Thyroid function in Danish greenhouse workers

BACKGROUND: From animal studies it is known that currently used pesticides can disturb thyroid function. METHODS: In the present study we investigated the thyroid function in 122 Danish greenhouse workers, to evaluate if greenhouse workers classified as highly exposed to pesticides experiences altered thyroid levels compared to greenhouse workers with lower exposure. Serum samples from the greenhouse workers were sampled both in the spring and the fall to evaluate if differences in pesticide use between seasons resulted in altered thyroid hormone levels. RESULTS: We found a moderate reduction of free thyroxine (FT4) (10–16%) among the persons working in greenhouses with a high spraying load both in samples collected in the spring and the fall, but none of the other measured thyroid hormones differed significantly between exposure groups in the cross-sectional comparisons. However, in longitudinal analysis of the individual thyroid hormone level between the spring and the fall, more pronounced differences where found with on average 32% higher thyroid stimulating hormone (TSH) level in the spring compared to the fall and at the same time a 5–9% lower total triiodthyroxin (TT3), free triiodthyroxine (FT3) and FT4. The difference between seasons was not consistently more pronounced in the group classified as high exposure compared to the low exposure groups. CONCLUSION: The present study indicates that pesticide exposure among Danish greenhouse workers results in only minor disturbances of thyroid hormone levels

Breakpoint characterization of large deletions in EXT1 or EXT2 in 10 Multiple Osteochondromas families

<p>Abstract</p> <p>Background</p> <p>Osteochondromas (cartilage-capped bone tumors) are by far the most commonly treated of all primary benign bone tumors (50%). In 15% of cases, these tumors occur in the context of a hereditary syndrome called multiple osteochondromas (MO), an autosomal dominant skeletal disorder characterized by the formation of multiple cartilage-capped bone tumors at children's metaphyses. MO is caused by various mutations in <it>EXT1 </it>or <it>EXT2</it>, whereby large genomic deletions (single-or multi-exonic) are responsible for up to 8% of MO-cases.</p> <p>Methods</p> <p>Here we report on the first molecular characterization of ten large <it>EXT1</it>- and <it>EXT2</it>-deletions in MO-patients. Deletions were initially indentified using MLPA or FISH analysis and were subsequently characterized using an MO-specific tiling path array, allele-specific PCR-amplification and sequencing analysis.</p> <p>Results</p> <p>Within the set of ten large deletions, the deleted regions ranged from 2.7 to 260 kb. One <it>EXT2 </it>exon 8 deletion was found to be recurrent. All breakpoints were located outside the coding exons of <it>EXT1 </it>and <it>EXT2</it>. Non-allelic homologous recombination (NAHR) mediated by <it>Alu</it>-sequences, microhomology mediated replication dependent recombination (MMRDR) and non-homologous end-joining (NHEJ) were hypothesized as the causal mechanisms in different deletions.</p> <p>Conclusions</p> <p>Molecular characterization of <it>EXT1</it>- and <it>EXT2</it>-deletion breakpoints in MO-patients indicates that NAHR between <it>Alu-</it>sequences as well as NHEJ are causal and that the majority of these deletions are nonrecurring. These observations emphasize once more the huge genetic variability which is characteristic for MO. To our knowledge, this is the first study characterizing large genomic deletions in <it>EXT1 </it>and <it>EXT2</it>.</p

A Covering Method for Detecting Genetic Associations between Rare Variants and Common Phenotypes

Genome wide association (GWA) studies, which test for association between common genetic markers and a disease phenotype, have shown varying degrees of success. While many factors could potentially confound GWA studies, we focus on the possibility that multiple, rare variants (RVs) may act in concert to influence disease etiology. Here, we describe an algorithm for RV analysis, RARECOVER. The algorithm combines a disparate collection of RVs with low effect and modest penetrance. Further, it does not require the rare variants be adjacent in location. Extensive simulations over a range of assumed penetrance and population attributable risk (PAR) values illustrate the power of our approach over other published methods, including the collapsing and weighted-collapsing strategies. To showcase the method, we apply RARECOVER to re-sequencing data from a cohort of 289 individuals at the extremes of Body Mass Index distribution (NCT00263042). Individual samples were re-sequenced at two genes, FAAH and MGLL, known to be involved in endocannabinoid metabolism (187Kbp for 148 obese and 150 controls). The RARECOVER analysis identifies exactly one significantly associated region in each gene, each about 5 Kbp in the upstream regulatory regions. The data suggests that the RVs help disrupt the expression of the two genes, leading to lowered metabolism of the corresponding cannabinoids. Overall, our results point to the power of including RVs in measuring genetic associations.National Science Foundation (U.S.) (grant (IIS-0810905)National Institutes of Health (U.S.) (U19 AG023122-05)National Institutes of Health (U.S.) (R01 MH078151-03)Louis & Harold Price FoundationNational Institutes of Health (U.S.) (N01 MH22005)National Institutes of Health (U.S.) (U01-DA024417-01)National Institutes of Health (U.S.) (P50 MH081755-01)National Institutes of Health (U.S.) (R01 AG030474-02)National Institutes of Health (U.S.) (N01 MH022005)National Institutes of Health (U.S.) (R01 HL089655-02)National Institutes of Health (U.S.) (R01 MH080134-03)National Institutes of Health (U.S.) (U54 CA143906-01)National Institutes of Health (U.S.) (UL1 RR025774-03)Scripps Genomic Medicine ProgramNational Human Genome Research Institute (U.S.) (Grant Number T32 HG002295

