Major depressive disorder (MDD) is a leading cause of disability worldwide, and is commonly treated with antidepressant drugs (AD). Although effective, many patients fail to respond to AD treatment, ...and accordingly identifying factors that can predict AD response would greatly improve treatment outcomes. In this study, we developed a machine learning tool to integrate multi-omic datasets (gene expression, DNA methylation, and genotyping) to identify biomarker profiles associated with AD response in a cohort of individuals with MDD.
Individuals with MDD (N = 111) were treated for 8 weeks with antidepressants and were separated into responders and non-responders based on the Montgomery-Åsberg Depression Rating Scale (MADRS). Using peripheral blood samples, we performed RNA-sequencing, assessed DNA methylation using the Illumina EPIC array, and performed genotyping using the Illumina PsychArray. To address this rich multi-omic dataset with high dimensional features, we developed integrative Geneset-Embedded non-negative Matrix factorization (iGEM), a non-negative matrix factorization (NMF) based model, supplemented with auxiliary information regarding gene sets and gene-methylation relationships. In particular, we factorize the subjects by features (i.e., gene expression or DNA methylation) into subjects-by-factors and factors-by-features. We define the factors as the meta-phenotypes as they represent integrated composite scores of the molecular measurements for each subject.
Using our model, we identified a number of meta-phenotypes which were related to AD response. By integrating geneset information into the model, we were able to relate these meta-phenotypes to biological processes, including a meta-phenotype related to immune and inflammatory functions as well as other genes related to depression or AD response. The meta-phenotype identified several genes including immune interleukin 1 receptor like 1 (IL1RL1) and interleukin 5 receptor (IL5) subunit alpha (IL5RA), AKT/PIK3 pathway related phosphoinositide-3-kinase regulatory subunit 6 (PIK3R6), and sphingomyelin phosphodiesterase 3 (SMPD3), which has been identified as a target of AD treatment.
The derived meta-phenotypes and associated biological functions represent both biomarkers to predict response, as well as potential new treatment targets. Our method is applicable to other diseases with multi-omic data, and the software is open source and available on Github (https://github.com/li-lab-mcgill/iGEM).
ABSTRACT
Pulsar wind nebulae (PWNe) represent the largest class of sources that upcoming γ-ray surveys will detect. Therefore, accurate modelling of their global emission properties is one of the ...most urgent problems in high-energy astrophysics. Correctly characterizing these dominant objects is a needed step to allow γ-ray surveys to detect fainter sources, investigate the signatures of cosmic ray propagation, and estimate the diffuse emission in the Galaxy. In this paper, we present an observationally motivated construction of the Galactic PWNe population. We made use of a modified one-zone model to evolve for a long period of time the entire population. The model provides, for every source, at any age, a simplified description of the dynamical and spectral evolution. The long-term effects of the reverberation phase on the spectral evolution are described, for the first time, based on physically motivated prescriptions for the evolution of the nebular radius supported by numerical studies. This effort tries to solve one of the most critical aspects of one-zone modelling, namely the typical overcompression of the nebula during the reverberation phase, resulting in a strong modification of its spectral properties at all frequencies. We compare the emission properties of our synthetic PWNe population with the most updated catalogues of TeV Galactic sources. We find that the firmly identified and candidate PWNe sum up to about 50 per cent of the expected objects in this class above threshold for detection. Finally, we estimate that Cherenkov Telescope Array will increase the number of TeV-detected PWNe by a factor of ≳3.
Major depressive disorder (MDD) is a common, heterogenous, and potentially serious psychiatric illness. Diverse brain cell types have been implicated in MDD etiology. Significant sexual differences ...exist in MDD clinical presentation and outcome, and recent evidence suggests different molecular bases for male and female MDD. We evaluated over 160,000 nuclei from 71 female and male donors, leveraging new and pre-existing single-nucleus RNA-sequencing data from the dorsolateral prefrontal cortex. Cell type specific transcriptome-wide threshold-free MDD-associated gene expression patterns were similar between the sexes, but significant differentially expressed genes (DEGs) diverged. Among 7 broad cell types and 41 clusters evaluated, microglia and parvalbumin interneurons contributed the most DEGs in females, while deep layer excitatory neurons, astrocytes, and oligodendrocyte precursors were the major contributors in males. Further, the Mic1 cluster with 38% of female DEGs and the ExN10_L46 cluster with 53% of male DEGs, stood out in the meta-analysis of both sexes.
