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The heterogenous aetiology of Parkinson's disease is increasingly recognized; both mitochondrial and lysosomal dysfunction have been implicated. Powerful, clinically applicable tools are required to enable mechanistic stratification for future precision medicine approaches. The aim of this study was to characterize bioenergetic dysfunction in Parkinson's disease by applying a multimodal approach, combining standardized clinical assessment with midbrain and putaminal 31-phosphorus magnetic resonance spectroscopy (31P-MRS) and deep phenotyping of mitochondrial and lysosomal function in peripheral tissue in patients with recent-onset Parkinson's disease and control subjects. Sixty participants (35 patients with Parkinson's disease and 25 healthy controls) underwent 31P-MRS for quantification of energy-rich metabolites [ATP, inorganic phosphate (Pi) and phosphocreatine] in putamen and midbrain. In parallel, skin biopsies were obtained from all research participants to establish fibroblast cell lines for subsequent quantification of total intracellular ATP and mitochondrial membrane potential (MMP) as well as mitochondrial and lysosomal morphology, using high content live cell imaging. Lower MMP correlated with higher intracellular ATP (r = −0.55, P = 0.0016), higher mitochondrial counts (r = −0.72, P < 0.0001) and higher lysosomal counts (r = −0.62, P = 0.0002) in Parkinson's disease patient-derived fibroblasts only, consistent with impaired mitophagy and mitochondrial uncoupling. 31P-MRS-derived posterior putaminal Pi/ATP ratio variance was considerably greater in Parkinson's disease than in healthy controls (F-tests, P = 0.0036). Furthermore, elevated 31P-MRS-derived putaminal, but not midbrain Pi/ATP ratios (indicative of impaired oxidative phosphorylation) correlated with both greater mitochondrial (r = 0.37, P = 0.0319) and lysosomal counts (r = 0.48, P = 0.0044) as well as lower MMP in both short (r = −0.52, P = 0.0016) and long (r = −0.47, P = 0.0052) mitochondria in Parkinson's disease. Higher 31P-MRS midbrain phosphocreatine correlated with greater risk of rapid disease progression (r = 0.47, P = 0.0384). Our data suggest that impaired oxidative phosphorylation in the striatal dopaminergic nerve terminals exceeds mitochondrial dysfunction in the midbrain of patients with early Parkinson's disease. Our data further support the hypothesis of a prominent link between impaired mitophagy and impaired striatal energy homeostasis as a key event in early Parkinson's disease. [ABSTRACT FROM AUTHOR]

Background: Rescue of mitochondrial function is a promising neuroprotective strategy for Parkinson's disease (PD). Ursodeoxycholic acid (UDCA) has shown considerable promise as a mitochondrial rescue agent across a range of preclinical in vitro and in vivo models of PD. Objectives: To investigate the safety and tolerability of high‐dose UDCA in PD and determine midbrain target engagement. Methods: The UP (UDCA in PD) study was a phase II, randomized, double‐blind, placebo‐controlled trial of UDCA (30 mg/kg daily, 2:1 randomization UDCA vs. placebo) in 30 participants with PD for 48 weeks. The primary outcome was safety and tolerability. Secondary outcomes included 31‐phosphorus magnetic resonance spectroscopy (31P‐MRS) to explore target engagement of UDCA in PD midbrain and assessment of motor progression, applying both the Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III (MDS‐UPDRS‐III) and objective, motion sensor‐based quantification of gait impairment. Results: UDCA was safe and well tolerated, and only mild transient gastrointestinal adverse events were more frequent in the UDCA treatment group. Midbrain 31P‐MRS demonstrated an increase in both Gibbs free energy and inorganic phosphate levels in the UDCA treatment group compared to placebo, reflecting improved ATP hydrolysis. Sensor‐based gait analysis indicated a possible improvement of cadence (steps per minute) and other gait parameters in the UDCA group compared to placebo. In contrast, subjective assessment applying the MDS‐UPDRS‐III failed to detect a difference between treatment groups. Conclusions: High‐dose UDCA is safe and well tolerated in early PD. Larger trials are needed to further evaluate the disease‐modifying effect of UDCA in PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Oestrogen receptor-α (ER) is the defining and driving transcription factor in the majority of breast cancers and its target genes dictate cell growth and endocrine response, yet genomic understanding of ER function has been restricted to model systems (1-3). Here we map genome-wide ER-binding events, by chromatin immunoprecipitation followed by high-throughput sequencing (ChlP-seq), in primary breast cancers from patients with different clinical outcomes and in distant ER-positive metastases. We find that drug-resistant cancers still recruit ER to the chromatin, but that ER binding is a dynamic process, with the acquisition of unique ER-binding regions in tumours from patients that are likely to relapse. The acquired ER regulatory regions associated with poor clinical outcome observed in primary tumours reveal gene signatures that predict clinical outcome in ER-positive disease exclusively. We find that the differential ER-binding programme observed in tumours from patients with poor outcome is not due to the selection of a rare subpopulation of cells, but is due to the FOXA1-mediated reprogramming of ER binding on a rapid timescale. The parallel redistribution of ER and FOXA1 binding events in drug-resistant cellular contexts is supported by histological co-expression of ER and FOXA1 in metastatic samples. By establishing transcription-factor mapping in primary tumour material, we show that there is plasticity in ER-binding capacity, with distinct combinations of cis-regulatory elements linked with the different clinical outcomes., Recent technological advances have allowed mapping of ER-binding events, with the goal of discovering the cis-regulatory elements and factors involved in mediating ER binding and transcription. Several genome-wide maps of [...]

