Duration of adenosine-induced myocardial hyperemia - Insights from quantitative 13N-ammonia positron emission tomography myocardial perfusion imaging

AIMS To assess the impact of adenosine on quantitative myocardial blood flow (MBF) in a rapid stress-rest protocol compared to a rest-stress protocol using 13N-ammonia positron emission tomography (PET) myocardial perfusion imaging (MPI) and to gain insights into the time dependency of such effects. METHODS AND RESULTS Quantitative MBF at rest (rMBF), during adenosine-induced stress (sMBF) and myocardial flow reserve (MFR) were obtained from 331 retrospectively identified patients who underwent 13N-ammonia PET-MPI for suspected chronic coronary syndrome and who all exhibited no perfusion defects. Of these, 146 (44.1%) underwent a rapid stress-rest protocol with a time interval (Δtstress-rest) of 20 ± 4 minutes between adenosine infusion offset and rest-imaging, as per clinical routine. The remaining 185 (55.9%) patients underwent a rest-stress protocol and served as the reference. Groups did not differ regarding demographics, risk factors, medication, left ventricular function, and calcium scores. rMBF was significantly higher in the stress-rest vs. the rest-stress group (0.80 [IQR 0.66-1.00] vs. 0.70 [0.58-0.83] ml·min-1·g-1, p < 0.001) and, as sMBF was identical between groups (2.52 [2.20-2.96] vs. 2.50 [1.96-3.11], p = 0.347), MFR was significantly lower in the stress-rest group (3.07 [2.43-3.88] vs. 3.50 [2.63-4.10], p < 0.001). There was a weak correlation between Δtstress-rest and rMBF (r = -0.259, p = 0.002) and between Δtstress-rest and MFR (r = 0.163, p = 0.049), and the proportion of patients with abnormally high rMBF was significantly decreasing with increasing Δtstress-rest. CONCLUSIONS Intravenously applied adenosine induces a long-lasting hyperemic effect on the myocardium. Consequently, rapid stress-rest protocols could lead to an overestimation of rMBF and an underestimation of MFR

High Resolution Discrimination of Clinical Mycobacterium tuberculosis Complex Strains Based on Single Nucleotide Polymorphisms

Recently, the diversity of the Mycobacterium tuberculosis complex (MTBC) population structure has been described in detail. Based on geographical separation and specific host pathogen co-evolution shaping MTBC virulence traits, at least 20 major lineages/genotypes have evolved finally leading to a clear influence of strain genetic background on transmissibility, clinical presentation/outcome, and resistance development. Therefore, high resolution genotyping for characterization of strains in larger studies is mandatory for understanding mechanisms of host-pathogen-interaction and to improve tuberculosis (TB) control. Single nucleotide polymorphisms (SNPs) represent the most reliable markers for lineage classification of clinical isolates due to the low levels of homoplasy, however their use is hampered either by low discriminatory power or by the need to analyze a large number of genes to achieve higher resolution. Therefore, we carried out de novo sequencing of 26 genes (approx. 20000 bp per strain) in a reference collection of MTBC strains including all major genotypes to define a highly discriminatory gene set. Overall, 161 polymorphisms were detected of which 59 are genotype-specific, while 13 define deeper branches such as the Euro-American lineage. Unbiased investigation of the most variable set of 11 genes in a population based strain collection (one year, city of Hamburg, Germany) confirmed the validity of SNP analysis as all strains were classified with high accuracy. Taken together, we defined a diagnostic algorithm which allows the identification of 17 MTBC phylogenetic lineages with high confidence for the first time by sequencing analysis of just five genes. In conclusion, the diagnostic algorithm developed in our study is likely to open the door for a low cost high resolution sequence/SNP based differentiation of the MTBC with a very high specificity. High throughput assays can be established which will be needed for large association studies that are mandatory for detailed investigation of host-pathogen-interaction during TB infection

Evidence that breast cancer risk at the 2q35 locus is mediated through IGFBP5 regulation.

GWAS have identified a breast cancer susceptibility locus on 2q35. Here we report the fine mapping of this locus using data from 101,943 subjects from 50 case-control studies. We genotype 276 SNPs using the 'iCOGS' genotyping array and impute genotypes for a further 1,284 using 1000 Genomes Project data. All but two, strongly correlated SNPs (rs4442975 G/T and rs6721996 G/A) are excluded as candidate causal variants at odds against &gt;100:1. The best functional candidate, rs4442975, is associated with oestrogen receptor positive (ER+) disease with an odds ratio (OR) in Europeans of 0.85 (95% confidence interval=0.84-0.87; P=1.7 × 10(-43)) per t-allele. This SNP flanks a transcriptional enhancer that physically interacts with the promoter of IGFBP5 (encoding insulin-like growth factor-binding protein 5) and displays allele-specific gene expression, FOXA1 binding and chromatin looping. Evidence suggests that the g-allele confers increased breast cancer susceptibility through relative downregulation of IGFBP5, a gene with known roles in breast cell biology

Fine-mapping of the HNF1B multicancer locus identifies candidate variants that mediate endometrial cancer risk.

