Discovering a junction tree behind a Markov network by a greedy algorithm

In an earlier paper we introduced a special kind of k-width junction tree, called k-th order t-cherry junction tree in order to approximate a joint probability distribution. The approximation is the best if the Kullback-Leibler divergence between the true joint probability distribution and the approximating one is minimal. Finding the best approximating k-width junction tree is NP-complete if k>2. In our earlier paper we also proved that the best approximating k-width junction tree can be embedded into a k-th order t-cherry junction tree. We introduce a greedy algorithm resulting very good approximations in reasonable computing time. In this paper we prove that if the Markov network underlying fullfills some requirements then our greedy algorithm is able to find the true probability distribution or its best approximation in the family of the k-th order t-cherry tree probability distributions. Our algorithm uses just the k-th order marginal probability distributions as input. We compare the results of the greedy algorithm proposed in this paper with the greedy algorithm proposed by Malvestuto in 1991.Comment: The paper was presented at VOCAL 2010 in Veszprem, Hungar

Genome-wide association study of antipsychotic-induced QTc interval prolongation

QT prolongation is associated with increased risk of cardiac arrhythmias. Identifying the genetic variants that mediate antipsychotic induced prolongation may help to minimize this risk, which might prevent the removal of efficacious drugs from the market. We performed candidate gene analysis and five drug specific genome-wide association studies (GWAS) with 492K SNPs to search for genetic variation mediating antipsychotic induced QT prolongation in 738 schizophrenia patients from the Clinical Antipsychotic Trial of Intervention Effectiveness (CATIE) study.Our candidate gene study suggests the involvement of NOS1AP and NUBPL (p-values =1.45×10−05 and 2.66×10−13, respectively). Furthermore, our top GWAS hit achieving genome-wide significance, defined as a q-value <0.10, (p-value =1.54×10−7, q-value =0.07), located in SLC22A23, mediated the effects of quetiapine on prolongation. SLC22A23 belongs to a family of organic ion transporters that shuttle a variety of compounds including drugs, environmental toxins, and endogenous metabolites across the cell membrane. This gene is expressed in the heart and is integral in mouse heart development. The genes mediating antipsychotic induced QT prolongation partially overlap with the genes affecting normal QT interval variation. However, some genes may also be unique for drug induced prolongation. This study demonstrates the potential of GWAS to discover genes and pathways that mediate antipsychotic induced QT prolongation

Genomewide pharmacogenomic study of metabolic side effects to antipsychotic drugs

Understanding individual differences in the susceptibility to metabolic side effects as a response to antipsychotic therapy is essential to optimize the treatment of schizophrenia. Here we perform genomewide association studies (GWAS) to search for genetic variation affecting the susceptibility to metabolic side effects. The analysis sample consisted of 738 schizophrenia patients, successfully genotyped for 492K SNPs, from the genomic subsample of the Clinical Antipsychotic Trial of Intervention Effectiveness (CATIE) study. Outcomes included twelve indicators of metabolic side effects, quantifying antipsychotic-induced change in weight, blood lipids, glucose and hemoglobin A1c, blood pressure and heart rate. Our criterion for genomewide significance was a pre-specified threshold that ensures, on average, only 10% of the significant findings are false discoveries. Twenty-one SNPs satisfied this criterion. The top finding indicated a SNP in MEIS2 mediated the effects of risperidone on hip circumference (q =.004). The same SNP was also found to mediate risperidone's effect on waist circumference (q =.055). Genomewide significant finding were also found for SNPs in PRKAR2B, GPR98, FHOD3, RNF144A, ASTN2, SOX5 and ATF7IP2, as well as several intergenic markers. PRKAR2B and MEIS2 both have previous research indicating metabolic involvement and PRKAR2B has previously been shown to mediate antipsychotic response. Although our findings require replication and functional validation, this study demonstrates the potential of GWAS to discover genes and pathways that potentially mediate adverse effects of antipsychotic medication

A Comprehensive Family-Based Replication Study of Schizophrenia Genes

Schizophrenia (SCZ) is a devastating psychiatric condition. Identifying the specific genetic variants and pathways that increase susceptibility to SCZ is critical to improve disease understanding and address the urgent need for new drug targets

On two-stage convex chance constrained problems

In this paper we develop approximation algorithms for two-stage convex chance constrainedproblems. Nemirovski and Shapiro [16] formulated this class of problems and proposed anellipsoid-like iterative algorithm for the special case where the impact function f (x, h) is bi-affine.We show that this algorithm extends to bi-convex f (x, h) in a fairly straightforward fashion.The complexity of the solution algorithm as well as the quality of its output are functions of theradius r of the largest Euclidean ball that can be inscribed in the polytope defined by a randomset of linear inequalities generated by the algorithm [16]. Since the polytope determining ris random, computing r is diffiult. Yet, the solution algorithm requires r as an input. Inthis paper we provide some guidance for selecting r. We show that the largest value of r isdetermined by the degree of robust feasibility of the two-stage chance constrained problem –the more robust the problem, the higher one can set the parameter r. Next, we formulate ambiguous two-stage chance constrained problems. In this formulation,the random variables defining the chance constraint are known to have a fixed distribution;however, the decision maker is only able to estimate this distribution to within some error. Weconstruct an algorithm that solves the ambiguous two-stage chance constrained problem whenthe impact function f (x, h) is bi-affine and the extreme points of a certain “dual” polytope areknown explicitly

SNP-based analysis of neuroactive ligand-receptor interaction pathways implicates PGE2 as a novel mediator of antipsychotic treatment response : data from the CATIE study

Identifying specific neuroactive pathways involved in antipsychotic pharmacology is vital to developing improved therapeutic strategies for schizophrenia. Our results implicate the PGE2 pathway as a novel biomarker mediating response to three atypical antipsychotic drugs