Enantioselective in vitro ADME, absolute oral bioavailability, and pharmacokinetics of (-)-lumefantrine and (+)-lumefantrine in mice.

Lumefantrine (LFN) is a chiral antimalarial drug. Enantioselective in vitro attributes and absolute oral pharmacokinetics for (-)-LFN and (+)-LFN have been characterized in mice. No stereoselectivity was seen with either of the enantiomers when compared with rac-LFN in the executed in vitro studies (solubility, metabolic stability, protein binding, permeability and blood partitioning). Post intravenous or oral administration of rac-LFN, the AUC0-∞ and MRT of (+)-LFN was higher over (-)-LFN, which is reflected in higher clearance value for (-)-LFN. Following (-)-LFN intravenous administration to mice, the key PK parameters were comparable to (-)-LFN from rac-LFN; however, post intravenous administration of (+)-LFN alone to mice, the AUC0-∞ was 1.3-fold higher than (+)-LFN from rac-LFN. Similarly, post oral administration of (-)-LFN to mice, both AUC0-∞ and Cmax were 1.3-fold higher than (-)-LFN from rac-LFN. On other hand, (+)-LFN showed 1.4-fold higher AUC0-∞ and 1.7-fold higher Cmax post oral administration over (+)-LFN from rac-LFN.

Multivariate Analyses Reveal Biological Components Related to Neuronal Signaling and Immunity Mediating Electroencephalograms Abnormalities in Alcohol-Dependent Individuals from the Collaborative Study on the Genetics of Alcoholism Cohort.

BACKGROUND: The underlying molecular mechanisms associated with alcohol use disorder (AUD) risk have only been partially revealed using traditional approaches such as univariate genomewide association and linkage-based analyses. We therefore aimed to identify gene clusters related to Electroencephalograms (EEG) neurobiological phenotypes distinctive to individuals with AUD using a multivariate approach. METHODS: The current project adopted a bimultivariate data-driven approach, parallel independent component analysis (para-ICA), to derive and explore significant genotype-phenotype associations in a case-control subset of the Collaborative Study on the Genetics of Alcoholism (COGA) dataset. Para-ICA subjects comprised N = 799 self-reported European Americans (367 controls and 432 AUD cases), recruited from COGA, who had undergone resting EEG and genotyping. Both EEG and genomewide single nucleotide polymorphism (SNP) data were preprocessed prior to being subjected to para-ICA in order to derive genotype-phenotype relationships. RESULTS: From the data, 4 EEG frequency and 4 SNP components were estimated, with 2 significantly correlated EEG-genetic relationship pairs. The first such pair primarily represented theta activity, negatively correlated with a genetic cluster enriched for (but not limited to) ontologies/disease processes representing cell signaling, neurogenesis, transmembrane drug transportation, alcoholism, and lipid/cholesterol metabolism. The second component pair represented mainly alpha activity, positively correlated with a genetic cluster with ontologies similarly enriched as the first component. Disease-related enrichments for this component revealed heart and autoimmune disorders as top hits. Loading coefficients for both the alpha and theta components were significantly reduced in cases compared to controls. CONCLUSIONS: Our data suggest plausible multifactorial genetic components, primarily enriched for neuronal/synaptic signaling/transmission, immunity, and neurogenesis, mediating low-frequency alpha and theta abnormalities in alcohol addiction.

Multivariate analysis reveals genetic associations of the resting default mode network in psychotic bipolar disorder and schizophrenia.

The brain's default mode network (DMN) is highly heritable and is compromised in a variety of psychiatric disorders. However, genetic control over the DMN in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is largely unknown. Study subjects (n = 1,305) underwent a resting-state functional MRI scan and were analyzed by a two-stage approach. The initial analysis used independent component analysis (ICA) in 324 healthy controls, 296 SZ probands, 300 PBP probands, 179 unaffected first-degree relatives of SZ probands (SZREL), and 206 unaffected first-degree relatives of PBP probands to identify DMNs and to test their biomarker and/or endophenotype status. A subset of controls and probands (n = 549) then was subjected to a parallel ICA (para-ICA) to identify imaging-genetic relationships. ICA identified three DMNs. Hypo-connectivity was observed in both patient groups in all DMNs. Similar patterns observed in SZREL were restricted to only one network. DMN connectivity also correlated with several symptom measures. Para-ICA identified five sub-DMNs that were significantly associated with five different genetic networks. Several top-ranking SNPs across these networks belonged to previously identified, well-known psychosis/mood disorder genes. Global enrichment analyses revealed processes including NMDA-related long-term potentiation, PKA, immune response signaling, axon guidance, and synaptogenesis that significantly influenced DMN modulation in psychoses. In summary, we observed both unique and shared impairments in functional connectivity across the SZ and PBP cohorts; these impairments were selectively familial only for SZREL. Genes regulating specific neurodevelopment/transmission processes primarily mediated DMN disconnectivity. The study thus identifies biological pathways related to a widely researched quantitative trait that might suggest novel, targeted drug treatments for these diseases.

