Cells (Dec 2021)
Alterations in SLC4A2, SLC26A7 and SLC26A9 Drive Acid–Base Imbalance in Gastric Neuroendocrine Tumors and Uncover a Novel Mechanism for a Co-Occurring Polyautoimmune Scenario
Abstract
Autoimmune polyendocrine syndrome (APS) is assumed to involve an immune system malfunction and entails several autoimmune diseases co-occurring in different tissues of the same patient; however, they are orphans of its accurate diagnosis, as its genetic basis and pathogenic mechanism are not understood. Our previous studies uncovered alterations in the ATPase H+/K+ Transporting Subunit Alpha (ATP4A) proton pump that triggered an internal cell acid–base imbalance, offering an autoimmune scenario for atrophic gastritis and gastric neuroendocrine tumors with secondary autoimmune pathologies. Here, we propose the genetic exploration of APS involving gastric disease to understand the underlying pathogenic mechanism of the polyautoimmune scenario. The whole exome sequencing (WES) study of five autoimmune thyrogastric families uncovered different pathogenic variants in SLC4A2, SLC26A7 and SLC26A9, which cotransport together with ATP4A. Exploratory in vitro studies suggested that the uncovered genes were involved in a pathogenic mechanism based on the alteration of the acid–base balance. Thus, we built a custom gene panel with 12 genes based on the suggested mechanism to evaluate a new series of 69 APS patients. In total, 64 filtered putatively damaging variants in the 12 genes of the panel were found in 54.17% of the studied patients and none of the healthy controls. Our studies reveal a constellation of solute carriers that co-express in the tissues affected with different autoimmune diseases, proposing a unique genetic origin for co-occurring pathologies. These results settle a new-fangled genetics-based mechanism for polyautoimmunity that explains not only gastric disease, but also thyrogastric pathology and disease co-occurrence in APS that are different from clinical incidental findings. This opens a new window leading to the prediction and diagnosis of co-occurring autoimmune diseases and clinical management of patients.
Keywords
