Alcohol use, psychiatric disorders and gambling behaviors: A multi-sample study testing causal relationships via the co-twin control design.
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ABSTRACT:
SUBMITTER: Huggett SB
PROVIDER: S-EPMC7170180 | biostudies-literature | 2019 Jun
REPOSITORIES: biostudies-literature
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Project description:BackgroundObservational studies have suggested the potential associations between atopic dermatitis (AD) and psychiatric disorders. However, the causal relationship between them remains uncertain. This study aimed to evaluate the potential bidirectional causal relationship between AD and psychiatric disorders, including autism spectrum disorder (ASD), major depressive disorder (MDD), attention deficit hyperactivity disorder (ADHD), bipolar disorder (BD), anorexia nervosa (AN), Tourette syndrome (TS), schizophrenia, and anxiety.MethodsBidirectional two-sample Mendelian randomization (MR) was employed to elucidate the causality between AD and psychiatric disorders, using summary statistics from the most comprehensive genome-wide association studies conducted on AD (Ncases = 60,653, Ncontrols = 804,329). Psychiatric disorders were derived from the Psychiatric Genomics Consortium and were independent of AD data sources. The MR analysis entailed the implementation of multiple methods, including the inverse variance weighted method, MR-Egger regression method, weighted median method, simple mode method, and weighted mode method.ResultsBidirectional two-sample MR analysis uncovered significant causal associations between AD and severe psychiatric disorders. Specifically, liability to AD was associated with increased risk of ADHD (OR = 1.116; 95% CI: [1.009, 1.234]; P = 0.033) and ASD (OR = 1.131; 95% CI: [1.023, 1.251]; P = 0.016). Additionally, evidence suggested that liability to ADHD (OR = 1.112; 95% CI: [1.094, 1.130]; P = 9.20e-40), liability to AN (OR = 1.1; 95% CI: [1.068, 1.134]; P = 4.45e-10) and liability to BD (OR = 1.067; 95% CI: [1.009, 1.128]; P = 0.023) were associated with an increased risk of AD. Only the causal association between AD and ASD was independent of the reverse effect bias. These causal associations were robust and not affected by biases of heterogeneity and horizontal pleiotropy.ConclusionsOur study emphasizes the significant causal association between AD and an increased risk of ASD, and also identifying BD and AN as risk factors for AD.
| S-EPMC10763185 | biostudies-literature
Project description:BackgroundThis study aims to explore the relationship between psychiatric disorders and the risk of epilepsy using Mendelian randomization (MR) analysis.MethodsWe collected summary statistics of seven psychiatric traits from recent largest genome-wide association study (GWAS), including major depressive disorder (MDD), anxiety disorder, autism spectrum disorder (ASD), bipolar disorder (BIP), attention deficit hyperactivity disorder (ADHD), schizophrenia (SCZ), and insomnia. Then, MR analysis estimates were performed based on International League Against Epilepsy (ILAE) consortium data (ncase = 15,212 and ncontrol = 29,677), the results of which were subsequently validated in FinnGen consortium (ncase = 6260 and ncontrol = 176,107). Finally, a meta-analysis was conducted based on the ILAE and FinnGen data.ResultsWe found significant causal effects of MDD and ADHD on epilepsy in the meta-analysis of the ILAE and FinnGen, with corresponding odds ratios (OR) of 1.20 (95% CI 1.08-1.34, p = .001) and 1.08 (95% CI 1.01-1.16, p = .020) by the inverse-variance weighted (IVW) method respectively. MDD increases the risk of focal epilepsy while ADHD has a risk effect on generalized epilepsy. No reliable evidence regarding causal effects of other psychiatric traits on epilepsy was identified.ConclusionsThis study suggests that major depressive disorder and attention deficit hyperactivity disorder may causally increase the risk of epilepsy.
