Decomposing P300 to identify its genetic basis

Trial latencies estimation of event-related potentials in EEG by means of genetic algorithms

OBJECTIVE

Event-related potentials (ERPs) are usually obtained by averaging thus neglecting the trial-to-trial latency variability in cognitive electroencephalography (EEG) responses. As a consequence the shape and the peak amplitude of the averaged ERP are smeared and reduced, respectively, when the single-trial latencies show a relevant variability. To date, the majority of the methodologies for single-trial latencies inference are iterative schemes providing suboptimal solutions, the most commonly used being the Woody's algorithm.

APPROACH

In this study, a global approach is developed by introducing a fitness function whose global maximum corresponds to the set of latencies which renders the trial signals most aligned as possible. A suitable genetic algorithm has been implemented to solve the optimization problem, characterized by new genetic operators tailored to the present problem.

MAIN RESULTS

The results, on simulated trials, showed that the proposed algorithm performs better than Woody's algorithm in all conditions, at the cost of an increased computational complexity (justified by the improved quality of the solution). Application of the proposed approach on real data trials, resulted in an increased correlation between latencies and reaction times w.r.t. the output from RIDE method.

SIGNIFICANCE

The above mentioned results on simulated and real data indicate that the proposed method, providing a better estimate of single-trial latencies, will open the way to more accurate study of neural responses as well as to the issue of relating the variability of latencies to the proper cognitive and behavioural correlates.

Effect of GAD1 genotype status on auditory attention and acute nicotine administration in healthy volunteers

OBJECTIVE

The effects of GABA modulating drugs and nicotine, the prototypical nicotinic cholinergic agonist, on attention have been investigated using subcomponents of the P300 event-related potentials (ERP), which index involuntary (P3a) and voluntary attention (P3b). However, investigations into how such pharmacologic effects interact with genetic features in the GABA system remain unclear. This study examined the moderating effects of a single nucleotide polymorphism (rs7557793) in the glutamic acid decarboxylase 67 (GAD1) gene, which is implicated in the conversion of glutamate to GABA, on P300-indices of auditory attentional processing; the influence of nicotine administration was also assessed.

METHODS

The effects of GAD1 genotype (TT/CC/CT) were examined on the P3a/b in response to an auditory selective attention task in healthy, nonsmoking male volunteers (N = 126; 18-40 years). Participants responded to rare target stimuli (P3b-eliciting) and ignored frequent nontarget stimuli as well as rare distractor stimuli (P3a-eliciting). In a subsample (N = 59), P3a/b profiles to acute nicotine (vs. placebo) administration were examined as a function of GAD1 genotype. As a secondary aim, earlier sensory processes were assessed with N200 ERP subcomponents elicited by novel (N2a) and target (N2b) auditory stimuli.

RESULTS

GAD1 allelic variation moderated early sensory processes, enhancing N2a amplitudes in CT versus TT carriers. Further, TT homozygotes exhibited larger P3b amplitudes than CC homozygotes in the placebo versus nicotine condition. Regardless of genotype, nicotine versus placebo moderated the N200 ERP.

CONCLUSION

These findings expand our knowledge regarding the attentional effects of GAD1 genetic variants in relation to nicotine.

Associations between psychosis endophenotypes across brain functional, structural, and cognitive domains

BACKGROUND

A range of endophenotypes characterise psychosis, however there has been limited work understanding if and how they are inter-related.

METHODS

This multi-centre study includes 8754 participants: 2212 people with a psychotic disorder, 1487 unaffected relatives of probands, and 5055 healthy controls. We investigated cognition [digit span (N = 3127), block design (N = 5491), and the Rey Auditory Verbal Learning Test (N = 3543)], electrophysiology [P300 amplitude and latency (N = 1102)], and neuroanatomy [lateral ventricular volume (N = 1721)]. We used linear regression to assess the interrelationships between endophenotypes.

RESULTS

The P300 amplitude and latency were not associated (regression coef. -0.06, 95% CI -0.12 to 0.01, p = 0.060), and P300 amplitude was positively associated with block design (coef. 0.19, 95% CI 0.10-0.28, p 0.38). All the cognitive endophenotypes were associated with each other in the expected directions (all p < 0.001). Lastly, the relationships between pairs of endophenotypes were consistent in all three participant groups, differing for some of the cognitive pairings only in the strengths of the relationships.

