Evaluation and limitations of different approaches among COVID-19 fatal cases using whole-exome sequencing data.

BACKGROUND: COVID-19 caused by the SARS-CoV-2 infection may result in various disease symptoms and severity, ranging from asymptomatic, through mildly symptomatic, up to very severe and even fatal cases. Although environmental, clinical, and social factors play important roles in both susceptibility to the SARS-CoV-2 infection and progress of COVID-19 disease, it is becoming evident that both pathogen and host genetic factors are important too. In this study, we report findings from whole-exome sequencing (WES) of 27 individuals who died due to COVID-19, especially focusing on frequencies of DNA variants in genes previously associated with the SARS-CoV-2 infection and the severity of COVID-19. RESULTS: We selected the risk DNA variants/alleles or target genes using four different approaches: 1) aggregated GWAS results from the GWAS Catalog; 2) selected publications from PubMed; 3) the aggregated results of the Host Genetics Initiative database; and 4) a commercial DNA variant annotation/interpretation tool providing its own knowledgebase. We divided these variants/genes into those reported to influence the susceptibility to the SARS-CoV-2 infection and those influencing the severity of COVID-19. Based on the above, we compared the frequencies of alleles found in the fatal COVID-19 cases to the frequencies identified in two population control datasets (non-Finnish European population from the gnomAD database and genomic frequencies specific for the Slovak population from our own database). When compared to both control population datasets, our analyses indicated a trend of higher frequencies of severe COVID-19 associated risk alleles among fatal COVID-19 cases. This trend reached statistical significance specifically when using the HGI-derived variant list. We also analysed other approaches to WES data evaluation, demonstrating its utility as well as limitations. CONCLUSIONS: Although our results proved the likely involvement of host genetic factors pointed out by previous studies looking into severity of COVID-19 disease, careful considerations of the molecular-testing strategies and the evaluated genomic positions may have a strong impact on the utility of genomic testing.

APOC3 and ABCA1 variants in unusual combined hypolipidaemia showing premature peripheral vascular disease.

BACKGROUND: Familial combined hypolipidaemia is a condition characterised by very low concentrations of circulating very-low-density lipoprotein (VLDL), low-density lipoprotein cholesterol (LDL), and high-density lipoprotein cholesterol (HDL). It is thought that low LDL/combined hypolipidaemia can protect from cardiovascular disease (CVD), but this is not what we found in a case we present. OBJECTIVE: We report on a 57-years-old male patient with combined hypolipidaemia who presented with premature peripheral vascular disease. We investigated also his two sons, 32- and 27-years-old, who manifested a tendency to low lipid levels. METHODS AND RESULTS: We used Illumina exome analysis in all three individuals and in all of them we could exclude the major effect of the variants within the genes most frequently mutated in hypolipidaemia, including recently reported LIPC gene variant. Instead, in all three individuals we identified a novel ABCA1 variant, possibly responsible for the decreased HDL levels. The proband and one of his sons also share the splicing APOC3 variant rs138326449, known to be associated with decreased TG levels. CONCLUSION: The heterogeneous nature and the risk of atherosclerosis in combined hypolipidaemia seems to be variable, based on an interplay between low HDL and LDL levels, and it depends on the combination of variants that cause it (Tab. 2, Ref. 38).

Alzheimer's Disease-Associated SNP rs708727 in SLC41A1 May Increase Risk for Parkinson's Disease: Report from Enlarged Slovak Study.

SLC41A1 (A1) SNPs rs11240569 and rs823156 are associated with altered risk for Parkinson's disease (PD), predominantly in Asian populations, and rs708727 has been linked to Alzheimer's disease (AD). In this study, we have examined a potential association of the three aforementioned SNPs and of rs9438393, rs56152218, and rs61822602 (all three lying in the A1 promoter region) with PD in the Slovak population. Out of the six tested SNPs, we have identified only rs708727 as being associated with an increased risk for PD onset in Slovaks. The minor allele (A) in rs708727 is associated with PD in dominant and completely over-dominant genetic models (ORD = 1.36 (1.05-1.77), p = 0.02, and ORCOD = 1.34 (1.04-1.72), p = 0.02). Furthermore, the genotypic triplet GG(rs708727) + AG(rs823156) + CC(rs61822602) might be clinically relevant despite showing a medium (h ≥ 0.5) size difference (h = 0.522) between the PD and the control populations. RandomForest modeling has identified the power of the tested SNPs for discriminating between PD-patients and the controls to be essentially zero. The identified association of rs708727 with PD in the Slovak population leads us to hypothesize that this A1 polymorphism, which is involved in the epigenetic regulation of the expression of the AD-linked gene PM20D1, is also involved in the pathoetiology of PD (or universally in neurodegeneration) through the same or similar mechanism as in AD.

