NIPSNAP protein family emerges as a sensor of mitochondrial health.

Since their discovery over two decades ago, the molecular and cellular functions of the NIPSNAP family of proteins (NIPSNAPs) have remained elusive until recently. NIPSNAPs interact with a variety of mitochondrial and cytoplasmic proteins. They have been implicated in multiple cellular processes and associated with different physiologic and pathologic conditions, including pain transmission, Parkinson's disease, and cancer. Recent evidence demonstrated a direct role for NIPSNAP1 and NIPSNAP2 proteins in regulation of mitophagy, a process that is critical for cellular health and maintenance. Importantly, NIPSNAPs contain a 110 amino acid domain that is evolutionary conserved from mammals to bacteria. However, the molecular function of the conserved NIPSNAP domain and its potential role in mitophagy have not been explored. It stands to reason that the highly conserved NIPSNAP domain interacts with a substrate that is ubiquitously present across all species and can perhaps act as a sensor for mitochondrial health.

Coronavirus Disease 2019 (COVID-19) Seropositivity and Asymptomatic Rates in Healthcare Workers Are Associated with Job Function and Masking.

BACKGROUND: Although the risk of exposure to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is higher for frontline healthcare workers, not all personnel have similar risks. Determining infection rate is difficult due to the limits on testing and the high rate of asymptomatic individuals. Detection of antibodies against SARS-CoV-2 may be useful for determining prior exposure to the virus and assessing mitigation strategies, such as isolation, masks, and other protective equipment. METHODS: An online assessment that included demographic, clinical, and exposure information and a blood sample was collected from 20 614 participants out of ~43 000 total employees at Beaumont Health, which includes 8 hospitals distributed across the Detroit metropolitan area in southeast Michigan. The presence of anti-SARS-CoV-2 IgG was determined using the EUROIMMUN assay. RESULTS: A total of 1818 (8.8%) participants were seropositive between April 13 and May 28, 2020. Among the seropositive individuals, 44% reported that they were asymptomatic during the month prior to blood collection. Healthcare roles such as phlebotomy, respiratory therapy, and nursing/nursing support exhibited significantly higher seropositivity. Among participants reporting direct exposure to a Coronavirus Disease 2019 (COVID-19) positive individual, those wearing an N95/PAPR mask had a significantly lower seropositivity rate (10.2%) compared to surgical/other masks (13.1%) or no mask (17.5%). CONCLUSIONS: Direct contact with COVID-19 patients increased the likelihood of seropositivity among employees but study participants who wore a mask during COVID-19 exposures were less likely to be seropositive. Additionally, a large proportion of seropositive employees self-reported as asymptomatic. (Funded by Beaumont Health and by major donors through the Beaumont Health Foundation). CLINICALTRIALS.GOV NUMBER: NCT04349202.

Evaluation of Sirtuin-3 probe quality and co-expressed genes using literature cohesion.

BACKGROUND: Gene co-expression studies can provide important insights into molecular and cellular signaling pathways. The GeneNetwork database is a unique resource for co-expression analysis using data from a variety of tissues across genetically distinct inbred mice. However, extraction of biologically meaningful co-expressed gene sets is challenging due to variability in microarray platforms, probe quality, normalization methods, and confounding biological factors. In this study, we tested whether literature derived functional cohesion could be used as an objective metric in lieu of 'ground truth' to evaluate the quality of probes and microarray datasets. RESULTS: We examined Sirtuin-3 (Sirt3) co-expressed gene sets extracted from either liver or brain tissues of BXD recombinant inbred mice in the GeneNetwork database. Depending on the microarray platform, there were as many as 26 probes that targeted different regions of Sirt3 primary transcript. Co-expressed gene sets (ranging from 100-1000 genes) associated with each Sirt3 probe were evaluated using the previously developed literature-derived cohesion p-value (LPv) and benchmarked against 'gold standards' derived from proteomic studies or Gene Ontology classifications. We found that the maximal F-measure was obtained at an average window size of 535 genes. Using set size of 500 genes, the Pearson correlations between LPv and F-measure as well as between LPv and mitochondrial gene enrichment p-values were 0.90 and 0.93, respectively. Importantly, we found that the LPv approach can distinguish high quality Sirt3 probes. Analysis of the most functionally cohesive Sirt3 co-expressed gene set revealed core metabolic pathways that were shared between hippocampus and liver as well as distinct pathways which were unique to each tissue. These results are consistent with other studies that suggest Sirt3 is a key metabolic regulator and has distinct functions in energy-producing vs. energy-demanding tissues. CONCLUSIONS: Our results provide proof-of-concept that literature cohesion analysis is useful for evaluating the quality of probes and microarray datasets, particularly when experimentally derived gold standards are unavailable. Our approach would enable researchers to rapidly identify biologically meaningful co-expressed gene sets and facilitate discovery from high throughput genomic data.

