Jonathan D. Wren

The Achilles' heel of senescent cells: from transcriptome to senolytic drugs

The healthspan of mice is enhanced by killing senescent cells using a transgenic suicide gene. Achieving the same using small molecules would have a tremendous impact on quality of life and the burden of age‐related chronic diseases. Here, we describe the rationale for identification and validation of a new class of drugs termed senolytics, which selectively kill senescent cells. By transcript analysis, we discovered increased expression of pro‐survival networks in senescent cells, consistent with their established resistance to apoptosis. Using siRNA to silence expression of key nodes of this network, including ephrins (EFNB1 or 3), PI3Kδ, p21, BCL‐xL, or plasminogen‐activated inhibitor‐2, killed senescent cells, but not proliferating or quiescent, differentiated cells. Drugs targeting these same factors selectively killed senescent cells. Dasatinib eliminated senescent human fat cell progenitors, while quercetin was more effective against senescent human endothelial cells and mouse BM‐MSCs. The combination of dasatinib and quercetin was effective in eliminating senescent MEFs. In vivo, this combination reduced senescent cell burden in chronologically aged, radiation‐exposed, and progeroid Ercc1−/Δ mice. In old mice, cardiac function and carotid vascular reactivity were improved 5 days after a single dose. Following irradiation of one limb in mice, a single dose led to improved exercise capacity for at least 7 months following drug treatment. Periodic drug administration extended healthspan in Ercc1−/∆ mice, delaying age‐related symptoms and pathology, osteoporosis, and loss of intervertebral disk proteoglycans. These results demonstrate the feasibility of selectively ablating senescent cells and the efficacy of senolytics for alleviating symptoms of frailty and extending healthspan.

Variants at multiple loci implicated in both innate and adaptive immune responses are associated with Sjögren’s syndrome

Sjögrens syndrome is a common autoimmune disease (affecting ∼0.7% of European Americans) that typically presents as keratoconjunctivitis sicca and xerostomia. Here we report results of a large-scale association study of Sjögrens syndrome. In addition to strong association within the human leukocyte antigen (HLA) region at 6p21 (Pmeta = 7.65 × 10−114), we establish associations with IRF5-TNPO3 (Pmeta = 2.73 × 10−19), STAT4 (Pmeta = 6.80 × 10−15), IL12A (Pmeta = 1.17 × 10−10), FAM167A-BLK (Pmeta = 4.97 × 10−10), DDX6-CXCR5 (Pmeta = 1.10 × 10−8) and TNIP1 (Pmeta = 3.30 × 10−8). We also observed suggestive associations (Pmeta < 5 × 10−5) with variants in 29 other regions, including TNFAIP3, PTTG1, PRDM1, DGKQ, FCGR2A, IRAK1BP1, ITSN2 and PHIP, among others. These results highlight the importance of genes that are involved in both innate and adaptive immunity in Sjögrens syndrome.

Genome-wide DNA methylation patterns in CD4+ T cells from patients with systemic lupus erythematosus

Systemic lupus erythematosus is a chronic-relapsing autoimmune disease of incompletely understood etiology. Recent evidence strongly supports an epigenetic contribution to the pathogenesis of lupus. To understand the extent and nature of dysregulated DNA methylation in lupus T cells, we performed a genome-wide DNA methylation study in CD4+ T cells in lupus patients compared to normal healthy controls. Cytosine methylation was quantified in 27,578 CG sites located within the promoter regions of 14,495 genes. We identified 236 hypomethylated and 105 hypermethylated CG sites in lupus CD4+ T cells compared to normal controls, consistent with widespread DNA methylation changes in lupus T cells. Of interest, hypomethylated genes in lupus T cells include CD9, which is known to provide potent T-cell co-stimulation signals. Other genes with known involvement in autoimmunity such as MMP9 and PDGFRA were also hypomethylated. The BST2 gene, an interferon-inducible membrane-bound protein that helps restrict the release of retroviral particles was also hypomethylated in lupus patients. Genes involved in folate biosynthesis, which plays a role in DNA methylation, were overrepresented among hypermethylated genes. In addition, the transcription factor RUNX3 was hypermethylated in patients, suggesting an impact on T-cell maturation. Protein-protein interaction maps identified a transcription factor, HNF4a, as a regulatory hub affecting a number of differentially methylated genes. Apoptosis was also an overrepresented ontology in these interaction maps. Further, our data suggest that the methylation status of RAB22A, STX1B2, LGALS3BP, DNASE1L1 and PREX1 correlates with disease activity in lupus patients.

