Background: Cancer-associated cachexia is a multifactorial metabolic syndrome characterized by progressive skeletal muscle and/or adipose tissue loss and affects approximately 40% of patients with non-small cell lung cancer (NSCLC). However, reliable circulating biomarkers for early detection and risk stratification remain undefined. Based on prior observations linking elevated circulating mitochondrial DNA (mtDNA) to cachexia, we hypothesized that mtDNA and inflammatory protein levels in plasma could predict cachexia onset and trajectories. Methods: We evaluated 27 patients with stage IV NSCLC enrolled in the SeroNet-CORALE cohort with plasma samples collected between 2020 and 2023. Forty biomarkers were quantified at two timepoints (T1 and T2) using a multiplexed MesoScale Discovery platform. Associations between log2-transformed biomarker levels and cachexia status were assessed using Firth's penalized logistic regression. Results: Among 27 patients (65% female; mean age 65 ± 10 years; 89% adenocarcinoma histology), cachectic patients exhibited lower body mass index at both time points (T1: 21.0 ± 2.0 vs. 27.0 ± 7.0; T2: 21.8 ± 4.9 vs. 25.2 ± 4.9). At T1, cachexia was strongly associated with elevated GDF15 (OR 4.29; 95% CI 1.04-29.74; p = 0.044) and IL-15 (OR 43.83; 95% CI 2.39->999; p = 0.007), whereas IL-4 had a protective association (OR 0.09; 95% CI 0.00-0.66; p = 0.013). At T2, cachexia was associated with higher mtDNA levels (OR 2.13; 95% CI 1.07-7.69; p = 0.022) and lower levels of IL-15, IL12/IL23p40, and MDC. Conclusions: Distinct inflammatory and mitochondrial biomarkers tracked cachexia evolution in advanced NSCLC, with early GDF-15/IL-15 elevations and later increases in circulating mtDNA. Larger longitudinal studies are warranted to validate these findings and define their clinical relevance.

This report describes single-cell proteomic analyses of cells dissociated from a complex mammalian tissue using direct label-free mass spectrometry (single-cell proteomics by mass spectrometry, SCP-MS). The nanoDTSC approach was applied to profile individual cells from aorta of male and female wild-type and Fbn1C1041G/+ Marfan mice. Leiden clustering identified all major aortic cell types including seven distinct smooth muscle cell (SMC) subtypes, with informative differences in cell proportions and differentially expressed proteins within cell types observed for both genotype and sex. Comparisons between single-cell RNA and single-cell proteomic profiles showed similarities in detection of major subtypes but not differentiation between SMC subtypes. Integrated multiomics analysis further identified genotype-dependent enrichment of unique SMC subtypes, relative to either protein or RNA datasets. Multiplexed-fluorescence based spatial proteomics validated several of these key genotype markers. Overall, these studies demonstrate the power of SCP-MS to detect novel aneurysm biology and serve as a guide for future development of SCP-MS methodology as it is applied to complex tissue cell mixtures and its integration with other omic modalities.

CD11c (integrin αX) is one of the β2 integrin members traditionally recognized as a dendritic cell marker. It forms the CD11c/CD18 heterodimer—also known as complement receptor 4 (CR4)—and mediates ligand binding to complement fragments, fibrinogen, and intercellular adhesion molecules in vitro. Although its expression on dendritic cells and a subset of macrophage populations has been well recognized historically, recent findings reveal that it demonstrates a broader expression profile, including in neutrophils. In neutrophils, CD11c is predominantly intracellular, suggesting a non-canonical role beyond cellular adhesion. We previously identified IQGAP1 as an intracellular binding partner of CD11c/CD18, implicating this interaction in neutrophil maturation. Here, mature CD11c-deficient neutrophils displayed impaired reactive oxygen species (ROS) generation while maintaining normal phagocytosis, indicating a selective defect in oxidative burst. Given the central role of NADPH oxidase and Rac activation in ROS production, we hypothesized that CD11c would influence this pathway. Phosphoproteomic profiling revealed reduced phosphorylation of the Rac guanine nucleotide exchange factor DOCK2 in CD11c-deficient neutrophils upon phorbol 12-myristate 13-acetate (PMA) stimulation. The analysis involving immunoprecipitation and proteomics confirmed a CD11c–DOCK2 association. These results supported a model in which CD11c would directly engage DOCK2 to promote Rac activation and NADPH oxidase function, uncovering a novel integrin-mediated mechanism regulating neutrophil effector activity. This work expands the functional repertoire of CD11c and provides a new insight into integrin signaling in innate immunity.

Systemic sclerosis (SSc) is a rare connective tissue disease, frequently affecting the skin, lungs, and pulmonary vasculature. Approximately 30–50