Memphis FitKids: implementing a mobile-friendly web-based application to enhance parents' participation in improving child health.

BACKGROUND: Child obesity is a major public health challenge, increasing the risk of chronic medical conditions such as type 2 diabetes, metabolic syndrome, and hypertension. Among U.S. states, Tennessee has one of the highest rates of child obesity. Emerging communication technologies can help to deliver highly disseminable population-level interventions to improve health behavior. The aim of this paper is to report the implementation and the evaluation of the reach of Memphis FitKids, a web-based application, intended to promote healthy behaviors for families and children. METHODS: A community-level demonstration project, Memphis FitKids, was developed and implemented in Tennessee's Greater Memphis Area. This application ( www.memphisfitkids.org ) was designed for parents to assess their children's obesity risk through determinants such as weight, diet, physical activity, screen time, and sleep adequacy. A built-in "FitCheck" tool used this collected information to create a report with tailored recommendations on how to make healthy changes. A Geographic Information Systems component was implemented to suggest low-cost neighborhood resources that support a healthy lifestyle. A social marketing framework was used to develop and implement FitKids, and a Community Advisory Board with representatives from community partners (e.g., the YMCA of Memphis, the Pink Palace Family of Museums, and the Memphis Public Library) supported the implementation of the project. Five kiosks distributed in the community served as public access points to provide a broad reach across socioeconomic strata. Presentations at community events and the use of Facebook facilitated the promotion of FitKids. Website traffic and Facebook usage were evaluated with Google Analytics and Facebook Insights, respectively. RESULTS: In Tennessee, 33,505 users completed 38,429 FitCheck sessions between July 2014 and December 2016. Among these, 6763 sessions were completed at the five kiosks in the community. FitKids was presented at 112 community events and the social media posts reached 23,767 unique Facebook users. CONCLUSIONS: The Memphis FitKids demonstration project showed that web-based health tools may be a viable strategy to increase access to information about healthy weight and lifestyle options for families. Mobile-friendly web-based applications like Memphis FitKids may also serve health professionals in their efforts to support their clients in adopting healthy behaviors.

Loss of C-5 Sterol Desaturase Activity Results in Increased Resistance to Azole and Echinocandin Antifungals in a Clinical Isolate of Candida parapsilosis.

Among emerging non-albicans Candida species, Candida parapsilosis is of particular concern as a cause of nosocomial bloodstream infections in neonatal and intensive care unit patients. While fluconazole and echinocandins are considered effective treatments for such infections, recent reports of fluconazole and echinocandin resistance in C. parapsilosis indicate a growing problem. The present study describes a novel mechanism of antifungal resistance in this organism affecting susceptibility to azole and echinocandin antifungals in a clinical isolate obtained from a patient with prosthetic valve endocarditis. Transcriptome analysis indicated differential expression of several genes in the resistant isolate, including upregulation of ergosterol biosynthesis pathway genes ERG2, ERG5, ERG6, ERG11, ERG24, ERG25, and UPC2 Whole-genome sequencing revealed that the resistant isolate possessed an ERG3 mutation resulting in a G111R amino acid substitution. Sterol profiles indicated a reduction in sterol desaturase activity as a result of this mutation. Replacement of both mutant alleles in the resistant isolate with the susceptible isolate's allele restored wild-type susceptibility to all azoles and echinocandins tested. Disruption of ERG3 in the susceptible and resistant isolates resulted in a loss of sterol desaturase activity, high-level azole resistance, and an echinocandin-intermediate to -resistant phenotype. While disruption of ERG3 in C. albicans resulted in azole resistance, echinocandin MICs, while elevated, remained within the susceptible range. This work demonstrates that the G111R substitution in Erg3 is wholly responsible for the altered azole and echinocandin susceptibilities observed in this C. parapsilosis isolate and is the first report of an ERG3 mutation influencing susceptibility to the echinocandins.

