Yakov A. Tsepilov

Development and application of genomic control methods for genome-wide association studies using non-additive models

Genome-wide association studies (GWAS) comprise a powerful tool for mapping genes of complex traits. However, an inflation of the test statistic can occur because of population substructure or cryptic relatedness, which could cause spurious associations. If information on a large number of genetic markers is available, adjusting the analysis results by using the method of genomic control (GC) is possible. GC was originally proposed to correct the Cochran-Armitage additive trend test. For non-additive models, correction has been shown to depend on allele frequencies. Therefore, usage of GC is limited to situations where allele frequencies of null markers and candidate markers are matched. In this work, we extended the capabilities of the GC method for non-additive models, which allows us to use null markers with arbitrary allele frequencies for GC. Analytical expressions for the inflation of a test statistic describing its dependency on allele frequency and several population parameters were obtained for recessive, dominant, and over-dominant models of inheritance. We proposed a method to estimate these required population parameters. Furthermore, we suggested a GC method based on approximation of the correction coefficient by a polynomial of allele frequency and described procedures to correct the genotypic (two degrees of freedom) test for cases when the model of inheritance is unknown. Statistical properties of the described methods were investigated using simulated and real data. We demonstrated that all considered methods were effective in controlling type 1 error in the presence of genetic substructure. The proposed GC methods can be applied to statistical tests for GWAS with various models of inheritance. All methods developed and tested in this work were implemented using R language as a part of the GenABEL package.

Nonadditive Effects of Genes in Human Metabolomics

Genome-wide association studies (GWAS) are widely applied to analyze the genetic effects on phenotypes. With the availability of high-throughput technologies for metabolite measurements, GWAS successfully identified loci that affect metabolite concentrations and underlying pathways. In most GWAS, the effect of each SNP on the phenotype is assumed to be additive. Other genetic models such as recessive, dominant, or overdominant were considered only by very few studies. In contrast to this, there are theories that emphasize the relevance of nonadditive effects as a consequence of physiologic mechanisms. This might be especially important for metabolites because these intermediate phenotypes are closer to the underlying pathways than other traits or diseases. In this study we analyzed systematically nonadditive effects on a large panel of serum metabolites and all possible ratios (22,801 total) in a population-based study [Cooperative Health Research in the Region of Augsburg (KORA) F4, N = 1,785]. We applied four different 1-degree-of-freedom (1-df) tests corresponding to an additive, dominant, recessive, and overdominant trait model as well as a genotypic model with two degree-of-freedom (2-df) that allows a more general consideration of genetic effects. Twenty-three loci were found to be genome-wide significantly associated (Bonferroni corrected P ≤ 2.19 × 10−12) with at least one metabolite or ratio. For five of them, we show the evidence of nonadditive effects. We replicated 17 loci, including 3 loci with nonadditive effects, in an independent study (TwinsUK, N = 846). In conclusion, we found that most genetic effects on metabolite concentrations and ratios were indeed additive, which verifies the practice of using the additive model for analyzing SNP effects on metabolites.

Genome-wide meta-analysis of 158,000 individuals of European ancestry identifies three loci associated with chronic back pain

Back pain is the #1 cause of years lived with disability worldwide, yet surprisingly little is known regarding the biology underlying this symptom. We conducted a genome-wide association study (GWAS) meta-analysis of chronic back pain (CBP). Adults of European ancestry were included from 15 cohorts in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, and from the UK Biobank interim data release. CBP cases were defined as those reporting back pain present for ≥3–6 months; non-cases were included as comparisons (“controls”). Each cohort conducted genotyping using commercially available arrays followed by imputation. GWAS used logistic regression models with additive genetic effects, adjusting for age, sex, study-specific covariates, and population substructure. The threshold for genome-wide significance in the fixed-effect inverse-variance weighted meta-analysis was p<5×10−8. Suggestive (p<5×10−7) and genome-wide significant (p<5×10−8) variants were carried forward for replication or further investigation in the remaining UK Biobank participants not included in the discovery sample. The discovery sample comprised 158,025 individuals, including 29,531 CBP cases. A genome-wide significant association was found for the intronic variant rs12310519 in SOX5 (OR 1.08, p = 7.2×10−10). This was subsequently replicated in 283,752 UK Biobank participants not included in the discovery sample, including 50,915 cases (OR 1.06, p = 5.3×10−11), and exceeded genome-wide significance in joint meta-analysis (OR 1.07, p = 4.5×10−19). We found suggestive associations at three other loci in the discovery sample, two of which exceeded genome-wide significance in joint meta-analysis: an intergenic variant, rs7833174, located between CCDC26 and GSDMC (OR 1.05, p = 4.4×10−13), and an intronic variant, rs4384683, in DCC (OR 0.97, p = 2.4×10−10). In this first reported meta-analysis of GWAS for CBP, we identified and replicated a genetic locus associated with CBP (SOX5). We also identified 2 other loci that reached genome-wide significance in a 2-stage joint meta-analysis (CCDC26/GSDMC and DCC).

Identification of 12 genetic loci associated with human healthspan

The mounting challenge of preserving the quality of life in an aging population directs the focus of longevity science to the regulatory pathways controlling healthspan. To understand the nature of the relationship between the healthspan and lifespan and uncover the genetic architecture of the two phenotypes, we studied the incidence of major age-related diseases in the UK Biobank (UKB) cohort. We observed that the incidence rates of major chronic diseases increase exponentially. The risk of disease acquisition doubled approximately every eight years, i.e., at a rate compatible with the doubling time of the Gompertz mortality law. Assuming that aging is the single underlying factor behind the morbidity rates dynamics, we built a proportional hazards model to predict the risks of the diseases and therefore the age corresponding to the end of healthspan of an individual depending on their age, gender, and the genetic background. We suggested a computationally efficient procedure for the determination of the effect size and statistical significance of individual gene variants associations with healthspan in a form suitable for a Genome-Wide Association Studies (GWAS). Using the UKB sub-population of 300,447 genetically Caucasian, British individuals as a discovery cohort, we identified 12 loci associated with healthspan and reaching the whole-genome level of significance. We observed strong (|ρg| > 0.3) genetic correlations between healthspan and the incidence of specific age-related disease present in our healthspan definition (with the notable exception of dementia). Other examples included all-cause mortality (as derived from parental survival, with ρg = −0.76), life-history traits (metrics of obesity, age at first birth), levels of different metabolites (lipids, amino acids, glycemic traits), and psychological traits (smoking behaviour, cognitive performance, depressive symptoms, insomnia). We conclude by noting that the healthspan phenotype, suggested and characterized here, offers a promising new way to investigate human longevity by exploiting the data from genetic and clinical data on living individuals.

Polymorphisms of genes involved in inflammation and blood vessel development influence the risk of varicose veins

Heredity plays an important role in the etiology of varicose veins (VVs). However, the genetic basis underlying this condition remains poorly understood. Our aim was to replicate top association signals from genome‐wide association studies (GWASs) for VVs of lower extremities using 2 independent datasets—our sample of ethnic Russian individuals (709 cases and 278 controls) and a large cohort of British residents from UK Biobank (10 861 cases and 397u2009594 controls). Associations of polymorphisms rs11121615, rs6712038, rs507666, rs966562, rs7111987, rs6062618, and rs6905288 were validated in the UK Biobank individuals at a Bonferroni‐corrected significance level. In Russian cohort, only rs11121615 reached a nominal significance level of Pu2009<u2009.05. Results of original GWAS and replication studies were combined by a meta‐analysis, and polymorphisms listed above as well as rs111434909 and rs4463578 passed a genome‐wide significant threshold. Notably, the majority of these polymorphisms were located within or near genes involved in vascular development and remodeling, and regulation of inflammatory response. Our results confirm the role of these polymorphisms in genetic susceptibility to VVs and indicate the revealed genomic regions as good candidates for further fine‐mapping studies and functional analysis. Moreover, our findings implicate inflammation and abnormal vascular architecture in VVs pathogenesis.

Varicose veins of lower extremities: insights from the first large-scale genetic study

Varicose veins of lower extremities (VVs) are a common multifactorial vascular disease. Genetic factors underlying VVs development remain largely unknown. Here we report the first large-scale study of VVs performed on a freely available genetic data of 408,455 European-ancestry individuals. We identified 7 reliably associated loci that explain 10% of the SNP-based heritability, and prioritized the most likely causal genes CASZ1, PPP3R1, EBF1, STIM2, and HFE. Genetic correlation analysis confirmed known epidemiological associations and found genetic overlap with various traits including fluid intelligence score, educational attainment, smoking, and pain. Finally, we observed causal effects of height, weight, both fat and fat-free mass, and plasma levels of MICB and CD209 proteins.

Defining the genetic control of human blood plasma N-glycome using genome-wide association study

Glycosylation is a common post-translational modification of proteins. It is known, that glycans are directly involved in the pathophysiology of every major disease. Defining genetic factors altering glycosylation may provide a basis for novel approaches to diagnostic and pharmaceutical applications. Here, we report a genome-wide association study of the human blood plasma N-glycome composition in up to 3811 people. We discovered and replicated twelve loci. This allowed us to demonstrate a clear overlap in genetic control between total plasma and IgG glycosylation. Majority of loci contained genes that encode enzymes directly involved in glycosylation (FUT3/FUT6, FUT8, B3GAT1, ST6GAL1, B4GALT1, ST3GAL4, MGAT3, and MGAT5). We, however, also found loci that are likely to reflect other, more complex, aspects of plasma glycosylation process. Functional genomic annotation suggested the role of DERL3, which potentially highlights the role of glycoprotein degradation pathway, and such transcription factor as IKZF1.