A large scale multivariate parallel ICA method reveals novel imaging-genetic relationships for Alzheimer's disease in the ADNI cohort.

The underlying genetic etiology of late onset Alzheimer's disease (LOAD) remains largely unknown, likely due to its polygenic architecture and a lack of sophisticated analytic methods to evaluate complex genotype-phenotype models. The aim of the current study was to overcome these limitations in a bi-multivariate fashion by linking intermediate magnetic resonance imaging (MRI) phenotypes with a genome-wide sample of common single nucleotide polymorphism (SNP) variants. We compared associations between 94 different brain regions of interest derived from structural MRI scans and 533,872 genome-wide SNPs using a novel multivariate statistical procedure, parallel-independent component analysis, in a large, national multi-center subject cohort. The study included 209 elderly healthy controls, 367 subjects with amnestic mild cognitive impairment and 181 with mild, early-stage LOAD, all of them Caucasian adults, from the Alzheimer's Disease Neuroimaging Initiative cohort. Imaging was performed on comparable 1.5 T scanners at over 50 sites in the USA/Canada. Four primary "genetic components" were associated significantly with a single structural network including all regions involved neuropathologically in LOAD. Pathway analysis suggested that each component included several genes already known to contribute to LOAD risk (e.g. APOE4) or involved in pathologic processes contributing to the disorder, including inflammation, diabetes, obesity and cardiovascular disease. In addition significant novel genes identified included ZNF673, VPS13, SLC9A7, ATP5G2 and SHROOM2. Unlike conventional analyses, this multivariate approach identified distinct groups of genes that are plausibly linked in physiologic pathways, perhaps epistatically. Further, the study exemplifies the value of this novel approach to explore large-scale data sets involving high-dimensional gene and endophenotype data.

Evaluating the Outcomes of an Organizational Initiative to Expand End-of-Life Resources in Intensive Care Units With Palliative Support Tools and Floating Hospice.

BACKGROUND: There is evidence that palliative care and floating (inpatient) hospice can improve end-of-life experiences for patients and their families in the intensive care unit (ICU). However, both palliative care and hospice remain underutilized in the ICU setting. OBJECTIVES: This study examined palliative consultations and floating hospice referrals for ICU patients during a phased launch of floating hospice, 2 palliative order sets, and general education to support implementation of palliative care guidelines. METHODS: This descriptive, retrospective study was conducted at a level I trauma and academic medical center. Electronic medical records of 400 ICU patients who died in the hospital were randomly selected. These electronic medical records were reviewed to determine if patients received a palliative consult and/or a floating hospice referral, as well as whether the new palliative support tools were used during the course of care. The numbers of floating hospice referrals and palliative consults were measured over time. RESULTS: Although not significant, palliative consults increased over time (P = .055). After the initial introduction of floating hospice, 27% of the patients received referrals; however, referrals did not significantly increase over time (P = .807). Of the 68 patients who received a floating hospice referral (24%), only 38 were discharged to floating hospice. There was a trend toward earlier palliative care consults, although this was not statistically significant (P = .285). CONCLUSION: This study provided the organization with vital information about their initiative to expand end-of-life resources. Utilization and timing of palliative consults and floating hospice referrals were lower and later than expected, highlighting the importance of developing purposeful strategies beyond education to address ICU cultural and structural barriers.

NRXN1 is associated with enlargement of the temporal horns of the lateral ventricles in psychosis.

Schizophrenia, Schizoaffective, and Bipolar disorders share behavioral and phenomenological traits, intermediate phenotypes, and some associated genetic loci with pleiotropic effects. Volumetric abnormalities in brain structures are among the intermediate phenotypes consistently reported associated with these disorders. In order to examine the genetic underpinnings of these structural brain modifications, we performed genome-wide association analyses (GWAS) on 60 quantitative structural brain MRI phenotypes in a sample of 777 subjects (483 cases and 294 controls pooled together). Genotyping was performed with the Illumina PsychChip microarray, followed by imputation to the 1000 genomes multiethnic reference panel. Enlargement of the Temporal Horns of Lateral Ventricles (THLV) is associated with an intronic SNP of the gene NRXN1 (rs12467877, P = 6.76E-10), which accounts for 4.5% of the variance in size. Enlarged THLV is associated with psychosis in this sample, and with reduction of the hippocampus and enlargement of the choroid plexus and caudate. Eight other suggestively significant associations (P < 5.5E-8) were identified with THLV and 5 other brain structures. Although rare deletions of NRXN1 have been previously associated with psychosis, this is the first report of a common SNP variant of NRXN1 associated with enlargement of the THLV in psychosis.

