Association of ACE polymorphisms with left ventricular hypertrophy

The angiotensin converting enzyme gene (ACE) is a candidate gene for an individual's genetic susceptibility to left ventricular hypertrophy (LVH). LVH has long been thought to be an end point of essential hypertension (EH), rather than a separate entity, though it is influenced by a unique set of hormonal, vascular and genetic factors. In this study, we attempted to determine whether two representative polymorphisms of the ACE gene, ACE I/D and 2350 G>A, known to be associated with EH and to influence plasma ACE levels most significantly, could implicate ACE as a quantitative trait locus (QTL) for LVH. We carried out a retrospective, case-control study of the two ACE polymorphisms amongst 180 nationals (50 LVH patients and 130 controls) from the United Arab Emirates--an ethnic group characterized by no alcohol intake and no cigarette smoking--for correlations with LVH. Clinical diagnosis of LVH was based on echocardiographic and ECG criteria. ACE I/D and 2350 G>A genotypes were determined by PCR and restriction digestion. Univariate and multivariate logistic regression analyses revealed an association between ACE polymorphisms and LVH. Haplotype analysis further supported this finding. ACE I/D and ACE 2350 G>A polymorphisms are in strong linkage disequilibrium and are associated with LVH, suggesting that ACE is likely to be a QTL for LVH.     

Can Zipf's law be adapted to normalize microarrays?

Background  

Normalization is the process of removing non-biological sources of variation between array experiments. Recent investigations of data in gene expression databases for varying organisms and tissues have shown that the majority of expressed genes exhibit a power-law distribution with an exponent close to -1 (i.e. obey Zipf's law). Based on the observation that our single channel and two channel microarray data sets also followed a power-law distribution, we were motivated to develop a normalization method based on this law, and examine how it compares with existing published techniques. A computationally simple and intuitively appealing technique based on this observation is presented.     

Pre-symptomatic detection of prions by cyclic amplification of protein misfolding

Transmissible spongiform encephalopathies (TSEs) are neurodegenerative disorders affecting humans and animals. At present, it is not possible to recognize individuals incubating the disease before the clinical symptoms appear. We investigated the effectiveness of the "Protein Misfolding Cyclic Amplification" (PMCA) technology to detect the protease-resistance disease-associated prion protein (PrP(res)) in pre-symptomatic stages. PMCA allowed detection of PrP(res) in the brain of pre-symptomatic hamsters, enabling a clear identification of infected animals as early as two weeks after inoculation. Furthermore, PMCA was able to amplify minute quantities of PrP(res) from a variety of experimental and natural TSEs. Finally, PMCA allowed the demonstration of PrP(res) in an experimentally infected cow 32 month post-inoculation, that did not show clinical signs and was negative by standard Western blot analysis. Our findings indicate that PMCA may be useful for the development of an ultra-sensitive diagnostic test to minimize the risk of further propagation of TSEs.