Exploring the utility of whole‐exome sequencing as a diagnostic tool in a child with atypical episodic muscle weakness

The advent of whole‐exome next‐generation sequencing (WES) has been pivotal for the molecular characterization of Mendelian disease; however, the clinical applicability of WES has remained relatively unexplored. We describe our exploration of WES as a diagnostic tool in a 3½‐year old female patient with a 2‐year history of episodic muscle weakness and paroxysmal dystonia who presented following a previous extensive but unrevealing diagnostic work‐up. WES was performed on the proband and her two parents. Parental exome data was used to filter potential de novo genomic events in the proband and suspected variants were confirmed using di‐deoxy sequencing. WES revealed a de novo non‐synonymous mutation in exon 21 of the calcium channel gene CACNA1S that has been previously reported in a single patient as a rare cause of atypical hypokalemic periodic paralysis. This was unexpected, as the proband's original differential diagnosis had included hypokalemic periodic paralysis, but clinical and laboratory features were equivocal, and standard clinical molecular testing for hypokalemic periodic paralysis and related disorders was negative. This report highlights the potential diagnostic utility of WES in clinical practice, with implications for the approach to similar diagnostic dilemmas in the future.     

Haemophilic pseudotumour presenting with large bowel obstruction

Osseous haemophilic pseudotumours are uncommon. The commonest sites of involvement are the femur and the pelvis. Trauma is the initiating factor in most reported cases and repeated bleeding into the lesion contributes to their growth. Most lesions grow slowly and are often asymptomatic. Complications include massive haemorrhage, infection and pathological fracture. We present an extremely unusual presentation where a large haemophilic pseudotumour of the pelvis extended to impinge the adjacent colon, resulting in large bowel obstruction.     

The coeliac iceberg in Italy. A multicentre antigliadin antibodies screening for coeliac disease in school-age subjects

Background : Recent studies suggest that coeliac disease (CD) is one of the commonest, life-long disorders in Italy. The aims of this multicentre work were: (a) to establish the prevalence of CD on a nationwide basis; and (b) to characterize the CD clinical spectrum in Italy. Patients and methods : Fifteen centres screened 17201 students aged 6–15 years (68.6% of the eligible population) by the combined determination of serum IgG- and IgA-antigliadin antibody (AGA) test; 1289 (7.5%) were IgG and/or IgA-AGA positive and were recalled for the second-level investigation; 111 of them met the criteria for the intestinal biopsy: IgA-AGA positivity and/or AEA positivity or IgG-AGA positivity plus serum IgA deficiency. Results : Intestinal biopsy was performed on 98 of the 111 subjects. CD was diagnosed in 82 subjects (75 biopsy proven, 7 not biopsied but with associated AGA and AEA positivity). Most of the screening-detected coeliac patients showed low-grade intensity illness often associated with decreased psychophysical well-being. There were two AEA negative cases with associated CD and IgA deficiency. The prevalence of undiagnosed CD was 4.77 × 1000 (95% CI 3.79–5.91), 1 in 210 subjects. The overall prevalence of CD, including known CD cases, was 5.44 × 1000 (95% CI 4.57–6.44), 1 in 184 subjects. The ratio of known to undiagnosed CD cases was 1 in 7. Conclusions : These findings confirm that, in Italy, CD is one of the most common chronic disorders showing a wide and heterogeneous clinical spectrum. Most CD cases remain undiagnosed unless actively searched.     

Pretreatment ADC Histogram Analysis Is a Predictive Imaging Biomarker for Bevacizumab Treatment but Not Chemotherapy in Recurrent Glioblastoma

