Sage Journals: Discover world-class research

Abstract

Diagnostic World Health Organization (WHO) Group 1 pulmonary arterial hypertension (PAH) and Diagnostic Group 1' pulmonary veno-occlusive disease (PVOD) and/or pulmonary capillary hemangiomatosis (PCH) are progressive and fatal disorders. Past registries provided important insights into these disorders, but did not include hormonal exposures or genomic data. The United States Pulmonary Hypertension Scientific Registry (USPHSR) will provide demographic, physiologic, anorexigen and hormone exposure, genomic, and survival data in the current therapeutic era for 499 patients diagnosed with PAH, PVOD, or PCH. The USPHSR also will explore the relationship between pharmacologic, non-pharmacologic, and dietary hormonal exposures and the increased risk for women to develop idiopathic or heritable PAH.

Keywords

Phenotype genotype pulmonary hypertension hormones toxins

Background

Pulmonary arterial hypertension (PAH), a pulmonary vascular condition which includes the historic diagnosis previously described as primary pulmonary hypertension (PPH), was once a progressive and fatal disorder for which there was no effective treatment.^1,2 Over the past four decades, investigators have made basic discoveries^3–5 and completed pivotal clinical trials of 12 medications which have received regulatory approval for the treatment of PAH.⁶

As treatment evolved, national patient registries provided important data to inform the pulmonary hypertension (PH) community. In the United States (US), National Institutes of Health (NIH) Registry investigators enrolled 187 patients diagnosed with PPH during 1983–1987, an era before specific treatment for this disorder.⁷ NIH Registry investigators reported that women were more likely than men to be diagnosed with PPH;⁷ they used hemodynamic measurements from the NIH Registry population to derive a prediction equation for survival.⁸ Twenty years later, Registry to Evaluate Early and Long-term PAH Disease Management (REVEAL) investigators enrolled 3515 patients diagnosed with World Health Organization (WHO) Group 1 PAH.⁹ REVEAL patients also included disproportionately more women than men and more diverse phenotypic patterns than the NIH Registry cohort.¹⁰ Furthermore, in an era of PAH targeted therapies, REVEAL investigators observed improved survival of patients with baseline characteristics matched to NIH Registry patients.¹¹ REVEAL investigators also derived and validated a new method to predict survival for PAH patients treated in the REVEAL era.^12,13

Four medications received regulatory approval for the treatment of PAH after REVEAL. Riociguat,¹⁴ macitentan,¹⁵ and an oral formulation of treprostinil¹⁶ received FDA approval in 2013; selexipag¹⁷ received FDA approval in 2016. These new medications altered the therapeutic landscape for PAH.

Advances in genomic understanding of PAH paralleled advances in treatment of PAH. The discovery that heterozygous BMPR2 mutations cause familial PPH^18,19 and recognition that BMPR2 mutations were often the unrecognized cause of sporadic PPH^20,21 led to an updated clinical classification of PH which included heritable PAH (HPAH).²² Subsequent discoveries of mutations in ALK1,²³ ENG,²⁴ SMAD8,²⁵ CAV1,²⁶ KCNK3,²⁷ and TBX4²⁸ expanded the known causes of HPAH. In 2014, investigators reported that homozygous or compound heterozygous mutations in EIF2AK4 caused heritable pulmonary capillary hemangiomatosis (PCH) and pulmonary veno-occlusive disease (PVOD).^29,30 A recent study of > 1000 patients diagnosed with idiopathic PAH (IPAH) identified mutations in ATP13A3, SOX17, AQP1, and GDF2 and suggested additional genes that will require further validation.³¹ SOX17 variants were also identified in patients with PAH associated with congenital heart disease.³² These discoveries permitted researchers to organize the first United States registry to incorporate genetic characteristics of PAH patients.

The United States Pulmonary Hypertension Scientific Registry (USPHSR) is a contemporary PAH registry which will provide data for PAH patients diagnosed between 2012 and 2018. Patients in the USPHSR will be characterized using targeted sequence and copy number analysis, genome-wide single nucleotide polymorphism (SNP) data, and whole exome sequencing. USPHSR investigators will use reproductive histories and hormonal exposure data to examine these potential contributors to the disproportionate numbers of women diagnosed with PAH.

