Comparison of different statistical approaches to evaluate morphometric sperm subpopulations in men

Abstract

This study was designed to characterize morphometric sperm subpopulations in normozoospermic men by using different statistical methods and examining their suitability to classify correctly different sperm nuclear morphologies present in human ejaculates. Ejaculates from 21 normozoospermic men were collected for the study. After semen collection and analysis, samples were prepared for morphometric determination. At least 200 spermatozoa per sample were assessed for sperm morphometry by computer-assisted sperm morphometry analysis (CASA-Morph) using fluorescence. Clustering and discriminant procedures were performed to identify sperm subpopulations from the morphometric data obtained. Clustering procedures resulted in the classification of spermatozoa into three morphometric subpopulations (large-round 30.4%, small-round 46.6%, and large-elongated 22.9%). In the second analysis, using discriminant methods, the classification was made independently of size and shape. Three morphological categories according to nuclear size (small 13.07 μm2) and four categories were defined on 400 canonical cells (100 × 4) from 10 men according to sperm nuclear shape (oval, pyriform, round, and elongated). Thereafter, the resulting classification functions were used to categorize 4200 spermatozoa from 21 men. Differences in the class distribution were observed among men from both clustering and discriminant procedures. It was concluded that the combination of CASA-Morph fluorescence-based technology with multivariate cluster or discriminant analyses provides new information on the description of different morphometric sperm subpopulations in normal individuals, and that important variations in the distribution of morphometric sperm subpopulations may exist between men, with possible functional implications.

Keywords

• computer-assisted sperm morphometry analysis; man; sperm subpopulations