BackgroundRisk stratification plays an essential role in the management of patients with pulmonary arterial hypertension (PAH). The current European guidelines propose a 3-strata model to categorise risk as low, intermediate, or high, based on the expected 1-year mortality. However, with this model, most patients are categorised as intermediate risk. We investigated a modified approach based on 4 risk categories with intermediate risk subdivided into intermediate-low and intermediate-high risk.MethodsWe analysed data from COMPERA, a European pulmonary hypertension registry, and calculated risk at diagnosis and first follow-up based on functional class (FC), 6 min walking distance (6 MWD) and serum levels of brain natriuretic peptide (BNP) or N-terminal fragment of pro-BNP (NT-proBNP), using refined cut-off values. Survival was assessed with Kaplan-Meier analyses, log-rank testing, and Cox proportional hazards models.ResultsData from 1,655 patients with PAH were analysed. Using the 3-strata model, most patients were classified as intermediate risk (76.0% at baseline and 63.9% at first follow-up). The refined 4-strata risk model yielded a more nuanced separation and predicted long-term survival, especially at follow-up assessment. Changes in risk from baseline to follow-up were observed in 31.1% of the patients with the 3-strata model and in 49.2% with the 4-strata model. These changes, including those between the intermediate-low and intermediate-high strata, were associated with changes in long-term mortality risk.ConclusionsModified risk stratification using a 4-strata model based on refined cut-off levels for FC, 6MWD and BNP/NT-proBNP was more sensitive to prognostically relevant changes in risk than the original 3-strata model.

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Background A genetic predisposition can lead to the rare disease pulmonary arterial hypertension (PAH). Most mutations have been identified in the gene BMPR2 in heritable PAH. However, as of today 15 further PAH genes have been described. The exact prevalence across these genes particularly in other PAH forms remains uncertain. We present the distribution of mutations across PAH genes identified at the largest German referral centre for genetic diagnostics in PAH over a course of > 3 years. Methods Our PAH-specific gene diagnostics panel was used to sequence 325 consecutive PAH patients from March 2017 to October 2020. For the first year the panel contained thirteen PAH genes: ACVRL1, BMPR1B, BMPR2, CAV1, EIF2AK4, ENG, GDF2, KCNA5, KCNK3, KLF2, SMAD4, SMAD9 and TBX4.These were extended by the three genes ATP13A3, AQP1 and SOX17 from March 2018 onwards following the genes’ discovery. Results A total of 79 mutations were identified in 74 patients (23%). Of the variants 51 (65%) were located in the gene BMPR2 while the other 28 variants were found in ten further PAH genes. We identified disease-causing variants in the genes AQP1, KCNK3 and SOX17 in families with at least two PAH patients. Mutations were not only detected in patients with heritable and idiopathic but also with associated PAH. Conclusions Genetic defects were identified in 23% of the patients in a total of 11 PAH genes. This illustrates the benefit of the specific gene panel containing all known PAH genes.