Evaluation of Therapeutic Oligonucleotides for Familial Amyloid Polyneuropathy in Patient-Derived Hepatocyte-Like Cells

Familial amyloid polyneuropathy (FAP) is caused by mutations of the transthyretin (TTR) gene, predominantly expressed in the liver. Two compounds that knockdown TTR, comprising a small interfering RNA (siRNA; ALN-TTR-02) and an antisense oligonucleotide (ASO; IONIS-TTRRx), are currently being evaluated in clinical trials. Since primary hepatocytes from FAP patients are rarely available for molecular analysis and commercial tissue culture cells or animal models lack the patient-specific genetic background, this study uses primary cells derived from urine of FAP patients. Urine-derived cells were reprogrammed to induced pluripotent stem cells (iPSCs) with high efficiency. Hepatocyte-like cells (HLCs) showing typical hepatic marker expression were obtained from iPSCs of the FAP patients. TTR mRNA expression of FAP HLCs almost reached levels measured in human hepatocytes. To assess TTR knockdown, siTTR1 and TTR-ASO were introduced to HLCs. A significant downregulation (>80%) of TTR mRNA was induced in the HLCs by both oligonucleotides. TTR protein present in the cell culture supernatant of HLCs was similarly downregulated. Gene expression of other hepatic markers was not affected by the therapeutic oligonucleotides. Our data indicate that urine cells (UCs) after reprogramming and hepatic differentiation represent excellent primary human target cells to assess the efficacy and specificity of novel compounds

Identification, clinical manifestation and structural mechanisms of mutations in AMPK associated cardiac glycogen storage disease

BACKGROUND: Although 21 causative mutations have been associated with PRKAG2 syndrome, our understanding of the syndrome remains incomplete. The aim of this project is to further investigate its unique genetic background, clinical manifestations, and underlying structural changes. METHODS: We recruited 885 hypertrophic cardiomyopathy (HCM) probands and their families internationally. Targeted next-generation sequencing of sudden cardiac death (SCD) genes was performed. The role of the identified variants was assessed using histological techniques and computational modeling. FINDINGS: Twelve PRKAG2 syndrome kindreds harboring 5 distinct variants were identified. The clinical penetrance of 25 carriers was 100.0%. Twenty-two family members died of SCD or heart failure (HF). All probands developed bradycardia (HRmin, 36.3+/-9.8bpm) and cardiac conduction defects, and 33% had evidence of atrial fibrillation/paroxysmal supraventricular tachycardia (PSVT) and 67% had ventricular preexcitation, respectively. Some carriers presented with apical hypertrophy, hypertension, hyperlipidemia, and renal insufficiency. Histological study revealed reduced AMPK activity and major cardiac channels in the heart tissue with K485E mutation. Computational modelling suggests that K485E disrupts the salt bridge connecting the beta and gamma subunits of AMPK, R302Q/P decreases the binding affinity for ATP, T400N and H401D alter the orientation of H383 and R531 residues, thus altering nucleotide binding, and N488I and L341S lead to structural instability in the Bateman domain, which disrupts the intramolecular regulation. INTERPRETATION: Including 4 families with 3 new mutations, we describe a cohort of 12 kindreds with PRKAG2 syndrome with novel pathogenic mechanisms by computational modelling. Severe clinical cardiac phenotypes may be developed, including HF, requiring close follow-up

Genetic, environmental and stochastic factors in monozygotic twin discordance with a focus on epigenetic differences

PMCID: PMC3566971This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

A phenomic perspective on factors influencing breast cancer treatment: integrating aging and lifestyle in blood and tissue biomarker profiling

Breast cancer is the most common malignancy among women worldwide. Over the last four decades, diagnostic and therapeutic procedures have improved substantially, giving patients with localized disease a better chance of cure, and those with more advanced cancer, longer periods of disease control and survival. However, understanding and managing heterogeneity in the clinical response exhibited by patients remains a challenge. For some treatments, biomarkers are available to inform therapeutic options, assess pathological response and predict clinical outcomes. Nevertheless, some measurements are not employed universally and lack sensitivity and specificity, which might be influenced by tissue-specific alterations associated with aging and lifestyle. The first part of this article summarizes available and emerging biomarkers for clinical use, such as measurements that can be made in tumor biopsies or blood samples, including so-called liquid biopsies. The second part of this article outlines underappreciated factors that could influence the interpretation of these clinical measurements and affect treatment outcomes. For example, it has been shown that both adiposity and physical activity can modify the characteristics of tumors and surrounding tissues. In addition, evidence shows that inflammaging and immunosenescence interact with treatment and clinical outcomes and could be considered prognostic and predictive factors independently. In summary, changes to blood and tissues that reflect aging and patient characteristics, including lifestyle, are not commonly considered clinically or in research, either for practical reasons or because the supporting evidence base is developing. Thus, an aim of this article is to encourage an integrative phenomic approach in oncology research and clinical management

International criteria for electrocardiographic interpretation in athletes: Consensus statement.

Sudden cardiac death (SCD) is the leading cause of mortality in athletes during sport. A variety of mostly hereditary, structural or electrical cardiac disorders are associated with SCD in young athletes, the majority of which can be identified or suggested by abnormalities on a resting 12-lead electrocardiogram (ECG). Whether used for diagnostic or screening purposes, physicians responsible for the cardiovascular care of athletes should be knowledgeable and competent in ECG interpretation in athletes. However, in most countries a shortage of physician expertise limits wider application of the ECG in the care of the athlete. A critical need exists for physician education in modern ECG interpretation that distinguishes normal physiological adaptations in athletes from distinctly abnormal findings suggestive of underlying pathology. Since the original 2010 European Society of Cardiology recommendations for ECG interpretation in athletes, ECG standards have evolved quickly, advanced by a growing body of scientific data and investigations that both examine proposed criteria sets and establish new evidence to guide refinements. On 26-27 February 2015, an international group of experts in sports cardiology, inherited cardiac disease, and sports medicine convened in Seattle, Washington (USA), to update contemporary standards for ECG interpretation in athletes. The objective of the meeting was to define and revise ECG interpretation standards based on new and emerging research and to develop a clear guide to the proper evaluation of ECG abnormalities in athletes. This statement represents an international consensus for ECG interpretation in athletes and provides expert opinion-based recommendations linking specific ECG abnormalities and the secondary evaluation for conditions associated with SCD

Gain-of-Function R225W Mutation in Human AMPKγ3 Causing Increased Glycogen and Decreased Triglyceride in Skeletal Muscle

BACKGROUND: AMP-activated protein kinase (AMPK) is a heterotrimeric enzyme that is evolutionarily conserved from yeast to mammals and functions to maintain cellular and whole body energy homeostasis. Studies in experimental animals demonstrate that activation of AMPK in skeletal muscle protects against insulin resistance, type 2 diabetes and obesity. The regulatory gamma(3) subunit of AMPK is expressed exclusively in skeletal muscle; however, its importance in controlling overall AMPK activity is unknown. While evidence is emerging that gamma subunit mutations interfere specifically with AMP activation, there remains some controversy regarding the impact of gamma subunit mutations. Here we report the first gain-of-function mutation in the muscle-specific regulatory gamma(3) subunit in humans. METHODS AND FINDINGS: We sequenced the exons and splice junctions of the AMPK gamma(3) gene (PRKAG3) in 761 obese and 759 lean individuals, identifying 87 sequence variants including a novel R225W mutation in subjects from two unrelated families. The gamma(3) R225W mutation is homologous in location to the gamma(2)R302Q mutation in patients with Wolf-Parkinson-White syndrome and to the gamma(3)R225Q mutation originally linked to an increase in muscle glycogen content in purebred Hampshire Rendement Napole (RN-) pigs. We demonstrate in differentiated muscle satellite cells obtained from the vastus lateralis of R225W carriers that the mutation is associated with an approximate doubling of both basal and AMP-activated AMPK activities. Moreover, subjects bearing the R225W mutation exhibit a approximately 90% increase of skeletal muscle glycogen content and a approximately 30% decrease in intramuscular triglyceride (IMTG). CONCLUSIONS: We have identified for the first time a mutation in the skeletal muscle-specific regulatory gamma(3) subunit of AMPK in humans. The gamma(3)R225W mutation has significant functional effects as demonstrated by increases in basal and AMP-activated AMPK activities, increased muscle glycogen and decreased IMTG. Overall, these findings are consistent with an important regulatory role for AMPK gamma(3) in human muscle energy metabolism

Beyond gene-disease validity: capturing structured data on inheritance, allelic-requirement, disease-relevant variant classes, and disease mechanism for inherited cardiac conditions

Background: As the availability of genomic testing grows, variant interpretation will increasingly be performed by genomic generalists, rather than domain-specific experts. Demand is rising for laboratories to accurately classify variants in inherited cardiac condition (ICC) genes, including secondary findings. Methods: We analyse evidence for inheritance patterns, allelic requirement, disease mechanism and disease-relevant variant classes for 65 ClinGen-curated ICC gene-disease pairs. We present this information for the first time in a structured dataset, CardiacG2P, and assess application in genomic variant filtering. Results: For 36/65 gene-disease pairs, loss of function is not an established disease mechanism, and protein truncating variants are not known to be pathogenic. Using the CardiacG2P dataset as an initial variant filter allows for efficient variant prioritisation whilst maintaining a high sensitivity for retaining pathogenic variants compared with two other variant filtering approaches. Conclusions: Access to evidence-based structured data representing disease mechanism and allelic requirement aids variant filtering and analysis and is a pre-requisite for scalable genomic testing

Structural equation modeling in medical research: a primer

<p>Abstract</p> <p>Background</p> <p>Structural equation modeling (SEM) is a set of statistical techniques used to measure and analyze the relationships of observed and latent variables. Similar but more powerful than regression analyses, it examines linear causal relationships among variables, while simultaneously accounting for measurement error. The purpose of the present paper is to explicate SEM to medical and health sciences researchers and exemplify their application.</p> <p>Findings</p> <p>To facilitate its use we provide a series of steps for applying SEM to research problems. We then present three examples of how SEM has been utilized in medical and health sciences research.</p> <p>Conclusion</p> <p>When many considerations are given to research planning, SEM can provide a new perspective on analyzing data and potential for advancing research in medical and health sciences.</p