21 - Personalized Medicine for Pulmonary Hypertension

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Personalized Medicine for
Pulmonary Hypertension:
The Future Management of Pulmonary
Hypertension Requires a New Taxonomy
Martin R. Wilkins, MD, FMedSci
KEYWORDS
� Pulmonary hypertension � Precision medicine � Genetics � Endophenotypes � Deep-phenotyping
KEY POINTS
� Pulmonary hypertension is an unmet clinical need that presents late in the natural history of the
condition.
� It is a convergent phenotype with a complex molecular pathology.
� The current clinical classification lacks the granularity needed to assist the development and
deployment of new treatments.
� The future treatment of pulmonary hypertension depends on the integration of clinical and molec-
ular information to create a new taxonomy that defines patient clusters coupled to druggable tar-
gets.
om
INTRODUCTION
Pulmonary hypertension (PH), whether defined by
a resting mean pulmonary artery pressure
(mPAP) greater than 20 mm Hg or greater than or
equal to 25 mm Hg, is classified into 5 major
groups by international consensus1 (Box 1). The
classification, first considered in 1973 and revis-
ited at regular intervals since, seeks to include all
clinical conditions associated with the develop-
ment or progression of PH. Patients are assigned
to a major group according to whether their PH
is judged to be precapillary or postcapillary and
the nature of any comorbidities.
Precapillary PH is distributed over Groups 1, 3, 4
and 5 while post-capillary PH is found in Groups 2
and 5.1 Group 1, labeled pulmonary arterial hyper-
tension (PAH), hosts idiopathic (IPAH), heritable
(HPAH), and drug-induced PH, which are diagno-
ses of exclusion of coexisting diseases, alongside
PH caused by congenital heart disease, PH
Dr. Wilkins is supported by the British Heart Foundation
National Heart and Lung Institute, Imperial College Lon
W12 0NN, UK
E-mail address: m.wilkins@imperial.ac.uk
Clin Chest Med 42 (2021) 207–216
https://doi.org/10.1016/j.ccm.2020.10.004
0272-5231/21/� 2020 The Author. Published by Elsevier Inc
(http://creativecommons.org/licenses/by/4.0/).
associated with connective tissue lung disease,
and porto-pulmonary PH. Group 3 includes lung
disease, including idiopathic pulmonary fibrosis,
obstructive sleep apnea and chronic obstructive
pulmonary disease, and hypoxia-induced PH.
Group 4 is PH caused by chronic thromboembolic
disease. Left-sided heart failure from whatever
cause is placed in Group 2. Group 5 includes PH
from a miscellaneous collection of comorbidities.
This classification is used to develop and assign
treatments. There has been some success. Drugs
that improve patient symptoms have been
licensed for Group 1 and Group 4. Group 1 and
Group 4 represent rare conditions with unmet clin-
ical needs and an accelerated route to market. But
progress with the development of treatments for
PH in Group 2 and Group 3, the most common
presentations of PH, has been disappointing. Mor-
tality in these groups remains high, with both
elevated pulmonary artery pressure and right
(RE/18/4/34215).
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mailto:m.wilkins@imperial.ac.uk
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https://doi.org/10.1016/j.ccm.2020.10.004
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http://chestmed.theclinics.com
Box 1
Clinical classification of pulmonary
hypertension
Group 1: PAH
Subgroups
� Idiopathic PAH
� Heritable PAH
� Drug- and toxin-induced PAH
� PAH associated with:
� Connective tissue disease
� HIV infection
� Portal hypertension
� Congenital heart disease
� Schistosomiasis
� PAH long-term responders to calcium channel
blockers
� PAH with overt features of venous/capillaries
(pulmonary venous occlusive disease/pulmo-
nary capillary hemangiogenesis) involvement
� Persistent PH of the newborn syndrome
Group 2: PH caused by left heart disease
Subgroups
� PH caused by heart failure with preserved left
ventricular ejection fraction (LVEF)
� PH due to heart failure with reduced LVEF
� Valvular heart disease
� Congenital/acquired cardiovascular condi-
tions leading to postcapillary PH
Group 3: PH caused by lung diseases and/or
hypoxia
Subgroups
� Obstructive lung disease
� Restrictive lung disease
� Other lung disease with mixed restrictive/
obstructive pattern
� Hypoxia without lung disease
� Developmental lung disorders
Group 4: PH caused by pulmonary artery
obstructions
Subgroups
� Chronic thromboembolic PH
� Other pulmonary artery obstructions
Group 5: PH with unclear and/or multifactorial
mechanisms
Subgroups
� Hematological disorders
� Systemic and metabolic disorders
� Others
� Complex congenital heart disease
Abbreviations: PCH, pulmonary capillary hemangio-
matosis; PVOD, pulmonary veno-occlusive disease.
