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Background: Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50–70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder. Methods: To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations. Findings: We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07–1·15, p=1·84 × 10 −9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86–0·93, p=6·46 × 10 −9). Cannabis use disorder and cannabis use were genetically correlated (r g 0·50, p=1·50 × 10 −21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia. Interpretation: These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder. Funding: National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences.

Objective: To investigate the genetic architecture of internalizing symptoms in childhood and adolescence. Method: In 22 cohorts, multiple univariate genome-wide association studies (GWASs) were performed using repeated assessments of internalizing symptoms, in a total of 64,561 children and adolescents between 3 and 18 years of age. Results were aggregated in meta-analyses that accounted for sample overlap, first using all available data, and then using subsets of measurements grouped by rater, age, and instrument. Results: The meta-analysis of overall internalizing symptoms (INToverall) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI = 0.84-2.48%, neffective = 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI = 3.08%-8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (|rg| > 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range |rg| = 0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa. Conclusion: Genetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success. Dr. Border has received support from the National Institutes of Health (NIH; MH100141 and MH016880 ). Dr. Peterson has received support from NIH (K01MH113848) and the Brain & Behavior Research Foundation Young Investigator Grant (28632). Drs. Sallis and Munafò have served as members of the MRC Integrative Epidemiology Unit at the University of Bristol (MC_UU_00011/7). Dr. Shabalin has received support from a NARSAD Young Investigator Award. Dr. Vilor-Tejedor has received support from a post-doctoral grant, Juan de la Cierva Programme (FJC2018-038085-I), Ministerio de Ciencia, Innovación y Universidades – Spanish State Research Agency. Her research has received additional support of “la Caixa” Foundation (LCF/PR/GN17/10300004) and the Health Department of the Catalan Government (Health Research and Innovation Strategic Plan (PERIS) 2016-2020 grant# SLT002/16/00201). She has acknowledged the support of the Spanish Ministry of Science, Innovation and Universities to the EMBL partnership, the Centro de Excelencia Severo Ochoa, and the CERCA Programme/Generalitat de Catalunya. Dr. Alemany has received support from a Juan de la Cierva – Incorporación Postdoctoral Contract from Ministerio de Economía, Industria y Competitividad (IJCI-2017-34068). Dr. Corley has received support from NIH (DA011015, AG046938, and DA035804). Dr. Evans has received support from NIH (MH100141, DA044283, and AG046938). Dr. Havdahl has received support from the South-Eastern Norway Regional Health Authority (2018059) at Nic Waals Institute, Lovisenberg Diaconal Hospital. Dr. Rimfeld has received support from a Sir Henry Wellcome Postdoctoral Fellowship. Dr. Andreassen has served as a consultant to HealthLytix and has received funding from the Research Council of Norway (223273 and 273291) and KG Jebsen Stiftelsen. Dr. Boomsma has received support from the Royal Netherlands Academy of Science Professor Award (PAH/5535). Dr. Brown has received support from NIH (DA035804). Dr. Copeland has received support from NIH (MH117559 and HD093651). Dr. Dick has received support from a mid-career award NIH K02 AA018755, NIH R01 AA015416 (Finnish Twin Study), P50 AA022537 (Alcohol Research Center), R25 AA027402 (VCU GREAT), and U10 AA008401 (COGA) from the National Institute on Alcohol Abuse and Alcoholism. Drs. Hewitt, Krauter, Smolen, and Stallings have received support from NIH (DA011015 and DA035804). Dr. Hopfer has received support from NIH (DA042755, DA035804, and DA032555). Dr. Kaprio has received support from the Academy of Finland (grants 308248 and 312073). Dr. Larsson has served as a speaker for Evolan Pharma and Shire/Takeda and has received research grants from Shire/Takeda, all outside the submitted work. Dr. Lichtenstein has received support from the Swedish Research Council for Health, Working Life and Welfare (project 2012-1678) and the Swedish Research Council (2016-1989). Dr. Lundström has received support from the Swedish Research Council ( 2017-02552 ). Dr. Magnus has received support from the Research Council of Norway through its Centers of Excellence scheme, project no 262700. Dr. Njølstad has received support from the European Research Council (AdG #293574). Stiftelsen Kristian Gerhard Jebsen has received support from the Research Council of Norway (FRIPRO 240413), the Western Norway Regional Health Authority (Strategic Fund “Personalized Medicine for Children and Adults”) and the Novo Nordisk Foundation (54741). Dr. Plomin has received support from a MRC Professorship award (G19/2). Dr. Reichborn-Kjennerud has received support from the Research Council of Norway grant 274611 . Drs. Reynolds and Wadsworth have received support from NIH (AG046938). Dr. Rose has received support from a NIH Research Scientist Award (AA-000145). Dr. Wall has received support from NIH (DA03580 and DA021905). Dr. Whitehouse has received support from an Investigator Grant from the National Health and Medical Research Council. Dr. Ystrøm has received support from the Research Council of Norway (262177 and 288083). Dr. Nivard has received support from ZonMW (849200011), the Netherlands Organisation for Health Research and Development (531003014 937), a Jacobs Foundation Research Fellowship, and a VENI grant awarded by NWO (VI.Veni.191G.030). Dr. Bartels has received support from an ERC Consolidator Grant (WELL-BEING 771057). Ms. Hagenbeek and Mr. Ip have received support from the Aggression in Children: Unraveling gene-environment interplay to inform Treatment and Intervention strategies project (ACTION). ACTION received funding from the European Union Seventh Framework Program (FP7/2007-2013) under grant agreement no 602768

Recent studies have shown a critical role of the gastrointestinal microbiome in brain and behavior via the complex gut–microbiome–brain axis. However, the influence of the oral microbiome in neurological processes is much less studied, especially in response to the stimuli, such as smoking, within the oral microenvironment. Additionally, given the complex structural and functional networks in brain, our knowledge about the relationship between microbiome and brain function through specific brain circuits is still very limited. In this pilot study, we leveraged next generation microbial sequencing with functional neuroimaging techniques to enable the delineation of microbiome-brain network links as well as their relationship to cigarette smoking. Thirty smokers and 30 age- and sex-matched nonsmokers were recruited for 16S sequencing of their oral microbial community. Among them, 56 subjects were scanned by resting-state functional magnetic resonance imaging to derive brain functional networks. Statistical analyses were performed to demonstrate the influence of smoking on the oral microbial community, functional network connectivity among brain regions, and the associations between microbial shifts and the brain functional network connectivity alternations. Compared to nonsmokers, we found a significant decrease of beta diversity (P = 6 × 10 −3 ) in smokers and identified several classes (Betaproteobacteria, Spirochaetia, Synergistia, and Mollicutes) with significant alterations in microbial abundance. Pathway analysis on the predicted KEGG pathways shows that the microbiota with altered abundance are mainly involved in pathways related to cell processes, DNA repair, immune system, and neurotransmitters signaling. One brain functional network connectivity component was identified to have a significant difference between smokers and nonsmokers (P = 0.032), mainly including connectivity between brain default network and other task-positive networks. This brain functional component was also significantly associated with smoking related oral microbiota, suggesting a related cross-individual pattern between smoking-induced oral microbiome dysbiosis and brain functional connectivity alternation, possibly involving immunological and neurotransmitter signaling pathways. This work is the first attempt to link oral microbiome and brain functional networks, and provides support for future work in characterizing the role of oral microbiome in mediating smoking effects on brain activity.

Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data, i.e., within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGGoverall) was 3.31% (SE = 0.0038). We found no genome-wide significant SNPs for AGGoverall. The gene-based analysis returned three significant genes: ST3GAL3 (P = 1.6E–06), PCDH7 (P = 2.0E–06), and IPO13 (P = 2.5E–06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (rg) among rater-specific assessment of AGG ranged from rg = 0.46 between self- and teacher-assessment to rg = 0.81 between mother- and teacher-assessment. We obtained moderate-to-strong rgs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range $$\left| {r_g} \right|$$ r g : 0.19–1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg = ~−0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range $$\left| {r_g} \right|$$ r g : 0.46–0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG.

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa (BN) and problem alcohol use (genetic correlation [rg], twin-based=0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge-eating, AN without binge-eating, and a BN factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder (MDD). Total sample sizes per phenotype ranged from ~2,400 to ~537,000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg=0.18; false discovery rate q=0.0006), cannabis initiation and AN (rg=0.23; qwith binge-eating (rg=0.27; q=0.0016). Conversely, significant negative genetic correlations were observed between three non-diagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge-eating (rgs=-0.19 to −0.23; qs

Internalising symptoms in childhood and adolescence are as heritable as adult depression and anxiety, yet little is known of their molecular basis. This genome-wide association meta-analysis of internalising symptoms included repeated observations from 64,641 individuals, aged between 3 and 18. The N-weighted meta-analysis of overall internalising symptoms (INToverall) detected no genome-wide significant hits and showed low SNP heritability (1.66%, 95% confidence intervals 0.84-2.48%, Neffective=132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalising symptoms showing the highest heritability (5.63%, 95% confidence intervals 3.08-8.18%). Additive genetic effects on internalising symptoms appeared stable over age, with overlapping estimates of SNP heritability from early-childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the wellbeing spectrum (|rg|> 0.70), as well as with insomnia, loneliness, attention-deficit hyperactivity disorder, autism, and childhood aggression (range |rg|=0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa. The pattern of genetic correlations suggests that childhood and adolescent internalising symptoms share substantial genetic vulnerabilities with adult internalising disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalising symptoms over time and the high comorbidity amongst childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.

Emerging links between gut microbiota and diseases of aging point to possible shared immune, metabolic, and cellular damage mechanisms, operating long before diseases manifest. We conducted 16S rRNA sequencing of fecal samples collected from a subsample (n = 668) of Add Health Wave V, a nationally representative longitudinal study of adults aged 32–42. An overlapping subsample (n = 345) included whole-blood RNA-seq. We examined associations between fecal taxonomic abundances and dried blood spot-based markers of lipid and glucose homeostasis and C-reactive protein (measured in Wave IV), as well as gene expression markers of inflammation, cellular damage, immune cell composition, and transcriptomic age (measured in Wave V), using Bayesian hierarchical models adjusted for potential confounders. We additionally estimated a co-abundance network between inflammation-related genes and bacterial taxa using penalized Gaussian graphical models. Strong and consistent microbiota associations emerged for HbA1c, glucose, C-reactive protein, and principal components of genes upregulated in inflammation, DNA repair, and reactive oxygen species, with Streptococcus infantis, Pseudomonas spp., and Peptoniphilus as major players for each. This pattern was largely echoed (though attenuated) for immunological cell composition gene sets, and only Serratia varied meaningfully by transcriptomic age. Network co-abundance indicated relationships between Prevotella sp., Bacteroides sp., and Ruminococcus sp. and gut immune/metabolic regulatory activity, and Ruminococcus sp, Dialister, and Butyrivibrio crossotus with balance between Th1 and Th2 inflammation. In conclusion, many common associations between microbiota and major physiologic aging mechanisms are evident in early-mid adulthood and suggest avenues for early detection and prevention of accelerated aging.

International audience; DNA interstrand cross-links (ICLs) represent a major barrier blocking DNA replication fork progression. ICL accumulation results in growth arrest and cell death-particularly in cell populations undergoing high replicative activity, such as cancer and leukemic cells. For this reason, agents able to induce DNA ICLs are widely used as chemotherapeutic drugs. However, ICLs are also generated in cells as byproducts of normal metabolic activities. Therefore, every cell must be capable of rescuing lCL-stalled replication forks while maintaining the genetic stability of the daughter cells in order to survive, replicate DNA and segregate chromosomes at mitosis. Inactivation of the Fanconi anemia/breast cancer-associated (FANC/BRCA) pathway by inherited mutations leads to Fanconi anemia (FA), a rare developmental, cancer-predisposing and chromosome-fragility syndrome. FANC/BRCA is the key hub for a complex and wide network of proteins that-upon rescuing ICL-stalled DNA replication forks-allows cell survival. Understanding how cells cope with ICLs is mandatory to ameliorate ICL-based anticancer therapies and provide the molecular basis to prevent or bypass cancer drug resistance. Here, we review our state-of-the-art understanding of the mechanisms involved in ICL resolution during DNA synthesis, with a major focus on how the FANC/BRCA pathway ensures DNA strand opening and prevents genomic instability.

There is great interest in understanding the impact of rare variants in human diseases using large sequence datasets. In deep sequence datasets of &gt, 10,000 samples, ~10% of the variant sites are observed to be multi-allelic. Many of the multi-allelic variants have been shown to be functional and disease-relevant. Proper analysis of multi-allelic variants is critical to the success of a sequencing study, but existing methods do not properly handle multi-allelic variants and can produce highly misleading association results. We discuss practical issues and methods to encode multi-allelic sites, conduct single-variant and gene-level association analyses, and perform meta-analysis for multi-allelic variants. We evaluated these methods through extensive simulations and the study of a large meta-analysis of ~18,000 samples on the cigarettes-per-day phenotype. We showed that our joint modeling approach provided an unbiased estimate of genetic effects, greatly improved the power of single-variant association tests among methods that can properly estimate allele effects, and enhanced gene-level tests over existing approaches. Software packages implementing these methods are available online.

