Associations between genetically predicted concentrations of plasma proteins and the risk of prostate cancer
These videos have been matched automatically. Contact us if they are not relevant.
These videos have been matched automatically. Contact us if they are not relevant.
View abstract on PubMed
Summary
This summary is machine-generated.This study identified specific proteins linked to prostate cancer (PCa) risk using proteome-wide Mendelian randomization. These findings highlight potential new biomarkers and therapeutic targets for PCa.
Area Of Science
- Genetics
- Proteomics
- Oncology
Background
- Prostate cancer (PCa) is a significant cause of cancer mortality in men.
- Understanding the proteomic factors influencing PCa risk is crucial for developing targeted therapies.
Purpose Of The Study
- To investigate associations between genetically predicted plasma protein concentrations and prostate cancer (PCa) risk.
- To identify novel protein biomarkers and potential therapeutic targets for PCa.
Main Methods
- A proteome-wide Mendelian randomization (MR) analysis of 4,364 proteins was conducted.
- Significant associations were identified, validated, and subjected to sensitivity analyses.
- Multivariable MR (MVMR) analysis was used to pinpoint key proteins.
Main Results
- Genetically predicted concentrations of 14 proteins showed positive associations with PCa risk (e.g., HCN1, ATG4B).
- Inverse associations were observed for ATG7, B2M, MSMB, and TMEM108.
- Replication and meta-analysis confirmed associations for MDH1, LSM1, and MSMB, with B2M and MSMB identified by MVMR.
Conclusions
- Genetic evidence refines the list of proteins associated with PCa risk.
- Identified proteins hold potential as PCa biomarkers or therapeutic targets.
- Further mechanistic and translational studies are warranted.
These videos have been matched automatically. Contact us if they are not relevant.
These videos have been matched automatically. Contact us if they are not relevant.
Related Concept Videos
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
Several factors can increase the risk of cancer in an individual. About 50% of cancer cases can be prevented by adopting a healthy lifestyle, regular exercise, eating healthy, and following a modest cancer prevention diet. Epidemiological studies have consistently shown that populations with vegetable and fruit-rich diets have reduced the incidence of cancer. On the other hand, populations who have a diet rich in animal fat, red meat, junk food, or high calories are predisposed to cancer.
Some...
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...