John P. Rice

Juxtaposed regions of extensive and minimal linkage disequilibrium in human Xq25 and Xq28

Linkage disequilibrium (LD), or the non-random association of alleles, is poorly understood in the human genome. Population genetic theory suggests that LD is determined by the age of the markers, population history, recombination rate, selection and genetic drift. Despite the uncertainties in determining the relative contributions of these factors, some groups have argued that LD is a simple function of distance between markers. Disease-gene mapping studies and a simulation study gave differing predictions on the degree of LD in isolated and general populations. In view of the discrepancies between theory and experimental observations, we constructed a high-density SNP map of the Xq25–Xq28 region and analysed the male genotypes and haplotypes across this region for LD in three populations. The populations included an outbred European sample (CEPH males) and isolated population samples from Finland and Sardinia. We found two extended regions of strong LD bracketed by regions with no evidence for LD in all three samples. Haplotype analysis showed a paucity of haplotypes in regions of strong LD. Our results suggest that, in this region of the X chromosome, LD is not a monotonic function of the distance between markers, but is more a property of the particular location in the human genome.

Genome-wide association study of alcohol dependence implicates a region on chromosome 11

BACKGROUND Alcohol dependence is a complex disease, and although linkage and candidate gene studies have identified several genes associated with the risk for alcoholism, these explain only a portion of the risk. METHODS We carried out a genome-wide association study (GWAS) on a case-control sample drawn from the families in the Collaborative Study on the Genetics of Alcoholism. The cases all met diagnostic criteria for alcohol dependence according to the Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition; controls all consumed alcohol but were not dependent on alcohol or illicit drugs. To prioritize among the strongest candidates, we genotyped most of the top 199 single nucleotide polymorphisms (SNPs) (p < or = 2.1 x 10(-4)) in a sample of alcohol-dependent families and performed pedigree-based association analysis. We also examined whether the genes harboring the top SNPs were expressed in human brain or were differentially expressed in the presence of ethanol in lymphoblastoid cells. RESULTS Although no single SNP met genome-wide criteria for significance, there were several clusters of SNPs that provided mutual support. Combining evidence from the case-control study, the follow-up in families, and gene expression provided strongest support for the association of a cluster of genes on chromosome 11 (SLC22A18, PHLDA2, NAP1L4, SNORA54, CARS, and OSBPL5) with alcohol dependence. Several SNPs nominated as candidates in earlier GWAS studies replicated in ours, including CPE, DNASE2B, SLC10A2, ARL6IP5, ID4, GATA4, SYNE1, and ADCY3. CONCLUSIONS We have identified several promising associations that warrant further examination in independent samples.

Family-based association of FKBP5 in bipolar disorder.

The FKBP5 gene product forms part of a complex with the glucocorticoid receptor and can modulate cortisol-binding affinity. Variations in the gene have been associated with increased recurrence of depression and with rapid response to antidepressant treatment. We sought to determine whether common FKBP5 variants confer risk for bipolar disorder. We genotyped seven tag single-nucleotide polymorphisms (SNPs) in FKBP5, plus two SNPs previously associated with illness, in 317 families with 554 bipolar offspring, derived primarily from two studies. Single marker and haplotypic analyses were carried out with FBAT and EATDT employing the standard bipolar phenotype. Association analyses were also conducted using 11 disease-related variables as covariates. Under an additive genetic model, rs4713902 showed significant overtransmission of the major allele (P=0.0001), which was consistent across the two sample sets (P=0.004 and 0.006). rs7757037 showed evidence of association that was strongest under the dominant model (P=0.001). This result was consistent across the two datasets (P=0.017 and 0.019). The dominant model yielded modest evidence for association (P<0.05) for three additional markers. Covariate-based analyses suggested that genetic variation within FKBP5 may influence attempted suicide and number of depressive episodes in bipolar subjects. Our results are consistent with the well-established relationship between the hypothalamic–pituitary–adrenal (HPA) axis, which mediates the stress response through regulation of cortisol, and mood disorders. Ongoing whole-genome association studies in bipolar disorder and major depression should further clarify the role of FKBP5 and other HPA genes in these illnesses.

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.

