Asokan, Aneesh K

BACKGROUND: Some symptomatic patients manifest pulmonary hypertension (PH), despite normal pulmonary vascular resistance and pulmonary artery wedge pressure—a condition termed unclassified PH. Although hypothesized to reflect increased flow as seen in congenital heart disease, broader clinical implications remain unknown. METHODS: The current analysis included pulmonary vascular disease phenomics participants with either no PH or unclassified PH who underwent dynamic right heart catheterization and transpulmonary metabolomics. In a validation cohort, patients with no PH or unclassified PH underwent exercise right heart catheterization. In exploratory cohorts to understand the impact of increased flow, the prevalence of unclassified PH was assessed in (1) adult congenital heart disease and (2) high output heart failure. RESULTS: The overall prevalence of unclassified PH in pulmonary vascular disease phenomics (n=1046) and the validation cohort (n=1202) was 7.8% (175/2248), which was comparable to the 6.6% (66/1005) prevalence in adult congenital heart disease (n=1005), and lower than high output heart failure (n=159, prevalence 14.5% [23/159]; P =0.006). Increased flow occurred in a minority of unclassified PH from both pulmonary vascular disease phenomics (28%; 15/53) and the validation cohort (11%; 13/122). Unclassified PH (n=53) was associated with greater adiposity, higher heart failure with preserved ejection fraction (HFpEF)–age, body mass index, atrial fibrillation score probability, and more left heart remodeling compared with those with no PH (n=216). Metabolomics revealed lower glycine metabolites in unclassified PH indicative of metabolic dysfunction. Left heart remodeling, quality of life, exercise capacity, and glycine levels were all abnormal in unclassified PH relative to healthy controls (n=96). In the validation cohort, pulmonary artery wedge pressure, pulmonary vascular resistance, and pulmonary artery compliance were subtly abnormal at rest in unclassified PH (n=122) compared with no PH (n=312). With exercise testing, 59% (72/122) with unclassified PH had exertional pulmonary artery wedge pressure elevation consistent with undiagnosed HFpEF. CONCLUSIONS: The presence of PH without obvious cause most often reflects subclinical left heart and metabolic dysfunction consistent with unrecognized early-stage HFpEF. Dynamic provocation during right heart catheterization can unmask unrecognized HFpEF in over half of unclassified PH, which may help guide appropriate initiation of proven HFpEF therapies to improve symptoms and functional status. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02980887.

BACKGROUND: With pulmonary hypertension (PH), a pulmonary artery wedge pressure (PAWP)>15 mm Hg is used to diagnose left heart dysfunction, but some patients with adjudicated group 1 PH demonstrate PAWP>15 mm Hg. The primary objective of the study was to evaluate group 1 PH with high PAWP>15 mm Hg. METHODS: Patients with adjudicated group 1 PH from PVDOMICS between 2016 and 2019 were separated into high PAWP(>15 mm Hg) or normal PAWP and compared with adjudicated combined pre- and postcapillary (Cpc) PH related to heart failure with preserved ejection fraction (HFpEF). Participants underwent dynamic right heart catheterization and metabolomics. Findings were validated in 3 independent cohorts with adjudicated group 1 PH (validation cohorts 1 and 2 with exercise right heart catheterization and validation cohort 3 with resting right heart catheterization). RESULTS: Of 325 patients with group 1 PH (73% women, mean age 53.0±14.3 years), 15% (n=48) had high PAWP. Group 1 PH+high PAWP demonstrated greater obesity, left ventricular hypertrophy ( P <0.0002), left ventricular strain impairment ( P <0.0001), and decreased left ventricular compliance ( P <0.0001) compared with group 1 PH+normal PAWP, with changes comparable to Cpc-PH HFpEF (n=75). Compared with Cpc-PH HFpEF, left atrial function was better in group 1 PH+high PAWP with lower PAWP V wave, higher left atrial compliance, and left atrial ejection fraction ( P <0.0001 for all). Metabolomics demonstrated little difference between group 1 PH with high versus normal PAWP but large differences between group 1 PH+high PAWP versus Cpc-PH HFpEF (100 metabolites altered at false discovery rate P <0.05). Elevated PAWP was also observed in 18% of group 1 PH in the validation cohort 1 (n=402), with exercise PAWP response intermediately abnormal in group 1 PH+high PAWP relative to Cpc-PH HFpEF and group 1 PH+normal PAWP (interaction P <0.0001). Elevated PAWP was similarly observed in 22% and 19% of group 1 PH in validation cohorts 2 (n=55) and 3 (n=787), respectively. CONCLUSIONS: Approximately 1 in 5 adjudicated patients with group 1 PH has elevation in resting PAWP despite severe pulmonary vascular dysfunction and metabolomics consistent with traditionally defined group 1 PH. Despite resting PAWP elevation, these patients with group 1 PH were metabolomically and biologically distinct from Cpc PH HFpEF, with better left atrial function and diastolic reserve during exercise. These data emphasize the limitations of using resting PAWP alone to separate group 1 PH from HFpEF and call for development of more integrated clinical diagnostic criteria.

Abstract Rationale A subset of patients with group 1 pulmonary hypertension (PH) have superimposed left heart abnormalities with unclear metabolic implications. Objectives To compare serum/transpulmonary metabolome between group 1 PH stratified by heart failure with preserved ejection fraction (HFpEF) probability. Methods Patients with group 1 PH were stratified into low (&lt;25%) and high (⩾75%) HFpEF-ABA (age, body mass index, and atrial fibrillation) probability, with healthy control subjects and subjects with clinical HFpEF used for comparison of venous and transpulmonary metabolomics. Measurements and Main Results Group 1 PH + high HFpEF probability (n = 131) was associated with a significant increase in 207 metabolites (false discovery rate [FDR] P &lt; 0.05 and fold change &gt;1) (n = 193, t test) and a significant decrease in 231 metabolites (FDR P &lt; 0.05 and fold change &lt;1) (n = 193, t test) compared with group 1 PH + low HFpEF probability (n = 62). Group 1 PH + high HFpEF probability was associated with enhanced tryptophan metabolism with higher downstream kynurenine metabolite concentrations and lower serotonin concentrations (FDR P &lt; 0.002 for all, n = 193, t test). Linoleate (precursor to arachidonic acid and prostaglandins) and arginine and homoarginine (precursors to nitric oxide) were all lower in group 1 PH + high HFpEF probability (FDR P &lt; 0.03 for all, n = 193, t test). Metabolome changes in group 1 PH + high HFpEF probability overlapped with clinical HFpEF (n = 240) but were abnormal relative to control subjects (n = 85) (P &lt; 0.0001 for all, n = 456, t test). There was no evidence of differential transpulmonary uptake/release of most metabolites, suggesting probable nonpulmonary origin (except for serotonin, interaction P = 0.04; and kynurenine, interaction P = 0.03; n = 433, mixed model). Conclusions Patients with group 1 PH + high HFpEF probability have a unique metabolome characterized by enhanced tryptophan-kynurenine pathway breakdown, deficiency of amino acids (such as glycine and serine), lower serotonin, and decreased prostaglandin and nitric oxide precursors. Despite fulfilling clinical criteria for group 1 PH, these metabolome changes were comparable with clinical HFpEF, supporting biological overlap between these two forms of PH.

Insulin is a key regulator of amino acid metabolism. Many plasma amino acids, including lysine and its metabolite, α-aminoadipic acid (α-AA), a predictor for developing diabetes, are elevated in insulin resistance (IR). In 18 overweight women with IR and polycystic ovary syndrome compared with 12 lean control women, high physiological insulin during a euglycemic clamp failed to normalize many elevated amino acid metabolites, including branched-chain and aromatic amino acids, α-aminobutyric acid, and lysine, but normalized α-AA. To understand the underpinnings of differential responses of lysine and its metabolic product α-AA to high physiological insulin in IR compared with control participants, we developed a kinetic model using [α-15N1]-lysine and [13C1]-α-AA as tracers and measured the two tracers simultaneously in α-AA by innovative mass spectrometry. High insulin increased lysine conversion to α-AA in the IR and control groups but failed to normalize plasma lysine concentrations in IR due to a decrease in lysine metabolic clearance rate (MCR). In contrast, despite higher conversion rates of lysine to α-AA by high insulin, α-AA concentration decreased in IR because of the sustained greater MCR of α-AA. The abnormal amino acids and metabolites, even while on high physiological insulin, could potentially explain many functional derangements in IR. Article Highlights

We investigated the link between enhancement of SI (by hyperinsulinemic–euglycemic clamp) and muscle metabolites after 12 weeks of aerobic (high-intensity interval training [HIIT]), resistance training (RT), or combined training (CT) exercise in 52 lean healthy individuals. Muscle RNA sequencing revealed a significant association between SI after both HIIT and RT and the branched-chain amino acid (BCAA) metabolic pathway. Concurrently with increased expression and activity of branched-chain ketoacid dehydrogenase enzyme, many muscle amino metabolites, including BCAAs, glutamate, phenylalanine, aspartate, asparagine, methionine, and γ-aminobutyric acid, increased with HIIT, supporting the substantial impact of HIIT on amino acid metabolism. Short-chain C3 and C5 acylcarnitines were reduced in muscle with all three training modes, but unlike RT, both HIIT and CT increased tricarboxylic acid metabolites and cardiolipins, supporting greater mitochondrial activity with aerobic training. Conversely, RT and CT increased more plasma membrane phospholipids than HIIT, suggesting a resistance exercise effect on cellular membrane protection against environmental damage. Sex and age contributed modestly to the exercise-induced changes in metabolites and their association with cardiometabolic parameters. Integrated transcriptomic and metabolomic analyses suggest various clusters of genes and metabolites are involved in distinct effects of HIIT, RT, and CT. These distinct metabolic signatures of different exercise modes independently link each type of exercise training to improved SI and cardiometabolic risk. Article Highlights We aimed to understand the link between skeletal muscle metabolites and cardiometabolic health after exercise training. Although aerobic, resistance, and combined exercise training each enhance muscle insulin sensitivity as well as other cardiometabolic parameters, they disparately alter amino and citric acid metabolites as well as the lipidome, linking these metabolomic changes independently to the improvement of cardiometabolic risks with each exercise training mode. These findings reveal an important layer of the unique exercise mode–dependent changes in muscle metabolism, which may eventually lead to more informed exercise prescription for improving SI.