Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).

We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.

Based on individual genotypes from case–control cohorts of BPD and MDD shared through the Psychiatric Genomics Consortium, we compile case–case–control cohorts, applying a careful quality control procedure. In a resulting cohort of 51 149 individuals (15 532 BPD patients, 12 920 MDD patients and 22 697 controls), we perform a variety of GWAS and PRS analyses.

Although our GWAS is not well powered to identify genome-wide significant loci, we find significant chip heritability and demonstrate the ability of the resulting PRS to distinguish BPD from MDD, including BPD cases with depressive onset (BPD-D). We replicate our PRS findings in an independent Danish cohort (iPSYCH 2015, N = 25 966). We observe strong genetic correlation between our case–case GWAS and that of case–control BPD.

We find that MDD and BPD, including BPD-D are genetically distinct. Our findings support that controls, MDD and BPD patients primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BPD and, importantly, BPD-D from MDD.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Negative symptoms are perhaps the most disabling feature of schizophrenia. Their pathogenesis remains poorly understood and it has been difficult to assess their development over time with imaging techniques.

To examine, using tensor-based structural imaging techniques, whether there are regions of progressive grey matter volume change associated with the development of negative symptoms.

A total of 43 adolescents at risk of psychosis were examined using magnetic resonance imaging and whole brain tensor-based morphometry at two time points, 6 years apart.

When comparing the individuals with significant negative symptoms with the remaining participants, we identified five regions of significant grey matter tissue loss over the 6-year period. These regions included the left temporal lobe, the left cerebellum, the left posterior cingulate and the left inferior parietal sulcus.

Negative symptoms are associated with longitudinal grey matter tissue loss. The regions identified include areas associated with psychotic symptoms more generally but also include regions uniquely associated with negative symptoms.

No longitudinal study has yet examined the association between substance use and brain volume changes in a population at high risk of schizophrenia.

To examine the effects of cannabis on longitudinal thalamus and amygdala-hippocampal complex volumes within a population at high risk of schizophrenia.

Magnetic resonance imaging scans were obtained from individuals at high genetic risk of schizophrenia at the point of entry to the Edinburgh High-Risk Study (EHRS) and approximately 2 years later. Differential thalamic and amygdala-hippocampal complex volume change in high-risk individuals exposed (n = 25) and not exposed (n = 32) to cannabis in the intervening period was investigated using repeated-measures analysis of variance.

Cannabis exposure was associated with bilateral thalamic volume loss. This effect was significant on the left (F = 4.47, P = 0.04) and highly significant on the right (F=7.66, P=0.008). These results remained significant when individuals using other illicit drugs were removed from the analysis.

These are the first longitudinal data to demonstrate an association between thalamic volume loss and exposure to cannabis in currently unaffected people at familial high risk of developing schizophrenia. This observation may be important in understanding the link between cannabis exposure and the subsequent development of schizophrenia.