Association of polymorphic variants in human genome with the COVID-2019 severity and post-COVID syndrome development

Background/Objectives: Despite intensive research of the novel coronavirus SARS-CoV-2 and COVID-2019 caused by it, factors affecting the severity of the disease remains poorly understood. Clinical manifestations of COVID-2019 may vary from asymptomatic form to pneumonia, acute respiratory distress syndrome (ARDS) and multiorgan failure. Features of individual genetic landscape of patients can play an important role in development of the pathological process of COVID-19. In this regard the purpose of this study was to investigate the influence of polymorphic variants in genes (ADD1, CAT, IL17F, IL23R, NOS3, IFNL3, IL6, F2, F13A1, ITGB3, HIF1A, MMP12, VEGFA), associated with cardiovascular, respiratory and autoimmune pathologies, on the severity of COVID-19 and post-COVID syndrome in patients from Russia. Method(s): The study included 200 patients recovered from COVID-19. Two groups of patients were formed in accordance with clinical manifestations: with mild and moderate forms of the disease. The polymorphic variants were analysed with real-time PCR using commercial kits (Syntol). Result(s): 13 SNPs (rs4961;rs1001179;rs612242;rs11209026;rs2070744;rs8099917;rs1800795;rs1799963;rs5985;rs5918;rs11549465;rs652438;rs699947) were genotyped and comparative analysis of allele frequency distribution was carried out in two groups of patients recovered from COVID-2019. Conclusion(s): Identification of polymorphic variants in genome associated with severity of pathological processes in patients infected with SARS-CoV-2 can contribute to the identification of individuals with an increased risk of severe infection process and can also serve as a basis for developing personalized therapeutic approaches to the treatment of post-COVID syndrome.

A comprehensive knowledgebase of known and predicted human genetic variants associated with COVID-19 susceptibility and severity

Host genetic susceptibility is a key risk factor for severe illness associated with COVID-19. Despite numerous studies of COVID-19 host genetics, our knowledge of COVID-19-associated variants is still limited, and there is no resource comprising all the published variants and categorizing them based on their confidence level. Also, there are currently no computational tools available to predict novel COVID-19 severity variants. Therefore, we collated 820 host genetic variants reported to affect COVID-19 susceptibility by means of a systematic literature search and confidence evaluation, and obtained 196 high-confidence variants. We then developed the first machine learning classifier of severe COVID-19 variants to perform a genome-wide prediction of COVID-19 severity for 82,468,698 missense variants in the human genome. We further evaluated the classifier's predictions using feature importance analyses to investigate the biological properties of COVID-19 susceptibility variants, which identified conservation scores as the most impactful predictive features. The results of enrichment analyses revealed that genes carrying high-confidence COVID-19 susceptibility variants shared pathways, networks, diseases and biological functions, with the immune system and infectious disease being the most significant categories. Additionally, we investigated the pleiotropic effects of COVID-19-associated variants using phenome-wide association studies (PheWAS) in ~40,000 BioMe BioBank genotyped individuals, revealing pre-existing conditions that could serve to increase the risk of severe COVID-19 such as chronic liver disease and thromboembolism. Lastly, we generated a web-based interface for exploring, downloading and submitting genetic variants associated with COVID-19 susceptibility for use in both research and clinical settings (https://itanlab.shinyapps.io/COVID19webpage/). Taken together, our work provides the most comprehensive COVID-19 host genetics knowledgebase to date for the known and predicted genetic determinants of severe COVID-19, a resource that should further contribute to our understanding of the biology underlying COVID-19 susceptibility and facilitate the identification of individuals at high risk for severe COVID-19.Copyright © 2023 Elsevier Inc.

