Diagnosis and Risk Prediction of Dilated Cardiomyopathy in the Era of Big Data and Genomics

Dilated cardiomyopathy (DCM) is a leading cause of heart failure and life-threatening ventricular arrhythmias (LTVA). Work-up and risk stratification of DCM is clinically challenging, as there is great heterogeneity in phenotype and genotype. Throughout the last decade, improved genetic testing of patients has identified genotype–phenotype associations and enhanced evaluation of at-risk relatives leading to better patient prognosis. The field is now ripe to explore opportunities to improve personalised risk assessments. Multivariable risk models presented as “risk calculators” can incorporate a multitude of clinical variables and predict outcome (such as heart failure hospitalisations or LTVA). In addition, genetic risk scores derived from genome/exome-wide association studies can estimate an individual’s lifetime genetic risk of developing DCM. The use of clinically granular investigations, such as late gadolinium enhancement on cardiac magnetic resonance imaging, is warranted in order to increase predictive performance. To this end, constructing big data infrastructures improves accessibility of data by using electronic health records, existing research databases, and disease registries. By applying methods such as machine and deep learning, we can model complex interactions, identify new phenotype clusters, and perform prognostic modelling. This review aims to provide an overview of the evolution of DCM definitions as well as its clinical work-up and considerations in the era of genomics. In addition, we present exciting examples in the field of big data infrastructures, personalised prognostic assessment, and artificial intelligence

Automatic multilabel detection of ICD10 codes in Dutch cardiology discharge letters using neural networks

Standard reference terminology of diagnoses and risk factors is crucial for billing, epidemiological studies, and inter/intranational comparisons of diseases. The International Classification of Disease (ICD) is a standardized and widely used method, but the manual classification is an enormously time-consuming endeavor. Natural language processing together with machine learning allows automated structuring of diagnoses using ICD-10 codes, but the limited performance of machine learning models, the necessity of gigantic datasets, and poor reliability of terminal parts of these codes restricted clinical usability. We aimed to create a high performing pipeline for automated classification of reliable ICD-10 codes in the free medical text in cardiology. We focussed on frequently used and well-defined three- and four-digit ICD-10 codes that still have enough granularity to be clinically relevant such as atrial fibrillation (I48), acute myocardial infarction (I21), or dilated cardiomyopathy (I42.0). Our pipeline uses a deep neural network known as a Bidirectional Gated Recurrent Unit Neural Network and was trained and tested with 5548 discharge letters and validated in 5089 discharge and procedural letters. As in clinical practice discharge letters may be labeled with more than one code, we assessed the single- and multilabel performance of main diagnoses and cardiovascular risk factors. We investigated using both the entire body of text and only the summary paragraph, supplemented by age and sex. Given the privacy-sensitive information included in discharge letters, we added a de-identification step. The performance was high, with F1 scores of 0.76–0.99 for three-character and 0.87–0.98 for four-character ICD-10 codes, and was best when using complete discharge letters. Adding variables age/sex did not affect results. For model interpretability, word coefficients were provided and qualitative assessment of classification was manually performed. Because of its high performance, this pipeline can be useful to decrease the administrative burden of classifying discharge diagnoses and may serve as a scaffold for reimbursement and research applications

Evaluation of the cardiac amyloidosis clinical pathway implementation: A real-world experience

AIMS: The aim of this study is to evaluate the implementation of the cardiac amyloidosis (CA) clinical pathway on awareness among referring cardiologists, diagnostic delay, and severity of CA at diagnosis. METHODS AND RESULTS: Patients with CA were retrospectively included in this study and divided into two periods: pre-implementation of the CA clinical pathway (2007–18; T1) and post-implementation (2019–20; T2). Patients’ and disease characteristics were extracted from electronic health records and compared. In total, 113 patients (mean age 67.8 ± 8.5 years, 26% female) were diagnosed with CA [T1 (2007–18): 56; T2 (2019–20): 57]. The number of CA diagnoses per year has increased over time. Reasons for referral changed over time, with increased awareness of right ventricular hypertrophy (9% in T1 vs. 36% in T2) and unexplained heart failure with preserved ejection fraction (22% in T1 vs. 38% in T2). Comparing T1 with T2, the diagnostic delay also improved (14 vs. 8 months, P < 0.01), New York Heart Association Class III (45% vs. 23%, P = 0.03), and advanced CA stage (MAYO/Gillmore Stage III/IV; 61% vs. 33%, P ≤ 0.01) at time of diagnosis decreased. CONCLUSION: After implementation of the CA clinical pathway, the awareness among referring cardiologists improved, diagnostic delay was decreased, and patients had less severe CA at diagnosis. Further studies are warranted to assess the prognostic impact of CA clinical pathway implementation

Truncating Titin (TTN) Variants in Chemotherapy-Induced Cardiomyopathy

Chemotherapy-induced cardiomyopathy (CCMP) is a complication of chemotherapy treatment occurring in 9% of patients treated with the use of anthracyclines. Currently, risk stratification is based on clinical risk factors that do not adequately account for variable individual susceptibility. This suggests the presence of other determinants. In this case series, we describe 2 women with breast cancer who developed severe heart failure within months after chemotherapy. Genetic screening revealed truncating frameshift mutations in TTN, encoding the myofilament titin, in both women. To our knowledge, this is the 1st report of an association between truncating TTN variants and CCMP. Because truncations in TTN are the most common cause of familial and sporadic dilated cardiomyopathy, further research is needed to establish their prevalence in patients presenting with CCMP

Circulating Acylcarnitines Associated with Hypertrophic Cardiomyopathy Severity: an Exploratory Cross-Sectional Study in MYBPC3 Founder Variant Carriers

Hypertrophic cardiomyopathy (HCM) is a relatively common genetic heart disease characterised by myocardial hypertrophy. HCM can cause outflow tract obstruction, sudden cardiac death and heart failure, but severity is highly variable. In this exploratory cross-sectional study, circulating acylcarnitines were assessed as potential biomarkers in 124 MYBPC3 founder variant carriers (59 with severe HCM, 26 with mild HCM and 39 phenotype-negative [G + P-]). Elastic net logistic regression identified eight acylcarnitines associated with HCM severity. C3, C4, C6-DC, C8:1, C16, C18 and C18:2 were significantly increased in severe HCM compared to G + P-, and C3, C6-DC, C8:1 and C18 in mild HCM compared to G + P-. In multivariable linear regression, C6-DC and C8:1 correlated to log-transformed maximum wall thickness (coefficient 5.01, p = 0.005 and coefficient 0.803, p = 0.007, respectively), and C6-DC to log-transformed ejection fraction (coefficient -2.50, p = 0.004). Acylcarnitines seem promising biomarkers for HCM severity, however prospective studies are required to determine their prognostic value

Genomic DNA Pooling Strategy for Next-Generation Sequencing-Based Rare Variant Discovery in Abdominal Aortic Aneurysm Regions of Interest—Challenges and Limitations

The costs and efforts for sample preparation of hundreds of individuals, their genomic enrichment for regions of interest, and sufficient deep sequencing bring a significant burden to next-generation sequencing-based experiments. We investigated whether pooling of samples at the level of genomic DNA would be a more versatile strategy for lowering the costs and efforts for common disease-associated rare variant detection in candidate genes or associated loci in a substantial patient cohort. We performed a pilot experiment using five pools of 20 abdominal aortic aneurysm (AAA) patients that were enriched on separate microarrays for the reported 9p21.3 associated locus and 42 additional AAA candidate genes, and sequenced on the SOLiD platform. Here, we discuss challenges and limitations connected to this approach and show that the high number of novel variants detected per pool and allele frequency deviations to the usually highly false positive cut-off region for variant detection in non-pooled samples can be limiting factors for successful variant prioritization and confirmation. We conclude that barcode indexing of individual samples before pooling followed by a multiplexed enrichment strategy should be preferred for detection of rare genetic variants in larger sample sets rather than a genomic DNA pooling strategy

LKB1 Destabilizes Microtubules in Myoblasts and Contributes to Myoblast Differentiation

