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Maximal oxygen uptake (VO2max) is a direct measure of human cardiorespiratory fitness and is associated with health. However, the molecular determinants of interindividual differences in baseline (intrinsic) VO2max, and of increases of VO2max in response to exercise training (ΔVO2max), are largely unknown. Here, we measure ~5,000 plasma proteins using an affinity-based platform in over 650 sedentary adults before and after a 20-week endurance-exercise intervention and identify 147 proteins and 102 proteins whose plasma levels are associated with baseline VO2max and ΔVO2max, respectively. Addition of a protein biomarker score derived from these proteins to a score based on clinical traits improves the prediction of an individual’s ΔVO2max. We validate findings in a separate exercise cohort, further link 21 proteins to incident all-cause mortality in a community-based cohort and reproduce the specificity of ~75% of our key findings using antibody-based assays. Taken together, our data shed light on biological pathways relevant to cardiorespiratory fitness and highlight the potential additive value of protein biomarkers in identifying exercise responsiveness in humans. Plasma proteomic profiles from 650 adult humans are measured before and after a 20-week exercise regimen to determine proteins associated with baseline cardiorespiratory fitness and improvements in response to exercise.

In addition to their fundamental role in clearance, the kidneys release select molecules into the circulation, but whether any of these anabolic functions provides insight on kidney health is unknown. Using aptamer-based proteomics, we characterized arterial (A)-to-renal venous (V) gradients for >1,300 proteins in 22 individuals who underwent invasive sampling. Although most of the proteins that changed significantly decreased from A to V, consistent with renal clearance, several were found to increase, the most significant of which was testican-2. To assess the clinical implications of these physiologic findings, we examined proteomic data in the Jackson Heart Study (JHS), an African-American cohort (n = 1,928), with replication in the Framingham Heart Study (FHS), a White cohort (n = 1,621). In both populations, testican-2 had a strong, positive correlation with estimated glomerular filtration rate (eGFR). In addition, higher baseline testican-2 levels were associated with a lower rate of eGFR decline in models adjusted for age, gender, hypertension, type 2 diabetes, body mass index, baseline eGFR, and albuminuria. Glomerular expression of testican-2 in human kidneys was demonstrated by immunohistochemistry, immunofluorescence, and electron microscopy, while single-cell RNA sequencing of human kidneys showed expression of the cognate gene, SPOCK2, exclusively in podocytes. In vitro, testican-2 increased glomerular endothelial tube formation and motility, raising the possibility that its secretion has a functional role within the glomerulus. Taken together, our findings identify testican-2 as a podocyte-derived biomarker of kidney health and prognosis.

BackgroundRapidly and efficiently identifying critically ill infants for WGS is a costly and challenging task currently performed by scarce, highly trained experts, and is a major bottleneck for application of WGS in the NICU. Automated means to prioritize patients for WGS are thus badly needed.MethodsInstitutional databases of Electronic Health Records (EHRs) are logical starting points for identifying patients with undiagnosed Mendelian diseases. We have developed automated means to prioritize patients for Rapid and Whole Genome Sequencing (rWGS and WGS) directly from clinical notes. Our approach combines a Clinical Natural Language Processing (CNLP) workflow with a machine learning-based prioritization tool we call the Mendelian Phenotype Search Engine (MPSE).ResultsMPSE accurately and robustly identified NICU patients selected for WGS by clinical experts from Rady Children’s Hospital in San Diego (AUC 0.86) and the University of Utah (AUC 0.85). In addition to effectively identifying patients for WGS, MPSE scores also strongly prioritize diagnostic cases over non-diagnostic cases, with projected diagnostic yields exceeding 50% throughout the first and second quartiles of score-ranked patients.ConclusionsOur results indicate that an entirely automated pipeline for selecting acutely ill infants in neonatal intensive care units (NICU) for WGS can meet or exceed diagnostic yields obtained through current selection procedures, which require time-consuming manual review of clinical notes and histories by specialized personnel.

