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Biomedical subjects

John P Rice

Publications and source records attributed to John P Rice.

At least 19 recordsLinked to original sources

Novel genes identified in a high-density genome wide association study for nicotine dependence.

Tobacco use is a leading contributor to disability and death worldwide, and genetic factors contribute in part to the development of nicotine dependence. To identify novel genes for which natural variation contributes to the development of nicotine dependence, we performed a comprehensive genome wide association study using nicotine dependent smokers as cases and non-dependent smokers as controls. To allow the efficient, rapid, and cost effective screen of the genome, the study was carried out using a two-stage design. In the first stage, genotyping of over 2.4 million single nucleotide polymorphisms (SNPs) was completed in case and control pools. In the second stage, we selected SNPs for individual genotyping based on the most significant allele frequency differences between cases and controls from the pooled results. Individual genotyping was performed in 1050 cases and 879 controls using 31 960 selected SNPs. The primary analysis, a logistic regression model with covariates of age, gender, genotype and gender by genotype interaction, identified 35 SNPs with P-values less than 10(-4) (minimum P-value 1.53 x 10(-6)). Although none of the individual findings is statistically significant after correcting for multiple tests, additional statistical analyses support the existence of true findings in this group. Our study nominates several novel genes, such as Neurexin 1 (NRXN1), in the development of nicotine dependence while also identifying a known candidate gene, the beta3 nicotinic cholinergic receptor. This work anticipates the future directions of large-scale genome wide association studies with state-of-the-art methodological approaches and sharing of data with the scientific community.

Case-Control Studies↗

Cholinergic nicotinic receptor genes implicated in a nicotine dependence association study targeting 348 candidate genes with 3713 SNPs.

Nicotine dependence is one of the world's leading causes of preventable death. To discover genetic variants that influence risk for nicotine dependence, we targeted over 300 candidate genes and analyzed 3713 single nucleotide polymorphisms (SNPs) in 1050 cases and 879 controls. The Fagerström test for nicotine dependence (FTND) was used to assess dependence, in which cases were required to have an FTND of 4 or more. The control criterion was strict: control subjects must have smoked at least 100 cigarettes in their lifetimes and had an FTND of 0 during the heaviest period of smoking. After correcting for multiple testing by controlling the false discovery rate, several cholinergic nicotinic receptor genes dominated the top signals. The strongest association was from an SNP representing CHRNB3, the beta3 nicotinic receptor subunit gene (P = 9.4 x 10(-5)). Biologically, the most compelling evidence for a risk variant came from a non-synonymous SNP in the alpha5 nicotinic receptor subunit gene CHRNA5 (P = 6.4 x 10(-4)). This SNP exhibited evidence of a recessive mode of inheritance, resulting in individuals having a 2-fold increase in risk of developing nicotine dependence once exposed to cigarette smoking. Other genes among the top signals were KCNJ6 and GABRA4. This study represents one of the most powerful and extensive studies of nicotine dependence to date and has found novel risk loci that require confirmation by replication studies.

Adult↗

Genomewide linkage scan of 409 European-ancestry and African American families with schizophrenia: suggestive evidence of linkage at 8p23.3-p21.2 and 11p13.1-q14.1 in the combined sample.

We report the clinical characteristics of a schizophrenia sample of 409 pedigrees--263 of European ancestry (EA) and 146 of African American ancestry (AA)--together with the results of a genome scan (with a simple tandem repeat polymorphism interval of 9 cM) and follow-up fine mapping. A family was required to have a proband with schizophrenia (SZ) and one or more siblings of the proband with SZ or schizoaffective disorder. Linkage analyses included 403 independent full-sibling affected sibling pairs (ASPs) (279 EA and 124 AA) and 100 all-possible half-sibling ASPs (15 EA and 85 AA). Nonparametric multipoint linkage analysis of all families detected two regions with suggestive evidence of linkage at 8p23.3-q12 and 11p11.2-q22.3 (empirical Z likelihood-ratio score [Z(lr)] threshold >/=2.65) and, in exploratory analyses, two other regions at 4p16.1-p15.32 in AA families and at 5p14.3-q11.2 in EA families. The most significant linkage peak was in chromosome 8p; its signal was mainly driven by the EA families. Z(lr) scores >2.0 in 8p were observed from 30.7 cM to 61.7 cM (Center for Inherited Disease Research map locations). The maximum evidence in the full sample was a multipoint Z(lr) of 3.25 (equivalent Kong-Cox LOD of 2.30) near D8S1771 (at 52 cM); there appeared to be two peaks, both telomeric to neuregulin 1 (NRG1). There is a paracentric inversion common in EA individuals within this region, the effect of which on the linkage evidence remains unknown in this and in other previously analyzed samples. Fine mapping of 8p did not significantly alter the significance or length of the peak. We also performed fine mapping of 4p16.3-p15.2, 5p15.2-q13.3, 10p15.3-p14, 10q25.3-q26.3, and 11p13-q23.3. The highest increase in Z(lr) scores was observed for 5p14.1-q12.1, where the maximum Z(lr) increased from 2.77 initially to 3.80 after fine mapping in the EA families.

