Early Antiretroviral Therapy at High CD4 Counts Does Not Improve Arterial Elasticity: A Substudy of the Strategic Timing of AntiRetroviral Treatment (START) Trial

BACKGROUND: Both human immunodeficiency virus (HIV) infection and antiretroviral therapy (ART) may increase cardiovascular disease (CVD) risk. Vascular function assessments can be used to study CVD pathogenesis. We compared the effect of immediate versus deferred ART initiation at CD4 counts >500 cells/mm(3) on small arterial elasticity (SAE) and large artery elasticity (LAE). METHODS: Radial artery blood pressure waveforms were recorded noninvasively. Small arterial elasticity and LAE were derived from analysis of the diastolic pulse waveform. Randomized treatment groups were compared with linear models at each visit and longitudinal mixed models. RESULTS: Study visits involved 332 participants in 8 countries: mean (standard deviation [SD]) age 35 (10), 70% male, 66% nonwhite, 30% smokers, and median CD4 count 625 cells/mm(3) and 10-year Framingham risk score for CVD 1.7%. Mean (SD) SAE and LAE values at baseline were 7.3 (2.9) mL/mmHg × 100 and 16.6 (4.1) mL/mmHg × 10, respectively. Median time on ART was 47 and 12 months in the immediate and deferred ART groups, respectively. The treatment groups did not demonstrate significant within-person changes in SAE or LAE during the follow-up period, and there was no difference in mean change from baseline between treatment groups. The lack of significant differences persisted after adjustment, when restricted to early or late changes, after censoring participants in deferred group who started ART, and among subgroups defined by CVD and HIV risk factors. CONCLUSIONS: Among a diverse global population of HIV-positive persons with high CD4 counts, these randomized data suggest that ART treatment does not have a substantial influence on vascular function among younger HIV-positive individuals with preserved immunity

The Parametric Inverse Problem in Transient Scattering

Scattering problems in many areas of applied physics are governed by the wave equation. In the most usual situation, we are given the incident wave (input) and the scatterer(s) and attempt, through analytical, experimental, or numerical methods, to produce the scattered waves (output). Such procedures can be carried out in either the frequency domain or the time domain and are categorized under the general heading of “forward problems.” In a less usual, but no less important situation, we are given the incident wave (input) and the scattered waves (output) and attempt to find the scatterer(s) that produced the output. In this case, we call the procedures “inverse” problems

Estimates of array and pool-construction variance for planning efficient DNA-pooling genome wide association studies

<p>Abstract</p> <p>Background</p> <p>Until recently, genome-wide association studies (GWAS) have been restricted to research groups with the budget necessary to genotype hundreds, if not thousands, of samples. Replacing individual genotyping with genotyping of DNA pools in Phase I of a GWAS has proven successful, and dramatically altered the financial feasibility of this approach. When conducting a pool-based GWAS, how well SNP allele frequency is estimated from a DNA pool will influence a study's power to detect associations. Here we address how to control the variance in allele frequency estimation when DNAs are pooled, and how to plan and conduct the most efficient well-powered pool-based GWAS.</p> <p>Methods</p> <p>By examining the variation in allele frequency estimation on SNP arrays between and within DNA pools we determine how array variance [var(e_array)] and pool-construction variance [var(e_construction)] contribute to the total variance of allele frequency estimation. This information is useful in deciding whether replicate arrays or replicate pools are most useful in reducing variance. Our analysis is based on 27 DNA pools ranging in size from 74 to 446 individual samples, genotyped on a collective total of 128 Illumina beadarrays: 24 1M-Single, 32 1M-Duo, and 72 660-Quad.</p> <p>Results</p> <p>For all three Illumina SNP array types our estimates of var(e_array) were similar, between 3-4 × 10^-4for normalized data. Var(e_construction) accounted for between 20-40% of pooling variance across 27 pools in normalized data.</p> <p>Conclusions</p> <p>We conclude that relative to var(e_array), var(e_construction) is of less importance in reducing the variance in allele frequency estimation from DNA pools; however, our data suggests that on average it may be more important than previously thought. We have prepared a simple online tool, PoolingPlanner (available at <url>http://www.kchew.ca/PoolingPlanner/</url>), which calculates the effective sample size (ESS) of a DNA pool given a range of replicate array values. ESS can be used in a power calculator to perform pool-adjusted calculations. This allows one to quickly calculate the loss of power associated with a pooling experiment to make an informed decision on whether a pool-based GWAS is worth pursuing.</p

Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays

We use high-density single nucleotide polymorphism (SNP) genotyping microarrays to demonstrate the ability to accurately and robustly determine whether individuals are in a complex genomic DNA mixture. We first develop a theoretical framework for detecting an individual's presence within a mixture, then show, through simulations, the limits associated with our method, and finally demonstrate experimentally the identification of the presence of genomic DNA of specific individuals within a series of highly complex genomic mixtures, including mixtures where an individual contributes less than 0.1% of the total genomic DNA. These findings shift the perceived utility of SNPs for identifying individual trace contributors within a forensics mixture, and suggest future research efforts into assessing the viability of previously sub-optimal DNA sources due to sample contamination. These findings also suggest that composite statistics across cohorts, such as allele frequency or genotype counts, do not mask identity within genome-wide association studies. The implications of these findings are discussed

MSH3 polymorphisms and protein levels affect CAG repeat instability in huntington's disease mice

Expansions of trinucleotide CAG/CTG repeats in somatic tissues are thought to contribute to ongoing disease progression through an affected individual's life with Huntington's disease or myotonic dystrophy. Broad ranges of repeat instability arise between individuals with expanded repeats, suggesting the existence of modifiers of repeat instability. Mice with expanded CAG/CTG repeats show variable levels of instability depending upon mouse strain. However, to date the genetic modifiers underlying these differences have not been identified. We show that in liver and striatum the R6/1 Huntington's disease (HD) (CAG)~100 transgene, when present in a congenic C57BL/6J (B6) background, incurred expansion-biased repeat mutations, whereas the repeat was stable in a congenic BALB/cByJ (CBy) background. Reciprocal congenic mice revealed the Msh3 gene as the determinant for the differences in repeat instability. Expansion bias was observed in congenic mice homozygous for the B6 Msh3 gene on a CBy background, while the CAG tract was stabilized in congenics homozygous for the CBy Msh3 gene on a B6 background. The CAG stabilization was as dramatic as genetic deficiency of Msh2. The B6 and CBy Msh3 genes had identical promoters but differed in coding regions and showed strikingly different protein levels. B6 MSH3 variant protein is highly expressed and associated with CAG expansions, while the CBy MSH3 variant protein is expressed at barely detectable levels, associating with CAG stability. The DHFR protein, which is divergently transcribed from a promoter shared by the Msh3 gene, did not show varied levels between mouse strains. Thus, naturally occurring MSH3 protein polymorphisms are modifiers of CAG repeat instability, likely through variable MSH3 protein stability. Since evidence supports that somatic CAG instability is a modifier and predictor of disease, our data are consistent with the hypothesis that variable levels of CAG instability associated with polymorphisms of DNA repair genes may have prognostic implications for various repeat-associated diseases

The SNAPSHOT study protocol : SNAcking, Physical activity, Self-regulation, and Heart rate Over Time

Peer reviewedPublisher PD

Monogenic diabetes in children and young adults: Challenges for researcher, clinician and patient

Monogenic diabetes results from one or more mutations in a single gene which might hence be rare but has great impact leading to diabetes at a very young age. It has resulted in great challenges for researchers elucidating the aetiology of diabetes and related features in other organ systems, for clinicians specifying a diagnosis that leads to improved genetic counselling, predicting of clinical course and changes in treatment, and for patients to altered treatment that has lead to coming off insulin and injections with no alternative (Glucokinase mutations), insulin injections being replaced by tablets (e.g. low dose in HNFα or high dose in potassium channel defects -Kir6.2 and SUR1) or with tablets in addition to insulin (e.g. metformin in insulin resistant syndromes). Genetic testing requires guidance to test for what gene especially given limited resources. Monogenic diabetes should be considered in any diabetic patient who has features inconsistent with their current diagnosis (unspecified neonatal diabetes, type 1 or type 2 diabetes) and clinical features of a specific subtype of monogenic diabetes (neonatal diabetes, familial diabetes, mild hyperglycaemia, syndromes). Guidance is given by clinical and physiological features in patient and family and the likelihood of the proposed mutation altering clinical care. In this article, I aimed to provide insight in the genes and mutations involved in insulin synthesis, secretion, and resistance, and to provide guidance for genetic testing by showing the clinical and physiological features and tests for each specified diagnosis as well as the opportunities for treatment

Identification of a Novel Risk Locus for Multiple Sclerosis at 13q31.3 by a Pooled Genome-Wide Scan of 500,000 Single Nucleotide Polymorphisms

Multiple sclerosis is a chronic inflammatory demyelinating disease of the central nervous system with an important genetic component and strongest association driven by the HLA genes. We performed a pooling-based genome-wide association study of 500,000 SNPs in order to find new loci associated with the disease. After applying several criteria, 320 SNPs were selected from the microarrays and individually genotyped in a first and independent Spanish Caucasian replication cohort. The 8 most significant SNPs validated in this cohort were also genotyped in a second US Caucasian replication cohort for confirmation. The most significant association was obtained for SNP rs3129934, which neighbors the HLA-DRB/DQA loci and validates our pooling-based strategy. The second strongest association signal was found for SNP rs1327328, which resides in an unannotated region of chromosome 13 but is in linkage disequilibrium with nearby functional elements that may play important roles in disease susceptibility. This region of chromosome 13 has not been previously identified in MS linkage genome screens and represents a novel risk locus for the disease

Utility of the pooling approach as applied to whole genome association scans with high-density Affymetrix microarrays

Background: We report an attempt to extend the previously successful approach of combining SNP (single nucleotide polymorphism) microarrays and DNA pooling (SNP-MaP) employing high-density microarrays. Whereas earlier studies employed a range of Affymetrix SNP microarrays comprising from 10 K to 500 K SNPs, this most recent investigation used the 6.0 chip which displays 906,600 SNP probes and 946,000 probes for the interrogation of CNVs (copy number variations). The genotyping assay using the Affymetrix SNP 6.0 array is highly demanding on sample quality due to the small feature size, low redundancy, and lack of mismatch probes. Findings: In the first study published so far using this microarray on pooled DNA, we found that pooled cheek swab DNA could not accurately predict real allele frequencies of the samples that comprised the pools. In contrast, the allele frequency estimates using blood DNA pools were reasonable, although inferior compared to those obtained with previously employed Affymetrix microarrays. However, it might be possible to improve performance by developing improved analysis methods. Conclusions: Despite the decreasing costs of genome-wide individual genotyping, the pooling approach may have applications in very large-scale case-control association studies. In such cases, our study suggests that high-quality DNA preparations and lower density platforms should be preferred