St. Petersburg University Journal of Economic Studies

Abstract Background The protective effects of higher educational attainment (EA) and intelligence on COVID-19 outcomes are not yet understood with regard to their dependency on income. The objective of our study was to examine the overall as well as independent effects of the three psychosocial factors on the susceptibility to and severity of COVID-19. To accomplish this, we utilized genetic correlation, Mendelian randomization (MR), and multivariable MR (MVMR) analyses to evaluate genetic associations between EA, intelligence, household income, and three specific COVID-19 outcomes: SARS-CoV-2 infection, hospitalized COVID-19, and critical COVID-19. Results The genetic correlation analysis revealed that COVID-19 outcomes were negatively correlated with the three psychosocial factors (rg: -0.19‒-0.36). The MR analysis indicated that genetic liability to EA, intelligence, and income exerted overall protective effects against SARS-CoV-2 infection (OR: 0.86‒0.92), hospitalized COVID-19 (OR: 0.70‒0.80), and critical COVID-19 (OR: 0.65‒0.85). MVMR analysis revealed that elevated levels of EA conferred independent protective effects against SARS-CoV-2 infection (OR: 0.85), hospitalization due to COVID-19 (OR: 0.79), and critical COVID-19 (OR: 0.63). Furthermore, intelligence exhibited a negative association with the risk of SARS-CoV-2 infection (OR: 0.91), whereas a higher income was linked to an elevated risk of SARS-CoV-2 infection (OR: 1.13). Conclusions Our findings indicated that EA could significantly reduce the risk and severity of COVID-19, regardless of intelligence and income. However, the impact of intelligence or income on COVID-19 severity was not supported by our research.

Next-generation sequencing (NGS)-based testing is a cost-effective method for identifying pathogenic germline genetic variations in cancer-predisposing genes in hereditary breast cancer. However, many of the variants detected through NGS are classified as variants of uncertain significance (VUS), where the impact of the variants on protein function remains unclear. Bioinformatics analysis using multiple computational tools is postulated to aid in generating new knowledge regarding the functional relevance of these VUS. This study aimed to gain new insights into the potential pathogenicity of a selected set of VUS identified in a cohort of Sri Lankan hereditary breast cancer patients using advanced bioinformatics tools. The cancer database at the Centre for Genetics and Genomics contains genomic and clinical data from patients who had undergone germline genetic testing between 2015 and 2023. Five germline VUS detected in breast cancer affected patients were identified from the existing database and selected for further bioinformatics analysis using a combination of in-silico pathogenicity prediction tools, 3D protein modeling with structural analysis, and protein structural stability assessment with molecular dynamic simulation (MDS). The VUS included: BRCA1:(NM_007294.4):c.3392A > G;p.Asp1131Gly, (rs1555587813); BRIP1:(NM_032043.3):c.3103C > T;p.Arg1035Cys, (rs45437094); CHEK2:(NM_007194.4):c.60G > T;p.Gln20His, (rs375507194); MET:(NM_000245.4):c.840G > T;p.Arg280Ser, (rs1207381066); and STK11:(NM_000455.5):c.355A > G;p.Asn119Asp, (rs545015076). Two variants MET:(NM_000245.4):c.840G > T;p.Arg280Ser and BRCA1:(NM_007294.4):c.3392A > G; p.Asp1131Gly are predicted to have high-risk potential for causing significant impacts on the protein structure and function. Align GVGD results and the MDS data for the BRIP1:(NM_032043.3):c.3103C > T;p.Arg1035Cys variant suggested some alterations that require further confirmation. The CHEK2:(NM_007194.4):c.60G > T;p.Gln20His variant suggested an intermediate impact, whereas STK11:(NM_000455.5):c.355A > G;p.Asn119Asp suggested no significant structural or functional impact on the protein. This study contributes valuable insights into the potential structural and functional implications of five VUS in cancer predisposition genes. Our results suggest a high-risk potential for variants in MET, BRCA1 and BRIP1, warranting further investigation to delineate their exact biological effects and to better understand their role in breast cancer risk.

Abstract Pharmacogenomics (PGx) aims to delineate a patient’s genetic profile with differences in drug efficacy and/or toxicity, particularly focusing on genes encoding for drug-metabolizing enzymes and transporters. Clinical implementation of PGx is a complex undertaking involving a multidisciplinary approach that includes, among others, a thorough understanding of a country’s preparedness to adopt this modern discipline and a detailed knowledge of PGx biomarkers allelic spectrum at a population level. In several European populations, particularly in countries with lower income, clinical implementation of PGx is still in its infancy. We have previously performed a pilot study to determine the prevalence of PGx biomarkers in 18 European populations, as the first step towards population PGx at the European level. Here, we provide a comprehensive analysis of the current state of PGx in Greece, including a detailed allelic frequency spectrum of clinically actionable PGx biomarkers, the level of PGx education in academia, the provision of PGx testing services from public and private laboratories, and the aspects of the regulatory PGx environment, especially with respect to the discrepancies between the Greek National Organization of Medicines and the European Medicine Agency and health technology assessment. This study would not only provide the foundations for expediting the adoption of PGx in clinical reality in Greece but can also serve as a paradigm for replicating future studies in other European countries, to expand on previously available pilot studies.

Sideroflexin (SFXN) family genes encode for a group of mitochondrial proteins involved in cellular processes such as iron homeostasis, amino acid metabolism, and energy production. Recent studies showed that they were aberrantly expressed in certain human cancers. However, there is a paucity of information about their expression in prostate cancer. In this study, we took a comprehensive approach to investigate their expression profiles in benign prostate tissue, prostate-derived cell lines, and prostate cancer tissues using multiple transcriptome datasets. Our results showed that SFXN1/3/4 genes were predominantly expressed in prostate tissue and cell lines. SFXN2/4 genes were significantly upregulated while the SFXN3 expression was significantly downregulated in malignant tissues compared to benign tissues. SFXN4 expression was identified as a diagnostic biomarker and prognostic factor for unfavorite survival outcomes. In advanced prostate cancers, SFXN2/4 expressions were positively correlated with the androgen receptor signaling activity but negatively correlated with the neuroendocrinal features. Further analysis discovered that SFXN5 expression was significantly elevated in neuroendocrinal prostate cancers. In conclusion, SFXN2/4 expressions are novel biomarkers in prostate cancer diagnosis and prognosis.

The progression of liver fibrosis involves complex interactions between hepatic stellate cells (HSCs) and multiple immune cells in the liver, including macrophages. However, the mechanism of exosomes in the crosstalk between liver macrophages and HSCs remains unclear. Exosomes were extracted from primary mouse macrophages and cultured with HSCs, and the differential expression of microRNAs was evaluated using high-throughput sequencing technology. The functions of miR-342-3p in exosomes were verified by qPCR and luciferase reporter gene experiments with HSCs. The function of the target gene Hippocalcin-like protein 1 (HPCAL1) in HSCs was verified by Western blotting, qPCR, cellular immunofluorescence and co-IP in vivo and in vitro. We demonstrated that exosomal microRNA-342-3p derived from primary liver macrophages could activate HSCs by inhibiting the expression of HPCAL1 in HSCs. HPCAL1, which is a fibrogenesis suppressor, could inhibit TGF-β signaling in HSCs by regulating the ubiquitination of Smad2 through direct interactions with its EF-hand 4 domain. This study reveals a previously unidentified profibrotic mechanism of crosstalk between macrophages and HSCs in the liver and suggests an attractive novel therapeutic strategy for treating fibroproliferative liver diseases.

Abstract Non-communicable diseases (NCDs) such as cardiovascular diseases, chronic respiratory diseases, cancers, diabetes, and mental health disorders pose a significant global health challenge, accounting for the majority of fatalities and disability-adjusted life years worldwide. These diseases arise from the complex interactions between genetic, behavioral, and environmental factors, necessitating a thorough understanding of these dynamics to identify effective diagnostic strategies and interventions. Although recent advances in multi-omics technologies have greatly enhanced our ability to explore these interactions, several challenges remain. These challenges include the inherent complexity and heterogeneity of multi-omic datasets, limitations in analytical approaches, and severe underrepresentation of non-European genetic ancestries in most omics datasets, which restricts the generalizability of findings and exacerbates health disparities. This scoping review evaluates the global landscape of multi-omics data related to NCDs from 2000 to 2024, focusing on recent advancements in multi-omics data integration, translational applications, and equity considerations. We highlight the need for standardized protocols, harmonized data-sharing policies, and advanced approaches such as artificial intelligence/machine learning to integrate multi-omics data and study gene-environment interactions. We also explore challenges and opportunities in translating insights from gene-environment (GxE) research into precision medicine strategies. We underscore the potential of global multi-omics research in advancing our understanding of NCDs and enhancing patient outcomes across diverse and underserved populations, emphasizing the need for equity and fairness-centered research and strategic investments to build local capacities in underrepresented populations and regions.