| S-EPMC10097067 | biostudies-literature
Project description:Importance:Psychiatric traits associated with categorically defined psychiatric disorders are heritable and present to varying degrees in the general population. It is commonly assumed that diagnoses represent the extreme end of continuously distributed traits in the population, but this assumption has yet to be robustly tested for many psychiatric phenotypes. Objective:To assess whether genetic risk factors associated with psychiatric disorders are also associated with continuous variation in milder population traits. Design, Setting, and Participants:This study combined a novel twin analytic approach with polygenic risk score (PRS) analyses in a large population-based twin sample. Phenotypic and genetic data were available from the Child and Adolescent Twin Study in Sweden. Inpatient data were available for January 1, 1987, to December 31, 2014, and outpatient data for January 1, 2001, to December 31, 2013. The last day of follow-up was December 31, 2014. Data analysis was performed from January 1, 2017, to September 30, 2017. Main Outcomes and Measures:Questionnaires that assessed traits of autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), learning difficulties, tic disorders (TDs), obsessive-compulsive disorder (OCD), anxiety, major depressive disorder (MDD), mania, and psychotic experiences were administered to a large Swedish twin sample. Individuals with clinical psychiatric diagnoses were identified using the Swedish National Patient Register. Joint categorical/continuous twin modeling was used to estimate genetic correlations between psychiatric diagnoses and continuous traits. The PRSs for psychiatric disorders were calculated based on independent discovery genetic data. The association between PRSs for each disorder and associated continuous traits was tested. Results:Phenotype data were available for 13 923 twin pairs (35.1% opposite sex and 31.7% same-sex females) at 9 years of age, 5165 pairs (36.9% opposite sex and 34.0% same-sex females) at 15 years of age, and 4273 pairs (36.5% opposite sex and 34.4% same-sex females) at 18 years of age. Genetic data were available for 13 412 individuals (50.2% females). Twin genetic correlations between numerous psychiatric diagnoses and corresponding traits ranged from 0.31 to 0.69. Disorder PRSs were associated with related population traits for ASD (β [SE] = 0.04 [0.01] at 9 years of age), ADHD (β [SE] = 0.27 [0.03] at 9 years of age), TDs (β [SE] = 0.02 [0.004] at 9 years of age), OCD (β [SE] = 0.13 [0.05] at 18 years of age), anxiety (β [SE] = 0.18 [0.08] at 9 years of age; β [SE] = 0.07 [0.02] at 15 years of age; and β [SE] = 0.40 [0.17] at 18 years of age), MDD (β [SE] = 0.10 [0.03] at 9 years of age; β [SE] = 0.11 [0.02] at 15 years of age; and β [SE] = 0.41 [0.10] at 18 years of age), and schizophrenia (β [SE] = 0.02 [0.01] at 18 years of age). Polygenic risk scores for depressive symptoms were associated with MDD diagnoses (odds ratio, 1.16; 95% CI, 1.02-1.32). Conclusions and Relevance:These results suggest that genetic factors associated with psychiatric disorders are also associated with milder variation in characteristic traits throughout the general population for many psychiatric phenotypes. This study suggests that many psychiatric disorders are likely to be continuous phenotypes rather than the categorical entities currently defined in diagnostic manuals, which has strong implications for genetic research in particular.
| S-EPMC6439816 | biostudies-other
Project description:BackgroundWhether the positive associations of blood lipids with psychiatric disorders are causal is uncertain. We conducted this two-sample Mendelian randomization (MR) analysis to comprehensively investigate associations of blood lipids with psychiatric disorders.MethodsUnivariable and multivariable models were established for MR analyses. Inverse variance-weighted (IVW) MR was employed as the main approach; weighted median and MR-Egger were used as sensitivity analysis methods. The possibility of violating MR assumptions was evaluated utilizing several sensitivity analyses, including heterogeneity statistics, horizontal pleiotropy statistics, single SNP analysis, leave-one-out analysis and MR-PRESSO analysis. As instrumental variables, we screened 362 independent single-nucleotide polymorphisms (SNP) related to blood lipids from a recent genome-wide association study involving 76,627 individuals of European ancestry, with a genome-wide significance level of p < 5 × 10- 8. Summary-level information for the six psychiatric disorders was extracted from Psychiatric Genomics Consortium and Alzheimer Disease Genetics Consortium.ResultsWe observed eight significant associations in univariable MR analysis, four of which were corroborated by multivariable MR (MVMR) analysis modified for the other three lipid traits: high-density lipoprotein cholesterol (HDL-C) level with the risk of PTSD (OR = 0.91, 95% CI = 0.85-0.97, p = 0.002) and AD (OR = 0.79, 95% CI = 0.71-0.88, p < 0.001) and triglycerides (TG) level with the risk of MDD (OR = 1.02, 95% CI = 1.003-1.03, p = 0.01) and panic disorder (OR = 0.83, 95% CI = 0.74-0.92, p < 0.001). In addition, four associations were not significant in MVMR analysis after adjustment for three lipid traits: total cholesterol (TC) level with the risk of PTSD, low-density lipoprotein cholesterol (LDL-C) level with the risk of MDD and AD and TG level with the risk of AD.ConclusionsOur results show that blood lipids and psychiatric disorders may be related in a causal manner. This shows that abnormal blood lipid levels may act as reliable biomarker of psychiatric disorders and as suitable targets for their prevention and treatment.
