Evaluation of 16S rDNA-based community profiling for human microbiome research

The Human Microbiome Project will establish a reference data set for analysis of the microbiome of healthy adults by surveying multiple body sites from 300 people and generating data from over 12,000 samples. To characterize these samples, the participating sequencing centers evaluated and adopted 16S rDNA community profiling protocols for ABI 3730 and 454 FLX Titanium sequencing. In the course of establishing protocols, we examined the performance and error characteristics of each technology, and the relationship of sequence error to the utility of 16S rDNA regions for classification- and OTU-based analysis of community structure. The data production protocols used for this work are those used by the participating centers to produce 16S rDNA sequence for the Human Microbiome Project. Thus, these results can be informative for interpreting the large body of clinical 16S rDNA data produced for this project.     

Dynamic modelling under uncertainty: the case of Trypanosoma brucei energy metabolism

Kinetic models of metabolism require detailed knowledge of kinetic parameters. However, due to measurement errors or lack of data this knowledge is often uncertain. The model of glycolysis in the parasitic protozoan Trypanosoma brucei is a particularly well analysed example of a quantitative metabolic model, but so far it has been studied with a fixed set of parameters only. Here we evaluate the effect of parameter uncertainty. In order to define probability distributions for each parameter, information about the experimental sources and confidence intervals for all parameters were collected. We created a wiki-based website dedicated to the detailed documentation of this information: the SilicoTryp wiki (http://silicotryp.ibls.gla.ac.uk/wiki/Glycolysis). Using information collected in the wiki, we then assigned probability distributions to all parameters of the model. This allowed us to sample sets of alternative models, accurately representing our degree of uncertainty. Some properties of the model, such as the repartition of the glycolytic flux between the glycerol and pyruvate producing branches, are robust to these uncertainties. However, our analysis also allowed us to identify fragilities of the model leading to the accumulation of 3-phosphoglycerate and/or pyruvate. The analysis of the control coefficients revealed the importance of taking into account the uncertainties about the parameters, as the ranking of the reactions can be greatly affected. This work will now form the basis for a comprehensive Bayesian analysis and extension of the model considering alternative topologies.     

Intracranial aneurysm risk locus 5q23.2 is associated with elevated systolic blood pressure

Although genome-wide association studies (GWAS) have identified hundreds of complex trait loci, the pathomechanisms of most remain elusive. Studying the genetics of risk factors predisposing to disease is an attractive approach to identify targets for functional studies. Intracranial aneurysms (IA) are rupture-prone pouches at cerebral artery branching sites. IA is a complex disease for which GWAS have identified five loci with strong association and a further 14 loci with suggestive association. To decipher potential underlying disease mechanisms, we tested whether there are IA loci that convey their effect through elevating blood pressure (BP), a strong risk factor of IA. We performed a meta-analysis of four population-based Finnish cohorts (n(FIN) = 11 266) not selected for IA, to assess the association of previously identified IA candidate loci (n = 19) with BP. We defined systolic BP (SBP), diastolic BP, mean arterial pressure, and pulse pressure as quantitative outcome variables. The most significant result was further tested for association in the ICBP-GWAS cohort of 200 000 individuals. We found that the suggestive IA locus at 5q23.2 in PRDM6 was significantly associated with SBP in individuals of European descent (p(FIN) = 3.01E-05, p(ICBP-GWAS) = 0.0007, p(ALL) = 8.13E-07). The risk allele of IA was associated with higher SBP. PRDM6 encodes a protein predominantly expressed in vascular smooth muscle cells. Our study connects a complex disease (IA) locus with a common risk factor for the disease (SBP). We hypothesize that common variants in PRDM6 can contribute to altered vascular wall structure, hence increasing SBP and predisposing to IA. True positive associations often fail to reach genome-wide significance in GWAS. Our findings show that analysis of traditional risk factors as intermediate phenotypes is an effective tool for deciphering hidden heritability. Further, we demonstrate that common disease loci identified in a population isolate may bear wider significance.     

Loss of ATRX, genome instability, and an altered DNA damage response are hallmarks of the alternative lengthening of telomeres pathway

The Alternative Lengthening of Telomeres (ALT) pathway is a telomerase-independent pathway for telomere maintenance that is active in a significant subset of human cancers and in vitro immortalized cell lines. ALT is thought to involve templated extension of telomeres through homologous recombination, but the genetic or epigenetic changes that unleash ALT are not known. Recently, mutations in the ATRX/DAXX chromatin remodeling complex and histone H3.3 were found to correlate with features of ALT in pancreatic neuroendocrine cancers, pediatric glioblastomas, and other tumors of the central nervous system, suggesting that these mutations might contribute to the activation of the ALT pathway in these cancers. We have taken a comprehensive approach to deciphering ALT by applying genomic, molecular biological, and cell biological approaches to a panel of 22 ALT cell lines, including cell lines derived in vitro. Here we show that loss of ATRX protein and mutations in the ATRX gene are hallmarks of ALT-immortalized cell lines. In addition, ALT is associated with extensive genome rearrangements, marked micronucleation, defects in the G2/M checkpoint, and altered double-strand break (DSB) repair. These attributes will facilitate the diagnosis and treatment of ALT positive human cancers.     

Further Evidence of Subphenotype Association with Systemic Lupus Erythematosus Susceptibility Loci: A European Cases Only Study

Introduction

Systemic Lupus Erythematosus (SLE) shows a spectrum of clinical manifestations that complicate its diagnosis, treatment and research. This variability is likely related with environmental exposures and genetic factors among which known SLE susceptibility loci are prime candidates. The first published analyses seem to indicate that this is the case for some of them, but results are still inconclusive and we aimed to further explore this question.

Methods

European SLE patients, 1444, recruited at 17 centres from 10 countries were analyzed. Genotypes for 26 SLE associated SNPs were compared between patients with and without each of 11 clinical features: ten of the American College of Rheumatology (ACR) classification criteria (except ANAs) and age of disease onset. These analyses were adjusted for centre of recruitment, top ancestry informative markers, gender and time of follow-up. Overlap of samples with previous studies was excluded for assessing replication.

Results

There were three new associations: the SNPs in XKR6 and in FAM167A-BLK were associated with lupus nephritis (OR = 0.76 and 1.30, P_corr = 0.007 and 0.03, respectively) and the SNP of MECP2, which is in chromosome X, with earlier age of disease onset in men. The previously reported association of STAT4 with early age of disease onset was replicated. Some other results were suggestive of the presence of additional associations. Together, the association signals provided support to some previous findings and to the characterization of lupus nephritis, autoantibodies and age of disease onset as the clinical features more associated with SLE loci.

Conclusion

Some of the SLE loci shape the disease phenotype in addition to increase susceptibility to SLE. This influence is more prominent for some clinical features than for others. However, results are only partially consistent between studies and subphenotype specific GWAS are needed to unravel their genetic component.