Open AccessPrediction of DNA Integrity from Morphological Parameters Using a Single‐Sperm DNA Fragmentation Index Assay
Author(s) -
Wang Yihe,
Riordon Jason,
Kong Tian,
Xu Yi,
Nguyen Brian,
Zhong Junjie,
You Jae Bem,
Lagunov Alexander,
Hannam Thomas G.,
Jarvi Keith,
Sinton David
Publication year - 2019
Publication title -
advanced science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.388
H-Index - 100
ISSN - 2198-3844
DOI - 10.1002/advs.201900712
Subject(s) - sperm , dna fragmentation , acridine orange , biology , logistic regression , linear regression , andrology , statistics , mathematics , medicine , genetics , staining , apoptosis , programmed cell death
Intracytoplasmic sperm injection is a popular form of in vitro fertilization, where single sperm are selected by a clinician and injected into an egg. Whereas clinicians employ general morphology‐based guidelines to select the healthiest‐looking sperm, it remains unclear to what extent an individual sperm's physical parameters correlate with the quality of internal DNA cargo—a measurement that cannot be obtained without first damaging the sperm. Herein, a single‐cell DNA fragmentation index (DFI) assay is demonstrated, which combines the single‐cell nature of the acridine orange test with the quantitative aspect of the sperm chromatin structure assay, to create a database of DFI‐scored brightfield images. Two regression predictive models, linear and nonlinear regression, are used to quantify the correlations between individual sperm morphological parameters and DFI score (with model test r at 0.558 and 0.620 for linear and nonlinear regression models, respectively). The sample is also split into two categories of either relatively good or bad DFIs and a classification predictive model based on logistic regression is used to categorize sperm, resulting in a test accuracy of 0.827. Here, the first systematic study is presented on the correlation and prediction of sperm DNA integrity from morphological parameters at the single‐cell level.