Adolescent↗

Power-based, phase-informed selection of single nucleotide polymorphisms for disease association screens.

Single nucleotide polymorphisms (SNPs) are becoming widely used as genotypic markers in genetic association studies of common, complex human diseases. For such association screens, a crucial part of study design is determining what SNPs to prioritize for genotyping. We present a novel power-based algorithm to select a subset of tag SNPs for genotyping from a map of available SNPs. Blocks of markers in strong linkage disequilibrium (LD) are identified, and SNPs are selected to represent each block such that power to detect disease association with an underlying disease allele in LD with block members is preserved; all markers outside of blocks are also included in the tagging subset. A key, novel element of this method is that it incorporates information about the phase of LD observed among marker pairs to retain markers likely to be in coupling phase with an underlying disease locus, thus increasing power compared to a phase-blind approach. Power calculations illustrate important issues regarding LD phase and make clear the advantages of our approach to SNP selection. We apply our algorithm to genotype data from the International HapMap Consortium and demonstrate that considerable reduction in SNP genotyping may be attained while retaining much of the available power for a disease association screen. We also demonstrate that these tag SNPs effectively represent underlying variants not included in the LD analysis and SNP selection, by using leave-one-out tests to show that most (approximately 90%) of the "untyped" variants lying in blocks are in coupling-phase LD with a tag SNP. Additional performance tests using the HapMap ENCyclopedia of DNA Elements (ENCODE) regions show that the method compares well with the popular r2 bin tagging method. This work is a concrete example of how empirical LD phase may be used to benefit study design.

Algorithms↗

A cholinergic receptor gene (CHRM2) affects event-related oscillations.

We report genetic linkage and association findings which implicate the gene encoding the muscarinic acetylcholine receptor M2 (CHRM2) in the modulation of a scalp-recorded electrophysiological phenotype. The P3 (P300) response was evoked using a three-stimulus visual oddball paradigm and a phenotype that relates to the energy in the theta band (4-5 Hz) was analyzed. Studies have shown that similar electrophysiological measures represent cognitive correlates of attention, working memory, and response selection; a role has been suggested for the ascending cholinergic pathway in the same functions. The results of our genetic association tests, combined with knowledge regarding the presence of presynaptic cholinergic M2 autoreceptors in the basal forebrain, indicate that the cognitive processes required by the experiment may in part be mediated by inhibitory neural networks. These findings underscore the utility of electrophysiology and neurogenetics in the understanding of cognitive function and the study of brain-related disorders.

Chromosome Mapping↗

Genetic analysis of the maximum drinks phenotype.

Using data provided by the Collaborative Study on the Genetics of Alcoholism we studied the genetics of a quantitative trait: the maximum number of drinks consumed in a 24-hour period. A two-stage method was used. First, linkage analysis was performed, followed by association analysis in regions where linkage was detected. Additionally, the extent of linkage disequilibrium among single-nucleotide polymorphisms (SNP) associated with the phenotype was assessed. Linkage to chromosomes 2 and 7 was detected, and follow-up association analysis found multiple trait-associated SNPs in the chromosome 7 linkage region. Chromosome 4, which has been implicated in previous studies of the maximum drinks phenotype, did not pass our threshold for linkage evidence in stage 1, but secondary analyses of this chromosome indicated modest evidence for both linkage and association. The evidence suggests that chromosome 7 may harbor an additional locus influencing the maximum drinks consumption phenotype.

Alcohol Drinking↗

Description of the data from the Collaborative Study on the Genetics of Alcoholism (COGA) and single-nucleotide polymorphism genotyping for Genetic Analysis Workshop 14.

