Adapting the randomised controlled trial (RCT) for precision medicine: introducing the nested-precision RCT (npRCT)

Adaptations to the gold standard randomised controlled trial (RCT) have been introduced to decrease trial costs and avoid high sample sizes. To facilitate development of precision medicine algorithms that aim to optimise treatment allocation for individual patients, we propose a new RCT adaptation termed the nested-precision RCT (npRCT). The npRCT combines a traditional RCT (intervention A versus B) with a precision RCT (stratified versus randomised allocation to A or B). This combination allows online development of a precision algorithm, thus providing an integrated platform for algorithm development and its testing. Moreover, as both the traditional and the precision RCT include participants randomised to interventions of interest, data from these participants can be jointly analysed to determine the comparative effectiveness of intervention A versus B, thus increasing statistical power. We quantify savings of the npRCT compared to two independent RCTs by highlighting sample size requirements for different target effect sizes and by introducing an open-source power calculation app. We describe important practical considerations such as blinding issues and potential biases that need to be considered when designing an npRCT. We also highlight limitations and research contexts that are less suited for an npRCT. In conclusion, we introduce the npRCT as a novel precision medicine trial design strategy which may provide one opportunity to efficiently combine traditional and precision RCTs

Evaluation of the Performance of AmpliSeq and SureSelect Exome Sequencing Libraries for Ion Proton

Library preparation for whole-exome sequencing is a critical step serving the enrichment of the regions of interest. For Ion Proton, there are only two exome library preparation methods available, AmpliSeq and SureSelect. Although of major interest, a comparison of the two methods is hitherto missing in the literature. Here, we systematically evaluate the performance of AmpliSeq and SureSelect and present an improved variant calling pipeline. We used 12 in-house DNA samples with genome-wide and exome microarray data and a commercially available reference DNA (NA12878) for evaluation. Both methods had a high concordance (>97%) with microarray genotypes and, when validating against NA12878, a sensitivity and positive predictive values of >93% and >80%, respectively. Application of our variant calling pipeline decreased the number of false positive variants dramatically by 90% and resulted in positive predictive value of 97%. This improvement is highly relevant in research as well as clinical setting

DNA-methylation dynamics across short-term, exposure-containing CBT in patients with panic disorder

Interaction of genetic predispositions and environmental factors via epigenetic mechanisms have been hypothesized to play a central role in Panic Disorder (PD) aetiology and therapy. Cognitive Behavioral Therapy (CBT), including exposure interventions, belong to the most efficient treatments of PD although its biological mechanism of action remains unknown. For the first time, we explored the dynamics and magnitude of DNA-methylation and immune cell-type composition during CBT (n = 38) and the therapeutic exposure intervention (n = 21) to unravel their biological correlates and identify possible biomarkers of therapy success. We report transient regulation of the CD4 + T-Cells, Natural Killers cells, Granulocytes during exposure and a significant change in the proportions of CD4 + T cells, CD8 + T cells and B-Cells and Granulocytes during therapy. In an epigenome-wide association study we identified cg01586609 located in a CpG island and annotated to the serotonin receptor 3 A (HTR3A) to be differentially methylated during fear exposure and regulated at gene expression level with significant differences between remitters and non-remitters (p = 0.028). We moreover report cg01699630 annotated to ARG1 to undergo long lasting methylation changes during therapy (paired t test, genome-wide adj.p value = 0.02). This study reports the first data-driven biological candidates for epigenetically mediated effects of acute fear exposure and CBT in PD patients. Our results provide evidence of changes in the serotonin receptor 3 A methylation and expression during fear exposure associated with different long-term CBT trajectories and outcome, making it a possible candidate in the search of markers for therapy success. Finally, our results add to a growing body of evidence showing immune system changes associated with PD

Metabolic profiling of maternal serum of women a high-risk of spontaneous preterm birth using NMR and MGWAS approach

Preterm birth (PTB) is a leading global cause of infant mortality. Risk factors include genetics, lifestyle choices and infection. Understanding the mechanism of PTB could aid the development of novel approaches to prevent PTB. This study aimed to investigate the metabolic biomarkers of PTB in early pregnancy and the association of significant metabolites with participant genotypes. Maternal sera collected at 16 and 20 weeks of gestation, from women who previously experienced PTB (high-risk) and women who did not (low-risk controls), were analysed using (1)H nuclear magnetic resonance (NMR) metabolomics and genome-wide screening microarray. ANOVA and probabilistic neural network (PNN) modelling were performed on the spectral bins. Metabolomics genome-wide association (MGWAS) of the spectral bins and genotype data from the same participants was applied to determine potential metabolite-gene pathways. Phenylalanine, acetate and lactate metabolite differences between PTB cases and controls were obtained by ANOVA and PNN showed strong prediction at week 20 (AUC = 0.89). MGWAS identified several metabolite bins with strong genetic associations. Cis-eQTL analysis highlighted TRAF1 (involved in the inflammatory pathway) local to a non-coding SNP associated with lactate at week 20 of gestation. MGWAS of a well-defined cohort of participants highlighted a lactate-TRAF1 relationship that could potentially contribute to PTB