Nontargeted metabolomics methods have increased potential to identify new disease biomarkers, but assessments of the additive information provided in large human cohorts by these less biased techniques are limited. To diversify our knowledge of diabetes associated metabolites, we leveraged a method that measures 305 targeted or “known” and 2,342 nontargeted or “unknown” compounds in fasting plasma samples from 2,750 participants (315 incident cases) in the Jackson Heart Study (JHS)—a community cohort of self-identified African Americans (AAs), who are underrepresented in omics studies. We found 307 unique compounds (82 known) associated with diabetes after adjusting for age and sex at a false discovery rate (FDR)

Introduction: Use of upfront chemotherapy or novel hormonal therapy (NHT) in patients (pts) with mCSPC has been approved based on improved outcomes. Baseline clinical and genomic correlates associated with inferior outcomes on intensified therapy would help identify pts at high risk for early progression or death, may improve patient counselling and guide drug development. Methods: In this IRB-approved study, pt-level data were collected retrospectively. Eligibility: mCSPC pts undergoing ADT plus NHT or docetaxel with available pre-treatment tumor comprehensive genomic profiling from a CLIA-certified lab. Study endpoint: progression-free survival (PFS) per PCWG-2, is defined as PSA, or radiographic, or clinical progression or death whichever occurred first. Variants of unknown significance and mutated genes present in ≤5% pts were excluded. Cox proportional hazards was used to evaluate the relationship between PFS and age at diagnosis, Gleason score, volume of disease (per CHAARTED), presence of visceral mets, PSA at baseline and genomic alterations. Significance was pre-set at p ≤ 0.05. Results: 106 pts with mCSPC were included: median follow-up was 20 months. Median age at diagnosis was 62 yrs (58 - 68); 85 pts (80%) had a Gleason score ≥8; 67 pts (63%) had de-novo metastatic disease; 69 pts (56%) had high-volume disease; and 20 (19%) had visceral metastases at time of diagnosis of metastatic disease. Most frequently mutated genes: TP53 (28%, n=30), TMPRSS2 (27%, n=29), and PTEN (21%, n=22). See table for COX regression results. Conclusion: In this real-world cohort of mCSPC pts undergoing intensified ADT we identify clinical and genomic markers that are significantly associated with a an inferior PFS. These hypothesis-generating data need external validation. Hazard Ratio (95% CI) P Age 0.98 (0.94-1.02) 0.40 De Novo 1.28 (0.61-2.62) 0.52 Gleason Score ≥8 2.61 (0.98-6.93) 0.05 Log-PSA at Baseline 1.17 (1.03-1.33) 0.02 High Vol of Disease 2.47 (1.23-4.99) 0.01 Visceral Mets 1.25 (0.54-3.92) 0.60 Mutated Genes MYC 5.17 (1.39-19.27) 0.01 KDM6A 0.97 (0.20-4.52) 0.97 RB1 3.14 (0.97-10.17) 0.06 PTEN 1.07 (0.48-2.36) 0.87 TMPRSS2 1.09 (0.55-2.14) 0.81 TP53 0.89 (0.47-1.74) 0.74 Citation Format: Nicolas Sayegh, Bennet Peterson, Nishita Tripathi, Beverly Chigarira, Haoran Li, Kamal Kant Sahu, Deepika Sirohi, Roberto Nussenzveig, Benjamin L. Maughan, Neeraj Agarwal, Umang Swami. Clinical and genomic correlates of survival outcomes in patients (pts) with metastatic castration-sensitive prostate cancer (mCSPC) receiving intensified androgen deprivation therapy (ADT) in a real-world population [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5142.

Background: Heart failure (HF) is a heterogeneous disease characterized by significant metabolic disturbances; however, the breadth of metabolic dysfunction before the onset of overt disease is not well understood. The purpose of this study was to determine the association of circulating metabolites with incident HF to uncover novel metabolic pathways to disease. Methods: We performed targeted plasma metabolomic profiling in a deeply phenotyped group of Black adults from the JHS (Jackson Heart Study; n=2199). We related metabolites associated with incident HF to established etiological mechanisms, including increased left ventricular mass index and incident coronary heart disease. Furthermore, we evaluated differential associations of metabolites with HF with preserved ejection fraction versus HF with reduced ejection fraction. Results: Metabolites associated with incident HF included products of posttranscriptional modifications of RNA, as well as polyamine and nitric oxide metabolism. A subset of metabolite-HF associations was independent of well-established HF pathways such as increased left ventricular mass index and incident coronary heart disease and included homoarginine (per 1 SD increase in metabolite level, hazard ratio, 0.77; P =1.2×10 −3 ), diacetylspermine (hazard ratio, 1.34; P =3.4×10 −3 ), and uridine (hazard ratio, 0.79; P , 3×10 −4 ). Furthermore, metabolites involved in pyrimidine metabolism (orotic acid) and collagen turnover ( N -methylproline) among others were part of a distinct metabolic signature that differentiated individuals with HF with preserved ejection fraction versus HF with reduced ejection fraction. Conclusions: The integration of clinical phenotyping with plasma metabolomic profiling uncovered novel metabolic processes in nontraditional disease pathways underlying the heterogeneity of HF development in Black adults.

