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Common and unique susceptibility loci in Graves and Hashimoto diseases: results of whole-genome screening in a data set of 102 multiplex families.

The autoimmune thyroid diseases (AITDs), comprising Graves disease (GD) and Hashimoto thyroiditis (HT), develop as a result of a complex interaction between predisposing genes and environmental triggers. Previously, we identified six loci that showed evidence for linkage with AITD in a data set of 56 multiplex families. The goals of the present study were to replicate/reject the previously identified loci before fine mapping and sequencing the candidate genes in these regions. We performed a whole-genome linkage study in an expanded data set of 102 multiplex families with AITD (540 individuals), through use of 400 microsatellite markers. Seven loci showed evidence for linkage to AITD. Three loci, on chromosomes 6p, 8q, and 10q, showed evidence for linkage with both GD and HT (maximum multipoint heterogeneity LOD scores [HLOD] 2.0, 3.5, and 4.1, respectively). Three loci showed evidence for linkage with GD: on 7q (HLOD 2.3), 14q (HLOD 2.1), and 20q (LOD 3.3, in a subset of the families). One locus on 12q showed evidence of linkage with HT, giving an HLOD of 3.4. Comparison with the results obtained in the original data set showed that the 20q (GD-2) and 12q (HT-2) loci continued to show evidence for linkage in the expanded data set; the 6p and 14q loci were located within the same region as the previously identified 6p and 14q loci (AITD-1 and GD-1, respectively), but the Xq (GD-3) and 13q (HT-1) loci were not replicated in the expanded data set. These results demonstrated that multiple genes may predispose to GD and HT and that some may be common to both diseases and some are unique. The loci that continue to show evidence for linkage in the expanded data set represent serious candidate regions for gene identification.

Chromosome Mapping↗

Issues in genomic screening: critical values, sample sizes, and the ability to detect linkage.

The aims of this study were to empirically investigate the ability of affected sib pairs (ASPs) to localize a gene through screening and to explore estimation of lod score critical values through resampling. To do so, we repartitioned 25 replicates of 100 simulated nuclear families into six data sets of sizes 100, 200, 300, 400, 500, and 1,000 and chose at most one mildly ASP per family. Using all marker data, we calculated maximum lod scores across the six-chromosome genome for each set. Then, we determined the cutoff value corresponding to a 5% genome-wide false positive rate using both the method of Lander and Kruglyak [1995] and a simple resampling algorithm that allows greater scan-specific flexibility. For chromosome 1, the ability of the ASPs to detect the region between markers 9 and 10 clearly increases with the sample size, and genome-wide significance is achieved for samples of size 400 or greater. Also, as expected, the critical values based on the less conservative resampling approach are generally slightly smaller than those from theoretical calculations based on the Ornstein-Uhlenbeck diffusion process of Lander and Kruglyak.

Genetic Linkage↗

Isolation and identification of three new 5-alkenyl-3,3(2H)-furanones from two streptomyces species using a genomic screening approach.

Analyses of biosynthetic gene clusters derived from Streptomyces aculeolatus NRRL 18422 and Streptomyces sp. Eco86 indicated that both microorganisms have similar type I polyketide synthase (PKS) gene clusters with relatively few genes encoding post-PKS elaborative enzymes. However both gene clusters included a sequence coding for a relatively uncommon oxidative enzyme related to Baeyer-Villiger, flavin-type monooxygenases. Screening of culture extracts for compounds with the predicted physicochemical properties of the end products from these loci, led to the isolation of three 5-alkenyl-3,3(2H)-furanones, one (E-837, 1) from the former and two (E-492, 2, E-975, 3) from the latter strain. The structures, confirmed by spectral analyses including MS, and ID and 2D NMR experiments, were in accord with those predicted by genomic analyses. Baeyer-Villiger type oxidation is postulated to be involved in the formation of the furanone moieties in these molecules. All three new compounds were tested for their electron transport inhibitory activities. They had IC50 values of 1-4 microg/ml against Ascaris suum NADH-fumarate reductase and 1-12 microg/ml against bovine heart NADH oxidase.

Fermentation↗

Genomic screen for substance dependence and body mass index in southwest California Indians.

Substance abuse and obesity are health disparities that may afflict Native Americans more than some other ethnic groups. One theoretical assumption concerning Native people is that the long history of dependence on foraging and subsistence agriculture may have led to selective enrichment of traits that improve genetic fitness, so called 'thrifty' or 'fat sparing' genes. We have speculated that this same selective pressure may have enriched for genetic variants that increase the risk for consumption of alcohol and drugs of abuse. Here, we report the results of a genome scan that compared findings for two consumption phenotypes: 'any drug dependence and/or regular tobacco use' and body mass index (BMI) in southwest California (SWC) Indian families. Variance component analyses from SOLAR were used to generate log of the odds ratio (LOD) scores. Evidence for linkage was found on chromosome 6 for both the 'any drug' (LOD score = 3.3) and BMI (LOD score = 2.3) phenotypes. Bivariate analyses of the two phenotypes revealed a combined LOD score of 4.1 at that location. Additional loci on chromosomes 6, 15, 16 and 21 were found for the 'any drug' phenotype, and on chromosomes 8, 16 and 18 for BMI (LOD scores ranged between 1.2 and 2.3). These results provide suggestive evidence for linkage for substance abuse and BMI in this Mission Indian population and, furthermore, provide preliminary data suggesting that 'consumption phenotypes' may share some genetic determinants.

Adolescent↗

In silico whole-genome screening for cancer-related single-nucleotide polymorphisms located in human mRNA untranslated regions.

BACKGROUND: A promising application of the huge amounts of genetic data currently available lies in developing a better understanding of complex diseases, such as cancer. Analysis of publicly available databases can help identify potential candidates for genes or mutations specifically related to the cancer phenotype. In spite of their huge potential to affect gene function, no systematic attention has been paid so far to the changes that occur in untranslated regions of mRNA. RESULTS: In this study, we used Expressed Sequence Tag (EST) databases as a source for cancer-related sequence polymorphism discovery at the whole-genome level. Using a novel computational procedure, we focused on the identification of untranslated region (UTR)-localized non-coding Single Nucleotide Polymorphisms (UTR-SNPs) significantly associated with the tumoral state. To explore possible relationships between genetic mutation and phenotypic variation, bioinformatic tools were used to predict the potential impact of cancer-associated UTR-SNPs on mRNA secondary structure and UTR regulatory elements. We provide a comprehensive and unbiased description of cancer-associated UTR-SNPs that may be useful to define genotypic markers or to propose polymorphisms that can act to alter gene expression levels. Our results suggest that a fraction of cancer-associated UTR-SNPs may have functional consequences on mRNA stability and/or expression. CONCLUSION: We have undertaken a comprehensive effort to identify cancer-associated polymorphisms in untranslated regions of mRNA and to characterize putative functional UTR-SNPs. Alteration of translational control can change the expression of genes in tumor cells, causing an increase or decrease in the concentration of specific proteins. Through the description of testable candidates and the experimental validation of a number of UTR-SNPs discovered on the secreted protein acidic and rich in cysteine (SPARC) gene, this report illustrates the utility of a cross-talk between in silico transcriptomics and cancer genetics.

Computational Biology↗

A genome screen of systemic lupus erythematosus using affected-relative-pair linkage analysis with covariates demonstrates genetic heterogeneity.

Systemic lupus erythematosus (SLE) appears to be the consequence of complex genetics and of only partly understood environmental contributions. Previous work by ourselves and by others has established genetic effects on 1q, 2q, 4p, 6p, and 16p using SLE as the phenotype. However, individual SLE affecteds are extraordinarily different from one another by clinical and laboratory measures. This variation may have a genetic basis; if so, it is advantageous to incorporate measures of between-family clinical variability as covariates in a genetic linkage analysis of affected relative pairs (ARPs) to allow for locus heterogeneity. This approach was applied to genome scan marker data from 160 pedigrees multiplex for SLE and containing 202 ARPs. Because the number of potential covariates was large, we used both ad hoc methods and formal principal components analysis to construct four composite covariates using the SLE classification criteria plus age of onset, ethnicity, and sex. Linkage analysis without covariates has detected evidence for linkage at 1q22-24, 2q37, 4p16, 12p12-11, and 17p13. Linkage analysis with these covariates uncovered linkage at 13p11, 17q11-25, and 20q12 and greatly improved evidence for linkage at 1q22-24, 2q37, 12p12-11, and 17p13. Follow-up analysis identified the original variables contributing to locus heterogeneity in each of these locations. In conclusion, allowing for locus heterogeneity through the incorporation of covariates in linkage analysis is a useful way to dissect the genetic contributions to SLE and uncover new genetic effects.

Analysis of Variance↗

Genomic screen for QTLs underlying alcohol consumption in the P and NP rat lines.

Selective breeding for voluntary alcohol consumption was utilized to establish the alcohol-preferring (P) and alcohol-nonpreferring (NP) rat lines. Inbreeding was initiated after 30 generations of selection and, after 19 generations of inbreeding, 384 F2 intercross progeny were created to identify quantitative trait loci (QTLs) influencing alcohol consumption. We had reported previously a QTL on Chromosome (Chr) 4; additional markers genotyped on Chr 4 have increased the maximum lod score from 8.6 to 9.2. This QTL acts in an additive fashion and continues to account for approximately 11% of the phenotypic variability. The 95% confidence interval is 12.5 cM and includes the candidate gene, neuropeptide Y. Subsequent to the identification of the QTL on Chr 4, a genome scan was completed to identify additional QTLs influencing alcohol consumption. A lod score of 2.5 was obtained on Chr 3, syntenic to a region previously reported for alcohol preference in mice. Analysis of Chr 8 produced a lod score of 2.2 near the dopamine D2 and serotonin 1b receptors, which have been previously reported as candidate genes for alcohol preference. Evidence for linkage to alcohol consumption was not found on any other chromosome. It therefore appears likely that, in addition to the QTL on Chr 4, multiple loci of small to moderate effect, such as those on Chrs 3 and 8, underlie the difference in alcohol consumption in the P/NP lines.

Alcohol Drinking↗

A genome screen for linkage disequilibrium in Turkish multiple sclerosis.

In order to screen the Turkish population for evidence of association with multiple sclerosis, we typed 6000 microsatellite markers in separately pooled DNA samples from 197 cases and 199 controls following the Genetic Analysis of Multiple sclerosis in EuropeanS (GAMES) protocol. Twelve markers showing evidence for association were identified. One of these markers lying directly in a region which is also implicated in the Turkish linkage screen (chromosome 5p15) and thus shows evidence for both linkage and association in independent data sets.

Adult↗

Statistical tests for detection of misspecified relationships by use of genome-screen data.

Misspecified relationships can have serious consequences for linkage studies, resulting in either reduced power or false-positive evidence for linkage. If some individuals in the pedigree are untyped, then Mendelian errors may not be observed. Previous approaches to detection of misspecified relationships by use of genotype data were developed for sib and half-sib pairs. We extend the likelihood calculations of Göring and Ott and Boehnke and Cox to more-general relative pairs, for which identity-by-descent (IBD) status is no longer a Markov chain, and we propose a likelihood-ratio test. We also extend the identity-by-state (IBS)-based test of Ehm and Wagner to nonsib relative pairs. The likelihood-ratio test has high power, but its drawbacks include the need to construct and apply a separate Markov chain for each possible alternative relationship and the need for simulation to assess significance. The IBS-based test is simpler but has lower power. We propose two new test statistics-conditional expected IBD (EIBD) and adjusted IBS (AIBS)-designed to retain the simplicity of IBS while increasing power by taking into account chance sharing. In simulations, the power of EIBD is generally close to that of the likelihood-ratio test. The power of AIBS is higher than that of IBS, in all cases considered. We suggest a strategy of initial screening by use of EIBD and AIBS, followed by application of the likelihood-ratio test to only a subset of relative pairs, identified by use of EIBD and AIBS. We apply the methods to a Genetic Analysis Workshop 11 data set from the Collaborative Study on the Genetics of Alcoholism.

Alcoholism↗

A genome screen in multiple sclerosis reveals susceptibility loci on chromosome 6p21 and 17q22.

The population prevalence of multiple sclerosis is 0.1%; however, the risk of the disease in the siblings of affected individuals is very much higher at 3-5%. The importance of genetic factors in accounting for this increased risk is confirmed by the results of twin and adoption studies. Despite the evidence for a strong genetic effect, a weak major histocompatibility complex (MHC) association is the only consistently observed feature in the genetics of multiple sclerosis. Other candidates have been proposed, including genes encoding the immunoglobulin heavy chain, T cell receptor beta chain and APOC2, but none has yet been confirmed. Evidence for linkage and association to the myelin basic protein gene has been reported in a genetically isolated Finnish population, but it has not been possible to reproduce these results in other populations. We used a two-stage approach to search the human genome for the genes causing susceptibility to multiple sclerosis. Two principal regions of linkage are identified, chromosomes 17q22 and 6p21 (MHC). Our results are compatible with genetic models involving epistatic interaction between these and several additional genes.

