Intra- and inter-individual genetic differences in gene expression

Genetic variation is known to influence the amount of mRNA produced by a gene. Given that the molecular machines control mRNA levels of multiple genes, we expect genetic variation in the components of these machines would influence multiple genes in a similar fashion. In this study we show that this assumption is correct by using correlation of mRNA levels measured independently in the brain, kidney or liver of multiple, genetically typed, mice strains to detect shared genetic influences. These correlating groups of genes (CGG) have collective properties that account for 40-90% of the variability of their constituent genes and in some cases, but not all, contain genes encoding functionally related proteins. Critically, we show that the genetic influences are essentially tissue specific and consequently the same genetic variations in the one animal may up-regulate a CGG in one tissue but down-regulate the same CGG in a second tissue. We further show similarly paradoxical behaviour of CGGs within the same tissues of different individuals. The implication of this study is that this class of genetic variation can result in complex inter- and intra-individual and tissue differences and that this will create substantial challenges to the investigation of phenotypic outcomes, particularly in humans where multiple tissues are not readily available.

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Alumina-on-alumina total hip replacement for femoral neck fracture in healthy patients

<p>Abstract</p> <p>Background</p> <p>Total hip replacement is considered the best option for treatment of displaced intracapsular fractures of the femoral neck (FFN). The size of the femoral head is an important factor that influences the outcome of a total hip arthroplasty (THA): implants with a 28 mm femoral head are more prone to dislocate than implants with a 32 mm head. Obviously, a large head coupled to a polyethylene inlay can lead to more wear, osteolysis and failure of the implant. Ceramic induces less friction and minimal wear even with larger heads.</p> <p>Methods</p> <p>A total of 35 THAs were performed for displaced intracapsular FFN, using a 32 mm alumina-alumina coupling.</p> <p>Results</p> <p>At a mean follow-up of 80 months, 33 have been clinically and radiologically reviewed. None of the implants needed revision for any reason, none of the cups were considered to have failed, no dislocations nor breakage of the ceramic components were recorded. One anatomic cementless stem was radiologically loose.</p> <p>Conclusions</p> <p>On the basis of our experience, we suggest that ceramic-on-ceramic coupling offers minimal friction and wear even with large heads.</p

Long-term durability of alumina ceramic heads in THA

Background: The optimal type of bearing for hip arthroplasty remains a matter of debate. Ceramic-on-polyethylene (CoP) bearings are frequently used in younger and more active patients to reduce wear and increase biocompatibility compared to Metal-on-Polyethylene (MoP) bearings. However, in comparison to metal heads, the fracture risk of ceramic heads is higher. In addition, ceramic head fractures pose a serious complication which often necessitates major revision surgery. To date, there are no long-term data (>20 years of follow-up) reporting fracture rates of the ceramic femoral heads in CoP bearings. The purpose of this research was to investigate long-term CoP fracture rate. Methods: We evaluated the clinical and radiographic results of 348 cementless THAs treated with 2nd generation Biolox® Al2O3 Ceramic-on-Polyethylene (CoP) bearings consecutively implanted between January 1985 and December 1989. The mean age at implantation was 57 years. The patients were followed for a minimum of 20 years. At the final 111 had died, and 5 were lost to follow-up. The cumulative incidence of ceramic head fractures in the long-term was estimated using a competing risk analysis. Results: The cumulative incidence of ceramic head fracture after 22-years was estimated with a competing risk analysis at 0.29% after 22-years (SE = 2.09%; 95% - CI: 0.03-1.5%). The radiographic analysis revealed no impending failures at final follow-up. Discussion/Conclusion: The fracture rate of second-generation ceramic heads using a CoP articulation remains very low into the third decade after cementless THA

Using Network Component Analysis to Dissect Regulatory Networks Mediated by Transcription Factors in Yeast

Understanding the relationship between genetic variation and gene expression is a central question in genetics. With the availability of data from high-throughput technologies such as ChIP-Chip, expression, and genotyping arrays, we can begin to not only identify associations but to understand how genetic variations perturb the underlying transcription regulatory networks to induce differential gene expression. In this study, we describe a simple model of transcription regulation where the expression of a gene is completely characterized by two properties: the concentrations and promoter affinities of active transcription factors. We devise a method that extends Network Component Analysis (NCA) to determine how genetic variations in the form of single nucleotide polymorphisms (SNPs) perturb these two properties. Applying our method to a segregating population of Saccharomyces cerevisiae, we found statistically significant examples of trans-acting SNPs located in regulatory hotspots that perturb transcription factor concentrations and affinities for target promoters to cause global differential expression and cis-acting genetic variations that perturb the promoter affinities of transcription factors on a single gene to cause local differential expression. Although many genetic variations linked to gene expressions have been identified, it is not clear how they perturb the underlying regulatory networks that govern gene expression. Our work begins to fill this void by showing that many genetic variations affect the concentrations of active transcription factors in a cell and their affinities for target promoters. Understanding the effects of these perturbations can help us to paint a more complete picture of the complex landscape of transcription regulation. The software package implementing the algorithms discussed in this work is available as a MATLAB package upon request

The Complex Genetic Architecture of the Metabolome

Discovering links between the genotype of an organism and its metabolite levels can increase our understanding of metabolism, its controls, and the indirect effects of metabolism on other quantitative traits. Recent technological advances in both DNA sequencing and metabolite profiling allow the use of broad-spectrum, untargeted metabolite profiling to generate phenotypic data for genome-wide association studies that investigate quantitative genetic control of metabolism within species. We conducted a genome-wide association study of natural variation in plant metabolism using the results of untargeted metabolite analyses performed on a collection of wild Arabidopsis thaliana accessions. Testing 327 metabolites against >200,000 single nucleotide polymorphisms identified numerous genotype–metabolite associations distributed non-randomly within the genome. These clusters of genotype–metabolite associations (hotspots) included regions of the A. thaliana genome previously identified as subject to recent strong positive selection (selective sweeps) and regions showing trans-linkage to these putative sweeps, suggesting that these selective forces have impacted genome-wide control of A. thaliana metabolism. Comparing the metabolic variation detected within this collection of wild accessions to a laboratory-derived population of recombinant inbred lines (derived from two of the accessions used in this study) showed that the higher level of genetic variation present within the wild accessions did not correspond to higher variance in metabolic phenotypes, suggesting that evolutionary constraints limit metabolic variation. While a major goal of genome-wide association studies is to develop catalogues of intraspecific variation, the results of multiple independent experiments performed for this study showed that the genotype–metabolite associations identified are sensitive to environmental fluctuations. Thus, studies of intraspecific variation conducted via genome-wide association will require analyses of genotype by environment interaction. Interestingly, the network structure of metabolite linkages was also sensitive to environmental differences, suggesting that key aspects of network architecture are malleable