Lipidome changes due to improved dietary fat quality inform cardiometabolic risk reduction and precision nutrition.
Eichelmann F, Prada M, Sellem L, Jackson KG, Salas Salvadó J, Razquin Burillo C, Estruch R, Friedén M, Rosqvist F, Risérus U, Rexrode KM, Guasch-Ferré M, Sun Q, Willett WC, Martinez-Gonzalez MA, Lovegrove JA, Hu FB, Schulze MB, Wittenbecher C
- DOI
- 10.1038/s41591-024-03124-1
- Record issued
- 2026-08-16
- Engine
- 7.39.0
- Exported
- 2026-09-21
Prepared by Alpha1. This document is confidential: it is intended for the recipient it was shared with and must not be redistributed. The live record at alpha1science.com/verify/83ab8286-b0ea-43d0-b313-52c5b3ed02f3 is authoritative.
How this rating was calculated
- IntegrityIntegrity concern ×5−2.5★
- ClaimsEfficacy rests on an unvalidated surrogate endpoint−0.5★
- ClaimsTreatment effect not shown to be clinically meaningful−0.5★
- CitationsUnresolved reference−0.25★
- LinksDead data/code link−0.25★
- 01Efficacy rests on an unvalidated surrogate endpoint
The primary efficacy claim is based on a lipidomics-derived score (MLS/rMLS) as a surrogate for cardiometabolic risk reduction. The paper does not demonstrate target engagement at the tested dose (i.e., no PK/PD or dose-exposure relationship for the lipid changes) and does not cite validated evidence linking the specific lipidomic changes to clinical outcomes. The surrogate is a composite of lipid concentrations, and the claim of reduced CVD and T2D risk is inferred from observational associations, not from a validated surrogate-to-clinical-outcome link.
“In the EPIC-Potsdam cohort, a difference in the MLS, reflecting better dietary fat quality, was associated with a significant reduction in the incidence of cardiovascular disease (−32%; 95% confidence interval (95% CI): −21% to −42%) and type 2 diabetes…”
- 02Treatment effect not shown to be clinically meaningful
The reported effect sizes (e.g., 32% CVD risk reduction, 26% T2D risk reduction) are presented as relative risk reductions but are not anchored to a minimal clinically important difference or to the normal/reference range of the surrogate. The magnitude of the lipidomic changes is not expressed as a fraction of normal values, and the clinical meaningfulness is not explicitly established. The effect sizes are statistically significant but lack a clear anchor to clinical or biological meaningfulness.
“In the EPIC-Potsdam cohort, the DIVAS diet-induced MLS difference was associated with 32% (95% confidence interval (95% CI): 21% to 42%) lower CVD (composite endpoint of primary incidence of myocardial infarction (MI) and stroke) and 26% (95% CI: 15% to 35%)…”
- 03Other integrity concern
Trial NCT01478958 was first submitted to ClinicalTrials.gov on 2011-11-16, after the registered study start date of 2010-05. Retrospective registration means the protocol and outcomes were not on the public record before the study ran, which is what prospective registration exists to establish.
NCT01478958
reviewer’s wording - 04Declared data/code link does not resolve
Dead link — nothing to verify.
“https://research.reading.ac.uk/ifnh/cases/milk-dairy-consumption-risk-cardiovascular-diseases-cause-mortality/”
This Kaimen Rigor review uses Kaimen Rigor reviewers trained on a curated corpus of high-fidelity and retracted papers, with expert supervision and curation. It can still make mistakes; verify each finding against the source before relying on it.
The paper is methodologically strong, integrating an RCT with prospective cohorts and another RCT to derive and validate a lipidomics-based score. Reporting is generally transparent with detailed methods, ethics approvals, and data/code availability. Minor gaps include lack of explicit power analysis, outlier handling, and some threshold p-values.
Both reviewers classified the study as mixed, and this was adopted. The evaluation covered all eight dimensions; several sub-criteria were not applicable (e.g., animal-related items). The statistics verification recomputed only 4 tests, all consistent, but this does not validate the entire statistical analysis. The citation check flagged one reference not found in registry.
