Genetic association between FADS and ELOVL polymorphisms and the circulating levels of EPA/DHA in humans: a scoping review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) are two omega-3 fatty acids that can be synthesized out of their precursor alpha-linolenic acid (ALA). FADS and ELOVL genes encode the desaturase and elongase enzymes required for EPA and DHA synthesis from ALA; however, single nucleotide polymorphisms (SNPs) in FADS and ELOVL genes could modify the levels of EPA and DHA synthesized from ALA although there is no consensus in this area. This review aims to investigate EPA and DHA circulating levels in human blood and their association with FADS or ELOVL. METHODS: PubMed, Cochrane, and Scopus databases were used to identify research articles. They were subsequently reviewed by two independent investigators. RESULTS: Initially, 353 papers were identified. After removing duplicates and articles not meeting inclusion criteria, 98 full text papers were screened. Finally, this review included 40 studies investigating FADS and/or ELOVL polymorphisms. A total of 47 different SNPs in FADS genes were reported. FADS1 rs174537, rs174547, rs174556 and rs174561 were the most studied SNPs, with minor allele carriers having lower levels of EPA and DHA. SNPs in the FADS genes were in high linkage disequilibrium. SNPs in FADS were correlated with levels of EPA and DHA. No conclusion could be drawn with the ELOVL polymorphisms since the number of studies was too low. CONCLUSION: Specific SNPs in FADS gene, such as rs174537, have strong associations with circulating levels of EPA and DHA. Continued investigation regarding the impact of genetic variants related to EPA and DHA synthesis is warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it