The role of rare compound heterozygous events in autism spectrum disorder.

The identification of genetic variants underlying autism spectrum disorders (ASDs) may contribute to a better understanding of their underlying biology. To examine the possible role of a specific type of compound heterozygosity in ASD, namely, the occurrence of a deletion together with a functional nucleotide variant on the remaining allele, we sequenced 550 genes in 149 individuals with ASD and their deletion-transmitting parents. This approach allowed us to identify additional sequence variants occurring in the remaining allele of the deletion. Our main goal was to compare the rate of sequence variants in remaining alleles of deleted regions between probands and the deletion-transmitting parents. We also examined the predicted functional effect of the identified variants using Combined Annotation-Dependent Depletion (CADD) scores. The single nucleotide variant-deletion co-occurrence was observed in 13.4% of probands, compared with 8.1% of parents. The cumulative burden of sequence variants (n = 68) in pooled proband sequences was higher than the burden in pooled sequences from the deletion-transmitting parents (n = 41, X2 = 6.69, p = 0.0097). After filtering for those variants predicted to be most deleterious, we observed 21 of such variants in probands versus 8 in their deletion-transmitting parents (X2 = 5.82, p = 0.016). Finally, cumulative CADD scores conferred by these variants were significantly higher in probands than in deletion-transmitting parents (burden test, ß = 0.13; p = 1.0 × 10-5). Our findings suggest that the compound heterozygosity described in the current study may be one of several mechanisms explaining variable penetrance of CNVs with known pathogenicity for ASD.

Long-term follow-up of the Shelhigh™ superstentless bioprosthesis aortic valve and valved conduit in a monocentric experience.

BACKGROUND: The Shelhigh™ SuperStentless (Shelhigh, INC., Union, NJ, USA) is a stentless aortic valve bioprosthesis and aortic root valved conduit. In 2007, this device was recalled by FDA due to malfunction, and subsequently reintegrated by BioIntegral Surgical™ Few data are available over late durability of this device. We performed a long-term follow-up of Shelhigh™ devices implanted at our center. METHODS: Between 2002 and 2007, 44 patients underwent aortic valve replacement with a Shelhigh™ device (40 aortic valve bioprosthesis and 4 valved conduit). We performed a clinical and echocardiographic follow-up (9.2 years±4.3). Standardized definitions of valve-related events were adopted. RESULTS: At discharge, maximum and mean aortic gradients averaged 36.1±11.3 and 21.0±6.8 mmHg, respectively. The 30-days mortality was 2.3%. Over the follow-up period, 29 patients died (65.9%); 2 deaths were valve related. Overall survival at 1, 5 and 10 years was 97.7%, 85.8% and 54% respectively. At last echocardiography, average transvalvular gradients had remained globally stable in the population (33.6±12 and 20.4±10.5 mmHg). Eight (19%) structural valve deterioration (SVD) events were reported. Two (5%) non-structural valve dysfunction (NSVD) events occurred (periprosthetic leak). Two (5%) infectious endocarditis events and two (5%) valve thromboses were also deplored. Three (7%) patients required re-operation (2 due to SVD and 1 due to endocarditis). CONCLUSIONS: The immediate hemodynamic performance of the Shelhigh™ aortic bioprostheses was unexpectedly suboptimal. Despite this, hemodynamic performance remained stable over time. Patients survival at follow-up was satisfactory, however, continued surveillance is necessary.

Current results of left ventricular assist device therapy in France: the ASSIST-ICD registry.

OBJECTIVES: Our goal was to provide a picture of left ventricular assist device (LVAD) activity in France between 2007 and 2016 based on the multicentric ASSIST-ICD registry. METHODS: We retrospectively collected 136 variables including in-hospital data, follow-up survival rates and adverse events from 671 LVAD recipients at 20 out of 24 LVAD implant centres in France. The average follow-up time was 1.2 years (standard deviation: 1.4); the total follow-up time was 807.5 patient-years. RESULTS: The included devices were the HeartMate II®, HeartWare LVAS® or Jarvik 2000®. The overall likelihood of being alive while on LVAD support or having a transplant (primary end point) at 1, 2, 3 and 5 years postimplantation was 65.2%, 59.7%, 55.9% and 47.7%, respectively, given a cumulative incidence of 29.2% of receiving a transplant at year 5. At implantation, 21.5% of patients were on extracorporeal life support. The overall rate of cardiogenic shock at implantation was 53%. The major complications were driveline infection (26.1%), pump pocket or cannula infection (12.6%), LVAD thrombosis (12.2%), ischaemic (12.8%) or haemorrhagic stroke (5.4%; all strokes 18.2%), non-cerebral haemorrhage (9.1%) and LVAD exchange (5.2%). The primary end point (survival) was stratified by age at surgery and by the type of device used, with inference from baseline profiles. The primary end point combined with an absence of complications (secondary end point) was also stratified by device type. CONCLUSIONS: The ASSIST-ICD registry provides a real-life picture of LVAD use in 20 of the 24 implant centres in France. Despite older average age and a higher proportion of patients chosen for destination therapy, survival rates improved compared to those in previous national registry results. This LVAD registry contrasts with other international registries because patients with implants have more severe disease, and the national policy for graft attribution is distinct. We recommend referring patients for LVAD earlier and suggest a discussion of the optimal timing of a transplant for bridged patients (more dismal results after the second year of support?).

Genetic analysis of DNA methylation and gene expression levels in whole blood of healthy human subjects.

BACKGROUND: The predominant model for regulation of gene expression through DNA methylation is an inverse association in which increased methylation results in decreased gene expression levels. However, recent studies suggest that the relationship between genetic variation, DNA methylation and expression is more complex. RESULTS: Systems genetic approaches for examining relationships between gene expression and methylation array data were used to find both negative and positive associations between these levels. A weighted correlation network analysis revealed that i) both transcriptome and methylome are organized in modules, ii) co-expression modules are generally not preserved in the methylation data and vice-versa, and iii) highly significant correlations exist between co-expression and co-methylation modules, suggesting the existence of factors that affect expression and methylation of different modules (i.e., trans effects at the level of modules). We observed that methylation probes associated with expression in cis were more likely to be located outside CpG islands, whereas specificity for CpG island shores was present when methylation, associated with expression, was under local genetic control. A structural equation model based analysis found strong support in particular for a traditional causal model in which gene expression is regulated by genetic variation via DNA methylation instead of gene expression affecting DNA methylation levels. CONCLUSIONS: Our results provide new insights into the complex mechanisms between genetic markers, epigenetic mechanisms and gene expression. We find strong support for the classical model of genetic variants regulating methylation, which in turn regulates gene expression. Moreover we show that, although the methylation and expression modules differ, they are highly correlated.

Clinical subtypes of Parkinson's disease.

The clinical heterogeneity of Parkinson's disease (PD) may point at the existence of subtypes. Because subtypes likely reflect distinct underlying etiologies, their identification may facilitate future genetic and pharmacotherapeutic studies. Aim of this study was to identify subtypes by a data-driven approach applied to a broad spectrum of motor and nonmotor features of PD. Data of motor and nonmotor PD symptoms were collected in 802 patients in two different European prevalent cohorts. A model-based cluster analysis was conducted on baseline data of 344 patients of a Dutch cohort (PROPARK). Reproducibility of these results was tested in data of the second annual assessment of the same cohort and validated in an independent Spanish cohort (ELEP) of 357 patients. The subtypes were subsequently characterized on clinical and demographic variables. Four similar PD subtypes were identified in two different populations and are largely characterized by differences in the severity of nondopaminergic features and motor complications: Subtype 1 was mildly affected in all domains, Subtype 2 was predominantly characterized by severe motor complications, Subtype 3 was affected mainly on nondopaminergic domains without prominent motor complications, while Subtype 4 was severely affected on all domains. The subtypes had largely similar mean disease durations (nonsignificant differences between three clusters) but showed considerable differences with respect to their association with demographic and clinical variables. In prevalent disease, PD subtypes are largely characterized by the severity of nondopaminergic features and motor complications and likely reflect complex interactions between disease mechanisms, treatment, aging, and gender.

Finding discriminative subtypes of aggressive brain tumours using magnetic resonance spectroscopy.

Aggressive tumour types such as glioblastomas (gl) and metastases (me) are known to be difficult to discriminate on the basis of single-voxel proton magnetic resonance spectroscopy (SV 1H-MRS) information. Each of them is also heterogeneous in nature and a statistically robust subtyping analysis is likely to shed light on their structure and, possibly, on their differences. In this brief paper we carry out such analysis. From the original MRS frequencies and their first derivative approximation, the most discriminant variables are first selected by χ(2)-testing. Subtypes are then discovered in the distribution of gl and me by repeated model based cluster analysis. Then, the mean of each subtype is contrasted with the original distribution of MRS spectra by t-testing with tail probabilities for the proportion of false positive (TPPFP) control. Finally, the distribution of gl and me in each subtype is compared with random expectation by χ(2)-testing. The experimental results confirm the existence of consistent subtypes. They exhibit relative proportions of gl and me very unlikely to occur at random.

Reliability of cluster results for different types of time adjustments in complex disease research.

We aim to identify subtypes of diseases like Osteoarthritis (OA) and Parkinson's Disease (PD) that present clinical heterogeneity. We do so by searching for homogeneous clusters in values of markers that reflect the severity of the disease. In the current paper we consider two important items for a cluster analysis. First, as time can contribute largely to the measured variability in the data, we search for the most appropriate way to adjust for it. Second, as we aim for reliable cluster analyses, cluster results should exhibit robustness to little change in the data. To investigate these issues, we transform the data by adding noise of different levels before cluster modeling and we rely on a chi(2)-based measure of association to compare cluster results for different types of time adjustment. The results of our experiments suggest to adjust data for a logarithmic age effect for OA and a square root effect of the disease duration for PD because these adjustments lead more reliable cluster results.