| S-EPMC10585856 | biostudies-literature
Project description:BackgroundThe question of whether a correlation exists between migraine and five psychiatric disorders, including posttraumatic stress disorder (PTSD), major depressive disorder (MDD), anorexia nervosa (AN), bipolar disorder (BIP), and schizophrenia (SCZ), remains a matter of controversy. Hence, this research aims to investigate whether there is a possible association between migraine and five psychiatric disorders.MethodsWe performed a bidirectional 2-sample Mendelian randomization (MR) analysis to assess the causality between migraine and five psychiatric disorders. Genetic associations of PTSD, MDD, AN, BIP, and SCZ were obtained from the Psychiatric Genomics Consortium (PGC) database and genetic associations of migraine with aura and migraine without aura were obtained from the FinnGen dataset. We used the inverse-variance weighted (IVW), weighted median, weighted mode, MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and MR Egger regression methods to evaluate the association of genetically predicted exposure with the risk of outcome.ResultsMR demonstrated that MDD was associated with a high risk of migraine without aura (OR = 1.930578, 95% confidence interview (CI): 1.224510, 3.043550, p < 0.05), but BIP was related to a low risk of migraine without aura (OR = 0.758650, 95%CI: 0.639601, 0.899858, p < 0.05). According to the results of reverse MR, migraine with aura was associated with a high risk of BIP (OR = 1.019100, 95%CI: 1.002538, 1.035935, p < 0.05), and migraine without aura was associated with an increased risk of AN (OR = 1.055634, 95%CI: 1.023859, 1.088394, p < 0.05).ConclusionOur results provide evidence of the potential causal association between migraine and some psychiatric disorders. It may contribute to the prevention of migraine and some psychiatric disorders.
| S-EPMC11330824 | biostudies-literature
Project description:Background Despite psychiatric traits were associated with intracranial aneurysms (IAs) in observational studies, their causal relationships remain largely undefined. We aimed to assess the causality between psychiatric traits and IAs. Methods We firstly collected the genome-wide association statistics of IAs (sample size, n = 79,429) and ten psychiatric traits from Europeans, including insomnia (n = 1,331,010), mood instability (n = 363,705), anxiety disorder (n = 83,566), major depressive disorder (MDD) (n = 480,359), subjective wellbeing (n = 388,538), attention deficit/hyperactivity disorder (ADHD) (n = 53,293), autism spectrum disorder (ASD) (n = 46,350), bipolar disorder (BIP) (n = 51,710), schizophrenia (SCZ) (n = 105,318), and neuroticism (n = 168,105). We then conducted a series of bi-directional two-sample Mendelian randomization (MR) analyses, of which the Robust Adjusted Profile Score (RAPS) was the primary method to estimate the causal effects between these psychiatric traits and IAs. Results We found that insomnia exhibited a significant risk effect on IAs with the odds ratio (OR) being 1.22 (95% CI: 1.11-1.34, p = 4.61 × 10-5) from the RAPS method. There was suggestive evidence for risk effect of mood instability on IAs (RAPS, OR = 4.16, 95% CI: 1.02-17.00, p = 0.047). However, no clear evidence of causal effects on IAs for the rest eight psychiatric traits (anxiety disorder, MDD, subjective wellbeing, ADHD, ASD, BIP, SCZ, and neuroticism) was identified. In the reverse MR analyses, no causal effects of IAs on psychiatric traits were found. Conclusions Our findings provide strong evidence for a causal risk effect of insomnia on IAs and suggestive evidence for mood instability as a causal risk effect on IAs. These results could inform the prevention and clinical intervention of IAs.
| S-EPMC8560679 | biostudies-literature
Project description:IntroductionSleep is associated with psychiatric disorders. However, their causality remains unknown.MethodsThe study explored the causal relationship between seven sleep parameters (sleep duration, insomnia, sleep apnea, chronotype, daytime dozing, napping during the day, and snoring) and three psychiatric disorders including major depressive disorder (MDD), schizophrenia, and attention-deficit/hyperactivity disorder (ADHD) using two-sample Mendelian randomization (MR). Genome-wide association study (GWAS) summary data for sleep parameters were obtained from the United Kingdom biobank, FinnGen biobank, and EBI databases. MR-Egger, weighted median, inverse-variance weighted (IVW), simple mode, weighted mode, maximum likelihood, penalized weighted median, and IVW(fixed effects) were used to perform the MR analysis. The heterogeneity was detected by Cochran's Q statistic. The horizontal pleiotropy was detected by MR Egger. The sensitivity was investigated by the leave-one-out analysis.ResultsInsomnia (OR = 2.02, 95%CI = 1.34-3.03, p = 0.001, False-discovery rate (FDR) corrected p-value = 0.011) and napping during the day (OR = 1.81, 95%CI = 1.34-2.44, FDR corrected p-value<0.001) were associated with an increased risk of MDD. Longer sleep duration (OR = 2.20, 95%CI = 1.24-3.90, FDR corrected p-value = 0.049) had an association with the increased risk of schizophrenia, while daytime dozing (OR = 4.44, 95%CI = 1.20-16.41, corrected p-value = 0.088)and napping during the day (OR = 2.11, 95%CI = 1.11-4.02, FDR corrected p-value = 0.088) had a suggestive association with an increased risk of schizophrenia. Longer sleep duration had a suggestive association with a decreased risk of ADHD (OR = 0.66, 95%CI = 0.42-0.93, FDR corrected p-value = 0.088).ConclusionThis study provides further evidence for a complex relationship between sleep and psychiatric disorders. Our findings highlight the potential benefits of addressing sleep problems in the prevention of psychiatric disorders.