Molecularly confirmed pontocerebellar hypoplasia in a large family from Slovakia with four severely affected children.

BACKGROUND: Pontocerebellar hypoplasia type 1 (PCH1) is characterized by a central and peripheral motor dysfunction associated with anterior horn cell degeneration, similar to spinal muscular atrophy (SMA). OBJECTIVES: We analysed three probands (later discovered to be siblings) suspected to have severe SMA, however, not confirmed by genetic test. METHODS: Clinical-exome analysis (Illumina) was performed to identify causative variants, followed by Sanger sequencing confirmation in probands and other 10 family members. RESULTS: Homozygous pathogenic variant c.92G>C (p.(Gly31Ala)) in the Exosome Component 3 (EXOSC3) gene was found in all 3 probands, thus confirming the diagnosis of a severe form of PCH1B. The parents and six siblings were carriers, while one sibling was homozygous for a reference allele. This variant is frequent in the Czech Roma population, where it is considered a founder mutation. Haplotype analysis in this largest reported PCH1B family showed that our patients inherited from their father (of Roma origin) a haplotype identical to that found in the Czech Roma population, thus indicating these alleles have a common origin. CONCLUSION: This EXOSC3 variant is rare among the general population but most likely frequent also among Roma people in Slovakia. PCH1B should be considered for a differential diagnosis in infants manifesting SMA-like phenotype, especially if of Roma origin (Tab. 1, Fig. 1, Ref. 22). Text in PDF www.elis.sk Keywords: pontocerebellar hypoplasia, PCH1B, EXOSC3, SMA plus syndromes, pathogenic sequence variant.

Privacy-preserving storage of sequenced genomic data.

BACKGROUND: The current and future applications of genomic data may raise ethical and privacy concerns. Processing and storing of this data introduce a risk of abuse by potential offenders since the human genome contains sensitive personal information. For this reason, we have developed a privacy-preserving method, named Varlock providing secure storage of sequenced genomic data. We used a public set of population allele frequencies to mask the personal alleles detected in genomic reads. Each personal allele described by the public set is masked by a randomly selected population allele with respect to its frequency. Masked alleles are preserved in an encrypted confidential file that can be shared in whole or in part using public-key cryptography. RESULTS: Our method masked the personal variants and introduced new variants detected in a personal masked genome. Alternative alleles with lower population frequency were masked and introduced more often. We performed a joint PCA analysis of personal and masked VCFs, showing that the VCFs between the two groups cannot be trivially mapped. Moreover, the method is reversible and personal alleles in specific genomic regions can be unmasked on demand. CONCLUSION: Our method masks personal alleles within genomic reads while preserving valuable non-sensitive properties of sequenced DNA fragments for further research. Personal alleles in the desired genomic regions may be restored and shared with patients, clinics, and researchers. We suggest that the method can provide an additional security layer for storing and sharing of the raw aligned reads.

Technical and Methodological Aspects of Cell-Free Nucleic Acids Analyzes.

Analyzes of cell-free nucleic acids (cfNAs) have shown huge potential in many biomedical applications, gradually entering several fields of research and everyday clinical care. Many biological properties of cfNAs can be informative to gain deeper insights into the function of the organism, such as their different types (DNA, RNAs) and subtypes (gDNA, mtDNA, bacterial DNA, miRNAs, etc.), forms (naked or vesicle bound NAs), fragmentation profiles, sequence composition, epigenetic modifications, and many others. On the other hand, the workflows of their analyzes comprise many important steps, from sample collection, storage and transportation, through extraction and laboratory analysis, up to bioinformatic analyzes and statistical evaluations, where each of these steps has the potential to affect the outcome and informational value of the performed analyzes. There are, however, no universal or standard protocols on how to exactly proceed when analyzing different cfNAs for different applications, at least according to our best knowledge. We decided therefore to prepare an overview of the available literature and products commercialized for cfNAs processing, in an attempt to summarize the benefits and limitations of the currently available approaches, devices, consumables, and protocols, together with various factors influencing the workflow, its processes, and outcomes.

Microsatellite instability assessment is instrumental for Predictive, Preventive and Personalised Medicine: status quo and outlook.

A form of genomic alteration called microsatellite instability (MSI) occurs in a class of tandem repeats (TRs) called microsatellites (MSs) or short tandem repeats (STRs) due to the failure of a post-replicative DNA mismatch repair (MMR) system. Traditionally, the strategies for determining MSI events have been low-throughput procedures that typically require assessment of tumours as well as healthy samples. On the other hand, recent large-scale pan-tumour studies have consistently highlighted the potential of massively parallel sequencing (MPS) on the MSI scale. As a result of recent innovations, minimally invasive methods show a high potential to be integrated into the clinical routine and delivery of adapted medical care to all patients. Along with advances in sequencing technologies and their ever-increasing cost-effectiveness, they may bring about a new era of Predictive, Preventive and Personalised Medicine (3PM). In this paper, we offered a comprehensive analysis of high-throughput strategies and computational tools for the calling and assessment of MSI events, including whole-genome, whole-exome and targeted sequencing approaches. We also discussed in detail the detection of MSI status by current MPS blood-based methods and we hypothesised how they may contribute to the shift from conventional medicine to predictive diagnosis, targeted prevention and personalised medical services. Increasing the efficacy of patient stratification based on MSI status is crucial for tailored decision-making. Contextually, this paper highlights drawbacks both at the technical level and those embedded deeper in cellular/molecular processes and future applications in routine clinical testing.

Combination of expert guidelines-based and machine learning-based approaches leads to superior accuracy of automated prediction of clinical effect of copy number variations.

Clinical interpretation of copy number variants (CNVs) is a complex process that requires skilled clinical professionals. General recommendations have been recently released to guide the CNV interpretation based on predefined criteria to uniform the decision process. Several semiautomatic computational methods have been proposed to recommend appropriate choices, relieving clinicians of tedious searching in vast genomic databases. We have developed and evaluated such a tool called MarCNV and tested it on CNV records collected from the ClinVar database. Alternatively, the emerging machine learning-based tools, such as the recently published ISV (Interpretation of Structural Variants), showed promising ways of even fully automated predictions using broader characterization of affected genomic elements. Such tools utilize features additional to ACMG criteria, thus providing supporting evidence and the potential to improve CNV classification. Since both approaches contribute to evaluation of CNVs clinical impact, we propose a combined solution in the form of a decision support tool based on automated ACMG guidelines (MarCNV) supplemented by a machine learning-based pathogenicity prediction (ISV) for the classification of CNVs. We provide evidence that such a combined approach is able to reduce the number of uncertain classifications and reveal potentially incorrect classifications using automated guidelines. CNV interpretation using MarCNV, ISV, and combined approach is available for non-commercial use at https://predict.genovisio.com/ .

DNA copy number variation: Main characteristics, evolutionary significance, and pathological aspects.

Copy number variants (CNVs) were the subject of extensive research in the past years. They are common features of the human genome that play an important role in evolution, contribute to population diversity, development of certain diseases, and influence host-microbiome interactions. CNVs have found application in the molecular diagnosis of many diseases and in non-invasive prenatal care, but their full potential is only emerging. CNVs are expected to have a tremendous impact on screening, diagnosis, prognosis, and monitoring of several disorders, including cancer and cardiovascular disease. Here, we comprehensively review basic definitions of the term CNV, outline mechanisms and factors involved in CNV formation, and discuss their evolutionary and pathological aspects. We suggest a need for better defined distinguishing criteria and boundaries between known types of CNVs.