Data from: Age of heart disease presentation and dysmorphic nuclei in patients with LMNA mutations

Nuclear shape defects are a distinguishing characteristic in
laminopathies, cancers, and other pathologies. Correlating these defects
to the symptoms, mechanisms, and progression of disease requires unbiased,
quantitative, and high-throughput means of quantifying nuclear morphology.
To accomplish this, we developed a method of automatically segmenting
fluorescently stained nuclei in 2D microscopy images and then classifying
them as normal or dysmorphic based on three geometric features of the
nucleus using a package of Matlab codes. As a test case, cultured
skin-fibroblast nuclei of individuals possessing LMNA splice-site mutation
(c.357-2A>G), LMNA nonsense mutation (c.736 C>T, pQ246X) in
exon 4, LMNA missense mutation (c.1003C>T, pR335W) in exon 6,
Hutchinson-Gilford Progeria Syndrome, and no LMNA mutations were analyzed.
For each cell type, the percentage of dysmorphic nuclei, and other
morphological features such as average nuclear area and average
eccentricity were obtained. Compared to blind observers, our procedure
implemented in Matlab codes possessed similar accuracy to manual counting
of dysmorphic nuclei while being significantly more consistent. The
automatic quantification of nuclear defects revealed a correlation between
in vitro results and age of patients for initial symptom onset. Our
results demonstrate the method's utility in experimental studies of
diseases affecting nuclear shape through automated, unbiased, and accurate
identification of dysmorphic nuclei.