Multi-locus genome-wide association analysis supports the role of glutamatergic synaptic transmission in the etiology of major depressive disorder

Oxidative & nitrosative stress in depression: why so much stress?

Many studies support a crucial role for oxidative & nitrosative stress (O&NS) in the pathophysiology of unipolar and bipolar depression. These disorders are characterized inter alia by lowered antioxidant defenses, including: lower levels of zinc, coenzyme Q10, vitamin E and glutathione; increased lipid peroxidation; damage to proteins, DNA and mitochondria; secondary autoimmune responses directed against redox modified nitrosylated proteins and oxidative specific epitopes. This review examines and details a model through which a complex series of environmental factors and biological pathways contribute to increased redox signaling and consequently increased O&NS in mood disorders. This multi-step process highlights the potential for future interventions that encompass a diverse range of environmental and molecular targets in the treatment of depression.

Natural selection and infectious disease in human populations

Infectious pathogens are among the strongest selective forces that shape the human genome. Migrations and cultural changes in the past 100,000 years exposed populations to dangerous new pathogens.

Host genetics influences susceptibility to infectious disease. Evolutionary adaptations for resistance and symbiosis may underlie common immune-mediated diseases.

Signatures of selection and methods to detect them vary with the age, geographical spread and virulence of the pathogen.

A history of selection on a trait adds power to association studies by driving the emergence of common alleles of strong effect. Combining selection and association metrics can further increase power.

Genome-wide association studies (GWASs) of susceptibility to pathogens that are moderately old (1,000–50,000 years ago), geographically limited in history and exerted strong positive selective pressure will have the most power if GWASs can be done in the historically affected population.

An understanding of host–pathogen interactions can inform the development of new therapies for both infectious diseases and common immune-mediated diseases.

The impact of various infectious agents on human survival and reproduction over thousands of years has exerted selective pressure on numerous regions of the human genome. This Review describes how such signatures of selection can be detected and integrated with data from complementary approaches, such as genome-wide association studies, to provide biological insights into host–pathogen interactions.

The ancient biological 'arms race' between microbial pathogens and humans has shaped genetic variation in modern populations, and this has important implications for the growing field of medical genomics. As humans migrated throughout the world, populations encountered distinct pathogens, and natural selection increased the prevalence of alleles that are advantageous in the new ecosystems in both host and pathogens. This ancient history now influences human infectious disease susceptibility and microbiome homeostasis, and contributes to common diseases that show geographical disparities, such as autoimmune and metabolic disorders. Using new high-throughput technologies, analytical methods and expanding public data resources, the investigation of natural selection is leading to new insights into the function and dysfunction of human biology.

Microarray profiling and co-expression network analysis of circulating lncRNAs and mRNAs associated with major depressive disorder

LncRNAs, which represent one of the most highly expressed classes of ncRNAs in the brain, are becoming increasingly interesting with regard to brain functions and disorders. However, changes in the expression of regulatory lncRNAs in Major Depressive Disorder (MDD) have not yet been reported. Using microarrays, we profiled the expression of 34834 lncRNAs and 39224 mRNAs in peripheral blood sampled from MDD patients as well as demographically-matched controls. Among these, we found that 2007 lncRNAs and 1667 mRNAs were differentially expressed, 17 of which were documented as depression-related gene in previous studies. Gene Ontology (GO) and pathway analyses indicated that the biological functions of differentially expressed mRNAs were related to fundamental metabolic processes and neurodevelopment diseases. To investigate the potential regulatory roles of the differentially expressed lncRNAs on the mRNAs, we also constructed co-expression networks composed of the lncRNAs and mRNAs, which shows significant correlated patterns of expression. In the MDD-derived network, there were a greater number of nodes and connections than that in the control-derived network. The lncRNAs located at chr10:874695-874794, chr10:75873456-75873642, and chr3:47048304-47048512 may be important factors regulating the expression of mRNAs as they have previously been reported associations with MDD. This study is the first to explore genome-wide lncRNA expression and co-expression with mRNA patterns in MDD using microarray technology. We identified circulating lncRNAs that are aberrantly expressed in MDD and the results suggest that lncRNAs may contribute to the molecular pathogenesis of MDD.

