Microvascular insulin resistance associates with enhanced muscle glucose disposal in CD36 deficiency

Dysfunction of endothelial insulin delivery to muscle associates with insulin resistance. CD36, a fatty acid transporter and modulator of insulin signaling is abundant in endothelial cells, especially in capillaries. Humans with inherited 50% reduction in CD36 expression have endothelial dysfunction but whether it is associated with insulin resistance is unclear. Using hyperinsulinemic/euglycemic clamps in Cd36-/- and wildtype mice, and in 50% CD36 deficient humans and matched controls we found that Cd36-/- mice have enhanced systemic glucose disposal despite unaltered transendothelial insulin transfer and reductions in microvascular perfusion and blood vessel compliance. Partially CD36 deficient humans also have better glucose disposal than controls with no capillary recruitment by insulin. CD36 knockdown in primary human-derived microvascular cells impairs insulin action on AKT, endothelial nitric oxide synthase, and nitric oxide release. Thus, insulin resistance of microvascular function in CD36 deficiency paradoxically associates with increased glucose utilization, likely through a remodeling of muscle gene expression.

The broad impact of cell death genes on the human disease phenome

Apoptotic, necroptotic, and pyroptotic cell death pathways are attractive and druggable targets for many human diseases, however the tissue specificity of these pathways and the relationship between these pathways and human disease is poorly characterized. Understanding the impact of modulating cell death gene expression on the human phenome could inform clinical investigation of cell death pathway-modulating therapeutics in human disorders by identifying novel trait associations and by detecting tissue-specific side effect profiles. We analyzed the expression profiles of an array of 44 cell death genes across somatic tissues in GTEx v8 and investigated the relationship between tissue-specific genetically determined expression of 44 cell death genes and the human phenome using summary statistics-based transcriptome wide association studies (TWAS) on human traits in the UK Biobank V3 (n ~500,000). We evaluated 513 traits encompassing ICD-10 defined diagnoses and hematologic traits (blood count labs). Our analysis revealed hundreds of significant (FDR<0.05) associations between cell death gene expression and diverse human phenotypes, which were independently validated in another large-scale biobank. Cell death genes were highly enriched for significant associations with blood traits versus non-cell-death genes, with apoptosis-associated genes enriched for leukocyte and platelet traits and necroptosis gene associations enriched for erythroid traits (e.g., Reticulocyte count, FDR=0.004). This suggests that immunogenic cell death pathways play an important role in regulating erythropoiesis and reinforces the paradigm that apoptosis pathway genes are critical for white blood cell and platelet development. Of functionally analogous genes, for instance pro-survival BCL2 family members, trait/direction-of-effect relationships were heterogeneous across blood traits. Overall, these results suggest that even functionally similar and/or orthologous cell death genes play distinct roles in their contribution to human phenotypes, and that cell death genes influence a diverse array of human traits.

Abstract 4582: Enrichment of colorectal cancer and inflammatory bowel disease risk variants in colon expression quantitative trait loci in African Americans

Background: Genome wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with diseases of the colon including colorectal cancer (CRC) and inflammatory bowel diseases (IBD). However, the functional role of many of these SNPs is largely unknown. Expression quantitative trait loci (eQTL) mapping is a tool to identify target genes of disease-associated SNPs. We have comprehensively assessed eQTLs in the human colon and tested for enrichment of GWAS-associated variants of colon diseases. We also characterized the genetic and functional properties of colonic eQTLs.

Methods: Distal colonic biopsies were obtained from 48 healthy African American males and total RNA was extracted. Genomic DNA was obtained from the same patients and genotyped using the Axiom Pan-African array. In total, 8.4 million genotyped and imputed SNPs were included. RNA expression levels were estimated using the Illumina HT-12v4 Expression Beadchip. eQTLs were identified using Matrix eQTL. False discovery rate calculations were performed according to the Benjamini and Hochberg method. Significance thresholds for other associations were determined using permutation-based methods.

Results: 1941 significant cis-eQTLs, corresponding to 122 independent signals, were identified at a false discovery rate of 0.01. There was substantial overlap between cis-eQTLs found in liver and ileum and less overlap in lymphoblastoid cells, brain, and skin fibroblasts. Overall, there was enrichment for GWAS variants associated with CRC and IBD, as well as 2 metabolic traits–Type 2 diabetes and body mass index–among colon cis-eQTLs. The CRC-associated eQTL rs3802842 was significantly associated with the expression of C11orf93 (COLCA2). The CRC-associated SNP rs1862748 is associated with 2 cis-eQTLs that are associated with expression differences in the NFATC3 gene, which regulates beta-catenin activation in response to WNT signaling. We also identified UBA7, INPP5E, ERAP2, SFMBT1, NXPE1, REXO2 as target genes for IBD-associated variants. There was significant enrichment of colonic cis-eQTLs near the transcription start sites (TSSs), for active histone marks and for SNPs with high population differentiation.

Conclusion: Through this comprehensive study of eQTLs in the human colon, we have identified novel and known target genes for IBD- and CRC-associated genetic variants. The cis-eQTLs are useful in identification of the causal functional variation underlying IBD and CRC associations. The eQTL catalog is now expanded to include the human colon and the functional characteristics of colonic eQTLs.

