A genome-wide association study of behavioral disinhibition

Developmental genetic effects on externalizing behavior and alcohol use: Examination across two longitudinal samples

Externalizing behavior in early adolescence is associated with alcohol use in adolescence and early adulthood and these behaviors often emerge as part of a developmental sequence. This pattern can be the result of heterotypic continuity, in which different behaviors emerge over time based on an underlying shared etiology. In particular, there is largely a shared genetic etiology underlying externalizing and substance use behaviors. We examined whether polygenic risk for alcohol use disorder predicted (1) externalizing behavior in early adolescence and alcohol use in adolescence in the Early Steps Multisite sample and (2) externalizing behavior in adolescence and alcohol use in early adulthood in the Project Alliance 1 (PAL1) sample. We examined associations separately for African Americans and European Americans. When examining European Americans in the Early Steps sample, greater polygenic risk was associated with externalizing behavior in early adolescence. In European Americans in PAL1, we found greater polygenic risk was associated with alcohol use in early adulthood. Effects were largely absent in African Americans in both samples. Results imply that genetic predisposition for alcohol use disorder may increase risk for externalizing and alcohol use as these behaviors emerge developmentally.

Mechanisms of cognitive disinhibition explain individual differences in adult attention deficit hyperactivity disorder traits

BACKGROUND

Attention deficit hyperactivity disorder (ADHD) in adults is strongly associated with psychiatric comorbidity and functional impairment. Here, we aimed to use a newly developed online cognitive battery with strong psychometric properties for measuring individual differences in three cognitive mechanisms proposed to underlie ADHD traits in adults: 1) attentional control - the ability to mobilize cognitive resources to stop a prepotent motor response; 2) information sampling/gathering - adequate sampling of information in a stimulus detection task prior to making a decision; and 3) shifting - the ability to adapt behavior in response to positive and negative contingencies.

METHODS

This cross-sectional and correlational study recruited 650 adults (330 males) aged 18-69 years (M = 33.06; MD = 31.00; SD = 10.50), with previously diagnosed ADHD (n = 329) and those from the general community without a history of ADHD (n = 321). Self-report measures of ADHD traits (i.e., inattention/disorganization, impulsivity, hyperactivity) and the cognitive battery were completed online.

RESULTS

Latent class analysis, exploratory structural equation modeling and factor mixture modeling revealed self-reported ADHD traits formed a unidimensional and approximately normally distributed phenotype. Bayesian structural equation modeling demonstrated that all three mechanisms measured by the cognitive battery, explained unique, incremental variance in ADHD traits, with a total of 15.9% explained in the ADHD trait factor.

CONCLUSIONS

Attentional control and shifting, as well as the less researched cognitive process of information gathering, explain individual difference variance in self-reported ADHD traits with potential to yield genetic and neurobiological insights into adult ADHD.

Extensive genetic admixture between Tai-Kadai-speaking people and their neighbours in the northeastern region of the Yungui Plateau inferred from genome-wide variations

BACKGROUND

Yungui Plateau in Southwest China is characterized by multi-language and multi-ethnic communities and is one of the regions with the wealthiest ethnolinguistic, cultural and genetic diversity in East Asia. There are numerous Tai-Kadai (TK)-speaking populations, but their detailed evolutionary history and biological adaptations are still unclear.

RESULTS

Here, we genotyped genome-wide SNP data of 77 unrelated TK-speaking Zhuang and Dong individuals from the Yungui Plateau and explored their detailed admixture history and adaptive features using clustering patterns, allele frequency differentiation and sharing haplotype patterns. TK-speaking Zhuang and Dong people in Guizhou are closely related to geographically close TK and Hmong-Mien (HM)-speaking populations. Besides, we identified that Guizhou TK-speaking people have a close genetic relationship with Austronesian (AN)-speaking Atayal and Paiwan people, which is supported by the common origin of the ancient Baiyue tribe. We additionally found subtle genetic differences among the newly studied TK people and previously reported Dais via the fine-scale genetic substructure analysis based on the shared haplotype chunks. Finally, we identified specific selection candidate signatures associated with several essential human immune systems and neurological disorders, which could provide evolutionary evidence for the allele frequency distribution pattern of genetic risk loci.

CONCLUSIONS

Our comprehensive genetic characterization of TK people suggested the strong genetic affinity within TK groups and extensive gene flow with geographically close HM and Han people. We also provided genetic evidence that supported the common origin hypothesis of TK and AN people. The best-fitted admixture models further suggested that ancestral sources from northern millet farmers and southern inland and coastal people contributed to the formation of the gene pool of the Zhuang and Dong people.

Cross-Sectional Gene-Smoking Interaction Analysis in Relation to Subclinical Atherosclerosis-Results From the IMPROVE Study

BACKGROUND

Smoking is associated with carotid intima-media thickness (C-IMT). However, knowledge about how genetics may influence this association is limited. We aimed to perform nonhypothesis driven gene-smoking interaction analyses to identify potential genetic variants, among those included in immune and metabolic platforms, that may modify the effect of smoking on carotid intima-media thickness.

METHODS

We used baseline data from 1551 men and 1700 women, aged 55 to 79, included in a European multi-center study. Carotid intima-media thickness maximum, the maximum of values measured at different locations of the carotid tree, was dichotomized with cut point values ≥75, respectively. Genetic data were retrieved through use of the Illumina Cardio-Metabo- and Immuno- Chips. Gene-smoking interactions were evaluated through calculations of Synergy index (S). After adjustments for multiple testing, P values of <2.4×10-7 for S were considered significant. The models were adjusted for age, sex, education, physical activity, type of diet, and population stratification.

RESULTS

Our screening of 207 586 SNPs available for analysis, resulted in the identification of 47 significant gene-smoking synergistic interactions in relation to carotid intima-media thickness maximum. Among the significant SNPs, 28 were in protein coding genes, 2 in noncoding RNA and the remaining 17 in intergenic regions.

CONCLUSIONS

Through nonhypothesis-driven analyses of gene-smoking interactions, several significant results were observed. These may stimulate further research on the role of specific genes in the process that determines the effect of smoking habits on the development of carotid atherosclerosis.

Simultaneous selection of multiple important single nucleotide polymorphisms in familial genome wide association studies data

We propose a resampling-based fast variable selection technique for detecting relevant single nucleotide polymorphisms (SNP) in a multi-marker mixed effect model. Due to computational complexity, current practice primarily involves testing the effect of one SNP at a time, commonly termed as 'single SNP association analysis'. Joint modeling of genetic variants within a gene or pathway may have better power to detect associated genetic variants, especially the ones with weak effects. In this paper, we propose a computationally efficient model selection approach-based on the e-values framework-for single SNP detection in families while utilizing information on multiple SNPs simultaneously. To overcome computational bottleneck of traditional model selection methods, our method trains one single model, and utilizes a fast and scalable bootstrap procedure. We illustrate through numerical studies that our proposed method is more effective in detecting SNPs associated with a trait than either single-marker analysis using family data or model selection methods that ignore the familial dependency structure. Further, we perform gene-level analysis in Minnesota Center for Twin and Family Research (MCTFR) dataset using our method to detect several SNPs using this that have been implicated to be associated with alcohol consumption.

An Efficient Bayesian Method for Estimating the Degree of the Skewness of X Chromosome Inactivation Based on the Mixture of General Pedigrees and Unrelated Females

Skewed X chromosome inactivation (XCI-S) has been reported to be associated with some X-linked diseases. Several methods have been proposed to estimate the degree of XCI-S (denoted as γ) for quantitative and qualitative traits based on unrelated females. However, there is no method available for estimating γ based on general pedigrees. Therefore, in this paper, we propose a Bayesian method to obtain the point estimate and the credible interval of γ based on the mixture of general pedigrees and unrelated females (called mixed data for brevity), which is also suitable for only general pedigrees. We consider the truncated normal prior and the uniform prior for γ. Further, we apply the eigenvalue decomposition and Cholesky decomposition to our proposed methods to accelerate the computation speed. We conduct extensive simulation studies to compare the performances of our proposed methods and two existing Bayesian methods which are only applicable to unrelated females. The simulation results show that the incorporation of general pedigrees can improve the efficiency of the point estimation and the precision and the accuracy of the interval estimation of γ. Finally, we apply the proposed methods to the Minnesota Center for Twin and Family Research data for their practical use.

Genome-wide association studies on Northern Italy isolated populations provide further support concerning genetic susceptibility for major depressive disorder

OBJECTIVES

Major depressive disorder (MDD) is a psychiatric disorder with pathogenesis influenced by both genetic and environmental factors. To date, the molecular-level understanding of its aetiology remains unclear. Thus, we aimed to identify genetic variants and susceptibility genes for MDD with a genome-wide association study (GWAS) approach.

METHODS

We performed a meta-analysis of GWASs and a gene-based analysis on two Northern Italy isolated populations (cases/controls n = 166/472 and 33/320), followed by replication and polygenic risk score (PRS) analyses in Italian independent samples (cases n = 464, controls n = 339).

RESULTS

We identified two novel MDD-associated genes, KCNQ5 (lead SNP rs867262, p = 3.82 × 10^-9) and CTNNA2 (rs6729523, p = 1.25 × 10^-8). The gene-based analysis revealed another six genes (p < 2.703 × 10^-6): GRM7, CTNT4, SNRK, SRGAP3, TRAPPC9, and FHIT. No replication of the genome-wide significant SNPs was found in the independent cohort, even if 14 SNPs around CTNNA2 showed association with MDD and related phenotypes at the nominal level of p (<0.05). Furthermore, the PRS model developed in the discovery cohort discriminated cases and controls in the replication cohort.

CONCLUSIONS

Our work suggests new possible genes associated with MDD, and the PRS analysis confirms the polygenic nature of this disorder. Future studies are required to better understand the role of these findings in MDD.

Genetics and epigenetics of human aggression

There is substantial variation between humans in aggressive behavior, with its biological etiology and molecular genetic basis mostly unknown. This review chapter offers an overview of genomic and omics studies revealing the genetic contribution to aggression and first insights into associations with epigenetic and other omics (e.g., metabolomics) profiles. We allowed for a broad phenotype definition including studies on "aggression," "aggressive behavior," or "aggression-related traits," "antisocial behavior," "conduct disorder," and "oppositional defiant disorder." Heritability estimates based on family and twin studies in children and adults of this broadly defined phenotype of aggression are around 50%, with relatively small fluctuations around this estimate. Next, we review the genome-wide association studies (GWAS) which search for associations with alleles and also allow for gene-based tests and epigenome-wide association studies (EWAS) which seek to identify associations with differently methylated regions across the genome. Both GWAS and EWAS allow for construction of Polygenic and DNA methylation scores at an individual level. Currently, these predict a small percentage of variance in aggression. We expect that increases in sample size will lead to additional discoveries in GWAS and EWAS, and that multiomics approaches will lead to a more comprehensive understanding of the molecular underpinnings of aggression.

A Century of Behavioral Genetics at the University of Minnesota

The University of Minnesota has played an important role in the resurgence and eventual mainstreaming of human behavioral genetics in psychology and psychiatry. We describe this history in the context of three major movements in behavioral genetics: (1) radical eugenics in the early 20th century, (2) resurgence of human behavioral genetics in the 1960s, largely using twin and adoption designs to obtain more precise estimates of genetic and environmental influences on individual differences in behavior; and (3) use of measured genotypes to understand behavior. University of Minnesota scientists made significant contributions especially in (2) and (3) in the domains of cognitive ability, drug abuse and mental health, and endophenotypes. These contributions are illustrated through a historical perspective of major figures and events in behavioral genetics.

Common and distinguishing genetic factors for substance use behavior and disorder: an integrated analysis of genomic and transcriptomic studies from both human and animal studies

BACKGROUND AND AIMS

Genomic and transcriptomic findings greatly broaden the biological knowledge regarding substance use. However, systematic convergence and comparison evidence of genome-wide findings is lacking for substance use. Here, we combined all the genome-wide findings from both substance use behavior and disorder (SUBD) and identified common and distinguishing genetic factors for different SUBDs.

METHODS

Systemic literature search for genome-wide association (GWAS) and RNA-seq studies of alcohol/nicotine/drug use behavior (partially meets or not reported diagnostic criteria) and alcohol use behavior and disorder (AUBD), nicotine use behavior and disorder (NUBD) and drug use behavior and disorder (DUBD) was performed using PubMed and the GWAS catalog. Drug use was focused upon cannabis, opioid, cocaine and methamphetamine use. GWAS studies required case-control or case/cohort samples. RNA-seq studies were based on brain tissues. The genes which contained significant single nucleotide polymorphism (P ≤ 1 × 10^-6 ) in GWAS and reported as significant in RNA-seq studies were extracted. Pathway enrichment was performed by using Metascape. Gene interaction networks were identified by using the Protein Interaction Network Analysis database.

RESULTS

Total SUBD-related 2910 genes were extracted from 75 GWAS studies (2 773 889 participants) and 17 RNA-seq studies. By overlapping the genes and pathways of AUBD, NUBD and DUBD, four shared genes (CACNB2, GRIN2B, PLXDC2 and PKNOX2), four shared pathways [two Gene Ontology (GO) terms of 'modulation of chemical synaptic transmission', 'regulation of trans-synaptic signaling', two Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of 'dopaminergic synapse', 'cocaine addiction'] were identified (significantly higher than random, P < 1 × 10^-5 ). The top shared KEGG pathways (Benjamini-Hochberg-corrected P-value < 0.05) in the pairwise comparison of AUBD versus DUBD, NUBD versus DUBD, AUBD versus NUBD were 'Epstein-Barr virus infection', 'protein processing in endoplasmic reticulum' and 'neuroactive ligand-receptor interaction', respectively. We also identified substance-specific genetic factors: i.e. ADH1B and ALDH2 were unique for AUBD, while CHRNA3 and CHRNA4 were unique for NUBD.

CONCLUSIONS

This systematic review identifies the shared and unique genes and pathways for alcohol, nicotine and drug use behaviors and disorders at the genome-wide level and highlights critical biological processes for the common and distinguishing vulnerability of substance use behaviors and disorders.

Zhx2 Is a Candidate Gene Underlying Oxymorphone Metabolite Brain Concentration Associated with State-Dependent Oxycodone Reward

Understanding the pharmacogenomics of opioid metabolism and behavior is vital to therapeutic success, as mutations can dramatically alter therapeutic efficacy and addiction liability. We found robust, sex-dependent BALB/c substrain differences in oxycodone behaviors and whole brain concentration of oxycodone metabolites. BALB/cJ females showed robust state-dependent oxycodone reward learning as measured via conditioned place preference when compared with the closely related BALB/cByJ substrain. Accordingly, BALB/cJ females also showed a robust increase in brain concentration of the inactive metabolite noroxycodone and the active metabolite oxymorphone compared with BALB/cByJ mice. Oxymorphone is a highly potent, full agonist at the mu opioid receptor that could enhance drug-induced interoception and state-dependent oxycodone reward learning. Quantitative trait locus (QTL) mapping in a BALB/c F2 reduced complexity cross revealed one major QTL on chromosome 15 underlying brain oxymorphone concentration that explained 32% of the female variance. BALB/cJ and BALB/cByJ differ by fewer than 10,000 variants, which can greatly facilitate candidate gene/variant identification. Hippocampal and striatal cis-expression QTL (eQTL) and exon-level eQTL analysis identified Zhx2, a candidate gene coding for a transcriptional repressor with a private BALB/cJ retroviral insertion that reduces Zhx2 expression and sex-dependent dysregulation of cytochrome P450 enzymes. Whole brain proteomics corroborated the Zhx2 eQTL and identified upregulated CYP2D11 that could increase brain oxymorphone in BALB/cJ females. To summarize, Zhx2 is a highly promising candidate gene underlying brain oxycodone metabolite levels. Future studies will validate Zhx2 and its site of action using reciprocal gene editing and tissue-specific viral manipulations in BALB/c substrains. SIGNIFICANCE STATEMENT: Our findings show that genetic variation can result in sex-specific alterations in whole brain concentration of a bioactive opioid metabolite after oxycodone administration, reinforcing the need for sex as a biological factor in pharmacogenomic studies. The cooccurrence of female-specific increased oxymorphone and state-dependent reward learning suggests that this minor yet potent and efficacious metabolite of oxycodone could increase opioid interoception and drug-cue associative learning of opioid reward, which has implications for cue-induced relapse of drug-seeking behavior and for precision pharmacogenetics.

Detection of Parent-of-Origin Effects for the Variants Associated With Behavioral Disinhibition in the MCTFR Data

Behavioral disinhibition is one of the important characteristics of many mental diseases. It has been reported in literature that serious behavioral disinhibition will affect people's health and greatly reduce people's quality of life. Meanwhile, behavioral disinhibition can easily lead to illegal drug abuse and violent crimes, etc., which will bring great harm to the society. At present, large-scale genome-wide association analysis has identified many loci associated with behavioral disinhibition. However, these studies have not incorporated the parent-of-origin effects (POE) into analysis, which may ignore or underestimate the genetic effects of loci on behavioral disinhibition. Therefore, in this article, we analyzed the five phenotypes related to behavioral disinhibition in the Minnesota Center for Twin and Family Research data (nicotine, alcohol consumption, alcohol dependence, illicit drugs, and non-substance use related behavioral disinhibition), to further explore the POE of variants on behavioral disinhibition. We applied a linear mixed model to test for the POE at a genome-wide scale on five transformed phenotypes, and found nine SNPs with statistically significant POE at the significance level of 5 × 10^-8. Among them, SNPs rs4141854, rs9394515, and rs4711553 have been reported to be associated with two neurological disorders (restless legs syndrome and Tourette's syndrome) which are related to behavioral disinhibition; SNPs rs12960235 and rs715351 have been found to be associated with head and neck squamous cell carcinoma, skin cancer and type I diabetes, while both SNPs have not been identified to be related to behavioral disinhibition in literature; SNPs rs704833, rs6837925, rs1863548, and rs11067062 are novel loci identified in this article, and their function annotations have not been reported in literature. Follow-up study in molecular genetics is needed to verify whether they are surely related to behavioral disinhibition.

Gene-Based Methods for Estimating the Degree of the Skewness of X Chromosome Inactivation

Skewed X chromosome inactivation (XCI-S) has been reported to be associated with some X-linked diseases, and currently several methods have been proposed to estimate the degree of the XCI-S (denoted as γ) for a single locus. However, no method has been available to estimate γ for genes. Therefore, in this paper, we first propose the point estimate and the penalized point estimate of γ for genes, and then derive its confidence intervals based on the Fieller’s and penalized Fieller’s methods, respectively. Further, we consider the constraint condition of γ∈[0, 2] and propose the Bayesian methods to obtain the point estimates and the credible intervals of γ, where a truncated normal prior and a uniform prior are respectively used (denoted as GBN and GBU). The simulation results show that the Bayesian methods can avoid the extreme point estimates (0 or 2), the empty sets, the noninformative intervals ([0, 2]) and the discontinuous intervals to occur. GBN performs best in both the point estimation and the interval estimation. Finally, we apply the proposed methods to the Minnesota Center for Twin and Family Research data for their practical use. In summary, in practical applications, we recommend using GBN to estimate γ of genes.

Alcohol and nicotine polygenic scores are associated with the development of alcohol and nicotine use problems from adolescence to young adulthood

BACKGROUND AND AIMS

Molecular genetic studies of alcohol and nicotine use have identified many genome-wide association study (GWAS) loci. We measured associations between drinking and smoking polygenic scores (PGS) and trajectories of alcohol and nicotine use outcomes from late childhood to early adulthood, substance-specific versus broader-liability PGS effects, and if PGS performance varied for consumption versus problematic substance use.

DESIGN, SETTING, PARTICIPANTS AND MEASUREMENTS

We fitted latent growth curve models with structured residuals to scores on measures of alcohol and nicotine use and problems from ages 14 to 34 years. We then estimated associations between the intercept (initial status) and slope (rate of change) parameters and PGSs for drinks per week (DPW), problematic alcohol use (PAU), cigarettes per day (CPD) and ever being a regular smoker (SMK), controlling for sex and genetic principal components. All data were analyzed in the United States. PGSs were calculated for participants of the Minnesota Twin Family Study (n = 3225) using results from the largest GWAS of alcohol and nicotine consumption and problematic use to date.

FINDINGS

Each PGS was associated with trajectories of use for their respective substances [i.e. DPW (βmean  = 0.08; βrange  = 0.02-0.12) and PAU (βmean  = 0.12; βrange  = -0.02 to 0.31) for alcohol; CPD (βmean  = 0.08; βrange  = 0.04-0.14) and SMK (βmean  = 0.18; βrange  = 0.05-0.36) for nicotine]. The PAU and SMK PGSs also exhibited cross-substance associations (i.e. PAU for nicotine-specific intercepts and SMK for alcohol intercepts and slope). All identified SMK PGS effects remained as significant predictors of nicotine and alcohol trajectories (βmean  = 0.15; βrange  = 0.02-0.33), even after adjusting for the respective effects of all other PGSs.

CONCLUSIONS

Substance use-related polygenic scores (PGSs) vary in the strength and generality versus specificity of their associations with substance use and problems over time. The regular smoking PGS appears to be a robust predictor of substance use trajectories and seems to measure both nicotine-specific and non-specific genetic liability for substance use, and potentially externalizing problems in general.

A Low-Activity Polymorphic Variant of Human NEIL2 DNA Glycosylase

Human NEIL2 DNA glycosylase (hNEIL2) is a base excision repair protein that removes oxidative lesions from DNA. A distinctive feature of hNEIL2 is its preference for the lesions in bubbles and other non-canonical DNA structures. Although a number of associations of polymorphisms in the hNEIL2 gene were reported, there is little data on the functionality of the encoded protein variants, as follows: only hNEIL2 R103Q was described as unaffected, and R257L, as less proficient in supporting the repair in a reconstituted system. Here, we report the biochemical characterization of two hNEIL2 variants found as polymorphisms in the general population, R103W and P304T. Arg103 is located in a long disordered segment within the N-terminal domain of hNEIL2, while Pro304 occupies a position in the β-turn of the DNA-binding zinc finger motif. Similar to the wild-type protein, both of the variants could catalyze base excision and nick DNA by β-elimination but demonstrated a lower affinity for DNA. Steady-state kinetics indicates that the P304T variant has its catalytic efficiency (in terms of k_cat/K_M) reduced ~5-fold compared with the wild-type hNEIL2, whereas the R103W enzyme is much less affected. The P304T variant was also less proficient than the wild-type, or R103W hNEIL2, in the removal of damaged bases from single-stranded and bubble-containing DNA. Overall, hNEIL2 P304T could be worthy of a detailed epidemiological analysis as a possible cancer risk modifier.

Molecular genetics of cocaine use disorders in humans

Drug addiction, one of the major health problems worldwide, is characterized by the loss of control in drug intake, craving, and withdrawal. At the individual level, drugs of abuse produce serious consequences on health and have a negative impact on the family environment and on interpersonal and work relationships. At a wider scale, they have significant socio-economic and public health consequences and they cause delinquency and citizen insecurity. Cocaine, a psychostimulant substance, is one of the most used illicit drugs, especially in America, Western Europe, and Australia. Cocaine use disorders (CUD) are complex multifactorial conditions driven by both genetic and environmental influences. Importantly, not all people who use cocaine develop CUD, and this is due, at least in part, to biological factors that are encoded in the genome of individuals. Acute and repeated use of cocaine induces epigenetic and gene expression changes responsible for the neuronal adaptations and the remodeling of brain circuits that lead to the transition from use to abuse or dependence. The purpose of this review is to delineate such factors, which should eventually help to understand the inter-individual variability in the susceptibility to cocaine addiction. Heritability estimates for CUD are high and genetic risk factors for cocaine addiction have been investigated by candidate gene association studies (CGAS) and genome-wide association studies (GWAS), reviewed here. Also, the high comorbidity that exists between CUD and several other psychiatric disorders is well known and includes phenotypes like schizophrenia, aggression, antisocial or risk-taking behaviors. Such comorbidities are associated with a worse lifetime trajectory, and here we report shared genetic factors that may contribute to them. Gene expression changes and epigenetic modifications induced by cocaine use and chronic abuse in humans are addressed by reviewing transcriptomic studies performed on neuronal cells and on postmortem brains. We report some genes which expression is altered by cocaine that also bear genetic risk variants for the disorder. Finally, we have a glance to the pharmacogenetics of CUD treatments, still in early stages. A better understanding of the genetic underpinnings of CUD will foster the search of effective treatments and help to move forward to personalized medicine.