Whole-genome pathway analysis on 132,497 individuals identifies novel gene-sets associated with body mass index

Whole genome pathway analysis is a powerful tool for the exploration of the combined effects of gene-sets within biological pathways. This study applied Interval Based Enrichment Analysis (INRICH) to perform whole-genome pathway analysis of body-mass index (BMI). We used a discovery set composed of summary statistics from a meta-analysis of 123,865 subjects performed by the GIANT Consortium, and an independent sample of 8,632 subjects to assess replication of significant pathways. We examined SNPs within nominally significant pathways using linear mixed models to estimate their contribution to overall BMI heritability. Six pathways replicated as having significant enrichment for association after correcting for multiple testing, including the previously unknown relationships between BMI and the Reactome regulation of ornithine decarboxylase pathway, the KEGG lysosome pathway, and the Reactome stabilization of P53 pathway. Two non-overlapping sets of genes emerged from the six significant pathways. The clustering of shared genes based on previously identified protein-protein interactions listed in PubMed and OMIM supported the relatively independent biological effects of these two gene-sets. We estimate that the SNPs located in examined pathways explain ∼20% of the heritability for BMI that is tagged by common SNPs (3.35% of the 16.93% total).

Higher risk of developing major depression and bipolar disorder in later life among adolescents with asthma: a nationwide prospective study

OBJECTIVE

Previous studies have suggested an immunological dysfunction in mood disorders, but rarely have investigated the temporal association between allergic diseases and mood disorders. Using the Taiwan National Health Insurance Research Database, we attempted to investigate the association between asthma in early adolescence and the risk of unipolar depression and bipolar disorder in later life.

METHODS

In all, 1453 adolescents with asthma aged between 10 and 15 years and 5812 age-/gender-matched controls were selected in 1998-2000. Subjects with unipolar depression and bipolar disorder that occurred up to the end of follow-up (December 31 2010) were identified.

RESULTS

Adolescents with asthma had a higher incidence of major depression (2.8% vs. 1.1%, p < 0.001), any depressive disorder (6.1% vs. 2.6%, p < 0.001), and bipolar disorder (1.0% vs. 0.3%, p < 0.001) than the control group. Cox regression analysis showed that asthma in early adolescence was associated with an increased risk of developing major depression (hazard ratio [HR]: 1.81, 95% confidence interval [CI]: 1.14-2.89), any depressive disorder (HR: 1.74, 95% CI: 1.27-2.37), and bipolar disorder (HR: 2.27, 95% CI: 1.01-5.07), after adjusting for demographic data and comorbid allergic diseases.

DISCUSSION

Adolescents with asthma had an elevated risk of developing mood disorders in later life. Further studies would be required to investigate the underlying mechanisms for this comorbid association and elucidate whether prompt intervention for asthma would decrease the risk of developing mood disorders.

Peripheral blood mononuclear cell-based metabolomic profiling of a chronic unpredictable mild stress rat model of depression

Major depressive disorder (MDD) is a debilitating mood disorder with various etiopathological hypotheses.

Genome-wide analyses implicate 33 loci in heritable dog osteosarcoma, including regulatory variants near CDKN2A/B

Background

Canine osteosarcoma is clinically nearly identical to the human disease, but is common and highly heritable, making genetic dissection feasible.

