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Individuals with a mental health disorder appear to be at increased risk of medical illness. To examine rates of medical illnesses in patients with bipolar disorder (n = 1720) and to examine the clinical course of the bipolar illness according to lifetime medical illness burden. Participants recruited within the UK were asked about the lifetime occurrence of 20 medical illnesses, interviewed using the Schedules for Clinical Assessment in Neuropsychiatry (SCAN) and diagnosed according to DSM-IV criteria. We found significantly increased rates of several medical illnesses in our bipolar sample. A high medical illness burden was associated with a history of anxiety disorder, rapid cycling mood episodes, suicide attempts and mood episodes with a typically acute onset. Bipolar disorder is associated with high rates of medical illness. This comorbidity needs to be taken into account by services in order to improve outcomes for patients with bipolar disorder and also in research investigating the aetiology of affective disorder where shared biological pathways may play a role.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease of motor neurons that results in progressive weakness and death from respiratory failure, commonly within about 3 years. Previous studies have shown association of a locus on chromosome 9p with ALS and linkage with ALS–frontotemporal dementia. We aimed to test whether this genomic region is also associated with ALS in an independent set of UK samples, and to identify risk factors associated with ALS in a further genome-wide association study that combined data from the independent analysis with those from other countries. We collected samples from patients with sporadic ALS from 20 UK hospitals and obtained UK control samples from the control groups of the Depression Case Control study, the Bipolar Affective Case Control Study, and the British 1958 birth cohort DNA collection. Genotyping of DNA in this independent analysis was done with Illumina HumanHap550 BeadChips. We then undertook a joint genome-wide analysis that combined data from the independent set with published data from the UK, USA, Netherlands, Ireland, Italy, France, Sweden, and Belgium. The threshold for significance was p=0·05 in the independent analysis, because we were interested in replicating a small number of previously reported associations, whereas the Bonferroni-corrected threshold for significance in the joint analysis was p=2·20×10 −7 After quality control, samples were available from 599 patients and 4144 control individuals in the independent set. In this analysis, two single nucleotide polymorphisms in a locus on chromosome 9p21.2 were associated with ALS: rs3849942 (p=2·22×10 −6; odds ratio [OR] 1·39, 95% CI 1·21–1·59) and rs2814707 (p=3·32×10 −6; 1·38, 1·20–1·58). In the joint analysis, which included samples from 4312 patients with ALS and 8425 control individuals, rs3849942 (p=4·64×10 −10; OR 1·22, 95% CI 1·15–1·30) and rs2814707 (p=4·72×10 −10; 1·22, 1·15–1·30) were associated with ALS. We have found strong evidence of a genetic association of two single nucleotide polymorphisms on chromosome 9 with sporadic ALS, in line with findings from previous independent GWAS of ALS and linkage studies of ALS–frontotemporal dementia. Our findings together with these earlier findings suggest that genetic variation at this locus on chromosome 9 causes sporadic ALS and familial ALS–frontotemporal dementia. Resequencing studies and then functional analysis should be done to identify the defective gene. ALS Therapy Alliance, the Angel Fund, the Medical Research Council, the Motor Neurone Disease Association of Great Britain and Northern Ireland, the Wellcome Trust, and the National Institute for Health Research Dementias and Neurodegenerative Diseases Research Network (DeNDRoN).

White matter abnormalities have been implicated in the aetiology of major depressive disorder; however, the relationship between the severity of symptoms and white matter integrity is currently unclear. To investigate white matter integrity in people with major depression and healthy controls, and to assess its relationship with depressive symptom severity. Diffusion tensor imaging data were acquired from 66 patients with recurrent major depression and a control group of 66 healthy individuals matched for age, gender and IQ score, and analysed with tract-based spatial statistics. The relationship between white matter integrity and severity of depression as measured by the Beck Depression Inventory was examined. Depressive illness was associated with widespread regions of decreased white matter integrity, including regions in the corpus callosum, superior longitudinal fasciculus and anterior corona radiata, compared with the control group. Increasing symptom severity was negatively correlated with white matter integrity, predominantly in the corpus callosum. Widespread alterations in white matter integrity are evident in major depressive disorder. These abnormalities are heightened with increasing severity of depressive symptoms.

Suicidal behaviour can be conceptualised as a continuum from suicidal ideation, to suicidal attempts to completed suicide. In this study we identify genes contributing to suicidal behaviour in the depression study RADIANT. A quantitative suicidality score was composed of two items from the SCAN interview. In addition, the 251 depression cases with a history of serious suicide attempts were classified to form a discrete trait. The quantitative trait was correlated with younger onset of depression and number of episodes of depression, but not with gender. A genome-wide association study of 2,023 depression cases was performed to identify genes that may contribute to suicidal behaviour. Two Munich depression studies were used as replication cohorts to test the most strongly associated SNPs. No SNP was associated at genome-wide significance level. For the quantitative trait, evidence of association was detected at GFRA1, a receptor for the neurotrophin GDRA (p = 2e-06). For the discrete trait of suicide attempt, SNPs in KIAA1244 and RGS18 attained p-values of <5e-6. None of these SNPs showed evidence for replication in the additional cohorts tested. Candidate gene analysis provided some support for a polymorphism in NTRK2, which was previously associated with suicidality. This study provides a genome-wide assessment of possible genetic contribution to suicidal behaviour in depression but indicates a genetic architecture of multiple genes with small effects. Large cohorts will be required to dissect this further.