Correction of Population Stratification in Large Multi-Ethnic Association Studies

The vast majority of genetic risk factors for complex diseases have, taken individually, a small effect on the end phenotype. Population-based association studies therefore need very large sample sizes to detect significant differences between affected and non-affected individuals. Including thousands of affected individuals in a study requires recruitment in numerous centers, possibly from different geographic regions. Unfortunately such a recruitment strategy is likely to complicate the study design and to generate concerns regarding population stratification.We analyzed 9,751 individuals representing three main ethnic groups - Europeans, Arabs and South Asians - that had been enrolled from 154 centers involving 52 countries for a global case/control study of acute myocardial infarction. All individuals were genotyped at 103 candidate genes using 1,536 SNPs selected with a tagging strategy that captures most of the genetic diversity in different populations. We show that relying solely on self-reported ethnicity is not sufficient to exclude population stratification and we present additional methods to identify and correct for stratification.Our results highlight the importance of carefully addressing population stratification and of carefully “cleaning” the sample prior to analyses to obtain stronger signals of association and to avoid spurious results

Forward-time simulation of realistic samples for genome-wide association studies

<p>Abstract</p> <p>Background</p> <p>Forward-time simulations have unique advantages in power and flexibility for the simulation of genetic samples of complex human diseases because they can closely mimic the evolution of human populations carrying these diseases. However, a number of methodological and computational constraints have prevented the power of this simulation method from being fully explored in existing forward-time simulation methods.</p> <p>Results</p> <p>Using a general-purpose forward-time population genetics simulation environment, we developed a forward-time simulation method that can be used to simulate realistic samples for genome-wide association studies. We examined the properties of this simulation method by comparing simulated samples with real data and demonstrated its wide applicability using four examples, including a simulation of case-control samples with a disease caused by multiple interacting genetic and environmental factors, a simulation of trio families affected by a disease-predisposing allele that had been subjected to either slow or rapid selective sweep, and a simulation of a structured population resulting from recent population admixture.</p> <p>Conclusions</p> <p>Our algorithm simulates populations that closely resemble the complex structure of the human genome, while allows the introduction of signals of natural selection. Because of its flexibility to generate different types of samples with arbitrary disease or quantitative trait models, this simulation method can simulate realistic samples to evaluate the performance of a wide variety of statistical gene mapping methods for genome-wide association studies.</p

Diverse Splicing Patterns of Exonized Alu Elements in Human Tissues

Exonization of Alu elements is a major mechanism for birth of new exons in primate genomes. Prior analyses of expressed sequence tags show that almost all Alu-derived exons are alternatively spliced, and the vast majority of these exons have low transcript inclusion levels. In this work, we provide genomic and experimental evidence for diverse splicing patterns of exonized Alu elements in human tissues. Using Exon array data of 330 Alu-derived exons in 11 human tissues and detailed RT-PCR analyses of 38 exons, we show that some Alu-derived exons are constitutively spliced in a broad range of human tissues, and some display strong tissue-specific switch in their transcript inclusion levels. Most of such exons are derived from ancient Alu elements in the genome. In SEPN1, mutations of which are linked to a form of congenital muscular dystrophy, the muscle-specific inclusion of an Alu-derived exon may be important for regulating SEPN1 activity in muscle. Realtime qPCR analysis of this SEPN1 exon in macaque and chimpanzee tissues indicates human-specific increase in its transcript inclusion level and muscle specificity after the divergence of humans and chimpanzees. Our results imply that some Alu exonization events may have acquired adaptive benefits during the evolution of primate transcriptomes

Generalised Anxiety Disorder – A Twin Study of Genetic Architecture, Genome-Wide Association and Differential Gene Expression

Generalised Anxiety Disorder (GAD) is a common anxiety-related diagnosis, affecting approximately 5% of the adult population. One characteristic of GAD is a high degree of anxiety sensitivity (AS), a personality trait which describes the fear of arousal-related sensations. Here we present a genome-wide association study of AS using a cohort of 730 MZ and DZ female twins. The GWAS showed a significant association for a variant within the RBFOX1 gene. A heritability analysis of the same cohort also confirmed a significant genetic component with h2 of 0.42. Additionally, a subset of the cohort (25 MZ twins discordant for AS) was studied for evidence of differential expression using RNA-seq data. Significant differential expression of two exons with the ITM2B gene within the discordant MZ subset was observed, a finding that was replicated in an independent cohort. While previous research has shown that anxiety has a high comorbidity with a variety of psychiatric and neurodegenerative disorders, our analysis suggests a novel etiology specific to AS