Numerical inconsistencies
1 finding · worst lowValues that contradict each other or are impossible for the stated sample: recomputed p-values and test statistics, GRIM/GRIMMER checks on summary numbers, percentages against their own counts, totals against their parts, and estimates against their own confidence intervals.
- Internal contradictions in the reported numbersAssessed
Recomputed 4 tests: 4 consistent, 0 inconsistent; 4 via agent-written checks.
- CONSISTENTreported p < .001 · recomputed p = <.001Reviewer 1Check p-value for T2D risk association in NHS (odds ratio per s.d. = 0.72, 95% CI 0.65-0.79).
“In age-matched models, 1 s.d. higher rMLS was associated with 28% lower relative T2D risk (odds ratio per s.d. = 0.72, 95% CI: 0.65 to 0.79, P = 6.4 × 10–12)”
Taken as given: The odds ratio is on a log scale.; The 95% CI is two-sided.; The p-value is two-sided.Method: Used pCI function to compute p-value from OR and CI.How we recomputed it: pCI(0.72, 0.65, 0.79, 1) - CONSISTENTreported p < .050 · recomputed p = .021Reviewer 1Check p-value for stroke risk association in NHS (odds ratio per s.d. = 0.90, 95% CI 0.82-0.98).
“Higher rMLS levels, indicative of better dietary fat quality, were associated with a 10% lower relative stroke risk (odds ratio per s.d. = 0.90, 95% CI: 0.82 to 0.98, P < 0.05)”
Taken as given: The odds ratio is on a log scale.; The 95% CI is two-sided.; The p-value is two-sided.Method: Used pCI function to compute p-value from OR and CI.How we recomputed it: pCI(0.90, 0.82, 0.98, 1) - CONSISTENTreported p < .050 · recomputed p = .034Reviewer 2Check p-value for rMLS change association with T2D risk in NHS (OR per SD = 0.76, 95% CI 0.59-0.98).
“odds ratio per standard deviation of 0.76; 95% CI: 0.59 to 0.98”
Taken as given: The reported OR is a ratio estimate with a 95% confidence interval.; The CI is two-sided at 95%.Method: Recomputed p-value from the reported OR and 95% CI using the pCI function for a log-scale ratio.How we recomputed it: pCI(0.76, 0.59, 0.98, 1) - CONSISTENTreported p < .001 · recomputed p = <.001Reviewer 2Check p-value for rMLS association with T2D risk in NHS (OR per SD = 0.72, 95% CI 0.65-0.79).
“odds ratio per s.d. = 0.72, 95% CI: 0.65 to 0.79, P = 6.4 × 10 –12”
Taken as given: The reported OR is a ratio estimate with a 95% confidence interval.; The CI is two-sided at 95%.Method: Recomputed p-value from the reported OR and 95% CI using the pCI function for a log-scale ratio.How we recomputed it: pCI(0.72, 0.65, 0.79, 1)
- lowinternal contradictionThe number of participants in the DIVAS trial is reported as 195 in the Methods, but the lipidomics subset is 113. The abstract and results consistently use 113 for the lipidomics analysis, but the total randomized number is not consistently stated.
Lipidomics analysis was performed in a subset of participants (n = 113 of 195) from the DIVAS trial
Methodsreviewer’s wording - lowinternal contradictionThe number of participants in the DIVAS control group with lipidomics data is reported as 38 in the Methods but as 65 in the Results section.
n = 38 with lipidomics data (Methods) vs n = 65 (Results)
Methodsreviewer’s wording
Overstated conclusions
3 findings · worst highConclusions that reach past what the paper's own results support — including a significance claim that no longer holds when the statistic is recomputed, and efficacy resting on an unvalidated surrogate endpoint.
- Efficacy rests on an unvalidated surrogate endpointAssessed
- Treatment effect not shown to be clinically meaningfulAssessed
- Conclusions only partially backed by the presented evidenceAssessed
8 major claims checked against the paper's own evidence: 3 only partially supported (evidence backs part of the claim; gaps or caveats remain); the rest adequately supported.
- partialReviewers 1, 2The MLS captures the cardiometabolic health impact of dietary fat quality better than established surrogate biomarkers.The paper shows stronger associations for MLS than non-HDL-C, but this is based on a single comparison and may be influenced by the specific biomarker chosen.Evidence: MLS associated with 32% CVD risk reduction vs. 5% for non-HDL-C; mutual adjustment attenuates non-HDL-C but not MLS.
“the increase in MLS, which reflects improved fat quality, resulted in sixfold stronger CVD (32% versus 5%) and fivefold stronger T2D (26% versus 5%) relative risk reductions compared to the risk reductions associated with changes in non-HDL-C levels”
ResultsFind in source - partialReviewer 1The effects of dietary fat quality on the lipidome can contribute to precision nutrition.The PREDIMED interaction suggests potential for precision nutrition, but the paper acknowledges that validation in de novo RCTs is needed.Evidence: PREDIMED interaction analysis shows differential T2D risk reduction by rMLS strata.
“our findings support the concept that lipidomics-based scores may help identify vulnerable population groups and more precisely target dietary interventions focusing on fat quality for T2D prevention.”
DiscussionFind in source - partialReviewer 2The findings support the concept of using lipidomics-based scores for precision nutrition.The PREDIMED interaction suggests potential for precision nutrition, but the paper acknowledges the need for de novo RCTs to validate clinical utility.Evidence: Effect modification in PREDIMED and consistent associations across cohorts.
“our findings support the concept that lipidomics-based scores may help identify vulnerable population groups and more precisely target dietary interventions focusing on fat quality for T2D prevention.”
DiscussionFind in source - supportedReviewers 1, 2The MLS, reflecting improved dietary fat quality, is associated with reduced CVD and T2D risk in the EPIC-Potsdam cohort.The paper provides direct evidence from the EPIC-Potsdam case-cohort analysis with hazard ratios and confidence intervals.Evidence: Cox proportional hazards models show 32% lower CVD and 26% lower T2D incidence associated with the MLS.
a difference in the MLS, reflecting better dietary fat quality, was associated with a significant reduction in the incidence of cardiovascular disease (−32%; 95% CI: −21% to −42%) and type 2 diabetes (−26%; 95% CI: −15% to −35%)
Abstractreviewer’s wording - supportedReviewer 1The rMLS, a simplified score, is associated with lower T2D risk in the NHS cohorts, and 10-year changes in rMLS are associated with lower subsequent T2D risk.The paper reports odds ratios from nested case-control studies, including a 10-year change analysis, with appropriate adjustments.Evidence: Odds ratio per s.d. of 0.72 (95% CI 0.65-0.79) for baseline rMLS and 0.76 (95% CI 0.59-0.98) for 10-year change.
In age-matched models, 1 s.d. higher rMLS was associated with 28% lower relative T2D risk (odds ratio per s.d. = 0.72, 95% CI: 0.65 to 0.79, P = 6.4 × 10–12)
Resultsreviewer’s wording - supportedReviewer 1The Mediterranean diet intervention primarily reduces T2D incidence among participants with unfavorable preintervention rMLS levels.The paper reports a statistically significant interaction and stratified analyses showing a 42% risk reduction in the low-rMLS group.Evidence: Interaction P < 0.05; stratified analysis shows 42% (95% CI 15-61%) reduction in low-rMLS group vs. 3% in high-rMLS group.
“Participants with lower preintervention rMLS (suggestive of disturbed lipid metabolism and adverse dietary fat quality) showed a 42% (95% CI: 15% to 61%, n = 349) reduction in T2D risk by the Mediterranean diet intervention”
ResultsFind in source - supportedReviewer 2Changes in rMLS over 10 years are associated with lower T2D risk in NHS.The claim is supported by the reported odds ratio and confidence interval.Evidence: Conditional logistic regression shows OR per SD = 0.76 (95% CI 0.59-0.98) for 10-year rMLS change.
“beneficial rMLS changes, suggesting improved dietary fat quality over 10 years, were associated with lower diabetes risk (odds ratio per standard deviation of 0.76; 95% CI: 0.59 to 0.98)”
AbstractFind in source - supportedReviewer 2The Mediterranean diet intervention primarily reduced diabetes incidence among participants with unfavorable preintervention rMLS levels.The interaction analysis and stratified results support this claim.Evidence: Statistically significant interaction (P < 0.05) and stratified analysis showing 42% T2D risk reduction in low rMLS group vs 3% in high rMLS group.