Background and aims: Cannabis is one of the most commonly used substances among adolescents and young adults. Earlier age at cannabis initiation is linked to adverse life outcomes, including multi-substance use and dependence. This study estimated the heritability of age at first cannabis use and identified associations with genetic variants. Methods: A twin-based heritability analysis using 8055 twins from three cohorts was performed. We then carried out a genome-wide association meta-analysis of age at first cannabis use in a discovery sample of 24 953 individuals from nine European, North American and Australian cohorts, and a replication sample of 3735 individuals. Results: The twin-based heritability for age at first cannabis use was 38% [95% confidence interval (CI) = 19–60%]. Shared and unique environmental factors explained 39% (95% CI = 20–56%) and 22% (95% CI = 16–29%). The genome-wide association meta-analysis identified five single nucleotide polymorphisms (SNPs) on chromosome 16 within the calcium-transporting ATPase gene (ATP2C2) at P 0.8), with the strongest association at the intronic variant rs1574587 (P = 4.09E-09). Gene-based tests of association identified the ATP2C2 gene on 16q24.1 (P = 1.33e-06). Although the five SNPs and ATP2C2 did not replicate, ATP2C2 has been associated with cocaine dependence in a previous study. ATP2B2, which is a member of the same calcium signalling pathway, has been associated previously with opioid dependence. SNP-based heritability for age at first cannabis use was non-significant. Conclusion: Age at cannabis initiation appears to be moderately heritable in western countries, and individual differences in onset can be explained by separate but correlated genetic liabilities. The significant association between age of initiation and ATP2C2 is consistent with the role of calcium signalling mechanisms in substance use disorders.

Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case–control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 × 10–13) and African ancestries (rs2066702; P = 2.2 × 10–9). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit–hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.

ObjectiveInadequate immunoregulation and elevated inflammation may be risk factors for posttraumatic stress disorder (PTSD), and microbial inputs are important determinants of immunoregulation; however, the association between the gut microbiota and PTSD is unknown. This study investigated the gut microbiome in a South African sample of PTSD-affected individuals and trauma-exposed (TE) controls to identify potential differences in microbial diversity or microbial community structure.MethodsThe Clinician-Administered PTSD Scale for DSM-5 was used to diagnose PTSD according to Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria. Microbial DNA was extracted from stool samples obtained from 18 individuals with PTSD and 12 TE control participants. Bacterial 16S ribosomal RNA gene V3/V4 amplicons were generated and sequenced. Microbial community structure, α-diversity, and β-diversity were analyzed; random forest analysis was used to identify associations between bacterial taxa and PTSD.ResultsThere were no differences between PTSD and TE control groups in α- or β-diversity measures (e.g., α-diversity: Shannon index, t = 0.386, p = .70; β-diversity, on the basis of analysis of similarities: Bray-Curtis test statistic = -0.033, p = .70); however, random forest analysis highlighted three phyla as important to distinguish PTSD status: Actinobacteria, Lentisphaerae, and Verrucomicrobia. Decreased total abundance of these taxa was associated with higher Clinician-Administered PTSD Scale scores (r = -0.387, p = .035).ConclusionsIn this exploratory study, measures of overall microbial diversity were similar among individuals with PTSD and TE controls; however, decreased total abundance of Actinobacteria, Lentisphaerae, and Verrucomicrobia was associated with PTSD status.

Background The human oral microbiome is formed early in development. Its composition is influenced by environmental factors including diet, substance use, oral health, and overall health and disease. The influence of human genes on the composition and stability of the oral microbiome is still poorly understood. We studied both environmental and genetic characteristics on the oral microbiome in a large twin sample as well as in a large cohort of unrelated individuals. We identify several significantly heritable features of the oral microbiome. The heritability persists in twins even when their cohabitation changes. The heritability of these traits correlates with the cumulative genetic contributions of over half a million single nucleotide sequence variants measured in a different population of unrelated individuals. Comparison of same-sex and opposite sex cotwins showed no significant differences. We show that two new loci on chromosomes 7 and 12 are associated with the most heritable traits. Results An analysis of 752 twin pairs from the Colorado Twin Registry, shows that the beta-diversity of monozygotic twins is significantly lower than for dizygotic or unrelated individuals. This is independent of cohabitation status. Intraclass correlation coefficients of nearly all taxa examined were higher for MZ than DZ twin pairs. A comparison of individuals sampled over 2-7 years confirmed previous reports that the oral microbiome remains relatively more stable in individuals over that time than to unrelated people. Twin modeling shows that a number of microbiome phenotypes were more than 50% heritable consistent with the hypothesis that human genes influence microbial populations. To identify loci that could influence microbiome phenotypes, we carried out an unbiased GWAS analysis which identified one locus on chromosome 7 near the gene IMMPL2 that reached genome-wide significance after correcting for multiple testing. Another locus on chromosome 12 near the non-coding RNA gene INHBA-AS1 achieved genome-wide significance when analyzed using KGG4 that sums SNP significance across coding genes. Discussion Using multiple methods, we have demonstrated that some aspects of the human oral microbiome are heritable and that with a relatively small sample we were able to identify two previously unidentified loci that may be involved. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-4008-8) contains supplementary material, which is available to authorized users.

To provide novel insights into the biology of opioid dependence (OD) and opioid use (i.e., exposure, OE), we completed a genome-wide analysis comparing up to 4,503 OD cases, 4,173 opioid-exposed controls, and 32,500 opioid-unexposed controls. Among the variants identified, rs9291211 was associated with OE (a comparison of exposed vs. unexposed controls; z=-5.39, p=7.2×10−8). This variant regulates the transcriptomic profiles of SLC30A9 and BEND4 in multiple brain tissues and was previously associated with depression, alcohol consumption, and neuroticism. A phenome-wide scan of rs9291211 in the UK Biobank (N>360,000) found association of this variant with propensity to use dietary supplements (p=1.68×10−8). With respect to the same OE phenotype in the gene-based analysis, we identified SDCCAG8 (z=4.69, p=10−6), which was previously associated with educational attainment, risk-taking behaviors, and schizophrenia. In addition, rs201123820 showed a genome-wide significant difference between OD cases and unexposed controls (z=5.55, p=2.9×10−8) and a significant association with musculoskeletal disorders in the UK Biobank (p=4.88×10−7). A polygenic risk score (PRS) based on a GWAS of risk-tolerance (N=466,571) was positively associated with OD (OD cases vs. unexposed controls, p=8.1×10−5; OD cases vs. exposed controls, p=0.054) and OE (exposed controls vs. unexposed controls, p=3.6×10−5). A PRS based on a GWAS of neuroticism (N=390,278) was positively associated with OD (OD cases vs. unexposed controls, p=3.2×10−5; OD cases vs. exposed controls, p=0.002) but not with OE (p=0.671). Our analyses highlight the difference between dependence and exposure and the importance of considering the definition of controls (exposed vs. unexposed) in studies of addiction.

