Trajectories of dementia-related cognitive decline in a large mental health records derived patient cohort.

BACKGROUND: Modeling trajectories of decline can help describe the variability in progression of cognitive impairment in dementia. Better characterisation of these trajectories has significant implications for understanding disease progression, trial design and care planning. METHODS: Patients with at least three Mini-mental State Examination (MMSE) scores recorded in the South London and Maudsley NHS Foundation Trust Electronic Health Records, UK were selected (N = 3441) to form a retrospective cohort. Trajectories of cognitive decline were identified through latent class growth analysis of longitudinal MMSE scores. Demographics, Health of Nation Outcome Scales and medications were compared across trajectories identified. RESULTS: Four of the six trajectories showed increased rate of decline with lower baseline MMSE. Two trajectories had similar initial MMSE scores but different rates of decline. In the faster declining trajectory of the two, a higher incidence of both behavioral problems and sertraline prescription were present. CONCLUSIONS: We find suggestive evidence for association of behavioral problems and sertraline prescription with rate of decline. Further work is needed to determine whether trajectories replicate in other datasets.

Genetic Risk as a Marker of Amyloid-ß and Tau Burden in Cerebrospinal Fluid.

BACKGROUND: The search for a biomarker of Alzheimer's disease (AD) pathology (amyloid-ß (Aß) and tau) is ongoing, with the best markers currently being measurements of Aß and tau in cerebrospinal fluid (CSF) and via positron emission tomography (PET) scanning. These methods are relatively invasive, costly, and often have high screening failure rates. Consequently, research is aiming to elucidate blood biomarkers of Aß and tau. OBJECTIVE: This study aims to investigate a case/control polygenic risk score (PGRS) as a marker of tau and investigate blood markers of a combined Aß and tau outcome for the first time. A sub-study also considers plasma tau as markers of Aß and tau pathology in CSF. METHODS: We used data from the EDAR*, DESCRIPA**, and Alzheimer's Disease Neuroimaging Initiative (ADNI) cohorts in a logistic regression analysis to investigate blood markers of Aß and tau in CSF. In particular, we investigated the extent to which a case/control PGRS is predictive of CSF tau, CSF amyloid, and a combined amyloid and tau outcome. The predictive ability of models was compared to that of age, gender, and APOE genotype ('basic model'). RESULTS: In EDAR and DESCRIPA test data, inclusion of a case/control PGRS was no more predictive of Aß, and a combined Aß and tau endpoint than the basic models (accuracies of 66.0%, and 73.3% respectively). The tau model saw a small increase in accuracy compared to basic models (59.6%). ADNI 2 test data also showed a slight increase in accuracy for the Aß model when compared to the basic models (61.4%). CONCLUSION: We see some evidence that a case/control PGRS is marginally more predictive of Aß and tau pathology than the basic models. The search for predictive factors of Aß and tau pathologies, above and beyond demographic information, is still ongoing. Better understanding of AD risk alleles, development of more sensitive assays, and studies of larger sample size are three avenues that may provide such factors. However, the clinical utility of possible predictors of brain Aß and tau pathologies must also be investigated.*'Beta amyloid oligomers in the early diagnosis of AD and as marker for treatment response'**'Development of screening guidelines and criteria for pre-dementia Alzheimer's disease'.

Toward a next-generation atlas of RNA secondary structure.

RNA structure plays a crucial role in gene maturation, regulation and function. Determining the form and frequency of RNA folds is essential for a better understanding of how RNA exerts its functions. Low-throughput studies have focused on RNA primary sequences and expression levels, but with an emphasis on relatively small numbers of transcripts. However, with the recent advent of high-throughput technologies, it is realistic to begin analyzing RNA secondary structures on a genome-wide scale. Here, we review genome-wide RNA secondary structure profiles as well as advances in computational structure predictions. We further discuss the novel characteristics of RNA secondary structure across messenger RNAs. Probing RNA secondary structure by high-throughput sequencing will enable us to build atlases of RNA secondary structures, an important step in helping us to understand the versatility of RNA functions in diverse cellular processes.

A Pathway Based Classification Method for Analyzing Gene Expression for Alzheimer's Disease Diagnosis.

BACKGROUND: Recent studies indicate that gene expression levels in blood may be able to differentiate subjects with Alzheimer's disease (AD) from normal elderly controls and mild cognitively impaired (MCI) subjects. However, there is limited replicability at the single marker level. A pathway-based interpretation of gene expression may prove more robust. OBJECTIVES: This study aimed to investigate whether a case/control classification model built on pathway level data was more robust than a gene level model and may consequently perform better in test data. The study used two batches of gene expression data from the AddNeuroMed (ANM) and Dementia Case Registry (DCR) cohorts. METHODS: Our study used Illumina Human HT-12 Expression BeadChips to collect gene expression from blood samples. Random forest modeling with recursive feature elimination was used to predict case/control status. Age and APOE ɛ4 status were used as covariates for all analysis. RESULTS: Gene and pathway level models performed similarly to each other and to a model based on demographic information only. CONCLUSIONS: Any potential increase in concordance from the novel pathway level approach used here has not lead to a greater predictive ability in these datasets. However, we have only tested one method for creating pathway level scores. Further, we have been able to benchmark pathways against genes in datasets that had been extensively harmonized. Further work should focus on the use of alternative methods for creating pathway level scores, in particular those that incorporate pathway topology, and the use of an endophenotype based approach.

The Neurogenic Potential of Astrocytes Is Regulated by Inflammatory Signals.

Although the adult brain contains neural stem cells (NSCs) that generate new neurons throughout life, these astrocyte-like populations are restricted to two discrete niches. Despite their terminally differentiated phenotype, adult parenchymal astrocytes can re-acquire NSC-like characteristics following injury, and as such, these 'reactive' astrocytes offer an alternative source of cells for central nervous system (CNS) repair following injury or disease. At present, the mechanisms that regulate the potential of different types of astrocytes are poorly understood. We used in vitro and ex vivo astrocytes to identify candidate pathways important for regulation of astrocyte potential. Using in vitro neural progenitor cell (NPC)-derived astrocytes, we found that exposure of more lineage-restricted astrocytes to either tumor necrosis factor alpha (TNF-α) (via nuclear factor-κB (NFκB)) or the bone morphogenetic protein (BMP) inhibitor, noggin, led to re-acquisition of NPC properties accompanied by transcriptomic and epigenetic changes consistent with a more neurogenic, NPC-like state. Comparative analyses of microarray data from in vitro-derived and ex vivo postnatal parenchymal astrocytes identified several common pathways and upstream regulators associated with inflammation (including transforming growth factor (TGF)-ß1 and peroxisome proliferator-activated receptor gamma (PPARγ)) and cell cycle control (including TP53) as candidate regulators of astrocyte phenotype and potential. We propose that inflammatory signalling may control the normal, progressive restriction in potential of differentiating astrocytes as well as under reactive conditions and represent future targets for therapies to harness the latent neurogenic capacity of parenchymal astrocytes.

Negative symptoms in schizophrenia: a study in a large clinical sample of patients using a novel automated method.

OBJECTIVES: To identify negative symptoms in the clinical records of a large sample of patients with schizophrenia using natural language processing and assess their relationship with clinical outcomes. DESIGN: Observational study using an anonymised electronic health record case register. SETTING: South London and Maudsley NHS Trust (SLaM), a large provider of inpatient and community mental healthcare in the UK. PARTICIPANTS: 7678 patients with schizophrenia receiving care during 2011. MAIN OUTCOME MEASURES: Hospital admission, readmission and duration of admission. RESULTS: 10 different negative symptoms were ascertained with precision statistics above 0.80. 41% of patients had 2 or more negative symptoms. Negative symptoms were associated with younger age, male gender and single marital status, and with increased likelihood of hospital admission (OR 1.24, 95% CI 1.10 to 1.39), longer duration of admission (ß-coefficient 20.5 days, 7.6-33.5), and increased likelihood of readmission following discharge (OR 1.58, 1.28 to 1.95). CONCLUSIONS: Negative symptoms were common and associated with adverse clinical outcomes, consistent with evidence that these symptoms account for much of the disability associated with schizophrenia. Natural language processing provides a means of conducting research in large representative samples of patients, using data recorded during routine clinical practice.

No Evidence to Suggest that the Use of Acetylcholinesterase Inhibitors Confounds the Results of Two Blood-Based Biomarker Studies in Alzheimer's Disease.

BACKGROUND: There is an urgent need to discover Alzheimer's disease (AD) biomarkers that are both easily measured and reliable. Research into blood-based biomarkers for AD using transcriptomics and proteomics has been an attractive and promising area of research. However, to date researchers have not looked into the possibility of AD medication being a confounding factor in these studies. OBJECTIVE: This study explored whether acetylcholinesterase inhibitors (AChEIs), the main class of AD medication, are a confounding factor in AD blood biomarker studies. METHODS: The most promising blood transcriptomic and proteomic biomarkers from two recent studies were analyzed to determine if they were differentially expressed between AD subjects on AChEIs and subjects that were not. RESULTS: None of the gene or protein biomarkers analyzed were found to be significantly altered between subjects in either group. CONCLUSION: This study found no evidence that AChEIs are a confounding factor in these published AD blood biomarker studies. Further work is needed to confirm that this is also the case for other proposed biomarkers.

Identification of Adverse Drug Events from Free Text Electronic Patient Records and Information in a Large Mental Health Case Register.

OBJECTIVES: Electronic healthcare records (EHRs) are a rich source of information, with huge potential for secondary research use. The aim of this study was to develop an application to identify instances of Adverse Drug Events (ADEs) from free text psychiatric EHRs. METHODS: We used the GATE Natural Language Processing (NLP) software to mine instances of ADEs from free text content within the Clinical Record Interactive Search (CRIS) system, a de-identified psychiatric case register developed at the South London and Maudsley NHS Foundation Trust, UK. The tool was built around a set of four movement disorders (extrapyramidal side effects [EPSEs]) related to antipsychotic therapy and rules were then generalised such that the tool could be applied to additional ADEs. We report the frequencies of recorded EPSEs in patients diagnosed with a Severe Mental Illness (SMI) and then report performance in identifying eight other unrelated ADEs. RESULTS: The tool identified EPSEs with >0.85 precision and >0.86 recall during testing. Akathisia was found to be the most prevalent EPSE overall and occurred in the Asian ethnic group with a frequency of 8.13%. The tool performed well when applied to most of the non-EPSEs but least well when applied to rare conditions such as myocarditis, a condition that appears frequently in the text as a side effect warning to patients. CONCLUSIONS: The developed tool allows us to accurately identify instances of a potential ADE from psychiatric EHRs. As such, we were able to study the prevalence of ADEs within subgroups of patients stratified by SMI diagnosis, gender, age and ethnicity. In addition we demonstrated the generalisability of the application to other ADE types by producing a high precision rate on a non-EPSE related set of ADE containing documents. AVAILABILITY: The application can be found at http://git.brc.iop.kcl.ac.uk/rmallah/dystoniaml.

Ascl1 Coordinately Regulates Gene Expression and the Chromatin Landscape during Neurogenesis.

The proneural transcription factor Ascl1 coordinates gene expression in both proliferating and differentiating progenitors along the neuronal lineage. Here, we used a cellular model of neurogenesis to investigate how Ascl1 interacts with the chromatin landscape to regulate gene expression when promoting neuronal differentiation. We find that Ascl1 binding occurs mostly at distal enhancers and is associated with activation of gene transcription. Surprisingly, the accessibility of Ascl1 to its binding sites in neural stem/progenitor cells remains largely unchanged throughout their differentiation, as Ascl1 targets regions of both readily accessible and closed chromatin in proliferating cells. Moreover, binding of Ascl1 often precedes an increase in chromatin accessibility and the appearance of new regions of open chromatin, associated with de novo gene expression during differentiation. Our results reveal a function of Ascl1 in promoting chromatin accessibility during neurogenesis, linking the chromatin landscape at Ascl1 target regions with the temporal progression of its transcriptional program.

Alzheimer's disease biomarker discovery using SOMAscan multiplexed protein technology.

Blood proteins and their complexes have become the focus of a great deal of interest in the context of their potential as biomarkers of Alzheimer's disease (AD). We used a SOMAscan assay for quantifying 1001 proteins in blood samples from 331 AD, 211 controls, and 149 mild cognitive impaired (MCI) subjects. The strongest associations of protein levels with AD outcomes were prostate-specific antigen complexed to α1-antichymotrypsin (AD diagnosis), pancreatic prohormone (AD diagnosis, left entorhinal cortex atrophy, and left hippocampus atrophy), clusterin (rate of cognitive decline), and fetuin B (left entorhinal atrophy). Multivariate analysis found that a subset of 13 proteins predicted AD with an accuracy of area under the curve of 0.70. Our replication of previous findings provides further evidence that levels of these proteins in plasma are truly associated with AD. The newly identified proteins could be potential biomarkers and are worthy of further investigation.

Candidate blood proteome markers of Alzheimer's disease onset and progression: a systematic review and replication study.

A blood-based protein biomarker, or set of protein biomarkers, that could predict onset and progression of Alzheimer's disease (AD) would have great utility; potentially clinically, but also for clinical trials and especially in the selection of subjects for preventative trials. We reviewed a comprehensive list of 21 published discovery or panel-based (> 100 proteins) blood proteomics studies of AD, which had identified a total of 163 candidate biomarkers. Few putative blood-based protein biomarkers replicate in independent studies but we found that some proteins do appear in multiple studies; for example, four candidate biomarkers are found to associate with AD-related phenotypes in five independent research cohorts in these 21 studies: α-1-antitrypsin, α-2-macroglobulin, apolipoprotein E, and complement C3. Using SomaLogic's SOMAscan proteomics technology, we were able to conduct a large-scale replication study for 94 of the 163 candidate biomarkers from these 21 published studies in plasma samples from 677 subjects from the AddNeuroMed (ANM) and the Alzheimer's Research UK/Maudsley BRC Dementia Case Registry at King's Health Partners (ARUK/DCR) research cohorts. Nine of the 94 previously reported candidates were found to associate with AD-related phenotypes (False Discovery Rate (FDR) q-value < 0.1). These proteins show sufficient replication to be considered for further investigation as a biomarker set. Overall, we show that there are some signs of a replicable signal in the range of proteins identified in previous studies and we are able to further replicate some of these. This suggests that AD pathology does affect the blood proteome with some consistency.

BBGRE: brain and body genetic resource exchange.

Studies of copy number variation (genomic imbalance) are providing insight into both complex and Mendelian genetic disorders. Array comparative genomic hybridization (array CGH), a tool for detecting copy number variants at a resolution previously unattainable in clinical diagnostics, is increasingly used as a first-line test at clinical genetics laboratories. Many copy number variants are of unknown significance; correlation and comparison with other patients will therefore be essential for interpretation. We present a resource for clinicians and researchers to identify specific copy number variants and associated phenotypes in patients from a single catchment area, tested using array CGH at the SE Thames Regional Genetics Centre, London. User-friendly searching is available, with links to external resources, providing a powerful tool for the elucidation of gene function. We hope to promote research by facilitating interactions between researchers and patients. The BBGRE (Brain and Body Genetic Resource Exchange) resource can be accessed at the following website: http://bbgre.org DATABASE URL: http://bbgre.org.

An epigenetic signature of developmental potential in neural stem cells and early neurons.

A cardinal property of neural stem cells (NSCs) is their ability to adopt multiple fates upon differentiation. The epigenome is widely seen as a read-out of cellular potential and a manifestation of this can be seen in embryonic stem cells (ESCs), where promoters of many lineage-specific regulators are marked by a bivalent epigenetic signature comprising trimethylation of both lysine 4 and lysine 27 of histone H3 (H3K4me3 and H3K27me3, respectively). Bivalency has subsequently emerged as a powerful epigenetic indicator of stem cell potential. Here, we have interrogated the epigenome during differentiation of ESC-derived NSCs to immature GABAergic interneurons. We show that developmental transitions are accompanied by loss of bivalency at many promoters in line with their increasing developmental restriction from pluripotent ESC through multipotent NSC to committed GABAergic interneuron. At the NSC stage, the promoters of genes encoding many transcriptional regulators required for differentiation of multiple neuronal subtypes and neural crest appear to be bivalent, consistent with the broad developmental potential of NSCs. Upon differentiation to GABAergic neurons, all non-GABAergic promoters resolve to H3K27me3 monovalency, whereas GABAergic promoters resolve to H3K4me3 monovalency or retain bivalency. Importantly, many of these epigenetic changes occur before any corresponding changes in gene expression. Intriguingly, another group of gene promoters gain bivalency as NSCs differentiate toward neurons, the majority of which are associated with functions connected with maturation and establishment and maintenance of connectivity. These data show that bivalency provides a dynamic epigenetic signature of developmental potential in both NSCs and in early neurons.

A blood gene expression marker of early Alzheimer's disease.

A marker of Alzheimer's disease (AD) that can accurately diagnose disease at the earliest stage would significantly support efforts to develop treatments for early intervention. We have sought to determine the sensitivity and specificity of peripheral blood gene expression as a diagnostic marker of AD using data generated on HT-12v3 BeadChips. We first developed an AD diagnostic classifier in a training cohort of 78 AD and 78 control blood samples and then tested its performance in a validation group of 26 AD and 26 control and 118 mild cognitive impairment (MCI) subjects who were likely to have an AD-endpoint. A 48 gene classifier achieved an accuracy of 75% in the AD and control validation group. Comparisons were made with a classifier developed using structural MRI measures, where both measures were available in the same individuals. In AD and control subjects, the gene expression classifier achieved an accuracy of 70% compared to 85% using MRI. Bootstrapping validation produced expression and MRI classifiers with mean accuracies of 76% and 82%, respectively, demonstrating better concordance between these two classifiers than achieved in a single validation population. We conclude there is potential for blood expression to be a marker for AD. The classifier also predicts a large number of people with MCI, who are likely to develop AD, are more AD-like than normal with 76% of subjects classified as AD rather than control. Many of these people do not have overt brain atrophy, which is known to emerge around the time of AD diagnosis, suggesting the expression classifier may detect AD earlier in the prodromal phase. However, we accept these results could also represent a marker of diseases sharing common etiology.

Dysregulation of REST-regulated coding and non-coding RNAs in a cellular model of Huntington's disease.

Huntingtin (Htt) protein interacts with many transcriptional regulators, with widespread disruption to the transcriptome in Huntington's disease (HD) brought about by altered interactions with the mutant Htt (muHtt) protein. Repressor Element-1 Silencing Transcription Factor (REST) is a repressor whose association with Htt in the cytoplasm is disrupted in HD, leading to increased nuclear REST and concomitant repression of several neuronal-specific genes, including brain-derived neurotrophic factor (Bdnf). Here, we explored a wide set of HD dysregulated genes to identify direct REST targets whose expression is altered in a cellular model of HD but that can be rescued by knock-down of REST activity. We found many direct REST target genes encoding proteins important for nervous system development, including a cohort involved in synaptic transmission, at least two of which can be rescued at the protein level by REST knock-down. We also identified several microRNAs (miRNAs) whose aberrant repression is directly mediated by REST, including miR-137, which has not previously been shown to be a direct REST target in mouse. These data provide evidence of the contribution of inappropriate REST-mediated transcriptional repression to the widespread changes in coding and non-coding gene expression in a cellular model of HD that may affect normal neuronal function and survival.

Plasma based markers of [11C] PiB-PET brain amyloid burden.

Changes in brain amyloid burden have been shown to relate to Alzheimer's disease pathology, and are believed to precede the development of cognitive decline. There is thus a need for inexpensive and non-invasive screening methods that are able to accurately estimate brain amyloid burden as a marker of Alzheimer's disease. One potential method would involve using demographic information and measurements on plasma samples to establish biomarkers of brain amyloid burden; in this study data from the Alzheimer's Disease Neuroimaging Initiative was used to explore this possibility. Sixteen of the analytes on the Rules Based Medicine Human Discovery Multi-Analyte Profile 1.0 panel were found to associate with [(11)C]-PiB PET measurements. Some of these markers of brain amyloid burden were also found to associate with other AD related phenotypes. Thirteen of these markers of brain amyloid burden--c-peptide, fibrinogen, alpha-1-antitrypsin, pancreatic polypeptide, complement C3, vitronectin, cortisol, AXL receptor kinase, interleukin-3, interleukin-13, matrix metalloproteinase-9 total, apolipoprotein E and immunoglobulin E--were used along with co-variates in multiple linear regression, and were shown by cross-validation to explain >30% of the variance of brain amyloid burden. When a threshold was used to classify subjects as PiB positive, the regression model was found to predict actual PiB positive individuals with a sensitivity of 0.918 and a specificity of 0.545. The number of APOE [Symbol: see text] 4 alleles and plasma apolipoprotein E level were found to contribute most to this model, and the relationship between these variables and brain amyloid burden was explored.

Repressor element 1 silencing transcription factor couples loss of pluripotency with neural induction and neural differentiation.

Neural differentiation of embryonic stem cells (ESCs) requires coordinated repression of the pluripotency regulatory program and reciprocal activation of the neurogenic regulatory program. Upon neural induction, ESCs rapidly repress expression of pluripotency genes followed by staged activation of neural progenitor and differentiated neuronal and glial genes. The transcriptional factors that underlie maintenance of pluripotency are partially characterized whereas those underlying neural induction are much less explored, and the factors that coordinate these two developmental programs are completely unknown. One transcription factor, REST (repressor element 1 silencing transcription factor), has been linked with terminal differentiation of neural progenitors and more recently, and controversially, with control of pluripotency. Here, we show that in the absence of REST, coordination of pluripotency and neural induction is lost and there is a resultant delay in repression of pluripotency genes and a precocious activation of both neural progenitor and differentiated neuronal and glial genes. Furthermore, we show that REST is not required for production of radial glia-like progenitors but is required for their subsequent maintenance and differentiation into neurons, oligodendrocytes, and astrocytes. We propose that REST acts as a regulatory hub that coordinates timely repression of pluripotency with neural induction and neural differentiation.

A novel function of the proneural factor Ascl1 in progenitor proliferation identified by genome-wide characterization of its targets.

Proneural genes such as Ascl1 are known to promote cell cycle exit and neuronal differentiation when expressed in neural progenitor cells. The mechanisms by which proneural genes activate neurogenesis--and, in particular, the genes that they regulate--however, are mostly unknown. We performed a genome-wide characterization of the transcriptional targets of Ascl1 in the embryonic brain and in neural stem cell cultures by location analysis and expression profiling of embryos overexpressing or mutant for Ascl1. The wide range of molecular and cellular functions represented among these targets suggests that Ascl1 directly controls the specification of neural progenitors as well as the later steps of neuronal differentiation and neurite outgrowth. Surprisingly, Ascl1 also regulates the expression of a large number of genes involved in cell cycle progression, including canonical cell cycle regulators and oncogenic transcription factors. Mutational analysis in the embryonic brain and manipulation of Ascl1 activity in neural stem cell cultures revealed that Ascl1 is indeed required for normal proliferation of neural progenitors. This study identified a novel and unexpected activity of the proneural gene Ascl1, and revealed a direct molecular link between the phase of expansion of neural progenitors and the subsequent phases of cell cycle exit and neuronal differentiation.

T-cell infiltration and signaling in the adult dorsal spinal cord is a major contributor to neuropathic pain-like hypersensitivity.

Partial peripheral nerve injury in adult rats results in neuropathic pain-like hypersensitivity, while that in neonatal rats does not, a phenomenon also observed in humans. We therefore compared gene expression profiles in the dorsal horn of adult and neonatal rats in response to the spared nerve injury (SNI) model of peripheral neuropathic pain. The 148 differentially regulated genes in adult, but not young, rat spinal cords indicate a greater microglial and T-cell response in adult than in young animals. T-cells show a large infiltration in the adult dorsal horn but not in the neonate after SNI. T-cell-deficient Rag1-null adult mice develop less neuropathic mechanical allodynia than controls, and central expression of cytokines involved in T-cell signaling exhibits large relative differences between young and adult animals after SNI. One such cytokine, interferon-gamma (IFNgamma), is upregulated in the dorsal horn after nerve injury in the adult but not neonate, and we show that IFNgamma signaling is required for full expression of adult neuropathic hypersensitivity. These data reveal that T-cell infiltration and activation in the dorsal horn of the spinal cord following peripheral nerve injury contribute to the evolution of neuropathic pain-like hypersensitivity. The neuroimmune interaction following peripheral nerve injury has therefore a substantial adaptive immune component, which is absent or suppressed in the young CNS.

Establishing a major cause of discrepancy in the calibration of Affymetrix GeneChips.

BACKGROUND: Affymetrix GeneChips are a popular platform for performing whole-genome experiments on the transcriptome. There are a range of different calibration steps, and users are presented with choices of different background subtractions, normalisations and expression measures. We wished to establish which of the calibration steps resulted in the biggest uncertainty in the sets of genes reported to be differentially expressed. RESULTS: Our results indicate that the sets of genes identified as being most significantly differentially expressed, as estimated by the z-score of fold change, is relatively insensitive to the choice of background subtraction and normalisation. However, the contents of the gene list are most sensitive to the choice of expression measure. This is irrespective of whether the experiment uses a rat, mouse or human chip and whether the chip definition is made using probe mappings from Unigene, RefSeq, Entrez Gene or the original Affymetrix definitions. It is also irrespective of whether both Present and Absent, or just Present, Calls from the MAS5 algorithm are used to filter genelists, and this conclusion holds for genes of differing intensities. We also reach the same conclusion after assigning genes to be differentially expressed using t-statistics, although this approach results in a large amount of false positives in the sets of genes identified due to the small numbers of replicates typically used in microarray experiments. CONCLUSION: The major calibration uncertainty that biologists need to consider when analysing Affymetrix data is how their multiple probe values are condensed into one expression measure.