Using polymorphisms in FKBP5 to define biologically distinct subtypes of posttraumatic stress disorder: Evidence from endocrine and gene expression studies

Context: Polymorphisms in the gene encoding the glucocorticoid receptor (GR) regulating co-chaperone FKBP5 have been shown to alter GR sensitivity and are associated with an increased risk to develop posttraumatic stress disorder (PTSD). Objective: To investigate interactions of the FKBP5 single-nucleotide polymorphism rs9296158 and PTSD symptoms on baseline cortisol level, low-dose dexamethasone suppression, and whole-blood gene expression. Design: Association of FKBP5 genotypes and PTSD symptoms with endocrine measures and genome-wide expression profiles. Setting: Waiting rooms of general medical and gynecological clinics of an urban hospital at Emory University. Participants: The 211 participants were primarily African American (90.05%) and of low socioeconomic status and had high rates of trauma and PTSD. Main Outcome Measures: Baseline and post-dexamethasone suppression cortisol measures and gene expression levels. Results: In our endocrine study, we found that only risk allele A carriers of rs9296158 showed GR supersensitivity with PTSD; in contrast, baseline cortisol levels were decreased in PTSD only in patients with the GG genotype. Expression of 183 transcripts was significantly correlated with PTSD symptoms after multiple testing corrections. When adding FKBP5 genotype and its interaction with PTSD symptoms, expression levels of an additional 32 genes were significantly regulated by the interaction term. Within these 32 genes, previously reported PTSD candidates were identified, including FKBP5 and the IL18 and STAT pathways. Significant overrepresentation of steroid hormone transcription factor binding sites within these 32 transcripts was observed, highlighting the fact that the earlier-described genotype and PTSDdependent differences in GR sensitivity could drive the observed gene expression pattern. Results were validated by reverse transcriptase-polymerase chain reaction and replicated in an independent sample (N=98). Conclusions: These data suggest that the inheritance of GR sensitivity-moderating FKBP5 polymorphisms can determine specific types of hypothalamic-pituitaryadrenal axis dysfunction within PTSD, which are also reflected in gene-expression changes of a subset of GRresponsive genes. Thus, these findings indicate that functional variants in FKBP5 are associated with biologically distinct subtypes of PTSD

SKP2 attenuates autophagy through Beclin1-ubiquitination and its inhibition reduces MERS-Coronavirus infection

Autophagy is an essential cellular process affecting virus infections and other diseases and Beclin1 (BECN1) is one of its key regulators. Here, we identified S-phase kinase-associated protein 2 (SKP2) as E3 ligase that executes lysine-48-linked poly-ubiquitination of BECN1, thus promoting its proteasomal degradation. SKP2 activity is regulated by phosphorylation in a hetero-complex involving FKBP51, PHLPP, AKT1, and BECN1. Genetic or pharmacological inhibition of SKP2 decreases BECN1 ubiquitination, decreases BECN1 degradation and enhances autophagic flux. Middle East respiratory syndrome coronavirus (MERS-CoV) multiplication results in reduced BECN1 levels and blocks the fusion of autophagosomes and lysosomes. Inhibitors of SKP2 not only enhance autophagy but also reduce the replication of MERS-CoV up to 28,000-fold. The SKP2-BECN1 link constitutes a promising target for host-directed antiviral drugs and possibly other autophagy-sensitive conditions

Treatment response classes in major depressive disorder identified by model-based clustering and validated by clinical prediction models

The identification of generalizable treatment response classes (TRC[s]) in major depressive disorder (MDD) would facilitate comparisons across studies and the development of treatment prediction algorithms. Here, we investigated whether such stable TRCs can be identified and predicted by clinical baseline items. We analyzed data from an observational MDD cohort (Munich Antidepressant Response Signature [MARS] study, N = 1017), treated individually by psychopharmacological and psychotherapeutic means, and a multicenter, partially randomized clinical/pharmacogenomic study (Genome-based Therapeutic Drugs for Depression [GENDEP], N = 809). Symptoms were evaluated up to week 16 (or discharge) in MARS and week 12 in GENDEP. Clustering was performed on 809 MARS patients (discovery sample) using a mixed model with the integrated completed likelihood criterion for the assessment of cluster stability, and validated through a distinct MARS validation sample and GENDEP. A random forest algorithm was used to identify prediction patterns based on 50 clinical baseline items. From the clustering of the MARS discovery sample, seven TRCs emerged ranging from fast and complete response (average 4.9 weeks until discharge, 94% remitted patients) to slow and incomplete response (10% remitted patients at week 16). These proved stable representations of treatment response dynamics in both the MARS and the GENDEP validation sample. TRCs were strongly associated with established response markers, particularly the rate of remitted patients at discharge. TRCs were predictable from clinical items, particularly personality items, life events, episode duration, and specific psychopathological features. Prediction accuracy improved significantly when cluster-derived slopes were modelled instead of individual slopes. In conclusion, model-based clustering identified distinct and clinically meaningful treatment response classes in MDD that proved robust with regard to capturing response profiles of differently designed studies. Response classes were predictable from clinical baseline characteristics. Conceptually, model-based clustering is translatable to any outcome measure and could advance the large-scale integration of studies on treatment efficacy or the neurobiology of treatment response