Antiviral activity of the human endogenous retrovirus-R envelope protein against SARS-CoV-2

Coronavirus-induced disease-19 (COVID-19), caused by SARS-CoV-2, is still a major global health challenge. Human endogenous retroviruses (HERVs) represent retroviral elements that were integrated into the ancestral human genome. HERVs are important in embryonic development as well as in the manifestation of diseases, including cancer, inflammation, and viral infections. Here, we analyze the expression of several HERVs in SARS-CoV-2-infected cells and observe increased activity of HERV-E, HERV-V, HERV-FRD, HERV-MER34, HERV-W, and HERV-K-HML2. In contrast, the HERV-R envelope is downregulated in cell-based models and PBMCs of COVID-19 patients. Overexpression of HERV-R inhibits SARS-CoV-2 replication, suggesting its antiviral activity. Further analyses demonstrate the role of the extracellular signal-regulated kinase (ERK) in regulating HERV-R antiviral activity. Lastly, our data indicate that the crosstalk between ERK and p38 MAPK controls the synthesis of the HERV-R envelope protein, which in turn modulates SARS-CoV-2 replication. These findings suggest the role of the HERV-R envelope as a prosurvival host factor against SARS-CoV-2 and illustrate a possible advantage of integration and evolutionary maintenance of retroviral elements in the human genome.Copyright © 2023 The Authors.

Acceptance of genetic editing and of whole genome sequencing of human embryos by patients with infertility before and after the onset of the COVID-19 pandemic.

RESEARCH QUESTION: Has acceptance of heritable genome editing (HGE) and whole genome sequencing for preimplantation genetic testing (PGT-WGS) of human embryos changed after the onset of COVID-19 among infertility patients? DESIGN: A written survey conducted between April and June 2018 and July and December 2021 among patients at a university-affiliated infertility practice. The questionnaire ascertained the acceptance of HGE for specific therapeutic or genetic 'enhancement' indications and of PGT-WGS to prevent adult disease. RESULTS: In 2021 and 2018, 172 patients and 469 patients (response rates: 90% and 91%, respectively) completed the questionnaire. In 2021, significantly more participants reported a positive attitude towards HGE, for therapeutic and enhancement indications. In 2021 compared with 2018, respondents were more likely to use HGE to have healthy children with their own gametes (85% versus 77%), to reduce disease risk for adult-onset polygenic disorders (78% versus 67%), to increase life expectancy (55% versus 40%), intelligence (34% versus 26%) and creativity (33% versus 24%). Fifteen per cent of the 2021 group reported a more positive attitude towards HGE because of COVID-19 and less than 1% a more negative attitude. In contrast, support for PGT-WGS was similar in 2021 and 2018. CONCLUSIONS: A significantly increased acceptance of HGE was observed, but not of PGT-WGS, after the onset of COVID-19. Although the pandemic may have contributed to this change, the exact reasons remain unknown and warrant further investigation. Whether increased acceptability of HGE may indicate an increase in acceptability of emerging biomedical technologies in general needs further investigation.

Biobanking: Paving Way For Medical Research

Biobank is a place where biosamples and associated data are collected and stored. The concept of biobanks may spark little excitement for most people. Biobanks are more developed in economically reach countries while it is a new for LMICs. As the advancement of science and technology, completion of human genome project, the treatment of patients are transformed from conventional to personalised. Human Genome project has advanced science through its application in microbiology, virology and pathology. In parallel to Human Genome project, Biobank has become a vital infrastructure for research, new drug discovery, it is also leading to the development of novel technologies, analytical tools and advancement of patient treatment through medical research. Biobanks are a key component of personalized medicine built on the three pillars of cancer research: proteomics, metabolomics, and epigenomics.lt has the potential to advance personalised medicine. Biobank aided in intense development in cancer research from the diagnostic, prognostic and therapeutic aspects. In recent pandemic Biobank have played and proved its role in fight against Covid-19 by allowing researches to study the disease and develop vaccines and treatment in short time. Without involvement of biobank and good quality of samples from patients infected with Covid-19, it would have been unachievable to sequence SARS-COV-2 virus and develop effective vaccines in record times.

Genomic Data Science And COVID -19 Genome Analysis Using Bio Python

The last few years have been amazing for biology and healthcare and the best thing that happens in this field was the human genome project .it was an international research project with the goal of mapping and understanding the entire human genome .data science is the field in which we study data, understand the data to get valuable insight from that. Data science has already become an umbrella under which every industry and field comes. We can work in medical, marketing, Information technology, and every other field, even far before data science comes into the real world, we were using statistical and computational knowledge to get an outcome from our data. But today with the grace of the internet and social media our ability to decipher the information from that data is out of our range, where data science has come as a saviour. Because of the amount of genomic data being generated it become essential that the field of genomics or biology must be combined with modern technology and tools so that we can properly analyze such big data for precise and accurate prediction of disease and prevention mechanisms for that, which ultimately will result in improved human health. The data collected from a single week-long sequence today can create more data than whole genome research done a few years ago. "Bioinformatics", "computational genomics" and "genomic data science" are all very similar fields. To provide biological insights in these disciplines, we must be able to process and analyse huge genomics datasets, as well as validate the processed data's quality and transform it. Afterwards, depending on the nature of our issue, we must apply statistical or machine-learning models. The most likely scenario is to first perform some dimension reduction and clustering, then visualisation. In this paper, I will use python to pass my accountancies over genomic data science and genomic data analysis. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

