Yu, Bing

BACKGROUND: It is unknown whether cardiac resynchronization therapy (CRT) improves systemic metabolomic profile by enhancing left ventricular function. The observational cohort study aimed to investigate the effect of CRT on left ventricular ejection fraction (LVEF) and circulating plasma metabolites in patients who had heart failure with reduced LVEF. METHODS: We prospectively screened patients with ischemic cardiomyopathy and nonischemic cardiomyopathy who received CRT with a defibrillator for LVEF ≤35% according to current guidelines. Clinical assessment included echocardiography and device interrogation. Blood samples for metabolomic analysis were collected before CRT and at 6-month follow-up. Plasma was subjected to gas chromatography-mass spectrometry and 1 H nuclear magnetic resonance-based metabolomic analysis. RESULTS: Totally 92 patients were enrolled, with a mean age of 67.3±11.3 years (37.0% female). LVEF was significantly improved from 28.9±7.6% at baseline to 36.0±11.3% at 6 months ( P <0.001) and to 40.1±12.6% at 12 months ( P <0.001). After CRT, 42 metabolite features were significantly decreased compared with the baseline. The ketone bodies, including 3-hydroxybutyrate ( P <0.001) and acetone ( P =0.01), were reduced. A branched-chain amino acid, isoleucine, was also decreased after CRT ( P =0.01). These metabolomic changes were mainly observed in the nonischemic cardiomyopathy group, while the metabolomic profile in the ischemic cardiomyopathy group was characterized by enhanced amino acid oxidation and elevated levels of lactate and pyruvate. The improvement in LVEF positively correlated with the ratio of changes in ketone bodies and isoleucine. CONCLUSIONS: CRT may modulate the systemic plasma metabolomic profile, which correlated with improvement in left ventricular function in patients with severe heart failure with reduced ejection fraction.

Abstract Background:Chronic obstructive pulmonary disease (COPD) is a major global health burden, with genome-wide association studies explaining only a fraction of its heritability. Recent advancements, including large-scale, multi-ancestry whole-genome sequencing and a focus on severe, early-onset cases, offer promising avenues to identify additional COPD-related variants. Furthermore, recent studies show that adjusting for polygenic risk scores (PRS) enhances statistical power to detect rare variants, advancing efforts to understand COPD's genetic basis. Methods:We performed a whole genome sequencing association study of severe, early-onset COPD (FEV1 &lt; 50%, age ≤ 55), FEV1 and FEV1/FVC in eight population-based studies (ARIC, CARDIA, CFS, CHS, FHS, HCHS/SOL, JHS, MESA) and seven COPD-enriched studies (COPDGene, ECLIPSE, Boston Early-Onset COPD Study, LTRC, TCGS (Poland), ICGN, SPIROMICS). We performed single-variant analyses using regenie software, applying a genome-wide significance threshold of P &lt; 5.0 x 10-8. For rare variant set (MAF &lt;1%) analysis, we annotated variants with loss of function or deleterious missense using WGS Annotator and prediction tools LOFTEE, SIFT, and PolyPhen2, then analyzed these variants with SKATO-ACAT method in regenie, adjusting for covariates including sex, sequencing center, and principal components of ancestry. We additionally evaluated adjusting the analyses for PRSs for lung function traits. Results: We analyzed 53,028 participants including 34,751 European, 12,508 African, 1,088 Latino American, and 674 East Asian ancestry. Across cohorts, we analyzed 5,063 severe (FEV1 &lt; 50%) COPD cases, among whom 1,103 were early-onset (age ≤ 55). Excluding variants within 1 Mbp of known variants, single-variant analysis identified 68 novel associations (MAC ≥ 30), with 8 common associations (MAF ≥ 1%) in 6 genomic regions. Our most significant novel association for severe early-onset COPD was rs74297390 (intergenic to POM121L12, MAF = 9.6%, Beta = 0.41, P = 3.5 x 10-8). For FEV1 and FEV1/FVC ratio, variants near DKK2 and AKR1E2 were significantly associated and were replicated in an independent dataset (Shrine et al., 2019). DKK2 is an antagonist in the Wnt pathway. In a preliminary variant set analysis, CHRM3-AS1 was associated with severe early-onset COPD, GPAT with FEV1, and COL8A1I and HMCN1 with FEV1/FVC. With PRS adjustment, ST6GALNAC5 was associated with FEV1/FVC. Conclusions: In a whole genome sequencing study of lung function and severe early-onset COPD, we identified new loci for COPD-related phenotypes, including two novel loci that replicated in an independent dataset. Ongoing work involves variant set-based analyses with additional covariate adjustments, as well as PRS adjustments for binary traits.

Background The immune response to infections may become dysregulated and promote myocardial damage contributing to heart failure (HF). We examined the relationship between infection‐related hospitalization (IRH) and HF, HF with preserved ejection fraction, and HF with reduced ejection fraction. Methods and Results We studied 14 468 adults aged 45 to 64 years in the ARIC (Atherosclerosis Risk in Communities) Study who were HF free at visit 1 (1987–1989). IRH was identified using select International Classification of Diseases ( ICD ) codes in hospital discharge records and was treated as a time‐varying exposure. HF incidence was defined as the first occurrence of either a hospitalization that included an ICD, Ninth Revision ( ICD‐9 ) discharge code of 428 (428.0–428.9) among the primary or secondary diagnoses or a death certificate with an ICD‐9 code of 428 or an ICD, Tenth Revision ( ICD‐10 ) code of I50 among any of the listed diagnoses or underlying causes of death. We used multivariable‐adjusted Cox proportional hazards models to assess the association between IRH and incident HF, HF with reduced ejection fraction, and HF with preserved ejection fraction. Median follow‐up time was 27 years, 55% were women, 26% were Black, mean age at baseline was 54±6 years, 46% had an IRH, and 3565 had incident HF. Hazard ratio (HR) for incident HF events among participants who had an IRH compared with those who did not was 2.35 (95% CI, 2.19–2.52). This relationship was consistent across different types of infections. Additionally, IRH was associated with both HF with reduced ejection fraction and HF with preserved ejection fraction: 1.77 (95% CI, 1.35–2.32) and 2.97 (95% CI, 2.36–3.75), respectively. Conclusions IRH was associated with incident HF, HF with reduced ejection fraction, and HF with preserved ejection fraction. IRH might represent a modifiable risk factor for HF pathophysiology.

ImportanceClonal hematopoiesis of indeterminate potential (CHIP) may contribute to the risk of atrial fibrillation (AF) through its association with inflammation and cardiac remodeling.ObjectiveTo determine whether CHIP was associated with AF, inflammatory and cardiac biomarkers, and cardiac structural changes.Design, Setting, and ParticipantsThis was a population-based, prospective cohort study in participants of the Atherosclerosis Risk in Communities (ARIC) study and UK Biobank (UKB) cohort. Samples were collected and echocardiography was performed from 2011 to 2013 in the ARIC cohort, and samples were collected from 2006 to 2010 in the UKB cohort. Included in this study were adults without hematologic malignancies, mitral valve stenosis, or previous mitral valve procedure from both the ARIC and UKB cohorts; additionally, participants without hypertrophic cardiomyopathy and congenital heart disease from the UKB cohort were also included. Data analysis was completed in 2023.ExposuresCHIP (variant allele frequency [VAF] ≥2%), common gene-specific CHIP subtypes (DNMT3A, TET2, ASXL1), large CHIP (VAF ≥10%), inflammatory and cardiac biomarkers (high-sensitivity C-reactive protein, interleukin 6 [IL-6], IL-18, high-sensitivity troponin T [hs-TnT] and hs-TnI, N-terminal pro–B-type natriuretic peptide), and echocardiographic indices.Main Outcome MeasureIncident AF.ResultsA total of 199 982 adults were included in this study. In ARIC participants (4131 [2.1%]; mean [SD] age, 76 [5] years; 2449 female [59%]; 1682 male [41%]; 935 Black [23%] and 3196 White [77%]), 1019 had any CHIP (24.7%), and 478 had large CHIP (11.6%). In UKB participants (195 851 [97.9%]; mean [SD] age, 56 [8] years; 108 370 female [55%]; 87 481 male [45%]; 3154 Black [2%], 183 747 White [94%], and 7971 other race [4%]), 11 328 had any CHIP (5.8%), and 5189 had large CHIP (2.6%). ARIC participants were followed up for a median (IQR) period of 7.0 (5.3-7.7) years, and UKB participants were followed up for a median (IQR) period of 12.2 (11.3-13.0) years. Meta-analyzed hazard ratios for AF were 1.12 (95% CI, 1.01-1.25; P = .04) for participants with vs without large CHIP, 1.29 (95% CI, 1.05-1.59; P = .02) for those with vs without large TET2 CHIP (seen in 1340 of 197 209 [0.67%]), and 1.45 (95% CI, 1.02-2.07; P = .04) for those with vs without large ASXL1 CHIP (seen in 314 of 197 209 [0.16%]). Large TET2 CHIP was associated with higher IL-6 levels. Additionally, large ASXL1 was associated with higher hs-TnT level and increased left ventricular mass index.Conclusions and RelevanceLarge TET2 and ASXL1, but not DNMT3A, CHIP was associated with higher IL-6 level, indices of cardiac remodeling, and increased risk for AF. Future research is needed to elaborate on the mechanisms driving the associations and to investigate potential interventions to reduce the risk.

