Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues

Human Genomics, Journal Year: 2025, Volume and Issue: 19(1)

Published: Jan. 31, 2025

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

Language: Английский

---

Genetic Profiling of Acute and Chronic Leukemia via Next-Generation Sequencing: Current Insights and Future Perspectives

Hematology Reports, Journal Year: 2025, Volume and Issue: 17(2), P. 18 - 18

Published: March 28, 2025

Leukemia is a heterogeneous group of hematologic malignancies characterized by distinct genetic and molecular abnormalities. Advancements in genomic technologies have significantly transformed the diagnosis, prognosis, treatment strategies for leukemia. Among these, next-generation sequencing (NGS) has emerged as powerful tool, enabling high-resolution profiling that surpasses conventional diagnostic approaches. By providing comprehensive insights into mutations, clonal evolution, resistance mechanisms, NGS revolutionized precision medicine leukemia management. Despite its transformative potential, clinical integration presents challenges, including data interpretation complexities, standardization issues, cost considerations. However, continuous advancements platforms bioinformatics pipelines are enhancing reliability accessibility routine practice. The expanding role paving way improved risk stratification, targeted therapies, real-time disease monitoring, ultimately leading to better patient outcomes. This review highlights impact on research applications, discussing advantages over traditional techniques, key approaches, emerging challenges. As oncology continues evolve, expected play an increasingly central diagnosis management leukemia, driving innovations personalized therapeutic interventions.

Language: Английский

---

A novel hybrid feature fusion approach using handcrafted features with transfer learning model for enhanced skin cancer classification

Computers in Biology and Medicine, Journal Year: 2025, Volume and Issue: 190, P. 110104 - 110104

Published: April 2, 2025

Language: Английский

---

Deep Learning-Based Detection and Classification of Acute Lymphoblastic Leukemia with Explainable AI Techniques

Array, Journal Year: 2025, Volume and Issue: unknown, P. 100397 - 100397

Published: April 1, 2025

Language: Английский

---

New Era of Intelligent Medicine: Future Scope and Challenges

2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), Journal Year: 2024, Volume and Issue: unknown, P. 1 - 6

Published: March 14, 2024

The integration of Artificial Intelligence (AI) into the global healthcare landscape has undergone a remarkable transformation, presenting unprecedented opportunities and challenges. This review explores transformative impact in health care, examining current applications, growth projections, projected compound annual rate (CAGR) for AI market is 37%, reaching $188 billion by 2030. AI's potential to reduce drug development costs prevent medication dosing errors evident. From early models like CASNET contemporary Deep Learning, revolutionized medical diagnostics. envisions future with accessible through chatbots telemedicine, data-driven platforms personalized treatment, data cards. Technological advancements, including increased computational power cloud storage, play pivotal role, challenges managing vast heterogeneous data. concludes addressing dynamic must overcome impact.

Language: Английский

---

A Comprehensive Assessment and Classification of Acute Lymphocytic Leukemia

Mathematical and Computational Applications, Journal Year: 2024, Volume and Issue: 29(3), P. 45 - 45

Published: June 9, 2024

Leukemia is a form of blood cancer that results in an increase the number white cells body. The correct identification leukemia at any stage essential. current traditional approaches rely mainly on field experts’ knowledge, which time consuming. A lengthy testing interval combined with inadequate comprehension could harm person’s health. In this situation, automated delivers more reliable and accurate diagnostic information. To effectively diagnose acute lymphoblastic from smear pictures, new strategy based image analysis techniques machine learning composite approach were constructed experiment. process separated into two parts: detection identification. was utilized to identify images. Finally, four widely recognized algorithms used specific type leukemia. It discovered Support Vector Machine (SVM) provides highest accuracy scenario. boost performance, deep model Resnet50 hybridized model. it revealed achieved 99.9% accuracy.

Language: Английский

---

Acute Lymphoblastic Leukemia Detection Employing Deep Learning and Transfer Learning Techniques

2022 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI), Journal Year: 2024, Volume and Issue: unknown, P. 1 - 6

Published: May 9, 2024

Language: Английский

---

A retrospective case-control study for Clinical Validation of mutated ZNF208 as a novel biomarker of fatal blast crisis in Chronic Myeloid Leukemia

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: March 15, 2024

Abstract The hallmark of Chronic Myeloid Leukemia (CML) is Philadelphia chromosome t(9:22), which leads to formation BCR-ABL1 fusion oncogene. induces genetic instability, causing the progression chronic myeloid leukemia from manageable Phase (CP-CML) accelerated phase (AP-CML) and ultimately lethal blast crisis (BC-CML). precise mechanism responsible for CML are not well comprehended, there a lack specific molecular biomarkers advanced CML. Mutations in transcription factors (TFs) have significant role cancer initiation, relapses, invasion, metastasis, resistance anti-cancer drugs. Recently, our group reported association novel factor, ZNF208, with was dire need clinical validation this biomarker. Therefore, aim study clinically validate mutated ZNF208 as biomarker larger cohort AP- BC-CML patients using control-case studies. A total 73 (N=73) King Saud University Medical City Riyadh Abdulaziz National Guard Hospital, Al-Ahsa, Saudi Arabia were enrolled (2020-2023), experimental (cases) consisting AP-CML (n=20) (n=12). controls consisted age/sex matched CP-CML (n=41). approved by Research Ethics Committees participating institutes all provided informed consent study. Clinical evaluations conducted according guidelines established European LeukemiaNet 2020. Targeted resequencing ZNF 208 employed Illumina NextSeq500 instrument (Illumina, San Diego, CA, USA) mutations confirmed Sanger sequencing. Both next generation sequencing identified missense mutation (c.64G>A) ZNF208. 56 (93.3) and12 (100) CP-, respectively, while none (0%) or healthy genomic databases (p=0.0001). studies show that very AP-and patients. other such proteins may cause carcinogenesis interacting KAP-1 repressor silence many target genes thus prove be drug targets well. we recommend carrying out prospective trials further its utilization decision, investigating pathogenesis investigate potential Simple Summary type blood caused oncogene, leading instability changes. This results advancement (CP) an (AP) finally (BC). development known, dearth dependable shared indicators. Transcription class molecules that, when altered, significantly contribute cancer, including has been factor gene associated BC-CML. Here, carried targeted resequencing. detected 0 (0%), respectively (p=0.0001) demonstrating high specificity shows progression. We

Language: Английский

---

Predictive Healthcare Analytics

Advances in medical technologies and clinical practice book series, Journal Year: 2024, Volume and Issue: unknown, P. 171 - 199

Published: June 28, 2024

The integration of digital twin technology with healthcare systems promises to revolutionize clinical decision-making and patient outcomes in Healthcare 6.0. This chapter explores predictive analytics' role preventive care, resource optimization, patient-centered outcomes. It examines theoretical foundations, methodologies like machine learning, real-world applications, highlighting maintenance risk stratification. Ethical considerations regulatory compliance are emphasized, a look at future trends. Ultimately, the serves as guide for stakeholders navigating analytics 6.0, advocating proactive, data-driven improved

Language: Английский

---