Genetics of gene expression and its effect on disease. Nature. 2008;452:423-428. [PMID: 18344981 DOI: 10.1038/nature06758]

Sequence variant on 8q24 confers susceptibility to urinary bladder cancer

We conducted a genome-wide SNP association study on 1,803 urinary bladder cancer (UBC) cases and 34,336 controls from Iceland and The Netherlands and follow up studies in seven additional case-control groups (2,165 cases and 3,800 controls). The strongest association was observed with allele T of rs9642880 on chromosome 8q24, 30 kb upstream of MYC (allele-specific odds ratio (OR) = 1.22; P = 9.34 x 10(-12)). Approximately 20% of individuals of European ancestry are homozygous for rs9642880[T], and their estimated risk of developing UBC is 1.49 times that of noncarriers. No association was observed between UBC and the four 8q24 variants previously associated with prostate, colorectal and breast cancers, nor did rs9642880 associate with any of these three cancers. A weaker signal, but nonetheless of genome-wide significance, was captured by rs710521[A] located near TP63 on chromosome 3q28 (allele-specific OR = 1.19; P = 1. 15 x 10(-7)).

Genome-wide association studies: a new window into immune-mediated diseases

Given the recent explosion of genetic discoveries, 2007 is becoming known to human geneticists as the year of genome-wide association studies. In fact, more genetic risk factors for common diseases were identified in this one year than had been collectively reported before 2007. In particular, 2007 witnessed the discovery of many genes that influence susceptibility to individual immune-mediated diseases, as well as other genes that are associated with susceptibility to more than one disease. Although much work remains to be done, in this Review we discuss what effect these studies are having on our understanding of disease pathogenesis and their potential impact on future immunology studies.

Tilting at quixotic trait loci (QTL): an evolutionary perspective on genetic causation

Recent years have seen great advances in generating and analyzing data to identify the genetic architecture of biological traits. Human disease has understandably received intense research focus, and the genes responsible for most Mendelian diseases have successfully been identified. However, the same advances have shown a consistent if less satisfying pattern, in which complex traits are affected by variation in large numbers of genes, most of which have individually minor or statistically elusive effects, leaving the bulk of genetic etiology unaccounted for. This pattern applies to diverse and unrelated traits, not just disease, in basically all species, and is consistent with evolutionary expectations, raising challenging questions about the best way to approach and understand biological complexity.

Cannabinoid type 1 receptor blockade promotes mitochondrial biogenesis through endothelial nitric oxide synthase expression in white adipocytes

OBJECTIVE

Cannabinoid type 1 (CB1) receptor blockade decreases body weight and adiposity in obese subjects; however, the underlying mechanism is not yet fully understood. Nitric oxide (NO) produced by endothelial NO synthase (eNOS) induces mitochondrial biogenesis and function in adipocytes. This study was undertaken to test whether CB1 receptor blockade increases the espression of eNOS and mitochondrial biogenesis in white adipocytes.

RESEARCH DESIGN AND METHODS

We examined the effects on eNOS and mitochondrial biogenesis of selective pharmacological blockade of CB1 receptors by SR141716 (rimonabant) in mouse primary white adipocytes. We also examined eNOS expression and mitochondrial biogenesis in white adipose tissue (WAT) and isolated mature white adipocytes of CB1 receptor-deficient (CB1(-/-)) and chronically SR141716-treated mice on either a standard or high-fat diet.

RESULTS

SR141716 treatment increased eNOS expression in cultured white adipocytes. Moreover, SR141716 increased mitochondrial DNA amount, mRNA levels of genes involved in mitochondrial biogenesis, and mitochondrial mass and function through eNOS induction, as demonstrated by reversal of SR141716 effects by small interfering RNA-mediated decrease in eNOS. While high-fat diet-fed wild-type mice showed reduced eNOS expression and mitochondrial biogenesis in WAT and isolated mature white adipocytes, genetic CB1 receptor deletion or chronic treatment with SR141716 restored these parameters to the levels observed in wild-type mice on the standard diet, an effect linked to the prevention of adiposity and body weight increase.

