Genetic Investigation of an Iranian Supercentenarian by Whole Exome Sequencing.
Bibliographic record
Abstract
BACKGROUND: The genetic basis of longevity is an important field of study because the majority of supercentenarian cases experience healthy aging and may only show age-related diseases in their last few years of life. It is clear that genetic factors play an important role in survival beyond 90 years of age, but the exact relationship of genetic variants to this phenomenon remains unknown. OBJECTIVE: The aim of this project was to investigate different hypotheses that describe the relationship between genetic variants and human longevity in a living Iranian man by Whole Exome Sequencing. METHODS: Initially, we conducted high quality DNA extraction on a peripheral blood sample. Then, whole exome sequencing was performed on the DNA and different bioinformatic software packages and databases were used to analyze the data. Tertiary analysis was performed on four genetic hypotheses for longevity. RESULTS: Analysis showed that among 27 metabolic variants which are related to longevity, 18 variants encompassed the exceptional longevity allele. In comparison with the NHGRI GWAS catalog, the case had 58 trait-associated variants of which 11 were homozygous for the risk allele. We also discovered 25 novel variants within candidate genes for aging and longevity and we detected seven longevity-associated variants in the sample. CONCLUSION: This study was performed on just one sample and so the results cannot be interpreted as a generalized principle for other elderly societies, but this is the first step towards investigation of the genetic basis of longevity in Iran and provides an insight for further studies in the field of longevity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".