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Electroconvulsive therapy (ECT) is the most effective treatment for severe depression, but the biological changes induced by ECT remain poorly understood.

Antidepressant medication is used extensively to treat bipolar depression despite uncertain efficacy. The cytochrome P450 (CYP) 2C19 enzyme metabolize several antidepressants, and polymorphisms in the corresponding gene CYP2C19influence plasma concentration and hence treatment outcomes in major depressive disorder. Here, we investigate if CYP2C19polymorphisms are associated with antidepressant treatment patterns and the risk of mania when antidepressants are used in bipolar disorder. Two single nucleotide polymorphisms (rs4244285 and rs12248560) were used to classify 5019 bipolar disorder patients into CYP2C19metabolic phenotypes ranging from poor to ultra-rapid metabolizers. We used Swedish national registry data 2005–2017 on dispensed medications and inpatient care to estimate risks for early-treatment persistence, treatment discontinuation, switching to a new antidepressant medication, and mania within 3 months of treatment initiation in patients treated with citalopram, escitalopram, sertraline, amitriptyline, and clomipramine. Metabolic phenotypes of CYP2C19were not robustly associated with the investigated treatment outcomes based on dispense patterns. Slower metabolism was associated with an increased risk of treatment emergent mania for sertraline (hazard ratio [HR] = 1.3, 95% CI = 1.04–1.62, p= 0.02) and the tricyclic antidepressants amitriptyline and clomipramine (HR = 1.46, 95% CI = 1.05–2.02, p= 0.024). In a large study of the impact of CYP2C19metabolic phenotypes on antidepressant treatment of bipolar depression, we found an association between slower CYP2C19 metabolism and higher risk of treatment emergent mania, which is a step towards personalized risk assessments. There were, however, no clear associations with early treatment persistence, treatment discontinuation, and switching to a new antidepressant.

Suicide is a major cause of death worldwide. Several biological systems have been implicated in suicidal behavior but studies of candidate biomarkers have failed to produce clinically relevant biomarkers for suicide prediction. The objective of the present study was to identify novel candidate biomarkers for suicidal behavior. We used a nested case-control study design where a large cohort of patients with bipolar disorder (N= 5 110) were followed up to 8 years after blood sampling. We included patients that attempted suicide during follow-up (N= 348) and matched bipolar disorder patients from the same cohort who did not attempt suicide during the study period (N= 348) and analyzed a total of 92 proteins with a neuro exploratory multiplex panel. Using a multivariate classification algorithm devised to minimize bias in variable selection, we identified a parsimonious set of proteins that best discriminated bipolar disorder patients with and without prospective suicide attempts. The algorithm selected 16 proteins for the minimal-optimal classification model, which outperformed 500 models with permuted outcome (p= 0.0004) but had low sensitivity (53%) and specificity (64%). The candidate proteins were then entered in separate logistic regression models to calculate protein-specific associations with prospective suicide attempts. In individual analyses, three of these proteins were significantly associated with prospective suicide attempt (SCGB1A1, ANXA10, and CETN2). Most of the candidate proteins are novel to suicide research.

The etiopathology of bipolar disorder is largely unknown. We collected cerebrospinal fluid (CSF) samples from two independent case-control cohorts (total n= 351) to identify proteins associated with bipolar disorder. A panel of 92 proteins targeted towards central nervous system processes identified two proteins that replicated across the cohorts: the CSF concentrations of testican-1 were lower, and the CSF concentrations of C-type lectin domain family 1 member B (CLEC1B) were higher, in cases than controls. In a restricted subgroup analysis, we compared only bipolar type 1 with controls and identified two additional proteins that replicated in both cohorts: draxin and tumor necrosis factor receptor superfamily member 21 (TNFRSF21), both lower in cases than controls. This analysis additionally revealed several proteins significantly associated with bipolar type 1 in one cohort, falling just short of replicated statistical significance in the other (tenascin-R, disintegrin and metalloproteinase domain-containing protein 23, cell adhesion molecule 3, RGM domain family member B, plexin-B1, and brorin). Next, we conducted genome-wide association analyses of the case-control-associated proteins. In these analyses, we found associations with the voltage-gated calcium channel subunit CACNG4, and the lipid-droplet-associated gene PLIN5with CSF concentrations of TNFRSF21 and CLEC1B, respectively. The reported proteins are involved in neuronal cell-cell and cell-matrix interactions, particularly in the developing brain, and in pathways of importance for lithium’s mechanism of action. In summary, we report four novel CSF protein associations with bipolar disorder that replicated in two independent case-control cohorts, shedding new light on the central nervous system processes implicated in bipolar disorder.

