Publications by authors named "Angelika Erhardt-Lehmann"

3 Publications

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The role of pharmacogenetics in the treatment of anxiety disorders and the future potential for targeted therapeutics.

Expert Opin Drug Metab Toxicol 2021 Oct 15:1-12. Epub 2021 Oct 15.

Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital of Würzburg, Würzburg, Germany.

Introduction: Anxiety disorders (AD) are among the most common mental disorders worldwide. Pharmacotherapy, including benzodiazepines, selective serotonin reuptake inhibitors, serotonin-norepinephrine reuptake inhibitors, and tricyclic antidepressants is currently based on 'trial-and-error,' and is effective in a subset of patients or produces partial response only. Recent research proposes that treatment response and tolerability of the drugs are associated with genetic factors.

Areas Covered: In the present review, we provide information on pharmacogenetics (PGx) in AD, including pharmacokinetic and pharmacodynamic genes. Moreover, we discuss the future potential of PGx for personalized treatment.

Expert Opinion: In psychiatry, PGx testing is still in its infancy, especially in the treatment of AD. As of today, implementation in clinical routine is recommended only for CYP2D6 and CYP2C19, mainly in terms of safety of treatment and potentially of treatment outcome in general. However, the evidence for PGx testing addressing pharmacodynamics for specific AD is limited to date. Nevertheless, PGx may develop into a valuable and promising tool to improve therapy in AD, but there is a need for more research to fully exploit its possibilities. Future perspectives include research into single genes, polygenic risk scores, and pharmacoepigenetics to provide targeted therapy.
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October 2021

EPIBLASTER-fast exhaustive two-locus epistasis detection strategy using graphical processing units.

Eur J Hum Genet 2011 Apr 8;19(4):465-71. Epub 2010 Dec 8.

Max-Planck-Institute of Psychiatry, Munich, Germany.

Detection of epistatic interaction between loci has been postulated to provide a more in-depth understanding of the complex biological and biochemical pathways underlying human diseases. Studying the interaction between two loci is the natural progression following traditional and well-established single locus analysis. However, the added costs and time duration required for the computation involved have thus far deterred researchers from pursuing a genome-wide analysis of epistasis. In this paper, we propose a method allowing such analysis to be conducted very rapidly. The method, dubbed EPIBLASTER, is applicable to case-control studies and consists of a two-step process in which the difference in Pearson's correlation coefficients is computed between controls and cases across all possible SNP pairs as an indication of significant interaction warranting further analysis. For the subset of interactions deemed potentially significant, a second-stage analysis is performed using the likelihood ratio test from the logistic regression to obtain the P-value for the estimated coefficients of the individual effects and the interaction term. The algorithm is implemented using the parallel computational capability of commercially available graphical processing units to greatly reduce the computation time involved. In the current setup and example data sets (211 cases, 222 controls, 299468 SNPs; and 601 cases, 825 controls, 291095 SNPs), this coefficient evaluation stage can be completed in roughly 1 day. Our method allows for exhaustive and rapid detection of significant SNP pair interactions without imposing significant marginal effects of the single loci involved in the pair.
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April 2011