Chromosome Mapping↗

Comparison of sib-pair and variance-components methods for genomic screening.

The statistical properties of sib-pair and variance-components linkage methods were compared using the nuclear family data from Problem 2. Overall, the power to detect linkage was not high for either method. The variance-components method had better power for detection of linkage, particularly when covariates were included in the model. Type I error rates were similar to nominal error rates for both methods.

Analysis of Variance↗

A graphical approach for presenting linkage results from a genomic screen.

Initially, a sib-pair linkage analysis was performed between the marker loci and six untransformed variables. Results from several variations of this initial analysis were compared using a graphical approach (P-plots) to simplify presentation. When results were compared to the generating model, most of the aspects of the generating model were recovered, although we did not find evidence of the polygenic component shared by Q2 and Q3, or evidence of linkage between MG4 and Q4 at the 0.01 level.

Chromosome Mapping↗

Genomic screening for fucosidosis in English Springer Spaniels.

OBJECTIVE: To develop a robust molecular genetic test for alpha-L-fucosidosis in English Springer Spaniels and to screen dogs from the United Kingdom and United States for the mutant allele. ANIMALS: 35 English-bred English Springer Spaniels, 60 American-bred English Springer Spaniels, and 1 affected dog and its parents from a family of English Springer Spaniels in Colorado. PROCEDURE: Polymerase chain reaction analysis was used to amplify the mutated region in the gene encoding alpha-L-fucosidase. High guanine-cytosine (GC) content of the region required use of an amplification buffer with high pH. Mutant and normal alleles were separated by polyacrylamide gel electrophoresis. Molecular genetic test results were compared with enzyme data. RESULTS: A 262-bp PCR product was amplified from normal dogs and compared with a 248-bp product from affected dogs. Carriers had 1 copy of each allele, distinguishable by the 14-bp size difference. Two carriers among the English-bred dogs were identified by use of enzyme and genomic DNA analyses. The molecular defect in dogs from Colorado was proven to be the same as that in British and Australian dogs. None of the other 60 American-bred dogs carried the mutant allele. CONCLUSIONS AND CLINICAL RELEVANCE: A PCR method that can be used to identify dogs affected with or carriers of the autosomal recessive disease fucosidosis was established. Amplification was achieved within a GC-rich region, using a method that may be useful in overcoming amplification problems in GC-rich areas within other genes. Using this test, fucosidosis can be controlled and ultimately eradicated from the English Springer Spaniel population.

Animals↗

A whole genome screen for association in Polish multiple sclerosis patients.

We have performed the first systematic search for MS susceptibility genes completed in the Polish population. This screen was performed using 6000 microsatellite markers typed in pooled DNA from cases (n=200), controls (n=200) and trio families (n=129). Five associated markers are identified, one (D6S2444) from the HLA region and four are from novel regions not previously associated with MS, 2p16 (D2S2153), 3p13 (D3S3568), 7p22 (D7S2521) and 15q26 (D15S649).

Adult↗

Monte Carlo Markov chain methods for genome screening.

We used Monte Carlo Markov chain (MCMC) methods to analyze a quantitative trait, MAO level, and a discrete trait, Collaborative Study on the Genetics of Alcoholism (COGA) alcoholism. Segregation, linkage, and haplotype sharing were analyzed and effects of marker map features were examined. For MAO, modest signals were found on chromosomes 1 and 17 for raw data, and 15 for covariate-adjusted data. For alcoholism, a strong signal was found on chromosome 1 with modest signals on chromosomes 4 and 10.

Alcoholism↗

Genetic dissection of familial autoimmune thyroid diseases using whole genome screening.

The autoimmune thyroid diseases (AITDs) are multifactorial disease which are caused by genetic susceptibility and environmental triggers. Various epidemiological and genetic techniques can be employed to study the genetic contribution to disease development. Most epidemiologic data support an important genetic contribution to the development of AITD. The genetic susceptibility to AITD involves several genes with varying effects. Some AITD susceptibility genes are most likely immune modifying genes which increase the susceptibility to autoimmunity in general (e.g. HLA, CTLA-4) while others may be thyroid-specific (e.g. thyroglobulin). These genes probably act in concert to increase the autoimmune reactions in susceptible individuals and direct them towards the thyroid.

Abatacept↗