Composite impulsivity-related domains in college students.

Impulsivity is a complex, multidimensional construct with prior theoretically and empirically derived characterizations of impulsivity-related behaviors varying considerably among studies. We assessed college students (N = 440) longitudinally with five impulsivity-related self-reported assessments and two computerized behavioral measures. Using a combination of exploratory and confirmatory factor analysis (CFA), we derived then validated several composite impulsivity-related domains (CIRDs). These factors replicated, in large part, findings from a previous study conducted by our group in an independent sample that used a similar analytical approach. The four CIRDs derived in current study are: 'Impulsive action', 'Approach/Appetite Motivation', 'Impulsivity/Compulsivity' and 'Experience and thrill seeking/Fearlessness'. Subsequent psychometric analyses found these CIRDs were relatively stable over the two-year period. Moreover, multiple regression analysis found that CIRD profiles associated with clinical and behavioral characteristics including anxiety, depression, attention deficit hyperactivity disorder and substance use symptomology. Overall, our data suggest that empirically-derived CIRDs have potential for organizing previous impulsivity-related constructs into a more naturalistic framework where distinct constructs are often expressed together in the same individuals. This framework might facilitate future research of neuropsychiatric disorder risk and etiology.

Novel gene-brain structure relationships in psychotic disorder revealed using parallel independent component analyses.

BACKGROUND: Schizophrenia, schizoaffective disorder, and psychotic bipolar disorder overlap with regard to symptoms, structural and functional brain abnormalities, and genetic risk factors. Neurobiological pathways connecting genes to clinical phenotypes across the spectrum from schizophrenia to psychotic bipolar disorder remain largely unknown. METHODS: We examined the relationship between structural brain changes and risk alleles across the psychosis spectrum in the multi-site Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) cohort. Regional MRI brain volumes were examined in 389 subjects with a psychotic disorder (139 schizophrenia, 90 schizoaffective disorder, and 160 psychotic bipolar disorder) and 123 healthy controls. 451,701 single-nucleotide polymorphisms were screened and processed using parallel independent component analysis (para-ICA) to assess associations between genes and structural brain abnormalities in probands. RESULTS: 482 subjects were included after quality control (364 individuals with psychotic disorder and 118 healthy controls). Para-ICA identified four genetic components including several risk genes already known to contribute to schizophrenia and bipolar disorder and revealed three structural components that showed overlapping relationships with the disease risk genes across the three psychotic disorders. Functional ontologies representing these gene clusters included physiological pathways involved in brain development, synaptic transmission, and ion channel activity. CONCLUSIONS: Heritable brain structural findings such as reduced cortical thickness and surface area in probands across the psychosis spectrum were associated with somewhat distinct genes related to putative disease pathways implicated in psychotic disorders. This suggests that brain structural alterations might represent discrete psychosis intermediate phenotypes along common neurobiological pathways underlying disease expression across the psychosis spectrum.

Multivariate Genetic Correlates of the Auditory Paired Stimuli-Based P2 Event-Related Potential in the Psychosis Dimension From the BSNIP Study.

OBJECTIVE: The complex molecular etiology of psychosis in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is not well defined, presumably due to their multifactorial genetic architecture. Neurobiological correlates of psychosis can be identified through genetic associations of intermediate phenotypes such as event-related potential (ERP) from auditory paired stimulus processing (APSP). Various ERP components of APSP are heritable and aberrant in SZ, PBP and their relatives, but their multivariate genetic factors are less explored. METHODS: We investigated the multivariate polygenic association of ERP from 64-sensor auditory paired stimulus data in 149 SZ, 209 PBP probands, and 99 healthy individuals from the multisite Bipolar-Schizophrenia Network on Intermediate Phenotypes study. Multivariate association of 64-channel APSP waveforms with a subset of 16 999 single nucleotide polymorphisms (SNPs) (reduced from 1 million SNP array) was examined using parallel independent component analysis (Para-ICA). Biological pathways associated with the genes were assessed using enrichment-based analysis tools. RESULTS: Para-ICA identified 2 ERP components, of which one was significantly correlated with a genetic network comprising multiple linearly coupled gene variants that explained ~4% of the ERP phenotype variance. Enrichment analysis revealed epidermal growth factor, endocannabinoid signaling, glutamatergic synapse and maltohexaose transport associated with P2 component of the N1-P2 ERP waveform. This ERP component also showed deficits in SZ and PBP. CONCLUSIONS: Aberrant P2 component in psychosis was associated with gene networks regulating several fundamental biologic functions, either general or specific to nervous system development. The pathways and processes underlying the gene clusters play a crucial role in brain function, plausibly implicated in psychosis.