The etiology of major depression remains unclear, but reduced activity of the serotonin (5-HT) system remains implicated and treatments that increase 5-HT neurotransmission can ameliorate depressive ...symptoms. 5-HT1A receptors are critical regulators of the 5- HT system. They are expressed as both presynaptic autoreceptors that negatively regulate 5-HT neurons, and as post-synaptic heteroreceptors on non-serotonergic neurons in the hippocampus, cortex, and limbic system that are critical to mediate the antidepressant actions of 5-HT. Thus, 5-HT1A auto- and heteroreceptors have opposite actions on serotonergic neurotransmission. Because most 5-HT1A ligands target both auto- and heteroreceptors their efficacy has been limited, resulting in weak or unclear responses. We propose that by understanding the transcriptional regulation of the 5-HT1A receptor it may be possible to regulate its expression differentially in raphe and projection regions. Here we review the transcriptional architecture of the 5-HT1A gene (HTR1A) with a focus on specific DNA elements and transcription factors that have been shown to regulate 5-HT1A receptor expression in the brain. Association studies with the functional HTR1A promoter polymorphism rs6295 suggest a new model for the role of the 5-HT1A receptor in susceptibility to depression involving early deficits in cognitive, fear and stress reactivity as stressors that may ultimately lead to depression. We present evidence that by targeting specific transcription factors it may be possible to oppositely regulate 5-HT1A auto- and heteroreceptor expression, synergistically increasing serotonergic neurotransmission for the treatment of depression.
Lung cancer is the leading cause of tumor-related death. The lack of effective treatments urges the development of new therapeutic approaches able to selectively kill cancer cells. The connection ...between aberrant microRNA (miRNA - miR) expression and tumor progression suggests a new strategy to fight cancer by interfering with miRNA function. In this regard, LNAs (locked nucleic acids) have proven to be very promising candidates for miRNA neutralization. Here, we employed an LNA-based anti-miR library in a functional screening to identify putative oncogenic miRNAs in non-small-cell lung cancer (NSCLC). By screening NIH-H460 and A549 cells, miR-197 was identified as a new functional oncomiR, whose downregulation induces p53-dependent lung cancer cell apoptosis and impairs the capacity to establish tumor xenografts in immunodeficient mice. We further identified the two BH3-only proteins NOXA and BMF as new miR-197 targets responsible for induction of apoptosis in p53 wild-type cells, delineating miR-197 as a key survival factor in NSCLC. Thus, we propose the inhibition of miR-197 as a novel therapeutic approach against lung cancer.
Major depressive disorder (MDD) is a complex and potentially debilitating illness whose etiology and pathology remains unclear. Non-coding RNAs have been implicated in MDD, where they display ...differential expression in the brain and the periphery. In this study, we quantified small nucleolar RNA (snoRNA) expression by small RNA sequencing in the lateral habenula (LHb) of individuals with MDD (n = 15) and psychiatrically-healthy controls (n = 15). We uncovered five snoRNAs that exhibited differential expression between MDD and controls (FDR < 0.01). Specifically, SNORA69 showed increased expression in MDD and was technically validated via RT-qPCR. We further investigated the expression of Snora69 in the LHb and peripheral blood of an unpredicted chronic mild stress (UCMS) mouse model of depression. Snora69 was specifically up-regulated in mice that underwent the UCMS paradigm. SNORA69 is known to guide pseudouridylation onto 5.8S and 18S rRNAs. We quantified the relative abundance of pseudouridines on 5.8S and 18S rRNA in human post-mortem LHb samples and found increased abundance of pseudouridines in the MDD group. Overall, our findings indicate the importance of brain snoRNAs in the pathology of MDD. Future studies characterizing SNORA69's role in MDD pathology is warranted.
