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Objectives: The role of neurological proteins in the development of bipolar disorder (BD) and schizophrenia (SCZ) remains elusive now. The current study aims to explore the potential genetic correlations of plasma neurological proteins with BD and SCZ. Methods: By using the latest genome-wide association study (GWAS) summary data of BD and SCZ (including 41,917 BD cases, 11,260 SCZ cases, and 396,091 controls) derived from the Psychiatric GWAS Consortium website (PGC) and a recently released GWAS of neurological proteins (including 750 individuals), we performed a linkage disequilibrium score regression (LDSC) analysis to detect the potential genetic correlations between the two common psychiatric disorders and each of the 92 neurological proteins. Two-sample Mendelian randomisation (MR) analysis was then applied to assess the bidirectional causal relationship between the neurological proteins identified by LDSC, BD and SCZ. Results: LDSC analysis identified one neurological protein, NEP , which shows suggestive genetic correlation signals for both BD (coefficient = −0.165, p value = 0.035) and SCZ (coefficient = −0.235, p value = 0.020). However, those association did not remain significant after strict Bonferroni correction. Two sample MR analysis found that there was an association between genetically predicted level of NEP protein, BD (odd ratio [OR] = 0.87, p value = 1.61 × 10−6) and SCZ (OR = 0.90, p value = 4.04 × 10−6). However, in the opposite direction, there is no genetically predicted association between BD, SCZ, and NEP protein level. Conclusion: This study provided novel clues for understanding the genetic effects of neurological proteins on BD and SCZ. [ABSTRACT FROM AUTHOR]

Background: Depression is a debilitating mental disorder that often coexists with anxiety. The genetic mechanisms of depression and anxiety have considerable overlap, and studying depression in non-anxiety samples could help to discover novel gene. We assess the genetic variation of depression in non-anxiety samples, using genome-wide association studies (GWAS) and linkage disequilibrium score regression (LDSC)., Methods: The GWAS of depression score and self-reported depression were conducted using the UK Biobank samples, comprising 99,178 non-anxiety participants with anxiety score <5 and 86,503 non-anxiety participants without self-reported anxiety, respectively. Replication analysis was then performed using two large-scale GWAS summary data of depression from Psychiatric Genomics Consortium (PGC). LDSC was finally used to evaluate genetic correlations with 855 health-related traits based on the primary GWAS., Results: Two genome-wide significant loci for non-anxiety depression were identified: rs139702470 ( p  = 1.54 × 10 -8 , OR = 0.29) locate in PIEZO2 , and rs6046722 ( p  = 2.52 × 10 -8 , OR = 1.09) locate in CFAP61. These associated genes were replicated in two GWAS of depression from PGC, such as rs1040582 ( p replication GWAS1  = 0.02, p replication GWAS2  = 2.71 × 10 -3 ) in CFAP61 , and rs11661122 ( p replication GWAS1  = 8.16 × 10 -3 , p replication GWAS2  = 8.08 × 10 -3 ) in PIEZO2. LDSC identified 19 traits genetically associated with non-anxiety depression ( p  < 0.001), such as marital separation/divorce ( rg  = 0.45, SE = 0.15)., Conclusions: Our findings provide novel clues for understanding of the complex genetic architecture of depression.