Citations

ABSTRACT The concentration of cells is a key component of modern blood tests. Given the biomarker potential of extracellular vesicles (EVs) in blood, we aimed to establish reference ranges for blood cell‐derived EVs using flow cytometry. To address the orders‐of‐magnitude variability in reported EV concentrations between different flow cytometers (FCMs), we first validated a calibration methodology to enable reproducible EV concentration measurements. The methodology was evaluated in an interlaboratory comparison study and shows that calibration reduces the median absolute deviation of EV concentrations measured on 25 different FCMs from 67 % to 25 %–31 %. The calibration methodology was then used to determine reference ranges of erythrocyte‐, leukocyte‐, and platelet‐derived EVs in human blood plasma in a cohort of healthy individuals ( n = 224). This study demonstrates that calibration enables comparable concentration measurements of blood cell‐derived EVs, thereby bringing EVs one step closer to clinical applications.

Abstract Background Standardizing beam modeling in the treatment planning system is challenging due to machine‐specific configuration variations. Because of the proton therapy system (PTS) complexity and continuous development, there is no vendor's representative (“golden”) beam data like in LINACs at this stage. Purpose The primary goal of this study is to create a PTS‐specific repository of source model parameters and beam commissioning data for scanning proton therapy treatment planning systems and establish a set of reference values with associated bands of variations for this data. Methods We conducted a survey of 31 PTSs at 27 proton therapy centers to gather beam commissioning source model parameters used in their treatment planning system, ensuring a diverse selection of PTSs from major vendors: Hitachi, IBA, Varian, and Mevion. For each proton therapy center, we collected (i) beam meterset calibration in protons per MU, (ii) in‐air spot size at isocenter in terms of standard deviation in x‐ (crossline, σ x ) and y‐ (inline, σ y ) directions, (iii) in‐air angular spread at isocenter in x‐direction (θ x ) and y‐direction (θ y ) and (iv) distal falloff. For each PTS, we plotted each parameter as a function of nominal energy and performed polynomial regression analysis with optimal model selection based on Akaike Information Criterion. We calculated intraclass correlation coefficients (ICC) to quantify inter‐PTS variability and generated uncertainty bands representing standard deviations across PTSs for each parameter. Additionally, we computed percentage deviations of each individual PTS from the overall multi‐vendor mean to identify systematic vendor‐specific patterns and outliers across the 31 total PTSs analyzed. Results Multi‐vendor beam parameter analysis across 31 PTSs revealed systematic vendor‐specific patterns in inter‐PTS consistency and energy dependencies. Beam meterset calibration demonstrated excellent inter‐PTS consistency across most vendors (ICC: Varian ProBeam ≈ 0, IBA Proteus ONE = 0.006, Mevion S250i with HYPERSCAN = 0.015), with IBA Proteus PLUS systems showing moderate variation (ICC = 0.156 for the dedicated nozzle, ICC = 0.248, for the universal nozzle). Spot size and angular spread variability were highly vendor‐dependent, ranging from excellent consistency in IBA Proteus ONE to substantial variation in IBA Proteus PLUS with the universal nozzle (angular spread ICC = 0.566). Distal falloff maintained excellent consistency across all vendors (ICC < 0.023), indicating reliable energy spread characteristics. Uncertainty band analysis revealed characteristic energy‐dependent patterns, with most systems showing larger uncertainties at lower energies for spot size and angular spread, while IBA Proteus PLUS with the universal nozzle exhibited the largest uncertainty bands overall. Percentage deviation analysis demonstrated vendor‐specific clustering patterns, with some systems showing systematic positive or negative deviations from the multi‐vendor mean. Conclusions The reference data provided in this work will help to cross‐check the beam model during treatment planning system commissioning. Furthermore, this information is useful for Monte Carlo applications and research, where beam characteristics are required to set up phase space parameters, thereby avoiding the need to model the entire PTS. Finally, the results of this study will have indispensable educational value by providing valuable insights into the characteristics and capabilities of different PTSs.

