The gray matter structural connectome and its relationship to alcohol relapse: Reconnecting for recovery.

Gray matter (GM) atrophy associated with alcohol use disorders (AUD) affects predominantly the frontal lobes. Less is known how frontal lobe GM loss affects GM loss in other regions and how it influences drinking behavior or relapse after treatment. The profile similarity index (PSI) combined with graph analysis allows to assess how GM loss in one region affects GM loss in regions connected to it, ie, GM connectivity. The PSI was used to describe the pattern of GM connectivity in 21 light drinkers (LDs) and in 54 individuals with AUD (ALC) early in abstinence. Effects of abstinence and relapse were determined in a subgroup of 36 participants after 3 months. Compared with LD, GM losses within the extended brain reward system (eBRS) at 1-month abstinence were similar between abstainers (ABST) and relapsers (REL), but REL had also GM losses outside the eBRS. Lower GM connectivities in ventro-striatal/hypothalamic and dorsolateral prefrontal regions and thalami were present in both ABST and REL. Between-networks connectivity loss of the eBRS in ABST was confined to prefrontal regions. About 3 months later, the GM volume and connectivity losses had resolved in ABST, and insula connectivity was increased compared with LD. GM losses and GM connectivity losses in REL were unchanged. Overall, prolonged abstinence was associated with a normalization of within-eBRS connectivity and a reconnection of eBRS structures with other networks. The re-formation of structural connectivities within and across networks appears critical for cognitive-behavioral functioning related to the capacity to maintain abstinence after outpatient treatment

Brainstem atrophy in focal epilepsy destabilizes brainstem-brain interactions: Preliminary findings.

BACKGROUND: MR Imaging has shown atrophy in brainstem regions that were linked to autonomic dysfunction in epilepsy patients. The brainstem projects to and modulates the activation state of several wide-spread cortical/subcortical regions. The goal was to investigate 1. Impact of brainstem atrophy on gray matter connectivity of cortical/subcortical structures and autonomic control. 2. Impact on the modulation of cortical/subcortical functional connectivity. METHODS: 11 controls and 18 patients with non-lesional focal epilepsy (FE) underwent heart rate variability (HRV) measurements and a 3 T MRI (T1 in all subjects, task-free fMRI in 7 controls/ 12 FE). The brainstem was extracted, and atrophy assessed using deformation-based-morphometry. The age-corrected z-scores of the mean Jacobian determinants were extracted from 71 5x5x5 mm grids placed in brainstem regions associated with autonomic function. Cortical and non-brainstem subcortical gray matter atrophy was assessed with voxel-based-morphometry and mean age corrected z-scores of the modulated gray matter volumes extracted from 380 cortical/subcortical rois. The profile similarity index was used to characterize the impact of brainstem atrophy on gray matter connectivity. The fMRI was preprocessed in SPM12/Conn17 and the BOLD signal extracted from 398 ROIs (16 brainstem). A dynamic task-free analysis approach was used to identify activation states. Connectivity HRV relationship were assessed with Spearman rank correlations. RESULTS: HRV was negatively correlated with reduced brainstem right hippocampus/parahippocampus gray matter connectivity in controls (p \u3c .05, FDR) and reduced brainstem to right parietal cortex, lingual gyrus, left hippocampus/amygdala, parahippocampus, temporal pole, and bilateral anterior thalamus connectivity in FE (p \u3c .05, FDR). Dynamic task-free fMRI analysis identified 22 states. The strength of the functional brainstem/cortical connectivity of state 15 was negatively associated with HRV (r = -0.5, p = .03) and positively with decreased brainstem-cortical (0.49, p = .03) gray matter connectivity. CONCLUSION: The findings of this small pilot study suggest that impaired brainstem-cortex gray matter connectivity in FE negatively affects the brainstem\u27s ability to control cortical activation

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

Widespread extrahippocampal NAA/(Cr+Cho) abnormalities in TLE with and without mesial temporal sclerosis

MR spectroscopy has demonstrated extrahippocampal NAA/(Cr+Cho) reductions in medial temporal lobe epilepsy with (TLE-MTS) and without (TLE-no) mesial temporal sclerosis. Because of the limited brain coverage of those previous studies, it was, however, not possible to assess differences in the distribution and extent of these abnormalities between TLE-MTS and TLE-no. This study used a 3D whole brain echoplanar spectroscopic imaging (EPSI) sequence to address the following questions: (1) Do TLE-MTS and TLE-no differ regarding severity and distribution of extrahippocampal NAA/(Cr+Cho) reductions? (2) Do extrahippocampal NAA/(Cr+Cho) reductions provide additional information for focus lateralization? Forty-three subjects (12 TLE-MTS, 13 TLE-no, 18 controls) were studied with 3D EPSI. Statistical parametric mapping (SPM2) was used to identify regions of significantly decreased NAA/(Cr+Cho) in TLE groups and in individual patients. TLE-MTS and TLE-no had widespread extrahippocampal NAA/(Cr+Cho) reductions. NAA/(Cr+Cho) reductions had a bilateral fronto-temporal distribution in TLE-MTS and a more diffuse, less well defined distribution in TLE-no. Extrahippocampal NAA/(Cr+Cho) decreases in the single subject analysis showed a large inter-individual variability and did not provide additional focus lateralizing information. Extrahippocampal NAA/(Cr+Cho) reductions in TLE-MTS and TLE-no are neither focal nor homogeneous. This reduces their value for focus lateralization and suggests a heterogeneous etiology of extrahippocampal spectroscopic metabolic abnormalities in TLE

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

Interaction of developmental factors and ordinary stressful life events on brain structure in adults

An interplay of early environmental and genetic risk factors with recent stressful life events (SLEs) in adulthood increases the risk for adverse mental health outcomes. The interaction of early risk and current SLEs on brain structure has hardly been investigated. Whole brain voxel-based morphometry analysis was performed in N = 786 (64.6% female, mean age = 33.39) healthy subjects to identify correlations of brain clusters with commonplace recent SLEs. Genetic and early environmental risk factors, operationalized as those for severe psychopathology (i.e., polygenic scores for neuroticism, childhood maltreatment, urban upbringing and paternal age) were assessed as modulators of the impact of SLEs on the brain. SLEs were negatively correlated with grey matter volume in the left medial orbitofrontal cortex (mOFC, FWE p = 0.003). This association was present for both, positive and negative, life events. Cognitive-emotional variables, i.e., neuroticism, perceived stress, trait anxiety, intelligence, and current depressive symptoms did not account for the SLE-mOFC association. Further, genetic and environmental risk factors were not correlated with grey matter volume in the left mOFC cluster and did not affect the association between SLEs and left mOFC grey matter volume. The orbitofrontal cortex has been implicated in stress-related psychopathology, particularly major depression in previous studies. We find that SLEs are associated with this area. Important early life risk factors do not interact with current SLEs on brain morphology in healthy subjects

Global Genotype-Phenotype Correlations in Pseudomonas aeruginosa

Once the genome sequence of an organism is obtained, attention turns from identifying genes to understanding their function, their organization and control of metabolic pathways and networks that determine its physiology. Recent technical advances in acquiring genome-wide data have led to substantial progress in identifying gene functions. However, we still do not know the function of a large number of genes and, even when a gene product has been assigned to a functional class, we cannot normally predict its contribution to the phenotypic behaviour of the cell or organism - the phenome. In this study, we assessed bacterial growth parameters of 4030 non-redundant PA14 transposon mutants in the pathogenic bacterium Pseudomonas aeruginosa. The genome-wide simultaneous analysis of 119 distinct growth-related phenotypes uncovered a comprehensive phenome and provided evidence that most genotypes are not phenotypically isolated but rather define specific complex phenotypic clusters of genotypes. Since phenotypic overlap was demonstrated to reflect the relatedness of genotypes on a global scale, knowledge of an organism's phenome might significantly contribute to the advancement of functional genomics

The association between genetically determined ABO blood types and major depressive disorder

ABO blood types and their corresponding antigens have long been assumed to be related to different human diseases. So far, smaller studies on the relationship between mental disorders and blood types yielded contra-dicting results. In this study we analyzed the association between ABO blood types and lifetime major depressive disorder (MDD). We performed a pooled analysis with data from 26 cohorts that are part of the MDD working group of the Psychiatric Genomics Consortium (PGC). The dataset included 37,208 individuals of largely Eu-ropean ancestry of which 41.6% were diagnosed with lifetime MDD. ABO blood types were identified using three single nucleotide polymorphisms in the ABO gene: rs505922, rs8176746 and rs8176747. Regression analyses were performed to assess associations between the individual ABO blood types and MDD diagnosis as well as putative interaction effects with sex. The models were adjusted for sex, cohort and the first ten genetic principal components. The percentage of blood type A was slightly lower in cases than controls while blood type O was more prominent in cases. However, these differences were not statistically significant. Our analyses found no evidence of an association between ABO blood types and major depressive disorder

Immunogenicity of an additional mRNA-1273 SARS-CoV-2 vaccination in people with HIV with hyporesponse after primary vaccination

Background:The COVIH study is a prospective coronavirus disease 2019 (COVID-19) vaccination study in 1154 people with HIV (PWH), of whom 14% showed reduced antibody levels after primary vaccination. We evaluated whether an additional vaccination boosts immune responses in these hyporesponders. Methods: The primary end point was the increase in antibodies 28 days after additional mRNA-1273 vaccination. Secondary end points included neutralizing antibodies, S-specific T-cell and B-cell responses, and reactogenicity. Results:Of the 66 participants, 40 previously received 2 doses ChAdOx1-S, 22 received 2 doses BNT162b2, and 4 received a single dose Ad26.COV2.S. The median age was 63 years (interquartile range [IQR], 60–66), 86% were male, and median CD4 + T-cell count was 650/μL (IQR, 423–941). The mean S1-specific antibody level increased from 35 binding antibody units (BAU)/ mL (95% confidence interval [CI], 24–46) to 4317 BAU/mL (95% CI, 3275–5360) (P &lt; .0001). Of all participants, 97% showed an adequate response and the 45 antibody-negative participants all seroconverted. A significant increase in the proportion of PWH with ancestral S-specific CD4 + T cells (P = .04) and S-specific B cells (P = .02) was observed. Conclusions:An additional mRNA-1273 vaccination induced a robust serological response in 97% of PWH with a hyporesponse after primary vaccination.</p

Epigenetic upregulation of FKBP5 by aging and stress contributes to NF-κB-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