Bivariate linkage analysis of cholesterol and triglyceride levels in the Framingham Heart Study

We performed a bivariate analysis on cholesterol and triglyceride levels on data from the Framingham Heart Study using a new score statistic developed for the detection of potential pleiotropic, or cluster, genes. Univariate score statistics were also computed for each trait. At a significance level 0.001, linkage signals were found at markers GATA48B01 on chromosome 1, GATA21C12 on chromosome 8, and ATA55A11 on chromosome 16 using the bivariate analysis. At the same significance level, linkage signals were found at markers 036yb8 on chromosome 3 and GATA3F02 on chromosome 12 using the univariate analysis. A strong linkage signal was also found at marker GATA112F07 by both the bivariate analysis and the univariate analysis, a marker for which evidence for linkage had been reported previously in a related study.     

Joint Multipoint Linkage Analysis of Multivariate Qualitative and Quantitative Traits. II. Alcoholism and Event-Related Potentials

The availability of robust quantitative biological markers that are correlated with qualitative psychiatric phenotypes can potentially improve the power of linkage methods to detect quantitative-trait loci influencing psychiatric disorders. We apply a variance-component method for joint multipoint linkage analysis of multivariate discrete and continuous traits to the extended pedigree data from the Collaborative Study on the Genetics of Alcoholism, in a bivariate analysis of qualitative alcoholism phenotypes and quantitative event-related potentials. Joint consideration of the DSM-IV diagnosis of alcoholism and the amplitude of the P300 component of the Cz event-related potential significantly increases the evidence for linkage of these traits to a chromosome 4 region near the class I alcohol dehydrogenase locus ADH3. A likelihood-ratio test for complete pleiotropy is significant, suggesting that the same quantitative-trait locus influences both risk of alcoholism and the amplitude of the P300 component.     

Genome-wide associations for fertility traits in Holstein–Friesian dairy cows using data from experimental research herds in four European countries

Genome-wide association studies for difficult-to-measure traits are generally limited by the sample population size with accurate phenotypic data. The objective of this study was to utilise data on primiparous Holstein–Friesian cows from experimental farms in Ireland, the United Kingdom, the Netherlands and Sweden to identify genomic regions associated with traditional measures of fertility, as well as a fertility phenotype derived from milk progesterone profiles. Traditional fertility measures investigated were days to first heat, days to first service, pregnancy rate to first service, number of services and calving interval (CI); post-partum interval to the commencement of luteal activity (CLA) was derived using routine milk progesterone assays. Phenotypic and genotypic data on 37 590 single nucleotide polymorphisms (SNPs) were available for up to 1570 primiparous cows. Genetic parameters were estimated using linear animal models, and univariate and bivariate genome-wide association analyses were undertaken using Bayesian stochastic search variable selection performed using Gibbs sampling. Heritability estimates of the traditional fertility traits varied from 0.03 to 0.16; the heritability for CLA was 0.13. The posterior quantitative trait locus (QTL) probabilities, across the genome, for the traditional fertility measures were all <0.021. Posterior QTL probabilities of 0.060 and 0.045 were observed for CLA on SNPs each on chromosome 2 and chromosome 21, respectively, in the univariate analyses; these probabilities increased when CLA was included in the bivariate analyses with the traditional fertility traits. For example, in the bivariate analysis with CI, the posterior QTL probability of the two aforementioned SNPs were 0.662 and 0.123. Candidate genes in the vicinity of these SNPs are discussed. The results from this study suggest that the power of genome-wide association studies in cattle may be increased by sharing of data and also possibly by using physiological measures of the trait under investigation.     

