Serotonin-induced hyperactivity in SSRI-resistant major depressive disorder patient-derived neurons

Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.

Recent decades have witnessed tremendous advances in the neuroscience of emotion, learning and memory, and in animal models for understanding depression and anxiety. This review focuses on new rationally designed psychiatric treatments derived from preclinical human and animal studies. Nonpharmacological treatments that affect disrupted emotion circuits include vagal nerve stimulation, rapid transcranial magnetic stimulation and deep brain stimulation, all borrowed from neurological interventions that attempt to target known pathological foci. Other approaches include drugs that are given in relation to specific learning events to enhance or disrupt endogenous emotional learning processes. Imaging data suggest that common regions of brain activation are targeted with pharmacological and somatic treatments as well as with the emotional learning in psychotherapy. Although many of these approaches are experimental, the rapidly developing understanding of emotional circuit regulation is likely to provide exciting and powerful future treatments for debilitating mood and anxiety disorders.

This systematic review summarizes pharmacogenetic studies on antidepressant response and side effects. Out of the 17 genes we reviewed, 8 genes were entered into the meta-analysis (SLC6A4, HTR1A, HTR2A, TPH1, gene encoding the beta-3 subunit, brain-derived neurotrophic factor (BDNF), HTR3A and HTR3B). TPH1 218C/C genotype (7 studies, 754 subjects) was significantly associated with a better response (odds ratio, OR=1.62; P=0.005) with no heterogeneity between ethnicities. A better response was also observed in subjects with the Met variant within the BDNF 66Val/Met polymorphism (4 studies, 490 subjects; OR=1.63, P=0.02). Variable number of tandem repeats polymorphism within intron 2 (STin2) 12/12 genotype showed a trend toward a better response in Asians (STin2: 5 studies, 686 subjects; OR=3.89, P=0.03). As for side effects, pooled ORs of serotonin transporter gene promoter polymorphism (5-HTTLPR) l (9 studies, 2642 subjects) and HTR2A -1438G/G (7 studies, 801 subjects) were associated with a significant risk modulation (OR=0.64, P=0.0005) and (OR=1.91, P=0.0006), respectively. Interestingly, this significance became more robust when analyzed with side effect induced by selective serotonin reuptake inhibitors only (5-HTTLPR: P=0.0001, HTR2A: P<0.0001). No significant result could be observed for the other variants. These results were not corrected for multiple testing in each variant, phenotype and subcategory. This would have required a Bonferroni significance level of P<0.0023. Although some heterogeneity was present across studies, our finding suggests that 5-HTTLPR, STin2, HTR1A, HTR2A, TPH1 and BDNF may modulate antidepressant response.