21 research outputs found
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Dissociable Genetic Contributions to Error Processing: A Multimodal Neuroimaging Study
Background: Neuroimaging studies reliably identify two markers of error commission: the error-related negativity (ERN), an event-related potential, and functional MRI activation of the dorsal anterior cingulate cortex (dACC). While theorized to reflect the same neural process, recent evidence suggests that the ERN arises from the posterior cingulate cortex not the dACC. Here, we tested the hypothesis that these two error markers also have different genetic mediation. Methods: We measured both error markers in a sample of 92 comprised of healthy individuals and those with diagnoses of schizophrenia, obsessive-compulsive disorder or autism spectrum disorder. Participants performed the same task during functional MRI and simultaneously acquired magnetoencephalography and electroencephalography. We examined the mediation of the error markers by two single nucleotide polymorphisms: dopamine D4 receptor (DRD4) C-521T (rs1800955), which has been associated with the ERN and methylenetetrahydrofolate reductase (MTHFR) C677T (rs1801133), which has been associated with error-related dACC activation. We then compared the effects of each polymorphism on the two error markers modeled as a bivariate response. Results: We replicated our previous report of a posterior cingulate source of the ERN in healthy participants in the schizophrenia and obsessive-compulsive disorder groups. The effect of genotype on error markers did not differ significantly by diagnostic group. DRD4 C-521T allele load had a significant linear effect on ERN amplitude, but not on dACC activation, and this difference was significant. MTHFR C677T allele load had a significant linear effect on dACC activation but not ERN amplitude, but the difference in effects on the two error markers was not significant. Conclusions: DRD4 C-521T, but not MTHFR C677T, had a significant differential effect on two canonical error markers. Together with the anatomical dissociation between the ERN and error-related dACC activation, these findings suggest that these error markers have different neural and genetic mediation
An Evaluation of Antiepileptic Drug Therapy in Nursing Facilities
Objectives: To describe the prescribing and use of antiepileptic drug (AED) therapy in nursing facility residents. Design: A retrospective, multicenter drug use evaluation. Setting: A total of 85 nursing facilities (average size, 119 beds) in five states. Participants: 1132 residents of the total 10,168 residents screened were prescribed at least one AED. Measures: Demographic information, primary indication for AED, comorbid conditions, prescribing physician\u27s specialty, concomitant medications, and AED dosage regimen information were collected. Laboratory tests obtained in the most recent 6 months and seizure occurrence and seizure-related diagnostic assessments made in the most recent 3 months were also recorded. Results: Of 1132 residents receiving AED therapy, 892 (78.8%) were prescribed AED therapy for a seizure-related diagnosis although 86% of seizure types were unspecified. Another 215 residents (19.0%) were prescribed AEDs for nonseizure diagnoses, and 25 (2.2%) had no indication for AED therapy. AEDs most frequently prescribed were phenytoin (56.8%), carbamazepine (23.0%), phenobarbital (15.6%), and valproic acid (13.1%). For residents with a seizure diagnosis, the most frequently prescribed monotherapy agents were phenytoin (52.0%), carbamazepine (12.2%), and phenobarbitol (7.1%). Almost 25% of residents with a seizure diagnosis took a combination of AEDs; more than 50% of all combinations included phenobarbital. About 9% of residents with a seizure diagnosis had one or more documented seizures during a 3-month review period. Conclusion: Among the substantial percentage of residents treated with AEDs, the lack of diagnosis of seizure type has serious implications for the choice of AED therapy. Opportunities exist for prescribing physicians, consultant pharmacists, and nursing staff to improve the medical management of nursing facility residents with seizures and of others receiving AEDs
An Evaluation of Antiepileptic Drug Therapy in Nursing Facilities
Objectives:
To describe the prescribing and use of antiepileptic drug (AED) therapy in nursing facility residents.
Design:
A retrospective, multicenter drug use evaluation.
Setting:
A total of 85 nursing facilities (average size, 119 beds) in five states.
Participants:
1132 residents of the total 10,168 residents screened were prescribed at least one AED.
Measures:
Demographic information, primary indication for AED, comorbid conditions, prescribing physician\u27s specialty, concomitant medications, and AED dosage regimen information were collected. Laboratory tests obtained in the most recent 6 months and seizure occurrence and seizure-related diagnostic assessments made in the most recent 3 months were also recorded.
Results:
Of 1132 residents receiving AED therapy, 892 (78.8%) were prescribed AED therapy for a seizure-related diagnosis although 86% of seizure types were unspecified. Another 215 residents (19.0%) were prescribed AEDs for nonseizure diagnoses, and 25 (2.2%) had no indication for AED therapy. AEDs most frequently prescribed were phenytoin (56.8%), carbamazepine (23.0%), phenobarbital (15.6%), and valproic acid (13.1%). For residents with a seizure diagnosis, the most frequently prescribed monotherapy agents were phenytoin (52.0%), carbamazepine (12.2%), and phenobarbitol (7.1%). Almost 25% of residents with a seizure diagnosis took a combination of AEDs; more than 50% of all combinations included phenobarbital. About 9% of residents with a seizure diagnosis had one or more documented seizures during a 3-month review period.
Conclusion:
Among the substantial percentage of residents treated with AEDs, the lack of diagnosis of seizure type has serious implications for the choice of AED therapy. Opportunities exist for prescribing physicians, consultant pharmacists, and nursing staff to improve the medical management of nursing facility residents with seizures and of others receiving AEDs
Outcome measures divided by diagnosis.
1<p>Collapsed across fMRI and EEG sessions. Note that participants with fewer than 10 usable error trials per modality were excluded from the study.</p
Genetic modulation of error-related dACC activation.
<p>A: <i>MTHFR C677T</i>. B: <i>DRD4 C-521T</i>. Statistical maps show regressions of activation in the error vs. correct contrast on allele load. Blue colors represent a negative correlation, i.e., stronger activation associated with more 677T (A) or -521C (B) alleles. The gray masks cover subcortical regions in which activity is displaced in a surface rendering.</p
Genetic dissociation between error-related dACC activation and the ERN.
<p>Both error markers are shown in standardized units as a function of risk allele load (677T for <i>MTHFR C677T</i>, -521C for <i>DRD4 C-521T</i>). Error bars represent within subject confidence intervals <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0101784#pone.0101784-Loftus1" target="_blank">[75]</a> for each allele combination.</p
fMRI and EEG error markers.
<p>A. Error-related dACC activation. Statistical maps of activation at 6 s in the contrast of error vs. correct are displayed on the inflated medial cortical surfaces. The dACC ROI is outlined in black. Warm colors indicate stronger activation on errors. The gray masks cover subcortical regions in which activity is displaced in a surface rendering. Line graphs show hemodynamic response functions for correct and error trials in the vertices with maximal error-related activation in the dACC. B. The ERN. The left panel shows grand average waveforms for correct (black) and error (red) trials, time locked to the onset of the saccade. The right panel shows the difference waveform, obtained by subtracting the correct waveform from the error waveform. The thin lines on either side of the waveforms represent the standard error of the mean at each time point.</p
Breakdown of study sample by allele load for each SNP.
<p>Allele load (0,1,2) refers to the number of risk alleles: <i>677T</i> for <i>MTHFR C677T</i> and <i>521C</i> for <i>DRD4 C-521T.</i></p
Genetic modulation of the ERN.
<p>A: <i>MTHFR</i> C677T. B: <i>DRD4 C-</i>521T. Correct and error trial waveforms are shown for every allele combination of each polymorphism. The error-correct difference waveforms for each allele combination is shown on the right column. The thin lines on either side of the waveforms represent the standard error of the mean at each time point.</p
Results of the bivariate analyses testing the differential effects of each SNP on error markers.
<p>The primary analysis included the entire sample, allele load, and no covariate for diagnosis.</p><p>*significant at p≤.05.</p