Polygenic Risk for Aggression Predicts Adult Substance Use Disorder Diagnoses via Substance Use Offending in Emerging Adulthood and is Moderated by a Family-Centered Intervention

A substance use offense reflects an encounter with law enforcement and the court system in response to breaking the law which may increase risk for substance use problems later in life. Individuals may also be at risk for substance use offending and substance use problems based on genetic predisposition. We examined a mediation model in which polygenic risk for aggression predicted adult substance use disorder diagnoses (SUD) via substance use offending in emerging adulthood. In addition, we explored for potential attenuation of genetic influences on these outcomes by a family-based intervention, the Family Check-Up (FCU). Secondary data analyses based upon the Project Alliance 1 sample was conducted among those with genetic data (n = 631; 322 from control and 309 from FCU intervention). The sample was ethnically diverse (30% African American, 44% European American, 6% Latinx, 4% Asian American, 3% Native American, and 13% Other). Greater polygenic risk for aggression was found to increase risk for substance use violations (age 19-23), which in turn was associated with greater likelihood of being diagnosed with SUD at age 27. A gene-by-intervention effect was found in which individuals in the control group had greater risk for SUD with increasing polygenic risk for aggression. Some convergence in results was found when replicating analyses in African American and European American subgroups. Results imply that genetic predisposition may increase risk for problematic substance use later in life via antisocial behavior, such as substance use offending, and that this can be attenuated by a family-centered intervention.

Co-development of alcohol use problems and antisocial peer affiliation from ages 11 to 34: selection, socialization and genetic and environmental influences

BACKGROUND AND AIMS

Social context is an important factor in determining the developmental trajectory of alcohol use. We examined the co-development between alcohol use problems and antisocial peer affiliation. We also estimated the genetic and environmental influences on alcohol use problems, antisocial peer affiliation and their co-development over time.

DESIGN

Longitudinal study using bivariate latent basis models with structured residuals (LBM-SR). A biometric model was then fitted to estimate the genetic and environmental influences on the growth factors and their covariances.

SETTING

The United States mid-west region.

PARTICIPANTS

Members of the Minnesota Twin Family Study (MTFS), an ongoing, longitudinal study of 3762 (52% female) twins (1881 pairs).

MEASUREMENTS

Alcohol use problems were assessed using a composite measure of average number of drinks per occasion in the past 12 months, maximum number of drinks in 24 hours and DSM-III-R symptoms of alcohol abuse and dependence. Antisocial peer affiliation was measured by self-report of the proportion of one's friends who exhibited types of antisocial behaviors.

FINDINGS

The LBM-SR model revealed that there was a large correlation between the growth factors for alcohol use problems and antisocial peer affiliation [r = 0.78, 95% confidence interval (CI) = 0.76, 0.80] and cross-lagged effects consistent with both selection and socialization effects. Additionally, antisocial peer affiliation in adolescence was associated with greater increases in alcohol use problems over time (r = 0.57, 95% CI = 0.54, 0.60). Genetic influences largely accounted for the association between antisocial peer affiliation in pre-adolescence and growth in alcohol use problems, while shared environmental influences accounted for the correlation between antisocial peer affiliation and alcohol use problems growth factors.

CONCLUSIONS

Antisocial peer affiliation in adolescence appears to be a salient, genetically influenced risk factor for early alcohol use and increase in alcohol use from adolescence to young adulthood.

A statistical measure for the skewness of X chromosome inactivation for quantitative traits and its application to the MCTFR data

Background

X chromosome inactivation (XCI) is that one of two chromosomes in mammalian females is silenced during early development of embryos. There has been a statistical measure for the degree of the skewness of XCI for qualitative traits. However, no method is available for such task at quantitative trait loci.

Results

In this article, we extend the existing statistical measure for the skewness of XCI for qualitative traits, and the likelihood ratio, Fieller’s and delta methods for constructing the corresponding confidence intervals, and make them accommodate quantitative traits. The proposed measure is a ratio of two linear regression coefficients when association exists. Noting that XCI may cause variance heterogeneity of the traits across different genotypes in females, we obtain the point estimate and confidence intervals of the measure by incorporating such information. The hypothesis testing of the proposed methods is also investigated. We conduct extensive simulation studies to assess the performance of the proposed methods. Simulation results demonstrate that the median of the point estimates of the measure is very close to the pre-specified true value. The likelihood ratio and Fieller’s methods control the size well, and have the similar test power and accurate coverage probability, which perform better than the delta method. So far, we are not aware of any association study for the X-chromosomal loci in the Minnesota Center for Twin and Family Research data. So, we apply our proposed methods to these data for their practical use and find that only the rs792959 locus, which is simultaneously associated with the illicit drug composite score and behavioral disinhibition composite score, may undergo XCI skewing. However, this needs to be confirmed by molecular genetics.

Conclusions

We recommend the Fieller’s method in practical use because it is a non-iterative procedure and has the similar performance to the likelihood ratio method.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-00978-z.

Genetic underpinnings of affective temperaments: a pilot GWAS investigation identifies a new genome-wide significant SNP for anxious temperament in ADGRB3 gene

Although recently a large-sample GWASs identified significant loci in the background of depression, the heterogeneity of the depressive phenotype and the lack of accurate phenotyping hinders applicability of findings. We carried out a pilot GWAS with in-depth phenotyping of affective temperaments, considered as subclinical manifestations and high-risk states for affective disorders, in a general population sample of European origin. Affective temperaments were measured by TEMPS-A. SNP-level association was assessed by linear regression models, assuming an additive genetic effect, using PLINK1.9. Gender, age, the first ten principal components (PCs) and the other four temperaments were included in the regression models as covariates. SNP-level relevances (p-values) were aggregated to gene level using the PEGASUS method¹. In SNP-based tests, a Bonferroni-corrected significance threshold of p ≤ 5.0 × 10^-8 and a suggestive significance threshold of p ≤ 1.0 × 10^-5, whereas in gene-based tests a Bonferroni-corrected significance of 2.0 × 10^-6 and a suggestive significance of p ≤ 4.0 × 10^-4 was established. To explore known functional effects of the most significant SNPs, FUMA v1.3.5 was used. We identified 1 significant and 21 suggestively significant SNPs in ADGRB3, expressed in the brain, for anxious temperament. Several other brain-relevant SNPs and genes emerged at suggestive significance for the other temperaments. Functional analyses reflecting effect on gene expression and participation in chromatin interactions also pointed to several genes expressed in the brain with potentially relevant phenotypes regulated by our top SNPs. Our findings need to be tested in larger GWA studies and candidate gene analyses in well-phenotyped samples in relation to affective disorders and related phenotypes.

Model-based assessment of replicability for genome-wide association meta-analysis

Genome-wide association meta-analysis (GWAMA) is an effective approach to enlarge sample sizes and empower the discovery of novel associations between genotype and phenotype. Independent replication has been used as a gold-standard for validating genetic associations. However, as current GWAMA often seeks to aggregate all available datasets, it becomes impossible to find a large enough independent dataset to replicate new discoveries. Here we introduce a method, MAMBA (Meta-Analysis Model-based Assessment of replicability), for assessing the "posterior-probability-of-replicability" for identified associations by leveraging the strength and consistency of association signals between contributing studies. We demonstrate using simulations that MAMBA is more powerful and robust than existing methods, and produces more accurate genetic effects estimates. We apply MAMBA to a large-scale meta-analysis of addiction phenotypes with 1.2 million individuals. In addition to accurately identifying replicable common variant associations, MAMBA also pinpoints novel replicable rare variant associations from imputation-based GWAMA and hence greatly expands the set of analyzable variants.

The influence of regression models on genome-wide association studies of alcohol dependence: a comparison of binary and quantitative analyses

INTRODUCTION

Genome-wide association studies (GWAS) of alcohol dependence syndrome (ADS) offer a platform to detect genetic risk loci. However, the majority of the ADS GWAS undertaken, to date, have utilized a case-control design and have failed to identify consistently replicable loci with the exception of protective variants within the alcohol metabolizing genes, notably ADH1B. The ADS phenotype shows considerable variability which means that the use of quantitative variables as a proxy for the severity of ADS has the potential to facilitate identification of risk loci by increasing statistical power. The current study aims to examine the influences of using binary and adjusted quantitative measures of ADS on GWAS outcomes and on calculated polygenic risk scores (PRS).

METHODS

A GWAS was performed in 1251 healthy controls with no history of excess alcohol use and 739 patients with ADS classified using binary DMS-IV criteria. Two additional GWAS were undertaken using a quantitative score based on DSM-IV criteria, which were applied assuming both normal and non-normal distributions of the phenotypic variables. PRS analyses were performed utilizing the data from the binary and the quantitative trait analyses.

RESULTS

No associations were identified at genome-wide significance in any of the individual GWAS; results were comparable in all three. The top associated single nucleotide polymorphism was located on the alcohol dehydrogenase gene cluster on chromosome 4, consistent with previous ADS GWAS. The quantitative trait analysis adjusted for the distribution of the criterion score and the associated PRS had the smallest standard errors and thus the greatest precision.

CONCLUSION

Further exploitation of the use of qualitative trait analysis in GWAS in ADS is warranted.

A robust and unified framework for estimating heritability in twin studies using generalized estimating equations

The 'heritability' of a phenotype measures the proportion of trait variance due to genetic factors in a population. In the past 50 years, studies with monozygotic and dizygotic twins have estimated heritability for 17,804 traits;¹ thus twin studies are popular for estimating heritability. Researchers are often interested in estimating heritability for non-normally distributed outcomes such as binary, counts, skewed or heavy-tailed continuous traits. In these settings, the traditional normal ACE model (NACE) and Falconer's method can produce poor coverage of the true heritability. Therefore, we propose a robust generalized estimating equations (GEE2) framework for estimating the heritability of non-normally distributed outcomes. The traditional NACE and Falconer's method are derived within this unified GEE2 framework, which additionally provides robust standard errors. Although the traditional Falconer's method cannot adjust for covariates, the corresponding 'GEE2-Falconer' can incorporate mean and variance-level covariate effects (e.g. let heritability vary by sex or age). Given a non-normally distributed outcome, the GEE2 models are shown to attain better coverage of the true heritability compared to traditional methods. Finally, a scenario is demonstrated where NACE produces biased estimates of heritability while Falconer remains unbiased. Therefore, we recommend GEE2-Falconer for estimating the heritability of non-normally distributed outcomes in twin studies.

Heritability of overlapping impulsivity and compulsivity dimensional phenotypes

Impulsivity and compulsivity are traits relevant to a range of mental health problems and have traditionally been conceptualised as distinct constructs. Here, we reconceptualised impulsivity and compulsivity as partially overlapping phenotypes using a bifactor modelling approach and estimated heritability for their shared and unique phenotypic variance within a classical twin design. Adult twin pairs (N = 173) completed self-report questionnaires measuring psychological processes related to impulsivity and compulsivity. We fitted variance components models to three uncorrelated phenotypic dimensions: a general impulsive-compulsive dimension; and two narrower phenotypes related to impulsivity and obsessiveness.There was evidence of moderate heritability for impulsivity (A² = 0.33), modest additive genetic or common environmental effects for obsessiveness (A² = 0.25; C² = 0.23), and moderate effects of common environment (C² = 0.36) for the general dimension, This general impulsive-compulsive phenotype may reflect a quantitative liability to related mental health disorders that indexes exposure to potentially modifiable environmental risk factors.

Sexual Development in Adolescence: An Examination of Genetic and Environmental Influences

Sexual development entails many experiences and is a major feature of adolescence. Most relevant behavioral genetic studies, however, focus primarily on sexual behaviors associated with health risks. We took a more normative, developmental perspective by examining genetic and environmental influences on five sexual behaviors ranging from dating to pregnancy in middle (M_age  = 14.90 years) and late adolescence (M_age  = 17.85 years) in a sample of twins (N = 3,762). Overall, behaviors that are more common and socially sanctioned (e.g., dating) were more heritable than behaviors that are less common and socially acceptable (e.g., sexual intercourse). That the etiology of different sexual behaviors is tied to their normativeness highlights the importance of considering the broader developmental context when studying sexual development.

A Family-Based Genome Wide Association Study of Externalizing Behaviors

Shared genetic factors contribute to the high degree of comorbidity among externalizing problems (e.g. substance use and antisocial behavior). We leverage this common genetic etiology to identify genetic influences externalizing problems in participants from the Collaborative Study on the Genetics of Alcoholism (European ancestry = 7568; African ancestry = 3274). We performed a family-based genome-wide association study (GWAS) on externalizing scores derived from criterion counts of five DSM disorders (alcohol dependence, alcohol abuse, illicit drug dependence, illicit drug abuse, and either antisocial personality disorder or conduct disorder). We meta analyzed these results with a similar measure of externalizing in an independent sample, Spit for Science (combined sample N = 15,112). We did not discover any robust genome-wide significant signals. Polygenic scores derived from the ancestry-specific GWAS summary statistics predicted externalizing problems in an independent European ancestry sample, but not in those of African ancestry. However, these PRS were no longer significant after adjusting for multiple testing. Larger samples with deep phenotyping are necessary for the discovery of SNPs related to externalizing problems.

Genomics of human aggression: current state of genome-wide studies and an automated systematic review tool

There are substantial differences, or variation, between humans in aggression, with its molecular genetic basis mostly unknown. This review summarizes knowledge on the genetic contribution to variation in aggression with the following three foci: (1) a comprehensive overview of reviews on the genetics of human aggression, (2) a systematic review of genome-wide association studies (GWASs), and (3) an automated tool for the selection of literature based on supervised machine learning. The phenotype definition 'aggression' (or 'aggressive behaviour', or 'aggression-related traits') included anger, antisocial behaviour, conduct disorder, and oppositional defiant disorder. The literature search was performed in multiple databases, manually and using a novel automated selection tool, resulting in 18 reviews and 17 GWASs of aggression. Heritability estimates of aggression in children and adults are around 50%, with relatively small fluctuations around this estimate. In 17 GWASs, 817 variants were reported as suggestive (P ≤ 1.0E), including 10 significant associations (P ≤ 5.0E). Nominal associations (P ≤ 1E) were found in gene-based tests for genes involved in immune, endocrine, and nervous systems. Associations were not replicated across GWASs. A complete list of variants and their position in genes and chromosomes are available online. The automated literature search tool produced literature not found by regular search strategies. Aggression in humans is heritable, but its genetic basis remains to be uncovered. No sufficiently large GWASs have been carried out yet. With increases in sample size, we expect aggression to behave like other complex human traits for which GWAS has been successful.

Redefining phenotypes to advance psychiatric genetics: Implications from hierarchical taxonomy of psychopathology

Genetic discovery in psychiatry and clinical psychology is hindered by suboptimal phenotypic definitions. We argue that the hierarchical, dimensional, and data-driven classification system proposed by the Hierarchical Taxonomy of Psychopathology (HiTOP) consortium provides a more effective approach to identifying genes that underlie mental disorders, and to studying psychiatric etiology, than current diagnostic categories. Specifically, genes are expected to operate at different levels of the HiTOP hierarchy, with some highly pleiotropic genes influencing higher order psychopathology (e.g., the general factor), whereas other genes conferring more specific risk for individual spectra (e.g., internalizing), subfactors (e.g., fear disorders), or narrow symptoms (e.g., mood instability). We propose that the HiTOP model aligns well with the current understanding of the higher order genetic structure of psychopathology that has emerged from a large body of family and twin studies. We also discuss the convergence between the HiTOP model and findings from recent molecular studies of psychopathology indicating broad genetic pleiotropy, such as cross-disorder SNP-based shared genetic covariance and polygenic risk scores, and we highlight molecular genetic studies that have successfully redefined phenotypes to enhance precision and statistical power. Finally, we suggest how to integrate a HiTOP approach into future molecular genetic research, including quantitative and hierarchical assessment tools for future data-collection and recommendations concerning phenotypic analyses. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

On the path towards personalized medicine: Implications of pharmacogenetic studies of alcohol use disorder medications

Introduction

The heritability of alcohol use disorder (AUD) is estimated to be ~50%; however, the genetic basis of the disease is still poorly understood. The genetic variants identified thus far only explain a small percentage of AUD phenotypic variability. While genome-wide association studies (GWAS) are impacted by technical and methodological limitations, genetic variants that have been identified independently of GWAS findings can moderate the efficacy of AUD medications.

Areas Covered

This review discusses findings from clinical pharmacogenetic studies of AUD medications. While the pharmacogenetic studies reviewed involve several genetic variants in the major neurotransmitter systems, genetic loci in the opioid system have garnered the most attention.

Expert Opinion

The clinical utility of pharmacogenetics in AUD populations is uncertain at this time. There are several ongoing prospective clinical trials that will enhance knowledge regarding the applicability of pharmacogenetics in clinical populations. We recommend that future work in this area consider reverse translating from genotype to phenotype, mapping genes to stages of the addiction cycle, mapping genes to neural circuits, and harnessing large population-based cohorts.

Genetic variation in health insurance coverage

We provide the first investigation into whether and how much genes explain having health insurance coverage or not and possible mechanisms for genetic variation. Using a twin-design that compares identical and non-identical twins from a national sample of US twins from the National Survey of Midlife Development in the United States, we find that genetic effects explain over 40% of the variation in whether a person has any health coverage versus not, and nearly 50% of the variation in whether individuals younger than 65 have private coverage versus whether they have no coverage at all. Nearly one third of the genetic variation in being uninsured versus having private coverage is explained by employment industry, self-employment status, and income, and together with education, they explain over 40% of the genetic influence. Marital status, number of children, and available measures of health status, risk preferences, and prevention effort do not appear to be important channels for genetic effects. That genes have meaningful effects on the insurance status suggests an important source of heterogeneity in insurance take up.

Conduct disorder

Conduct disorder (CD) is a common and highly impairing psychiatric disorder that usually emerges in childhood or adolescence and is characterized by severe antisocial and aggressive behaviour. It frequently co-occurs with attention-deficit/hyperactivity disorder (ADHD) and often leads to antisocial personality disorder in adulthood. CD affects ~3% of school-aged children and is twice as prevalent in males than in females. This disorder can be subtyped according to age at onset (childhood-onset versus adolescent-onset) and the presence or absence of callous-unemotional traits (deficits in empathy and guilt). The aetiology of CD is complex, with contributions of both genetic and environmental risk factors and different forms of interplay among the two (gene-environment interaction and correlation). In addition, CD is associated with neurocognitive impairments; smaller grey matter volume in limbic regions such as the amygdala, insula and orbitofrontal cortex, and functional abnormalities in overlapping brain circuits responsible for emotion processing, emotion regulation and reinforcement-based decision-making have been reported. Lower hypothalamic-pituitary-adrenal axis and autonomic reactivity to stress has also been reported. Management of CD primarily involves parent-based or family-based psychosocial interventions, although stimulants and atypical antipsychotics are sometimes used, especially in individuals with comorbid ADHD.

A Hierarchical Taxonomy of Psychopathology Can Transform Mental Health Research

For more than a century, research on psychopathology has focused on categorical diagnoses. Although this work has produced major discoveries, growing evidence points to the superiority of a dimensional approach to the science of mental illness. Here we outline one such dimensional system-the Hierarchical Taxonomy of Psychopathology (HiTOP)-that is based on empirical patterns of co-occurrence among psychological symptoms. We highlight key ways in which this framework can advance mental-health research, and we provide some heuristics for using HiTOP to test theories of psychopathology. We then review emerging evidence that supports the value of a hierarchical, dimensional model of mental illness across diverse research areas in psychological science. These new data suggest that the HiTOP system has the potential to accelerate and improve research on mental-health problems as well as efforts to more effectively assess, prevent, and treat mental illness.

Genetic determinants of beverage consumption: Implications for nutrition and health

Beverages make important contributions to nutritional intake and their role in health has received much attention. This review focuses on the genetic determinants of common beverage consumption and how research in this field is contributing insight to what and how much we consume and why this genetic knowledge matters from a research and public health perspective. The earliest efforts in gene-beverage behavior mapping involved genetic linkage and candidate gene analysis but these approaches have been largely replaced by genome-wide association studies (GWAS). GWAS have identified biologically plausible loci underlying alcohol and coffee drinking behavior. No GWAS has identified variants specifically associated with consumption of tea, juice, soda, wine, beer, milk or any other common beverage. Thus far, GWAS highlight an important behavior-reward component (as opposed to taste) to beverage consumption which may serve as a potential barrier to dietary interventions. Loci identified have been used in Mendelian randomization and gene×beverage interaction analysis of disease but results have been mixed. This research is necessary as it informs the clinical relevance of SNP-beverage associations and thus genotype-based personalized nutrition, which is gaining interest in the commercial and public health sectors.

Fine-mapping scan of bipolar disorder susceptibility loci in Latino pedigrees

We previously identified bipolar disorder (BD) susceptibility loci on 8q24, 14q32, and 2q12-14 in a genome-wide nonparametric linkage screen in a Latino cohort. We now perform a fine mapping analysis using a dense map of additional SNPs to identify BD susceptibility genes within these regions. One thousand nine hundred and thirty-eight individuals with Latino ancestry (880 individuals with BD Type I or Schizoaffective, Bipolar Type) from 416 Latino pedigrees from the United States, Mexico, Costa Rica, and Guatemala were genotyped with 3,074 SNPs to provide dense coverage of the 8q24 (11.5 cM), 14q32 (7.5 cM), and 2q12-14 (6.5 cM) chromosomal loci. Single-marker association tests in the presence of linkage were performed using the LAMP software. The top linkage peak (rs7834818; LOD = 5.08, p = 3.30E - 5) and associated single marker (rs2280915, p = 2.70E - 12) were located within FBXO32 on 8q24. On chromosome 2, the top linkage peak (rs6750326; LOD = 5.06, p = 3.50E - 5) and associated single marker (rs11887088, p = 2.90E - 6) were located in intragenic regions near ACTR3 and DPP10. None of the additional markers in the region around chromosome 14q32 met significance levels for linkage or association. We identified six SNPs on 2q12-q14 and one SNP in FBXO32 on 8q24 that were significantly associated with BD in this Latino cohort.

