Exploring the influences of education,intelligence and income on mental disorders

Background Previous studies have shown that educational attainment(EA),intelligence and income are key factors associated with mental disorders.However,the direct effects of each factor on major mental disorders are unclear.Aims We aimed to evaluate the overall and independent causal effects of the three psychosocial factors on common mental disorders.Methods Using genome-wide association study summary datasets,we performed Mendelian randomisation(MR)and multivariable MR(MVMR)analyses to assess potential associations between the 3 factors(EA,N=766345;household income,N=392422;intelligence,N=146808)and 13 common mental disorders,with sample sizes ranging from 9907 to 807553.Inverse-variance weighting was employed as the main method in the MR analysis.Results Our MR analysis showed that(1)higher EA was a protective factor for eight mental disorders but contributed to anorexia nervosa,obsessive-compulsive disorder(OCD),bipolar disorder(BD)and autism spectrum disorder(ASD);(2)higher intelligence was a protective factor for five mental disorders but a risk factor for OCD and ASD;(3)higher household income protected against 10 mental disorders but confers risk for anorexia nervosa.Our MVMR analysis showed that(1)higher EA was a direct protective factor for attention-deficit/hyperactivity disorder(ADHD)and insomnia but a direct risk factor for schizophrenia,BD and ASD;(2)higher intelligence was a direct protective factor for schizophrenia but a direct risk factor for major depressive disorder(MDD)and ASD;(3)higher income was a direct protective factor for seven mental disorders,including schizophrenia,BD,MDD,ASD,post-traumatic stress disorder,ADHD and anxiety disorder.Conclusions Our study reveals that education,intelligence and income intertwine with each other.For each factor,its independent effects on mental disorders present a more complex picture than its overall effects.

Causal associations between major depressive disorder and COVID-19

Background We aimed to evaluate whether major depressive disorder(MDD)could aggravate the outcomes of coronavirus disease 2019(COVID-19)or whether the genetic liability to COVID-19 could trigger MDD.Aims We aimed to assess bidirectional causal associations between MDD and COVID-19.Methods We performed genetic correlation and Mendelian randomisation(MR)analyses to assess potential associations between MDD and three COVID-19 outcomes.Literature-based network analysis was conducted to construct molecular pathways connecting MDD and COVID-19.Results We found that MDD has positive genetic correlations with COVID-19 outcomes(rg:0.10–0.15).Our MR analysis indicated that genetic liability to MDD is associated with increased risks of COVID-19 infection(odds ratio(OR)=1.05,95%confidence interval(CI):1.00 to 1.10,p=0.039).However,genetic liability to the three COVID-19 outcomes did not confer any causal effects on MDD.Pathway analysis identified a panel of immunity-related genes that may mediate the links between MDD and COVID-19.Conclusions Our study suggests that MDD may increase the susceptibility to COVID-19.Our findings emphasise the need to increase social support and improve mental health intervention networks for people with mood disorders during the pandemic.

Shared genetics and bidirectional causal relationships between type 2 diabetes and attention-deficit/hyperactivity disorder

Background Type 2 diabetes(T2D)is a chronic metabolic disorder with high comorbidity with mental disorders.The genetic links between attention-deficit/hyperactivity disorder(ADHD)and T2D have yet to be elucidated.Aims We aim to assess shared genetics and potential associations between ADHD and T2D.Methods We performed genetic correlation,two-sample Mendelian randomisation and polygenic overlap analyses between ADHD and T2D.The genome-wide association study(GWAS)summary results of T2D(80154 cases and 853816 controls),ADHD2019(20183 cases and 35191 controls from the 2019 GWAS ADHD dataset)and ADHD2022(38691 cases and 275986 controls from the 2022 GWAS ADHD dataset)were used for the analyses.The T2D dataset was obtained from the DIAGRAM Consortium.The ADHD datasets were obtained from the Psychiatric Genomics Consortium.We compared genome-wide association signals to reveal shared genetic variation between T2D and ADHD using the larger ADHD2022 dataset.Moreover,molecular pathways were constructed based on large-scale literature data to understand the connection between ADHD and T2D.Results T2D has positive genetic correlations with ADHD2019(rg=0.33)and ADHD2022(rg=0.31).Genetic liability to ADHD2019 was associated with an increased risk for T2D(odds ratio(OR):1.30,p<0.001),while genetic liability to ADHD2022 had a suggestive causal effect on T2D(OR:1.30,p=0.086).Genetic liability to T2D was associated with a higher risk for ADHD2019(OR:1.05,p=0.001)and ADHD2022(OR:1.03,p<0.001).The polygenic overlap analysis showed that most causal variants of T2D are shared with ADHD2022.T2D and ADHD2022 have three overlapping loci.Molecular pathway analysis suggests that ADHD and T2D could promote the risk of each other through inflammatory pathways.Conclusions Our study demonstrates substantial shared genetics and bidirectional causal associations between ADHD and T2D.

Altered asymmetries of resting-state MRI in the left thalamus of first-episode schizophrenia

Background:Schizophrenia(SCZ)is a complex psychiatric disorder associated with widespread alterations in the subcortical brain structure.Hemispheric asymmetries are a fundamental organizational principle of the human brain and relate to human psychological and behavioral characteristics.We aimed to explore the state of thalamic lateralization of SCZ.Methods:We used voxel-based morphometry(VBM)analysis,whole-brain analysis of low-frequency fluctuations(ALFF),fractional amplitude of low-frequency fluctuations(fALFF),and resting-state seed-based functional connectivity(FC)analysis to investigate brain structural and functional deficits in SCZ.Also,we applied Pearson’’s correlation analysis to validate the correlation between Positive and Negative Symptom Scale(PANSS)scores and them.Results:Compared with healthy controls,SCZ showed increased gray matter volume(GMV)of the left thalamus(t=2.214,p=0.029),which positively correlated with general psychosis(r=0.423,p=0.010).SCZ also showed increased ALFF in the putamen,the caudate nucleus,the thalamus,fALFF in the nucleus accumbens(NAc),and the caudate nucleus,and decreased fALFF in the precuneus.The left thalamus showed significantly weaker resting-state FC with the amygdala and insula in SCZ.PANSS negative symptom scores were negatively correlated with the resting-state FC between the thalamus and the insula(r=-0.414,p=0.025).Conclusions:Collectively,these results suggest the possibility of aberrant laterality in the left thalamus and its FC with other related brain regions involved in the limbic system.