From Simonneau et al. Haemodynamic definitions and
updated clinical classification of pulmonary hyperten-
sion. European Respiratory Journal 53 (1) 1801913;
DOI: 10.1183/13993003.01913-2018 Published 24
January 2019. Reproduced with permission of the �
ERS 2020.
Wilkins208
ventricular dysfunction representing independent
predictors of death.2–4 Even in Group 1, progress
with developing effective therapies is qualified by
a lack of impact on disease progression; these
drugs, particularly in combination, may slow dis-
ease progression but do not arrest or reverse it.
This is evident is survival statistics, which show
that 5-year mortality is near 50%.5
Fortunately, pulmonary vascular disease re-
mains an active area for drug discovery. There is
no shortage of potential therapeutic targets, for
both new chemical entities and repurposed
drugs.6 To improve success, however, future
treatments for PH need to be focused more
acutely on the patient as an individual, rather
than the patient as part of a group, and this re-
quires a new taxonomy of pulmonary vascular
disease.
FIRST, THE PROBLEM WITH AVERAGES
It is widely recognized that patients vary in their
response to drugs. This is evident in all studies
evaluating treatments for PH. It can be easily
overlooked when the data are presented as the
mean change in each study group, even when
shown with confidence intervals. For example,
in a Phase 3 study with imatinib (IMPRES), which
investigated the effects of imatinib in patients
with Group 1 PAH, the mean placebo-corrected
change in 6-minute walk distance (6MWD) after
24 weeks was 32 m (95% confidence interval,
12–52 m; P5.002).7 When the absolute change
in 6MWD is plotted as a distribution, the range
of responses becomes stark (Fig. 1) and difficult
to ignore. The fact that more patients improved
with active treatment is still evident, but it be-
comes clear that some patients did not show a
beneficial response as judged by the change in
their 6MWD.
Various factors, both extrinsic and intrinsic, may
influence the outcome measurement. Some, such
as concomitant medication, comorbidity, and the
genetics of drug transport and metabolism, may
http://10.1183/13993003.01913-2018
Fig. 1. Distribution of change in 6-
minute walk distance after 6 months
treatment with either imatinib or pla-
cebo. (Data from Hoeper MM et al.
Imatinib Mesylate as Add-On Therapy
for Pulmonary Arterial Hypertension:
Results of the Randomized IMPRES
Study Circulation. 2013;127:1128-38.
https://doi.org/10.1161/
CIRCULATIONAHA.112.000765.)
Personalized medicine for pulmonary hypertension 209
affect the pharmacokinetics of the study medica-
tion. Others, such as age, comorbidity, and herita-
ble factors, can affect the pharmacodynamic
response.
Prior consideration is given to these in the
design of clinical trial protocols, with the aim of
minimizing the noise to improve detection of the
signal, but pragmatic factors intervene. A consid-
eration of the process around designing a study
for Group 1 PAH illustrates this. Because the aim
is to find a treatment for pulmonary vascular dis-
ease, these studies start out targeting patients
with idiopathic, heritable, anddrug-induced PAH
to reduce the influence of comorbidity. Boundaries
are set for age, baseline walk distance, hemody-
namics, and licensed therapies. In deciding the in-
clusion and exclusion criteria, there will be a
discussion around whether to enroll patients with
connective tissue disease and what constitutes
significant parenchymal lung disease. Once the
study is started, time pressures on recruitment
from a rare patient population mean that trial pro-
tocols extend inclusion criteria (or patients are
recruited that an adjudication panel might ques-
tion), and the final study population is not so
pure. In the end, patients are recruited from addi-
tional subgroups within Group 1, and so trials fin-
ish with a cohort of patients with mixed
underlying pathology.7–9
If the mean response to the study drug is judged
to be clinically beneficial in a pivotal trial, the study
drug may be licensed for all of Group 1 PAH. The
inclusion of small but representative patients
from other PAH subgroups in Group 1 is used to
justify this. A trivial but enlightening example of
the folly of this approach is to apply it to waist
size. No one would take the average waist size of
a cohort to design a pair of trousers to fit all. Yet
this is what is done for drugs for PAH, driven
admittedly by the desire to offer a treatment for a
desperate medical condition.
At best, this practice may dilute any signal of ef-
ficacy. At worst, the signal may be lost altogether
in the average response, and potential therapies
may be discarded. A post hoc responder analysis
is often used in a successful study to explore
whether benefit is observed across all patient
groups or, in a less successful trial, to determine
whether there is a subgroup that showed some
benefit. Unfortunately, the granularity of informa-
tion available from clinical trials to make this mean-
ingful is poor. Analysts have to rely on a limited
clinical vocabulary and range of investigations.
THE LIMITATIONS OF THE CURRENT CLINICAL
CLASSIFICATION
The clinical classification of PH was never
intended as a guide to drug development.10 It is
understandable that it has been adopted as
such, in the absence of anything else, but it was
first proposed with the aim of collating the clinical
and histologic characteristics of PH.11 Importantly,
it is not based on a deep comprehension of pulmo-
nary vascular disease and plausible drug targets.
Iterative revisions have resulted in a few new sub-
groups or reassigning a patient subgroup to a
different major group, but the major categories
have remained the same. Simple inspection shows
heterogeneity and ambiguity within and between
https://doi.org/10.1161/CIRCULATIONAHA.112.000765
https://doi.org/10.1161/CIRCULATIONAHA.112.000765
Wilkins210
the major groups,1 a statement to a limited under-
standing of underlying pathology. In clinical prac-
tice, patients can move from one subgroup to
another or even a different major group during
the course of their illness.
The problem starts with the defining investiga-
tion of PH. A key measurement in the diagnostic
workup of a patient is the pulmonary artery wedge
pressure (PAWP); it influences the group to which
a PH patient is assigned. Greater than 15 mmHg is
considered to be raised and indicates a high left-
sided filling pressure caused by significant left
heart disease; the patient is placed in Group 2
(or in a few cases, Group 5). This is not always
an easy measurement to make with confi-
dence,12,13 and yet a difference of 1 mm Hg can
define a patient’s diagnostic category and his or
her suitability for licensed targeted treatments.
A further complication is that 12% to 38% of pa-
tients with PH and a raised PAWP have evidence
of a precapillary component to their PH pheno-
type, based on a diastolic pressure gradient of at
least 7 mm Hg or pulmonary vascular resistance
(PVR) greater than 3 Wood units.12 The European
Society of Cardiology and European Respiratory
Society guidelines recognize these patients as
having combined precapillary and postcapillary
PH.14 With an aging population, the number of pa-
tients in this category is likely to grow.
The changing demographics of patients also
adds complexity to the diagnosis of IPAH. IPAH
is now more frequently diagnosed in older
(>55 years) patients, but many in the older age
group have cardiovascular risk factors (eg, coro-
nary artery disease, systemic hypertension, hyper-
lipidemia, or diabetes) that predispose to left heart
disease. IPAH patients with at least 3 cardiovascu-
lar risk factors have been labeled atypical IPAH.15
The risk profiles and demographic characteristics
of patients with atypical IPAH resemble those of
PH with heart failure, particularly heart failure
with preserved ejection fraction (HFpEF); many of
these patients might be regarded as having com-
bined precapillary and postcapillary PH. It has
been proposed that typical IPAH, atypical IPAH,
and HFpEF might form a disease continuum.15
This has implications for clinical trials. Data from
patient registries and from clinical trials indicate
that patients with PAH and additional cardiovascu-
lar risk factors are less responsive to targeted PAH
treatments and show higher discontinuation
rates.9,15–17
The ambiguity extends beyond a discussion of
heart failure. Experts frequently have to make an
assessment about PH in the context of accompa-
nying lung disease, the size of a septal defect, and
the significance of circulating autoantibodies. With
the exception of the response to an acute vasodi-
lator challenge, predicting an increased probability
of response to calcium channel blockade, there
are several additional phenotypes that are not
captured in the current classification. These
include insulin resistance, iron deficiency, and
inflammation, all of which impact on prognosis
and so are clinically relevant.
AND THEN THERE IS THE HISTOLOGY
The pioneers struggled with the morphologic fea-
tures of PH.11 Fast forward to the present day
and the histology of the pulmonary vasculature of
patients with PH is still a topic of discussion.
It is clear that the increased PVR in PAH is asso-
ciated with pronounced vascular remodeling of
pulmonary arterioles involving all cellular elements
(endothelial cells, vascular smooth muscle cells,
and fibroblasts) in the intimal, medial, and adventi-
tial layers of the vessel wall, leading to narrowing
of the vessel lumen and increased vascular stiff-
ness.18,19 The idea that plexiform lesions are
pathognomonic of PAH is a misconception. It is
also misguided to view structural remodeling of
pulmonary arterioles as confined to Group 1. Arte-
riolar medial hypertrophy and intimal proliferation
can occur in patients with pulmonary hypertension
that falls into Groups 3 and 4, and have also been
described in Group 2 (Fig. 2).
The pulmonary veins in PAH patients have been
largely ignored, but studies show clear changes
including smooth muscle cell hyperplasia and
collagen-rich thickening of the intima of pulmonary
veins and venules. A recent systematic description
of the pulmonary vasculature of patients with
Group 2 PH reports changes in the veins and small
venules, with similarities to pulmonary venous
occlusive disease.20 In brief, a spectrum of struc-
tural changes affecting arterioles through to ve-
nules is seen in PH that underscores the difficulty
of using hemodynamic measurements to separate
disease entities.
INSIGHTS FROM GENETICS
An inevitable conclusion from this discussion is
that PH is a convergent phenotype, the end mani-
festation of several pathologic drivers, and that
clinical descriptors are blunt tools for dissecting
the late-stage clinical presentation of PH. The
development of effective new treatments depends
on a better understanding of the pathologic mech-
anisms operating at a more individual level. Ge-
netics is a good place to start.
Progress with understanding the genetic archi-
tecture of PH is most advanced in heritable and
Fig. 2. The pulmonary vasculature in lung tissue from 4 patientswith severe pulmonary hypertension is shown.
The patients were characterized clinically as Category 1 (IPAH), Category 2 (left ventricular failure), Category 3
(interstitial lung disease), and Category 4 (chronic thromboembolic disease). However, each specimen reveals
similar changes in the pulmonary arteriole showing medial hypertrophy and intimal proliferation. Without
knowing the clinical phenotype, it would not be possible to distinguish them based on the vascular pathology
(From Rich S. What is pulmonary arterial hypertension? Pulm Circ. 2012 Jul;2(3):271-2. https://doi.org/10.4103/
2045-8932.101388. PMID: 23130095; PMCID: PMC3487295; with permission.)
Personalized medicine for pulmonary hypertension 211
idiopathic PAH. Pathogenic mutations in BMPR2,
which encodes bone morphogenetic protein re-
ceptor type-2 (BMPR-2), segregate with PAH in
families with a history of the condition.21,22 These
mutations predict loss of function. BMPR-2 is a
member of the transforming growth factor-b
(TGF-b) signaling pathway, and the working hy-
pothesis is that reduced BMPR-2 activity creates
an imbalance in bone morphogenetic protein
(BMP)–TGF-b, in favor of TGF-b. Rare deleterious
variants are now well documented in other genes
in this pathway in PAH patients, emphasizing
its significance, notably GDF-2, ACVRL1, ENG,
and SMAD8.23 Nonetheless, there is a growing
list of genes associated with PAH out with those
with a direct impact on BMP-TGF-b signaling,
including KCNK3, TBX4, SOX17, ATP13A3,
AQP1, ABCC8, and KDR.23–25 These studies
reveal the genetic diversity underlying a clinical
diagnosis of PAH.
The obvious question is, “Does this genetic di-
versity translate into recognizable clinical
https://doi.org/10.4103/2045-8932.101388
https://doi.org/10.4103/2045-8932.101388
Wilkins212
phenotypes?” This might be demanding, even for
rare mutations, which tend to be associated with
a larger effect than common variants. Apart from
evidence that PAH patients with BMPR2 muta-
tions have a worse prognosis than patients without
documented mutations in this gene,26 the data are
few. But the power of genetics to dissect the PH
phenotype and inform clinical management is illus-
trated by EIF2AK4, a gene associated with pulmo-
nary venous occlusive disease (PVOD).25 In a UK
study of 880 patients with IPAH, HPAH, or drug-
induced PAH, 9 patients carried biallelic EIF2AK4
mutations, despite a clinical diagnosis of IPAH
made in an expert center.27 Further investigation
of clinical records showed that these patients
were younger, had a reduced transfer coefficient
for carbon monoxide (Kco), and more interlobular
septal thickening and mediastinal lymphadenopa-
thy on computed tomography of the chest
compared with patients with PAHwithout EIF2AK4
mutations. Radiological assessment alone could
not accurately identify the biallelic EIF2AK4 muta-
tion carriers. Patients with PVODmay not do well if
given treatments currently licensed for PAH. The
lesson is that young patients with a clinical diag-
nosis of PAH and low Kco should be tested for
EIF2AK4 mutations.
These genetic insights not only mandate care in
patient selection for clinical trials, they also inform
drug development. Reviewing the high attrition
rate in this space, it is keenly noted that selecting
genetically validated drug targets can increase
success rates.28 In consequence, a genetic link
between a druggable target and a disease should
prioritize that target for further investigation. In that
context, targeting BMP-TGF-b signaling deserves
priority. The most clinically advanced strategy in-
volves using a fusion protein (Sotatercept) consist-
ing of the extracellular domain of activin receptor
IIa (ActRIIa) attached to the Fc portion of human
immunoglobulin G1 (IgG1) to sequester TGF-b su-
perfamily ligands, such as activin A and B and
growth differentiation factor (GDF)-11, thereby
suppressing TGF-b signaling and rebalancing defi-
cient BMPR-2 signaling29 (ClinicalTrials.gov Iden-
tifier: NCT03496207). Early reports from a Phase
2 study are encouraging, and the detail around
the data is anticipated with interest. Another
approach under early clinical evaluation is directed
at improving post-BMPR-2 signaling with tacroli-
mus.30 Administering BMP9, a ligand for BMPR-
2, is an option in preclinical development, based
on the association between GDF2 mutations and
PAH.31
Whether these treatments should or could be
targeted more accurately is yet unknown, but
detailed knowledge of the 300-plus mutations
identified in BMPR2 suggest more selective thera-
pies.32 Aside from exogenous BMPR2 gene deliv-
ery, still some time away in terms of clinical
investigation, there are more immediate options
for novel or repurposed drugs. Around 70% of
BMPR2 mutations are nonsense (frame-shift dele-
tions and insertions) mutations.32 Aminoglycoside
antibiotics and drugs such as ataluren permit
read-through of premature stop codons and the
translation of full-length protein. Around 30% of
mutations are missense mutations with single
amino acid substitutions, disrupting protein folding
and trafficking to the cell surface; chemical chap-
erones, such as sodium phenyl-butyrate, may
rescue BMPR-2 trafficking, while hydroxychloro-
quine and chloroquine may have a beneficial effect
by inhibiting autophagic degradation of BMPR-2.
Studies are in setup to examine whether therapies
directed at specific BMPR2 mutations offer thera-
peutic benefit in PAH, taking personalized medi-
cine to the point of a private medicine.
How far can this be taken? It remains to be
established whether other genetically defined tar-
gets and their downstream pathways (ie, outside
of BMP-TGF-b signaling) are druggable and might
permit more precise targeting. Furthermore, the
list of genes currently identified accounts for only
25% to 30% of IPAH patients.24 Additional rare
variants that influence thrombosis, inflammation,
right ventricular (RV) function and other relevant
pathologies may emerge from large-scale interna-
tional efforts underway, but for most patients with
PAH, and certainly PH, there will not be a single
major genetic determinant of their phenotype.
Common genetic variants, such as those found
to influence risk of PAH,33 have a smaller effect
on phenotype. There is interest in their collective
value to produce polygenic risk scores. Individu-
ally, common variants can provide instruments
for Mendelian randomization analysis to define
mechanistic pathways and inform druggable tar-
gets.34 But the idea that complex cardiovascular
phenotypes, such as PH, can be reduced to a sim-
ple genotype-phenotype relationship has been
rightfully challenged.35
BIG DATA TO THE RESCUE
It has been proposed that complex cardiovascular
phenotypes are the clinical manifestation of an
interaction of subphenotypes or endo-pheno-
types35 And that these can be resolved by big
data.
The importance of accurate phenotyping to the
interpretation of genetic data has long been recog-
nized. The value of deep phenotyping, collecting
as much information about a patient as possible,
http://ClinicalTrials.gov
Personalized medicine for pulmonary hypertension 213
has taken on greater significance with the opportu-
nity to use machine learning and network analysis
to find clusters that relay clinical information. There
are emerging examples of the potential value of
this approach.
In a cohort of patients with a clinical diagnosis of
HFpEF, a suite of statistical learning algorithms
used to analyze phenotype data (67 continuous
variables) classified participants into 3 distinct
groups that differed markedly in clinical character-
istics, cardiac structure and function, invasive he-
modynamics, and outcomes.36 Using data from
invasive cardiopulmonary exercise testing (iCPET),
network analysis of clinical parameters from 738
patients enabled the development of a novel 10-
variable model that defined 4 exercise groups.37
The patient groups were characterized by exercise
profiles drawn from pulmonary function, exercise
hemodynamics,and metabolic data and defined
differences in rates of hard clinical end points,
expanding the range of useful clinical variables
beyond peak VO2 that predict hospitalization in pa-
tients with exercise intolerance.
Cardiac imaging readily provides high-
dimensional data that can be used to better cap-
ture the nonlinear motion dynamics of the beating
heart. These data can be mined for phenotypes
beyond crude measures of global contraction
that are only moderately reproducible and insensi-
tive to the underlying disturbances of cardiovascu-
lar physiology. In a study of 302 patients with PH,
image sequences of the heart acquired using car-
diac magnetic resonance imaging (MRI) were used
to create time-resolved 3-dimensional segmenta-
tions using a fully convolutional network trained
on anatomic shape priors.38 The resulting model
was used for survival predictions and outper-
formed a conventional model based on manually
derived volumetric measures.
Advances in technology increase the prospects
of collecting more detailed clinical phenotypic in-
formation while patients are engaged in activities
of daily living. Experience from implanted devices
and wearable sensors that permit remote moni-
toring of electrocardiogram (ECG), blood pressure,
oxygen saturation, mobility, and even environment
exposure is racing ahead.39,40 Integrated with
electronic patient records, the depth and volume
of data will provide a detailed database to identify
important phenotypes associated with response
to drugs that will inevitably cut across current clin-
ical boundaries.
Add to this a wealth of ‘omic’ data from noninva-
sive sampling and cataloging the proteome, tran-
scriptome, metabolome, and microbiome.41–44 It
is now possible to measure thousands of analytes
in a small aliquot of plasma or serum. High-
throughput platforms for measuring up to 5000
proteins and hundreds of identifiable metabolites
(and many thousand unannotated more) and
microRNAs in the same sample offer a window
on the molecular choreography of PH.
It is still early days, with most ‘omic’ data from
cross-sectional studies comparing PAH, and
indeed, more specifically, IPAH and HPAH, with
healthy controls. The main aim of these studies
has been to identify molecular signatures of dis-
ease that might inform prognosis, with some suc-
cess. Over 1000 proteins have been measured in
the plasma proteome of patients with IPAH and
HPAH, identifying several that distinguish these
patients from healthy controls and around 40 that
relate to survival.41 The transcriptome of circu-
lating white cells and the plasma metabolome
can also discriminate IPAH and HPAH from health
and categorize patients according to risk.42,43
Applied to patients within a larger PH group (as
opposed to a clinically defined subgroup) or
across currently defined PH groups should bring
larger rewards. A panel of 48 circulating cytokines,
chemokines, and growth factors has been shown
to distinguish immune phenotypes in a population
of patients drawn from Group 1 PAH.45 Unsuper-
vised machine learning (consensus clustering)
classified patients into 4 proteomic immune clus-
ters, without guidance from clinical features. The
identified clusters were associated with distinctive
clinical risk profiles providing information that was
not contained in the clinical descriptions of these
patients.
These clusters define inflammation endopheno-
types. The availability of big data for describing PH
sets the scene for describing further endopheno-
types, such as thrombosis, fibrosis, cell prolifera-
tion, and autophagy. PH might then be regarded
as an assembly of these different endopheno-
types.35 Understanding how these are perturbed
in each patient who presents with a raised mPAP
(or indeed, with breathlessness) offers a more
granular view of his or her underlying pathology.
This, in turn, can be used to guide targeted inter-
vention(s) to repair the condition. Delivering this re-
quires adopting a more extensive toolset for
investigating patients and a different approach to
treating them.
TOWARD MECHANISM-BASED
THERAPEUTICS
Much has been made of the similarities between
PH and cancer, in particular dysregulated cell pro-
liferation and resistance to apoptosis, to the extent
that some drugs developed for malignancies are
under investigation for PAH.46 Oncology has
Wilkins214
begun a transition in treatment strategy toward
tumor-agnostic therapies, specifically, the use of
drugs based on the genetic andmolecular features
of the cancer in question without regard to type or
primary location.47 To move to that scenario in PH
will require the depth of molecular knowledge
about the PH of each patient that oncology
currently enjoys.
Oncology has the advantage of tissue biopsies,
permitting sequencing for somatic and germline
mutations. PH will need to rely more on liquid bi-
opsies, the composition of circulating molecules
that report on health. At present, multiplex assays,
such as a panel of proteins, are available that
improve on single-protein assays (eg, NT-
proBNP) and clinical risk scores for defining risk
or prognosis.41 Building on this, combinations of
circulating factors (ie, molecular signatures) could
be used to define druggable pathologic pathways.
For example, further network analysis of a prote-
ome dataset from patients with clinically defined
PAH has unmasked increased activity of the com-
plement alternative pathway in some patients.41,48
A protein cluster was identified that distinguished
patients with poor survival, raising interest in tria-
ling intervention with a complement inhibitor (eg,
a complement C5a inhibitor) in this group in a
biomarker-driven study design. The extent to
which the complement alternative pathway is
disturbed in other presentations of PH merits
investigation.
THE FUTURE OF PULMONARY
HYPERTENSION TREATMENT
PH is a global unmet clinical need. It progresses
silently and presents late as a convergent pheno-
type. Dividing PH into broad overlapping clinical
categories inhibits rather than assists the
Fig. 3. Personalized medicine based on consensus cluste
drug treatment.
development of new treatments. The early use of
dual therapy and even triple therapy in the man-
agement plan for PAH has benefited patients, but
it is a desperate response to a deeper problem.
The current licensed treatments have been
developed on an empiric basis, rather than on an
in depth understanding of the underlying pathol-
ogy. Identifying a therapeutic signal and the pa-
tients who may benefit most can be lost in the
noise. Without change, the next generation of
treatments will be constrained by the same limited
vocabulary for categorizing a complex phenotype.
The ability to deep-phenotype patients at both the
clinical and molecular level and integrate with ge-
netic information opens the door to revisiting
how one views and manages this condition
(Fig. 3). It will require and drive a new taxonomy
of PH, one that reduces the reliance on traditional
diagnostic criteria alone and incorporates scienti-
fic advances in molecular and genetic medicine
and innovations in clinical phenotyping, such as
advanced imaging and remote sensors.
A major step in this direction has been taken
with the National Heart, Lung, and Blood Institute
initiative PVDOMICS (Redefining Pulmonary Hy-
pertension through Pulmonary Vascular Disease
Phenomics) study49 (Clinicaltrials.gov
NCT02980887). The aim of PVDOMICS is to up-
date the classification of pulmonary vascular dis-
ease using a combination of deep clinical
phenotyping and ‘omic’ techniques. It is important
to note that ‘omic’ data are not alternatives to clin-
ical data. Indeed, the project is explicit in requiring
in-depth clinical phenotyping using standard oper-
ating protocols. The data will be subjected to unbi-
ased network analyses and machine learning to
cluster patients according to shared features and
identify the molecular basis of these clusters. The
expectation is that this will generate new
ring of multidimensional data andmechanism-based
http://Clinicaltrials.gov
Personalized medicine for pulmonary hypertension 215
pulmonary vascular disease ontologies, highlight
relevant druggable pathways, and enable targeted
mechanism-based treatments.
This is no small task. It will require validation in a
separate data set. It will impact on how clinical tri-
als are performed and drugs are licensed. It will
need the combined efforts of all interested in
improving the management of patients with PH.
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http://refhub.elsevier.com/S0272-5231(20)30110-6/sref48
http://refhub.elsevier.com/S0272-5231(20)30110-6/sref48
http://refhub.elsevier.com/S0272-5231(20)30110-6/sref49
http://refhub.elsevier.com/S0272-5231(20)30110-6/sref49
http://refhub.elsevier.com/S0272-5231(20)30110-6/sref49
http://refhub.elsevier.com/S0272-5231(20)30110-6/sref49
	Personalized Medicine for Pulmonary Hypertension:
	Key points
	Introduction
	First, the problem with averages
	The limitations of the current clinical classification
	And then there is the histology
	Insights from genetics
	Big data to the rescue
	Toward mechanism-based therapeutics
	The future of pulmonary hypertension treatment
	References