Sequence Composition and Gene Content of the Short Arm of Rye (Secale cereale) Chromosome 1

BACKGROUND: The purpose of the study is to elucidate the sequence composition of the short arm of rye chromosome 1 (Secale cereale) with special focus on its gene content, because this portion of the rye genome is an integrated part of several hundreds of bread wheat varieties worldwide. METHODOLOGY/PRINCIPAL FINDINGS: Multiple Displacement Amplification of 1RS DNA, obtained from flow sorted 1RS chromosomes, using 1RS ditelosomic wheat-rye addition line, and subsequent Roche 454FLX sequencing of this DNA yielded 195,313,589 bp sequence information. This quantity of sequence information resulted in 0.43× sequence coverage of the 1RS chromosome arm, permitting the identification of genes with estimated probability of 95%. A detailed analysis revealed that more than 5% of the 1RS sequence consisted of gene space, identifying at least 3,121 gene loci representing 1,882 different gene functions. Repetitive elements comprised about 72% of the 1RS sequence, Gypsy/Sabrina (13.3%) being the most abundant. More than four thousand simple sequence repeat (SSR) sites mostly located in gene related sequence reads were identified for possible marker development. The existence of chloroplast insertions in 1RS has been verified by identifying chimeric chloroplast-genomic sequence reads. Synteny analysis of 1RS to the full genomes of Oryza sativa and Brachypodium distachyon revealed that about half of the genes of 1RS correspond to the distal end of the short arm of rice chromosome 5 and the proximal region of the long arm of Brachypodium distachyon chromosome 2. Comparison of the gene content of 1RS to 1HS barley chromosome arm revealed high conservation of genes related to chromosome 5 of rice. CONCLUSIONS: The present study revealed the gene content and potential gene functions on this chromosome arm and demonstrated numerous sequence elements like SSRs and gene-related sequences, which can be utilised for future research as well as in breeding of wheat and rye

A genome-wide CRISPR screen identifies a restricted set of HIV host dependency factors

Host proteins are essential for HIV entry and replication and can be important nonviral therapeutic targets. Large-scale RNA interference (RNAi)-based screens have identified nearly a thousand candidate host factors, but there is little agreement among studies and few factors have been validated. Here we demonstrate that a genome-wide CRISPR-based screen identifies host factors in a physiologically relevant cell system. We identify five factors, including the HIV co-receptors CD4 and CCR5, that are required for HIV infection yet are dispensable for cellular proliferation and viability. Tyrosylprotein sulfotransferase 2 (TPST2) and solute carrier family 35 member B2 (SLC35B2) function in a common pathway to sulfate CCR5 on extracellular tyrosine residues, facilitating CCR5 recognition by the HIV envelope. Activated leukocyte cell adhesion molecule (ALCAM) mediates cell aggregation, which is required for cell-to-cell HIV transmission. We validated these pathways in primary human CD4 + T cells through Cas9-mediated knockout and antibody blockade. Our findings indicate that HIV infection and replication rely on a limited set of host-dispensable genes and suggest that these pathways can be studied for therapeutic intervention

Informed Conditioning on Clinical Covariates Increases Power in Case-Control Association Studies

Genetic case-control association studies often include data on clinical covariates, such as body mass index (BMI), smoking status, or age, that may modify the underlying genetic risk of case or control samples. For example, in type 2 diabetes, odds ratios for established variants estimated from low–BMI cases are larger than those estimated from high–BMI cases. An unanswered question is how to use this information to maximize statistical power in case-control studies that ascertain individuals on the basis of phenotype (case-control ascertainment) or phenotype and clinical covariates (case-control-covariate ascertainment). While current approaches improve power in studies with random ascertainment, they often lose power under case-control ascertainment and fail to capture available power increases under case-control-covariate ascertainment. We show that an informed conditioning approach, based on the liability threshold model with parameters informed by external epidemiological information, fully accounts for disease prevalence and non-random ascertainment of phenotype as well as covariates and provides a substantial increase in power while maintaining a properly controlled false-positive rate. Our method outperforms standard case-control association tests with or without covariates, tests of gene x covariate interaction, and previously proposed tests for dealing with covariates in ascertained data, with especially large improvements in the case of case-control-covariate ascertainment. We investigate empirical case-control studies of type 2 diabetes, prostate cancer, lung cancer, breast cancer, rheumatoid arthritis, age-related macular degeneration, and end-stage kidney disease over a total of 89,726 samples. In these datasets, informed conditioning outperforms logistic regression for 115 of the 157 known associated variants investigated (P-value = 1×10−9). The improvement varied across diseases with a 16% median increase in χ2 test statistics and a commensurate increase in power. This suggests that applying our method to existing and future association studies of these diseases may identify novel disease loci