Microsatellite linkage analysis, single-nucleotide polymorphisms, and haplotype associations with ECB21 in the COGA data

This study, part of the Genetic Analysis Workshop 14 (GAW14), explored real Collaborative Study on the Genetics of Alcoholism data for linkage and association mapping between genetic polymorphisms (microsatellite and single-nucleotide polymorphisms (SNPs)) and beta (16.5-20 Hz) oscillations of the brain rhythms (ecb21). The ecb21 phenotype underwent the statistical adjustments for the age of participants, and for attaining a normal distribution. A total of 1,000 subjects' available phenotypes were included in linkage analysis with microsatellite markers. Linkage analysis was performed only for chromosome 4 where a quantitative trait locus with 5.01 LOD score had been previously reported. Previous findings related this location with the gamma-aminobutyric acid type A (GABAA) receptor. At the same location, our analysis showed a LOD score of 2.2. This decrease in the LOD score is the result of a drastic reduction (one-third) of the available GAW14 phenotypic data. We performed SNP and haplotype association analyses with the same phenotypic data under the linkage peak region on chromosome 4. Seven Affymetrix and two Illumina SNPs showed significant associations with ecb21 phenotype. A haplotype, a combination of SNPs TSC0044171 and TSC0551006 (the latter almost under the region of GABAA genes), showed a significant association with ecb21 (p = 0.015) and a relatively high frequency in the sample studied. Our results affirmed that the GABA region has potential of harboring genes that contribute quantitatively to the beta oscillation of the brain rhythms. The inclusion of the remaining 614 subjects, which in the GAW14 had missing data for the ecb21, can improve the strength of the associations as they have already shown that they contribute quite important information in the linkage analysis.     

A study of genetic association with electrophysiological measures related to alcoholism: GAW14 data

Recently, alcohol-related traits have been shown to have a genetic component. Here, we study the association of specific genetic measures in one of the three sets of electrophysiological measures in families with alcoholism distributed as part of the Genetic Analysis Workshop 14 data, the NTTH (non-target case of Visual Oddball experiment for 4 electrode placements) phenotypes: ntth1, ntth2, ntth3, and ntth4. We focused on the analysis of the 786 Affymetrix markers on chromosome 4. Our desire was to find at least a partial answer to the question of whether ntth1, ntth2, ntth3, and ntth4 are separately or jointly genetically controlled, so we studied the principal components that explain most of the covariation of the four quantitative traits. The first principal component, which explains 70% of the covariation, showed association but not genetic linkage to two markers: tsc0272102 and tsc0560854. On the other hand, ntth1 appeared to be the trait driving the variation in the second principal component, which showed association and genetic linkage at markers in four regions: tsc0045058, tsc1213381, tsc0055068, and tsc0051777 at map distances 53.26, 85.42, 89.31, and 172.86, respectively. These results show that the partial answer to our starting question for this brief analysis is that the NTTH phenotypes are not jointly genetically controlled. The component ntth1 displays marked genetic linkage.     

Linkage analysis of alcoholism-related electrophysiological phenotypes: genome scans with microsatellites compared to single-nucleotide polymorphisms

P300 amplitude is an electrophysiological quantitative trait that is correlated with both alcoholism and smoking status. Using the Collaborative Study on the Genetics of Alcoholism data, we performed model-free linkage analysis to investigate the relationship between alcoholism, P300 amplitude, and habitual smoking. We also analyzed the effect of parent-of-origin on alcoholism, and utilized both microsatellites (MS) markers and single-nucleotide polymorphisms (SNPs). We found significant evidence of linkage for alcoholism to chromosome 10; inclusion of P300 amplitude as a covariate provided additional evidence of linkage to chromosome 12. This same region on chromosome 12 showed some evidence for a parent-of-origin effect. We found evidence of linkage for the P300 phenotype to chromosome 7 in non-smokers, and to chromosome 17 in alcoholics. The effects of alcoholism and habitual smoking on P300 amplitude appear to have separate genetic determinants. Overall, there were few differences between MS and SNP genome scans. The use of covariates and parent-of-origin effects allowed detection of linkage not seen otherwise.     

Quantitative trait locus-specific genotype x alcoholism interaction on linkage for evoked electroencephalogram oscillations

We explored the evidence for a quantitative trait locus (QTL)-specific genotype x alcoholism interaction for an evoked electroencephalogram theta band oscillation (ERP) phenotype on a region of chromosome 7 in participants of the US Collaborative Study on the Genetics of Alcoholism. Among 901 participants with both genotype and phenotype data available, we performed variance component linkage analysis (SOLAR version 2.1.2) in the full sample and stratified by DSM-III-R and Feighner-definite alcoholism categories. The heritability of the ERP phenotype after adjusting for age and sex effects in the combined sample and in the alcoholism classification sub-groups ranged from 40% to 66%. Linkage on chromosome 7 was identified at 158 cM (LOD = 3.8) in the full sample and at 108 in the non-alcoholic subgroup (LOD = 3.1). Further, we detected QTL-specific genotype x alcoholism interaction at these loci. This work demonstrates the importance of considering the complexity of common complex traits in our search for genes that predispose to alcoholism.     

A genome-wide linkage scan identifies multiple chromosomal regions influencing serum lipid levels in the population on the Samoan islands

Abnormal lipid levels are important risk factors for cardiovascular diseases. We conducted genome-wide variance component linkage analyses to search for loci influencing total cholesterol (TC), LDL, HDL and triglyceride in families residing in American Samoa and Samoa as well as in a combined sample from the two polities. We adjusted the traits for a number of environmental covariates, such as smoking, alcohol consumption, physical activity, and material lifestyle. We found suggestive univariate linkage with log of the odds (LOD) scores > 3 for LDL on 6p21-p12 (LOD 3.13) in Samoa and on 12q21-q23 (LOD 3.07) in American Samoa. Furthermore, in American Samoa on 12q21, we detected genome-wide linkage (LOD(eq) 3.38) to the bivariate trait TC-LDL. Telomeric of this region, on 12q24, we found suggestive bivariate linkage to TC-HDL (LOD(eq) 3.22) in the combined study sample. In addition, we detected suggestive univariate linkage (LOD 1.9-2.93) on chromosomes 4p-q, 6p, 7q, 9q, 11q, 12q 13q, 15q, 16p, 18q, 19p, 19q and Xq23 and suggestive bivariate linkage (LOD(eq) 2.05-2.62) on chromosomes 6p, 7q, 12p, 12q, and 19p-q. In conclusion, chromosome 6p and 12q may host promising susceptibility loci influencing lipid levels; however, the low degree of overlap between the three study samples strongly encourages further studies of the lipid-related traits.     

A search for candidate genes for lipodystrophy,obesity and diabetes via gene expression analysis of A-ZIP/F-1 mice

Genome scans for diabetes have identified many regions of the human genome that correlate with the disease state. To identify candidate genes for type 2 diabetes, we examined the transgenic A-ZIP/F-1 mouse. This mouse model has no white fat, resulting in abnormal levels of glucose, insulin, and leptin, making the A-ZIP/F-1 mice a good model for lipodystrophy and insulin resistance. We used cDNA-based microarrays to find differentially expressed genes in four tissues of these mice. We examined these results in the context of human linkage scans for lipodystrophy, obesity, and type 2 diabetes. We combined 199 known human orthologs of the misregulated mouse genes with 33 published human genome scans on a genome map. Integrating expression data with human linkage results permitted us to suggest and prioritize candidate genes for lipodystrophy and related disorders. These genes include a cluster of 3 S100A genes on chromosome 1 and SLPI1 on chromosome 20.     

Using mixture models to characterize disease-related traits

We consider 12 event-related potentials and one electroencephalogram measure as disease-related traits to compare alcohol-dependent individuals (cases) to unaffected individuals (controls). We use two approaches: 1) two-way analysis of variance (with sex and alcohol dependency as the factors), and 2) likelihood ratio tests comparing sex adjusted values of cases to controls assuming that within each group the trait has a 2 (or 3) component normal mixture distribution. In the second approach, we test the null hypothesis that the parameters of the mixtures are equal for the cases and controls. Based on the two-way analysis of variance, we find 1) males have significantly (p < 0.05) lower mean response values than females for 7 of these traits. 2) Alcohol-dependent cases have significantly lower mean response than controls for 3 traits. The mixture analysis of sex-adjusted values of 1 of these traits, the event-related potential obtained at the parietal midline channel (ttth4), found the appearance of a 3-component normal mixture in cases and controls. The mixtures differed in that the cases had significantly lower mean values than controls and significantly different mixing proportions in 2 of the 3 components. Implications of this study are: 1) Sex needs to be taken into account when studying risk factors for alcohol dependency to prevent finding a spurious association between alcohol dependency and the risk factor. 2) Mixture analysis indicates that for the event-related potential "ttth4", the difference observed reflects strong evidence of heterogeneity of response in both the cases and controls.     

