{"doi":"10.3390/nu16152433","title":"Causal Relationship between Meat Intake and Biological Aging: Evidence from Mendelian Randomization Analysis","abstract":"<jats:p>Existing research indicates that different types of meat have varying effects on health and aging, but the specific causal relationships remain unclear. This study aimed to explore the causal relationship between different types of meat intake and aging-related phenotypes. This study employed Mendelian randomization (MR) to select genetic variants associated with meat intake from large genomic databases, ensuring the independence and pleiotropy-free nature of these instrumental variables (IVs), and calculated the F-statistic to evaluate the strength of the IVs. The validity of causal estimates was assessed through sensitivity analyses and various MR methods (MR-Egger, weighted median, inverse-variance weighted (IVW), simple mode, and weighted mode), with the MR-Egger regression intercept used to test for pleiotropy bias and Cochran’s Q test employed to evaluate the heterogeneity of the results. The findings reveal a positive causal relationship between meat consumers and DNA methylation PhenoAge acceleration, suggesting that increased meat intake may accelerate the biological aging process. Specifically, lamb intake is found to have a positive causal effect on mitochondrial DNA copy number, while processed meat consumption shows a negative causal effect on telomere length. No significant causal relationships were observed for other types of meat intake. This study highlights the significant impact that processing and cooking methods have on meat’s role in health and aging, enhancing our understanding of how specific types of meat and their preparation affect the aging process, providing a theoretical basis for dietary strategies aimed at delaying aging and enhancing quality of life.</jats:p>","journal":"Nutrients","year":2024,"id":655420,"datarank":0.37273599746820013,"base_score":2.4849066497880004,"endowment":2.4849066497880004,"self_citation_contribution":0.37273599746820013,"citation_network_contribution":0.0,"self_endowment_contribution":0.37273599746820013,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":11,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1710952,"name":"Yinyun Deng","orcid":null,"position":1,"is_corresponding":false},{"id":688983,"name":"Hui Liu","orcid":"0000-0003-1340-4672","position":2,"is_corresponding":false},{"id":1710954,"name":"Zhengzheng Fu","orcid":null,"position":3,"is_corresponding":false},{"id":1481832,"name":"Yinghui Wang","orcid":"0000-0002-6275-0777","position":4,"is_corresponding":false},{"id":1710955,"name":"Meijuan Zhou","orcid":null,"position":5,"is_corresponding":false},{"id":1710956,"name":"Zhijun Feng","orcid":null,"position":6,"is_corresponding":false},{"id":1710950,"name":"Shupeng Liu","orcid":"0000-0002-0951-7562","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Causal Relationship between Meat Intake and Biological Aging: Evidence from Mendelian Randomization Analysis","abstract":"<jats:p>Existing research indicates that different types of meat have varying effects on health and aging, but the specific causal relationships remain unclear. This study aimed to explore the causal relationship between different types of meat intake and aging-related phenotypes. This study employed Mendelian randomization (MR) to select genetic variants associated with meat intake from large genomic databases, ensuring the independence and pleiotropy-free nature of these instrumental variables (IVs), and calculated the F-statistic to evaluate the strength of the IVs. The validity of causal estimates was assessed through sensitivity analyses and various MR methods (MR-Egger, weighted median, inverse-variance weighted (IVW), simple mode, and weighted mode), with the MR-Egger regression intercept used to test for pleiotropy bias and Cochran’s Q test employed to evaluate the heterogeneity of the results. The findings reveal a positive causal relationship between meat consumers and DNA methylation PhenoAge acceleration, suggesting that increased meat intake may accelerate the biological aging process. Specifically, lamb intake is found to have a positive causal effect on mitochondrial DNA copy number, while processed meat consumption shows a negative causal effect on telomere length. No significant causal relationships were observed for other types of meat intake. This study highlights the significant impact that processing and cooking methods have on meat’s role in health and aging, enhancing our understanding of how specific types of meat and their preparation affect the aging process, providing a theoretical basis for dietary strategies aimed at delaying aging and enhancing quality of life.</jats:p>","is_dataset_classified":null,"base_score":2.4849066497880004,"endowment":2.4849066497880004,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"39125314","pmcid":null,"openalex_id":"https://openalex.org/W4401016659","authors":[],"funders":[{"funder_name":"National Natural Science Foundation of China","grant_id":"82273582","title":null},{"funder_name":"National Natural Science Foundation of China","grant_id":"82103785","title":null},{"funder_name":"The National Natural Science Foundation of China","grant_id":"82273582 and 82103785","title":null}],"total_grants":3,"fwci":2.8171,"citation_percentile":0.89989773,"influential_citations":0,"citation_trend":[{"year":2024,"count":3},{"year":2025,"count":7},{"year":2026,"count":1}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://www.mdpi.com/2072-6643/16/15/2433/pdf?version=1722332817","host_type":"journal"},{"url":"https://www.mdpi.com/2072-6643/16/15/2433/pdf?version=1722332817","host_type":"publisher"},{"url":"https://www.mdpi.com/2072-6643/16/15/2433/pdf","host_type":"publisher"},{"url":"https://doi.org/10.3390/nu16152433","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/39125314","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11313912","host_type":"repository"},{"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11313912/pdf/nutrients-16-02433.pdf","host_type":"repository"}],"fields_of_study":["Meat and Animal Product Quality","Agriculture Sustainability and Environmental Impact","Nutritional Studies and Diet","Mendelian Randomization Analysis","Humans","Aging","Meat","DNA Methylation","Animals","DNA, Mitochondrial","Phenotype","Sheep","Diet","Causality","Red Meat"],"mesh_terms":["Red Meat","Aging","Animals","Diet","DNA, Mitochondrial","Humans","Meat","Phenotype","Sheep","Causality","DNA Methylation","Mendelian Randomization Analysis"],"keywords":["Mendelian randomization","Pleiotropy","Biology","Genetics","Phenotype","Gene","Genetic variants","Genotype","biological aging","causal relationship","meat consumption","processed meat","red meat","white meat"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Zero hunger"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-11T10:49:10.412393Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}