Search

Abstract High altitude acclimatization and disease have been the centerpiece of investigations concerning human health at high altitude. Almost all investigations have focused on either understanding and ameliorating high altitude disease or finding better methods of acclimatization/training at high altitude. The aspect of altitude de-induction/de-acclimatization has remained clouded despite the fact that it was documented since the first decade of twentieth century. A few recent studies, particularly in China, have stated unanimously that high altitude de-acclimatization involved multiple observable clinical symptoms ranging from headache to abdominal distention. These symptoms have been collectively referred to as “high altitude de-acclimatization syndrome” (HADAS). However, computational omics and network biology centric investigations concerning HADAS are nascent. In this study, we focus on the quantitative proteo-informatics, especially network biology, of human plasma proteome in individuals who successfully descended from high altitude areas after a stay of 120 days. In brief, the protein list was uploaded into STRING and IPA to compute z-score based cut-offs which were used to analyze the directionality and significance of various identified protein networks as well as the proteins within them. Relevant upstream regulators extracted using computational strategies were also validated. Time-points till the 180th day of de-induction have been investigated to comparatively assess the changes in the plasma proteome and protein pathways of such individuals since the 7th day of arrival at altitude. Our investigation revealed extensive effects of de-induction on lipid metabolism, inflammation and innate immune system as well as coagulation system. This novel study provides a conceptual framework for formulating therapeutic strategies to ease the symptoms of HADAS during de-acclimatization. Such strategies should focus on normalization of lipid metabolism, inflammatory signaling and coagulation systems.

Abstract Millions of people worldwide visit, live or work in the hypoxic environment encountered at high altitudes and it is important to understand the biomolecular responses to this stress. This would help design mitigation strategies for high altitude illnesses. In spite of a number of studies spanning over 100 years, still the complex mechanisms controlling acclimatization to hypoxia remain largely unknown. To identify potential diagnostic, therapeutic and predictive markers for HA stress, it is important to comprehensively compare and analyse these studies. Towards this goal, HighAltitudeOmicsDB is a unique resource that provides a comprehensive, curated, user-friendly and detailed compilation of various genes/proteins which have been experimentally validated to be associated with various HA conditions, their protein–protein interactions (PPIs) and gene ontology (GO) semantic similarities. For each database entry, HighAltitudeOmicsDB additionally stores the level of regulation (up/down-regulation), fold change, study control group, duration and altitude of exposure, tissue of expression, source organism, level of hypoxia, method of experimental validation, place/country of study, ethnicity, geographical location etc. The database also collates information on disease and drug association, tissue-specific expression level, GO and KEGG pathway associations. The web resource is a unique server platform that offers interactive PPI networks and GO semantic similarity matrices among the interactors.These unique features help to offer mechanistic insights into the disease pathology. Hence, HighAltitudeOmicsDBis a unique platform for researchers working in this area to explore, fetch, compare and analyse HA-associated genes/proteins, their PPI networks, and GO semantic similarities. The database is available at http://www.altitudeomicsdb.in .