CONCLUSIONS

The P300 amplitude and latency are independent endophenotypes; the former indexing spatial visualisation and working memory, and the latter is hypothesised to index basic processing speed. Individuals with psychotic illnesses, their unaffected relatives, and healthy controls all show similar patterns of associations between endophenotypes, endorsing the theory of a continuum of psychosis liability across the population.

Decomposing P300 into correlates of genetic risk and current symptoms in schizophrenia: An inter-trial variability analysis

BACKGROUND

The P300 event-related potential (ERP) component, which reflects cognitive processing, is a candidate biomarker for schizophrenia. However, the role of P300 in the pathophysiology of schizophrenia remains unclear because averaged P300 amplitudes reflect both genetic predisposition and current clinical status. Thus, we sought to identify which aspects of P300 are associated with genetic risk versus symptomatic status via an inter-trial variability analysis.

METHODS

Auditory P300, clinical symptoms, and neurocognitive function assessments were obtained from forty-five patients with schizophrenia, thirty-two subjects at genetic high risk (GHR), thirty-two subjects at clinical high risk (CHR), and fifty-two healthy control (HC) participants. Both conventional averaging and inter-trial variability analyses were conducted for P300, and results were compared across groups using analysis of variance (ANOVA). Pearson's correlation was utilized to determine associations among inter-trial variability for P300, current symptoms and neurocognitive status.

RESULTS

Average P300 amplitude was reduced in the GHR, CHR, and schizophrenia groups compared with that in the HC group. P300 inter-trial variability was elevated in the CHR and schizophrenia groups but relatively normal in the GHR and HC groups. Furthermore, P300 inter-trial variability was significantly related to negative symptom severity and neurocognitive performance results in schizophrenia patients.

CONCLUSIONS

These results suggest that P300 amplitude is an endophenotype for schizophrenia and that greater inter-trial variability of P300 is associated with more severe negative and cognitive symptoms in schizophrenia patients.

A polygenic risk score analysis of psychosis endophenotypes across brain functional, structural, and cognitive domains

This large multi-center study investigates the relationships between genetic risk for schizophrenia and bipolar disorder, and multi-modal endophenotypes for psychosis. The sample included 4,242 individuals; 1,087 patients with psychosis, 822 unaffected first-degree relatives of patients, and 2,333 controls. Endophenotypes included the P300 event-related potential (N = 515), lateral ventricular volume (N = 798), and the cognitive measures block design (N = 3,089), digit span (N = 1,437), and the Ray Auditory Verbal Learning Task (N = 2,406). Data were collected across 11 sites in Europe and Australia; all genotyping and genetic analyses were done at the same laboratory in the United Kingdom. We calculated polygenic risk scores for schizophrenia and bipolar disorder separately, and used linear regression to test whether polygenic scores influenced the endophenotypes. Results showed that higher polygenic scores for schizophrenia were associated with poorer performance on the block design task and explained 0.2% (p = 0.009) of the variance. Associations in the same direction were found for bipolar disorder scores, but this was not statistically significant at the 1% level (p = 0.02). The schizophrenia score explained 0.4% of variance in lateral ventricular volumes, the largest across all phenotypes examined, although this was not significant (p = 0.063). None of the remaining associations reached significance after correction for multiple testing (with alpha at 1%). These results indicate that common genetic variants associated with schizophrenia predict performance in spatial visualization, providing additional evidence that this measure is an endophenotype for the disorder with shared genetic risk variants. The use of endophenotypes such as this will help to characterize the effects of common genetic variation in psychosis.

Theta- and delta-band EEG network dynamics during a novelty oddball task

While the P3 component during target detection and novelty processing has been widely studied, less is known about its underlying network dynamics. A recent cognitive model suggests that frontal-parietal and frontal-temporal interregional connectivity are related to attention/action selection and target-related memory updating during the P3, respectively, but empirical work testing this model is lacking. Other work suggests the importance of theta- and delta-band connectivity between the medial frontal cortex and distributed cortical regions during attention, stimulus detection, and response selection processes, and similar dynamics may underlie P3-related network connectivity. The present study evaluated the functional connectivity elicited during a visual task, which combined oddball target and novelty stimuli, in a sample of 231 same-sex twins. It was hypothesized that both target and novel conditions would involve theta frontoparietal connectivity and medial frontal theta power, but that target stimuli would elicit the strongest frontotemporal connectivity. EEG time-frequency analysis revealed greater theta-band frontoparietal connectivity and medial frontal power during both target and novel conditions compared to standards, which may index conflict/uncertainty resolution processes. Theta-band frontotemporal connectivity was maximal during the target condition, potentially reflecting context updating or stimulus-response activation. Delta-band frontocentral-parietal connectivity was also strongest following targets, which may be sensitive to response-related demands. These results suggest the existence of functional networks related to P3 that are differentially engaged by target oddballs and novel distractors. Compared to simple P3 amplitude, network measures may provide a more nuanced view of the neural dynamics during target detection/novelty processing in normative and pathological populations.

What can time-frequency and phase coherence measures tell us about the genetic basis of P3 amplitude?

In a recent comprehensive investigation, we largely failed to identify significant genetic markers associated with P3 amplitude or to corroborate previous associations between P3 and specific single nucleotide polymorphisms (SNPs) or genes. In the present study we extended this line of investigation to examine time-frequency (TF) activity and intertrial phase coherence (ITPC) in the P3 time window, both of which are associated with P3 amplitude. Previous genome-wide research has reported associations between P3-related theta and delta activity and individual genetic variants. A large, population-based sample of 4211 subjects, comprising male and female adolescent twins and their parents, was genotyped for 527,828 single nucleotide polymorphisms (SNPs), from which over six million SNPs were accurately imputed. Heritability estimates were greater for TF energy than ITPC, whether based on biometric models or the combined influence of all measured SNPs (derived from genome-wide complex trait analysis). The magnitude of overlap in the specific SNPs associated with delta energy and ITPC and P3 amplitude was significant. A genome-wide analysis of all SNPs, accompanied by an analysis of approximately 17,600 genes, indicated a region of chromosome 2 around TEKT4 that was significantly associated with theta ITPC. Analysis of candidate SNPs and genes previously reported to be associated with P3 or related phenotypes yielded one association surviving correction for multiple tests: between theta energy and CRHR1. However, we did not obtain significant associations for SNPs implicated in previous genome-wide studies of TF measures. Identifying specific genetic variants associated with P3 amplitude remains a challenge.

Electrophysiological Endophenotypes for Schizophrenia

Endophenotypes are quantitative, heritable traits that may help to elucidate the pathophysiologic mechanisms underlying complex disease syndromes, such as schizophrenia. They can be assessed at numerous levels of analysis; here, we review electrophysiological endophenotypes that have shown promise in helping us understand schizophrenia from a more mechanistic point of view. For each endophenotype, we describe typical experimental procedures, reliability, heritability, and reported gene and neurobiological associations. We discuss recent findings regarding the genetic architecture of specific electrophysiological endophenotypes, as well as converging evidence from EEG studies implicating disrupted balance of glutamatergic signaling and GABAergic inhibition in the pathophysiology of schizophrenia. We conclude that refining the measurement of electrophysiological endophenotypes, expanding genetic association studies, and integrating data sets are important next steps for understanding the mechanisms that connect identified genetic risk loci for schizophrenia to the disease phenotype.

Knowns and unknowns for psychophysiological endophenotypes: integration and response to commentaries

We review and summarize seven molecular genetic studies of 17 psychophysiological endophenotypes that comprise this special issue of Psychophysiology, address criticisms raised in accompanying Perspective and Commentary pieces, and offer suggestions for future research. Endophenotypes are polygenic, and possibly influenced by rare genetic variants. Because they are not simpler genetically than clinical phenotypes, they are unlikely to assist gene discovery for psychiatric disorder. Once genetic variants for clinical phenotypes are identified, associated endophenotypes are likely to provide valuable insights into the psychological and neural mechanisms important to disorder pathology. This special issue provides a foundation for informed future steps in endophenotype genetics, including the formation of large sample consortia capable of fleshing out the many genetic variants contributing to individual differences in psychophysiological measures.