Baseline Plasma Samples Research Articles

Multiomics Profiling of Plasma Reveals Molecular Alterations Prior to a Diagnosis with Stroke Among Chinese Hypertension Patients.

We aimed to investigate the correlation between plasma proteins and metabolites and the occurrence of future strokes using mass spectrometry and bioinformatics as well as to identify other biomarkers that could predict stroke risk in hypertensive patients. In a nested case-control study, baseline plasma samples were collected from 50 hypertensive subjects who developed stroke and 50 gender-, age- and body mass index-matched controls. Plasma untargeted metabolomics and data independent acquisition-based proteomics analysis were performed in hypertensive patients, and 19 metabolites and 111 proteins were found to be differentially expressed. Integrative analyses revealed that molecular changes in plasma indicated dysregulation of protein digestion and absorption, salivary secretion, and regulation of actin cytoskeleton, along with significant metabolic suppression. C4BPA, Caprolactam, Col15A1, and HBB were identified as predictors of stroke occurrence, and the Support Vector Machines (SVM) model was determined to be the optimal predictive model by integrating six machine-learning classification models. The SVM model showed strong performance in both the internal validation set (area under the curve [AUC]: 0.977, 95% confidence interval [CI]: 0.941-1.000) and the external independent validation set (AUC: 0.973, 95% CI: 0.921-0.999).

Early inflammation as a footprint of increased mortality risk in infants living with HIV from three African countries

In this work our aim was to identify early biomarkers in plasma samples associated with mortality in children with perinatal HIV treated early in life, to potentially inform early intervention targeting this vulnerable group. 20/215 children (9.3%) with perinatal HIV, enrolled within 3 months of age died prematurely within the first year of the study, despite early ART initiation. Using a propensity score, we selected 40 alive study participants having similar clinical and virological records compared to the deceased group. 13 HIV unexposed (HU) healthy children were additionally used as controls. Baseline plasma samples were analyzed using a targeted proteomic approach, and to assess pathogen-associated and damage-associated molecular patterns (PAMPs, DAMPs) levels. Data from deceased participants were compared to both control groups, with multivariate logistic regression models used to evaluate the association between mortality and plasma proteins. We developed a machine learning model to predict mortality risk, finding that IL-6 and CXCL11 not only were higher in deceased children than Matched-children with HIV (p < 0.001 and p = 0.0034) but also predictive of mortality (accuracy of 77%); levels of PAMPs were higher in deceased children (p = 0.0016). Thus, measuring early inflammatory biomarkers, particularly IL-6, could help mortality risk prediction and potentially guide targeted interventions.

Proteomic Analysis Uncovers Multi-Protein Signatures Associated with Early Diabetic Kidney Disease in Youth with Type 2 Diabetes Mellitus.

The onset of diabetic kidney disease (DKD) in youth with type 2 diabetes mellitus often occurs early, leading to complications in young adulthood. Risk biomarkers associated with the early onset of DKD are urgently needed in youth with type 2 diabetes. We conducted an in-depth analysis of 6596 proteins (SomaScan 7K) in 374 baseline plasma samples from the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) study to identify multi-protein signatures associated with the onset of albuminuria (urine albumin-to-creatinine ratio [UACR] ≥30 mg/g), a rapid decline in estimated glomerular filtration rate (eGFR) [annual eGFR decline >3 mL/min/1.73m2 and/or ≥3.3% at two consecutive visits], and hyperfiltration (≥135 mL/min/1.73m2 at two consecutive visits). Elastic net Cox regression with 10-fold cross-validation was applied to the top 100 proteins (ranked by p-value) to identify multi-protein signatures of time to development of DKD outcomes. Participants in the TODAY study (14±2 years old, 63% female, 7±6 months diabetes duration) experienced high rates of early DKD: 43% developed albuminuria, 48% hyperfiltration, and 16% rapid eGFR decline. Increased levels of seven and three proteins were predictive of shorter time to develop albuminuria and rapid eGFR decline, respectively; 118 proteins predicted time to development of hyperfiltration. Elastic net Cox proportional hazards model identified multi-protein signatures of time to incident early DKD with concordance for models with clinical covariates and selected proteins between 0.81 and 0.96, while the concordance for models with clinical covariates only was between 0.56 and 0.63. Our research sheds new light on proteomic changes early in the course of youth-onset type 2 diabetes that associate with DKD. Proteomic analyses identified promising risk factors that predict DKD risk in youth with type 2 diabetes and could deepen our understanding of DKD mechanisms and potential interventions.

Inflammatory proteins associated with Alzheimer’s disease reduced by a GLP1 receptor agonist: a post hoc analysis of the EXSCEL randomized placebo controlled trial

BackgroundGlucagon-like peptide-1 receptor agonists are a viable option for the prevention of Alzheimer’s disease (AD) but the mechanisms of this potential disease modifying action are unclear. We investigated the effects of once-weekly exenatide (EQW) on AD associated proteomic clusters.MethodsThe Exenatide Study of Cardiovascular Event Lowering study compared the cardiovascular effects of EQW 2 mg with placebo in 13,752 people with type 2 diabetes mellitus. 4,979 proteins were measured (Somascan V0.4) on baseline and 1-year plasma samples of 3,973 participants. C-reactive protein (CRP), ficolin-2 (FCN2), plasminogen activator inhibitor 1 (PAI-1), soluble vascular cell adhesion protein 1 (sVCAM1) and 4 protein clusters were tested in multivariable mixed models.ResultsEQW affected FCN2 (Cohen’s d -0.019), PAI-1 (Cohen’s d -0.033), sVCAM-1 (Cohen’s d 0.035) and a cytokine-cytokine cluster (Cohen’s d 0.037) significantly compared with placebo. These effects were sustained in individuals over the age of 65 but not in those under 65.ConclusionsEQW treatment was associated with significant change in inflammatory proteins associated with AD.Trial RegistrationEXSCEL is registered on ClinicalTrials.gov: NCT01144338 on 10th of June 2010.

Proteogenomic Analysis Identifies a Causal Association between Plasma Apolipoprotein B Levels and Liver Cancer Risk.

Liver oncogenesis is accompanied by discernible protein changes in the bloodstream. By employing plasma proteomic profiling, we can delve into the molecular mechanisms of liver cancer and pinpoint potential biomarkers. In this nested case-control study, we applied liquid chromatography-tandem mass spectrometry for proteome profiling in baseline plasma samples. Differential protein expression was determined and was subjected to functional enrichment, network, and Mendelian randomization (MR) analyses. We identified 193 proteins with notable differential levels between the groups. Of these proteins, MR analysis offered a compelling negative association between apolipoprotein B (APOB) and liver cancer. This association was further corroborated in the UK Biobank cohort: genetically predicted APOB levels were associated with a 31% (95% CI 19-42%) decreased risk of liver cancer; and phenotypic analysis indicated an 11% (95% CI 8-14%) decreased liver cancer risk for every 0.1 g/L increase of circulating APOB levels. Multivariable MR analysis suggested that the hepatic fat content might fully mediate the APOB-liver cancer connection. In summary, we identified some plasma proteins, particularly APOB, as potential biomarkers of liver cancer. Our findings underscore the intricate link between lipid metabolism and liver cancer, offering hints for targeted prophylactic strategies and early detection.

Proteomic Correlates and Prognostic Significance of Kidney Injury in Heart Failure With Preserved Ejection Fraction.

Kidney disease is common in heart failure with preserved ejection fraction (HFpEF). However, the biologic correlates and prognostic significance of kidney injury (KI), in HFpEF, beyond the estimated glomerular filtration rate (eGFR), are unclear. Using baseline plasma samples from the TOPCAT (Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist) trial, we measured the following KI biomarkers: cystatin-C, fatty acid-binding protein-3, Beta-2 microglobulin, neutrophil gelatinase-associated lipocalin, and kidney-injury molecule-1. Factor analysis was used to extract the common variability underlying these biomarkers. We assessed the relationship between the KI-factor score and the risk of death or HF-related hospital admission in models adjusted for the Meta-Analysis Global Group in Chronic Heart Failure risk score and eGFR. We also assessed the relationship between the KI factor score and ~5000 plasma proteins, followed by pathway analysis. We validated our findings among HFpEF participants in the Penn Heart Failure Study. KI was associated with the risk of death or HF-related hospital admission independent of the Meta-Analysis Global Group in Chronic Heart Failure risk score and eGFR. Both the risk score and eGFR were no longer associated with death or HF-related hospital admission after adjusting for the KI factor score. KI was predominantly associated with proteins and biologic pathways related to complement activation, inflammation, fibrosis, and cholesterol homeostasis. KI was associated with 140 proteins, which reproduced across cohorts. Findings regarding biologic associations and the prognostic significance of KI were also reproduced in the validation cohort. KI is associated with adverse outcomes in HFpEF independent of baseline eGFR. Patients with HFpEF and KI exhibit a plasma proteomic signature indicative of complement activation, inflammation, fibrosis, and impaired cholesterol homeostasis.

Persistent endocrine-disrupting chemicals and incident uterine leiomyomata: A mixtures analysis

BackgroundUterine leiomyomata (UL; fibroids) are hormone-dependent neoplasms that can cause significant gynecologic morbidity. Studies have documented associations between concentrations of persistent endocrine-disrupting chemicals (EDCs) and UL incidence; however, few have assessed the effects of EDC mixtures on UL. MethodsIn the Study of Environment, Lifestyle, and Fibroids, a prospective cohort study, participants attended study visits at baseline and approximately every 20 months for up to 10 years; at each visit, they completed questionnaires, provided blood samples, and underwent standardized ultrasound examinations. In baseline plasma samples (n = 1155), we quantified concentrations of polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and organochlorine pesticides using high-resolution mass spectrometry. We selected nine EDCs detected in >60 % of samples (4 PCBs, 4 PBDEs, and 2,2-bis(4-chlorophenyl)-1,1-dichloroethene (p,p’-DDE)) and conducted probit Bayesian kernel machine regression with hierarchical variable selection to estimate effects of the EDC mixture and individual EDCs on UL incidence, adjusting for potential confounders. ResultsDuring 10 years of follow-up, 32 % of participants developed ultrasound-detected UL. The EDC mixture was not appreciably associated with the probit of UL (β comparing all EDCs at their 75th vs. 50th percentile:= − 0.01, 95 % credible interval [CrI]: −0.11, 0.10). However, individual EDC concentrations were associated with UL in opposing directions: PCB138/158 was positively associated with UL (β for 25th-to-75th-percentile increase when all other chemicals were set to their 50th percentile = 0.18, 95 % CrI: −0.09, 0.44), whereas PBDE99 and p,p’-DDE were inversely associated with UL (β = −0.06, 95 % CrI: −0.21, 0.10 and β = −0.12, 95 % CrI: −0.34, 0.10, respectively). There was little evidence of interaction between EDCs. ConclusionIn this prospective ultrasound study, a mixture of persistent EDCs was not appreciably associated with incident UL during 10 years of follow-up, but individual EDCs were associated with UL in opposite directions.

Neurofilament Light Chain and Risk of Stroke in Patients With Atrial Fibrillation.

Biomarkers reflecting brain injury are not routinely used in risk assessment of stroke in atrial fibrillation (AF). Neurofilament light chain (NFL) is a novel biomarker released into blood after cerebral insults. We investigated the association between plasma concentrations of NFL, other biomarkers, and risk of stroke and death in patients with AF not receiving oral anticoagulation. For this observational study, baseline plasma samples were available from 3077 patients with AF randomized to aspirin in ACTIVE A (Atrial Fibrillation Clopidogrel Trial With Irbesartan for Prevention of Vascular Events; 2003 to 2008) and AVERROES (Apixaban Versus Acetylsalicylic Acid [ASA] to Prevent Stroke in Atrial Fibrillation Patients Who Have Failed or Are Unsuitable for Vitamin K Antagonist Treatment; 2007 to 2009). Median follow-up was 1.5 years. NFL was analyzed with a Single Molecule Array (Simoa). Associations with outcomes (total stroke or systemic embolism, ischemic stroke, cardiovascular death, and all-cause death) were explored with Cox regression models. In the combined cohort, the median NFL level was 16.9 ng/L (interquartile range, 11.1-26.5 ng/L), the median age was 71 years, 58% were men, and 13% had a history of previous stroke. NFL was associated with older age, higher creatinine, lower body mass index, previous stroke, female sex, and diabetes but not cardiac rhythm. Higher NFL was associated with a higher risk of stroke or systemic embolism (n=206) independently of clinical characteristics (hazard ratio, 1.27 [95% CI, 1.10-1.46] per doubling of NFL) and other biomarkers (hazard ratio, 1.18 [95% CI, 1.01-1.37]) and including in patients without previous stroke (hazard ratio, 1.23 [95% CI, 1.02-1.48]). NFL was also independently associated with cardiovascular (n=219) and all-cause (n=311) death. The C index for stroke using only NFL was 0.642, on par with the currently used clinical risk scores. Addition of information on NFL improved discrimination in a model also including clinical information, NT-proBNP (N-terminal pro-B-type natriuretic peptide), and high-sensitivity cardiac troponin T, yielding a C index of 0.727. NFL reflects overt and covert episodes of cerebral ischemia and improves risk assessment of stroke and death in patients with AF without oral anticoagulation, including in patients without previous stroke. The combination of NFL with information on age, history of stroke, and other biomarkers should be explored as a future avenue for stroke risk assessments in patients with AF.

Plasma soluble fms-like tyrosine kinase-1, placental growth factor, and vascular endothelial growth factor system gene variants as predictors of survival in heart failure.

Soluble fms-like tyrosine kinase-1 (sFlt-1) and placental growth factor (PlGF), components of the vascular endothelial growth factor (VEGF) system, play key roles in angiogenesis. Reports of elevated plasma levels of sFlt-1 and PlGF in coronary heart disease and heart failure (HF) led us to investigate their utility, and VEGF system gene single nucleotide polymorphisms (SNPs), as prognostic biomarkers in HF. ELISA assays for sFlt-1, PlGF and N-terminal pro-B-type natriuretic peptide (NT-proBNP) were performed on baseline plasma samples from the PEOPLE cohort (n = 890), a study of outcomes among patients after an episode of acute decompensated HF. Eight SNPs potentially associated with sFlt-1 or PlGF levels were genotyped. sFlt-1 and PlGF were assayed in 201 subjects from the Canterbury Healthy Volunteers Study (CHVS) matched to PEOPLE participants. All-cause death was the major endpoint for clinical outcome considered. In PEOPLE participants, mean plasma levels for both sFlt-1 (125 ± 2.01 pg/ml) and PlGF (17.5 ± 0.21 pg/ml) were higher (both p < 0.044) than in the CHVS cohort (81.2 ± 1.31 pg/ml and 15.5 ± 0.32 pg/ml, respectively). sFlt-1 was higher in HF with reduced ejection fraction compared to HF with preserved ejection fraction (p = 0.005). The PGF gene SNP rs2268616 was univariately associated with death (p = 0.016), and was also associated with PlGF levels, as was rs2268614 genotype. Cox proportional hazards modelling (n = 695, 246 deaths) showed plasma sFlt-1, but not PlGF, predicted survival (hazard ratio 6.44, 95% confidence interval 2.57-16.1; p < 0.001) in PEOPLE, independent of age, NT-proBNP, ischaemic aetiology, diabetic status and beta-blocker therapy. Plasma sFlt-1 concentrations have potential as an independent predictor of survival and may be complementary to established prognostic biomarkers in HF.

Circulating Metabolite Profiles and Risk of Coronary Heart Disease Among Racially and Geographically Diverse Populations.

Metabolomics may reveal novel biomarkers for coronary heart disease (CHD). We aimed to identify circulating metabolites and construct a metabolite risk score (MRS) associated with incident CHD among racially and geographically diverse populations. Untargeted metabolomics was conducted using baseline plasma samples from 900 incident CHD cases and 900 age-/sex-/race-matched controls (300 pairs of Black Americans, White Americans, and Chinese adults, respectively), which detected 927 metabolites with known identities among ≥80% of samples. After quality control, 896 case-control pairs remained and were randomly divided into discovery (70%) and validation (30%) sets within each race. In the discovery set, conditional logistic regression and least absolute shrinkage and selection operator over 100 subsamples were applied to identify metabolites robustly associated with CHD risk and construct the MRS. The MRS-CHD association was evaluated using conditional logistic regression and the C-index. Mediation analysis was performed to examine if MRS mediated associations between conventional risk factors and incident CHD. The results from the validation set were presented as the main findings. Twenty-four metabolites selected in ≥90% of subsamples comprised the MRS, which was significantly associated with incident CHD (odds ratio per 1 SD, 2.21 [95% CI, 1.62-3.00] after adjusting for sociodemographics, lifestyles, family history, and metabolic health status). MRS could distinguish incident CHD cases from matched controls (C-index, 0.69 [95% CI, 0.63-0.74]) and improve CHD risk prediction when adding to conventional risk factors (C-index, 0.71 [95% CI, 0.65-0.76] versus 0.67 [95% CI, 0.61-0.73]; P<0.001). The odds ratios and C-index were similar across subgroups defined by race, sex, socioeconomic status, lifestyles, metabolic health, family history, and follow-up duration. The MRS mediated large portions (46.0%-74.2%) of the associations for body mass index, smoking, diabetes, hypertension, and dyslipidemia with incident CHD. In a diverse study sample, we identified 24 circulating metabolites that, when combined into an MRS, were robustly associated with incident CHD and modestly improved CHD risk prediction beyond conventional risk factors.

One-Year Effects of High-Intensity Statin on Bioactive Lipids: Findings From the JUPITER Trial.

Statin effects extend beyond low-density lipoprotein cholesterol reduction, potentially modulating the metabolism of bioactive lipids (BALs), crucial for biological signaling and inflammation. These bioactive metabolites may serve as metabolic footprints, helping uncover underlying processes linked to pleiotropic effects of statins and yielding a better understanding of their cardioprotective properties. This study aimed to investigate the impact of high-intensity statin therapy versus placebo on plasma BALs in the JUPITER trial (Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin; NCT00239681), a randomized primary prevention trial involving individuals with low-density lipoprotein cholesterol <130 mg/dL and high-sensitivity C-reactive protein ≥2 mg/L. Using a nontargeted mass spectrometry approach, over 11 000 lipid features were assayed from baseline and 1-year plasma samples from cardiovascular disease noncases from 2 nonoverlapping nested substudies: JUPITERdiscovery (n=589) and JUPITERvalidation (n=409). The effect of randomized allocation of rosuvastatin 20 mg versus placebo on BALs was examined by fitting a linear regression with delta values (∆=year 1-baseline) adjusted for age and baseline levels of each feature. Significant associations in discovery were analyzed in the validation cohort. Multiple comparisons were adjusted using 2-stage overall false discovery rate. We identified 610 lipid features associated with statin randomization with significant replication (overall false discovery rate, <0.05), including 26 with annotations. Statin therapy significantly increased levels of 276 features, including BALs with anti-inflammatory activity and arterial vasodilation properties. Concurrently, 334 features were significantly lowered by statin therapy, including arachidonic acid and proinflammatory and proplatelet aggregation BALs. By contrast, statin therapy reduced an eicosapentaenoic acid-derived hydroxyeicosapentaenoic acid metabolite, which may be related to impaired glucose metabolism. Additionally, we observed sex-related differences in 6 lipid metabolites and 6 unknown features. Statin allocation was significantly associated with upregulation of BALs with anti-inflammatory, antiplatelet aggregation and antioxidant properties and downregulation of BALs with proinflammatory and proplatelet aggregation activity, supporting the pleiotropic effects of statins beyond low-density lipoprotein cholesterol reduction.

Associations of per- and polyfluoroalkyl substances with uterine leiomyomata incidence and growth: a prospective ultrasound study.

Per- and polyfluoroalkyl substances (PFAS) are endocrine-disrupting chemicals used in commercial and consumer products. We evaluated PFAS exposure in relation to incidence and growth of uterine leiomyomata (UL), hormone-dependent neoplasms that are associated with severe gynecologic morbidity. We studied 1158 participants in the Study of Environment, Lifestyle, and Fibroids, a Detroit-based prospective cohort study of Black females aged 23-35 years at enrollment (2010-2012). At enrollment and four subsequent visits during 10 years of follow-up, participants attended in-person clinic visits, completed questionnaires, provided non-fasting blood samples, and underwent ultrasound for UL detection. We quantified 7 PFAS in baseline plasma samples using mass spectrometry. We used Cox regression and probit Bayesian kernel machine regression to estimate individual and joint effects of PFAS on UL incidence. We fit linear mixed models to estimate effects of individual PFAS on UL growth. We stratified by parity, an important route of PFAS elimination and determinant of UL. In individual PFAS analyses, we observed inverse associations for perfluorodecanoate (PFDA; ≥0.3 vs. <0.2 ng/ml: hazard ratio [HR] = 0.74; 95% confidence interval [CI]: 0.54-1.00) and perfluoroundecanoate (detected vs. non-detected: HR = 0.78; 95% CI: 0.61-1.01) and a weak positive association for perfluorohexane sulfonate (≥1 vs. <0.6 ng/ml: HR = 1.17; 95% CI: 0.85-1.61), while perfluorooctane sulfonate, perfluorooctanoate, perfluorononanoate (PFNA), and 2-N-methyl-perfluorooctane sulfonamido acetate (MeFOSAA) showed little association with UL incidence. The PFAS mixture was inversely associated with UL incidence, a finding driven by MeFOSAA and PFDA; however, PFNA was positively associated with UL incidence. The inverse association for PFDA and positive association for PFNA were stronger among nulliparous participants. Most PFAS showed slight inverse associations with UL growth. In this prospective ultrasound study of 1158 Black females aged 23-35 years at enrollment, we conducted a mixtures analysis to account for co-pollutant confounding and interaction. MeFOSAA and PFDA concentrations were inversely associated with UL incidence, while PFNA concentrations were positively associated with UL incidence. Concentrations of most PFAS were associated with decreased UL growth. This study contributes data to the sparse literature on PFAS exposure and UL development.

Associations of neighborhood sociodemographic environment with mortality and circulating metabolites among low-income black and white adults living in the southeastern United States

BackgroundResiding in a disadvantaged neighborhood has been linked to increased mortality. However, the impact of residential segregation and social vulnerability on cause-specific mortality is understudied. Additionally, the circulating metabolic correlates of neighborhood sociodemographic environment remain unexplored. Therefore, we examined multiple neighborhood sociodemographic metrics, i.e., neighborhood deprivation index (NDI), residential segregation index (RSI), and social vulnerability index (SVI), with all-cause and cardiovascular disease (CVD) and cancer-specific mortality and circulating metabolites in the Southern Community Cohort Study (SCCS).MethodsThe SCCS is a prospective cohort of primarily low-income adults aged 40–79, enrolled from the southeastern United States during 2002–2009. This analysis included self-reported Black/African American or non-Hispanic White participants and excluded those who died or were lost to follow-up ≤ 1 year. Untargeted metabolite profiling was performed using baseline plasma samples in a subset of SCCS participants.ResultsAmong 79,631 participants, 23,356 deaths (7214 from CVD and 5394 from cancer) were documented over a median 15-year follow-up. Higher NDI, RSI, and SVI were associated with increased all-cause, CVD, and cancer mortality, independent of standard clinical and sociodemographic risk factors and consistent between racial groups (standardized HRs among all participants were 1.07 to 1.20 in age/sex/race-adjusted model and 1.04 to 1.08 after comprehensive adjustment; all P < 0.05/3 except for cancer mortality after comprehensive adjustment). The standard risk factors explained < 40% of the variations in NDI/RSI/SVI and mediated < 70% of their associations with mortality. Among 1110 circulating metabolites measured in 1688 participants, 134 and 27 metabolites were associated with NDI and RSI (all FDR < 0.05) and mediated 61.7% and 21.2% of the NDI/RSI-mortality association, respectively. Adding those metabolites to standard risk factors increased the mediation proportion from 38.4 to 87.9% and 25.8 to 42.6% for the NDI/RSI-mortality association, respectively.ConclusionsAmong low-income Black/African American adults and non-Hispanic White adults living in the southeastern United States, a disadvantaged neighborhood sociodemographic environment was associated with increased all-cause and CVD and cancer-specific mortality beyond standard risk factors. Circulating metabolites may unveil biological pathways underlying the health effect of neighborhood sociodemographic environment. More public health efforts should be devoted to reducing neighborhood environment-related health disparities, especially for low-income individuals.

Prospective evaluation of the relevance of Epstein-Barr virus antibodies for early detection of nasopharyngeal carcinoma in Chinese adults.