Prioritization, clustering and functional annotation of MicroRNAs using latent semantic indexing of MEDLINE abstracts.

BACKGROUND: The amount of scientific information about MicroRNAs (miRNAs) is growing exponentially, making it difficult for researchers to interpret experimental results. In this study, we present an automated text mining approach using Latent Semantic Indexing (LSI) for prioritization, clustering and functional annotation of miRNAs. RESULTS: For approximately 900 human miRNAs indexed in miRBase, text documents were created by concatenating titles and abstracts of MEDLINE citations which refer to the miRNAs. The documents were parsed and a weighted term-by-miRNA frequency matrix was created, which was subsequently factorized via singular value decomposition to extract pair-wise cosine values between the term (keyword) and miRNA vectors in reduced rank semantic space. LSI enables derivation of both explicit and implicit associations between entities based on word usage patterns. Using miR2Disease as a gold standard, we found that LSI identified keyword-to-miRNA relationships with high accuracy. In addition, we demonstrate that pair-wise associations between miRNAs can be used to group them into categories which are functionally aligned. Finally, term ranking by querying the LSI space with a group of miRNAs enabled annotation of the clusters with functionally related terms. CONCLUSIONS: LSI modeling of MEDLINE abstracts provides a robust and automated method for miRNA related knowledge discovery. The latest collection of miRNA abstracts and LSI model can be accessed through the web tool miRNA Literature Network (miRLiN) at http://bioinfo.memphis.edu/mirlin .

CbGRiTS: cerebellar gene regulation in time and space.

The mammalian CNS is one of the most complex biological systems to understand at the molecular level. The temporal information from time series transcriptome analysis can serve as a potent source of associative information between developmental processes and regulatory genes. Here, we introduce a new transcriptome database called, Cerebellar Gene Regulation in Time and Space (CbGRiTS). This dataset is populated with transcriptome data across embryonic and postnatal development from two standard mouse strains, C57BL/6J and DBA/2J, several recombinant inbred lines and cerebellar mutant strains. Users can evaluate expression profiles across cerebellar development in a deep time series with graphical interfaces for data exploration and link-out to anatomical expression databases. We present three analytical approaches that take advantage of specific aspects of the time series for transcriptome analysis. We demonstrate the use of CbGRiTS dataset as a community resource to explore patterns of gene expression and develop hypotheses concerning gene regulatory networks in brain development.

A Bayesian approach for inducing sparsity in generalized linear models with multi-category response.

BACKGROUND: The dimension and complexity of high-throughput gene expression data create many challenges for downstream analysis. Several approaches exist to reduce the number of variables with respect to small sample sizes. In this study, we utilized the Generalized Double Pareto (GDP) prior to induce sparsity in a Bayesian Generalized Linear Model (GLM) setting. The approach was evaluated using a publicly available microarray dataset containing 99 samples corresponding to four different prostate cancer subtypes. RESULTS: A hierarchical Sparse Bayesian GLM using GDP prior (SBGG) was developed to take into account the progressive nature of the response variable. We obtained an average overall classification accuracy between 82.5% and 94%, which was higher than Support Vector Machine, Random Forest or a Sparse Bayesian GLM using double exponential priors. Additionally, SBGG outperforms the other 3 methods in correctly identifying pre-metastatic stages of cancer progression, which can prove extremely valuable for therapeutic and diagnostic purposes. Importantly, using Geneset Cohesion Analysis Tool, we found that the top 100 genes produced by SBGG had an average functional cohesion p-value of 2.0E-4 compared to 0.007 to 0.131 produced by the other methods. CONCLUSIONS: Using GDP in a Bayesian GLM model applied to cancer progression data results in better subclass prediction. In particular, the method identifies pre-metastatic stages of prostate cancer with substantially better accuracy and produces more functionally relevant gene sets.

Dab2IP Regulates Neuronal Positioning, Rap1 Activity and Integrin Signaling in the Developing Cortex.

Dab2IP (DOC-2/DAB2 interacting protein) is a GTPase-activating protein which is involved in various aspects of brain development in addition to its roles in tumor formation and apoptosis in other systems. In this study, we carefully examined the expression profile of Dab2IP and investigated its physiological role during brain development using a Dab2IP-knockdown (KD) mouse model created by retroviral insertion of a LacZ-encoding gene-trapping cassette. LacZ staining revealed that Dab2IP is expressed in the ventricular zone as well as the cortical plate and the intermediate zone. Immunohistochemical analysis showed that Dab2IP protein is localized in the leading process and proximal cytoplasmic regions of migrating neurons in the intermediate zone. Bromodeoxyuridine birth dating experiments in combination with immunohistochemical analysis using layer-specific markers showed that Dab2IP is important for proper positioning of a subset of layer II-IV neurons in the developing cortex. Notably, neuronal migration was not completely disrupted in the cerebral cortex of Dab2IP-KD mice and disruption of migration was not strictly layer specific. Previously, we found that Dab2IP regulates multipolar transition in cortical neurons. Others have shown that Rap1 regulates the transition from multipolar to bipolar morphology in migrating postmitotic neurons through N-cadherin signaling and somal translocation in the superficial layer of the cortical plate through integrin signaling. Therefore, we examined whether Rap1 and integrin signaling were affected in Dab2IP-KD brains. We found that Dab2IP-KD resulted in higher levels of activated Rap1 and integrin in the developing cortex. Taken together, our results suggest that Dab2IP plays an important role in the migration and positioning of a subpopulation of later-born (layers II-IV) neurons, likely through the regulation of Rap1 and integrin signaling.

Tetraspanin CD9 modulates human lymphoma cellular proliferation via histone deacetylase activity.

Non-Hodgkin Lymphoma (NHL) is a type of hematological malignancy that affects two percent of the overall population in the United States. Tetraspanin CD9 is a cell surface protein that has been thoroughly demonstrated to be a molecular facilitator of cellular phenotype. CD9 expression varies in two human lymphoma cell lines, Raji and BJAB. In this report, we investigated the functional relationship between CD9 and cell proliferation regulated by histone deacetylase (HDAC) activity in these two cell lines. Introduction of CD9 expression in Raji cells resulted in significantly increased cell proliferation and HDAC activity compared to Mock transfected Raji cells. The increase in CD9-Raji cell proliferation was significantly inhibited by HDAC inhibitor (HDACi) treatment. Pretreatment of BJAB cells with HDAC inhibitors resulted in a significant decrease in endogenous CD9 mRNA and cell surface expression. BJAB cells also displayed decreased cell proliferation after HDACi treatment. These results suggest a significant relationship between CD9 expression and cell proliferation in human lymphoma cells that may be modulated by HDAC activity.

Glutamate dysfunction associated with developmental cerebellar damage: relevance to autism spectrum disorders.

Neural abnormalities commonly associated with autism spectrum disorders include prefrontal cortex (PFC) dysfunction and cerebellar pathology in the form of Purkinje cell loss and cerebellar hypoplasia. It has been reported that loss of cerebellar Purkinje cells results in aberrant dopamine neurotransmission in the PFC which occurs via dysregulation of multisynaptic efferents from the cerebellum to the PFC. Using a mouse model, we investigated the possibility that developmental cerebellar Purkinje cell loss could disrupt glutamatergic cerebellar projections to the PFC that ultimately modulate DA release. We measured glutamate release evoked by local electrical stimulation using fixed-potential amperometry in combination with glutamate selective enzyme-based recording probes in urethane-anesthetized Lurcher mutant and wildtype mice. Target sites included the mediodorsal and ventrolateral thalamic nuclei, reticulotegmental nuclei, pedunculopontine nuclei, and ventral tegmental area. With the exception of the ventral tegmental area, the results indicated that in comparison to wildtype mice, evoked glutamate release was reduced in Lurcher mutants by between 9 and 72% at all stimulated sites. These results are consistent with the notion that developmental loss of cerebellar Purkinje cells drives reductions in evoked glutamate release in cerebellar efferent pathways that ultimately influence PFC dopamine release. Possible mechanisms whereby reductions in glutamate release could occur are discussed.

Risk factors associated with glycated hemoglobin A1c trajectories progressing to type 2 diabetes.

