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Dimitrios Avramopoulos - One of the best experts on this subject based on the ideXlab platform.
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schizophrenia risk alleles often affect the expression of many genes and each gene may have a different effect on the risk a mediation analysis
American Journal of Medical Genetics, 2021Co-Authors: Xi Peng, Joel S Bader, Dimitrios AvramopoulosAbstract:Variants identified by genome-wide association studies (GWAS) are often expression quantitative trait loci (eQTLs), suggesting they are proxies or are themselves regulatory. Across many data sets, analyses show that variants often affect multiple genes. Lacking data on many tissue types, developmental time points, and homogeneous cell types, the extent of this One-to-Many Relationship is underestimated. This raises questions on whether a disease eQTL target gene explains the genetic association or is a bystander and puts into question the direction of expression effect of on the risk, since the many variants-regulated genes may have opposing effects, imperfectly balancing each other. We used two brain gene expression data sets (CommonMind and BrainSeq) for mediation analysis of schizophrenia-associated variants. We confirm that eQTL target genes often mediate risk but the direction in which expression affects risk is often different from that in which the risk allele changes expression. Of 38 mediator genes significant in both data sets 33 showed consistent mediation direction (Chi2 test p = 6 × 10-6 ). One might expect that the expression would correlate with the risk allele in the same direction it correlates with the disease. For 15 of these 33 (45%), however, the expression change associated with the risk allele was protective, suggesting the likely presence of other target genes with overriding effects. Our results identify specific risk mediating genes and suggest caution in interpreting the biological consequences of targeted modifications of gene expression, as not all eQTL targets may be relevant to disease while those that are, might have different from expected directions.
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schizophrenia risk alleles often affect the expression of many genes and each gene may have a different effect on the risk a mediation analysis
bioRxiv, 2020Co-Authors: Xi Peng, Joel S Bader, Dimitrios AvramopoulosAbstract:Variants identified by genome-wide association studies (GWAS) are often expression quantitative trait loci (eQTLs), suggesting they are proxies or are themselves regulatory. Across many datasets analyses show that variants often affect multiple genes. Lacking data on many tissue types, developmental time points and homogeneous cell types, the extent of this One-to-Many Relationship is underestimated. This raises questions on whether a disease eQTL target gene explains the genetic association or is a by-stander and puts into question the direction of expression effect of on the risk, since the many variant - regulated genes may have opposing effects, imperfectly balancing each other. We used two brain gene expression datasets (CommonMind and BrainSeq) for mediation analysis of schizophrenia-associated variants. We confirm that eQTL target genes often mediate risk but the direction in which expression affects risk is often different from that in which the risk allele changes expression. Of 38 mediator genes significant in both datasets 33 showed consistent mediation direction (Chi2 test P=6*10-6). One might expect that the expression would correlate with the risk allele in the same direction it correlates with disease. For 15 of these 33 (45%), however, the expression change associated with the risk allele was protective, suggesting the likely presence of other target genes with overriding effects. Our results identify specific risk mediating genes and suggest caution in interpreting the biological consequences of targeted modifications of gene expression, as not all eQTL targets may be relevant to disease while those that are, might have different than expected directions
Xi Peng - One of the best experts on this subject based on the ideXlab platform.
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schizophrenia risk alleles often affect the expression of many genes and each gene may have a different effect on the risk a mediation analysis
American Journal of Medical Genetics, 2021Co-Authors: Xi Peng, Joel S Bader, Dimitrios AvramopoulosAbstract:Variants identified by genome-wide association studies (GWAS) are often expression quantitative trait loci (eQTLs), suggesting they are proxies or are themselves regulatory. Across many data sets, analyses show that variants often affect multiple genes. Lacking data on many tissue types, developmental time points, and homogeneous cell types, the extent of this One-to-Many Relationship is underestimated. This raises questions on whether a disease eQTL target gene explains the genetic association or is a bystander and puts into question the direction of expression effect of on the risk, since the many variants-regulated genes may have opposing effects, imperfectly balancing each other. We used two brain gene expression data sets (CommonMind and BrainSeq) for mediation analysis of schizophrenia-associated variants. We confirm that eQTL target genes often mediate risk but the direction in which expression affects risk is often different from that in which the risk allele changes expression. Of 38 mediator genes significant in both data sets 33 showed consistent mediation direction (Chi2 test p = 6 × 10-6 ). One might expect that the expression would correlate with the risk allele in the same direction it correlates with the disease. For 15 of these 33 (45%), however, the expression change associated with the risk allele was protective, suggesting the likely presence of other target genes with overriding effects. Our results identify specific risk mediating genes and suggest caution in interpreting the biological consequences of targeted modifications of gene expression, as not all eQTL targets may be relevant to disease while those that are, might have different from expected directions.
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schizophrenia risk alleles often affect the expression of many genes and each gene may have a different effect on the risk a mediation analysis
bioRxiv, 2020Co-Authors: Xi Peng, Joel S Bader, Dimitrios AvramopoulosAbstract:Variants identified by genome-wide association studies (GWAS) are often expression quantitative trait loci (eQTLs), suggesting they are proxies or are themselves regulatory. Across many datasets analyses show that variants often affect multiple genes. Lacking data on many tissue types, developmental time points and homogeneous cell types, the extent of this One-to-Many Relationship is underestimated. This raises questions on whether a disease eQTL target gene explains the genetic association or is a by-stander and puts into question the direction of expression effect of on the risk, since the many variant - regulated genes may have opposing effects, imperfectly balancing each other. We used two brain gene expression datasets (CommonMind and BrainSeq) for mediation analysis of schizophrenia-associated variants. We confirm that eQTL target genes often mediate risk but the direction in which expression affects risk is often different from that in which the risk allele changes expression. Of 38 mediator genes significant in both datasets 33 showed consistent mediation direction (Chi2 test P=6*10-6). One might expect that the expression would correlate with the risk allele in the same direction it correlates with disease. For 15 of these 33 (45%), however, the expression change associated with the risk allele was protective, suggesting the likely presence of other target genes with overriding effects. Our results identify specific risk mediating genes and suggest caution in interpreting the biological consequences of targeted modifications of gene expression, as not all eQTL targets may be relevant to disease while those that are, might have different than expected directions
Joel S Bader - One of the best experts on this subject based on the ideXlab platform.
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schizophrenia risk alleles often affect the expression of many genes and each gene may have a different effect on the risk a mediation analysis
American Journal of Medical Genetics, 2021Co-Authors: Xi Peng, Joel S Bader, Dimitrios AvramopoulosAbstract:Variants identified by genome-wide association studies (GWAS) are often expression quantitative trait loci (eQTLs), suggesting they are proxies or are themselves regulatory. Across many data sets, analyses show that variants often affect multiple genes. Lacking data on many tissue types, developmental time points, and homogeneous cell types, the extent of this One-to-Many Relationship is underestimated. This raises questions on whether a disease eQTL target gene explains the genetic association or is a bystander and puts into question the direction of expression effect of on the risk, since the many variants-regulated genes may have opposing effects, imperfectly balancing each other. We used two brain gene expression data sets (CommonMind and BrainSeq) for mediation analysis of schizophrenia-associated variants. We confirm that eQTL target genes often mediate risk but the direction in which expression affects risk is often different from that in which the risk allele changes expression. Of 38 mediator genes significant in both data sets 33 showed consistent mediation direction (Chi2 test p = 6 × 10-6 ). One might expect that the expression would correlate with the risk allele in the same direction it correlates with the disease. For 15 of these 33 (45%), however, the expression change associated with the risk allele was protective, suggesting the likely presence of other target genes with overriding effects. Our results identify specific risk mediating genes and suggest caution in interpreting the biological consequences of targeted modifications of gene expression, as not all eQTL targets may be relevant to disease while those that are, might have different from expected directions.
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schizophrenia risk alleles often affect the expression of many genes and each gene may have a different effect on the risk a mediation analysis
bioRxiv, 2020Co-Authors: Xi Peng, Joel S Bader, Dimitrios AvramopoulosAbstract:Variants identified by genome-wide association studies (GWAS) are often expression quantitative trait loci (eQTLs), suggesting they are proxies or are themselves regulatory. Across many datasets analyses show that variants often affect multiple genes. Lacking data on many tissue types, developmental time points and homogeneous cell types, the extent of this One-to-Many Relationship is underestimated. This raises questions on whether a disease eQTL target gene explains the genetic association or is a by-stander and puts into question the direction of expression effect of on the risk, since the many variant - regulated genes may have opposing effects, imperfectly balancing each other. We used two brain gene expression datasets (CommonMind and BrainSeq) for mediation analysis of schizophrenia-associated variants. We confirm that eQTL target genes often mediate risk but the direction in which expression affects risk is often different from that in which the risk allele changes expression. Of 38 mediator genes significant in both datasets 33 showed consistent mediation direction (Chi2 test P=6*10-6). One might expect that the expression would correlate with the risk allele in the same direction it correlates with disease. For 15 of these 33 (45%), however, the expression change associated with the risk allele was protective, suggesting the likely presence of other target genes with overriding effects. Our results identify specific risk mediating genes and suggest caution in interpreting the biological consequences of targeted modifications of gene expression, as not all eQTL targets may be relevant to disease while those that are, might have different than expected directions
Horia Ciocarlie - One of the best experts on this subject based on the ideXlab platform.
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business process similarity metric supporting one to many Relationship
Symposium on Applied Computational Intelligence and Informatics, 2015Co-Authors: Maria Laura Sebu, Horia CiocarlieAbstract:In many areas graph match techniques are used to compare and identify common characteristics. In this paper we apply graph similarity techniques on the business processes used inside organizations and extracted with process mining techniques. The scope is to identify if an organization uses a similar process for a specific business case as another organization. However as the existence of exact matching is less probable, error tolerant graph matching techniques are more suitable for real life data. Business processes could have a different granularity level; one business process is more detailed in specific areas than the business process subject of the comparison. The custom algorithm for business process match presented in this paper takes into consideration a One-to-Many relation for activities: one activity is matched with a set of activities in the other graph. Such information is important in extracting the common characteristics of organizations and could represent an input for choosing a collaborator. Business processes if not available are extracted with process mining techniques and are reduced to directed graph format. A custom graph similarity algorithm extended for multivalent nodes is applied and a business process similarity factor is retrieved.
Maria Laura Sebu - One of the best experts on this subject based on the ideXlab platform.
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business process similarity metric supporting one to many Relationship
Symposium on Applied Computational Intelligence and Informatics, 2015Co-Authors: Maria Laura Sebu, Horia CiocarlieAbstract:In many areas graph match techniques are used to compare and identify common characteristics. In this paper we apply graph similarity techniques on the business processes used inside organizations and extracted with process mining techniques. The scope is to identify if an organization uses a similar process for a specific business case as another organization. However as the existence of exact matching is less probable, error tolerant graph matching techniques are more suitable for real life data. Business processes could have a different granularity level; one business process is more detailed in specific areas than the business process subject of the comparison. The custom algorithm for business process match presented in this paper takes into consideration a One-to-Many relation for activities: one activity is matched with a set of activities in the other graph. Such information is important in extracting the common characteristics of organizations and could represent an input for choosing a collaborator. Business processes if not available are extracted with process mining techniques and are reduced to directed graph format. A custom graph similarity algorithm extended for multivalent nodes is applied and a business process similarity factor is retrieved.