Abstract Background The demands of microarray expression technologies for quantities of RNA place a limit on the questions they can address. As a consequence, the RNA requirements have reduced over time as technologies have improved. In this paper we investigate the costs of reducing the starting quantity of RNA for the Illumina BeadArray platform. This we do via a dilution data set generated from two reference RNA sources that have become the standard for investigations into microarray and sequencing technologies. Results We find that the starting quantity of RNA has an effect on observed intensities despite the fact that the quantity of cRNA being hybridized remains constant. We see a loss of sensitivity when using lower quantities of RNA, but no great rise in the false positive rate. Even with 10 ng of starting RNA, the positive results are reliable although many differentially expressed genes are missed. We see that there is some scope for combining data from samples that have contributed differing quantities of RNA, but note also that sample sizes should increase to compensate for the loss of signal-to-noise when using low quantities of starting RNA. Conclusions The BeadArray platform maintains a low false discovery rate even when small amounts of starting RNA are used. In contrast, the sensitivity of the platform drops off noticeably over the same range. Thus, those conducting experiments should not opt for low quantities of starting RNA without consideration of the costs of doing so. The implications for experimental design, and the integration of data from different starting quantities, are complex.

Abstract Background A key stage for all microarray analyses is the extraction of feature-intensities from an image. If this step goes wrong, then subsequent preprocessing and processing stages will stand little chance of rectifying the matter. Illumina employ random construction of their BeadArrays, making feature-intensity extraction even more important for the Illumina platform than for other technologies. In this paper we show that using raw Illumina data it is possible to identify, control, and perhaps correct for a range of spatial-related phenomena that affect feature-intensity extraction. Results We note that feature intensities can be unnaturally high when in the proximity of a number of phenomena relating either to the images themselves or to the layout of the beads on an array. Additionally we note that beads neighbour beads of the same type more often than one might expect, which may cause concern in some models of hybridization. We highlight issues in the identification of a bead's location, and in particular how this both affects and is affected by its intensity. Finally we show that beads can be wrongly identified in the image on either a local or array-wide scale, with obvious implications for data quality. Conclusions The image processing issues identified will often pass unnoticed by an analysis of the standard data returned from an experiment. We detail some simple diagnostics that can be implemented to identify problems of this nature, and outline approaches to correcting for such problems. These approaches require access to the raw data from the arrays, not just the summarized data usually returned, making the acquisition of such raw data highly desirable.

Abstract Background The accurate and high resolution mapping of DNA copy number aberrations has become an important tool by which to gain insight into the mechanisms of tumourigenesis. There are various commercially available platforms for such studies, but there remains no general consensus as to the optimal platform. There have been several previous platform comparison studies, but they have either described older technologies, used less-complex samples, or have not addressed the issue of the inherent biases in such comparisons. Here we describe a systematic comparison of data from four leading microarray technologies (the Affymetrix Genome-wide SNP 5.0 array, Agilent High-Density CGH Human 244A array, Illumina HumanCNV370-Duo DNA Analysis BeadChip, and the Nimblegen 385 K oligonucleotide array). We compare samples derived from primary breast tumours and their corresponding matched normals, well-established cancer cell lines, and HapMap individuals. By careful consideration and avoidance of potential sources of bias, we aim to provide a fair assessment of platform performance. Results By performing a theoretical assessment of the reproducibility, noise, and sensitivity of each platform, notable differences were revealed. Nimblegen exhibited between-replicate array variances an order of magnitude greater than the other three platforms, with Agilent slightly outperforming the others, and a comparison of self-self hybridizations revealed similar patterns. An assessment of the single probe power revealed that Agilent exhibits the highest sensitivity. Additionally, we performed an in-depth visual assessment of the ability of each platform to detect aberrations of varying sizes. As expected, all platforms were able to identify large aberrations in a robust manner. However, some focal amplifications and deletions were only detected in a subset of the platforms. Conclusion Although there are substantial differences in the design, density, and number of replicate probes, the comparison indicates a generally high level of concordance between platforms, despite differences in the reproducibility, noise, and sensitivity. In general, Agilent tended to be the best aCGH platform and Affymetrix, the superior SNP-CGH platform, but for specific decisions the results described herein provide a guide for platform selection and study design, and the dataset a resource for more tailored comparisons.

The COVID-19 pandemic is shifting teaching to an online setting all over the world. The Galaxy framework facilitates the online learning process and makes it accessible by providing a library of high-quality community-curated training materials, enabling easy access to data and tools, and facilitates sharing achievements and progress between students and instructors. By combining Galaxy with robust communication channels, effective instruction can be designed inclusively, regardless of the students' environments. [ABSTRACT FROM AUTHOR]

Abstract Background Variance-stabilizing techniques have been used for some time in the analysis of gene expression microarray data. A new adaptation, the variance-stabilizing transformation (VST), has recently been developed to take advantage of the unique features of Illumina BeadArrays. VST has been shown to perform well in comparison with the widely-used approach of taking a log2 transformation, but has not been validated on a spike-in experiment. We apply VST to the data from a recently published spike-in experiment and compare it both to a regular log2 analysis and a recently recommended analysis that can be applied if all raw data are available. Findings VST provides more power to detect differentially expressed genes than a log2 transformation. However, the gain in power is roughly the same as utilizing the raw data from an experiment and weighting observations accordingly. VST is still advantageous when large changes in expression are anticipated, while a weighted log2 approach performs better for smaller changes. Conclusion VST can be recommended for summarized Illumina data regardless of which Illumina pre-processing options have been used. However, using the raw data is still encouraged whenever possible.

Abstract Background Illumina bead-based arrays are becoming increasingly popular due to their high degree of replication and reported high data quality. However, little attention has been paid to the pre-processing of Illumina data. In this paper, we present our experience of analysing the raw data from an Illumina spike-in experiment and offer guidelines for those wishing to analyse expression data or develop new methodologies for this technology. Results We find that the local background estimated by Illumina is consistently low, and subtracting this background is beneficial for detecting differential expression (DE). Illumina's summary method performs well at removing outliers, producing estimates which are less biased and are less variable than other robust summary methods. However, quality assessment on summarised data may miss spatial artefacts present in the raw data. Also, we find that the background normalisation method used in Illumina's proprietary software (BeadStudio) can cause problems with a standard DE analysis. We demonstrate that variances calculated from the raw data can be used as inverse weights in the DE analysis to improve power. Finally, variability in both expression levels and DE statistics can be attributed to differences in probe composition. These differences are not accounted for by current analysis methods and require further investigation. Conclusion Analysing Illumina expression data using BeadStudio is reasonable because of the conservative estimates of summary values produced by the software. Improvements can however be made by not using background normalisation. Access to the raw data allows for a more detailed quality assessment and flexible analyses. In the case of a gene expression study, data can be analysed on an appropriate scale using established tools. Similar improvements can be expected for other Illumina assays.

Rationale: Idiopathic and heritable pulmonary arterial hypertension (PAH) are rare but comprise a genetically heterogeneous patient group. RNA sequencing linked to the underlying genetic architecture can be used to better understand the underlying pathology by identifying key signaling pathways and stratify patients more robustly according to clinical risk.Objectives: To use a three-stage design of RNA discovery, RNA validation and model construction, and model validation to define a set of PAH-associated RNAs and a single summarizing RNA model score. To define genes most likely to be involved in disease development, we performed Mendelian randomization (MR) analysis.Methods: RNA sequencing was performed on whole-blood samples from 359 patients with idiopathic, heritable, and drug-induced PAH and 72 age- and sex-matched healthy volunteers. The score was evaluated against disease severity markers including survival analysis using all-cause mortality from diagnosis. MR used known expression quantitative trait loci and summary statistics from a PAH genome-wide association study.Measurements and Main Results: We identified 507 genes with differential RNA expression in patients with PAH compared with control subjects. A model of 25 RNAs distinguished PAH with 87% accuracy (area under the curve 95% confidence interval: 0.791-0.945) in model validation. The RNA model score was associated with disease severity and long-term survival (P = 4.66 × 10-6) in PAH. MR detected an association between SMAD5 levels and PAH disease susceptibility (odds ratio, 0.317; 95% confidence interval, 0.129-0.776; P = 0.012).Conclusions: A whole-blood RNA signature of PAH, which includes RNAs relevant to disease pathogenesis, associates with disease severity and identifies patients with poor clinical outcomes. Genetic variants associated with lower SMAD5 expression may increase susceptibility to PAH. [ABSTRACT FROM AUTHOR]

Skeletal metastasis occurs in around 75% of advanced breast cancers, with the disease incurable once cancer cells disseminate to bone, but there remains an unmet need for biomarkers to identify patients at high risk of bone recurrence. This study aimed to identify such a biomarker and to assess its utility in predicting response to adjuvant zoledronic acid (zoledronate). We used quantitative proteomics (stable isotope labelling by amino acids in cell culture‐mass spectrometry; SILAC‐MS) to compare protein expression in a bone‐homing variant (BM1) of the human breast cancer cell line MDA‐MB‐231 with parental non‐bone‐homing cells to identify novel biomarkers for risk of subsequent bone metastasis in early breast cancer. SILAC‐MS showed that dedicator of cytokinesis protein 4 (DOCK4) was upregulated in bone‐homing BM1 cells, confirmed by western blotting. BM1 cells also had enhanced invasive ability compared with parental cells, which could be reduced by DOCK4‐shRNA. In a training tissue microarray (TMA) comprising 345 patients with early breast cancer, immunohistochemistry followed by Cox regression revealed that high DOCK4 expression correlated with histological grade (p = 0.004) but not oestrogen receptor status (p = 0.19) or lymph node involvement (p = 0.15). A clinical validation TMA used tissue samples and the clinical database from the large AZURE adjuvant study (n = 689). Adjusted Cox regression analyses showed that high DOCK4 expression in the control arm (no zoledronate) was significantly prognostic for first recurrence in bone (HR 2.13, 95%CI 1.06–4.30, p = 0.034). No corresponding association was found in patients who received zoledronate (HR 0.812, 95%CI 0.176–3.76, p = 0.790), suggesting that treatment with zoledronate may counteract the higher risk for bone relapse from high DOCK4‐expressing tumours. High DOCK4 expression was not associated with metastasis to non‐skeletal sites when these were assessed collectively. In conclusion, high DOCK4 in early breast cancer is significantly associated with aggressive disease and with future bone metastasis and is a potentially useful biomarker for subsequent bone metastasis risk. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Prostate cancer is the most common cancer in men, resulting in over 10,000 deaths per year in the UK. Sequencing and copy number analysis of primary tumours has revealed heterogeneity within tumours and an absence of recurrent founder mutations, consistent with non-genetic disease initiating events. Using methylation profiling in a series of multi-focal prostate tumours we identify promoter methylation of the transcription factor HES5 as an early event in prostate tumourigenesis. We confirm that this epigenetic alteration occurs in 86-97% of cases in two independent prostate cancer cohorts (n=49 and n=39 tumour-normal pairs). Treatment of prostate cancer cells with the demethylating agent 5-aza-2'-deoxycytidine increased HES5 expression and down-regulated its transcriptional target HES6, consistent with functional silencing of the HES5 gene in prostate cancer. Finally we identify and test a transcriptional module involving the AR, ERG, HES1 and HES6 and propose a model for the impact of HES5 silencing on tumourigenesis as a starting point for future functional studies. [ABSTRACT FROM AUTHOR]

