Neuroimaging-based classification of PTSD using data-driven computational approaches: a multisite big data study from the ENIGMA-PGC PTSD consortium

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for D-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.Stress-related psychiatric disorders across the life spa

Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium

A growing number of studies have examined alterations in white matter organization in people with posttraumatic stress disorder (PTSD) using diffusion MRI (dMRI), but the results have been mixed which may be partially due to relatively small sample sizes among studies. Altered structural connectivity may be both a neurobiological vulnerability for, and a result of, PTSD. In an effort to find reliable effects, we present a multi-cohort analysis of dMRI metrics across 3047 individuals from 28 cohorts currently participating in the PGC-ENIGMA PTSD working group (a joint partnership between the Psychiatric Genomics Consortium and the Enhancing NeuroImaging Genetics through Meta-Analysis consortium). Comparing regional white matter metrics across the full brain in 1426 individuals with PTSD and 1621 controls (2174 males/873 females) between ages 18-83, 92% of whom were trauma-exposed, we report associations between PTSD and disrupted white matter organization measured by lower fractional anisotropy (FA) in the tapetum region of the corpus callosum (Cohen's d = -0.11, p = 0.0055). The tapetum connects the left and right hippocampus, for which structure and function have been consistently implicated in PTSD. Results were consistent even after accounting for the effects of multiple potentially confounding variables: childhood trauma exposure, comorbid depression, history of traumatic brain injury, current alcohol abuse or dependence, and current use of psychotropic medications. Our results show that PTSD may be associated with alterations in the broader hippocampal network.New methods for child psychiatric diagnosis and treatment outcome evaluatio

Cox18p Is Required for Export of the Mitochondrially Encoded Saccharomyces cerevisiae Cox2p C-Tail and Interacts with Pnt1p and Mss2p in the Inner Membrane

The amino- and carboxy-terminal domains of mitochondrially encoded cytochrome c oxidase subunit II (Cox2p) are translocated out of the matrix to the intermembrane space. We have carried out a genetic screen to identify components required to export the biosynthetic enzyme Arg8p, tethered to the Cox2p C terminus by a translational gene fusion inserted into mtDNA. We obtained multiple alleles of COX18, PNT1, and MSS2, as well as mutations in CBP1 and PET309. Focusing on Cox18p, we found that its activity is required to export the C-tail of Cox2p bearing a short C-terminal epitope tag. This is not a consequence of reduced membrane potential due to loss of cytochrome oxidase activity because Cox2p C-tail export was not blocked in mitochondria lacking Cox4p. Cox18p is not required to export the Cox2p N-tail, indicating that these two domains of Cox2p are translocated by genetically distinct mechanisms. Cox18p is a mitochondrial integral inner membrane protein. The inner membrane proteins Mss2p and Pnt1p both coimmunoprecipitate with Cox18p, suggesting that they work together in translocation of Cox2p domains, an inference supported by functional interactions among the three genes

Lipopolysaccharides from atherosclerosis-associated bacteria antagonize TLR4, induce formation of TLR2/1/CD36 complexes in lipid rafts and trigger TLR2-induced inflammatory responses in human vascular endothelial cells

Infection with bacteria such as Chlamydia pneumonia, Helicobacter pylori, or Porphyromonas gingivalis may be triggering the secretion of inflammatory cytokines that leads to atherogenesis. The mechanisms by which the innate immune recognition of these pathogens could lead to atherosclerosis remain unclear. In this study, using human vascular endothelial cells or HEK293 cells engineered to express pattern-recognition receptors (PRRs), we set out to determine Toll-like receptors (TLRs) and functionally associated PRRs involved in the innate recognition of and response to LPS from H. pylori or P. gingivalis. Using siRNA interference or recombinant expression of cooperating PRRs, we show that H. pylori and P. gingivalis LPS-induced cell activation is mediated through TLR2. Human vascular endothelial cell activation was found to be lipid-raft dependent and to require the formation of heterotypic receptor complexes comprising of TLR2, TLR1, CD36 and CD11b/CD18. In addition, we report that LPS from these bacterial strains are able to antagonise TLR4. This antagonistic activity of H. pylori or P. gingivalis LPS, as well as their TLR2 activation capability may be associated with their ability to contribute to atherosclerosis

An enhanced target-enrichment bait set for Hexacorallia provides phylogenomic resolution of the staghorn corals (Acroporidae) and close relatives

Targeted enrichment of genomic DNA can profoundly increase the phylogenetic resolution of clades and inform taxonomy. Here, we redesign a custom bait set previously developed for the cnidarian class Anthozoa to more efficiently target and capture ultraconserved elements (UCEs) and exonic loci within the subclass Hexacorallia. We test this enhanced bait set (targeting 2476 loci) on 99 specimens of scleractinian corals spanning both the "complex" (Acroporidae, Agariciidae) and "robust" (Fungiidae) clades. Focused sampling in the staghorn corals (genus Acropora) highlights the ability of sequence capture to inform the taxonomy of a Glade previously deficient in molecular resolution. A mean of 1850 ( +/- 298) loci were captured per taxon (955 UCEs, 894 exons), and a 75% complete concatenated alignment of 96 samples included 1792 loci (991 UCE, 801 exons) and similar to 1.87 million base pairs. Maximum likelihood and Bayesian analyses recovered robust molecular relationships and revealed that species-level relationships within the Acropora are incongruent with traditional morphological groupings. Both UCE and exon datasets delineated six well-supported clades within Acropora. The enhanced bait set will facilitate investigations of the evolutionary history of many important groups of reef corals, particularly where previous molecular marker development has been unsuccessful