Background: Skeletal muscle myoblast differentiation and fusion into multinucleate myotubes is associated with dramatic cytoskeletal changes. We find that microtubules in differentiated myotubes are highly stabilized, but premature microtubule stabilization blocks differentiation. Factors responsible for microtubule destabilization in myoblasts have not been identified. Findings: We find that a transient decrease in microtubule stabilization early during myoblast differentiation precedes the ultimate microtubule stabilization seen in differentiated myotubes. We report a role for the serine-threonine kinase LKB1 in both microtubule destabilization and myoblast differentiation. LKB1 overexpression reduced microtubule elongation in a Nocodazole washout assay, and LKB1 RNAi increased it, showing LKB1 destabilizes microtubule assembly in myoblasts. LKB1 levels and activity increased during myoblast differentiation, along with activation of the known LKB1 substrates AMPactivated protein kinase (AMPK) and microtubule affinity regulating kinases (MARKs). LKB1 overexpression accelerated differentiation, whereas RNAi impaired it. Conclusions: Reduced microtubule stability precedes myoblast differentiation and the associated ultimate microtubule stabilization seen in myotubes. LKB1 plays a positive role in microtubule destabilization in myoblasts and in myoblast differentiation. This work suggests a model by which LKB1-induced microtubule destabilization facilitates the cytoskeleta

Improving outcomes for donation after circulatory death kidney transplantation: Science of the times

The use of kidneys donated after circulatory death (DCD) remains controversial due to concerns with regard to high incidences of early graft loss, delayed graft function (DGF), and impaired graft survival. As these concerns are mainly based on data from historical cohorts, they are prone to time-related effects and may therefore not apply to the current timeframe. To assess the impact of time on outcomes, we performed a time-dependent comparative analysis of outcomes of DCD and donation after brain death (DBD) kidney transplantations. Data of all 11,415 deceased-donor kidney transplantations performed in The Netherlands between 1990-2018 were collected. Based on the incidences of early graft loss, two eras were defined (1998-2008 [n = 3,499] and 2008-2018 [n = 3,781]), and potential time-related effects on outcomes evaluated. Multivariate analyses were applied to examine associations between donor type and outcomes. Interaction tests were used to explore presence of effect modification. Results show clear time-related effects on posttransplant outcomes. The 1998-2008 interval showed compromised outcomes for DCD procedures (higher incidences of DGF and early graft loss, impaired 1-year renal function, and inferior graft survival), whereas DBD and DCD outcome equivalence was observed for the 2008-2018 interval. This occurred despite persistently high incidences of DGF in DCD grafts, and more adverse recipient and donor risk profiles (recipients were 6 years older and the KDRI increased from 1.23 to 1.39 and from 1.35 to 1.49 for DBD and DCD donors). In contrast, the median cold ischaemic period decreased from 20 to 15 hours. This national study shows major improvements in outcomes of transplanted DCD kidneys over time. The time-dependent shift underpins that kidney transplantation has come of age and DCD results are nowadays comparable to DBD transplants. It also calls for careful interpretation of conclusions based on historical cohorts, and emphasises that retrospective studies should correct for time-related effects.Transplant surger

BIO FOr CARE: biomarkers of hypertrophic cardiomyopathy development and progression in carriers of Dutch founder truncating MYBPC3 variants-design and status

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is the most prevalent monogenic heart disease, commonly caused by truncating variants in the MYBPC3 gene. HCM is an important cause of sudden cardiac death; however, overall prognosis is good and penetrance in genotype-positive individuals is incomplete. The underlying mechanisms are poorly understood and risk stratification remains limited. AIM: To create a nationwide cohort of carriers of truncating MYBPC3 variants for identification of predictive biomarkers for HCM development and progression. METHODS: In the multicentre, observational BIO FOr CARe (Identification of BIOmarkers of hypertrophic cardiomyopathy development and progression in Dutch MYBPC3 FOunder variant CARriers) cohort, carriers of the c.2373dupG, c.2827C > T, c.2864_2865delCT and c.3776delA MYBPC3 variants are included and prospectively undergo longitudinal blood collection. Clinical data are collected from first presentation onwards. The primary outcome constitutes a composite endpoint of HCM progression (maximum wall thickness ≥ 20 mm, septal reduction therapy, heart failure occurrence, sustained ventricular arrhythmia and sudden cardiac death). RESULTS: So far, 250 subjects (median age 54.9 years (interquartile range 43.3, 66.6), 54.8% male) have been included. HCM was diagnosed in 169 subjects and dilated cardiomyopathy in 4. The primary outcome was met in 115 subjects. Blood samples were collected from 131 subjects. CONCLUSION: BIO FOr CARe is a genetically homogeneous, phenotypically heterogeneous cohort incorporating a clinical data registry and longitudinal blood collection. This provides a unique opportunity to study biomarkers for HCM development and prognosis. The established infrastructure can be extended to study other genetic variants. Other centres are invited to join our consortium