Total Brain Volumetric Measures and Schizophrenia Risk: A Two-Sample Mendelian Randomization Study

Mendelian randomization reveals association between retinal thickness and non-motor symptoms of Parkinson's disease

Retinal thickness is related to Parkinson's disease (PD), but its association with the severity of PD is still unclear. We conducted a Mendelian randomized (MR) study to explore the association between retinal thickness and PD. For the two-sample MR analysis, the summary statistics obtained from genome-wide association studies on the thickness of Retinal nerve fiber layer (RNFL) and ganglion cell inner plexiform layer (GCIPL) were employed as exposure, while the summary statistics associated with PD were used as the outcome. The primary approach utilized was inverse variance weighted. To correct for multiple testing, the false discovery rate (FDR) was employed. For sensitivity analysis, an array of robust MR methods was utilized. We found genetically predicted significant association between reduced RNFL thickness and a reduced risk of constipation in PD (odds ratio [OR] = 0.854, 95% confidence interval [CI] (0.782, 0.933), P < 0.001, FDR-corrected P = 0.018). Genetically predicted reduced RNFL thickness was associated with a reduced Unified Parkinson's Disease Rating Scale total score (β = -0.042, 95% CI (-0.079, 0.005), P = 0.025), and reduced GCIPL thickness was associated with a lower risk of constipation (OR = 0.901, 95% CI (0.821, 0.988), P = 0.027) but a higher risk of depression (OR = 1.103, 95% CI (1.016, 1.198), P = 0.020), insomnia (OR = 1.090, 95% CI (1.013, 1.172), P = 0.021), and rapid eye movement sleep behaviour disorder (RBD) (OR = 1.198, 95% CI (1.061, 1.352), P = 0.003). In conclusion, we identify an association between retinal thickness and non-motor symptoms (constipation, depression, insomnia and RBD) in PD, highlighting the potential of retinal thickness as a biomarker for PD nonmotor symptoms.

Identifying the mediating role of socioeconomic status on the relationship between schizophrenia and major depressive disorder: a Mendelian randomisation analysis

Depressive disorder prevalence in patients with schizophrenia has been reported to be 40%. People with low socioeconomic status (SES) are more likely to suffer from schizophrenia and major depressive disorder (MDD). However, the causal relationship between schizophrenia and depression and the potential mediating role of SES remains unclear. Two-sample Mendelian randomization (MR) analyses were conducted to explore the bidirectional causal relationship between schizophrenia and MDD with the largest sample size of European ancestry from public genome-wide association studies (sample size ranged from 130,644 to 480,359). Inverse variance weighted (IVW) method was used as the primary analysis, and several canonical MR methods were used as validation analyses. The mediating role of SES (educational years, household income, employment status, and Townsend deprivation index) was estimated by the two-step MR method. MR analyses showed that genetically predicted schizophrenia was associated with an increased risk of MDD (IVW odds ratio [OR] = 1.137 [95% CI 1.095, 1.181]). Reversely, MDD was also associated with an increased risk of schizophrenia (IVW OR = 1.323 [95% CI 1.118, 1.565]). The mediation analysis via the two-step MR method revealed that the causal effect of schizophrenia on MDD was partly mediated by the Townsend deprivation index with a proportion of 10.27%, but no significant mediation effect was found of SES on the causal effect of MDD on schizophrenia. These results suggest a robust bidirectional causal effect between schizophrenia and MDD. Patients with schizophrenia could benefit from the early and effective intervention of the Townsend deprivation index.

Causal associations of brain structure with bone mineral density: a large-scale genetic correlation study

In this study, we aimed to investigate the causal associations of brain structure with bone mineral density (BMD). Based on the genome-wide association study (GWAS) summary statistics of 1 325 brain imaging-derived phenotypes (BIDPs) of brain structure from the UK Biobank and GWAS summary datasets of 5 BMD locations, including the total body, femoral neck, lumbar spine, forearm, and heel from the GEFOS Consortium, linkage disequilibrium score regression (LDSC) was conducted to determine the genetic correlations, and Mendelian randomization (MR) was then performed to explore the causal relationship between the BIDPs and BMD. Several sensitivity analyses were performed to verify the strength and stability of the present MR outcomes. To increase confidence in our findings, we also performed confirmatory MR between BIDPs and osteoporosis. LDSC revealed that 1.93% of BIDPs, with a false discovery rate (FDR) < 0.01, were genetically correlated with BMD. Additionally, we observed that 1.31% of BIDPs exhibited a significant causal relationship with BMD (FDR < 0.01) through MR. Both the LDSC and MR results demonstrated that the BIDPs "Volume of normalized brain," "Volume of gray matter in Left Inferior Frontal Gyrus, pars opercularis," "Volume of Estimated Total Intra Cranial" and "Volume-ratio of brain segmentation/estimated total intracranial" had strong associations with BMD. Interestingly, our results showed that more left BIDPs were causally associated with BMD, especially within and around the left frontal region. In conclusion, a part of the brain structure causally influences BMD, which may provide important perspectives for the prevention of osteoporosis and offer valuable insights for further research on the brain-bone axis.