Abstract Background: Sickle cell disease (SCD) is marked by wide variability in clinical phenotypes and severity due to environmental, clinical, and genetic factors. Variants in iron-regulatory genes are well described modifiers of clinical presentation in different diseases, but their role in modulating SCD phenotype has been sparsely studied in African populations. In this cross-sectional study, we investigated the role of single nucleotide polymorphisms (SNPs) in iron-regulatory genes in SCD severity and lifetime transfusion(Tx) requirement. Methods: The study was approved by the institutional review board of Lagos University Teaching Hospital, Lagos, Nigeria. Clinical data were abstracted from medical records and patient interviews using a structured questionnaire. Participants were recruited in steady state and were stratified according to the severity score previously described by Shah et al. (Clinicoecon Outcomes Res. 2020;12:625). Biochemical analyses included serum transferrin and serum iron; transferrin saturation (TS) was calculated. Genotyping was performed using the Axiom Precision Medicine Research Array (PMRA; Thermo Fisher Scientific). Seventy-one single nucleotide polymorphisms (SNPs) in genes implicated in iron metabolism were analyzed, including SLC40A1 (ferroportin), HFE (homeostatic iron regulator), HJV (hemojuvelin), HAMP (hepcidin), and TFR2 (transferrin receptor 2). SNPs whose variants were not represented in this cohort, including HFE C282Y and H63D, were excluded. Ensembl and NCBI databases were used to describe the wild-type (WT)/variant alleles and gene consequences. Univariate and multivariate logistic regression were used to analyze binary outcomes, and age-adjusted linear regression for Tx burden. Odds ratios (OR) and regression coefficients (β) were estimated using the WT as the reference. Multiple-testing correction was performed as necessary. Statistical analyses were conducted in R version 4.4.1, with p&lt;0.05 considered significant. Results: We included 60 genotyped, confirmed HbSS patients; median age was 22 years (range: 18–43), 22 (37.3%) were female, 42 (70.0%) were classified as mild severity (Class I), 5 (8.0%) as Class II, and 13 (22.0%) as severe (Class III). Twenty-seven (45.0%) had never received a blood Tx, while 33 (55.0%) had received Tx, median of 2units (range: 1-10). On univariate analysis (UVA), five SNPs (rs10218795, rs10188230, rs114250626, rs4287798, and rs634349) were significantly associated with severe phenotype; three of these remained significant on multivariable analysis (MVA). Two were associated with higher odds of severe phenotype: rs10177654 (OR = 28.9, 95% CI: 3.0–100.0, p = 0.03) and rs10218795 (OR = 15.0, 95% CI: 2.4–327.0, p&lt;0.01), while rs10188230 was associated with lower odds (OR = 0.03, 95% CI: 0.008–0.28, p&lt;0.01). Results remained consistent after adjusting for age. For lifetime transfusion burden, both UVA and MVA identified two significant SNPs: rs4667289, associated with higher transfusion burden (β = 2.6, 95% CI: 0.04–5.2, p = 0.047) and rs11568344, associated with lower transfusion burden (β = –1.8, 95% CI: –3.5 to –0.36, p = 0.02). Genotype distributions for the five significant SNPs were as follows: rs10177654 (SLC40A1, transcription factor binding site), TT(WT) 12 (20.3%), TC 30 (50.8%), CC 17 (28.8%); rs10188230 (SLC40A1, intron variant), TT (WT) 32 (54.2%), TC 22 (37.3%), CC 5 (8.5%); rs10218795 (HJV, intron variant), CC (WT) 22 (37.3%), TC 29 (49.2%), TT 8 (13.6%); rs4667289 (SLC40A1 proximal intergenic), GG (WT) 46 (78.0%), AG 10 (16.9%), AA 3 (5.1%); rs11568344 (SLC40A1 splice region variant), GG (WT) 47 (79.7%), AG 9 (15.3%), AA 3 (5.1%). Compared with the homozygous WT, patients with rs10188230 had a lower median TS (21.65% vs. 43.3%, p = 0.04), while those with rs4667289 had a higher median TS (83% vs. 31%, p&lt;0.01). When adjusted for age and lifetime Tx, rs4667289 remained significant (β = 47.8, 95% CI 3.6-82.8, p = 0.03). No other SNPs showed association with TS. Conclusion: We present novel genetic data on iron-regulatory variants in African patients with sickle cell disease, identifying SNPs in SLC40A1 and HJV associated with disease severity. Most of these are yet to be fully described in the literature, and their intronic locations suggest possible regulatory roles. We hope to further validate these findings in larger cohorts and through functional studies to clarify their impact on iron metabolism and clinical significance.

Abstract Introduction Defining the epidemiology of myelodysplastic syndromes/neoplasms (MDS) and precursor conditions, such as clonal cytopenia of undetermined significance (CCUS), is challenging due to inconsistent reporting, complex diagnostics, and evolving criteria. The National MDS Natural History Study (NHS) overcomes these challenges through central pathology review, prospective follow-up, and a nationally representative cohort enrolled at the time of suspected MDS, enabling robust analysis across the myeloid disease spectrum. We analyzed clinical, genetic, and pathologic features in NHS participants by race, ethnicity, and sex to characterize disease variation across populations. Methods The NHS (NCT02775383) enrolled individuals undergoing evaluation for suspected MDS from June 2016–July 2024 at 102 US sites. Participants underwent bone marrow assessment with centralized, adjudicated histopathology review. Those meeting WHO 2016 criteria for MDS, MDS/myeloproliferative neoplasm (MPN), CCUS, idiopathic cytopenia/dysplasia of undetermined significance (ICUS/IDUS), or oligoblastic AML were followed longitudinally. Demographics, comorbidities, exposures, and clinical data were collected at baseline and every 6 months. Deep DNA sequencing was performed on baseline marrow, with pathogenic variants manually curated (53 genes). Statistical analyses assessed associations using chi-squared, Fisher's exact, Kruskal-Wallis, logistic regression, and Cox models. A p-value &lt;0.05 was considered significant. Results Among 2,021 participants, 1,174 (58%) were diagnosed with MDS or precursor conditions. Median age was 74 years (yrs) and 66% were male. Most identified as Non-Hispanic White (NHW, 92%), with 4% Black and 4% Hispanic. The most common diagnoses were MDS (42%) and CCUS (37%). Pathogenic somatic mutations were identified in 84% (774/918) of MDS/CCUS, with TET2 (26% of 918), DNMT3A (21%), and ASXL1 (16%) most frequent. Median follow-up was 1.8yrs and consistent across race, ethnicity, and sex (p≥0.6). Black, compared to NHW, participants were younger (69 vs 74 yrs, p=0.006) and trended toward more females (47% vs 34%, p=0.09) and more MDS diagnoses (51% vs 41%, p=0.07). Black participants showed more advanced disease (e.g., lower hemoglobin, higher peripheral blood blasts, higher variant allele frequencies (VAFs) of pathogenic mutations), yet received less MDS-directed treatment (14% vs 41%, p=0.01). Black, compared to NHW, participants had more mutations in RUNX1, TP53, BCOR, and DNMT3A, but fewer in TET2 and ASXL1. Hispanic, compared to Non-Hispanic, participants had fewer known pathogenic mutations, leading to more ICUS (19% vs 5%, p=0.02). Females, compared to males, were younger at diagnosis (72 vs 75yrs, p&lt;0.001), had more ICUS/IDUS (20% vs 10%, p&lt;0.001), fewer pathogenic mutations, especially in splicing/chromatin modifier genes (U2AF1, SRSF2, ASXL1, ZRSR2), more DNMT3A mutations, and lower VAFs (0.27 vs 0.33, p&lt;0.001). Median overall survival (OS) was 6.4yrs, and shorter in MDS (4.2yrs) than CCUS (not reached). Worse OS was associated with age (adjusted hazard ratio (aHR) 1.06), MDS (vs CCUS; aHR 1.89), higher-risk disease by IPSS-R/CCRS (aHR 2.15), and TP53 mutations (aHR 2.17) (all p&lt;0.001). A trend toward improved OS in Black participants was attenuated after adjustment (aHR 0.79, p=0.6). Progression (e.g., worsening of disease, increase in transfusion dependency, death) occurred in 53% of participants. Worse progression-free survival (PFS) was associated with MDS diagnosis (aHR 2.59), higher-risk disease by IPSS-R/CCRS (aHR 2.17), and TP53 mutations (aHR 1.86) (all p&lt;0.001). Despite more advanced disease and less MDS therapy, Black participants trended toward improved PFS (aHR 0.62, p=0.14), while age was borderline significant (aHR 1.01, p=0.05). Conclusions For the first time, we show that among individuals evaluated for suspected MDS at sites across the US, 58% had MDS or precursor conditions. Differences across demographics underscore the heterogeneity of MDS. Black participants presented with more advanced MDS, received less treatment, but trended toward improved outcomes, particularly PFS, even after adjustment, suggesting biological rather than access-to-care differences driving disparities. These findings highlight the complex interplay of sex, race, and genetics in shaping MDS outcomes and reinforce the need for diverse, large-scale studies to improve risk stratification and personalized care.

Abstract Recent updates to the monocyte count thresholds for diagnosing chronic myelomonocytic leukemia (CMML) have recognized oligomonocytic CMML (OM-CMML) as an early stage within the CMML spectrum. However, the clinical validity of these revised criteria remains uncertain without considering biological factors and might misclassify myelodysplastic syndromes (MDS) with mild monocytosis as CMML. To characterize the genomic landscape of OM-CMML, we evaluated OM-CMML (n=249), MDS (n=304) and myelodysplastic CMML (MD-CMML, n=358) patients (pts) treated at three academic institutions. Targeted next-generation sequencing was performed on bone marrow (BM) at initial diagnosis or first referral. OM-CMML was characterized by lower frequencies of biallelic TET2 (biTET2) and RAS pathway (RASp) gene mutations (BRAF, CBL, KRAS, NF1, NRAS and PTPN11) compared to MD-CMML (p&lt;0.001) but higher frequencies than MDS (p&lt;0.001). BM monocyte frequencies, assessed morphologically, were higher in OM-CMML than in MDS (p&lt;0.001) but lower than in MD-CMML (p&lt;0.001), indicating that OM-CMML is a heterogenous group including true CMML and distinct MDS subsets. Unsupervised hierarchical clustering based on genomic alterations across all cases (n=911) identified three distinct clusters: 1) TP53 alterations (predominantly multihit TP53) and complex karyotype (TP53-complex); 2) biTET2 or TET2-SRSF2 co-mutation (biTET2/SRSF2); 3) a heterogenous group lacking these features (not otherwise specifiable [NOS]). Among OM-CMML pts, 11%, 34% and 55% belonged to these clusters, respectively. Model-based unsupervised clustering further identified 9 unique clusters that could be consolidated into 6 groups: 1) TP53-complex; 2) biTET2/SRSF2; 3) SF3B1 (without biTET2 or SRSF2); 4) SRSF2 without TET2 and frequent IDH2 mutations (SRSF2-IDH2); 5) ASXL1 and U2AF1 mutations and copy number alterations (CNA-ASXL1/U2AF1); 6) no somatic mutations (No mutation). biTET2/SRSF2 group exhibited monocytic bias with higher AMC, PB and BM monocyte % even among OM-CMML cases. This bias was not attributed to higher RAS pathway mutation frequencies, as biTET2/SRSF2 cases had similar RASp mutation frequencies but lower median variant allele frequencies for RASp mutations compared to NOS cases (9% vs. 21%, p=0.029). PB monocyte partitioning using flow cytometry (FC) in a subset of OM-CMML pts (n=50) demonstrated higher frequency of classical monocytosis (&gt;94% CD14+/CD16- monocytes) in biTET2/SRSF2 vs other OM-CMML. To further determine if biTET2/SRSF2 genotype defines a distinct biological subgroup, we performed RNA-sequencing of BM CD34+ cells from healthy donors (n=15) and pts with OM-CMML (n=12), MD-CMML (n=14) and MDS (n=55). Unsupervised clustering based on gene expression profiles revealed that biTET2/SRSF2 clustered irrespective of their diagnostic group with greater dispersion being observed based on diagnosis. MDS and CMML with biTET2/SRSF2 had less differentially expressed genes compared to MDS and CMML with biTET2/SRSF2 relative to other MDS and CMML genotypes. Among 138 OM-CMML pts in whom progression to overt CMML was evaluable, 37 (27%) progressed to overt CMML of which 26 (70%) belonged to the biTET2/SRSF2 group. Competing risk analysis confirmed higher cumulative incidence and shorter time to CMML progression among biTET2/SRSF2 OM-CMML. Using ElasticNet regression we identified BM monocytosis and 14 genomic variables (including biTET2 and TET2-SRSF2) as predictors of overt CMML progression among OM-CMML. We developed a score-based model able to predict progression with high reliability (AUC 0.805, sensitivity 0.70, specificity 0.76). Model accuracy was confirmed by optimism-corrected bootstrap internal validation (AUC 0.668). Monocytic bias, BM classical monocytosis (&gt;94% CD16- monocytes) and higher overt CMML progression in biTET2/SRSF2 was confirmed in a validation cohort (28, 66 and 22 pts with OM-CMML, MDS and MD-CMML, respectively). BM monocytosis of biTET2/SRSF2 was confirmed in this cohort with morphologic and FC monocyte frequency quantification having high concordance (r=0.737, p&lt;0.001). Genomic subgroup analysis discriminated survival outcomes more reliably than diagnostic categories alone. Our findings suggest that the presence of biTET2 or TET2-SRSF2 co-mutations, combined with BM monocytosis, can more reliably identify true CMML cases within the OM-CMML spectrum. Integrating genomic determinants into the CMML diagnostic framework enhances diagnostic accuracy.

Abstract Cyclin D1, encoded by CCND1, is a cell cycle regulator, overexpressed in ~15% of multiple myeloma (MM) cases via CCND1::IGH super-enhancer juxtaposition through t(11;14). Cyclin D1 also plays a non-canonical role in transcriptional regulation, but in t(11;14) MM its function in gene regulation remains undefined. We investigated the global transcriptional and epigenomic consequences of CCND1overexpression in t(11;14) MM. To define a CCND1 signature, RNA-seq from two independent primary MM patient cohorts, CoMMpass and Mayo, was utilized to compare high CCND1 t(11;14) cases (≥300 transcripts-per-million [TPM], n=271) vs. low CCND1 hyperdiploid cases (&lt;30 TPM, n=233). Two CCND1 knockout (KO) clones in t(11;14) MM U266B1 were also generated by CRISPR/Cas9, introducing a frameshift insertion (A) after chr11:69641478 (hg38) in exon 1. ATAC-seq and ChIP-seq (H3K4me3, H3K4me1, and H3K27ac) were performed in duplicates, and RNA-seq in triplicates in U266B1 wild-type (WT) and KO. Libraries were sequenced on Illumina NextSeq 2000 (2x51 bp for ChIP/ATAC, 2x150 bp for RNA-seq). Reads were mapped to hg38 by BWA (ChIP/ATAC) or STAR (RNA-seq), peaks called by MACS2 (FDR&lt; 0.01), peak and gene raw counts estimated by featureCounts. Differential peaks (fold-change ≥1.5) and differentially expressed genes (fold-change ≥2) were identified by edgeR (FDR&lt;0.05), including peaks detected in ≥2 samples and genes with TPM ≥0.1 in ≥1 sample. Interactions between promoters and distal regulatory regions were identified using publicly available chromatin interaction data in blood cell types. Pathway analysis was performed using Enrichr. Co-immunoprecipitation was performed in t(11;14) KMS12BM cells. Differential analysis comparing CCND1-high t(11;14) and CCND1-low MM cases in the two patient cohorts identified 21 upregulated and 21 downregulated genes associated with CCND1 expression which were also captured in the wild-typevs. CCND1 KO U266 cells. Enriched pathways (p&lt;0.05) included Notch signaling, early/late estrogen response, epithelial-mesenchymal transition and reduced mitotic spindle and myogenesis. Dysregulated genes included those related to apoptosis, ubiquitin-proteosome, extracellular matrix, adhesion, and immune response, demonstrating a broader role for cyclin D1 in MM beyond cell cycle control. To explore the epigenomic basis of this transcriptional regulation, for each of the 42 differentially expressed genes we examined the changes of histone marks and chromatin accessibility in promoter and the interacting distal regulatory regions in the U266 KO model. Ten of the 21 genes upregulated in CCND1-high (downloaded in KO; e.g., argininosuccinate synthase 1 [ASS1], PMAIP1, MYEOV, CCR7, and DTX1) and 12 of the 21 genes downregulated in CCND1-high (upregulated in KO; e.g., UACA, RASAL2, PTPRZ1, PPT2, and IL23R) showed concordant changes in histone marks and/or chromatin accessibility, predominantly in distal regulatory regions, suggesting a chromatin-mediated mechanism of gene regulation by cyclin D1. The most prominent changes involved H3K27ac, a mark defining active enhancers. As H3K27ac is deposited by histone acetyltransferases CBP, we tested for the possible cyclin D1-CBP interaction. Co-IP confirmed this interaction, suggesting a role for this complex in chromatin remodeling and transcriptional control in t(11;14) MM. One gene notably upregulated in association with CCND1 is ASS1, which encodes a urea cycle enzyme responsible for endogenous arginine synthesis. Metabolomic studies demonstrated KO cells had elevated aspartate and citrulline and lowered arginine and ornithine compared to WT cells (p&lt;0.01) demonstrating impaired urea cycle function. Further, KO cells displayed significantly reduced ASS1 protein expression, cell growth and S-phase entry compared to WT cells in arginine-replete conditions, with both WT and KO cell types further inhibited by arginine depletion (p&lt;0.05). Together, a cyclin D1-associated gene signature was identified supporting its role in t(11;14) MM beyond the CDK4/6 mediated cell cycle control, including a role in metabolic plasticity and survival under arginine depleted conditions. These findings highlight cyclin D1 as a therapeutic vulnerability and open new avenues for personalized treatment strategies.

Abstract Introduction Venetoclax combined with hypomethylating agents (VEN/HMA) is an approved frontline induction therapy for older or unfit patients with acute myeloid leukemia (AML). However, data comparing its efficacy and safety to intensive chemotherapy (IC) in intermediate-risk AML—characterized by molecular and cytogenetic heterogeneity—remain limited. Methods This multicenter, real-world retrospective study analyzed newly diagnosed intermediate-risk AML patients who received either VEN/HMA or IC. We evaluated composite complete remission (CRc) rates, transfusion and infection rates, long-term outcomes including overall survival (OS) and progression-free survival (PFS), and performed subgroup analyses to identify mutation-specific predictors of treatment response. Multivariable Cox regression was used to identify independent prognostic factors. Results A total of 229 intermediate-risk AML patients were included. VEN/HMA achieved a comparable CRc rate to IC (75.3% vs. 63.4%) with lower transfusion needs and fewer infections. Patients harboring FLT3-ITD, DNMT3A, or TET2 mutations showed greater benefit from VEN/HMA, while KIT-mutated patients responded more favorably to IC. Among patients who did not undergo allo-HSCT, VEN/HMA significantly improved 3-year OS (P = 0.001) and PFS (P = 0.008). No significant OS or PFS difference was observed in the allo-HSCT subgroup. In MRD-negative patients without transplant, those treated with VEN/HMA had superior OS compared to IC. Multivariable analysis identified VEN/HMA (HR = 0.613, P = 0.038) and allo-HSCT (HR = 0.11, P = 0.001) as independent predictors of better survival. Conclusions VEN/HMA is a safe and effective induction strategy for intermediate-risk AML, particularly in patients with BCL-2 inhibitor–sensitive mutations (FLT3-ITD, DNMT3A, TET2). These findings support a genotype-guided treatment approach in AML, complementing current risk stratification frameworks and informing individualized induction therapy decisions.

BACKGROUND: Although obesity and insulin resistance (IR) are established risk factors for left heart dysfunction, their clinical impact in group 1 pulmonary hypertension (PH) remains unclear. We sought to determine the impact of excess adiposity versus IR on biventricular hemodynamic and functional reserve in group 1 PH. METHODS: Homeostasis model of insulin resistance and adiposity indices (body mass index [BMI], fat mass, waist circumference) were measured among group 1 patients with PH recruited to PVDOMICS (Redefining Pulmonary Hypertension Through Pulmonary Vascular Disease Phenomics). Functional capacity, and dynamic pulmonary capillary wedge pressure (PCWP) and right atrial pressure responses were compared stratified by obesity (BMI≥30 kg/m 2 ) and IR status (HOMA-IR≥2.6) using repeated-measure mixed models. RESULTS: Among patients with group 1 PH (n=418), 158 (38%) had BMI≥30 kg/m 2 (94 [60%] of whom had IR), and 260 (62%) had BMI<30 kg/m 2 (74 [28%] of whom had IR). Among those with waist circumference measurement (n=375), 287 (77%) had excess adiposity by elevated waist/height ratio, with 214 (57%) having elevated waist circumference. Patients with obesity had worse quality of life, exercise capacity and left heart remodeling, along with higher resting/dynamic PCWP, right atrial pressure and cardiac output ( P <0.0001 for all). Higher PCWP response with obesity persisted after adjusting for IR (IR-adjusted PCWP+2.5 mm Hg [95% CI, +1.4 to +3.6]; P <0.0001). All adiposity indices were consistently associated with PCWP response, but IR was not. Similar associations were observed between adiposity indices with higher right atrial pressure and cardiac output. Greater visceral adiposity as measured by body shape index (hazard ratio, 2.01 [95% CI, 1.16–3.47]; P =0.01) or weight-adjusted waist index (hazard ratio, 1.64 [95% CI, 1.10–2.46]; P =0.01) was associated with worse survival. CONCLUSIONS: Excess adiposity is common in group 1 PH, occurring in 4 out of 5 patients by the more sensitive waist/height ratio, in contrast to only 2 out of 5 patients having obesity by traditional BMI criteria. Excess adiposity is associated with higher biventricular filling pressures, cardiac output demand, worse functional status and reduced survival. These data support trials of adipose-reducing therapies in patients with group 1 PH and excess adiposity.