Although large genome-wide association studies (GWAS) of major depressive disorder (MDD) have identified many significant loci, the SNP-based heritability remains notably low, which might be due to etiological heterogeneity in existing samples. Here, we test the utility of targeting the severe end of the MDD spectrum through genome-wide SNP genotyping of 2725 cases who received electroconvulsive therapy (ECT) for a major depressive episode (MDE) and 4035 controls. A subset of cases (n= 1796) met a narrow case definition (MDE occurring in the context of MDD). Standard GWAS quality control procedures and imputation were conducted. SNP heritability and genetic correlations with other traits were estimated using linkage disequilibrium score regression. Results were compared with MDD cases of mild-moderate severity receiving internet-based cognitive behavioral therapy (iCBT) and summary results from the Psychiatric Genomics Consortium (PGC). The SNP-based heritability was estimated at 29–34% (SE: 6%) for the narrow case definition, considerably higher than the 6.5–8.0% estimate in the most recent PGC MDD study. Our severe MDE cases had smaller genetic correlations with neurodevelopmental disorders and neuroticism than PGC MDD cases but higher genetic risk scores for bipolar disorder than iCBT MDD cases. One genome-wide significant locus was identified (rs114583506, P= 5e−8) in an intron of HLA-Bin the major histocompatibility locus on chr6. These results indicate that individuals receiving ECT for an MDE have higher burden of common variant risk loci than individuals with mild-moderate MDD. Furthermore, severe MDE shows stronger relations with other severe adult-onset psychiatric disorders but weaker relations with personality and stress-related traits than mild-moderate MDD. These findings suggest a different genetic architecture at the severest end of the spectrum, and support further study of the severest MDD cases as an extreme phenotype approach to understand the etiology of MDD.

Pharmacological treatment, imaging, and neurochemistry studies identify altered dopamine signaling in bipolar disorder. Our previous work has shown higher concentration of homovanillic acid (HVA), the end metabolite of dopamine, in cerebrospinal fluid (CSF) from individuals with bipolar disorder compared to healthy controls. Here, we analyzed HVA concentrations from a follow-up visit in 103 adults with bipolar disorder and 57 controls from our first cohort. Further, we analyzed CSF monoamine metabolite concentrations in a second cohort of 152 adults with bipolar disorder and 55 controls. At the follow-up visit for the first cohort, HVA was higher in individuals with bipolar disorder (278 ± 102 nmol/L, p = 0.003) compared with controls (232 ± 83 nmol/L). In the second cohort, individuals with bipolar disorder had higher HVA (272 ± 97 nmol/L, p = 0.001) and lower 3-methoxy-4-hydroxyphenylglycol (MHPG, 40 ± 9 nmol/L, p = 0.002) concentrations than controls (HVA, 231 ± 71 nmol/L and MHPG, 45 ± 9 nmol/L). Baseline and follow-up measures of monoamine metabolites showed medium to high correlation to each other but did not predict course of illness. We failed to replicate the association of HVA concentration and psychotic symptoms but confirmed lower 5-hydroxyindoleacetic acid (5-HIAA) concentration in individuals treated with antidepressants. In conclusion, we confirmed high HVA concentration in CSF in patients with bipolar disorder compared to a control group. Previous work suggest that this is a feature shared with ADHD but distinct from schizophrenia and major depressive disorder. The role of increased HVA concentration in the course of illness in bipolar disorder remains unclear.

Bipolar disorder (BD) is a severe and debilitating psychiatric disorder. However, the precise biological basis remains unknown, hampering the search for novel biomarkers. We performed a metabolomics analysis to discover novel peripheral biomarkers for BD.