Longitudinal transcriptome-wide gene expression analysis of sleep deprivation treatment shows involvement of circadian genes and immune pathways

Therapeutic sleep deprivation (SD) rapidly induces robust, transient antidepressant effects in a large proportion of major mood disorder patients suffering from a depressive episode, but underlying biological factors remain poorly understood. Research suggests that these patients may have altered circadian molecular genetic 'clocks' and that SD functions through 'resetting' dysregulated genes; additional factors may be involved, warranting further investigation. Leveraging advances in microarray technology enabling the transcriptome-wide assessment of gene expression, this study aimed to examine gene expression changes accompanying SD and recovery sleep in patients suffering from an episode of depression. Patients (N = 78) and controls (N = 15) underwent SD, with blood taken at the same time of day before SD, after one night of SD and after recovery sleep. A transcriptome-wide gene-by-gene approach was used, with a targeted look also taken at circadian genes. Furthermore, gene set enrichment, and longitudinal gene set analyses including the time point after recovery sleep, were conducted. Circadian genes were significantly affected by SD, with patterns suggesting that molecular clocks of responders and non-responders, as well as patients and controls respond differently to chronobiologic stimuli. Notably, gene set analyses revealed a strong widespread effect of SD on pathways involved in immune function and inflammatory response, such as those involved in cytokine and especially in interleukin signalling. Longitudinal gene set analyses showed that in responders these pathways were upregulated after SD; in non-responders, little response was observed. Our findings emphasize the close relationship between circadian, immune and sleep systems and their link to etiology of depression at the transcriptomic level

Genome-wide mapping of genetic determinants influencing DNA methylation and gene expression in human hippocampus

Emerging evidence emphasizes the strong impact of regulatory genomic elements in neurodevelopmental processes and the complex pathways of brain disorders. The present genome-wide quantitative trait loci analyses explore the cis-regulatory effects of single-nucleotide polymorphisms (SNPs) on DNA methylation (meQTL) and gene expression (eQTL) in 110 human hippocampal biopsies. We identify cis-meQTLs at 14,118 CpG methylation sites and cis-eQTLs for 302 3'-mRNA transcripts of 288 genes. Hippocampal cis-meQTL-CpGs are enriched in flanking regions of active promoters, CpG island shores, binding sites of the transcription factor CTCF and brain eQTLs. Cis-acting SNPs of hippocampal meQTLs and eQTLs significantly overlap schizophrenia-associated SNPs. Correlations of CpG methylation and RNA expression are found for 34 genes. Our comprehensive maps of cis-acting hippocampal meQTLs and eQTLs provide a link between disease-associated SNPs and the regulatory genome that will improve the functional interpretation of non-coding genetic variants in the molecular genetic dissection of brain disorders

Epigenetic upregulation of FKBP5 by aging and stress contributes to NF-kappa B-driven inflammation and cardiovascular risk

Aging and psychosocial stress are associated with increased inflammation and disease risk, but the underlying molecular mechanisms are unclear. Because both aging and stress are also associated with lasting epigenetic changes, a plausible hypothesis is that stress along the lifespan could confer disease risk through epigenetic effects on molecules involved in inflammatory processes. Here, by combining large-scale analyses in human cohorts with experiments in cells, we report that FKBP5, a protein implicated in stress physiology, contributes to these relations. Across independent human cohorts (total n > 3,000), aging synergized with stress-related phenotypes, measured with childhood trauma and major depression questionnaires, to epigenetically up-regulate FKBP5 expression. These age/stress-related epigenetic effects were recapitulated in a cellular model of replicative senescence, whereby we exposed replicating human fibroblasts to stress (glucocorticoid) hormones. Unbiased genome-wide analyses in human blood linked higher FKBP5 mRNA with a proinflammatory profile and altered NF-kappa B-related gene networks. Accordingly, experiments in immune cells showed that higher FKBP5 promotes inflammation by strengthening the interactions of NF-kappa B regulatory kinases, whereas opposing FKBP5 either by genetic deletion (CRISPR/Cas9-mediated) or selective pharmacological inhibition prevented the effects on NF-kappa B. Further, the age/stress-related epigenetic signature enhanced FKBP5 response to NF-kappa B through a positive feedback loop and was present in individuals with a history of acute myocardial infarction, a disease state linked to peripheral inflammation. These findings suggest that aging/stress-driven FKBP5-NF-kappa B signaling mediates inflammation, potentially contributing to cardiovascular risk, and may thus point to novel biomarker and treatment possibilities.Peer reviewe