1. |
- Locke, Adam E, et al.
(author)
-
Genetic studies of body mass index yield new insights for obesity biology.
- 2015
-
In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 518:7538, s. 197-401
-
Journal article (peer-reviewed)abstract
- Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
|
|
2. |
- Berndt, Sonja I., et al.
(author)
-
Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
- 2013
-
In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:5, s. 501-U69
-
Journal article (peer-reviewed)abstract
- Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
|
|
3. |
- Yang, Jian, et al.
(author)
-
FTO genotype is associated with phenotypic variability of body mass index
- 2012
-
In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 490:7419, s. 267-272
-
Journal article (peer-reviewed)abstract
- There is evidence across several species for genetic control of phenotypic variation of complex traits(1-4), such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using similar to 170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype)(5-7), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of similar to 0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI8, possibly mediated by DNA methylation(9,10). Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.
|
|
4. |
- DeNardo, David G., et al.
(author)
-
Leukocyte Complexity Predicts Breast Cancer Survival and Functionally Regulates Response to Chemotherapy
- 2011
-
In: Cancer Discovery. - 2159-8274. ; 1:1, s. 54-67
-
Journal article (peer-reviewed)abstract
- Immune-regulated pathways influence multiple aspects of cancer development. In this article we demonstrate that both macrophage abundance and T-cell abundance in breast cancer represent prognostic indicators for recurrence-free and overall survival. We provide evidence that response to chemotherapy is in part regulated by these leukocytes; cytotoxic therapies induce mammary epithelial cells to produce monocyte/macrophage recruitment factors, including colony stimulating factor 1 (CSF1) and interleukin-34, which together enhance CSF1 receptor (CSF1R)-dependent macrophage infiltration. Blockade of macrophage recruitment with CSF1R-signaling antagonists, in combination with paclitaxel, improved survival of mammary tumor-bearing mice by slowing primary tumor development and reducing pulmonary metastasis. These improved aspects of mammary carcinogenesis were accompanied by decreased vessel density and appearance of antitumor immune programs fostering tumor suppression in a CD8(+) T-cell-dependent manner. These data provide a rationale for targeting macrophage recruitment/response pathways, notably CSF1R, in combination with cytotoxic therapy, and identification of a breast cancer population likely to benefit from this novel therapeutic approach. SIGNIFICANCE: These findings reveal that response to chemotherapy is in part regulated by the tumor immune microenvironment and that common cytotoxic drugs induce neoplastic cells to produce monocyte/macrophage recruitment factors, which in turn enhance macrophage infiltration into mammary adenocarcinomas. Blockade of pathways mediating macrophage recruitment, in combination with chemotherapy, significantly decreases primary tumor progression, reduces metastasis, and improves survival by CD8(+) T-cell-dependent mechanisms, thus indicating that the immune microenvironment of tumors can be reprogrammed to instead foster antitumor immunity and improve response to cytotoxic therapy. Cancer Discovery; 1(1); 54-67. (C) 2011 AACR.
|
|
5. |
- Morris, Andrew P, et al.
(author)
-
Trans-ethnic kidney function association study reveals putative causal genes and effects on kidney-specific disease aetiologies
- 2019
-
In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1
-
Journal article (peer-reviewed)abstract
- Chronic kidney disease (CKD) affects ~10% of the global population, with considerable ethnic differences in prevalence and aetiology. We assemble genome-wide association studies of estimated glomerular filtration rate (eGFR), a measure of kidney function that defines CKD, in 312,468 individuals of diverse ancestry. We identify 127 distinct association signals with homogeneous effects on eGFR across ancestries and enrichment in genomic annotations including kidney-specific histone modifications. Fine-mapping reveals 40 high-confidence variants driving eGFR associations and highlights putative causal genes with cell-type specific expression in glomerulus, and in proximal and distal nephron. Mendelian randomisation supports causal effects of eGFR on overall and cause-specific CKD, kidney stone formation, diastolic blood pressure and hypertension. These results define novel molecular mechanisms and putative causal genes for eGFR, offering insight into clinical outcomes and routes to CKD treatment development.
|
|
6. |
- Mulrane, Laoighse, et al.
(author)
-
miR-187 Is an Independent Prognostic Factor in Breast Cancer and Confers Increased Invasive Potential In Vitro
- 2012
-
In: Clinical Cancer Research. - 1078-0432. ; 18:24, s. 6702-6713
-
Journal article (peer-reviewed)abstract
- Purpose: Here, we describe an integrated bioinformatics, functional analysis, and translational pathology approach to identify novel miRNAs involved in breast cancer progression. Experimental Design: Coinertia analysis (CIA) was used to combine a database of predicted miRNA target sites and gene expression data. Using two independent breast cancer cohorts, CIA was combined with correspondence analysis and between group analysis to produce a ranked list of miRNAs associated with disease progression. Ectopic expression studies were carried out in MCF7 cells and miRNA expression evaluated in two additional cohorts of patients with breast cancer by in situ hybridization on tissue microarrays. Results: CIA identified miR-187 as a key miRNA associated with poor outcome in breast cancer. Ectopic expression of miR-187 in breast cancer cells resulted in a more aggressive phenotype. In a test cohort (n = 117), high expression of miR-187 was associated with a trend toward reduced breast cancer-specific survival (BCSS; P = 0.058), and a significant association with reduced BCSS in lymph node-positive patients (P = 0.036). In a validation cohort (n = 470), high miR-187 was significantly associated with reduced BCSS in the entire cohort (P = 0.021) and in lymph node-positive patients (P = 0.012). Multivariate Cox regression analysis revealed that miR-187 is an independent prognostic factor in both cohorts [cohort 1: HR, 7.37; 95% confidence interval (CI), 2.05-26.51; P = 0.002; cohort 2: HR, 2.80; 95% CI, 1.52-5.16; P = 0.001] and in lymph node-positive patients in both cohorts (cohort 1: HR, 13.74; 95% CI, 2.62-72.03; P = 0.002; cohort 2: HR, 2.77; 95% CI, 1.32-5.81; P = 0.007). Conclusions: miR-187 expression in breast cancer leads to a more aggressive, invasive phenotype and acts as an independent predictor of outcome. Clin Cancer Res; 18(24); 6702-13. (C) 2012 AACR.
|
|
7. |
- Cruz, Rodrigo G.B., et al.
(author)
-
Human epidermal growth factor receptor-3 expression is regulated at transcriptional level in breast cancer settings by junctional adhesion molecule-a via a pathway involving beta-catenin and foxa1
- 2021
-
In: Cancers. - : MDPI AG. - 2072-6694. ; 13:4
-
Journal article (peer-reviewed)abstract
- The success of breast cancer therapies targeting the human epidermal growth factor receptor-2 (HER2) is limited by the development of drug resistance by mechanisms including upregulation of HER3. Having reported that HER2 expression and resistance to HER2-targeted therapies can be regulated by Junctional Adhesion Molecule-A (JAM-A), this study investigated if JAM-A regulates HER3 expression. Expressional alteration of JAM-A in breast cancer cells was used to test expressional effects on HER3 and its effectors, alongside associated functional behaviors, in vitro and semi-in vivo. HER3 transcription factors were identified and tested for regulation by JAM-A. Finally a patient tissue microarray was used to interrogate connections between putative pathway components connecting JAM-A and HER3. This study reveals for the first time that HER3 and its effectors are regulated at gene/protein expression level by JAM-A in breast cancer cell lines; with functional consequences in in vitro and semi-in vivo models. In bioinformatic, cellular and patient tissue models, this was associated with regulation of the HER3 transcription factor FOXA1 by JAM-A via a pathway involving β-catenin. Our data suggest a novel model whereby JAM-A expression regulates β-catenin localization, in turn regulating FOXA1 expression, which could drive HER3 gene transcription. JAM-A merits investigation as a novel target to prevent upregulation of HER3 during the development of resistance to HER2-targeted therapies, or to reduce HER3-dependent tumorigenic signaling.
|
|
8. |
- Lanigan, Fiona, et al.
