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Background Lactase persistence — the ability to digest lactose through adulthood — is closely related to evolutionary adaptations and has affected many populations since the beginning of cattle breeding. Nevertheless, the contrast initial phenotype, lactase non-persistence or adult lactase deficiency, is still affecting large numbers of people worldwide. Methods We performed the largest multiethnic genetic study of lactase deficiency on 24439 people in Russia to date. The percent of each population group was estimated according to the local ancestry inference results. Additionally, we calculated frequencies of rs4988235 GG genotype in Russian regions using the information of current location and birthplace data in client’s questionnaire. Results It turned out that among all studied population groups the frequency of GG genotype in rs4988235 was higher than in average in the European populations. In particular, the prevalence of lactase deficiency genotype in the East Slavs group was 42.8% (95% CI: 42.1–43.4%). We also investigated the regional prevalence of lactase deficiency by current place of residence. Conclusions Our study emphasizes the diagnostic significance of genetic testing, i.e. specifically for lactose intolerance parameter, as well as the scale of the problem of lactase deficiency in Russia which needs to be addressed by healthcare and food industry.

The Minusinsk Basin in Southern Siberia had unique conditions for the development of ancient societies, thanks to its geographical location, favorable climatic conditions, and relative isolation. Located at the northern periphery of the eastern Eurasian steppe, surrounded by the Altai-Sayan Mountains this area witnessed numerous ancient human migrations with specific types of interaction between outside and local archaeological cultures. The genomic history of the human population of Southern Siberia from the Chalcolithic to the middle Bronze Age has been relatively well described in the recent genome-wide studies, while the genetic ancestry of populations, represented by diverse archaeological cultures of the Late Bronze and Early Iron Ages, remains a blank spot for modern paleogenomics. Here, for the first time, we present two ancient nuclear genomes of the individuals buried in the Oglakhty cemetery (early Tashtyk culture, 2nd to 4th centuries AD). Our pilot study is undertaken within a multidisciplinary project on this noteworthy site with well-preserved organic remains and provides fresh paleogenomic data on the ancient societies of Southern Siberia.

In a cohort of 106 donors, we analyzed correlations in the binding of natural antibodies to human glycans in a composition of the glycan array. Along with trivial relationships (between structurally similar glycans), we found a high positive correlation between completely unrelated glycans. The most intriguing among the negative is the correlation of average strength (close to –0.5) between antibodies to Galβ1-3GlcNAc and antibodies to lactosamines (Galβ1-4GlcNAc)n. The reason for the functional antagonism between these antibodies is not yet clear.

Accurate library quantification is very important during post-pooling captured target sequencing. There are a number of methods available to quantify libraries prior to sequencing, but no gold standard for the quantification of libraries exists. In this study, we compared common library quantification methods (Labchip, Qubit 3.0, qPCR with three primer sets) with ultra-low coverage sequencing (MiSeq with and without insert size correction). Cost, time and quantification accuracy were considered. We found that Qubit and MiSeq were better than qPCR and LabChip at predicting the final concentration. Also we revealed that MiSeq with insert size correction was the most accurate method for library quantification prior to target sequencing. This method allows for correction shifts in the ratio due to enrichment. Ultra-low coverage sequencing by Illumina MiSeq is the most accurate method for library quantification prior to pooling and post-pooling target enrichment.

Body mass index (BMI) is a highly heritable polygenic trait. It is also affected by various environmental and behavioral risk factors. We used a BMI polygenic risk score (PRS) to study the interplay between the genetic and environmental factors defining BMI. First, we generated a BMI PRS that explained more variance than a BMI genetic risk score (GRS), which was using only genome-wide significant BMI-associated variants (R2= 13.1% compared to 6.1%). Second, we analyzed interactions between BMI PRS and seven environmental factors. We found a significant interaction between physical activity and BMI PRS, even when the well-known effect of theFTOregion was excluded from the PRS, using a small dataset of 6,179 samples. Third, we stratified the study population into two risk groups using BMI PRS. The top 22% of the studied populations were included in a high PRS risk group. Engagement in self-reported physical activity was associated with a 1.66 kg/m2decrease in BMI in this group, compared to a 0.84 kg/m2decrease in BMI in the rest of the population. Our results (i) confirm that genetic background strongly affects adult BMI in the general population, (ii) show a non-linear interaction between BMI genetics and physical activity, and (iii) provide a standardized framework for future gene-environment interaction analyses.

