Title: Human blood metabolites and gastric cancer: a Mendelian Randomization Analysis
Version: 1 Date: 24 Nov 2024
Reviewer's report:
This study uses Mendelian randomization (MR) to investigate the causal relationship between
circulating blood metabolites and gastric cancer (GC). The authors analyzed 486 blood
metabolites based on large-scale genome-wide association study (GWAS) data and validated
the robustness of their findings through various sensitivity analyses. Three metabolites were
identified to have significant associations with GC risk: 3-methyl-2-oxovalerate, piperine,
and phenylalanylphenylalanine. Elevated levels of 3-methyl-2-oxovalerate and piperine were
associated with an increased risk of GC, while phenylalanylphenylalanine appeared to have a
protective effect. This research provides new insights into the metabolic mechanisms underlying
GC and supports the potential use of these metabolites as biomarkers or therapeutic targets.
Strengths
Innovative Methodology: The study employs the MR approach, effectively mitigating the
influence of confounding factors and reverse causality that typically hinder observational
studies.
Comprehensive Data: The use of multiple GWAS datasets and validation studies enhances the
applicability and reliability of the results.
Rigorous Sensitivity Analyses: The evaluation of pleiotropy and heterogeneity confirms the
robustness of causal estimates.
Clinical Relevance: The identification of metabolite-GC associations provides promising
directions for early diagnosis and personalized treatment strategies.
Areas for Improvement
Background and Research Significance:The introduction does not sufficiently address how
metabolic dysregulation uniquely contributes to GC pathogenesis.
Suggestion: Supplement the discussion with details on specific metabolic pathways (e.g., amino
acid metabolism, xenobiotic metabolism) linked to GC and emphasize the study’s innovation
in addressing gaps in existing research.
Data Source and Interpretation:
The study predominantly relies on GWAS data from European populations, limiting the
generalizability to other ethnic groups. Excluding metabolites with insufficient SNPs may have
restricted the scope of new discoveries.
Suggestion: Elaborate on population-specific limitations and advocate for future studies
involving more diverse populations. Consider alternative methods to analyze understudied
metabolites.
Statistical Significance and Biological Mechanisms:While the statistical findings are robust, the
biological mechanisms linking metabolites to GC are not thoroughly explored.
Suggestion: Provide detailed discussions on potential mechanisms, such as how 3-methyl-2-
oxovalerate and piperine may influence GC risk through insulin resistance or mitochondrial
signaling. For phenylalanylphenylalanine, hypothesize its protective mechanisms.
Clinical Translation:
The discussion on clinical applications is brief, lacking analysis of challenges in translating
genetic findings into therapeutic interventions.
Suggestion: Address potential barriers such as metabolite stability and pharmacokinetics, and
outline future clinical research directions.
Language and Structure:
Some sections are overly technical, potentially hindering readability for non-specialist readers.
Suggestion: Simplify key expressions, particularly in discussions on MR assumptions and
sensitivity analyses, to improve accessibility.
Discussion Enhancements:
Strengthen the link between metabolic dysregulation and GC, highlighting the advantages of
MR methodology.
Discuss translational challenges in detail and propose future research directions.
Improve clarity by simplifying technical terms and enhancing the flow of information. Include
additional details on SNP selection and effect direction tests, supported by visual aids to better
convey the study design and methodology.
In summary, this study leverages the MR approach to validate the relationship between
metabolites and GC, providing important groundwork for research on GC pathogenesis and
therapeutic strategies. With refinements in the background, interpretation of findings, and
discussion sections, the manuscript holds strong potential for publication.
Title: Human blood metabolites and gastric cancer: a Mendelian Randomization Analysis
Version: 1 Date: 24 Nov 2024
Reviewer's report:
This study uses Mendelian randomization (MR) to investigate the causal relationship between
circulating blood metabolites and gastric cancer (GC). The authors analyzed 486 blood
metabolites based on large-scale genome-wide association study (GWAS) data and validated
the robustness of their findings through various sensitivity analyses. Three metabolites were
identified to have significant associations with GC risk: 3-methyl-2-oxovalerate, piperine,
and phenylalanylphenylalanine. Elevated levels of 3-methyl-2-oxovalerate and piperine were
associated with an increased risk of GC, while phenylalanylphenylalanine appeared to have a
protective effect. This research provides new insights into the metabolic mechanisms underlying
GC and supports the potential use of these metabolites as biomarkers or therapeutic targets.
Strengths
Innovative Methodology: The study employs the MR approach, effectively mitigating the
influence of confounding factors and reverse causality that typically hinder observational
studies.
Comprehensive Data: The use of multiple GWAS datasets and validation studies enhances the
applicability and reliability of the results.
Rigorous Sensitivity Analyses: The evaluation of pleiotropy and heterogeneity confirms the
robustness of causal estimates.
Clinical Relevance: The identification of metabolite-GC associations provides promising
directions for early diagnosis and personalized treatment strategies.
Areas for Improvement
Background and Research Significance:The introduction does not sufficiently address how
metabolic dysregulation uniquely contributes to GC pathogenesis.
Suggestion: Supplement the discussion with details on specific metabolic pathways (e.g., amino
acid metabolism, xenobiotic metabolism) linked to GC and emphasize the study’s innovation
in addressing gaps in existing research.
Data Source and Interpretation:
The study predominantly relies on GWAS data from European populations, limiting the
generalizability to other ethnic groups. Excluding metabolites with insufficient SNPs may have
restricted the scope of new discoveries.
Suggestion: Elaborate on population-specific limitations and advocate for future studies
involving more diverse populations. Consider alternative methods to analyze understudied
metabolites.
Statistical Significance and Biological Mechanisms:While the statistical findings are robust, the
biological mechanisms linking metabolites to GC are not thoroughly explored.
Suggestion: Provide detailed discussions on potential mechanisms, such as how 3-methyl-2-
oxovalerate and piperine may influence GC risk through insulin resistance or mitochondrial
signaling. For phenylalanylphenylalanine, hypothesize its protective mechanisms.
Clinical Translation:
The discussion on clinical applications is brief, lacking analysis of challenges in translating
genetic findings into therapeutic interventions.
Suggestion: Address potential barriers such as metabolite stability and pharmacokinetics, and
outline future clinical research directions.
Language and Structure:
Some sections are overly technical, potentially hindering readability for non-specialist readers.
Suggestion: Simplify key expressions, particularly in discussions on MR assumptions and
sensitivity analyses, to improve accessibility.
Discussion Enhancements:
Strengthen the link between metabolic dysregulation and GC, highlighting the advantages of
MR methodology.
Discuss translational challenges in detail and propose future research directions.
Improve clarity by simplifying technical terms and enhancing the flow of information. Include
additional details on SNP selection and effect direction tests, supported by visual aids to better
convey the study design and methodology.
In summary, this study leverages the MR approach to validate the relationship between
metabolites and GC, providing important groundwork for research on GC pathogenesis and
therapeutic strategies. With refinements in the background, interpretation of findings, and
discussion sections, the manuscript holds strong potential for publication.
Please review this paper.
user
Title: Human blood metabolites and gastric cancer: a Mendelian Randomization Analysis
Version: 1 Date: 24 Nov 2024
Reviewer's report:
This study uses Mendelian randomization (MR) to investigate the causal relationship between
circulating blood metabolites and gastric cancer (GC). The authors analyzed 486 blood
metabolites based on large-scale genome-wide association study (GWAS) data and validated
the robustness of their findings through various sensitivity analyses. Three metabolites were
identified to have significant associations with GC risk: 3-methyl-2-oxovalerate, piperine,
and phenylalanylphenylalanine. Elevated levels of 3-methyl-2-oxovalerate and piperine were
associated with an increased risk of GC, while phenylalanylphenylalanine appeared to have a
protective effect. This research provides new insights into the metabolic mechanisms underlying
GC and supports the potential use of these metabolites as biomarkers or therapeutic targets.
Strengths
Innovative Methodology: The study employs the MR approach, effectively mitigating the
influence of confounding factors and reverse causality that typically hinder observational
studies.
Comprehensive Data: The use of multiple GWAS datasets and validation studies enhances the
applicability and reliability of the results.
Rigorous Sensitivity Analyses: The evaluation of pleiotropy and heterogeneity confirms the
robustness of causal estimates.
Clinical Relevance: The identification of metabolite-GC associations provides promising
directions for early diagnosis and personalized treatment strategies.
Areas for Improvement
Background and Research Significance:The introduction does not sufficiently address how
metabolic dysregulation uniquely contributes to GC pathogenesis.
Suggestion: Supplement the discussion with details on specific metabolic pathways (e.g., amino
acid metabolism, xenobiotic metabolism) linked to GC and emphasize the study’s innovation
in addressing gaps in existing research.
Data Source and Interpretation:
The study predominantly relies on GWAS data from European populations, limiting the
generalizability to other ethnic groups. Excluding metabolites with insufficient SNPs may have
restricted the scope of new discoveries.
Suggestion: Elaborate on population-specific limitations and advocate for future studies
involving more diverse populations. Consider alternative methods to analyze understudied
metabolites.
Statistical Significance and Biological Mechanisms:While the statistical findings are robust, the
biological mechanisms linking metabolites to GC are not thoroughly explored.
Suggestion: Provide detailed discussions on potential mechanisms, such as how 3-methyl-2-
oxovalerate and piperine may influence GC risk through insulin resistance or mitochondrial
signaling. For phenylalanylphenylalanine, hypothesize its protective mechanisms.
Clinical Translation:
The discussion on clinical applications is brief, lacking analysis of challenges in translating
genetic findings into therapeutic interventions.
Suggestion: Address potential barriers such as metabolite stability and pharmacokinetics, and
outline future clinical research directions.
Language and Structure:
Some sections are overly technical, potentially hindering readability for non-specialist readers.
Suggestion: Simplify key expressions, particularly in discussions on MR assumptions and
sensitivity analyses, to improve accessibility.
Discussion Enhancements:
Strengthen the link between metabolic dysregulation and GC, highlighting the advantages of
MR methodology.
Discuss translational challenges in detail and propose future research directions.
Improve clarity by simplifying technical terms and enhancing the flow of information. Include
additional details on SNP selection and effect direction tests, supported by visual aids to better
convey the study design and methodology.
In summary, this study leverages the MR approach to validate the relationship between
metabolites and GC, providing important groundwork for research on GC pathogenesis and
therapeutic strategies. With refinements in the background, interpretation of findings, and
discussion sections, the manuscript holds strong potential for publication.
assistant