The data provided to the Genetic Analysis Workshop 14 (GAW 14) was the result of a collaboration among several different groups, catalyzed by Elizabeth Pugh from The Center for Inherited Disease Research (CIDR) and the organizers of GAW 14, Jean MacCluer and Laura Almasy. The DNA, phenotypic characterization, and microsatellite genomic survey were provided by the Collaborative Study on the Genetics of Alcoholism (COGA), a nine-site national collaboration funded by the National Institute of Alcohol and Alcoholism (NIAAA) and the National Institute of Drug Abuse (NIDA) with the overarching goal of identifying and characterizing genes that affect the susceptibility to develop alcohol dependence and related phenotypes. CIDR, Affymetrix, and Illumina provided single-nucleotide polymorphism genotyping of a large subset of the COGA subjects. This article briefly describes the dataset that was provided.

Alcoholism↗

Combined analysis from eleven linkage studies of bipolar disorder provides strong evidence of susceptibility loci on chromosomes 6q and 8q.

Several independent studies and meta-analyses aimed at identifying genomic regions linked to bipolar disorder (BP) have failed to find clear and consistent evidence of linkage regions. Our hypothesis is that combining the original genotype data provides benefits of increased power and control over sources of heterogeneity that outweigh the difficulty and potential pitfalls of the implementation. We conducted a combined analysis using the original genotype data from 11 BP genomewide linkage scans comprising 5,179 individuals from 1,067 families. Heterogeneity among studies was minimized in our analyses by using uniform methods of analysis and a common, standardized marker map and was assessed using novel methods developed for meta-analysis of genome scans. To date, this collaboration is the largest and most comprehensive analysis of linkage samples involving a psychiatric disorder. We demonstrate that combining original genome-scan data is a powerful approach for the elucidation of linkage regions underlying complex disease. Our results establish genomewide significant linkage to BP on chromosomes 6q and 8q, which provides solid information to guide future gene-finding efforts that rely on fine-mapping and association approaches.

Bipolar Disorder↗

Alcoholism and related traits: a summary of Group 13 contributions.

Ten groups set out to study the genetics of alcoholism, using various measures of alcohol dependence such as Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria, and related endophenotypes such as the electrophysiological evaluation of event-related potentials. The groups used both genome-wide microsatellite and single-nucleotide polymorphism (SNP) genotyping data in families selected from the Collaborative Study on the Genetics of Alcoholism. The majority of investigators studied alcohol-related phenotypes and chose linkage rather than association analysis. The analysis of SNP data presented several challenges, including marker linkage disequilibrium issues and computational limitations. Many groups pursued novel techniques, both in dealing with the SNP data and the definition of phenotypes. While there was a limited amount of concordance among linkage findings, it was very instructive to see so many new strategies at work. Generally the SNP genotype data seemed to yield more information for multipoint linkage analysis than the microsatellite data, a finding that will benefit the genetic analysis of complex disease in the future. A novel linkage peak was detected using the SNP markers.

Alcoholism↗

A genomic scan for habitual smoking in families of alcoholics: common and specific genetic factors in substance dependence.

Smoking is a highly heritable, addictive disorder that commonly co-occurs with alcohol dependence. The purpose of this study is to perform a genomic screen for habitual smoking and comorbid habitual smoking and alcohol dependence in families from the Collaborative Study on the Genetics of Alcoholism (COGA). Subjects were assessed using the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) to evaluate alcohol dependence and habitual smoking (smoking one pack per day or more for at least 6 months). Sixty seven multi-generational families with 154 independent sibling pairs affected with habitual smoking were genotyped in a screening sample. Analyses on 79 multi-generational families with 173 independent sibling pairs were repeated in a replication sample. Sibpair analyses were performed using ASPEX. Four chromosomal regions in the screening sample had increased allele sharing among sibling pairs for habitual smoking with a LOD score greater than 1 (chromosomes 5, 9, 11, and 21). The highest LOD score was on chromosome 9 (LOD = 2.02; allele sharing 58.9%). Four chromosomal regions also had modest evidence for linkage to the comorbid phenotype habitual smoking and alcohol dependence (chromosomes 1, 2, 11, 15); and the strongest finding was on chromosome 2 (LOD = 3.30; allele sharing 69.1%). Previously identified areas (chromosomes 1 and 7) implicated in the development of alcohol dependence in this same data set did not provide evidence for linkage to habitual smoking in the screening sample. In the replication data set, there continued to be increased allele sharing near peaks identified in the screening sample on chromosomes 2 and 9, but the results were modest. An area on chromosome 7, approximately 60 cM from a location previously identified in linkage analysis with alcohol dependence, had increased allele sharing for the comorbid habitual smoking and alcohol dependence. These data provide evidence of specific genetic regions involved in the development of habitual smoking and not alcohol dependence. Conversely, genetic regions that influence the development of alcohol dependence do not appear to contribute to the development of habitual smoking. Finally, there is also evidence of an area on chromosome 2 that may reflect a common genetic vulnerability locus to both habitual smoking and alcohol dependence.

Adolescent↗

Linkage and linkage disequilibrium of evoked EEG oscillations with CHRM2 receptor gene polymorphisms: implications for human brain dynamics and cognition.

Event-related oscillations (ERO) offer an alternative theoretical and methodological approach to the analysis of event-related EEG responses. The P300 event-related potential (ERP) is elicited through the superposition of the delta (1-3 Hz) and theta (3-7 Hz) band oscillatory responses. The cholinergic neurotransmitter system has a key function in modulating excitatory post-synaptic potentials caused by glutamate, and therefore influences P300 generation and the underlying oscillatory responses. Here we report significant linkage and linkage disequilibrium between target case frontal theta band, visual evoked brain oscillations and a single nucleotide polymorphism (SNP) from the cholinergic muscarinic receptor gene (CHRM2) on chromosome 7. We also demonstrate significant linkage disequilibrium between CHRM2 SNPs and target case parietal delta band visual evoked oscillations (LD P<0.001). These findings were not observed for the equivalent non-target case data, suggesting a role for the CHRM2 gene in higher cognitive processing in humans.

Adolescent↗

The search for genetic risk factors associated with suicidal behavior.

BACKGROUND: Suicide and suicidal behavior are prevalent among individuals with psychiatric disorders, including alcohol dependence. A genome screen was performed in multiplex alcohol dependent families ascertained as part of the Collaborative Study on the Genetics of Alcoholism to identify chromosomal regions of interest related to two types of suicidal behavior: suicide attempts and suicidality. METHODS: Sibling pair analyses were used to conduct linkage analyses using both qualitative and quantitative suicide-related phenotypes. The qualitative trait of "suicide attempts" was examined using 59 affected sibling pairs. The quantitative trait of "suicidality" was examined using all possible 1366 sibling pairs and 705 independent sibling pairs. RESULTS: For the qualitative phenotype suicide attempts, chromosome 2 yielded a maximum lod score of 4.2. For the quantitative suicidality index, a maximum lod score of 1.8 was observed on chromosome 3, and a lod score of 1.5 was found on chromosome 1. CONCLUSIONS: This study represents the first genome-wide scan of suicidal behavior. Significant evidence of linkage was found on chromosome 2 for the phenotype suicide attempts, the same chromosomal region previously reported to be linked to alcohol dependence in this sample. This finding does not seem to be due solely to an association between suicide and alcohol dependence. There was more modest evidence of linkage to chromosomes 1 and 3 for suicidality; however, these findings did not reach statistical significance. There was no overlap in findings for these two phenotypes of suicidal behavior.

Alcoholism↗

Power loss for linkage analysis due to the dichotomization of trichotomous phenotypes.

OBJECTIVES: Some traits, while naturally polychotomous, are routinely dichotomized for genetic analysis. Dichotomization, intuitively, leads to a loss of power to detect linkage, as some phenotypic variability is discarded. This paper examines this power loss in the context of a trichotomous trait. METHODS: To examine this power loss, we performed a simulation study where a trichotomous trait was simulated in a sample of 1,000 sib-pairs under various genetic models. The study was replicated 1,000 times. Linkage analysis using a variance components method, as implemented in Mx, was then performed on the trichotomous trait and compared with that on a dichotomized version of the trait. RESULTS: A comparison of the power and false positive rates of the analyses shows that power to detect linkage was increased by up to 22 percentage points simply by examining the trait as a trichotomy instead of a dichotomy. Under all models examined, the trichotomous analysis outperformed the dichotomous version. CONCLUSIONS: Comparable levels of false positive rates under both methods confirm that this power gain comes solely from the information lost upon dichotomization. Thus, dichotomizing tri- or poly-chotomous traits can lead to crippling power loss, especially in the case of many loci of small effect.

Alleles↗

Genetic analysis of maximum cigarette-use phenotypes.