| S-EPMC11215123 | biostudies-literature
Project description:Smoking is associated with more severe/extensive gambling in adults. The purpose of this study was to examine relationships between smoking and gambling in adolescents.Analyses utilized survey data from 1591 Connecticut high-school students. Adolescents were classified by gambling (Low-Risk Gambling [LRG], At Risk/Problem Gambling [ARPG]) and smoking (current smoker, non-smoker). The main effects of smoking and the smoking-by-gambling interactions were examined for gambling behaviors (e.g., type, location), and gambling attitudes. Data were analyzed using chi-square and logistic regression; the latter controlled for gender, race/ethnicity, grade, and family structure.For APRG adolescents, smoking was associated with greater online, school, and casino gambling; gambling due to anxiety and pressure; greater time spent gambling; early gambling onset; perceived parental approval of gambling; and decreased importance of measures to prevent teen gambling. For LRG adolescents, smoking was associated with non-strategic gambling (e.g., lottery gambling); school gambling; gambling in response to anxiety; gambling for financial reasons; greater time spent gambling; and decreased importance of measures to prevent teen gambling. Stronger relationships were found between smoking and casino gambling, gambling due to pressure, earlier onset of gambling, and parental perceptions of gambling for ARPG versus LRG adolescents.Smoking is associated with more extensive gambling for both low- and high-risk adolescent gamblers.Smoking may be a marker of more severe gambling behaviors in adolescents and important to consider in gambling prevention and intervention efforts with youth.
| S-EPMC4439395 | biostudies-literature
Project description:IntroductionSuicidal thoughts and behaviors have partially distinct genetic etiologies.MethodsWe used PRS-CS to create polygenic risk scores (PRSs) from GWAS of non-suicidal self-injury, broad-sense self-harm ideation, nonfatal suicide attempt, death by suicide, and depression. Using mixed-effect models, we estimated whether these PRSs were associated with a range of suicidal thoughts and behaviors in the Collaborative Study on the Genetics of Alcoholism (N = 7,526).ResultsAll PRSs were significantly associated with suicidal ideation and suicide attempt (betas = 0.08-0.44, false discovery rate [FDR] <0.023). All PRSs except non-suicidal self-injury PRS were associated with active suicidal ideation (betas = 0.14-0.22, FDR <0.003). Several associations remained significant in models where all significant PRSs were included as simultaneous predictors, and when all PRSs predicted suicide attempt, the PRS together explained 6.2% of the variance in suicide attempt. Significant associations were also observed between some PRSs and persistent suicidal ideation, non-suicidal self-injury, compounded suicide attempt, and desire to die.ConclusionOur findings suggest that PRS for depression does not explain the entirety of the variance in suicidal thoughts and behaviors, with PRS specifically for suicidal thoughts and behaviors making additional and sometimes unique contributions.
| S-EPMC10697665 | biostudies-literature
Project description:Little is known about the association between problem-gambling severity and psychiatric disorders among American-Indian/Alaska-Native (AI/AN) individuals. Thus, we examined these factors among a nationally representative sample of AI/AN and other American adults in the USA.Using the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) data, we conducted separate Wald tests and multinomial logistic regression analyses comparing AI/AN to black/African American, white/Caucasian, and all other racial/ethnic groups, respectively.Relative to other American adults, AI/AN adults were least likely to report non-/low-frequency gambling (NG: AI/AN 66.5%, white/Caucasian 70.5%, black/African American 72.8%, other racial/ethnic group 72.3%) and most likely to report low-risk gambling (LRG: AI/AN 30.1%, white/Caucasian 26.5%, black/African American 23.4%, other racial/ethnic group 24.7%). The association between at-risk/problem-gambling (ARPG) and any past-year Axis-I disorder was stronger among AI/AN versus other American adults. Although ARPG and LRG were associated with multiple past-year Axis-I and lifetime Axis-II psychiatric disorders in both AI/AN and other American adults, LRG was more strongly associated with both Axis-I disorders (particularly major depression, generalized anxiety disorder and nicotine dependence) and Cluster-B Axis-II (particularly antisocial personality disorder) disorders in AI/AN versus other American adults.A stronger association between problem-gambling severity and past-year psychiatric disorders among AI/AN relative to other American adults suggests the importance of enhancing mental health and problem-gambling prevention and treatment strategies that may help AI/AN individuals.
| S-EPMC4744487 | biostudies-literature