Note: This abstract was not presented at the meeting.

Citation Format: Sonia S. Kupfer, Imge Hulur, Eric Gamazon, Andrew Skol, Xavier Llor, Kenan Onel, Nathan A. Ellis. Enrichment of colorectal cancer and inflammatory bowel disease risk variants in colon expression quantitative trait loci in African Americans. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4582. doi:10.1158/1538-7445.AM2015-4582

Genetic association signal near NTN4 in Tourette syndrome

Tourette syndrome (TS) is a neurodevelopmental disorder with a complex genetic etiology. Through an international collaboration, we genotyped 42 single nucleotide polymorphisms (p < 10(-3) ) from the recent TS genomewide association study (GWAS) in 609 independent cases and 610 ancestry-matched controls. Only rs2060546 on chromosome 12q22 (p = 3.3 × 10(-4) ) remained significant after Bonferroni correction. Meta-analysis with the original GWAS yielded the strongest association to date (p = 5.8 × 10(-7) ). Although its functional significance is unclear, rs2060546 lies closest to NTN4, an axon guidance molecule expressed in developing striatum. Risk score analysis significantly predicted case-control status (p = 0.042), suggesting that many of these variants are true TS risk alleles.

A genome-wide association study of early-onset breast cancer identifies PFKM as a novel breast cancer gene and supports a common genetic spectrum for breast cancer at any age

Early-onset breast cancer (EOBC) causes substantial loss of life and productivity, creating a major burden among women worldwide. We analyzed 1,265,548 Hapmap3 single-nucleotide polymorphisms (SNP) among a discovery set of 3,523 EOBC incident cases and 2,702 population control women ages ≤ 51 years. The SNPs with smallest P values were examined in a replication set of 3,470 EOBC cases and 5,475 control women. We also tested EOBC association with 19,684 genes by annotating each gene with putative functional SNPs, and then combining their P values to obtain a gene-based P value. We examined the gene with smallest P value for replication in 1,145 breast cancer cases and 1,142 control women. The combined discovery and replication sets identified 72 new SNPs associated with EOBC (P < 4 × 10(-8)) located in six genomic regions previously reported to contain SNPs associated largely with later-onset breast cancer (LOBC). SNP rs2229882 and 10 other SNPs on chromosome 5q11.2 remained associated (P < 6 × 10(-4)) after adjustment for the strongest published SNPs in the region. Thirty-two of the 82 currently known LOBC SNPs were associated with EOBC (P < 0.05). Low power is likely responsible for the remaining 50 unassociated known LOBC SNPs. The gene-based analysis identified an association between breast cancer and the phosphofructokinase-muscle (PFKM) gene on chromosome 12q13.11 that met the genome-wide gene-based threshold of 2.5 × 10(-6). In conclusion, EOBC and LOBC seem to have similar genetic etiologies; the 5q11.2 region may contain multiple distinct breast cancer loci; and the PFKM gene region is worthy of further investigation. These findings should enhance our understanding of the etiology of breast cancer.

Abstract PL07-02: Whole genome approaches to identify pharmacogenomic markers of anticancer agents

Preclinical and clinical genome-wide association studies (GWAS) in oncology provide an unprecedented opportunity for a comprehensive and unbiased assessment of the heritable factors associated with drug response. For chemotherapeutic drugs, there are many challenges with performing a clinical GWAS, including staggering costs because a homogenous population of patients treated with the same dosage regimen and minimal confounding variables is required. To get around these issues, we have developed preclinical cell-based models as a pharmacogenomic discovery tool but also a means to replicate or validate findings from clinical GWAS. Our model utilizes HapMap lymphoblastoid cell lines (LCLs) derived from individuals within different world populations (Caucasian, African, Asian, African American) that are evaluated for drug sensitivity to chemotherapeutic agents (platinating agents, antimetabolites, cyclophosphamide, paclitaxel). Evaluation of inter-ethnic differences revealed that LCLs from Africans tend to be more sensitive to antimetabolites and less sensitive to platinating agents than Caucasian derived LCLs. These LCLs are rich in genetic data as many are part of the International HapMap and the more recent 1000 Genome project. We utilized this data to identify disproportionately more expression quantitative trait loci (eQTLs, indicating that a SNP genotype is associated with the transcript abundance level of a gene) associated with pharmacologic traits than expected by chance based on minor allele frequency. We are attempting to unravel the functional consequence of top pharmacologic GWAS SNPs with local and distant regulatory roles in cellular resistance to chemotherapeutic agents. For example, we discovered a SNP (master regulator) that is local to PRPF39 and distant to more than 100 genes that is associated with cisplatin-induced cytotoxicity in LCLs derived from African populations. Our cell-based model provides potential targets for therapeutic intervention and provides us with a greater understanding of the genetic contribution to interethnic variation in chemotherapeutic sensitivity.

Citation Information: Cancer Epidemiol Biomarkers Prev 2011;20(10 Suppl):PL07-02.

