Dataset Information

Semi-Automated Biomarker Discovery from Pharmacodynamic Effects on EEG in ADHD Rodent Models.

ABSTRACT: We propose a novel semi-automatic approach to design biomarkers for capturing pharmacodynamic effects induced by pharmacological agents on the spectral power of electroencephalography (EEG) recordings. We apply this methodology to investigate the pharmacodynamic effects of methylphenidate (MPH) and atomoxetine (ATX) on attention deficit/hyperactivity disorder (ADHD), using rodent models. We inject the two agents into the spontaneously hypertensive rat (SHR) model of ADHD, the Wistar-Kyoto rat (WKY), and the Wistar rat (WIS), and record their EEG patterns. To assess individual EEG patterns quantitatively, we use an integrated methodological approach, which consists of calculating the mean, slope and intercept parameters of temporal records of EEG spectral power using a smoothing filter, outlier truncation, and linear regression. We apply Fisher discriminant analysis (FDA) to identify dominant discriminants to be heuristically consolidated into several new composite biomarkers. Results of the analysis of variance (ANOVA) and t-test show benefits in pharmacodynamic parameters, especially the slope parameter. Composite biomarker evaluation confirms their validity for genetic model stratification and the effects of the pharmacological agents used. The methodology proposed is of generic use as an approach to investigating thoroughly the dynamics of the EEG spectral power.

SUBMITTER: Yokota T

PROVIDER: S-EPMC5980101 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Semi-Automated Biomarker Discovery from Pharmacodynamic Effects on EEG in ADHD Rodent Models.

Yokota Tatsuya T Struzik Zbigniew R ZR Jurica Peter P Horiuchi Masahito M Hiroyama Shuichi S Li Junhua J Takahara Yuji Y Ogawa Koichi K Nishitomi Kohei K Hasegawa Minoru M Cichocki Andrzej A

Scientific reports 20180326 1

We propose a novel semi-automatic approach to design biomarkers for capturing pharmacodynamic effects induced by pharmacological agents on the spectral power of electroencephalography (EEG) recordings. We apply this methodology to investigate the pharmacodynamic effects of methylphenidate (MPH) and atomoxetine (ATX) on attention deficit/hyperactivity disorder (ADHD), using rodent models. We inject the two agents into the spontaneously hypertensive rat (SHR) model of ADHD, the Wistar-Kyoto rat (W ...[more]

PMID: 29581452

Similar Datasets

Project description:BackgroundThis study is the first to evaluate an assessment aid for attention-deficit/hyperactivity disorder (ADHD) according to both Class-I evidence standards of American Academy of Neurology and De Novo requirements of US Food and Drug Administration. The assessment aid involves a method to integrate an electroencephalographic (EEG) biomarker, theta/beta ratio (TBR), with a clinician's ADHD evaluation. The integration method is intended as a step to help improve certainty with criterion E (i.e., whether symptoms are better explained by another condition).MethodsTo evaluate the assessment aid, investigators conducted a prospective, triple-blinded, 13-site, clinical cohort study. Comprehensive clinical evaluation data were obtained from 275 children and adolescents presenting with attentional and behavioral concerns. A qualified clinician at each site performed differential diagnosis. EEG was collected by separate teams. The reference standard was consensus diagnosis by an independent, multidisciplinary team (psychiatrist, psychologist, and neurodevelopmental pediatrician), which is well-suited to evaluate criterion E in a complex clinical population.ResultsOf 209 patients meeting ADHD criteria per a site clinician's judgment, 93 were separately found by the multidisciplinary team to be less likely to meet criterion E, implying possible overdiagnosis by clinicians in 34% of the total clinical sample (93/275). Of those 93, 91% were also identified by EEG, showing a relatively lower TBR (85/93). Further, the integration method was in 97% agreement with the multidisciplinary team in the resolution of a clinician's uncertain cases (35/36). TBR showed statistical power specific to supporting certainty of criterion E per the multidisciplinary team (Cohen's d, 1.53). Patients with relatively lower TBR were more likely to have other conditions that could affect criterion E certainty (10 significant results; P ≤ 0.05). Integration of this information with a clinician's ADHD evaluation could help improve diagnostic accuracy from 61% to 88%.ConclusionsThe EEG-based assessment aid may help improve accuracy of ADHD diagnosis by supporting greater criterion E certainty.

