Machine learning modelling of blood lipid biomarkers in familial hypercholesterolaemia versus polygenic/environmental dyslipidaemia

AbstractFamilial hypercholesterolaemia increases circulating LDL-C levels and leads to premature cardiovascular disease when undiagnosed or untreated. Current guidelines support genetic testing in patients complying with clinical diagnostic criteria and cascade screening of their family members. However, most of hyperlipidaemic subjects do not present pathogenic variants in the known disease genes, and most likely suffer from polygenic hypercholesterolaemia, which translates into a relatively low yield of genetic screening programs. This study aims to identify new biomarkers and develop new approaches to improve the identification of individuals carrying monogenic causative variants. Using a machine-learning approach in a paediatric dataset of individuals, tested for disease causative genes and with an extended lipid profile, we developed new models able to classify familial hypercholesterolaemia patients with a much higher specificity than currently used methods. The best performing models incorporated parameters absent from the most common FH clinical criteria, namely apoB/apoA-I, TG/apoB and LDL1. These parameters were found to contribute to an improved identification of monogenic individuals. Furthermore, models using only TC and LDL-C levels presented a higher specificity of classification when compared to simple cut-offs. Our results can be applied towards the improvement of the yield of genetic screening programs and corresponding costs.

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Population-Based Screening in Children For Early Diagnosis and Treatment of Familial Hypercholesterolemia: Design of The VRONI Study

10.21203/rs.3.rs-339829/v1 ◽

2021 ◽

Author(s):

Veronika Sanin ◽

Raphael Schmieder ◽

Sara Ates ◽

Lea Dewi Schlieben ◽

Jens Wiehler ◽

...

Keyword(s):

Familial Hypercholesterolemia ◽

Screening Program ◽

Molecular Genetic ◽

Population Based ◽

Molecular Genetic Analysis ◽

Cascade Screening ◽

Screening Programs ◽

Pathogenic Variants ◽

Risk Indices ◽

Training Courses

Abstract Background: Heterozygous Familial Hypercholesterolemia (FH) represents the most frequent monogenic disorder with an estimated prevalence of 1:250 in the general population. Diagnosis during childhood enables early initiation of preventive measures, reducing the risk of severe consecutive atherosclerotic manifestations. Nevertheless, population-based screening programs for FH are scarce.Methods: In the VRONI study children aged 5 to 14 years in Bavaria are invited to participate in a FH screening program during regular pediatric visits. The screening is based on LDL-C measurements from capillary blood. If exceeding 130 mg/dl (3.34 mmol/l), i.e. the expected 95th percentile in this age group, subsequent molecular genetic analysis for FH is performed. Children with FH pathogenic variants enter a registry and are treated by specialized pediatricians. Furthermore, qualified training centers offer FH-focused training courses to affected families. For first degree relatives, reverse cascade screening is recommended to identify and treat affected family members.Results: Implementation of VRONI required intensive prearrangements for addressing ethical, educational, data-safety, legal and organisational aspects, which will be outlined in this paper. Recruitment started in January of 2021, within two months more than 280 pediatricians screened over 1,150 children. Approximately 60,000 children are expected to be enrolled in the VRONI study until 2024. Conclusion: VRONI aims to test the feasibility of a population-based screening for FH in children in Bavaria, intending to set the stage for a nation-wide FH screening infrastructure. Further we aim to validate genetic variants of unclear significance, detect novel causative mutations, and contribute to polygenic risk indices. (German Clinical Trials Register: DRKS00022140; registered August 21st2020.)

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Cadherin 2-Related Arrhythmogenic Cardiomyopathy: Prevalence and Clinical Features

Circulation Genomic and Precision Medicine ◽

10.1161/circgen.120.003097 ◽

2021 ◽

Author(s):

Alice Ghidoni ◽

Perry M. Elliott ◽

Petros Syrris ◽

Hugh Calkins ◽

Cynthia A. James ◽

...

Keyword(s):

Heart Failure ◽

Clinical Features ◽

Genetic Screening ◽

Rare Variants ◽

Family Members ◽

Arrhythmogenic Cardiomyopathy ◽

Cascade Screening ◽

Pathogenic Variants ◽

Fatty Replacement ◽

The Right

Background - Arrhythmogenic cardiomyopathy (ACM) is an inherited cardiac disease characterized by fibro-fatty replacement of the right and/or left ventricle, often causing ventricular dysfunction and life-threatening arrhythmias. Variants in desmosomal genes account for up to 60% of cases. Our objective was to establish the prevalence and clinical features of ACM stemming from pathogenic variants, in the non-desmosomal cadherin 2 ( CDH2 ), a novel genetic substrate of ACM. Methods - A cohort of 500 unrelated patients with a definite diagnosis of ACM and no disease-causing variants in the main ACM genes was assembled. Genetic screening of CDH2 was performed through next-generation or Sanger sequencing. Whenever possible, cascade screening was initiated in the families of CDH2 -positive probands, and clinical evaluation was assessed. Results - Genetic screening of CDH2 led to the identification of 7 rare variants: five, identified in 6 probands, were classified as pathogenic or likely pathogenic. The previously established p.D407N pathogenic variant was detected in 2 additional probands. Probands and family members with pathogenic/likely pathogenic variants in CDH2 were clinically evaluated, and along with previously published cases, altogether contributed to the identification of gene-specific features (13 cases from this cohort and 11 previously published, for a total of 9 probands and 15 family members). Ventricular arrhythmic events occurred in most CDH2 -positive subjects (20/24, 83%), while the occurrence of heart failure was rare (2/24, 8.3%). Among probands, sustained ventricular tachycardia and/or sudden cardiac death occurred in 5/9 (56%). Conclusions - In this worldwide cohort of previously genotype-negative ACM patients, the prevalence of probands with CDH2 pathogenic/likely pathogenic variants was 1.2% (6/500). Our data show that this cohort of CDH2 -ACM patients has a high incidence of ventricular arrhythmias, while evolution toward heart failure is rare.

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Familial Hypercholesterolaemia Diagnosis and Management

European Cardiology Review ◽

10.15420/ecr.2018:10:2 ◽

2018 ◽

Vol 13 (1) ◽

pp. 14 ◽

Cited By ~ 7

Author(s):

Rodrigo Alonso ◽

Leopoldo Perez de Isla ◽

Ovidio Muñiz-Grijalvo ◽

Jose Luis Diaz-Diaz ◽

Pedro Mata ◽

...

Keyword(s):

Ldl Cholesterol ◽

Familial Hypercholesterolaemia ◽

Receptor Gene ◽

Ldl Receptor ◽

Premature Coronary Artery Disease ◽

Cascade Screening ◽

Adequate Treatment ◽

Clinical Criteria ◽

Disease Mutations ◽

Artery Disease

Familial hypercholesterolaemia is the most common monogenic disorder associated with premature coronary artery disease. Mutations are most frequently found in the LDL receptor gene. Clinical criteria can be used to make the diagnosis; however, genetic testing will confirm the disorder and is very useful for cascade screening. Early identification and adequate treatment can improve prognosis, reducing negative clinical cardiovascular outcomes. Patients with familial hypercholesterolaemia are considered at high cardiovascular risk and the treatment target is LDL cholesterol <2.6 mmol/l or at least a 50 % reduction in LDL cholesterol. Patients require intensive treatment with statins and ezetimibe and/or colesevelam. Recently, proprotein convertase subtilisin/kexin type 9 inhibitors have been approved for the management of familial hypercholesterolaemia on top of statins.

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Avoiding the technological imperative: Criteria for genetic screening programs

10.21926/obm.genet.1703006 ◽

2017 ◽

Vol 1 (3) ◽

pp. 1-1 ◽

Cited By ~ 2

Author(s):

Anne-Marie Laberge ◽

◽

Wylie Burke ◽

◽

Keyword(s):

Genetic Screening ◽

Screening Programs ◽

Technological Imperative

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Diagnostic difficulties and possibilities of NF1-like syndromes in childhood

BMC Pediatrics ◽

10.1186/s12887-021-02791-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Eva Pinti ◽

Krisztina Nemeth ◽

Krisztina Staub ◽

Anna Lengyel ◽

Gyorgy Fekete ◽

...

Keyword(s):

Diagnostic Criteria ◽

Neurofibromatosis Type ◽

Early Years ◽

Diagnostic Efficiency ◽

Clinical Criteria ◽

Pathogenic Variants ◽

Clinical Diagnostic ◽

Long Time ◽

Diagnostic Difficulties ◽

Clinical Diagnostic Criteria

Abstract Background Neurofibromatosis type 1 (NF1), which is caused by heterozygous inactivating pathogenic variants in the NF1, has poor phenotypic expressivity in the early years of life and there are numerous conditions, including many other tumor predisposition syndromes, that can mimic its appearance. These are collectively termed NF1-like syndromes and are also connected by their genetic background. Therefore, the NF1’s clinical diagnostic efficiency in childhood could be difficult and commonly should be completed with genetic testing. Methods To estimate the number of syndromes/conditions that could mimic NF1, we compiled them through an extensive search of the scientific literature. To test the utility of NF1’s National Institutes of Health (NIH) clinical diagnostic criteria, which have been in use for a long time, we analyzed the data of a 40-member pediatric cohort with symptoms of the NF1-like syndromes’ overlapping phenotype and performed NF1 genetic test, and established the average age when diagnostic suspicion arises. To facilitate timely identification, we compiled strongly suggestive phenotypic features and anamnestic data. Results In our cohort the utility of NF1’s clinical diagnostic criteria were very limited (sensitivity: 80%, specificity: 30%). Only 53% of children with clinically diagnosed NF1 had a detectable NF1 pathogenic variation, whereas 40% of patients without fulfilled clinical criteria tested positive. The average age at first genetic counseling was 9 years, and 40% of children were referred after at least one tumor had already been diagnosed. These results highlight the need to improve NF1-like syndromes’ diagnostic efficiency in childhood. We collected the most extensive spectrum of NF1-like syndromes to help the physicians in differential diagnosis. We recommend the detailed, non-invasive clinical evaluation of patients before referring them to a clinical geneticist. Conclusions Early diagnosis of NF1-like syndromes can help to prevent severe complications by appropriate monitoring and management. We propose a potential screening, diagnostic and management strategy based on our findings and recent scientific knowledge.

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Pathogenic variants in GNPTAB and GNPTG encoding distinct subunits of GlcNAc-1-phosphotransferase differentially impact bone resorption in patients with mucolipidosis type II and III

Genetics in Medicine ◽

10.1038/s41436-021-01285-9 ◽

2021 ◽

Author(s):

Giorgia Di Lorenzo ◽

Lena M. Westermann ◽

Timur A. Yorgan ◽

Julian Stürznickel ◽

Nataniel F. Ludwig ◽

...

Keyword(s):

Bone Resorption ◽

Bone Remodeling ◽

Bone Cells ◽

Collagen Crosslinks ◽

Clinical Criteria ◽

Pathogenic Variants ◽

Bone Biopsies ◽

Appropriate Therapy ◽

Alpha Beta ◽

Deficient Mice

Abstract Purpose Pathogenic variants in GNPTAB and GNPTG, encoding different subunits of GlcNAc-1-phosphotransferase, cause mucolipidosis (ML) II, MLIII alpha/beta, and MLIII gamma. This study aimed to investigate the cellular and molecular bases underlying skeletal abnormalities in patients with MLII and MLIII. Methods We analyzed bone biopsies from patients with MLIII alpha/beta or MLIII gamma by undecalcified histology and histomorphometry. The skeletal status of Gnptgkoand Gnptab-deficient mice was determined and complemented by biochemical analysis of primary Gnptgko bone cells. The clinical relevance of the mouse data was underscored by systematic urinary collagen crosslinks quantification in patients with MLII, MLIII alpha/beta, and MLIII gamma. Results The analysis of iliac crest biopsies revealed that bone remodeling is impaired in patients with GNPTAB-associated MLIII alpha/beta but not with GNPTG-associated MLIII gamma. Opposed to Gnptab-deficient mice, skeletal remodeling is not affected in Gnptgko mice. Most importantly, patients with variants in GNPTAB but not in GNPTG exhibited increased bone resorption. Conclusion The gene-specific impact on bone remodeling in human individuals and in mice proposes distinct molecular functions of the GlcNAc-1-phosphotransferase subunits in bone cells. We therefore appeal for the necessity to classify MLIII based on genetic in addition to clinical criteria to ensure appropriate therapy.

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Reassessment of Gene-Elusive Familial Dilated Cardiomyopathy Leading to the Discovery of a Homozygous AARS2 Variant—The Importance of Regular Reassessment of Genetic Findings

Cardiogenetics ◽

10.3390/cardiogenetics11030013 ◽

2021 ◽

Vol 11 (3) ◽

pp. 122-128

Author(s):

Priya Bhardwaj ◽

Christoffer Rasmus Vissing ◽

Niels Kjær Stampe ◽

Kasper Rossing ◽

Alex Hørby Christensen ◽

...

Keyword(s):

Dilated Cardiomyopathy ◽

Genetic Screening ◽

Sanger Sequencing ◽

Mitochondrial Protein ◽

Trna Synthetase ◽

Familial Dilated Cardiomyopathy ◽

Pathogenic Variants ◽

Case Summary ◽

Heterozygous Carriers ◽

Important Enzyme

Background: AARS2 encodes the mitochondrial protein alanyl-tRNA synthetase 2 (MT-AlaRS), an important enzyme in oxidative phosphorylation. Variants in AARS2 have previously been associated with infantile cardiomyopathy. Case summary: A 4-year-old girl died of infantile-onset dilated cardiomyopathy (DCM) in 1996. Fifteen years later, her 21-year-old brother was diagnosed with DCM and ultimately underwent heart transplantation. Initial sequencing of 15 genes discovered no pathogenic variants in the brother at the time of his diagnosis. However, 9 years later re-screening in an updated screening panel of 129 genes identified a homozygous AARS2 (c.1774C > T) variant. Sanger sequencing of the deceased girl confirmed her to be homozygous for the AARS2 variant, while both parents and a third sibling were all found to be unaffected heterozygous carriers of the AARS2 variant. Discussion: This report underlines the importance of repeated and extended genetic screening of elusive families with suspected hereditary cardiomyopathies, as our knowledge of disease-causing mutations continuously grows. Although identification of the genetic etiology in the reported family would not have changed the clinical management, the genetic finding allows genetic counselling and holds substantial value in identifying at-risk relatives.

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“Guilt by association” is not competitive with genetic association for identifying autism risk genes

Scientific Reports ◽

10.1038/s41598-021-95321-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Margot Gunning ◽

Paul Pavlidis

Keyword(s):

Machine Learning ◽

Genetic Association ◽

Gene Networks ◽

Rare Variants ◽

Association Studies ◽

Genetic Disorders ◽

Autism Spectrum ◽

Biological Data ◽

Disease Genes ◽

Risk Genes

AbstractDiscovering genes involved in complex human genetic disorders is a major challenge. Many have suggested that machine learning (ML) algorithms using gene networks can be used to supplement traditional genetic association-based approaches to predict or prioritize disease genes. However, questions have been raised about the utility of ML methods for this type of task due to biases within the data, and poor real-world performance. Using autism spectrum disorder (ASD) as a test case, we sought to investigate the question: can machine learning aid in the discovery of disease genes? We collected 13 published ASD gene prioritization studies and evaluated their performance using known and novel high-confidence ASD genes. We also investigated their biases towards generic gene annotations, like number of association publications. We found that ML methods which do not incorporate genetics information have limited utility for prioritization of ASD risk genes. These studies perform at a comparable level to generic measures of likelihood for the involvement of genes in any condition, and do not out-perform genetic association studies. Future efforts to discover disease genes should be focused on developing and validating statistical models for genetic association, specifically for association between rare variants and disease, rather than developing complex machine learning methods using complex heterogeneous biological data with unknown reliability.

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One4Two®: An Integrated Molecular Approach to Optimize Infertile Couples’ Journey

Genes ◽

10.3390/genes12010060 ◽

2021 ◽

Vol 12 (1) ◽

pp. 60

Author(s):

Valeria D’Argenio ◽

Federica Cariati ◽

Rossella Tomaiuolo

Keyword(s):

Disease Genes ◽

Diagnostic Efficacy ◽

Whole Process ◽

Pathogenic Variants ◽

Limiting Step ◽

Number Of Genes ◽

Infertile Couples ◽

Next Generation Sequencing Ngs ◽

And Diffusion ◽

Generation Sequencing

The current diagnostic path of infertile couples is long lasting and often ineffective. Genetic tests, in particular, appear as a limiting step due to their jeopardized use on one side, and to the limited number of genes evaluated on the other. In this context, the development and diffusion, also in routine diagnostic settings, of next generation sequencing (NGS)-based methods for the analyses of several genes in multiple subjects at a time is improving the diagnostic sensitivity of molecular analyses. Thus, we developed One4Two®, a custom NGS panel to optimize the diagnostic journey of infertile couples. The panel validation was carried out in three steps analyzing a total of 83 subjects. Interestingly, all the previously identified variants were confirmed, assessing the analytic sensitivity of the method. Moreover, additional pathogenic variants have been identified underlying the diagnostic efficacy of the proposed method. One4Two® allows the simultaneous analysis of infertility-related genes, disease-genes of common inherited diseases, and of polymorphisms related to therapy outcome. Thus, One4Two® is able to improve the diagnostic journey of infertile couples by simplifying the whole process not only for patients, but also for laboratories and reproduction specialists moving toward an even more personalized medicine.

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Recurrent Clostridioides difficile infection can be predicted using inflammatory mediator and toxin activity levels

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.568 ◽

2020 ◽

Vol 41 (S1) ◽

pp. s77-s78

Author(s):

Jonathan Motyka ◽

Aline Penkevich ◽

Vincent Young ◽

Krishna Rao

Keyword(s):

Machine Learning ◽

Inflammatory Mediators ◽

Inflammatory Mediator ◽

Characteristic Curve ◽

Receiver Operator Characteristic Curve ◽

Sensitivity Analyses ◽

Activity Levels ◽

Clinical Criteria ◽

Clostridioides Difficile ◽

Potential Biomarker

Background:Clostridioides difficile infection (CDI) frequently recurs after initial treatment. Predicting recurrent CDI (rCDI) early in the disease course can assist clinicians in their decision making and improve outcomes. However, predictions based on clinical criteria alone are not accurate and/or do not validate other results. Here, we tested the hypothesis that circulating and stool-derived inflammatory mediators predict rCDI. Methods: Consecutive subjects with available specimens at diagnosis were included if they tested positive for toxigenic C. difficile (+enzyme immunoassay [EIA] for glutamate dehydrogenase and toxins A/B, with reflex to PCR for the tcdB gene for discordants). Stool was thawed on ice, diluted 1:1 in PBS with protease inhibitor, centrifuged, and used immediately. A 17-plex panel of inflammatory mediators was run on a Luminex 200 machine using a custom antibody-linked bead array. Prior to analysis, all measurements were normalized and log-transformed. Stool toxin activity levels were quantified using a custom cell-culture assay. Recurrence was defined as a second episode of CDI within 100 days. Ordination characterized variation in the panel between outcomes, tested with a permutational, multivariate ANOVA. Machine learning via elastic net regression with 100 iterations of 5-fold cross validation selected the optimal model and the area under the receiver operator characteristic curve (AuROC) was computed. Sensitivity analyses excluding those that died and/or lived >100 km away were performed. Results: We included 186 subjects, with 95 women (51.1%) and average age of 55.9 years (±20). More patients were diagnosed by PCR than toxin EIA (170 vs 55, respectively). Death, rCDI, and no rCDI occurred in 32 (17.2%), 36 (19.4%), and 118 (63.4%) subjects, respectively. Ordination revealed that the serum panel was associated with rCDI (P = .007) but the stool panel was not. Serum procalcitonin, IL-8, IL-6, CCL5, and EGF were associated with recurrence. The machine-learning models using the serum panel predicted rCDI with AuROCs between 0.74 and 0.8 (Fig. 1). No stool inflammatory mediators independently predicted rCDI. However, stool IL-8 interacted with toxin activity to predict rCDI (Fig. 2). These results did not change significantly upon sensitivity analysis. Conclusions: A panel of serum inflammatory mediators predicted rCDI with up to 80% accuracy, but the stool panel alone was less successful. Incorporating toxin activity levels alongside inflammatory mediator measurements is a novel, promising approach to studying stool-derived biomarkers of rCDI. This approach revealed that stool IL-8 is a potential biomarker for rCDI. These results need to be confirmed both with a larger dataset and after adjustment for clinical covariates.Funding: NoneDisclosure: Vincent Young is a consultant for Bio-K+ International, Pantheryx, and Vedanta Biosciences.

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