Some of the most widely studied variants in psychiatric genetics include variable number tandem repeat variants (VNTRs) in SLC6A3, DRD4, SLC6A4, and MAOA. While initial findings suggested large effects, their importance with respect to psychiatric phenotypes is the subject of much debate with broadly conflicting results. Despite broad interest, these loci remain absent from the largest available samples, such as the UK Biobank, limiting researchers' ability to test these contentious hypotheses rigorously in large samples. Here, using two independent reference datasets, we report out-of-sample imputation accuracy estimates of >0.96 for all four VNTR variants and one modifying SNP, depending on the reference and target dataset. We describe the imputation procedures of these candidate variants in 486,551 UK Biobank individuals, and have made the imputed variant data available to UK Biobank researchers. This resource, provided to the scientific community, will allow the most rigorous tests to-date of the roles of these variants in behavioral and psychiatric phenotypes.

Meta-analysis of genetic association studies increases sample size and the power for mapping complex traits. Existing methods are mostly developed for datasets without missing values, i.e. the summary association statistics are measured for all variants in contributing studies. In practice, genotype imputation is not always effective. This may be the case when targeted genotyping/sequencing assays are used or when the un-typed genetic variant is rare. Therefore, contributed summary statistics often contain missing values. Existing methods for imputing missing summary association statistics and using imputed values in meta-analysis, approximate conditional analysis, or simple strategies such as complete case analysis all have theoretical limitations. Applying these approaches can bias genetic effect estimates and lead to seriously inflated type-I or type-II errors in conditional analysis, which is a critical tool for identifying independently associated variants. To address this challenge and complement imputation methods, we developed a method to combine summary statistics across participating studies and consistently estimate joint effects, even when the contributed summary statistics contain large amounts of missing values. Based on this estimator, we proposed a score statistic called PCBS (partial correlation based score statistic) for conditional analysis of single-variant and gene-level associations. Through extensive analysis of simulated and real data, we showed that the new method produces well-calibrated type-I errors and is substantially more powerful than existing approaches. We applied the proposed approach to one of the largest meta-analyses to date for the cigarettes-per-day phenotype. Using the new method, we identified multiple novel independently associated variants at known loci for tobacco use, which were otherwise missed by alternative methods. Together, the phenotypic variance explained by these variants was 1.1%, improving that of previously reported associations by 71%. These findings illustrate the extent of locus allelic heterogeneity and can help pinpoint causal variants., Author summary It is of great interest to estimate the joint effects of multiple variants from large scale meta-analyses, in order to fine-map causal variants and understand the genetic architecture for complex traits. The summary association statistics from participating studies in a meta-analysis often contain missing values at some variant sites, as the imputation methods may not work well and the variants with low imputation quality will be filtered out. Missingness is especially likely when the underlying genetic variant is rare or the participating studies use targeted genotyping array that is not suitable for imputation. Existing methods for conditional meta-analysis do not properly handle missing data, and can incorrectly estimate correlations between score statistics. As a result, they can produce highly inflated type-I errors for conditional analysis, which will result in overestimated phenotypic variance explained and incorrect identification of causal variants. We systematically evaluated this bias and proposed a novel partial correlation based score statistic. The new statistic has valid type-I errors for conditional analysis and much higher power than the existing methods, even when the contributed summary statistics contain a large fraction of missing values. We expect this method to be highly useful in the sequencing age for complex trait genetics.

Some of the most widely studied polymorphisms in psychiatric genetics include variable number tandem repeat polymorphisms (VNTRs) in SLC6A3, DRD4, SLC6A4, and MAOA. While initial findings suggested large effects, their importance with respect to psychiatric phenotypes is the subject of much debate with broadly conflicting results. Despite broad interest, these loci remain absent from the largest available samples, such as the UK Biobank, limiting researchers’ ability to test these contentious hypotheses rigorously in large samples. Here, using two independent reference datasets, we report out-of-sample imputation accuracy estimates of >0.96 for all four VNTR polymorphisms and one modifying SNP, depending on the reference and target dataset. We describe the imputation procedures of these candidate polymorphisms in 486,551 UK Biobank individuals, and have made the imputed polymorphism data available to UK Biobank researchers. This resource, provided to the community, will allow the most rigorous tests to-date of the roles of these polymorphisms in behavioral and psychiatric phenotypes.

© 2015, Springer Science+Business Media New York. Behavioral disinhibition (BD) is a quantitative measure designed to capture the heritable variation encompassing risky and impulsive behaviors. As a result, BD represents an ideal target for discovering genetic loci that predispose individuals to a wide range of antisocial behaviors and substance misuse that together represent a large cost to society as a whole. Published genome-wide association studies (GWAS) have examined specific phenotypes that fall under the umbrella of BD (e.g. alcohol dependence, conduct disorder); however no GWAS has specifically examined the overall BD construct. We conducted a GWAS of BD using a sample of 1,901 adolescents over-selected for characteristics that define high BD, such as substance and antisocial behavior problems, finding no individual locus that surpassed genome-wide significance. Although no single SNP was significantly associated with BD, restricted maximum likelihood analysis estimated that 49.3 % of the variance in BD within the Caucasian sub-sample was accounted for by the genotyped SNPs (p = 0.06). Gene-based tests identified seven genes associated with BD (p ≤ 2.0 × 10−6). Although the current study was unable to identify specific SNPs or pathways with replicable effects on BD, the substantial sample variance that could be explained by all genotyped SNPs suggests that larger studies could successfully identify common variants associated with BD.

Meta-analysis of genetic association studies increases sample size and the power for mapping complex traits. Existing methods are mostly developed for datasets without missing values. In practice, genotype imputation is not always effective, e.g. when targeted genotyping/sequencing assays are used or when the un-typed genetic variant is rare. Therefore, contributed summary statistics often contain missing values. Naïve extensions of existing methods either replace missing summary statistics with 0 or discard studies with missing data. These approaches can bias genetic effect estimates and lead to seriously inflated type-I or II errors in conditional analysis, which is a critical tool for identifying independently associated variants.To address this challenge and complement imputation methods, we developed a method to combine summary statistics across participating studies and consistently estimate joint effects, even when the contributed summary statistics contain large amount of missing values. Based on this estimator, we propose a score statistic we call PCBS (partial correlation based score statistic) for conditional analysis of single-variant and gene-level associations. Through extensive analysis of simulated and real data, we showed that the new method produces well-calibrated type-I errors and is substantially more powerful than existing approaches. We applied the proposed approach to analyze the CHRNA5-CHRNB4-CHRNA3 locus in a large-scale meta-analysis for cigarettes-per-day. Using the new method, we identified three novel variants, independent of known association signals, which were otherwise missed by alternative methods. Together, the phenotypic variance explained by these variants is .46%, improving that of previously reported associations by 17%. These findings illustrate the extent of locus allelic heterogeneity and can help pinpoint causal variants.AUTHOR SUMMARYIt is of great interest to estimate the joint and conditional effects of multiple correlated variants from large scale meta-analysis, in order to fine map causal variants and understand the genetic architecture for complex traits. The contributed summary statistics from participating studies in a meta-analysis often contain missing values, as the imputation methods are not often effective, especially when the underlying genetic variant is rare or the participating studies use targeted genotyping array that is not suitable for imputation. Existing meta-analysis methods do not properly handle missing data, and can incorrectly estimate correlations between score statistics. As a result, they can produce highly biased estimates of joint effects and highly inflated type-I errors for conditional analysis, which will in turn result in overestimated phenotypic variance explained and incorrect identification of causal variants. We systematically evaluated this bias and proposed a novel partial correlation based score statistic. The new statistic has valid type-I errors for conditional analysis and much higher power than the existing methods, even when the contributed summary statistics in the meta-analysis contain a large fraction of missing values. We expect this method to be highly useful in the sequencing age for complex trait genetics.

