Lipidomics Reveals Early Metabolic Changes in Subjects with Schizophrenia: Effects of Atypical Antipsychotics

There is a critical need for mapping early metabolic changes in schizophrenia to capture failures in regulation of biochemical pathways and networks. This information could provide valuable insights about disease mechanisms, trajectory of disease progression, and diagnostic biomarkers. We used a lipidomics platform to measure individual lipid species in 20 drug-naïve patients with a first episode of schizophrenia (FE group), 20 patients with chronic schizophrenia that had not adhered to prescribed medications (RE group), and 29 race-matched control subjects without schizophrenia. Lipid metabolic profiles were evaluated and compared between study groups and within groups before and after treatment with atypical antipsychotics, risperidone and aripiprazole. Finally, we mapped lipid profiles to n3 and n6 fatty acid synthesis pathways to elucidate which enzymes might be affected by disease and treatment. Compared to controls, the FE group showed significant down-regulation of several n3 polyunsaturated fatty acids (PUFAs), including 20:5n3, 22:5n3, and 22:6n3 within the phosphatidylcholine and phosphatidylethanolamine lipid classes. Differences between FE and controls were only observed in the n3 class PUFAs; no differences where noted in n6 class PUFAs. The RE group was not significantly different from controls, although some compositional differences within PUFAs were noted. Drug treatment was able to correct the aberrant PUFA levels noted in FE patients, but changes in re patients were not corrective. Treatment caused increases in both n3 and n6 class lipids. These results supported the hypothesis that phospholipid n3 fatty acid deficits are present early in the course of schizophrenia and tend not to persist throughout its course. These changes in lipid metabolism could indicate a metabolic vulnerability in patients with schizophrenia that occurs early in development of the disease. © 2013 McEvoy et al

CrossHybDetector: detection of cross-hybridization events in DNA microarray experiments

Background\ud DNA microarrays contain thousands of different probe sequences represented on their surface. These are designed in such a way that potential cross-hybridization reactions with non-target sequences are minimized. However, given the large number of probes, the occurrence of cross hybridization events cannot be excluded. This problem can dramatically affect the data quality and cause false positive/false negative results.\ud \ud Results\ud CrossHybDetector is a software package aimed at the identification of cross-hybridization events occurred during individual array hybridization, by using the probe sequences and the array intensity values. As output, the software provides the user with a list of array spots potentially 'corrupted' and their associated p-values calculated by Monte Carlo simulations. Graphical plots are also generated, which provide a visual and global overview of the quality of the microarray experiment with respect to cross-hybridization issues.\ud \ud Conclusion\ud CrossHybDetector is implemented as a package for the statistical computing environment R and is freely available under the LGPL license within the CRAN project

Seminal plasma as a source of prostate cancer peptide biomarker candidates for detection of indolent and advanced disease

Background:Extensive prostate specific antigen screening for prostate cancer generates a high number of unnecessary biopsies and over-treatment due to insufficient differentiation between indolent and aggressive tumours. We hypothesized that seminal plasma is a robust source of novel prostate cancer (PCa) biomarkers with the potential to improve primary diagnosis of and to distinguish advanced from indolent disease. <br>Methodology/Principal Findings: In an open-label case/control study 125 patients (70 PCa, 21 benign prostate hyperplasia, 25 chronic prostatitis, 9 healthy controls) were enrolled in 3 centres. Biomarker panels a) for PCa diagnosis (comparison of PCa patients versus benign controls) and b) for advanced disease (comparison of patients with post surgery Gleason score <7 versus Gleason score >>7) were sought. Independent cohorts were used for proteomic biomarker discovery and testing the performance of the identified biomarker profiles. Seminal plasma was profiled using capillary electrophoresis mass spectrometry. Pre-analytical stability and analytical precision of the proteome analysis were determined. Support vector machine learning was used for classification. Stepwise application of two biomarker signatures with 21 and 5 biomarkers provided 83% sensitivity and 67% specificity for PCa detection in a test set of samples. A panel of 11 biomarkers for advanced disease discriminated between patients with Gleason score 7 and organ-confined (<pT3a) or advanced (≥pT3a) disease with 80% sensitivity and 82% specificity in a preliminary validation setting. Seminal profiles showed excellent pre-analytical stability. Eight biomarkers were identified as fragments of N-acetyllactosaminide beta-1,3-N-acetylglucosaminyltransferase​,prostatic acid phosphatase, stabilin-2, GTPase IMAP family member 6, semenogelin-1 and -2. Restricted sample size was the major limitation of the study.</br> <br>Conclusions/Significance: Seminal plasma represents a robust source of potential peptide makers for primary PCa diagnosis. Our findings warrant further prospective validation to confirm the diagnostic potential of identified seminal biomarker candidates.</br&gt

Altered DNA methylation associated with a translocation linked to major mental illness

Recent work has highlighted a possible role for altered epigenetic modifications, including differential DNA methylation, in susceptibility to psychiatric illness. Here, we investigate blood-based DNA methylation in a large family where a balanced translocation between chromosomes 1 and 11 shows genome-wide significant linkage to psychiatric illness. Genome-wide DNA methylation was profiled in whole-blood-derived DNA from 41 individuals using the Infinium HumanMethylation450 BeadChip (Illumina Inc., San Diego, CA). We found significant differences in DNA methylation when translocation carriers (n = 17) were compared to related non-carriers (n = 24) at 13 loci. All but one of the 13 significant differentially methylated positions (DMPs) mapped to the regions surrounding the translocation breakpoints. Methylation levels of five DMPs were associated with genotype at SNPs in linkage disequilibrium with the translocation. Two of the five genes harbouring significant DMPs, DISC1 and DUSP10, have been previously shown to be differentially methylated in schizophrenia. Gene Ontology analysis revealed enrichment for terms relating to neuronal function and neurodevelopment among the genes harbouring the most significant DMPs. Differentially methylated region (DMR) analysis highlighted a number of genes from the MHC region, which has been implicated in psychiatric illness previously through genetic studies. We show that inheritance of a translocation linked to major mental illness is associated with differential DNA methylation at loci implicated in neuronal development/function and in psychiatric illness. As genomic rearrangements are over-represented in individuals with psychiatric illness, such analyses may be valuable more widely in the study of these conditions

Maternal depression is associated with DNA methylation changes in cord blood T lymphocytes and adult hippocampi

Depression affects 10-15% of pregnant women and has been associated with preterm delivery and later developmental, behavioural and learning disabilities. We tested the hypothesis that maternal depression is associated with DNA methylation alterations in maternal T lymphocytes, neonatal cord blood T lymphocytes and adult offspring hippocampi. Genome-wide DNA methylation of CD3+ T lymphocytes isolated from 38 antepartum maternal and 44 neonatal cord blood samples were analyzed using Illumina Methylation 450 K microarrays. Previously obtained methylation data sets using methylated DNA immunoprecipitation and array-hybridization of 62 postmortem hippocampal samples of adult males were re-analyzed to test associations with history of maternal depression. We found 145 (false discovery rate (FDR) q<0.05) and 2520 (FDR q<0.1) differentially methylated CG-sites in cord blood T lymphocytes of neonates from the maternal depression group as compared with the control group. However, no significant DNA methylation differences were detected in the antepartum maternal T lymphocytes of our preliminary data set. We also detected 294 differentially methylated probes (FDR q<0.1) in hippocampal samples associated with history of maternal depression. We observed a significant overlap (P=0.002) of 33 genes with changes in DNA methylation in T lymphocytes of neonates and brains of adult offspring. Many of these genes are involved in immune system functions. Our results show that DNA methylation changes in offspring associated with maternal depression are detectable at birth in the immune system and persist to adulthood in the brain. This is consistent with the hypothesis that system-wide epigenetic changes are involved in life-long responses to maternal depression in the offspring. © 2015 Translational Psychiatry

Characterizing Dynamic Changes in the Human Blood Transcriptional Network

Gene expression data generated systematically in a given system over multiple time points provides a source of perturbation that can be leveraged to infer causal relationships among genes explaining network changes. Previously, we showed that food intake has a large impact on blood gene expression patterns and that these responses, either in terms of gene expression level or gene-gene connectivity, are strongly associated with metabolic diseases. In this study, we explored which genes drive the changes of gene expression patterns in response to time and food intake. We applied the Granger causality test and the dynamic Bayesian network to gene expression data generated from blood samples collected at multiple time points during the course of a day. The simulation result shows that combining many short time series together is as powerful to infer Granger causality as using a single long time series. Using the Granger causality test, we identified genes that were supported as the most likely causal candidates for the coordinated temporal changes in the network. These results show that PER1 is a key regulator of the blood transcriptional network, in which multiple biological processes are under circadian rhythm regulation. The fasted and fed dynamic Bayesian networks showed that over 72% of dynamic connections are self links. Finally, we show that different processes such as inflammation and lipid metabolism, which are disconnected in the static network, become dynamically linked in response to food intake, which would suggest that increasing nutritional load leads to coordinate regulation of these biological processes. In conclusion, our results suggest that food intake has a profound impact on the dynamic co-regulation of multiple biological processes, such as metabolism, immune response, apoptosis and circadian rhythm. The results could have broader implications for the design of studies of disease association and drug response in clinical trials

Association between KCNJ6 (GIRK2) Gene Polymorphisms and Postoperative Analgesic Requirements after Major Abdominal Surgery

Opioids are commonly used as effective analgesics for the treatment of acute and chronic pain. However, considerable individual differences have been widely observed in sensitivity to opioid analgesics. We focused on a G-protein-activated inwardly rectifying potassium (GIRK) channel subunit, GIRK2, that is an important molecule in opioid transmission. In our initial polymorphism search, a total of nine single-nucleotide polymorphisms (SNPs) were identified in the whole exon, 5′-flanking, and exon-intron boundary regions of the KCNJ6 gene encoding GIRK2. Among them, G-1250A and A1032G were selected as representative SNPs for further association studies. In an association study of 129 subjects who underwent major open abdominal surgery, the A/A genotype in the A1032G SNP and -1250G/1032A haplotype were significantly associated with increased postoperative analgesic requirements compared with other genotypes and haplotypes. The total dose (mean±SEM) of rescue analgesics converted to equivalent oral morphine doses was 20.45±9.27 mg, 10.84±2.24 mg, and 13.07±2.39 mg for the A/A, A/G, and G/G genotypes in the A1032G SNP, respectively. Additionally, KCNJ6 gene expression levels in the 1032A/A subjects were significantly decreased compared with the 1032A/G and 1032G/G subjects in a real-time quantitative PCR analysis using human brain tissues, suggesting that the 1032A/A subjects required more analgesics because of lower KCNJ6 gene expression levels and consequently insufficient analgesic effects. The results indicate that the A1032G SNP and G-1250A/A1032G haplotype could serve as markers that predict increased analgesic requirements. Our findings will provide valuable information for achieving satisfactory pain control and open new avenues for personalized pain treatment

A Pilot Study of Abnormal Growth in Autism Spectrum Disorders and Other Childhood Psychiatric Disorders

The aims of the current study were to examine whether early growth abnormalities are (a) comparable in autism spectrum disorders (ASD) and other childhood psychiatric disorders, and (b) specific to the brain or generalized to the whole body. Head circumference, height, and weight were measured during the first 19 months of life in 129 children with ASD and 59 children with non-ASD psychiatric disorders. Both groups showed comparable abnormal patterns of growth compared to population norms, especially regarding height and head circumference in relation to height. Thus abnormal growth appears to be related to psychiatric disorders in general and is mainly expressed as an accelerated growth of height not matched by an increase in weight or head circumference

Transcriptional Analysis of Shewanella oneidensis MR-1 with an Electrode Compared to Fe(III)Citrate or Oxygen as Terminal Electron Acceptor

Shewanella oneidensis is a target of extensive research in the fields of bioelectrochemical systems and bioremediation because of its versatile metabolic capabilities, especially with regard to respiration with extracellular electron acceptors. The physiological activity of S. oneidensis to respire at electrodes is of great interest, but the growth conditions in thin-layer biofilms make physiological analyses experimentally challenging. Here, we took a global approach to evaluate physiological activity with an electrode as terminal electron acceptor for the generation of electric current. We performed expression analysis with DNA microarrays to compare the overall gene expression with an electrode to that with soluble iron(III) or oxygen as the electron acceptor and applied new hierarchical model-based statistics for the differential expression analysis. We confirmed the differential expression of many genes that have previously been reported to be involved in electrode respiration, such as the entire mtr operon. We also formulate hypotheses on other possible gene involvements in electrode respiration, for example, a role of ScyA in inter-protein electron transfer and a regulatory role of the cbb3-type cytochrome c oxidase under anaerobic conditions. Further, we hypothesize that electrode respiration imposes a significant stress on S. oneidensis, resulting in higher energetic costs for electrode respiration than for soluble iron(III) respiration, which fosters a higher metabolic turnover to cover energy needs. Our hypotheses now require experimental verification, but this expression analysis provides a fundamental platform for further studies into the molecular mechanisms of S. oneidensis electron transfer and the physiologically special situation of growth on a poised-potential surface

A cohort study of Plasmodium falciparum infection dynamics in Western Kenya Highlands

Abstract Background The Kenyan highlands were malaria-free before the 1910s, but a series of malaria epidemics have occurred in the highlands of western Kenya since the 1980s. Longitudinal studies of the genetic structure, complexity, infection dynamics, and duration of naturally acquired Plasmodium falciparum infections are needed to facilitate a comprehensive understanding of malaria epidemiology in the complex Kenyan highland eco-epidemiological systems where malaria recently expanded, as well as the evaluation of control measures. Methods We followed a cohort of 246 children residing in 3 villages at altitudes 1430 - 1580 m in western Kenya. Monthly parasitological surveys were undertaken for one year, yielding 866 P. falciparum isolates that were analyzed using 10 microsatellite markers. Results Infection complexity and genetic diversity were high (HE = 0.787-0.816), with ≥83% of infections harboring more than one parasite clone. Diversity remained high even during the low malaria transmission season. There was no significant difference between levels of genetic diversity and population structure between high and low transmission seasons. Infection turn-over rate was high, with the average infection duration of single parasite genotypes being 1.11 months, and the longest genotype persistence was 3 months. Conclusions These data demonstrate that despite the relatively recent spread of malaria to the highlands, parasite populations seem to have stabilized with no evidence of bottlenecks between seasons, while the ability of residents to clear or control infections indicates presence of effective anti-plasmodial immune mechanisms