CONCLUSIONS

CB1 receptor blockade increases mitochondrial biogenesis in white adipocytes by inducing the expression of eNOS. This is linked to the prevention of high-fat diet-induced fat accumulation, without concomitant changes in food intake.

The environmental contribution to gene expression profiles

Microarray analysis provides a bridge between the molecular genetic analysis of model organisms in laboratory settings and studies of physiology, development, and adaptation in the wild. By sampling species across a range of environments, it is possible to gain a broad picture of the genomic response to environmental perturbation. Incorporating estimates of genetic relationships into study designs will facilitate genomic analysis of environmental plasticity by aiding the identification of major regulatory loci in natural populations.

Genes and networks expressed in perioperative omental adipose tissue are correlated with weight loss from Roux-en-Y gastric bypass

CONTEXT

Gastric bypass surgery is the most commonly performed bariatric surgical procedure in the United States. Variable weight loss following this relatively standardized intervention has been reported. To date, a method for reliable profiling of patients who will successfully sustain weight loss for the long term has not been established. In addition, the mechanisms of action in accomplishing major weight loss as well as the explanation for the variable weight loss have not been established.

OBJECTIVE

To examine whether gene expression in perioperative omental adipose is associated with gastric bypass-induced weight loss.

DESIGN

Cross-sectional study of gene expression in perisurgical omental adipose tissues taken/available at the time of operation and total excess weight loss (EWL).

SUBJECTS

Fifteen overweight individuals who underwent Roux-en-Y gastric bypass (RYGB) surgery at the University of California Davis Medical Center (BMI: 40.6-72.8 kg/m(2)).

MEASUREMENTS

Body weight before and following weight stabilization 18-42 months after surgery. Perioperative omental adipose RNA isolated from 15 subjects was hybridized to Affymetrix HG-U133A chips for 22,283 transcript expression measurements.

RESULTS

Downstream analysis identified a set of genes whose expression was significantly correlated with RYGB-induced weight loss. The significant individual genes include acyl-coenzyme A oxidase 1 (ACOX1), phosphodiesterase 3A cGMP-inhibited (PDE3A) and protein kinase, AMP-activated, beta 1 non-catalytic subunit (PRKAB1). Specifically, ACOX1 plays a role in fatty acid metabolism. PDE3A is involved in purine metabolism and hormone-stimulated lipolysis. PRKAB1 is involved in adipocytokine signaling pathway. Gene network analysis revealed that pathways for glycerolipid metabolism, breast cancer and apoptosis were significantly correlated with long-term weight loss.

CONCLUSION

This study demonstrates that RNA expression profiles from perioperative adipose tissue are associated with weight loss outcome following RYGB surgery. Our data suggest that EWL could be predicted from preoperative samples, which would allow for informed decisions about whether or not to proceed to surgery.

Mapping the genetic architecture of gene expression in human liver

Genetic variants that are associated with common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in higher-order disease traits. Therefore, identifying the molecular phenotypes that vary in response to changes in DNA and that also associate with changes in disease traits has the potential to provide the functional information required to not only identify and validate the susceptibility genes that are directly affected by changes in DNA, but also to understand the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. Toward that end, we profiled more than 39,000 transcripts and we genotyped 782,476 unique single nucleotide polymorphisms (SNPs) in more than 400 human liver samples to characterize the genetic architecture of gene expression in the human liver, a metabolically active tissue that is important in a number of common human diseases, including obesity, diabetes, and atherosclerosis. This genome-wide association study of gene expression resulted in the detection of more than 6,000 associations between SNP genotypes and liver gene expression traits, where many of the corresponding genes identified have already been implicated in a number of human diseases. The utility of these data for elucidating the causes of common human diseases is demonstrated by integrating them with genotypic and expression data from other human and mouse populations. This provides much-needed functional support for the candidate susceptibility genes being identified at a growing number of genetic loci that have been identified as key drivers of disease from genome-wide association studies of disease. By using an integrative genomics approach, we highlight how the gene RPS26 and not ERBB3 is supported by our data as the most likely susceptibility gene for a novel type 1 diabetes locus recently identified in a large-scale, genome-wide association study. We also identify SORT1 and CELSR2 as candidate susceptibility genes for a locus recently associated with coronary artery disease and plasma low-density lipoprotein cholesterol levels in the process.