Results

Through genome-wide association analyses in three breeds (greyhounds, Rottweilers, and Irish wolfhounds), we identify 33 inherited risk loci explaining 55% to 85% of phenotype variance in each breed. The greyhound locus exhibiting the strongest association, located 150 kilobases upstream of the genes CDKN2A/B, is also the most rearranged locus in canine osteosarcoma tumors. The top germline candidate variant is found at a >90% frequency in Rottweilers and Irish wolfhounds, and alters an evolutionarily constrained element that we show has strong enhancer activity in human osteosarcoma cells. In all three breeds, osteosarcoma-associated loci and regions of reduced heterozygosity are enriched for genes in pathways connected to bone differentiation and growth. Several pathways, including one of genes regulated by miR124, are also enriched for somatic copy-number changes in tumors.

Conclusions

Mapping a complex cancer in multiple dog breeds reveals a polygenic spectrum of germline risk factors pointing to specific pathways as drivers of disease.

What psychiatric genetics has taught us about the nature of psychiatric illness and what is left to learn

Psychiatric genetics has taught us a great deal about the nature of psychiatric disorders. Traditional family, twin and adoption studies have demonstrated the substantial role of genetic factors in their etiology, clarified the role of genetic factors in comorbidity, elucidated development pathways, and documented the importance of gene-environment correlation and interaction. We have also received some hard lessons when we were unable to detect replicable genes of large effect size and found that our much-valued candidate genes did not live up to their expected promise. With more mature molecular and statistical methods, we are entering now a different era. Statistical analyses of aggregate molecular signals are validating earlier heritability estimates. Replicated findings from genome-wide association studies are beginning to emerge, as are discoveries of large-effect size rare genomic variants. The number of such findings is likely to soon grow dramatically. The most pressing question facing the field is what biological picture these results will reveal. I articulate four possible scenarios that reflect (i) no, (ii) minimal, (iii) moderate and (iv) high biological coherence in the replicated molecular variant findings, which are soon likely to emerge. I discuss the factors that will likely influence these patterns, including the problems of etiological heterogeneity and multiple realizability. These findings could provide critical insights into the underlying biology of our psychiatric syndromes and potentially permit us to perceive, 'through a glass darkly,' the levels of the mind-brain system that are disordered.

Novel genetic analysis for case-control genome-wide association studies: quantification of power and genomic prediction accuracy

Genome-wide association studies (GWAS) are routinely conducted for both quantitative and binary (disease) traits. We present two analytical tools for use in the experimental design of GWAS. Firstly, we present power calculations quantifying power in a unified framework for a range of scenarios. In this context we consider the utility of quantitative scores (e.g. endophenotypes) that may be available on cases only or both cases and controls. Secondly, we consider, the accuracy of prediction of genetic risk from genome-wide SNPs and derive an expression for genomic prediction accuracy using a liability threshold model for disease traits in a case-control design. The expected values based on our derived equations for both power and prediction accuracy agree well with observed estimates from simulations.

Ketamine as a fast acting antidepressant: current knowledge and open questions

Several recent studies have shown that a single intravenous subanesthetic dose of ketamine, a NMDA receptor antagonist, exerts rapid antidepressant effects in patients with treatment refractory mood disorders and reduces suicidal ideation. Those insights have fueled tremendous excitement in the efforts to elucidate the mechanism underlying ketamine's antidepressant properties in animal models of depression, as well as in humans through the use of brain imaging as well as peripheral blood measurements. For example, there is emerging evidence that ketamine's antidepressant properties rely on increasing AMPA signaling and rapidly inducing synaptogenesis. While pilot clinical studies are promising, a number of critical questions still remain unanswered. They relate to the safe and effective use of ketamine in patients with mood disorders regarding the optimal dose range, modality and method of administration for acute and long-term maintenance of effect, and the biomarkers associated with response/nonresponse. In this review article, we first summarize the clinical evidence about the use of ketamine in mood disorders, as well as preclinical and humans studies which investigated the mechanisms of action of ketamine, and predictors of antidepressant response in clinical populations. We then provide a critical overview of the knowledge gaps about the use of ketamine in depression and suggest some future research directions for the investigation of ketamine as a promising tool to develop novel more effective and fast acting antidepressants.