Challenges of interpreting copy number variation in syndromic and non-syndromic congenital heart defects.

Array comparative genomic hybridization (aCGH) has led to an increased detection of causal chromosomal imbalances in individuals with congenital heart defects (CHD). The introduction of aCGH as a diagnostic tool in a clinical cardiogenetic setting entails numerous challenges. Based on our own experience as well as those of others described in the literature, we outline the state of the art and attempt to answer a number of outstanding questions such as the detection frequency of causal imbalances in different patient populations, the added value of higher-resolution arrays, and the existence of predictive factors in syndromic cases. We introduce a step-by-step approach for clinical interpretation of copy number variants (CNV) detected in CHD, which is primarily based on gene content and overlap with known chromosomal syndromes, rather than on CNV inheritance and size. Based on this algorithm, we have reclassified the detected aberrations in aCGH studies for their causality for syndromic and non-syndromic CHD. From this literature overview, supplemented with own investigations in a cohort of 46 sporadic patients with severe non-syndromic CHD, it seems clear that the frequency of causal CNVs in non-syndromic CHD populations is lower than that in syndromic CNV populations (3.6 vs. 19%). Moreover, causal CNVs in non-syndromic CHD mostly involve imbalances with a moderate effect size and reduced penetrance, whereas the majority of causal imbalances in syndromic CHD consistently affects human development and significantly reduces reproductive fitness.

Physical-chemistry-based analysis of affymetrix microarray data.

We analyze publicly available data on Affymetrix microarray spike-in experiments on the human HGU133 chipset in which sequences are added in solution at known concentrations. The spike-in set contains sequences of bacterial, human, and artificial origin. Our analysis is based on a recently introduced molecular-based model (Carlon, E.; Heim, T. Physica A 2006, 362, 433) that takes into account both probe-target hybridization and target-target partial hybridization in solution. The hybridization free energies are obtained from the nearest-neighbor model with experimentally determined parameters. The molecular-based model suggests a rescaling that should result in a "collapse" of the data at different concentrations into a single universal curve. We indeed find such a collapse, with the same parameters as obtained previously for the older HGU95 chip set. The quality of the collapse varies according to the probe set considered. Artificial sequences, chosen by Affymetrix to be as different as possible from any other human genome sequence, generally show a much better collapse and thus a better agreement with the model than all other sequences. This suggests that the observed deviations from the predicted collapse are related to the choice of probes or have a biological origin rather than being a problem with the proposed model.