An integrative analysis of consortium-based multi-omics QTL and genome-wide association study data uncovers new biomarkers for lung cancer DOI Open Access
Yanru Wang, Angela Yee‐Moon Wang, Ning Xie

et al.

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

Published: Dec. 16, 2024

Abstract The role of molecular traits (e.g., gene expression and protein abundance) in the occurrence, development, prognosis lung cancer has been extensively studied. However, biomarkers other layers connections among various that influence risk remain largely underexplored. We conducted first comprehensive assessment associations between (i.e., DNA methylation, expression, metabolite) through epigenome-wide association study (EWAS), transcriptome-wide (TWAS), proteome-wide (PWAS) metabolome-wide (MWAS), then we synthesized all omics to reveal potential regulatory mechanisms across layers. Our analysis identified 61 CpG sites, 62 genes, 6 proteins, 5 metabolites, yielding 123 novel biomarkers. These highlighted 90 relevant genes for cancer, 83 them were established our study. Multi-omics integrative revealed 12 these overlapped layers, suggesting cross-omics interactions. Moreover, 106 cross-layer pathways, indicating cell proliferation, differentiation, immunity, protein-catalyzed metabolite reaction interact risk. Further subgroup analyses biomarker distributions differ patient subgroups. To share signals different with community, released a free online platform, LungCancer-xWAS, which can be accessed at http://bigdata.njmu.edu.cn/LungCancer-xWAS/ . findings underscore importance xWAS integrating types quantitative trait loci (xQTL) data genome-wide (GWAS) deepen understanding pathophysiology, may provide valuable insights into therapeutic targets disease.

Language: Английский

Plant secondary metabolites against biotic stresses for sustainable crop protection DOI
Tanzim Jahan, Md. Nurul Huda, Kaixuan Zhang

et al.

Biotechnology Advances, Journal Year: 2025, Volume and Issue: unknown, P. 108520 - 108520

Published: Jan. 1, 2025

Language: Английский

Citations

2
Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues DOI Creative Commons

Robel Alemu,

Nigussie Tadesse Sharew,

Yodit Y. Arsano

et al.

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

Citations

2
Spatially resolved mapping of cells associated with human complex traits DOI Creative Commons

Liyang Song,

Wenhao Chen,

Junren Hou

et al.

Nature, Journal Year: 2025, Volume and Issue: unknown

Published: March 19, 2025

Depicting spatial distributions of disease-relevant cells is crucial for understanding disease pathology1,2. Here we present genetically informed mapping complex traits (gsMap), a method that integrates transcriptomics data with summary statistics from genome-wide association studies to map human traits, including diseases, in spatially resolved manner. Using embryonic datasets covering 25 organs, benchmarked gsMap through simulation and by corroborating known trait-associated or regions various organs. Applying brain data, reveal the distribution glutamatergic neurons associated schizophrenia more closely resembles cognitive than mood such as depression. The schizophrenia-associated were distributed near dorsal hippocampus, upregulated expression calcium signalling regulation genes, whereas depression-associated deep medial prefrontal cortex, neuroplasticity psychiatric drug target genes. Our study provides demonstrates gain biological insights (such trait-relevant related signature genes) these maps. Integration enables diseases other traits.

Language: Английский

Citations

1
Identifying therapeutic target genes for migraine by systematic druggable genome-wide Mendelian randomization DOI Creative Commons
Chengcheng Zhang,

Yiwei He,

Lu Liu

et al.

The Journal of Headache and Pain, Journal Year: 2024, Volume and Issue: 25(1)

Published: June 12, 2024

Currently, the treatment and prevention of migraine remain highly challenging. Mendelian randomization (MR) has been widely used to explore novel therapeutic targets. Therefore, we performed a systematic druggable genome-wide MR potential targets for migraine.

Language: Английский

Citations

5
Decoding the Therapeutic Target SVEP1: Harnessing Molecular Trait GWASs to Unravel Mechanisms of Human Disease DOI
Jared S. Elenbaas, Paul C. Lee, Ved Patel

et al.

The Annual Review of Pharmacology and Toxicology, Journal Year: 2025, Volume and Issue: 65(1), P. 131 - 148

Published: Jan. 23, 2025

Although human genetics has substantial potential to illuminate novel disease pathways and facilitate drug development, identifying causal variants deciphering their mechanisms remain challenging. We believe these challenges can be addressed, in part, by creatively repurposing the results of molecular trait genome-wide association studies (GWASs). In this review, we introduce techniques related GWASs unconventionally apply them understanding SVEP1, a coronary artery risk locus. Our analyses highlight SVEP1's link cardiometabolic glaucoma, as well surprising discovery SVEP1 first known physiologic ligand for PEAR1, critical receptor governing platelet reactivity. further employ dissect interactions between Ang/Tie pathway, with therapeutic implications constellation diseases. This review underscores guide unravel complexities health demonstrating an integrative approach that grounds mechanistic research biology.

Language: Английский

Citations

0
Novel drug targets for delirium based on genetic causality DOI

Shuhua Zhu,

Xiaofeng Ding,

Jacqueline Bo

et al.

Journal of Affective Disorders, Journal Year: 2025, Volume and Issue: 378, P. 128 - 137

Published: Feb. 27, 2025

Language: Английский

Citations

0
A computational framework for extracting biological insights from SRA cancer data DOI Creative Commons

Paul Anderson Souza Guimarães,

Maria Gabriela Reis Carvalho,

Jerônimo Conceição Ruiz

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 8, 2025

The integration of sequenced samples and clinical data from independent yet related studies public domain databases, such as Sequence Read Archive (SRA), has the potential to increase sample sizes enhance statistical power needed for more precise bioinformatic analysis. Data mining grouping are starting points in this process still present several challenges, including presence structured unstructured data, missing deposited varying experimental conditions techniques applied across studies. Designed address main challenges biomarkers research, proposed methodology employs a computational approach integrating relational database construction, text mining, natural language processing, network analysis, search by Pubmed publications, combining MeSH, TTD WordNet identify groups with same characteristics. As result, it identifies illustrates relationships among collections, aiming discover cancer biomarkers. In colorectal (CRC) acute lymphoblastic leukemia (ALL) case studies, effectively navigates SRA metadata, retrieving, extracting, data. It highlights significant connections between patient revealing important biological insights. study grouped 2,737 3,655 into comparison groups, demonstrating method's identifying aiding biomarker discovery.

Language: Английский

Citations

0
Exploring Bidens Genomics: Evolutionary Insights and Applications DOI

Wajiha Zaka Ansari,

Hamid Mukhtar, Haris Ahmed Khan

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Receptor Pharmacogenomics: Deciphering Genetic Influence on Drug Response DOI Open Access
Sorina Andreea Anghel, Cristina-Elena Dinu-Pîrvu,

Mihaela-Andreea Costache

et al.

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(17), P. 9371 - 9371

Published: Aug. 29, 2024

The paradigm “one drug fits all” or dose will soon be challenged by pharmacogenetics research and application. Drug response—efficacy safety—depends on interindividual variability. current clinical practice does not include genetic screening as a routine procedure account for variation. Patients with the same illness receive treatment, yielding different responses. Integrating pharmacogenomics in therapy would provide critical information about how patient respond to certain drug. Worldwide, great efforts are being made achieve personalized therapy-based approach. Nevertheless, global harmonized guideline is still needed. Plasma membrane proteins, like receptor tyrosine kinase (RTK) G protein-coupled receptors (GPCRs), ubiquitously expressed, involved diverse array of physiopathological processes. Over 30% drugs approved FDA target GPCRs, reflecting importance assessing variability among individuals who treated these drugs. Pharmacogenomics transmembrane protein dynamic field profound implications precision medicine. Understanding variations provides framework optimizing therapies, minimizing adverse reactions, advancing healthcare.

Language: Английский

Citations

2
SMR-Portal: an online platform for integrative analysis of GWAS and xQTL data to identify complex trait genes DOI
Yuanjun Guo, Tao Xu, Chuansong Zhan

et al.

Nature Methods, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 2, 2024

Language: Английский

Citations

2