Role of endocrine PACAP in age-related diseases

Front Endocrinol (Lausanne). 2023 Mar 9:14:1118927. doi: 10.3389/fendo.2023.1118927. eCollection 2023.

Abstract

Pituitary adenylate cyclase activating polypeptide (PACAP) is a conserved neuropeptide, which confers diverse anti-aging endocrine and paracrine/autocrine effects, including anti-apoptotic, anti-inflammatory and antioxidant action. The results of the in vivo and in vitro experiments show that increasing emphasis is being placed on the diagnostic/prognostic biomarker potential of this neuropeptide in a wide array of age-related diseases. After the initial findings regarding the presence and alteration of PACAP in different body fluids in physiological processes, an increasing number of studies have focused on the changes of its levels in various pathological conditions associated with advanced aging. Until 2016 - when the results of previous human studies were reviewed - a vast majority of the studies had dealt with age-related neurological diseases, like cerebrovascular and neurodegenerative diseases, multiple sclerosis, as well as some other common diseases in elderly such as migraine, traumatic brain injury and post-traumatic stress disorder, chronic hepatitis and nephrotic syndrome. The aim of this review is to summarize the old and the new results and highlight those 'classical' and emerging clinical fields in which PACAP may become subject to further investigation as a diagnostic and/or prognostic biomarker in age-related diseases.

Keywords: PACAP; aging; biomarker; body fluids; diseases; endocrine.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aging
  • Biomarkers
  • Brain Injuries, Traumatic*
  • Humans
  • Pituitary Adenylate Cyclase-Activating Polypeptide*
  • Prognosis

Substances

  • Pituitary Adenylate Cyclase-Activating Polypeptide
  • Biomarkers

Grants and funding

This work was supported by the Health Sub–programme of the 2021 Thematic Excellence Program of the Ministry for Innovation and Technology in Hungary, within the framework of the EGA–16 project of the University of Pecs (TKP2021-EGA-16). The study was further supported by the National Research, Development and Innovation Fund K119759, K135457 and National Academy of Scientists Education, National Brain Research Program NAP3.0., ELKH–TKI–1401.