Multi-TGDR: a regularization method for multi-class classification in microarray experiments

Background With microarray technology becoming mature and popular, the selection and use of a small number of relevant genes for accurate classification of samples is a hot topic in the circles of biostatistics and bioinformatics. However, most of the developed algorithms lack the ability to handle multiple classes, which arguably a common application. Here, we propose an extension to an existing regularization algorithm called Threshold Gradient Descent Regularization (TGDR) to specifically tackle multi-class classification of microarray data. When there are several microarray experiments addressing the same/similar objectives, one option is to use meta-analysis version of TGDR (Meta-TGDR), which considers the classification task as combination of classifiers with the same structure/model while allowing the parameters to vary across studies. However, the original Meta-TGDR extension did not offer a solution to the prediction on independent samples. Here, we propose an explicit method to estimate the overall coefficients of the biomarkers selected by Meta-TGDR. This extension permits broader applicability and allows a comparison between the predictive performance of Meta-TGDR and TGDR using an independent testing set. Results Using real-world applications, we demonstrated the proposed multi-TGDR framework works well and the number of selected genes is less than the sum of all individualized binary TGDRs. Additionally, Meta-TGDR and TGDR on the batch-effect adjusted pooled data approximately provided same results. By adding Bagging procedure in each application, the stability and good predictive performance are warranted. Conclusions Compared with Meta-TGDR, TGDR is less computing time intensive, and requires no samples of all classes in each study. On the adjusted data, it has approximate same predictive performance with Meta-TGDR. Thus, it is highly recommended

"Harshlighting" small blemishes on microarrays

BACKGROUND: Microscopists are familiar with many blemishes that fluorescence images can have due to dust and debris, glass flaws, uneven distribution of fluids or surface coatings, etc. Microarray scans show similar artefacts, which affect the analysis, particularly when one tries to detect subtle changes. However, most blemishes are hard to find by the unaided eye, particularly in high-density oligonucleotide arrays (HDONAs). RESULTS: We present a method that harnesses the statistical power provided by having several HDONAs available, which are obtained under similar conditions except for the experimental factor. This method "harshlights" blemishes and renders them evident. We find empirically that about 25% of our chips are blemished, and we analyze the impact of masking them on screening for differentially expressed genes. CONCLUSION: Experiments attempting to assess subtle expression changes should be carefully screened for blemishes on the chips. The proposed method provides investigators with a novel robust approach to improve the sensitivity of microarray analyses. By utilizing topological information to identify and mask blemishes prior to model based analyses, the method prevents artefacts from confounding the process of background correction, normalization, and summarization

Harshlight: a "corrective make-up" program for microarray chips

BACKGROUND: Microscopists are familiar with many blemishes that fluorescence images can have due to dust and debris, glass flaws, uneven distribution of fluids or surface coatings, etc. Microarray scans do show similar artifacts, which might affect subsequent analysis. Although all but the starkest blemishes are hard to find by the unaided eye, particularly in high-density oligonucleotide arrays (HDONAs), few tools are available to help with the detection of those defects. RESULTS: We develop a novel tool, Harshlight, for the automatic detection and masking of blemishes in HDONA microarray chips. Harshlight uses a combination of statistic and image processing methods to identify three different types of defects: localized blemishes affecting a few probes, diffuse defects affecting larger areas, and extended defects which may invalidate an entire chip. CONCLUSION: We demonstrate the use of Harshlight can materially improve analysis of HDONA chips, especially for experiments with subtle changes between samples. For the widely used MAS5 algorithm, we show that compact blemishes cause an average of 8 gene expression values per chip to change by more than 50%, two of them by more than twofold; our masking algorithm restores about two thirds of this damage. Large-scale artifacts are successfully detected and eliminated

Comparing independent microarray studies: the case of human embryonic stem cells

BACKGROUND: Microarray studies of the same phenomenon in different labs often appear at variance because the published lists of regulated transcripts have disproportionately small intersections. We demonstrate that comparing studies by intersecting lists in this manner is methodologically flawed by reanalyzing three studies of the molecular signature of "stemness" in human embryonic stem cells. There are only 7 genes common to all three published lists, suggesting disagreement. RESULTS: Carefully reanalyzing all three together from the raw data we detect 111 genes upregulated and 95 downregulated in all three studies. The upregulated list was subject to rtRTPCR analysis and 75% of the genes were confirmed. CONCLUSION: Our findings show that the three studies have a substantial core of common genes, which is missed if only the published lists are examined. Combined analysis of multiple experiments can be a powerful way to distil coherent conclusions

A Bioequivalence Test by the Direct Comparison of Concentration-versus-Time Curves Using Local Polynomial Smoothers

In order to test if two chemically or pharmaceutically equivalent products have the same efficacy and/or toxicity, a bioequivalence (BE) study is conducted. The 80%/125% rule is the most commonly used criteria for BE and states that BE cannot be claimed unless the 90% CIs for the ratio of selected pharmacokinetics (PK) parameters of the tested to the reference drug are within 0.8 to 1.25. Considering that estimates of these PK parameters are derived from the concentration-versus-time curves, a direct comparison between these curves motivates an alternative and more flexible approach to test BE. Here, we propose to frame the BE test in terms of an equivalence of concentration-versus-time curves which are constructed using local polynomial smoother (LPS). A metric is presented to quantify the distance between the curves and its 90% CIs are calculated via bootstrapping. Then, we applied the proposed procedures to data from an animal study and found that BE between a generic drug and its brand name cannot be concluded, which was consistent with the results by applying the 80%/125% rule. However, the proposed procedure has the advantage of testing only on a single metric, instead of all PK parameters

