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

Unravelling the GSK3β-related genotypic interaction network influencing hippocampal volume in recurrent major depressive disorder

Objective Glycogen synthase kinase 3β (GSK3β) has been implicated in mood disorders. We previously reported associations between a GSK3β polymorphism and hippocampal volume in major depressive disorder (MDD). We then reported similar associations for a subset of GSK3β-regulated genes. We now investigate a comprehensive list of genes encoding proteins that directly interact with GSK3β to identify a genotypic network influencing hippocampal volume in MDD. Participants and methods We used discovery (N=141) and replication (N=77) recurrent MDD samples. Our gene list was generated from the NetworKIN database. Hippocampal measures were derived using an optimized Freesurfer protocol. We identified interacting single nucleotide polymorphisms using the machine learning algorithm Random Forest and verified interactions using likelihood ratio tests between nested linear regression models. Results The discovery sample showed multiple two-single nucleotide polymorphism interactions with hippocampal volume. The replication sample showed a replicable interaction (likelihood ratio test: P=0.0088, replication sample; P=0.017, discovery sample; Stouffer’s combined P=0.0007) between genes associated previously with endoplasmic reticulum stress, calcium regulation and histone modifications. Conclusion Our results provide genetic evidence supporting associations between hippocampal volume and MDD, which may reflect underlying cellular stress responses. Our study provides evidence of biological mechanisms that should be further explored in the search for disease-modifying therapeutic targets for depression

The Risk of Severe Infections Following Rituximab Administration in Patients With Autoimmune Kidney Diseases: Austrian ABCDE Registry Analysis.

OBJECTIVE: To characterize the incidence, type, and risk factors of severe infections (SI) in patients with autoimmune kidney diseases treated with rituximab (RTX). METHODS: We conducted a multicenter retrospective cohort study of adult patients with immune-related kidney diseases treated with at least one course of RTX between 2015 and 2019. As a part of the ABCDE Registry, detailed data on RTX application and SI were collected. SI were defined by Common Terminology Criteria for Adverse Events v5.0 as infectious complications grade 3 and above. Patients were dichotomized between "nephrotic" and "nephritic" indications. The primary outcome was the incidence of SI within 12 months after the first RTX application. RESULTS: A total of 144 patients were included. Twenty-five patients (17.4%) presented with SI, mostly within the first 3 months after RTX administration. Most patients in the nephritic group had ANCA-associated vasculitis, while membranous nephropathy was the leading entity in the nephrotic group. Respiratory infections were the leading SI (n= 10, 40%), followed by urinary tract (n=3, 12%) and gastrointestinal infections (n=2, 8%). On multivariable analysis, body mass index (BMI, 24.6 kg/m2versus 26.9 kg/m2, HR: 0.88; 95%CI: 0.79-0.99; p=0.039) and baseline creatinine (HR: 1.25; 95%CI: 1.04-1.49; p=0.017) were significantly associated with SI. All patients in the nephritic group (n=19; 100%) who experienced a SI received oral glucocorticoid (GC) treatment at the time of infection. Hypogammaglobulinemia was frequent (58.5%) but not associated with SI. CONCLUSIONS: After RTX administration, impaired kidney function and lower BMI are independent risk factors for SI. Patients with nephritic glomerular diseases having concomitant GC treatment might be at higher risk of developing SI

Genetic factors influencing a neurobiological substrate for psychiatric disorders

A retrospective meta-analysis of magnetic resonance imaging voxel-based morphometry studies proposed that reduced gray matter volumes in the dorsal anterior cingulate and the left and right anterior insular cortex-areas that constitute hub nodes of the salience network-represent a common substrate for major psychiatric disorders. Here, we investigated the hypothesis that the common substrate serves as an intermediate phenotype to detect genetic risk variants relevant for psychiatric disease. To this end, after a data reduction step, we conducted genome-wide association studies of a combined common substrate measure in four population-based cohorts (n = 2271), followed by meta-analysis and replication in a fifth cohort (n = 865). After correction for covariates, the heritability of the common substrate was estimated at 0.50 (standard error 0.18). The top single-nucleotide polymorphism (SNP) rs17076061 was associated with the common substrate at genome-wide significance and replicated, explaining 1.2% of the common substrate variance. This SNP mapped to a locus on chromosome 5q35.2 harboring genes involved in neuronal development and regeneration. In follow-up analyses, rs17076061 was not robustly associated with psychiatric disease, and no overlap was found between the broader genetic architecture of the common substrate and genetic risk for major depressive disorder, bipolar disorder, or schizophrenia. In conclusion, our study identified that common genetic variation indeed influences the common substrate, but that these variants do not directly translate to increased disease risk. Future studies should investigate gene-by-environment interactions and employ functional imaging to understand how salience network structure translates to psychiatric disorder risk

ENIGMA-anxiety working group : Rationale for and organization of large-scale neuroimaging studies of anxiety disorders

Altres ajuts: Anxiety Disorders Research Network European College of Neuropsychopharmacology; Claude Leon Postdoctoral Fellowship; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, 44541416-TRR58); EU7th Frame Work Marie Curie Actions International Staff Exchange Scheme grant 'European and South African Research Network in Anxiety Disorders' (EUSARNAD); Geestkracht programme of the Netherlands Organization for Health Research and Development (ZonMw, 10-000-1002); Intramural Research Training Award (IRTA) program within the National Institute of Mental Health under the Intramural Research Program (NIMH-IRP, MH002781); National Institute of Mental Health under the Intramural Research Program (NIMH-IRP, ZIA-MH-002782); SA Medical Research Council; U.S. National Institutes of Health grants (P01 AG026572, P01 AG055367, P41 EB015922, R01 AG060610, R56 AG058854, RF1 AG051710, U54 EB020403).Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA-Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA-Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA-Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders

Association of GSK3β polymorphisms with brain structural changes in major depressive disorder

Context: Indirect evidence suggests that the glycogen synthase kinase-3β (GSK3β) gene might be implicated in major depressive disorder (MDD). Background: We evaluated 15 GSK3β single-nucleotide polymorphisms (SNPs) to test for associations with regional gray matter (GM) volume differences in patients with recurrent MDD. We then used the defined regions of interest based on significant associations to test for MDD x genotype interactions by including a matched control group without any psychiatric disorder, including MDD. Design: General linear model with nonstationary cluster-based inference. Setting: Munich, Germany. Participants: Patients with recurrent MDD (n = 134) and age-, sex-, and ethnicity-matched healthy controls (n = 143). Main Outcome Measures: Associations between GSK3β polymorphisms and regional GM volume differences. Results: Variation in GM volume was associated with GSK3β polymorphisms; the most significant associations were found for rs6438552, a putative functional intronic SNP that showed 3 significant GM clusters in the right and left superior temporal gyri and the right hippocampus (P < .001, P = .02, and P = .02, respectively, corrected for multiple comparisons across the whole brain). Similar results were obtained with rs12630592, an SNP in high linkage disequilibrium. A significant SNP x MDD status interaction was observed for the effect on GM volumes in the right hippocampus and superior temporal gyri (P < .001 and P = .01, corrected, respectively). Conclusions: The GSK3β gene may have a role in determining regional GM volume differences of the right hippocampus and bilateral superior temporal gyri. The association between genotype and brain structure was specific to the patients with MDD, suggesting that GSK3β genotypes might interact with MDD status. We speculate that this is a consequence of regional neocortical, glial, or neuronal growth or survival. In considering core cognitive features of MDD, the association of GSK3β polymorphisms with structural variation in the temporal lobe and hippocampus is of particular interest in the context of other evidence for structural and functional abnormalities in the hippocampi of patients with MDD

Pathway-based approaches to imaging genetics association studies: Wnt signaling, GSK3beta substrates and major depression

