Michal Seweryn
Ohio State University
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Publication
Featured researches published by Michal Seweryn.
Nature | 2013
Anna Cebula; Michal Seweryn; Grzegorz A. Rempala; Simarjot Singh Pabla; Richard A. McIndoe; Timothy L. Denning; Lynn Bry; Piotr Kraj; Pawel Kisielow; Leszek Ignatowicz
Peripheral mechanisms preventing autoimmunity and maintaining tolerance to commensal microbiota involve CD4+ Foxp3+ regulatory T (Treg) cells generated in the thymus or extrathymically by induction of naive CD4+ Foxp3− T cells. Previous studies suggested that the T-cell receptor repertoires of thymic Treg cells and induced Treg cells are biased towards self and non-self antigens, respectively, but their relative contribution in controlling immunopathology, such as colitis and other untoward inflammatory responses triggered by different types of antigens, remains unresolved. The intestine, and especially the colon, is a particularly suitable organ to study this question, given the variety of self-, microbiota- and food-derived antigens to which Treg cells and other T-cell populations are exposed. Intestinal environments can enhance conversion to a regulatory lineage and favour tolerogenic presentation of antigens to naive CD4+ T cells, suggesting that intestinal homeostasis depends on microbiota-specific induced Treg cells. Here, to identify the origin and antigen-specificity of intestinal Treg cells, we performed single-cell and high-throughput sequencing of the T-cell receptor repertoires of CD4+ Foxp3+ and CD4+ Foxp3− T cells, and analysed their reactivity against specific commensal species. We show that thymus-derived Treg cells constitute most Treg cells in all lymphoid and intestinal organs, including the colon, where their repertoire is heavily influenced by the composition of the microbiota. Our results suggest that thymic Treg cells, and not induced Treg cells, dominantly mediate tolerance to antigens produced by intestinal commensals.
Human Genetics | 2014
Wolfgang Sadee; Katherine Hartmann; Michal Seweryn; Maciej Pietrzak; Samuel K. Handelman; Grzegorz A. Rempala
Genetic factors strongly influence risk of common human diseases and treatment outcomes but the causative variants remain largely unknown; this gap has been called the ‘missing heritability’. We propose several hypotheses that in combination have the potential to narrow the gap. First, given a multi-stage path from wellness to disease, we propose that common variants under positive evolutionary selection represent normal variation and gate the transition between wellness and an ‘off-well’ state, revealing adaptations to changing environmental conditions. In contrast, genome-wide association studies (GWAS) focus on deleterious variants conveying disease risk, accelerating the path from off-well to illness and finally specific diseases, while common ‘normal’ variants remain hidden in the noise. Second, epistasis (dynamic gene–gene interactions) likely assumes a central role in adaptations and evolution; yet, GWAS analyses currently are poorly designed to reveal epistasis. As gene regulation is germane to adaptation, we propose that epistasis among common normal regulatory variants, or between common variants and less frequent deleterious variants, can have strong protective or deleterious phenotypic effects. These gene–gene interactions can be highly sensitive to environmental stimuli and could account for large differences in drug response between individuals. Residing largely outside the protein-coding exome, common regulatory variants affect either transcription of coding and non-coding RNAs (regulatory SNPs, or rSNPs) or RNA functions and processing (structural RNA SNPs, or srSNPs). Third, with the vast majority of causative variants yet to be discovered, GWAS rely on surrogate markers, a confounding factor aggravated by the presence of more than one causative variant per gene and by epistasis. We propose that the confluence of these factors may be responsible to large extent for the observed heritability gap.