USPHSR study overview

USPHSR is a multicenter, longitudinal, observational, and hypothesis-driven study of 499 patients diagnosed with WHO Group 1 PAH or PVOD/PCH. The study protocol was approved by the Institutional Review Boards at each participating center. USPHSR differs from the NIH Registry and REVEAL in three important ways: (1) USPHSR patients were diagnosed, characterized and treated in the current genomic, imaging, and therapeutic era; (2) USPHSR includes both observational data and pre-specified hypothesis driven research; and (3) USPHSR links with the NHLBI sponsored National Biological Sample and Data Repository for PAH (PAH Biobank, NHLBI HL105333).

Study objectives

Table 1 lists the four primary objectives of the USPHSR. The first objective, to characterize the demographics and clinical course of patients diagnosed with PAH in the current genomic, imaging, and treatment era, provides the PH community with baseline data and longitudinal outcome data in PAH patients diagnosed after completion of REVEAL. The second objective, to examine the potential contributions of genomic data to current risk prediction tools for PAH patients, allows the investigators to assess whether genomic characteristics of PAH patients enhance risk assessment in the contemporary treatment era. The third and fourth objectives will use a case control design to test hypotheses which examine and identify environmental and genetic factors responsible for the female predominance of IPAH, and the interactions between environmental exposures and the genetic characteristics of patients diagnosed with PAH.

Table 1.

Primary objectives of USPHSR.

1.	To characterize the demographics and clinical course of patients diagnosed with WHO Group I PAH in the current genomic, imaging, and treatment era
2.	To test hypotheses related to the accuracy and precision of clinical prediction tools for survival of PAH patients diagnosed and treated in the current genomic, imaging, and treatment era
3.	To identify factors responsible for the female predominance in IPAH
4.	To examine the interaction of environmental exposures and genomics of patients diagnosed with WHO Group 1 PAH

Table 2 lists additional objectives of the USPHSR. These objectives allow investigators to examine USPHSR data in defined areas of interest using protocols approved by the USPHSR Board.

Table 2.

Additional objectives of USPHSR.

1.	To identify genetic and genomic variants for specific clinical phenotypes
2.	To examine potential pharmaco-genomic links to treatment outcomes
3.	To identify and/or confirm new genetic susceptibility loci/mutations
4.	To educate IPAH and HPAH patients and to evaluate their attitudes about genetic counseling and genetic testing
5.	To support any evolving science and research needs of the PAH community approved by the USPHSR board

Patient population

A total of 499 consecutively screened consenting adult (age > 18 years) patients diagnosed with WHO Group 1 PAH or Group 1' PVOD/PCH³³ at participating study sites (Supplementary Appendix 1) enrolled in USPHSR after they were enrolled in the PAH Biobank (https://www.pahbiobank.org, PI William Nichols, PhD). Only patients who enrolled in the PAH Biobank within five years of PAH diagnosis were eligible for enrollment in USPHSR. Consonant with REVEAL, the date of diagnosis was defined as the date of the diagnostic pulmonary artery catheterization.

Inclusion criteria

Before enrollment in the study, candidates met the following inclusion criteria:

diagnosis of PAH, PVOD, or PCH;

documentation of the following hemodynamic parameters by pulmonary artery catheterization

∘ mean pulmonary arterial pressure (PAPm) ≥25 mmHg at rest;

∘ pulmonary artery wedge pressure (PAWP) or left ventricular end-diastolic pressure (LVEDP) ≤15 mmHg in the absence of mitral stenosis;

∘ pulmonary vascular resistance (PVR) >3 Wood Units (WU).

Exclusion criteria

Patients not eligible for enrollment included:

patients unwilling or unable to provide written consent for USPHSR;

patients with an underlying medical disorder (e.g. metastatic cancer) with an anticipated life expectancy of <2 years;

patients with complex adult congenital heart disease associated with PAH.

Informed consent procedure

Patients eligible for enrollment were asked to provide informed consent for participation in USPHSR. To maintain patient confidentiality according to HIPAA, each patient was assigned a unique patient-identifier. In addition, patients were asked to consent to data sharing for collaborative research among investigators conducting research deemed by the USPHSR steering committee to be of value to the PH community.