Genetic loci for alcohol-related life events and substance-induced affective symptoms: indexing the "dark side" of addiction

A limited number of genetic variants have been identified in traditional GWAS as risk or protective factors for alcohol use disorders (AUD) and related phenotypes. We herein report whole-genome association and rare-variant analyses on AUD traits in American Indians (AI) and European Americans (EA). We evaluated 742 AIs and 1711 EAs using low-coverage whole-genome sequencing. Phenotypes included: (1) a metric based on the occurrence of 36 alcohol-related life events that reflect AUD severity; (2) two alcohol-induced affective symptoms that accompany severe AUDs. We identified two new loci for alcohol-related life events with converging evidence from both cohorts: rare variants of K_2P channel gene KCNK2, and rare missense and splice-site variants in pro-inflammatory mediator gene PDE4C. A NAF1-FSTL5 intergenic variant and an FSTL5 variant were respectively associated with alcohol-related life events in AI and EA. PRKG2 of serine/threonine protein kinase family, and rare variants in interleukin subunit gene EBI3 (IL-27B) were uniquely associated with alcohol-induced affective symptoms in AI. LncRNA LINC02347 on 12q24.32 was uniquely associated with alcohol-induced depression in EA. The top GWAS findings were primarily rare/low-frequency variants in AI, and common variants in EA. Adrenal gland was the most enriched in tissue-specific gene expression analysis for alcohol-related life events, and nucleus accumbens was the most enriched for alcohol-induced affective states in AI. Prefrontal cortex was the most enriched in EA for both traits. These studies suggest that whole-genome sequencing can identify novel, especially uncommon, variants associated with severe AUD phenotypes although the findings may be population specific.

A case-control genome wide association study of substance use disorder (SUD) identifies novel variants on chromosome 7p14.1 in patients from the United Arab Emirates (UAE)

Genome wide association studies (GWASs) have provided insights into the molecular basis of the disorder in different population. This study presents the first GWAS of substance use disorder (SUD) in patients from the United Arab Emirates (UAE). The aim was to identify genetic association(s) that may provide insights into the molecular basis of the disorder. The GWAS discovery cohort consisted of 512 (250 cases and 262 controls) male participants from the UAE. Controls with no prior history of SUD were available from the Emirates family registry. The replication cohort consisted of 520 (415 cases and 105 controls) Australian male Caucasian participants. The GWAS discovery samples were genotyped for 4.6 million single nucleotide polymorphism (SNP). The replication cohort was genotyped using TaqMan assay. The GWAS association analysis identified three potential SNPs rs118129027 (p-value = 6.24 × 10^-8 ), rs74477937 (p-value = 8.56 × 10^-8 ) and rs78707086 (p-value = 8.55 × 10^-8 ) on ch7p14.1, that did not meet the GWAS significance threshold but were highly suggestive. In the replication cohort, the association of the three top SNPs did not reach statistical significance. In a meta-analysis of the discovery and the replication cohorts, there were no strengthen evidence for association of the three SNPs. The top identified rs118129027 overlaps with a regulatory factor (enhancer) region that targets three neighboring genes LOC105375237, LOC105375240, and YAE1D1. The YAE1D1, which represents a potential locus that is involved in regulating translation initiation pathway. Novel associations that require further confirmation were identified, suggesting a new insight to the genetic basis of SUD.

A linear mixed model framework for gene-based gene-environment interaction tests in twin studies

Interaction between genes and environments (G×E) can be well investigated in families due to the shared genes and environment among family members. However, the majority of the current tests of G×E interaction between a set of variants and an environment are only suitable for studies with unrelated subjects. In this paper, we extend several G×E interaction tests to a linear mixed model framework to study interaction between a set of correlated environments and a candidate gene in families. The correlated environments can either be modeled separately or jointly in one model. We demonstrate theoretically that the tests developed by modeling correlated environments separately are valid and present a computationally fast alternative to detect G×E interaction in families. For either strategy, we propose treating the genetic main effects as a random effect to reduce the number of main-effect parameters and thus improve the power to detect interactions. Additionally, we propose a generalization of a test of interaction that adaptively sums the interactions using a sequential algorithm. This generalized set of tests, referred to as the sequential algorithm for the sum of powered score (Seq-SPU) family of tests, can be expressed as a weighted version of the SPU. We find that the adaptive version of our test, Seq-aSPU, can outperform aSPU in cases where the interactions effects are in opposite directions. We applied these methods to the Minnesota Center for Twin and Family Research data set and found one significant gene in interaction with four psychosocial environmental factors affecting the alcohol consumption among the twins.

Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries

Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.

GABAA receptor polymorphisms in alcohol use disorder in the GWAS era

Alcohol use disorder (AUD) is a chronic, relapsing, neuro-psychiatric illness of high prevalence and with a serious public health impact worldwide. It is complex and polygenic, with a heritability of about 50%, and influenced by environmental causal heterogeneity. Risk factors associated with its etiology have a genetic component. GABA (γ-aminobutyric acid) is a major inhibitory neurotransmitter in mammalian brain. GABA_A receptors are believed to mediate some of the physiological and behavioral actions of alcohol. In this critical review, relevant genetic terms and type and methodology of the genetic studies are briefly explained. Postulated candidate genes that encode subunits of GABA_A receptors, with all the reported SNPs, are presented. Genetic studies and meta-analyses examining polymorphisms of the GABA_A receptor and their association with AUD predisposition are presented. The data are critically examined with reference to recent GWAS studies that failed to show relations between GABA_A receptors and AUD. Restrictions and perspectives of the different findings are discussed.

Evaluation of previous substance dependence genome-wide significant findings in a Spanish sample

BACKGROUND

Substance dependence is a chronic and relapsing disorder explained by genetic and environmental risk factors. The aim of our study is to replicate previous genome-wide significant (GWS) hits identified in substance dependence in general or in cocaine dependence in particular using an independent sample from Spain.

METHODS

We evaluated, in a Spanish sample of 1711 subjects with substance dependence (1011 of them cocaine dependent) and 1719 control individuals, three SNPs identified as GWS in previous studies: rs1868152 and rs2952621 (located near LINC02052 and LINC01854, respectively), associated with substance dependence, and rs2629540 (in the first intron of FAM53B), associated with cocaine dependence.

RESULTS

We replicated the association between rs2952621 and substance dependence under the dominant model (P = 0.020), with the risk allele (T) being the same in our sample and in those two reported previously. We then performed a meta-analysis of the two samples used in the original study that reported the association of rs2952621 with substance dependence (Collaborative Studies on Genetics of Alcoholism (COGA) and Study of Addiction: Genetics and Environment (SAGE)) together with our Spanish sample. The meta-analysis of 3747 cases and 4043 controls confirmed the association (OR = 1.26, 95% CI = 1.15-1.39).

CONCLUSIONS

The rs2952621 variant, located downstream from the yet uncharacterized gene LINC01854, is associated with substance dependence in our Spanish sample. Further research is needed to understand its contribution to the susceptibility to substance dependence.

Investigation of common, low-frequency and rare genome-wide variation in anorexia nervosa

Anorexia nervosa (AN) is a complex neuropsychiatric disorder presenting with dangerously low body weight, and a deep and persistent fear of gaining weight. To date, only one genome-wide significant locus associated with AN has been identified. We performed an exome-chip based genome-wide association studies (GWAS) in 2158 cases from nine populations of European origin and 15 485 ancestrally matched controls. Unlike previous studies, this GWAS also probed association in low-frequency and rare variants. Sixteen independent variants were taken forward for in silico and de novo replication (11 common and 5 rare). No findings reached genome-wide significance. Two notable common variants were identified: rs10791286, an intronic variant in OPCML (P=9.89 × 10-6), and rs7700147, an intergenic variant (P=2.93 × 10-5). No low-frequency variant associations were identified at genome-wide significance, although the study was well-powered to detect low-frequency variants with large effect sizes, suggesting that there may be no AN loci in this genomic search space with large effect sizes.

Human Genetics of Addiction: New Insights and Future Directions

PURPOSE OF REVIEW

With the advent of the genome-wide association study (GWAS), our understanding of the genetics of addiction has made significant strides forward. Here, we summarize genetic loci containing variants identified at genome-wide statistical significance (P < 5 × 10-8) and independently replicated, review evidence of functional or regulatory effects for GWAS-identified variants, and outline multi-omics approaches to enhance discovery and characterize addiction loci.

RECENT FINDINGS

Replicable GWAS findings span 11 genetic loci for smoking, eight loci for alcohol, and two loci for illicit drugs combined and include missense functional variants and noncoding variants with regulatory effects in human brain tissues traditionally viewed as addiction-relevant (e.g., prefrontal cortex [PFC]) and, more recently, tissues often overlooked (e.g., cerebellum). GWAS analyses have discovered several novel, replicable variants contributing to addiction. Using larger sample sizes from harmonized datasets and new approaches to integrate GWAS with multiple 'omics data across human brain tissues holds great promise to significantly advance our understanding of the biology underlying addiction.

