Variants in autophagy-related genes and clinical characteristics in melanoma: a population-based study

Autophagy has been linked with melanoma risk and survival, but no polymorphisms in autophagy-related (ATG) genes have been investigated in relation to melanoma progression. We examined five single-nucleotide polymorphisms (SNPs) in three ATG genes (ATG5; ATG10; and ATG16L) with known or suspected impact on autophagic flux in an international population-based case-control study of melanoma. DNA from 911 melanoma patients was genotyped. An association was identified between (GG) (rs2241880) and earlier stage at diagnosis (OR 0.47; 95% Confidence Intervals (CI) = 0.27-0.81, P = 0.02) and a decrease in Breslow thickness (P = 0.03). The ATG16L heterozygous genotype (AG) (rs2241880) was associated with younger age at diagnosis (P = 0.02). Two SNPs in ATG5 were found to be associated with increased stage (rs2245214 CG, OR 1.47; 95% CI = 1.11-1.94, P = 0.03; rs510432 CC, OR 1.84; 95% CI = 1.12-3.02, P = 0.05). Finally, we identified inverse associations between ATG5 (GG rs2245214) and melanomas on the scalp or neck (OR 0.20, 95% CI = 0.05-0.86, P = 0.03); ATG10 (CC) (rs1864182) and brisk tumor infiltrating lymphocytes (TILs) (OR 0.42; 95% CI = 0.21-0.88, P = 0.02), and ATG5 (CC) (rs510432) with nonbrisk TILs (OR 0.55; 95% CI = 0.34-0.87, P = 0.01). Our data suggest that ATG SNPs might be differentially associated with specific host and tumor characteristics including age at diagnosis, TILs, and stage. These associations may be critical to understanding the role of autophagy in cancer, and further investigation will help characterize the contribution of these variants to melanoma progression

Associations of Cumulative Sun Exposure and Phenotypic Characteristics with Histologic Solar Elastosis

Solar elastosis adjacent to melanomas in histologic sections is regarded as an indicator of sun exposure although the associations of ultraviolet (UV) exposure and phenotype with solar elastosis are yet to be fully explored

The hippocampal network model: A transdiagnostic metaconnectomic approach

Purpose: The hippocampus plays a central role in cognitive and affective processes and is commonly implicated in neurodegenerative diseases. Our study aimed to identify and describe a hippocampal network model (HNM) using trans-diagnostic MRI data from the BrainMap® database. We used meta-analysis to test the network degeneration hypothesis (NDH) (Seeley et al., 2009) by identifying structural and functional covariance in this hippocampal network. Methods: To generate our network model, we used BrainMap's VBM database to perform a region-to-whole-brain (RtWB) meta-analysis of 269 VBM experiments from 165 published studies across a range of 38 psychiatric and neurological diseases reporting hippocampal gray matter density alterations. This step identified 11 significant gray matter foci, or nodes. We subsequently used meta-analytic connectivity modeling (MACM) to define edges of structural covariance between nodes from VBM data as well as functional covariance using the functional task-activation database, also from BrainMap. Finally, we applied a correlation analysis using Pearson's r to assess the similarities and differences between the structural and functional covariance models. Key findings: Our hippocampal RtWB meta-analysis reported consistent and significant structural covariance in 11 key regions. The subsequent structural and functional MACMs showed a strong correlation between HNM nodes with a significant structural-functional covariance correlation of r = .377 (p = .000049). Significance: This novel method of studying network covariance using VBM and functional meta-analytic techniques allows for the identification of generalizable patterns of functional and structural abnormalities pertaining to the hippocampus. In accordance with the NDH, this framework could have major implications in studying and predicting spatial disease patterns using network-based assays. Keywords: Anatomic likelihood estimation, ALE, BrainMap, Functional covariance, Functional MRI, Gray matter density, Hippocampal network model, Hippocampus, Magnetic resonance imaging, MRI, Meta-analysis, Meta-analytic connectivity modeling, MACM, Structural covariance, Structural MRI, Voxel-based morphometry, VB

BrainMap VBM: An environment for structural meta-analysis

The BrainMap database is a community resource that curates peer-reviewed, coordinate-based human neuroimaging literature. By pairing the results of neuroimaging studies with their relevant meta-data, BrainMap facilitates coordinate-based meta-analysis (CBMA) of the neuroimaging literature en masse or at the level of experimental paradigm, clinical disease, or anatomic location. Initially dedicated to the functional, task-activation literature, BrainMap is now expanding to include voxel-based morphometry (VBM) studies in a separate sector, titled: BrainMap VBM. VBM is a whole-brain, voxel-wise method that measures significant structural differences between or within groups which are reported as standardized, peak x-y-z coordinates. Here we describe BrainMap VBM, including the meta-data structure, current data volume, and automated reverse inference functions (region-to-disease profile) of this new community resource. CBMA offers a robust methodology for retaining true-positive and excluding false-positive findings across studies in the VBM literature. As with BrainMap's functional database, BrainMap VBM may be synthesized en masse or at the level of clinical disease or anatomic location. As a use-case scenario for BrainMap VBM, we illustrate a trans-diagnostic data-mining procedure wherein we explore the underlying network structure of 2,002 experiments representing over 53,000 subjects through independent components analysis (ICA). To reduce data-redundancy effects inherent to any database, we demonstrate two data-filtering approaches that proved helpful to ICA. Finally, we apply hierarchical clustering analysis (HCA) to measure network- and disease-specificity. This procedure distinguished psychiatric from neurological diseases. We invite the neuroscientific community to further exploit BrainMap VBM with other modeling approaches

Brain pathology recapitulates physiology: A network meta-analysis

Network architecture is a brain-organizational motif present across spatial scales from cell assemblies to distributed systems. Structural pathology in some neurodegenerative disorders selectively afflicts a subset of functional networks, motivating the network degeneration hypothesis (NDH). Recent evidence suggests that structural pathology recapitulating physiology may be a general property of neuropsychiatric disorders. To test this possibility, we compared functional and structural network meta-analyses drawing upon the BrainMap database. The functional meta-analysis included results from >7,000 experiments of subjects performing >100 task paradigms; the structural meta-analysis included >2,000 experiments of patients with >40 brain disorders. Structure-function network concordance was high: 68% of networks matched (pFWE < 0.01), confirming the broader scope of NDH. This correspondence persisted across higher model orders. A positive linear association between disease and behavioral entropy (p = 0.0006;R2 = 0.53) suggests nodal stress as a common mechanism. Corroborating this interpretation with independent data, we show that metabolic 'cost' significantly differs along this transdiagnostic/multimodal gradient

Pharmacodynamics of Telavancin (TD-6424), a Novel Bactericidal Agent, against Gram-Positive Bacteria

Telavancin (TD-6424) is a novel lipoglycopeptide that produces rapid and concentration-dependent killing of clinically relevant gram-positive organisms in vitro. The present studies evaluated the in vivo pharmacodynamics of telavancin in the mouse neutropenic thigh (MNT) and mouse subcutaneous infection (MSI) animal models. Pharmacokinetic-pharmacodynamic studies in the MNT model demonstrated that the 24-h area under the concentration-time curve (AUC)/MIC ratio was the best predictor of efficacy. Telavancin produced dose-dependent reduction of thigh titers of several organisms, including methicillin-susceptible Staphylococcus aureus (MSSA) and methicillin-resistant Staphylococcus aureus (MRSA), penicillin-susceptible and -resistant strains of Streptococcus pneumoniae, and vancomycin-resistant Enterococcus faecalis. The 50% effective dose (ED(50)) estimates for telavancin ranged from 0.5 to 6.6 mg/kg of body weight (administered intravenously), and titers were reduced by up to 3 log(10) CFU/g from pretreatment values. Against MRSA ATCC 33591, telavancin was 4- and 30-fold more potent (on an ED(50) basis) than vancomycin and linezolid, respectively. Against MSSA ATCC 13709, telavancin was 16- and 40-fold more potent than vancomycin and nafcillin, respectively. Telavancin, vancomycin, and linezolid were all efficacious and more potent against MRSA ATCC 33591 in the MSI model compared to the MNT model. This deviation in potency was, however, disproportionately greater for vancomycin and linezolid than for telavancin, suggesting that activity of telavancin is less affected by the immune status. The findings of these studies collectively suggest that once-daily dosing of telavancin may provide an effective approach for the treatment of clinically relevant infections with gram-positive organisms