Comprehensive meta-analysis of excess mortality in depression in the general community versus patients with specific illnesses

Objective: Several hundred studies have shown that depression is associated with an elevated risk of dying at follow-up. It is not clear, however, whether the mechanisms for this association are disease specific, leading to higher mortality in specific patient groups, or generic, resulting in comparable mortality rates in all patient groups as well as in community samples. The authors conducted a comprehensive meta-analysis of prospective studies of community as well as patient samples associating depression at baseline with excess mortality at follow-up

Is excess mortality higher in depressed men than in depressed women? A meta-analytic comparison

Background: It is not well established whether excess mortality associated with depression is higher in men than in women

Increased prevalence of ECG markers for sudden cardiac arrest in refractory epilepsy.

BACKGROUND AND AIM: People with epilepsy are at increased risk of sudden cardiac arrest (SCA) due to ECG-confirmed ventricular tachycardia/fibrillation, as seen in a community-based study. We aimed to determine whether ECG-risk markers of SCA are more prevalent in people with epilepsy. METHODS: In a cross-sectional, retrospective study, we analysed the ECG recordings of 185 people with refractory epilepsy and 178 controls without epilepsy. Data on epilepsy characteristics, cardiac comorbidity, and drug use were collected, and general ECG variables (heart rate (HR), PQ and QRS intervals) assessed. We analysed ECGs for three markers of SCA risk: severe QTc prolongation (male >450 ms, female >470 ms), Brugada ECG pattern, and early repolarisation pattern (ERP). Multivariate regression models were used to analyse differences between groups, and to identify associated clinical and epilepsy-related characteristics. RESULTS: People with epilepsy had higher HR (71 vs 62 bpm, p<0.001) and a longer PQ interval (162.8 vs 152.6 ms, p=0.001). Severe QTc prolongation and ERP were more prevalent in people with epilepsy (QTc prolongation: 5% vs 0%; p=0.002; ERP: 34% vs 13%, p<0.001), while the Brugada ECG pattern was equally frequent in both groups (2% vs 1%, p>0.999). After adjustment for covariates, epilepsy remained associated with ERP (ORadj 2.4, 95% CI 1.1 to 5.5) and severe QTc prolongation (ORadj 9.9, 95% CI 1.1 to 1317.7). CONCLUSIONS: ERP and severe QTc prolongation appear to be more prevalent in people with refractory epilepsy. Future studies must determine whether this contributes to increased SCA risk in people with epilepsy

Loss of brain graph network efficiency in alcohol dependence

Alcohol dependence (AD) is characterized by corticostriatal impairments in individual brain areas such as the striatum. As yet however, complex brain network topology in AD and its association with disease progression are unknown. We applied graph theory to resting‐state functional magnetic resonance imaging (RS‐fMRI) to examine weighted global efficiency and local (clustering coefficient, degree and eigenvector centrality) network topology and the functional role of the striatum in 24 AD patients compared with 20 matched healthy controls (HCs), and their association with dependence characteristics. Graph analyses were performed based on Pearson's correlations between RS‐fMRI time series, while correcting for age, gender and head motion. We found no significant group differences between AD patients and HCs in network topology. Notably, within the patient group, but not in HCs, the whole‐brain network showed reduced average cluster coefficient with more severe alcohol use, whereas longer AD duration within the patient group was associated with a global decrease in efficiency, degree and clustering coefficient. Additionally, within four a‐priori chosen bilateral striatal nodes, alcohol use severity was associated with lower clustering coefficient in the left caudate. Longer AD duration was associated with reduced clustering coefficient in caudate and putamen, and reduced degree in bilateral caudate, but with increased eigenvector centrality in left posterior putamen. Especially changes in global network topology and clustering coefficient in anterior striatum remained strikingly robust after exploratory variations in network weight. Our results show adverse effects of AD on overall network integration and possibly on striatal efficiency, putatively contributing to the increasing behavioral impairments seen in chronically addicted patients.FSW – Publicaties zonder aanstelling Universiteit Leide

