Genetic factors involved in the co‑occurrence of endometriosis with ankylosing spondylitis (Review)

Previous research has revealed an association between endometriosis and various autoimmune diseases, while recent data suggest, for the first time, an association between endometriosis and the risk of developing ankylosing spondylitis (AS). AS, the prototype of spondyloarthritides diseases, is a systemic, chronic, immune‑mediated inflammatory arthritis, which primarily affects the spine and sacroiliac joints, as well as the axial skeleton with or without extraspinal manifestations. AS is of polygenic inheritance and numerous immunologically relevant genes contribute to its development. Endometriosis is an enigmatic, relatively common, benign, estrogen‑dependent, heterogeneous gynecological disease, influenced by multiple genetic, epigenetic and environmental factors. It is characterized by the growth of endometrial tissue occurring in sites other than the uterine cavity, most commonly in the pelvic cavity, including the ovaries and the uterosacral ligaments, affecting up to 10% of the female population of childbearing age, causing pain and infertility. The present review discusses whether a partially shared genetic background may explain the co‑occurrence of these disorders, as well as potential similarities regarding the underlying pathogenetic mechanisms and specific molecular and cellular pathways.

Association of endometriosis with cardiovascular disease: Genetic aspects (Review)

Cardiovascular disease (CVD) comprises a broad spectrum of pathological conditions that affect the heart or blood vessels, including sequelae that arise from damaged vasculature in other organs of the body, such as the brain, kidneys or eyes. Atherosclerosis is a chronic inflammatory disease of the arterial intima and is the primary cause of coronary artery disease, peripheral vascular disease, heart attack, stroke and renal pathology. It represents a leading cause of mortality worldwide and the loss of human productivity that is marked by an altered immune response. Endometriosis is a heritable, heterogeneous, common gynecological condition influenced by multiple genetic, epigenetic and environmental factors, affecting up to 10% of the female population of childbearing age, causing pain and infertility; it is characterized by the ectopic growth of endometrial tissue outside the uterine cavity. Of note, epidemiological data obtained thus far have suggested a link between endometriosis and the risk of developing CVD. The similarities observed in specific molecular and cellular pathways of endometriosis and CVD may be partially explained by a shared genetic background. The present review presents and discusses the shared genetic factors which have been reported to be associated with the development of both disorders.

DRDs and Brain-Derived Neurotrophic Factor Share a Common Therapeutic Ground: A Novel Bioinformatic Approach Sheds New Light Toward Pharmacological Treatment of Cognitive and Behavioral Disorders

Cognitive and behavioral disorders are subgroups of mental health disorders. Both cognitive and behavioral disorders can occur in people of different ages, genders, and social backgrounds, and they can cause serious physical, mental, or social problems. The risk factors for these diseases are numerous, with a range from genetic and epigenetic factors to physical factors. In most cases, the appearance of such a disorder in an individual is a combination of his genetic profile and environmental stimuli. To date, researchers have not been able to identify the specific causes of these disorders, and as such, there is urgent need for innovative study approaches. The aim of the present study was to identify the genetic factors which seem to be more directly responsible for the occurrence of a cognitive and/or behavioral disorder. More specifically, through bioinformatics tools and software as well as analytical methods such as systemic data and text mining, semantic analysis, and scoring functions, we extracted the most relevant single nucleotide polymorphisms (SNPs) and genes connected to these disorders. All the extracted SNPs were filtered, annotated, classified, and evaluated in order to create the "genomic grammar" of these diseases. The identified SNPs guided the search for top suspected genetic factors, dopamine receptors D and neurotrophic factor BDNF, for which regulatory networks were built. The identification of the "genomic grammar" and underlying factors connected to cognitive and behavioral disorders can aid in the successful disease profiling and the establishment of novel pharmacological targets and provide the basis for personalized medicine, which takes into account the patient's genetic background as well as epigenetic factors.

An Updated Evolutionary and Structural Study of TBK1 Reveals Highly Conserved Motifs as Potential Pharmacological Targets in Neurodegenerative Diseases

TANK-binding kinase 1 protein (TBK1) is a kinase that belongs to the IκB (IKK) family. TBK1, also known as T2K, FTDALS4, NAK, IIAE8, and NF-κB, is responsible for the phosphorylation of the amino acid residues, serine and threonine. This enzyme is involved in various key biological processes, including interferon activation and production, homeostasis, cell growth, autophagy, insulin production, and the regulation of TNF-α, IFN-β, and IL-6. Mutations in the TBK1 gene alter the protein's normal function and may lead to an array of pathological conditions, including disorders of the central nervous system. The present study sought to elucidate the role of the TBK1 protein in amyotrophic lateral sclerosis (ALS), a human neurodegenerative disorder. A broad evolutionary and phylogenetic analysis of TBK1 was performed across numerous organisms to distinguish conserved regions important for the protein's function. Subsequently, mutations and SNPs were explored, and their potential effect on the enzyme's function was investigated. These analytical steps, in combination with the study of the secondary, tertiary, and quaternary structure of TBK1, enabled the identification of conserved motifs, which can function as novel pharmacological targets and inform therapeutic strategies for amyotrophic lateral sclerosis.

A Genomic Study of the Japanese Population Focusing on the Glucocorticoid Receptor Interactome Highlights Distinct Genetic Characteristics Associated with Stress Response

All living organisms have been programmed to maintain a complex inner equilibrium called homeostasis, despite numerous adversities during their lifespan. Any threatening or perceived as such stimuli for homeostasis is termed a stressor, and a highly conserved response system called the stress response system has been developed to cope with these stimuli and maintain or reinstate homeostasis. The glucocorticoid receptor, a transcription factor belonging to the nuclear receptors protein superfamily, has a major role in the stress response system, and research on its interactome may provide novel information regarding the mechanisms underlying homeostasis maintenance. A list of 149 autosomal genes that have an essential role in GR function or are prime examples of GRE-containing genes was composed in order to gain a comprehensive view of the GR interactome. A search for SNPs on those particular genes was conducted on a dataset of 3554 Japanese individuals, with mentioned polymorphisms being annotated with relevant information from the ClinVar, LitVar, and dbSNP databases. Forty-two SNPs of interest and their genomic locations were identified. These SNPs have been associated with drug metabolism and neuropsychiatric, metabolic, and immune system disorders, while most of them were located in intronic regions. The frequencies of those SNPs were later compared with a dataset consisting of 1465 Korean individuals in order to find population-specific characteristics based on some of the identified SNPs of interest. The results highlighted.that rs1043618 frequencies were different in the two populations, with mentioned polymorphism having a potential role in chronic obstructive pulmonary disease in response to environmental stressors. This SNP is located in the HSPA1A gene, which codes for an essential GR co-chaperone, and such information showcases that similar gene may be novel genomic targets for managing or combatting stress-related pathologies.

