BackgroundArray-based comparative genomic hybridization has been assumed to be the first genetic test offered to detect genomic imbalances in patients with unexplained intellectual disability with or without dysmorphisms, multiple congenital anomalies, learning difficulties and autism spectrum disorders.Our study contributes to the genotype/phenotype correlation with the delineation of laboratory criteria which help to classify the different copy number variants (CNVs) detected. We clustered our findings into five classes ranging from an imbalance detected in a microdeletion/duplication syndrome region (class I) to imbalances that had previously been reported in normal subjects in the Database of Genomic Variants (DGV) and thus considered common variants (class IV).ResultsAll the analyzed 1000 patients had at least one CNV independently of its clinical significance. Most of them, as expected, were alterations already reported in the DGV for normal individuals (class IV) or without known coding genes (class III-B). In approximately 14 % of the patients an imbalance involving known coding genes, but with partially overlapping or low frequency of CNVs described in the DGV was identified (class IIIA). In 10.4 % of the patients a pathogenic CNV that explained the phenotype was identified consisting of: 40 class I imbalances, 44 class II de novo imbalances and 21 class II X-chromosome imbalances in male patients. In 20 % of the patients a familial pathogenic or potentially pathogenic CNV, consisting of inherited class II imbalances, was identified that implied a family evaluation by the clinical geneticists.ConclusionsAs this interpretation can be sometimes difficult, particularly if it is not possible to study the parents, using the proposed classification we were able to prioritize the multiple imbalances that are identified in each patient without immediately having to classify them as pathogenic or benign.

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Left atrial ejection fraction (LAEF) has been previously shown to accurately distinguish between patients with and without clearly defined left ventricle diastolic dysfunction (LVDD) by ASE/EACVI criteria, but indeterminate cases were excluded. We sought to determine if LAEF could accurately distinguish between normal, indeterminate and LVDD patients. A retrospective cohort of 125 patients who underwent transthoracic echocardiography was studied. Comprehensive echocardiographic study was performed with measurement of validated diastolic parameters. Subjects were assigned LVDF ASE/EACVI categories. ANOVA test was used to compare means between groups and binary logistic regression and ROC curves to assess diagnostic accuracy. Mean LAEF was statistically different between groups (p < 0.001): 56.3% ± 4.5 for normal patients, 50.2% ± 5.5 for indeterminate patients and 44% ± 8.5 for patients with LVDD. LAEF distinguished LVDD from patients without diastolic dysfunction (OR = 0.73, 95% CI 0.63-0.65, p < 0.001) and ROC curve reveals excellent discriminative power (AUC 0.91, 95% CI 0.84-0.97, p < 0.001). LAEF also distinguished indeterminate patients from LVDD (OR = 0.9, 95% CI 0.83-0.95, p < 0.001) and ROC curve revealed good discriminative power (AUC 0.72, 95% CI 0.62-0.82, p < 0.001). LAEF can accurately differentiate between normal, indeterminate and LVDD patients and could be considered as an additional parameter in the study of diastolic function.

A palette of copy number changes in long-term epilepsy-associated tumors (LEATs) have been reported, but the data are heterogeneous. To better understand the molecular basis underlying the development of LEATs, we performed array-comparative genomic hybridization analysis to investigate chromosomal imbalances across the entire genome in 8 cases of LEATs. A high number of aberrations were found in 4 patients, among which deletions predominated. Both whole-chromosome and regional abnormalities were observed, including monosomy 19, deletion of 1p, deletions of 4p, 12p, and 22q, and gain of 20p. The common altered regions are located mainly on chromosomes 19 and 4p, identifying genes potentially involved in biological processes and cellular mechanisms related to tumorigenesis. Our study highlights new genomic alterations and reinforces others previously reported, offering new molecular insights that may help in diagnosis and therapeutic decision-making.