Insight into the genetic architecture of back pain and its risk factors from a study of 509,000 individuals

Back pain (BP) is a common condition of major social importance and poorly understood pathogenesis. Combining data from the UK Biobank and CHARGE consortium cohorts allowed us to perform a very large GWAS (total N = 509,070) and examine the genetic correlation and pleiotropy between BP and its clinical and psychosocial risk factors. We identified and replicated three BP associated loci, including one novel region implicating SPOCK2/CHST3 genes. We provide evidence for pleiotropic effects of genetic factors underlying BP, height, and intervertebral disc problems. We also identified independent genetic correlations between BP and depression symptoms, neuroticism, sleep disturbance, overweight, and smoking. A significant enrichment for genes involved in central nervous system and skeletal tissue development was observed. The study of pleiotropy and genetic correlations, supported by the pathway analysis, suggests at least two strong molecular axes of BP genesis, one related to structural/anatomic factors such as intervertebral disk problems and anthropometrics; and another related to the psychological component of pain perception and pain processing. These findings corroborate with the current biopsychosocial model as a paradigm for BP. Overall, the results demonstrate BP to have an extremely complex genetic architecture that overlaps with the genetic predisposition to its biopsychosocial risk factors. The work sheds light on pathways of relevance in the prevention and management of LBP.

Mycoplasma hyorhinis reduces sensitivity of human lung carcinoma cells to Nutlin-3 and promotes their malignant phenotype

PurposeMDM2 inhibitors are promising anticancer agents that induce cell cycle arrest and tumor cells death via p53 reactivation. We examined the influence of Mycoplasma hyorhinis infection on sensitivity of human lung carcinoma cells NCI-H292 to MDM2 inhibitor Nutlin-3. In order to unveil possible mechanisms underlying the revealed effect, we investigated gene expression changes and signal transduction networks activated in NCI-H292 cells in response to mycoplasma infection.MethodsSensitivity of NCI-Н292 cells to Nutlin-3 was estimated by resazurin-based cell viability assay. Genome-wide transcriptional profiles of NCI-H292 and NCI-Н292Myc.h cell lines were determined using Illumina Human HT-12 v3 Expression BeadChip. Search for key transcription factors and key node molecules was performed using the geneXplain platform. Ability for anchorage-independent growth was tested by soft agar colony formation assay.ResultsNCI-Н292Myc.h cells were shown to be 1.5- and 5.2-fold more resistant to killing by Nutlin-3xa0at concentrations of 15 and 30xa0µM than uninfected NCI-Н292 cells (Pu2009<u20090.05 and Pu2009<u20090.001, respectively). Transcriptome analysis revealed differential expression of multiple genes involved in cancer progression and metastasis as well as epithelial–mesenchymal transition (EMT). Moreover, we have shown experimentally that NCI-Н292Myc.h cells were more capable of growing and dividing without binding to a substrate. The most likely mechanism explaining the observed changes was found to be TLR4- and IL-1b-mediated activation of NF-κB pathway.ConclusionsOur results provide evidence that mycoplasma infection is an important factor modulating the effect of MDM2 inhibitors on cancer cells and is able to induce EMT-related changes.

Polymorphisms in inflammation-related genes and the risk of primary varicose veins in ethnic Russians

Inflammation was shown to be activated in varicose veins, although its role in the development of vein wall transformation remains inconclusive. We aimed to investigate the influence of 13 inflammation-related single nucleotide polymorphisms (SNPs) TNF rs1800629 and rs3093661, IL1A rs1800587, IL1RN rs4251961, IL6 rs1800795 and rs1800796, IFNG rs2430561, IL10 rs1800896, TGFB1 rs1800469, HIF1A rs11549465, NFKB1 rs28362491, and rs4648068 on the risk of primary varicose veins (PVVs) in ethnic Russians. We genotyped 709 patients with PVVs and 278 individuals without a history of chronic venous disease and performed a single SNP and a haplotype analysis. Several associations with Pu2009<u20090.05 were revealed in our study. Variant allele HIF1A rs11549465 T, TNF rs3093661 A, and NFKB1 rs28362491 ATTG deletion showed the reverse association with PVV risk, and allele IL6 rs1800795 C was associated with the increased risk of the studied pathology. Haplotype analysis revealed associations of TNF haplotypes rs3093661 A-rs1800629 G and IL6 rs1800795 C-rs1800796 G with the decreased and the increased risk of PVVs, correspondingly. However, all the observed associations failed to reach statistical significance after the correction for multiple testing, which was set at a level of 10−3 due to many tests performed. Our study therefore provides evidence that investigated polymorphisms do not play a major role in susceptibility to PVVs.