A gene signature for post-infectious chronic fatigue syndrome

Background: At present, there are no clinically reliable disease markers for chronic fatigue syndrome. DNA chip microarray technology provides a method for examining the differential expression of mRNA from a large number of genes. Our hypothesis was that a gene expression signature, generated by microarray assays, could help identify genes which are dysregulated in patients with post-infectious CFS and so help identify biomarkers for the condition. Methods: Human genome-wide Affymetrix GeneChip arrays (39,000 transcripts derived from 33,000 gene sequences) were used to compare the levels of gene expression in the peripheral blood mononuclear cells of male patients with post-infectious chronic fatigue (n = 8) and male healthy control subjects (n = 7). Results: Patients and healthy subjects differed significantly in the level of expression of 366 genes. Analysis of the differentially expressed genes indicated functional implications in immune modulation, oxidative stress and apoptosis. Prototype biomarkers were identified on the basis of differential levels of gene expression and possible biological significance Conclusion: Differential expression of key genes identified in this study offer an insight into the possible mechanism of chronic fatigue following infection. The representative biomarkers identified in this research appear promising as potential biomarkers for diagnosis and treatment

Merkel cell carcinoma of skin-current controversies and recommendations

The review covers the current recommendations for Merkel cell carcinoma (MCC), with detailed discussion of many controversies. The 2010 AJCC staging system is more in-line with other skin malignancies although more complicated to use. The changes in staging system over time make comparison of studies difficult. A wide excision with margins of 2.5–3 cm is generally recommended. Even for primary </= 1 cm, there is a significant risk of nodal and distant metastases and hence sentinel node biopsy should be done if possible; otherwise adjuvant radiotherapy to the primary and nodal region should be given. Difficulties of setting up trials owing to the rarity of the disease and the mean age of the patient population result in infrequent reports of adjuvant or concurrent chemotherapy in the literature. The benefit, if any, is not great from published studies so far. However, there may be a subgroup of patients with high-risk features, e.g. node-positive and excellent performance status, for whom adjuvant or concurrent chemotherapy may be considered. Since local recurrence and metastases generally occur within 2 years of the initial diagnosis, patients should be followed more frequently in the first 2 years. However delayed recurrence can still occur in a small proportion of patients and long-term follow-up by a specialist is recommended provided that the general condition of the patient allows it. In summary, physician judgment in individual cases of MCC is advisable, to balance the risk of recurrence versus the complications of treatment

Accounting for dynamic fluctuations across time when examining fMRI test-retest reliability: Analysis of a reward paradigm in the EMBARC study

Longitudinal investigation of the neural correlates of reward processing in depression may represent an important step in defining effective biomarkers for antidepressant treatment outcome prediction, but the reliability of reward-related activation is not well understood. Thirty-seven healthy control participants were scanned using fMRI while performing a reward-related guessing task on two occasions, approximately one week apart. Two main contrasts were examined: right ventral striatum (VS) activation fMRI BOLD signal related to signed prediction errors (PE) and reward expectancy (RE). We also examined bilateral visual cortex activation coupled to outcome anticipation. Significant VS PE-related activity was observed at the first testing session, but at the second testing session, VS PE-related activation was significantly reduced. Conversely, significant VS RE-related activity was observed at time 2 but not time 1. Increases in VS RE-related activity from time 1 to time 2 were significantly associated with decreases in VS PE-related activity from time 1 to time 2 across participants. Intraclass correlations (ICCs) in VS were very low. By contrast, visual cortex activation had much larger ICCs, particularly in individuals with high quality data. Dynamic changes in brain activation are widely predicted, and failure to account for these changes could lead to inaccurate evaluations of the reliability of functional MRI signals. Conventional measures of reliability cannot distinguish between changes specified by algorithmic models of neural function and noisy signal. Here, we provide evidence for the former possibility: reward-related VS activations follow the pattern predicted by temporal difference models of reward learning but have low ICCs

Epigenetic Effects of Prenatal Stress on 11β-Hydroxysteroid Dehydrogenase-2 in the Placenta and Fetal Brain

Maternal exposure to stress during pregnancy is associated with significant alterations in offspring neurodevelopment and elevated maternal glucocorticoids likely play a central role in mediating these effects. Placental 11β-hydroxysteroid dehydrogenase type 2 (HSD11B2) buffers the impact of maternal glucocorticoid exposure by converting cortisol/corticosterone into inactive metabolites. However, previous studies indicate that maternal adversity during the prenatal period can lead to a down-regulation of this enzyme. In the current study, we examined the impact of prenatal stress (chronic restraint stress during gestational days 14–20) in Long Evans rats on HSD11B2 mRNA in the placenta and fetal brain (E20) and assessed the role of epigenetic mechanisms in these stress-induced effects. In the placenta, prenatal stress was associated with a significant decrease in HSD11B2 mRNA, increased mRNA levels of the DNA methyltransferase DNMT3a, and increased DNA methylation at specific CpG sites within the HSD11B2 gene promoter. Within the fetal hypothalamus, though we find no stress-induced effects on HSD11B2 mRNA levels, prenatal stress induced decreased CpG methylation within the HSD11B2 promoter and increased methylation at sites within exon 1. Within the fetal cortex, HSD11B2 mRNA and DNA methylation levels were not altered by prenatal stress, though we did find stress-induced elevations in DNMT1 mRNA in this brain region. Within individuals, we identified CpG sites within the HSD11B2 gene promoter and exon 1 at which DNA methylation levels were highly correlated between the placenta and fetal cortex. Overall, our findings implicate DNA methylation as a mechanism by which prenatal stress alters HSD11B2 gene expression. These findings highlight the tissue specificity of epigenetic effects, but also raise the intriguing possibility of using the epigenetic status of placenta to predict corresponding changes in the brain