Predicting the 9-year course of mood and anxiety disorders with automated machine learning: a comparison between auto-sklearn, naïve Bayes classifier, and traditional logistic regression

Background: Predicting the onset and course of mood and anxiety disorders is of clinical importance but remains difficult. We compared the predictive performances of traditional logistic regression, basic probabilistic machine learning (ML) methods, and automated ML (Auto-sklearn).Methods: Data were derived from the Netherlands Study of Depression and Anxiety. We compared how well multinomial logistic regression, a na?ve Bayes classifier, and Auto-sklearn predicted depression and anxiety diagnoses at a 2-, 4-, 6-, and 9-year follow up, operationalized as binary or categorical variables. Predictor sets included demographic and self-report data, which can be easily collected in clinical practice at two initial time points (baseline and 1-year follow up).Results: At baseline, participants were 42.2 years old, 66.5% were women, and 53.6% had a current mood or anxiety disorder. The three methods were similarly successful in predicting (mental) health status, with correct predictions for up to 79% (95% CI 75?81%). However, Auto-sklearn was superior when assessing a more complex dataset with individual item scores.Conclusions: Automated ML methods added only limited value, compared to traditional data modelling when predicting the onset and course of depression and anxiety. However, they hold potential for automatization and may be better suited for complex datasets.Algorithms and the Foundations of Software technolog

Association of CRTC1 polymorphisms with obesity markers in subjects from the general population with lifetime depression.

Psychiatric disorders have been hypothesized to share common etiological pathways with obesity, suggesting related neurobiological bases. We aimed to examine whether CRTC1 polymorphisms were associated with major depressive disorder (MDD) and to test the association of these polymorphisms with obesity markers in several large case-control samples with MDD. The association between CRTC1 polymorphisms and MDD was investigated in three case-control samples with MDD (PsyCoLaus n1=3,362, Radiant n2=3,148 and NESDA/NTR n3=4,663). The effect of CRTC1 polymorphisms on obesity markers was then explored. CRTC1 polymorphisms were not associated with MDD in the three samples. CRTC1 rs6510997C>T was significantly associated with fat mass in the PsyCoLaus study. In fact, a protective effect of this polymorphism was found in MDD cases (n=1,434, β=-1.32%, 95% CI -2.07 to -0.57, p<0.001), but not in controls. In the Radiant study, CRTC1 polymorphisms were associated with BMI, exclusively in individuals with MDD (n=2,138, β=-0.75kg/m(2), 95% CI -1.30 to -0.21, p=0.007), while no association with BMI was found in the NESDA/NTR study. Estimated fat mass using bioimpedance that capture more accurately adiposity was only present in the PsyCoLaus sample. CRTC1 polymorphisms seem to play a role with obesity markers in individuals with MDD rather than non-depressive individuals. Therefore, the weak association previously reported in the population-based samples was driven by cases diagnosed with lifetime MDD. However, CRTC1 seems not to be implicated directly in the development of psychiatric diseases

Meta-analysis of genome-wide association studies of anxiety disorders.