Semantic and Population Analysis of the Genetic Targets Related to COVID-19 and Its Association with Genes and Diseases

SARS-CoV-2 is a coronavirus responsible for one of the most serious, modern worldwide pandemics, with lasting and multifaceted effects. By late 2021, SARS-CoV-2 has infected more than 180 million people and has killed more than 3 million. The virus gains entrance to human cells through binding to ACE2 via its surface spike protein and causes a complex disease of the respiratory system, termed COVID-19. Vaccination efforts are being made to hinder the viral spread, and therapeutics are currently under development. Toward this goal, scientific attention is shifting toward variants and SNPs that affect factors of the disease such as susceptibility and severity. This genomic grammar, tightly related to the dark part of our genome, can be explored through the use of modern methods such as natural language processing. We present a semantic analysis of SARS-CoV-2-related publications, which yielded a repertoire of SNPs, genes, and disease ontologies. Population data from the 1000 Genomes Project were subsequently integrated into the pipeline. Data mining approaches of this scale have the potential to elucidate the complex interaction between COVID-19 pathogenesis and host genetic variation; the resulting knowledge can facilitate the management of high-risk groups and aid the efforts toward precision medicine.

ADRA2B and HTR1A: An Updated Study of the Biogenic Amine Receptors Reveals Novel Conserved Motifs Which Play Key Role in Mental Disorders

Mental disorders are strongly connected with several psychiatric conditions including depression, bipolar disorder, schizophrenia, eating disorder, and suicides. There are many biological conditions and pathways that define these complicated illnesses. For example, eating disorders are complex mental health conditions that require the intervention of geneticists, psychiatrists, and medical experts in order to alleviate their symptoms. A patient with suicidal ideation should first be identified and consequently monitored by a similar team of specialists. Both genetics and epigenetics can shed light on eating disorders and suicides as they are found in the main core of such investigations. In the present study, an analysis has been performed on two specific members of the GPCR family toward drawing conclusions regarding their functionality and implementation in mental disorders. Specifically, evolutionary and structural studies on the adrenoceptor alpha 2b (ADRA2B) and the 5-hydroxytryptamine receptor 1A (HTR1A) have been carried out. Both receptors are classified in the biogenic amine receptors sub-cluster of the GPCRs and have been connected in many studies with mental diseases and malnutrition conditions. The major goal of this study is the investigation of conserved motifs among biogenic amine receptors that play an important role in this family signaling pathway, through an updated evolutionary analysis and the correlation of this information with the structural features of the HTR1A and ADRA2B. Furthermore, the structural comparison of ADRA2B, HTR1A, and other members of GPCRs related to mental disorders is performed.

Dark DNA and stress (Review)

Over the past few decades, research at the molecular level has focused on the part of the genome that does not encode protein sequences. Since the discovery of transcriptional evidence from the hitherto considered 'junk' DNA, this region of the genome, which is currently termed dark DNA, is constantly gaining interest. The term borrows an analogy from the corresponding eminent fields of dark matter and dark energy in physics and cosmology. In fact, an increasing number of attempts are being made to enhance the current understanding of the non‑coding RNA (ncRNA) transcripts produced by such regions. Although the base‑pair length and gene number appear to be very diverse between species, it appears that the amount of the non‑coding regions of the genome of an organism is a sign of evolutional superiority. ncRNA molecules are able to orchestrate the expression of genetic information in the most complex, rapid and reversible manner, participating in almost every major biological process. A prime example of such a process is the maintenance of homeostasis, the internal physiological balance, despite internal and external stressful stimuli. These molecules have been shown to be excellent regulators of gene expression, with marked spatiotemporal specificity, rendering them ideal tools for regulating stress responses. Herein, an attempt is made to extract and fuse information from a repertoire of studies, which have demonstrated that the expression of a number of these molecules was modified following exposure to acute and chronic stress, as well as in patients with anxiety disorders and their respective animal models. All in all, ncRNAs have the potential to be used either as biomarkers or as therapeutic targets for disorders resulting from the loss of equilibrium, the disruption of homeostasis and the destabilization of the hypothalamic‑pituitary‑adrenal axis.

Novel computational pipelines in antiviral structure‑based drug design (Review)

Viral infections constitute a fundamental and continuous challenge for the global scientific and medical community, as highlighted by the ongoing COVID-19 pandemic. In combination with prophylactic vaccines, the development of safe and effective antiviral drugs remains a pressing need for the effective management of rare and common pathogenic viruses. The design of potent antivirals can be informed by the study of the three-dimensional structure of viral protein targets. Structure-based design of antivirals in silico provides a solution to the arduous and costly process of conventional drug development pipelines. Furthermore, rapid advances in high-throughput computing, along with the growth of available biomolecular and biochemical data, enable the development of novel computational pipelines in the hunt of antivirals. The incorporation of modern methods, such as deep-learning and artificial intelligence, has the potential to revolutionize the structure-based design and repurposing of antiviral compounds, with minimal side effects and high efficacy. The present review aims to provide an outline of both traditional computational drug design and emerging, high-level computing strategies.

Multiple sclerosis and computational biology (Review)

Multiple sclerosis (MS) is an autoimmune neurodegenerative disease whose prevalence has increased worldwide. The resultant symptoms may be debilitating and can substantially reduce the of patients. Computational biology, which involves the use of computational tools to answer biomedical questions, may provide the basis for novel healthcare approaches in the context of MS. The rapid accumulation of health data, and the ever-increasing computational power and evolving technology have helped to modernize and refine MS research. From the discovery of novel biomarkers to the optimization of treatment and a number of quality-of-life enhancements for patients, computational biology methods and tools are shaping the field of MS diagnosis, management and treatment. The final goal in such a complex disease would be personalized medicine, i.e., providing healthcare services that are tailored to the individual patient, in accordance to the particular biology of their disease and the environmental factors to which they are subjected. The present review article summarizes the current knowledge on MS, modern computational biology and the impact of modern computational approaches of MS.

Recent approaches on Huntington's disease (Review)

Huntington's disease (HD) is a neurodegenerative disorder characterized by severe motor, cognitive and psychiatric symptoms. Patients of all ages can present with a dysfunction of the nervous system, which leads to the progressive loss of movement control and disabilities in speech, swallowing, communications, etc. The molecular basis of the disease is well-known, as HD is related to a mutated gene, a trinucleotide expansion, which encodes to the huntingtin protein. This protein is linked to neurogenesis and the loss of its function leads to neurodegenerative disorders. Although the genetic cause of the disorder has been known for decades, no effective treatment is yet available to prevent onset or to eliminate the progression of symptoms. Thus, the present review focused on the development of novel methods for the timely and accurate diagnosis of HD in an aim to aid the development of therapies which may reduce the severity of the symptoms and control their progression. The majority of the therapies include gene-silencing mechanisms of the mutated huntingtin gene aiming to suppress its expression, and the use of various substances as drugs with highly promising results. In the present review, the latest approaches on the diagnosis of HD are discussed along with the need for genetic counseling and an up-to-date presentation of the applied treatments.

AB0008 ACESO APPLICATION: AN INTEGRATED GENOTYPE ANALYSIS WEB SERVER FOR CLINICAL GENOMICS IN CROHN’S DISEASE AND IBD-RELATED ARTHRITIS

Background

Genome Wide Association Studies (GWAS) observe the set of different variants throughout the genome of different individuals and study whether a particular trait is due to one variant. Many autoimmune diseases have been identified to have a linkage with specific loci and metabolic pathways, but the exact cause of disorders is still remaining unknown [1]. Aceso Application is an integrated bioinformatics web-tool designed for researchers and medical experts towards to estimating the clinical genomic profile of a candidate patient with Crohn’s Disease (CD)[2-4].

Objectives

To identify the most reliable gene variants, single nucleotide polymorphisms (SNPs) and epigenetic related SNPs that causing CD using the genomic data provided for the patient and aid the medical expert in CD diagnosis.

Methods

In the present study, we have analyzed more than 149.000 CD related publications using data mining and semantic techniques towards extracting the Crohn’s Disease-related genes, non-coding regions and generally candidate SNPs. The extracted knowledge has been filtered, evaluated, annotated, classified, and stored in the Aceso Application Database (AAD). This was followed by the design and development of the Aceso application, in which the generated datasets and results were included. The application has been tested and presented here with whole-exome sequencing data from several related patients with CD.

Results

CD-related SNPs and variants identified in genome-wide association studies (GWAS), whole-genome (WGS), whole-exome (WES), or targeted sequencing information are classified, annotated, and analyzed in an integrated patient profile with clinical significance information. Probable genes associated with the patient’s genomic profile are visualized with chromosome ideograms, statistic bars, and regulatory networks through data mining studies with relative publications. An evaluation study was performed on 2 patients from a three-generation family with CD [5].

Conclusion

The Aceso application was designed to assist early stage diagnosis by using the patients’s genomic data. It provides the patient’s genomic profile which is generated based on the list of the most predictable candidate gene variants related to CD and has implications also for IBD-related arthritis. This novel and accessible webserver tool of CD to assist medical experts in the clinical genomics and precision medicine procedure is available at http://geneticslab.aua.gr/aceso.

References

[1]Ramos et al, J Hum Genet 2015;60:657

[2]Papageorgiou et al, Int J Mol Med 2022;49:8

[3]Papageorgiou et al, Int J Mol Med 2021;47:115

[4]Van Limbergen and Satsangi, Annu Rev Genomics Hum Genet 2009;10:89

[5]Albertsen et al, Mol Med Rep 2019;19:1716

Figure 1.

The Aceso app web-server Database. Left are shown the three identified SNPs classes of the genomic “grammar“ of CD.

Disclosure of Interests

None declared

OP0108 NEW INSIGHTS IN THE GENOMIC “GRAMMAR” OF RHEUMATOID ARTHRITIS

Background

Rheumatoid arthritis (RA) is a complex disease, caused by a combination of genetic, epigenetic and environmental factors common to other related autoimmune diseases including Multiple Sclerosis (MS) and Systemic Lupus Erythematosus (SLE) [1]. Using state of the art Bioinformatics tools we are able to formulate an ensemble of associated components (genomic grammar) for each disease and distinguish important differences and common aspects in a specific group of disease such as ensembles of autoimmune diseases [2].

Objectives

To create, collect and evaluate the most credible and unique gene variants, epigenetic variants and single nucleotide polymorphisms (SNPs) causing the basis of an immune disease (the genomic grammar of the disease), which could potentially assist in the process of the RA disease prevention, diagnosis and treatment [3].

Methods

RA related publications from the PubMed have been analyzed using data mining and semantic techniques towards extracting the candidate causative SNPs. The extracted knowledge has been filtered, evaluated, annotated, and classified in a structured database which also includes GWAS information regarding SNPs. Additional clinical, genomic, structural, functional and biological information was also extracted from biological databases including dbSNP, LitVar, ClinVar and OMIM and cross-correlated with other available autoimmune disease related SNP databases, including the Demetra application, Epione application and Panacea application databases [3, 4].

Results

A holistic genetic map of the studied autoimmune diseases with more than 2000 related SNPs has been estimated and specific sub-clusters with crucial nodes have been identified across the RA, SLE and MS diseases. Based on these results, the three studied autoimmune diseases share a 10% common SNPs genetic background (Figure 1 and Table 1) [5]. The optimal genomic grammar of the RA contains 1682 SNPs, with 73% responding to non-coding regions and 27% responding to coding regions of more than 1.300 genes, pseudogenes, primers and promoters. RA also shares 464 common SNPs with SLE and 113 with MS.

Table 1.

Common Related Genes based on the analyzed SNP targets in the studied disease.

A/AGene / RegionA/AGene / Region1.ADAM332.LOC2856263.ADIPOQ4.MIR3142HG5.CD406.MIR499A7.CIITA8.MTHFR9.CTLA410.MT-ND511.FCRL312.NCF113.HLA-DPB114.NLRP115.HLA-DRA16.NOS317.HLA-G18.NR3C119.IL17A20.PADI421.IL1RN22.PDCD123.IL224.PON125.IL23R26.STAT427.IL628.TGFB129.IL7R30.TLR931.IRAK132.TNF33.VDR34.TNFRSF1A35.IRF536.TYK237.KIF5A38.UCP239.LEPFigure 1.

Three class Venn diagram of the genomic grammar between RA, MS and SLE.

Conclusion

The identification of the optimal genomic grammar in RA will help towards understanding the nature of the disease. Specific genetic targets via determined SNPs could act as biomarkers that aid in forming the right diagnosis [6].

References

[1]Acosta-Herrera et al, J Clin Med 2019;8:826

[2]Chatzikyriakidou et al, Semin Arthritis Rheum 2013;43:29

[3]Papageorgiou et al, Int J Mol Med 2021;47:115

[4]Papageorgiou et al, Int J Mol Med 2022;49:8

[5]Wang, Y et al, Ann Rheum Dis 2021Epub ahead of print:doi:10.1136/annrheumdis-2021-220066

[6]Kurko et al, Clin Rev Allergy Immunol 2013;45:170

Disclosure of Interests

None declared

Epione application: An integrated web‑toolkit of clinical genomics and personalized medicine in systemic lupus erythematosus

Genome wide association studies (GWAS) have identified autoimmune disease-associated loci, a number of which are involved in numerous disease-associated pathways. However, much of the underlying genetic and pathophysiological mechanisms remain to be elucidated. Systemic lupus erythematosus (SLE) is a chronic, highly heterogeneous auto-immune disease, characterized by differences in autoantibody profile, serum cytokines and a multi-system involvement. This study presents the Epione application, an integrated bioinformatics web-toolkit, designed to assist medical experts and researchers in more accurately diagnosing SLE. The application aims to identify the most credible gene variants and single nucleotide polymorphisms (SNPs) associated with SLE susceptibility, by using patient's genomic data to aid the medical expert in SLE diagnosis. The application contains useful knowledge of >70,000 SLE-related publications that have been analyzed, using data mining and semantic techniques, towards extracting the SLE-related genes and the corresponding SNPs. Probable genes associated with the patient's genomic profile are visualized with several graphs, including chromosome ideograms, statistic bars and regulatory networks through data mining studies with relative publications, to obtain a representative number of the most credible candidate genes and biological pathways associated with the SLE. Furthermore, an evaluation study was performed on a patient diagnosed with SLE and is presented herein. Epione has also been expanded in family-related candidate patients to evaluate its predictive power. All the recognized gene variants that were previously considered to be associated with SLE were accurately identified in the output profile of the patient, and by comparing the results, novel findings have emerged. The Epione application may assist and facilitate in early stage diagnosis by using the patients' genomic profile to compare against the list of the most predictable candidate gene variants related to SLE. Its diagnosis-oriented output presents the user with a structured set of results on variant association, position in genome and links to specific bibliography and gene network associations. The overall aim of the present study was to provide a reliable tool for the most effective study of SLE. This novel and accessible webserver tool of SLE is available at http://geneticslab.aua.gr/epione/.

Clinical Genomic, phenotype and epigenetic insights into the pathology, autoimmunity and weight management of patients with Myasthenia Gravis (Review)

Myasthenia Gravis (MG) is an autoimmune disease that affects neuromuscular junctions and is characterized by muscle weakness as a result of autoantibodies against certain proteins. As a heterogeneous disorder, MG presents with different types, including neonatal, ocular and generalized in both juveniles and adults. Different types of antibodies serve a role in how MG presents. The main biological characteristic of MG is the production of antibodies against the muscular acetylcholine receptor; however, other types of antibody have been associated with the disorder. The role of the thymus gland has been established and thymectomy is a possible treatment of the disease, along with traditional medication such as pyridostigmine bromide (Mestinon) and immunosuppresants. In recent years, steps have been made towards developing more sensitive diagnostic methods. Additionally, novel treatments have demonstrated promising results. Developing new assays may lead to an increased understanding of the disease and to unravelling the genetic pathway that leads to the development of neuromuscular diseases.

POS0350 EPIONE APPLICATION: AN INTEGRATED GENOTYPE ANALYSIS WEB SERVER FOR CLINICAL GENOMICS IN SYSTEMIC LUPUS ERYTHEMATOSUS (SLE)

Background:

Genome wide association studies (GWAS) have successfully identified novel autoimmune disease-associated loci, with many of them shared by multiple disease-associated pathways but much of the genetics and pathophysiological mechanisms remain still obscure [1-3]. SLE is a chronic, highly heterogeneous autoimmune disease, characterized by differences in autoantibody profile, serum cytokines, and a multi-system involvement [4]. Epione Application is an integrated bioinformatics web-tool designed to assist medical experts and researchers in the process of diagnosing SLE [5].

Objectives:

To identify the most credible gene variants and single nucleotide polymorphisms (SNPs), causing SLE using the genomic data provided for the patient and aid the medical expert in SLE diagnosis [5].

Methods:

In the present study, we have analyzed more than 70.000 SLE-related publications using data mining and semantic techniques towards extracting the SLE -related genes and SNPs [6]. The extracted knowledge has been filtered, evaluated, annotated, classified, and stored in the Epione Application Database (EAD) (Figure 1). Moreover, an updated gene regulatory network with the genes implements in SLE has been estimated [7]. This was followed by the design and development of the Epione application, in which the generated datasets and results were included. The application has been tested and presented here with WES data from several related patients with SLE [8].

Results:

SLE-related SNPs and variants identified in genome-wide association studies (GWAS), whole-genome (WGS), whole-exome (WES), or targeted sequencing information are classified, annotated, and analyzed in an integrated patient profile with clinical significance information. Probable genes associated with the patient’s genomic profile are visualized with several graphs, including chromosome ideograms, statistic bars, and regulatory networks through data mining studies with relative publications, to obtain a representative number of the most credible candidate genes and biological pathways associated with the SLE. An evaluation study was performed on 7 patients from a three-generation family with SLE [9]. All the recognized gene variants that were previously considered SLE-associated were properly identified in the output profile per patient, and by comparing the results, new findings have emerged.

Conclusion:

The Epione application was designed to assist medical doctor diagnosis from the early stages by using the patients’ genomic data [5, 8, 10]. Its diagnosis-oriented output presents the patient profile through which the user is provided with a structured set of results in various categories, which are generated based on the list of the most predictable candidate gene variants related to SLE. This novel and accessible webserver tool of SLE to assist medical experts in the clinical genomics and precision medicine procedure is available at http://143.233.188.162/epione/.

References:

[1]Molineros JE et al. (2017). Hum Mol Genet 26:1205-1216.

[2]Sciascia S et al. (2018). F1000 Res, 2018:1-17.

[3]Gonzalez-Serna D et al. (2020). Sci Rep 10:1862.

[4]Harley JB et al. (2006). Springer Semin Immun 28:119–130.

[5]Goulielmos GN et al. (2018). Gene 668:59-72.

[6]Zhao Y et al. (2020). Front Genet 11:400.

[7]Song YL and Chen S (2009). Interdiscip Sci 1:179-186.

[8]Koile D et al. (2018). BMC Bioinformatics 19:25.

[9]Albertsen HM et al. (2019). Mol Med Rep 19:1716-1720.

[10]Ebrahimiyan H et al. (2018). Meta Gene 16:241-247.

Figure 1.

The Epione application database (EAD) for SLE.

Disclosure of Interests:

None declared

Demetra Application: An integrated genotype analysis web server for clinical genomics in endometriosis

Demetra Application is a holistic integrated and scalable bioinformatics web-based tool designed to assist medical experts and researchers in the process of diagnosing endometriosis. The application identifies the most prominent gene variants and single nucleotide polymorphisms (SNPs) causing endometriosis using the genomic data provided for the patient by a medical expert. The present study analyzed >28.000 endometriosis-related publications using data mining and semantic techniques aimed towards extracting the endometriosis-related genes and SNPs. The extracted knowledge was filtered, evaluated, annotated, classified, and stored in the Demetra Application Database (DAD). Moreover, an updated gene regulatory network with the genes implements in endometriosis was established. This was followed by the design and development of the Demetra Application, in which the generated datasets and results were included. The application was tested and presented herein with whole-exome sequencing data from seven related patients with endometriosis. Endometriosis-related SNPs and variants identified in genome-wide association studies (GWAS), whole-genome (WGS), whole-exome (WES), or targeted sequencing information were classified, annotated and analyzed in a consolidated patient profile with clinical significance information. Probable genes associated with the patient's genomic profile were visualized using several graphs, including chromosome ideograms, statistic bars and regulatory networks through data mining studies with relative publications, in an effort to obtain a representative number of the most credible candidate genes and biological pathways associated with endometriosis. An evaluation analysis was performed on seven patients from a three-generation family with endometriosis. All the recognized gene variants that were previously considered to be associated with endometriosis were properly identified in the output profile per patient, and by comparing the results, novel findings emerged. This novel and accessible webserver tool of endometriosis to assist medical experts in the clinical genomics and precision medicine procedure is available at http://geneticslab.aua.gr/.

An updated evolutionary study of the Notch family reveals a new ancient origin and novel invariable motifs as potential pharmacological targets

Notch family proteins play a key role in a variety of developmental processes by controlling cell fate decisions and operating in a great number of biological processes in several organ systems, such as hematopoiesis, somatogenesis, vasculogenesis, neurogenesis and homeostasis. The Notch signaling pathway is crucial for the majority of developmental programs and regulates multiple pathogenic processes. Notch family receptors' activation has been largely related to its multiple effects in sustaining oncogenesis. The Notch signaling pathway constitutes an ancient and conserved mechanism for cell to cell communication. Much of what is known about Notch family proteins function comes from studies done in Caenorhabditis Elegans and Drosophila Melanogaster. Although, human Notch homologs had also been identified, the molecular mechanisms which modulate the Notch signaling pathway remained substantially unknown. In this study, an updated evolutionary analysis of the Notch family members among 603 different organisms of all kingdoms, from bacteria to humans, was performed in order to discover key regions that have been conserved throughout evolution and play a major role in the Notch signaling pathway. The major goal of this study is the presentation of a novel updated phylogenetic tree for the Notch family as a reliable phylogeny "map", in order to correlate information of the closely related members and identify new possible pharmacological targets that can be used in pathogenic cases, including cancer.

Drugena: A Fully Automated Immunoinformatics Platform for the Design of Antibody-Drug Conjugates Against Neurodegenerative Diseases

Antibodies are proteins that are the first line of defense in the adaptive immune response of vertebrates. Thereby, they are involved in a multitude of biochemical mechanisms and clinical manifestations with significant medical interest, such as autoimmunity, the regulation of infection, and cancer. An emerging field in antibody science that is of huge medicinal interest is the development of novel antibody-interacting drugs. Such entities are the antibody-drug conjugates (ADCs), which are a new type of targeted therapy, which consist of an antibody linked to a payload drug. Overall, the underlying principle of ADCs is the discerning delivery of a drug to a target, hoping to increase the potency of the original drug. Drugena suite is a pioneering platform that employs state-of-the-art computational biology methods in the fight against neurodegenerative diseases using ADCs. Drugena encompasses an up-to-date structural database of specialized antibodies for neurological disorders and the NCI database with over 96 million entities for the in silico development of ADCs. The pipeline of the Drugena suite has been divided into several steps and modules that are closely related with a synergistic fashion under a user-friendly graphical user interface.

Structural Study of the DNA: Clock/Bmal1 Complex Provides Insights for the Role of Cortisol, hGR, and HPA Axis in Stress Management and Sleep Disorders

Herein, we deploy an in silico pipeline of structural bioinformatics, thermodynamics, and molecular dynamics to investigate the role of cortisol in circadian rhythms, biorhythms, stress response, and even sleep disorders. Our study shows that high concentrations of cortisol intercalate in the minor groove of DNA. This phenomenon widens the adjacent major grooves and provides the Clock/Bmal1 complex with more space to dock and interact with DNA. Then, the strong charges of cortisol pull the alpha helices of the Clock/Bmal1 complex and bend it inward, thus establishing stronger interactions and prolonged signaling. Our results indicate that elevated cortisol levels play an important role in stress, inflammation, and sleep disorders as a result of prolonged and stronger dsDNA - Clock/Bmal1 interactions.

Antibody Clustering Using a Machine Learning Pipeline that Fuses Genetic, Structural, and Physicochemical Properties

Antibody V domain clustering is of paramount importance to a repertoire of immunology-related areas. Although several approaches have been proposed for antibody clustering, still no consensus has been reached. Numerous attempts use information from genes, protein sequences, 3D structures, and 3D surfaces in an effort to elucidate unknown action mechanisms directly related to their function and to either link them directly to diseases or drive the discovery of new medicines, such as antibody drug conjugates (ADC). Herein, we describe a new V domain antibody clustering method based on the comparison of the interaction sites between each antibody and its antigen. A more specific clustering analysis of the antibody's V domain was provided using deep learning and data mining techniques. The multidimensional information was extracted from the structural resolved antibodies when they were captured to interact with other proteins. The available 3D structures of protein antigen-antibody (Ag-Ab) interfaces contain information about how antibody V domains recognize antigens as well as about which amino acids are involved in the recognition. As such, the antibody surface holds information about antigens' folding that reside with the Ab-Ag interface residues and how they interact. In order to gain insight into the nature of such interactions, we propose a new simple philosophy to transform the conserved framework (fragment regions, complementarity-determining regions) of antibody V domain in a binary form using structural features of antibody-antigen interactions, toward identifying new antibody signatures in V domain binding activity. Finally, an advanced three-level hybrid classification scheme has been set for clustering antibodies in subgroups, which can combine the information from the protein sequences, the three-dimensional structures, and specific "key patterns" of recognized interactions. The clusters provide multilevel information about antibodies and antibody-antigen complexes.

Carcinogenic Pesticide Control via Hijacking Endosymbiosis; The Paradigm of DSB-A from Wolbachia pipientis for the Management of Otiorhynchus singularis

BACKGROUND/AIM

Pesticides have little, if any specificity, to the pathogen they target in most cases. Wide spectrum toxic chemicals are being used to remove pestcides and salvage crops and economies linked to agriculture. The burden on the environment, public health and economy is huge. Traditional pestcide control is based on administering heavy loads of highly toxic compounds and elements that essentially strip all life from the field. Those chemicals are a leading cause of increased cancer related deaths in countryside. Herein, the Trojan horse of endosymbiosis was used, in an effort to control pests using high specificity compounds in reduced quantities.

MATERIALS AND METHODS

Our pipeline has been applied on the case of Otiorhynchus singularis, which is a very widespread pest, whose impact is devastating on a repertoire of crops. To date, there is no specific pesticide nor agent to control it. The deployed strategy involves the inhibition of the key DSB-A enzyme of its endosymbiotic Wolbachia pipientis bacterial strain.

RESULTS

Our methodology, provides the means to design, test and identify highly specific pestcide control substances that minimize the impact of toxic chemicals on health, economy and the environment.

CONCLUSION

All in all, in this study a radical computer-based pipeline is proposed that could be adopted under many other similar scenarios and pave the way for precision agriculture via optimized pest control.

Human Emotions on the Onset of Cardiovascular and Small Vessel Related Diseases

BACKGROUND/AIM

The aim of the present study was to examine the relation between understanding of emotions and cardiovascular related diseases, namely coronary heart disease, diabetes mellitus and obesity. The uniqueness of this study lies in the fact that it examined the relationship between the cardiovascular related diseases named above and the understanding of emotions in the context of Emotional Intelligence (EI).

PATIENTS AND METHODS

The study was conducted in 300 participants during a 3 year period. All participants completed a self-report questionnaire, assessing various aspects of EI, such as self-emotion appraisal, other emotion appraisal, emotion regulation and use of emotions. As hypothesized, coronary heart disease is a prognostic factor of regulation of emotions.

RESULTS

The present study is an attempt to examine the relation between emotional understanding and cardiovascular related diseases, namely coronary heart disease, diabetes mellitus and obesity. Establishing which diseases are independent risk factors for the understanding of emotions, could have a significant impact on emotional health, through the treatment of these cardiovascular related diseases. Emotions were studied within the theoretical context of Emotional Intelligence (EI), which affects people's physical and mental health.

CONCLUSION

The results of this study emphasize on the relationship of cardiovascular related diseases and psychological characteristics, such as anxiety and anger, being aspects of EI. Additionally, this work fills a gap in the relevant Greek literature, as a first attempt to examine the correlation of EI with cardiovascular related diseases.

