scholarly journals Causal associations of intelligence with schizophrenia and bipolar disorder: A Mendelian randomization analysis

2021 ◽  
Vol 64 (1) ◽  
Author(s):  
Kazutaka Ohi ◽  
Kentaro Takai ◽  
Ayumi Kuramitsu ◽  
Shunsuke Sugiyama ◽  
Midori Soda ◽  
...  

Abstract Background Intelligence is inversely associated with schizophrenia (SCZ) and bipolar disorder (BD); it remains unclear whether low intelligence is a cause or consequence. We investigated causal associations of intelligence with SCZ or BD risk and a shared risk between SCZ and BD and SCZ-specific risk. Methods To estimate putative causal associations, we performed multi-single nucleotide polymorphism (SNP) Mendelian randomization (MR) using generalized summary-data-based MR (GSMR). Summary-level datasets from five GWASs (intelligence, SCZ vs. control [CON], BD vs. CON, SCZ + BD vs. CON, and SCZ vs. BD; sample sizes of up to 269,867) were utilized. Results A strong bidirectional association between risks for SCZ and BD was observed (odds ratio; ORSCZ → BD = 1.47, p = 2.89 × 10−41, ORBD → SCZ = 1.44, p = 1.85 × 10−52). Low intelligence was bidirectionally associated with a high risk for SCZ, with a stronger effect of intelligence on SCZ risk (ORlower intelligence → SCZ = 1.62, p = 3.23 × 10−14) than the reverse (ORSCZ → lower intelligence = 1.06, p = 3.70 × 10−23). Furthermore, low intelligence affected a shared risk between SCZ and BD (OR lower intelligence → SCZ + BD = 1.23, p = 3.41 × 10−5) and SCZ-specific risk (ORlower intelligence → SCZvsBD = 1.64, p = 9.72 × 10−10); the shared risk (ORSCZ + BD → lower intelligence = 1.04, p = 3.09 × 10−14) but not SCZ-specific risk (ORSCZvsBD → lower intelligence = 1.00, p = 0.88) weakly affected low intelligence. Conversely, there was no significant causal association between intelligence and BD risk (p > 0.05). Conclusions These findings support observational studies showing that patients with SCZ display impairment in premorbid intelligence and intelligence decline. Moreover, a shared factor between SCZ and BD might contribute to impairment in premorbid intelligence and intelligence decline but SCZ-specific factors might be affected by impairment in premorbid intelligence. We suggest that patients with these genetic factors should be categorized as having a cognitive disorder SCZ or BD subtype.

Genes ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 772
Author(s):  
João Botelho ◽  
Vanessa Machado ◽  
José João Mendes ◽  
Paulo Mascarenhas

The latest evidence revealed a possible association between periodontitis and Parkinson’s disease (PD). We explored the causal relationship of this bidirectional association through two-sample Mendelian randomization (MR) in European ancestry populations. To this end, we used openly accessible data of genome-wide association studies (GWAS) on periodontitis and PD. As instrumental variables for periodontitis, seventeen single-nucleotide polymorphisms (SNPs) from a GWAS of periodontitis (1817 periodontitis cases vs. 2215 controls) and eight non-overlapping SNPs of periodontitis from an additional GWAS for validation purposes. Instrumental variables to explore for the reverse causation included forty-five SNPs from a GWAS of PD (20,184 cases and 397,324 controls). Multiple approaches of MR were carried-out. There was no evidence of genetic liability of periodontitis being associated with a higher risk of PD (B = −0.0003, Standard Error [SE] 0.0003, p = 0.26). The eight independent SNPs (B = −0.0000, SE 0.0001, p = 0.99) validated this outcome. We also found no association of genetically primed PD towards periodontitis (B = −0.0001, SE 0.0001, p = 0.19). These MR study findings do not support a bidirectional causal genetic liability between periodontitis and PD. Further GWAS studies are needed to confirm the consistency of these results.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kaitlyn M. Roman ◽  
Aaron K. Jenkins ◽  
David A. Lewis ◽  
David W. Volk

AbstractBipolar disorder and schizophrenia have multiple clinical and genetic features in common, including shared risk associated with overlapping susceptibility loci in immune-related genes. Higher activity of the nuclear factor-κB (NF-κB) transcription factor complex, which regulates the transcription of multiple immune markers, has been reported to contribute to immune activation in the prefrontal cortex in schizophrenia. These findings suggest the hypothesis that elevated NF-κB activity is present in the prefrontal cortex in bipolar disorder in a manner similar to that seen in schizophrenia. Therefore, we quantified levels of NF-κB-related mRNAs in the prefrontal cortex of 35 matched pairs of bipolar disorder and unaffected comparison subjects using quantitative PCR. We found that transcript levels were higher in the prefrontal cortex of bipolar disorder subjects for several NF-κB family members, NF-κB activation receptors, and NF-κB-regulated mRNAs, and were lower for an NF-κB inhibitor. Transcript levels for NF-κB family members, NF-κB activation receptors, and NF-κB-regulated mRNAs levels were also highly correlated with each other. This pattern of elevated transcript levels for NF-κB-related markers in bipolar disorder is similar to that previously reported in schizophrenia, suggesting that cortical immune activation is a shared pathophysiological feature between the two disorders.


2018 ◽  
Author(s):  
Amy E. Taylor ◽  
Rebecca C. Richmond ◽  
Teemu Palviainen ◽  
Anu Loukola ◽  
Jaakko Kaprio ◽  
...  

AbstractBackgroundGiven clear evidence that smoking lowers weight, it is possible that individuals with higher body mass index (BMI) smoke in order to lose or maintain their weight.Methods and FindingsWe undertook Mendelian randomization analyses using 97 genetic variants associated with BMI. We performed two sample Mendelian randomization analyses of the effects of BMI on smoking behaviour in UK Biobank (N=335,921) and the Tobacco and Genetics consortium genomewide association study (GWAS) (N≤74,035) respectively, and two sample Mendelian randomization analyses of the effects of BMI on cotinine levels (N≤4,548) and nicotine metabolite ratio (N≤1,518) in published GWAS, and smoking-related DNA methylation in the Avon Longitudinal Study of Parents and Children (N≤846).In inverse variance weighted Mendelian randomization analysis, there was evidence that higher BMI was causally associated with smoking initiation (OR for ever vs never smoking per one SD increase in BMI: 1.19, 95% CI: 1.11 to 1.27) and smoking heaviness (1.45 additional cigarettes smoked per day per SD increase in BMI, 95% CI: 1.03 to 1.86), but little evidence for a causal effect with smoking cessation. Results were broadly similar using pleiotropy robust methods (MR-Egger, median and weighted mode regression). These results were supported by evidence for a causal effect of BMI on DNA methylation at the aryl-hydrocarbon receptor repressor (AHRR) locus. There was no strong evidence that BMI was causally associated with cotinine, but suggestive evidence for a causal negative association with the nicotine metabolite ratio.ConclusionsThere is a causal bidirectional association between BMI and smoking, but the relationship is likely to be complex due to opposing effects on behaviour and metabolism. It may be useful to consider BMI and smoking together when designing prevention strategies to minimise the effects of these risk factors on health outcomes.


2019 ◽  
Vol 60 ◽  
pp. 79-85 ◽  
Author(s):  
Xue Gao ◽  
Ling-Xian Meng ◽  
Kai-Li Ma ◽  
Jie Liang ◽  
Hui Wang ◽  
...  

AbstractBackground:Several observational studies have investigated the association of insomnia with psychiatric disorders. Such studies yielded mixed results, and whether these associations are causal remains unclear. Thus, we aimed to identify the causal relationships between insomnia and five major psychiatric disorders.Methods:The analysis was implemented with six genome-wide association studies; one for insomnia and five for psychiatric disorders (attention-deficit/hyperactivity disorder, autism spectrum disorder, major depressive disorder, schizophrenia, and bipolar disorder). A heterogeneity in dependent instrument (HEIDI) approach was used to remove the pleiotropic instruments, Mendelian randomization (MR)-Egger regression was adopted to test the validity of the screened instruments, and bidirectional generalized summary data-based MR was performed to estimate the causal relationships between insomnia and these major psychiatric disorders.Results:We observed significant causal effects of insomnia on the risk of autism spectrum disorder and bipolar disorder, with odds ratios of 1.739 (95% confidence interval: 1.217–2.486, p = 0.002) and 1.786 (95% confidence interval: 1.396–2.285, p = 4.02 × 10−6), respectively. There was no convincing evidence of reverse causality for insomnia with these two disorders (p = 0.945 and 0.546, respectively). When insomnia was considered as either the exposure or outcome variable, causal estimates for the remaining three psychiatric disorders were not significant.Conclusions:Our results suggest a causal role of insomnia in autism spectrum disorder and bipolar disorder. Future disease models should include insomnia as a factor for these two disorders to develop effective interventions. More detailed mechanism studies may also be inspired by this causal inference.