Anxiety disorders (ADs), namely generalized AD, panic disorder and phobias, are common, etiologically complex conditions with a partially genetic basis. Despite differing on diagnostic definitions based on clinical presentation, ADs likely represent various expressions of an underlying common diathesis of abnormal regulation of basic threat-response systems. We conducted genome-wide association analyses in nine samples of European ancestry from seven large, independent studies. To identify genetic variants contributing to genetic susceptibility shared across interview-generated DSM-based ADs, we applied two phenotypic approaches: (1) comparisons between categorical AD cases and supernormal controls, and (2) quantitative phenotypic factor scores (FS) derived from a multivariate analysis combining information across the clinical phenotypes. We used logistic and linear regression, respectively, to analyze the association between these phenotypes and genome-wide single nucleotide polymorphisms. Meta-analysis for each phenotype combined results across the nine samples for over 18 000 unrelated individuals. Each meta-analysis identified a different genome-wide significant region, with the following markers showing the strongest association: for case-control contrasts, rs1709393 located in an uncharacterized non-coding RNA locus on chromosomal band 3q12.3 (P=1.65 × 10(-8)); for FS, rs1067327 within CAMKMT encoding the calmodulin-lysine N-methyltransferase on chromosomal band 2p21 (P=2.86 × 10(-9)). Independent replication and further exploration of these findings are needed to more fully understand the role of these variants in risk and expression of ADs.Molecular Psychiatry advance online publication, 12 January 2016; doi:10.1038/mp.2015.197

Differences between unipolar mania and bipolar-I disorder: Evidence from nine epidemiological studies.

Although clinical evidence suggests important differences between unipolar mania and bipolar-I disorder (BP-I), epidemiological data are limited. Combining data from nine population-based studies, we compared subjects with mania (M) or mania with mild depression (Md) to those with BP-I with both manic and depressive episodes with respect to demographic and clinical characteristics in order to highlight differences. Participants were compared for gender, age, age at onset of mania, psychiatric comorbidity, temperament, and family history of mental disorders. Generalized linear mixed models with adjustment for sex and age as well as for each study source were applied. Analyses were performed for the pooled adult and adolescent samples, separately. Within the included cohorts, 109 adults and 195 adolescents were diagnosed with M/Md and 323 adults and 182 adolescents with BP-I. In both adult and adolescent samples, there was a male preponderance in M/Md, whereas lifetime generalized anxiety and/panic disorders and suicide attempts were less common in M/Md than in BP-I. Furthermore, adults with mania revealed bulimia/binge eating and drug use disorders less frequently than those with BP-I. The significant differences found in gender and comorbidity between mania and BP-I suggest that unipolar mania, despite its low prevalence, should be established as a separate diagnosis both for clinical and research purposes. In clinical settings, the rarer occurrence of suicide attempts, anxiety, and drug use disorders among individuals with unipolar mania may facilitate successful treatment of the disorder and lead to a more favorable course than that of BP-I disorder

Discovery and fine-mapping of glycaemic and obesity-related trait loci using high-density imputation

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated

Genome-wide association study of kidney function decline in individuals of European descent.

Genome-wide association studies (GWASs) have identified multiple loci associated with cross-sectional eGFR, but a systematic genetic analysis of kidney function decline over time is missing. Here we conducted a GWAS meta-analysis among 63,558 participants of European descent, initially from 16 cohorts with serial kidney function measurements within the CKDGen Consortium, followed by independent replication among additional participants from 13 cohorts. In stage 1 GWAS meta-analysis, single-nucleotide polymorphisms (SNPs) at MEOX2, GALNT11, IL1RAP, NPPA, HPCAL1, and CDH23 showed the strongest associations for at least one trait, in addition to the known UMOD locus, which showed genome-wide significance with an annual change in eGFR. In stage 2 meta-analysis, the significant association at UMOD was replicated. Associations at GALNT11 with Rapid Decline (annual eGFR decline of 3 ml/min per 1.73 m(2) or more), and CDH23 with eGFR change among those with CKD showed significant suggestive evidence of replication. Combined stage 1 and 2 meta-analyses showed significance for UMOD, GALNT11, and CDH23. Morpholino knockdowns of galnt11 and cdh23 in zebrafish embryos each had signs of severe edema 72 h after gentamicin treatment compared with controls, but no gross morphological renal abnormalities before gentamicin administration. Thus, our results suggest a role in the deterioration of kidney function for the loci GALNT11 and CDH23, and show that the UMOD locus is significantly associated with kidney function decline.Kidney International advance online publication, 10 December 2014; doi:10.1038/ki.2014.361