First genetic analysis of aneurysm genes in familial and sporadic abdominal aortic aneurysm

Genetic causes for abdominal aortic aneurysm (AAA) have not been identified and the role of genes associated with familial thoracic aneurysms in AAA has not been explored. We analyzed nine genes associated with familial thoracic aortic aneurysms, the vascular Ehlers–Danlos gene COL3A1 and the MTHFR p.Ala222Val variant in 155 AAA patients. The thoracic aneurysm genes selected for this study were the transforming growth factor-beta pathway genes EFEMP2, FBN1, SMAD3, TGBF2, TGFBR1, TGFBR2, and the smooth muscle cells genes ACTA2, MYH11 and MYLK. Sanger sequencing of all coding exons and exon–intron boundaries of these genes was performed. Patients with at least one first-degree relative with an aortic aneurysm were classified as familial AAA (n = 99), the others as sporadic AAA. We found 47 different rare heterozygous variants in eight genes: two pathogenic, one likely pathogenic, twenty-one variants of unknown significance (VUS) and twenty-three unlikely pathogenic variants. In familial AAA we found one pathogenic and segregating variant (COL3A1 p.Arg491X), one likely pathogenic and segregating (MYH11 p.Arg254Cys), and fifteen VUS. In sporadic patients we found one pathogenic (TGFBR2 p.Ile525Phefs*18) and seven VUS. Thirteen patients had two or more variants. These results show a previously unknown association and overlapping genetic defects between AAA and familial thoracic aneurysms, indicating that genetic testing may help to identify the cause of familial and sporadic AAA. In this view, genetic testing of these genes specifically or in a genome-wide approach may help to identify the cause of familial and sporadic AAA

Privacy-preserving dataset combination and Lasso regression for healthcare predictions

Background: Recent developments in machine learning have shown its potential impact for clinical use such as risk prediction, prognosis, and treatment selection. However, relevant data are often scattered across different stakeholders and their use is regulated, e.g. by GDPR or HIPAA. As a concrete use-case, hospital Erasmus MC and health insurance company Achmea have data on individuals in the city of Rotterdam, which would in theory enable them to train a regression model in order to identify high-impact lifestyle factors for heart failure. However, privacy and confdentiality concerns make it unfeasible to exchange these data. Methods: This article describes a solution where vertically-partitioned synthetic data of Achmea and of Erasmus MC are combined using Secure Multi-Party Computation. First, a secure inner join protocol takes place to securely determine the identifiers of the patients that are represented in both datasets. Then, a secure Lasso Regression model is trained on the securely combined data. The involved parties thus obtain the prediction model but no further information on the input data of the other parties. Results: We implement our secure solution and describe its performance and scalability: we can train a prediction model on two datasets with 5000 records each and a total of 30 features in less than one hour, with a minimal difference from the results of standard (non-secure) methods. Conclusions: This article shows that it is possible to combine datasets and train a Lasso regression model on this combination in a secure way. Such a solution thus further expands the potential of privacy-preserving data analysis in the medical domain

Decreased mitochondrial respiration in aneurysmal aortas of Fibulin-4 mutant mice is linked to PGC1A regulation

Aim Thoracic aortic aneurysms are a life-threatening condition often diagnosed too late. To discover novel robust biomarkers, we aimed to better understand the molecular mechanisms underlying aneurysm formation. Methods and results In Fibulin-4R/R mice, the extracellular matrix protein Fibulin-4 is 4-fold reduced, resulting in progressive ascending aneurysm formation and early death around 3 months of age. We performed proteomics and genomics studies on Fibulin-4R/R mouse aortas. Intriguingly, we observed alterations in mitochondrial protein composition in Fibulin-4R/R aortas. Consistently, functional studies in Fibulin-4R/R vascular smooth muscle cells (VSMCs) revealed lower oxygen consumption rates, but increased acidification rates. Yet, mitochondria in Fibulin-4R/R VSMCs showed no aberrant cytoplasmic localization. We found similar reduced mitochondrial respiration in Tgfbr-1M318R/+ VSMCs, a mouse model for Loeys-Dietz syndrome (LDS). Interestingly, also human fibroblasts from Marfan (FBN1) and LDS (TGFBR2 and SMAD3) patients showed lower oxygen consumption. While individual mitochondrial Complexes I–V activities were unaltered in Fibulin-4R/R heart and muscle, these tissues showed similar decreased oxygen consumption. Furthermore, aortas of aneurysmal Fibulin-4R/R mice displayed increased reactive oxygen species (ROS) levels. Consistent with these findings, gene expression analyses revealed dysregulation of metabolic pathways. Accordingly, blood ketone levels of Fibulin-4R/R mice were reduced and liver fatty acids were decreased, while liver glycogen was increased, indicating dysregulated metabolism at the organismal level. As predicted by gene expression analysis, the activity of PGC1α, a key regulator between mitochondrial function and organismal metabolism, was downregulated in Fibulin-4R/R VSMCs. Increased TGFβ reduced PGC1α levels, indicating involvement of TGFβ signalling in PGC1α regulation. Activation of PGC1α restored the decreased oxygen consumption in Fibulin-4R/R VSMCs and improved their reduced growth potential, emphasizing the importance of this key regulator. Conclusion Our data indicate altered mitochondrial function and metabolic dysregulation, leading to increased ROS levels and altered energy production, as a novel mechanism, which may contribute to thoracic aortic aneurysm formation

First genetic analysis of aneurysm genes in familial and sporadic abdominal aortic aneurysm

Genetic causes for abdominal aortic aneurysm (AAA) have not been identified and the role of genes associated with familial thoracic aneurysms in AAA has not been explored. We analyzed nine genes associated with familial thoracic aortic aneurysms, the vascular Ehlers-Danlos gene COL3A1 and the MTHFR p.Ala222Val variant in 155 AAA patients. The thoracic aneurysm genes selected for this study were the transforming growth factor-beta pathway genes EFEMP2, FBN1, SMAD3, TGBF2, TGFBR1, TGFBR2, and the smooth muscle cells genes ACTA2, MYH11 and MYLK. Sanger sequencing of all coding exons and exon-intron boundaries of these genes was performed. Patients with at least one first-degree relative with an aortic aneurysm were classified as familial AAA (n = 99), the others as sporadic AAA. We found 47 different rare heterozygous variants in eight genes: two pathogenic, one likely pathogenic, twenty-one variants of unknown significance (VUS) and twenty-three unlikely pathogenic variants. In familial AAA we found one pathogenic and segregating variant (COL3A1 p.Arg491X), one likely pathogenic and segregating (MYH11 p.Arg254Cys), and fifteen VUS. In sporadic patients we found one pathogenic (TGFBR2 p.Ile525Phefs*18) and seven VUS. Thirteen patients had two or more variants. These results show a previously unknown association and overlapping genetic defects between AAA and familial thoracic aneurysms, indicating that genetic testing may help to identify the cause of familial and sporadic AAA. In this view, genetic testing of these genes specifically or in a genome-wide approach may help to identify the cause of familial and sporadic AAA

Cardiac Phenotypes, Genetics, and Risks in Familial Noncompaction Cardiomyopathy

BACKGROUND There is overlap in genetic causes and cardiac features in noncompaction cardiomyopathy (NCCM), hypertrophic cardiomyopathy (HCM), and dilated cardiomyopathy (DCM). OBJECTIVES The goal of this study was to predict phenotype and outcome in relatives according to the clinical features and genotype of NCCM index cases. METHODS Retrospective DNA and cardiac screening of relatives of 113 families from 143 index patients were used to classify NCCM cases according to the cardiac phenotype. These cases were classified as isolated NCCM, NCCM with left ventricular (LV) dilation (DCM), and NCCM with LV hypertrophy (HCM). RESULTS In 58 (51%) families, screening identified 73 relatives with NCCM and 34 with DCM or HCM without NCCM. The yield of family screening was higher in families with a mutation (p <0.001). Fifty-four families had a mutation. Nonpenetrance was observed in 37% of the relatives with a mutation. Index cases were more often symptomatic than affected relatives (p <0.001). NCCM with DCM (53%) was associated with LV systolic dysfunction (p <0.001), increased risk for major adverse cardiac events, mutations in the tail of MYH7 (p <0.001), and DCM without NCCM in relatives (p <0.001). Isolated NCCM (43%) was associated with a milder course, mutations in the head of MYH7, asymptomatic NCCM (42%) (p = 0.018), and isolated NCCM in relatives (p = 0.004). NCCM with HCM (4%) was associated with MYBPC3 and HCM without NCCM in relatives (p <0.001). CONCLUSIONS The phenotype of relatives may be predicted according to the NCCM phenotype and the mutation of index patients. NCCM phenotypes were related to outcome. In this way, clinical and genetic features of index patients may help prediction of outcome in relatives. (C) 2019 by the American College of Cardiology Foundation

Genetics, Clinical Features, and Long-Term Outcome of Noncompaction Cardiomyopathy

Background: The clinical outcomes of noncompaction cardiomyopathy (NCCM) range from asymptomatic to heart failure, arrhythmias, and sudden cardiac death. Genetics play an important role in NCCM. Objectives: This study investigated the correlations among genetics, clinical features, and outcomes in adults and children diagnosed with NCCM. Methods: A retrospective multicenter study from 4 cardiogenetic centers in the Netherlands classified 327 unrelated NCCM patients into 3 categories: 1) genetic, with a mutation in 32% (81 adults; 23 children) of patients; 2) probably genetic, familial cardiomyopathy without a mutation in 16% (45 adults; 8 children) of patients; or 3) sporadic, no family history, without mutation in 52% (149 adults; 21 children) of patients. Clinical features and major adverse cardiac events (MACE) during follow-up were compared across the children and adults. Results: MYH7, MYBPC3, and TTN mutations were the most common mutations (71%) found in genetic NCCM. The risk of having reduced left ventricular (LV) systolic dysfunction was higher for genetic patients compared with the probably genetic and sporadic cases (p = 0.024), with the highest risk in patients with multiple mutations and TTN mutations. Mutations were more frequent in children (p = 0.04) and were associated with MACE (p = 0.025). Adults were more likely to have sporadic NCCM. High risk for cardiac events in children and adults was related to LV systolic dysfunction in mutation carriers, but not in sporadic cases. Patients with MYH7 mutations had low risk for MACE (p = 0.03). Conclusions: NCCM is a heterogeneous condition, and genetic stratification has a role in clinical care. Distinguishing genetic from nongenetic NCCM complements prediction of outcome and may lead to management and follow-up tailored to genetic status

Genetics, Clinical Features, and Long-Term Outcome of Noncompaction Cardiomyopathy

The clinical outcomes of noncompaction cardiomyopathy (NCCM) range from asymptomatic to heart failure, arrhythmias, and sudden cardiac death. Genetics play an important role in NCCM. This study investigated the correlations among genetics, clinical features, and outcomes in adults and children diagnosed with NCCM. A retrospective multicenter study from 4 cardiogenetic centers in the Netherlands classified 327 unrelated NCCM patients into 3 categories: 1) genetic, with a mutation in 32% (81 adults; 23 children) of patients; 2) probably genetic, familial cardiomyopathy without a mutation in 16% (45 adults; 8 children) of patients; or 3) sporadic, no family history, without mutation in 52% (149 adults; 21 children) of patients. Clinical features and major adverse cardiac events (MACE) during follow-up were compared across the children and adults. MYH7, MYBPC3, and TTN mutations were the most common mutations (71%) found in genetic NCCM. The risk of having reduced left ventricular (LV) systolic dysfunction was higher for genetic patients compared with the probably genetic and sporadic cases (p = 0.024), with the highest risk in patients with multiple mutations and TTN mutations. Mutations were more frequent in children (p = 0.04) and were associated with MACE (p = 0.025). Adults were more likely to have sporadic NCCM. High risk for cardiac events in children and adults was related to LV systolic dysfunction in mutation carriers, but not in sporadic cases. Patients with MYH7 mutations had low risk for MACE (p = 0.03). NCCM is a heterogeneous condition, and genetic stratification has a role in clinical care. Distinguishing genetic from nongenetic NCCM complements prediction of outcome and may lead to management and follow-up tailored to genetic statu