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To assess the role of lithium treatment in the relationship between bipolar disorder (BD) and leukocyte telomere length (LTL). We compared LTL between 131 patients with BD, with or without a history of lithium treatment, and 336 controls. We tested the association between genetically determined LTL and BD in two large genome-wide association datasets. Patients with BD with a history lithium treatment showed longer LTL compared with never-treated patients (p = 0.015), and similar LTL compared with controls. Patients never treated with lithium showed shorter LTL compared with controls (p = 0.029). Mendelian randomization analysis showed no association between BD and genetically determined LTL. Our data support previous findings showing that long-term lithium treatment might protect against telomere shortening.

Abstract Context Observational studies indicated obesity and glutamatergic dysfunction as potential risk factors of depression, and reported disturbance of glutamine metabolism in obese state. However, it remains unclear whether the interrelationships between obesity, glutamine, and depression are causal. Objective We conducted 2-sample bidirectional mendelian randomization (MR) analyses to explore the causalities between circulating glutamine levels, specific depressive symptoms, major depressive disorder (MDD), and body mass index (BMI). Methods Univariable MR, multivariable MR (MVMR), and linkage disequilibrium score regression (LDSR) analyses were performed. Results Genetic downregulation of glutamine was causally associated with MDD, anhedonia, tiredness, and depressed mood at the false discovery rate (FDR)-controlled significance level (estimate, −0.036 ∼ −0.013; P = .005 to P = .050). Elevated BMI was causally linked to lower glutamine level (estimate, –0.103; P = .037), as well as more severe depressed mood, tiredness, and anhedonia (estimate, 0.017 ∼ 0.050; P < .001 to P = .040). In MVMR analysis, BMI was causally related to depressed mood dependently of glutamine levels. Conversely, it showed limited evidence supporting causal effects of depression on glutamine levels or BMI, except a causal association of tiredness with elevated BMI (estimate, 0.309; P = .003). LDSR estimates were directionally consistent with MR results. Conclusion The present study reported that higher BMI was causally associated with lower glutamine levels. Both obesity and downregulation of glutamine were causally linked to depression.

PCSK9-inhibitors (PCSK9i) are new drugs recently approved to lower LDL-cholesterol levels. However, due to the lack of long-term clinical data, the potential adverse effects of long-term use are still unknown. The PCSK9 genetic locus has been recently implicated in mood disorders and hence we wanted to assess if the effect of PCSK9i that block the PCSK9 protein can lead to an increase in the incidence of mood disorders. We used genetically-reduced PCSK9 protein levels (pQTLs) in plasma, serum, cerebrospinal fluid as a proxy for the effect of PCSK9i. We performed Mendelian randomization analyses using PCSK9 levels as exposure and mood disorder traits major depressive disorder, mood instability, and neuroticism score as outcomes. We find no association of PCSK9 levels with mood disorder traits in serum, plasma, and cerebrospinal fluid. We can conclude that genetically proxied on-target effect of pharmacological PCSK9 inhibition is unlikely to contribute to mood disorders.

Prescription of PCSK9-inhibitors has increased in recent years but not much is known about its off-target effects. PCSK9 -expression is evident in non-hepatic tissues, notably the brain, and genetic variation in the PCSK9 locus has recently been shown to be associated with mood disorder-related traits. We investigated whether PCSK9 inhibition, proxied by a genetic reduction in expression of PCSK9 mRNA, might have a causal adverse effect on mood disorder-related traits. We used genetic variants in the PCSK9 locus associated with reduced PCSK9 expression (eQTLs) in the European population from GTEx v8 and examined the effect on PCSK9 protein levels and three mood disorder-related traits (major depressive disorder, mood instability, and neuroticism), using summary statistics from the largest European ancestry genome-wide association studies. We conducted summary-based Mendelian randomization analyses to estimate the causal effects, and attempted replication using data from eQTLGen, Brain-eMETA, and the CAGE consortium. We found that genetically reduced PCSK9 gene-expression levels were significantly associated with reduced PCSK9 protein levels but not with increased risk of mood disorder-related traits. Further investigation of nearby genes demonstrated that reduced USP24 gene-expression levels was significantly associated with increased risk of mood instability (p-value range = 5.2x10 -5 –0.03), and neuroticism score (p-value range = 2.9x10 -5 –0.02), but not with PCSK9 protein levels. Our results suggest that genetic variation in this region acts on mood disorders through a PCSK9-independent pathway, and therefore PCSK9-inhibitors are unlikely to have an adverse impact on mood disorder-related traits.