Project description:BACKGROUND:Circulating biomarkers can facilitate diagnosis and risk stratification for complex conditions such as heart failure (HF). Newer molecular platforms can accelerate biomarker discovery, but they require significant resources for data and sample acquisition. OBJECTIVES:The purpose of this study was to test a pragmatic biomarker discovery strategy integrating automated clinical biobanking with proteomics. METHODS:Using the electronic health record, the authors identified patients with and without HF, retrieved their discarded plasma samples, and screened these specimens using a DNA aptamer-based proteomic platform (1,129 proteins). Candidate biomarkers were validated in 3 different prospective cohorts. RESULTS:In an automated manner, plasma samples from 1,315 patients (31% with HF) were collected. Proteomic analysis of a 96-patient subset identified 9 candidate biomarkers (p < 4.42 × 10-5). Two proteins, angiopoietin-2 and thrombospondin-2, were associated with HF in 3 separate validation cohorts. In an emergency department-based registry of 852 dyspneic patients, the 2 biomarkers improved discrimination of acute HF compared with a clinical score (p < 0.0001) or clinical score plus B-type natriuretic peptide (p = 0.02). In a community-based cohort (n = 768), both biomarkers predicted incident HF independent of traditional risk factors and N-terminal pro-B-type natriuretic peptide (hazard ratio per SD increment: 1.35 [95% confidence interval: 1.14 to 1.61; p = 0.0007] for angiopoietin-2, and 1.37 [95% confidence interval: 1.06 to 1.79; p = 0.02] for thrombospondin-2). Among 30 advanced HF patients, concentrations of both biomarkers declined (80% to 84%) following cardiac transplant (p < 0.001 for both). CONCLUSIONS:A novel strategy integrating electronic health records, discarded clinical specimens, and proteomics identified 2 biomarkers that robustly predict HF across diverse clinical settings. This approach could accelerate biomarker discovery for many diseases.

Project description:ADHD is the most common neurobehavioral disorder in school-aged children. In addition to genetic factors, environmental influences or gene x environmental interactions also play an important role in ADHD. One example of a well studied environmental risk factor for ADHD is exposure to polychlorinated biphenyls (PCBs). In this study, we investigated whether the well-established genetic model of ADHD based on the Spontaneously Hypertensive Rat (SHR) and a well established PCB-based model of ADHD exhibited similar molecular changes in brain circuits involved in ADHD. The brains from 28 male rats (8 SHR, 8 Sprague-Dawley (SD) controls, 8 Wistar-Kyoto (WKY) controls, and 4 PCB-exposed SD rats) were harvested at postnatal day 55-65 and RNA was isolated from six brain regions of interest. The RNA was analyzed for differences in expression of a set of 308 probe sets interrogating 218 unique genes considered highly relevant to ADHD or epigenetic gene regulation using the Rat RAE 230 2.0 GeneChip (Affymetrix). Selected observations were confirmed by real time quantitative RT-PCR. The results show that the expression levels of genes Gnal, COMT, Adrbk1, Ntrk2, Hk1, Syt11 and Csnk1a1 were altered in both the SHR rats and the PCB-exposed SD rats. Arrb2, Stx12, Aqp6, Syt1, Ddc and Pgk1 expression levels were changed only in the PCB-exposed SD rats. Genes with altered expression only in the SHRs included Oprm1, Calcyon, Calmodulin, Lhx1 and Hes6.The epigenetic genes Crebbp, Mecp2 and Hdac5 are significantly altered in both models. The data provide strong evidence that genes and environment can affect different set of genes in two different models of ADHD and yet result in the similar disease-like symptoms. The brains from 28 male rats (8 SHR, 8 Sprague-Dawley (SD) controls, 8 Wistar-Kyoto (WKY) controls, and 4 PCB-exposed SD rats) were harvested at postnatal day 55-65 and RNA was isolated from six brain regions of interest. The RNA was analyzed for differences in expression of a set of 308 probe sets interrogating 218 unique genes considered highly relevant to ADHD or epigenetic gene regulation using the Rat RAE 230 2.0 GeneChip (Affymetrix). Selected observations were confirmed by real time quantitative RT-PCR.

Dataset Information

Semi-Automated Biomarker Discovery from Pharmacodynamic Effects on EEG in ADHD Rodent Models.

Publications

Semi-Automated Biomarker Discovery from Pharmacodynamic Effects on EEG in ADHD Rodent Models.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets