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The p.Val142Ile variant in transthyretin (encoded by the TTR gene) is the most common genetic cause of transthyretin-related amyloidosis. This allele is particularly prevalent in communities of African descent compared with populations of different ancestries, where its frequency is two orders of magnitude lower. For this reason, p.Val142Ile has always been considered an “African” variant, with limited studies performed on individuals of European descent. However, recent reports of higher-than-expected prevalence in European-ancestry populations question the African specificity of this allele. Here we show that the high recurrence of p.Val142Ile in central Italy is due to a founder effect and not to recent admixture from African populations, highlighting how this may be the case in other communities. This suggests a probable underestimate of the global prevalence of p.Val142Ile, and further emphasizes the importance of routine inclusion of TTR in gene panels used for clinical genetic testing in hypertrophic cardiomyopathy (independently of the patient's geographical origin), that transthyretin-related amyloidosis can mimic. Figure.Principal Component Analysis (PCA) of the 16 probands together with the 25044 individuals of the 1000 Genomes Project (Phase 3) having been genotyped both within the 1000 Genomes Project (NA10851_1KG) and in-house (NA10851_internal). The proband clustering within the smear of native Americans is A228.

The p.Val142Ile variant in transthyretin (encoded by the TTR gene) is the most common genetic cause of transthyretin-related amyloidosis. This allele is particularly prevalent in communities ofAfrican descent compared with populations of different ancestries, where its frequency is two orders of magnitude lower. For this reason, p.Val142Ile has always been considered an "African" variant, with limited studies performed on individuals of European descent. However, recent reports of higher-than-expected prevalence in European-ancestry populations question the African specificity of this allele. Here we show that the high recurrence of p.Val142Ile in central Italy is due to a founder effect and not to recent admixture from African populations, highlighting how this may be the case in other communities. This suggests a probable underestimate of the global prevalence of p.Val142Ile, and further emphasizes the importance of routine inclusion of TTR in gene panels used for clinical genetic testing in hypertrophic cardiomyopathy (independently of the patient's geographical origin), that transthyretin-related amyloidosis can mimic.

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.

Background Left 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. Purpose 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. Methods We 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. Results We 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 in MYH7, ACTN2 and PRDM16 may represent a distinct LVNC aetiology. MYH7 truncating 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. Additionally, structural variants (exon deletions) in RYR2 and missense variants in the transmembrane region of HCN4 were enriched in LVNC cases, confirming prior reports regarding the association of these variant classes with combined LVNC and arrhythmia phenotypes. Conclusions We 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. Cardiomyopathy rare variant frequencies Funding Acknowledgement Type of funding source: None

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.

Sudden cardiac death (SCD) is one of the most common causes of death; most SCD are related to secondary arrhythmias, to structural heart disease, or to primary electrical abnormalities of the heart. A significant number of SCD, especially among young people, are due to genetic heart disorders, both with structural and arrhythmogenic abnormalities. However SCD occurs also in patients with negative clinical history, autopsy is not always conclusive for a diagnosis. Recent technological advances in DNA sequencing, have led to the commercialization of genetic testing now widely available in clinical practice. In particular, next generation sequencing, allows the large-scale and rapid assessment of entire genomes. Analysis of SCD with a NGS panel of 174 genes was performed in our laboratory in order to identify the genetic causes and thus to direct the clinician to an accurate clinical and genetic screening of relatives. Two SDC were studied: Case 1: female, 57, without story of syncope and no previously highlighted cardiac alteration, died post cardiac arrest; negative family history. Autopsy was apparently negative. Case 2: male, 52, who died during a football game; negative family history, neurological episodes occurred before death was reported by close relative. Autopsy was positive for ventricular hypertrophic. In both cases we made a genetic diagnosis.

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.

Hematopoietic stem cell transplantation (HSCT) is the predominant curative treatment for many malignant and non-malignant haematological diseases. Early detection of graft rejection and disease relapse following HSCT improves patient outcomes by allowing treatment to be initiated as quickly as possible. In order to evaluate the level of donor engraftment, mixed chimerism levels must be carefully monitored after transplantation. Short-tandem repeat (STR) genotyping is widely used to determine the proportions of donor and recipient cells after HSCT. In this study, Devyser Chimerism NGS kit in combination with a MiSeq System was introduced in our laboratory for monitoring HSCT. This system is a complete workflow solution for labs, combining a reliable testing process with a designed for-purpose analytical software. Up to 24 informative markers in a recipient/donor pair distributed through the human genome have strong discriminative power with low bias from ethnic parameters. These IND/DEL genetic markers with population independent discriminative power are distributed across 17 chromosomes and were further selected to allow sensitive detection combined with accurate and precise quantification of mixed chimerism. Streamlined, simple and robust NGS workflow uses just one multiplex PCR reaction per patient sample. Minimal hands-on time reduces assay complexity and risk of sample contamination and mix-up. User-friendly, designed-for-purpose software perfectly complements testing kit with an automatic detection of informative markers. Insertion/deletion (indel) polymorphisms have been used in the fields of forensic investigations owing to the advantages of their low mutation rates, widespread distributions in the human genome and small amplicon sizes. Thus, forensic efficiency evaluation of this system for forensic individual identification will be also tested.

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.