Use of pairwise marker combination and recursive partitioning in a pharmacogenetic genome-wide scan

Warren, Liling; Hughes, Arlene R.; Lai, Eric; Zaykin, Dmitri V.; Haneline, Stephen; Bansal, Aruna T.; Wooster, A W; Spreen, William; Hernández, Jaime E.; Scott, Trevor R.; Roses, Allen D.; Mosteller, Michael

doi:10.1038/sj.tpj.6500414

Cited by 13 publications

(6 citation statements)

References 29 publications

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“…The strategy to investigate potentially useful predictive marker combinations has been applied elsewhere (Warren, et al, 2007). The pair-wise marker combination method can yield a collection of marker pairs that featured a spectrum of sensitivities to specific outcome.…”

Section: Discussionmentioning

confidence: 99%

Association of HPA axis genes with suicidal behaviour in schizophrenia

et al. 2008

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Family, adoption and twin studies show that genetics influences suicidal behaviour, but do not indicate specific susceptibility variants. Stress response is thought to be mediated by the corticotrophin-releasing hormone (CRH), which is known to be a regulator of the hypothalamic-pituitary-adrenal pathway (HPA). Alterations in HPA system have been related to impulsivity, aggression and suicidal behaviour, common feature in schizophrenia. CRH is the hypothalamic factor that stimulates the pituitary gland. To search for markers conferring genetic susceptibility to suicide, we typed six HPA axis genes (CRH, CRHR1, CRHR2, CRHBP, MC2R, NC3R1) in a cohort of 231 subjects with schizophrenia in which 81 attempted suicide. The genotype analyses yielded significant association between CRH binding protein (CRHBP) and suicide attempt (P = 0.035). The genotype analysis for quantitative measures of suicidal behaviour showed no association. The interaction analysis showed a significant interaction between CRH receptor type 1 (CRHR1) and CRH binding protein (CRHBP) in influencing suicide attempt and the severity of suicidal behaviour. Current results show that genetic variation in HPA axis genes could be associated with suicidal behaviour in schizophrenia. This is to our knowledge the first study on suicidal behaviour investigating the interaction among the HPA axis genes.

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Section: Discussionmentioning

confidence: 99%

Association of HPA axis genes with suicidal behaviour in schizophrenia

et al. 2008

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“…(McCarthy et al, 2008;Frayling, 2007;Zanke et al, 2007;Warren et al, 2007;Zeggini et al, 2007;Sladek et al, 2007;North et al, 2004;Libioulle et al, 2007;Wellcome Trust Case-Control Consortium, 2007;Raelson et al, 2007;Coon et al, 2007;Scott et al, 2007;Hunter et al, 2007;Schymick et al, 2007;Li et al, 2008). The time required to genotype and analyze the data derived from pre-existing clinical collections can be as little as several weeks.…”

Section: Genome-wide Association Interpretationsfthe 'Linkage' Of Thementioning

confidence: 99%

The Medical and Economic Roles of Pipeline Pharmacogenetics: Alzheimer's Disease as a Model of Efficacy and HLA-B*5701 as a Model of Safety