BACKGROUND AND OBJECTIVE: The notion of prediabetes, defined by the ADA as glycated hemoglobin A1c (HbA1c) of 5.7-6.4%, implies increased vascular inflammatory and immunologic processes and higher risk for developing diabetes mellitus and major cardiovascular events. We aimed to determine the risk factors associated with rapid progression of normal and prediabetes patients to type 2 diabetes mellitus (T2DM). METHODS: Retrospective cohort study in a single 8-hospital health system in southeast Michigan, between 2006 and 2020. All patients with HbA1c <6.5% at baseline and at least 2 other HbA1c measurements were clustered in five trajectories encompassing more than 95% of the study population. Multivariate linear regression analysis was performed to examine the association of demographic and comorbidities with HbA1c trajectories progressing to diabetes. RESULTS: A total of 5,347 prediabetic patients were clustered based on their HbA1c progression (C1: 4,853, C2: 253, C66: 102, C12: 85, C68: 54). The largest cluster (C1) had a baseline median HbA1c value of 6.0% and exhibited stable HbA1c levels in prediabetic range across all subsequent years. The smallest cluster (C68) had the lowest median baseline HbA1c value and also remained stable across subsequent years. The proportion of normal HbA1c in each of the pre-diabetic trajectories ranged from 0 to 12.7%, whereas 81.5% of the reference cluster (C68) were normal HbA1c at baseline. The C2 (steady rising) trajectory was significantly associated with BMI (adj OR 1.10, 95%CI 1.03-1.17), and family history of DM (adj OR 2.75, 95%CI 1.32-5.74). With respect to the late rising trajectories, baseline BMI was significantly associated with both C66 and C12 trajectory (adj OR 1.10, 95%CI 1.03-1.18) and (adj OR 1.13, 95%CI 1.05-1.23) respectively, whereas, the C12 trajectory was also significantly associated with age (adj OR 1.62, 95%CI 1.04-2.53) and history of MACE (adj OR 3.20, 95%CI 1.14-8.93). CONCLUSIONS: We suggest that perhaps a more aggressive preventative approach should be considered in patients with a family history of T2DM who have high BMI and year-to-year increase in HbA1c, whether they have normal hemoglobin A1c or they have prediabetes.KEY MESSAGESProgression to diabetes from normal or prediabetic hemoglobin A1c within four years is associated with baseline BMI.A steady rise in HbA1c during a four-year period is associated with age and family history of T2DM, whereas age and personal history of MACE are associated with a rapid rise in HbA1c.A more aggressive preventative approach should be considered in patients with a family history of T2DM who have high BMI and year-to-year increase in HbA1c.

Paradoxical experiences of healthcare workers during COVID-19: a qualitative analysis of anonymous, web-based, audio narratives.

PURPOSE: To gain a deeper understanding of healthcare workers experiences during COVID-19 using an anonymous, web-based, audio narrative platform. METHODS: Data were collected from healthcare workers in the midwestern United States using a web-enabled audio diary approach. Participant recordings were analysed using a narrative coding and conceptualization process derived from grounded theory coding techniques. RESULTS: Fifteen healthcare workers, in direct patient care or non-patient care roles, submitted 18 audio narratives. Two paradoxical themes emerged: 1) A paradox of distress and meaningfulness, where a harsh work environment resulted in psychological distress while simultaneously resulting in new rewarding experiences, sense of purpose and positive outlooks. 2) A paradox of social isolation and connection, where despite extreme isolation, healthcare workers formed intense and meaningful interpersonal connections with patients and colleagues in new ways. CONCLUSIONS: A web-enabled audio diary approach provided an opportunity for healthcare workers to reflect deeper on their experiences without investigator influence, which led to some unique findings. Paradoxically, amid social isolation and extreme distress, a sense of value, meaning and rewarding human connections emerged. These findings suggest that interventions addressing healthcare worker burnout and distress might be enhanced by leveraging naturally occurring positive experiences as much as mitigating negative ones.

Dried blood spots are a valid alternative to venipuncture for COVID-19 antibody testing.