Background: Increased left ventricular (LV) mass is associated with future adverse cardiovascular events including heart failure (HF). Both increased LV mass and HF disproportionately affect black individuals. To understand the mechanisms that drive disease, particularly in black individuals, we undertook a proteomic screen in a black cohort and compared it to a white cohort. Methods: We measured 1305 plasma proteins using an aptamer-based proteomic platform (SOMAscan™) in 1772 black participants in the Jackson Heart Study (JHS) with available baseline LV mass as assessed by 2D echocardiography, as well as 1600 free of HF with follow-up assessment of incident cases. Mean follow-up time was 11 years; 152 cases of incident HF hospitalization were identified. Models were adjusted for age, sex, body mass index, estimated glomerular filtration rate (as calculated by CKD-EPI equation), systolic blood pressure, hypertension treatment, presence of diabetes, total/HDL cholesterol, prevalent coronary disease, and current smoking status. Incident HF models were also adjusted for incident coronary heart disease. We then compared protein associations in JHS to those observed in whites from the Framingham Heart Study (FHS) to examine significant differences. Results: In JHS, there were 112 proteins associated with LV mass and 10 proteins associated with incident HF hospitalization with FDR -8 , HR = 1.46 [1.20, 1.79], p = 0.0002). The strongest association with LV mass was more novel: leukotriene A4 hydrolase (LKHA4) (β = 0.05 [0.04, 0.06], p = 2.6 x 10 -15 ). Conversely, Fractalkine/CX3CL1 showed a novel association with incident HF (HR = 1.32 [1.14, 1.54], p = 0.0003). While proteins like Cystatin C and N-terminal pro-BNP showed consistent effects in FHS, LKHA4 and Fractalkine were significantly different. Conclusions: We identify several novel biological pathways specific to black individuals hypothesized to contribute to the pathophysiologic cascade of LV hypertrophy and incident HF including LKHA4 and Fractalkine. Further studies are needed to validate these results and elucidate the detailed underlying mechanisms.

Brief SummaryCOVID-19 is one of the most consequential pandemics in the last century, yet the biological mechanisms that confer disease risk are incompletely understood. Further, heterogeneity in disease outcomes is influenced by race, though the relative contributions of structural/social and genetic factors remain unclear.1,2Very recent unpublished work has identified two genetic risk loci that confer greater risk for respiratory failure in COVID-19: theABOlocus and the 3p21.31 locus.3To understand how these loci might confer risk and whether this differs by race, we utilized proteomic profiling and genetic information from three cohorts including black and white participants to identify proteins influenced by these loci. We observed that variants in theABOlocus are associated with levels of CD209/DC-SIGN, a known binding protein for SARS-CoV and other viruses,4as well as multiple inflammatory and thrombotic proteins, while the 3p21.31 locus is associated with levels of CXCL16, a known inflammatory chemokine.5Thus, integration of genetic information and proteomic profiling in biracial cohorts highlights putative mechanisms for genetic risk in COVID-19 disease.

IMPORTANCE: African American individuals have disproportionate rates of coronary heart disease (CHD) but lower levels of coronary artery calcium (CAC), a marker of subclinical CHD, than non-Hispanic White individuals. African American individuals may have distinct metabolite profiles associated with incident CHD risk compared with non-Hispanic White individuals, and examination of these differences could highlight important processes that differ between them. OBJECTIVES: To identify novel biomarkers of incident CHD and CAC among African American individuals and to replicate incident CHD findings in a multiethnic cohort. DESIGN, SETTING, AND PARTICIPANTS: This analysis targeted plasma metabolomic profiling of 2346 participants in the Jackson Heart Study (JHS), a prospective population-based cohort study that included 5306 African American participants who were examined at baseline (2000-2004) and 2 follow-up visits. Replication of CHD-associated metabolites was sought among 1588 multiethnic participants from the Women’s Health Initiative (WHI), a prospective population-based multiethnic cohort study of 161 808 postmenopausal women who were examined at baseline (1991-1995) and ongoing follow-up visits. Regression analyses were performed for each metabolite to examine the associations with incident CHD and CAC scores. Data were collected from the WHI between 1994 and 2009 and from the JHS between 2000 and 2015. All data were analyzed from November 2020 to August 2021. EXPOSURES: Plasma metabolites. MAIN OUTCOMES AND MEASURES: Incident CHD was defined as definite or probable myocardial infarction or definite fatal CHD in both the JHS and WHI cohorts. In the JHS cohort, silent myocardial infarction between examinations (as determined by electrocardiography) and coronary revascularization were included in the incident CHD analysis. Coronary artery calcium was measured using a 16-channel computed tomographic system and reported as an Agatston score. RESULTS: Among 2346 African American individuals in the JHS cohort, the mean (SD) age was 56 (13) years, and 1468 individuals (62.6%) were female. Among 1588 postmenopausal women in the WHI cohort, the mean (SD) age was 67 (7) years; 217 individuals (13.7%) self-identified as African American, 1219 (76.8%) as non-Hispanic White, and 152 (9.6%) as other races or ethnicities. In the fully adjusted model including 1876 individuals, 46 of 303 targeted metabolites were associated with incident CHD (false discovery rate q