Roses

2008

Neuropsychopharmacol

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Pharmacogenetics (PGX) is the study of drug response as a function of an individual's DNA. PGX is often viewed as an extension of disease association genetics, and although this information may be related, it is not the study of drug response. Although medicines are used to treat diseases, the value of strategies that identify and incorporate DNA biomarkers associated with clinical efficacy, or DNA biomarkers for untoward clinical responses, can be applied directly to pharmaceutical pipelines. The growth of adverse event PGX studies involving marketed medicines generally uses relatively large numbers of affected patients, but has been productive. However, the two critical strategies for pipeline genetics must make use of fewer patients: (1) the early identification of efficacy signals so that they can be applied early in development for targeted therapies and (2) identification of safety signals that can subsequently be validated prospectively during development using the least number of patients with adverse responses. Assumptions are often made that large numbers of patients are necessary to recognize PGX hypotheses and to validate DNA biomarkers. In some ways, pipeline pharmacogenetics may be viewed as the opposite of current genome-wide scanning designs. The goal is to obtain PGX signals in as few patients as possible, and then validate PGX hypotheses for specificity and sensitivity as development trials go forward--not using hundreds of thousand of markers to detect strong linkage disequilibrium signals in thousands of patients and their controls. Drug development takes 5-7 years for a drug candidate to traverse to registration--and this is similar to the timeframe for validating genetic biomarkers using sequential clinical trials. Two important examples are discussed, the association of APOE genotypes to the demonstration of actionable efficacy signals for the use of rosiglitazone for Alzheimer's disease; and the identification of HLA-B(*)5701 as a highly sensitive and specific predictive marker for abacavir treated patients who will develop hypersensitivity syndrome (HSS). The rosiglitazone study prevented pipeline attrition by changing the interpretation of a critical Phase IIB proof of concept study (2005) from a failed study, to a positive efficacy response in a genetically predictable proportion of patients. Now, three years later, a Phase III program of clinical trials using pharmacogenetic designs is months away from completion (late08). If successfully registered (early09), millions of patients could benefit, and efficacy PGX would have achieved its first prospective block-buster. The use of safety candidate gene association genetics in patients who received abacavir therapy and developed HSS starting in 1998 culminated in a double blind clinical trial that determined sensitivity > 97% and specificity >99% in 2007. Clinical consensus panels rapidly recommended abacavir as the preferred therapy along with HLA-B(*)5701 pre-testing, immediately increasing the market share of abacavir with respect to ot...

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“…Predictive marker combinations may be identified as interaction terms in cross-tabulations, analyses of variance or logistic regression analyses, and data mining tools, such as recursive partitioning, are particularly helpful for this. The situations in which such recursive partitioning should be performed in whole genome scans is not yet clear: in the entire data sets or, as some authors have performed, in subsets identified in a monofactorial analysis as possible risk factors [ 30 ].…”

Section: Role Of Pharmacogenomics In Pvmentioning

confidence: 99%

Role of Pharmacovigilance in India: An overview

Suke

Kosta²,

Negi

2015

OJPHI

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Pharmacovigilance (PV) plays a key role in the healthcare system through assessment, monitoring and discovery of interactions amongst drugs and their effects in human. Pharmaceutical and biotechnological medicines are designed to cure, prevent or treat diseases; however, there are also risks particularly adverse drug reactions (ADRs) can cause serious harm to patients. Thus, for safety medication ADRs monitoring required for each medicine throughout its life cycle, during development of drug such as pre-marketing including early stages of drug design, clinical trials, and post-marketing surveillance. PV is concerns with the detection, assessment, understanding and prevention of ADRs. Pharmacogenetics and pharmacogenomics are an indispensable part of the clinical research. Variation in the human genome is a cause of variable response to drugs and susceptibility to diseases are determined, which is important for early drug discovery to PV. Moreover, PV has traditionally involved in mining spontaneous reports submitted to national surveillance systems. The research focus is shifting toward the use of data generated from platforms outside the conventional framework such as electronic medical records, biomedical literature, and patient-reported data in health forums. The emerging trend in PV is to link premarketing data with human safety information observed in the post-marketing phase. The PV system team obtains valuable additional information, building up the scientific data contained in the original report and making it more informative. This necessitates an utmost requirement for effective regulations of the drug approval process and conscious pre and post approval vigilance of the undesired effects, especially in India. Adverse events reported by PV system potentially benefit to the community due to their proximity to both population and public health practitioners, in terms of language and knowledge, enables easy contact with reporters by electronically. Hence, PV helps to the patients get well and to manage optimally or ideally, avoid illness is a collective responsibility of industry, drug regulators, clinicians and other healthcare professionals to enhance their contribution to public health. This review summarized objectives and methodologies used in PV with critical overview of existing PV in India, challenges to overcome and future prospects with respect to Indian context.

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Use of pairwise marker combination and recursive partitioning in a pharmacogenetic genome-wide scan

Cited by 13 publications

References 29 publications

Association of HPA axis genes with suicidal behaviour in schizophrenia

Association of HPA axis genes with suicidal behaviour in schizophrenia

The Medical and Economic Roles of Pipeline Pharmacogenetics: Alzheimer's Disease as a Model of Efficacy and HLA-B*5701 as a Model of Safety

Role of Pharmacovigilance in India: An overview

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