BACKGROUND: Serologic analysis is an important tool towards assessing the humoral response to COVID-19 infection and vaccination. Numerous serologic tests and platforms are currently available to support this line of testing. Two broad antibody testing categories are point-of-care lateral flow immunoassays and semi-quantitative immunoassays performed in clinical laboratories, which typically require blood collected from a finger-stick and a standard venipuncture blood draw, respectively. This study evaluated the use of dried blood spot (DBS) collections as a sample source for COVID-19 antibody testing using an automated clinical laboratory test system. METHODS: Two hundred and ninety-four participants in the BLAST COVID-19 seroprevalence study (NCT04349202) were recruited at the time of a scheduled blood draw to have an additional sample taken via finger stick as a DBS collection. Using the EUROIMMUN assay to assess SARS-CoV-2 anti-spike IgG status, DBS specimens were tested on 7, 14, 21, and 28 days post- collection and compared to the reference serum sample obtained from a blood draw for the BLAST COVID-19 study. RESULTS: SARS-CoV-2 anti-spike IgG status from DBS collections demonstrated high concordance with serum across all time points (7-28 days). However, the semi-quantitative value from DBS collections was lower on average than that from serum, resulting in increased uncertainty around the equivocal-to-positive analytical decision point. CONCLUSIONS: DBS collections can be substituted for venipuncture when assaying for COVID-19 IgG antibody, with samples being stable for at least 28 days at room temperature. Finger-stick sampling can therefore be advantageous for testing large populations for SARS-CoV-2 antibodies without the need for phlebotomists or immediate processing of samples. We have high confidence in serostaus determination from DBS collections, although the reduced semi-quantitative value may cause some low-level positives to fall into the equivocal or even negative range.

Influenza vaccine effectiveness against hospitalized SARS-CoV-2 infection.

Background: Some studies conducted before the Delta and Omicron variant-dominant periods have indicated that influenza vaccination provided protection against COVID-19 infection or hospitalization, but these results were limited by small study cohorts and a lack of comprehensive data on patient characteristics. No studies have examined this question during the Delta and Omicron periods (08/01/2021 to 2/22/2022). Methods: We conducted a retrospective cohort study of influenza-vaccinated and unvaccinated patients in the Corewell Health East(CHE, formerly known as Beaumont Health), Corewell Health West(CHW, formerly known as Spectrum Health) and Michigan Medicine (MM) healthcare system during the Delta-dominant and Omicron-dominant periods. We used a test-negative, case-control analysis to assess the effectiveness of the influenza vaccine against hospitalized SARS-CoV-2 outcome in adults, while controlling for individual characteristics as well as pandameic severity and waning immunity of COVID-19 vaccine. Results: The influenza vaccination has shown to provided some protection against SARS-CoV-2 hospitalized outcome across three main healthcare systems. CHE site (odds ratio [OR]=0.73, vaccine effectiveness [VE]=27%, 95% confidence interval [CI]: [18-35], p<0.001), CHW site (OR=0.85, VE=15%, 95% CI: [6-24], p<0.001), MM (OR=0.50, VE=50%, 95% CI: [40-58], p <0.001) and overall (OR=0.75, VE=25%, 95% CI: [20-30], p <0.001). Conclusion: The influenza vaccine provides a small degree of protection against SARS-CoV-2 infection across our study sites.

Literature aided determination of data quality and statistical significance threshold for gene expression studies.

BACKGROUND: Gene expression data are noisy due to technical and biological variability. Consequently, analysis of gene expression data is complex. Different statistical methods produce distinct sets of genes. In addition, selection of expression p-value (EPv) threshold is somewhat arbitrary. In this study, we aimed to develop novel literature based approaches to integrate functional information in analysis of gene expression data. METHODS: Functional relationships between genes were derived by Latent Semantic Indexing (LSI) of Medline abstracts and used to calculate the function cohesion of gene sets. In this study, literature cohesion was applied in two ways. First, Literature-Based Functional Significance (LBFS) method was developed to calculate a p-value for the cohesion of differentially expressed genes (DEGs) in order to objectively evaluate the overall biological significance of the gene expression experiments. Second, Literature Aided Statistical Significance Threshold (LASST) was developed to determine the appropriate expression p-value threshold for a given experiment. RESULTS: We tested our methods on three different publicly available datasets. LBFS analysis demonstrated that only two experiments were significantly cohesive. For each experiment, we also compared the LBFS values of DEGs generated by four different statistical methods. We found that some statistical tests produced more functionally cohesive gene sets than others. However, no statistical test was consistently better for all experiments. This reemphasizes that a statistical test must be carefully selected for each expression study. Moreover, LASST analysis demonstrated that the expression p-value thresholds for some experiments were considerably lower (p < 0.02 and 0.01), suggesting that the arbitrary p-values and false discovery rate thresholds that are commonly used in expression studies may not be biologically sound. CONCLUSIONS: We have developed robust and objective literature-based methods to evaluate the biological support for gene expression experiments and to determine the appropriate statistical significance threshold. These methods will assist investigators to more efficiently extract biologically meaningful insights from high throughput gene expression experiments.