“Participants with lower preintervention rMLS (suggestive of disturbed lipid metabolism and adverse dietary fat quality) showed a 42% (95% CI: 15% to 61%, n = 349) reduction in T2D risk by the Mediterranean diet intervention, whereas those with beneficial rMLS levels (above the median) did not show a diabetes risk reduction”
ResultsFind in source
Premise concern: surrogate not validated for clinical benefit; effect size not shown to be clinically meaningful.
- INADEQUATESurrogate endpointThe primary efficacy claim is based on a lipidomics-derived score (MLS/rMLS) as a surrogate for cardiometabolic risk reduction. The paper does not demonstrate target engagement at the tested dose (i.e., no PK/PD or dose-exposure relationship for the lipid changes) and does not cite validated evidence linking the specific lipidomic changes to clinical outcomes. The surrogate is a composite of lipid concentrations, and the claim of reduced CVD and T2D risk is inferred from observational associations, not from a validated surrogate-to-clinical-outcome link.
“In the EPIC-Potsdam cohort, a difference in the MLS, reflecting better dietary fat quality, was associated with a significant reduction in the incidence of cardiovascular disease (−32%; 95% confidence interval (95% CI): −21% to −42%) and type 2 diabetes (−26%; 95% CI: −15% to −35%).”
- INADEQUATEEffect sizeThe reported effect sizes (e.g., 32% CVD risk reduction, 26% T2D risk reduction) are presented as relative risk reductions but are not anchored to a minimal clinically important difference or to the normal/reference range of the surrogate. The magnitude of the lipidomic changes is not expressed as a fraction of normal values, and the clinical meaningfulness is not explicitly established. The effect sizes are statistically significant but lack a clear anchor to clinical or biological meaningfulness.
“In the EPIC-Potsdam cohort, the DIVAS diet-induced MLS difference was associated with 32% (95% confidence interval (95% CI): 21% to 42%) lower CVD (composite endpoint of primary incidence of myocardial infarction (MI) and stroke) and 26% (95% CI: 15% to 35%) lower T2D incidence.”
Data authenticity concerns
1 finding · worst mediumAn adversarial read for patterns associated with data that may not be genuine: results that look too clean, implausibly large effects, duplicated data or images, and methods that do not match the results reported.
- Other integrity concernAssessed
5 integrity concerns flagged (0 high).
- mediumotherTrial NCT01478958 was first submitted to ClinicalTrials.gov on 2011-11-16, after the registered study start date of 2010-05. Retrospective registration means the protocol and outcomes were not on the public record before the study ran, which is what prospective registration exists to establish.
NCT01478958
reviewer’s wording - lowotherThe paper reports a 32% CVD risk reduction in EPIC-Potsdam associated with the MLS, but the confidence interval is wide and the analysis is based on a case-cohort design; the effect size may be overestimated due to the surrogate nature of the score.
“a difference in the MLS, reflecting better dietary fat quality, was associated with a significant reduction in the incidence of cardiovascular disease (−32%; 95% confidence interval (95% CI): −21% to −42%)”
AbstractFind in source - lowotherThe paper reports a 10% lower stroke risk in NHS that becomes non-significant after adjustment, but the abstract highlights the T2D findings; this is not a validity threat but a reporting nuance.
“Higher rMLS levels, indicative of better dietary fat quality, were associated with a 10% lower relative stroke risk (odds ratio per s.d. = 0.90, 95% CI: 0.82 to 0.98, P < 0.05) in age-adjusted models. Further adjustment for BMI and diet quality (AHEI without alcohol points) slightly attenuated this association and rendered it statistically nonsignificant”
ResultsFind in source
Reporting gaps
None foundRequired detail the manuscript never states — study design, biological variables, ethics approval and consent, key resources, statistical reporting, data and code availability, and overall transparency.
Checked — nothing surfaced.
