Publications by authors named "Aulchenko Y"

N-glycome analysis of individual proteins and tissues is crucial for fundamental and applied biomedical research and medical diagnosis and plays an important role in the evaluation of the quality of biopharmaceutical and biotechnological products. The interest in this research area continues to grow annually, thereby increasing the demand for the high-throughput profiling of human blood plasma N-glycome. In response to this need, we have developed an optimized, simple, and rapid protocol for the N-glycome profiling of human plasma proteins.

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The course of COVID-19 is highly variable, with genetics playing a significant role. Through large-scale genetic association studies, a link between single nucleotide polymorphisms and disease susceptibility and severity was established. However, individual single nucleotide polymorphisms identified thus far have shown modest effects, indicating a polygenic nature of this trait, and individually have limited predictive performance.

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Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioural traits and the disease aetiology of neuropsychiatric disorders. Here the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,000 individuals for 184 neuro-related proteins in human plasma. The analysis identified 125 cis-regulatory protein quantitative trait loci (cis-pQTL) and 164 trans-pQTL.

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Glycans are an essential structural component of immunoglobulin G (IgG) that modulate its structure and function. However, regulatory mechanisms behind this complex posttranslational modification are not well known. Previous genome-wide association studies (GWAS) identified 29 genomic regions involved in regulation of IgG glycosylation, but only a few were functionally validated.

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Conventional measurements of fasting and postprandial blood glucose levels investigated in genome-wide association studies (GWAS) cannot capture the effects of DNA variability on 'around the clock' glucoregulatory processes. Here we show that GWAS meta-analysis of glucose measurements under nonstandardized conditions (random glucose (RG)) in 476,326 individuals of diverse ancestries and without diabetes enables locus discovery and innovative pathophysiological observations. We discovered 120 RG loci represented by 150 distinct signals, including 13 with sex-dimorphic effects, two cross-ancestry and seven rare frequency signals.

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Chronic back pain (CBP) is a complex heritable trait and a major cause of disability worldwide. We developed and validated a genome-wide polygenic risk score (PRS) for CBP using a large-scale GWAS based on UK Biobank participants of European ancestry (N = 265,000). The PRS showed poor overall predictive ability (AUC = 0.

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Glycosylation is an important protein modification, which influences the physical and chemical properties as well as biological function of these proteins. Large-scale population studies have shown that the levels of various plasma protein N-glycans are associated with many multifactorial human diseases. Observed associations between protein glycosylation levels and human diseases have led to the conclusion that N-glycans can be considered a potential source of biomarkers and therapeutic targets.

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Article Synopsis
  • A bidirectional Mendelian randomization study was conducted to analyze how six personality traits (including anxiety and neuroticism) impact back pain, and how back pain influences these traits.
  • Genetic data from major studies of individuals with European ancestry were used to perform sophisticated statistical analyses for this investigation.
  • Results indicated a strong causal relationship between neuroticism and back pain, suggesting that managing neuroticism could be beneficial for patients suffering from back pain.
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Background Context: Chronic back pain (CBP) is a common debilitating condition with substantial societal impact. While understanding genotype-by-environment (GxE) interactions may be crucial to achieving the goals of personalized medicine, there are few large-scale studies investigating this topic for CBP. None of them systematically explore multiple CBP risk factors.

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Background Context: Cardiovascular risk factors (hypertension, dyslipidemia, and type II diabetes) have been proposed as risk factors for back pain. However, few longitudinal studies have found significant associations between cardiovascular risk factors and back pain, and these may be explained by confounding or reverse causation.

Purpose: To examine potential causal effects of cardiovascular risk factors on back pain, and vice versa.

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Back pain is the leading cause of years lived with disability worldwide, yet surprisingly, little is known regarding the biology underlying this condition. The impact of genetics is known for chronic back pain: its heritability is estimated to be at least 40%. Large genome-wide association studies have shown that common variation may account for up to 35% of chronic back pain heritability; rare variants may explain a portion of the heritability not explained by common variants.

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The problem of isolating high-quality total RNA from intervertebral discs has no recognized solution yet. This is due to the extremely low content of live cells in the samples and the voluminous intercellular matrix. A variety of published protocols focused on isolating RNA from articular cartilage have recommended the use of expensive equipment, enzymatic matrix cleavage, or cell culture.

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In recent years, the number of genome-wide association studies (GWAS) carried out for various economically important animal traits has been increasing. GWAS discoveries provide summary statistics that can be used both for targeted marker-oriented selection and for studying the genetic control of economically important traits of farm animals. In contrast to research in human genetics, GWAS on farm animals often does not meet generally accepted standards (availability of information about effect and reference alleles, the size and direction of the effect, etc.

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Purpose: Risk factors for chronic back pain (CBP) may share underlying genetic factors, making them difficult to study using conventional methods. We conducted a bi-directional Mendelian randomisation (MR) study to examine the causal effects of risk factors (education, smoking, alcohol consumption, physical activity, sleep and depression) on CBP and the causal effect of CBP on the same risk factors.