2019 ◽  
Vol 29 ◽  
pp. S1319
Author(s):  
Claudia Pisanu ◽  
Nirmala Akula ◽  
Maria Del Zompo ◽  
Alessio Squassina ◽  
Francis J. McMahon

2020 ◽  
Vol 49 (3) ◽  
pp. 1057-1057
Author(s):  
Eleanor Sanderson ◽  
George Davey Smith ◽  
Frank Windmeijer ◽  
Jack Bowden

PLoS ONE ◽  
2017 ◽  
Vol 12 (2) ◽  
pp. e0171595 ◽  
Author(s):  
Andreas J. Forstner ◽  
Julian Hecker ◽  
Andrea Hofmann ◽  
Anna Maaser ◽  
Céline S. Reinbold ◽  
...  
Keyword(s):  

2018 ◽  
Vol 48 (3) ◽  
pp. 684-690 ◽  
Author(s):  
Wes Spiller ◽  
Neil M Davies ◽  
Tom M Palmer

Abstract Motivation In recent years, Mendelian randomization analysis using summary data from genome-wide association studies has become a popular approach for investigating causal relationships in epidemiology. The mrrobust Stata package implements several of the recently developed methods. Implementation mrrobust is freely available as a Stata package. General features The package includes inverse variance weighted estimation, as well as a range of median, modal and MR-Egger estimation methods. Using mrrobust, plots can be constructed visualizing each estimate either individually or simultaneously. The package also provides statistics such as IGX2, which are useful in assessing attenuation bias in causal estimates. Availability The software is freely available from GitHub [https://raw.github.com/remlapmot/mrrobust/master/].


2017 ◽  
Vol 36 (11) ◽  
pp. 1783-1802 ◽  
Author(s):  
Jack Bowden ◽  
Fabiola Del Greco M ◽  
Cosetta Minelli ◽  
George Davey Smith ◽  
Nuala Sheehan ◽  
...  

2020 ◽  
Author(s):  
Oskar Hougaard Jefsen ◽  
Maria Speed ◽  
Doug Speed ◽  
Søren Dinesen Østergaard

AbstractAimsCannabis use is associated with a number of psychiatric disorders, however the causal nature of these associations has been difficult to establish. Mendelian randomization (MR) offers a way to infer causality between exposures with known genetic predictors (genome-wide significant single nucleotide polymorphisms (SNPs)) and outcomes of interest. MR has previously been applied to investigate the relationship between lifetime cannabis use (having ever used cannabis) and schizophrenia, depression, and attention-deficit / hyperactivity disorder (ADHD), but not bipolar disorder, representing a gap in the literature.MethodsWe conducted a two-sample bidirectional MR study on the relationship between bipolar disorder and lifetime cannabis use. Genetic instruments (SNPs) were obtained from the summary statistics of recent large genome-wide association studies (GWAS). We conducted a two-sample bidirectional MR study on the relationship between bipolar disorder and lifetime cannabis use, using inverse-variance weighted regression, weighted median regression and Egger regression.ResultsGenetic liability to bipolar disorder was significantly associated with an increased risk of lifetime cannabis use: scaled log-odds ratio (standard deviation) = 0.0174 (0.039); P-value = 0.00001. Genetic liability to lifetime cannabis use showed no association with the risk of bipolar disorder: scaled log-odds ratio (standard deviation) = 0.168 (0.180); P-value = 0.351. The sensitivity analyses showed no evidence for pleiotropic effects.ConclusionsThe present study finds evidence for a causal effect of liability to bipolar disorder on the risk of using cannabis at least once. No evidence was found for a causal effect of liability to cannabis use on the risk of bipolar disorder. These findings add important new knowledge to the understanding of the complex relationship between cannabis use and psychiatric disorders.


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