The familial transmission of primary major depressive disorder

This is a study of the familial transmission of Primary Major Depressive Disorder in the families of 235 probands with this disorder ascertained as part of the NIMH-CRB Collaborative Depression Program. Eight hundred and twenty-six interviewed first degree relatives and 109 spouses are included. Research Diagnostic Criteria have been used and interviews were done using the SADS-L schedule. Prior analyses of these data have established the presence of strong secular trends in the age-of-onset and prevalence of Major Depressive Disorder in these families. Accordingly, new methods for the analysis of family data which incorporate secular variation were developed. Non-parametric Survival Analysis, using the Cox Proportional Hazards Model, guided the formulation of a quantitative family transmission model. Then a family analysis was conducted with the Multifactorial Model of Disease Transmission and the Tau Path Analytic Model. Using the non-parametric approach, only the sibs birth cohort, sex and affectational status of the mother were significantly related to the time of onset of illness in siblings. Proband sex, age-of-onset, and the presence of illness in the father were not significant. The quantitative analysis confirmed that more recently born cohorts of individuals had an increased expected lifetime prevalence and a decreased age-of-onset of Primary Major Depressive Disorder. Assortative mating was present and environmental factors common to siblings did not make a significant contribution to the phenotypic variance. Sex specific transmissibilities were found and the transmissibility in females (t2 = 0.62) was significantly greater than that of males (t2 = 0.28). There was a trend for the transmissibility of Primary Major Disorder to be greater in more recently born cohorts.

Risk of suicide by psychiatric diagnosis in Stockholm County: A longitudinal study of 80,970 psychiatric inpatients.

SummaryThe risk of suicide associated with different psychiatric diagnoses was estimated in 80,970 inpatients in Stockholm County (population 1.6 million). All patients discharged with at least one psychiatric diagnosis between 1973 and 1986 were followed by linkage with the cause-of-death registry through 1987. There were 1,115 definite suicides and 467 undetermined suicides among these during the 15-year follow-up. When 12 diagnostic categories were entered in a proportional hazards model, the highest relative risk (RR) of definite suicide, controlling for sex and age, was noted for affective disorders (RR 2.82), followed by unspecified psychoses (RR 2.69), paranoid psychoses (RR 2.60), addiction to prescription drugs (RR 2.38), neuroses and reactive psychoses (RR 1.96), and schizophrenia (RR 1.64). Alcoholism, personality disorders, organic psychoses, and street drug addiction did not have significantly increased risks of suicide. Male sex increased the risk for definite suicide by 1.56, while the risk was somewhat higher among the young. Having more than one diagnosis increased the relative risk by 1.42. When undetermined suicides were included in the analysis, to alcoholism and street drug abuse were attributed significantly increased risks of suicide, probably owing to the greater difficulty of verifying such cases. We conclude that several psychiatric disorders were conductive to suicide, but that the risk did not vary much with the type of diagnosis. Further studies of confounders are needed, such as the reasons for being admitted to inpatient care, and the impact of somatic and psychiatric comorbidity.

In search of causal variants: refining disease association signals using cross-population contrasts

BackgroundGenome-wide association (GWA) using large numbers of single nucleotide polymorphisms (SNPs) is now a powerful, state-of-the-art approach to mapping human disease genes. When a GWA study detects association between a SNP and the disease, this signal usually represents association with a set of several highly correlated SNPs in strong linkage disequilibrium. The challenge we address is to distinguish among these correlated loci to highlight potential functional variants and prioritize them for follow-up.ResultsWe implemented a systematic method for testing association across diverse population samples having differing histories and LD patterns, using a logistic regression framework. The hypothesis is that important underlying biological mechanisms are shared across human populations, and we can filter correlated variants by testing for heterogeneity of genetic effects in different population samples. This approach formalizes the descriptive comparison of p-values that has typified similar cross-population fine-mapping studies to date. We applied this method to correlated SNPs in the cholinergic nicotinic receptor gene cluster CHRNA5-CHRNA3-CHRNB4, in a case-control study of cocaine dependence composed of 504 European-American and 583 African-American samples. Of the 10 SNPs genotyped in the r2 ≥ 0.8 bin for rs16969968, three demonstrated significant cross-population heterogeneity and are filtered from priority follow-up; the remaining SNPs include rs16969968 (heterogeneity p = 0.75). Though the power to filter out rs16969968 is reduced due to the difference in allele frequency in the two groups, the results nevertheless focus attention on a smaller group of SNPs that includes the non-synonymous SNP rs16969968, which retains a similar effect size (odds ratio) across both population samples.ConclusionFiltering out SNPs that demonstrate cross-population heterogeneity enriches for variants more likely to be important and causative. Our approach provides an important and effective tool to help interpret results from the many GWA studies now underway.