(author)
-
Delineating Transcriptional Networks of Prognostic Gene Signatures Refines Treatment Recommendations for Lymph Node-negative Breast Cancer Patients.
- 2015
-
In: The FEBS Journal. - : Wiley. - 1742-464X. ; 282:18, s. 3455-3473
-
Journal article (peer-reviewed)abstract
- The majority of women diagnosed with lymph node-negative breast cancer are unnecessarily treated with damaging chemotherapeutics following surgical resection. This highlights the importance of understanding and more accurately predicting patient prognosis. Here, we define the transcriptional networks regulating well-established prognostic gene expression signatures. We find that the same set of transcriptional regulators consistently lie upstream of both 'prognosis' and 'proliferation' gene signatures, suggesting that a central transcriptional network underpins a shared phenotype within these signatures. Strikingly, the master transcriptional regulators within this network predict recurrence risk for lymph node-negative breast cancer better than currently used multi-gene prognostic assays, particularly in lymph node-negative, estrogen receptor-positive patients. Simultaneous examination of p16(INK) (4A ) expression, which predicts tumors that have bypassed cellular senescence, revealed that intermediate levels of p16(INK) (4A) correlate with an intact pRB pathway and improved survival. A combination of these master transcriptional regulators and p16(INK) (4A) , termed the OncoMasTR score, stratifies tumours based on their proliferative and senescence capacity, facilitating a clearer delineation of lymph node-negative breast cancer patients at high risk of recurrence, and thus requiring chemotherapy. Furthermore, OncoMasTR accurately classifies over 60% of patients as 'low risk', an improvement on existing prognostic assays, which has the potential to reduce overtreatment in early-stage patients. Taken together, this study provides new insights into the transcriptional regulation of cellular proliferation in breast cancer and provides an opportunity to enhance and streamline breast cancer prognosis. This article is protected by copyright. All rights reserved.
|
|
9. |
- Li, Bo, et al.
(author)
-
Therapeutic rationale to target highly expressed CDK7 conferring poor outcomes in triple-negative breast cancer
- 2017
-
In: Cancer Research. - 0008-5472. ; 77:14, s. 3834-3845
-
Journal article (peer-reviewed)abstract
- Triple-negative breast cancer (TNBC) patients commonly exhibit poor prognosis and high relapse after treatment, but there remains a lack of biomarkers and effective targeted therapies for this disease. Here, we report evidence highlighting the cell-cycle–related kinase CDK7 as a driver and candidate therapeutic target in TNBC. Using publicly available transcriptomic data from a collated set of TNBC patients (n ¼ 383) and the METABRIC TNBC dataset (n ¼ 217), we found CDK7 mRNA levels to be correlated with patient prognosis. High CDK7 protein expression was associated with poor prognosis within the RATHER TNBC cohort (n ¼ 109) and the METABRIC TNBC cohort (n ¼ 203). The highly specific CDK7 kinase inhibitors, BS-181 and THZ1, each downregulated CDK7-mediated phosphorylation of RNA polymerase II, indicative of transcriptional inhibition, with THZ1 exhibiting 500-fold greater potency than BS-181. Mechanistic investigations revealed that the survival of MDA-MB-231 TNBC cells relied heavily on the BCL-2/BCL-XL signaling axes in cells. Accordingly, we found that combining the BCL-2/BCL-XL inhibitors ABT-263/ABT199 with the CDK7 inhibitor THZ1 synergized in producing growth inhibition and apoptosis of human TNBC cells. Collectively, our results highlight elevated CDK7 expression as a candidate biomarker of poor prognosis in TNBC, and they offer a preclinical proof of concept for combining CDK7 and BCL-2/BCL-XL inhibitors as a mechanism-based therapeutic strategy to improve TNBC treatment.
|
|
10. |
- Madden, Stephen F., et al.
(author)
-
Detecting microRNA activity from gene expression data
- 2010
-
In: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 11
-
Journal article (peer-reviewed)abstract
- Background: MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. Results: Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. Conclusions: We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.
|
|