Huntington disease (HD) is an autosomal dominantly inherited neurodegenerative disease that affects motor, cognitive and psychiatric functions, and ultimately leads to death. The pathology of the disease is based on an expansion of CAG repeats in exon 1 of the huntingtin gene on chromosome 4, which produces a mutant huntingtin protein (mHtt). This protein is involved in neurotoxicity and brain atrophy, and can form β-sheets and abnormal mHtt aggregates. Currently, there are no approved effective treatments for HD, although tetrabenazine (Xenazine™) and deutetrabenazine (AUSTEDO™) have been approved for treatment of the motor symptom chorea in HD. This literature review aims to address the latest research on promising therapeutics based on influencing the hypothesized pathological mechanisms.

OBJECTIVE: The objective of this study was to evaluate the short-term efficacy and safety of the atypical antipsychotic agent lurasidone in the treatment of schizophrenia. METHODS: In this phase II, randomized, double-blind, placebo-controlled study, hospitalized adult patients diagnosed with schizophrenia and experiencing an acute exacerbation of psychotic symptoms were randomly assigned to 6 weeks of fixed-dose lurasidone 20 mg/day (n = 71), lurasidone 40 mg/day (n = 67), lurasidone 80 mg/day (n = 71), haloperidol 10 mg/day (n = 72, included to test for assay sensitivity), or placebo (n = 72). Efficacy was assessed using the brief psychiatric rating scale, positive and negative syndrome scale, and clinical global impression-severity. Safety assessments included incidence of adverse events and clinical laboratory measures. RESULTS: Numerical improvement was observed from baseline to week 6 (last observation carried forward) on all efficacy measures in all treatment groups; however, no statistically significant differences were noted between any lurasidone group and placebo, or between haloperidol and placebo. The most common adverse events in lurasidone-treated patients, with an incidence of at least 10% (dose groups combined) and greater than placebo, were sedation (15.3%), dyspepsia (13.4%), nausea (13.4%), akathisia (12.4%), and vomiting (10.5%); for haloperidol, the most common adverse events (incidence ⩾ 10% and greater than placebo) were extrapyramidal disorder (20.8%), sedation (19.4%), akathisia (19.4%), dystonia (15.3%), insomnia (13.9%), and somnolence (12.5%). Lurasidone was associated with minimal changes in weight, metabolic parameters, and prolactin levels. CONCLUSIONS: None of the lurasidone groups separated from placebo in this clinical study of patients with acute schizophrenia. In addition, haloperidol, which was included for assay sensitivity, did not separate from placebo, resulting in a failed study. Possible reasons for the lack of assay sensitivity in this study include the use of multiple active treatment arms and the relatively large placebo response. Consistent with other studies, lurasidone was generally safe and well tolerated, with minimal effects on weight or metabolic parameters.

Photically driven electroencephalography was tested in 17 chronic schizophrenia patients who were treated with clozapine for 5 weeks. Eight of the 17 patients showed clinical improvement on the Brief Psychiatric Rating Scale (delta BPRS > 30%) while the other 9 patients remained unchanged (delta BPRS < 15%). In comparison with the nonresponders, clozapine responders had a significantly greater increase in photic driving in the electroencephalogram (EEG), primarily in the low-frequency range of alpha band (7.2 hertz [Hz], 8.3 Hz, 9.0 Hz, and 9.6 Hz, but not 12.0 Hz). The difference in the resting EEG between the responders and nonresponders did not reach statistical significance. These findings suggested that EEG photic driving might be more sensitive than the resting EEG in detecting the central nervous system drug effect. Further analysis revealed that the increase of EEG photic driving was positively correlated with patients' clinical improvement. Combined with our previous observation in the drug-free schizophrenia patients who had lower EEG photic driving, present results supported the hypothesis that the amount of EEG alpha activity, particularly its synchronization to the external stimuli, could reflect the thalamic function in sensory information processing in schizophrenia.

Abstract Background The research goal is to better understand prescriber, patient, and caregiver perspectives about long-acting injectable (LAI) antipsychotic therapy and how these perspectives affect LAI use. Addressing these perspectives in the clinic may lead to greater success in achieving therapeutic goals for the patient with schizophrenia. Methods Ethnographic information was collected from a non-random sample of 69 prescriber-patient conversations (60 with community mental health center [CMHC] psychiatrists; 9 with nurse-practitioners) recorded during treatment visits from August 2011 to February 2012, transcribed and analyzed. Discussions were categorized according to 11 predetermined CMHC topics. In-person observations were also conducted at 4 CMHCs, including home visits by researchers (n = 15 patients) prior to the CMHC visit and observations of patients receiving injections and interacting with staff. Telephone in-depth interviews with psychiatrists, patients, and caregivers to gather additional information on LAI discussion, prescription, or use were conducted. Results Antipsychotic treatment decisions were made without patient or caregiver input in 40 of 60 (67%) of psychiatrist-patient conversations. Involvement of patients or caregivers in treatment decisions was greater when discussing LAI (15 of 60 [25%]) vs oral antipsychotic treatment (5 of 60 [8%]). LAIs were not discussed by psychiatrists in 11 of 22 (50%) patients taking oral antipsychotics. When offered, more LAI-naïve patients expressed neutral (9 of 19 [47%]) rather than favorable (3 of 19 [16%]) or unfavorable (7 of 19 [37%]) responses. Prescribers were most concerned about potentially damaging the therapeutic relationship and side-effects when discussing LAIs while patient resistance was often related to negative feelings about injections. Psychiatrists had some success in overcoming patient objections to LAIs by addressing and decomposing initial resistance. More than half (11 of 19 [58%]) of LAI-naïve patients agreed to start LAI treatment following office visits. Patient-described benefits of LAIs vs orals included perceived rapid symptom improvement and greater overall efficacy. Conclusions In this study, many psychiatrists did not offer LAIs and most patients and caregivers were not involved in antipsychotic treatment decision making. Opportunities to increase active patient engagement, address resistances, guide patient drug-formulation selection, and provide better LAI-relevant information for more individualized approaches to treating the patient with schizophrenia were present.

Abstract Background Recently we have witnessed a surge of interest in using genome-wide association studies (GWAS) to discover the genetic basis of complex diseases. Many genetic variations, mostly in the form of single nucleotide polymorphisms (SNPs), have been identified in a wide spectrum of diseases, including diabetes, cancer, and psychiatric diseases. A common theme arising from these studies is that the genetic variations discovered by GWAS can only explain a small fraction of the genetic risks associated with the complex diseases. New strategies and statistical approaches are needed to address this lack of explanation. One such approach is the pathway analysis, which considers the genetic variations underlying a biological pathway, rather than separately as in the traditional GWAS studies. A critical challenge in the pathway analysis is how to combine evidences of association over multiple SNPs within a gene and multiple genes within a pathway. Most current methods choose the most significant SNP from each gene as a representative, ignoring the joint action of multiple SNPs within a gene. This approach leads to preferential identification of genes with a greater number of SNPs. Results We describe a SNP-based pathway enrichment method for GWAS studies. The method consists of the following two main steps: 1) for a given pathway, using an adaptive truncated product statistic to identify all representative (potentially more than one) SNPs of each gene, calculating the average number of representative SNPs for the genes, then re-selecting the representative SNPs of genes in the pathway based on this number; and 2) ranking all selected SNPs by the significance of their statistical association with a trait of interest, and testing if the set of SNPs from a particular pathway is significantly enriched with high ranks using a weighted Kolmogorov-Smirnov test. We applied our method to two large genetically distinct GWAS data sets of schizophrenia, one from European-American (EA) and the other from African-American (AA). In the EA data set, we found 22 pathways with nominal P-value less than or equal to 0.001 and corresponding false discovery rate (FDR) less than 5%. In the AA data set, we found 11 pathways by controlling the same nominal P-value and FDR threshold. Interestingly, 8 of these pathways overlap with those found in the EA sample. We have implemented our method in a JAVA software package, called SNP Set Enrichment Analysis (SSEA), which contains a user-friendly interface and is freely available at http://cbcl.ics.uci.edu/SSEA. Conclusions The SNP-based pathway enrichment method described here offers a new alternative approach for analysing GWAS data. By applying it to schizophrenia GWAS studies, we show that our method is able to identify statistically significant pathways, and importantly, pathways that can be replicated in large genetically distinct samples.

Central nervous system (CNS) inhibitory mechanisms hypothesized to "gate" repetitive sensory inputs have been implicated in the pathology of schizophrenia. The present study investigated gender differences in inhibitory gating of evoked brain responses to repeated stimuli in normal subjects (30 women and 30 men) using an auditory conditioning-testing paradigm. Pairs of click stimuli (S1 and S2) were presented with a 0.5 s intrapair and a 10 s interpair interval. The amplitudes and latencies of the P50, N100, P180 components of the auditory evoked response to the conditioning (S1) and test response (S2) were measured, and the gating ratios were computed (T/C ratio = S2/S1 * 100). The amplitudes to S1 were not significantly different between men and women at P50, N100, or P180. However, women had significantly higher amplitudes to S2 at P50 (p = 0.03) and N100 (p = 0.04). The T/C ratios for women were higher (i.e., less suppression of response to S2) for P50 (p = 0.08) and N100 (p = 0.04) compared to men. The results suggested that differences in auditory gating between men and women were not due to biological differences in the P50 and N100 generators but possibly to differential influence of inhibitory mechanisms acting on the generator substrates of these evoked responses.

Background

Recently we have witnessed a surge of interest in using genome-wide association studies (GWAS) to discover the genetic basis of complex diseases. Many genetic variations, mostly in the form of single nucleotide polymorphisms (SNPs), have been identified in a wide spectrum of diseases, including diabetes, cancer, and psychiatric diseases. A common theme arising from these studies is that the genetic variations discovered by GWAS can only explain a small fraction of the genetic risks associated with the complex diseases. New strategies and statistical approaches are needed to address this lack of explanation. One such approach is the pathway analysis, which considers the genetic variations underlying a biological pathway, rather than separately as in the traditional GWAS studies. A critical challenge in the pathway analysis is how to combine evidences of association over multiple SNPs within a gene and multiple genes within a pathway. Most current methods choose the most significant SNP from each gene as a representative, ignoring the joint action of multiple SNPs within a gene. This approach leads to preferential identification of genes with a greater number of SNPs.

Results

We describe a SNP-based pathway enrichment method for GWAS studies. The method consists of the following two main steps: 1) for a given pathway, using an adaptive truncated product statistic to identify all representative (potentially more than one) SNPs of each gene, calculating the average number of representative SNPs for the genes, then re-selecting the representative SNPs of genes in the pathway based on this number; and 2) ranking all selected SNPs by the significance of their statistical association with a trait of interest, and testing if the set of SNPs from a particular pathway is significantly enriched with high ranks using a weighted Kolmogorov-Smirnov test. We applied our method to two large genetically distinct GWAS data sets of schizophrenia, one from European-American (EA) and the other from African-American (AA). In the EA data set, we found 22 pathways with nominal P-value less than or equal to 0.001 and corresponding false discovery rate (FDR) less than 5%. In the AA data set, we found 11 pathways by controlling the same nominal P-value and FDR threshold. Interestingly, 8 of these pathways overlap with those found in the EA sample. We have implemented our method in a JAVA software package, called SNP Set Enrichment Analysis (SSEA), which contains a user-friendly interface and is freely available at http://cbcl.ics.uci.edu/SSEA.

Conclusions

The SNP-based pathway enrichment method described here offers a new alternative approach for analysing GWAS data. By applying it to schizophrenia GWAS studies, we show that our method is able to identify statistically significant pathways, and importantly, pathways that can be replicated in large genetically distinct samples.