Author Correction: GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability

Causal relationship between addictive behaviors and epilepsy risk: A mendelian randomization study

BACKGROUND

Previous studies have reported inconsistent results regarding the potential relationships between addictive behaviors and the risk of epilepsy.

OBJECTIVE

To assess whether genetically predicted addictive behaviors are causally associated with the risk of epilepsy outcomes.

METHODS

The causation between five addictive behaviors (including cigarettes per day, alcoholic drinks per week, tea intake, coffee intake, and lifetime cannabis use) and epilepsy was evaluated by using a two-sample Mendelian Randomization (MR) analysis. The inverse-variance weighted (IVW) method was used as the primary outcome. The other MR analysis methods (MR Egger, weighted median, simulation extrapolation corrected MR-Egger, and Mendelian Randomization Pleiotropy Residual Sum and Outlier (MR-PRESSO)) were performed to complement IVW. In addition, the robustness of the MR analysis results was assessed by leave-one-out analysis.

RESULTS

The IVW analysis method indicated an approximately 20% increased risk of epilepsy per standard deviation increase in lifetime cannabis use (odds ratio [OR], 1.20; 95% confidence interval [CI]), 1.02-1.42, P = 0.028). However, there is no causal association between the other four addictive behaviors and the risk of epilepsy (cigarettes per day: OR, 1.04; 95% CI, 0.92-1.18, P = 0.53; alcoholic drinks per week: OR, 1.31; 95% CI, 0.93-1.84, P = 0.13; tea intake: OR, 1.15; 95% CI, 0.84-1.56, P = 0.39; coffee intake: OR, 0.86; 95% CI, 0.59-1.23, P = 0.41). The other MR analysis methods and further leave-one-out sensitivity analysis suggested the results were robust.

CONCLUSION

This MR study indicated a potential genetically predicted causal association between lifetime cannabis use and higher risk of epilepsy. As for the other four addictive behaviors, no evidence of a causal relationship with the risk of epilepsy was found in this study.

Lower-Risk Cannabis Use Guidelines (LRCUG) for reducing health harms from non-medical cannabis use: A comprehensive evidence and recommendations update

BACKGROUND

Cannabis use is common, especially among young people, and is associated with risks for various health harms. Some jurisdictions have recently moved to legalization/regulation pursuing public health goals. Evidence-based 'Lower Risk Cannabis Use Guidelines' (LRCUG) and recommendations were previously developed to reduce modifiable risk factors of cannabis-related adverse health outcomes; related evidence has evolved substantially since. We aimed to review new scientific evidence and to develop comprehensively up-to-date LRCUG, including their recommendations, on this evidence basis.

METHODS

Targeted searches for literature (since 2016) on main risk factors for cannabis-related adverse health outcomes modifiable by the user-individual were conducted. Topical areas were informed by previous LRCUG content and expanded upon current evidence. Searches preferentially focused on systematic reviews, supplemented by key individual studies. The review results were evidence-graded, topically organized and narratively summarized; recommendations were developed through an iterative scientific expert consensus development process.

RESULTS

A substantial body of modifiable risk factors for cannabis use-related health harms were identified with varying evidence quality. Twelve substantive recommendation clusters and three precautionary statements were developed. In general, current evidence suggests that individuals can substantially reduce their risk for adverse health outcomes if they delay the onset of cannabis use until after adolescence, avoid the use of high-potency (THC) cannabis products and high-frequency/-intensity of use, and refrain from smoking-routes for administration. While young people are particularly vulnerable to cannabis-related harms, other sub-groups (e.g., pregnant women, drivers, older adults, those with co-morbidities) are advised to exercise particular caution with use-related risks. Legal/regulated cannabis products should be used where possible.

CONCLUSIONS

Cannabis use can result in adverse health outcomes, mostly among sub-groups with higher-risk use. Reducing the risk factors identified can help to reduce health harms from use. The LRCUG offer one targeted intervention component within a comprehensive public health approach for cannabis use. They require effective audience-tailoring and dissemination, regular updating as new evidence become available, and should be evaluated for their impact.

Smoking is significantly associated with increased risk of COVID-19 and other respiratory infections

Observational studies suggest smoking, cannabis use, alcohol consumption, and substance use disorders (SUDs) may impact risk for respiratory infections, including coronavirus 2019 (COVID-2019). However, causal inference is challenging due to comorbid substance use. Using summary-level European ancestry data (>1.7 million participants), we performed single-variable and multivariable Mendelian randomization (MR) to evaluate relationships between substance use behaviors, COVID-19 and other respiratory infections. Genetic liability for smoking demonstrated the strongest associations with COVID-19 infection risk, including the risk for very severe respiratory confirmed COVID-19 (odds ratio (OR) = 2.69, 95% CI, 1.42, 5.10, P-value = 0.002), and COVID-19 infections requiring hospitalization (OR = 3.49, 95% CI, 2.23, 5.44, P-value = 3.74 × 10-8); these associations generally remained robust in models accounting for other substance use and cardiometabolic risk factors. Smoking was also strongly associated with increased risk of other respiratory infections, including asthma-related pneumonia/sepsis (OR = 3.64, 95% CI, 2.16, 6.11, P-value = 1.07 × 10-6), chronic lower respiratory diseases (OR = 2.29, 95% CI, 1.80, 2.91, P-value = 1.69 × 10-11), and bacterial pneumonia (OR = 2.14, 95% CI, 1.42, 3.24, P-value = 2.84 × 10-4). We provide strong genetic evidence showing smoking increases the risk for COVID-19 and other respiratory infections even after accounting for other substance use behaviors and cardiometabolic diseases, which suggests that prevention programs aimed at reducing smoking may be important for the COVID-19 pandemic and have substantial public health benefits.

