Multimodal assessment of mitochondrial function in Parkinson's disease.

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.

A Double-Blind, Randomized, Placebo-Controlled Trial of Ursodeoxycholic Acid (UDCA) in Parkinson's Disease.

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 (31 P-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 31 P-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.

Fostering accessible online education using Galaxy as an e-learning platform.

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.

Whole-Blood RNA Profiles Associated with Pulmonary Arterial Hypertension and Clinical Outcome.

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.

Distinct Concentration-Dependent Molecular Pathways Regulate Bone Cell Responses to Cobalt and Chromium Exposure from Joint Replacement Prostheses.

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.

The failure of microglia to digest developmental apoptotic cells contributes to the pathology of RNASET2-deficient leukoencephalopathy.

The contribution of microglia in neurological disorders is emerging as a leading disease driver rather than a consequence of pathology. RNAseT2-deficient leukoencephalopathy is a severe childhood white matter disorder affecting patients in their first year of life and mimicking a cytomegalovirus brain infection. The early onset and resemblance of the symptoms to a viral infection suggest an inflammatory and embryonic origin of the pathology. There are no treatments available for this disease as our understanding of the cellular drivers of the pathology are still unknown. In this study, using a zebrafish mutant for the orthologous rnaset2 gene, we have identified an inflammatory signature in early development and an antiviral immune response in mature adult brains. Using the optical transparency and the ex utero development of the zebrafish larvae we studied immune cell behavior during brain development and identified abnormal microglia as an early marker of pathology. Live imaging and electron microscopy identified that mutant microglia displayed an engorged morphology and were filled with undigested apoptotic cells and undigested substrate. Using microglia-specific depletion and rescue experiments, we identified microglia as drivers of this embryonic phenotype and potential key cellular player in the pathology of RNAseT2-deficient leukoencephalopathy. Our zebrafish model also presented with reduced survival and locomotor defects, therefore recapitulating many aspects of the human disease. Our study therefore placed our rnaset2 mutant at the forefront of leukodystrophy preclinical models and highlighted tissue-specific approaches as future therapeutic avenues.

Identification and validation of DOCK4 as a potential biomarker for risk of bone metastasis development in patients with early breast cancer.

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.

Differential oestrogen receptor binding is associated with clinical outcome in breast cancer.

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. Here we map genome-wide ER-binding events, by chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-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.

The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups.

The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in ~40% of genes, with the landscape dominated by cis- and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP and MAP2K4. Unsupervised analysis of paired DNA­RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the 'CNA-devoid' subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome.

Analysis of circulating tumor DNA to monitor metastatic breast cancer.

BACKGROUND: The management of metastatic breast cancer requires monitoring of the tumor burden to determine the response to treatment, and improved biomarkers are needed. Biomarkers such as cancer antigen 15-3 (CA 15-3) and circulating tumor cells have been widely studied. However, circulating cell-free DNA carrying tumor-specific alterations (circulating tumor DNA) has not been extensively investigated or compared with other circulating biomarkers in breast cancer. METHODS: We compared the radiographic imaging of tumors with the assay of circulating tumor DNA, CA 15-3, and circulating tumor cells in 30 women with metastatic breast cancer who were receiving systemic therapy. We used targeted or whole-genome sequencing to identify somatic genomic alterations and designed personalized assays to quantify circulating tumor DNA in serially collected plasma specimens. CA 15-3 levels and numbers of circulating tumor cells were measured at identical time points. RESULTS: Circulating tumor DNA was successfully detected in 29 of the 30 women (97%) in whom somatic genomic alterations were identified; CA 15-3 and circulating tumor cells were detected in 21 of 27 women (78%) and 26 of 30 women (87%), respectively. Circulating tumor DNA levels showed a greater dynamic range, and greater correlation with changes in tumor burden, than did CA 15-3 or circulating tumor cells. Among the measures tested, circulating tumor DNA provided the earliest measure of treatment response in 10 of 19 women (53%). CONCLUSIONS: This proof-of-concept analysis showed that circulating tumor DNA is an informative, inherently specific, and highly sensitive biomarker of metastatic breast cancer. (Funded by Cancer Research UK and others.).

Tumour genomic and microenvironmental heterogeneity for integrated prediction of 5-year biochemical recurrence of prostate cancer: a retrospective cohort study.

BACKGROUND: Clinical prognostic groupings for localised prostate cancers are imprecise, with 30-50% of patients recurring after image-guided radiotherapy or radical prostatectomy. We aimed to test combined genomic and microenvironmental indices in prostate cancer to improve risk stratification and complement clinical prognostic factors. METHODS: We used DNA-based indices alone or in combination with intra-prostatic hypoxia measurements to develop four prognostic indices in 126 low-risk to intermediate-risk patients (Toronto cohort) who will receive image-guided radiotherapy. We validated these indices in two independent cohorts of 154 (Memorial Sloan Kettering Cancer Center cohort [MSKCC] cohort) and 117 (Cambridge cohort) radical prostatectomy specimens from low-risk to high-risk patients. We applied unsupervised and supervised machine learning techniques to the copy-number profiles of 126 pre-image-guided radiotherapy diagnostic biopsies to develop prognostic signatures. Our primary endpoint was the development of a set of prognostic measures capable of stratifying patients for risk of biochemical relapse 5 years after primary treatment. FINDINGS: Biochemical relapse was associated with indices of tumour hypoxia, genomic instability, and genomic subtypes based on multivariate analyses. We identified four genomic subtypes for prostate cancer, which had different 5-year biochemical relapse-free survival. Genomic instability is prognostic for relapse in both image-guided radiotherapy (multivariate analysis hazard ratio [HR] 4·5 [95% CI 2·1-9·8]; p=0·00013; area under the receiver operator curve [AUC] 0·70 [95% CI 0·65-0·76]) and radical prostatectomy (4·0 [1·6-9·7]; p=0·0024; AUC 0·57 [0·52-0·61]) patients with prostate cancer, and its effect is magnified by intratumoral hypoxia (3·8 [1·2-12]; p=0·019; AUC 0·67 [0·61-0·73]). A novel 100-loci DNA signature accurately classified treatment outcome in the MSKCC low-risk to intermediate-risk cohort (multivariate analysis HR 6·1 [95% CI 2·0-19]; p=0·0015; AUC 0·74 [95% CI 0·65-0·83]). In the independent MSKCC and Cambridge cohorts, this signature identified low-risk to high-risk patients who were most likely to fail treatment within 18 months (combined cohorts multivariate analysis HR 2·9 [95% CI 1·4-6·0]; p=0·0039; AUC 0·68 [95% CI 0·63-0·73]), and was better at predicting biochemical relapse than 23 previously published RNA signatures. INTERPRETATION: This is the first study of cancer outcome to integrate DNA-based and microenvironment-based failure indices to predict patient outcome. Patients exhibiting these aggressive features after biopsy should be entered into treatment intensification trials. FUNDING: Movember Foundation, Prostate Cancer Canada, Ontario Institute for Cancer Research, Canadian Institute for Health Research, NIHR Cambridge Biomedical Research Centre, The University of Cambridge, Cancer Research UK, Cambridge Cancer Charity, Prostate Cancer UK, Hutchison Whampoa Limited, Terry Fox Research Institute, Princess Margaret Cancer Centre Foundation, PMH-Radiation Medicine Program Academic Enrichment Fund, Motorcycle Ride for Dad (Durham), Canadian Cancer Society.

BeadArray expression analysis using bioconductor.

Illumina whole-genome expression BeadArrays are a popular choice in gene profiling studies. Aside from the vendor-provided software tools for analyzing BeadArray expression data (GenomeStudio/BeadStudio), there exists a comprehensive set of open-source analysis tools in the Bioconductor project, many of which have been tailored to exploit the unique properties of this platform. In this article, we explore a number of these software packages and demonstrate how to perform a complete analysis of BeadArray data in various formats. The key steps of importing data, performing quality assessments, preprocessing, and annotation in the common setting of assessing differential expression in designed experiments will be covered.

A re-annotation pipeline for Illumina BeadArrays: improving the interpretation of gene expression data.

Illumina BeadArrays are among the most popular and reliable platforms for gene expression profiling. However, little external scrutiny has been given to the design, selection and annotation of BeadArray probes, which is a fundamental issue in data quality and interpretation. Here we present a pipeline for the complete genomic and transcriptomic re-annotation of Illumina probe sequences, also applicable to other platforms, with its output available through a Web interface and incorporated into Bioconductor packages. We have identified several problems with the design of individual probes and we show the benefits of probe re-annotation on the analysis of BeadArray gene expression data sets. We discuss the importance of aspects such as probe coverage of individual transcripts, alternative messenger RNA splicing, single-nucleotide polymorphisms, repeat sequences, RNA degradation biases and probes targeting genomic regions with no known transcription. We conclude that many of the Illumina probes have unreliable original annotation and that our re-annotation allows analyses to focus on the good quality probes, which form the majority, and also to expand the scope of biological information that can be extracted.

Hyaluronan nanoscale clustering and Hyaluronan synthase 2 expression are linked to the invasion of child fibroblasts and infantile fibrosarcoma in vitro and in vivo.

Infantile fibrosarcoma is a rare childhood tumour that originates in the fibrous connective tissue of the long bones for which there is an urgent need to identify novel therapeutic targets. This study aims to clarify the role of the extracellular matrix component hyaluronan in the invasion of child fibroblasts and Infantile fibrosarcoma into the surrounding environment. Using nanoscale super-resolution STED (Stimulated emission depletion) microscopy followed by computational image analysis, we observed, for the first time, that invasive child fibroblasts showed increased nanoscale clustering of hyaluronan at the cell periphery, as compared to control cells. Hyaluronan was not observed within focal adhesions. Bioinformatic analyses further revealed that the increased nanoscale hyaluronan clustering was accompanied by increased gene expression of Hyaluronan synthase 2, reduced expression of Hyaluronidase 2 and CD44, and no change of Hyaluronan synthase 1 and Hyaluronidases 1, 3, 4 or 5. We further observed that the expression of the Hyaluronan synthase 1, 2 and 3, and the Hyaluronidase 3 and 5 genes was linked to reduced life expectancy of fibrosarcoma patients. The invasive front of infantile fibrosarcoma tumours further showed increased levels of hyaluronan, as compared to the tumour centre. Taken together, our findings are consistent with the possibility that while Hyaluronan synthase 2 increases the levels, the Hyaluronidases 3 and 5 reduce the weight of hyaluronan, resulting in the nanoscale clustering of hyaluronan at the leading edge of cells, cell invasion and the spread of Infantile fibrosarcoma.

JAG1-NOTCH4 mechanosensing drives atherosclerosis.

Endothelial cell (EC) sensing of disturbed blood flow triggers atherosclerosis, a disease of arteries that causes heart attack and stroke, through poorly defined mechanisms. The Notch pathway plays a central role in blood vessel growth and homeostasis, but its potential role in sensing of disturbed flow has not been previously studied. Here, we show using porcine and murine arteries and cultured human coronary artery EC that disturbed flow activates the JAG1-NOTCH4 signaling pathway. Light-sheet imaging revealed enrichment of JAG1 and NOTCH4 in EC of atherosclerotic plaques, and EC-specific genetic deletion of Jag1 (Jag1ECKO) demonstrated that Jag1 promotes atherosclerosis at sites of disturbed flow. Mechanistically, single-cell RNA sequencing in Jag1ECKO mice demonstrated that Jag1 suppresses subsets of ECs that proliferate and migrate. We conclude that JAG1-NOTCH4 sensing of disturbed flow enhances atherosclerosis susceptibility by regulating EC heterogeneity and that therapeutic targeting of this pathway may treat atherosclerosis.

Biological heterogeneity in idiopathic pulmonary arterial hypertension identified through unsupervised transcriptomic profiling of whole blood.

Idiopathic pulmonary arterial hypertension (IPAH) is a rare but fatal disease diagnosed by right heart catheterisation and the exclusion of other forms of pulmonary arterial hypertension, producing a heterogeneous population with varied treatment response. Here we show unsupervised machine learning identification of three major patient subgroups that account for 92% of the cohort, each with unique whole blood transcriptomic and clinical feature signatures. These subgroups are associated with poor, moderate, and good prognosis. The poor prognosis subgroup is associated with upregulation of the ALAS2 and downregulation of several immunoglobulin genes, while the good prognosis subgroup is defined by upregulation of the bone morphogenetic protein signalling regulator NOG, and the C/C variant of HLA-DPA1/DPB1 (independently associated with survival). These findings independently validated provide evidence for the existence of 3 major subgroups (endophenotypes) within the IPAH classification, could improve risk stratification and provide molecular insights into the pathogenesis of IPAH.

Identification and correction of previously unreported spatial phenomena using raw Illumina BeadArray data.

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.

The cost of reducing starting RNA quantity for Illumina BeadArrays: a bead-level dilution experiment.

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.

The pitfalls of platform comparison: DNA copy number array technologies assessed.

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.

Statistical issues in the analysis of Illumina data.

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.