Data collection

At the time of USPHSR entry, data were obtained for all enrolled patients from a patient interview, medical record review, and from data stored at the National Biological Sample and Data Repository for PAH. Baseline demographic data elements, including PAH medications, were collected and entered into the electronic case report forms (Table 3).

Table 3.

Baseline data.

Demographics

Age at enrollment, years

Age at diagnosis, years

Female sex, %

Race, %

Body mass index, kg/m²

Time from diagnosis to enrollment, months

Newly diagnosed (within 6 months), %

WHO PAH Group 1 Classification

Diagnostic/clinical data at enrollment

WHO functional class, %

6MWD, m

Hemodynamics

Mean RA pressure, mmHg

Mean PA pressure, mmHg

PCWP, mmHg

PVR, Wood units

Thermodilution CO, L/min

Fick CO, L/min

Heart rate, bpm

SvO2, %

Systolic blood pressure, mmHg

Mean arterial pressure, mmHg

Presenting symptoms

Time from first PAH symptom to diagnosis

Co-morbidities

Renal insufficiency

PAH-specific medications

Concomitant medications

Reproductive factors and sex hormone exposures

Endogenous exposures (i.e. pregnancy, menarche)

Exogenous exposures (i.e. oral contraceptive pills, hormone replacement therapy)

Environmental exposures

Weight loss drugs

Soy products

Well/spring water

Cigarette smoking

Alcohol use

Drug use

Genomics data

6MWD, 6-min walking distance.

Environmental and hormone exposure data were collected by a structured interview using a questionnaire. Study interviewers administered an expanded version of the previously validated and extensively published Nurses' Health Study (NHS) I and II questionnaire (http://www.channing.harvard.edu/nhs/index.html).^34,35 NHS questionnaires address a person's exposure to hormones via a large array of questions related to contraceptive therapy (CT) and hormone replacement therapy (HRT), menstruation, menopause, pregnancy, abortions, and parity. In addition, basic data elements concerning exposure to tobacco smoke, alcohol use, illicit substance use, and anorexigen exposure were collected.

Each patient's vital status will be determined at one-year intervals after enrollment without altering clinical practice. Patients will be followed for the duration of the study with plans for minimum follow-up of one year for the last patient enrolled in USPHSR and with permission to contact the patient or a designated contact in the future.

USPHSR Investigators will access biologic data according to protocols established by the PAH Biobank Steering Committee and the Steering Committee of the USPHSR. Biologic specimens include DNA, RNA, plasma, serum, and EBV immortalized cell lines. Genetic data generated by the PAH Biobank include Illumina OMNI5 SNP data (∼4.5 million SNPS), coding sequence data for BMPR2, ACVRL1, ENG, CAV1, SMAD9, KCNK3, EIF2AK4, ABCC8, GDF2, KCNA5, SMAD4, and TBX4, and dosage data for BMPR2, ACVRL1, and ENG by MLPA. As of 30 October 2018, sequencing analyses were completed for 2688 PAH patients of 2853 patients enrolled in the PAH Biobank. In addition, whole exome sequencing data generated by the Regeneron Genetic Center are available on 2517 patients in the PAH Biobank.

Sample size

A total of 499 patients diagnosed with WHO group 1 or 1' PAH were enrolled over a period of three years. These patients were a subset of the 2853 patients enrolled in the PAH Biobank. The sample size was selected based upon budgetary constraints.

Data analysis

The USPHSR will support two approaches to data analysis. The first approach is for USPHSR demographics and the second approach is for individual studies which test specific hypotheses. Individual studies will have a specific statistical analysis plan to address specific research questions.

The statistical plan will incorporate standards for reporting observational research³⁶ and the checklist provided by the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE).³⁷

For the observed characteristics of the study cohort, descriptive statistics will be employed. In brief, we will describe quantitative variables using mean, median, standard deviation, and minimum to maximum intervals. To compare quantitative data of two groups (e.g. men compared to women), we will use the Student's t test or the Wilcoxon rank-sum test as appropriate, depending on the normality of the data. In the event of multiple group comparisons, quantitative data will be analyzed using analysis of variance or Kruskal–Wallis non-parametric tests, as appropriate. For categorical variables, description will be made using typical measures with analysis via χ² tests or Fisher's exact test. The level for determination of statistical significance will be set at P < 0.05 unless otherwise noted.

We will construct Kaplan–Meier survival curves for time to event endpoints and use the Cox proportional hazards regression model to analyze survival in the current era of diagnosis and treatment. Multivariate regression analysis will be employed to adjust for non-random treatment assignments. Multivariate Cox proportional hazards regression will be employed to identify predictors of outcomes, including time to death or lung transplant.^38,39 As done previously in REVEAL, methods that account for survivor bias will be used due to the variable time from diagnosis to enrollment.⁴⁰ This will allow us to account for variable length of follow-up.

A major goal of the USPHR is to update clinical prediction tools with genomic data. We will determine the accuracy of clinical prediction tools, with and without genomic data, to predict survival of PAH patients diagnosed and treated after REVEAL. Updated algorithms will be evaluated for calibration and discrimination. Model calibration will be determined by comparing one-year survival predicted by an updated algorithm with observed one-year survival of the USPHSR cohort. Calibration plots will be employed to demonstrate agreement between predicted and observed survival.

Evaluating hormone exposures

USPHSR investigators will test the hypothesis that PAH patients have a higher exposure to exogenous sources of female sex hormones than controls. We are currently planning to recruit control individuals from Research.Match.org. These controls will be matched to newly diagnosed PAH women according to age, self-reported race, ethnicity, and body mass index (BMI).

Analyses will be stratified by sex. For women, the primary exposure endpoint will be > 1 year of CT and/or HRT use. For cases, only data before diagnosis will be collected. For controls, the entire lifetime will be evaluated. For male cases, the primary exposure endpoint will be BMI (kg/m²) > 24.9 at diagnosis. For the primary exposure, conditional logistic regression will be used to generate odds ratios (OR) and 95% confidence intervals (CI) for the association between CT/HRT exposure >1 year and PAH in women, as well as the association between BMI >24.9 kg/m² and PAH in men. We will also analyze hormone exposure and BMI as continuous variables, comparing cases and controls, using Student's t test for normally distributed data, or the non-parametric Mann–Whitney U test for data that are not normally distributed. We will determine the univariate association of the other exposures determined, such as tobacco smoke exposure, and PAH/control status, and assess for effect modification by biologically relevant genes as appropriate. In addition, multivariable conditional logistic regression models will be used to calculate adjusted ORs and 95% CIs for each sex. The models will include covariates and sources of effect modification. Analysis for continuous outcome variables, such as age at diagnosis among cases, will be similar but utilize techniques appropriate to a continuous variable, such as Student's t test and linear or Cox regression analyses. All distributions will be examined for deviations from normality (and transformed as necessary, if indicated, or non-parametric analysis methods may be applied). To avoid multiple comparisons and over-fitting the separate model for each sex, a limited number of covariates will be included in each. Those covariates will be identified a priori and will include those relevant biologically and by univariable analysis. The logistic models will be assessed for adequacy of the fit for the matched case-control data. We will employ both graphical and numerical methods according to previously published approaches. These techniques allow for examination of the functional form of each covariate, as well as the overall adequacy of the models.^41–43

Evolving research needs

To adapt to the evolving science and research needs of the PAH community, separate analysis plans will be developed for new objectives. Minor changes (if approved by the Steering Committee) in the electronic case report form (eCRF) may occur in response to new diagnostic approaches and treatments. Ongoing assessment of enrollment and data captured will also be performed by the Steering Committee to be certain the goals of the Registry are being met.

General issues

Except for the exposure questionnaire, clinical practice should not be changed in any way to accommodate collection of additional data. The exposure questionnaire was completed in person at the time of enrollment, by telephone interview, or by mail. Participants may have follow-up studies performed at institutions different from the enrolling site. Investigators/coordinators were encouraged to request copies of these results and enter data into the eCRF.

Discussion

Observation and analysis of demographic, hormone exposures, and genomic characteristics of patients diagnosed with Group 1 PAH represent important unmet needs for the PH community. A recent survey underscored the need for increased awareness of the genetics of PAH.⁴⁴ In addressing this need, the USPHSR uses several study design features which are unique when compared with past US registries of patients diagnosed with PAH (Table 4).

Table 4.

Past United States Registries of patients diagnosed with PAH.

