title: Minimizing the effects of multicollinearity in the polynomial regression of age relationships and sex differences in serum levels of pregnenolone sulfate in healthy subjects.
abstract: BACKGROUND
  Pregnenolone sulfate (PregS) is known as a steroid conjugate positively modulating N-methyl-D-aspartate receptors on neuronal membranes. These receptors are responsible for permeability of calcium channels and activation of neuronal function. Neuroactivating effect of PregS is also exerted via non-competitive negative modulation of GABA(A) receptors regulating the chloride influx. Recently, a penetrability of blood-brain barrier for PregS was found in rat, but some experiments in agreement with this finding were reported even earlier. It is known that circulating levels of PregS in human are relatively high depending primarily on age and adrenal activity.
  
  
  METHODS
  Concerning the neuromodulating effect of PregS, we recently evaluated age relationships of PregS in both sexes using polynomial regression models known to bring about the problems of multicollinearity, i.e., strong correlations among independent variables. Several criteria for the selection of suitable bias are demonstrated. Biased estimators based on the generalized principal component regression (GPCR) method avoiding multicollinearity problems are described.
  
  
  RESULTS
  Significant differences were found between men and women in the course of the age dependence of PregS. In women, a significant maximum was found around the 30th year followed by a rapid decline, while the maximum in men was achieved almost 10 years earlier and changes were minor up to the 60th year. The investigation of gender differences and age dependencies in PregS could be of interest given its well-known neurostimulating effect, relatively high serum concentration, and the probable partial permeability of the blood-brain barrier for the steroid conjugate.
  
  
  CONCLUSIONS
  GPCR in combination with the MEP (mean quadric error of prediction) criterion is extremely useful and appealing for constructing biased models. It can also be used for achieving such estimates with regard to keeping the model course corresponding to the data trend, especially in polynomial type regression models.
authors.affiliation: Department of Analytical Chemistry, Faculty of Chemical Technology, Pardubice University, Pardubice, Czech Republic. milan.meloun@upce.cz
authors.forename: Milan
authors.initials: M
authors.lastname: Meloun
authors.forename: Martin
authors.initials: M
authors.lastname: Hill
authors.forename: Helena
authors.initials: H
authors.lastname: Vceláková-Havlíková
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000375:Aging / Q000097:blood*; D002648:Child; D002675:Child, Preschool; D005260:Female; D006262:Health; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D011284:Pregnenolone / Q000097:blood*; D012727:Sex Characteristics
chemical_list: C018370:pregnenolone sulfate; D011284:Pregnenolone