With the expansion of public repositories such as the Gene Expression Omnibus (GEO), we are rapidly cataloging cellular transcriptional responses to diverse experimental conditions. Methods that query these repositories based on gene expression content, rather than textual annotations, may enable more effective experiment retrieval as well as the discovery of novel associations between drugs, diseases, and other perturbations.

Serum proteins are routinely used to diagnose diseases, but are hard to find due to low sensitivity in screening the serum proteome. Public repositories of microarray data, such as the Gene Expression Omnibus (GEO), contain RNA expression profiles for more than 16,000 biological conditions, covering more than 30% of United States mortality. We hypothesized that genes coding for serum- and urine-detectable proteins, and showing differential expression of RNA in disease-damaged tissues would make ideal diagnostic protein biomarkers for those diseases. We showed that predicted protein biomarkers are significantly enriched for known diagnostic protein biomarkers in 22 diseases, with enrichment significantly higher in diseases for which at least three datasets are available. We then used this strategy to search for new biomarkers indicating acute rejection (AR) across different types of transplanted solid organs. We integrated three biopsy-based microarray studies of AR from pediatric renal, adult renal and adult cardiac transplantation and identified 45 genes upregulated in all three. From this set, we chose 10 proteins for serum ELISA assays in 39 renal transplant patients, and discovered three that were significantly higher in AR. Interestingly, all three proteins were also significantly higher during AR in the 63 cardiac transplant recipients studied. Our best marker, serum PECAM1, identified renal AR with 89% sensitivity and 75% specificity, and also showed increased expression in AR by immunohistochemistry in renal, hepatic and cardiac transplant biopsies. Our results demonstrate that integrating gene expression microarray measurements from disease samples and even publicly-available data sets can be a powerful, fast, and cost-effective strategy for the discovery of new diagnostic serum protein biomarkers.

Preeclampsia (PE) is a pregnancy-related vascular disorder which is the leading cause of maternal morbidity and mortality. We sought to identify novel serological protein markers to diagnose PE with a multi-'omics' based discovery approach.

The Asian citrus psyllid, Diaphorina citri Kuwayama (Hemiptera: Psyllidae) is a vector for the causative agents of Huanglongbing, which threatens citrus production worldwide. This study reports and discusses the first D. citri transcriptomes, encompassing the three main life stages of D. citri, egg, nymph and adult. The transcriptomes were annotated using Gene Ontology (GO) and insecticide-related genes within each life stage were identified to aid the development of future D. citri insecticides. Transcriptome assemblies and other sequence data are available for download at the International Asian Citrus Psyllid Genome Consortium website [http://psyllid.org/download] and at NCBI [http://www.ncbi.nlm.nih.gov/bioproject/29447].

Using meta-analysis of eight independent transplant datasets (236 graft biopsy samples) from four organs, we identified a common rejection module (CRM) consisting of 11 genes that were significantly overexpressed in acute rejection (AR) across all transplanted organs. The CRM genes could diagnose AR with high specificity and sensitivity in three additional independent cohorts (794 samples). In another two independent cohorts (151 renal transplant biopsies), the CRM genes correlated with the extent of graft injury and predicted future injury to a graft using protocol biopsies. Inferred drug mechanisms from the literature suggested that two FDA-approved drugs (atorvastatin and dasatinib), approved for nontransplant indications, could regulate specific CRM genes and reduce the number of graft-infiltrating cells during AR. We treated mice with HLA-mismatched mouse cardiac transplant with atorvastatin and dasatinib and showed reduction of the CRM genes, significant reduction of graft-infiltrating cells, and extended graft survival. We further validated the beneficial effect of atorvastatin on graft survival by retrospective analysis of electronic medical records of a single-center cohort of 2,515 renal transplant patients followed for up to 22 yr. In conclusion, we identified a CRM in transplantation that provides new opportunities for diagnosis, drug repositioning, and rational drug design.

Neurodegenerative diseases share common pathologic features including neuroinflammation, mitochondrial dysfunction and protein aggregation, suggesting common underlying mechanisms of neurodegeneration. We undertook a meta-analysis of public gene expression data for neurodegenerative diseases to identify a common transcriptional signature of neurodegeneration.

The transforming growth factor β (TGF-β) family of growth factors are key regulators of mammalian development and their dysregulation is implicated in human disease, notably, heritable vasculopathies including Marfan (MFS, OMIM #154700) and Loeys-Dietz syndromes (LDS, OMIM #609192). We described a syndrome presenting at birth with distal arthrogryposis, hypotonia, bifid uvula, a failure of normal post-natal muscle development but no evidence of vascular disease; some of these features overlap with MFS and LDS. A de novo mutation in TGFB3 was identified by exome sequencing. Several lines of evidence indicate the mutation is hypomorphic suggesting that decreased TGF-β signaling from a loss of TGFB3 activity is likely responsible for the clinical phenotype. This is the first example of a mutation in the coding portion of TGFB3 implicated in a clinical syndrome suggesting TGFB3 is essential for both human palatogenesis and normal muscle growth.

