524 research outputs found
Genome-wide linkage analysis for alcohol dependence: a comparison between single-nucleotide polymorphism and microsatellite marker assays
Both theoretical and applied studies have proven that the utility of single nucleotide polymorphism (SNP) markers in linkage analysis is more powerful and cost-effective than current microsatellite marker assays. Here we performed a whole-genome scan on 115 White, non-Hispanic families segregating for alcohol dependence, using one 10.3-cM microsatellite marker set and two SNP data sets (0.33-cM, 0.78-cM spacing). Two definitions of alcohol dependence (ALDX1 and ALDX2) were used. Our multipoint nonparametric linkage analysis found alcoholism was nominal linked to 12 genomic regions. The linkage peaks obtained by using the microsatellite marker set and the two SNP sets had a high degree of correspondence in general, but the microsatellite marker set was insufficient to detect some nominal linkage peaks. The presence of linkage disequilibrium between markers did not significantly affect the results. Across the entire genome, SNP datasets had a much higher average linkage information content (0.33 cM: 0.93, 0.78 cM: 0.91) than did microsatellite marker set (0.57). The linkage peaks obtained through two SNP datasets were very similar with some minor differences. We conclude that genome-wide linkage analysis by using approximately 5,000 SNP markers evenly distributed across the human genome is sufficient and might be more powerful than current 10-cM microsatellite marker assays
Whole-genome variance components linkage analysis using single-nucleotide polymorphisms versus microsatellites on quantitative traits of derived phenotypes from factor analysis of electroencephalogram waves
Alcohol dependence is a serious public health problem. We studied data from families participating in the Collaborative Study on the Genetics of Alcoholism (COGA) and made available to participants in the Genetic Analysis Workshop 14 (GAW14) in order to search for genes predisposing to alcohol dependence. Using factor analysis, we identified four factors (F1, F2, F3, F4) related to the electroencephalogram traits. We conducted variance components linkage analysis with each of the factors. Our results using the Affymetrix single-nucleotide polymorphism dataset showed significant evidence for a novel linkage of F3 (factor comprised of the three midline channel EEG measures from the target case of the Visual Oddball experiment ttdt2, 3, 4) to chromosome 18 (LOD = 3.45). This finding was confirmed by analyses of the microsatellite data (LOD = 2.73) and Illumina SNP data (LOD = 3.30). We also demonstrated that, in a sample like the COGA data, a dense single-nucleotide polymorphism map provides better linkage signals than low-resolution microsatellite map with quantitative traits
Multifactor-dimensionality reduction versus family-based association tests in detecting susceptibility loci in discordant sib-pair studies
Complex diseases are generally thought to be under the influence of multiple, and possibly interacting, genes. Many association methods have been developed to identify susceptibility genes assuming a single-gene disease model, referred to as single-locus methods. Multilocus methods consider joint effects of multiple genes and environmental factors. One commonly used method for family-based association analysis is implemented in FBAT. The multifactor-dimensionality reduction method (MDR) is a multilocus method, which identifies multiple genetic loci associated with the occurrence of complex disease. Many studies of late onset complex diseases employ a discordant sib pairs design. We compared the FBAT and MDR in their ability to detect susceptibility loci using a discordant sib-pair dataset generated from the simulated data made available to participants in the Genetic Analysis Workshop 14. Using FBAT, we were able to identify the effect of one susceptibility locus. However, the finding was not statistically significant. We were not able to detect any of the interactions using this method. This is probably because the FBAT test is designed to find loci with major effects, not interactions. Using MDR, the best result we obtained identified two interactions. However, neither of these reached a level of statistical significance. This is mainly due to the heterogeneity of the disease trait and noise in the data
Empirically derived phenotypic subgroups – qualitative and quantitative trait analyses
BACKGROUND: The Framingham Heart Study has contributed a great deal to advances in medicine. Most of the phenotypes investigated have been univariate traits (quantitative or qualitative). The aims of this study are to derive multivariate traits by identifying homogeneous groups of people and assigning both qualitative and quantitative trait scores; to assess the heritability of the derived traits; and to conduct both qualitative and quantitative linkage analysis on one of the heritable traits. METHODS: Multiple correspondence analysis, a nonparametric analogue of principal components analysis, was used for data reduction. Two-stage clustering, using both k-means and agglomerative hierarchical clustering, was used to cluster individuals based upon axes (factor) scores obtained from the data reduction. Probability of cluster membership was calculated using binary logistic regression. Heritability was calculated using SOLAR, which was also used for the quantitative trait analysis. GENEHUNTER-PLUS was used for the qualitative trait analysis. RESULTS: We found four phenotypically distinct groups. Membership in the smallest group was heritable (38%, p < 1 × 10(-6)) and had characteristics consistent with atherogenic dyslipidemia. We found both qualitative and quantitative LOD scores above 3 on chromosomes 11 and 14 (11q13, 14q23, 14q31). There were two Kong & Cox LOD scores above 1.0 on chromosome 6 (6p21) and chromosome 11 (11q23). CONCLUSION: This approach may be useful for the identification of genetic heterogeneity in complex phenotypes by clarifying the phenotype definition prior to linkage analysis. Some of our findings are in regions linked to elements of atherogenic dyslipidemia and related diagnoses, some may be novel, or may be false positives
Search for genetic factors predisposing to atherogenic dyslipidemia
BACKGROUND: Atherogenic dyslipidemia (AD) is a common feature in persons with premature coronary heart disease. While several linkage studies have been carried out to dissect the genetic etiology of lipid levels, few have investigated the AD lipid triad comprising elevated serum triglyceride, small low density lipoprotein (LDL) particles, and reduced high density lipoprotein (HDL) cholesterol levels. Here we report the results of a whole-genome screen for AD using the Framingham Heart Study population. RESULTS: Our analyses provide some evidence for linkage to AD on chromosomes 1q31, 3q29, 10q26, 14p12, 14q13, 16q24, 18p11, and 19q13. CONCLUSION: AD susceptibility is modulated by multiple genes in different chromosomes. Our study confirms results from other populations and suggests new areas of potential importance
Genome-wide screen for heavy alcohol consumption
BACKGROUND: To find specific genes predisposing to heavy alcohol consumption (self-reported consumption of 24 grams or more of alcohol per day among men and 12 grams or more among women), we studied 330 families collected by the Framingham Heart Study made available to participants in the Genetic Analysis Workshop 13 (GAW13). RESULTS: Parametric and nonparametric methods of linkage analysis were used. No significant evidence of linkage was found; however, weak signals were identified in several chromosomal regions, including 1p22, 4q12, 4q25, and 11q24, which are in the vicinity of those reported in other similar studies. CONCLUSION: Our study did not reveal significant evidence of linkage to heavy alcohol use; however, we found weak confirmation of studies carried out in other populations
Evaluating the role of a galanin enhancer genotype on a range of metabolic, depressive and addictive phenotypes
Funded by •ERC. Grant Number: 284167 •NIH. Grant Number: 1RO1DK0921127-01 •NWO. Grant Numbers: 463-06-001, 451-04-034Peer reviewedPublisher PD
Behavioral Variant Frontotemporal Lobar Degeneration with Amyotrophic Lateral Sclerosis with a Chromosome 9p21 Hexanucleotide Repeat
To determine the genetic basis of familial frontotemporal lobar degeneration (FTLD) with amyotrophic lateral sclerosis (ALS) we performed a clinical and genetic analysis of an affected family. A 51-year-old man with behavioral variant FTLD with ALS had a family history of the disease suggestive of autosomal dominant inheritance with incomplete penetrance. Genetic studies in this patient demonstrated the presence of an amplified hexanucleotide repeat (>30) polymorphism in the chromosome 9 open reading frame 72 (C9ORF72) gene which was previously identified as a cause of FTLD. Five others unaffected from the family were negative (all had less than 11 repeats). Because of the clinical and pathological overlap between FTLD and AD we performed a larger genome-wide association study and did not find association of single nucleotide polymorphisms (SNPs) in the C9ORF72 gene with Alzheimer’s disease (AD) risk. Bioinformatic analysis of C9ORF72 using the Gene Expression Omnibus database showed expression differences in patients with muscular dystrophy, neural tube defects, and schizophrenia. We also report analysis of gene expression in brain regions using the Allen Human Brain Atlas. Defects in this recently reported gene are now believed to be the most common cause of inherited ALS and an important cause of inherited FTLD. Our work suggests that the gene may also be important in other neurological and psychiatric conditions
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