X chromosome effects and their interactions with mitochondrial effects

We report a simple and rapid method for detecting additive genetic variance due to X-linked loci in the absence of marker data for this chromosome. We examined the interaction of this method with an established method for detecting mitochondrial linkage (another source of sex-asymmetric genetic covariance). When applied to data from the Collaborative Study on the Genetics of Alcoholism, this method found evidence of X-chromosomal linkage for one continuous trait (ntth1) and one discrete trait (SPENT). Evidence of mitochondrial contribution was found for one discrete trait (CRAVING) and three continuous traits (ln(CIGPKYR), ecb21, and tth1). Results for ntth1 suggest that methods that do not also allow for male-female heterogeneity in environmental variance may be overly conservative in detection of X-chromosomal effects.     

A QTL on 12q Influencing an Inflammation Marker and Obesity in White Women: The NHLBI Family Heart Study

It has been recognized that obese individuals are intrinsically in a state of chronic inflammation, as indicated by positive correlations between serum levels of C‐reactive protein (CRP) and various anthropometric measures of obesity. To explore the hypothesis that a gene(s) may underlie this relationship, we conducted bivariate linkage analyses of BMI and CRP in white and African‐American (AA) families of the National Heart, Lung, and Blood Institute (NHLBI) Family Heart Study (FHS). Variance components linkage analysis as implemented in SOLAR was performed in 1,825 whites (840 men and 985 women) and 548 AAs (199 men and 351 women). CRP exhibited significant genetic correlations with BMI in women (0.54 ± 0.10 for white and 0.53 ± 0.14 for AA) and the combined samples (0.37 ± 0.09 for white and 0.56 ± 0.13 for AA), but not in men. We detected a maximum bivariate lod score of 3.86 on chromosome 12q24.2–24.3 at 139 cM and a suggestive linkage signal (lod = 2.19) on chromosome 19p13.1 (44 cM) in white women. Both bivariate peaks were substantially higher than their respective univariate lods at the same locus for each trait. No significant lod scores were detected in AAs. Our results indicate that chromosome 12q may harbor quantitative trait loci (QTLs) jointly regulating BMI and CRP in white women.     

Pleiotropic QTL on chromosome 12q23-q24 influences triglyceride and high-density lipoprotein cholesterol levels: the HERITAGE family study

To determine whether a common quantitative trait locus (QTL) influences the variation of fasting triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C) levels, we used a bivariate multipoint linkage analysis with 654 polymorphic markers in 99 white and 101 black families. The phenotypes were investigated under two conditions: at baseline and after a 20-week exercise training intervention. A maximum genome-wide bivariate LOD score of 3.0 (p = 0.00010) was found on chromosome 12q23-q24, located within the IGF1 gene (insulin-like growth factor 1, at 107 cM) for TG and HDL-C at baseline in whites. This bivariate linkage peak is considerably higher than the univariate linkage results at the same chromosome location for either trait (for TG, LOD = 2.07, p = 0.00108; for HDL-C, LOD = 2.04, p = 0.00101). The genetic correlations between baseline TG and HDL-C levels were -0.14 for the residual and -0.33 for the QTL components. Moreover, association analysis showed that TG, HDL-C, and IGF1 are significantly associated (p = 0.04). In conclusion, these results suggest that a QTL on chromosome 12q23-q24 influences the variation of plasma TG and HDL-C levels. Further investigation should confirm whether IGF1 or another nearby gene is responsible for the concomitant variation in TG and HDL-C levels.     

Dissecting the correlation structure of a bivariate phenotype: Common genes or shared environment?

High correlations between two quantitative traits may be either due to common genetic factors or common environmental factors or a combination of both. In this study, we develop statistical methods to extract the genetic contribution to the total correlation between the components of a bivariate phenotype. Using data on bivariate phenotypes and marker genotypes for sib-pairs, we propose a test for linkage between a common QTL and a marker locus based on the conditional cross-sib trait correlations (trait 1 of sib 1—trait 2 of sib 2 and conversely) given the identity-by-descent (i.b.d.) sharing at the marker locus. We use Monte-Carlo simulations to evaluate the performance of the proposed test under different trait parameters and quantitative trait distributions. An application of the method is illustrated using data on two alcohol-related phenotypes from a project on the collaborative study on the genetics of alcoholism.     

Variations in GABRA2, encoding the alpha 2 subunit of the GABA(A) receptor, are associated with alcohol dependence and with brain oscillations

Alcoholism is a complex disease with both genetic and environmental risk factors. To identify genes that affect the risk for alcoholism, we systematically ascertained and carefully assessed individuals in families with multiple alcoholics. Linkage and association analyses suggested that a region of chromosome 4p contained genes affecting a quantitative endophenotype, brain oscillations in the beta frequency range (13-28 Hz), and the risk for alcoholism. To identify the individual genes that affect these phenotypes, we performed linkage disequilibrium analyses of 69 single-nucleotide polymorphism (SNPs) within a cluster of four GABA(A) receptor genes, GABRG1, GABRA2, GABRA4, and GABRB1, at the center of the linked region. GABA(A) receptors mediate important effects of alcohol and also modulate beta frequencies. Thirty-one SNPs in GABRA2, but only 1 of the 20 SNPs in the flanking genes, showed significant association with alcoholism. Twenty-five of the GABRA2 SNPs, but only one of the SNPs in the flanking genes, were associated with the brain oscillations in the beta frequency. The region of strongest association with alcohol dependence extended from intron 3 past the 3' end of GABRA2; all 43 of the consecutive three-SNP haplotypes in this region of GABRA2 were highly significant. A three-SNP haplotype was associated with alcoholism, with P=.000000022. No coding differences were found between the high-risk and low-risk haplotypes, suggesting that the effect is mediated through gene regulation. The very strong association of GABRA2 with both alcohol dependence and the beta frequency of the electroencephalogram, combined with biological evidence for a role of this gene in both phenotypes, suggest that GABRA2 might influence susceptibility to alcohol dependence by modulating the level of neural excitation.     

Bivariate Linkage between Acylation‐Stimulating Protein and BMI and High‐Density Lipoproteins

Objective: Given the importance of visceral adiposity in the metabolic syndrome, whether levels of adipokines have shared genetic effects (pleiotropy) with aspects of the metabolic syndrome should be addressed. Acylation‐stimulating protein (ASP), an adipose‐derived protein, influences lipid metabolism, obesity, and glucose use. Therefore, our objective was to examine the genetic regulation of ASP and associated pleiotropic effects. Research Methods and Procedures: We assayed serum ASP levels in 435 Mexican Americans participating in the San Antonio Family Heart Study and performed univariate and bivariate variance components analysis. Results: Additive genetic heritability of ASP was 26% (p = 0.0004). Bivariate genetic analysis detected significant genetic correlations between ASP and several lipid measures but not between ASP and adiposity or diabetes measures. We detected two potential quantitative trait loci influencing ASP levels. The strongest signal was on chromosome 17 near marker D17S1303 [log of the odds ratio (LOD) = 2.7]. The signal on chromosome 15 reached its peak near marker D15S641 (LOD = 2.1). Both signals localize in regions reported to harbor quantitative trait loci influencing obesity and lipid phenotypes in this population. Bivariate linkage analysis yielded LODs of 4.7 for ASP and BMI on chromosome 17 and 3.2 for ASP and high‐density lipoprotein_2a on chromosome 15. Discussion: Given these findings, there seems to be a significant genetic contribution to variation in circulating levels of ASP and an interesting pattern of genetic correlation (i.e., pleiotropy) with other risk factors associated with the metabolic syndrome.     

