An official American Thoracic Society Statement: pulmonary hypertension phenotypes

Abstract

Background: Current classification of pulmonary hypertension (PH) is based on a relatively simple combination of patient characteristics and hemodynamics. This limits customization of treatment, and lacks the clarity of a more granular identification based on individual patient phenotypes. Rapid advances in mechanistic understanding of the disease, improved imaging methods, and innovative biomarkers now provide an opportunity to define PH phenotypes on the basis of biomarkers, advanced imaging, and pathobiology. This document organizes our current understanding of PH phenotypes and identifies gaps in our knowledge.

Methods: A multidisciplinary committee with expertise in clinical care (pulmonary, cardiology, pediatrics, and pathology), clinical research, and/or basic science in the areas of PH identified important questions and reviewed and synthesized the literature.

Results: This document describes selected PH phenotypes and serves as an initial platform to define additional relevant phenotypes as new knowledge is generated. The biggest gaps in our knowledge stem from the fact that our present understanding of PH phenotypes has not come from any particularly organized effort to identify such phenotypes, but rather from reinterpreting studies and reports that were designed and performed for other purposes.

Conclusions: Accurate phenotyping of PH can be used in research studies to increase the homogeneity of study cohorts. Once the ability of the phenotypes to predict outcomes has been validated, phenotyping may also be useful for determining prognosis and guiding treatment. This important next step in PH patient care can optimally be addressed through a consortium of study sites with well-defined goals, tasks, and structure. Planning and support for this could include the National Institutes of Health and the U.S. Food and Drug Administration, with industry and foundation partnerships.

Figure 1.

Deep phenotyping calls for measuring and integrating genomics, transcriptomics, proteomics, metabolomics, cell biology and tissue functioning, and imaging. High-throughput and large-scale measurements are emerging as epidemiological tools, with tools for genetic measurements leading the way. Genomics is currently being used in the form of genome-wide association studies, and large-scale candidate genotyping is starting to be done. Transcriptomics measures gene expression at the mRNA level, and by extrapolation it estimates expression at the protein level (dotted line). Technically, this method is relatively easy to use, but uncertainty about translational efficiencies and posttranslational modifications limits its effectiveness in the long run. Proteomics directly addresses these issues, but is technically challenging at present. Metabolomics has emerged as a potential deep phenotyping tool but, as for proteomics, technical issues limit its current use. Integrated metabolomics holds potential for allowing deep phenotyping at the tissue level (dotted line). Cell biological approaches essentially consider small-scale physiological phenotypes, and may provide critical intermediate phenotypes that may elucidate genotype–phenotype associations (phenomics). The use of tissue arrays provides information on the tissue distribution of proteins, and high-throughput methods are emerging. Both high-resolution anatomical imaging and functional imaging are currently being used in epidemiological research to provide more detailed intermediate, and in some cases subclinical (preclinical), phenotypes. Reproduced by permission from Reference .