Mood disorders consist of two etiologically related, but distinctly treated illnesses, major depressive disorder (MDD) and bipolar disorder (BPD). These disorders share similarities in their clinical presentation, and thus show high rates of misdiagnosis. Recent research has revealed significant transcriptional differences within the inflammatory cytokine pathway between MDD patients and controls, and between BPD patients and controls, suggesting this pathway may possess important biomarker properties. This exploratory study attempts to identify disorder-specific transcriptional biomarkers within the inflammatory cytokine pathway, which can distinguish between control subjects, MDD patients and BPD patients. This is achieved using RNA extracted from subject blood and applying synthesized complementary DNA to quantitative PCR arrays containing primers for 87 inflammation-related genes. Initially, we use ANOVA to test for transcriptional differences in a 'discovery cohort' (total n = 90) and then we use t-tests to assess the reliability of any identified transcriptional differences in a 'validation cohort' (total n = 35). The two most robust and reliable biomarkers identified across both the discovery and validation cohort were Chemokine (C-C motif) ligand 24 (CCL24) which was consistently transcribed higher amongst MDD patients relative to controls and BPD patients, and C-C chemokine receptor type 6 (CCR6) which was consistently more lowly transcribed amongst MDD patients relative to controls. Results detailed here provide preliminary evidence that transcriptional measures within inflammation-related genes might be useful in aiding clinical diagnostic decision-making processes. Future research should aim to replicate findings detailed in this exploratory study in a larger medication-free sample and examine whether identified biomarkers could be used prospectively to aid clinical diagnosis.

A key feature of major depressive disorder (MDD) is anhedonia, which is a predictor of response to antidepressant treatment. In order to shed light on its genetic underpinnings, we conducted a genome-wide association study (GWAS) followed by investigation of biological pathway enrichment using an anhedonia dimension for 759 patients with MDD in the GENDEP study. The GWAS identified 18 SNPs associated at genome-wide significance with the top one being an intronic SNP (rs9392549) in PRPF4B (pre-mRNA processing factor 4B) located on chromosome 6 (P = 2.07 × 10−9) while gene-set enrichment analysis returned one gene ontology term, axon cargo transport (GO: 0008088) with a nominally significant P value (1.15 × 10−5). Furthermore, our exploratory analysis yielded some interesting, albeit not statistically significant genetic correlation with Parkinson’s Disease and nucleus accumbens gray matter. In addition, polygenic risk scores (PRSs) generated from our association analysis were found to be able to predict treatment efficacy of the antidepressants in this study. In conclusion, we found some markers significantly associated with anhedonia, and some suggestive findings of related pathways and biological functions, which could be further investigated in other studies.

The aim of this study was to investigate genetic predictors of an increase in suicidal ideation during treatment with a selective serotonin reuptake inhibitor or a tricyclic antidepressant. A total of 796 adult patients with major depressive disorder who were treated with a flexible dosage of escitalopram or nortriptyline in Genome-based Therapeutic Drugs for Depression (GENDEP) were included in the sample and provided data on suicidal ideation. Nine candidate genes involved in neurotrophic, serotonergic, and noradrenergic pathways were selected based on previous association studies with suicidal ideation or behavior. Using a logistic regression model, 123 polymorphisms in these genes were compared between subjects with an increase in suicidal ideation and those without any increase in suicidal ideation. Polymorphisms in BDNF , the gene encoding the brain-derived neurotrophic factor, were significantly associated with an increase in suicidal ideation. The strongest association was observed for rs962369 in BDNF ( p =0.0015). Moreover, a significant interaction was found between variants in BDNF and NTRK2 , the gene encoding the BNDF receptor ( p =0.0003). Among men taking nortriptyline, suicidality was also associated with rs11195419 SNP in the alpha 2A -adrenergic receptor gene ( ADRA2A ) ( p =0.007). The associations observed with polymorphisms in BDNF suggest the involvement of the neurotrophic system in vulnerability to suicidality. Epistasis between BDNF and NTRK2 suggests that genetic variations in the two genes are involved in the same causal mechanisms leading to suicidality during antidepressant treatment. Among men, genetic variation in noradrenergic signaling may interact with norepinephrine reuptake-inhibiting antidepressants, thereby contributing to suicidality.

Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P <0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance ( P <5 × 10 −8 ), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083–53 822 102, minimum P =5.9 × 10 −9 at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.