Dislocation of primary total hip arthroplasty and the risk of redislocation.

6554 primary total hip arthroplasties were reviewed. Risk factors for dislocation were analysed to assess which were important in terms of predicting recurrent instability. The patients risk of having a second dislocation was independently associated with the surgical approach adopted (p = 0.03) and the time to first dislocation from the primary hip replacement (p = 0.002). Early dislocators whose surgery was performed through an anterolateral approach had less recurrence than late dislocators through a posterior or transtrochanteric approach. None of the other risk factors including head size (p = 0.59), modularity (p = 0.54), mechanism of dislocation (p = 0.23), leg length discrepancy (p = 0.69) and acetabular inclination (p = 0.31) were influential. The use of an abduction brace was not useful in preventing a further dislocation with 69.2% of those braced re-dislocating compared to 68.5% who were not braced (p = 0.96).

Influence of weather variables on pain severity in end-stage osteoarthritis.

PURPOSE: Patients often attribute increasing pain in an arthritic joint to changing weather patterns. Studies examining the impact of weather on pain severity have yielded equivocal and sometimes contradictory results. The relationship between subchondral pseudocysts and the role they play in this phenomenon has not been explored. METHODS: Fifty-three patients with end-stage osteoarthritis of the hip completed daily pain severity visual analogue scale (VAS) scores over a one month period. Radiographs were reviewed to determine the presence of pseudocysts. Data pertaining to precipitation, atmospheric pressure and temperature were collected from the nearest weather station. A generalised linear mixed model was used to explore the relationship between weather variables, cysts and pain severity. RESULTS: Pain levels increased as a function of absolute change in atmospheric pressure from one day to the next. Precipitation, temperature and the presence of subchondral pseudocysts were not shown to influence pain severity. CONCLUSIONS: This data supports the belief held by many osteoarthritic patients that changing weather patterns influence their pain severity.

Transcriptomic coordination in the human metabolic network reveals links between n-3 fat intake, adipose tissue gene expression and metabolic health.

Understanding the molecular link between diet and health is a key goal in nutritional systems biology. As an alternative to pathway analysis, we have developed a joint multivariate and network-based approach to analysis of a dataset of habitual dietary records, adipose tissue transcriptomics and comprehensive plasma marker profiles from human volunteers with the Metabolic Syndrome. With this approach we identified prominent co-expressed sub-networks in the global metabolic network, which showed correlated expression with habitual n-3 PUFA intake and urinary levels of the oxidative stress marker 8-iso-PGF(2α). These sub-networks illustrated inherent cross-talk between distinct metabolic pathways, such as between triglyceride metabolism and production of lipid signalling molecules. In a parallel promoter analysis, we identified several adipogenic transcription factors as potential transcriptional regulators associated with habitual n-3 PUFA intake. Our results illustrate advantages of network-based analysis, and generate novel hypotheses on the transcriptomic link between habitual n-3 PUFA intake, adipose tissue function and oxidative stress.

Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome.

BACKGROUND: Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. RESULTS: Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p < 0.05), followed by muscle (601 genes) and adipose (16 genes). Results from modified GSEA showed that the high-CLA beef diet affected diverse biological processes across the three tissues, and that the majority of pathway changes reached significance only with the bi-directional test. Combining the liver tissue microarray results with plasma marker data revealed 110 CLA-sensitive genes showing strong canonical correlation with one or more plasma markers of metabolic health, and 9 significantly overrepresented pathways among this set; each of these pathways was also significantly changed by the high-CLA diet. Closer inspection of two of these pathways--selenoamino acid metabolism and steroid biosynthesis--illustrated clear diet-sensitive changes in constituent genes, as well as strong correlations between gene expression and plasma markers of metabolic syndrome independent of the dietary effect. CONCLUSION: Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of analysis has the potential to generate novel transcriptome-based biomarkers of disease.