Genome-wide association studies seek to identify regions of the genome in which changes in DNA in a given population are correlated with disease, drug response, or other phenotypes of interest. However, changes in DNA that associate with traits like common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in the higher-order disease traits. Therefore, identifying molecular phenotypes that vary in response to changes in DNA that also associate with changes in disease traits can provide the functional information necessary to not only identify and validate the susceptibility genes directly affected by changes in DNA, but to understand as well the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. To enable this type of approach we profiled the expression levels of 39,280 transcripts and genotyped 782,476 SNPs in 427 human liver samples, identifying thousands of DNA variants that strongly associated with liver gene expression. These relationships were then leveraged by integrating them with genotypic and expression data from other human and mouse populations, leading to the direct identification of candidate susceptibility genes corresponding to genetic loci identified as key drivers of disease. Our analysis is able to provide much needed functional support for these candidate susceptibility genes.

Identifying changes in DNA that associate with changes in gene expression in human tissues elucidates the genetic architecture of gene expression in human populations and enables the direct identification of functionally supported candidate susceptibility genes in genomic regions associated with disease.

Effect of polymorphisms within probe-target sequences on olignonucleotide microarray experiments

Hybridization-based technologies, such as microarrays, rely on precise probe-target interactions to ensure specific and accurate measurement of RNA expression. Polymorphisms present in the probe–target sequences have been shown to alter probe- hybridization affinities, leading to reduced signal intensity measurements and resulting in false-positive results. Here, we characterize this effect on exon and gene expression estimates derived from the Affymetrix Exon Array. We conducted an association analysis between expression levels of probes, exons and transcripts and the genotypes of neighboring SNPs in 57 CEU HapMap individuals. We quantified the dependence of the effect of genotype on signal intensity with respect to the number of polymorphisms within target sequences, number of affected probes and position of the polymorphism within each probe. The effect of SNPs is quite severe and leads to considerable false-positive rates, particularly when the analysis is performed at the exon level and aimed at detecting alternative splicing events. Finally, we propose simple solutions, based on ‘masking’ probes, which are putatively affected by polymorphisms and show that such strategy results in a large decrease in false-positive rates, with a very modest reduction in coverage of the transcriptome.

Revealing the architecture of gene regulation: the promise of eQTL studies

Expression quantitative trait loci (eQTL) mapping studies have become a widely used tool for identifying genetic variants that affect gene regulation. In these studies, expression levels are viewed as quantitative traits, and gene expression phenotypes are mapped to particular genomic loci by combining studies of variation in gene expression patterns with genome-wide genotyping. Results from recent eQTL mapping studies have revealed substantial heritable variation in gene expression within and between populations. In many cases, genetic factors that influence gene expression levels can be mapped to proximal (putatively cis) eQTLs and, less often, to distal (putatively trans) eQTLs. Beyond providing great insight into the biology of gene regulation, a combination of eQTL studies with results from traditional linkage or association studies of human disease may help predict a specific regulatory role for polymorphic sites previously associated with disease.

Combining transcriptional profiling and genetic linkage analysis to uncover gene networks operating in hematopoietic stem cells and their progeny

Stem cells are unique in that they possess both the capacity to self-renew and thereby maintain their original pool as well as the capacity to differentiate into mature cells. In the past number of years, transcriptional profiling of enriched stem cell populations has been extensively performed in an attempt to identify a universal stem cell gene expression signature. While stem-cell-specific transcripts were identified in each case, this approach has thus far been insufficient to identify a universal group of core “stemness” genes ultimately responsible for self-renewal and multipotency. Similarly, in the hematopoietic system, comparisons of transcriptional profiles between different hematopoietic cell stages have had limited success in revealing core genes ultimately responsible for the initiation of differentiation and lineage specification. Here, we propose that the combined use of transcriptional profiling and genetic linkage analysis, an approach called “genetical genomics”, can be a valuable tool to assist in the identification of genes and gene networks that specify “stemness” and cell fate decisions. We review past studies of hematopoietic cells that utilized transcriptional profiling and/or genetic linkage analysis, and discuss several potential future applications of genetical genomics.