A novel and robust method for testing bimodality and characterizing porcine adipocytes of adipose tissue of 5 purebred lines of pig

Abstract

Adipocyte sizes from adipose tissue of mature animals form a bimodal distribution, thus reporting mean cell size is misleading. The objectives of this study were to develop a robust method for testing bimodality of porcine adipocytes, describe the size distribution with an informative metric, and statistically test hypertrophy and appearance of new small adipocytes, possibly resulting from hyperplasia or lipid filling of previously divided fibroblastic cells. Ninety-three percent of adipose samples measured were bimodal (P < 0.0001); therefore, we describe and propose a method of testing hyperplasia or lipid filling of previously divided fibroblastic cells based upon the probability of an adipocyte falling into 2 chosen competing “bins” as adiposity increases. We also conclude that increased adiposity is correlated positively with an adipocyte being found in the minor mode (r = 0.46) and correlated negatively with an adipocyte being found in the major mode (r = −0.22), providing evidence of either hyperplasia or lipid filling of previously divided fibroblastic cells. We additionally conclude that as adiposity increases, the mode of the major distribution of cells occurs at a larger diameter of adipocyte, indicating hypertrophy.

Patterns of ‘Analytical Irreproducibility’ in Multimodal Diseases

“…In our report thus far, we have used unimodal simulations to show how random sampling affects statistical results. However, there has been an increased interest in understanding data multimodality in various biological processes 52,53 for which new statistical approaches have been proposed. Methods to simulate multimodal distributions are however not trivial, in part due to the unknown nature of multimodality in biological processes.…”

“…The dip test 61 quantifies departures from unimodality and does not require a priori knowledge of potential multimodality and thus information can be easily interpreted from the test statistics and the P-value 62,63 . Although reports and comparative analysis of statistical performance have been described for various multimodality tests ( e.g ., Dip test, Bimodality test, Silverman’s test and likelihood ratio test 64 , and kernel methods), including simpler alternatives that use benchmarks to determine the influence of data outliers 52,53,62,65 , it is important to emphasize that every method depends on its intended application and data set (and data shape), 66 and therefore must be accompanied by the inspection of the data distributions (‘shoulders’, ‘bumps’, and respective ‘valleys’).…”

Patterns of 'Analytical Irreproducibility' in Multimodal Diseases

“…Therefore, personalized research has the potential to identify different functional microbiome subtypes (on a given outcome, e.g., assay or hGM-FMT mice) for one individual. and kernel methods), including simpler alternatives that use benchmarks to determine the in uence of data outliers [52,53,62,65], it is important to emphasize that every method depends on its intended application and data set (and data shape), [66] and therefore must be accompanied by the inspection of the data distributions ('shoulders', 'bumps', and respective 'valleys').…”

Cellularity Description of Adipose Depots in Domesticated Animals

“…Alfonso and Mendizabal [81] proposed using the bimodality coefficient (BC) [83] and the dip statistic [84] to test the unimodal distribution of the data without having to assume any distribution underlying the bimodal distribution, though other approaches have also been described [85]. If the data prove not to be unimodal, the bimodal adipocyte size distribution can be described by estimating the two distribution modes and the proportion of adipocytes located under the inflexion point (nadir) between the two, thus enabling one population of small adipocytes to be differentiated from a second population of large ones.…”

“…Analysing the data in this way allows differences between groups of animals to be described even in the presence of bimodality. Thus, differences between tissues in cattle [68] and pigs [81,85], between breeds [85] and between animals grouped by age [88] and sex [85] have been described. Describing these differences is an essential basis for subsequently studying cell multiplication and differentiation both at the genetic level and at the level of expression, the better to explain the mechanisms of adipose tissue growth and be able to act appropriately so as to modulate them with a view to improving animal production systems.…”