Quantitative trait loci for peripheral blood cell counts: a study in baboons

Increasingly, baseline peripheral blood cell counts are implicated as risk factors for common complex diseases. While genetic influences on these hematologic parameters are firmly established, the genetic architecture of the blood counts is still poorly understood. In this article we used data from 582 healthy pedigreed baboons and variance components methods to localize quantitative trait loci (QTLs) influencing complete blood count variables. Besides performing genome-wide linkage scans for each trait individually, we conducted bivariate linkage analyses for all pairwise trait combinations to also identify pleiotropic QTLs influencing several blood counts. While significant and suggestive QTLs were localized throughout the genome (LOD range: 1.5–3.5), chromosomal regions associated with the expression of various hematologic parameters stand out. In particular, our results provide significant and consistent evidence for a QTL on the orthologous human chromosome 1p that is shared by several blood counts, mainly erythrocyte parameters. In addition, multiple suggestive evidence of linkage was detected on the orthologous human chromosomes 10 (near the q-terminus) and 19 (centromeric section). Future studies should help identify the genes responsible for these QTL and elucidate their role on baseline variation in hematologic indicators of health and disease.     

Mapping quantitative trait loci for principal components of bone measurements and osteochondrosis scores in a wild boar x large white intercross

Data on osteochondrosis and femur dimensions from 195 F2 pigs from a wild boar x Large White intercross were analysed with the aim of detecting quantitative trait loci (QTLs) for normal and disturbed bone formation. The information from numerous recorded traits was summarized by principal component analysis and analysed by least-squares interval mapping. An increase in the proportion of wild boar alleles across the genome increased length versus width of femur and reduced the prevalence of osteochondrosis. The presence of QTLs with an impact on femur dimensions was indicated on chromosomes 2, 4, 16 and 17 and on osteochondrosis on chromosomes 5, 13 and 15. A substantial effect of the chromosome 5 QTL calls for further studies within commercial populations to evaluate whether marker-assisted selection could be used to reduce the prevalence of osteochondrosis.     

Joint Multipoint Linkage Analysis of Multivariate Qualitative and Quantitative Traits. I. Likelihood Formulation and Simulation Results

We describe a variance-components method for multipoint linkage analysis that allows joint consideration of a discrete trait and a correlated continuous biological marker (e.g., a disease precursor or associated risk factor) in pedigrees of arbitrary size and complexity. The continuous trait is assumed to be multivariate normally distributed within pedigrees, and the discrete trait is modeled by a threshold process acting on an underlying multivariate normal liability distribution. The liability is allowed to be correlated with the quantitative trait, and the liability and quantitative phenotype may each include covariate effects. Bivariate discrete-continuous observations will be common, but the method easily accommodates qualitative and quantitative phenotypes that are themselves multivariate. Formal likelihood-based tests are described for coincident linkage (i.e., linkage of the traits to distinct quantitative-trait loci [QTLs] that happen to be linked) and pleiotropy (i.e., the same QTL influences both discrete-trait status and the correlated continuous phenotype). The properties of the method are demonstrated by use of simulated data from Genetic Analysis Workshop 10. In a companion paper, the method is applied to data from the Collaborative Study on the Genetics of Alcoholism, in a bivariate linkage analysis of alcoholism diagnoses and P300 amplitude of event-related brain potentials.     

A retrotransposon-derived gene, PEG10, is a novel imprinted gene located on human chromosome 7q21

A novel paternally expressed imprinted gene, PEG10 (Paternally Expressed 10), was identified on human chromosome 7q21. PEG10 is located near the SGCE (Sarcoglycan epsilon) gene, whose mouse homologue was recently shown to be imprinted. Therefore, it is highly possible that a new imprinted gene cluster exists on human chromosome 7q21. Analysis of two predicted open reading frames (ORF1 and ORF2) revealed that ORF1 and ORF2 have homology to the gag and pol proteins of some vertebrate retrotransposons, respectively. These data suggest that PEG10 is derived from a retrotransposon that was previously integrated into the mammalian genome. PEG10 is likely to be essential for understanding how exogenous genes become imprinted.