CAV3 mutation in a patient with transient hyperCKemia and myalgia

Mutations in caveolin-3 (CAV3) can lead to different clinical phenotypes affecting skeletal or cardiac muscles. Here, we describe a patient with Klinefelter syndrome, ulcerative colitis and Sjögren syndrome, who developed transient hyperCKemia, myalgia and mild muscular weakness. Using whole exome sequencing (WES), a missense mutation G169A was found in the CAV3 gene. In addition, we identified a homozygous frameshift deletion in MS4A12 that may contribute to inflammatory bowel disease, further demonstrating usefulness of WES in dual molecular diagnoses

Extending the scope of pooled analyses of individual patient biomarker data from heterogeneous laboratory platforms and cohorts using merging algorithms

Background: A common challenge in medicine, exemplified in the analysis of biomarker data, is that large studies are needed for sufficient statistical power. Often, this may only be achievable by aggregating multiple cohorts. However, different studies may use disparate platforms for laboratory analysis, which can hinder merging. Methods: Using circulating placental growth factor (PIGF), a potential biomarker for hypertensive disorders of pregnancy (HDP) such as preeclampsia, as an example, we investigated how such issues can be overcome by inter-platform standardization and merging algorithms. We studied 16,462 pregnancies from 22 study cohorts. PIGF measurements (gestational age >= 20 weeks) analyzed on one of four platforms: R & Systems, Alere (R) Triage, Roche (R) Elecsys or Abbott (R) Architect, were available for 13,429 women. Two merging algorithms, using Z-Score and Multiple of Median transformations, were applied. Results: Best reference curves (BRC), based on merged, transformed PIGF measurements in uncomplicated pregnancy across six gestational age groups, were estimated. Identification of HDP by these PIGF-BRCS was compared to that of platform-specific curves. Conclusions: We demonstrate the feasibility of merging PIGF concentrations from different analytical platforms. Overall BRC identification of HDP performed at least as well as platform-specific curves. Our method can be extended to any set of biomarkers obtained from different laboratory platforms in any field. Merged biomarker data from multiple studies will improve statistical power and enlarge our understanding of the pathophysiology and management of medical syndromes. (C) 2015 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.Peer reviewe

Comparative Analyses of Lung Transcriptomes in Patients with Alveolar Capillary Dysplasia with Misalignment of Pulmonary Veins and in <i>Foxf1</i> Heterozygous Knockout Mice

<div><p>Alveolar Capillary Dysplasia with Misalignment of Pulmonary Veins (ACDMPV) is a developmental disorder of the lungs, primarily affecting their vasculature. <i>FOXF1</i> haploinsufficiency due to heterozygous genomic deletions and point mutations have been reported in most patients with ACDMPV. The majority of mice with heterozygous loss-of-function of <i>Foxf1</i> exhibit neonatal lethality with evidence of pulmonary hemorrhage in some of them. By comparing transcriptomes of human ACDMPV lungs with control lungs using expression arrays, we found that several genes and pathways involved in lung development, angiogenesis, and in pulmonary hypertension development, were deregulated. Similar transcriptional changes were found in lungs of the postnatal day 0.5 <i>Foxf1</i>^+/− mice when compared to their wildtype littermate controls; 14 genes, <i>COL15A1, COL18A1, COL6A2, ESM1, FSCN1, GRINA, IGFBP3, IL1B, MALL, NOS3, RASL11B, MATN2, PRKCDBP,</i> and <i>SIRPA,</i> were found common to both ACDMPV and <i>Foxf1</i> heterozygous lungs. Our results advance knowledge toward understanding of the molecular mechanism of ACDMPV, lung development, and its vasculature pathology. These data may also be useful for understanding etiologies of other lung disorders, e.g. pulmonary hypertension, bronchopulmonary dysplasia, or cancer.</p></div

ACDMPV lung microarray analysis: heat map, clustering, DAVID analysis, and IHC validation.

<p>(A) Heat map for genes differentially expressed (adjusted p-value <0.05, fold change approximately >/ =  2 or </p

ACDMPV patient sample information.

<p>No clinical or genetic information is available for patients 7 and 8.</p

Networks involving deregulated genes in ACDMPV lungs identified using IPA; down-regulated genes are shown in green and up-regulated genes are shown in red.

<p>Deregulated genes involved in (A) Cellular movement, immune cell trafficking, inflammatory response; (B) Cellular development, cellular growth and proliferation, tumor morphology; (C) Cellular development, hematological system development and function, immune cell trafficking; (D) Cardiovascular disease, inflammatory response and cellular movement; (E) Carbohydrate metabolism, lipid metabolism and molecular transport.</p

Deregulated genes common to both ACDMPV lungs and P0.5 <i>Foxf1^+/−</i> lungs.

<p><b>(A)</b> Heat map comparing expression of 14 overlapping genes in ACDMPV lung samples and control lung samples; (B) Heat map comparing expression of 14 overlapping genes in <i>Foxf1</i>^+/− lung samples and control lung samples.</p