Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1057
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3175
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Objective: This study aimed to explore the association between serum omega-3 (n-3) and omega-6 (n-6) polyunsaturated fatty acids (PUFAs) and biological aging, along with the potential mediating role of systemic immune inflammation (SII).
Methods: Data from the National Health and Nutrition Examination Survey (NHANES) 2011-2014 were used for analyses. Accelerated aging in participants was assessed by calculating the difference between phenotypic age (PhenoAge) and chronological age. Weighted multivariate linear regression models and subgroup analysis were used to investigate the correlation between serum n-3 and n-6 PUFAs and accelerated aging, and restricted cubic spline (RCS) model was applied to explore potential nonlinear relationships. We further conducted mediation analyses to assess the role of SII in these relationships. Additionally, weighted quantile sum (WQS) regression and quantile g-computation (QGC) models were conducted to investigate the mixed effects of serum PUFAs and identify the key contributor.
Results: A total of 3376 participants were enrolled in this study. In multivariate linear regression models, eight of the twelve individual serum PUFAs showed a significantly negative association with PhenoAge acceleration, Specifically, per-unit increases in linoleic acid (LA), gamma-linolenic acid (GLA), arachidonic acid (AA), alpha-linolenic acid (ALA), stearidonic acid (SDA), eicosapentaenoic acid (EPA), docosapentaenoic acid (n-3 DPA), and docosahexaenoic acid (DHA) were all associated with reduced PhenoAge acceleration (P < 0.05, respectively). Subgroup analysis demonstrated robust consistence results when stratified by age, sex, and race/ethnicity. L-shaped nonlinear relationships were observed between PhenoAge acceleration with total n-6 PUFAs, LA and ALA (all P for nonlinear < 0.05). Mediation analyses indicated that SII mediated the relationship between serum PUFAs and reduced PhenoAge acceleration. Mixed-effects analysis using WQS and QGC models revealed that the combined effect of serum PUFAs on reducing PhenoAge acceleration, with DHA showing the strongest significant contribution.
Conclusions: This study demonstrated that higher levels of certain PUFAs were associated with a reduction in PhenoAge acceleration either individually or in combination, with DHA having the most prominent effect in mixed effects. The SII mediated these relationships, suggesting that PUFAs may slow biological aging by reducing inflammation. These findings highlighted the potential role of PUFAs in mitigating accelerated aging and their implications for aging-related health interventions.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11890405 | PMC |
http://dx.doi.org/10.1007/s40520-025-02964-2 | DOI Listing |
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