BACKGROUND:Association of the BCL11A (rs4671393), HBG2 (rs7482144), and HBG2HBS1L-MYB (rs28384513, rs9399137, and rs4895441) variants with susceptibility to thalassemia was observed. METHODOLOGY:Blood samples from 600 individuals, including 300 thalassemia patients and 300 controls, age- and gender-matched, were collected. DNA was extracted, followed by DNA Amplification. RESULTS:Results show that the homozygous mutant (GG) of variant rs4671393 of the BCL11A gene showed a strong association with increased risk of thalassemia by 3-fold (OR = 3.05; p = 0.0002), heterozygous (AG) also showed a strong association but with a decreased risk (OR = 0.49; p = 0.0028). The heterozygote (AC) and the mutant of variant rs28384513 of gene HBG2HBS1L-MYB showed a significant association by increasing the risk of thalassemia by 2-fold (OR = 2.07; p = 0.001; OR = 2.79; p = 0.0002, respectively). In the case of rs4895441 of gene HBS1L-MYB, the AG heterozygote showed a significant association by increasing the risk by 2.55-fold (OR = 2.55; p = 0.0002). For gene HBG2, the heterozygote (CT) of the rs7482144 variant significantly decreased the risk of thalassemia (OR = 0.37; p = 0.0001). Its homozygous mutant (TT) also showed a significant association, but with an increased risk of thalassemia by 2-fold (OR = 1.81; p = 0.036). . CONCLUSION:The polymorphisms rs4671393 (BCL11A), rs7482144 (HBG2), and rs28384513, rs9399137, and rs4895441 (HBS1L-MYB) are significantly associated with an increased risk of thalassemia.
OBJECTIVE:This work aims to analyze the clinical significance of microRNA-27a-3p (miR-27a-3p) in hepatocellular carcinoma (HCC) and its impact on HCC cell behavior. METHODS:RT-qPCR was performed on 57 paired HCC tumor and adjacent normal tissues to assess miR-27a-3p levels and its correlation with prognosis and clinicopathological features. HCC cells were transfected with miR-27a-3p inhibitor/mimic, si-TET1, or corresponding controls. RT-qPCR/Western blot measured miR-27a-3p, TET1, and p53 levels. CCK-8/Transwell/flow cytometry assay evaluated cell activities. Dual-luciferase reporter and RNA pull-down assays confirmed the direct interaction between miR-27a-3p and TET1. In vivo, a subcutaneous xenograft model was used to assess the effect of miR-27a-3p antagomir on tumor growth via tail vein injection. RESULTS:miR-27a-3p was upregulated in HCC tissues, correlating with poor survival, TNM stage, tumor size, alongside vascular invasion. miR-27a-3p knockdown diminished HCC cell growth while promoting apoptosis. Mechanistically, miR-27a-3p targeted TET1. Rescue experiments reflected that TET1 inhibition partially reversed the tumor-suppressive impacts of miR-27a-3p silencing. Further, miR-27a-3p knockdown enhanced p53 levels via TET1, whereas its overexpression suppressed both TET1 and p53. In vivo, miR-27a-3p antagomir suppressed HCC xenograft tumor growth. CONCLUSION:Downregulation of miR-27a-3p exerts a tumor-suppressive impact in HCC by inhibiting malignant biological behaviors, potentially via the TET1/p53 axis.
AIM:Colorectal cancer (CRC) is a widespread health issue that attains high mortality. The adaptor protein SH3BP2 amplification results in metabolic changes, oxidative stress, NK cell activity, and inflammation. The NK cells are capable of destroying tumor cells without prior activation, help prevent metastasis, and have prognostic value. Targeting SH3BP2 to regulate NK cell activity in the TME could enhance CRC-based immunotherapy. MATERIALS AND METHODS:The cancer hallmark tool helps in understanding SH3BP2 hallmark annotation. Utilizing the STRING tool and the KEGG pathway, protein functional enrichment and PPI networking were analyzed. TIMER 2.0 was used for immune cell infiltration correlation analysis, and UALCAN was used for CPTAC-based protein expression profiling. RESULTS AND CONCLUSIONS:The GEO (GSE9348) dataset showed SH3BP2 is upregulated in CRC (log2 fold change = 1.18). GEO, TCGA, and cBioPortal revealed SH3BP2 alterations in CRC cases, potentially aiding immune evasion. Mutations in SH3BP2 influence cancer growth, suppressing tumors or promoting them by activating NF-κB and affecting immune responses through WNT/β-catenin, PI3K, MAPK, and JAK-STAT pathways. Overall, SH3BP2 plays a key role in cancer growth and immune regulation, making it a promising target for CRC therapy. Further experimental validation is needed to demonstrate its diagnostic and therapeutic potency.
BACKGROUND:Dapsone is a drug used to treat leprosy. Dapsone causes a highly morbid and potentially fatal severe drug hypersensitivity reaction (DHS) in 1-3% of leprosy cases. The allele HLA-B*13:01 is a known genetic risk factor for DHS. However, resource-intensive genotyping methods preclude its testing in resource-limited settings. This study aimed to develop an endpoint PCR assay to detect the presence of HLA-B*13:01. RESEARCH DESIGN AND METHODS:DNA was extracted from blood samples of leprosy patients at Anandaban Hospital, Nepal (2022-24). A duplex endpoint PCR was optimized and validated against a previously validated commercial qPCR method and NGS (next‑generation sequencing). RESULTS:In 113 samples, duplex PCR showed 100% (95% CI: 79.4-100%) sensitivity and 100% specificity (95% CI: 96.2-100%) compared to the validated qPCR method. The same accuracy was confirmed in 58 NGS-typed samples (concordance 98.3%, 95% CI: 90.7-99.9%). The assay reliably differentiated HLA-B*13:01 from closely related allele. Analytical sensitivity reached a lower detection limit of 100 genome equivalents (0.67 ng DNA/reaction). CONCLUSION:The developed duplex endpoint PCR offers a simple and affordable method for detecting HLA-B*13:01, suitable in low-resource settings. Its use may significantly reduce the risk of DHS by guiding safer drug choices prior to MDT initiation.
This review examines the integration of causal artificial intelligence (AI) and data-driven decision intelligence within healthcare informatics systems to advance personalized medicine and clinical decision-making. A narrative review methodology was employed, synthesizing interdisciplinary literature from major databases, including PubMed, Scopus, Web of Science, IEEE Xplore, and ScienceDirect. Studies focusing on causal inference, decision intelligence, and healthcare informatics applications in personalized medicine were included. Data were extracted on methodological approaches, healthcare settings, analytical techniques, and clinical applications, followed by thematic synthesis. Findings indicate that causal AI enhances clinical decision support by enabling estimation of treatment effects and simulation of intervention outcomes at the individual patient level. Integration of multimodal health data such as electronic health records, genomic data, and real-time monitoring improves prediction accuracy and supports tailored treatment strategies. Additionally, causal models improve interpretability, fostering clinician trust and facilitating transparent decision-making. Robust healthcare informatics infrastructures, including interoperable systems and data warehouses, were identified as critical enablers of causal analytics. Overall, causal AI represents a transformative advancement in healthcare analytics, supporting more informed, individualized, and evidence-based clinical decisions. Its integration within healthcare informatics systems has significant potential to improve patient outcomes and guide the future of intelligent, personalized healthcare delivery.
BACKGROUND:Chronic obstructive pulmonary disease (COPD) ranks among the leading causes of morbidity and mortality globally. Genomic susceptibility factors are acknowledged as critical modulators of disease variability and progression. The Sonic Hedgehog (SHH) pathway regulates epithelial tissue healing, mucin synthesis, and airway remodeling. GLI1 polymorphic variants may influence the manifestations of COPD. METHODOLOGY:A case-control study was conducted, involving 500 patients with COPD and 500 controls from the North Indian population. We genotyped two GLI1 polymorphisms (rs61739569 (T>C) and rs2228226 (G>C). Logistic regression models were applied to examine the associations between COPD susceptibility and clinical features. RESULTS:rs61739569 and rs2228226 show no association with an increased risk of COPD overall. Nonetheless, rs61739569 exhibited significant phenotype-specific correlations: individuals possessing the CC genotype demonstrated a markedly elevated risk of chronic cough, sputum production, and exacerbations, while displaying a diminished risk of dyspnea and activity limitation. CONCLUSION:Variations in GLI1 may influence the symptoms of COPD, rather than the overall likelihood of developing COPD. The rs61739569 is particularly applicable to mucus-dominant phenotypes, such as those resembling chronic bronchitis. This study suggests that GLI1 signaling exhibits context-dependent functional significance in COPD.
AIMS:This study investigated the association between BAFF gene polymorphisms (rs1041569 and rs9514828) and preeclampsia (PE) susceptibility in an Iranian population, with a focus on disease severity and onset timing. PATIENTS AND METHODS:This case-control study included 560 pregnant women (280 with PE and 280 normotensive controls) from Zahedan, southeastern Iran. Genotyping was performed using PCR-RFLP. Associations were assessed using logistic regression to calculate odds ratios (ORs) with 95% confidence intervals (CIs). RESULTS:For rs9514828, the CT and TT genotypes were associated with increased PE risk (OR = 1.81, p = 0.011; OR = 2.13, p = 0.002). For rs1041569, the AT and TT genotypes were also associated with increased risk (OR = 1.48, p = 0.033; OR = 1.68, p = 0.037). Haplotype analysis revealed that the C-A haplotype was protective (OR = 0.69, p = 0.003), while the T-T haplotype showed similar protection (OR = 0.69, p = 0.003). All genotype distributions were in Hardy-Weinberg equilibrium in the control group. CONCLUSION:BAFF polymorphisms are significantly associated with PE susceptibility in the Iranian population and may serve as potential biomarkers for PE risk assessment.
INTRODUCTION:The paradigm of personalized medicine is rapidly shifting from traditional, evidence-based genomics to advanced, data-driven ecosystems. Understanding this transition, supported by the computational tools of precision medicine, is critical for managing high-dimensional biomedical data. AREAS COVERED:Synthesizing current biomedical and medical informatics literature, this narrative review explores the historical milestones of personalized medicine, including the Human Genome Project and next-generation sequencing. It critically examines the contemporary integration of multi-omics data, HL7 FHIR interoperability standards, and the investigational applications of Large Language Models (LLMs) in clinical decision support. Furthermore, we analyze the shift from traditional machine learning to Graph Neural Networks (GNNs), such as node2vec and DeepWalk, for decoding complex biological network topologies. COMMENTARY:The translation of the future personalized medicine vision into broad clinical practice relies on emerging frameworks like Clinical Digital Twins for in silico therapeutic simulations. However, transitioning these technologies from investigational stages to routine practice - and achieving equitable global health outcomes - requires rigorously addressing algorithmic bias, socioeconomic disparities, and breaking institutional data silos through privacy-preserving architectures like Federated Learning. Biomedical informatics acts as the primary catalyst in safely bridging raw genomic data with actionable clinical foresight.
AIMS:The rapid integration of genetics into clinical care and research has outpaced the supply of genetic professionals, creating persistent challenges in patient education, communication, and clinical follow-up. Chatbotsrepresent a scalable tool to address these gaps by supporting patient education, risk assessment, informed consent, return of results, and family communication. METHODS:We conducted a scoping review of the literature on chatbots applied to genetics and genomics based on a PubMed search of the terms "chatbot*" AND "genetic" conducted on 26 January 2025. RESULTS:From 35 eligible publications, we identified five primary applications of chatbots in genetics: (1) pre-testing and pre-counseling education; (2) family health history collection for risk assessment and triage; (3) informed consent for clinical or research testing; (4) facilitation of family communication and cascade testing; and (5) disease management. Reported benefits included improved patient knowledge, high usability and satisfaction, convenience, and the potential to streamline workflows and broaden access to services. CONCLUSIONS:While promising, challenges remain in ensuring content accuracy, addressing privacy and ethical concerns, and ensuring access and utilization. Future development should focus on culturally adaptive, user-centered design and rigorous evaluation to ensure safe, equitable, and effective integration of chatbots into clinical genetics and genomic research.
INTRODUCTION:Chronic diseases remain leading contributors to global mortality, yet digital biomarkers offer transformative potential for personalized management. This systematic review evaluates the clinical performance of digital biomarkers across multiple chronic disease areas and the ethical, privacy, and equity barriers to their adoption. METHODS:Following PRISMA guidelines, we searched PubMed (January 2010-August 2024) for studies evaluating digital biomarkers in chronic disease management. English-language, peer-reviewed studies reporting original empirical data were included; reviews and protocols were retained as contextual references. Study quality was assessed qualitatively given heterogeneity in designs and outcome metrics, precluding meta-analysis. RESULTS:Sixty-eight studies (33 primary empirical, 35 contextual) were included, spanning cardiovascular disease, diabetes, respiratory conditions, neurological disorders, and mental health. Key findings included 100% atrial fibrillation detection sensitivity (KardiaMobile), 92-94% seizure detection sensitivity (Embrace Watch), significant HbA1c improvement with smart insulin pens (p = 0.006), and 87% versus 74% CPAP adherence with smart monitoring. However, device costs ($80-$1,690), regulatory gaps, limited population diversity in validation studies, and poor data interoperability hinder equitable adoption. CONCLUSIONS:Digital biomarkers demonstrate strong clinical utility but require harmonized regulatory standards, diverse-population validation, algorithmic transparency, and expanded reimbursement to achieve equitable, personalized chronic disease management. Evidence remains preliminary, necessitating large-scale, multi-site trials.
BACKGROUND:Measurable residual disease (MRD) is a key prognostic factor in acute myeloid leukemia (AML). The Measurable residual disease Partnership and Alliance in Acute Myeloid Leukemia Clinical Treatment (MPAACT) Consortium aims to accelerate AML therapy development by validating MRD as an early clinical trial endpoint within the regulatory framework. This blinded pilot study evaluated commercial next-generation sequencing (NGS) MRD assays to identify those meeting technical, regulatory, and quality criteria for development. METHODS:Of 19 vendors meeting eligibility criteria, eight responded and seven assays from six vendors proceeded to blinded testing. Using 45 contrived DNA samples with variant allele frequencies (VAFs) from 0.1% to 15%, MPAACT evaluated sensitivity, specificity, reproducibility, accuracy, and dynamic range at 50 ng and 200 ng DNA inputs from vendor-submitted raw and annotated data. RESULTS:Two assays were eliminated due to inadequate variant detection or gene coverage. Among the remaining five, sensitivity varied and none reliably detected VAFs <0.5%. Increased DNA input improved low-VAF detection but elevated false positives. Assays 3, 4, and 7 showed the strongest performance; Assay 7 had the lowest detection limit but higher false positives. CONCLUSIONS:Commercial NGS assay performance varied widely, particularly at low VAFs. Selected assays merit further optimization for MRD assessments.
OBJECTIVE:This study aimed to investigate the expression levels of microRNA-550a-5p (miR-550a-5p) in patients with spinal metastases from non-small cell lung cancer (NSCLC) and to explore its clinical significance. METHODS:Serum miR‑550a‑5p levels were measured by RT‑qPCR in NSCLC patients with spinal metastasis, those without metastasis, and healthy controls. The correlation between miR‑550a‑5p and SPECT Soloway grading was assessed via Spearman correlation analysis. Univariate and multivariate logistic regression analyses were performed to identify risk factors for spinal metastasis, while ROC analysis was used to evaluate the diagnostic value of miR‑550a‑5p. RESULTS:Both the non-spine metastasis and spine metastasis groups exhibited higher miR-550a-5p expression than the control group, with the highest expression observed in the spine metastasis group. Univariate analysis showed that serum miR-550a-5p expression and Tumor-Node-Metastasis stage were associated with spinal metastasis, while multivariate analysis confirmed miR-550a-5p as an independent influencing factor. ROC analysis demonstrated that miR-550a-5p had good discriminatory ability between NSCLC patients with and without spinal metastasis. miR-550a-5p expression showed a significant positive correlation with Soloway grading of SPECT bone imaging. CONCLUSION:miR-550a-5p is upregulated in NSCLC patients with spinal metastases and may serve as a molecular marker for diagnosing spinal metastases and assessing clinical severity.
Multiple sclerosis (MS) is a complex neurological disorder with inflammation, demyelination, and neurodegeneration in the CNS. Disease-modifying therapies (DMTs) exist, but their efficacy is limited by MS's varied nature, highlighting the need for personalized treatments. From January 2009 to March 2025, a literature search across PubMed, Scopus, Web of Science, and Google Scholar identified over 200 multiple sclerosis (MS) genetic loci. HLA-DRB1*15:01 is a key genetic risk factor, alongside significant environmental contributors such as Epstein-Barr virus infection, smoking, and vitamin D deficiency. Epigenetic modifications, such as DNA methylation and non-coding RNAs, mediate the interaction between genetic predisposition and environmental factors. Altered methylation patterns in genes like FOXP3 and IL-10 disrupt immune regulation, exacerbating disease progression. Emerging biomarkers such as CHI3L1, miR-155, and IL-10 methylation patterns have shown potential for diagnosis and prognosis. Multi-omics strategies and artificial intelligence (AI) offer innovative solutions for integrating these biomarkers into clinical practice. Personalized therapy options, such as low-dose IL-2 and JAK-STAT pathway inhibitors, highlight the potential of precision medicine in enhancing treatment outcomes. This synthesis identifies inconsistencies and methodological limitations in current research, proposing a roadmap for pathway-specific therapies based on integrated genetic-epigenetic profiling.
BACKGROUND:Fibrosis is a systemic disorder driven by inflammation, immune imbalance, and extracellular matrix remodeling. Pirfenidone (PFD) and nintedanib (NTB), approved for idiopathic pulmonary fibrosis, may exert broader antifibrotic effects by modulating conserved fibrotic signaling pathways across multiple organs, including the heart, pancreas, lungs, liver, skin, intestine, bone marrow, eyes, and kidneys. METHODS:Organ-specific fibrosis-related genes were retrieved from GeneCards, while drug-target data for PFD and NTB were collected from CTD, STITCH, KEGG, BindingDB, and TargetNet. Overlapping targets were subjected to pathway enrichment analysis using KEGG, Reactome, and WikiPathways. RESULTS:72 protein targets for PFD and 27 for NTB were identified after removal of duplicate targets. PFD showed common targets with cardiac-20, pancreatic-24, lung-38, liver-34, skin-29, intestine-23, bone marrow-43, eyes-18, and kidney fibrosis-30, while NTB showed 2, 6, 13, 6, 8, 5, 16, 4, and 3 targets, respectively. PFD regulates immune and fibrotic pathways beyond the lung (IL-17, TNF, HIF-1, TGF-β, and matrix metalloproteinase activation), which are relevant to hepatic, renal, and hematopoietic fibrosis. NTB modulated PI3K-Akt, MAPK, and Ras signaling in bone marrow, skin, and intestinal fibrosis. CONCLUSIONS:These findings suggest that PFD and NTB target key molecular pathways involved in multi-organ fibrosis, supporting their repurposing for fibrotic diseases beyond the lung.
INTRODUCTION:The functional single nucleotide polymorphism (SNP) rs767649 in the miR-155 gene has been linked to other neurological disorders, but its association with sporadic Parkinson's disease (PD) remains unclear. METHODS:The rs767649 SNP was genotyped via TaqMan assay. Serum miR-155 levels were measured by RT-qPCR. Statistical analyses included ROC analysis for assessing diagnostic value, Pearson correlation analysis with clinical scores (UPDRS-III, H-Y staging, MoCA), and logistic regression for identifying risk factors of PD. RESULTS:The miR-155 rs767649 A allele served as a protective factor against PD, with AA homozygotes showing the lowest risk. The TT genotype was associated with elevated serum miR‑155, greater motor impairment (UPDRS‑III, H‑Y stage), and reduced cognitive function (MoCA) in PD patients when compared to TA or AA carriers. In PD patients, elevated serum miR-155 levels correlated with disease severity, distinguished patients from healthy controls, and emerged as an independent risk factor for PD. CONCLUSION:The miR-155 rs767649 polymorphism might affect PD susceptibility, and its A allele potentially exerted a protective effect against PD in Han Chinese population. Elevated miR-155 levels appear to be correlated with disease severity and may be an independent risk factor, suggesting its potential as a biomarker for PD diagnosis.
AIMS:The Melanocortin-4 receptor is a key regulator of energy homeostasis, and loss-of-function variants are the most common cause of monogenic obesity. This study aimed to characterize MC4R genetic variants and evaluate their potential impact on receptor function and interaction with Setmelanotide. MATERIALS AND METHODS:An in silico approach was applied to analyze MC4R single nucleotide polymorphisms (SNPs). Variants were retrieved from ClinVar and dbSNP and evaluated using PredictSNP and complementary tools to assess evolutionary conservation, protein stability, and structural and functional effects. Structural modeling and interaction analyses were performed to investigate receptor-ligand binding. RESULTS:Among 84 ClinVar variants, 15 were predicted as deleterious, while 10 of 350 dbSNP variants showed similar predictions. A total of 25 variants were further analyzed, revealing effects on protein stability, conserved residues, and structural conformation. Interaction modeling identified key amino acids involved in Setmelanotide binding and suggested that specific variants may influence receptor-agonist interactions. CONCLUSIONS:These findings provide insights into the structural and functional consequences of MC4R variants and highlight their potential relevance for pharmacogenomic studies, supporting future experimental validation in MC4R-related obesity.
BACKGROUND:Sepsis-induced acute kidney injury (SI-AKI) is a prevalent critical complication characterized by delayed early diagnosis, inadequate prognosis evaluation, and unclear pathogenesis. MicroRNAs (miRNAs) are promising SI-AKI biomarkers, yet their regulatory roles remain undefined. OBJECTIVE:To clarify the diagnostic value and functional mechanism of miR-132-3p in SI-AKI. METHODS:208 sepsis patients were divided into SI-AKI (n = 108) and non-SI-AKI (n = 100) groups. Plasma/urine miR-132-3p levels were measured via qRT-PCR, with ROC curves and Logistic regression for diagnostic and risk factor analysis; KM curves and COX regression assessed 28-day prognosis. HK-2 cells were transfected with miR-132-3p mimics/inhibitors to assess cell proliferation, apoptosis, and inflammation; StarBase and dual-luciferase assays were used to verify target genes. RESULTS:MiR-132-3p was significantly upregulated in patients with SI-AKI and served as an independent risk factor with diagnostic and prognostic value. In vitro, it inhibited HK-2 cell proliferation, promoted apoptosis and inflammation, and mediated SI-AKI progression by targeting ERBIN. CONCLUSION:miR-132-3p is a potential diagnostic/prognostic biomarker for SI-AKI, and regulates renal cell function via ERBIN to participate in SI-AKI pathogenesis.
The expansion of precision medicine has shifted toward individualized care tailored to a patient's genetic profile. While randomized controlled trials (RCTs) remain the gold standard for establishing efficacy, they often struggle to reflect the phenotypic diversity of patients in routine clinical practice. This paper explores the role of Real-World Data (RWD) and Real-World Evidence (RWE) in bridging this translational gap. A structured literature search identified peer-reviewed articles examining RWE applications in identifying rare genetic targets, informing clinical trial design, and supporting U.S. Food and Drug Administration (FDA) regulatory decisions. This review synthesizes recent regulatory advances through early 2026, including frameworks supporting the use of aggregated RWD that expand large-scale, multi-institutional evidence generation. RWE provides a scalable mechanism for identifying rare genetic variants and validating biomarker-driven therapies across heterogeneous patient populations while enabling longitudinal assessment of natural disease history and treatment safety. Operational successes in oncology, transplant medicine, and rare diseases demonstrate regulatory acceptance of RWE alongside critical challenges in data standardization, interoperability, and bias mitigation through causal inference frameworks, including target trial emulation. RWD and RWE serve as necessary complements to RCTs, providing the hybrid evidentiary framework needed to realize precision medicine's potential.
PURPOSE:The Surviving Sepsis Campaign (SSC) guidelines recommend norepinephrine to achieve a mean arterial pressure (MAP) target of ≥65 mmHg. While norepinephrine counteracts decreased vascularresistance and improves tissue perfusion, high doses may induce excessivevasoconstriction, compromising perfusion and leading to organ failure. Thisreview examines whether microcirculatory resuscitation should be prioritizedover macrocirculatory MAP targets in norepinephrine therapy. METHODS:A narrative review was conductedusing PubMed, Scopus, and Science Direct (2009-2025). We included clinicalstudies and reviews on adults with septic shock, focusing on norepinephrinedosing and its effects on MAP and tissue perfusion. RESULTS:Evidence suggests that a fixed MAP target of ≥65 mmHg may not universally optimize outcomes, as tissue perfusion does not consistently correlate with MAP. Advanced monitoring of microcirculation helps correct microcirculatory stagnant hypoxia and tissue perfusion. Achieving the minimum required tissue perfusion through perfusion-guided monitoring allows physicians and nurses to determine the optimal norepinephrine dosage and ideal MAP for each patient, based on their clinical condition and medical history. CONCLUSION:Consequently, optimizing microcirculation using bedside monitoring technologies may replace the rigid MAP target of ≥65 mmHg. Integration of microcirculatory monitoring into clinical practice represents a paradigm shift toward personalized hemodynamic management.
OBJECTIVE:Telecommunication-based cross-sectional study aimed to assess prevalence and health-related correlates of pharmacogenetic (PGx) drug administration. METHODS:Online survey population sample (n = 2149) was initiated by SMS invitations to random adults. Questionnaire included questions on demographics, health, and clinical pharmacology. PGx drugs were identified using ClinPGx/PharmGKB database. Combined number of drug-gene interactions involving CYP2C19, CYP2C9, CYP2D6, and/or UGT1A1 was referred to as Z-score. Subgroup of respondents was genotyped for CYP2C19, CYP2C9, CYP2D6, and UGT1A1 variants. RESULTS:Nearly 70% of respondents were taking pharmacotherapy. Susceptibility to adverse drug reactions (ADRs) positively correlated with PGx drug intake (p = 0.03454, n = 2149). Susceptibility to ADRs in genotyped group (n = 83) correlated with carriership of loss-of-function variants of UGT1A1 (7TA/7TA, r = 0.2355, p = 0.03796), CYP2C19 (*2/*17, r = 0.3317, p = 0.003012), and combined carriership of loss-of-function variants of four study genes (r = 0.2291, p = 0.04361). One, two, and three actionable drug-gene interactions were present in 15.7%, 10.8%, and 1.2% of cases, respectively. CONCLUSIONS:Carriership of loss-of-function variants of study pharmacogenes was associated with increased susceptibility of participants to ADRs. Further research is needed to elucidate clinical relevance of PGx burden at population level.
