Detection of potentially myocardial infarction susceptible individuals in indian population: a mathematical model based on copper and zinc status.

Zinc (Zn) and copper (Cu) concentrations in hair and urine of patients diagnosed and hospitalized for myocardial infarction (MI patients) and in their descendants (MI descendants) were estimated and compared with their age-matched healthy volunteers with no family history of MI (control group and control descendants). The data revealed approximately twofold higher Zn and twofold lower Cu in the urine of the patients; Zn was lower and Cu was higher in the urine of MI descendants than those of the patients (p < 0.001), but Zn in hair and urine was higher and Cu in hair was lower in MI descendants compared with their control counterparts (p < 0.001). The data suggested that there was a consistent rise in Zn and fall in Cu reserves in the genetically predisposed subjects (MI descendants) prior to the manifestation of clinical symptoms. Based on this, the data were subjected to logistic regression and a model was obtained to predict the susceptibility to MI (LR-MI), having impact factors values as follows: constant (C), -3.342; impact factor of body mass index, -0.776; impact factor of hair Zn, -2.449; impact factor of urine Zn, +3.441; impact factor of hair Cu, -15.077; impact factor of urine Cu, -24.153. For the equation Y = e(x)/(1 + e(x)), the value of x was obtained as follows: -3.342 + [BMI (kg/m2) (-0.776)] + [Hair Zn (micromol/g) (-2.449)] + [Urine Zn (micromol/L) (3.441)] + [Hair Cu (micromol/g) (-15.077)] + [Urine Cu (micromol/L) (-24.153)]. On substituting the values of BMI, hair Zn, urine Zn, hair Cu, and urine Cu in x, the response variable Y as zero for healthy controls and 0.99 or 99.9% susceptibility in MI patients were obtained. In between these two extremes, the response variable ranged between 0 and 0.99 or 99.9% susceptibility to MI in their descendants. It is envisaged that the MI patients have an operational component of a genetic disorder of ionic imbalance at a young age that can be exploited in making a prediction of susceptibility to heart stroke in individuals much before its onset and diagnosis in asymptomatic patients, particularly in genetic and epidemiological studies of MI.