Methods: Genetic instruments for risk factors and CBP were obtained from the largest published genome-wide association studies (GWAS) of risk factor traits conducted in individuals of European ancestry.

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Being one of the most dynamic entities in the human body, glycosylation of proteins fine-tunes the activity of the organismal machinery, including the immune system, and mediates the interaction with the human microbial consortium, typically represented by the gut microbiome. Using data from 194 healthy individuals, we conducted an associational study to uncover potential relations between the gut microbiome and the blood plasma N-glycome, including N-glycome of immunoglobulin G. While lacking strong linkages on the multivariate level, we were able to identify associations between alpha and beta microbiome diversity and the blood plasma N-glycome profile.

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Lumbar intervertebral disc degeneration (DD) disease is one of the main risk factors for low back pain and a leading cause of population absenteeism and disability worldwide. Despite a variety of biological studies, lumbar DD is not yet fully understood, partially because there are only few studies that use systematic and integrative approaches. This urges the need for studies that integrate different omics (including genomics and transcriptomics) measured on samples within a single cohort.

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We present ANANASTRA, https://ananastra.autosome.org, a web server for the identification and annotation of regulatory single-nucleotide polymorphisms (SNPs) with allele-specific binding events.

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Article Synopsis
  • Post-translational modifications (PTMs) play a crucial role in protein function and cell signaling, yet their genetic regulation is still not fully understood.
  • This study compares the genetic regulation of glycosylation in two proteins, transferrin and immunoglobulin G (IgG), identifying new genetic loci associated with transferrin glycosylation.
  • The findings reveal that while some genes affecting glycosylation are specific to each protein, there are also shared genetic influences, indicating a complex interplay in how these modifications are regulated.
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Article Synopsis
  • - Changes in the N-glycosylation of immunoglobulin G (IgG) are linked to various diseases, but it's unclear if these changes are a cause or a result of the diseases.
  • - This study used a method called two sample Mendelian randomization (MR) to analyze the relationship between IgG N-glycosylation traits and 12 diseases, finding a positive causal effect of systemic lupus erythematosus (SLE) on specific IgG glycosylation patterns.
  • - The authors recommend considering the glycosylation trait as a potential biomarker for SLE and highlight the need for more comprehensive genome-wide association studies (GWAS) to better understand the connections between Ig
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Background: Understanding the influence of genetic variants on DNA methylation is fundamental for the interpretation of epigenomic data in the context of disease. There is a need for systematic approaches not only for determining methylation quantitative trait loci (methQTL), but also for discriminating general from cell type-specific effects.

Results: Here, we present a two-step computational framework MAGAR ( https://bioconductor.

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Although changes in protein glycosylation are observed in a wide range of diseases and pathological states, the examples of use of glycans as biomarkers and therapeutic targets are limited. This is not in small part because the understanding of human glycome regulation in vivo is incomplete and fragmented. Combination of human glycomics and genomics offers a powerful "data-driven hypotheses" approach to dissect the complex human glycobiology in vivo in an agnostic manner.

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Article Synopsis
  • Chronic widespread musculoskeletal pain (CWP) is closely related to fibromyalgia and has a heritable component of 48%-54%, but its genetic factors are still unclear, prompting a genome-wide association study for insight.
  • The study involved 6,914 cases of CWP from the UK Biobank and aimed to validate findings in multiple European cohorts, focusing on genetic correlations and tissue specificity.
  • Results identified three significant genetic loci associated with CWP, with one locus showing strong replication, while another displayed a suggestive link; findings also highlighted the relevance of skeletal muscle in the condition's genetic background.
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Identifying genetic risk factors for lumbar spine disorders may lead to knowledge regarding underlying mechanisms and the development of new treatments. We conducted a genome-wide association study involving 100,811 participants with genotypes and longitudinal electronic health record data from the Electronic Medical Records and Genomics Network and Geisinger Health. Cases and controls were defined using validated algorithms and clinical diagnostic codes.

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The N-glycosylation of immunoglobulin G (IgG) affects its structure and function. It has been demonstrated that IgG N-glycosylation patterns are inherited as complex quantitative traits. Genome-wide association studies identified loci harboring genes encoding enzymes directly involved in protein glycosylation as well as loci likely to be involved in regulation of glycosylation biochemical pathways.

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Article Synopsis
  • Adult height has been a key focus in studies of heritability and helped develop the classical polygenic model for understanding complex traits.
  • The traditional model assumes that effects are additive and residuals are normally distributed, but this may not hold true in larger studies involving many individuals.
  • Findings suggest that for large-scale analyses, incorporating non-additive interactions among sex, environment, and genes is essential, or alternatively, using a log-normal approximation can maintain the robustness of the additive model.
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