Genomic big data hitting the storage bottleneck

During the last decades, there is a vast data explosion in bioinformatics. Big data centres are trying to face this data crisis, reaching high storage capacity levels. Although several scientific giants examine how to handle the enormous pile of information in their cupboards, the problem remains unsolved. On a daily basis, there is a massive quantity of permanent loss of extensive information due to infrastructure and storage space problems.  The motivation for sequencing has fallen behind. Sometimes, the time that is spent to solve storage space problems is longer than the one dedicated to collect and analyse data. To bring sequencing to the foreground, scientists have to slide over such obstacles and find alternative ways to approach the issue of data volume. Scientific community experiences the data crisis era, where, out of the box solutions may ease the typical research workflow, until technological development meets the needs of Bioinformatics. 

Genomic big data hitting the storage bottleneck

During the last decades, there is a vast data explosion in bioinformatics. Big data centres are trying to face this data crisis, reaching high storage capacity levels. Although several scientific giants examine how to handle the enormous pile of information in their cupboards, the problem remains unsolved. On a daily basis, there is a massive quantity of permanent loss of extensive information due to infrastructure and storage space problems. The motivation for sequencing has fallen behind. Sometimes, the time that is spent to solve storage space problems is longer than the one dedicated to collect and analyse data. To bring sequencing to the foreground, scientists have to slide over such obstacles and find alternative ways to approach the issue of data volume. Scientific community experiences the data crisis era, where, out of the box solutions may ease the typical research workflow, until technological development meets the needs of Bioinformatics.

HCV genetics and genotypes dictate future antiviral strategies

At the end of the 1980s, the hepatitis C virus (HCV) was cloned and formally identified as the cause of the majority of non-A and non-B hepatitis cases. Today, around 170 million people worldwide are infected with HCV, making it five times more common than infection with the human immunodeficiency virus (HIV). Several methods exist which mediate the spread of infection. One of the most common and efficient is sharing or re-using injecting equipment; studies have indicated that 80-90% of individuals in some populations of intravenous drug users test positive in serum HCV assays. Contracting HCV from infected blood transfusions was also a major cause of infection before screening tests were introduced in the early 1990s. Other possible, but less common, methods of infection transmission include mother-to-child during pregnancy, sexual contact and nosocomial acquisition (for example between surgical or dialysis patients). It appears that concurrent HIV-1 infection increases the risk of HCV transmission via the mother-to-child or sexual routes.

Insights into the molecular mechanisms of stress and inflammation in ageing and frailty of the elderly

Frailty is a natural state of physical, cognitive and mental decline that is expected in the elderly. The role of inflammation in the pathogenesis of frailty has been hypothesized, and so far many studies have been performed in order to understand the mechanism of action underlying this association. Recent studies support this hypothesis and show a clear association between inflammation, frailty, and age-related disease. Chronic inflammation is key pathophysiologic process that contributes to the frailty directly and indirectly through other intermediate physiologic systems, such as the musculoskeletal, endocrine, and hematologic systems. The complex multifactorial etiologies of frailty also include obesity and other age-related specific diseases. Herein, we investigate the link between chronic inflammation and frailty of the older people. In particular, we present an up-to-date review of the role of cytokines, interleukins, cardiovascular abnormalities, chronic high blood pressure, hyperlipidemia and diabetes in relation to the severity of frailty in the elderly.

An updated evolutionary study of Flaviviridae NS3 helicase and NS5 RNA-dependent RNA polymerase reveals novel invariable motifs as potential pharmacological targets

The rate of Flaviviridae family virus infections worldwide has increased dramatically in the last few years. In addition, infections caused by arthropod vector viruses including Hepatitis C, West Nile, Dengue fever, Yellow fever and Japanese encephalitis are emerging throughout the world. Based on a recent taxon update, the Flaviviridae family comprises four main genera; Flavivirus, Hepacivirus, Pestivirus and a recent genus Pegivirus. Although the new scientific classification plays a key role in providing useful information about the relationships between viruses, many new documented viruses remain unclassified. Furthermore, based on the different results of several studies the classification is unclear. In an effort to provide more insights into the classification of viruses, a holistic evolutionary study of the two viral enzymes NS3 helicase and NS5 RNA-dependent RNA polymerase (RdRp) has been conducted in this study. These two viral enzymes are very crucial for the inhibition of viruses due to the fact that they are involved in the survival, proliferation and transmission of viruses. The main goal of this study is the presentation of two novel updated phylogenetic trees of the enzymes NS3 helicase and NS5 RdRp as a reliable phylogeny "map" to correlate the information of the closely related viruses and identify new possible targets for the Flaviviridae family virus inhibition. Despite the earliest trials for drugs against Flaviviridae related viruses, no antiviral drug vaccine has been available to date. Therefore there is an urgent need for research towards the development of efficient antiviral agents.

Antibodies as stratagems against cancer

Antibodies have been in the frontline of anticancer research during the last few decades, since a number of different ways have been discovered to utilize them as parts or main components of anticancer drugs. Antibodies are used as the only component of some anticancer drugs, but they can also be conjugated with a variety of substances. Antibody engineering methods such as humanization, chimerization and Fc engineering are applied in order to modify their properties according to the requirements of anticancer drug application. Given the continuous advances in biology and informatics, the role of antibodies in anticancer treatment is expected to be prominent.

Genetic and structural study of DNA-directed RNA polymerase II of Trypanosoma brucei, towards the designing of novel antiparasitic agents

Trypanosoma brucei brucei (TBB) belongs to the unicellular parasitic protozoa organisms, specifically to the Trypanosoma genus of the Trypanosomatidae class. A variety of different vertebrate species can be infected by TBB, including humans and animals. Under particular conditions, the TBB can be hosted by wild and domestic animals; therefore, an important reservoir of infection always remains available to transmit through tsetse flies. Although the TBB parasite is one of the leading causes of death in the most underdeveloped countries, to date there is neither vaccination available nor any drug against TBB infection. The subunit RPB1 of the TBB DNA-directed RNA polymerase II (DdRpII) constitutes an ideal target for the design of novel inhibitors, since it is instrumental role is vital for the parasite’s survival, proliferation, and transmission. A major goal of the described study is to provide insights for novel anti-TBB agents via a state-of-the-art drug discovery approach of the TBB DdRpII RPB1. In an attempt to understand the function and action mechanisms of this parasite enzyme related to its molecular structure, an in-depth evolutionary study has been conducted in parallel to the in silico molecular designing of the 3D enzyme model, based on state-of-the-art comparative modelling and molecular dynamics techniques. Based on the evolutionary studies results nine new invariant, first-time reported, highly conserved regions have been identified within the DdRpII family enzymes. Consequently, those patches have been examined both at the sequence and structural level and have been evaluated in regard to their pharmacological targeting appropriateness. Finally, the pharmacophore elucidation study enabled us to virtually in silico screen hundreds of compounds and evaluate their interaction capabilities with the enzyme. It was found that a series of chlorine-rich set of compounds were the optimal inhibitors for the TBB DdRpII RPB1 enzyme. All-in-all, herein we present a series of new sites on the TBB DdRpII RPB1 of high pharmacological interest, alongside the construction of the 3D model of the enzyme and the suggestion of a new in silico pharmacophore model for fast screening of potential inhibiting agents.

Genetic background modifies amyloidosis in a mouse model of ATTR neuropathy

Penetrance and age of onset of ATTRV30M amyloidotic neuropathy varies significantly among different populations. This variability has been attributed to both genetic and environmental modifiers. We studied the effect of genetic background on phenotype in two lines of transgenic mice bearing the same ATTRV30M transgene. Amyloid deposition, transthyretin (TTR), megalin, clusterin and disease markers of endoplasmic reticulum stress, the ubiquitin-proteasome system, apoptosis, and complement activation were assessed with WB and immunohistochemistry in donor and recipient tissue. Our results indicate that genetic background modulates amyloid deposition by influencing TTR handling in recipient tissue and may partly account for the marked variability in penetrance observed in various world populations.

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Genetic background modulates ATTR amyloid deposition.

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Genetic background affects pathogenic cascades involved in amyloidogenesis.

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Megalin and clustering possibly involved in the handing of TTR monomers.

Structural models for the design of novel antiviral agents against Greek Goat Encephalitis

The Greek Goat Encephalitis virus (GGE) belongs to the Flaviviridae family of the genus Flavivirus. The GGE virus constitutes an important pathogen of livestock that infects the goat’s central nervous system. The viral enzymes of GGE, helicase and RNA-dependent RNA polymerase (RdRP), are ideal targets for inhibitor design, since those enzymes are crucial for the virus’ survival, proliferation and transmission. In an effort to understand the molecular structure underlying the functions of those viral enzymes, the three dimensional structures of GGE NS3 helicase and NS5 RdRP have been modelled. The models were constructed in silico using conventional homology modelling techniques and the known 3D crystal structures of solved proteins from closely related species as templates. The established structural models of the GGE NS3 helicase and NS5 RdRP have been evaluated for their viability using a repertoire of in silico tools. The goal of this study is to present the 3D conformations of the GGE viral enzymes as reliable structural models that could provide the platform for the design of novel anti-GGE agents.

Molecular dynamics simulations through GPU video games technologies

Bioinformatics is the scientific field that focuses on the application of computer technology to the management of biological information. Over the years, bioinformatics applications have been used to store, process and integrate biological and genetic information, using a wide range of methodologies. One of the most de novo techniques used to understand the physical movements of atoms and molecules is molecular dynamics (MD). MD is an in silico method to simulate the physical motions of atoms and molecules under certain conditions. This has become a state strategic technique and now plays a key role in many areas of exact sciences, such as chemistry, biology, physics and medicine. Due to their complexity, MD calculations could require enormous amounts of computer memory and time and therefore their execution has been a big problem. Despite the huge computational cost, molecular dynamics have been implemented using traditional computers with a central memory unit (CPU). A graphics processing unit (GPU) computing technology was first designed with the goal to improve video games, by rapidly creating and displaying images in a frame buffer such as screens. The hybrid GPU-CPU implementation, combined with parallel computing is a novel technology to perform a wide range of calculations. GPUs have been proposed and used to accelerate many scientific computations including MD simulations. Herein, we describe the new methodologies developed initially as video games and how they are now applied in MD simulations.

A series of Notch3 mutations in CADASIL; insights from 3D molecular modelling and evolutionary analyses

CADASIL disease belongs to the group of rare diseases. It is well established that the Notch3 protein is primarily responsible for the development of CADASIL syndrome. Herein, we attempt to shed light to the actual molecular mechanism underlying CADASIL via insights that we have from preliminary in silico and proteomics studies on the Notch3 protein. At the moment, we are aware of a series of Notch3 point mutations that promote CADASIL. In this direction, we investigate the nature, extent, physicochemical and structural significance of the mutant species in an effort to identify the underlying mechanism of Notch3 role and implications in cell signal transduction. Overall, our in silico study has revealed a rather complex molecular mechanism of Notch3 on the structural level; depending of the nature and position of each mutation, a consensus significant loss of beta-sheet structure is observed throughout all in silico modeled mutant/wild type biological systems.

Responses to facial and non-facial stimuli presented tachistoscopically in either or both visual fields by patients with the Capgras delusion and paranoid schizophrenics

An experiment was carried out designed primarily to test A B Joseph's suggestion that patients with Capgras delusion may have problems integrating information between the two cortical hemispheres; and at the same time it was meant to examine J Cutting's ideas linking schizophrenia in general, and the Capgras delusion in particular, to right hemisphere dysfunction. Three patients with the Capgras delusion and three matched controls diagnosed as paranoid schizophrenics were briefly presented pairs of line-drawn object and photographs of faces randomly in the left visual field, the right visual field or bilaterally. The results with objects revealed no particular pattern of performance for either group; but, when faces were shown, the controls revealed the usual left visual field/right hemisphere advantage while for the Capgras group this was reversed. The results are not consistent with a simple prediction from Joseph's hypothesis but they are in accord with Cutting's theory-though they also pose some problems for it, which are discussed.