Do Greenlandic Carriers of the TBC1D4 p.Arg684Ter Variant Have Increased Risk of Cardiovascular Disease?
Bibliographic record
Abstract
Background: The nonsense polymorphism p.Arg684Ter in the TBC1D4 gene is associated with severe skeletal muscle insulin resistance and postprandial hyperglycemia in the Greenlandic population. Homozygous carriers have an increased risk for type 2 diabetes (odds ratio of 10.3) and the variant has an allele frequency of 17% with 4% homozygous carriers in the population. However, we do not know, if p.Arg684Ter carrier status also confers a greater risk of cardiovascular disease (CVD). Thus the aim is to investigate if carriers of the variant are more at risk of CVD than non-carriers. Materials and Methods: The study included adult participants in the Inuit Health in Transition study completed in the years 2005-2010 with sampling from 12 regions in Greenland (n= 3115) and the B99 study conducted from 1999-2001 (n=1401). Outcome was a first time CVD event from the Greenlandic Patien Register or the Causes of Death Register. Incidence rates of CVD were estimated by Poisson regression for wild type, heterozygous and homozygous carriers followed until the end of 2013, adjusted for European admixture proportion, age, sex, smoking, lipids, blood pressure, lipid- and blood pressure lowering drugs, blood glucose and known diabetes. Results: During a median follow-up time of 7 years [IQR: 5.0, 10.0], 273 had an incident CVD event, 13 events among homozygous (HO), and 78 events among heterozygous (HE) carriers. Both in crude and adjusted analyses, there was a higher risk of incident CVD with p.Arg684Ter carrier status, although not statistically significant, with unadjusted incidence rate ratios (IRR) of 2.2 [CI 0.3- 15.5] for HO vs. WT; multivariable adjusted IRR 1.6 [0.12-19.5] for HO vs. WT. The same pattern was seen for HE vs. WT. Conclusions: Overall, there was a trend towards increased risk of incident CVD with the TBC1D4 p.Arg684Ter variant although not statistically significant. Lack of statistical power may partly explain this, and replication in a larger sample or longer follow-up is needed. Disclosure M.E. Jørgensen: Stock/Shareholder; Self; Novo Nordisk A/S. Research Support; Self; AstraZeneca, Amgen Inc.. M. Tvermosegaard: None. P.F. Rønn: Employee; Spouse/Partner; Novo Nordisk A/S. Stock/Shareholder; Spouse/Partner; Novo Nordisk A/S. P. Bjerregaard: None. I.K. Dahl-Petersen: None. C.V. Larsen: None. M.L. Pedersen: None. A. Albrechtsen: None. I. Moltke: None. N. Grarup: None. T. Hansen: None.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".