Genome-wide associations of gene expression variation in humans

The exploration of quantitative variation in human populations has become one of the major priorities for medical genetics. The successful identification of variants that contribute to complex traits is highly dependent on reliable assays and genetic maps. We have performed a genome-wide quantitative trait analysis of 630 genes in 60 unrelated Utah residents with ancestry from Northern and Western Europe using the publicly available phase I data of the International HapMap project. The genes are located in regions of the human genome with elevated functional annotation and disease interest including the ENCODE regions spanning 1% of the genome, Chromosome 21 and Chromosome 20q12-13.2. We apply three different methods of multiple test correction, including Bonferroni, false discovery rate, and permutations. For the 374 expressed genes, we find many regions with statistically significant association of single nucleotide polymorphisms (SNPs) with expression variation in lymphoblastoid cell lines after correcting for multiple tests. Based on our analyses, the signal proximal (cis-) to the genes of interest is more abundant and more stable than distal and trans across statistical methodologies. Our results suggest that regulatory polymorphism is widespread in the human genome and show that the 5-kb (phase I) HapMap has sufficient density to enable linkage disequilibrium mapping in humans. Such studies will significantly enhance our ability to annotate the non-coding part of the genome and interpret functional variation. In addition, we demonstrate that the HapMap cell lines themselves may serve as a useful resource for quantitative measurements at the cellular level

Concordance for clonal hematopoiesis is limited in elderly twins.

Although acquisition of leukemia-associated somatic mutations by 1 or more hematopoietic stem cells is inevitable with advancing age, its consequences are highly variable, ranging from clinically silent clonal hematopoiesis (CH) to leukemic progression. To investigate the influence of heritable factors on CH, we performed deep targeted sequencing of blood DNA from 52 monozygotic (MZ) and 27 dizygotic (DZ) twin pairs (aged 70-99 years). Using this highly sensitive approach, we identified CH (variant allele frequency ≥0.5%) in 62% of individuals. We did not observe higher concordance for CH within MZ twin pairs as compared with that within DZ twin pairs, or to that expected by chance. However, we did identify 2 MZ pairs in which both twins harbored identical rare somatic mutations, suggesting a shared cell of origin. Finally, in 3 MZ twin pairs harboring mutations in the same driver genes, serial blood samples taken 4 to 5 years apart showed substantial twin-to-twin variability in clonal trajectories. Our findings propose that the inherited genome does not exert a dominant influence on the behavior of adult CH and provide evidence that CH mutations may be acquired in utero

Evaluating the glucose raising effect of established loci via a genetic risk score.

Recent genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) associated with glucose levels. We tested the hypothesis here whether the cumulative effect of glucose raising SNPs, assessed via a score, is associated with glucose levels. A total of 1,434 participants of Greek descent from the THISEAS study and 1,160 participants form the GOMAP study were included in this analysis. We developed a genetic risk score (GRS), based on the known glucose-raising loci, in order to investigate the cumulative effect of known glucose loci on glucose levels. In the THISEAS study, the GRS score was significantly associated with increased glucose levels (mmol/L) (β ± SE: 0.024 ± 0.004, P = 8.27e-07). The effect of the genetic risk score was also significant in the GOMAP study (β ± SE: 0.011 ± 0.005, P = 0.031). In the meta-analysis of the two studies both scores were significantly associated with higher glucose levels GRS: β ± SE: 0.019 ± 0.003, P = 1.41e-09. Also, variants at the SLC30A8, PROX1, MTNR1B, ADRA2A, G6PC2, LPIN3 loci indicated nominal evidence for association with glucose levels (p < 0.05). We replicate associations of the established glucose raising variants in the Greek population and confirm directional consistency of effects (binomial sign test p = 6.96e-05). We also demonstrate that the cumulative effect of the established glucose loci yielded a significant association with increasing glucose levels

Data analysis issues for allele-specific expression using Illumina's GoldenGate assay.

BACKGROUND: High-throughput measurement of allele-specific expression (ASE) is a relatively new and exciting application area for array-based technologies. In this paper, we explore several data sets which make use of Illumina's GoldenGate BeadArray technology to measure ASE. This platform exploits coding SNPs to obtain relative expression measurements for alleles at approximately 1500 positions in the genome. RESULTS: We analyze data from a mixture experiment where genomic DNA samples from pairs of individuals of known genotypes are pooled to create allelic imbalances at varying levels for the majority of SNPs on the array. We observe that GoldenGate has less sensitivity at detecting subtle allelic imbalances (around 1.3 fold) compared to extreme imbalances, and note the benefit of applying local background correction to the data. Analysis of data from a dye-swap control experiment allowed us to quantify dye-bias, which can be reduced considerably by careful normalization. The need to filter the data before carrying out further downstream analysis to remove non-responding probes, which show either weak, or non-specific signal for each allele, was also demonstrated. Throughout this paper, we find that a linear model analysis of the data from each SNP is a flexible modelling strategy that allows for testing of allelic imbalances in each sample when replicate hybridizations are available. CONCLUSIONS: Our analysis shows that local background correction carried out by Illumina's software, together with quantile normalization of the red and green channels within each array, provides optimal performance in terms of false positive rates. In addition, we strongly encourage intensity-based filtering to remove SNPs which only measure non-specific signal. We anticipate that a similar analysis strategy will prove useful when quantifying ASE on Illumina's higher density Infinium BeadChips.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Collaborative Meta-analysis: Associations of 150 Candidate Genes With Osteoporosis and Osteoporotic Fracture

