A Risk Score with Additional Four Independent Factors to Predict the Incidence and Recovery from Metabolic Syndrome: Development and Validation in Large Japanese Cohorts

<div><p>Background</p><p>Although many risk factors for Metabolic syndrome (MetS) have been reported, there is no clinical score that predicts its incidence. The purposes of this study were to create and validate a risk score for predicting both incidence and recovery from MetS in a large cohort.</p><p>Methods</p><p>Subjects without MetS at enrollment (n = 13,634) were randomly divided into 2 groups and followed to record incidence of MetS. We also examined recovery from it in rest 2,743 individuals with prevalent MetS.</p><p>Results</p><p>During median follow-up of 3.0 years, 878 subjects in the derivation and 757 in validation cohorts developed MetS. Multiple logistic regression analysis identified 12 independent variables from the derivation cohort and initial score for subsequent MetS was created, which showed good discrimination both in the derivation (c-statistics 0.82) and validation cohorts (0.83). The predictability of the initial score for recovery from MetS was tested in the 2,743 MetS population (906 subjects recovered from MetS), where nine variables (including age, sex, γ-glutamyl transpeptidase, uric acid and five MetS diagnostic criteria constituents.) remained significant. Then, the final score was created using the nine variables. This score significantly predicted both the recovery from MetS (c-statistics 0.70, p<0.001, 78% sensitivity and 54% specificity) and incident MetS (c-statistics 0.80) with an incremental discriminative ability over the model derived from five factors used in the diagnosis of MetS (continuous net reclassification improvement: 0.35, p < 0.001 and integrated discrimination improvement: 0.01, p<0.001).</p><p>Conclusions</p><p>We identified four additional independent risk factors associated with subsequent MetS, developed and validated a risk score to predict both incident and recovery from MetS.</p></div

Multivariate Logistic Regression Analysis for the Recovery from Metabolic Syndrome and Risk Scoring System in individuals with Prevalent Metabolic Syndrome.

<p>*Odds ratios to predict recovery from MetS (e.g. Odds ratio<1 means less likely to be recovered subsequently).</p><p>Other Abbreviations as in Tables <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133884#pone.0133884.t001" target="_blank">1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133884#pone.0133884.t002" target="_blank">2</a>.</p><p>Multivariate Logistic Regression Analysis for the Recovery from Metabolic Syndrome and Risk Scoring System in individuals with Prevalent Metabolic Syndrome.</p

Final score predicts incidence of MetS in the entire Non-MetS population.

<p>Final risk scores for incident MetS were calculated for each individual participant in the entire population without MetS at enrollment (derivation and validation cohorts combined, n = 13,634) as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133884#pone.0133884.t004" target="_blank">Table 4</a>. Incidence (%) in the bottom table represents the developed MetS cases in the population (n = 1,635). I bars represent 95% confidential interval (CI). Other abbreviations as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133884#pone.0133884.g001" target="_blank">Fig 1</a>.</p

Comparison of area under the curves between final risk score and model derived from only the five MetS diagnostic components.

<p>The final score had a significantly larger area under the curve compared with the area obtained using the model that was derived from only the five MetS diagnostic components (0.80 vs. 0.79, p < 0.0001). Abbreviations as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133884#pone.0133884.g001" target="_blank">Fig 1</a>.</p

The study flow chart.

<p>MetS: metabolic syndrome.</p

Receiver-operating characteristics curves and predicted risk versus observed risk of outcomes of a final risk score for predicting MetS and recovery from it.

<p><b>(A)</b> In MetS cohort, the final risk model predicted the recovery from MetS. <b>(B)</b> The final score predicted subsequent MetS in the whole population without MetS at enrollment. <b>(C)</b> Calibration plots for prediction of recovery from MetS in the prevalent MetS population at enrollment were good with an intercept of 0.95, a slope of 0.96, and an R² of 97% (p <0.001). <b>(D)</b> The final score demonstrated good calibration for predicting incident MetS in the whole population with an intercept of 0.69, a slope of 0.95, and an R² of 98% (p <0.001). Abbreviations as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133884#pone.0133884.g001" target="_blank">Fig 1</a>.</p

TGs stored in BAT in DKO mice were more depleted after cold exposure in the fasted state.

<p>The mice were exposed to a cold environment (4°C) with or without prior fasting. (A and B) TG concentration in BAT. (C and D) The total amount of TGs in interscapular BAT was calculated from the concentration of TGs in BAT and the weight of BAT. n = 4–5/group. *p<0.05; **p<0.01; ***p<0.001. (E) Gross appearance of BAT. (F) Hematoxylin/eosin staining of BAT. Bar indicates 50 µm.</p

The reduced weight of BAT in the DKO mice subjected to a 20 h fast was not altered after cold exposure.

<p>The mice were exposed to a cold environment (4°C) with or without prior fasting. (A and B) Original body weight (BW) of mice in each group before cold exposure. (A) BW of the mice included in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090825#pone-0090825-g004" target="_blank">Figures 4C and 4E</a> before the experiment. (B) Left panel: BW of mice included in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090825#pone-0090825-g004" target="_blank">Figures 4D and 4F</a> before fasting. Right panel: BW of mice included in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090825#pone-0090825-g004" target="_blank">Figures 4D and 4F</a> after a 20 h fast but before cold exposure. (C and D) Weight of interscapular BAT in each group before and after cold exposure in the fed (C) and the fasted states (D). (E and F) The ratio of the BAT weight to the BW before fasting was calculated from the data shown above. Note that the BAT is significantly shrunk after fasting or cold exposure and that the reduced weight of BAT in the DKO mice after a 20 h fast was not altered after cold exposure. n = 4–5/group. *p<0.05; **p<0.01; ***p<0.001.</p

Reduced induction of genes associated with thermogenesis in BAT in both WT and DKO mice after cold exposure in the fasted state.

<p>The mice were maintained at room temperature or in a cold room (4°C) for 4 h with or without prior fasting. The total RNA from BAT was extracted for quantitative real-time PCR. n = 4–5/group. *p<0.05; **p<0.01; ***p<0.001.</p

Very low glucose levels in FABP4/5 DKO mice in the fasted state regardless of cold exposure.

<p>(A to H) Blood was collected from the retro-orbital plexus before and after cold exposure to measure the serum levels of glucose (A and B), TGs (C and D), NEFAs (E and F), and ketone bodies (G and H) in the fed (A, C, E, and G) and the fasted states (B, D, F, and H). n = 5–6/group. *p<0.05; **p<0.01; ***p<0.001. Note that the blood was collected 4 h after cold exposure for the fed groups and 2 h after cold exposure for the fasted groups because many DKO mice died during prolonged cold exposure in the fasted state.</p