Protein-protein interaction network-based integration of GWAS and functional data for blood pressure regulation analysis.

BACKGROUND: It is valuable to analyze the genome-wide association studies (GWAS) data for a complex disease phenotype in the context of the protein-protein interaction (PPI) network, as the related pathophysiology results from the function of interacting polyprotein pathways. The analysis may include the design and curation of a phenotype-specific GWAS meta-database incorporating genotypic and eQTL data linking to PPI and other biological datasets, and the development of systematic workflows for PPI network-based data integration toward protein and pathway prioritization. Here, we pursued this analysis for blood pressure (BP) regulation. METHODS: The relational scheme of the implemented in Microsoft SQL Server BP-GWAS meta-database enabled the combined storage of: GWAS data and attributes mined from GWAS Catalog and the literature, Ensembl-defined SNP-transcript associations, and GTEx eQTL data. The BP-protein interactome was reconstructed from the PICKLE PPI meta-database, extending the GWAS-deduced network with the shortest paths connecting all GWAS-proteins into one component. The shortest-path intermediates were considered as BP-related. For protein prioritization, we combined a new integrated GWAS-based scoring scheme with two network-based criteria: one considering the protein role in the reconstructed by shortest-path (RbSP) interactome and one novel promoting the common neighbors of GWAS-prioritized proteins. Prioritized proteins were ranked by the number of satisfied criteria. RESULTS: The meta-database includes 6687 variants linked with 1167 BP-associated protein-coding genes. The GWAS-deduced PPI network includes 1065 proteins, with 672 forming a connected component. The RbSP interactome contains 1443 additional, network-deduced proteins and indicated that essentially all BP-GWAS proteins are at most second neighbors. The prioritized BP-protein set was derived from the union of the most BP-significant by any of the GWAS-based or the network-based criteria. It included 335 proteins, with ~ 2/3 deduced from the BP PPI network extension and 126 prioritized by at least two criteria. ESR1 was the only protein satisfying all three criteria, followed in the top-10 by INSR, PTN11, CDK6, CSK, NOS3, SH2B3, ATP2B1, FES and FINC, satisfying two. Pathway analysis of the RbSP interactome revealed numerous bioprocesses, which are indeed functionally supported as BP-associated, extending our understanding about BP regulation. CONCLUSIONS: The implemented workflow could be used for other multifactorial diseases.

Arguments for and against the whole-genome sequencing of newborns.

Recent decades have brought enormous progress in both genetics and genomics, as well as in information technology (IT). The sequence of the human genome is now known, and although our knowledge is far from complete, great progress has been made in understanding how the genome works. With the developments in storage capacity, artificial intelligence, and learning algorithms, we are now able to learn and interpret complex systems such as the human genome in a very short time. Perhaps the most important goal of learning about the human genome is to understand diseases better: how they develop; how their processes can be prevented or slowed down; and after diseases have developed, how they can be cured or their symptoms alleviated. The vast majority of diseases have a genetic background, i.e., genes, sequence variations, and gene-gene interactions play a role in most diseases to a greater or lesser extent. Accordingly, the first step is to discover which genes, or genomic variants, cause or contribute to the development of a particular disease in a given patient. Given that an individual's genome remains virtually unchanged throughout their life (with one or two exceptions, such as in the case of cancer, which is caused by somatic mutations), it might be considered advantageous to sequence the genome of every person at birth. In this paper, we set out to show the possible benefits of sequencing the entire genome of every human being at birth, while also discussing the main arguments against it.

Discovery of first novel sigma/HDACi dual-ligands with a potent in vitro antiproliferative activity.

Designing and discovering compounds for dual-target inhibitors is challenging to synthesize new, safer, and more efficient drugs than single-target drugs, especially to treat multifactorial diseases such as cancer. The simultaneous regulation of multiple targets might represent an alternative synthetic approach to optimize patient compliance and tolerance, minimizing the risk of target-based drug resistance due to the modulation of a few targets. To this end, we conceived for the first time the design and synthesis of dual-ligands σR/HDACi to evaluate possible employment as innovative candidates to address this complex disease. Among all synthesized compounds screened for several tumoral cell lines, compound 6 (Kiσ1R = 38 ± 3.7; Kiσ2R = 2917 ± 769 and HDACs IC50 = 0.59 µM) is the most promising candidate as an antiproliferative agent with an IC50 of 0.9 µM on the HCT116 cell line and no significant toxicity to normal cells. Studies of molecular docking, which confirmed the affinity over σ1R and a pan-HDACs inhibitory behavior, support a possible balanced affinity and activity between both targets.

Human Exome Sequencing and Prospects for Predictive Medicine: Analysis of International Data and Own Experience.

Today, whole-exome sequencing (WES) is used to conduct the massive screening of structural and regulatory genes in order to identify the allele frequencies of disease-associated polymorphisms in various populations and thus detect pathogenic genetic changes (mutations or polymorphisms) conducive to malfunctional protein sequences. With its extensive capabilities, exome sequencing today allows both the diagnosis of monogenic diseases (MDs) and the examination of seemingly healthy populations to reveal a wide range of potential risks prior to disease manifestation (in the future, exome sequencing may outpace costly and less informative genome sequencing to become the first-line examination technique). This review establishes the human genetic passport as a new WES-based clinical concept for the identification of new candidate genes, gene variants, and molecular mechanisms in the diagnosis, prediction, and treatment of monogenic, oligogenic, and multifactorial diseases. Various diseases are addressed to demonstrate the extensive potential of WES and consider its advantages as well as disadvantages. Thus, WES can become a general test with a broad spectrum pf applications, including opportunistic screening.

Dimensionality reduction approach for many-objective epistasis analysis.

In epistasis analysis, single-nucleotide polymorphism-single-nucleotide polymorphism interactions (SSIs) among genes may, alongside other environmental factors, influence the risk of multifactorial diseases. To identify SSI between cases and controls (i.e. binary traits), the score for model quality is affected by different objective functions (i.e. measurements) because of potential disease model preferences and disease complexities. Our previous study proposed a multiobjective approach-based multifactor dimensionality reduction (MOMDR), with the results indicating that two objective functions could enhance SSI identification with weak marginal effects. However, SSI identification using MOMDR remains a challenge because the optimal measure combination of objective functions has yet to be investigated. This study extended MOMDR to the many-objective version (i.e. many-objective MDR, MaODR) by integrating various disease probability measures based on a two-way contingency table to improve the identification of SSI between cases and controls. We introduced an objective function selection approach to determine the optimal measure combination in MaODR among 10 well-known measures. In total, 6 disease models with and 40 disease models without marginal effects were used to evaluate the general algorithms, namely those based on multifactor dimensionality reduction, MOMDR and MaODR. Our results revealed that the MaODR-based three objective function model, correct classification rate, likelihood ratio and normalized mutual information (MaODR-CLN) exhibited the higher 6.47% detection success rates (Accuracy) than MOMDR and higher 17.23% detection success rates than MDR through the application of an objective function selection approach. In a Wellcome Trust Case Control Consortium, MaODR-CLN successfully identified the significant SSIs (P < 0.001) associated with coronary artery disease. We performed a systematic analysis to identify the optimal measure combination in MaODR among 10 objective functions. Our combination detected SSIs-based binary traits with weak marginal effects and thus reduced spurious variables in the score model. MOAI is freely available at https://sites.google.com/view/maodr/home.

Patients with inflammatory bowel disease have a higher chance of developing periodontitis: A systematic review and meta-analysis.

Background and objective: Periodontitis affects up to one billion people worldwide, and has been proven to be associated with several systemic inflammatory conditions. This study investigates the specific relationship between two multifactorial diseases: Inflammatory bowel disease (IBD) and periodontitis. To thoroughly explore this issue, we investigated separately whether IBD patients have a higher chance of developing periodontitis, and equally, whether patients with periodontitis have a higher chance of developing IBD. Methods: The systematic search was performed in three databases: MEDLINE, Cochrane Trials, and Embase, up to 26 October 2021. The protocol was registered in PROSPERO. All eligible studies investigating the association between IBD and periodontitis from either direction were included. The Newcastle-Ottawa Scale was used to assess the risk of bias. As a primary outcome, we investigated the prevalence of IBD and periodontitis, and calculated the odds ratio (OR). Our secondary outcomes involved comparing the clinical periodontal outcomes of IBD patients to those of IBD-free patients. Results: The systematic search resulted in 1,715 records, 14 of which were eligible for qualitative synthesis and 8 for quantitative synthesis. On the basis of the results of the primary outcome, IBD diagnosis was associated with significantly higher odds of periodontitis: OR = 2.65 (CI: 2.09-3.36, I 2 = 0 (CI: 0-0.75)). For subgroup analysis, we investigated separately the odds in Crohn's disease (CD) patients: OR = 2.22 (CI: 1.49-3.31, I 2 = 0.05 (CI: 0-0.76)) and in ulcerative colitis (UC) patients: OR = 3.52 (CI: 2.56 to 4.83, I 2 = 0 (CI: 0-0.75)); the odds were significantly higher in all cases. Two studies investigated whether patients with periodontitis were more susceptible to IBD, and both found that periodontitis was significantly associated with the risk of subsequent UC, but not with subsequent CD. However, more studies are needed to prove an association. Conclusion: Our analysis confirmed that IBD patients have a higher chance of developing periodontitis, and are a higher risk population in dentistry. Both dentists and gastroenterologists should be aware of this relationship and should emphasize the importance of prevention even more than in the healthy population. Systematic review registration: [https://www.crd.york.ac.uk/prospero/], identifier [CRD42021286161].

Design of Improved Antidiabetic Drugs: A Journey from Single to Multitarget Agents.

Multifactorial diseases exhibit a complex pathophysiology with several factors contributing to their pathogenesis and development. Examples of such disorders are neurodegenerative (e. g. Alzheimer's, Parkinson's) and cardiovascular diseases (e. g. atherosclerosis, metabolic syndrome, diabetes II). Traditional therapeutic approaches with single-target drugs have been proven, in many cases, unsatisfactory for the treatment of multifactorial diseases such as diabetes II. The well-established by now strategy of multitarget drugs is constantly gaining interest and momentum, as a more effective approach. The development of pharmacomolecules able to simultaneously modulate multiple relevant-to-the-disease targets has already several successful examples in various fields and has, as such, inspired the design of multitarget antidiabetic agents; this review highlights the design aspect and efficacy of this approach for improved antidiabetics by presenting several examples of successful pharmacophore combinations in (multitarget) agents that modulate two or more molecular targets involved in diabetes II, resulting in a superior antihyperglycemic profile.

Unveiling the Multitarget Anti-Alzheimer Drug Discovery Landscape: A Bibliometric Analysis.

Multitarget anti-Alzheimer agents are the focus of very intensive research. Through a comprehensive bibliometric analysis of the publications in the period 1990-2020, we have identified trends and potential gaps that might guide future directions. We found that: (i) the number of publications boomed by 2011 and continued ascending in 2020; (ii) the linked-pharmacophore strategy was preferred over design approaches based on fusing or merging pharmacophores or privileged structures; (iii) a significant number of in vivo studies, mainly using the scopolamine-induced amnesia mouse model, have been performed, especially since 2017; (iv) China, Italy and Spain are the countries with the largest total number of publications on this topic, whereas Portugal, Spain and Italy are the countries in whose scientific communities this topic has generated greatest interest; (v) acetylcholinesterase, ß-amyloid aggregation, oxidative stress, butyrylcholinesterase, and biometal chelation and the binary combinations thereof have been the most commonly pursued, while combinations based on other key targets, such as tau aggregation, glycogen synthase kinase-3ß, NMDA receptors, and more than 70 other targets have been only marginally considered. These results might allow us to spot new design opportunities based on innovative target combinations to expand and diversify the repertoire of multitarget drug candidates and increase the likelihood of finding effective therapies for this devastating disease.

What are the challenges with multi-targeted drug design for complex diseases?

INTRODUCTION: Current findings on multifactorial diseases with a complex pathomechanism confirm that multi-target drugs are more efficient ways in treating them as opposed to single-target drugs. However, to design multi-target ligands, a number of factors and challenges must be taken into account. AREAS COVERED: In this perspective, we summarize the concept of application of multi-target drugs for the treatment of complex diseases such as neurodegenerative diseases, schizophrenia, diabetes, and cancer. We discuss the aspects of target selection for multifunctional ligands and the application of in silico methods in their design and optimization. Furthermore, we highlight other challenges such as balancing affinities to different targets and drug-likeness of obtained compounds. Finally, we present success stories in the design of multi-target ligands for the treatment of common complex diseases. EXPERT OPINION: Despite numerous challenges resulting from the design of multi-target ligands, these efforts are worth making. Appropriate target selection, activity balancing, and ligand drug-likeness belong to key aspects in the design of ligands acting on multiple targets. It should be emphasized that in silico methods, in particular inverse docking, pharmacophore modeling, machine learning methods and approaches derived from network pharmacology are valuable tools for the design of multi-target drugs.

First genome-wide association study of esophageal atresia identifies three genetic risk loci at CTNNA3, FOXF1/FOXC2/FOXL1, and HNF1B.

Esophageal atresia with or without tracheoesophageal fistula (EA/TEF) is the most common congenital malformation of the upper digestive tract. This study represents the first genome-wide association study (GWAS) to identify risk loci for EA/TEF. We used a European case-control sample comprising 764 EA/TEF patients and 5,778 controls and observed genome-wide significant associations at three loci. On chromosome 10q21 within the gene CTNNA3 (p = 2.11 × 10-8; odds ratio [OR] = 3.94; 95% confidence interval [CI], 3.10-5.00), on chromosome 16q24 next to the FOX gene cluster (p = 2.25 × 10-10; OR = 1.47; 95% CI, 1.38-1.55) and on chromosome 17q12 next to the gene HNF1B (p = 3.35 × 10-16; OR = 1.75; 95% CI, 1.64-1.87). We next carried out an esophageal/tracheal transcriptome profiling in rat embryos at four selected embryonic time points. Based on these data and on already published data, the implicated genes at all three GWAS loci are promising candidates for EA/TEF development. We also analyzed the genetic EA/TEF architecture beyond the single marker level, which revealed an estimated single-nucleotide polymorphism (SNP)-based heritability of around 37% ± 14% standard deviation. In addition, we examined the polygenicity of EA/TEF and found that EA/TEF is less polygenic than other complex genetic diseases. In conclusion, the results of our study contribute to a better understanding on the underlying genetic architecture of ET/TEF with the identification of three risk loci and candidate genes.

Natural isoquinoline alkaloids: Pharmacological features and multi-target potential for complex diseases.

Complex diseases such as neurodegenerative disorders and cancer constitute a growing public health problem due to the rising incidence and lack in effective therapies. Since pharmacotherapy based on a single target has been insufficient for drug development in complex diseases, the emerging multi-target approach is a promising strategy for the search of new drug candidates. Plant-derived isoquinoline alkaloids comprise a vast source of multimodal agents with unique structural diversity, and variated range of pharmacological activities. This review offers an exhaustive compilation of the pharmacological relevance and multi-target potential of natural isoquinolines, emphasizing their features and promising activity in complex diseases such as Alzheimer, Parkinson, and Cancer. Selected examples were discussed in depth to illustrate the most relevant structural motifs and their possible relationship with the multimodal activity offering a comprehensive baseline in the search and optimization of isoquinoline scaffolds with polypharmacological potential for complex diseases.

Blood biomarkers for assessment of mitochondrial dysfunction: An expert review.

Although mitochondrial dysfunction is the known cause of primary mitochondrial disease, mitochondrial dysfunction is often difficult to measure and prove, especially when biopsies of affected tissue are not available. In order to identify blood biomarkers of mitochondrial dysfunction, we reviewed studies that measured blood biomarkers in genetically, clinically or biochemically confirmed primary mitochondrial disease patients. In this way, we were certain that there was an underlying mitochondrial dysfunction which could validate the biomarker. We found biomarkers of three classes: 1) functional markers measured in blood cells, 2) biochemical markers of serum/plasma and 3) DNA markers. While none of the reviewed single biomarkers may perfectly reveal all underlying mitochondrial dysfunction, combining biomarkers that cover different aspects of mitochondrial impairment probably is a good strategy. This biomarker panel may assist in the diagnosis of primary mitochondrial disease patients. As mitochondrial dysfunction may also play a significant role in the pathophysiology of multifactorial disorders such as Alzheimer's disease and glaucoma, the panel may serve to assess mitochondrial dysfunction in complex multifactorial diseases as well and enable selection of patients who could benefit from therapies targeting mitochondria.

Potentiating the Benefits of Melatonin through Chemical Functionalization: Possible Impact on Multifactorial Neurodegenerative Disorders.

Although melatonin is an astonishing molecule, it is possible that chemistry will help in the discovery of new compounds derived from it that may exceed our expectations regarding antioxidant protection and perhaps even neuroprotection. This review briefly summarizes the significant amount of data gathered to date regarding the multiple health benefits of melatonin and related compounds. This review also highlights some of the most recent directions in the discovery of multifunctional pharmaceuticals intended to act as one-molecule multiple-target drugs with potential use in multifactorial diseases, including neurodegenerative disorders. Herein, we discuss the beneficial activities of melatonin derivatives reported to date, in addition to computational strategies to rationally design new derivatives by functionalization of the melatonin molecular framework. It is hoped that this review will promote more investigations on the subject from both experimental and theoretical perspectives.

Characteristics Associated with Tumor Development in Individuals Diagnosed with Beckwith-Wiedemann Spectrum: Novel Tumor-(epi)Genotype-Phenotype Associations in the BWSp Population.

Beckwith-Wiedemann Spectrum (BWSp) is the most common epigenetic childhood cancer predisposition disorder. BWSp is caused by (epi)genetic changes affecting the BWS critical region on chromosome 11p15. Clinically, BWSp represents complex molecular and phenotypic heterogeneity resulting in a range of presentations from Classic BWS to milder features. The previously reported tumor risk based on Classic BWS cohorts is 8-10% and routine tumor screening has been recommended. This work investigated the tumor risk and correlation with phenotype within a cohort of patients from Classic BWS to BWSp using a mixed-methods approach to explore phenotype and epigenotype profiles associated with tumor development through statistical analyses with post-hoc retrospective case series review. We demonstrated that tumor risk across BWSp differs from Classic BWS and that certain phenotypic features are associated with specific epigenetic causes; nephromegaly and/or hyperinsulinism appear associated with cancer in some patients. We also demonstrated that prenatal and perinatal factors that are not currently part of the BWSp classification may factor into tumor risk. Additionally, blood testing results are not necessarily synonymous with tissue testing results. Together, it appears that the current understanding from Classic BWS of (epi)genetics and phenotype correlations with tumors is not represented in the BWSp. Further study is needed in this complex population.

Immuno-regenerative biomaterials for in situ cardiovascular tissue engineering - Do patient characteristics warrant precision engineering?

In situ tissue engineering using bioresorbable material implants - or scaffolds - that harness the patient's immune response while guiding neotissue formation at the site of implantation is emerging as a novel therapy to regenerate human tissues. For the cardiovascular system, the use of such implants, like blood vessels and heart valves, is gradually entering the stage of clinical translation. This opens up the question if and to what extent patient characteristics influence tissue outcomes, necessitating the precision engineering of scaffolds to guide patient-specific neo-tissue formation. Because of the current scarcity of human in vivo data, herein we review and evaluate in vitro and preclinical investigations to predict the potential role of patient-specific parameters like sex, age, ethnicity, hemodynamics, and a multifactorial disease profile, with special emphasis on their contribution to the inflammation-driven processes of in situ tissue engineering. We conclude that patient-specific conditions have a strong impact on key aspects of in situ cardiovascular tissue engineering, including inflammation, hemodynamic conditions, scaffold resorption, and tissue remodeling capacity, suggesting that a tailored approach may be required to engineer immuno-regenerative biomaterials for safe and predictive clinical applicability.

[Genetics of epilepsy: successes, problems and development prospects]. / Genetika epilepsii: uspekhi, problemy i perspektivy razvitiya.

The authors present a detailed review of current advances in the field of genetics of epilepsy. Separately, new views on the etiology and pathogenesis of genetic epileptic encephalopathies, focal epilepsy and idiopathic generalized epilepsies are examined. The authors emphasize the importance of genetic discoveries for the clinical practice, including the prospects in the development of patients' personalized treatment. A comparative analysis of the value of various methods of genetic research in the diagnosis of epilepsy, methods of integrating molecular genetic analyses into everyday practical medicine is presented.

Causality assessment of adverse events following immunization: the problem of multifactorial pathology.

The analysis of Adverse Events Following Immunization (AEFI) is important in a balanced epidemiological evaluation of vaccines and in the issues related to vaccine injury compensation programs. The majority of adverse reactions to vaccines occur as excessive or biased inflammatory and immune responses. These unwanted phenomena, occasionally severe, are associated with many different endogenous and exogenous factors, which often interact in complex ways. The confirmation or denial of the causal link between an AEFI and vaccination is determined pursuant to WHO guidelines, which propose a four-step analysis and algorithmic diagramming. The evaluation process from the onset considers all possible "other causes" that might explain the AEFI and thus exclude the role of the vaccine. Subsequently, even if there was biological plausibility and temporal compatibility for a causal association between the vaccine and the AEFI, the guidelines ask to look for any possible evidence that the vaccine could not have caused that event. Such an algorithmic method presents several concerns that are discussed here, in the light of the multifactorial nature of the inflammatory and immune pathologies induced by vaccines, including emerging knowledge of genetic susceptibility to adverse effects. It is proposed that the causality assessment could exclude a consistent association of the adverse event with the vaccine only when the presumed "other cause" is independent of an interaction with the vaccine. Furthermore, the scientific literature should be viewed not as an exclusion criterion but as a comprehensive analysis of all the evidence for or against the role of the vaccine in causing an adverse reaction. Given these inadequacies in the evaluation of multifactorial diseases, the WHO guidelines need to be reevaluated and revised. These issues are discussed in relation to the laws that, in some countries, regulate the mandatory vaccinations and the compensation for those who have suffered serious adverse effects.

Bioethical problems arising in the study of single-nucleotide gene polymorphisms of occupational diseases.

In Ukraine, about 3 million people work in hazardous and dangerous conditions. The study of hereditary specificity in development of occupational diseases is being actively conducted through molecular genetic analysis of single-nucleotide gene polymorphisms. While studying single-nucleotide gene polymorphisms of occupational diseases, many complicated bioethical questions arise regarding the confidentiality of personal data, the choice between the profession chosen and the risk to one's own health. Complicated bioethical issues that arise when studying single-nucleotide gene polymorphisms of occupational diseases need to be actively discussed, not only by physicians, occupational pathologists, employers, scientists, but also by politicians and lawyers, taking into account ethical and social norms and implications.

Poly(Ethylene Glycol) Crosslinked Multi-Armed Poly(l-Lysine) with Encapsulating Capacity and Antimicrobial Activity for the Potential Treatment of Infection-Involved Multifactorial Diseases.

With the development of modern medical technology, common diseases usually can be treated by traditional medicines and their formulation, while diseases with multiple etiologies still remain a great challenge in clinic. Nanoformulation was widely explored to address this problem. However, due to limited drug loading space of nanocarriers, co-delivery strategy usually fails to achieve sufficient loading of multiple drugs simultaneously. In this research, we explored the potential of poly(ethylene glycol) (PEG) crosslinked alternating copolymers MPLL-alt-PEG as both an anionic drug carrier and antimicrobial agent. The high cationic charge density of multi-armed poly(l-lysine) (MPLL) segments in MPLL-alt-PEG could endow the electrostatic encapsulation of anionic model drugs through the formation of polyion complex micelles with a MPLL/drug complex core and crosslinked PEG outer shell, enabling pH-sensitive drug release. Meanwhile, the MPLL-alt-PEG copolymer exhibits a broad spectrum of antimicrobial activities against various clinically relevant microorganisms with low hemolytic activity. Studies on antibacterial mechanism revealed that MPLL-alt-PEG attacked bacteria through the membrane disruption mechanism which is similar to that of typical antimicrobial peptides. Taken together, the present study shed light on the possibility of endowing a polymeric carrier with therapeutic effect and thus offered a promising strategy for achieving a comprehensive treatment of bacterial infection-involved multifactorial diseases.