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Zheng, Z.

Publications and source records attributed to Zheng, Z..

6 recordsLinked to original sources

Repression of Transcription Factor AP-2 Alpha by Peroxisome Proliferator Activated Receptor Gamma Reveals a Novel Transcriptional Circuit in basal-squamous Bladder Cancer

The discovery of bladder cancer transcriptional subtypes provides an opportunity to identify high risk patients, and tailor disease management. Recent studies suggest tumor heterogeneity contributes to \"plasticity\" of molecular subtype during progression and following treatment. Nonetheless, the transcriptional drivers of the aggressive basal-squamous subtype remain unidentified. As PPAR{gamma} has been repeatedly implicated in the luminal subtype of bladder cancer, we hypothesized inactivation of this transcriptional master regulator during progression results in increased expression of basal-squamous specific transcription factors (TFs) which act to drive aggressive behavior. We initiated a pharmacologic and RNA-seq-based screen to identify PPAR{gamma}-repressed, basal-squamous specific TFs. Hierarchical clustering of RNA-seq data following treatment of a panel of human bladder cancer cell lines with a PPAR{gamma} agonist identified a number of TFs regulated by PPAR{gamma} activation, several of which are implicated in urothelial and squamous differentiation. One PPAR{gamma}-repressed TF implicated in squamous differentiation identified is Transcription Factor Activating Protein 2 alpha (TFAP2A). We show TFAP2A and its paralog TFAP2C are overexpressed in basal-squamous bladder cancer and in squamous areas of cystectomy samples, and that overexpression is associated with increased lymph node metastasis and distant recurrence, respectively. Biochemical analysis confirmed the ability of PPAR{gamma} activation to repress TFAP2A, while PPAR{gamma} antagonist studies indicate the requirement of a functional receptor. In vivo tissue recombination studies show TFAP2A and TFAP2C promote tumor growth in line with the aggressive nature of basal-squamous bladder cancer. Our findings suggest PPAR{gamma} inactivation, as well as TFAP2A and TFAP2C overexpression cooperate with other TFs to promote the basal-squamous transition.

cancer biology

Novel susceptibility loci and genetic regulation mechanisms for type 2 diabetes

We conducted a meta-analysis of genome-wide association studies (GWAS) with [~]16 million genotyped/imputed genetic variants in 62,892 type 2 diabetes (T2D) cases and 596,424 controls of European ancestry. We identified 139 common and 4 rare (minor allele frequency < 0.01) variants associated with T2D, 42 of which (39 common and 3 rare variants) were independent of the known variants. Integration of the gene expression data from blood (n = 14,115 and 2,765) and other T2D-relevant tissues (n = up to 385) with the GWAS results identified 33 putative functional genes for T2D, three of which were targeted by approved drugs. A further integration of DNA methylation (n = 1,980) and epigenomic annotations data highlighted three putative T2D genes (CAMK1D, TP53INP1 and ATP5G1) with plausible regulatory mechanisms whereby a genetic variant exerts an effect on T2D through epigenetic regulation of gene expression. We further found evidence that the T2D-associated loci have been under purifying selection.

genetics

Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

Understanding the difference in genetic regulation of gene expression between brain and blood is important for discovering genes associated with brain-related traits and disorders. Here, we estimate the correlation of genetic effects at the top associated cis-expression (cis-eQTLs or cis-mQTLs) between brain and blood for genes expressed (or CpG sites methylated) in both tissues, while accounting for errors in their estimated effects (rb). Using publicly available data (n = 72 to l,366), we find that the genetic effects of cis-eQTLs (PeQTL < 5x10-8) or mQTLs (PmQTL < 1x10-10) are highly correlated between independent brain and blood samples ([Formula] with SE = 0.015 for cis-eQTL and [Formula] with SE = 0.006 for cis-mQTLs). Using meta-analyzed brain eQTL/mQTL data (n = 526 to 1,194), we identify 61 genes and 167 DNA methylation (DNAm) sites associated with 4 brain-related traits and disorders. Most of these associations are a subset of the discoveries (97 genes and 295 DNAm sites) using data from blood with larger sample sizes (n = l,980 to 14,115). We further find that cis-eQTLs with tissue-specific effects are approximately uniformly distributed across all the functional annotation categories, and that mean difference in gene expression level between brain and blood is almost independent of the difference in the corresponding cis-eQTL effect. Our results demonstrate the gain of power in gene discovery for brain-related phenotypes using blood cis-eQTL or cis-mQTL data with large sample sizes.

genetics

Meta-analysis of genome-wide association studies for height and body mass index in ~700,000 individuals of European ancestry