Exploring genetic associations with ceRNA regulation in the human genome

Competing endogenous RNAs (ceRNAs) are RNA molecules that sequester shared microRNAs (miRNAs) thereby affecting the expression of other targets of the miRNAs. Whether genetic variants in ceRNA can affect its biological function and disease development is still an open question. Here we identified a large number of genetic variants that are associated with ceRNA's function using Geuvaids RNA-seq data for 462 individuals from the 1000 Genomes Project. We call these loci competing endogenous RNA expression quantitative trait loci or 'cerQTL', and found that a large number of them were unexplored in conventional eQTL mapping. We identified many cerQTLs that have undergone recent positive selection in different human populations, and showed that single nucleotide polymorphisms in gene 3΄UTRs at the miRNA seed binding regions can simultaneously regulate gene expression changes in both cis and trans by the ceRNA mechanism. We also discovered that cerQTLs are significantly enriched in traits/diseases associated variants reported from genome-wide association studies in the miRNA binding sites, suggesting that disease susceptibilities could be attributed to ceRNA regulation. Further in vitro functional experiments demonstrated that a cerQTL rs11540855 can regulate ceRNA function. These results provide a comprehensive catalog of functional non-coding regulatory variants that may be responsible for ceRNA crosstalk at the post-transcriptional level.

The utility of twins in developmental cognitive neuroscience research: How twins strengthen the ABCD research design

The ABCD twin study will elucidate the genetic and environmental contributions to a wide range of mental and physical health outcomes in children, including substance use, brain and behavioral development, and their interrelationship. Comparisons within and between monozygotic and dizygotic twin pairs, further powered by multiple assessments, provide information about genetic and environmental contributions to developmental associations, and enable stronger tests of causal hypotheses, than do comparisons involving unrelated children. Thus a sub-study of 800 pairs of same-sex twins was embedded within the overall Adolescent Brain and Cognitive Development (ABCD) design. The ABCD Twin Hub comprises four leading centers for twin research in Minnesota, Colorado, Virginia, and Missouri. Each site is enrolling 200 twin pairs, as well as singletons. The twins are recruited from registries of all twin births in each State during 2006-2008. Singletons at each site are recruited following the same school-based procedures as the rest of the ABCD study. This paper describes the background and rationale for the ABCD twin study, the ascertainment of twin pairs and implementation strategy at each site, and the details of the proposed analytic strategies to quantify genetic and environmental influences and test hypotheses critical to the aims of the ABCD study.

Identifying pleiotropic genes in genome-wide association studies from related subjects using the linear mixed model and Fisher combination function

Background

A multivariate genome-wide association test is proposed for analyzing data on multivariate quantitative phenotypes collected from related subjects. The proposed method is a two-step approach. The first step models the association between the genotype and marginal phenotype using a linear mixed model. The second step uses the correlation between residuals of the linear mixed model to estimate the null distribution of the Fisher combination test statistic.

Results

The simulation results show that the proposed method controls the type I error rate and is more powerful than the marginal tests across different population structures (admixed or non-admixed) and relatedness (related or independent). The statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that applying the multivariate association test may facilitate identification of the pleiotropic genes contributing to the risk for alcohol dependence commonly expressed by four correlated phenotypes.

Conclusions

This study proposes a multivariate method for identifying pleiotropic genes while adjusting for cryptic relatedness and population structure between subjects. The two-step approach is not only powerful but also computationally efficient even when the number of subjects and the number of phenotypes are both very large.

Resampling-based tests for Lasso in genome-wide association studies

Background

Genome-wide association studies involve detecting association between millions of genetic variants and a trait, which typically use univariate regression to test association between each single variant and the phenotype. Alternatively, Lasso penalized regression allows one to jointly model the relationship between all genetic variants and the phenotype. However, it is unclear how to best conduct inference on the individual Lasso coefficients, especially in high-dimensional settings.

Methods

We consider six methods for testing the Lasso coefficients: two permutation (Lasso-Ayers, Lasso-PL) and one analytic approach (Lasso-AL) to select the penalty parameter for type-1-error control, residual bootstrap (Lasso-RB), modified residual bootstrap (Lasso-MRB), and a permutation test (Lasso-PT). Methods are compared via simulations and application to the Minnesota Center for Twins and Family Study.

Results

We show that for finite sample sizes with increasing number of null predictors, Lasso-RB, Lasso-MRB, and Lasso-PT fail to be viable methods of inference. However, Lasso-PL and Lasso-AL remain fast and powerful tools for conducting inference with the Lasso, even in high-dimensions.

Conclusion

Our results suggest that the proposed permutation selection procedure (Lasso-PL) and the analytic selection method (Lasso-AL) are fast and powerful alternatives to the standard univariate analysis in genome-wide association studies.

Using Patterns of Genetic Association to Elucidate Shared Genetic Etiologies Across Psychiatric Disorders

Twin studies indicate that latent genetic factors overlap across comorbid psychiatric disorders. In this study, we used a novel approach to elucidate shared genetic factors across psychiatric outcomes by clustering single nucleotide polymorphisms based on their genome-wide association patterns. We applied latent profile analysis (LPA) to p-values resulting from genome-wide association studies across three phenotypes: symptom counts of alcohol dependence (AD), antisocial personality disorder (ASP), and major depression (MD), using the European-American case-control genome-wide association study subsample of the collaborative study on the genetics of alcoholism (N = 1399). In the 3-class model, classes were characterized by overall low associations (85.6% of SNPs), relatively stronger association only with MD (6.8%), and stronger associations with AD and ASP but not with MD (7.6%), respectively. These results parallel the genetic factor structure identified in twin studies. The findings suggest that applying LPA to association results across multiple disorders may be a promising approach to identify the specific genetic etiologies underlying shared genetic variance.

Phenotypic and Genetic Relationship Between BMI and Drinking in a Sample of UK Adults

The health impairments derived from both alcoholism and obesity are well known. However, reports that relate increased alcohol use with increased measures of obesity have been mixed in their findings, especially with respect to genetic factors that could potentially link these two behaviors. Here, using a large sample of adults from the UK (n ≈ 113,000), we report both the observed and genetic correlations between BMI (kg/m2) and two measures of alcohol use: reported quantity (drinks per week) and frequency of use (from never to daily). Overall, both observationally and genetically, alcohol intake is negatively correlated with BMI. Phenotypic correlations ranged from -0.01 to -0.17, and genetic correlations ranged from -0.1 to -0.4. Genetic correlations tended to be stronger than the phenotypic correlations, and these correlations were stronger in females and between BMI and, specifically, frequency of use. Though the mechanisms driving these relationships are yet to be identified, we can conclude that the genetic factors related to drinking both more and more often are shared with those responsible for lower BMI.

Revealing phenotype-associated functional differences by genome-wide scan of ancient haplotype blocks

Genome-wide scans for positive selection have become important for genomic medicine, and many studies aim to find genomic regions affected by positive selection that are associated with risk allele variations among populations. Most such studies are designed to detect recent positive selection. However, we hypothesize that ancient positive selection is also important for adaptation to pathogens, and has affected current immune-mediated common diseases. Based on this hypothesis, we developed a novel linkage disequilibrium-based pipeline, which aims to detect regions associated with ancient positive selection across populations from single nucleotide polymorphism (SNP) data. By applying this pipeline to the genotypes in the International HapMap project database, we show that genes in the detected regions are enriched in pathways related to the immune system and infectious diseases. The detected regions also contain SNPs reported to be associated with cancers and metabolic diseases, obesity-related traits, type 2 diabetes, and allergic sensitization. These SNPs were further mapped to biological pathways to determine the associations between phenotypes and molecular functions. Assessments of candidate regions to identify functions associated with variations in incidence rates of these diseases are needed in the future.