Motivation:There is great interest to understand the impact of rare variants in human diseases using large sequence datasets. In deep sequences datasets of >10,000 samples, ∼10% of the variant sites are observed to be multi-allelic. Many of the multi-allelic variants have been shown to be functional and disease relevant. Proper analysis of multi-allelic variants is critical to the success of a sequencing study, but existing methods do not properly handle multi-allelic variants and can produce highly misleading association results.Results:We propose novel methods to encode multi-allelic sites, conduct single variant and gene-level association analyses, and perform meta-analysis for multi-allelic variants. We evaluated these methods through extensive simulations and the study of a large meta-analysis of ∼18,000 samples on the cigarettes-per-day phenotype. We showed that our joint modeling approach provided an unbiased estimate of genetic effects, greatly improved the power of single variant association tests, and enhanced gene-level tests over existing approaches.Availability:Software packages implementing these methods are available at (https://github.com/zhanxw/rvtestshttp://genome.sph.umich.edu/wiki/RareMETAL).Contact:xiaowei.zhan@utsouthwestem.edu; dajiang.liu@psu.edu

Recent work using a mouse model has identified the glutamate metabotropic receptor 7 (Grm7) gene as a strong candidate gene for alcohol consumption. Although there has been some work examining the effect of human glutamate metabotropic receptor 7 (GRM7) polymorphisms on human substance use disorders, the majority of the work has focused on other psychiatric disorders such as ADHD, major depressive disorder, schizophrenia, bipolar disorder, panic disorder, and autism spectrum disorders. The current study aimed to evaluate evidence for association between GRM7 and alcohol behaviors in humans using a single nucleotide polymorphism (SNP) approach, as well as a gene-based approach. Using 1803 non-Hispanic European Americans (EAs) (source: the Colorado Center on Antisocial Drug Dependence [CADD]) and 1049EA subjects from an independent replication sample (source: the Genetics of Antisocial Drug Dependence [GADD]), two SNPs in GRM7 were examined for possible association with alcohol consumption using two family-based association tests implemented in FBAT and QTDT. Rs3749380 was suggestively associated with alcohol consumption in the CADD sample (p=0.010) with the minor T allele conferring risk. There was no evidence for association in the GADD sample. A gene-based test using four Genome-Wide Association Studies (GWAS) revealed no association between variation in GRM7 and alcohol consumption. This study had several limitations: the SNPs chosen likely do not tag expression quantitative trait loci; a human alcohol consumption phenotype was used, complicating the interpretation with respect to rodent studies that found evidence for a cis-regulatory link between alcohol preference and Grm7; and only common SNPs imputed in all four datasets were included in the gene-based test. These limitations highlight the fact that rare variants, some potentially important common signals in the gene, and regions farther upstream were not examined.

Variation in the composition of the human oral microbiome in health and disease has been observed. We have characterized inter- and intra-individual variation of microbial communities of 107 individuals in one of the largest cohorts to date (264 saliva samples), using culture-independent 16S rRNA pyrosequencing. We examined the salivary microbiome in up to three time-points during 10 yr spanning adolescence, and determined the influence of human genotype, gender, age, and weight class. Participants, including 27 monozygotic and 18 dizygotic twin pairs, were sampled mainly at ages 12–13, 17–18, and 22–24, with a few sampled as early as 8 yr of age. In contrast to gut or skin microbiomes, there is a core genus-level salivary microbiome. Individuals are more similar to themselves and their co-twins in the 12–17 and in the 17–22 cohorts than to the whole sample population, but not over the 10 yr from 12 to 22; and monozygotic twin pairs are statistically not more similar than dizygotic twin pairs. The data are most consistent with shared environment serving as the main determinant of microbial populations. Twins resemble each other more closely than the whole population at all time-points, but become less similar to each other when they age and no longer cohabit. Several organisms have age-specific abundance profiles, including members of the genera Veillonella, Actinomyces, and Streptococcus. There is no clear effect of weight class and gender. The results of this work will provide a basis to further study oral microbes and human health.

This study explores the association between a highly heritable behavioral disinhibition phenotype and the protein kinase C gamma (PRKCG) gene in an ethnically diverse youth sample from Colorado, USA. The rationale for this study was based on the impulsive behavior and increased ethanol consumption observed in the protein kinase C gamma (PKC-gamma)-deficient mouse model. Two composite behavioral disinhibition phenotypes and their component behavioral scores [conduct disorder, attention-deficit hyperactivity disorder (ADHD), substance experimentation (SUB) and novelty-seeking] were examined for association with five independent PRKCG single nucleotide polymorphisms (SNPs). Association analysis for the five individual SNPs revealed modest genetic association of Exon 14 (rs2242244) and Upstream (rs307941) markers with the behavioral disinhibition composite variables in the combined, Hispanic and African-American samples. Additionally, haplotype-based association analysis for two SNPs located in Intron 3 (rs402691) and Exon 6 (rs3745406) indicated a significant overall association of the PRKCG locus with the ADHD-hyperactive subscale scores in the combined and Caucasian samples, supporting the relation between impulsive behaviors and the PRKCG gene. A significant haplotype association was also observed with SUB scores but only in the Hispanic ethnic group, highlighting the marker variability for each ethnic group. In conclusion, our results support the role of the PKC-gamma enzyme in behavioral impulsivity previously observed in mice. This study provides the first exploration of the PRKCG gene and its association with behavioral disinhibition and warrants further study in other larger population samples.

Cannabis is a major substance of abuse, and the gene encoding for the central cannabinoid receptor (CNR1) is a logical candidate gene for vulnerability toward developing symptoms of cannabis dependence. We studied four single-nucleotide polymorphisms (SNPs) in the CNR1 gene for association with having one or more symptoms of cannabis dependence in 541 adolescent subjects who had all tried cannabis five or more times. Cases (327) were defined as those who had tried marijuana and developed one or more symptoms, and controls (214) as those who had tried marijuana but developed no dependence symptoms. Cannabis dependence symptoms were assessed in these youth when they were 17 or older with the Composite International Diagnostic Interview- Substance Abuse Module. Univariate (single-marker) association tests demonstrated that SNP rs806380, located in intron 2 of the CNR1 gene, was significantly associated with developing one or more cannabis dependence symptoms, with the G allele having a protective effect (p < 0.02). This was consistent with the results of the global haplotype test (p < 0.01). One of the common haplotypes examined (present in 21% of the subjects) was significantly associated with a lower rate of having one or more cannabis dependence symptoms. Our findings provide evidence suggesting that a common CNR1 haplotype is associated with developing fewer cannabis dependence symptoms among adolescents who have experimented with cannabis.

The mu1 opioid receptor gene, OPRM1, has long been a high-priority candidate for human genetic studies of addiction. Because of its potential functional significance, the non-synonymous variant rs1799971 (A118G, Asn40Asp) in OPRM1 has been extensively studied, yet its role in addiction has remained unclear, with conflicting association findings. To resolve the question of what effect, if any, rs1799971 has on substance dependence risk, we conducted collaborative meta-analyses of 25 datasets with over 28,000 European-ancestry subjects. We investigated non-specific risk for “general” substance dependence, comparing cases dependent on any substance to controls who were non-dependent on all assessed substances. We also examined five specific substance dependence diagnoses: DSM-IV alcohol, opioid, cannabis, and cocaine dependence, and nicotine dependence defined by the proxy of heavy/light smoking (cigarettes-per-day >20 vs. ≤10). The G allele showed a modest protective effect on general substance dependence (OR = 0.90, 95 % C.I. [0.83–0.97], p value = 0.0095, N = 16,908). We observed similar effects for each individual substance, although these were not statistically significant, likely because of reduced sample sizes. We conclude that rs1799971 contributes to mechanisms of addiction liability that are shared across different addictive substances. This project highlights the benefits of examining addictive behaviors collectively and the power of collaborative data sharing and meta-analyses.

Human chromosome 18 differs from its homologues in the great apes by a pericentric inversion. We have identified a chimpanzee bacterial artificial chromosome that spans a region where a break is likely to have occurred in a human progenitor and have characterized the corresponding regions in both chimpanzees and humans. Interspecies sequence comparisons indicate that the ancestral break occurred between the genes ROCK1 and USP14. In humans, the inversion places ROCK1 near centromeric heterochromatin and USP14 adjacent to highly repetitive subtelomeric repeats. In addition, we provide evidence for a human segmental duplication that may have provided a mechanism for the inversion.

Previous studies have shown associations between single nucleotide polymorphisms (SNPs) in gamma aminobutyric acid receptor alpha 2 (GABRA2) and adolescent conduct disorder (CD) and alcohol dependence in adulthood, but not adolescent alcohol dependence. The present study was intended as a replication and extension of this work, focusing on adolescent CD, adolescent alcohol abuse and dependence (AAD), and adult AAD. Family based association tests were run using Hispanics and non-Hispanic European American subjects from two independent longitudinal samples. Although the analysis provided nominal support for an association with rs9291283 and AAD in adulthood and CD in adolescence, the current study failed to replicate previous associations between two well replicated GABRA2 SNPs and CD and alcohol dependence. Overall, these results emphasize the utility of including an independent replication sample in the study design, so that the results from an individual sample can be weighted in the context of its reproducibility. © 2014 Springer Science+Business Media New York.

Comorbidity among childhood disruptive behavioral disorders is commonly reported in both epidemiologic and clinical studies. These problems are also associated with early substance use and other markers of behavioral disinhibition. Previous twin research has suggested that much of the covariation between antisocial behavior and alcohol dependence is due to common genetic influences. Similar results have been reported for conduct problems and hyperactivity. For the present study, an adolescent sample consisting of 172 MZ and 162 DZ twin pairs, recruited through the Colorado Twin Registry and the Colorado Longitudinal Twin Study were assessed using standardized psychiatric interviews and personality assessments. DSM-IV symptom counts for conduct disorder and attention deficit hyperactivity disorder, along with a measure of substance experimentation and novelty seeking, were used as indices of a latent behavioral disinhibition trait. A confirmatory factor model fit to individual-level data showed a strong common factor accounting for 16‐42% of the observed variance in each measure. A common pathway model evaluating the genetic and environmental architecture of the latent phenotype suggested that behavioral disinhibition is highly heritable (a 2 = 0.84), and is not influenced significantly by shared environmental factors. A residual correlation between conduct disorder and substance experimentation was explained by shared environmental effects, and a residual correlation between attention deficit hyperactivity disorder and novelty seeking was accounted for by genetic dominance. These results suggest that a variety of adolescent problem behaviors may share a common underlying genetic risk. Am. J. Med. Genet. (Neuropsychiatr. Genet.)

Myosin heavy chains (MyHCs) are highly conserved ubiquitous actin-based motor proteins that drive a wide range of motile processes in eukaryotic cells. MyHC isoforms expressed in skeletal muscles are encoded by a multigene family that is clustered on syntenic regions of human and mouse chromosomes 17 and 11, respectively. In an effort to gain a better understanding of the genomic organization of the skeletal MyHC genes and its effects on the regulation, function, and molecular genetics of this multigene family, we have constructed high-resolution physical maps of both human and mouse loci using PCR-based marker content mapping of P1-artificial chromosome clones. Genes encoding six MyHC isoforms have been mapped with respect to their linear order and transcriptional orientations within a 350-kb region in both human and mouse. These maps reveal that the order, transcriptional orientation, and relative intergenic distances of these genes are remarkably conserved between these species. Unlike many clustered gene families, this order does not reflect the known temporal expression patterns of these genes. However, the conservation of gene organization since the estimated divergence of these species (≈75–110 million years ago) suggests that the physical organization of these genes may be significant for their regulation and function.

The t(11;18)(q21;q21) translocation has recently been identified as a recurring chromosomal abnormality in a subset of extranodal marginal zone B-cell lymphoma, a low-grade lymphoma of mucosa-associated lymphoid tissue (MALT). Neither the 11q21 nor the 18q21 breakpoints have been characterized by molecular genetic analysis. As a prelude to isolation of the gene(s) involved in this translocation, we have mapped the 18q21 breakpoint region by fluorescence in situ hybridization (FISH) of YAC and PAC clones. We mapped 37 YACs assigned to a 29-cM region within the chromosomal band 18q21. Using nine of these YACs in single- and/or dual-color FISH to analyze three cases of MALT lymphomas with the t(11;18)(q21;q21) translocation, we localized the breakpoints within a 1.6-Mb nonchimeric YAC (938E1). This YAC is useful for the detection of the translocation in metaphase and in interphase cells. A nonchimeric YAC contig of an 8-cM region around the breakpoint comprising nine YACs and a PAC contig of YAC 938E1 were constructed, which enabled the refinement of the breakpoint region in the proximal region of the YAC within a

The alpha1-protease inhibitor proteins of laboratory mice are homologous in sequence and function to human alpha1-antitrypsin and are encoded by a highly conserved multigene family comprised of five members. In humans, the inhibitor is expressed in liver and in macrophages and decreased expression or inhibitory activity is associated with a deficiency syndrome which can result in emphysema and liver disease in affected individuals. It has been proposed that macrophage expression may be an important component of the function of human alpha1-antitrypsin. Clearly, it is desirable to develop a mouse model of this deficiency syndrome, however, efforts to do this have been largely unsuccessful. In this paper, we report that aside from the issues of potentially redundant gene function, the mouse may not be a suitable animal for such studies, because there is no significant expression of murine alpha1-protease inhibitor in the macrophages of mice. This difference between the species appears to result from an absence of a functional macrophage-specific promoter in mice.

Keratin proteins constitute intermediate filaments and are the major differentiation products of mammalian epithelial cells. The epithelial keratins are classified into two groups, type I and type II, and one member of each group is expressed in a given epithelial cell differentiation stage. Mutations in type I and type II keratin genes have now been implicated in three different human genetic disorders, epidermolysis bullosa simplex, epidermolytic hyperkeratosis, and epidermolytic palmoplantar keratoderma. Members of the type I keratins are mapped to human chromosome 17, and the type II keratin genes are mapped to chromosome 12. To understand the organization of the type II keratin genes on chromosome 12, we isolated several yeast artificial chromosomes carrying these keratin genes and examined them in detail. We show that eight already known type II keratin genes are located in a cluster at 12q13, and their relative organization reflects their evolutionary relationship. We also determined that a type I keratin gene, KRT18, is located next to its partner, KRT8, in this cluster. Careful examination of the cluster also revealed that there may be a number of additional keratin genes at this locus that have not been described previously.

The consistent involvement of the region 12q13-q15 in numerous human tumors speaks in favor of the presence of genes that may contribute to oncogenesis. Mapping genes within this region of chromosome 12 is a necessary step toward the identification of those that play a role in this process. We have undertaken a multiplex analysis using translocation breakpoint mapping to order from the centromere to the telomere a series of 24 loci from the region 12q12-q22. Thirteen adipose tissue tumors with seven different chromosome changes involving the long arm of chromosome 12 (12q) were used. Since most of these loci are genes or anonymous DNA segments largely available to the scientific community, this map should be useful for investigation of genetic disorders associated with chromosome 12q. While these breakpoints were used as natural landmarks to order groups of loci, this work has positioned them more accurately, leading to a better chromosomal definition of the translocations than the one derived from standard cytogenetic studies.

Use of in-class concept questions with clickers can transform an instructor-centered “transmissionist” environment to a more learner-centered constructivist classroom. To compare the effectiveness of three different approaches using clickers, pairs of similar questions were used to monitor student understanding in majors’ and nonmajors’ genetics courses. After answering the first question individually, students participated in peer discussion only, listened to an instructor explanation only, or engaged in peer discussion followed by instructor explanation, before answering a second question individually. Our results show that the combination of peer discussion followed by instructor explanation improved average student performance substantially when compared with either alone. When gains in learning were analyzed for three ability groups of students (weak, medium, and strong, based on overall clicker performance), all groups benefited most from the combination approach, suggesting that peer discussion and instructor explanation are synergistic in helping students. However, this analysis also revealed that, for the nonmajors, the gains of weak performers using the combination approach were only slightly better than their gains using instructor explanation alone. In contrast, the strong performers in both courses were not helped by the instructor-only approach, emphasizing the importance of peer discussion, even among top-performing students.

The Colorado Center For Antisocial Drug Dependence (CADD) is using several research designs and strategies in its study of the genetic basis for antisocial drug dependence in adolescents. This study reports single nucleotide polymorphism (SNP) association results from a targeted gene assay (SNP chip) of 231 primarily Caucasian male probands in treatment with antisocial drug dependence and a matched set of community controls. The SNP chip was designed to assay 1500 SNPs distributed across 50 candidate genes that have had associations with substance use disorders and conduct disorder. There was an average gene-wide inter-SNP interval of 3000 base pairs. After eliminating SNPs with poor signals and low minor allele frequencies, 60 nominally significant associations were found among the remaining 1073 SNPs in 18 of 49 candidate genes. Although none of the SNPs achieved genome-wide association significance levels (defined as p

Nicotine addiction and alcohol dependence are highly comorbid disorders that are likely to share overlapping genetic components. We have examined two neuronal nicotinic receptor subunit genes (CHRNA4 and CHRNB2) for possible associations with nicotine and alcohol phenotypes, including measures of frequency of use and measures of initial subjective response in the period shortly after first using the drugs. The subjects were 1,068 ethnically diverse young adults participating in ongoing longitudinal studies of adolescent drug behaviors at the University of Colorado, representing both clinical and community samples. Analysis of six SNPs in the CHRNA4 gene provided modest support for an association with past 6 month use of alcohol in Caucasians (three SNPs with P < 0.08), but no evidence for an association with tobacco and CHRNA4 was detected. However, a SNP (rs2072658) located immediately upstream of CHRNB2 was associated with the initial subjective response to both alcohol and tobacco. This study provides the first evidence for association between the CHRNB2 gene and nicotine- and alcohol-related phenotypes, and suggests that polymorphisms in CHRNB2 may be important in mediating early responses to nicotine and alcohol.

Objective: Cannabis is the most frequently abused illicit substance among adolescents and young adults. Genetic risk factors account for part of the variation in the development of cannabis dependence symptoms; however, no linkage studies have been performed for cannabis dependence symptoms. This study aimed to identify such loci. Method: Three hundred and twenty-four sibling pairs from 192 families were assessed for cannabis dependence symptoms. Probands (13-19 years of age) were recruited from consecutive admissions to substance abuse treatment facilities. The siblings of the probands ranged in age from 12 to 25 years. A community-based sample of 4843 adolescents and young adults was utilized to define an age- and sex-corrected index of cannabis dependence vulnerability. DSM-IV cannabis dependence symptoms were assessed in youth and their family members with the Composite International Diagnostic Instrument-Substance Abuse Module. Siblings and parents were genotyped for 374 microsatellite markers distributed across the 22 autosomes (average inter-marker distance = 9.2 cM). Cannabis dependence symptoms were analyzed using Merlin-regress, a regression-based method that is robust to sample selection. Results: Evidence for suggestive linkage was found on chromosome 3q21 near marker D3S1267 (LOD = 2.61), and on chromosome 9q34 near marker D9S1826 (LOD = 2.57). Conclusions: This is the first reported linkage study of cannabis dependence symptoms. Other reports of linkage regions for illicit substance dependence have been reported near 3q21, suggesting that this region may contain a quantitative trait loci influencing cannabis dependence and other substance use disorders. © 2006 Elsevier Ireland Ltd. All rights reserved., link_to_OA_fulltext