TCF4 sequence variants and mRNA levels are associated with neurodevelopmental characteristics in psychotic disorders

TCF4 is involved in neurodevelopment, and intergenic and intronic variants in or close to the TCF4 gene have been associated with susceptibility to schizophrenia. However, the functional role of TCF4 at the level of gene expression and relationship to severity of core psychotic phenotypes are not known. TCF4 mRNA expression level in peripheral blood was determined in a large sample of patients with psychosis spectrum disorders (n=596) and healthy controls (n=385). The previously identified TCF4 risk variants (rs12966547 (G), rs9960767 (C), rs4309482 (A), rs2958182 (T) and rs17512836 (C)) were tested for association with characteristic psychosis phenotypes, including neurocognitive traits, psychotic symptoms and structural magnetic resonance imaging brain morphometric measures, using a linear regression model. Further, we explored the association of additional 59 single nucleotide polymorphisms (SNPs) covering the TCF4 gene to these phenotypes. The rs12966547 and rs4309482 risk variants were associated with poorer verbal fluency in the total sample. There were significant associations of other TCF4 SNPs with negative symptoms, verbal learning, executive functioning and age at onset in psychotic patients and brain abnormalities in total sample. The TCF4 mRNA expression level was significantly increased in psychosis patients compared with controls and positively correlated with positive- and negative-symptom levels. The increase in TCF4 mRNA expression level in psychosis patients and the association of TCF4 SNPs with core psychotic phenotypes across clinical, cognitive and brain morphological domains support that common TCF4 variants are involved in psychosis pathology, probably related to abnormal neurodevelopment

Genetic or Other Causation Should Not Change the Clinical Diagnosis of Cerebral Palsy

High throughput sequencing is discovering many likely causative genetic variants in individuals with cerebral palsy. Some investigators have suggested that this changes the clinical diagnosis of cerebral palsy and that these individuals should be removed from this diagnostic category. Cerebral palsy is a neurodevelopmental disorder diagnosed on clinical signs, not etiology. All nonprogressive permanent disorders of movement and posture attributed to disturbances that occurred in the developing fetal and infant brain can be described as "cerebral palsy." This definition of cerebral palsy should not be changed, whatever the cause. Reasons include stability, utility and accuracy of cerebral palsy registers, direct access to services, financial and social support specifically offered to families with cerebral palsy, and community understanding of the clinical diagnosis. Other neurodevelopmental disorders, for example, epilepsy, have not changed the diagnosis when genomic causes are found. The clinical diagnosis of cerebral palsy should remain, should prompt appropriate genetic studies and can subsequently be subclassified by etiology

Convergent functional genomics of anxiety disorders: translational identification of genes, biomarkers, pathways and mechanisms

Anxiety disorders are prevalent and disabling yet understudied from a genetic standpoint, compared with other major psychiatric disorders such as bipolar disorder and schizophrenia. The fact that they are more common, diverse and perceived as embedded in normal life may explain this relative oversight. In addition, as for other psychiatric disorders, there are technical challenges related to the identification and validation of candidate genes and peripheral biomarkers. Human studies, particularly genetic ones, are susceptible to the issue of being underpowered, because of genetic heterogeneity, the effect of variable environmental exposure on gene expression, and difficulty of accrual of large, well phenotyped cohorts. Animal model gene expression studies, in a genetically homogeneous and experimentally tractable setting, can avoid artifacts and provide sensitivity of detection. Subsequent translational integration of the animal model datasets with human genetic and gene expression datasets can ensure cross-validatory power and specificity for illness. We have used a pharmacogenomic mouse model (involving treatments with an anxiogenic drug—yohimbine, and an anti-anxiety drug—diazepam) as a discovery engine for identification of anxiety candidate genes as well as potential blood biomarkers. Gene expression changes in key brain regions for anxiety (prefrontal cortex, amygdala and hippocampus) and blood were analyzed using a convergent functional genomics (CFG) approach, which integrates our new data with published human and animal model data, as a translational strategy of cross-matching and prioritizing findings. Our work identifies top candidate genes (such as FOS, GABBR1, NR4A2, DRD1, ADORA2A, QKI, RGS2, PTGDS, HSPA1B, DYNLL2, CCKBR and DBP), brain–blood biomarkers (such as FOS, QKI and HSPA1B), pathways (such as cAMP signaling) and mechanisms for anxiety disorders—notably signal transduction and reactivity to environment, with a prominent role for the hippocampus. Overall, this work complements our previous similar work (on bipolar mood disorders and schizophrenia) conducted over the last decade. It concludes our programmatic first pass mapping of the genomic landscape of the triad of major psychiatric disorder domains using CFG, and permitted us to uncover the significant genetic overlap between anxiety and these other major psychiatric disorders, notably the under-appreciated overlap with schizophrenia. PDE10A, TAC1 and other genes uncovered by our work provide a molecular basis for the frequently observed clinical co-morbidity and interdependence between anxiety and other major psychiatric disorders, and suggest schizo-anxiety as a possible new nosological domain

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs