Nair, K. Sreekumaran

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 The sections in this article are: Pathogenesis of Type I Diabetes Effect of Type I Diabetes on Carbohydrate Metabolism Insulin Secretion and Action Postabsorptive and Postprandial Carbohydrate Metabolism Effects of Type I Diabetes and Its Treatment on Fatty Acid Metabolism Adipose Tissue Postabsorptive FFA Metabolism Postprandial FFA Availability Effects of Exercise on Adipose Tissue Lipolysis Regulation of Lipolysis During Hypoglycemia Effects Of Type I Diabetes on Protein Metabolism Regulation of Body Protein Mass, Amino Acid Levels and Nitrogen Balance Effect of Insulin on Protein Balance and Interaction of Insulin with Other Hormones and Substrates Effects of Insulin on Whole‐Body Protein Dynamics Effect of Insulin on Amino Acid Transamination Effect of Insulin on Regional Protein Dynamics Effect of Insulin on the Synthesis Rates of Specific Proteins Impact of Type I Diabetes on Protein Metabolism

Intermuscular adipose tissue (IMAT) accumulates in the lower leg musculature of healthy older adults. IMAT was negatively associated with the rate of glucose infusion during a hyperinsulinemic-euglycemic clamp and muscle oxidative capacity. Exercise training decreased IMAT to a greater extent in young compared with older adults. Together these data support the implication that IMAT accumulation is linked with metabolic derangements in older adults but the restorative potential of exercise in older adults needs further evaluation.

Abstract Insulin resistance (IR) is a modifiable risk factor for dementia, yet its effects on brain metabolism and function remain unclear. In older adults, greater IR was associated with reduced cerebral glucose uptake (indicating impaired mitochondrial metabolism), atrophy, and weakened connectivity between brain regions critical for cognition. In neuron-specific insulin receptor knockout mice, brain IR produced deficits in hippocampal- and prefrontal-dependent tasks accompanied by reduced brain mitochondrial ATP and elevated reactive oxygen species. To evaluate reversibility of IR-induced brain deficits, forty older adults with IR were randomized to 40-weeks of metformin or placebo. Metformin improved insulin sensitivity, increased brain glucose uptake, strengthened cognitive network connectivity, and preserved whole-brain and regional volumes implicated in decision-making and learning. Metformin also improved processing speed and working memory. Collectively, these findings highlight IR as a driver of brain metabolism and support the concept that insulin sensitization can prevent neurobiological deficits in older people with IR.

AbstractSkeletal muscle atrophy was a characteristic of type 1 diabetes (T1DM) prior to insulin discovery and replacement. Indirect calorimetry during the post‐absorptive state demonstrated that increased fuel oxidation during transient insulin deprivation in T1DM caused depletion of energy stores. Further, insulin has a critical role in preserving muscle mitochondrial content and function by enhancing mitochondrial biogenesis and proteostasis. Insulin deficiency not only inhibits mitochondrial biogenesis but also accelerates the degradation of mitochondrial proteins, causing a decline in mitochondrial content and efficiency. Inefficient mitochondrial respiration, reflected by the uncoupling of oxidative phosphorylation and consequent decline in ATP production, adversely affects many cellular functions and causes high oxidative stress. Oxidative stress adversely affects cardiovascular functions and damages many skeletal muscle proteins, accelerating their degradation and explaining muscle atrophy. Increased degradation of muscle proteins increases amino acid efflux that stimulates the liver to synthesize many non‐insulin‐dependent proteins, potentially contributing to macrovascular complications. This phenomenon explains a paradoxical increase in whole‐body protein synthesis during insulin deficiency. Further, the mitochondrial biology of brain regions rich in insulin receptors concurrent with accelerated transport of ketones and lactate across the blood–brain barrier during insulin deficiency seems to protect the brain from oxidative stress. In contrast, insulin resistance associated with less ketone and lactate production renders the brain susceptible to protein oxidative damage. Oxidative damage and reduced ATP production potentially explain the higher prevalence of dementia in insulin‐resistant people. Enhancement of insulin sensitivity by aerobic exercise and metformin in pre‐clinical studies prevents mitochondrial dysfunction and oxidative damage to the brain.

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

AbstractBackgroundPrecursor plasma cell disorders such as monoclonal gammopathy of undetermined significance (MGUS) always precede the development of active malignancies such as multiple myeloma (MM). There is a need for novel biomarkers to identify those patients with such precursor plasma cell disorders who rapidly progress to MM. Plasma‐derived extracellular vesicles (EVs) may serve as a reservoir of potential biomarkers that can shed light on the pathogenesis and disease biology of MM.MethodsThis study isolated small EVs (SEVs) and large EVs (LEVs) from the platelet‐poor peripheral blood plasma of MGUS (n = 9) and MM (n = 12) patients using the size exclusion chromatography‐based method and evaluated their proteome using a label‐free proteomics workflow.ResultsIn total, 2055 proteins were identified in SEVs, while 2794 proteins were identified in LEVs. The transferrin receptor (or CD71) protein was upregulated in both populations of EVs derived from MM patients compared to MGUS patients and was of prognostic significance. Similarly, three isoforms of serum amyloid A (SAA) protein, SAA1, SAA2, and SAA4, were also highly upregulated in SEVs within MM patients relative to MGUS patients. Finally, CD40 expression was also higher in the LEVs derived from MM patients than in MGUS patients.ConclusionsThis study demonstrates the feasibility of successfully isolating both SEVs and LEVs from the peripheral blood of patients with plasma cell disorders and quantifying protein biomarkers within these EVs that could be of prognostic and diagnostic interest.