Registry	Dates of patient enrollment	Number enrolled	Physiologic data	Demographic data	PAH therapies	Genomics	Hormonal and reproductive data
NIH PPH	1 July 1981–31 December 1985	187	Yes	Yes	No	No	No
REVEAL	1 March 2006–2009	3515	Yes	Yes	Yes	No	No
USPHSR	30 August 2016–28 June 2018	499	Yes	Yes	Yes	Yes	Yes

First, USPHSR is designed to describe the genomic characteristics of patients diagnosed with PAH. Prior US PAH registries provided extensive demographic, clinical, and physiologic data, but genomic data were not available.^7,45 The USPHSR study design assures detailed genomic data through its link with the National Biological Sample and Data Repository for PAH (PAH Biobank). By design, all patients enrolled in USPHSR are also enrolled in the PAH Biobank. The PAH Biobank research team will provide genome wide SNP genotypes, sequencing for established PAH genes, multiplex ligation probe dosage data, and whole exome sequencing on samples from patients enrolled in USPHSR.

A second design feature that distinguishes USPHSR from previous US PAH registries is the prospective collection of hormonal and environmental exposures. Past registries provided limited data with respect to hormonal and environmental exposures, while they demonstrated that IPAH and HPAH affect women more often than men.^7,45,46 REVEAL investigators reported that PAH patients were older and more often women than previously reported, an important observation with implications for an interplay between hormonal, genetic, and environmental exposures.^45,47 In addition, exposure to anorexigens was more common among women than men with PAH.⁴⁷ Clinician investigators have suggested that exogenous estrogens (e.g. oral contraceptives) accelerate pulmonary vascular disease and PH, both in patients with predispositions (e.g. congenital heart disease, familial PAH, or in combination with anorexigens known to cause PAH) and in patients without known predispositions.^48–50

A third key design feature of USPHSR is a planned report of survival for a cohort of PAH patients diagnosed and treated in the contemporary diagnostic and therapeutic era. NIH registry investigators provided the first description of survival of patients diagnosed with PPH in an era (1981–1991) when there was no specific therapy.⁸ The median survival from diagnosis was 2.8 years. REVEAL investigators documented improved survival of PAH patients in an era (2006–2012) when treatment was available with prostacyclins, endothelin receptor antagonists, and phosphodiesterase inhibitors.^11,45 Four medications received regulatory approval for the treatment of PAH after completion of REVEAL.^14–17 USPHSR patients were diagnosed and treated in an era when these medications were available and in an era when clinicians often provided initial therapy with a combination of PAH-specific therapies.

A fourth key design feature is a planned evaluation of the contribution of genomic data to prediction of survival. Prior US Registries lacked access to genomic data. The NIH PPH registry investigators derived an equation to predict survival based upon hemodynamic data alone⁸ and REVEAL investigators derived and validated a risk assessment tool (REVEAL Risk Calculator) based upon multiple clinical variables.^12,13 Familial PAH, a surrogate for PAH caused by pathogenic gene mutations, was an important predictor of survival in the REVEAL Risk Calculator, but a family history of PAH is either incomplete or non-existent for many IPAH patients who carry genetic mutations which cause PAH.^51,52 Genomic data may improve survival predictions because mutations in BMPR2, ALK1, and EIF2AK4 identify patients with more severe disease and reduced transplant free survival.^52–57 Furthermore, the list of pathogenic mutations continues to expand, with data suggesting that many IPAH patients have pathogenic mutations in other genes (e.g. TBX4) responsible for more severe PAH with reduced survival.³¹ Correct identification of the influence of a broad spectrum of pathogenic mutations on mortality underlies the USPHSR plan to evaluate the contribution of genomic data to survival prediction.

Finally, a rich source of data which includes sex-hormone-related exposures and reproductive histories, exposures, and genomics will also allow USPHSR investigators to explore other relationships. For example, limited evidence suggests that combinations of a genetic predisposition such as a pathogenic BMPR2 mutation and exposure to an environmental stimulus such as an anorexigen increases the risk of developing severe PAH.⁵⁸ The USPHSR was designed to provide data for additional genes and exposures which may increase an individual's risk to develop severe PAH. Enhanced understanding of these risks may allow individuals with genetic predispositions to avoid exposures that increase their risk to develop PAH.

In conclusion, the USPHSR represents the first US Registry of PAH patients to provide demographic, physiologic, and genomic data along with hormonal and reproductive data and environmental exposures. The USPHSR will provide this data to the PH community in the current era of PAH diagnosis and treatment.

Footnotes

Acknowledgments

Samples and/or data from the National Biological Sample and Data Repository for PAH, which receives government support under an investigator-initiated grant (R24 HL105333) awarded by the National Heart Lung and Blood Institute (NHLBI), were used in support of this study. We thank contributors, including the Pulmonary Hypertension Centers who enrolled patients, completed questionnaires, and collected samples used in this study, as well as patients and their families, whose help and participation made this work possible.

Conflict of interest

The author(s) declare that there is no conflict of interest.

Funding

This work was supported by an unrestricted grant from Actelion Pharmaceuticals US, Inc. and donations from BikePHifty. WCN, MWP, and KAL were funded by HL105333.

References

Dresdale

Schultz

Michtom

. Primary pulmonary hypertension. I. Clinical and hemodynamic study. Am J Med 1951; 11: 686–705.

Fishman

. Clinical classification of pulmonary hypertension. Clin Chest Med 2001; 22: 385–91. vii.

Moncada

Gryglewski

Bunting

et al.

An enzyme isolated from arteries transforms prostaglandin endoperoxides to an unstable substance that inhibits platelet aggregation. Nature 1976; 263: 663–665.

Yanagisawa

Kurihara

Kimura

et al.

A novel potent vasoconstrictor peptide produced by vascular endothelial cells. Nature 1988; 332: 411–415.

Ignarro

Buga

Wood

et al.

Endothelium-derived relaxing factor produced and released from artery and vein is nitric oxide. Proc Natl Acad Sci U S A 1987; 84: 9265–9269.

Galie

Humbert

Vachiery

et al.

2015 ESC/ERS guidelines for the diagnosis and treatment of pulmonary hypertension: The joint task force for the diagnosis and treatment of pulmonary hypertension of the European Society of Cardiology (ESC) and the European Respiratory Society (ERS): Endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC), International Society for Heart and Lung Transplantation (ISHLT). Eur Respir J 2015; 46: 903–975.

Rich

Dantzker

Ayres

et al.

Primary pulmonary hypertension: A national prospective study. Ann Intern Med 1987; 107: 216–223.

D'Alonzo

Barst

Ayres

et al.

Survival in patients with primary pulmonary hypertension: Results from a national prospective registry. Ann Intern Med 1991; 115: 343–349.

McGoon

Miller

. REVEAL: A contemporary US pulmonary arterial hypertension registry. Eur Respir Rev 2012; 21: 8–18.

10.

Frost

Badesch

Barst

et al.

The changing picture of patients with pulmonary arterial hypertension in the United States: How REVEAL differs from historic and non-US contemporary registries. Chest 2011; 139: 128–137.

11.

Benza

Miller

Barst

et al.

An evaluation of long-term survival from time of diagnosis in pulmonary arterial hypertension from the REVEAL registry. Chest 2012; 142: 448–456.

12.

Benza

Miller

Gomberg-Maitland

et al.

Predicting survival in pulmonary arterial hypertension: Insights from the registry to evaluate early and long-term pulmonary arterial hypertension disease management (REVEAL). Circulation 2010; 122: 164–172.

13.

Benza

Gomberg-Maitland

Miller

et al.

The REVEAL registry risk score calculator in patients newly diagnosed with pulmonary arterial hypertension. Chest 2012; 141: 354–362.

14.

Ghofrani

H-A

Galiè

Grimminger

et al.

Riociguat for the treatment of pulmonary arterial hypertension. N Eng J Med 2013; 369: 330–340.

15.

Pulido

Adzerikho

Channick

et al.

Macitentan and morbidity and mortality in pulmonary arterial hypertension. N Eng J Med 2013; 369: 809–818.

16.

Tapson

Torres

Kermeen

et al.

Oral treprostinil for the treatment of pulmonary arterial hypertension in patients on background endothelin receptor antagonist and/or phosphodiesterase type 5 inhibitor therapy (the FREEDOM-C study): A randomized controlled trial. Chest 2012; 142: 1383–1390.

17.

Sitbon

Channick

Chin

et al.

Selexipag for the treatment of pulmonary arterial hypertension. N Engl J Med 2015; 373: 2522–2533.

18.

Deng

Morse

Slager

et al.

Familial primary pulmonary hypertension (gene PPH1) is caused by mutations in the bone morphogenetic protein receptor-II gene. Am J Hum Genet 2000; 67: 737–744.

19.

Lane

Machado

Pauciulo

et al.

Heterozygous germline mutations in BMPR2, encoding a TGF-beta receptor, cause familial primary pulmonary hypertension. The international PPH consortium. Nat Genet 2000; 26: 81–84.

20.

Thomson

Machado

Pauciulo

et al.

Sporadic primary pulmonary hypertension is associated with germline mutations of the gene encoding BMPR-II, a receptor member of the TGF-beta family. J Med Genet 2000; 37: 741–745.

21.

Newman

Wheeler

Lane

et al.

Mutation in the gene for bone morphogenetic protein receptor II as a cause of primary pulmonary hypertension in a large kindred. N Engl J Med 2001; 345: 319–324.

22.

Simonneau

Robbins

Beghetti

et al.

Updated clinical classification of pulmonary hypertension. J Am Coll Cardiol 2009; 54: S43–S54.

23.

Trembath

Thomson

Machado

et al.

Clinical and molecular genetic features of pulmonary hypertension in patients with hereditary hemorrhagic telangiectasia. N Engl J Med 2001; 345: 325–334.

24.

Harrison

Flanagan

Sankelo

et al.

Molecular and functional analysis identifies ALK-1 as the predominant cause of pulmonary hypertension related to hereditary haemorrhagic telangiectasia. J Med Genet 2003; 40: 865–871.

25.

Shintani

Yagi

Nakayama

et al.

A new nonsense mutation of SMAD8 associated with pulmonary arterial hypertension. J Med Genet 2009; 46: 331–337.

26.

Austin

LeDuc

et al.

Whole exome sequencing to identify a novel gene (CAVEOLIN-1) associated with human pulmonary arterial hypertension. Circ Cardiovasc Genet 2012; 5: 336–343.

27.

Roman-Campos

Austin

et al.

A novel channelopathy in pulmonary arterial hypertension. N Eng J Med 2013; 369: 351–361.

28.

Kerstjens-Frederikse

Bongers

Roofthooft

et al.

TBX4 mutations (small patella syndrome) are associated with childhood-onset pulmonary arterial hypertension. J Med Genet 2013; 50: 500–506.

29.

Best

Sumner

Austin

et al.

EIF2AK4 mutations in pulmonary capillary hemangiomatosis. Chest 2014; 145: 231–236.

30.

Eyries

Montani

Girerd

et al.

EIF2AK4 mutations cause pulmonary veno-occlusive disease, a recessive form of pulmonary hypertension. Nat Genet 2014; 46: 65–69.

31.

Graf

Haimel

Bleda

et al.

Identification of rare sequence variation underlying heritable pulmonary arterial hypertension. Nat Commun 2018; 9: 1416.

32.

Zhu

Welch

Wang

et al.

Rare variants in SOX17 are associated with pulmonary arterial hypertension with congenital heart disease. Genome Med 2018; 10: 56.

33.

Simonneau

Gatzoulis

Adatia

et al.

Updated clinical classification of pulmonary hypertension. J Am Coll Cardiol 2013; 62: D34–41.

34.

Hennekens

Speizer

Lipnick

et al.

A case-control study of oral contraceptive use and breast cancer. J Natl Cancer Inst 1984; 72: 39–42.

35.

Lipnick

Speizer

Bain

et al.

A case-control study of risk indicators among women with premenopausal and early postmenopausal breast cancer. Cancer 1984; 53: 1020–1024.

36.

Thomas

Peterson

. The value of statistical analysis plans in observational research: Defining high-quality research from the start. JAMA 2012; 308: 773–774.

37.

von Elm

Altman

Egger

et al.

The strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies. PLoS Med 2007; 4: e296.

38.

Cox

. Regression models and life-tables. J Roy Stat Soc B 1972; 34: 187–220.

39.

Cox DR and Oakes D. Analysis of Survival Data. London: Chapman and Hall, 1984.

40.

Gross

Lai

. Nonparametric estimation and regression analysis with left-truncated and right-censored data. J Am Stat Assoc 1996; 91: 1166–1180.

41.

Arbogast

Lin

. Model-checking techniques for stratified case-control studies. Stat Med 2005; 24: 229–247.

42.

Lemeshow

Hosmer

Jr . Estimating odds ratios with categorically scaled covariates in multiple logistic regression analysis. Am J Epidemiol 1984; 119: 147–151.

43.

Lemeshow

Hosmer

Jr . A review of goodness of fit statistics for use in the development of logistic regression models. Am J Epidemiol 1982; 115: 92–106.

44.

Jacher

Martin

Chung

et al.

Pulmonary arterial hypertension: Specialists' knowledge, practices, and attitudes of genetic counseling and genetic testing in the USA. Pulm Circ 2017; 7: 372–383.

45.

Badesch

Raskob

Elliott

et al.

Pulmonary arterial hypertension: Baseline characteristics from the REVEAL registry. Chest 2010; 137: 376–387.

46.

Larkin

Newman

Austin

et al.

Longitudinal analysis casts doubt on the presence of genetic anticipation in heritable pulmonary arterial hypertension. Am J Respir Crit Care Med 2012; 186: 892–896.

47.

Shapiro

Traiger

Turner

et al.

Sex differences in the diagnosis, treatment, and outcome of patients with pulmonary arterial hypertension enrolled in the registry to evaluate early and long-term pulmonary arterial hypertension disease management. Chest 2012; 141: 363–373.

48.

Oakley

Somerville

. Oral contraceptives and progressive pulmonary vascular disease. Lancet 1968; 1: 890–893.

49.

Kleiger

Boxer

Ingham

et al.

Pulmonary hypertension in patients using oral contraceptives. A report of six cases. Chest 1976; 69: 143–147.

50.

Abenhaim

Moride

Brenot

et al.

Appetite-suppressant drugs and the risk of primary pulmonary hypertension. N Engl J Med 1996; 335: 609–616.

51.

Thomson

Machado

Pauciulo

et al.

Sporadic primary pulmonary hypertension is associated with germline mutations of the gene encoding BMPR-II, a receptor member of the TGF-β family. J Med Genet 2000; 37: 741–745.

52.

Sztrymf

Coulet

Girerd

et al.

Clinical outcomes of pulmonary arterial hypertension in carriers of BMPR2 mutation. Am J Respir Crit Care Med 2008; 177: 1377–1383.

53.

Evans

Girerd

Montani

et al.

BMPR2 mutations and survival in pulmonary arterial hypertension: An individual participant data meta-analysis. Lancet Respir Med 2016; 4: 129–137.

54.

Girerd

Montani

Coulet

et al.

Clinical outcomes of pulmonary arterial hypertension in patients carrying an ACVRL1 (ALK1) mutation. Am J Respir Crit Care Med 2010; 181: 851–861.

55.

Girerd

Montani

Eyries

et al.

Absence of influence of gender and BMPR2 mutation type on clinical phenotypes of pulmonary arterial hypertension. Respir Res 2010; 11: 73.

56.

Elliott

Glissmeyer

Havlena

et al.

Relationship of BMPR2 mutations to vasoreactivity in pulmonary arterial hypertension. Circulation 2006; 113: 2509–2515.

57.

Chaisson

Dodson

Elliott

. Pulmonary capillary hemangiomatosis and pulmonary veno-occlusive disease. Clin Chest Med 2016; 37: 523–534.

58.

Humbert

Deng

Simonneau

et al.

BMPR2 germline mutations in pulmonary hypertension associated with fenfluramine derivatives. Eur Respir J 2002; 20: 518–523.

United States Pulmonary Hypertension Scientific Registry (USPHSR): rationale,design,and clinical implications

Abstract

Keywords

Background

USPHSR study overview

Study objectives

Patient population

Inclusion criteria

Exclusion criteria

Informed consent procedure

Data collection

Sample size

Data analysis

Evaluating hormone exposures

Evolving research needs

General issues

Discussion

Footnotes

Acknowledgments

Conflict of interest

Funding

References