The introduction cites WHO guidelines, evidence syntheses, and prior studies on dietary fat and cardiometabolic health, acknowledging controversies and gaps. The hypothesis that lipidome alterations interlink dietary fat substitution with disease risk is clearly stated and follows from the cited evidence. Limitations of prior research, such as confounding in observational studies and the need for RCT-based metabolite signatures, are addressed through the study's multi-design integration.
“The World Health Organization (WHO) recently issued dietary guidelines that advocate for reducing saturated fats while increasing unsaturated fats to prevent cardiometabolic diseases”
“Here we test the hypothesis that alterations of the lipidome interlink the replacement of dietary SFAs with UFAs and cardiometabolic disease risk.”
“However, assessing diet effects on the metabolome in a well-conducted RCT reduces measurement error, rules out confounding by other lifestyle factors and relates metabolite signatures to a precisely defined diet substitution.”
“The World Health Organization (WHO) recently issued dietary guidelines that advocate for reducing saturated fats while increasing unsaturated fats to prevent cardiometabolic diseases”
“Here we test the hypothesis that alterations of the lipidome interlink the replacement of dietary SFAs with UFAs and cardiometabolic disease risk.”
“However, assessing diet effects on the metabolome in a well-conducted RCT reduces measurement error, rules out confounding by other lifestyle factors and relates metabolite signatures to a precisely defined diet substitution.”
The DIVAS trial is described as a randomized controlled trial with minimization stratified for sex, age, BMI, and CVD risk, and is single-blinded. The randomization method and unit are reported. Power analysis is not explicitly reported, but the trial was designed with a specific sample size. Inclusion/exclusion criteria are detailed. Outlier handling is not explicitly described, but the analysis population is defined. Controls are appropriate (SFA-rich diet). Independent replication is addressed through the LIPOGAIN-2 trial and NHS/NHSII cohorts. For the observational cohorts, randomization and blinding are not applicable, but the case-cohort and case-control designs are well described.
“randomization was conducted by a study researcher using minimization stratified for sex, age, BMI and estimated CVD risk.”
“The trial was single blinded”
“All participants were nonsmokers; were not pregnant or lactating; had normal blood biochemistry and liver and kidney function; did not take dietary supplements or medication for hypertension, raised lipids or inflammatory disorders; had no prior diagnosis of MI, stroke or diabetes; did not consume excessive amounts of alcohol”
“randomization was conducted by a study researcher using minimization stratified for sex, age, BMI and estimated CVD risk.”
“The trial was single blinded”
“All participants were nonsmokers; were not pregnant or lactating; had normal blood biochemistry and liver and kidney function; did not take dietary supplements or medication for hypertension, raised lipids or inflammatory disorders; had no prior diagnosis of MI, stroke or diabetes; did not consume excessive amounts of alcohol”
Sex is reported for all cohorts (e.g., EPIC-Potsdam: 16,644 women and 10,904 men). Age ranges are given for DIVAS (21-60 years) and EPIC-Potsdam (35-65 years). Health status is described via inclusion criteria and baseline characteristics. Demographics such as race/ethnicity are mentioned for EPIC-Potsdam (primarily Middle European ancestry). Species/strain and housing are not applicable as these are human studies.
“recruited 27,548 participants (16,644 women and 10,904 men of primarily Middle European ancestry, age range: 35–65 years)”
“This study recruited men and women aged between 21 and 60 years”
“had normal blood biochemistry and liver and kidney function”
“recruited 27,548 participants (16,644 women and 10,904 men of primarily Middle European ancestry, age range: 35–65 years)”
“This study recruited men and women aged between 21 and 60 years”
“had normal blood biochemistry and liver and kidney function”
DIVAS received approval from named ethics committees (West Berkshire Local Research Ethics Committee and University of Reading Research Ethics Committee) with protocol numbers, and written informed consent was obtained. EPIC-Potsdam was approved by the ethics committee of the Medical Society of the State of Brandenburg, with written informed consent. NHS/NHSII and PREDIMED are referenced as having approvals, though details are not fully provided in the text. Regulatory compliance is stated for DIVAS (Declaration of Helsinki).
“favorable ethical opinion for conduct was given by the West Berkshire Local Research Ethics Committee (09/H0505/56) and the University of Reading Research Ethics Committee (09/40). All individuals provided written informed consent before participating.”
“The study protocol was approved by the ethics committee of the Medical Society of the State of Brandenburg, Germany, and all participants provided a statement of written informed consent before enrollment.”
“The DIVAS trial was conducted according to the guidelines of the Declaration of Helsinki”
“favorable ethical opinion for conduct was given by the West Berkshire Local Research Ethics Committee (09/H0505/56) and the University of Reading Research Ethics Committee (09/40).”
“All individuals provided written informed consent before participating.”
“The study protocol was approved by the ethics committee of the Medical Society of the State of Brandenburg, Germany”
The investigational diets are described in detail (macronutrient composition, food sources). Lipidomics platforms (Metabolon, Broad Institute) are named. Software (R version 4.3.0) is identified. Antibodies, cell lines, and mycoplasma testing are not applicable as this is a human nutrition study. Reagents are not applicable beyond the diets. The paper provides supplementary tables for detailed lipidomics methods.
“All analyses were performed using R (version 4.3.0).”
“We also analyzed the Nurses’ Health Study (NHS) and NHSII cohorts and the Prevención con Dieta Mediterránea (PREDIMED) trial with Broad Institute lipidomics data”
“The target compositions (percent total energy of total fat:SFA:MUFA:PUFA) were 36:17:11:4 for the SFA-rich diet”
“All analyses were performed using R (version 4.3.0).”
Statistical tests are named (Cox proportional hazards, conditional logistic regression, Spearman correlation). Assumptions are handled through standard methods (e.g., proportional hazards). Exact p-values are reported for many analyses (e.g., P = 6.7 × 10–54). Effect sizes with confidence intervals are reported throughout. Software is identified. Data presentation includes per-group n and confidence intervals. Mathematical plausibility checks were not possible for most analyses due to complex models, but no obvious errors were found.
“We used Prentice-weighted Cox proportional hazards regression to assess the association between the rMLS and the risk of incident disease endpoints in PREDIMED.”
“a significant reduction in the incidence of cardiovascular disease (−32%; 95% confidence interval (95% CI): −21% to −42%)”
“We used Prentice-weighted Cox proportional hazards regression to assess the association between the rMLS and the risk of incident disease endpoints in PREDIMED.”
“associated with a significant reduction in the incidence of cardiovascular disease (−32%; 95% confidence interval (95% CI): −21% to −42%)”
The data availability statement describes controlled access for all contributing studies, with specific review committees and contact points. This is appropriate for sensitive human data. Code is available via Zenodo with a DOI. Repository deposit and accession numbers are not applicable for patient-level data, but the code sharing is adequate.
“Access to these datasets is available for research and validation purposes, subject to adherence to institutional data security protocols.”
“Code is available via Zenodo at 10.5281/zenodo.11412029”
“Access to these datasets is available for research and validation purposes, subject to adherence to institutional data security protocols.”
“Code is available via Zenodo at 10.5281/zenodo.11412029”
Methods are detailed enough for replication. DIVAS is registered (NCT01478958). Limitations are explicitly discussed. Conclusions are proportional to the evidence. Funding sources and competing interests are provided. Reporting guidelines are not explicitly mentioned, but the paper follows a structured format.
“We did not conduct independent intervention studies to validate absolute effect sizes on all metabolites, establish thresholds or assess cost-effectiveness”
“This work was supported by a grant from the European Commission and the German Federal Ministry of Education and Research within the Joint Programming Initiative A Healthy Diet for a Healthy Life”
“However, this study has several limitations. We did not conduct independent intervention studies to validate absolute effect sizes on all metabolites”
“This work was supported by a grant from the European Commission and the German Federal Ministry of Education and Research within the Joint Programming Initiative A Healthy Diet for a Healthy Life”
Registered (3 IDs: ClinicalTrials.gov, ISRCTN). No reporting guideline cited.
Broken references and links
2 findings · worst mediumReferences checked against Crossref, OpenAlex and Retraction Watch for retractions and resolvability, plus declared data and code links probed for whether they resolve to content matching the paper.
- Dead data/code linksRecomputed
- References not resolvable to a published paperRecomputed
Checked 88 references by DOI: 76 verified — 1 DOI unresolved, 11 no DOI (shown, not verified).
- UNRESOLVED10.5281/zenodo.11412029feichel/MultiLipidScore: V1.0.0Cited DOI does not resolve to any Crossref record.
- NO DOISaturated Fatty Acid and Trans-Fatty Acid Intake for Adults and Children: WHO GuidelineNo DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
- NO DOIMyPlateNo DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
- NO DOIEndotextNo DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
- NO DOIFoodData CentralNo DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
- NO DOIFast unfolding of communities in large networksNo DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
- NO DOILinking Whole-Grain Bread, Coffee, and Red Meat to the Risk of Type 2 Diabetes: Using Metabolomics Networks to Infer Potential Biological MechanismsNo DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
- NO DOISaturated fat and trans -fat intakes and their replacement with other macronutrients: a systematic review and meta-analysis of prospective observational studiesNo DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
- NO DOIEffects of saturated fatty acids on serum lipids and lipoproteins: a systematic review and regression analysisNo DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
- NO DOIThe national survey of stroke. Clinical findingsNo DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
- NO DOIControlling the false discovery rate: a practical and powerful approach to multiple testingNo DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
- NO DOIOrder-independent constraint-based causal structure learningNo DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
3 of 4 data/code links checked; 2 live, 1 dead; 1 not probed.
- datahttps://research.reading.ac.uk/ifnh/cases/milk-dairy-consumption-risk-cardiovascular-diseases-cause-mortality/DEADHTTP 404Dead link — nothing to verify.
- datahttps://www.dife.de/en/research/cooperations/epic-study/LIVEHTTP 200Resolves, but the content could not be matched to the paper.
- datahttps://nurseshealthstudy.org/UNVERIFIEDLiveness indeterminate — content not checked.
- datahttp://www.predimed.es/LIVEHTTP 200Resolves, but the content could not be matched to the paper.
Copyediting
7 minorWording, consistency and formatting errors that need correcting before submission.
No major wording or formatting errors. 7 minor suggestions below.
7 copyedit issues flagged: mostly typo, consistency, clarity.
- MINORtypoDiscussion, paragraph 2“controled”→ controlledSpelling error.
- MINORtypoDiscussion, paragraph 7“trigylcerides”→ triglyceridesSpelling error.
- MINORconsistencyResults, Study design“n = 113 of 195”→ Ensure consistency with later mention of n=113 for lipidomics subset.The number 195 is mentioned in Methods, but the Results say n=113; clarify the total randomized vs. subset.
- MINORclarityMethods, Statistical analysis“We used Prentice-weighted Cox proportional hazards regression”→ Clarify that this is for the case-cohort design.The method is mentioned but not fully explained in the main text.
- MINORtypoDiscussion, paragraph 1“controled”→ controlledSpelling error.
- MINORconsistencyMethods, DIVAS trial“n = 38 with lipidomics data”→ Ensure consistent reporting of n values across text and tables.The n for the control group is reported as 38 here but earlier as 65 in the results section.
- MINORclarityMethods, Statistical analysis“We used Prentice-weighted Cox proportional hazards regression”→ Clarify the weighting method for readers.Prentice weighting is a specific method; consider a brief explanation.
The published work is robust overall, but an informed reader should weigh the minor reporting gaps (missing power analysis, outlier handling, threshold p-values) and the retrospective registration of the DIVAS trial. A correction or erratum is not strictly required, but addressing these gaps in a re-analysis or correspondence would strengthen confidence.
- 1.HIGHreportingAdd an explicit a priori power analysis or sample size justification for the DIVAS trial in the Methods section.Both reviewers noted the absence of power analysis, which is a standard reporting requirement for RCTs.
- 2.HIGHreportingDescribe outlier handling procedures for the lipidomics data in the Methods, or state that no outliers were excluded.Reviewer 2 flagged outlier handling as inadequate; transparency on this is needed for reproducibility.
- 3.HIGHstatisticsProvide exact p-values instead of thresholds (e.g., P < 0.05) where possible, or explicitly state that estimation-based reporting is used.Reviewer 2 noted threshold p-values; exact values improve transparency and allow verification.
- 4.HIGHreportingExplicitly mention adherence to reporting guidelines (e.g., CONSORT, STROBE) in the Methods or Reporting Summary.Reviewer 2 noted reporting guidelines are not mentioned; this is a standard expectation for clinical studies.
- 5.HIGHdata codeFix the dead link in the reproducibility check (one of four links was dead) and ensure all data/code links are live.A broken link undermines the data availability statement and reproducibility.
- 6.HIGHdata codeVerify the Zenodo reference 'feichel/MultiLipidScore: V1.0.0' (DOI 10.5281/zenodo.11412029) as it was not found in the registry; correct or replace if necessary.A reference not found in any registry may be a fabrication signal and must be resolved.
- 7.MEDIUMreportingClarify the total number of randomized participants in DIVAS (195) versus the lipidomics subset (113) in the Methods and Results for consistency.The integrity check flagged an internal contradiction in participant numbers; consistency is essential.
- 8.MEDIUMreportingClarify the number of participants in the DIVAS control group with lipidomics data (38 vs 65) across Methods and Results.The integrity check flagged an internal contradiction; consistent reporting is needed.
- 9.MEDIUMreportingAdd a note in the Data Availability section clarifying that individual participant data are not publicly available due to privacy, but aggregate data and code are accessible.Reviewer 1 suggested this clarification to avoid ambiguity about data access.
- 10.MEDIUMreportingInclude more details on the ethics approvals for NHS/NHSII and PREDIMED in the main text or supplement.Reviewer 2 noted that ethics details for these cohorts are not fully provided.
- 11.MEDIUMstatisticsAdd a statement on verification of statistical assumptions (e.g., proportional hazards) for the Cox models in the Methods.Both reviewers suggested this to improve transparency of model validity.
- 12.MEDIUMreportingClarify the Prentice-weighted Cox regression method for readers in the Methods.The copyedit pass noted the method is not fully explained; a brief explanation would aid understanding.
- 13.LOWcopyeditFix spelling errors: 'controled' to 'controlled' (Discussion paragraphs 1 and 2) and 'trigylcerides' to 'triglycerides' (Discussion paragraph 7).Copyedit pass flagged these typos; minor but should be corrected.
- 14.LOWreportingConsider depositing the lipidomics data (or processed data) in a public repository with an accession number, if possible.Reviewer 1 suggested this to enhance reproducibility, though controlled access is acceptable.
- 15.LOWreportingIn the Discussion, explicitly acknowledge the lack of independent validation of the MLS in a separate intervention trial as a limitation, and suggest future directions.Reviewer 1 suggested this; the paper already mentions this but could be more explicit.
The star rating is the report’s one-glance summary. Every paper starts at 5★ and loses stars for the concrete problems the review finds — so a rating is never a vague average, it’s a running total you can read line by line under “How this rating was calculated.”
- Reporting — 8 dimensionseach dimension that fully fails−½★
- each dimension partially met−¼★
- Statistics · Integrity · Claimseach serious problem−1★
- each medium problem−½★
- Citationseach retracted or unverifiable reference−¼★
- Copyeditonly when the manuscript needs a full edit−½★
The rating never drops below 1★, and a demonstrable critical failure (an impossible statistic, a proven ethics violation) caps it at 1★ on its own — so the stars can never look healthy when the verdict is CRITICAL.
The rating draws on a panel of agents. Three independent Kaimen Rigor reviewers grade the eight dimensions below across several independent passes (the shown verdict is their majority vote — steadier than any single run), isolate the paper’s major claims and check its own evidence backs them, and flag integrity concerns. Alongside them, a citation agent resolves every reference against Crossref, OpenAlex, and Retraction Watch; a statistics agent recomputes reported tests; and rule-based checks verify that declared data/code links actually resolve. Full text is required — an abstract-only submission is not analyzed.
Graded against NIH, MDAR, ARRIVE 2.0, CONSORT, EQUATOR, and RRID guidelines. A dimension that doesn’t apply to the study type is skipped, never penalized.
This Kaimen Rigor review is model-assisted and is not a substitute for formal expert review. It complements human evaluation by surfacing potential methodological concerns — verify each finding against the source.