Pulmonary arterial hypertension (PAH) is a rare yet fatal condition characterized by progressive proliferation, deposited collagen, and pulmonary vasculature remodeling, which causes right heart failure and, eventually, death. The prognosis of PAH is poor, and its pathogenesis remains unclear. Recently, mounting evidence has indicated the involvement of aberrant glucose/energy metabolism in PAH pathogenesis (Xu et al., 2021; Pokharel et al., 2023). PAH and cancer have been found to share a metabolic pathway known as the Warburg effect (Rehman and Archer, 2010) and several studies have identified this effect in pulmonary vascular cells (Cao et al., 2019; Kovacs et al., 2019). The Warburg effect, characterized by elevated lactate production through aerobic glycolysis (Fig. 1), was first identified by Otto Warburg in the 1920s (Warburg, 1928). He observed that tumor cells preferentially used anaerobic glycolysis to fuel their rapid growth, even in the presence of oxygen (Warburg, 1956). In recent years, growing evidence suggests that the Warburg effect also occurs in non-cancerous diseases, such as PAH (Chen et al., 2018b). Pulmonary vascular cells in PAH have a glycolytic phenotype, characterized by increased glycolysis and inhibition of glucose oxidation, previously described as the Warburg effect (McMurtry et al., 2004; Peng et al., 2016). Key glycolytic enzymes are important components of the Warburg effect and play crucial roles in disease pathogenesis. For example, in gastric cancer, Hexokinase 2 (HK2), a downstream target of the Wilms’ tumor 1-associated protein, plays a pivotal role in enhancing glucose uptake and metabolism. This, in turn, promotes cancer cell proliferation and tumor development (Yu et al., 2021). Additionally, monocytes and macrophages derived from patients with atherosclerotic coronary artery disease exhibit dimerization and nuclear translocation of M2-type pyruvate kinase (PKM2), a crucial glycolytic enzyme (Shirai et al., 2016). These changes exacerbate atherosclerosis progression. Furthermore, myocardial fibrosis and elevated plasma levels of 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase 3 (PFKFB3) are positively correlated in patients suffering from chronic heart failure (Zeng et al., 2022). Hence, conducting a comprehensive investigation of the alterations in key glycolytic enzymes in response to the Warburg effect is imperative. Such research is essential for a deeper understanding of the metabolic and molecular characteristics of these diseases.

The investigation into the Warburg effect in PAH has been ongoing for the past decade (Rehman and Archer, 2010). Over this period, numerous researchers have dedicated their efforts to exploring the impact of the Warburg effect on pulmonary artery vascular cells in patients with PAH. This field of research aims to unravel the intricate interactions between metabolic events and the onset and progression of PAH. A growing body of evidence suggests that key enzymes within the glycolytic pathway play crucial and multifaceted roles in governing the Warburg effect in the context of PAH. Consequently, the inhibition of glycolytic pathways may emerge as a promising avenue in PAH research, paving the way for the development of novel targeted therapies to effectively manage the condition.

Key enzymes in glycolysis are associated with widespread metabolic abnormalities in pulmonary arterial hypertension (PAH) relevant cell types, including pulmonary vascular cells. Metabolic alterations schematically represented include heightened glycolysis driven by hexokinase (HK), upstream glycolytic player 6-phosphofructo-2kinase/fructose-2,6-biphosphatase 3 (PFKFB3), pyruvate kinase M2 (PKM2) and lactate dehydrogenase (LDH); increased P2 receptors, forkhead transcription factor forkhead box O1 (FOXO1), polypyrimidine tract-binding protein 1 (PTBP1), Hypoxia inducible factor (HIF) expression and activity; reduced expression of glycogen synthesis kinase 3β (GSK-3β). The red text in the figure denotes abnormal expression/pathway activity. Thickened red and blue arrows denote upregulated and downregulated expression/pathways respectively.