ABSTRACT
SNR G0.9+0.1 is a well-known source in the direction of the Galactic Centre composed by a Supernova Remnant (SNR) and a Pulsar Wind Nebula (PWN) in the core. We investigate the potential of ...the future Cherenkov Telescope Array (CTA), simulating observations of SNR G0.9 + 0.1. We studied the spatial and spectral properties of this source and estimated the systematic errors of these measurements. The source will be resolved if the very high-energy emission region is bigger than ∼0.65′. It will also be possible to distinguish between different spectral models and calculate the cutoff energy. The systematic errors are dominated by the Instrument Response Function instrumental uncertainties, especially at low energies. We computed the evolution of a young PWN inside an SNR using a one-zone time-dependent leptonic model. We applied the model to the simulated CTA data and found that it will be possible to accurately measure the cutoff energy of the γ-ray spectrum. Fitting of the multiwavelength spectrum will allow us to constrain also the magnetization of the PWN. Conversely, a pure power-law spectrum would rule out this model. Finally, we checked the impact of the spectral shape and the energy density of the Inter-Stellar Radiation Fields on the estimate of the parameters of the PWN, finding that they are not significantly affected.
We report on the lowest-frequency detection to date of three bursts from the fast radio burst FRB 180916.J0158+65, observed at 328 MHz with the Sardinia Radio Telescope (SRT). The SRT observed the ...periodic repeater FRB 180916.J0158+65 for five days from 2020 February 20 to 24 during a time interval of active radio bursting, and detected the three bursts during the first hour of observations; no more bursts were detected during the remaining ∼30 hr. Simultaneous SRT observations at 1548 MHz did not detect any bursts. Burst fluences are in the range 37 to 13 Jy ms. No relevant scattering is observed for these bursts. We also present the results of the multi-wavelength campaign we performed on FRB 180916.J0158+65, during the five days of the active window. Simultaneously with the SRT observations, others with different time spans were performed with the Northern Cross at 408 MHz, with XMM-Newton, NICER, INTEGRAL, AGILE, and with the TNG and two optical telescopes in Asiago, which are equipped with fast photometers. XMM-Newton obtained data simultaneously with the three bursts detected by the SRT, and determined a luminosity upper limit in the 0.3-10 keV energy range of ∼1045 erg s−1 for the burst emission. AGILE obtained data simultaneously with the first burst and determined a fluence upper limit in the MeV range for millisecond timescales of . Our results show that absorption from the circumburst medium does not significantly affect the emission from FRB 180916.J0158+65, thus limiting the possible presence of a superluminous supernova around the source, and indicate that a cutoff for the bursting mechanism, if present, must be at lower frequencies. Our multi-wavelength campaign sensitively constrains the broadband emission from FRB 180916.J0158+65, and provides the best limits so far for the electromagnetic response to the radio bursting of this remarkable source of fast radio bursts.
Antidepressant treatment is associated with a high rate of poor response, and thus, biomarker development is warranted.
We aimed to synthesize studies investigating gene expression, small RNAs, and ...epigenomic biomarkers of antidepressant response. We conducted a narrative review of the literature.
Firstly, we detailed the challenges involved, in terms of biological tissues, relevant study time frames, and mandatory statistical tools. Secondly we synthesized results obtained in gene expression studies, focusing mainly on genome-wide studies, particularly small non-coding RNA, including micro-RNA and other small RNA species. In addition, we reviewed the potential biomarkers of antidepressant response arising from studies investigating DNA methylation variation and histone modifications.
We did not conduct a meta-analysis due to the heterogeneity of the study.
Although promising, the field of gene expression and epigenomic biomarkers of antidepressant response is still in its infancy, and needs further development to define useful biomarkers in clinical practice.
•Antidepressant treatment is associated with a high rate of poor response.•Our review highlights the challenges to develop biomarkers of antidepressant response.•Several mRNAs and micro-RNAs have been described as potential biomarkers but replications are needed.•DNA methylation and histone modifications are also a promising avenue to develop biomarkers.
Childhood maltreatment (CM) is all too frequent among western societies, with an estimated prevalence of 10 to 15%. CM associates with increased risk of several psychiatric disorders, and therefore ...represents a worrying public and socioeconomic burden. While associated clinical outcomes are well characterized, determining by which mechanisms early-life adverse experiences affect mental health over the lifespan is a major challenge. Epigenetic mechanisms, in particular DNA methylation, represent a form of molecular memory that may modify brain function over extended periods of time, as well as serve as a bio-marker of behavioral phenotypes associated with CM. Here, we review human studies suggesting that DNA methylation is a crucial substrate mediating neurobiological consequences of CM throughout life, thereby potentiating maladaptive behavioral patterns and psychopathological risk.
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