DIFFERENTIAL EXPRESSION OF REG-I AND REG-II GENES DURING AGING IN THENORMAL MOUSE

A cDNA termed reg (for regenerating gene) has been isolated from a rat pancreatic DMA library, peg expression has been shown to correlate wi th changes in beta cell mass and function. This finding has been recen tly challenged by studies showing a non-beta-cell-dependent regulation of reg expression. All studies to date, however, have neglected the f act that two nonallelic reg genes (reg-I and reg-II) exist in several species. In studying the regulation of each individual copy gene, we i nvestigated reg-I and -II gene expression in a naturally occurring mod ification of beta-cell physiology normal aging. RNA was isolated from individual pancreata of 1-, 3-, 9-, 20-, and 30-month-old C5BL/6J mice (n greater than or equal to 3 per group) and subjected to slot-blot a nalysis using homologous probes for reg-I, reg-II, insulin, and elasta se-1. A progressive age-dependent decrease in total reg mRNA levels (r eg-I and -II) was detected. At 30 months of age, total reg mRNA levels were approximately 45% of the level detected in 1-month-old mice (p = .01). This paralleled the decrease in insulin mRNA levels (p = .01), which fell below 50%; by contrast, mRNA levels for elastase-1 increase d with age (p = .05). Analysis of RNA isolated from purified islets di d not reveal any mRNA for reg, suggesting that in the normal mouse, re g is primarily a product of the exocrine pancreas. Reg mRNA were detec table in RNA extracts from stomach, duodenum, and small intestine. By hybridization bf total pancreatic RNA with oligonucleotide probes whic h specifically recognize reg-I or reg-II sequences, we show that reg-I mRNA levels declined with age (p = .001) while reg-II mRNA levels rem ained unchanged These data demonstrate that in mouse pancreas the two nonallelic reg genes are differentially expressed during aging and tha t the decrease in reg-I mRNA levels parallels the decrease in insulin gene expression. Differential regulation of reg-I and reg-II genes may explain the presence of conflicting data in the current literature.