Causal association between 637 human metabolites and ovarian cancer: A mendelian randomization study Original paper
Researched by:
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Divine Aleru
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Divine Aleru
Read MoreI am a biochemist with a deep curiosity for the human microbiome and how it shapes human health, and I enjoy making microbiome science more accessible through research and writing. With 2 years experience in microbiome research, I have curated microbiome studies, analyzed microbial signatures, and now focus on interventions as a Microbiome Signatures and Interventions Research Coordinator.
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Women’s Health
Women’s Health
Women’s health, a vital aspect of medical science, encompasses various conditions unique to women’s physiological makeup. Historically, women were often excluded from clinical research, leading to a gap in understanding the intricacies of women’s health needs. However, recent advancements have highlighted the significant role that the microbiome plays in these conditions, offering new insights and potential therapies. MicrobiomeSignatures.com is at the forefront of exploring the microbiome signature of each of these conditions to unravel the etiology of these diseases and develop targeted microbiome therapies.
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Ovarian Cancer
Ovarian Cancer
OverviewOvarian cancer (OC) remains one of the most deadly cancers affecting women, with an estimated 320,000 new cases diagnosed worldwide annually, making it the eighth most commonly diagnosed cancer. It also accounts for over 200,000 deaths each year, reflecting its high lethality. The disease is often diagnosed at advanced stages (stage III and IV) due […]
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Divine Aleru
Read More
Researched by:
-
Divine Aleru
ID
Divine Aleru
Read More
Microbiome Signatures identifies and validates condition-specific microbiome shifts and interventions to accelerate clinical translation. Our multidisciplinary team supports clinicians, researchers, and innovators in turning microbiome science into actionable medicine.
Divine Aleru
What was studied?
This study employed Mendelian randomization (MR) to assess causal associations between 637 human metabolites and ovarian cancer (OC). Researchers used data from the GWAS database to identify genetic variants associated with metabolites, applying this to a large ovarian cancer GWAS dataset. The goal was to determine the causal relationships between specific metabolites and the risk of developing OC, thereby revealing potential biomarkers for early diagnosis and treatment.
Who was studied?
The study utilized genetic data from European populations, focusing on GWAS datasets for both human metabolites and ovarian cancer. The metabolites were selected based on genetic loci associated with 637 metabolites, as identified in earlier genome-wide studies. The ovarian cancer dataset (encoded as ieu-b-4963) included over 199,000 samples, with outcomes specific to ovarian cancer subtypes, analyzed through MR techniques.
Most important findings
The MR analysis identified 31 metabolites with a significant causal relationship to OC. Among these, 9 metabolites passed additional tests for heterogeneity, pleiotropy, and causal direction. Notably, androsterone sulfate, propionylcarnitine, 5alpha-androstan-3beta-17beta-diol disulfate, and medium very-low-density lipoprotein (VLDL) were found to have a positive causal effect, promoting the development of OC. In contrast, metabolites like X-12,093, octanoylcarnitine, N2,N2-dimethylguanosine, and cis-4-decenoyl carnitine showed a negative association, suggesting protective effects against OC.
Key implications
These findings suggest that specific metabolites, especially lipids like VLDL and acylcarnitines, may play a crucial role in ovarian cancer development. Such metabolites could serve as potential biomarkers for early detection or therapeutic targets. While the study provides promising insights, it emphasizes the need for further clinical validation, particularly due to limitations like ethnic homogeneity in the dataset and the low statistical power associated with some metabolites.