Transcriptional Alterations in Dorsolateral Prefrontal Cortex and Nucleus Accumbens Implicate Neuroinflammation and Synaptic Remodeling in Opioid Use Disorder

BACKGROUND

Prevalence rates of opioid use disorder (OUD) have increased dramatically, accompanied by a surge of overdose deaths. While opioid dependence has been extensively studied in preclinical models, an understanding of the biological alterations that occur in the brains of people who chronically use opioids and who are diagnosed with OUD remains limited. To address this limitation, RNA sequencing was conducted on the dorsolateral prefrontal cortex and nucleus accumbens, regions heavily implicated in OUD, from postmortem brains in subjects with OUD.

METHODS

We performed RNA sequencing on the dorsolateral prefrontal cortex and nucleus accumbens from unaffected comparison subjects (n = 20) and subjects diagnosed with OUD (n = 20). Our transcriptomic analyses identified differentially expressed transcripts and investigated the transcriptional coherence between brain regions using rank-rank hypergeometric orderlap. Weighted gene coexpression analyses identified OUD-specific modules and gene networks. Integrative analyses between differentially expressed transcripts and genome-wide association study datasets using linkage disequilibrium scores assessed the genetic liability of psychiatric-related phenotypes in OUD.

RESULTS

Rank-rank hypergeometric overlap analyses revealed extensive overlap in transcripts between the dorsolateral prefrontal cortex and nucleus accumbens in OUD, related to synaptic remodeling and neuroinflammation. Identified transcripts were enriched for factors that control proinflammatory cytokine, chondroitin sulfate, and extracellular matrix signaling. Cell-type deconvolution implicated a role for microglia as a potential driver for opioid-induced neuroplasticity. Linkage disequilibrium score analysis suggested genetic liabilities for risky behavior, attention-deficit/hyperactivity disorder, and depression in subjects with OUD.

CONCLUSIONS

Overall, our findings suggest connections between the brain's immune system and opioid dependence in the human brain.

Association Between Environmental Factors and Asthma Using Mendelian Randomization: Increased Effect of Body Mass Index on Adult-Onset Moderate-to-Severe Asthma Subtypes

Although asthma is one of the most common chronic diseases throughout all age groups, its etiology remains unknown, primarily due to its heterogeneous characteristics. We examined the causal effects of various environmental factors on asthma using Mendelian randomization and determined whether the susceptibility to asthma due to the causal effect of a risk factor differs between asthma subtypes, based on age of onset, severity of asthma, and sex. We performed Mendelian randomization analyses (inverse variance weighted, weighted median, and generalized summary-data-based Mendelian randomization) using UK Biobank data to estimate the causal effects of 69 environmental factors on asthma. Additional sensitivity analyses (MR-Egger regression, Cochran’s Q test, clumping, and reverse Mendelian randomization) were performed to ensure minimal or no pleiotropy. For confirmation, two-sample setting analyses were replicated using BMI SNPs that had been reported by a meta-genome-wide association study in Japanese and European (GIANT) populations and a genome-wide association study in control individuals from the UK Biobank. We found that BMI causally affects the development of asthma and that the adult-onset moderate-to-severe asthma subtype is the most susceptible to causal inference by BMI. Further, it is likely that the female subtype is more susceptible to BMI than males among adult asthma cases. Our findings provide evidence that obesity is a considerable risk factor in asthma patients, particularly in adult-onset moderate-to-severe asthma cases, and that weight loss is beneficial for reducing the burden of asthma.

Heterogeneity and Polygenicity in Psychiatric Disorders: A Genome-Wide Perspective

Genome-wide association studies (GWAS) have been performed for many psychiatric disorders and revealed a complex polygenic architecture linking mental and physical health phenotypes. Psychiatric diagnoses are often heterogeneous, and several layers of trait heterogeneity may contribute to detection of genetic risks per disorder or across multiple disorders. In this review, we discuss these heterogeneities and their consequences on the discovery of risk loci using large-scale genetic data. We primarily highlight the ways in which sex and diagnostic complexity contribute to risk locus discovery in schizophrenia, bipolar disorder, attention deficit hyperactivity disorder, autism spectrum disorder, posttraumatic stress disorder, major depressive disorder, obsessive-compulsive disorder, Tourette’s syndrome and chronic tic disorder, anxiety disorders, suicidality, feeding and eating disorders, and substance use disorders. Genetic data also have facilitated discovery of clinically relevant subphenotypes also described here. Collectively, GWAS of psychiatric disorders revealed that the understanding of heterogeneity, polygenicity, and pleiotropy is critical to translate genetic findings into treatment strategies.