Presença de polimorfismos genéticos no receptor de vitamina D e padrão da reserva corporal de micronutrientes e suas relações com os marcadores do controle glicêmico, perfis lipídico e inflamatório de indivíduos com diabetes mellitus tipo 2
Bibliographic record
Abstract
Genetic single nucleotide polymorphisms (SNPs) and haplotypes in the vitamin D receptor (VDR), and deficiencies in vitamin D, magnesium (Mg), zinc (Zn), calcium (Ca) and potassium (K) are factors that alone contribute to inadequate metabolic control in individuals with type 2 diabetes mellitus (DM2). Thus, the aim of this study is to associate the presence of SNPs in the VDR, haplotypes and patterns of micronutrient body reserves with markers of glycemic control, lipid levels and inflammatory profile in individuals with DM2. To this end, a meta-analysis evaluated the association between the presence of SNPs in the VDR and markers of glycemic control, lipid levels and inflammatory profile in individuals with DM2, following the MOOSE guidelines and registered with PROSPERO (nºCRD42021268152). A systematic search of the data was carried out in the PubMed, EMBASE and SCOPUS databases. Studies comparing the values of markers of glycemic control, lipid profile and inflammation between the identified genotypes were included. The quality of the studies was assessed using the Newcastle-Ottawa scale. Effect sizes were tested using a random-effects model and reported as standardized mean difference (SMD) and 95% confidence interval (95%CI). In parallel, an observational, cross-sectional study was carried out with 160 adults with DM2, both sexes, living in Sergipe. Sociodemographic information was collected, anthropometric and body composition assessments were carried out, and blood was drawn to identify SNPs and assess biochemical markers of glycemic and lipid control. The frequency of SNPs, linkage disequilibrium and the Hardy-Weinberg test were calculated and SNPs with a frequency greater than 1% were inserted into the haplotype model. The SNPs and haplotypes, and the micronutrient body reserve patterns established by principal component analysis and stratified into quartiles, were entered into the binary logistic regression model tests (dependent variables therapeutic target values for fasting glycemia, percent of glycated hemoglobin (%HbA1c) and Homeostasis Model Assessment - Insulin Resistance (HOMA-IR) adjusted for gender, age, time of diagnosis and BMI, significance p<0.05. The meta-analysis identified four SNPs: Fokl (rs2228570); BsmI (rs1544410); Taql (rs731236) and Apal (rs7975232). The Fokl and BsmI SNPs were associated with higher %HbA1c (SMD=0.409, p=0.002) and triacylglycerol (SMD=0.206, p=0.023), respectively. In the observational study, the Bsml SNP was associated with increased %HbA1c (OR=2.071, p=0.045), but the haplotypes did not contribute to inadequate glycemic control. Two patterns of body micronutrient reserve were established. The lowest quartile of Pattern 1 (Mg, Zn, Ca and K) and Pattern 2 (25(OH)D and Zn) were 4.319 (p=0.019) and 3.970 (p=0.038) times more likely to increase HOMA-IR and %HbA1c values, respectively. It is concluded that SNPs in the VDR and the pattern of micronutrient body reserves explained by the lower concentration of 25(OH)D, Zn, Mg, Ca and K contribute to poor metabolic control in individuals with DM2.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".