Repeat Polymorphisms within Gene Regions: Phenotypic and Evolutionary Implications

We have developed an algorithm that predicted 11,265 potentially polymorphic tandem repeats within transcribed sequences. We estimate that 22% (2,207/9,717) of the annotated clusters within UniGene contain at least one potentially polymorphic locus. Our predictions were tested by allelotyping a panel of approximately 30 individuals for 5% of these regions, confirming polymorphism for more than half the loci tested. Our study indicates that tandem-repeat polymorphisms in genes are more common than is generally believed. Approximately 8% of these loci are within coding sequences and, if polymorphic, would result in frameshifts. Our catalogue of putative polymorphic repeats within transcribed sequences comprises a large set of potentially phenotypic or disease-causing loci. In addition, from the anomalous character of the repetitive sequences within unannotated clusters, we also conclude that the UniGene cluster count substantially overestimates the number of genes in the human genome. We hypothesize that polymorphisms in repeated sequences occur with some baseline distribution, on the basis of repeat homogeneity, size, and sequence composition, and that deviations from that distribution are indicative of the nature of selection pressure at that locus. We find evidence of selective maintenance of the ability of some genes to respond very rapidly, perhaps even on intragenerational timescales, to fluctuating selective pressures.

Identification of a novel senolytic agent, navitoclax, targeting the Bcl‐2 family of anti‐apoptotic factors

Clearing senescent cells extends healthspan in mice. Using a hypothesis‐driven bioinformatics‐based approach, we recently identified pro‐survival pathways in human senescent cells that contribute to their resistance to apoptosis. This led to identification of dasatinib (D) and quercetin (Q) as senolytics, agents that target some of these pathways and induce apoptosis preferentially in senescent cells. Among other pro‐survival regulators identified was Bcl‐xl. Here, we tested whether the Bcl‐2 family inhibitors, navitoclax (N) and TW‐37 (T), are senolytic. Like D and Q, N is senolytic in some, but not all types of senescent cells: N reduced viability of senescent human umbilical vein epithelial cells (HUVECs), IMR90 human lung fibroblasts, and murine embryonic fibroblasts (MEFs), but not human primary preadipocytes, consistent with our previous finding that Bcl‐xl siRNA is senolytic in HUVECs, but not preadipocytes. In contrast, T had little senolytic activity. N targets Bcl‐2, Bcl‐xl, and Bcl‐w, while T targets Bcl‐2, Bcl‐xl, and Mcl‐1. The combination of Bcl‐2, Bcl‐xl, and Bcl‐w siRNAs was senolytic in HUVECs and IMR90 cells, while combination of Bcl‐2, Bcl‐xl, and Mcl‐1 siRNAs was not. Susceptibility to N correlated with patterns of Bcl‐2 family member proteins in different types of human senescent cells, as has been found in predicting response of cancers to N. Thus, N is senolytic and acts in a potentially predictable cell type‐restricted manner. The hypothesis‐driven, bioinformatics‐based approach we used to discover that dasatinib (D) and quercetin (Q) are senolytic can be extended to increase the repertoire of senolytic drugs, including additional cell type‐specific senolytic agents.

The write position: A survey of perceived contributions to papers based on byline position and number of authors

Publications in peer‐reviewed journals are a major criterion for assessing scientists for promotion, tenure or funding (Beasley & Wright, 2003; Thomas et al , 2004). Yet, there are different ways of becoming an author on a scientific publication, and not all authors are viewed as equal contributors. Qualitatively speaking, those listed first or last in the byline are generally apportioned more credit for the work than middle authors. However, exactly how much authors are perceived to contribute from their byline position is not known. Given the central role of publications in evaluating scientific productivity and the trend towards more authors per published paper (Fig 1), it is important that we gain a better quantitative understanding of these perceptions. Figure 1. Frequency distribution of the number of authors per paper by decade since 1966. The graph was generated using MEDLINE bibliographic data and truncated at 15 authors maximum. All types of publication were included in the analysis, with journal article the most common type (86%). It is often not possible to objectively determine exactly how much credit each author on a paper deserves for the sum total of the work performed (Laurance, 2006; Tscharntke et al , 2007). Presumably, a larger number of authors dilutes the relative credit awarded to each contributor; however, this effect has not been scientifically confirmed or quantified. Yet, the number of authors per paper in PubMed is growing—so‐called ‘author inflation’. This is an increasing trend in many research fields largely owing to the increasing pressure to publish, specialization of research expertise, collaborative efforts and honorary authorships, also known as ‘gift authorships’ (Drenth, 1998; Lazar, 2004; Mussurakis, 1993; Kwok, 2005; Mowatt et al , 2002; Smith, 1994; Tarnow, 2004a). Although the International Committee of Medical Journal Editors (ICMJE; Washington, DC, USA) has formally …

Ska3 Is Required for Spindle Checkpoint Silencing and the Maintenance of Chromosome Cohesion in Mitosis

