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Purpose: To characterize the genetic architecture of left ventricular noncompaction (LVNC) and investigate the extent to which it may represent a distinct pathology or a secondary phenotype associated with other cardiac diseases. Methods: We performed rare variant association analysis with 840 LVNC cases and 125,748 gnomAD population controls, and compared results to similar analyses on dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM). Results: We observed substantial genetic overlap indicating that LVNC often represents a phenotypic variation of DCM or HCM. In contrast, truncating variants in MYH7, ACTN2, and PRDM16 were uniquely associated with LVNC and may reflect a distinct LVNC etiology. In particular, MYH7 truncating variants (MYH7tv), generally considered nonpathogenic for cardiomyopathies, were 20-fold enriched in LVNC cases over controls. MYH7tv heterozygotes identified in the UK Biobank and healthy volunteer cohorts also displayed significantly greater noncompaction compared with matched controls. RYR2 exon deletions and HCN4 transmembrane variants were also enriched in LVNC, supporting prior reports of association with arrhythmogenic LVNC phenotypes. Conclusion: LVNC is characterized by substantial genetic overlap with DCM/HCM but is also associated with distinct noncompaction and arrhythmia etiologies. These results will enable enhanced application of LVNC genetic testing and help to distinguish pathological from physiological noncompaction.

Genetic testing for hypertrophic cardiomyopathy ( HCM ) is an established clinical technique, supported by 30 years of research into its genetic etiology. Although pathogenic variants are often detected in patients and used to identify at‐risk relatives, the effectiveness of genetic testing has been hampered by ambiguous genetic associations (yielding uncertain and potentially false‐positive results), difficulties in classifying variants, and uncertainty about genotype‐negative patients. Recent case‐control studies on rare variation, improved data sharing, and meta‐analysis of case cohorts contributed to new insights into the genetic basis of HCM . In particular, although research into new genes and mechanisms remains essential, reassessment of Mendelian genetic associations in HCM argues that current clinical genetic testing should be limited to a small number of validated disease genes that yield informative and interpretable results. Accurate and consistent variant interpretation has benefited from new standardized variant interpretation guidelines and innovative approaches to improve classification. Most cases lacking a pathogenic variant are now believed to indicate non‐Mendelian HCM , with more benign prognosis and minimal risk to relatives. Here, we discuss recent advances in the genetics of HCM and their application to clinical genetic testing together with practical issues regarding implementation. Although this review focuses on HCM , many of the issues discussed are also relevant to other inherited cardiac diseases.

BackgroundLeft ventricular non-compaction (LVNC) is a condition characterised by trabeculations in the myocardial wall and is the subject of considerable conjecture as to whether it represents a distinct pathology or a secondary phenotype associated with other cardiac diseases, particularly cardiomyopathies. We sought to investigate the genetic architecture of LVNC by identifying genes and variant classes robustly associated with disease and comparing these to other genetically characterised cardiomyopathies.MethodsWe performed rare variant association analysis using six different LVNC cohorts comprising 840 cases together with 125,748 gnomAD population controls and compared results to similar analyses with dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM) cases.ResultsWe observed substantial overlap in genes and variant classes enriched in LVNC and DCM/HCM, indicating that in many cases LVNC belongs to a spectrum of more established cardiomyopathies, with non-compaction representing a phenotypic variation in patients with DCM- or HCM-causing variants. In contrast, five variant classes were uniquely enriched in LVNC cases, of which truncating variants inMYH7, ACTN2andPRDM16may represent a distinct LVNC aetiology.MYH7truncating variants are generally considered as non-pathogenic but were detected in 2% of LVNC cases compared to 0.1% of controls, including a cluster of variants around a single splice region. Individuals withMYH7truncating variants identified in the UK Biobank and cohorts of healthy volunteers also displayed significantly greater non-compaction compared to matched controls, with 50% meeting the diagnostic criteria for LVNC. Additionally, structural variants (exon deletions) inRYR2and missense variants in the transmembrane region ofHCN4were enriched in LVNC cases, confirming prior reports regarding the association of these variant classes with combined LVNC and arrhythmia phenotypes.ConclusionsWe demonstrated that genetic association analysis can clarify the relationship between LVNC and established cardiomyopathies, highlighted substantial overlap with DCM/HCM but also identified variant classes associated with distinct LVNC and with joint LVNC/arrhythmia phenotypes. These results underline the complex genetic landscape of LVNC and inform how genetic testing in LVNC cases should be pursued and interpreted.