BMC Genomics | 2015
Samuel K. Handelman; Michal Seweryn; Ryan M. Smith; Katherine Hartmann; Danxin Wang; Maciej Pietrzak; Andrew D. Johnson; Andrzej Kloczkowski; Wolfgang Sadee
BackgroundOver the past 50,000 years, shifts in human-environmental or human-human interactions shaped genetic differences within and among human populations, including variants under positive selection. Shaped by environmental factors, such variants influence the genetics of modern health, disease, and treatment outcome. Because evolutionary processes tend to act on gene regulation, we test whether regulatory variants are under positive selection. We introduce a new approach to enhance detection of genetic markers undergoing positive selection, using conditional entropy to capture recent local selection signals. Results We use conditional logistic regression to compare our Adjusted Haplotype Conditional Entropy (H|H) measure of positive selection to existing positive selection measures. H|H and existing measures were applied to published regulatory variants acting in cis (cis-eQTLs), with conditional logistic regression testing whether regulatory variants undergo stronger positive selection than the surrounding gene.These cis-eQTLs were drawn from six independent studies of genotype and RNA expression. The conditional logistic regression shows that, overall, H|H is substantially more powerful than existing positive-selection methods in identifying cis-eQTLs against other Single Nucleotide Polymorphisms (SNPs) in the same genes. When broken down by Gene Ontology, H|H predictions are particularly strong in some biological process categories, where regulatory variants are under strong positive selection compared to the bulk of the gene, distinct from those GO categories under overall positive selection. . However, cis-eQTLs in a second group of genes lack positive selection signatures detectable by H|H, consistent with ancient short haplotypes compared to the surrounding gene (for example, in innate immunity GO:0042742); under such other modes of selection, H|H would not be expected to be a strong predictor.. These conditional logistic regression models are adjusted for Minor allele frequency(MAF); otherwise, ascertainment bias is a huge factor in all eQTL data sets. Relationships between Gene Ontology categories, positive selection and eQTL specificity were replicated with H|H in a single larger data set. Our measure, Adjusted Haplotype Conditional Entropy (H|H), was essential in generating all of the results above because it: 1) is a stronger overall predictor for eQTLs than comparable existing approaches, and 2) shows low sequential auto-correlation, overcoming problems with convergence of these conditional regression statistical models.ConclusionsOur new method, H|H, provides a consistently more robust signal associated with cis-eQTLs compared to existing methods. We interpret this to indicate that some cis-eQTLs are under positive selection compared to their surrounding genes. Conditional entropy indicative of a selective sweep is an especially strong predictor of eQTLs for genes in several biological processes of medical interest. Where conditional entropy is a weak or negative predictor of eQTLs, such as innate immune genes, this would be consistent with balancing selection acting on such eQTLs over long time periods. Different measures of selection may be needed for variant prioritization under other modes of evolutionary selection.
Nature Communications | 2014
Lukasz Wojciech; Alicja Ignatowicz; Michal Seweryn; Grzegorz A. Rempala; Simarjot Singh Pabla; Richard A. McIndoe; Pawel Kisielow; Leszek Ignatowicz
The role of the T cell receptor (TCR) in commitment of thymocytes to regulatory CD4+Foxp3+ and conventional CD4−Foxp3− T cell lineages remains controversial. According to the prevailing view, commitment to the former lineage, in contrast to the latter, requires that high affinity TCRs bind rare class II MHC/peptide complexes presented in “thymic niches”, which could explain differences between their TCR repertoires. Here we challenge this view and show that the binding of identical TCRs to the same ubiquitously expressed MHC/peptide complex often directs thymocytes to both CD4+ lineages, indicating that the TCR affinity does not play the instructive role, and that restricted presentation of peptides in ”thymic niches” is not necessary for selection of CD4+Foxp3+ T cells. However, depending on whether immature thymocytes bound the ligand predominantly with low or high affinity, the repertoires of regulatory and conventional CD4+ T cells were correspondingly similar or mostly different, suggesting that negative rather than positive selection sets them apart.
PLOS ONE | 2015
Roshan Mascarenhas; Maciej Pietrzak; Ryan M. Smith; Amy Webb; Danxin Wang; Audrey C. Papp; Julia K. Pinsonneault; Michal Seweryn; Grzegorz A. Rempala; Wolfgang Sadee
mRNA translation into proteins is highly regulated, but the role of mRNA isoforms, noncoding RNAs (ncRNAs), and genetic variants remains poorly understood. mRNA levels on polysomes have been shown to correlate well with expressed protein levels, pointing to polysomal loading as a critical factor. To study regulation and genetic factors of protein translation we measured levels and allelic ratios of mRNAs and ncRNAs (including microRNAs) in lymphoblast cell lines (LCL) and in polysomal fractions. We first used targeted assays to measure polysomal loading of mRNA alleles, confirming reported genetic effects on translation of OPRM1 and NAT1, and detecting no effect of rs1045642 (3435C>T) in ABCB1 (MDR1) on polysomal loading while supporting previous results showing increased mRNA turnover of the 3435T allele. Use of high-throughput sequencing of complete transcript profiles (RNA-Seq) in three LCLs revealed significant differences in polysomal loading of individual RNA classes and isoforms. Correlated polysomal distribution between protein-coding and non-coding RNAs suggests interactions between them. Allele-selective polysome recruitment revealed strong genetic influence for multiple RNAs, attributable either to differential expression of RNA isoforms or to differential loading onto polysomes, the latter defining a direct genetic effect on translation. Genes identified by different allelic RNA ratios between cytosol and polysomes were enriched with published expression quantitative trait loci (eQTLs) affecting RNA functions, and associations with clinical phenotypes. Polysomal RNA-Seq combined with allelic ratio analysis provides a powerful approach to study polysomal RNA recruitment and regulatory variants affecting protein translation.
PLOS ONE | 2015
Judith A. Schwartzbaum; Michal Seweryn; Christopher Holloman; Randall E. Harris; Samuel K. Handelman; Grzegorz A. Rempala; Ruo Pan Huang; Brett Burkholder; Adam Brandemihl; Henrik Källberg; Tom Borge Johannesen; Anders Ahlbom; Maria Feychting; Tom K. Grimsrud
Allergy is inversely related to glioma risk. To determine whether prediagnostic allergy-related serum proteins are associated with glioma, we conducted a nested case-control study of seven cytokines (IL4, IL13, IL5, IL6, IL10, IFNG, TGFB2), two soluble cytokine receptors (sIL4RA, sIL13RA2) and three allergy-related transcription factors (FOXP3, STAT3, STAT6) using serum specimens from the Janus Serum Bank Cohort in Oslo, Norway. Blood donors subsequently diagnosed with glioma (n = 487) were matched to controls (n = 487) on age and date of blood draw and sex. We first estimated individual effects of the 12 serum proteins and then interactions between IL4 and IL13 and their receptors using conditional logistic regression. We next tested equality of case-control inter-correlations among the 12 serum proteins. We found that TGFB2 is inversely related to glioblastoma (Odds Ratio (OR) = 0.87, 95% Confidence Interval (CI)) = 0.76, 0.98). In addition, ≤ 5 years before diagnosis, we observed associations between IL4 (OR = 0.82, 95% CI = 0.66, 1.01), sIL4RA (OR = 0.80, 95% CI = 0.65, 1.00), their interaction (OR = 1.06, 95% CI = 1.01, 1.12) and glioblastoma. This interaction was apparent > 20 years before diagnosis (IL4-sIL4RA OR = 1.20, 95% CI = 1.05, 1.37). Findings for glioma were similar. Case correlations were different from control correlations stratified on time before diagnosis. Five years or less before diagnosis, correlations among case serum proteins were weaker than were those among controls. Our findings suggest that IL4 and sIL4RA reduce glioma risk long before diagnosis and early gliomagenesis affects circulating immune function proteins.
Human Mutation | 2017
Elizabeth S. Barrie; Katherine Hartmann; Sung-Ha Lee; John T. Frater; Michal Seweryn; Danxin Wang; Wolfgang Sadee
Functionally related genes often cluster into a genome region under coordinated regulation, forming a local regulome. To understand regulation of the CHRNA5/CHRNA3/CHRNB4 nicotinic receptor gene cluster, we integrate large‐scale RNA expression data (brain and peripheral) from GTEx (Genotype Tissue Expression), clinical associations (GRASP), and linkage disequilibrium data (1000 Genomes) to find candidate SNPs representing independent regulatory variants. CHRNA3, CHRNA5, CHRNB4 mRNAs, and a well‐expressed CHRNA5 antisense RNA (RP11‐650L12.2) are co‐expressed in many human tissues, suggesting common regulatory elements. The CHRNA5 enhancer haplotype tagged by rs880395 not only increases CHRNA5 mRNA expression in all tissues, but also enhances RP11‐650L12.2 and CHRNA3 expression, suggesting DNA looping to multiple promoters. However, in nucleus accumbens and putamen, but not other brain regions, CHRNA3 expression associates uniquely with a haplotype tagged by rs1948 (located in the CHRNB4 3′UTR). Haplotype/diplotype analysis of rs880395 and rs1948 plus rs16969968 (a nonsynonymous CHRNA5 risk variant) in GWAS (COGEND, UW‐TTURC, SAGE) yields a nicotine dependence risk profile only partially captured by rs16969968 alone. An example of local gene clusters, this nicotinic regulome is controlled by complex genetic variation, with broad implications for interpreting GWAS.
Nutrition and Cancer | 2015
Victoria Zigmont; Amy Garrett; Jin Peng; Michal Seweryn; Grzegorz A. Rempala; Randall E. Harris; Christopher Holloman; Thomas E. Gundersen; Anders Ahlbom; Maria Feychting; Tom Borge Johannesen; Tom K. Grimsrud; Judith A. Schwartzbaum
There are no previous studies of the association between prediagnostic serum vitamin D concentration and glioma. Vitamin D has immunosuppressive properties; as does glioma. It was, therefore, our hypothesis that elevated vitamin D concentration would increase glioma risk. We conducted a nested case-control study using specimens from the Janus Serum Bank cohort in Norway. Blood donors who were subsequently diagnosed with glioma (n = 592), between 1974 and 2007, were matched to donors without glioma (n = 1112) on date and age at blood collection and sex. We measured 25-hydroxyvitamin D [25(OH)D], an indicator of vitamin D availability, using liquid chromatography coupled with mass spectrometry. Seasonally adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) were estimated for each control quintile of 25(OH)D using conditional logistic regression. Among men diagnosed with high grade glioma >56, we found a negative trend (P = .04). Men diagnosed ≤ 56 showed a borderline positive trend (P = .08). High levels (>66 nmol/L) of 25(OH)D in men >56 were inversely related to high grade glioma from ≥2 yr before diagnosis (OR = 0.59; 95% CI = 0.38, 0.91) to ≥15 yr before diagnosis (OR = 0.61; 95% CI = 0.38,0.96). Our findings are consistent long before glioma diagnosis and are therefore unlikely to reflect preclinical disease.
BMC Genomics | 2015
Rong Lu; Ryan M. Smith; Michal Seweryn; Danxin Wang; Katherine Hartmann; Amy Webb; Wolfgang Sadee; Grzegorz A. Rempala
BackgroundMeasuring allele-specific RNA expression provides valuable insights into cis-acting genetic and epigenetic regulation of gene expression. Widespread adoption of high-throughput sequencing technologies for studying RNA expression (RNA-Seq) permits measurement of allelic RNA expression imbalance (AEI) at heterozygous single nucleotide polymorphisms (SNPs) across the entire transcriptome, and this approach has become especially popular with the emergence of large databases, such as GTEx. However, the existing binomial-type methods used to model allelic expression from RNA-seq assume a strong negative correlation between reference and variant allele reads, which may not be reasonable biologically.ResultsHere we propose a new strategy for AEI analysis using RNA-seq data. Under the null hypothesis of no AEI, a group of SNPs (possibly across multiple genes) is considered comparable if their respective total sums of the allelic reads are of similar magnitude. Within each group of “comparable” SNPs, we identify SNPs with AEI signal by fitting a mixture of folded Skellam distributions to the absolute values of read differences. By applying this methodology to RNA-Seq data from human autopsy brain tissues, we identified numerous instances of moderate to strong imbalanced allelic RNA expression at heterozygous SNPs. Findings with SLC1A3 mRNA exhibiting known expression differences are discussed as examples.ConclusionThe folded Skellam mixture model searches for SNPs with significant difference between reference and variant allele reads (adjusted for different library sizes), using information from a group of “comparable” SNPs across multiple genes. This model is particularly suitable for performing AEI analysis on genes with few heterozygous SNPs available from RNA-seq, and it can fit over-dispersed read counts without specifying the direction of the correlation between reference and variant alleles.
Computers in Biology and Medicine | 2015
Samuel K. Handelman; Jacob M. Aaronson; Michal Seweryn; Igor Voronkin; Jesse J. Kwiek; Wolfgang Sadee; Joseph S. Verducci; Daniel Janies
BACKGROUND Associations between genotype and phenotype provide insight into the evolution of pathogenesis, drug resistance, and the spread of pathogens between hosts. However, common ancestry can lead to apparent associations between biologically unrelated features. The novel method Cladograms with Path to Event (ClaPTE) detects associations between character-pairs (either a pair of mutations or a mutation paired with a phenotype) while adjusting for common ancestry, using phylogenetic trees. METHODS ClaPTE tests for character-pairs changing close together on the phylogenetic tree, consistent with an associated character-pair. ClaPTE is compared to three existing methods (independent contrasts, mixed model, and likelihood ratio) to detect character-pair associations adjusted for common ancestry. Comparisons utilize simulations on gene trees for: HIV Env, HIV promoter, and bacterial DnaJ and GuaB; and case studies for Oseltamavir resistance in Influenza, and for DnaJ and GuaB. Simulated data include both true-positive/associated character-pairs, and true-negative/not-associated character-pairs, used to assess type I (frequency of p-values in true-negatives) and type II (sensitivity to true-positives) error control. RESULTS AND CONCLUSIONS ClaPTE has competitive sensitivity and better type I error control than existing methods. In the Influenza/Oseltamavir case study, ClaPTE reports no new permissive mutations but detects associations between adjacent (in primary sequence) amino acid positions which other methods miss. In the DnaJ and GuaB case study, ClaPTE reports more frequent associations between positions both from the same protein family than between positions from different families, in contrast to other methods. In both case studies, the results from ClaPTE are biologically plausible.