Joint Coupling of Awake EEG Frequency Activity and MRI Gray Matter Volumes in the Psychosis Dimension: A BSNIP Study.

BACKGROUND: Many studies have examined either electroencephalogram (EEG) frequency activity or gray matter volumes (GMV) in various psychoses [including schizophrenia (SZ), schizoaffective (SZA), and psychotic bipolar disorder (PBP)]. Prior work demonstrated similar EEG and gray matter abnormalities in both SZ and PBP. Integrating EEG and GMV and jointly analyzing the combined data fully elucidates the linkage between the two and may provide better biomarker- or endophenotype-specificity for a particular illness. Joint exploratory investigations of EEG and GMV are scarce in the literature and the relationship between the two in psychosis is even less explored. We investigated a joint multivariate model to test whether the linear relationship or linkage between awake EEG (AEEG) frequency activity and GMV is abnormal across the psychosis dimension and if such effects are also present in first-degree relatives. METHODS: We assessed 607 subjects comprising 264 probands [105 SZ, 72 SZA, and 87 PBP], 233 of their first degree relatives [82 SZ relatives (SZR), 71 SZA relatives (SZAR), and 80 PBP relatives (PBPR)], and 110 healthy comparison subjects (HC). All subjects underwent structural MRI (sMRI) and EEG scans. Frequency activity and voxel-based morphometric GMV were derived from EEG and sMRI data, respectively. Seven AEEG frequency and gray matter components were extracted using Joint independent component analysis (jICA). The loading coefficients (LC) were examined for group differences using analysis of covariance. Further, the LCs were correlated with psychopathology scores to identify relationship with clinical symptoms. RESULTS: Joint ICA revealed a single component differentiating SZ from HC (p < 0.006), comprising increased posterior alpha activity associated with decreased volume in inferior parietal lobe, supramarginal, parahippocampal gyrus, middle frontal, inferior temporal gyri, and increased volume of uncus and culmen. No components were aberrant in either PBP or SZA or any relative group. No significant association was identified with clinical symptom measures. CONCLUSION: Our data suggest that a joint EEG and GMV model yielded a biomarker specific to SZ, not abnormal in PBP or SZA. Alpha activity was related to both increased and decreased volume in different cortical structures. Additionally, the joint model failed to identify endophenotypes across psychotic disorders.

Genetic Sources of Subcomponents of Event-Related Potential in the Dimension of Psychosis Analyzed From the B-SNIP Study.

OBJECTIVE: Biological risk factors underlying psychosis are poorly understood. Biological underpinnings of the dimension of psychosis can be derived using genetic associations with intermediate phenotypes such as subcomponents of auditory event-related potentials (ERPs). Various ERP subcomponent abnormalities in schizophrenia and psychotic bipolar disorder are heritable and are expressed in unaffected relatives, although studies investigating genetic contributions to ERP abnormalities are limited. The authors used a novel parallel independent component analysis (para-ICA) to determine which empirically derived gene clusters are associated with data-driven ERP subcomponents, assuming a complex etiology underlying psychosis. METHOD: The authors examined the multivariate polygenic association of ERP subcomponents from 64-channel auditory oddball data in 144 individuals with schizophrenia, 210 psychotic bipolar disorder probands, and 95 healthy individuals from the multisite Bipolar-Schizophrenia Network on Intermediate Phenotypes study. Data were reduced by principal components analysis to two target and one standard ERP waveforms. Multivariate association of compressed ERP waveforms with a set of 20,329 single-nucleotide polymorphisms (SNPs) (reduced from a 1-million-SNP array) was examined using para-ICA. Genes associated with SNPs were further examined using pathway analysis tools. RESULTS: Para-ICA identified four ERP components that were significantly correlated with three genetic components. Enrichment analysis revealed complement immune response pathway and multiple processes that significantly mediate ERP abnormalities in psychosis, including synaptic cell adhesion, axon guidance, and neurogenesis. CONCLUSIONS: This study identified three genetic components comprising multiple genes mediating ERP subcomponent abnormalities in schizophrenia and psychotic bipolar disorder. The data suggest a possible polygenic structure comprising genes influencing key neurodevelopmental processes, neural circuitry, and brain function mediating biological pathways plausibly associated with psychosis.