Common variants in the hepatocyte nuclear factor 1 homeobox B (HNF1B) gene are associated with the risk of Type II diabetes and multiple cancers. Evidence to date indicates that cancer risk may be mediated via genetic or epigenetic effects on HNF1B gene expression. We previously found single-nucleotide polymorphisms (SNPs) at the HNF1B locus to be associated with endometrial cancer, and now report extensive fine-mapping and in silico and laboratory analyses of this locus. Analysis of 1184 genotyped and imputed SNPs in 6608 Caucasian cases and 37 925 controls, and 895 Asian cases and 1968 controls, revealed the best signal of association for SNP rs11263763 (P = 8.4 × 10(-14), odds ratio = 0.86, 95% confidence interval = 0.82-0.89), located within HNF1B intron 1. Haplotype analysis and conditional analyses provide no evidence of further independent endometrial cancer risk variants at this locus. SNP rs11263763 genotype was associated with HNF1B mRNA expression but not with HNF1B methylation in endometrial tumor samples from The Cancer Genome Atlas. Genetic analyses prioritized rs11263763 and four other SNPs in high-to-moderate linkage disequilibrium as the most likely causal SNPs. Three of these SNPs map to the extended HNF1B promoter based on chromatin marks extending from the minimal promoter region. Reporter assays demonstrated that this extended region reduces activity in combination with the minimal HNF1B promoter, and that the minor alleles of rs11263763 or rs8064454 are associated with decreased HNF1B promoter activity. Our findings provide evidence for a single signal associated with endometrial cancer risk at the HNF1B locus, and that risk is likely mediated via altered HNF1B gene expression

Germline polymorphisms in an enhancer of PSIP1 are associated with progression-free survival in epithelial ovarian cancer.

Women with epithelial ovarian cancer (EOC) are usually treated with platinum/taxane therapy after cytoreductive surgery but there is considerable inter-individual variation in response. To identify germline single-nucleotide polymorphisms (SNPs) that contribute to variations in individual responses to chemotherapy, we carried out a multi-phase genome-wide association study (GWAS) in 1,244 women diagnosed with serous EOC who were treated with the same first-line chemotherapy, carboplatin and paclitaxel. We identified two SNPs (rs7874043 and rs72700653) in TTC39B (best P=7x10-5, HR=1.90, for rs7874043) associated with progression-free survival (PFS). Functional analyses show that both SNPs lie in a putative regulatory element (PRE) that physically interacts with the promoters of PSIP1, CCDC171 and an alternative promoter of TTC39B. The C allele of rs7874043 is associated with poor PFS and showed increased binding of the Sp1 transcription factor, which is critical for chromatin interactions with PSIP1. Silencing of PSIP1 significantly impaired DNA damage-induced Rad51 nuclear foci and reduced cell viability in ovarian cancer lines. PSIP1 (PC4 and SFRS1 Interacting Protein 1) is known to protect cells from stress-induced apoptosis, and high expression is associated with poor PFS in EOC patients. We therefore suggest that the minor allele of rs7874043 confers poor PFS by increasing PSIP1 expression.This project has been supported by a grant from Cancer Australia. The Mayo Clinic GWAS was supported by R01CA114343 (Haplotype-based genome screen for ovarian cancer loci). The Ovarian Cancer Association Consortium is supported by a grant from the Ovarian Cancer Research Fund thanks to donations by the family and friends of Kathryn Sladek Smith. The AOCS was supported by the U.S. Army Medical Research and Materiel Command under DAMD17-01-1-0729, the National Health and Medical Research Council (NHMRC) of Australia (grants 400281, 400413), Cancer Council Victoria, Cancer Council Queensland, Cancer Council New South Wales, Cancer Council South Australia, The Cancer Foundation of Western Australia, and Cancer Council Tasmania. G. Chenevix-Trench is a Senior Principal Research fellow of the NHMRC. Y. Lu is funded by NHMRC grant 496675, S. MacGregor is supported by an NHMRC career development award, S. Edwards and J. French are supported by Fellowships from the National Breast Cancer Foundation (NBCF) Australia. The QIMR Berghofer groups were supported by NHMRC project grants (1051698 to SM and 1058415 to SLE and JDF) and a Weekend to End Women’s Cancer Research Grant (to SLE). A deFazio is funded by the University of Sydney Cancer Research Fund and A deFazio and PR Harnett are funded by the Cancer Institute NSW through the Sydney-West Translational Cancer Research Centre. B. Gao is supported by NHMRC and Cancer Institute NSW scholarship. KBM and MO’R are funded by CR-UK. The Bavarian study (BAV) was supported by ELAN Funds of the University of Erlangen-Nuremberg. HSK would like to thank Ira Schwaab for her tireless work on sample preparation. The Belgian study (BEL) was funded by Nationaal Kankerplan and we would like to thank Gilian Peuteman, Thomas Van Brussel and Dominiek Smeets for technical assistance. The Japanese study (JPN) was funded by a Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare. The International Collaborative Ovarian Neoplasm study (ICON)7 trial team would like to thank the Medical Research Council (MRC) Clinical Trial Unit (CTU) at the University of London (UCL), the ICON7 Translational Research Sub-group, and the University of Leeds for their work on the coordination of samples and data from the ICON7 trial. The LAX study (Women’s Cancer Program) was supported by the American Cancer Society Early Detection Professorship (120950-SIOP-06-258-06-COUN) and Entertainment Industry Foundation. Funding for MALOVA (MAL) was provided by research grant RO1 CA 61107 from the National Cancer Institute, Bethesda, MD; research grant 94 222 52 from the Danish Cancer Society, Copenhagen, Denmark; and the Mermaid I project. The Mayo Clinic study (MAYO) was supported by R01 CA122443, P50 CA136393. The Oregon study (ORE) was funded by the Sherie Hildreth Ovarian Cancer Research Fund and the OHSU Foundation. We would like to thank all members of Scottish Gynaecological Clinical Trials group and the SCOTROC1 investigators. SCOTROC1 (SRO) was funded by Cancer Research UK, and the SCOTROC biological studies were supported by Cancer Research UK (grant C536/A6689). RSH receives support from NIH/NIGMS grant K08GM089941, NIH/NCI grant R21 CA139278, NIH/NIGMS grant UO1GM61393, University of Chicago Cancer Center Support Grant (#P30 CA14599) and Breast Cancer SPORE Career Development Award.This is the final version of the article. It first appeared from Impact Journals via http://dx.doi.org/10.18632/oncotarget.704

Chromatin interactome mapping at 139 independent breast cancer risk signals

Funder: National Breast Cancer Foundation; doi: http://dx.doi.org/10.13039/501100001026Funder: University of Queensland; doi: http://dx.doi.org/10.13039/501100001794Abstract: Background: Genome-wide association studies have identified 196 high confidence independent signals associated with breast cancer susceptibility. Variants within these signals frequently fall in distal regulatory DNA elements that control gene expression. Results: We designed a Capture Hi-C array to enrich for chromatin interactions between the credible causal variants and target genes in six human mammary epithelial and breast cancer cell lines. We show that interacting regions are enriched for open chromatin, histone marks for active enhancers, and transcription factors relevant to breast biology. We exploit this comprehensive resource to identify candidate target genes at 139 independent breast cancer risk signals and explore the functional mechanism underlying altered risk at the 12q24 risk region. Conclusions: Our results demonstrate the power of combining genetics, computational genomics, and molecular studies to rationalize the identification of key variants and candidate target genes at breast cancer GWAS signals

Chromatin interactome mapping at 139 independent breast cancer risk signals

Funder: National Breast Cancer Foundation; doi: http://dx.doi.org/10.13039/501100001026Funder: University of Queensland; doi: http://dx.doi.org/10.13039/501100001794Abstract: Background: Genome-wide association studies have identified 196 high confidence independent signals associated with breast cancer susceptibility. Variants within these signals frequently fall in distal regulatory DNA elements that control gene expression. Results: We designed a Capture Hi-C array to enrich for chromatin interactions between the credible causal variants and target genes in six human mammary epithelial and breast cancer cell lines. We show that interacting regions are enriched for open chromatin, histone marks for active enhancers, and transcription factors relevant to breast biology. We exploit this comprehensive resource to identify candidate target genes at 139 independent breast cancer risk signals and explore the functional mechanism underlying altered risk at the 12q24 risk region. Conclusions: Our results demonstrate the power of combining genetics, computational genomics, and molecular studies to rationalize the identification of key variants and candidate target genes at breast cancer GWAS signals

Brain structural covariance networks in obsessive-compulsive disorder : a graph analysis from the ENIGMA Consortium

In the largest brain structural covariance study of OCD to date, Yun et al. show a less segregated organization of structural covariance networks and a reorganization of brain hubs, including cingulate and orbitofrontal regions, in OCD. The findings point to altered trajectories of brain development and maturation. Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z -score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions