Genome-wide polygenic analysis of multiple sclerosis markers

Objective: to perform a genome-wide polygenic analysis of multiple sclerosis (MS) markers in the ethnic groups of Bashkirs, Russians, and Tatars living in the Republic of Bashkortostan (Russian Federation).Patients and methods. Genotyping was performed using allele-specific polymerase chain reaction (PCR) and PCR-restriction fragment length polymorphism analysis of genes of the human leukocyte differentiation antigens CD6 (rs17824933), CD40 (rs6074022), CD58 (rs2300747), CD86 (rs9282641), transcription factors SOX8 (rs2744148) and ZBTB46 (rs6062314), beta-mannosidase MANBA (rs228614), C-type lectin domain CLEC16A (rs12708716), ribosomal protein S6 kinase B1 RPS6KB1 (rs180515), and long noncoding RNA gene PVT1 (rs759648) in 644 patients with MS and 1408 controls. Multilocus analysis of the disease associations with combinations of genotypes and alleles of the studied polymorphic loci was performed using the APSampler algorithm.Results and discussion. We determined the distribution of genotype and allele frequencies of the studied polymorphic loci in the ethnic groups of Bashkirs, Russians, and Tatars. We also observed disease associations with CD58 (rs2300747) and RPS6KB1 (rs180515) polymorphic loci in Russian men, CD86 (rs9282641) in Russian, PVT1 (rs759648) in Tatar women, CD40 (rs6074022) in Bashkir men, and identified 19 combinations of genotypes and/or alleles significantly associated with MS.Conclusion. Based on the genome-wide polygenic analysis of MS markers, we identified ethno- and gender-specific combined markers of the disease susceptibility.

Inferring Causal Relationships Between Risk Factors and Outcomes from Genome-Wide Association Study Data

An observational correlation between a suspected risk factor and an outcome does not necessarily imply that interventions on levels of the risk factor will have a causal impact on the outcome (correlation is not causation). If genetic variants associated with the risk factor are also associated with the outcome, then this increases the plausibility that the risk factor is a causal determinant of the outcome. However, if the genetic variants in the analysis do not have a specific biological link to the risk factor, then causal claims can be spurious. We review the Mendelian randomization paradigm for making causal inferences using genetic variants. We consider monogenic analysis, in which genetic variants are taken from a single gene region, and polygenic analysis, which includes variants from multiple regions. We focus on answering two questions: When can Mendelian randomization be used to make reliable causal inferences, and when can it be used to make relevant causal inferences?

Polygenic Analysis in Absence of Major EffectorATF1Unveils Novel Components in Yeast Flavor Ester Biosynthesis

ABSTRACTFlavor production in yeast fermentation is of paramount importance for industrial production of alcoholic beverages. Although major enzymes of flavor compound biosynthesis have been identified, few specific mutations responsible for strain diversity in flavor production are known. TheATF1-encoded alcohol acetyl coenzyme A (acetyl-CoA) transferase (AATase) is responsible for the majority of acetate ester biosynthesis, but other components affecting strain diversity remain unknown. We have performed parallel polygenic analysis of low production of ethyl acetate, a compound with an undesirable solvent-like off-flavor, in strains with and without deletion ofATF1. We identified two unique causative mutations,eat1K179fsandsnf8E148*, not present in any other sequenced yeast strain and responsible for most ethyl acetate produced in absence ofATF1.EAT1encodes a putative mitochondrial ethanol acetyl-CoA transferase (EATase) and its overexpression, but not that ofEAT1K179fs, and strongly increases ethyl acetate without affecting other flavor acetate esters. Unexpectedly, a higher level of acetate esters (including ethyl acetate) was produced wheneat1K179fswas present together withATF1in the same strain, suggesting that the Eat1 and Atf1 enzymes are intertwined. On the other hand, introduction ofsnf8E148* lowered ethyl acetate levels also in the presence ofATF1, and it affected other aroma compounds, growth, and fermentation as well. Engineering ofsnf8E148* in three industrial yeast strains (for production of wine, saké, and ale beer) and fermentation in an application-relevant medium showed a high but strain-dependent potential for flavor enhancement. Our work has identifiedEAT1andSNF8as new genetic elements determining ethyl acetate production diversity in yeast strains.IMPORTANCEBasic research with laboratory strains of the yeastSaccharomyces cerevisiaehas identified the structural genes of most metabolic enzymes, as well as genes encoding major regulators of metabolism. On the other hand, more recent work on polygenic analysis of yeast biodiversity in natural and industrial yeast strains is revealing novel components of yeast metabolism. A major example is the metabolism of flavor compounds, a particularly important property of industrial yeast strains used for the production of alcoholic beverages. In this work, we have performed polygenic analysis of production of ethyl acetate, an important off-flavor compound in beer and other alcoholic beverages. To increase the chances of identifying novel components, we have used in parallel a wild-type strain and a strain with a deletion ofATF1encoding the main enzyme of acetate ester biosynthesis. This revealed a new structural gene,EAT1, encoding a putative mitochondrial enzyme, which was recently identified as an ethanol acetyl-CoA transferase in another yeast species. We also identified a novel regulatory gene,SNF8, which has not previously been linked to flavor production. Our results show that polygenic analysis of metabolic traits in the absence of major effector genes can reveal novel structural and regulatory genes. The mutant alleles identified can be used to affect the flavor profile in industrial yeast strains for production of alcoholic beverages in more subtle ways than by deletion or overexpression of the already known major effector genes and without significantly altering other industrially important traits. The effect of the novel variants was dependent on the genetic background, with a highly desirable outcome in the flavor profile of an ale brewing yeast.