We have analyzed nearly 2,000 myosin heavy chain gene (Myh) clones representing over 30 different transcripts from seven of eight striated muscle Myh genes expressed in mouse. We also report the transcriptional start sites (TSS) for the mouse developmental Myh genes. The data reveal a previously unknown diversity of TSSs and 5'-end alternative splicing in these transcripts. The cardiac Myh6 gene had two major TSSs. Use of the major downstream site led to an alternatively spliced second exon. Each of the other Myh genes had one major TATA-directed TSS and one or more minor alternative TSSs, some associated with alternative splicing. The minor transcripts were associated with polysomes and their spatial-temporal expression largely mirrored that of the major transcripts in wild-type, Myh1 null, Myh4 null, injured, and uninjured muscle, except that one form of Myh7, detected in heart, was not detected in diaphragm, and the ratio of the two major Myh6 transcripts varied in some circumstances. These findings indicate that alternative TSS usage and alternative splicing in the 5'-UTR are a general feature of murine Myh gene expression and that Myh gene regulation is more complex than previously appreciated.

Background Among adolescents, externalizing problem behavior and substance use disorders are often comorbid. Familial influences, including shared genetic risk factors, may account for part of this comorbidity. Previously we reported 2 chromosomal regions (3q24-3q25 and 9q34) likely to contain genes that influence substance dependence vulnerability (DV) in adolescence. Objectives To identify quantitative trait loci (QTLs) that influence externalizing problem behavior in adolescence and to determine whether any identified QTL overlap chromosomal regions that influence DV. Design Regression-based QTL mapping procedures designed for selected sibling pair samples. Setting Patient probands were drawn from consecutive admissions to residential and outpatient (milieu-type) treatment facilities for substance abuse and deliquency operated by the University of Colorado; most of these patients were referred for treatment by juvenile justice or social service agencies. Patients A total of 249 proband-sibling pairs from 191 families were selected for the study. Patient probands were 13 to 19 years of age; siblings of the probands ranged in age from 12 to 25 years. Main Outcome Measures A community-based sample of 4493 adolescents and young adults was used to define clinically significant, heritable, age- and sex-normed indexes of DV, conduct disorder symptoms (CDS), and a composite index of antisocial substance dependence (DV + CDS). Siblings and parents were genotyped for 374 microsatellite markers distributed across the 22 autosomes (mean intermarker distance, 9.2 centimorgans). Results For both DV and CDS, there was evidence of linkage to the same region on chromosome 9q34, as well as to 3q24-3q25 for DV, and a novel region on chromosome 17q12 for CDS. Our composite index (DV + CDS) yielded the strongest evidence for linkage (logarithm of odds = 2.65) to the chromosome 9q34 region. Conclusion These results provide the first evidence of a potential molecular genetic basis for the comorbidity between DV and antisocial behavior.

Early childhood externalizing behavior is a stable and heritable pattern of aggressive and delinquent behavior that often leads to the development of serious psychiatric disorders such as conduct disorder and attention deficit hyperactivity disorder. We examined the relationship between parent reported externalizing behavior (assessed at ages 4, 7, and 9 years) and the VNTR polymorphism of the 3' untranslated region of SLC6A3 (DAT1) in a community sample of 790 children ascertained as part of our longitudinal twin and adoption studies. We applied the sibling-based methodology developed by Fulker et al. [1999: Am J Hum Genet 64:259-267] for estimating allelic association with quantitative traits, while controlling for population stratification. An extension of these methods allowed for the inclusion of monozygotic twins, dizygotic twins, siblings, and singletons. We have demonstrated that the 9-repeat variant of the DAT1 is a significant risk allele for externalizing behavior at ages 4 (P=0.001) and 7 years (P=0.02). Although the effect size was negligible at age 9 (P=0.92), a formal test of the developmental decrease in effect across the three ages was non-significant (P=0.70).

The initial goals of the Human Genome Project (HGP), to sequence the human genome and identify its constituent genes, are on the verge of being achieved. However, the scientific community recognizes that sequencing must be followed by understanding the manifold functions of human genes throughout

This paper describes an approach that provides Internet-based support for a genome center to map human chromosome 12, as a collaboration between laboratories at the Albert Einstein College of Medicine in Bronx, New York, and the Yale University School of Medicine in New Haven, Connecticut. Informatics is well established as an important enabling technology within the genome mapping community. The goal of this paper is to use the chromosome 12 project as a case study to introduce a medical informatics audience to certain issues involved in genome informatics and in the Internet-based support of collaborative bioscience research. Central to the approach described is a shared database (DB/12) with Macintosh clients in the participating laboratories running the 4th Dimension database program as a user-friendly front end, and a Sun SPARCstation-2 server running Sybase. The central component of the database stores information about yeast artificial chromosomes (YACs), each containing a segment of human DNA from chromosome 12 to which genome markers have been mapped, such that an overlapping set of YACs (called a "contig") can be identified, along with an ordering of the markers. The approach also includes 1) a map assembly tool developed to help biologists interpret their data, proposing a ranked set of candidate maps, 2) the integration of DB/12 with external databases and tools, and 3) the dissemination of the results. This paper discusses several of the lessons learned that apply to many other areas of bioscience, and the potential role for the field of medical informatics in helping to provide such support.

The major urinary proteins (MUPs) of mouse are a family of at least three major proteins which are synthesized in the liver of all strains of mice. The relative levels of synthesis of these proteins with respect to each other in the presence of testosterone is regulated by the Mup-a locus located on chromosome 4. In an effort to determine the mechanism of this regulation in molecular terms, a cDNA clone containing most of the coding region of a MUP protein has been isolated and identified by partial DNA sequence analysis. Using a combination of hybridization analysis and somatic cell genetics, the structural gene family has been unambiguously mapped to mouse chromosome 4. These data suggest that Mup-a regulation operates in a cis fashion and that models proposing trans regulation of MUP protein synthesis are unlikely.

cDNA clones complementary to liver mRNA were prepared and used to determine transcription rates of specific genes in isolated nuclei from liver, brain, and hepatoma cells. The cDNA sequences complementary to mRNA found only (or mainly) in the liver hybridize to labeled nuclear RNA only from liver nuclei. It appears that transcriptional events are primarily responsible for the synthesis of these, and perhaps most, tissue-specific moderately abundant mRNAs.