Jose M de Miguel-Yanes

Massachusetts General Hospital, Boston, MA, United States

Are you Jose M de Miguel-Yanes?

Claim your profile

Publications (6)19.77 Total impact

  • [show abstract] [hide abstract]
    ABSTRACT: OBJECTIVE:: To test whether pancreatic beta-cell genetic frailty and hypertension (HTN) interact in their associations with change over time in fasting glucose (ΔFG) or type 2 diabetes mellitus (T2D) risk. METHODS AND RESULTS:: We pooled data from 3471 Framingham Offspring Study participants into six ∼4-year periods (15 852 person-examinations; mean age 52; 54% women). We defined two genetic exposures reflecting beta-cell genetic risk burden: single nucleotide polymorphism (SNP) score counts of fasting glucose-associated and T2D-associated risk alleles at 16 and 33 putative beta-cell loci, respectively; and three HTN exposures: HTN versus no-HTN; treated versus untreated HTN; and five mutually exclusive antihypertensive categories (beta-blockers, thiazides, renin-angiotensin system agents, combinations, others) versus untreated HTN. We tested ∼4-year mean ΔFG or odds of T2D by per-risk allele score change and HTN category, seeking genetic score-by-HTN interaction. Genetic scores increased ∼4-year ΔFG (0.6 mg/dl per-risk allele; P = 8.9 × 10) and T2D-risk (∼17% per-risk allele; P = 2.1 × 10). As compared to no-HTN, HTN conferred higher ΔFG (2.6 versus 1.7 mg/dl; P < 0.0001) and T2D-risk [odds ratio (OR) = 2.9, 95% confidence interval (CI) 2.8-3.0; P < 0.0001]. As compared to untreated HTN, treated HTN conferred higher ΔFG (3.4 versus 3.0 mg/dl; P < 0.0001) and T2D-risk (OR = 1.4, 95% CI 1.3-1.5; P = 0.02). Beta-blockers (OR = 1.6, 95% CI 1.1-2.4), combinations (OR = 1.6, 95% CI 1.1-2.5), and others (OR = 2.0, 95% CI 1.4-2.9) increased T2D-risk (all P < 0.02). In joint models including interaction terms, all genetic score-by-HTN interaction terms were P value greater than 0.05. In joint models without interaction, fasting glucose-SNP or T2D-SNP genetic scores (both P < 0.001) and HTN (P < 0.0001) independently increased ΔFG or T2D-risk. CONCLUSION:: HTN, HTN treatment, and common fasting glucose-SNP genetic score/T2D-SNP genetic score independently predicted ΔFG and T2D incidence, but did not modify each other's association with ΔFG or T2D risk.
    Journal of hypertension 02/2013; · 4.02 Impact Factor
  • [show abstract] [hide abstract]
    ABSTRACT: Inhibition of the endocannabinoid receptor CB1 improves insulin sensitivity, lowers glycemia, and slows atherosclerosis. We analyzed whether common variants in the gene encoding CB1, CNR1, are associated with insulin resistance, risk of type 2 diabetes (T2D) or coronary heart disease (CHD). We studied 2,411 participants of the Framingham Offspring Study (mean age 60 years, 52% women) for quantitative traits and CHD, and the Framingham SHARe database for T2D risk. We genotyped 19 single-nucleotide polymorphisms (SNPs) that tagged 85% (at r(2) = 0.8) of common (>5%) CNR1 SNPs. Fasting blood glucose and insulin at the 7th (1999-2001) exam were collected. We used age-, sex-, BMI-adjusted models to test additive associations of genotype with homeostasis model assessment of insulin resistance (HOMA(IR)) (linear mixed-effect models), T2D, or CHD. To account for multiple tests of SNPs, we generated empirical P values. The C allele at SNP rs806365 (frequency, 57.4%), ~4.1 kb 3' from CNR1, was associated with increased HOMA(IR) (n = 2,261, β = 0.05 per C, empirical P = 0.01), risk of T2D (674 cases, odds ratio = 1.19 per C, nominal P = 0.01) and CHD (237 cases, hazard ratio = 1.23 per C, nominal P = 0.04). The association of rs806365 with HOMA(IR) was replicated in a meta-analysis of two independent cohorts (National Health and Nutrition Examination Survey III genetic cohort (NHANES-III) plus Partners Case-Control Diabetes Study; 2,540 white individuals, β = 0.037, nominal P = 0.007), but not in the large Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) Consortium (n = 29,248, nominal P = 0.74). The association of rs806365 was not replicated either with T2D in Diabetes Genetics Replication and Meta-analysis (DIAGRAM) (n = 10,128, nominal P = 0.31), or with CHD in PROCARDIS (n = 13,614, nominal P = 0.37). Although supported by initial results, we found no reproducible statistical association of common variation at CNR1 with insulin resistance, T2D, or CHD.
    Obesity 06/2011; 19(10):2031-7. · 3.92 Impact Factor
  • Jose M. de Miguel-Yanes
    [show abstract] [hide abstract]
    ABSTRACT: There is evidence supporting that type 2 diabetes, either per se or through the concurrence of other factors and chronic conditions like obesity, confers a higher risk for some types of cancer. Association between type 1 diabetes and cancer seems to be weaker. It is a plausible hypothesis that some diabetes treatments modify the cancer risk that diabetes poses. The in vitro mitogenic properties of the insulin analogs have long been known. Metformin activates the AMP-activated protein kinase, thus interfering with metabolism of cancer cells. Randomized controlled trials including very large numbers of cases would be needed to definitely prove or discard these drugs specific cancer associations. In their absence, evidence comes from epidemiologic observational studies, which must include appropriate adjustments for confounding factors to avoid biases and misleading conclusions. This article presents an update of the last research on pathophysiology and on the association between diabetes and its treatments with cancer. KeywordsDiabetes–Cancer–Insulin resistance–Antidiabetic drugs–Glargine–Metformin
    Current Cardiovascular Risk Reports 01/2011; 5(1):70-78.
  • Source
    [show abstract] [hide abstract]
    ABSTRACT: To test if knowledge of type 2 diabetes genetic variants improves disease prediction. We tested 40 single nucleotide polymorphisms (SNPs) associated with diabetes in 3,471 Framingham Offspring Study subjects followed over 34 years using pooled logistic regression models stratified by age (<50 years, diabetes cases = 144; or ≥50 years, diabetes cases = 302). Models included clinical risk factors and a 40-SNP weighted genetic risk score. In people <50 years of age, the clinical risk factors model C-statistic was 0.908; the 40-SNP score increased it to 0.911 (P = 0.3; net reclassification improvement (NRI): 10.2%, P = 0.001). In people ≥50 years of age, the C-statistics without and with the score were 0.883 and 0.884 (P = 0.2; NRI: 0.4%). The risk per risk allele was higher in people <50 than ≥50 years of age (24 vs. 11%; P value for age interaction = 0.02). Knowledge of common genetic variation appropriately reclassifies younger people for type 2 diabetes risk beyond clinical risk factors but not older people.
    Diabetes care 10/2010; 34(1):121-5. · 7.74 Impact Factor
  • Jose M. de Miguel-Yanes, James B. Meigs
    Current Cardiovascular Risk Reports 01/2010; 4(4):248-250.
  • Source
    Jose M de Miguel-Yanes, James B Meigs
    The Oncologist 12/2009; 14(12):1175-7. · 4.10 Impact Factor