Validation and functional annotation of expression-based clusters based on gene ontology

BACKGROUND: The biological interpretation of large-scale gene expression data is one of the paramount challenges in current bioinformatics. In particular, placing the results in the context of other available functional genomics data, such as existing bio-ontologies, has already provided substantial improvement for detecting and categorizing genes of interest. One common approach is to look for functional annotations that are significantly enriched within a group or cluster of genes, as compared to a reference group. RESULTS: In this work, we suggest the information-theoretic concept of mutual information to investigate the relationship between groups of genes, as given by data-driven clustering, and their respective functional categories. Drawing upon related approaches (Gibbons and Roth, Genome Research 12:1574-1581, 2002), we seek to quantify to what extent individual attributes are sufficient to characterize a given group or cluster of genes. CONCLUSION: We show that the mutual information provides a systematic framework to assess the relationship between groups or clusters of genes and their functional annotations in a quantitative way. Within this framework, the mutual information allows us to address and incorporate several important issues, such as the interdependence of functional annotations and combinatorial combinations of attributes. It thus supplements and extends the conventional search for overrepresented attributes within a group or cluster of genes. In particular taking combinations of attributes into account, the mutual information opens the way to uncover specific functional descriptions of a group of genes or clustering result. All datasets and functional annotations used in this study are publicly available. All scripts used in the analysis are provided as additional files

Identifying individual-based injury patterns in multi-trauma road users by using an association rule mining method

In many road crashes the human body is exposed to high forces, commonly resulting in multiple injuries. This study of linked road crash data aimed to identify co-occurring injuries in multiple injured road users by using a novel application of a data mining technique commonly used in Market Basket Analysis. We expected that some injuries are statistically associated with each other and form Individual-Based Injury Patterns (IBIPs) and further that specific road users are associated with certain IBIPs. First, a new injury taxonomy was developed through a four-step process to allow the use of injury data recorded from either of the two major dictionaries used to document anatomical injury. Then data from the Swedish Traffic Accident Data Acquisition, which includes crash circumstances from the police and injury information from hospitals, was analysed for the years 2011 to 2017. The injury data was analysed using the Apriori algorithm to identify statistical association between injuries (IBIP). Each IBIP were then used as the outcome variable in logistic regression modelling to identify associations between specific road user types and IBIPs. A total of 48,544 individuals were included in the analysis of which 36,480 (75.1%) had a single injury category recorded and 12,064 (24.9%) were considered multiply injured. The data mining analysis identified 77 IBIPs in the multiply injured sample and 16 of these were associated with only one road user type. IBIPs and their relation to road user type are one step on the journey towards developing a tool to better understand and quantify injury severity and thereby improve the evidence-base supporting prioritisation of road safety countermeasures

Characterisation of the global transcriptional response to heat shock and the impact of individual genetic variation

Abstract Background The heat shock transcriptional response is essential to effective cellular function under stress. This is a highly heritable trait but the nature and extent of inter-individual variation in heat shock response remains unresolved. Methods We determined global transcription profiles of the heat shock response for a panel of lymphoblastoid cell lines established from 60 founder individuals in the Yoruba HapMap population. We explore the observed differentially expressed gene sets following heat shock, establishing functional annotations, underlying networks and nodal genes involving heat shock factor 1 recruitment. We define a multivariate phenotype for the global transcriptional response to heat shock using partial least squares regression and map this quantitative trait to associated genetic variation in search of the major genomic modulators. Results A comprehensive dataset of differentially expressed genes following heat shock in humans is presented. We identify nodal genes downstream of heat shock factor 1 in this gene set, notably involving ubiquitin C and small ubiquitin-like modifiers together with transcription factors. We dissect a multivariate phenotype for the global heat shock response which reveals distinct clustering of individuals in terms of variance of the heat shock response and involves differential expression of genes involved in DNA replication and cell division in some individuals. We find evidence of genetic associations for this multivariate response phenotype that involves trans effects modulating expression of genes following heat shock, including HSF1 and UBQLN1. Conclusion This study defines gene expression following heat shock for a cohort of individuals, establishing insights into the biology of the heat shock response and hypotheses for how variation in this may be modulated by underlying genetic diversity

Systemic pro- and anti-inflammatory profiles in acute non-specific low back pain : an exploratory longitudinal study of the relationship to six-month outcome