The mitotic spindle checkpoint monitors proper bipolar attachment of chromosomes to the mitotic spindle. Previously, depletion of the novel kinetochore complex Ska1/Ska2 was found to induce a metaphase delay. By using bioinformatics, we identified C13orf3, predicted to associate with kinetochores. Recently, three laboratories independently indentified C13orf3 as an additional Ska complex component, and therefore we adopted the name Ska3. We found that cells depleted of Ska3 by RNAi achieve metaphase alignment but fail to silence the spindle checkpoint or enter anaphase. After hours of metaphase arrest, chromatids separate but retain robust kinetochore-microtubule attachments. Ska3-depleted cells accumulate high levels of the checkpoint protein Bub1 at kinetochores. Ska3 protein accumulation at kinetochores in prometaphase is dependent on Sgo1 protein. Sgo1, which accumulates at the centromeres earlier, in prophase, is not dependent on Ska3. Sgo1-depleted cells show a stronger premature chromatid separation phenotype than those depleted of Ska3. We hypothesize that Ska3 functions to coordinate checkpoint signaling from the microtubule binding sites within a kinetochore by laterally linking the individual binding sites. We suggest that this network plays a major role in silencing the spindle checkpoint when chromosomes are aligned at metaphase to allow timely anaphase onset and mitotic exit.

Extending the mutual information measure to rank inferred literature relationships

BackgroundWithin the peer-reviewed literature, associations between two things are not always recognized until commonalities between them become apparent. These commonalities can provide justification for the inference of a new relationship where none was previously known, and are the basis of most observation-based hypothesis formation. It has been shown that the crux of the problem is not finding inferable associations, which are extraordinarily abundant given the scale-free networks that arise from literature-based associations, but determining which ones are informative. The Mutual Information Measure (MIM) is a well-established method to measure how informative an association is, but is limited to direct (i.e. observable) associations.ResultsHerein, we attempt to extend the calculation of mutual information to indirect (i.e. inferable) associations by using the MIM of shared associations. Objects of general research interest (e.g. genes, diseases, phenotypes, drugs, ontology categories) found within MEDLINE are used to create a network of associations for evaluation.ConclusionsMutual information calculations can be effectively extended into implied relationships and a significance cutoff estimated from analysis of random word networks. Of the models tested, the shared minimum MIM (MMIM) model is found to correlate best with the observed strength and frequency of known associations. Using three test cases, the MMIM method tends to rank more specific relationships higher than counting the number of shared relationships within a network.

404 not found: the stability and persistence of URLs published in MEDLINE

MOTIVATION The advent of the World Wide Web has enabled unprecedented supplementation of traditional journal publications, allowing access to resources, such as video, sound, software, databases, datasets too large to publish, and even supplementary information and discussion. However, unlike traditional publications, continued availability of these online resources is not guaranteed. An automated survey was conducted to quantify the growth in Uniform Resource Locators (URLs) published to date in MEDLINE abstracts, their current availability and distribution by journal. RESULTS Of 1630 unique URLs identified, formatting and/or spelling errors were detected within 201 (12%) of them as published. After corrections were made, a survey revealed that approximately 63% of these URLs were consistently available, and another 19% were available intermittently. The rate of failure was far worse for anonymous login to FTP sites, with only 12 of 33 sites (36%) responding. This survey also shows that journals vary disproportionately in the number of web citations published, suggesting policy implementation among a few could have a profound impact overall. Out of the 306 journals with a URL published in an abstract, Bioinformatics published the most (12% of total). AVAILABILITY URL database and program available by request.

A global meta-analysis of microarray expression data to predict unknown gene functions and estimate the literature-data divide

MOTIVATION Approximately 9334 (37%) of human genes have no publications documenting their function and, for those that are published, the number of publications per gene is highly skewed. Furthermore, for reasons not clear, the entry of new gene names into the literature has slowed in recent years. If we are to better understand human/mammalian biology and complete the catalog of human gene function, it is important to finish predicting putative functions for these genes based upon existing experimental evidence. RESULTS A global meta-analysis (GMA) of all publicly available GEO two-channel human microarray datasets (3551 experiments total) was conducted to identify genes with recurrent, reproducible patterns of co-regulation across different conditions. Patterns of co-expression were divided into parallel (i.e. genes are up and down-regulated together) and anti-parallel. Several ranking methods to predict a genes function based on its top 20 co-expressed gene pairs were compared. In the best method, 34% of predicted Gene Ontology (GO) categories matched exactly with the known GO categories for approximately 5000 genes analyzed versus only 3% for random gene sets. Only 2.4% of co-expressed gene pairs were found as co-occurring gene pairs in MEDLINE. CONCLUSIONS Via a GO enrichment analysis, genes co-expressed in parallel with the query gene were frequently associated with the same GO categories, whereas anti-parallel genes were not. Combining parallel and anti-parallel genes for analysis resulted in fewer significant GO categories, suggesting they are best analyzed separately. Expression databases contain much unexpected genetic knowledge that has not yet been reported in the literature. A total of 1642 Human genes with unknown function were differentially expressed in at least 30 experiments. AVAILABILITY Data matrix available upon request.