We prepared and evaluated training and test materials for an assessment of text mining methods in molecular biology. The goal of the assessment was to evaluate the ability of automated systems to generate a list of unique gene identifiers from PubMed abstracts for the three model organisms Fly, Mouse, and Yeast. This paper describes the preparation and evaluation of answer keys for training and testing. These consisted of lists of normalized gene names found in the abstracts, generated by adapting the gene list for the full journal articles found in the model organism databases. For the training dataset, the gene list was pruned automatically to remove gene names not found in the abstract; for the testing dataset, it was further refined by manual annotation by annotators provided with guidelines. A critical step in interpreting the results of an assessment is to evaluate the quality of the data preparation. We did this by careful assessment of interannotator agreement and the use of answer pooling of participant results to improve the quality of the final testing dataset.

The goal of the gene normalization task is to link genes or gene products mentioned in the literature to biological databases. This is a key step in an accurate search of the biological literature. It is a challenging task, even for the human expert; genes are often described rather than referred to by gene symbol and, confusingly, one gene name may refer to different genes (often from different organisms). For BioCreative II, the task was to list the Entrez Gene identifiers for human genes or gene products mentioned in PubMed/MEDLINE abstracts. We selected abstracts associated with articles previously curated for human genes. We provided 281 expert-annotated abstracts containing 684 gene identifiers for training, and a blind test set of 262 documents containing 785 identifiers, with a gold standard created by expert annotators. Inter-annotator agreement was measured at over 90%.

Whole exome sequencing is increasingly used for the clinical evaluation of genetic disease, yet the variation of coverage and sensitivity over medically relevant parts of the genome remains poorly understood. Several sequencing-based assays continue to provide coverage that is inadequate for clinical assessment.

Whole brain irradiation remains important in the management of brain tumors. Although necessary for improving survival outcomes, cranial irradiation also results in cognitive decline in long-term survivors. A chronic inflammatory state characterized by microglial activation has been implicated in radiation-induced brain injury. We here provide the first comprehensive transcriptional profile of irradiated microglia. Fluorescence-activated cell sorting was used to isolate CD11b+ microglia from the hippocampi of C57BL/6 and Balb/c mice 1 month after 10 Gy cranial irradiation. Affymetrix gene expression profiles were evaluated using linear modeling and rank product analyses. One month after irradiation, a conserved irradiation signature across strains was identified, comprising 448 and 85 differentially up- and downregulated genes, respectively. Gene set enrichment analysis demonstrated enrichment for inflammation, including M1 macrophage-associated genes, but also an unexpected enrichment for extracellular matrix and blood coagulation-related gene sets, in contrast previously described microglial states. Weighted gene coexpression network analysis confirmed these findings and further revealed alterations in mitochondrial function. The RNA-seq transcriptome of microglia 24-h postradiation proved similar to the 1-month transcriptome, but additionally featured alterations in apoptotic and lysosomal gene expression. Reanalysis of published aging mouse microglia transcriptome data demonstrated striking similarity to the 1-month irradiated microglia transcriptome, suggesting that shared mechanisms may underlie aging and chronic irradiation-induced cognitive decline. GLIA 2015;63:754-767.

Moyamoya disease (MMD) is a rare disorder characterized by cerebrovascular occlusion and development of hemorrhage-prone collateral vessels. Approximately 10-12% of cases are familial, with a presumed low penetrance autosomal dominant pattern of inheritance. Diagnosis commonly occurs only after clinical presentation. The recent identification of the RNF213 founder mutation (p.R4810K) in the Asian population has made a significant contribution, but the etiology of this disease remains unclear. To further develop the variant landscape of MMD, we performed high-depth whole exome sequencing of 125 unrelated, predominantly nonfamilial, ethnically diverse MMD patients in parallel with 125 internally sequenced, matched controls using the same exome and analysis platform. Three subpopulations were established: Asian, Caucasian, and non-RNF213 founder mutation cases. We provided additional support for the previously observed RNF213 founder mutation (p.R4810K) in Asian cases (P = 6.01×10(-5)) that was enriched among East Asians compared to Southeast Asian and Pacific Islander cases (P = 9.52×10(-4)) and was absent in all Caucasian cases. The most enriched variant in Caucasian (P = 7.93×10(-4)) and non-RNF213 founder mutation (P = 1.51×10(-3)) cases was ZXDC (p.P562L), a gene involved in MHC Class II activation. Collapsing variant methodology ranked OBSCN, a gene involved in myofibrillogenesis, as most enriched in Caucasian (P = 1.07×10(-4)) and non-RNF213 founder mutation cases (P = 5.31×10(-5)). These findings further support the East Asian origins of the RNF213 (p.R4810K) variant and more fully describe the genetic landscape of multiethnic MMD, revealing novel, alternative candidate variants and genes that may be important in MMD etiology and diagnosis.

STAT5A and STAT5B are highly homologous proteins whose distinctive roles in human immunity remain unclear. However, STAT5A sufficiency cannot compensate for STAT5B defects, and human STAT5B deficiency, a rare autosomal recessive primary immunodeficiency, is characterized by chronic lung disease, growth failure and autoimmunity associated with regulatory T cell (Treg) reduction. We therefore hypothesized that STAT5A and STAT5B play unique roles in CD4(+) T cells. Upon knocking down STAT5A or STAT5B in human primary T cells, we found differentially regulated expression of FOXP3 and IL-2R in STAT5B knockdown T cells and down-regulated Bcl-X only in STAT5A knockdown T cells. Functional ex vivo studies in homozygous STAT5B-deficient patients showed reduced FOXP3 expression with impaired regulatory function of STAT5B-null Treg cells, also of increased memory phenotype. These results indicate that STAT5B and STAT5A act partly as non-redundant transcription factors and that STAT5B is more critical for Treg maintenance and function in humans.

The molecular pathogenesis of renal cell carcinoma (RCC) is poorly understood. Whole-genome and exome sequencing followed by innovative tumorgraft analyses (to accurately determine mutant allele ratios) identified several putative two-hit tumor suppressor genes, including BAP1. The BAP1 protein, a nuclear deubiquitinase, is inactivated in 15% of clear cell RCCs. BAP1 cofractionates with and binds to HCF-1 in tumorgrafts. Mutations disrupting the HCF-1 binding motif impair BAP1-mediated suppression of cell proliferation but not deubiquitination of monoubiquitinated histone 2A lysine 119 (H2AK119ub1). BAP1 loss sensitizes RCC cells in vitro to genotoxic stress. Notably, mutations in BAP1 and PBRM1 anticorrelate in tumors (P = 3 × 10(-5)), [corrected] and combined loss of BAP1 and PBRM1 in a few RCCs was associated with rhabdoid features (q = 0.0007). BAP1 and PBRM1 regulate seemingly different gene expression programs, and BAP1 loss was associated with high tumor grade (q = 0.0005). Our results establish the foundation for an integrated pathological and molecular genetic classification of RCC, paving the way for subtype-specific treatments exploiting genetic vulnerabilities.

We investigated the common-disease relevant information obtained from sequencing compared with that reported from genotyping arrays.

With the continued exponential expansion of publicly available genomic data and access to low-cost, high-throughput molecular technologies for profiling patient populations, computational technologies and informatics are becoming vital considerations in genomic medicine. Although cloud computing technology is being heralded as a key enabling technology for the future of genomic research, available case studies are limited to applications in the domain of high-throughput sequence data analysis. The goal of this study was to evaluate the computational and economic characteristics of cloud computing in performing a large-scale data integration and analysis representative of research problems in genomic medicine. We find that the cloud-based analysis compares favorably in both performance and cost in comparison to a local computational cluster, suggesting that cloud computing technologies might be a viable resource for facilitating large-scale translational research in genomic medicine.

Combining the results of studies using highly parallelized measurements of gene expression such as microarrays and RNAseq offer unique challenges in meta analysis. Motivated by a need for a deeper understanding of organ transplant rejection, we combine the data from five separate studies to compare acute rejection versus stability after solid organ transplantation, and use this data to examine approaches to multiplex meta analysis.

BACKGROUND Systemic lupus erythematosus (SLE) leads to renal lesions, which may be clinically silent in patients with little or no proteinuria. Early detection of these lesions may improve prognosis, but early markers are controversial. This study aimed to determine renal marker proteins associated with renal lesion severity in patients with lupus nephropathy (LN) and little or no proteinuria. MATERIAL AND METHODS Patients with LN and little or no proteinuria (<0.5 g/24 hours) (n=187) that underwent kidney biopsy were grouped according to: low severity (Class I or II; n=116) versus high severity (Class III, IV, or V; n=71). Disease status was determined according to the SLE disease activity index (SLEDAI). Renal marker proteins (serum β2-macroglobulin, urinary β2-macroglobulin, albumin, IgG, and α1-macroglobulin) were measured using radioimmunoassay. RESULTS Compared with the low severity group, patients in the high severity group had higher urinary albumin (11.60±8.94 versus 7.08±10.07 µg/mL, p=0.008) and urinary IgG (13.21±9.35 versus 8.74±8.90 µg/mL, p=0.007) levels. Multivariate conditional logistic regression analysis showed that urinary albumin (odds ratio (OR)=1.417, 95% confidence interval (95% CI): 1.145-1.895, p=0.001) and SLEDAI (OR=2.004, 95% CI: 1.264-3.178, p=0.003) were independently associated with severe renal lesions in these patients. Using an optimal cutoff point of urinary albumin of 7.53 µg/mL resulted in 67% sensitivity and 82% specificity for the detection of high severity renal lesions. CONCLUSIONS Urinary albumin levels and SLEDAI were independently associated with histological severity of renal lesions in patients with LN and little or no proteinuria. These parameters could be used to help select patients for renal biopsy.

https://citrusgreening.org/.