One of the most promising areas of research into the biological underpinnings of depression is genetic studies. However, the absence of generally accepted phenotyping methods leads to the difficulties in generalizing their results due to the heterogeneity of the samples. Thus, the development of a reliable and convenient phenotyping method that allows large sample sizes to be included in studies remains a top priority for the further development of genetic studies of depression.The aim of this study was to evaluate the applicability of the online version of the depression subscale of Hospital Anxiety and Depression Scale (HADS-D) for depression phenotype screening in the general population. Using online HADS-D we performed screening of depressive symptoms and compared results with known population patterns of depression.We conducted an online survey of 2610 Russian-speaking respondents over the age of 18. The overall HADS-D score was higher in women (p=0.003), in individuals under 30 y.o compared to participants over 42 y.o. (p=0.004) and in individuals reporting cardiovascular diseases (CVD) symptoms (pLinear regression showed that the presence of CVD leads to higher HADS-D scores (pThese results are consistent with the known data on the association of sex, age, and the presence of CVD with the prevalence of depression. The online version of HADS-D, given the ease of its usage, can be regarded as an effective tool for phenotyping depression in the general population.

Non-invasive prenatal testing (NIPT) for aneuploidy on Chromosomes 21 (T21), 18 (T18) and 13 (T13) is actively used in clinical practice around the world. One of the limitations of the wider implementation of this test is the high cost of the analysis itself, as high-throughput sequencing is still relatively expensive. At the same time, there is an increasing trend in the length of reads yielded by sequencers. Since extracellular DNA is short, in the order of 140&ndash, 160 bp, it is not possible to effectively use long reads. The authors used high-performance sequencing of cell-free DNA (cfDNA) libraries that went through additional stages of enzymatic fragmentation and random ligation of the resulting products to create long chimeric reads. The authors used a controlled set of samples to analyze a set of cfDNA samples from pregnant women with a high risk of fetus aneuploidy according to the results of the first trimester screening and confirmed by invasive karyotyping of the fetus using laboratory and analytical approaches developed by the authors. They evaluated the sensitivity, specificity, PPV (positive predictive value), and NPV (negative predictive value) of the results. The authors developed a technique for constructing long chimeric reads from short cfDNA fragments and validated the test using a control set of extracellular DNA samples obtained from pregnant women. The obtained sensitivity and specificity parameters of the NIPT developed by the authors corresponded to the approaches proposed earlier (99.93% and 99.14% for T21, 100% and 98.34% for T18, 100% and 99.17% for T13, respectively).

Background Neuronal 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. Methods We 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. Results We 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. Conclusion Our 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., 5 distinct mutations were identified in 4 NCL‐caused genes, of which two mutations are novel. Also carrier frequency of pathogenic and likely pathogenic variants in 13 genes associated with different types of NCL were estimated in Russian population.

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 {\it 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 $\phi$X 174 bacteriophage. Our results pave a way for an increase in the efficiency of solving bioinformatics problems with the use of quantum computing and, in particular, quantum annealing. We expect that the new generation of quantum annealing devices would outperform existing techniques for {\it 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., Comment: 9 pages, 4 figures

Chromosomes of embryos of couples with reduced number of morphologically normal sperm cells (less than 4%) and couples with a normal level of morphologically normal sperm cells (over 4%) has revealed significant differences. In the group with a low level of normal spermatozoa, the frequency of embryos with normal chromosomes is significantly reduced and incidence of sex chromosome trisomies and autosomal monosomies and trisomies is increased; a tendency to decrease has been found for the frequency of male embryos. The obtained data may be useful to establish additional criteria for preimplantation genetic screening in the case of male infertility.

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.

We obtain the analogue of the classical result by Erdos and Kac on the limiting distribution of the maximum of partial sums for exchangeable random variables with zero mean and variance one. We show that, if the conditions of the central limit theorem of Blum et al. hold, the limit coincides with the classical one. Under more general assumptions, the probability of the random variables having conditional negative drift appears in the limit.

Liability to alcohol dependence is heritable, but little is known about its complex polygenic architecture. We performed a genome-wide association study (GWAS) of self-reported alcohol consumption in 1798 of Russian individuals. No SNP reached genome-wide significance for any alcohol drinking patterns: never drinking, everyday drinking, once per week drinking and once per month drinking. Polymorphisms in previously reported genes of KLB and AUTS2 were significant associated with everyday drinking and once per week drinking patterns, respectively. We also found associations of genes involved in nervous system function and mental disorders with some alcohol drinking patterns. This study identifies novel gene associations that should be the focus of future studies investigating the neurobiology of alcohol consumption.

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: IL1&beta, (rs1143633), IL4 (IL13) (rs20541), IL23R (rs2201841), and TNF&alpha, (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.

The principle of multifactorial traits (MTs) inheritance relies on the presence of a large number of genetic markers, with each marker contributing to the probability of developing those traits. This work proposes an algorithm for the selection of DNA markers that could be used to develope a prognostic test system for the assessment of individual predisposition to MTs. The method is based on the selection of genetic markers that have demonstrated a statistically significant association with an MT under consideration and have been described as functionally significant polymorphisms affecting MT development. If the functional significance of a polymorphism has not been described so far, then to be reliably associated with an MT, this polymorphism is expected to achieve genome-wide significance in one of the studies and such significance must be confirmed in an independent sample. Papers that are used to assess the association of genetic markers with MTs are expected to meet the proposed criteria depending on the study type., Принцип наследования многофакторных фенотипических особенностей (МФО) заключается в наличии значительного количества генетических маркеров, каждый из которых вносит некоторый вклад в вероятность развития данной особенности. В данной работе предложен алгоритм отбора ДНК-маркеров с целью разработки прогностических тест-систем для определения индивидуальной предрасположенности к МФО. Метод заключается в отборе генетических маркеров, показавших статистически достоверную ассоциацию с данной МФО, а также функционально значимые полиморфизмы, для которых описаны механизмы влияния на развитие МФО. Если функциональная значимость полиморфизма не описана, критерием его статистически достоверной ассоциации с МФО является достижение полногеномной значимости в одном из исследований и подтверждение данной ассоциации на независимой выборке. Научные публикации, используемые для оценки ассоциации генетических маркеров с МФО, в зависимости от типа исследования должны соответствовать приведенным критериям.

Depression is one of the leading causes of decreased quality of life and social functioning of patients. In the context of preventive medicine, the prevention of depression becomes a priority. To achieve the goals of prevention, it is necessary to identify specific population risk groups - individuals with a high genetic risk of depression. The paper describes the project aimed at developing a genetic test system based on polygenic risk scores (PRS) for depression, considering the multi-ethnicity and multicultural diversity of the Russian population. As a result of the study, data on the genetic architecture of depression (GWAS) and PRS for depression will be obtained for the first time. The emergence of a genetic test system developed in the study of the Russian population and in the conditions of a constant decrease in the cost of genetic research will allow an effective transition to preventive medicine in the area of mental health.Депрессия является одной из ведущих причин снижения качества жизни и социального функционирования пациентов. В рамках превентивной медицины профилактика депрессии становится приоритетным направлением. Для достижения задач профилактики необходимы возможности выявления в популяции групп риска — индивидуумов с высоким уровнем генетического риска развития депрессии. В статье описываются методология и дизайн проекта, направленного на разработку генетической тест-системы на основе полигенных шкал риска (PRS) развития депрессии с учетом полиэтничности и мультикультурального характера российской популяции. В результате выполнения исследования должны быть впервые получены данные о генетической архитектуре депрессии (методом GWAS) и выявлены полигенные шкалы риска (PRS) развития депрессии. Появление генетической тест-системы, разработанной при изучении российской популяции и в условиях постоянного снижения стоимости генетических исследований, позволит осуществить эффективный переход к развитию превентивной медицины в области психического здоровья.

We develop our previous works concerning the identification of the collection of significant factors determining some, in general, nonbinary random response variable. Such identification is important, e.g., in biological and medical studies. Our approach is to examine the quality of response variable prediction by functions in (certain part of) the factors. The prediction error estimation requires some cross-validation procedure, certain prediction algorithm, and estimation of the penalty function. Using simulated data, we demonstrate the efficiency of our method. We prove a new central limit theorem for introduced regularized estimates under some natural conditions for arrays of exchangeable random variables.

Effects of non-stationarity on the performance of hybrid ensemble filters are studied (by hybrid filters we mean those which blend ensemble covariances with some other regularizing covariances). To isolate effects of non-stationarity from effects due to nonlinearity (and the non-Gaussianity it causes), a new doubly stochastic advection-diffusion-decay model (DSADM) is proposed. The model is hierarchical: it is a linear stochastic partial differential equation whose coefficients are random fields defined through their own stochastic partial differential equations. DSADM generates conditionally Gaussian spatiotemporal random fields with a tunable degree of non-stationarity in space and time. DSADM allows the use of the exact Kalman filter as a baseline benchmark. In numerical experiments with DSADM as the "model of truth", the relative importance of the three kinds of covariance blending is studied: with static, time-smoothed, and space-smoothed covariances. It is shown that the stronger the non-stationarity, the less useful the static covariance matrix becomes and the more beneficial the time-smoothed covariances are. Time-smoothing of background-error covariances proved to be systematically more useful than their space-smoothing. Under non-stationarity, a filter that extends the (previously proposed by the authors) Hierarchical Bayes Ensemble Filter and accommodates the three covariance-blending techniques is shown to outperform all other configurations of the filters tested. The R code of the model and the filters is available from github.com/cyrulnic/NoStRa., Comment: The accepted version of the published article

The paper treats a new approach to reducing the dimension of factors which affect the non-binary response variable Y. This is relevant in analysis of a number of stochastic models, for instance, in biological and medical studies. The quality of Y estimation by means of a function in those factors is described by a specified error functional. It involves a penalty function to take into account the importance of the forecast for different response values. The joint distribution of factors and response variable is unknown. Thus it is quite natural to employ for statistical inference the estimates of the error functional constructed by prediction algorithm and cross-validation procedure. One of our main results provides the criterion of strong consistency of such estimates as the number of observations tends to infinity. Due to this result one can identify the significant factors. We introduce also the regularized versions of estimates and establish for them the central limit theorem (CLT). The statistical variant of our CLT permits to construct the approximate confidence intervals for unknown error functional.

Accurate DNA library quantification is very important in post-pooling captured exome sequencing. Underrepresented libraries will need additional sequencing, which takes extra time and money, whereas overexpressed DNA libraries can lead to the generation of more data than required, which leads to the waste of sequence capacity and a reduced number of samples per batch. There is a number of methods available to quantify DNA libraries prior to sequencings, such as UV absorption, use of intercalating dyes, capillary electrophoresis, 5’-hydrolysis probes (TaqMan©) coupled with quantitative PCR (qPCR) or droplet digital PCR. But there is no gold standard for the quantification of DNA libraries. This study compares common library quantification methods, including LabChip (PerkinElmer Inc., MA, USA), Qubit 3.0 (Thermo Fisher Scientific, MA, USA), several qPCR approaches, and ultralow coverage sequencing on Illumina MiSeq platform (with and without insert size correction). DNA libraries were prepared using the NEBNext Ultra DNA Library Prep Kit for Illumina (New England Biolabs, MA, USA). To compare the above-mentioned approaches, cost, time, and quantification accuracy were assessed in our study. Quantification methods involving the use of Qubit and MiSeq were found to be better than qPCR and LabChip approaches at predicting the final library concentration. It was also revealed that MiSeq with insert size correction was the most accurate method for library quantification prior to exome sequencing. This method allows for correction shifts in the ratio due to enrichment. Ultralow coverage sequencing on the Illumina MiSeq platform is the most accurate method of library quantification prior to pooling and post-pooling exome enrichment.