Cancer genome sequencing studies have identified numerous driver genes, but the relative timing of mutations in carcinogenesis remains unclear. The gradual progression from premalignant Barrett's esophagus to esophageal adenocarcinoma (EAC) provides an ideal model to study the ordering of somatic mutations. We identified recurrently mutated genes and assessed clonal structure using whole-genome sequencing and amplicon resequencing of 112 EACs. We next screened a cohort of 109 biopsies from 2 key transition points in the development of malignancy: benign metaplastic never-dysplastic Barrett's esophagus (NDBE; n = 66) and high-grade dysplasia (HGD; n = 43). Unexpectedly, the majority of recurrently mutated genes in EAC were also mutated in NDBE. Only TP53 and SMAD4 mutations occurred in a stage-specific manner, confined to HGD and EAC, respectively. Finally, we applied this knowledge to identify high-risk Barrett's esophagus in a new non-endoscopic test. In conclusion, mutations in EAC driver genes generally occur exceptionally early in disease development with profound implications for diagnostic and therapeutic strategies. [ABSTRACT FROM AUTHOR]

Sample tracking errors have been and always will be a part of the practical implementation of large experiments. It has recently been proposed that expression quantitative trait loci (eQTLs) and their associated effects could be used to identify sample mix-ups and this approach has been applied to a number of large population genomics studies to illustrate the prevalence of the problem. We had adopted a similar approach, termed 'BADGER', in the METABRIC project. METABRIC is a large breast cancer study that may have been the first in which eQTL-based detection of mismatches was used during the study, rather than after the event, to aid quality assurance. We report here on the particular issues associated with large cancer studies performed using historical samples, which complicate the interpretation of such approaches. In particular we identify the complications of using tumour samples, of considering cellularity and RNA quality, of distinct subgroups existing in the study population (including family structures), and of choosing eQTLs to use. We also present some results regarding the design of experiments given consideration of these matters. The eQTL-based approach to identifying sample tracking errors is seen to be of value to these studies, but requiring care in its implementation. [ABSTRACT FROM AUTHOR]

Background: A key stage for all microarray analyses is the extraction of feature-intensities from an image. If this step goes wrong, then subsequent preprocessing and processing stages will stand little chance of rectifying the matter. Illumina employ random construction of their BeadArrays, making feature-intensity extraction even more important for the Illumina platform than for other technologies. In this paper we show that using raw Illumina data it is possible to identify, control, and perhaps correct for a range of spatial-related phenomena that affect feature-intensity extraction. Results: We note that feature intensities can be unnaturally high when in the proximity of a number of phenomena relating either to the images themselves or to the layout of the beads on an array. Additionally we note that beads neighbour beads of the same type more often than one might expect, which may cause concern in some models of hybridization. We highlight issues in the identification of a bead's location, and in particular how this both affects and is affected by its intensity. Finally we show that beads can be wrongly identified in the image on either a local or array-wide scale, with obvious implications for data quality. Conclusions: The image processing issues identified will often pass unnoticed by an analysis of the standard data returned from an experiment. We detail some simple diagnostics that can be implemented to identify problems of this nature, and outline approaches to correcting for such problems. These approaches require access to the raw data from the arrays, not just the summarized data usually returned, making the acquisition of such raw data highly desirable. [ABSTRACT FROM AUTHOR]

Background: The accurate and high resolution mapping of DNA copy number aberrations has become an important tool by which to gain insight into the mechanisms of tumourigenesis. There are various commercially available platforms for such studies, but there remains no general consensus as to the optimal platform. There have been several previous platform comparison studies, but they have either described older technologies, used less-complex samples, or have not addressed the issue of the inherent biases in such comparisons. Here we describe a systematic comparison of data from four leading microarray technologies (the Affymetrix Genome-wide SNP 5.0 array, Agilent High-Density CGH Human 244A array, Illumina HumanCNV370-Duo DNA Analysis BeadChip, and the Nimblegen 385 K oligonucleotide array). We compare samples derived from primary breast tumours and their corresponding matched normals, well-established cancer cell lines, and HapMap individuals. By careful consideration and avoidance of potential sources of bias, we aim to provide a fair assessment of platform performance. Results: By performing a theoretical assessment of the reproducibility, noise, and sensitivity of each platform, notable differences were revealed. Nimblegen exhibited between-replicate array variances an order of magnitude greater than the other three platforms, with Agilent slightly outperforming the others, and a comparison of self-self hybridizations revealed similar patterns. An assessment of the single probe power revealed that Agilent exhibits the highest sensitivity. Additionally, we performed an in-depth visual assessment of the ability of each platform to detect aberrations of varying sizes. As expected, all platforms were able to identify large aberrations in a robust manner. However, some focal amplifications and deletions were only detected in a subset of the platforms. Conclusion: Although there are substantial differences in the design, density, and number of replicate probes, the comparison indicates a generally high level of concordance between platforms, despite differences in the reproducibility, noise, and sensitivity. In general, Agilent tended to be the best aCGH platform and Affymetrix, the superior SNP-CGH platform, but for specific decisions the results described herein provide a guide for platform selection and study design, and the dataset a resource for more tailored comparisons. [ABSTRACT FROM AUTHOR]

Background: Illumina bead-based arrays are becoming increasingly popular due to their high degree of replication and reported high data quality. However, little attention has been paid to the pre-processing of Illumina data. In this paper, we present our experience of analysing the raw data from an Illumina spike-in experiment and offer guidelines for those wishing to analyse expression data or develop new methodologies for this technology. Results: We find that the local background estimated by Illumina is consistently low, and subtracting this background is beneficial for detecting differential expression (DE). Illumina's summary method performs well at removing outliers, producing estimates which are less biased and are less variable than other robust summary methods. However, quality assessment on summarised data may miss spatial artefacts present in the raw data. Also, we find that the background normalisation method used in Illumina's proprietary software (BeadStudio) can cause problems with a standard DE analysis. We demonstrate that variances calculated from the raw data can be used as inverse weights in the DE analysis to improve power. Finally, variability in both expression levels and DE statistics can be attributed to differences in probe composition. These differences are not accounted for by current analysis methods and require further investigation. Conclusion: Analysing Illumina expression data using BeadStudio is reasonable because of the conservative estimates of summary values produced by the software. Improvements can however be made by not using background normalisation. Access to the raw data allows for a more detailed quality assessment and flexible analyses. In the case of a gene expression study, data can be analysed on an appropriate scale using established tools. Similar improvements can be expected for other Illumina assays. [ABSTRACT FROM AUTHOR]

Systemic cobalt (Co) and chromium (Cr) concentrations may be elevated in patients with metal joint replacement prostheses. Several studies have highlighted the detrimental effects of this exposure on bone cells in vitro, but the underlying mechanisms remain unclear. In this study, we use whole-genome microarrays to comprehensively assess gene expression in primary human osteoblasts, osteoclast precursors and mature resorbing osteoclasts following exposure to clinically relevant circulating versus local periprosthetic tissue concentrations of Co2+ and Cr3+ ions and CoCr nanoparticles. We also describe the gene expression response in osteoblasts on routinely used prosthesis surfaces in the presence of metal exposure. Our results suggest that systemic levels of metal exposure have no effect on osteoblasts, and primarily inhibit osteoclast differentiation and function via altering the focal adhesion and extracellular matrix interaction pathways. In contrast, periprosthetic levels of metal exposure inhibit both osteoblast and osteoclast activity by altering HIF-1α signaling and endocytic/cytoskeletal genes respectively, as well as increasing inflammatory signaling with mechanistic implications for adverse reactions to metal debris. Furthermore, we identify gene clusters and KEGG pathways for which the expression correlates with increasing Co2+:Cr3+ concentrations, and has the potential to serve as early markers of metal toxicity. Finally, our study provides a molecular basis for the improved clinical outcomes for hydroxyapatite-coated prostheses that elicit a pro-survival osteogenic gene signature compared to grit-blasted and plasma-sprayed titanium-coated surfaces in the presence of metal exposure. [ABSTRACT FROM AUTHOR]

The article discusses research on the JAG1-NOTCH4 pathway sensing of disturbed flow, which enhances atherosclerosis susceptibility by regulating Endothelial cell (EC) heterogeneity, and that the pathway may treat atherosclerosis. Researchers used porcine and murine arteries and cultured human coronary artery EC that disturbed flow activates the JAG1-NOTCH4 signaling pathway. Single-cell ribonucleic acid sequencing in Jag1ECKO mice demonstrated that Jag1 suppresses subsets of ECs.

The androgen receptor (AR) is the dominant growth factor in prostate cancer (PCa). Therefore, understanding how ARs regulate the human transcriptome is of paramount importance. The early effects of castration on human PCa have not previously been studied 27 patients medically castrated with degarelix 7 d before radical prostatectomy. We used mass spectrometry, immunohistochemistry, and gene expression array (validated by reverse transcription-polymerase chain reaction) to compare resected tumour with matched, controlled, untreated PCa tissue. All patients had levels of serum androgen, with reduced levels of intraprostatic androgen at prostatectomy. We observed differential expression of known androgen-regulated genes ( TMPRSS2, KLK3, CAMKK2, FKBP5 ). We identified 749 genes downregulated and 908 genes upregulated following castration. AR regulation of α-methylacyl-CoA racemase expression and three other genes ( FAM129A, RAB27A , and KIAA0101 ) was confirmed. Upregulation of oestrogen receptor 1 (ESR1) expression was observed in malignant epithelia and was associated with differential expression of ESR1-regulated genes and correlated with proliferation (Ki-67 expression). Patient summary This first-in-man study defines the rapid gene expression changes taking place in prostate cancer (PCa) following castration. Expression levels of the genes that the androgen receptor regulates are predictive of treatment outcome. Upregulation of oestrogen receptor 1 is a mechanism by which PCa cells may survive despite castration. [ABSTRACT FROM AUTHOR]

Background: Atherosclerotic plaques form unevenly due to disturbed blood flow, causing localized endothelial cell (EC) dysfunction. Obesity exacerbates this process, but the underlying molecular mechanisms are unclear. The transcription factor EPAS1 (HIF2A) has regulatory roles in endothelium, but its involvement in atherosclerosis remains unexplored. This study investigates the potential interplay between EPAS1, obesity, and atherosclerosis., Methods: Responses to shear stress were analyzed using cultured porcine aortic EC exposed to flow in vitro coupled with metabolic and molecular analyses and by en face immunostaining of murine aortic EC exposed to disturbed flow in vivo. Obesity and dyslipidemia were induced in mice via exposure to a high-fat diet or through Leptin gene deletion. The role of Epas1 in atherosclerosis was evaluated by inducible endothelial Epas1 deletion, followed by hypercholesterolemia induction (adeno-associated virus-PCSK9 [proprotein convertase subtilisin/kexin type 9]; high-fat diet)., Results: En face staining revealed EPAS1 enrichment at sites of disturbed blood flow that are prone to atherosclerosis initiation. Obese mice exhibited substantial reduction in endothelial EPAS1 expression. Sulforaphane, a compound with known atheroprotective effects, restored EPAS1 expression and concurrently reduced plasma triglyceride levels in obese mice. Consistently, triglyceride derivatives (free fatty acids) suppressed EPAS1 in cultured EC by upregulating the negative regulator PHD2. Clinical observations revealed that reduced serum EPAS1 correlated with increased endothelial PHD2 and PHD3 in obese individuals. Functionally, endothelial EPAS1 deletion increased lesion formation in hypercholesterolemic mice, indicating an atheroprotective function. Mechanistic insights revealed that EPAS1 protects arteries by maintaining endothelial proliferation by positively regulating the expression of the fatty acid-handling molecules CD36 (cluster of differentiation 36) and LIPG (endothelial type lipase G) to increase fatty acid beta-oxidation., Conclusions: Endothelial EPAS1 attenuates atherosclerosis at sites of disturbed flow by maintaining EC proliferation via fatty acid uptake and metabolism. This endothelial repair pathway is inhibited in obesity, suggesting a novel triglyceride-PHD2 modulation pathway suppressing EPAS1 expression. These findings have implications for therapeutic strategies addressing vascular dysfunction in obesity., Competing Interests: None.

The heterogenous aetiology of Parkinson's disease is increasingly recognized; both mitochondrial and lysosomal dysfunction have been implicated. Powerful, clinically applicable tools are required to enable mechanistic stratification for future precision medicine approaches. The aim of this study was to characterize bioenergetic dysfunction in Parkinson's disease by applying a multimodal approach, combining standardized clinical assessment with midbrain and putaminal 31-phosphorus magnetic resonance spectroscopy (31P-MRS) and deep phenotyping of mitochondrial and lysosomal function in peripheral tissue in patients with recent-onset Parkinson's disease and control subjects. Sixty participants (35 patients with Parkinson's disease and 25 healthy controls) underwent 31P-MRS for quantification of energy-rich metabolites [ATP, inorganic phosphate (Pi) and phosphocreatine] in putamen and midbrain. In parallel, skin biopsies were obtained from all research participants to establish fibroblast cell lines for subsequent quantification of total intracellular ATP and mitochondrial membrane potential (MMP) as well as mitochondrial and lysosomal morphology, using high content live cell imaging. Lower MMP correlated with higher intracellular ATP (r = -0.55, P = 0.0016), higher mitochondrial counts (r = -0.72, P < 0.0001) and higher lysosomal counts (r = -0.62, P = 0.0002) in Parkinson's disease patient-derived fibroblasts only, consistent with impaired mitophagy and mitochondrial uncoupling. 31P-MRS-derived posterior putaminal Pi/ATP ratio variance was considerably greater in Parkinson's disease than in healthy controls (F-tests, P = 0.0036). Furthermore, elevated 31P-MRS-derived putaminal, but not midbrain Pi/ATP ratios (indicative of impaired oxidative phosphorylation) correlated with both greater mitochondrial (r = 0.37, P = 0.0319) and lysosomal counts (r = 0.48, P = 0.0044) as well as lower MMP in both short (r = -0.52, P = 0.0016) and long (r = -0.47, P = 0.0052) mitochondria in Parkinson's disease. Higher 31P-MRS midbrain phosphocreatine correlated with greater risk of rapid disease progression (r = 0.47, P = 0.0384). Our data suggest that impaired oxidative phosphorylation in the striatal dopaminergic nerve terminals exceeds mitochondrial dysfunction in the midbrain of patients with early Parkinson's disease. Our data further support the hypothesis of a prominent link between impaired mitophagy and impaired striatal energy homeostasis as a key event in early Parkinson's disease., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Background: Localized prostate cancer is clinically heterogeneous, despite clinical risk groups that represent relative prostate cancer-specific mortality. We previously developed a 100-locus DNA classifier capable of substratifying patients at risk of biochemical relapse within clinical risk groups., Objective: The 100-locus genomic classifier was refined to 31 functional loci and tested with standard clinical variables for the ability to predict biochemical recurrence (BCR) and metastasis., Design, Setting, and Participants: Four retrospective cohorts of radical prostatectomy specimens from patients with localized disease were pooled, and an additional 102-patient cohort used to measure the 31-locus genomic classifier with the NanoString platform., Outcome Measurements and Statistical Analysis: The genomic classifier scores were tested for their ability to predict BCR (n=563) and metastasis (n=154), and compared with clinical risk stratification schemes., Results and Limitations: The 31-locus genomic classifier performs similarly to the 100-locus classifier. It identifies patients with elevated BCR rates (hazard ratio=2.73, p<0.001) and patients that eventually develop metastasis (hazard ratio=7.79, p<0.001). Combining the genomic classifier with standard clinical variables outperforms clinical models. Finally, the 31-locus genomic classifier was implemented using a NanoString assay. The study is limited to retrospective cohorts., Conclusions: The 100-locus and 31-locus genomic classifiers reliably identify a cohort of men with localized disease who have an elevated risk of failure. The NanoString assay will be useful for selecting patients for treatment deescalation or escalation in prospective clinical trials based on clinico-genomic scores from pretreatment biopsies., Patient Summary: It is challenging to determine whether tumors confined to the prostate are aggressive, leading to significant undertreatment and overtreatment. We validated a test based on prostate tumor DNA that improves estimations of relapse risk, and that can help guide treatment planning., (Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.)

Molecular characterization of genome-wide association study (GWAS) loci can uncover key genes and biological mechanisms underpinning complex traits and diseases. Here we present deep, high-throughput characterization of gene regulatory mechanisms underlying prostate cancer risk loci. Our methodology integrates data from 295 prostate cancer chromatin immunoprecipitation and sequencing experiments with genotype and gene expression data from 602 prostate tumor samples. The analysis identifies new gene regulatory mechanisms affected by risk locus SNPs, including widespread disruption of ternary androgen receptor (AR)-FOXA1 and AR-HOXB13 complexes and competitive binding mechanisms. We identify 57 expression quantitative trait loci at 35 risk loci, which we validate through analysis of allele-specific expression. We further validate predicted regulatory SNPs and target genes in prostate cancer cell line models. Finally, our integrated analysis can be accessed through an interactive visualization tool. This analysis elucidates how genome sequence variation affects disease predisposition via gene regulatory mechanisms and identifies relevant genes for downstream biomarker and drug development.