Objectives: Pro-inflammatory molecules are thought to underpin the development of chronic low back pain (LBP). Although research has begun to explore the association between pro-inflammatory molecules in acute LBP and long-term outcome, no study has explored the role of anti-inflammatory molecules. We aimed to explore whether levels of systemic pro- and anti-inflammatory molecules 1) changed over a period of six months from the onset of acute LBP; 2) differed between people who were recovered (N = 11) and unrecovered (N = 24) from their episode of LBP at six months; 3) baseline psychological factors were related to inflammatory molecule serum concentrations at baseline, three and six months. Methods: We retrospectively included participants with acute LBP included from a larger prospective trial and examined blood samples for the measurement of pro- and anti-inflammatory molecules and measures of pain, disability, and psychological factors at baseline, three and six months. Results: The serum concentrations of pro- and anti-inflammatory molecules did not differ over time when compared between participants who recovered and those who did not recover at six month follow-up. At three months, the unrecovered group had higher interleukin (IL)-8 and IL-10 serum concentrations than the recovered group. Baseline psychological factors were not related to inflammatory molecules at any time point. Discussion: This exploratory study showed that levels of systemic inflammatory molecules did not change over the course of LBP, irrespective of whether people were recovered or unrecovered at six months. There was no relationship between acute-stage psychological factors and systemic inflammatory molecules. Further investigation is needed to elucidate the contribution of pro- and anti-inflammatory molecules to long-term LBP outcome

Extensive characterization of NF-κB binding uncovers non-canonical motifs and advances the interpretation of genetic functional traits

Background Genetic studies have provided ample evidence of the influence of non-coding DNA polymorphisms on trait variance, particularly those occurring within transcription factor binding sites. Protein binding microarrays and other platforms that can map these sites with great precision have enhanced our understanding of how a single nucleotide polymorphism can alter binding potential within an in vitro setting, allowing for greater predictive capability of its effect on a transcription factor binding site. Results We have used protein binding microarrays and electrophoretic mobility shift assay-sequencing (EMSA-Seq), a deep sequencing based method we developed to analyze nine distinct human NF-κB dimers. This family of transcription factors is one of the most extensively studied, but our understanding of its DNA binding preferences has been limited to the originally described consensus motif, GGRRNNYYCC. We highlight differences between NF-κB family members and also put under the spotlight non-canonical motifs that have so far received little attention. We utilize our data to interpret the binding of transcription factors between individuals across 1,405 genomic regions laden with single nucleotide polymorphisms. We also associated binding correlations made using our data with risk alleles of disease and demonstrate its utility as a tool for functional studies of single nucleotide polymorphisms in regulatory regions. Conclusions NF-κB dimers bind specifically to non-canonical motifs and these can be found within genomic regions in which a canonical motif is not evident. Binding affinity data generated with these different motifs can be used in conjunction with data from chromatin immunoprecipitation-sequencing (ChIP-Seq) to enable allele-specific analyses of expression and transcription factor-DNA interactions on a genome-wide scale.Wellcome Trust (London, England) (grant 075491/Z/04)European Commission (Seventh Framework Programme FP7/2007-2013: Model-In (222008))European Commission (Seventh Framework Programme FP7 ITN Network INTEGER (214902))Medical Research Council (Canada) (MRC project grant G0700818

The impact of COVID-19 and associated lockdowns on traumatic spinal cord injury incidence: a population based study

Study design Natural experiment Objectives To determine whether COVID-19 restrictions were associated with changes in the incidence of traumatic spinal cord injury (TSCI) in Scotland. Setting The Queen Elizabeth National Spinal Injuries Unit (QENSIU), the sole provider of treatment for TSCI in Scotland. Methods Time series analysis of all admissions for TSCI between 1st January 2015 and 31st August 2022. Results Over the 8-year study period, 745 patients were admitted to the QENSIU with a TSCI. Interrupted time series analysis showed that level 3 and 4 COVID-19 lockdown restrictions (the most severe levels) were associated with lower incidence of TSCI (RR 0.63, CI% CI 0.47, 0.82, p < 0.001). The associations were stronger in people aged over 45 (additive interaction p = 0.001), males (additive interaction p = 0.01) and non-tetraplegia (additive interaction p = 0.002). The incidence of TSCI due to deliberate self-harm was higher (0.41 versus 0.23 per month) during restrictions. Conclusions Overall, TSCI incidence reduced in Scotland when lockdowns were implemented, presumably due to lower engagement in risky activities. The increase in TSCI due to deliberate self-harm may reflect increased mental health problems and social isolation and should be anticipated and targeted in future pandemics. The change in incidence during the COVID-19 pandemic may have an economic impact and see a temporary reduction in the burden on health and social care. The results of this study will be useful for resource planning in future pandemics

IgD attenuates the IgM-induced anergy response in transitional and mature B cells

Self-tolerance by clonal anergy of B cells is marked by an increase in IgD and decrease in IgM antigen receptor surface expression, yet the function of IgD on anergic cells is obscure. Here we define the RNA landscape of the in vivo anergy response, comprising 220 induced sequences including a core set of 97. Failure to co-express IgD with IgM decreases overall expression of receptors for self-antigen, but paradoxically increases the core anergy response, exemplified by increased Sdc1 encoding the cell surface marker syndecan-1. IgD expressed on its own is nevertheless competent to induce calcium signalling and the core anergy mRNA response. Syndecan-1 induction correlates with reduction of surface IgM and is exaggerated without surface IgD in many transitional and mature B cells. These results show that IgD attenuates the response to self-antigen in anergic cells and promotes their accumulation. In this way, IgD minimizes tolerance-induced holes in the pre-immune antibody repertoire.This work was supported by NIH grant U19 AI100627 and NHMRC grants 585490, 1016953 and 1081858 to C.C.G., NHMRC CJ Martin Fellowship 595989 to J.H.R., an Endeavour Award from the Australian Government to Z.S. and the National Collaborative Research Infrastructure Scheme Australian Phenomics Facilit

IgD attenuates the IgM-induced anergy response in transitional and mature B cells

Self-tolerance by clonal anergy of B cells is marked by an increase in IgD and decrease in IgM antigen receptor surface expression, yet the function of IgD on anergic cells is obscure. Here we define the RNA landscape of the in vivo anergy response, comprising 220 induced sequences including a core set of 97. Failure to co-express IgD with IgM decreases overall expression of receptors for self-antigen, but paradoxically increases the core anergy response, exemplified by increased Sdc1 encoding the cell surface marker syndecan-1. IgD expressed on its own is nevertheless competent to induce calcium signalling and the core anergy mRNA response. Syndecan-1 induction correlates with reduction of surface IgM and is exaggerated without surface IgD in many transitional and mature B cells. These results show that IgD attenuates the response to self-antigen in anergic cells and promotes their accumulation. In this way, IgD minimizes tolerance-induced holes in the pre-immune antibody repertoire

Synergistic cooperation and crosstalk betweenMYD88L265Pand mutations that dysregulate CD79B and surface IgM

CD79B andMYD88mutations are frequently and simultaneously detected in B cell malignancies. It is not known if these mutations cooperate or how crosstalk occurs. Here we analyze the consequences ofCD79BandMYD88L265Pmutations individually and combined in normal activated mouse B lymphocytes.CD79Bmutations alone increased surface IgM but did not enhance B cell survival, proliferation, or altered NF-κB responsive markers. Conversely, B cells expressingMYD88L265Pdecreased surface IgM coupled with accumulation of endoglycosidase H-sensitive IgM intracellularly, resembling the trafficking block in anergic B cells repeatedly stimulated by self-antigen. Mutation or overexpression of CD79B counteracted the effect ofMYD88L265PIn B cells chronically stimulated by self-antigen,CD79BandMYD88L265Pmutations in combination, but not individually, blocked peripheral deletion and triggered differentiation into autoantibody secreting plasmablasts. These results reveal that CD79B and surface IgM constitute a rate-limiting checkpoint against B cell dysregulation byMYD88L265Pand provide an explanation for the co-occurrence ofMYD88andCD79Bmutations in lymphomas

Parameter estimation for robust HMM analysis of ChIP-chip data

Tiling arrays are an important tool for the study of transcriptional activity, protein-DNA interactions and chromatin structure on a genome-wide scale at high resolution. Although hidden Markov models have been used successfully to analyse tiling array data, parameter estimation for these models is typically ad hoc. Especially in the context of ChIP-chip experiments, no standard procedures exist to obtain parameter estimates from the data. Common methods for the calculation of maximum likelihood estimates such as the Baum-Welch algorithm or Viterbi training are rarely applied in the context of tiling array analysis. Results: Here we develop a hidden Markov model for the analysis of chromatin structure ChIP-chip tiling array data, using t emission distributions to increase robustness towards outliers. Maximum likelihood estimates are used for all model parameters. Two different approaches to parameter estimation are investigated and combined into an efficient procedure. Conclusion: We illustrate an efficient parameter estimation procedure that can be used for HMM based methods in general and leads to a clear increase in performance when compared to the use of ad hoc estimates. The resulting hidden Markov model outperforms established methods like TileMap in the context of histone modification studies.13 page(s