Background Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic, there has been increasing urgency to identify pathophysiological characteristics leading to severe clinical course in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Human leukocyte antigen alleles (HLA) have been suggested as potential genetic host factors that affect individual immune response to SARS-CoV-2. We sought to evaluate this hypothesis by conducting a multicenter study using HLA sequencing. Methods We analyzed the association between COVID-19 severity and HLAs in 435 individuals from Germany ( n = 135), Spain ( n = 133), Switzerland ( n = 20) and the United States ( n = 147), who had been enrolled from March 2020 to August 2020. This study included patients older than 18 years, diagnosed with COVID-19 and representing the full spectrum of the disease. Finally, we tested our results by meta-analysing data from prior genome-wide association studies (GWAS). Findings We describe a potential association of HLA-C*04:01 with severe clinical course of COVID-19. Carriers of HLA-C*04:01 had twice the risk of intubation when infected with SARS-CoV-2 (risk ratio 1.5 [95% CI 1.1–2.1], odds ratio 3.5 [95% CI 1.9–6.6], adjusted p -value = 0.0074). These findings are based on data from four countries and corroborated by independent results from GWAS. Our findings are biologically plausible, as HLA-C*04:01 has fewer predicted bindings sites for relevant SARS-CoV-2 peptides compared to other HLA alleles. Interpretation HLA-C*04:01 carrier state is associated with severe clinical course in SARS-CoV-2. Our findings suggest that HLA class I alleles have a relevant role in immune defense against SARS-CoV-2. Funding Funded by Roche Sequencing Solutions, Inc.

Recent advances in DNA sequencing open prospects to make whole-genome analysis rapid and reliable, which is promising for various applications including personalized medicine. However, existing techniques for de novo genome assembly, which is used for the analysis of genomic rearrangements, chromosome phasing, and reconstructing genomes without a reference, require solving tasks of high computational complexity. Here we demonstrate a method for solving genome assembly tasks with the use of quantum and quantum-inspired optimization techniques. Within this method, we present experimental results on genome assembly using quantum annealers both for simulated data and the $$\phi $$ ϕ X 174 bacteriophage. Our results pave a way for a significant increase in the efficiency of solving bioinformatics problems with the use of quantum computing technologies and, in particular, quantum annealing might be an effective method. We expect that the new generation of quantum annealing devices would outperform existing techniques for de novo genome assembly. To the best of our knowledge, this is the first experimental study of de novo genome assembly problems both for real and synthetic data on quantum annealing devices and quantum-inspired techniques.

A new ensemble filter that allows for the uncertainty in the prior distribution is proposed and tested. The filter relies on the conditional Gaussian distribution of the state given the model-error and predictability-error covariance matrices. The latter are treated as random matrices and updated in a hierarchical Bayes scheme along with the state. The (hyper)prior distribution of the covariance matrices is assumed to be inverse Wishart. The new Hierarchical Bayes Ensemble Filter (HBEF) assimilates ensemble members as generalized observations and allows ordinary observations to influence the covariances. The actual probability distribution of the ensemble members is allowed to be different from the true one. An approximation that leads to a practicable analysis algorithm is proposed. The new filter is studied in numerical experiments with a doubly stochastic one-variable model of "truth". The model permits the assessment of the variance of the truth and the true filtering error variance at each time instance. The HBEF is shown to outperform the EnKF and the HEnKF by Myrseth and Omre (2010) in a wide range of filtering regimes in terms of performance of its primary and secondary filters.

BackgroundNeuronal ceroid lipofuscinoses (NCLs) are a group of neurodegenerative disorders characterized by an accumulation of lipofuscin in the body's tissues. NCLs are associated with variable age of onset and progressive symptoms including seizures, psychomotor decline, and loss of vision.MethodsWe describe the clinical and molecular characteristics of four Russian patients with NCL (one female and three males, with ages ranging from 4 to 5 years). The clinical features of these patients include cognitive and motor deterioration, seizures, stereotypies, and magnetic resonance imaging signs of brain atrophy. Exome sequencing was performed to identify the genetic variants of patients with NCL. Additionally, we tested 6,396 healthy Russians for NCL alleles.ResultsWe identified five distinct mutations in four NCL‐associated genes of which two mutations are novel. These include a novel homozygous frameshift mutation in the CLN6 gene, a compound heterozygous missense mutation in the KCTD7 gene, and previously known mutations in KCTD7, TPP1, and MFSD8 genes. Furthermore, we estimated the Russian population carrier frequency of pathogenic and likely pathogenic variants in 13 genes associated with different types of NCL.ConclusionOur study expands the spectrum of mutations in lipofuscinosis. This is the first study to describe the molecular basis of NCLs in Russia and has profound and numerous clinical implications for diagnosis, genetic counseling, genotype–phenotype correlations, and prognosis.

One of the target drugs for plaque psoriasis treatment is apremilast, which is a selective phosphodiesterase 4 (PDE4) inhibitor. In this study, 34 moderate-to-severe and severe plaque psoriasis patients from Russia were treated with apremilast for 26 weeks. This allowed us to observe the effectiveness of splitting patient cohorts based on clinical outcomes, which were assessed using the Psoriasis Area Severity Index (PASI). In total, 14 patients (41%) indicated having an advanced outcome with delta PASI 75 after treatment; 20 patients indicated having moderate or no effects. Genome variability was investigated using the Illumina Infinium Global Screening Array. Genome-wide analysis revealed apremilast therapy clinical outcome associations at three compact genome regions with undefined functions situated on chromosomes 2, 4, and 5, as well as on a single single-nucleotide polymorphism (SNP) on chromosome 23. Pre-selected SNP sets were associated with psoriasis vulgaris analysis, which was used to identify four SNP-associated targeted therapy efficiencies: IL1β (rs1143633), IL4 (IL13) (rs20541), IL23R (rs2201841), and TNFα (rs1800629) genes. Moreover, we showed that the use of the global polygenic risk score allowed for the prediction of onset psoriasis in Russians. Therefore, these results can serve as a starting point for creating a predictive model of apremilast therapy response in the targeted therapy of patients with psoriasis vulgaris.

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Haplotypes defined by rs7041/rs4588 in GC gene modulate 25-hydroxyvitamin D (25(OH)D) and vitamin D-binding protein (DBP) levels. To investigate the distributions of GC polymorphisms, the rs7041 and rs4588 allele and haplotypes frequencies were analyzed in samples from different Eurasian regions. The GC1S haplotype associated with high level of serum 25(OH)D had the maximum frequency in European populations (except Finish population). Such frequency distributions may be a result of adaptation to low solar insolation rate. Besides, there was a strong trend of increasing GC1F haplotype frequency from Europe (10-15%) to Siberia and Easter Asia (40-45%).