Junwen Wang

A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer

We conducted a genome-wide association study (GWAS) of breast cancer by genotyping 528,173 SNPs in 1,145 postmenopausal women of European ancestry with invasive breast cancer and 1,142 controls. We identified four SNPs in intron 2 of FGFR2 (which encodes a receptor tyrosine kinase and is amplified or overexpressed in some breast cancers) that were highly associated with breast cancer and confirmed this association in 1,776 affected individuals and 2,072 controls from three additional studies. Across the four studies, the association with all four SNPs was highly statistically significant (Ptrend for the most strongly associated SNP (rs1219648) = 1.1 × 10−10; population attributable risk = 16%). Four SNPs at other loci most strongly associated with breast cancer in the initial GWAS were not associated in the replication studies. Our summary results from the GWAS are available online in a form that should speed the identification of additional risk loci.

The support of human genetic evidence for approved drug indications

Over a quarter of drugs that enter clinical development fail because they are ineffective. Growing insight into genes that influence human disease may affect how drug targets and indications are selected. However, there is little guidance about how much weight should be given to genetic evidence in making these key decisions. To answer this question, we investigated how well the current archive of genetic evidence predicts drug mechanisms. We found that, among well-studied indications, the proportion of drug mechanisms with direct genetic support increases significantly across the drug development pipeline, from 2.0% at the preclinical stage to 8.2% among mechanisms for approved drugs, and varies dramatically among disease areas. We estimate that selecting genetically supported targets could double the success rate in clinical development. Therefore, using the growing wealth of human genetic data to select the best targets and indications should have a measurable impact on the successful development of new drugs.

Transcriptional Genomics Associates FOX Transcription Factors With Human Heart Failure

Background— Specific transcription factors (TFs) modulate cardiac gene expression in murine models of heart failure, but their relevance in human subjects remains untested. We developed and applied a computational approach called transcriptional genomics to test the hypothesis that a discrete set of cardiac TFs is associated with human heart failure. Methods and Results— RNA isolates from failing (n=196) and nonfailing (n=16) human hearts were hybridized with Affymetrix HU133A arrays, and differentially expressed heart failure genes were determined. TF binding sites overrepresented in the −5-kb promoter sequences of these heart failure genes were then determined with the use of public genome sequence databases. Binding sites for TFs identified in murine heart failure models (MEF2, NKX, NF-AT, and GATA) were significantly overrepresented in promoters of human heart failure genes (P<0.002; false discovery rate 2% to 4%). In addition, binding sites for FOX TFs showed substantial overrepresentation in both advanced human and early murine heart failure (P<0.002 and false discovery rate <4% for each). A role for FOX TFs was supported further by expression of FOXC1, C2, P1, P4, and O1A in failing human cardiac myocytes at levels similar to established hypertrophic TFs and by abundant FOXP1 protein in failing human cardiac myocyte nuclei. Conclusions— Our results provide the first evidence that specific TFs identified in murine models (MEF2, NKX, NFAT, and GATA) are associated with human heart failure. Moreover, these data implicate specific members of the FOX family of TFs (FOXC1, C2, P1, P4, and O1A) not previously suggested in heart failure pathogenesis. These findings provide a crucial link between animal models and human disease and suggest a specific role for FOX signaling in modulating the hypertrophic response of the heart to stress in humans.

GWASdb: a database for human genetic variants identified by genome-wide association studies

Recent advances in genome-wide association studies (GWAS) have enabled us to identify thousands of genetic variants (GVs) that are associated with human diseases. As next-generation sequencing technologies become less expensive, more GVs will be discovered in the near future. Existing databases, such as NHGRI GWAS Catalog, collect GVs with only genome-wide level significance. However, many true disease susceptibility loci have relatively moderate P values and are not included in these databases. We have developed GWASdb that contains 20 times more data than the GWAS Catalog and includes less significant GVs (P < 1.0 × 10−3) manually curated from the literature. In addition, GWASdb provides comprehensive functional annotations for each GV, including genomic mapping information, regulatory effects (transcription factor binding sites, microRNA target sites and splicing sites), amino acid substitutions, evolution, gene expression and disease associations. Furthermore, GWASdb classifies these GVs according to diseases using Disease-Ontology Lite and Human Phenotype Ontology. It can conduct pathway enrichment and PPI network association analysis for these diseases. GWASdb provides an intuitive, multifunctional database for biologists and clinicians to explore GVs and their functional inferences. It is freely available at http://jjwanglab.org/gwasdb and will be updated frequently.

GWAS3D: detecting human regulatory variants by integrative analysis of genome-wide associations, chromosome interactions and histone modifications

Interpreting the genetic variants located in the regulatory regions, such as enhancers and promoters, is an indispensable step to understand molecular mechanism of complex traits. Recent studies show that genetic variants detected by genome-wide association study (GWAS) are significantly enriched in the regulatory regions. Therefore, detecting, annotating and prioritizing of genetic variants affecting gene regulation are critical to our understanding of genotype–phenotype relationships. Here, we developed a web server GWAS3D to systematically analyze the genetic variants that could affect regulatory elements, by integrating annotations from cell type-specific chromatin states, epigenetic modifications, sequence motifs and cross-species conservation. The regulatory elements are inferred from the genome-wide chromosome interaction data, chromatin marks in 16 different cell types and 73 regulatory factors motifs from the Encyclopedia of DNA Element project. Furthermore, we used these function elements, as well as risk haplotype, binding affinity, conservation and P-values reported from the original GWAS to reprioritize the genetic variants. Using studies from low-density lipoprotein cholesterol, we demonstrated that our reprioritizing approach was effective and cell type specific. In conclusion, GWAS3D provides a comprehensive annotation and visualization tool to help users interpreting their results. The web server is freely available at http://jjwanglab.org/gwas3d.

Next generation sequencing has lower sequence coverage and poorer SNP-detection capability in the regulatory regions

The rapid development of next generation sequencing (NGS) technology provides a new chance to extend the scale and resolution of genomic research. How to efficiently map millions of short reads to the reference genome and how to make accurate SNP calls are two major challenges in taking full advantage of NGS. In this article, we reviewed the current software tools for mapping and SNP calling, and evaluated their performance on samples from The Cancer Genome Atlas (TCGA) project. We found that BWA and Bowtie are better than the other alignment tools in comprehensive performance for Illumina platform, while NovoalignCS showed the best overall performance for SOLiD. Furthermore, we showed that next-generation sequencing platform has significantly lower coverage and poorer SNP-calling performance in the CpG islands, promoter and 5′-UTR regions of the genome. NGS experiments targeting for these regions should have higher sequencing depth than the normal genomic region.

Hyperglycemia-Induced Protein Kinase C β2 Activation Induces Diastolic Cardiac Dysfunction in Diabetic Rats by Impairing Caveolin-3 Expression and Akt/eNOS Signaling

Protein kinase C (PKC)β2 is preferably overexpressed in the diabetic myocardium, which induces cardiomyocyte hypertrophy and contributes to diabetic cardiomyopathy, but the underlying mechanisms are incompletely understood. Caveolae are critical in signal transduction of PKC isoforms in cardiomyocytes. Caveolin (Cav)-3, the cardiomyocyte-specific caveolar structural protein isoform, is decreased in the diabetic heart. The current study determined whether PKCβ2 activation affects caveolae and Cav-3 expression. Immunoprecipitation and immunofluorescence analysis revealed that high glucose (HG) increased the association and colocalization of PKCβ2 and Cav-3 in isolated cardiomyocytes. Disruption of caveolae by methyl-β-cyclodextrin or Cav-3 small interfering (si)RNA transfection prevented HG-induced PKCβ2 phosphorylation. Inhibition of PKCβ2 activation by compound CGP53353 or knockdown of PKCβ2 expression via siRNA attenuated the reductions of Cav-3 expression and Akt/endothelial nitric oxide synthase (eNOS) phosphorylation in cardiomyocytes exposed to HG. LY333531 treatment (for a duration of 4 weeks) prevented excessive PKCβ2 activation and attenuated cardiac diastolic dysfunction in rats with streptozotocin-induced diabetes. LY333531 suppressed the decreased expression of myocardial NO, Cav-3, phosphorylated (p)-Akt, and p-eNOS and also mitigated the augmentation of O2−, nitrotyrosine, Cav-1, and iNOS expression. In conclusion, hyperglycemia-induced PKCβ2 activation requires caveolae and is associated with reduced Cav-3 expression in the diabetic heart. Prevention of excessive PKCβ2 activation attenuated cardiac diastolic dysfunction by restoring Cav-3 expression and subsequently rescuing Akt/eNOS/NO signaling.