To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldBACKGROUND: Osteoporosis is a highly heritable trait. Many candidate genes have been proposed as being involved in regulating bone mineral density (BMD). Few of these findings have been replicated in independent studies. OBJECTIVE: To assess the relationship between BMD and fracture and all common single-nucleotide polymorphisms (SNPs) in previously proposed osteoporosis candidate genes. DESIGN: Large-scale meta-analysis of genome-wide association data. SETTING: 5 international, multicenter, population-based studies. PARTICIPANTS: Data on BMD were obtained from 19 195 participants (14 277 women) from 5 populations of European origin. Data on fracture were obtained from a prospective cohort (n = 5974) from the Netherlands. MEASUREMENTS: Systematic literature review using the Human Genome Epidemiology Navigator identified autosomal genes previously evaluated for association with osteoporosis. We explored the common SNPs arising from the haplotype map of the human genome (HapMap) across all these genes. BMD at the femoral neck and lumbar spine was measured by dual-energy x-ray absorptiometry. Fractures were defined as clinically apparent, site-specific, validated nonvertebral and vertebral low-energy fractures. RESULTS: 150 candidate genes were identified and 36 016 SNPs in these loci were assessed. SNPs from 9 gene loci (ESR1, LRP4, ITGA1, LRP5, SOST, SPP1, TNFRSF11A, TNFRSF11B, and TNFSF11) were associated with BMD at either site. For most genes, no SNP was statistically significant. For statistically significant SNPs (n = 241), effect sizes ranged from 0.04 to 0.18 SD per allele. SNPs from the LRP5, SOST, SPP1, and TNFRSF11A loci were significantly associated with fracture risk; odds ratios ranged from 1.13 to 1.43 per allele. These effects on fracture were partially independent of BMD at SPP1 and SOST. Limitation: Only common polymorphisms in linkage disequilibrium with SNPs in HapMap could be assessed, and previously reported associations for SNPs in some candidate genes could not be excluded. CONCLUSION: In this large-scale collaborative genome-wide meta-analysis, 9 of 150 candidate genes were associated with regulation of BMD, 4 of which also significantly affected risk for fracture. However, most candidate genes had no consistent association with BMD

A Histone Map of Human Chromosome 20q13.12

We present a systematic search for regulatory elements in a 3.5 Mb region on human chromosome 20q13.12, a region associated with a number of medical conditions such as type II diabetes and obesity.We profiled six histone modifications alongside RNA polymerase II (PolII) and CTCF in two cell lines, HeLa S3 and NTERA-2 clone D1 (NT2/D1), by chromatin immunoprecipitation using an in-house spotted DNA array, constructed with 1.8 kb overlapping plasmid clones. In both cells, more than 90% of transcription start sites (TSSs) of expressed genes showed enrichments with PolII, di-methylated lysine 4 of histone H3 (H3K4me2), tri-methylated lysine 4 of histone H3 (H3K4me3) or acetylated H3 (H3Ac), whereas mono-methylated lysine 4 of histone H3 (H3K4me1) signals did not correlate with expression. No TSSs were enriched with tri-methylated lysine 27 of histone H3 (H3K27me3) in HeLa S3, while eight TSSs (4 expressed) showed enrichments in NT2/D1. We have also located several CTCF binding sites that are potential insulator elements.In summary, we annotated a number of putative regulatory elements in 20q13.12 and went on to verify experimentally a subset of them using dual luciferase reporter assays. Correlating this data to sequence variation can aid identification of disease causing variants

Gene expression changes with age in skin, adipose tissue, blood and brain

BACKGROUND Previous studies have demonstrated that gene expression levels change with age. These changes are hypothesized to influence the aging rate of an individual. We analyzed gene expression changes with age in abdominal skin, subcutaneous adipose tissue and lymphoblastoid cell lines in 856 female twins in the age range of 39-85 years. Additionally, we investigated genotypic variants involved in genotype-by-age interactions to understand how the genomic regulation of gene expression alters with age. RESULTS Using a linear mixed model, differential expression with age was identified in 1,672 genes in skin and 188 genes in adipose tissue. Only two genes expressed in lymphoblastoid cell lines showed significant changes with age. Genes significantly regulated by age were compared with expression profiles in 10 brain regions from 100 postmortem brains aged 16 to 83 years. We identified only one age-related gene common to the three tissues. There were 12 genes that showed differential expression with age in both skin and brain tissue and three common to adipose and brain tissues. CONCLUSIONS Skin showed the most age-related gene expression changes of all the tissues investigated, with many of the genes being previously implicated in fatty acid metabolism, mitochondrial activity, cancer and splicing. A significant proportion of age-related changes in gene expression appear to be tissue-specific with only a few genes sharing an age effect in expression across tissues. More research is needed to improve our understanding of the genetic influences on aging and the relationship with age-related diseases

Gene × dietary pattern interactions in obesity: Analysis of up to 68 317 adults of European ancestry

Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphisms were genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GR

The Molecular Genetic Architecture of Self-Employment

Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable-entrepreneurship-that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σg2/σP2= 25%, h2= 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10-5were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≥0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases