Plasma Cell-Free DNA Predicts Survival and Maps Specific Sources of Injury in Pulmonary Arterial Hypertension Article Swipe
Samuel B. Brusca
,
Jason M. Elinoff
,
Yvette Zou
,
Moon Kyoo Jang
,
Hyesik Kong
,
Cumhur Y. Demirkale
,
Junfeng Sun
,
Fayaz Seifuddin
,
Mehdi Pirooznia
,
Hannah A. Valantine
,
Carl Tanba
,
Abhishek Chaturvedi
,
Grace Graninger
,
Bonnie Harper
,
Li‐Yuan Chen
,
Justine Cole
,
Manreet Kanwar
,
Raymond L. Benza
,
Ioana R. Preston
,
Sean Agbor-Enoh
,
Michael A. Solomon
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1161/circulationaha.121.056719
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1161/circulationaha.121.056719
Background: Cell-free DNA (cfDNA) is a noninvasive marker of cellular injury. Its significance in pulmonary arterial hypertension (PAH) is unknown. Methods: Plasma cfDNA was measured in 2 PAH cohorts (A, n=48; B, n=161) and controls (n=48). Data were collected for REVEAL 2.0 (Registry to Evaluate Early and Long-Term PAH Disease Management) scores and outcome determinations. Patients were divided into the following REVEAL risk groups: low (≤6), medium (7–8), and high (≥9). Total cfDNA concentrations were compared among controls and PAH risk groups by 1-way analysis of variance. Log-rank tests compared survival between cfDNA tertiles and REVEAL risk groups. Areas under the receiver operating characteristic curve were estimated from logistic regression models. A sample subset from cohort B (n=96) and controls (n=16) underwent bisulfite sequencing followed by a deconvolution algorithm to map cell-specific cfDNA methylation patterns, with concentrations compared using t tests. Results: In cohort A, median (interquartile range) age was 62 years (47–71), with 75% female, and median (interquartile range) REVEAL 2.0 was 6 (4–9). In cohort B, median (interquartile range) age was 59 years (49–71), with 69% female, and median (interquartile range) REVEAL 2.0 was 7 (6–9). In both cohorts, cfDNA concentrations differed among patients with PAH of varying REVEAL risk and controls (analysis of variance P ≤0.002) and were greater in the high-risk compared with the low-risk category ( P ≤0.002). In cohort B, death or lung transplant occurred in 14 of 54, 23 of 53, and 35 of 54 patients in the lowest, middle, and highest cfDNA tertiles, respectively. cfDNA levels stratified as tertiles (log-rank: P =0.0001) and REVEAL risk groups (log-rank: P <0.0001) each predicted transplant-free survival. The addition of cfDNA to REVEAL improved discrimination (area under the receiver operating characteristic curve, 0.72–0.78; P =0.02). Compared with controls, methylation analysis in patients with PAH revealed increased cfDNA originating from erythrocyte progenitors, neutrophils, monocytes, adipocytes, natural killer cells, vascular endothelium, and cardiac myocytes (Bonferroni adjusted P <0.05). cfDNA concentrations derived from erythrocyte progenitor cells, cardiac myocytes, and vascular endothelium were greater in patients with PAH with high-risk versus low-risk REVEAL scores ( P ≤0.02). Conclusions: Circulating cfDNA is elevated in patients with PAH, correlates with disease severity, and predicts worse survival. Results from cfDNA methylation analyses in patients with PAH are consistent with prevailing paradigms of disease pathogenesis.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1161/circulationaha.121.056719
- https://www.ahajournals.org/doi/pdf/10.1161/CIRCULATIONAHA.121.056719
- OA Status
- bronze
- Cited By
- 27
- References
- 71
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4293102283
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- OpenAlex ID
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https://openalex.org/W4293102283Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1161/circulationaha.121.056719Digital Object Identifier
- Title
-
Plasma Cell-Free DNA Predicts Survival and Maps Specific Sources of Injury in Pulmonary Arterial HypertensionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-10-03Full publication date if available
- Authors
-
Samuel B. Brusca, Jason M. Elinoff, Yvette Zou, Moon Kyoo Jang, Hyesik Kong, Cumhur Y. Demirkale, Junfeng Sun, Fayaz Seifuddin, Mehdi Pirooznia, Hannah A. Valantine, Carl Tanba, Abhishek Chaturvedi, Grace Graninger, Bonnie Harper, Li‐Yuan Chen, Justine Cole, Manreet Kanwar, Raymond L. Benza, Ioana R. Preston, Sean Agbor-Enoh, Michael A. SolomonList of authors in order
- Landing page
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https://doi.org/10.1161/circulationaha.121.056719Publisher landing page
- PDF URL
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https://www.ahajournals.org/doi/pdf/10.1161/CIRCULATIONAHA.121.056719Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
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https://www.ahajournals.org/doi/pdf/10.1161/CIRCULATIONAHA.121.056719Direct OA link when available
- Concepts
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Interquartile range, Medicine, Cohort, Internal medicine, Quartile, Gastroenterology, Confidence intervalTop concepts (fields/topics) attached by OpenAlex
- Cited by
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27Total citation count in OpenAlex
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2025: 8, 2024: 6, 2023: 12, 2022: 1Per-year citation counts (last 5 years)
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71Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.subset | 113 |
| abstract_inverted_index.tests. | 140 |
| abstract_inverted_index.versus | 340 |
| abstract_inverted_index.(cfDNA) | 3 |
| abstract_inverted_index.(n=48). | 35 |
| abstract_inverted_index.(≤6), | 65 |
| abstract_inverted_index.(≥9). | 70 |
| abstract_inverted_index.=0.02). | 288 |
| abstract_inverted_index.Disease | 49 |
| abstract_inverted_index.Results | 364 |
| abstract_inverted_index.between | 91 |
| abstract_inverted_index.cardiac | 314, 327 |
| abstract_inverted_index.cohorts | 28 |
| abstract_inverted_index.derived | 322 |
| abstract_inverted_index.disease | 358, 379 |
| abstract_inverted_index.divided | 57 |
| abstract_inverted_index.female, | 155, 178 |
| abstract_inverted_index.greater | 211, 333 |
| abstract_inverted_index.groups. | 97 |
| abstract_inverted_index.groups: | 63 |
| abstract_inverted_index.highest | 248 |
| abstract_inverted_index.injury. | 10 |
| abstract_inverted_index.lowest, | 245 |
| abstract_inverted_index.middle, | 246 |
| abstract_inverted_index.models. | 110 |
| abstract_inverted_index.natural | 308 |
| abstract_inverted_index.outcome | 53 |
| abstract_inverted_index.varying | 199 |
| abstract_inverted_index.(4–9). | 164 |
| abstract_inverted_index.(6–9). | 187 |
| abstract_inverted_index.(7–8), | 67 |
| abstract_inverted_index.=0.0001) | 259 |
| abstract_inverted_index.Compared | 289 |
| abstract_inverted_index.Evaluate | 44 |
| abstract_inverted_index.Log-rank | 87 |
| abstract_inverted_index.Methods: | 20 |
| abstract_inverted_index.Patients | 55 |
| abstract_inverted_index.Results: | 141 |
| abstract_inverted_index.addition | 272 |
| abstract_inverted_index.adjusted | 317 |
| abstract_inverted_index.analyses | 368 |
| abstract_inverted_index.analysis | 84, 293 |
| abstract_inverted_index.arterial | 15 |
| abstract_inverted_index.category | 219 |
| abstract_inverted_index.cellular | 9 |
| abstract_inverted_index.cohorts, | 190 |
| abstract_inverted_index.compared | 75, 89, 137, 215 |
| abstract_inverted_index.controls | 34, 77, 119, 203 |
| abstract_inverted_index.differed | 193 |
| abstract_inverted_index.elevated | 351 |
| abstract_inverted_index.followed | 124 |
| abstract_inverted_index.improved | 277 |
| abstract_inverted_index.logistic | 108 |
| abstract_inverted_index.low-risk | 218, 341 |
| abstract_inverted_index.measured | 24 |
| abstract_inverted_index.myocytes | 315 |
| abstract_inverted_index.occurred | 230 |
| abstract_inverted_index.patients | 195, 242, 295, 335, 353, 370 |
| abstract_inverted_index.predicts | 361 |
| abstract_inverted_index.receiver | 101, 282 |
| abstract_inverted_index.revealed | 298 |
| abstract_inverted_index.survival | 90 |
| abstract_inverted_index.tertiles | 93, 256 |
| abstract_inverted_index.unknown. | 19 |
| abstract_inverted_index.variance | 206 |
| abstract_inverted_index.vascular | 311, 330 |
| abstract_inverted_index.(Registry | 42 |
| abstract_inverted_index.(analysis | 204 |
| abstract_inverted_index.Cell-free | 1 |
| abstract_inverted_index.Long-Term | 47 |
| abstract_inverted_index.algorithm | 128 |
| abstract_inverted_index.bisulfite | 122 |
| abstract_inverted_index.collected | 38 |
| abstract_inverted_index.controls, | 291 |
| abstract_inverted_index.estimated | 106 |
| abstract_inverted_index.following | 60 |
| abstract_inverted_index.high-risk | 214, 339 |
| abstract_inverted_index.increased | 299 |
| abstract_inverted_index.myocytes, | 328 |
| abstract_inverted_index.operating | 102, 283 |
| abstract_inverted_index.paradigms | 377 |
| abstract_inverted_index.patterns, | 134 |
| abstract_inverted_index.predicted | 268 |
| abstract_inverted_index.pulmonary | 14 |
| abstract_inverted_index.severity, | 359 |
| abstract_inverted_index.survival. | 270, 363 |
| abstract_inverted_index.tertiles, | 250 |
| abstract_inverted_index.underwent | 121 |
| abstract_inverted_index.variance. | 86 |
| abstract_inverted_index.≤0.002) | 208 |
| abstract_inverted_index.≤0.02). | 346 |
| abstract_inverted_index.<0.05). | 319 |
| abstract_inverted_index.(47–71), | 152 |
| abstract_inverted_index.(49–71), | 175 |
| abstract_inverted_index.(log-rank: | 257, 264 |
| abstract_inverted_index.consistent | 374 |
| abstract_inverted_index.correlates | 356 |
| abstract_inverted_index.monocytes, | 306 |
| abstract_inverted_index.prevailing | 376 |
| abstract_inverted_index.progenitor | 325 |
| abstract_inverted_index.regression | 109 |
| abstract_inverted_index.sequencing | 123 |
| abstract_inverted_index.stratified | 254 |
| abstract_inverted_index.transplant | 229 |
| abstract_inverted_index.≤0.002). | 222 |
| abstract_inverted_index.<0.0001) | 266 |
| abstract_inverted_index.(Bonferroni | 316 |
| abstract_inverted_index.Background: | 0 |
| abstract_inverted_index.Circulating | 348 |
| abstract_inverted_index.Management) | 50 |
| abstract_inverted_index.adipocytes, | 307 |
| abstract_inverted_index.endothelium | 331 |
| abstract_inverted_index.erythrocyte | 303, 324 |
| abstract_inverted_index.methylation | 133, 292, 367 |
| abstract_inverted_index.noninvasive | 6 |
| abstract_inverted_index.originating | 301 |
| abstract_inverted_index.0.72–0.78; | 286 |
| abstract_inverted_index.Conclusions: | 347 |
| abstract_inverted_index.endothelium, | 312 |
| abstract_inverted_index.hypertension | 16 |
| abstract_inverted_index.neutrophils, | 305 |
| abstract_inverted_index.progenitors, | 304 |
| abstract_inverted_index.significance | 12 |
| abstract_inverted_index.cell-specific | 131 |
| abstract_inverted_index.deconvolution | 127 |
| abstract_inverted_index.pathogenesis. | 380 |
| abstract_inverted_index.respectively. | 251 |
| abstract_inverted_index.(interquartile | 146, 158, 169, 181 |
| abstract_inverted_index.characteristic | 103, 284 |
| abstract_inverted_index.concentrations | 73, 136, 192, 321 |
| abstract_inverted_index.discrimination | 278 |
| abstract_inverted_index.determinations. | 54 |
| abstract_inverted_index.transplant-free | 269 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 21 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.800000011920929 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.95549246 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |