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.

Spinal meningiomas.

Spinal meningiomas (SM) are lesions with a mostly favorable oncological and surgical prognosis and a low incidence of tumor recurrence. SM account for approximately 1.2-12.7% of all meningiomas and 25% of all spinal cord tumors. Typically, SM are located in the intradural extramedullary space. SM grow slowly and spread laterally into the subarachnoid space, stretching and sometimes incorporating the surrounding arachnoid but rarely the pia. Standard treatment is surgery with the primary aims of achieving complete tumor resection as well as improving and recovering neurologic function. Radiotherapy may be considered in case of tumor recurrence, for challenging surgical cases, and for patients with higher-grade lesions (World Health Organization grade 2 or 3); however, radiotherapy is mostly used as an adjuvant therapy for SM. New molecular and genetic profiling increases the understanding of SM and may uncover additional treatment options.

Hepatic triglyceride content is intricately associated with numerous metabolites and biochemical pathways.

BACKGROUND AND AIMS: Non-alcoholic fatty liver disease (NAFLD) is characterized by the pathological accumulation of triglycerides in hepatocytes and is associated with insulin resistance, atherogenic dyslipidaemia and cardiometabolic diseases. Thus far, the extent of metabolic dysregulation associated with hepatic triglyceride accumulation has not been fully addressed. In this study, we aimed to identify metabolites associated with hepatic triglyceride content (HTGC) and map these associations using network analysis. METHODS: To gain insight in the spectrum of metabolites associated with hepatic triglyceride accumulation, we performed a comprehensive plasma metabolomics screening of 1363 metabolites in apparently healthy middle aged (age 45-65) individuals (N = 496) in whom HTGC was measured by proton magnetic resonance spectroscopy. An atlas of metabolite-HTGC associations, based on univariate results, was created using correlation-based Gaussian graphical model (GGM) and genome scale metabolic model network analyses. Pathways associated with the clinical prognosis marker fibrosis 4 (FIB-4) index were tested using a closed global test. RESULTS: Our analyses revealed that 118 metabolites were univariately associated with HTGC (p-value <6.59 × 10-5 ), including 106 endogenous, 1 xenobiotic and 11 partially characterized/uncharacterized metabolites. These associations were mapped to several biological pathways including branched amino acids (BCAA), diglycerols, sphingomyelin, glucosyl-ceramide and lactosyl-ceramide. We also identified a novel possible HTGC-related pathway connecting glutamate, metabolonic lactone sulphate and X-15245 using the GGM network. These pathways were confirmed to be associated with the FIB-4 index as well. The full interactive metabolite-HTGC atlas is provided online: https://tofaquih.github.io/AtlasLiver/. CONCLUSIONS: The combined network and pathway analyses indicated extensive associations between BCAA and the lipids pathways with HTGC and the FIB-4 index. Moreover, we report a novel pathway glutamate-metabolonic lactone sulphate-X-15245 with a potential strong association with HTGC. These findings can aid elucidating HTGC metabolomic profiles and provide insight into novel drug targets for fibrosis-related outcomes.

The Evolving Therapeutic Landscape for Malignant Pleural Mesothelioma.

PURPOSE OF REVIEW: For patients with malignant pleural mesothelioma, prognosis is poor with extremely low 5-year survival rates and limited therapeutic options. Here, we review the current treatment landscape for mesothelioma and highlight promising future therapeutic directions. RECENT FINDINGS: Evolving frontline therapeutic options for mesothelioma include VEGF inhibition in combination with chemotherapy and dual immune checkpoint inhibition, with synergisms between the therapies and response prediction via biomarkers also being explored. Evolving experimental treatments for mesothelioma include PARP and ALK inhibitors, dendritic and CAR T-cell therapies, anti-mesothelin vaccines, and oncolytic viral therapies, representing timely advances in the field. The therapeutic landscape for malignant pleural mesothelioma is evolving and preferred treatment in the frontline and later settings will likely evolve with it. However, this does not preclude the evidence for including multi-modal therapies spanning angiogenesis and immune checkpoint inhibitors, and biomarker utilization, in current clinical trials and management.

New therapeutic approaches to Parkinson's disease targeting GBA, LRRK2 and Parkin.

Parkinson's disease (PD) is defined as a complex disorder with multifactorial pathogenesis, yet a more accurate definition could be that PD is not a single entity, but rather a mixture of different diseases with similar phenotypes. Attempts to classify subtypes of PD have been made based on clinical phenotypes or biomarkers. However, the most practical approach, at least for a portion of the patients, could be to classify patients based on genes involved in PD. GBA and LRRK2 mutations are the most common genetic causes or risk factors of PD, and PRKN is the most common cause of autosomal recessive form of PD. Patients carrying variants in GBA, LRRK2 or PRKN differ in some of their clinical characteristics, pathology and biochemical parameters. Thus, these three PD-associated genes are of special interest for drug development. Existing therapeutic approaches in PD are strictly symptomatic, as numerous clinical trials aimed at modifying PD progression or providing neuroprotection have failed over the last few decades. The lack of precision medicine approach in most of these trials could be one of the reasons why they were not successful. In the current review we discuss novel therapeutic approaches targeting GBA, LRRK2 and PRKN and discuss different aspects related to these genes and clinical trials.

Genetically Targeted Clinical Trials in Parkinson's Disease: Learning from the Successes Made in Oncology.

Clinical trials in neurodegenerative disorders have been associated with high rate of failures, while in oncology, the implementation of precision medicine and focus on genetically defined subtypes of disease and targets for drug development have seen an unprecedented success. With more than 20 genes associated with Parkinson's disease (PD), most of which are highly penetrant and often cause early onset or atypical signs and symptoms, and an increasing understanding of the associated pathophysiology culminating in dopaminergic neurodegeneration, applying the technologies and designs into the field of neurodegeneration seems a logical step. This review describes some of the methods used in oncology clinical trials and some attempts in Parkinson's disease and the potential of further implementing genetics, biomarkers and smart clinical trial designs in this disease area.

Genetic Prioritization, Therapeutic Repositioning and Cross-Disease Comparisons Reveal Inflammatory Targets Tractable for Kidney Stone Disease.

Background: Formation of kidney stones resulting in urological disorders remains a major cause of morbidity in renal diseases and many others. Innate immunity, mainly inflammasome, has demonstrated a key role in the development of kidney stone disease (or "nephrolithiasis"), but a molecular rationale for therapeutic intervention targeting immunity is far from clear. We reason that identifying inflammatory gene networks underlying disease risk would inform immunotherapeutic targets for candidate drug discovery. Results: We generated an atlas of genetic target prioritization, with the top targets highly enriched for genes involved in the NF-kB regulation, including interaction neighbors of inflammasome genes. We identified a network of highly ranked and interconnecting genes that are of functional relevance to nephrolithiasis and mediate crosstalk between inflammatory pathways. Crosstalk genes can be utilized for therapeutic repositioning, as highlighted by identification of ulixertinib and losmapimod that are both under clinical investigation as inhibitors of inflammatory mediators. Finally, we performed cross-disease comparisons and druggable pocket predictions, identifying inflammatory targets that are specific to and tractable for nephrolithiasis. Conclusion: Genetic targets and candidate drugs, in silico identified in this study, provide the rich information of how to target innate immune pathways, with the potential of advancing immunotherapeutic strategies for nephrolithiasis.

Genetic Predictors of Early-Onset Spinal Intervertebral Disc Degeneration: Part Two of Two.

Understanding genetic indicators is a fundamental aspect to characterizing the pathophysiology of chronic diseases such as intervertebral disc degeneration (IVDD). In our previous spinal genetics review, we characterized some more common genetic influencers in the context of IVDD. In this second part of our two-part comprehensive spinal genetics review, we characterize the more infrequently studied genes that have pathophysiological relevance. In doing so, we aim to expand upon the current gene-library for IVDD. The genes of interest include: asporin, cartilage intermediate layer protein, insulin-like growth factor 1 receptor, matrix metallopeptidase 9, and thrombospondin 2. Findings show that these genetic indicators have trends and polymorphisms that may have causal associations with the manifestation of IVDD. However, there is a narrow selection of studies that use genetic indicators to describe correlations to the severity and longevity of the pathology. Nevertheless, with the continued identification of risk genes involved with IVDD, the possibilities for refined models of gene therapies can be established for future treatment trials.

Treatment of Fatty Liver Disease: The Present and the Future.

Non-alcoholic fatty liver disease (NAFLD) progressing to non-alcoholic steatohepatitis (NASH), cirrhosis, end-stage liver disease (ESRD), and hepatocellular carcinoma (HCC) is emerging as a global epidemic. Obesity, diabetes, and metabolic syndrome are some of the leading risk factors for NAFLD. The most prevalent treatment to stop the progression is aimed at dietary modification and lifestyle changes. Bariatric surgery is indicated for patients with morbid obesity with NAFLD. The progression of NAFLD to NASH and HCC can be arrested at various stages of pathogenesis by the already prevalent drugs and the emerging newer molecular and genetic targets. This review article analyzed various preclinical animal trials and clinical trials and has summarized various groups of drugs that can be life-altering in patients diagnosed with NAFLD. This study also discusses the obstacles in taking these clinical trials to bedside treatment.

Genome-wide DNA copy number analysis in clonally expanded human ovarian cancer cells with distinct invasive/migratory capacities.

Ovarian cancer has the worst prognosis of any gynecological malignancy, and generally presents with metastasis at advanced stages. Copy number variation (CNV) frequently contributes to the alteration of oncogenic drivers. In this study, we sought to identify genetic targets in heterogeneous clones from human ovarian cancers cells. We used array-based technology to systematically assess all the genes with CNVs in cell models clonally expanded from A2780 and SKOV3 ovarian cancer cell lines with distinct highly and minimally invasive/migratory capacities. We found that copy number alterations differed between matched highly and minimally invasive/migratory subclones, differentially affecting specific functional processes including immune response processes, DNA damage repair, cell cycle and cell proliferation. We also identified seven genes as strong candidates, including DDB1, ERCC1, ERCC2, PRPF19, BCAT1, CDKN1B and MARK4, by integrating the above data with gene expression and clinical outcome data. Thus, by determining the molecular signatures of heterogeneous invasive/migratory ovarian cancer cells, we identified genes that could be specifically targeted for the treatment and prognosis of advanced ovarian cancers.

Genetic Testing in the Multidisciplinary Management of Melanoma.

Melanoma is increasing in incidence and represents an aggressive type of cancer. Efforts have focused on identifying genetic factors in melanoma carcinogenesis to guide prevention, screening, early detection, and targeted therapy. This article reviews the hereditary risk factors associated with melanoma and the known molecular pathways and genetic mutations associated with this disease. This article also explores the controversies associated with genetic testing and the latest advances in identifying genetic targets in melanoma, which offer promise for future application in the multidisciplinary management of melanoma.

Applications of microarray technology to Acute Myelogenous Leukemia.

Microarray technology is a powerful tool, which has been applied to further the understanding of gene expression changes in disease. Array technology has been applied to the diagnosis and prognosis of Acute Myelogenous Leukemia (AML). Arrays have also been used extensively in elucidating the mechanism of and predicting therapeutic response in AML, as well as to further define the mechanism of AML pathogenesis. In this review, we discuss the major paradigms of gene expression array analysis, and provide insights into the use of software tools to annotate the array dataset and elucidate deregulated pathways and gene interaction networks. We present the application of gene expression array technology to questions in acute myelogenous leukemia; specifically, disease diagnosis, treatment and prognosis, and disease pathogenesis. Finally, we discuss several new and emerging array technologies, and how they can be further utilized to improve our understanding of AML.