Genome-wide association study implicates CHRNA2 in cannabis use disorder

Demontis, Ditte; Rajagopal, Veera; Thorgeirsson, Thorgeir E.; Als, Thomas Damm; Grove, Jakob; Leppälä, Kalle; Guðbjartsson, Daníel F.; Pallesen, Jonatan; Hjorthøj, Carsten; Reginsson, Gunnar W.; Tyrfingsson, Þorarinn; Rúnarsdóttir, Valgerður; Qvist, Per; Christensen, Jane H.; Bybjerg‐Grauholm, Jonas; Bækvad‐Hansen, Marie; Huckins, Laura; Stahl, Eli A.; Timmermann, Allan; Agerbo, Esben; Hougaard, David M.; Werge, Thomas; Mors, Ole; Mortensen, Preben Bo; Nordentoft, Merete; Daly, Mark J.; Stefánsson, Hreinn; Stefánsson, Kāri; Nyegaard, Mette; Børglum, Anders D.

doi:10.1038/s41593-019-0416-1

Cited by 109 publications

(72 citation statements)

References 79 publications

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“…Along these lines, several of the genes and genetic pathways found to be significant in sleep relatedvariable GWAS 56,58-61 have been associated with cannabis use and cannabinoid activity [62][63][64][65]67,68,[109][110][111][112] . Likewise, GWAS for lifetime cannabis use and CUD 65,66,69,70 have found genes that have been linked to sleep behaviors and circadian rhythm [71][72][73][74]113 .…”

Section: Discussionmentioning

confidence: 99%

Sleep Deficits and Cannabis Use Behaviors: An Analysis of Shared Genetics Using Linkage Disequilibrium Score Regression and Polygenic Risk Prediction

Winiger

Ellingson

Morrison

et al. 2020

Preprint

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Study Objectives: Estimate the genetic relationship of cannabis use with sleep deficits and eveningness chronotype. Methods:We used linkage disequilibrium score regression (LDSC) to analyze genetic correlations between sleep deficits and cannabis use behaviors. Secondly, we generated sleep deficit polygenic risk scores (PRSs) and estimated their ability to predict cannabis use behaviors using logistic regression. Summary statistics came from existing genome wide association studies (GWASs) of European ancestry that were focused on sleep duration, insomnia, chronotype, lifetime cannabis use, and cannabis use disorder (CUD). A target sample for PRS prediction consisted of high-risk participants and participants from twin/family communitybased studies (n = 796, male = 66%; mean age = 26.81). Target data consisted of self-reported sleep (sleep duration, feeling tired, and taking naps) and cannabis use behaviors (lifetime use, number of lifetime uses, past 180-day use, age of first use, and lifetime CUD symptoms).Results: Significant genetic correlation between lifetime cannabis use and eveningness chronotype (rG = 0.24, p < 0.01), as well as between CUD and both short sleep duration (<7 h) (rG = 0.23, p = 0.02) and insomnia (rG = 0.20, p = 0.02). Insomnia PRS predicted earlier age of first cannabis use (β = -0.09, p = 0.02) and increased lifetime CUD symptom count use (β = 0.07, p = 0.03). Conclusion:Cannabis use is genetically associated with both sleep deficits and an eveningness chronotype, suggesting that there are genes that predispose individuals to both cannabis use and sleep deficits.

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Section: Discussionmentioning

confidence: 99%

Sleep Deficits and Cannabis Use Behaviors: An Analysis of Shared Genetics Using Linkage Disequilibrium Score Regression and Polygenic Risk Prediction

Winiger

Ellingson

Morrison

et al. 2020

Preprint

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“…These were 675 genes, functionally assigned to autoimmune disease (p = 0.002), natural killer cell-mediated cytotoxicity (p = 0.003), measles (p = 0.003), arachidonic acid metabolism (p = 0.003), cGMP dependent protein kinase G signaling pathway (p = 0.005), and phenylalananine metabolism (p = 0.009), indicating an effect on immune functions found to be decreased by Meth, based on the comparison between Tat−/Meth vs. Tat−/Sal groups. Table 2 shows the 40 most downregulated genes; among them, the neuronal cholinergic receptor alpha 2 (Chrna2) where both gain and loss of function and mutations have been described in association with multiple neurological disorders [61][62][63][64], with cannabis use [65], and with antisocial behaviors in adolescent drug users [66]. In this list of 50 genes, the strongest representation was of genes acting epigenetically in the nucleus (p = 0.0072) and transcription factor complexes (p = 0.001).…”

Section: The Effects Of Meth-induced Sensitization: the Comparison Bementioning

confidence: 99%

Systems Biology Analysis of the Antagonizing Effects of HIV-1 Tat Expression in the Brain over Transcriptional Changes Caused by Methamphetamine Sensitization

Basova

Kesby

Kaul

et al. 2020

Viruses

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Methamphetamine (Meth) abuse is common among humans with immunodeficiency virus (HIV). The HIV-1 regulatory protein, trans-activator of transcription (Tat), has been described to induce changes in brain gene transcription that can result in impaired reward circuitry, as well as in inflammatory processes. In transgenic mice with doxycycline-induced Tat protein expression in the brain, i.e., a mouse model of neuroHIV, we tested global gene expression patterns induced by Meth sensitization. Meth-induced locomotor sensitization included repeated daily Meth or saline injections for seven days and Meth challenge after a seven-day abstinence period. Brain samples were collected 30 min after the Meth challenge. We investigated global gene expression changes in the caudate putamen, an area with relevance in behavior and HIV pathogenesis, and performed pathway and transcriptional factor usage predictions using systems biology strategies. We found that Tat expression alone had a very limited impact in gene transcription after the Meth challenge. In contrast, Meth-induced sensitization in the absence of Tat induced a global suppression of gene transcription. Interestingly, the interaction between Tat and Meth broadly prevented the Meth-induced global transcriptional suppression, by maintaining regulation pathways, and resulting in gene expression profiles that were more similar to the controls. Pathways associated with mitochondrial health, initiation of transcription and translation, as well as with epigenetic control, were heavily affected by Meth, and by its interaction with Tat in anti-directional ways. A series of systems strategies have predicted several components impacted by these interactions, including mitochondrial pathways, mTOR/RICTOR, AP-1 transcription factor, and eukaryotic initiation factors involved in transcription and translation. In spite of the antagonizing effects of Tat, a few genes identified in relevant gene networks remained downregulated, such as sirtuin 1, and the amyloid precursor protein (APP). In conclusion, Tat expression in the brain had a low acute transcriptional impact but strongly interacted with Meth sensitization, to modify effects in the global transcriptome.

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“…There is a growing desire to apply this integrative approach to the field of psychiatry (Fernandes et al, 2017;Lake & Turner, 2017), given the high personal and societal costs associated with psychiatric conditions (Lake & Turner, 2017;Roehrig, 2016). Although the idea of precision medicine for psychiatry may have seemed unlikely just a decade ago, it is becoming an increasing reality as large-scale gene identification efforts have advanced our understanding of the genetic architecture of many complex conditions, including psychiatric outcomes such as depression (Howard et al, 2019), alcohol and substance use disorders (Demontis et al, 2019;Hancock et al, 2015;Kranzler et al, 2019;Liu et al, 2019;Walters et al, 2018), and schizophrenia (Pardiñas et al, 2018;Ripke et al, 2014). Despite these advances, utilizing results from genome-wide association studies for genetic risk prediction for psychiatric outcomes is presently limited (Martin, Daly, Robinson, Hyman, & Neale, 2019).…”

Section: Introductionmentioning

confidence: 99%

Genetic feedback for psychiatric conditions: Where are we now and where are we going

Driver

Kuo

Dick

2020

American J of Med Genetics Pt B

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Genome‐wide association studies are rapidly advancing our understanding of the genetic architecture of complex disorders, including many psychiatric conditions such as major depression, schizophrenia, and substance use disorders. One common goal of genome‐wide association studies is to use findings for enhanced clinical prediction in the future, which can aid in identifying at‐risk individuals to enable more effective prevention screening and treatment strategies. In order to achieve this goal, we first need to gain a better understanding of the issues surrounding the return of complex genetic results. In this article, we summarize the current literature on: (a) genetic literacy in the general population, (b) the public's interest in receiving genetic test results for psychiatric conditions, (c) how individuals react to and interpret their genotypic information for specific psychiatric conditions, and (d) gaps in our knowledge that will be critical to address as we move toward returning genotypic information for psychiatric conditions in both research and clinical settings. By reviewing extant studies, we aim to increase awareness of the potential benefits and consequences of returning genotypic information for psychiatric conditions.

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Genome-wide association study implicates CHRNA2 in cannabis use disorder

Abstract: are employees of deCODE genetics/ Amgen. Data availabilitySummary statistics with the results from the CUD GWAS is available on the iPSYCH website (https://ipsych.au.dk/downloads/). For access to genotypes from the the iPSYCH cohort, interested researchers should contact A.D. Børglum.

Cited by 109 publications

References 79 publications

Sleep Deficits and Cannabis Use Behaviors: An Analysis of Shared Genetics Using Linkage Disequilibrium Score Regression and Polygenic Risk Prediction

Sleep Deficits and Cannabis Use Behaviors: An Analysis of Shared Genetics Using Linkage Disequilibrium Score Regression and Polygenic Risk Prediction

Systems Biology Analysis of the Antagonizing Effects of HIV-1 Tat Expression in the Brain over Transcriptional Changes Caused by Methamphetamine Sensitization

Genetic feedback for psychiatric conditions: Where are we now and where are we going

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