Whole exome sequencing in patients with Williams-Beuren syndrome followed by disease modeling in mice points to four novel pathways that may modify stenosis risk

Supravalvular aortic stenosis (SVAS) is a narrowing of the aorta caused by elastin (ELN) haploinsufficiency. SVAS severity varies among patients with Williams-Beuren syndrome (WBS), a rare disorder that removes one copy of ELN and 25-27 other genes. Twenty percent of children with WBS require one or more invasive and often risky procedures to correct the defect while 30% have no appreciable stenosis, despite sharing the same basic genetic lesion. There is no known medical therapy. Consequently, identifying genes that modify SVAS offers the potential for novel modifier-based therapeutics. To improve statistical power in our rare-disease cohort (N = 104 exomes), we utilized extreme-phenotype cohorting, functional variant filtration and pathway-based analysis. Gene set enrichment analysis of exome-wide association data identified increased adaptive immune system variant burden among genes associated with SVAS severity. Additional enrichment, using only potentially pathogenic variants known to differ in frequency between the extreme phenotype subsets, identified significant association of SVAS severity with not only immune pathway genes, but also genes involved with the extracellular matrix, G protein-coupled receptor signaling and lipid metabolism using both SKAT-O and RQTest. Complementary studies in Eln+/-; Rag1-/- mice, which lack a functional adaptive immune system, showed improvement in cardiovascular features of ELN insufficiency. Similarly, studies in mixed background Eln+/- mice confirmed that variations in genes that increase elastic fiber deposition also had positive impact on aortic caliber. By using tools to improve statistical power in combination with orthogonal analyses in mice, we detected four main pathways that contribute to SVAS risk

A verification protocol for the probe sequences of Affymetrix genome arrays reveals high probe accuracy for studies in mouse, human and rat

BACKGROUND: The Affymetrix GeneChip technology uses multiple probes per gene to measure its expression level. Individual probe signals can vary widely, which hampers proper interpretation. This variation can be caused by probes that do not properly match their target gene or that match multiple genes. To determine the accuracy of Affymetrix arrays, we developed an extensive verification protocol, for mouse arrays incorporating the NCBI RefSeq, NCBI UniGene Unique, NIA Mouse Gene Index, and UCSC mouse genome databases. RESULTS: Applying this protocol to Affymetrix Mouse Genome arrays (the earlier U74Av2 and the newer 430 2.0 array), the number of sequence-verified probes with perfect matches was no less than 85% and 95%, respectively; and for 74% and 85% of the probe sets all probes were sequence verified. The latter percentages increased to 80% and 94% after discarding one or two unverifiable probes per probe set, and even further to 84% and 97% when, in addition, allowing for one or two mismatches between probe and target gene. Similar results were obtained for other mouse arrays, as well as for human and rat arrays. Based on these data, refined chip definition files for all arrays are provided online. Researchers can choose the version appropriate for their study to (re)analyze expression data. CONCLUSION: The accuracy of Affymetrix probe sequences is higher than previously reported, particularly on newer arrays. Yet, refined probe set definitions have clear effects on the detection of differentially expressed genes. We demonstrate that the interpretation of the results of Affymetrix arrays is improved when the new chip definition files are used

Cation exchange HPLC analysis of desmosines in elastin hydrolysates

Desmosine crosslinks are responsible for the elastic properties of connective tissues in lungs and cardiovascular system and are often compromised in disease states. We developed a new, fast, and simple cation exchange HPLC assay for the analysis of desmosine and isodesmosine in animal elastin. The method was validated by determining linearity, accuracy, precision, and desmosines stability and was applied to measure levels of desmosines in porcine and murine organs. The detection and quantification limits were 2 and 4 pmol, respectively. The run-time was 8 min. Our cation exchange column does not separate desmosine and isodesmosine, but their level can be quantified from absorbance at different wavelengths. Using this assay, we found that desmosines levels were significantly lower in elastin isolated from various organs of immunodeficient severe combined immunodeficiency mice compared with wild-type animals. We also found that desmosines levels were lower in lung elastin isolated from hyperhomocysteinemic Pcft−/− mice deficient in intestinal folate transport compared with wild-type Pcft+/+ animals

Changes in elastin, elastin binding protein and versican in alveoli in chronic obstructive pulmonary disease

<p>Abstract</p> <p>Background</p> <p>COPD is characterised by loss of alveolar elastic fibers and by lack of effective repair. Elastic fibers are assembled at cell surfaces by elastin binding protein (EBP), a molecular chaperone whose function can be reversibility inhibited by chondroitin sulphate of matrix proteoglycans such as versican. This study aimed to determine if alveoli of patients with mild to moderate COPD contained increased amounts of versican and a corresponding decrease in EBP, and if these changes were correlated with decreases in elastin and FEV₁.</p> <p>Methods</p> <p>Lung samples were obtained from 26 control (FEV₁≥ 80% predicted, FEV₁/VC >0.7) and 17 COPD patients (FEV₁≥ 40% – <80% predicted, FEV₁/VC ≤ 0.7) who had undergone a lobectomy for bronchial carcinoma. Samples were processed for histological and immuno-staining. Volume fractions (<it>V</it>_v) of elastin in alveolar walls and alveolar rims were determined by point counting, and versican and EBP assessed by grading of staining intensities.</p> <p>Results</p> <p>Elastin <it>V</it>v was positively correlated with FEV₁for both the alveolar walls (r = 0.66, p < 0.001) and rims (r = 0.41, p < 0.01). Versican was negatively correlated with FEV₁in both regions (r = 0.30 and 0.32 respectively, p < 0.05), with the highest staining intensities found in patients with the lowest values for FEV₁. Conversely, staining intensities for EBP in alveolar walls and rims and were positively correlated with FEV₁(r = 0.43 and 0.46, p < 0.01).</p> <p>Conclusion</p> <p>Patients with mild to moderate COPD show progressively increased immuno-staining for versican and correspondingly decreased immuno-staining for EBP, with decreasing values of FEV₁. These findings may explain the lack of repair of elastic fibers in the lungs of patients with moderate COPD. Removal of versican may offer a strategy for effective repair.</p

Batch effect correction for genome-wide methylation data with Illumina Infinium platform

<p>Abstract</p> <p>Background</p> <p>Genome-wide methylation profiling has led to more comprehensive insights into gene regulation mechanisms and potential therapeutic targets. Illumina Human Methylation BeadChip is one of the most commonly used genome-wide methylation platforms. Similar to other microarray experiments, methylation data is susceptible to various technical artifacts, particularly batch effects. To date, little attention has been given to issues related to normalization and batch effect correction for this kind of data.</p> <p>Methods</p> <p>We evaluated three common normalization approaches and investigated their performance in batch effect removal using three datasets with different degrees of batch effects generated from HumanMethylation27 platform: quantile normalization at average β value (QNβ); two step quantile normalization at probe signals implemented in "lumi" package of R (lumi); and quantile normalization of A and B signal separately (ABnorm). Subsequent Empirical Bayes (EB) batch adjustment was also evaluated.</p> <p>Results</p> <p>Each normalization could remove a portion of batch effects and their effectiveness differed depending on the severity of batch effects in a dataset. For the dataset with minor batch effects (Dataset 1), normalization alone appeared adequate and "lumi" showed the best performance. However, all methods left substantial batch effects intact in the datasets with obvious batch effects and further correction was necessary. Without any correction, 50 and 66 percent of CpGs were associated with batch effects in Dataset 2 and 3, respectively. After QNβ, lumi or ABnorm, the number of CpGs associated with batch effects were reduced to 24, 32, and 26 percent for Dataset 2; and 37, 46, and 35 percent for Dataset 3, respectively. Additional EB correction effectively removed such remaining non-biological effects. More importantly, the two-step procedure almost tripled the numbers of CpGs associated with the outcome of interest for the two datasets.</p> <p>Conclusion</p> <p>Genome-wide methylation data from Infinium Methylation BeadChip can be susceptible to batch effects with profound impacts on downstream analyses and conclusions. Normalization can reduce part but not all batch effects. EB correction along with normalization is recommended for effective batch effect removal.</p