Genome-wide association studies (GWAS) stand as powerful experimental designs for identifying DNA variants associated with complex traits and diseases. In the past decade, both the number of such studies and their sample sizes have increased dramatically. Recent GWAS of height and body mass index (BMI) in [~]250,000 European participants have led to the discovery of [~]700 and [~]100 nearly independent SNPs associated with these traits, respectively. Here we combine summary statistics from those two studies with GWAS of height and BMI performed in [~]450,000 UK Biobank participants of European ancestry. Overall, our combined GWAS meta-analysis reaches N[~]700,000 individuals and substantially increases the number of GWAS signals associated with these traits. We identified 3,290 and 716 near-independent SNPs associated with height and BMI, respectively (at a revised genome-wide significance threshold of p<1 x 10-8), including 1,185 height-associated SNPs and 554 BMI-associated SNPs located within loci not previously identified by these two GWAS. The genome-wide significant SNPs explain [~]24.6% of the variance of height and [~]5% of the variance of BMI in an independent sample from the Health and Retirement Study (HRS). Correlations between polygenic scores based upon these SNPs with actual height and BMI in HRS participants were 0.44 and 0.20, respectively. From analyses of integrating GWAS and eQTL data by Summary-data based Mendelian Randomization (SMR), we identified an enrichment of eQTLs amongst lead height and BMI signals, prioritisting 684 and 134 genes, respectively. Our study demonstrates that, as previously predicted, increasing GWAS sample sizes continues to deliver, by discovery of new loci, increasing prediction accuracy and providing additional data to achieve deeper insight into complex trait biology. All summary statistics are made available for follow up studies.

genetics

Causal associations between risk factors and common diseases inferred from GWAS summary data

Health risk factors such as body mass index (BMI), serum cholesterol and blood pressure are associated with many common diseases. It often remains unclear whether the risk factors are cause or consequence of disease, or whether the associations are the result of confounding. Genetic methods are useful to infer causality because genetic variants are present from birth and therefore unlikely to be confounded with environmental factors. We develop and apply a method (GSMR) that performs a multi-SNP Mendelian Randomization analysis using summary-level data from large genome-wide association studies (sample sizes of up to 405,072) to test the causal associations of BMI, waist-to-hip ratio, serum cholesterols, blood pressures, height and years of schooling (EduYears) with a range of common diseases. We identify a number of causal associations including a protective effect of LDL-cholesterol against type-2 diabetes (T2D) that might explain the side effects of statins on T2D, a protective effect of EduYears against Alzheimers disease, and bidirectional associations with opposite effects (e.g. higher BMI increases the risk of T2D but the effect T2D of BMI is negative). HDL-cholesterol has a significant risk effect on age-related macular degeneration, and the effect size remains significant accounting for the other risk factors. Our study develops powerful tools to integrate summary data from large studies to infer causality, and provides important candidates to be prioritized for further studies in medical research and for drug discovery.

genetics

A Complete Electron Microscopy Volume Of The Brain Of Adult Drosophila melanogaster

Drosophila melanogaster has a rich repertoire of innate and learned behaviors. Its 100,000-neuron brain is a large but tractable target for comprehensive neural circuit mapping. Only electron microscopy (EM) enables complete, unbiased mapping of synaptic connectivity; however, the fly brain is too large for conventional EM. We developed a custom high-throughput EM platform and imaged the entire brain of an adult female fly. We validated the dataset by tracing brain-spanning circuitry involving the mushroom body (MB), intensively studied for its role in learning. Here we describe the complete set of olfactory inputs to the MB; find a new cell type providing driving input to Kenyon cells (the intrinsic MB neurons); identify neurons postsynaptic to Kenyon cell dendrites; and find that axonal arbors providing input to the MB calyx are more tightly clustered than previously indicated by light-level data. This freely available EM dataset will significantly accelerate Drosophila neuroscience.\n\nHIGHLIGHTS- A complete adult fruit fly brain was imaged, using electron microscopy (EM)\n- The EM volume enables brain-spanning mapping of neuronal circuits at the synaptic level\n- Olfactory projection neurons cluster more tightly in mushroom body calyx than expected from light-level data\n- The primary postsynaptic targets of Kenyon cells (KCs) in the MB are other KCs, as well as the anterior paired lateral (APL) neuron\n- A newly discovered cell type, MB-CP2, integrates input from several sensory modalities and provides microglomerular input to KCs in MB calyx\n- A software pipeline was created in which EM-traced skeletons can be searched for within existing large-scale light microscopy (LM) databases of neuronal morphology, facilitating cell type identification and discovery of relevant genetic driver lines

neuroscience