Navarro-Gonzalez, D. (David)
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- TyG Index change is more determinant for forecasting type 2 diabetes onset than weight gain(Lippincott, Williams & Wilkins, 2016) Martinez, J.A. (José Alfredo); Navarro-Gonzalez, D. (David); Sanchez-Iñigo, L. (Laura); Fernandez-Montero, A. (Alejandro); Pastrana-Delgado, J. (Juan)Abstract: The risk of type 2 diabetes associated with obesity appears to be influenced by other metabolic abnormalities, and there is controversy about the harmless condition of the metabolically healthy obese (MHO) state. The aim of this study is to assess the risk of diabetes and the impact of changes in weight and in triglyceride-glucose index (TyG index), according to the metabolic health and obesity states. We analyzed prospective data of the Vascular Metabolic CUN cohort, a population-based study among a White European population (mean follow-up, 8.9 years). Incident diabetes was assessed in 1923 women and 3016 men with a mean age at baseline of 55.33 13.68 and 53.78 12.98 years old. A Cox proportional-hazard analysis was conducted to estimate the hazard ratio (HR) of diabetes on metabolically healthy nonobese (MHNO), metabolically healthy obese, metabolically unhealthy nonobese (MUNO), and metabolically unhealthy obese (MUO). A continuous standardized variable (z-score) was derived to compute the HR for diabetes per 1-SD increment in the body mass index (BMI) and the TyG index. MHO, MUNO, and MUO status were associated with the development of diabetes, HR of 2.26 (95% CI: 1.25–4.07), 3.04 (95% CI: 1.69– 5.47), and 4.04 (95% CI: 2.14–7.63), respectively. MUNO individuals had 1.82 greater risk of diabetes compared to MHO subjects (95% CI: 1.04–3.22). The HRs for incident diabetes per 1-SD increment in BMI and TyG indexes were 1.23 (95% CI: 1.04–1.44) and 1.54 (95% CI: 1.40–1.68). The increase in BMI did not raise the risk of developing diabetes among metabolically unhealthy subjects, whereas increasing the TyG index significantly affect the risk in all metabolic health categories. Metabolic health is more important determinant for diabetes onset than weight gain. The increase in weight does not raise the risk of developing diabetes among metabolically unhealthy subjects.
- Estimation of fatty liver disease clinical role on glucose metabolic remodelling phenotypes and T2DM onset(Wiley, 2023) Landecho, M.F. (Manuel F.); Martinez, J.A. (José Alfredo); Navarro-Gonzalez, D. (David); Huerta, A. (Ana); Martinez-Urbistondo, D. (Diego); Sanchez-Iñigo, L. (Laura); Fernandez-Montero, A. (Alejandro); Pastrana-Delgado, J. (Juan)Introduction: Metabolic syndrome (MetS), prediabetes (PreDM) and Fatty Liver Disease (FLD) share pathophysiological pathways concerning type 2 diabetes mellitus (T2DM) onset. The non-invasive assessment of fatty liver combined with PreDM and MetS features screening might provide further accuracy in predicting hyperglycemic status in the clinical setting with the putative description of singu- lar phenotypes. The objective of the study is to evaluate and describe the links of a widely available FLD surrogate -the non-invasive serological biomarker Hepatic Steatosis Index (HSI)- with previously described T2DM risk predictors, such as preDM and MetS in forecasting T2DM onset. Patients and methods: A retrospective ancillary cohort study was performed on 2799 patients recruited in the Vascular-Metabolic CUN cohort. The main out- come was the incidence of T2DM according to ADA criteria. MetS and PreDM were defined according to ATP III and ADA criteria, respectively. Hepatic stea- tosis index (HSI) with standardized thresholds was used to discriminate patients with FLD, which was referred as estimated FLD (eFLD). Results: MetS and PreDM were more common in patients with eFLD as com- pared to those with an HSI < 36 points (35% vs 8% and 34% vs. 18%, respectively). Interestingly, eFLD showed clinical effect modification with MetS and PreDM in the prediction of T2DM [eFLD-MetS interaction HR = 4.48 (3.37-5.97) and eFLD-PreDM interaction HR = 6.34 (4.67-8.62)]. These findings supported thedescription of 5 different liver status-linked phenotypes with increasing risk of T2DM: Control group (1,5% of T2DM incidence), eFLD patients (4,4% of T2DM incidence), eFLD and MetS patients (10,6% of T2DM incidence), PreDM patients (11,1% of T2DM incidence) and eFLD and PreDM patients (28,2% of T2DM inci- dence). These phenotypes provided independent capacity of prediction of T2DM incidence after adjustment for age, sex, tobacco and alcohol consumption, obesity and number of SMet features with a c-Harrell=0.84. Conclusion: Estimated Fatty Liver Disease using HSI criteria (eFLD) interplay with MetS features and PreDM might help to discriminate patient risk of T2DM in the clinical setting through the description of independent metabolic risk phenotypes. [Correction added on 15 June 2023, after first online publication: The abstract section was updated in this current version.]
- Risk of incident ischemic stroke according to the metabolic health and obesity states in the Vascular-Metabolic CUN cohort(Sage Journals, 2016) Sanchez-Iñigo, L. (Laura); Navarro-Gonzalez, D. (David); Fernandez-Montero, A. (Alejandro); Pastrana-Delgado, J. (Juan); Martínez, J.A. (J.A.)Background: Whether obesity is a major risk factor for cardiovascular disease in the absence of metabolic comorbidities remains under debate. Indeed, some obese individuals may be at low risk of metabolic-related complications, while normal-weight individuals may not be ‘‘healthy.’’ Aims: To assess the incidence of ischemic stroke according to the metabolic health and obesity states of 5171 participants from the Vascular-Metabolic CUN cohort. Methods: A Cox proportional-hazard analysis was conducted to estimate the hazard ratio and their 95% confidence interval of stroke according to the metabolic health and obesity states based on TyG index and Adult Treatment Panel-III criteria, during 9.1 years of follow-up. Results: After 50,056.2 person-years of follow-up, 162 subjects developed an ischemic stroke (incidence rate 3.23 per 1000 person-years). Metabolically healthy obese subjects did not show greater risk of stroke, while metabolically unhealthy participants, obese and non-obese, had an increased risk of stroke, compared with healthy non-obese. The hazard ratios for the multivariable adjusted model were 1.55 (95% CI: 1.36–1.77) and 1.86 (95% CI: 1.57–2.21), respectively. Conclusions: Metabolically unhealthy individuals exhibited a greater risk of ischemic stroke than metabolically healthy obese individuals.
- Repercussions of absolute and time-rated BMI "yo-yo" fluctuations on cardiovascular stress-related morbidities within the vascular-metabolic CUN cohort(Lausanne: Frontiers Research Foundation, 2023) Sanchez-Iñigo, L. (Laura); Navarro-Gonzalez, D. (David); Martinez-Urbistondo, D. (Diego); Pastrana-Delgado, J. (Juan); Fernandez-Montero, A. (Alejandro); Martinez, J.A. (José Alfredo)Aims: The association between body mass index (BMI) fluctuation and BMI fluctuation rate with cardiovascular stress morbidities in a Caucasian European cohort was evaluated to ascertain the impact of weight cycling. Methods: A total of 4,312 patients of the Vascular-Metabolic CUN cohort (VMCUN cohort) were examined and followed up during 9.35 years ( ± 4.39). Cox proportional hazard ratio analyses were performed to assess the risk of developing cardiovascular stress-related diseases (CVDs) across quartiles of BMI fluctuation, measured as the average successive variability (ASV) (ASV = |BMIt0 - BMIt1| + |BMIt1 - BMIt2| + |BMIt2-BMIt3| +…+ |BMItn - 1 - BMItn|/n - 1), and quartiles of BMI fluctuation rate (ASV/year). Results: There were 436 incident cases of CVD-associated events involving 40,323.32 person-years of follow-up. A progressively increased risk of CVD in subjects with greater ASV levels was found. Also, a higher level of ASV/year was significantly associated with an increased risk of developing CVD stress independent of confounding factors with a value of 3.71 (95% CI: 2.71-5.07) for those in the highest quartile and 1.82 (95% CI: 1.33-2.50) for those in the third quartile. Conclusions: The BMI fluctuation rate seems to be a better predictor than BMI fluctuation of the potential development of cardiovascular stress morbidities. The time-rated weight fluctuations are apparently more determinant in increasing the risk of a CVD than the weight fluctuation itself, which is remarkable in subjects under "yo-yo" weight patterns for precision medicine.
- Interactive role of surrogate liver fibrosis assessment and insulin resistance on the incidence of major cardiovascular events(Basel MDPI, 2022) Martínez‑Urbistondo, D. (Diego); D'Avola, D. (Delia); Navarro-Gonzalez, D. (David); Sanchez-Iñigo, L. (Laura); Fernandez-Montero, A. (Alejandro); Pérez-Díaz-Campo, N. (Nuria) del; Bugianesi, E. (Elisabetta); Martinez, J.A. (José Alfredo); Pastrana-Delgado, J. (Juan)Introduction: The combination of easy-to-obtain validated biomarkers is interesting in the prognostic evaluation of patients at cardiovascular risk in a precision medicine scenario. The evaluation of the effect modification of insulin resistance and liver fibrosis with the Triglyceride-Glucose index (TyG) and Fibrosis-4 index (FIB4) might provide prognostic information in patients at cardiovascular risk. Patients and methods: A retrospective cohort study was performed with 2055 patients recruited in the Vascular Metabolic CUN cohort. The studied outcome was the incidence rate of major cardiovascular events (MACE). The Systematic Coronary Risk Evaluation (SCORE), FIB4 and TyG indexes were calculated according to validated formulas. Results: FIB4 and TyG showed a synergistic interaction using validated cut-offs for both indexes in the prediction of MACE (Hazard ratio (HR) 1.05 CI95% 1.01-1.08) which remained after adjustment by age, sex, SCORE subgroup, presence of diabetes, or previous MACE using standardized cut-off (HR 2.29 CI95% 1.33-3.94). Finally, a subgroup with significant TyG and FIB4 showed a higher cardiovascular risk in the study population (adjusted HR 3.34 CI 95% 1.94-5.77). Conclusion: The combined interpretation of TyG and FIB4 indexes might have a potential predictive value of major cardiovascular events.