BACKGROUND AND PURPOSE:Pre-treatment ADC characteristics have been shown to predict response to bevacizumab in recurrent glioblastoma multiforme. However, no studies have examined whether ADC characteristics are specific to this particular treatment. The purpose of the current study was to determine whether ADC histogram analysis is a bevacizumab-specific or treatment-independent biomarker of treatment response in recurrent glioblastoma multiforme.MATERIALS AND METHODS:Eighty-nine bevacizumab-treated and 43 chemotherapy-treated recurrent glioblastoma multiformes never exposed to bevacizumab were included in this study. In all patients, ADC values in contrast-enhancing ROIs from MR imaging examinations performed at the time of recurrence, immediately before commencement of treatment for recurrence, were extracted and the resulting histogram was fitted to a mixed model with a double Gaussian distribution. Mean ADC in the lower Gaussian curve was used as the primary biomarker of interest. The Cox proportional hazards model and log-rank tests were used for survival analysis.RESULTS:Cox multivariate regression analysis accounting for the interaction between bevacizumab- and non-bevacizumab-treated patients suggested that the ability of the lower Gaussian curve to predict survival is dependent on treatment (progression-free survival, P = .045; overall survival, P = .003). Patients with bevacizumab-treated recurrent glioblastoma multiforme with a pretreatment lower Gaussian curve > 1.2 μm²/ms had a significantly longer progression-free survival and overall survival compared with bevacizumab-treated patients with a lower Gaussian curve < 1.2 μm²/ms. No differences in progression-free survival or overall survival were observed in the chemotherapy-treated cohort. Bevacizumab-treated patients with a mean lower Gaussian curve > 1.2 μm²/ms had a significantly longer progression-free survival and overall survival compared with chemotherapy-treated patients.CONCLUSIONS:The mean lower Gaussian curve from ADC histogram analysis is a predictive imaging biomarker for bevacizumab-treated, not chemotherapy-treated, recurrent glioblastoma multiforme. Patients with recurrent glioblastoma multiforme with a mean lower Gaussian curve > 1.2 μm²/ms have a survival advantage when treated with bevacizumab.

Malignant gliomas, including anaplastic astrocytomas, anaplastic oligodendrogliomas, anaplastic mixed oligoastrocytomas, and glioblastoma multiforme (GBM), account for almost 80% of malignant primary brain tumors.¹ GBM, the most aggressive and malignant type of primary brain tumor, has a mean survival of only 12–14 months under the current standard of care of radiotherapy combined with concurrent temozolomide, along with adjuvant temozolomide.^2,3 GBMs are highly vascular tumors, recruiting existing vasculature and generating neovasculature from excessive levels of circulating angiogenic growth factors, including vascular endothelial growth factor (VEGF). The highly vascular nature of these tumors has led to a new class of antiangogenic agents, for which there are many ongoing clinical trials in GBM.^4–6Standard imaging techniques are limited in their ability to evaluate the effectiveness of antiangiogenic therapy in malignant gliomas due to a reduction in contrast enhancement. These limitations have resulted in a surge of more advanced imaging biomarkers aimed at predicting response to therapy, as summarized in various review articles.^7,8 Among these new imaging biomarkers showing promise are diffusion MR imaging techniques,^9–18 including ADC histogram analysis. Previous results have shown that pretreatment ADC histogram analysis performed within the contrast-enhancing tumor regions can stratify patients with recurrent GBM into high- and low-risk groups. When using a double Gaussian mixed model to represent the ADC histogram, previous studies have shown that a lower mean value of the Gaussian curve (ADC_L) results in a significantly shorter progression-free survival (PFS) and overall survival (OS) in both single-institution⁹ and multicenter clinical trial data¹⁹ when evaluating bevacizumab in malignant gliomas. An important question remains as to whether ADC histogram analysis is a predictive biomarker specific to antiangiogenic therapy in recurrent GBM or whether it is a predictive biomarker independent of the particular treatment administered. In the current study, we performed ADC histogram analysis in patients with recurrent GBM from the University of California, Los Angeles (UCLA) treated with bevacizumab and those with recurrent GBM from the University of Toronto treated with a variety of chemotherapies and never exposed to bevacizumab, to determine whether ADC histogram analysis performed before treatment in recurrent GBM is a bevacizumab-specific or treatment-independent biomarker of treatment response.     

Altered functional connectivity of the default mode network in diffuse gliomas measured with pseudo-resting state fMRI

The purpose of the current study was to explore whether brain tumors disrupt the integrity of the default mode network (DMN), a well-characterized resting-state fMRI network. We evaluated whether tumor grade, volume, post-surgical/clinical status, or location decreased the functional connectivity within the DMN in patients with gliomas. Task-based fMRI data was obtained from 68 diffuse glioma patients and 12 healthy volunteers. Pseudo-resting state fMRI data was calculated from task-based fMRI data using standard techniques. Data was preprocessed and DMN integrity was compared across WHO grade, tumor volume surgical status (new vs. recurrent tumors), age, and KPS using univariate and multivariate linear models. WHO grade was the most significant predictor of DMN integrity (P = 0.004), whereas T2 hyperintense lesion volume was not a predictor (P = 0.154). DMN integrity was lower in high-grade (WHO III–IV) compared with low-grade (WHO II) patients (P = 0.020). Tumors in the left parietal lobe showed a more impaired DMN compared with tumors in the frontal lobe, while tumors within and outside the network nodes did not differ significantly. Results suggest higher tumor grade along with prior surgery and/or treatment cause the largest reduction in DMN functional connectivity in patients with primary gliomas, and that tumor location has an impact on connectivity.