Background Observational studies and diagnostic criteria have indicated that Attention Deficit Hyperactivity Disorder (ADHD) frequently comorbid with various psychiatric disorders. Therefore, we conducted a Mendelian randomization (MR) study to explore this potential genetic association between ADHD and six psychiatric disorders. Methods Using a two-sample Mendelian randomization (MR) design, this study systematically screened genetic instrumental variables (IVs) based on the genome-wide association studies (GWAS) of ADHD and six psychiatric disorders, with the inverse variance weighted (IVW) method as the primary approach. Results The study revealed a positive and causal association between ADHD and the risk of ASD, with an odds ratio (OR) of 2.328 (95%CI: 1.241–4.368) in the IVW MR analysis. Additionally, ADHD showed a positive causal effect on an increased risk of schizophrenia, with an OR of 1.867 (95%CI: 1.260–2.767) in the IVW MR analysis. However, no causal effect of Tic disorder, Mental retardation, Mood disorders and Anxiety disorder with ADHD was found in the analysis mentioned above. Conclusion Our MR analysis provides robust evidence of the causal role of ADHD in increasing the risk of ASD and schizophrenia. However, ADHD is not associated with the risk of Tic Disorder, Mental Retardation, Mood Disorders and Anxiety Disorder. This suggests the need for increased attention to the co-occurrence of ADHD-ASD or ADHD-schizophrenia and the implementation of timely intervention and treatment.

Background Glucagon-like peptide-1 receptor (GLP1R) agonists have gained attention for their role in diabetes treatment along with their diverse effects, such as appetite suppression, suggesting potential psychiatric benefits. This study aimed to assess the effect of GLP1R perturbation on mood disorders based on protein and biomarker levels using Mendelian randomization (MR) approach. Methods We conducted two-sample MR using summary statistics for GLP1R plasma levels ( n  = 3,301) from the INTERVAL study, glycated hemoglobin (HbA1c) levels ( n  = 128,610) from the Meta-Analyses of Glucose and Insulin-related traits Consortium, and bipolar disorder (BD: 371 cases/360,823 controls) and major depressive disorder (MDD: 776 cases/360,418 controls) incidences from the UK Biobank. Genetic variants associated with the plasma levels of GLP1R and HbA1c were used as proxies for the variation in GLP1R. Results GLP1R level was significantly associated with a reduced risk of MDD (odds ratio [OR] = 0·9988, 95% confidence interval [CI] = 0·9978-0·9999, P  = 0·0291) and of BD (OR = 0·9990, 95% CI = 0·9982-0·9998, P  = 0·0182). GLP1R’s HbA1c level-lowering effect was significantly associated with a decreased risk of BD (OR = 0·9786, 95% CI = 0·9613-0·9962, P  = 0·0175) but not with MDD. Conclusions GLP1R perturbation may have protective effects on MDD and BD through different mechanisms, although additional clinical trials are required to determine the therapeutic implications. Trial registration Clinical trial number not applicable.

The etiology of depression remains poorly understood. Changes in blood lipid levels were reported to be associated with depression and suicide, however study findings were mixed. We performed a two-sample Mendelian randomisation (MR) analysis to investigate the causal relationship between blood lipids and depression phenotypes, based on large-scale GWAS summary statistics (N = 188 577/480 359 for lipid/depression traits respectively). Five depression-related phenotypes were included, namely major depression (MD; from PGC), depressive symptoms (DS; from SSGAC), longest duration and number of episodes of low mood, and history of deliberate self-harm (DSH)/suicide (from UK Biobank). MR was conducted with inverse-variance weighted (MR-IVW), Egger and Generalised Summary-data-based MR (GSMR) methods. There was consistent evidence that triglyceride (TG) is causally associated with DS (MR-IVW β for one-s.d. increase in TG = 0.0346, 95% CI 0.0114-0.0578), supported by MR-IVW and GSMR and multiple r2 clumping thresholds. We also observed relatively consistent associations of TG with DSH/suicide (MR-Egger OR = 2.514, CI 1.579-4.003). There was moderate evidence for positive associations of TG with MD and the number of episodes of low mood. For HDL-c, we observed moderate evidence for causal associations with DS and MD. LDL-c and TC did not show robust causal relationships with depression phenotypes, except for weak evidence that LDL-c is inversely related to DSH/suicide. We did not detect significant associations when depression phenotypes were treated as exposures. This study provides evidence to a causal relationship between TG, and to a lesser extent, altered cholesterol levels with depression phenotypes. Further studies on its mechanistic basis and the effects of lipid-lowering therapies are warranted.

