A large-scale genome-wide association study meta-analysis of cannabis use disorder.

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 (rg 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.

Early Signs of Gut Microbiome Aging: Biomarkers of Inflammation, Metabolism, and Macromolecular Damage in Young Adulthood.

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.

Association Analysis and Meta-Analysis of Multi-Allelic Variants for Large-Scale Sequence Data.

There is great interest in understanding the impact of rare variants in human diseases using large sequence datasets. In deep sequence 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. 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.

Leveraging genome-wide data to investigate differences between opioid use vs. opioid dependence in 41,176 individuals from the Psychiatric Genomics Consortium.

To provide insights into the biology of opioid dependence (OD) and opioid use (i.e., exposure, OE), we completed a genome-wide analysis comparing 4503 OD cases, 4173 opioid-exposed controls, and 32,500 opioid-unexposed controls, including participants of European and African descent (EUR and AFR, respectively). Among the variants identified, rs9291211 was associated with OE (exposed vs. unexposed controls; EUR 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 (EUR + AFR 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 (AFR 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 vs. unexposed controls, p = 8.1 × 10-5; OD cases vs. exposed controls, p = 0.054) and OE (exposed 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 vs. unexposed controls, p = 3.2 × 10-5; OD vs. exposed controls, p = 0.002) but not with OE (p = 0.67). Our analyses highlight the difference between dependence and exposure and the importance of considering the definition of controls in studies of addiction.

Association between the oral microbiome and brain resting state connectivity in smokers.

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 sequencing for microbiome and functional neuroimaging technique 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 composition, functional network connectivity, and the associations between microbial shifts and 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 microbiota, suggesting a correlated 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.

Proper conditional analysis in the presence of missing data: Application to large scale meta-analysis of tobacco use 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.

Genetic influences on the human oral microbiome.

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.

The Microbiome in Posttraumatic Stress Disorder and Trauma-Exposed Controls: An Exploratory Study.

OBJECTIVE: Inadequate 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. METHODS: The 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 ß-diversity were analyzed; random forest analysis was used to identify associations between bacterial taxa and PTSD. RESULTS: There were no differences between PTSD and TE control groups in α- or ß-diversity measures (e.g., α-diversity: Shannon index, t = 0.386, p = .70; ß-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). CONCLUSIONS: In 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.

Test for association of common variants in GRM7 with alcohol consumption.

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 1049 EA 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.

Examination of genetic variation in GABRA2 with conduct disorder and alcohol abuse and dependence in a longitudinal study.

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.

Nurture trumps nature in a longitudinal survey of salivary bacterial communities in twins from early adolescence to early adulthood.

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.

Association of candidate genes with antisocial drug dependence in adolescents.

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<.000001), two genes probed with multiple SNPs (OPRM1 and CHRNA2) emerged as plausible candidates for a role in antisocial drug dependence after gene-based permutation tests. The custom-designed SNP chip served as an effective and flexible platform for rapid interrogation of a large number of plausible candidate genes.

The human protein kinase C gamma gene (PRKCG) as a susceptibility locus for behavioral disinhibition.

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.

Association of the neuronal nicotinic receptor beta2 subunit gene (CHRNB2) with subjective responses to alcohol and nicotine.

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.

A genome-wide scan for loci influencing adolescent cannabis dependence symptoms: evidence for linkage on chromosomes 3 and 9.

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=9.2cM). 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.

Diversity in transcriptional start site selection and alternative splicing affects the 5'-UTR of mouse striated muscle myosin transcripts.

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.

A genome-wide search for quantitative trait Loci that influence antisocial drug dependence in adolescence.

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 delinquency 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.

Inversion, duplication, and changes in gene context are associated with human chromosome 18 evolution.

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.

A genome-wide search for quantitative trait loci influencing substance dependence vulnerability in adolescence.

This study describes results from a genome-wide search for quantitative trait loci (QTL) influencing substance dependence vulnerability in adolescence. We utilized regression-based multipoint (and single-point) QTL mapping procedures designed for selected sibpair samples. Selected sibling pairs included 250 proband-sibling pairs from 192 families. Clinical probands (13-19 years of age) were drawn from consecutive admissions to substance abuse treatment facilities in the Denver metropolitan area; siblings of probands ranged in age from 12 to 25 years. In addition to the selected sample, a community-based sample of 3676 adolescents and young adults were utilized to define a clinically-significant, heritable, age- and sex-normed index of substance dependence vulnerability-a priori and independent of our linkage results. Siblings and their parents were genotyped for 374 STR micro-satellite markers distributed across the 22 autosomes (average inter-marker distance=9.2 cM). Non-parametric single-point linkage results indicated 17 markers on 11 chromosomes with nominally significant tests of linkage; six markers with LOD scores greater than 1.0 and one marker (D3S1614) with a LOD score of 2.2. Multipoint mapping corroborated two locations and provided preliminary evidence for linkage to regions on chromosome 3q24-25 (near markers D3S1279 and D3S1614) and chromosome 9q34 (near markers D9S1826 and D9S1838).

Genotyping of three candidate genes after whole-genome preamplification of DNA collected from buccal cells.

The amount of genomic DNA obtained from buccal cell methods may be suboptimal for large-scale genetics projects, because the quantity of DNA may be insufficient for the number of analyses proposed. Primer extension preamplification (PEP) methods that can amplify the entire genome 100-fold or more, offer a potential solution to this problem. We compared PEP buccal DNA with genomic buccal DNA from 315 individuals from 97 families of the Colorado Longitudinal Twin Study for three loci: the dopamine transporter, dopamine D4 receptor, and serotonin transporter. A total of 1890 genomic and 1890 PEP alleles were assessed, and 1670 comparisons (88%) agreed after a single determination. Fifty-three individuals had one or more failed initial polymerase chain reactions (PCR), with 81 failed PCRs in total, accounting for 162 missing allele calls. The failed PCRs were repeated once, and 146 of the missing allele calls were recovered. Comparisons between genomic and PEP DNA allele calls showed 37 individuals had one or more discrepancies, for a total of 52 inconsistencies. Of these, the initial PEP result was found to be correct in 18 cases, the initial genomic result was found to be correct in 25 cases, and 9 could not be resolved. Overall, rates of true calls, missing data, and genotyping errors for genomic and PEP DNA samples were nearly identical: of the 1890 genotypes assessed, true calls were found in 1845 genomic and 1840 PEP samples, missing genotypes in 18 genomic and 16 PEP samples, and incorrect assignments in 18 genomic and 25 PEP samples. These results suggest that routine whole-genome preamplification of genomic DNA is an appropriate method for providing DNA to genotype these loci.