Introduction: Aging and inflammation are associated with risk of atrial fibrillation (AF), to which clonal hematopoiesis of indeterminate potential (CHIP) may contribute. We investigated whether CHIP was associated with AF, inflammatory and cardiac biomarkers and cardiac structural changes. Methods: We ascertained CHIP (variant allele frequency, VAF ≥2%) in the Atherosclerosis Risk in Community Study (ARIC visit-5, n = 4,131) and the UK Biobank (UKBB, n = 195,851) participants. Using multivariable Cox regression models, we studied the association of CHIP and the top three implicated genes (i.e., DNMT3A , TET2 , ASXL1 ) with incident AF and conducted a meta-analysis on both cohorts. We also ascertained high-sensitivity C-reactive protein (hs-CRP), interleukin 6 (IL6), IL18, high-sensitivity troponin T and I (hs-TnT and hs-TnI), NT-proBNP, and echocardiography indices in ARIC. We first standardized the natural log of all markers (st-ln) and used the adjusted quantile regression to compare the median in those with and without CHIP. Results: In ARIC, the mean ± SD age was 75.8 ± 5.2 years, 41% were men, 23% were Black, 25% had CHIP, and 11.6% had large CHIP (VAF ≥10%). These measures in UKBB were 56.4 ± 8.1 years, 45%, 2%, 5.8%, and 2.6%, respectively. In the meta-analysis, compared to those without CHIP, the hazard ratios (95% confidence interval) for AF were 1.12 (1.01 - 1.25, P =0.035), 1.31 (1.07 - 1.60, P =0.009), and 1.48 (1.05 - 2.08, P =0.026) for Large-CHIP, Large- TET2, and Large- ASXL1 , respectively. hs-CRP and IL18 levels were similar in those with and without CHIP as well as gene-specific subgroups. Large- TET2 and ASXL1 were associated with higher IL6, which was separately associated with AF. Additionally, Large- ASXL1 was associated with increased left ventricle mass index and NT-proBNP (coefficients in Figure 1 ). Conclusion: Large TET2 and ASXL1 but not DNMT3A CHIP is associated with higher IL6 levels, indices of cardiac remodeling, and an increased risk of AF.

Abstract Privacy protection is a core principle of genomic but not proteomic research. We identified independent single nucleotide polymorphism (SNP) quantitative trait loci (pQTL) from COPDGene and Jackson Heart Study (JHS), calculated continuous protein level genotype probabilities, and then applied a naïve Bayesian approach to match proteomes to genomes for 2,812 independent subjects from COPDGene, JHS, SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) and Multi-Ethnic Study of Atherosclerosis (MESA). We were able to correctly match 90%-95% of proteomes to their correct genome and for 95%-99% we could match the proteome to the 1% most likely genome. The accuracy of matching in subjects with African ancestry was lower (~ 60%) unless training included diverse subjects. With larger profiling (SomaScan 5K) in the Atherosclerosis Risk Communities (ARIC) correct identification was > 99% even in mixed ancestry populations. When serial proteomes are available, the matching algorithm can be used to identify and correct mislabeled samples. This work also demonstrates the importance of including diverse populations in omics research and that large proteomic datasets (> 1,000 proteins) can be accurately linked to a specific genome through pQTL knowledge and should not be considered unidentifiable.

Background: Previous studies suggest poor pulmonary function is associated with increased burden of cerebral white matter hyperintensities and brain atrophy among elderly individuals, but the results are inconsistent. Objective: To study the cross-sectional associations of pulmonary function with structural brain variables. Methods: Data from six large community-based samples (N = 11,091) were analyzed. Spirometric measurements were standardized with respect to age, sex, height, and ethnicity using reference equations of the Global Lung Function Initiative. Associations of forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), and their ratio FEV1/FVC with brain volume, gray matter volume, hippocampal volume, and volume of white matter hyperintensities were investigated using multivariable linear regressions for each study separately and then combined using random-effect meta-analyses. Results: FEV1 and FVC were positively associated with brain volume, gray matter volume, and hippocampal volume, and negatively associated with white matter hyperintensities volume after multiple testing correction, with little heterogeneity present between the studies. For instance, an increase of FVC by one unit was associated with 3.5 ml higher brain volume (95% CI: [2.2, 4.9]). In contrast, results for FEV1/FVC were more heterogeneous across studies, with significant positive associations with brain volume, gray matter volume, and hippocampal volume, but not white matter hyperintensities volume. Associations of brain variables with both FEV1 and FVC were consistently stronger than with FEV1/FVC, specifically with brain volume and white matter hyperintensities volume. Conclusion: In cross-sectional analyses, worse pulmonary function is associated with smaller brain volumes and higher white matter hyperintensities burden.