Background:Autoimmune thyroid disease (AITD) and major depressive disorder (MDD) are common genetic diseases. The comorbidity of AITD and MDD has been widely demonstrated by large amounts of epidemiological studies. However, the genetic architectures of the comorbidity remain unknown.Methods:We use large-scale GWAS summary data and novel genetic statistical methods to assess the genetic correlation and potential causality between AITD and MDD disorders. We perform cross-trait GWAS meta-analyses to identify genetic risk variants not previously associated with the individual traits. And we use summary-data-based mendelian randomisation to identify putative functional genes shared between diseases.Results:Both global and local genetic correlation study confirmed the genetic correlation of AITD and MDD. Through multi-trait analysis of GWAS (MTAG), we identified 112 SNPs associated with the conjoint phenotype, but not with individual traits. Mendelian randomisation confirmed the causal relationship between MDD (exposure) and AITD (outcome). The summary-based mendelian randomisation study found two plausible functional genes for AITD and MDD comorbidity.Conclusions:AITD and MDD are genetically correlated in global and local chromosomal regions. MR analyses support a putative casual effect of MDD on AITD risk, though residual pleiotropy or confounding cannot be fully excluded. These findings highlight the need for triangulation with experimental and longitudinal studies to confirm causality.

Observational studies have previously shown a potential link between psycho-emotional disorders, such as mood swings, highly strung, anxious feelings, and gastroesophageal reflux disease (GERD). However, the credibility of these associations could be influenced by various confounding factors. Consequently, our study sought to employ a Mendelian randomization (MR) approach to elucidate a potential causal relationship between psycho-emotional disorders and GERD. Information on independent genetic variants linked to mood swings, highly strung, and anxious feelings was gathered from European populations participating in the IEU Open GWAS research. The FinnGen Consortium provided the genome-wide association study (GWAS) summary statistics for GERD. Our analysis employed the inverse variance weighted (IVW) method under the random effects model as the main analytical method. To further bolster our findings, we employed the weighted median and MR Egger methods. In addition, we conducted a series of sensitivity analyses. Our study supports the existence of a causal relationship between psycho-emotional disorders and GERD. Mood swings, highly strung, and anxious feelings adversely affected GERD risk (mood swings: OR 2.21, 95% CI 1.19-5.59, p = 3.09 × 10-2; highly strung: OR 5.63, 95% CI 1.77-17.94, p = 3.42 × 10-3; anxious feelings: OR 2.48, 95% CI 1.08-4.33, p = 2.89 × 10-2). This Mendelian randomization study provides robust support for the notion that mood swings, highly strung and anxious feelings, are associated with an increased risk of developing GERD.

Background: Previous observational studies have shown that low back pain (LBP) often coexists with sleep disturbances, however, the causal relationship remains unclear. In the present study, the causal relationship between sleep disturbances and LBP was investigated and the importance of sleep improvement in the comprehensive management of LBP was emphasized. Methods: Genetic variants were extracted as instrumental variables (IVs) from the genome-wide association study (GWAS) of insomnia, sleep duration, short sleep duration, long sleep duration, and daytime sleepiness. Information regarding genetic variants in LBP was selected from a GWAS dataset and included 13,178 cases and 164,682 controls. MR-Egger, weighted median, inverse-variance weighted (IVW), penalized weighted median, and maximum likelihood (ML) were applied to assess the causal effects. Cochran’s Q test and MR-Egger intercept were performed to estimate the heterogeneity and horizontal pleiotropy, respectively. Outliers were identified and eliminated based on MR-PRESSO analysis to reduce the effect of horizontal pleiotropy on the results. Removing each genetic variant using the leave-one-out analysis can help evaluate the stability of results. Finally, the reverse causal inference involving five sleep traits was implemented. Results: A causal relationship was observed between insomnia-LBP (OR = 1.954, 95% CI: 1.119–3.411), LBP-daytime sleepiness (OR = 1.011, 95% CI: 1.004–1.017), and LBP-insomnia (OR = 1.015, 95% CI: 1.004–1.026), however, the results of bidirectional MR analysis between other sleep traits and LBP were negative. The results of most heterogeneity tests were stable and specific evidence was not found to support the disturbance of horizontal multiplicity. Only one outlier was identified based on MR-PRESSO analysis. Conclusion: The main results of our research showed a potential bidirectional causal association of genetically predicted insomnia with LBP. Sleep improvement may be important in comprehensive management of LBP.