Position and distance specificity are important determinants of cis-regulatory motifs in addition to evolutionary conservation

Computational discovery of cis-regulatory elements remains challenging. To cope with the high false positives, evolutionary conservation is routinely used. However, conservation is only one of the attributes of cis-regulatory elements and is neither necessary nor sufficient. Here, we assess two additional attributes—positional and inter-motif distance specificity—that are critical for interactions between transcription factors. We first show that for a greater than expected fraction of known motifs, the genes that contain the motifs in their promoters in a position-specific or distance-specific manner are related, both in function and/or in expression pattern. We then use the position and distance specificity to discover novel motifs. Our work highlights the importance of distance and position specificity, in addition to the evolutionary conservation, in discovering cis-regulatory motifs.

GWASdb v2: an update database for human genetic variants identified by genome-wide association studies

Genome-wide association studies (GWASs), now as a routine approach to study single-nucleotide polymorphism (SNP)-trait association, have uncovered over ten thousand significant trait/disease associated SNPs (TASs). Here, we updated GWASdb (GWASdb v2, http://jjwanglab.org/gwasdb) which provides comprehensive data curation and knowledge integration for GWAS TASs. These updates include: (i) Up to August 2015, we collected 2479 unique publications from PubMed and other resources; (ii) We further curated moderate SNP-trait associations (P-value < 1.0×10−3) from each original publication, and generated a total of 252 530 unique TASs in all GWASdb v2 collected studies; (iii) We manually mapped 1610 GWAS traits to 501 Human Phenotype Ontology (HPO) terms, 435 Disease Ontology (DO) terms and 228 Disease Ontology Lite (DOLite) terms. For each ontology term, we also predicted the putative causal genes; (iv) We curated the detailed sub-populations and related sample size for each study; (v) Importantly, we performed extensive function annotation for each TAS by incorporating gene-based information, ENCODE ChIP-seq assays, eQTL, population haplotype, functional prediction across multiple biological domains, evolutionary signals and disease-related annotation; (vi) Additionally, we compiled a SNP-drug response association dataset for 650 pharmacogenetic studies involving 257 drugs in this update; (vii) Last, we improved the user interface of website.

N-Acetylcysteine and allopurinol up-regulated the Jak/STAT3 and PI3K/Akt pathways via adiponectin and attenuated myocardial postischemic injury in diabetes

N-Acetylcysteine (NAC) and allopurinol (ALP) synergistically reduce myocardial ischemia reperfusion (MI/R) injury in diabetes. However, the mechanism is unclear. We postulated that NAC and ALP attenuated diabetic MI/R injury by up-regulating phosphatidylinositol 3-kinase/Akt (PI3K/Akt) and Janus kinase 2/signal transducer and activator of transcription-3 (JAK2/STAT3) pathways subsequent to adiponectin (APN) activation. Control (C) or streptozotocin-induced diabetic rats (D) were untreated or treated with NAC and ALP followed by MI/R. D rats displayed larger infarct size accompanied by decreased phosphorylation of Akt, STAT3 and decreased cardiac nitric oxide (NO) and APN levels. NAC and ALP decreased MI/R injury in D rats, enhanced phosphorylation of Akt and STAT3, and increased NO and APN. High glucose and hypoxia/reoxygenation exposure induced cell death and Akt and STAT3 inactivation in cultured cardiomyocytes, which were prevented by NAC and ALP. The PI3K inhibitor wortmannin and Jak2 inhibitor AG490 abolished the protection of NAC and ALP. Similarly, APN restored posthypoxic Akt and STAT3 activation and decreased cell death in cardiomyocytes. Gene silencing with AdipoR2 siRNA or STAT3 siRNA but not AdipoR1 siRNA abolished the protection of NAC and ALP. In conclusion, NAC and ALP prevented diabetic MI/R injury through PI3K/Akt and Jak2/STAT3 and cardiac APN may serve as a mediator via AdipoR2 in this process.