BACKGROUND: Using the Framingham Heart Study data set provided for Genetic Analysis Workshop 13, we defined the cigarette-use phenotype M for smokers to be the maximum number of cigarettes-per-day (MAXCIG) reported over the longitudinal course of the study. Adjustments were made for the significant covariates of gender and year of birth, and sib-pair based linkage analysis was performed. RESULTS: The primary analyses, in which individuals with MAXCIG = 0 were considered to have missing phenotype, resulted in modest linkage evidence, with LOD scores over 1 on chromosomes 5, 9, 13, 14, and 22. CONCLUSIONS: While the results reported here do not indicate definitive evidence for linkage to specific chromosomal regions, future studies may find it useful to include direct assessments of maximum and quantitative cigarette use. In defining and analyzing quantitative or "maximum use" phenotypes, the choice of how to handle individuals with MAXCIG = 0, or alternatively, individuals who are substance-naive, is a crucial one for genetic studies of nicotine and other substance use. In this study, the linkage results vary greatly depending on whether or not these "unexposed" individuals are included in the analyses.

Adult Children↗

Genome-wide scan and conditional analysis in bipolar disorder: evidence for genomic interaction in the National Institute of Mental Health genetics initiative bipolar pedigrees.

BACKGROUND: In 1989 the National Institute of Mental Health began a collaborative effort to identify genes for bipolar disorder. The first 97 pedigrees showed evidence of linkage to chromosomes 1, 6, 7, 10, 16, and 22 (Nurnberger et al 1997). An additional 56 bipolar families have been genotyped, and the combined sample of 153 pedigrees studied. METHODS: Three hierarchical affection status models were analyzed with 513 simple sequence repeat markers; 298 were common across all pedigrees. The primary analysis was a nonparametric genome-wide scan. We performed conditional analyses based on epistasis or heterogeneity for five regions. RESULTS: One region, on 16p13, was significant at the genome-wide p <.05 level. Four additional chromosomal regions (20p12, 11p15, 6q24, and 10p12) showed nominally significant linkage findings (p </=.01). Conditional analysis assuming epistasis identified a significant increase in linkage at four regions. Families linked to 6q24 showed a significant increase in nonparametric logarithms of the odds (NPL) scores at 5q11 and 7q21. Epistasis also was observed between 20p12 and 13q21, and 16p13 and 9q21. CONCLUSIONS: The findings are presented in rank order of nominal significance. Several of these regions have been previously implicated in independent studies of either bipolar disorder or schizophrenia. The strongest finding is at 16p13 at D16S748 with an NPL of 3.3, there is evidence of epistasis between this locus and 9q21. Application of conditional analyses is potentially useful in larger sample collections to identify susceptibility genes of modest influence that may not be identified in a genome-wide scan aimed to identify single gene effects.

Bipolar Disorder↗

Genome scan meta-analysis of schizophrenia and bipolar disorder, part III: Bipolar disorder.

Genome scans of bipolar disorder (BPD) have not produced consistent evidence for linkage. The rank-based genome scan meta-analysis (GSMA) method was applied to 18 BPD genome scan data sets in an effort to identify regions with significant support for linkage in the combined data. The two primary analyses considered available linkage data for "very narrow" (i.e., BP-I and schizoaffective disorder-BP) and "narrow" (i.e., adding BP-II disorder) disease models, with the ranks weighted for sample size. A "broad" model (i.e., adding recurrent major depression) and unweighted analyses were also performed. No region achieved genomewide statistical significance by several simulation-based criteria. The most significant P values (<.01) were observed on chromosomes 9p22.3-21.1 (very narrow), 10q11.21-22.1 (very narrow), and 14q24.1-32.12 (narrow). Nominally significant P values were observed in adjacent bins on chromosomes 9p and 18p-q, across all three disease models on chromosomes 14q and 18p-q, and across two models on chromosome 8q. Relatively few BPD pedigrees have been studied under narrow disease models relative to the schizophrenia GSMA data set, which produced more significant results. There was no overlap of the highest-ranked regions for the two disorders. The present results for the very narrow model are promising but suggest that more and larger data sets are needed. Alternatively, linkage might be detected in certain populations or subsets of pedigrees. The narrow and broad data sets had considerable power, according to simulation studies, but did not produce more highly significant evidence for linkage. We note that meta-analysis can sometimes provide support for linkage but cannot disprove linkage in any candidate region.

Bipolar Disorder↗