Background Differential diagnosis of genetic causes of left ventricular hypertrophy (LVH) is crucial for disease-specific therapy. We aim to describe the prevalence of Cardiac Amyloidosis (CA) among patients ≥40 years with an initial diagnosis of HCM referred for second opinion to national cardiomyopathy centres. Methods Consecutive patients aged ≥40 years referred with a tentative HCM diagnosis in the period 2014–2017 underwent clinical evaluation and genetic testing for HCM (including trans-thyretin-TTR). Patients with at least one red flag for CA underwent blood/urine tests, abdominal fat biopsy and/or bone-scintigraphy tracing and eventually ApoAI sequencing. Results Out of 343 patients (age 60 ± 13 years), 251 (73%) carried a likely/pathogenic gene variant, including 12 (3.5%) in the CA-associated genes TTR (n = 11) and ApoAI (n = 1). Furthermore, 6 (2%) patients had a mutation in GLA. Among the remaining, mutation-negative patients, 26 with ≥1 CA red-flag were investigated further: 3 AL-CA and 17 wild-type-TTR-CA were identified. Ultimately, 32(9%) patients were diagnosed with CA. Prevalence of CA increased with age: 1/75 (1%) at age 40–49, 2/86 (2%) at age 50–59, 8/84 (9%) at age 60–69, 13/61 (21%) at age 70–79, 8/31 (26%) at age ≥80 (p for trend Conclusions Among patients referred with and initial diagnosis of HCM, CA was the most common unrecognized mimic (9% prevalence) and increased with age (from 1% at ages 40–49 years to 26% >80 years). Age at diagnosis should be considered one of the most relevant red flags for CA in patients with HCM phenotypes; however, there is no clear age cut-off mandating scintigraphy and other second level investigations in the absence of other features suggestive of CA.

Purpose Genetic testing in hypertrophic cardiomyopathy (HCM) has long relied on Sanger sequencing of sarcomeric genes. The advent of next-generation sequencing (NGS) has catalyzed routine testing of additional genes of dubious HCM-causing potential. We used 19 years of genetic testing results to define a reliable set of genes implicated in Mendelian HCM and assess the value of expanded NGS panels. Methods We dissected genetic testing results from 1,198 single-center HCM probands and devised a widely applicable score to identify which genes yield effective results in the diagnostic setting. Results Compared with early panels targeting only fully validated sarcomeric HCM genes, expanded NGS panels allow the prompt recognition of probands with HCM-mimicking diseases. Scoring by “diagnostic effectiveness” highlighted that PLN should also be routinely screened besides historically validated genes for HCM and its mimics. Conclusion The additive value of expanded panels in HCM genetic testing lies in the systematic screening of genes associated with HCM mimics, requiring different patient management. Only variants in a limited set of genes are highly actionable and interpretable in the clinic, suggesting that larger panels offer limited additional sensitivity. A score estimating the relative effectiveness of a given gene’s inclusion in diagnostic panels is proposed.

In accordance with the Italian DNA legislation (DPR 7 April 2016, n. 87) a number of markers lower than seven are not considered usable for inclusion in the Italian forensic DNA database. For this reason, if the forensic DNA analysis performed in our laboratory do not provide acceptable results for a number greater than or equal to seven, the profile is not indicated in the final report. Thus, having indications about the possible success of an analysis before executing it, is a crucial point in the validation process of the accreditated method used in our laboratory. To achieve this goal, the quantification of extracts before typing plays a fundamental role. Especially when touched objects need to be examined tens or hundreds of nanograms may be present, but also very few or no cell can be present on the object. As such, quantification of every sample can ensure the maximum efficiency and prevent repeat analyses, over-amplified samples or completely useless examination. Quantifiler® Trio DNA quantification kit was validated in our laboratory according the guidelines approved by the ENFSI and always used before STR amplification of forensic casework DNA samples. Our attention has focused in particular on the definition of a minimum threshold at which it is useless to carry out DNA typing defining correlation of the negative results of the quantification by the absence of genetic profiles, as a result of DNA typing. Moreover, the validation of the Savant™ SPD131DDA SpeedVac™ Concentrator to get the maximum possible yield from DNA extracts was also investigated.