Metabolic and Innate Immune Cues Merge into a Specific Inflammatory Response via the UPR.

Innate immune responses are intricately linked with intracellular metabolism of myeloid cells. Toll-like receptor (TLR) stimulation shifts intracellular metabolism toward glycolysis, while anti-inflammatory signals depend on enhanced mitochondrial respiration. How exogenous metabolic signals affect the immune response is unknown. We demonstrate that TLR-dependent responses of dendritic cells (DCs) are exacerbated by a high-fatty-acid (FA) metabolic environment. FAs suppress the TLR-induced hexokinase activity and perturb tricarboxylic acid cycle metabolism. These metabolic changes enhance mitochondrial reactive oxygen species (mtROS) production and, in turn, the unfolded protein response (UPR), leading to a distinct transcriptomic signature with IL-23 as hallmark. Interestingly, chemical or genetic suppression of glycolysis was sufficient to induce this specific immune response. Conversely, reducing mtROS production or DC-specific deficiency in XBP1 attenuated IL-23 expression and skin inflammation in an IL-23-dependent model of psoriasis. Thus, fine-tuning of innate immunity depends on optimization of metabolic demands and minimization of mtROS-induced UPR.

An extended transcription factor regulatory network controls hepatocyte identity.

Cell identity is specified by a core transcriptional regulatory circuitry (CoRC), typically limited to a small set of interconnected cell-specific transcription factors (TFs). By mining global hepatic TF regulons, we reveal a more complex organization of the transcriptional regulatory network controlling hepatocyte identity. We show that tight functional interconnections controlling hepatocyte identity extend to non-cell-specific TFs beyond the CoRC, which we call hepatocyte identity (Hep-ID)CONNECT TFs. Besides controlling identity effector genes, Hep-IDCONNECT TFs also engage in reciprocal transcriptional regulation with TFs of the CoRC. In homeostatic basal conditions, this translates into Hep-IDCONNECT TFs being involved in fine tuning CoRC TF expression including their rhythmic expression patterns. Moreover, a role for Hep-IDCONNECT TFs in the control of hepatocyte identity is revealed in dedifferentiated hepatocytes where Hep-IDCONNECT TFs are able to reset CoRC TF expression. This is observed upon activation of NR1H3 or THRB in hepatocarcinoma or in hepatocytes subjected to inflammation-induced loss of identity. Our study establishes that hepatocyte identity is controlled by an extended array of TFs beyond the CoRC.

Biomarkers of haemodynamic severity of systemic sclerosis-associated pulmonary arterial hypertension by serum proteome analysis.

OBJECTIVES: To mine the serum proteome of patients with systemic sclerosis-associated pulmonary arterial hypertension (SSc-PAH) and to detect biomarkers that may assist in earlier and more effective diagnosis and treatment. METHODS: Patients with limited cutaneous SSc, no extensive interstitial lung disease and no PAH-specific therapy were included. They were classified as cases if they had PAH confirmed by right heart catheterisation (RHC) and serum collected on the same day as RHC; and as controls if they had no clinical evidence of PAH. RESULTS: Patients were mostly middle-aged females with anticentromere-associated SSc. Among 1129 proteins assessed by a high-throughput proteomic assay (SOMAscan), only 2 were differentially expressed and correlated significantly with pulmonary vascular resistance (PVR) in SSc-PAH patients (n=15): chemerin (ρ=0.62, p=0.01) and SET (ρ=0.62, p=0.01). To validate these results, serum levels of chemerin were measured by ELISA in an independent cohort. Chemerin levels were confirmed to be significantly higher (p=0.01) and correlate with PVR (ρ=0.42, p=0.04) in SSc-PAH patients (n=24). Chemerin mRNA expression was detected in fibroblasts, pulmonary artery smooth muscle cells (PA-SMCs)/pericytes and mesothelial cells in SSc-PAH lungs by single-cell RNA-sequencing. Confocal immunofluorescence revealed increased expression of a chemerin receptor, CMKLR1, on SSc-PAH PA-SMCs. SSc-PAH serum seemed to induce higher PA-SMC proliferation than serum from SSc patients without PAH. This difference appeared neutralised when adding the CMKLR1 inhibitor α-NETA. CONCLUSION: Chemerin seems an interesting surrogate biomarker for PVR in SSc-PAH. Increased chemerin serum levels and CMKLR1 expression by PA-SMCs may contribute to SSc-PAH pathogenesis by inducing PA-SMC proliferation.

The logic of transcriptional regulator recruitment architecture at cis-regulatory modules controlling liver functions.

Control of gene transcription relies on concomitant regulation by multiple transcriptional regulators (TRs). However, how recruitment of a myriad of TRs is orchestrated at cis-regulatory modules (CRMs) to account for coregulation of specific biological pathways is only partially understood. Here, we have used mouse liver CRMs involved in regulatory activities of the hepatic TR, NR1H4 (FXR; farnesoid X receptor), as our model system to tackle this question. Using integrative cistromic, epigenomic, transcriptomic, and interactomic analyses, we reveal a logical organization where trans-regulatory modules (TRMs), which consist of subsets of preferentially and coordinately corecruited TRs, assemble into hierarchical combinations at hepatic CRMs. Different combinations of TRMs add to a core TRM, broadly found across the whole landscape of CRMs, to discriminate promoters from enhancers. These combinations also specify distinct sets of CRM differentially organized along the genome and involved in regulation of either housekeeping/cellular maintenance genes or liver-specific functions. In addition to these TRMs which we define as obligatory, we show that facultative TRMs, such as one comprising core circadian TRs, are further recruited to selective subsets of CRMs to modulate their activities. TRMs transcend TR classification into ubiquitous versus liver-identity factors, as well as TR grouping into functional families. Hence, hierarchical superimpositions of obligatory and facultative TRMs bring about independent transcriptional regulatory inputs defining different sets of CRMs with logical connection to regulation of specific gene sets and biological pathways. Altogether, our study reveals novel principles of concerted transcriptional regulation by multiple TRs at CRMs.

A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis.

During the last 3 years, a number of approaches for the normalization of RNA sequencing data have emerged in the literature, differing both in the type of bias adjustment and in the statistical strategy adopted. However, as data continue to accumulate, there has been no clear consensus on the appropriate normalization method to be used or the impact of a chosen method on the downstream analysis. In this work, we focus on a comprehensive comparison of seven recently proposed normalization methods for the differential analysis of RNA-seq data, with an emphasis on the use of varied real and simulated datasets involving different species and experimental designs to represent data characteristics commonly observed in practice. Based on this comparison study, we propose practical recommendations on the appropriate normalization method to be used and its impact on the differential analysis of RNA-seq data.

Differential meta-analysis of RNA-seq data from multiple studies.

BACKGROUND: High-throughput sequencing is now regularly used for studies of the transcriptome (RNA-seq), particularly for comparisons among experimental conditions. For the time being, a limited number of biological replicates are typically considered in such experiments, leading to low detection power for differential expression. As their cost continues to decrease, it is likely that additional follow-up studies will be conducted to re-address the same biological question. RESULTS: We demonstrate how p-value combination techniques previously used for microarray meta-analyses can be used for the differential analysis of RNA-seq data from multiple related studies. These techniques are compared to a negative binomial generalized linear model (GLM) including a fixed study effect on simulated data and real data on human melanoma cell lines. The GLM with fixed study effect performed well for low inter-study variation and small numbers of studies, but was outperformed by the meta-analysis methods for moderate to large inter-study variability and larger numbers of studies. CONCLUSIONS: The p-value combination techniques illustrated here are a valuable tool to perform differential meta-analyses of RNA-seq data by appropriately accounting for biological and technical variability within studies as well as additional study-specific effects. An R package metaRNASeq is available on the CRAN (http://cran.r-project.org/web/packages/metaRNASeq).

MPAgenomics: an R package for multi-patient analysis of genomic markers.

BACKGROUND: Last generations of Single Nucleotide Polymorphism (SNP) arrays allow to study copy-number variations in addition to genotyping measures. RESULTS: MPAgenomics, standing for multi-patient analysis (MPA) of genomic markers, is an R-package devoted to: (i) efficient segmentation and (ii) selection of genomic markers from multi-patient copy number and SNP data profiles. It provides wrappers from commonly used packages to streamline their repeated (sometimes difficult) manipulation, offering an easy-to-use pipeline for beginners in R.The segmentation of successive multiple profiles (finding losses and gains) is performed with an automatic choice of parameters involved in the wrapped packages. Considering multiple profiles in the same time, MPAgenomics wraps efficient penalized regression methods to select relevant markers associated with a given outcome. CONCLUSIONS: MPAgenomics provides an easy tool to analyze data from SNP arrays in R. The R-package MPAgenomics is available on CRAN.

Toxoplasma transcription factor TgAP2XI-5 regulates the expression of genes involved in parasite virulence and host invasion.

Gene regulation in apicomplexan parasites, a phylum containing important protozoan parasites such as Plasmodium and Toxoplasma, is poorly understood. The life cycle of Toxoplasma gondii is complex, with multiple proliferation and differentiation steps, of which tachyzoite proliferation is the most relevant to pathogenesis in humans and animals. Tachyzoites express invasion and virulence factors that are crucial for their survival and manipulation of host cell functions. The expression of those factors is tightly controlled during the tachyzoite cell cycle to permit their correct packaging in newly formed apical secretory organelles named micronemes and rhoptries in the daughter cells. However, little is known about the factors that control the expression of genes encoding the virulence factors present in these parasite-specific secretory organelles. We report that the plant-like nuclear factor TgAP2XI-5 targets more than 300 gene promoters and actively controls the transcription of these genes. Most of these target genes, including those that are essential for parasite virulence, showed a peak of expression in the S and M phases of the cell cycle. Furthermore, we identified the cis-regulatory element recognized by TgAP2XI-5 and demonstrated its ability to actively drive gene transcription. Our results demonstrated that TgAP2XI-5 is a novel DNA sequence-specific transcription factor associated with promoter activation. TgAP2XI-5 may regulate gene transcription of crucial virulence factors in T. gondii.

Identification of a gene signature of a pre-transformation process by senescence evasion in normal human epidermal keratinocytes.

BACKGROUND: Epidemiological data show that the incidence of carcinomas in humans is highly dependent on age. However, the initial steps of the age-related molecular oncogenic processes by which the switch towards the neoplastic state occurs remain poorly understood, mostly due to the absence of powerful models. In a previous study, we showed that normal human epidermal keratinocytes (NHEKs) spontaneously and systematically escape from senescence to give rise to pre-neoplastic emerging cells. METHODS: Here, this model was used to analyze the gene expression profile associated with the early steps of age-related cell transformation. We compared the gene expression profiles of growing or senescent NHEKs to post-senescent emerging cells. Data analyses were performed by using the linear modeling features of the limma package, resulting in a two-sided t test or F-test based on moderated statistics. The p-values were adjusted for multiple testing by controlling the false discovery rate according to Benjamini Hochberg method.The common gene set resulting of differential gene expression profiles from these two comparisons revealed a post-senescence neoplastic emergence (PSNE) gene signature of 286 genes. RESULTS: About half of these genes were already reported as involved in cancer or premalignant skin diseases. However, bioinformatics analyses did not highlight inside this signature canonical cancer pathways but metabolic pathways, including in first line the metabolism of xenobiotics by cytochrome P450. In order to validate the relevance of this signature as a signature of pretransformation by senescence evasion, we invalidated two components of the metabolism of xenobiotics by cytochrome P450, AKR1C2 and AKR1C3. When performed at the beginning of the senescence plateau, this invalidation did not alter the senescent state itself but significantly decreased the frequency of PSNE. Conversely, overexpression of AKR1C2 but not AKR1C3 increased the frequency of PSNE. CONCLUSIONS: To our knowledge, this study is the first to identify reprogrammation of metabolic pathways in normal keratinocytes as a potential determinant of the switch from senescence to pre-transformation.

Performance of non-invasive tests for liver fibrosis resolution after bariatric surgery.

BACKGROUND & AIMS: The value of non-invasive tests for monitoring the resolution of significant liver fibrosis after treatment is poorly investigated. We compared the performances of six non-invasive tests to predict the resolution of significant fibrosis after bariatric surgery. METHODS: Participants were individuals with obesity submitted to needle liver biopsy at the time of bariatric surgery, and 12 and/or 60 months after surgery. We calculated the fibrosis-4 index (FIB-4), NAFLD fibrosis score (NFS), AST to platelet ratio index (APRI), Hepatic fibrosis score (HFS), Fibrotic NASH index (FNI), and Liver risk score (LRS) at each time point, and compared their performances for predicting significant fibrosis (F ≥ 2) and its resolution following surgery. RESULTS: At baseline, 2436 patients had liver biopsy, including 261 (10.7 %) with significant fibrosis. Overall, 672 patients had pre- and post-operative biopsies (564 at M12 and 328 at M60). The fibrosis stage decreased at M12 and M60 (p < 0.001 vs M0). Resolution of significant fibrosis occurred in 58/121 (47.9 %) at M12 and 32/50 (64 %) at M60. The mean value of all tests decreased after surgery, except for FIB-4. Performances for predicting fibrosis resolution was higher at M60 than at M12 for all tests, and maximal at M60 for FNI and LRS: area under the curve 0.843 (95%CI 0.71-0.95) and 0.92 (95%CI 0.84-1.00); positive likelihood ratio 3.75 (95 % CI 1.33-10.59) and 4.58 (95 % CI 1.65-12.70), respectively. CONCLUSIONS: Results showed the value and limits of non-invasive tests for monitoring the evolution of liver fibrosis after an intervention. Following bariatric surgery, the best performances to predict the resolution of significant fibrosis were observed at M60 with tests combining liver and metabolic traits, namely FNI and LRS.

Induction of AML cell differentiation using HOXA9/DNA binding inhibitors as a potential therapeutic option for HOXA9-dependent AML.

The mainstay of acute myeloid leukemia (AML) treatment still relies on traditional chemotherapy, with a survival rate of approximately 30% for patients under 65 years of age and as low as 5% for those beyond. This unfavorable prognosis primarily stems from frequent relapses, resistance to chemotherapy, and limited approved targeted therapies for specific AML subtypes. Around 70% of all AML cases show overexpression of the transcription factor HOXA9, which is associated with a poor prognosis, increased chemoresistance, and higher relapse rates. However, direct targeting of HOXA9 in a clinical setting has not been achieved yet. The dysregulation caused by the leukemic HOXA9 transcription factor primarily results from its binding activity to DNA, leading to differentiation blockade. Our previous investigations have identified two HOXA9/DNA binding competitors, namely DB1055 and DB818. We assessed their antileukemic effects in comparison to HOXA9 knockdown or cytarabine treatment. Using human AML cell models, DB1055 and DB818 induced in vitro cell growth reduction, death, differentiation, and common transcriptomic deregulation but did not impact human CD34+ bone marrow cells. Furthermore, DB1055 and DB818 exhibited potent antileukemic activities in a human THP-1 AML in vivo model, leading to the differentiation of monocytes into macrophages. In vitro assays also demonstrated the efficacy of DB1055 and DB818 against AML blasts from patients, with DB1055 successfully reducing leukemia burden in patient-derived xenografts in NSG immunodeficient mice. Our findings indicate that inhibiting HOXA9/DNA interaction using DNA ligands may offer a novel differentiation therapy for the future treatment of AML patients dependent on HOXA9.

Identification of patient subtypes based on protein expression for prediction of heart failure after myocardial infarction.

This study investigates the ability of high-throughput aptamer-based platform to identify circulating biomarkers able to predict occurrence of heart failure (HF), in blood samples collected during hospitalization of patients suffering from a first myocardial infarction (MI). REVE-1 (derivation) and REVE-2 (validation) cohorts included respectively 254 and 238 patients, followed up respectively 9 · 2 ± 4 · 8 and 7 · 6 ± 3 · 0 years. A blood sample collected during hospitalization was used for quantifying 4,668 proteins. Fifty proteins were significantly associated with long-term occurrence of HF with all-cause death as the competing event. k-means, an unsupervised clustering method, identified two groups of patients based on expression levels of the 50 proteins. Group 2 was significantly associated with a higher risk of HF in both cohorts. These results showed that a subset of 50 selected proteins quantified during hospitalization of MI patients is able to stratify and predict the long-term occurrence of HF.

A Novel 8-Predictors Signature to Predict Complicated Disease Course in Pediatric-onset Crohn's Disease: A Population-based Study.

BACKGROUND: The identification of patients at high risk of a disabling disease course would be invaluable in guiding initial therapy in Crohn's disease (CD). Our objective was to evaluate a combination of clinical, serological, and genetic factors to predict complicated disease course in pediatric-onset CD. METHODS: Data for pediatric-onset CD patients, diagnosed before 17 years of age between 1988 and 2004 and followed more than 5 years, were extracted from the population-based EPIMAD registry. The main outcome was defined by the occurrence of complicated behavior (stricturing or penetrating) and/or intestinal resection within the 5 years following diagnosis. Lasso logistic regression models were used to build a predictive model based on clinical data at diagnosis, serological data (ASCA, pANCA, anti-OmpC, anti-Cbir1, anti-Fla2, anti-Flax), and 369 candidate single nucleotide polymorphisms. RESULTS: In total, 156 children with an inflammatory (B1) disease at diagnosis were included. Among them, 35% (n = 54) progressed to a complicated behavior or an intestinal resection within the 5 years following diagnosis. The best predictive model (PREDICT-EPIMAD) included the location at diagnosis, pANCA, and 6 single nucleotide polymorphisms. This model showed good discrimination and good calibration, with an area under the curve of 0.80 after correction for optimism bias (sensitivity, 79%, specificity, 74%, positive predictive value, 61%, negative predictive value, 87%). Decision curve analysis confirmed the clinical utility of the model. CONCLUSIONS: A combination of clinical, serotypic, and genotypic variables can predict disease progression in this population-based pediatric-onset CD cohort. Independent validation is needed before it can be used in clinical practice.

Hepatitis C virus alters the morphology and function of peroxisomes.

Despite the introduction of effective treatments for hepatitis C in clinics, issues remain regarding the liver disease induced by chronic hepatitis C virus (HCV) infection. HCV is known to disturb the metabolism of infected cells, especially lipid metabolism and redox balance, but the mechanisms leading to HCV-induced pathogenesis are still poorly understood. In an APEX2-based proximity biotinylation screen, we identified ACBD5, a peroxisome membrane protein, as located in the vicinity of HCV replication complexes. Confocal microscopy confirmed the relocation of peroxisomes near HCV replication complexes and indicated that their morphology and number are altered in approximately 30% of infected Huh-7 cells. Peroxisomes are small versatile organelles involved among other functions in lipid metabolism and ROS regulation. To determine their importance in the HCV life cycle, we generated Huh-7 cells devoid of peroxisomes by inactivating the PEX5 and PEX3 genes using CRISPR/Cas9 and found that the absence of peroxisomes had no impact on replication kinetics or infectious titers of HCV strains JFH1 and DBN3a. The impact of HCV on peroxisomal functions was assessed using sub-genomic replicons. An increase of ROS was measured in peroxisomes of replicon-containing cells, correlated with a significant decrease of catalase activity with the DBN3a strain. In contrast, HCV replication had little to no impact on cytoplasmic and mitochondrial ROS, suggesting that the redox balance of peroxisomes is specifically impaired in cells replicating HCV. Our study provides evidence that peroxisome function and morphology are altered in HCV-infected cells.

Combining diabetes, sex, and menopause as meaningful clinical features associated with NASH and liver fibrosis in individuals with class II and III obesity: A retrospective cohort study.

OBJECTIVE: Steatotic liver disease (SLD) is frequent in individuals with obesity. In this study, type 2 diabetes (T2D), sex, and menopausal status were combined to refine the stratification of obesity regarding the risk of advanced SLD and gain further insight into disease physiopathology. METHODS: This study enrolled 1446 participants with obesity from the ABOS cohort (NCT01129297), who underwent extensive phenotyping, including liver histology and transcriptome profiling. Hierarchical clustering was applied to classify participants. The prevalence of metabolic disorders associated with steatohepatitis (NASH) and liver fibrosis (F ≥ 2) was determined within each identified subgroup and aligned to clinical and biological characteristics. RESULTS: The prevalence of NASH and F ≥ 2 was, respectively, 9.5% (N = 138/1446) and 11.7% (N = 159/1365) in the overall population, 20.3% (N = 107/726) and 21.1% (N = 106/502) in T2D patients, and 3.4% (N = 31/920) and 6.1% (N = 53/863) in non-T2D patients. NASH and F ≥ 2 prevalence was 15.4% (33/215) and 15.5% (32/206) among premenopausal women with T2D vs. 29.5% (33/112) and 30.3% (N = 36/119) in postmenopausal women with T2D (p < 0.01); and 21.0% (21/100) / 27.0% (24/89) in men with T2D ≥ age 50 years and 17.9% (17/95) / 18.5% (17/92) in men with T2D < age 50 years (NS). The distinct contribution of menopause was confirmed by the interaction between sex and age with respect to NASH among T2D patients (p = 0.048). Finally, several NASH-associated biological traits (lower platelet count; higher serum uric acid; gamma-glutamyl transferase; aspartate aminotransferase) and liver expressed genes AKR1B10 and CCL20 were significantly associated with menopause in women with T2D but not with age in men with T2D. CONCLUSIONS: This study unveiled a remarkably high prevalence of advanced SLD after menopause in women with T2D, associated with a dysfunctional biological liver profile.

Effects of Immunoglobulins G From Systemic Sclerosis Patients in Normal Dermal Fibroblasts: A Multi-Omics Study.

Autoantibodies (Aabs) are frequent in systemic sclerosis (SSc). Although recognized as potent biomarkers, their pathogenic role is debated. This study explored the effect of purified immunoglobulin G (IgG) from SSc patients on protein and mRNA expression of dermal fibroblasts (FBs) using an innovative multi-omics approach. Dermal FBs were cultured in the presence of sera or purified IgG from patients with diffuse cutaneous SSc (dcSSc), limited cutaneous SSc or healthy controls (HCs). The FB proteome and transcriptome were explored using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) and microarray assays, respectively. Proteomic analysis identified 3,310 proteins. SSc sera and purified IgG induced singular protein profile patterns. These FB proteome changes depended on the Aab serotype, with a singular effect observed with purified IgG from anti-topoisomerase-I autoantibody (ATA) positive patients compared to HC or other SSc serotypes. IgG from ATA positive SSc patients induced enrichment in proteins involved in focal adhesion, cadherin binding, cytosolic part, or lytic vacuole. Multi-omics analysis was performed in two ways: first by restricting the analysis of the transcriptomic data to differentially expressed proteins; and secondly, by performing a global statistical analysis integrating proteomics and transcriptomics. Transcriptomic analysis distinguished 764 differentially expressed genes and revealed that IgG from dcSSc can induce extracellular matrix (ECM) remodeling changes in gene expression profiles in FB. Global statistical analysis integrating proteomics and transcriptomics confirmed that IgG from SSc can induce ECM remodeling and activate FB profiles. This effect depended on the serotype of the patient, suggesting that SSc Aab might play a pathogenic role in some SSc subsets.

TgAP2IX-5 is a key transcriptional regulator of the asexual cell cycle division in Toxoplasma gondii.

Apicomplexan parasites have evolved efficient and distinctive strategies for intracellular replication where the timing of emergence of the daughter cells (budding) is a decisive element. However, the molecular mechanisms that provide the proper timing of parasite budding remain unknown. Using Toxoplasma gondii as a model Apicomplexan, we identified a master regulator that controls the timing of the budding process. We show that an ApiAP2 transcription factor, TgAP2IX-5, controls cell cycle events downstream of centrosome duplication. TgAP2IX-5 binds to the promoter of hundreds of genes and controls the activation of the budding-specific cell cycle expression program. TgAP2IX-5 regulates the expression of specific transcription factors that are necessary for the completion of the budding cycle. Moreover, TgAP2IX-5 acts as a limiting factor that ensures that asexual proliferation continues by promoting the inhibition of the differentiation pathway. Therefore, TgAP2IX-5 is a master regulator that controls both cell cycle and developmental pathways.

Moderated effect size and P-value combinations for microarray meta-analyses.

MOTIVATION: With the proliferation of microarray experiments and their availability in the public domain, the use of meta-analysis methods to combine results from different studies increases. In microarray experiments, where the sample size is often limited, meta-analysis offers the possibility to considerably increase the statistical power and give more accurate results. RESULTS: A moderated effect size combination method was proposed and compared with other meta-analysis approaches. All methods were applied to real publicly available datasets on prostate cancer, and were compared in an extensive simulation study for various amounts of inter-study variability. Although the proposed moderated effect size combination improved already existing effect size approaches, the P-value combination was found to provide a better sensitivity and a better gene ranking than the other meta-analysis methods, while effect size methods were more conservative. AVAILABILITY: An R package metaMA is available on the CRAN.

Sequential analysis for microarray data based on sensitivity and meta-analysis.

MOTIVATION: Transcriptomic studies using microarray technology have become a standard tool in life sciences in the last decade. Nevertheless the cost of these experiments remains high and forces scientists to work with small sample sizes at the expense of statistical power. In many cases, little or no prior knowledge on the underlying variability is available, which would allow an accurate estimation of the number of samples (microarrays) required to answer a particular biological question of interest. We investigate sequential methods, also called group sequential or adaptive designs in the context of clinical trials, for microarray analysis. Through interim analyses at different stages of the experiment and application of a stopping rule a decision can be made as to whether more samples should be studied or whether the experiment has yielded enough information already. RESULTS: The high dimensionality of microarray data facilitates the sequential approach. Since thousands of genes simultaneously contribute to the stopping decision, the marginal distribution of any single gene is nearly independent of the global stopping rule. For this reason, the interim analysis does not seriously bias the final p-values. We propose a meta-analysis approach to combining the results of the interim analyses at different stages. We consider stopping rules that are either based on the estimated number of true positives or on a sensitivity estimate and particularly discuss the difficulty of estimating the latter. We study this sequential method in an extensive simulation study and also apply it to several real data sets. The results show that applying sequential methods can reduce the number of microarrays without substantial loss of power. An R-package SequentialMA implementing the approach is available from the authors.