Copy number variations in 6q14.1 and 5q13.2 are associated with alcohol dependence

BACKGROUND Excessive alcohol use is the third leading cause of preventable death and is highly correlated with alcohol dependence, a heritable phenotype. Many genetic factors for alcohol dependence have been found, but many remain unknown. In search of additional genetic factors, we examined the association between Diagnostic and StatisticalManual of Mental Disorders, Fourth Edition (DSM-IV) alcohol dependence and all common copy number variations (CNVs) with good reliability in the Study of Addiction: Genetics and Environment (SAGE). METHODS All participants in SAGE were interviewed using the Semi-Structured Assessment for the Genetics of Alcoholism, as a part of 3 contributing studies. A total of 2,610 non-Hispanic European American samples were genotyped on the Illumina Human 1M array. We performed CNV calling by CNVPartition, PennCNV, and QuantiSNP, and only CNVs identified by all 3 software programs were examined. Association was conducted with the CNV (as a deletion/duplication) as well as with probes in the CNV region. Quantitative polymerase chain reaction (qPCR) was used to validate the CNVs in the laboratory. RESULTS CNVs in 6q14.1 (p = 1.04 × 10(-6)) and 5q13.2 (p = 3.37 × 10(-4)) were significantly associated with alcohol dependence after adjusting multiple tests. On chromosome 5q13.2, there were multiple candidate genes previously associated with various neurological disorders. The region on chromosome 6q14.1 is a gene desert that has been associated with mental retardation and language delay. The CNV in 5q13.2 was validated, whereas only a component of the CNV on 6q14.1 was validated by qPCR. Thus, the CNV on 6q14.1 should be viewed with caution. CONCLUSIONS This is the first study to show an association between DSM-IV alcohol dependence and CNVs. CNVs in regions previously associated with neurological disorders may be associated with alcohol dependence.

Genome-wide parametric linkage analyses of 644 bipolar pedigrees suggest susceptibility loci at chromosomes 16 and 20

Objective Our aim is to map chromosomal regions that harbor loci that increase susceptibility to bipolar disorder. Methods We analyzed 644 bipolar families ascertained by the National Institute of Mental Health Human Genetics Initiative for bipolar disorder. The families have been genotyped with microsatellite loci spaced every approximately 10 cM or less across the genome. Earlier analyses of these pedigrees have been limited to nonparametric (model-free) methods and thus, information from unaffected subjects with genotypes was not considered. In this study, we used parametric analyses assuming dominant and recessive transmission and specifying a maximum penetrance of 70%, so that information from unaffecteds could be weighed in the linkage analyses. As in previous linkage analyses of these pedigrees, we analyzed three diagnostic categories: model 1 included only bipolar I and schizoaffective, bipolar cases (1565 patients of whom approximately 4% were schizoaffective, bipolar); model 2 included all individuals in model 1 plus bipolar II patients (1764 total individuals); and model 3 included all individuals in model 2 with the addition of patients with recurrent major depressive disorder (2046 total persons). Results Assuming dominant inheritance the highest genome-wide pair-wise logarithm of the odds (LOD) score was 3.2 with D16S749 using model 2 patients. Multipoint analyses of this region yielded a maximum LOD score of 4.91. Under recessive transmission a number of chromosome 20 markers were positive and multipoint analyses of the area gave a maximum LOD of 3.0 with model 2 cases. Conclusion The chromosome 16p and 20 regions have been implicated by some studies and the data reported herein provide additional suggestive evidence of bipolar susceptibility genes in these regions.