Abstract 2761: Germline polymorphism discovered via a cell-based genome-wide approach predicts platinum response in ovarian and head and neck cancers

Identifying patients prior to treatment that are less likely to benefit from or most likely to experience adverse events from chemotherapeutic agents is essential. Even though humans are the most relevant system, pharmacogenomic discovery in the field of oncology is plagued by difficulties in executing large clinical trials and confounding factors such as co-morbidities, dosage, and concomitant medications. Therefore, we developed a genome-wide cell-based approach evaluating single nucleotide polymorphisms (SNPs) and gene expression to predict chemotherapy-induced response and toxicity and then validated our findings in clinically relevant patient cohorts. Our model utilizes the International HapMap lymphoblastoid cell lines (LCLs). Genome-wide association studies were performed to identify SNPs significantly associated with carboplatin sensitivity through their effects on mRNA expression. The significant findings were evaluated in an independent LCL replication set and in patient samples obtained from the Australian Ovarian Cancer Study (AOCS) and two Phase II head and neck clinical trials (UC12019 and UC13881) conducted at the University of Chicago. Four hundred and nine ovarian cancer patients receiving carboplatin and paclitaxel were analyzed in AOCS; while 60 and 32 head and neck cancer patients were evaluated in UC12019 and UC13881 trials. Carboplatin was used as induction and concomitant chemo-radiation therapy in UC12019 and UC13881 trials, respectively. Using LCLs, our genome-wide model identified 65 SNPs that are associated with at least one carboplatin sensitivity phenotype through the expression of 61 genes. Five of them were replicated in a separate set of LCLs. In AOCS, SNP (rs1649942) was significantly associated with progression-free survival (Plog-rank=0.009) and overall survival (Plog-rank=0.03). In the head and neck cancer trials, 2 other SNP-phenotype associations were identified and replicated in both trials, including the association between SNP (rs4946514) and overall response to carboplatin, and the association between SNP (rs7134205) and post treatment platelet changes. Given the obstacles to performing large, replicable pharmacogenomic studies in patients, the cell-based model is proven to be an effective alternative in novel pharmaco-SNP discovery. We demonstrate germline SNPs identified through the cell-based genome-wide approach are clinically important predictors of chemotherapy response and toxicity.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2761.

Trait-associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GWAS

Although genome-wide association studies (GWAS) of complex traits have yielded more reproducible associations than had been discovered using any other approach, the loci characterized to date do not account for much of the heritability to such traits and, in general, have not led to improved understanding of the biology underlying complex phenotypes. Using a web site we developed to serve results of expression quantitative trait locus (eQTL) studies in lymphoblastoid cell lines from HapMap samples (http://www.scandb.org), we show that single nucleotide polymorphisms (SNPs) associated with complex traits (from http://www.genome.gov/gwastudies/) are significantly more likely to be eQTLs than minor-allele-frequency–matched SNPs chosen from high-throughput GWAS platforms. These findings are robust across a range of thresholds for establishing eQTLs (p-values from 10⁻⁴–10⁻⁸), and a broad spectrum of human complex traits. Analyses of GWAS data from the Wellcome Trust studies confirm that annotating SNPs with a score reflecting the strength of the evidence that the SNP is an eQTL can improve the ability to discover true associations and clarify the nature of the mechanism driving the associations. Our results showing that trait-associated SNPs are more likely to be eQTLs and that application of this information can enhance discovery of trait-associated SNPs for complex phenotypes raise the possibility that we can utilize this information both to increase the heritability explained by identifiable genetic factors and to gain a better understanding of the biology underlying complex traits.

We show here that single nucleotide polymorphisms (SNPs) associated with complex traits (as identified in the catalog of results from genome-wide association studies http://www.genome.gov/gwastudies/) are more likely than other SNPs chosen from high-throughput genotyping platforms to predict expression levels of genes. These observations confirm that genetic risk factors for complex traits will often affect phenotype by altering the amount or timing of protein production, rather than by changing the type of protein produced. This knowledge can be used to improve our ability to discover genetic risk factors for complex traits and to improve our understanding of their underlying biology.

Biomolecular Systems of Disease Buried Across Multiple GWAS Unveiled by Information Theory and Ontology

A key challenge for genome-wide association studies (GWAS) is to understand how single nucleotide polymorphisms (SNPs) mechanistically underpin complex diseases. While this challenge has been addressed partially by Gene Ontology (GO) enrichment of large list of host genes of SNPs prioritized in GWAS, these enrichment have not been formally evaluated. Here, we develop a novel computational approach anchored in information theoretic similarity, by systematically mining lists of host genes of SNPs prioritized in three adult-onset diabetes mellitus GWAS. The "gold-standard" is based on GO associated with 20 published diabetes SNPs' host genes and on our own evaluation. We computationally identify 69 similarity-predicted GO independently validated in all three GWAS (FDR<5%), enriched with those of the gold-standard (odds ratio=5.89, P=4.81e-05), and these terms can be organized by similarity criteria into 11 groupings termed "biomolecular systems". Six biomolecular systems were corroborated by the gold-standard and the remaining five were previously uncharacterized. http://lussierlab.org/publications/ITS-GWAS.