Several lines of evidence implicate glycogen synthase kinase 3 beta (GSK3β) in mood disorders. We recently reported associations between GSK3β polymorphisms and brain structural changes in patients with recurrent major depressive disorder (MDD). Here we provide supporting observations by showing that polymorphisms in additional genes encoding proteins directly related to GSK3β biological functions are associated with similar regional grey matter (GM) volume changes in MDD patients. We tested specifically for associations with genetic variation in canonical Wnt signaling pathway genes and in genes that encode substrate proteins of GSK3β. We applied a general linear model with non-stationary cluster-based inference to examine associations between polymorphisms and regional voxel-based morphometry GM volume differences in recurrent MDD patients (n = 134) and in age-, gender-, and ethnicity-matched healthy controls (n = 144) to test for genotype-by-MDD interactions. We observed associations for polymorphisms in 8/13 canonical Wnt pathway genes and 5/10 GSK3β substrate genes, predominantly in the temporolateral and medial prefrontal cortices. Similar associations were not found for 100 unrelated polymorphisms tested. This work suggests that identifying SNPs related to genes that encode functionally-interacting proteins that modulate common anatomical regions offers a useful approach to increasing confidence in outcomes from imaging genetics association studies. This is of particular interest when replication datasets are not available. Our observations lend support to the hypothesis that polymorphisms in GSK3β play a role in MDD susceptibility or expression, in part, by acting via the canonical Wnt signaling pathway and related substrates

Thyroid hormone transporter genes and grey matter changes in patients with major depressive disorder and healthy controls

Several studies have established links between thyroid gland dysfunction and mood disorders, in particular major depressive disorder (MDD). Preliminary evidence also suggests that thyroid hormone gene variants influence grey matter (GM) volume, which is reportedly altered in patients with MDD. This study tested for associations of single nucleotide polymorphisms (SNPs) in two thyroid hormone transporter genes with regional GM volume differences in a large sample population of patients with recurrent MDD and healthy volunteers

Hippocampal volume is an independent predictor of cognitive performance in CADASIL

Recent evidence suggests that hippocampal changes are present in vascular cognitive impairment but their importance and relationship with ischaemic mechanisms remain controversial. To investigate these issues we performed MRI and cognitive assessment in a large cohort (n = 144) of patients with CADASIL, a hereditary small vessel disease and model of pure vascular cognitive impairment. Dementia status was ascribed according to DSM-IV and global cognitive function assessed with the Minimental State Examination (MMSE) and Mattis Dementia Rating Scale (MDRS). Hippocampalvolume (HV) correlated with age (r = −0.33, p < 0.001), brain volume (r = 0.39, p < 0.001) and lacunar lesion volume (r = −0.23, p = 0.008), but not white matter lesions or microhaemorrhages. HV was reduced in dementia (2272 ± 333 mm3 versus 2642 ± 349 mm3, p < 0.001) in the whole cohort and the subgroup progressing to dementia before age 60. HV correlated with MMSE (r = 0.30, p < 0.001), MDRS (r = 0.40, p < 0.001) and in a multivariate model predicted cognition independent of typical vascular lesions and whole brain atrophy. These findings strengthen the view that hippocampal atrophy is an important pathway of cognitive impairment in vascular as well as degenerative disease

Pupil Dilation during Reward Anticipation Is Correlated to Depressive Symptom Load in Patients with Major Depressive Disorder.

Depression is a debilitating disorder with high prevalence and socioeconomic cost, but the brain-physiological processes that are altered during depressive states are not well understood. Here, we build on recent findings in macaques that indicate a direct causal relationship between pupil dilation and anterior cingulate cortex mediated arousal during anticipation of reward. We translated these findings to human subjects with concomitant pupillometry/fMRI in a sample of unmedicated participants diagnosed with major depression and healthy controls. We could show that the upregulation and maintenance of arousal in anticipation of reward was disrupted in patients in a symptom-load dependent manner. We could further show that the failure to maintain reward anticipatory arousal showed state-marker properties, as it tracked the load and impact of depressive symptoms independent of prior diagnosis status. Further, group differences of anticipatory arousal and continuous correlations with symptom load were not traceable only at the level of pupillometric responses, but were mirrored also at the neural level within salience network hubs. The upregulation and maintenance of arousal during reward anticipation is a novel translational and well-traceable process that could prove a promising gateway to a physiologically informed patient stratification and targeted interventions