Resting state electroencephalogram oscillatory abnormalities in schizophrenia and psychotic bipolar patients and their relatives from the bipolar and schizophrenia network on intermediate phenotypes study.

BACKGROUND: Abnormal resting state electroencephalogram (EEG) oscillations are reported in schizophrenia (SZ) and bipolar disorder, illnesses with overlapping symptoms and genetic risk. However, less evidence exists on whether similar EEG spectral abnormalities are present in individuals with both disorders or whether these abnormalities are present in first-degree relatives, possibly representing genetic predisposition for these disorders. METHODS: Investigators examined 64-channel resting state EEGs of 225 SZ probands and 201 first-degree relatives (SZR), 234 psychotic bipolar (PBP) probands and 231 first-degree relatives (PBPR), and 200 healthy control subjects. Eight independent resting state EEG spectral components and associated spatial weights were derived using group independent component analysis. Analysis of covariance was conducted on spatial weights to evaluate group differences. Relative risk estimates and familiality were evaluated on abnormal spectral profiles in probands and relatives. RESULTS: Both SZ and PBP probands exhibited increased delta, theta, and slow and fast alpha activity. Post-hoc pair-wise comparison revealed increased frontocentral slow beta activity in SZ and PBP probands as well as SZR and PBPR. Augmented frontal delta activity was exhibited by SZ probands and SZR, whereas PBP probands and PBPR showed augmented fast alpha activity. CONCLUSIONS: Both SZ and PBP probands demonstrated aberrant low-frequency activity. Slow beta activity was abnormal in SZ and PBP probands as well as SZR and PBPR perhaps indicating a common endophenotype for both disorders. Delta and fast alpha activity were unique endophenotypes for SZ and PBP probands, respectively. The EEG spectral activity exhibited moderate relative risk and heritability estimates, serving as intermediate phenotypes in future genetic studies for examining biological mechanisms underlying the pathogenesis of the two disorders.

Effects of memantine on event-related potential, oscillations, and complexity in individuals with and without family histories of alcoholism.

OBJECTIVE: Enhanced N-methyl-D-aspartate (NMDA) receptor function associated with a positive family history of alcoholism (FHP) has been hypothesized to contribute to the heritable risk for alcoholism. The objective of this study was to evaluate the relationship of alcoholism family history, NMDA receptor function, and cortical information processing by testing acute effects of the NMDA receptor antagonist memantine on event-related potential (ERP). METHOD: Twenty-two healthy FHP and 20 healthy family history-negative (FHN; no alcoholic relatives) subjects were administered placebo or 40 mg of memantine under double-blind counterbalanced conditions on two separate occasions. Electroencephalogram data were collected from eight channels with eyes open during an auditory oddball discrimination task. We evaluated P3b amplitude, total theta, alpha activity, and fractal dimension from ERP trials. RESULTS: FHP and FHN subjects did not differ in P3b amplitude. A significant Group × Drug interaction was observed in theta, alpha activity, and fractal dimension at the parietal and occipital sites. FHP individuals exhibited significantly higher fractal dimension and lower theta and alpha activity after placebo relative to FHN subjects. Following memantine administration, theta activity decreased in both groups but more markedly for FHN individuals. Alpha activity decreased for FHN subjects and increased for FHP individuals, whereas the fractal dimension decreased for FHP subjects and increased for FHN subjects after memantine. CONCLUSIONS: A plausible interpretation of these results is that FHP individuals may have altered NMDA receptor function compared with FHN individuals. These findings provide additional evidence of differences in the regulation of NMDA receptor function between FHP and FHN individuals.

Scene-based nonuniformity correction technique that exploits knowledge of the focal-plane array readout architecture.

Spatial fixed-pattern noise is a common and major problem in modern infrared imagers owing to the nonuniform response of the photodiodes in the focal plane array of the imaging system. In addition, the nonuniform response of the readout and digitization electronics, which are involved in multiplexing the signals from the photodiodes, causes further nonuniformity. We describe a novel scene based on a nonuniformity correction algorithm that treats the aggregate nonuniformity in separate stages. First, the nonuniformity from the readout amplifiers is corrected by use of knowledge of the readout architecture of the imaging system. Second, the nonuniformity resulting from the individual detectors is corrected with a nonlinear filter-based method. We demonstrate the performance of the proposed algorithm by applying it to simulated imagery and real infrared data. Quantitative results in terms of the mean absolute error and the signal-to-noise ratio are also presented to demonstrate the efficacy of the proposed algorithm. One advantage of the proposed algorithm is that it requires only a few frames to obtain high-quality corrections.