Background: Despite recent advancements in systemic therapy in men with mCSPC, disease remains fatal. Identification of novel genomic and clinical correlates of survival in this setting remain a significant unmet need. Methods: Newly diagnosed mCSPC undergoing intensified ADT i.e., ADT plus docetaxel or novel hormonal therapy and available tumor comprehensive genomic profiling (CGP) were included in the analysis. CGP was performed by a CLIA certified Next Generation Sequencing panel (Foundation Medicine) and involved the following genes: FAS, KDM6A, MYC1, PTEN, RB1, TMPRSS2, and TP53. All variants of unknown significance were removed, and mutated genes present in ≥5 % patients were included. Cox proportional hazards was used to assess relationships between OS and multiple variables (age at diagnosis, Gleason score, baseline PSA, de-novo disease, volume of disease, presence of visceral metastases and presence of genetic aberrations on CGP). Results: 127 patients were eligible and included. Higher baseline PSA (HR 1.45, 95% CI 1.09-1.9, P=0.0097), presence of visceral metastases (HR 4.41, 95% CI 1.26-15.39, P=0.0199) and genomic aberrations in MYC1 (HR 5.23, 95% CI 1.05-26.04, P=0.0433) and RB1 (HR 32.72, 95% CI 5.35-200.2, P=0.0002) were significantly associated with inferior OS. High volume disease trended to associate with poor OS, but was not statistically significant (HR 1.63, 95% CI 0.56-4.71, P=0.367). PTEN loss and other genomic aberrations were not associated with OS. See Table. Conclusions: In this real-world patient population of men with mCSPC undergoing intensified ADT we identify clinical and genomic markers associated with poor OS. This study has limitations as expected in a retrospective analysis. These data, upon external validation, may aid with development of a risk stratification model, counseling of patients, treatment decision making in the clinic, as well as further drug development. Citation Format: Nicolas Sayegh, Bennet Peterson, Roberto Nussenzveig, Adam Kessel, Taylor Ryan McFarland, Andrew Warren Hahn, Deepika Sirohi, Manish Kohli, Benjamin Louis Maughan, Umang Swami, Mark Yandell, Neeraj Agarwal. Genomic and clinical correlates of overall survival (OS) in men with newly diagnosed metastatic castration-sensitive prostate cancer (mCSPC) undergoing intensified androgen deprivation therapy (ADT) [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr P012.

Background: Chronic obstructive pulmonary disease (COPD) is a common, complex respiratory disease characterized by airway obstruction and accelerated lung function decline. Our understanding of systemic protein biomarkers associated with COPD remains incomplete. We tested whether aptamer-based protein profiling could identify markers and pathways related to impaired pulmonary function and lung function decline in multiple studies. Methods: We studied 3,827 non-Hispanic/European White participants across six cohort studies with both aptamer-based proteomic and spirometry data. In linear regression models we examined protein associations with baseline FEV1 and FEV1/FVC. In linear mixed effects models we investigated the associations of baseline protein levels with rate of FEV1 decline (mL/year) in 2,636 participants with up to 7 years of follow-up spirometry. Findings: We identified 198 proteins associated with FEV1, twelve of the proteins were also significantly associated with FEV1/FVC, including retinal binding protein 4 FEV1 : β=0·0307, Q= 2·18×10-4; FEV1/FVC: β=0·008, Q =4·0×10-3 ) and bactericidal permeability-increasing protein (FEV1 : β=-0·0280, Q =6·80×10-3; FEV1/FVC: β=0·0050, Q =0·04). We further identified 15 proteins associated with the rate of FEV1 decline ( Q

162 Background: PARP inhibitors (PARPi) provide significant clinical benefit for men with aPC with BRCA 1 and BRCA 2 mutations. However, in clinical trials, pts with BRCA1 mutations appeared to derive less benefit than pts with BRCA2 (De Bono et al., 2020). Probabilistic Graphical Models (PGMs) are artificial intelligence (AI) algorithms that capture multivariate, multi-level dependencies in complex patterns in large datasets while retaining human interpretability. We hypothesize that PGMs can reveal variants in BRCA1 and 2 that co-segregate with other known pathogenic variants and may explain the difference in response to PARPi therapy. Methods: Multilevel gene interdependencies between BRCA1 or BRCA2 were assessed using a Bayesian Network (BN) machine learning approach and Fisher’s exact test. CGP was performed by a validated cfDNA NGS panel that sequenced 74 clinically relevant cancer genes (Guardant360, Redwood City, CA). Only variants of known significance and those of unknown significance with a pathogenic REVEL score were included in the analysis. Results: Of 4671 men with aPC undergoing cfDNA CGP, 1248 men with somatic mutations in BRCA1, BRCA2, ATM, or combinations of the three were included in the analysis. The Bayesian network analysis demonstrated positive interdependencies between pathogenic variants in BRCA1 and 7 other genes. A positive interdependency between BRCA2 and 2 genes was present (table). ATM displayed negative interdependency with both BRCA 1 and 2. Conclusions: Our results demonstrate a decreased association of BRCA2 versus BRCA1 with known or predicted pathogenic variants at other loci. This may explain increased sensitivity of aPC with BRCA2 mutations to PARPi due to fewer concurrent resistance pathways. For example, alteration of ERBB2, which segregates strongly with BRCA1, is known to induce tumor progression and invasion in aPC and is associated with castration-resistance. These hypothesis-generating data reveal differential genomic signatures associated with BRCA1 as compared to BRCA2 and may inform development of future combinatorial treatment regimens for these pts. [Table: see text]

The goal of this study is to identify mechanisms by which the oncogenic tyrosine kinase receptor HER2 promotes the growth and metastasis of breast cancer. Previously published work suggests that the phospho-binding protein 14-3-3ζ, which is highly expressed in a variety of breast cancer subtypes, promotes HER2-mediated oncogenic signaling. In this study, we hypothesized that 14-3-3ζ sustains HER2 signaling by binding to and modulating a network of proteins that are phosphorylated downstream of HER2 activation. Using proteomics as a tool to identify 14-3-3ζ interacting proteins in HER2+ breast cancer cells treated with or without Lapatinib (HER2 inhibitor), we identified a subset HER2-dependent 14-3-3ζ interacting proteins. We have focused our current effort on one of these proteins, SH3BP4, which plays a critical role in controlling mTOR activation. We have identified a nutrient-sensitive phosphorylation within a putative 14-3-3ζ binding site on SH3BP4 and we are currently working to understand its mechanism of regulation and impact on mTOR-mediated growth signaling downstream of HER2. Citation Format: Tsz Yin Chan, Courtney Banks, Bennet Peterson, Joshua Andersen. 14-3-3z-mediated oncogenic signaling downstream of HER2 in breast cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4568.

Recent advances in proteomic technologies have made high-throughput profiling of low-abundance proteins in large epidemiological cohorts increasingly feasible. We investigated whether aptamer-based proteomic profiling could identify biomarkers associated with future development of type 2 diabetes (T2DM) beyond known risk factors. We identified dozens of markers with highly significant associations with future T2DM across 2 large longitudinal cohorts (n = 2839) followed for up to 16 years. We leveraged proteomic, metabolomic, genetic, and clinical data from humans to nominate 1 specific candidate to test for potential causal relationships in model systems. Our studies identified functional effects of aminoacylase 1 (ACY1), a top protein association with future T2DM risk, on amino acid metabolism and insulin homeostasis in vitro and in vivo. Furthermore, a loss-of-function variant associated with circulating levels of the biomarker WAP, Kazal, immunoglobulin, Kunitz, and NTR domain–containing protein 2 (WFIKKN2) was, in turn, associated with fasting glucose, hemoglobin A1c, and HOMA-IR measurements in humans. In addition to identifying potentially novel disease markers and pathways in T2DM, we provide publicly available data to be leveraged for insights about gene function and disease pathogenesis in the context of human metabolism.