Blood Transcriptomes of Covid-19 Infected Kidney Recipients Demonstrate Frequent and Persistent SARS-CoV-2 Virome Gene Expression

Purpose: Kidney transplant recipients (KTRs) have poor outcomes vs non-KTRs with acute COVID-19. To provide insight into management of immunosuppression during acute COVID-19, we studied peripheral blood transcriptomes during and after COVID-19 from a multicenter KTR cohort. Method(s): Clinical data were collected by chart review. Paxgene blood RNA was polyA-selected and sequenced at enrollment. Result(s): A total of 64 KTRs with COVID-19 were enrolled (31 Early cases (<4weeks from a positive SARS-CoV-2 PCR test) and 33 late cases). Out of the 64 patients, eight died and three encountered graft losses during follow-up. Due to presence of mRNA reads in the blood transcriptome unmapped to the human genome, we aligned the mRNA short reads to the SARS-CoV-2 genome. Surprisingly, our strategy detected the SARS-Cov2 mRNA, especially Spike mRNA in 27 (87%) early cases, and 18 (54%) of late cases (Fig 1A and B). We then analyzed the raw reads from a public dataset of non-KTRs with Paxgene RNA (GSE172114). The SARS-CoV-2 Spike mRNA was detected in 2/47 (4.2%) critically ill COVID-19 cases and 0/25 noncritically ill cases in this non-KTR dataset (compared to KTRs, Chi-square P<0.001;Fig 1B). Among our KTRs, the amount of Spike mRNA was associated positively with the COVID-19 severity score (scale of 1 to 7 of increasing severity;Fig 1C) and inversely with time from initial positive PCR (Fig 1D). More interestingly, 7/64 patients had detectable Spike RNA-emia beyond 60 days after COVID-19 diagnosis. Of the 3 graft losses in our cohort, 2 occurred among these 7 patients. Conclusion(s): Blood transcriptome of KTRs with COVID-19 demonstrated a risk for persistent viremia with implications for pathogenesis of COVID-19 disease. This finding also supports using passive immune strategies in COVID-KTRs. (Figure Presented).

Microrna Profiles in Saliva of Children with and Without Severe Disease Due to Severe Acute Respiratory Syndrome Corona Virus 2 Infection

Background: The majority of children with exposure to SARSCoV-2 virus have mild disease. However severe diseases such as Multisystem inflammatory syndrome (MISC) and pneumonia do occur in children. Currently, there are no established biomarkers that can predict progression to severe disease in children exposed to the virus. MicroRNAs (miRNAs) are non-coding RNAs that can be found in saliva and are thought to play a role in the regulation of inflammation following an infection. Our objective was to compare the miRNA profile in saliva of children with or without severe disease due to SARS-CoV-2 infection. Methods: This prospective observational study was supported by the National Institutes of Health (NIH) RADx Program. Children ≤ 18 years of age presenting to two tertiary care children's hospitals with symptoms of SARS-CoV-2 infection (confirmed by PCR test, serology or epidemiological link) were enrolled between 03/29/2021 and 04/30/2021. Severe infection was defined as any of the following within 30 days of testing: MISC or Kawasaki disease diagnosis, requirement for oxygen > 2L, inotropes, mechanical ventilation or ECMO, or the occurrence of death. Informed consent and a saliva swab were obtained at the time of SARS-CoV-2 diagnosis (DNA Genotek, Ottowa Canada), and RNA was extracted (Qiagen, Germantown, MD). Small RNA species (<50 base pairs) were interrogated via shotgun sequencing (HiSeq 2500, Illumina, San Diego, CA) and miRNAs were quantified through alignment to the human genome (GRCh38). RNA features with sparse counts (<10 in 90% of samples) were filtered, and the data was quantile normalized and mean-center scaled. Salivary miRNA levels were compared between those with severe and non-severe SARS-CoV-2 infection using Wilcoxon tests with Benjamini Hochberg multiple testing corrections. In addition, a logistic regression analysis was used to identify miRNA pairs that could best discriminate severe cases based on a Monte Carlo 100-fold cross-validated area under receiver operating characteristic curve (AUROC). Results: Samples from 33 children were analyzed. Median age was 3 (3, 10) years and 54.5% were males. Of the total, 29 were RT PCR positive, 4 had a positive serology and 6 children had severe infection. Seven miRNAs displayed significant differences (Fold change >2, FDR adjusted p < 0.1) among children with severe SARS-CoV-2 infection (Table). All seven miRNAs were up-regulated in severe SARS-CoV-2 cases. A logistic regression using a single ratio of miR-296-5p/miR-378j yielded 1.0 AUROC for differentiating children with severe infection (Figure). Conclusion: In this interim analysis of salivary miRNA in childhood SARS-CoV-2 infection, we found a differential expression of 7 salivary miRNAs in children with severe infection. Ongoing work will seek to validate these findings and explore the role of miRNA in predicting severe SARS-CoV-2 infection in children. Receiver operating characteristic curve and box plot displaying the complete differentiation of severe and non- severe SARSCoV-2 cases using a ratio of miR-296-5p and miR-378j levels in saliva.

Abstracts from the 54th European Society of Human Genetics (ESHG) Conference

The proceedings contain 1623 papers. The topics discussed include: the COVID-19 host genetics initiative - an international, open science effort to identify genetic risk factors for COVID19 severity and susceptibility;clinical implementation of RNA sequencing for Mendelian disease diagnostics;local gene co-expression measurements in single-cells highlight inter-individual specificity;a cross-disorder dosage sensitivity map of the human genome;biallelic ATG7 variants impair autophagy leading to neurological disease;epilepsy polygenic risk scores in >269k individuals with and without epilepsy;machine learning methods for prioritizing genetic variants;Mendel Lecture - Cell-free DNA in plasma: coming in different sizes and shapes;imaging the accessible genome at nanometer scale;retrotransposition in brain: does LINE activity in the central nervous system matter?;activation of transposons in neurological disorders;how to transfer genomic data internationally in compliance with the GDPR;mutational signatures of environmental agents and chemotherapeutics in human cellular models;and the art, science and practice of implementing genomics in clinical care.

Bundling of cross-sectoral data flows in cancer care

Transparency in informational flows plays an essential role in cross-sectoral patient care, especially in the field of oncology, marked by data-rich interdisciplinary collaborations. The SARS-Cov-2-pandemic has shown that an inability to exchange and evaluate health data, and to understand the patient's illness holistically, continues to cost human lives. The introduction of electronic patient records that cover all areas of healthcare could be a decisive step to enable the bundling of data flows across healthcare sectors. From a patient perspective, intersectoral borders are artificial barriers originally created to make healthcare feasible and administrate its accounting. In fact, neither patients nor physicians have introduced non-interchangeable data formats, which are, at best, legacy issues from early generations of data management systems, or worse, purposely maintained to tie down software customers and/or patients inside of paywalls. Intersectoral barriers are a product of a misunderstood and fragmented data protection. Data protection means protecting patients, primarily, ensuring that patients have the right to receive the best possible analysis and use of their data across all sectors. The solution can be found in interoperable data formats that bundle interrelated data streams. High-resolution data is a key element in cancer care. For example, genome sequencing has become an important element of personalized oncology. 20 years after the first drafts of the human genome, the storage and transmission of molecular and genomics data is still not resolved. There is no coherently accessible system that allows patients to receive and retrieve their data, or physicians to use it for best possible results. The National Network of Genomic Medicine (nNGM) is one of several pilot projects that aims to to pool quality controlled molecular diagnostics data in cancer care. Through the formation of such nationwide networks, molecular diagnostics for cancer patients should be available throughout Germany in the future, thus enabling patient-oriented optimization of therapy. Only through exchange of data across sites without administrative boundaries, individual genetic and molecular characteristics of rare cancers could be adequately researched, and the treatment options consequently improved. Collection of real world and patient reported outcomes will furthermore help to understand the results of individualized and off label approaches to cancer treatment.

