (maximum of 7 years; exact deployment period varied across sites). The use of higher order decomposition models allowed us to distinguish between the effects of nutrients on early- versus late-stage decomposition. Across continents, the addition of N (but not other nutrients) accelerated early-stage decomposition and slowed late-stage decomposition, increasing the slowly decomposing fraction by 28% and the overall litter mean residence time by 58%. Synthesis. Using a novel, long-term cross-site experiment, we found widespread evidence that N enhances the early stages of above-ground plant litter decomposition across diverse and widespread temperate grassland sites but slows late-stage decomposition. These findings were corroborated by fitting the data to multiple decomposition models and have implications for N effects on soil organic matter formation. For example, following N enrichment, increased microbial processing of litter substrates early in decomposition could promote the production and transfer of low molecular weight compounds to soils and potentially enhance the stabilization of mineral-associated organic matter. By contrast, by slowing late-stage decomposition, N enrichment could promote particulate organic matter (POM) accumulation. Such hypotheses deserve further testing

A General Framework for Formal Tests of Interaction after Exhaustive Search Methods with Applications to MDR and MDR-PDT

The initial presentation of multifactor dimensionality reduction (MDR) featured cross-validation to mitigate over-fitting, computationally efficient searches of the epistatic model space, and variable construction with constructive induction to alleviate the curse of dimensionality. However, the method was unable to differentiate association signals arising from true interactions from those due to independent main effects at individual loci. This issue leads to problems in inference and interpretability for the results from MDR and the family-based compliment the MDR-pedigree disequilibrium test (PDT). A suggestion from previous work was to fit regression models post hoc to specifically evaluate the null hypothesis of no interaction for MDR or MDR-PDT models. We demonstrate with simulation that fitting a regression model on the same data as that analyzed by MDR or MDR-PDT is not a valid test of interaction. This is likely to be true for any other procedure that searches for models, and then performs an uncorrected test for interaction. We also show with simulation that when strong main effects are present and the null hypothesis of no interaction is true, that MDR and MDR-PDT reject at far greater than the nominal rate. We also provide a valid regression-based permutation test procedure that specifically tests the null hypothesis of no interaction, and does not reject the null when only main effects are present. The regression-based permutation test implemented here conducts a valid test of interaction after a search for multilocus models, and can be applied to any method that conducts a search to find a multilocus model representing an interaction