Molecular and Cellular Profiling of Scalp Psoriasis Reveals Differences and Similarities Compared to Skin Psoriasis

Scalp psoriasis shows a variable clinical spectrum and in many cases poses a great therapeutic challenge. However, it remains unknown whether the immune response of scalp psoriasis differs from understood pathomechanisms of psoriasis in other skin areas. We sought to determine the cellular and molecular phenotype of scalp psoriasis by performing a comparative analysis of scalp and skin using lesional and nonlesional samples from 20 Caucasian subjects with untreated moderate to severe psoriasis and significant scalp involvement and 10 control subjects without psoriasis. Our results suggest that even in the scalp, psoriasis is a disease of the inter-follicular skin. The immune mechanisms that mediate scalp psoriasis were found to be similar to those involved in skin psoriasis. However, the magnitude of dysregulation, number of differentially expressed genes, and enrichment of the psoriatic genomic fingerprint were more prominent in skin lesions. Furthermore, the scalp transcriptome showed increased modulation of several gene-sets, particularly those induced by interferon-gamma, compared with that of skin psoriasis, which was mainly associated with activation of TNFα/L-17/IL-22-induced keratinocyte response genes. We also detected differences in expression of gene-sets involving negative regulation, epigenetic regulation, epidermal differentiation, and dendritic cell or Th1/Th17/Th22-related T-cell processes

Meta-analysis derived atopic dermatitis (MADAD) transcriptome defines a robust AD signature highlighting the involvement of atherosclerosis and lipid metabolism pathways

BACKGROUND: Atopic dermatitis (AD) is a common inflammatory skin disease with limited treatment options. Several microarray experiments have been conducted on lesional/LS and non-lesional/NL AD skin to develop a genomic disease phenotype. Although these experiments have shed light on disease pathology, inter-study comparisons reveal large differences in resulting sets of differentially expressed genes (DEGs), limiting the utility of direct comparisons across studies. METHODS: We carried out a meta-analysis combining 4 published AD datasets to define a robust disease profile, termed meta-analysis derived AD (MADAD) transcriptome. RESULTS: This transcriptome enriches key AD pathways more than the individual studies, and associates AD with novel pathways, such as atherosclerosis signaling (IL-37, selectin E/SELE). We identified wide lipid abnormalities and, for the first time in vivo, correlated Th2 immune activation with downregulation of key epidermal lipids (FA2H, FAR2, ELOVL3), emphasizing the role of cytokines on the barrier disruption in AD. Key AD “classifier genes” discriminate lesional from nonlesional skin, and may evaluate therapeutic responses. CONCLUSIONS: Our meta-analysis provides novel and powerful insights into AD disease pathology, and reinforces the concept of AD as a systemic disease. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12920-015-0133-x) contains supplementary material, which is available to authorized users

A Single Intradermal Injection of IFN-γ Induces an Inflammatory State in Both Non-Lesional Psoriatic and Healthy Skin

Psoriasis is a chronic, debilitating, immune-mediated inflammatory skin disease. As IFN-γ is involved in many cellular processes, including activation of dendritic cells (DCs), antigen processing and presentation, cell adhesion and trafficking, and cytokine and chemokine production, IFN-γ–producing Th1 cells were proposed to be integral to the pathogenesis of psoriasis. Recently, IFN-γ was shown to enhance IL-23 and IL-1 production by DCs and subsequently induce Th17 cells, which are important contributors to the inflammatory cascade in psoriatic lesions. To determine whether IFN-γ indeed induces the pathways expressed in psoriatic lesions, a single intradermal injection of IFN-γ was administered to an area of clinically normal, non-lesional (NL) skin of psoriasis patients and biopsies were collected 24 hours later. Although there were no visible changes in the skin, IFN-γ induced many molecular and histological features characteristic of psoriatic lesions. IFN-γ increased a number of differentially expressed genes in the skin, including many chemokines concomitant with an influx of T cells and inflammatory DCs. Furthermore, inflammatory DC products tumor necrosis factor (TNF), inducible nitric oxide synthase, IL-23, and TNF-related apoptosis-inducing ligand were present in IFN-γ–treated skin. Thus, IFN-γ, which is significantly elevated in NL skin compared with healthy skin, appears to be a key pathogenic cytokine that can induce many features of the inflammatory cascade of psoriasis

Amelioration of epidermal hyperplasia by TNF inhibition is associated with reduced Th17 responses

Biological agents have dramatically improved treatment options for patients with severe psoriasis. Etanercept (tumor necrosis factor [TNF] receptor–immunoglobulin fusion protein) is an effective treatment for many psoriasis patients, and blockade of TNF is considered to be its primary action. However, in this clinical trial, we show that etanercept has early inhibitory effects on a newly appreciated type of T cells: T helper type 17 (Th17) cells. Etanercept reduced the inflammatory dendritic cell products that drive Th17 cell proliferation (interleukin [IL] 23), as well as Th17 cell products and downstream effector molecules (IL-17, IL-22, CC chemokine ligand 20, and β-defensin 4). In contrast, Th1 cellular products and effector molecules (interferon γ, lymphotoxin α, and myxovirus resistance 1) were reduced late in disease resolution. This study suggests a role for Th17 in addition to Th1 cells in the pathogenesis of psoriasis. Th17 cells may be particularly important in driving epidermal activation in psoriatic plaques, whereas Th1 cells must also be eliminated for final disease resolution