SARS-CoV-2 competes with host mRNAs for efficient translation by maintaining the mutations favorable for translation initiation.

During SARS-CoV-2 proliferation, the translation of viral RNAs is usually the rate-limiting step. Understanding the molecular details of this step is beneficial for uncovering the origin and evolution of SARS-CoV-2 and even for controlling the pandemic. To date, it is unclear how SARS-CoV-2 competes with host mRNAs for ribosome binding and efficient translation. We retrieved the coding sequences of all human genes and SARS-CoV-2 genes. We systematically profiled the GC content and folding energy of each CDS. Considering that some fixed or polymorphic mutations exist in SARS-CoV-2 and human genomes, all algorithms and analyses were applied to both pre-mutate and post-mutate versions. In SARS-CoV-2 but not human, the 5-prime end of CDS had lower GC content and less RNA structure than the 3-prime part, which was favorable for ribosome binding and efficient translation initiation. Globally, the fixed and polymorphic mutations in SARS-CoV-2 had created an even lower GC content at the 5-prime end of CDS. In contrast, no similar patterns were observed for the fixed and polymorphic mutations in human genome. Compared with human RNAs, the SARS-CoV-2 RNAs have less RNA structure in the 5-prime end and thus are more favorable of fast translation initiation. The fixed and polymorphic mutations in SARS-CoV-2 are further amplifying this advantage. This might serve as a strategy for SARS-CoV-2 to adapt to the human host.

Towards a Human Cell Atlas: Taking Notes from the Past.

Comprehensively characterizing the cellular composition and organization of tissues has been a long-term scientific challenge that has limited our ability to study fundamental and clinical aspects of human physiology. The Human Cell Atlas (HCA) is a global collaborative effort to create a reference map of all human cells as a basis for both understanding human health and diagnosing, monitoring, and treating disease. Many aspects of the HCA are analogous to the Human Genome Project (HGP), whose completion presents a major milestone in modern biology. To commemorate the HGP's 20-year anniversary of completion, we discuss the launch of the HCA in light of the HGP, and highlight recent progress by the HCA consortium.

Adenoviral Vector DNA- and SARS-CoV-2 mRNA-Based Covid-19 Vaccines: Possible Integration into the Human Genome - Are Adenoviral Genes Expressed in Vector-based Vaccines?

Vigorous vaccination programs against SARS-CoV-2-causing Covid-19 are the major chance to fight this dreadful pandemic. The currently administered vaccines depend on adenovirus DNA vectors or on SARS-CoV-2 mRNA that might become reverse transcribed into DNA, however infrequently. In some societies, people have become sensitized against the potential short- or long-term side effects of foreign DNA being injected into humans. In my laboratory, the fate of foreign DNA in mammalian (human) cells and organisms has been investigated for many years. In this review, a summary of the results obtained will be presented. This synopsis has been put in the evolutionary context of retrotransposon insertions into pre-human genomes millions of years ago. In addition, studies on adenovirus vector-based DNA, on the fate of food-ingested DNA as well as the long-term persistence of SARS-CoV-2 RNA/DNA will be described. Actual integration of viral DNA molecules and of adenovirus vector DNA will likely be chance events whose frequency and epigenetic consequences cannot with certainty be assessed. The review also addresses problems of remaining adenoviral gene expression in adenoviral-based vectors and their role in side effects of vaccines. Eventually, it will come down to weighing the possible risks of genomic insertions of vaccine-associated foreign DNA and unknown levels of vector-carried adenoviral gene expression versus protection against the dangers of Covid-19. A decision in favor of vaccination against life-threatening disease appears prudent. Informing the public about the complexities of biology will be a reliable guide when having to reach personal decisions about vaccinations.

The Human Genome Organisation (HUGO) and the 2020 COVID-19 pandemic.

This letter is the Human Genome Organisation's summary reaction to the 2020 COVID-19 pandemic. It identifies key areas for genomics research, and areas in which genomic scientists can contribute to a global response to the pandemic. The letter has been reviewed and endorsed by the HUGO Committee on Ethics, Law and Society (CELS) and the HUGO Council.