BACKGROUND AND AIMS:With pulmonary arterial hypertension (PAH), right ventricular (RV) function is a major determinant of survival. Despite current therapies, maladaptive changes ensue in the RV muscle of PAH patients, culminating in RV dysfunction and failure. The aims of the study were to evaluate the impact of intra-coronary (IC) cardiosphere-derived cells (CDCs) in attenuating the maladaptive pathobiology in the RV muscle and evaluating mechanisms underlying improvements in RV function. METHODS:Two groups of the Sugen/Hypoxia rat model of PAH, exhibiting significantly reduced RV function, via TAPSE measurements, received either intracoronary infusion of CDCs or PBS placebo. Immunohistochemistry methods were used to assess RV pathobiological changes. Additionally, advanced proteomics were employed to examine protein signaling pathways and upstream regulators. RESULTS:RV muscle capillarity was significantly reduced in the PAH rats while RV muscle fibrosis was increased. IC CDCs significantly increased RV muscle capillarity back to levels noted in healthy rats and reduced RV free wall fibrosis. Further, a significant reduction in iNOS+ (M1) macrophages was also observed within the RV free wall in CDC-treated animals. Proteomic analysis of RV muscle in CDC- or PBS-treated PAH rats showed alterations in protein pathways related to inflammation, fibrosis, autophagy, cell vitality, and angiogenesis. These changes were consistent with putative coordination by a small number of key upstream regulators (MYC, TP53, HNF4A, TGFB1, and KRAS). TAPSE was significantly reduced in PBS-treated animals but was maintained at or above baseline levels in CDC-treated animals. CONCLUSIONS:CDC therapy can significantly impact the maladaptive milieu of the RV myocardium in advanced PAH, by altering several pathobiological pathways. Such adjunctive therapy, in addition to those employed to reduce pulmonary vascular resistance, would be a great advance in managing RV failure, for which no effective current approved therapies exist.

HomeCirculationVol. 149, No. 12Apolipoproteins Quantified Using Blood Volumetric Absorptive Microsampling and High-Throughput Mass Spectrometry for Risk Assessment in Ischemic Heart Disease No AccessLetterRequest AccessFull TextAboutView Full TextView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toNo AccessLetterRequest AccessFull TextApolipoproteins Quantified Using Blood Volumetric Absorptive Microsampling and High-Throughput Mass Spectrometry for Risk Assessment in Ischemic Heart Disease Paul Marano, Kelly Mouapi, Andy Kim, Mitra Mastali, Irene van den Broek, Danica Manalo, Qin Fu, Susan Cheng, Chrisandra Shufelt, Brennan Spiegel, C. Noel Bairey Merz and Jennifer E. Van Eyk Paul MaranoPaul Marano https://orcid.org/0000-0002-0011-3369 Barbra Streisand Women's Heart Center, Smidt Heart Institute, Los Angeles, CA (P.M., A.K., S.C., C.S., C.N.B.M., J.E.V.E.). , Kelly MouapiKelly Mouapi Advanced Clinical Biosystems Research Institute, Cedars-Sinai Smidt Heart Institute, Los Angeles, CA (K.M., M.M., I.B., D.M., Q.F., J.E.V.E.). , Andy KimAndy Kim https://orcid.org/0000-0003-0395-9471 Barbra Streisand Women's Heart Center, Smidt Heart Institute, Los Angeles, CA (P.M., A.K., S.C., C.S., C.N.B.M., J.E.V.E.). , Mitra MastaliMitra Mastali Advanced Clinical Biosystems Research Institute, Cedars-Sinai Smidt Heart Institute, Los Angeles, CA (K.M., M.M., I.B., D.M., Q.F., J.E.V.E.). , Irene van den BroekIrene van den Broek Advanced Clinical Biosystems Research Institute, Cedars-Sinai Smidt Heart Institute, Los Angeles, CA (K.M., M.M., I.B., D.M., Q.F., J.E.V.E.). , Danica ManaloDanica Manalo Advanced Clinical Biosystems Research Institute, Cedars-Sinai Smidt Heart Institute, Los Angeles, CA (K.M., M.M., I.B., D.M., Q.F., J.E.V.E.). , Qin FuQin Fu https://orcid.org/0000-0001-9056-8449 Advanced Clinical Biosystems Research Institute, Cedars-Sinai Smidt Heart Institute, Los Angeles, CA (K.M., M.M., I.B., D.M., Q.F., J.E.V.E.). , Susan ChengSusan Cheng https://orcid.org/0000-0002-4977-036X Barbra Streisand Women's Heart Center, Smidt Heart Institute, Los Angeles, CA (P.M., A.K., S.C., C.S., C.N.B.M., J.E.V.E.). , Chrisandra ShufeltChrisandra Shufelt https://orcid.org/0000-0001-6886-9210 Barbra Streisand Women's Heart Center, Smidt Heart Institute, Los Angeles, CA (P.M., A.K., S.C., C.S., C.N.B.M., J.E.V.E.). , Brennan SpiegelBrennan Spiegel Cedars-Sinai Center for Outcomes Research and Education, Cedars-Sinai Medical Center, Los Angeles, CA (B.S.). , C. Noel Bairey MerzC. Noel Bairey Merz Correspondence to: C. Noel Bairey Merz, MD, Barbra Streisand Women's Heart Center, Cedars-Sinai Medical Center, 127 S San Vicente Blvd, Los Angeles, CA 90048. Email E-mail Address: [email protected] https://orcid.org/0000-0002-9933-5155 Barbra Streisand Women's Heart Center, Smidt Heart Institute, Los Angeles, CA (P.M., A.K., S.C., C.S., C.N.B.M., J.E.V.E.). and Jennifer E. Van EykJennifer E. Van Eyk https://orcid.org/0000-0001-9050-148X Barbra Streisand Women's Heart Center, Smidt Heart Institute, Los Angeles, CA (P.M., A.K., S.C., C.S., C.N.B.M., J.E.V.E.). Advanced Clinical Biosystems Research Institute, Cedars-Sinai Smidt Heart Institute, Los Angeles, CA (K.M., M.M., I.B., D.M., Q.F., J.E.V.E.). Originally published18 Mar 2024https://doi.org/10.1161/CIRCULATIONAHA.123.066034Circulation. 2024;149:970–972Footnotes*P. Marano and K. Mouapi contributed equally.†A. Kim and M. Mastali contributed equally.For Sources of Funding and Disclosures, see page 972.Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03064360.Circulation is available at www.ahajournals.org/journal/circCorrespondence to: C. Noel Bairey Merz, MD, Barbra Streisand Women's Heart Center, Cedars-Sinai Medical Center, 127 S San Vicente Blvd, Los Angeles, CA 90048. Email merz@cshs.orgREFERENCES1. Pechlaner R, Tsimikas S, Yin X, Willeit P, Baig F, Santer P, Oberhollenzer F, Egger G, Witztum JL, Alexander VJ, et al. Very-low-density lipoprotein–associated apolipoproteins predict cardiovascular events and are lowered by inhibition of APOC-III.J Am Coll Cardiol. 2017; 69:789–800. doi: 10.1016/j.jacc.2016.11.065CrossrefMedlineGoogle Scholar2. van den Broek I, Fu Q, Kushon S, Kowalski MP, Millis K, Percy A, Holewinski RJ, Venkatraman V, Van Eyk JE. Application of volumetric absorptive microsampling for robust, high-throughput mass spectrometric quantification of circulating protein biomarkers.Clin Mass Spectrom. 2017; 4-5:25–33. doi: 10.1016/j.clinms.2017.08.004CrossrefGoogle Scholar3. Fuller G, Njune Mouapi K, Joung S, Shufelt C, van den Broek I, Lopez M, Dhawan S, Mastali M, Spiegel C, Bairey Merz N, et al. Feasibility of patient-centric remote dried blood sampling: the Prediction, Risk, and Evaluation of Major Adverse Cardiac Events (PRE-MACE) study.Biodemography Soc Biol. 2019; 65:313–322. doi: 10.1080/19485565.2020.1765735CrossrefMedlineGoogle Scholar4. van den Broek I, Mastali M, Mouapi K, Bystrom C, Bairey Merz CN, Van Eyk JE. Quality control and outlier detection of targeted mass spectrometry data from multiplex protein panels.J Proteome Res. 2020; 19:2278–2293. doi: 10.1021/acs.jproteome.9b00854CrossrefMedlineGoogle Scholar5. Shufelt CL, Kim A, Joung S, Barsky L, Arnold C, Cheng S, Dhawan S, Fuller G, Speier W, Lopez M, et al. Biometric and psychometric remote monitoring and cardiovascular risk biomarkers in ischemic heart disease.J Am Heart Assoc. 2020; 9:e016023. doi: 10.1161/JAHA.120.016023LinkGoogle Scholar eLetters(0)eLetters should relate to an article recently published in the journal and are not a forum for providing unpublished data. Comments are reviewed for appropriate use of tone and language. Comments are not peer-reviewed. Acceptable comments are posted to the journal website only. Comments are not published in an issue and are not indexed in PubMed. Comments should be no longer than 500 words and will only be posted online. References are limited to 10. Authors of the article cited in the comment will be invited to reply, as appropriate.Comments and feedback on AHA/ASA Scientific Statements and Guidelines should be directed to the AHA/ASA Manuscript Oversight Committee via its Correspondence page.Sign In to Submit a Response to This Article Previous Back to top Next FiguresReferencesRelatedDetails March 19, 2024Vol 149, Issue 12 Advertisement Article InformationMetrics © 2024 American Heart Association, Inc.https://doi.org/10.1161/CIRCULATIONAHA.123.066034PMID: 38498608 Originally publishedMarch 18, 2024 KeywordsapolipoproteinsC-reactive proteinmass spectrometrypro-brain natriuretic peptide (1-76)troponinPDF download Advertisement SubjectsChronic Ischemic Heart Disease

Background: Among women with signs and symptoms of ischemia and no obstructive coronary arteries (INOCA) around 10% develop heart failure with preserved ejection fraction (HFpEF). Mechanisms contributing to AMI and HFpEF progression in INOCA are poorly understood. Purpose: To characterize clinical profile and stress cardiac magnetic resonance imaging (CMRI) myocardial features of INOCA patients with and without increased troponin levels in response to handgrip exercise. Methods: Women with suspected INOCA underwent cardiac MRI and invasive coronary function testing (CFT), including coronary sinus (CS) cannulation, handgrip exercise testing, and serial CS plasma sampling before, after 3 minutes of isometric handgrip stress at 30% of maximal voluntary contraction, and after 5 minutes of recovery. High sensitivity cardiac troponin I (hsTnI) was measured using commercial immunoassay (R-PLEX, Meso Scale Discovery, Rockville, MD) and compared using t-tests. Results: A total of 51 women with complete data were included, of whom 31 (60.7%) had handgrip provoked increases in hsTnI levels from baseline, while 20 (39.2%) did not. Baseline characteristics are shown in Table. Patients with increased hsTnI levels had greater impaired global longitudinal strain rates and early diastolic strain rates (radial and circumferential) compared to those without increased hsTnI. No significant differences were observed in myocardial perfusion reserve index (MPRI). Conclusion: Women with INOCA demonstrating objective evidence of handgrip exercise provoked myocardial injury exhibit evidence of myocardial dysfunction not related to myocardial perfusion. Further prospective research is needed to understand the sequence of relations between coronary microvascular dysfunction contribution to HFpEF progression.

Characterization of rare cell types in heterogeneous cell populations extracted from tissue or organs requires profiling hundreds of individual cells. Parallelized nanoflow dual-trap single-column liquid chromatography (nanoDTSC) quantifies peptides over 11.5 out of 15 minutes of total run time using standard commercial components, thus offering the most accessible and efficient LC solution for single-cell applications. Over 1,000 proteins were quantified in individual cardiomyocytes and heterogenous aorta cells using nanoDTSC.

Epithelial and stromal/mesenchymal limbal stem cells contribute to corneal homeostasis and cell renewal. Extracellular vesicles (EVs), including exosomes (Exos), can be paracrine mediators of intercellular communication. Previously, we described cargos and regulatory roles of limbal stromal cell (LSC)-derived Exos in non-diabetic (N) and diabetic (DM) limbal epithelial cells (LECs). Presently, we quantify the miRNA and proteome profiles of human LEC-derived Exos and their regulatory roles in N- and DM-LSC. We revealed some miRNA and protein differences in DM vs. N-LEC-derived Exos’ cargos, including proteins involved in Exo biogenesis and packaging that may affect Exo production and ultimately cellular crosstalk and corneal function. Treatment by N-Exos, but not by DM-Exos, enhanced wound healing in cultured N-LSCs and increased proliferation rates in N and DM LSCs vs. corresponding untreated (control) cells. N-Exos-treated LSCs reduced the keratocyte markers ALDH3A1 and lumican and increased the MSC markers CD73, CD90, and CD105 vs. control LSCs. These being opposite to the changes quantified in wounded LSCs. Overall, N-LEC Exos have a more pronounced effect on LSC wound healing, proliferation, and stem cell marker expression than DM-LEC Exos. This suggests that regulatory miRNA and protein cargo differences in DM- vs. N-LEC-derived Exos could contribute to the disease state.

Identification and proteomic characterization of rare cell types within complex organ-derived cell mixtures is best accomplished by label-free quantitative mass spectrometry. High throughput is required to rapidly survey hundreds to thousands of individual cells to adequately represent rare populations. Here we present parallelized nanoflow dual-trap single-column liquid chromatography (nanoDTSC) operating at 15 min of total run time per cell with peptides quantified over 11.5 min using standard commercial components, thus offering an accessible and efficient LC solution to analyze 96 single cells per day. At this throughput, nanoDTSC quantified over 1000 proteins in individual cardiomyocytes and heterogeneous populations of single cells from the aorta.

Systemic sclerosis is a rare connective tissue disease; and interstitial lung disease (SSc–ILD) is associated with significant morbidity and mortality. There are no clinical, radiologic features, nor biomarkers that identify the specific time when patients are at risk for progression at which the benefits from treatment outweigh the risks. Our study aimed to identify blood protein biomarkers associated with progression of interstitial lung disease in patients with SSc–ILD using an unbiased, high-throughput approach. We classified SSc–ILD as progressive or stable based on change in forced vital capacity over 12 months or less. We profiled serum proteins by quantitative mass spectrometry and analyzed the association between protein levels and progression of SSc–ILD via logistic regression. The proteins associated with at a p value of < 0.1 were queried in the ingenuity pathway analysis (IPA) software to identify interaction networks, signaling, and metabolic pathways. Through principal component analysis, the relationship between the top 10 principal components and progression was evaluated. Unsupervised hierarchical clustering with heatmapping was done to define unique groups. The cohort consisted of 72 patients, 32 with progressive SSc–ILD and 40 with stable disease with similar baseline characteristics. Of a total of 794 proteins, 29 were associated with disease progression. After adjusting for multiple testing, these associations did not remain significant. IPA identified five upstream regulators that targeted proteins associated with progression, as well as a canonical pathway with a higher signal in the progression group. Principal component analysis showed that the ten components with the highest Eigenvalues represented 41% of the variability of the sample. Unsupervised clustering analysis revealed no significant heterogeneity between the subjects. We identified 29 proteins associated with progressive SSc–ILD. While these associations did not remain significant after accounting for multiple testing, some of these proteins are part of pathways relevant to autoimmunity and fibrogenesis. Limitations included a small sample size and a proportion of immunosuppressant use in the cohort, which could have altered the expression of inflammatory and immunologic proteins. Future directions include a targeted evaluation of these proteins in another SSc–ILD cohort or application of this study design to a treatment naïve population.

HomeCirculation: Heart FailureVol. 16, No. 4Transforming Growth Factor-β Analysis of the VANISH Trial Cohort Free AccessLetterPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessLetterPDF/EPUBTransforming Growth Factor-β Analysis of the VANISH Trial Cohort Yuri Kim, Mitra Mastali, Jennifer E. Van Eyk, E. John Orav, Christoffer R. Vissing, Sharlene M. Day, Anna Axelsson Raja, Mark W. Russell, Kenneth Zahka, Harry M. Lever, Alexandre C. Pereira, Anne M. Murphy, Charles Canter, Richard G. Bach, Matthew T. Wheeler, Joseph W. Rossano, Anjali T. Owens, Henning Bundgaard, Lee Benson, Luisa Mestroni, Matthew R.G. Taylor, Amit R. Patel, Ivan Wilmot, Philip Thrush, Jonathan H. Soslow, Jason R. Becker, Christine E. Seidman and Carolyn Y. Ho Yuri KimYuri Kim Correspondence to: Yuri Kim, MD, PhD, Division of Cardiovascular Medicine, Brigham and Women's Hospital, 75 Francis St, Boston, MA 02115. Email E-mail Address: [email protected] https://orcid.org/0000-0001-5978-5779 Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, MA (Y.K., C.R.V., C.E.S., C.Y.H.). , Mitra MastaliMitra Mastali Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA (M.M., J.E.V.E.). , Jennifer E. Van EykJennifer E. Van Eyk https://orcid.org/0000-0001-9050-148X Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA (M.M., J.E.V.E.). , E. John OravE. John Orav Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA (E.J.O.). , Christoffer R. VissingChristoffer R. Vissing https://orcid.org/0000-0002-0834-206X Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, MA (Y.K., C.R.V., C.E.S., C.Y.H.). Department of Cardiology, Copenhagen University Hospital Rigshospitalet, Denmark (C.R.V., A.A.R., H.B.). , Sharlene M. DaySharlene M. Day https://orcid.org/0000-0001-9802-7188 Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia (S.M.D., A.T.O.). , Anna Axelsson RajaAnna Axelsson Raja https://orcid.org/0000-0001-8665-3309 Department of Cardiology, Copenhagen University Hospital Rigshospitalet, Denmark (C.R.V., A.A.R., H.B.). , Mark W. RussellMark W. Russell https://orcid.org/0000-0003-4855-9260 Division of Pediatric Cardiology, Department of Pediatrics, University of Michigan Medical Center, Ann Arbor (M.W.R.). , Kenneth ZahkaKenneth Zahka Department of Pediatric Cardiology, Cleveland Clinic Children's, Pediatric Institute, Cleveland Clinic Foundation, OH (K.Z., H.M.L.). , Harry M. LeverHarry M. Lever Department of Pediatric Cardiology, Cleveland Clinic Children's, Pediatric Institute, Cleveland Clinic Foundation, OH (K.Z., H.M.L.). , Alexandre C. PereiraAlexandre C. Pereira https://orcid.org/0000-0002-7782-5540 Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, Brazil (A.C.P.). , Anne M. MurphyAnne M. Murphy https://orcid.org/0000-0001-9254-3202 Division of Pediatric Cardiology, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD (A.M.M.). , Charles CanterCharles Canter https://orcid.org/0000-0002-0007-7337 Department of Pediatrics (C.C.), Washington University School of Medicine, St. Louis, MO. , Richard G. BachRichard G. Bach Department of Medicine (R.G.B.), Washington University School of Medicine, St. Louis, MO. , Matthew T. WheelerMatthew T. Wheeler https://orcid.org/0000-0001-8721-3022 Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, CA (M.T.W.). , Joseph W. RossanoJoseph W. Rossano https://orcid.org/0000-0002-8284-0673 Division of Cardiology, Children's Hospital of Philadelphia, PA (J.W.R.). , Anjali T. OwensAnjali T. Owens https://orcid.org/0000-0002-9669-8495 Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia (S.M.D., A.T.O.). , Henning BundgaardHenning Bundgaard https://orcid.org/0000-0002-0563-7049 Department of Cardiology, Copenhagen University Hospital Rigshospitalet, Denmark (C.R.V., A.A.R., H.B.). Department of Clinical Medicine, University of Copenhagen, Denmark (H.B.). , Lee BensonLee Benson https://orcid.org/0000-0002-1407-1825 The Labatt Family Heart Centre, The Hospital for Sick Children, University of Toronto, ON, Canada (L.B.). , Luisa MestroniLuisa Mestroni https://orcid.org/0000-0003-1116-2286 Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora (L.M., M.R.G.T.). , Matthew R.G. TaylorMatthew R.G. Taylor https://orcid.org/0000-0001-9043-0810 Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora (L.M., M.R.G.T.). , Amit R. PatelAmit R. Patel https://orcid.org/0000-0001-7621-6463 Division of Cardiology, University of Virginia, Charlottesville (A.R.P.). , Ivan WilmotIvan Wilmot Heart Institute, Cincinnati Children's Hospital Medical Center, OH (I.W.). , Philip ThrushPhilip Thrush Division of Pediatric Cardiology, Ann & Robert H. Lurie Children's Hospital of Chicago, IL (P.T.). , Jonathan H. SoslowJonathan H. Soslow https://orcid.org/0000-0001-9194-5330 Division of Pediatric Cardiology, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN (J.H.S.). , Jason R. BeckerJason R. Becker https://orcid.org/0000-0002-2107-8179 Division of Cardiology, University of Pittsburgh School of Medicine, PA (J.R.B.). , Christine E. SeidmanChristine E. Seidman https://orcid.org/0000-0001-6380-1209 Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, MA (Y.K., C.R.V., C.E.S., C.Y.H.). Howard Hughes Medical Institute, Chevy Chase, MD (C.E.S.). and Carolyn Y. HoCarolyn Y. Ho https://orcid.org/0000-0002-7334-7924 Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, MA (Y.K., C.R.V., C.E.S., C.Y.H.). and on behalf of the VANISH Investigators Originally published31 Mar 2023https://doi.org/10.1161/CIRCHEARTFAILURE.122.010314Circulation: Heart Failure. 2023;16Other version(s) of this articleYou are viewing the most recent version of this article. Previous versions: March 31, 2023: Ahead of Print Hypertrophic cardiomyopathy (HCM) is a primary myocardial disorder characterized by unexplained left ventricular hypertrophy. Rare damaging genetic variants in sarcomere genes, including myosin binding protein C3 (MYBPC3) and myosin heavy chain 7 (MYH7) are responsible for ≈70% of familial disease.1 Patients with HCM are at increased risk of developing heart failure, arrhythmias, and sudden cardiac death.1Previous basic investigation demonstrated that TGF-β (transforming growth factor β) plays an essential role in activating profibrotic pathways involved in the early pathogenesis of HCM.2,3 Furthermore, in a mouse model of sarcomeric HCM, treatment with either a TGF-β neutralizing antibody or with the angiotensin II receptor blocker (ARB) losartan attenuated the development of left ventricular hypertrophy and fibrosis. However, treatment was only effective if administered early in life, prior to the emergence of clinically overt features of HCM.3 These studies were the foundation for the VANISH trial (Valsartan for Attenuating Disease Evolution in Early Sarcomeric Hypertrophic Cardiomyopathy).4 One hundred seventy-eight participants with early stage sarcomeric HCM were randomized to receive placebo (n=90) or valsartan (n=88) for 2 years. The primary outcome assessed a composite z score reflecting changes in cardiac structure and function from baseline to end of study. The score included left ventricular (LV) wall thickness, LV mass, LV volumes, left atrial volume, tissue Doppler diastolic and systolic velocities, and serum levels of high-sensitivity troponin T and N-terminal pro-B-type natriuretic protein. VANISH demonstrated that ARB valsartan attenuated disease progression in this cohort. Participants receiving valsartan had an increase in composite z score, indicating relative improvement, whereas those receiving placebo had a decrease, indicating relative worsening (P=0.001; Figure [A]). However, the mechanism underlying this treatment benefit is unknown. While data in HCM are currently limited, a previous study in Marfan syndrome patients suggested that beneficial effects of ARB may be associated with a reduction in circulating TGF-β levels.5 Therefore, here, we investigated if circulating TGF-β levels changed in response to valsartan therapy in the VANISH trial cohort.Download figureDownload PowerPointFigure. Description of the study cohort and changes in TGF-β levels with placebo and valsartan treatment. A, Baseline characteristics of the study cohort and results of the primary outcome of the VANISH trial (Valsartan for Attenuating Disease Evolution in Early Sarcomeric Hypertrophic Cardiomyopathy).4 Nine clinical components, including serum troponin T and NT-proBNP (N-terminal pro-B-type natriuretic protein) levels, left ventricular (LV) mass index, LV end diastolic volume index, LV end systolic volume index, maximal LV wall thickness, left atrial volume index, E′ velocity, and S′ velocity, were integrated to create the composite z score (primary efficacy outcome). The positive z-score value indicates relative improvement. *n=77 and 80 for placebo and valsartan groups, respectively. ^n=73 and 77 for placebo and valsartan groups, respectively. B, Differences in log values of circulating TGF-β (transforming growth factor β) measurements (pg/mL) from baseline to year 2. No significant difference was identified between the 2 treatment groups in the primary cohort with early hypertrophic cardiomyopathy in the VANISH trial. P values were calculated using unpaired t test. IQR indicates interquartile range.The study population included 178 participants with early stage HCM in the VANISH trial. All participants provided informed consent, and the study was approved by institutional review committees. Peripheral blood was collected prior to randomization (placebo n=90 or valsartan n=88) and at end of study at year 2. We measured circulating TGF-β levels (pg/mL) in free and total (free plus TGF-β bound to latent TGF-β binding proteins) forms using an enzyme-linked immunosorbent assay (Quanterix, Billerica, MA) and compared the change in levels from baseline to year 2. TGF-β values were not normally distributed, therefore, log transformed for analysis. P values were calculated using paired t test when comparing changes within each subject and unpaired t test when comparing differences between 2 groups. Participants, who did not have interpretable TGF-β measurements available from both time points were excluded (21 for total TGF-β and 28 for free TGF-β). The data and analytic methods will be made available to other researchers upon request.We compared the change in TGF-β levels in placebo- and valsartan-treated participants. Overall, total TGF-β levels increased significantly during follow-up in both placebo (mean from 8.27 to 8.52; P=0.003) and valsartan-treated groups (mean from 8.26 to 8.49; P=0.02). However, the degree of increase of total TGF-β levels was not significantly different between the treatment groups (P=0.85; Figure [B]). Changes in free TGF-β levels were also similar between the 2 treatment groups (P=0.63; Figure [B]).In this study, we analyzed changes in circulating TGF-β levels in the VANISH trial to determine if valsartan treatment was associated with a decrease in TGF-β levels as a potential mechanism underlying the improvement in cardiac remodeling seen in patients with early HCM. No significant difference was seen in the change in circulating TGF-β levels between placebo- and valsartan-treated participants.Limitations of the current study include the small number of participants, uncertain relationship between the circulating levels of TGF-β measured and myocardial levels of TGF-β, which may be more biologically relevant, and inability to differentiate between the TGF-β isoforms (TGF-β1, TGF-β2, and TGF-β3). Although a previous study using animal models suggested potential effects of ARBs in downregulating TGF-β signaling,3 findings from animal studies may not directly translate to human studies. In addition, the current study focused on only 1 aspect of a very complex TGF-β signaling pathway, which includes a wide array of upstream and downstream regulators and interacts with multiple other signaling pathways. For example, ARBs may affect clinical progression of HCM via signaling pathways other than the TGF-β pathway such as the renin-angiotensin system or the PI3K/AKT pathway.Recognizing these limitations, our results suggest that disease-modifying effects of ARBs identified in early stage HCM are not dependent on decreasing circulating TGF-β levels. Further studies are needed to better characterize how ARBs improve cardiac remodeling in early HCM, to elucidate the pathogenesis of HCM, and to refine development of additional disease-modifying therapies.Article InformationAcknowledgmentsThe authors thank the families and patients, who participated in this study and the Cedars-Sinai Medical Center Proteomics and Metabolomics Core, who performed the ELISA.Sources of FundingThe VANISH trial (Valsartan for Attenuating Disease Evolution in Early Sarcomeric Hypertrophic Cardiomyopathy) was funded by the National Institutes of Health/National Heart, Lung, and Blood Institute (P50HL112349; Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01912534).AppendixVANISH Investigators: E. Kevin Hall, MD (Department of Pediatrics, Yale University School of Medicine, New Haven, CT); Lubna Choudhury, MD (Division of Cardiology, Feinberg School of Medicine, Bluhm Cardiovascular Institute, Northwestern University, Chicago, IL); Elfriede Pahl, MD (Division of Pediatric Cardiology, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN); Kimberly Y. Lin, MD (Division of Cardiology, Children's Hospital of Philadelphia, Philadelphia, PA).Disclosures Study medication (blinded valsartan and matching placebo) was provided by Novartis. Novartis was not involved in the design or conduct of the study; data collection, data management, data analysis, or data interpretation; preparation, review, or approval of the manuscript; or decision to submit the article for publication.Footnotes*A list of VANISH Investigators is provided in the Appendix.This manuscript was sent to John C. Burnett, Jr, MD, Guest Editor, for review by expert referees, editorial decision, and final disposition.For Sources of Funding and Disclosures, see page 376.Correspondence to: Yuri Kim, MD, PhD, Division of Cardiovascular Medicine, Brigham and Women's Hospital, 75 Francis St, Boston, MA 02115. Email ykim@genetics.med.harvard.eduReferences1. Ho CY, Day SM, Ashley EA, Michels M, Pereira AC, Jacoby D, Cirino AL, Fox JC, Lakdawala NK, Ware JS, et al. Genotype and lifetime burden of disease in hypertrophic cardiomyopathy.Circulation. 2018; 138:1387–1398. doi: 10.1161/CIRCULATIONAHA.117.033200LinkGoogle Scholar2. Kim JB, Porreca GJ, Song L, Greenway SC, Gorham JM, Church GM, Seidman CE, Seidman JG. Polony multiplex analysis of gene expression (PMAGE) in mouse hypertrophic cardiomyopathy.Science. 2007; 316:1481–1484. doi: 10.1126/science.1137325CrossrefMedlineGoogle Scholar3. Teekakirikul P, Eminaga S, Toka O, Alcalai R, Wang L, Wakimoto H, Nayor M, Konno T, Gorham JM, Wolf CM, et al. Cardiac fibrosis in mice with hypertrophic cardiomyopathy is mediated by non-myocyte proliferation and requires Tgf-β.J Clin Invest. 2010; 120:3520–3529. doi: 10.1172/JCI42028CrossrefMedlineGoogle Scholar4. Ho CY, Day SM, Axelsson A, Russell MW, Zahka K, Lever HM, Pereira AC, Colan SD, Margossian R, Murphy AM, et al. Valsartan in early-stage hypertrophic cardiomyopathy: a randomized phase 2 trial.Nat Med. 2021; 27:1818–1824. doi: 10.1038/s41591-021-01505-4CrossrefMedlineGoogle Scholar5. Matt P, Schoenhoff F, Habashi J, Holm T, Van Erp C, Loch D, Carlson OD, Griswold BF, Fu Q, De Backer J, et al. Circulating TGFβ in Marfan's syndrome.Circulation. 2009; 120:526–532. doi: 10.1161/CIRCULATIONAHA.108.841981LinkGoogle Scholar Previous Back to top Next FiguresReferencesRelatedDetails April 2023Vol 16, Issue 4 Advertisement Article Information Metrics © 2023 American Heart Association, Inc.https://doi.org/10.1161/CIRCHEARTFAILURE.122.010314PMID: 36999957 Originally publishedMarch 31, 2023 Keywordsangiotensin receptor blockershypertrophic cardiomyopathyTGF-βPDF download Advertisement Subjects Cardiomyopathy Hypertrophy Remodeling Translational Studies

Skeletal muscle is a major regulatory tissue of whole-body metabolism and is composed of a diverse mixture of cell (fiber) types. Aging and several diseases differentially affect the various fiber types, and therefore, investigating the changes in the proteome in a fiber-type specific manner is essential. Recent breakthroughs in isolated single muscle fiber proteomics have started to reveal heterogeneity among fibers. However, existing procedures are slow and laborious, requiring 2 h of mass spectrometry time per single muscle fiber; 50 fibers would take approximately 4 days to analyze. Thus, to capture the high variability in fibers both within and between individuals requires advancements in high throughput single muscle fiber proteomics. Here we use a single cell proteomics method to enable quantification of single muscle fiber proteomes in 15 min total instrument time. As proof of concept, we present data from 53 isolated skeletal muscle fibers obtained from two healthy individuals analyzed in 13.25 h. Adapting single cell data analysis techniques to integrate the data, we can reliably separate type 1 and 2A fibers. Ninety-four proteins were statistically different between clusters indicating alteration of proteins involved in fatty acid oxidation, oxidative phosphorylation, and muscle structure and contractile function. Our results indicate that this method is significantly faster than prior single fiber methods in both data collection and sample preparation while maintaining sufficient proteome depth. We anticipate this assay will enable future studies of single muscle fibers across hundreds of individuals, which has not been possible previously due to limitations in throughput.

Abstract Background Women with signs and symptoms of ischemia and no obstructive coronary arteries (INOCA) are suspected to have myocardial ischemia, ∼10% have prior myocardial scar often in the absence of acute myocardial infarction (AMI) diagnosis and the development of heart failure with preserved ejection fraction (HFpEF) is relatively frequent. The mechanisms contributing to AMI and HFpEF progression are poorly understood in INOCA. Purpose To compare clinical, invasive, and high sensitivity cardiac troponin I (hsTnI) parameters in women with INOCA at rest and in response to isometric handgrip exercise. Methods Women with suspected INOCA underwent cannulation of the coronary sinus (CS), handgrip exercise testing and serial CS plasma sampling before, after 3 minutes of isometric handgrip stress at 30% of maximal voluntary contraction, and after 5 minutes of recovery. hsTnI was measured using a commercial immunoassay (R-PLEX, Meso Scale Discovery, Rockville, MD) and compared using t-tests. Results A total of 54 women with complete invasive data were included with a mean age of 53 ± 10 years, mean body mass index 28 ± 7 kg/m2. 20 women (37% of the cohort) had detectable CS hsTnI from baseline. Among these women, median values were elevated in response to handgrip (Figure) (baseline median 33.75 (IQR 18.12-67.75) pg/mL vs peak handgrip median 56.23 (IQR 32.84-97.83) pg/mL, signed rank p=0.0007, baseline vs recovery median 52.35 (IQR 32.59-106.27) pg/mL, signed rank p=0.0002). Conclusion Among women with INOCA, handgrip stress leads to an increase in hsTnI in more than a third, demonstrating objective evidence of myocardial injury. More work is needed to better understand contribution of coronary microvascular dysfunction to HFpEF progression.

BACKGROUND The identification of circulating biomarkers specific for sudden cardiac arrest (SCA) could enhance risk prediction. Of particular interest are biomarkers specific to SCA, independent of coronary artery disease (CAD).OBJECTIVE The purpose of this study was to identify biomarkers of SCA obtained close to the SCA event.METHODS Twenty cases (survivors of SCA) and 40 age-and sex -matched controls were compared, with a replication analysis of 29 cases matched to 57 controls. A secondary analysis compared 20 SCA cases to 20 controls with CAD. Blood samples were obtained from SCA survivors at a median of 11 months after the SCA event. Proteins were analyzed on a mass spectrometer using data -independent acquisition; a subset of cytokines were analyzed using immunoassays; and 1153 lipids (13 classes) were analyzed. A false discovery rate P value of <.05 identified associated proteins.RESULTS Patients had a mean age of 58 years (range 25-87 years), and 70% were male. A total of 26 protein biomarkers associated with SCA when cases were compared with controls, of which 20 differentiated SCA from CAD. The replication analysis identified 8 of 26 biomarkers, of which 6 were not overlapping with CAD. The top identified biological processes involved the extracellular matrix, coagulation cascades, and platelet activation. Lipids in the lyso-phosphatidylcholine class were implicated in SCA through the CAD pathwayCONCLUSION We identified a panel of novel blood biomarkers spe-cifically associated with SCA, including several that may be involved outside the CAD pathway. These biomarkers could have mechanistic significance and the potential to enhance clinical prediction of SCA.

Sex-based differences are crucial to consider in the formulation of a personalized treatment plan. We evaluated sex-based differences in adherence and remotely monitored biometric, psychometric, and biomarker data among patients with stable ischemic heart disease (IHD). The Prediction, Risk, and Evaluation of Major Adverse Cardiac Events (PRE–MACE) study evaluated patients with stable IHD over a 12-week period. We collected biometric and sleep data using remote patient monitoring via FitBit and psychometric data from Patient-Reported Outcomes Measurement Information System (PROMIS), Kansas City Cardiomyopathy (KCC) and Seattle Angina Questionnaire-7 (SAQ-7) questionnaires. Serum biomarker levels were collected at the baseline visit. We explored sex-based differences in demographics, adherence to study protocols, biometric data, sleep, psychometric data, and biomarker levels. There were 198 patients enrolled, with mean age 65.5 ± 11 years (± Standard deviation, SD), and 60% were females. Females were less adherent to weekly collection of PROMIS, KCC and SAQ-7 physical limitations questionnaires (all p < 0.05), compared to males. There was no difference in biometric physical activity. There was a statistically significant (p < 0.05) difference in sleep duration between sexes, with females sleeping 6 min longer. However, females reported higher PROMIS sleep disturbance scores (p < 0.001) and poorer psychometric scores overall (p < 0.05). A higher proportion of males had clinically significant elevations of median N-terminal pro-brain natriuretic peptide (p = 0.005) and high-sensitivity cardiac troponin levels (p < 0.001) compared to females. Among females and males with stable IHD, there are sex-based differences in remote monitoring behavior and data. Females are less adherent to psychometric data collection and report poorer psychometric and sleep quality scores than males. Elevated levels of biomarkers for MACE are more common in males. These findings may improve sex-specific understanding of IHD using remote patient monitoring.

Background: Neurofilament light chain protein (NfL) and tau are plasma biomarkers of neuronal injury which can be elevated in patients with neurodegenerative diseases. N-terminal pro-brain natriuretic peptide (NT-proBNP) is an established marker of volume status in patients with heart failure (HF) and plasma cBIN1 score (CS) is an emerging biomarker of cardiac muscle health. It is not known if, in HF patients, there is a correlation between cardiac markers and brain injury markers.Methods: We studied ambulatory HF patients with either preserved and reduced ejection fraction (N = 50 with 25 HFrEF and 25 HFpEF) and age and sex matched healthy controls (N = 50). Plasma NT-proBNP and CS were determined using commercial kits. A bead-based ELISA assay was used to quantify femtomolar concentrations of plasma neuronal markers NfL and total tau.Results: Plasma levels of NT-proBNP and CS in heart failure patients were significantly higher than those from healthy controls. In both patients with HFrEF and HFpEF, we found independent and direct correlations between the volume status marker NT-proBNP, but not the cardiomyocyte origin muscle health marker CS, with NfL (r = 0.461, p = 0.0007) and tau (r = 0.333, p = 0.0183).Conclusion: In patients with HF with or without preserved ejection fraction, plasma levels of NfL and tau correlate with volume status rather than muscle health, indicating volume overload-associated neuronal injury.