Epstein-Barr virus (EBV) is a major cause of nasopharyngeal carcinoma (NPC) and measurement of different EBV antibodies in blood may improve early detection of NPC. Prospective studies can help assess the roles of different EBV antibodies in predicting NPC risk over time. A case-cohort study within the prospective China Kadoorie Biobank of 512 715 adults from 10 (including two NPC endemic) areas included 295 incident NPC cases and 745 subcohort participants. A multiplex serology assay was used to quantify IgA and IgG antibodies against 16 EBV antigens in stored baseline plasma samples. Cox regression was used to estimate adjusted hazard ratios (HRs) for NPC and C-statistics to assess the discriminatory ability of EBV-markers, including two previously identified EBV-marker combinations, for predicting NPC. Sero-positivity for 15 out of 16 EBV-markers was significantly associated with higher NPC risk. Both IgA and IgG antibodies against the same three EBV-markers showed the most extreme HRs, i.e. BGLF2 (IgA: 124.2 (95% CI: 63.3-243.9); IgG: 8.6 (5.5-13.5); LF2: [67.8 (30.0-153.1), 10.9 (7.2-16.4)]); and BFRF1: 26.1 (10.1-67.5), 6.1 (2.7-13.6). Use of a two-marker (i.e. LF2/BGLF2 IgG) and a four-marker (i.e. LF2/BGLF2 IgG and LF2/EA-D IgA) combinations yielded C-statistics of 0.85 and 0.84, respectively, which persisted for at least 5 years after sample collection in both endemic and non-endemic areas. In Chinese adults, plasma EBV markers strongly predict NPC occurrence many years before clinical diagnosis. LF2 and BGLF2 IgG could identify NPC high-risk individuals to improve NPC early detection in community and clinical settings.

IL17RB genetic variants are associated with acamprosate treatment response in patients with alcohol use disorder: A proteomics-informed genomics study

Acamprosate is a Food and Drug Administration (FDA) approved medication for the treatment of alcohol use disorder (AUD). However, only a subset of patients achieves optimal treatment outcomes. Currently, no biological measures are utilized to predict response to acamprosate treatment. We applied our established pharmaco-omics informed genomics strategy to identify potential biomarkers associated with acamprosate treatment response. Specifically, our previous open-label acamprosate clinical trial recruited 442 patients with AUD who were treated with acamprosate for three months. We first performed proteomics using baseline plasma samples to identify potential biomarkers associated with acamprosate treatment outcomes. Next, we applied our established “proteomics-informed genome-wide association study (GWAS)” research strategy, and identified 12 proteins, including interleukin-17 receptor B (IL17RB), associated with acamprosate treatment response.​ A GWAS for IL17RB concentrations identified several genome-wide significant signals. Specifically, the top hit single nucleotide polymorphism (SNP) rs6801605 with a minor allele frequency of 38% in the European American population mapped 4 kilobase (Kb) upstream of IL17RB, and intron 1 of the choline dehydrogenase (CHDH) gene on chromosome 3 (p: 4.8E-20). The variant genotype (AA) for the SNP rs6801605 was associated with lower IL17RB protein expression. In addition, we identified a series of genetic variants in IL17RB that were associated with acamprosate treatment outcomes. Furthermore, the variantgenotypes for all of those IL17RB SNPs were protective for alcohol relapse. Finally, we demonstrated that the basal level of mRNA expression of IL17RB was inversely correlated with those of nuclear factor-κB (NF-κB) subunits, and a significantly higher expression of NF-κB subunits was observed in AUD patients who relapsed to alcohol use. In summary, this study illustrates that IL17RB genetic variants might contribute to acamprosate treatment outcomes. This series of studies represents an important step toward generating functional hypotheses that could be tested to gain insight into mechanisms underlying acamprosate treatment response phenotypes.(The ClinicalTrials.gov Identifier: NCT00662571).

Updated results and biomarker analyses from the phase 2 trial of nab-paclitaxel plus sintilimab as second-line therapy for advanced or metastatic gastric/gastroesophageal junction adenocarcinoma (G/GEJA).

4037 Background: Sintilimab plus Nab-paclitaxel (nab-PTX) has exhibited promising efficacy and safety in the second line (2L) treatment of PD-1/PD-L1 inhibitor naïve advanced G/GEJA (ZC Jiang et al 2022 ASCO GI). This update presents the latest findings on efficacy, survival outcomes and exploration of biological markers. Methods: We collected blood samples from the advanced G/GEJA patients (pts) who were enrolled in our Phase 2 clinical trial and treated with sintilimab plus nab-PTX. Target-capture deep sequencing of 1,021 genes was conducted to identify somatic variants in circulating tumor DNA (ctDNA) from the baseline plasma samples (N=55) and disease progression samples of the pts with PFS &gt;4 months (N=17). And T cell repertoire sequencing was performed on pretreatment samples (N=55) as well as on paired blood samples obtained during the first tumor evaluation (N=45). Results: From Nov 2019 to Sep 2022, 58 pts were enrolled, with a median follow-up of 20.9 months (95% CI 17.04-24.76) until July 10, 2023. The objective response rate (ORR) and disease control rate (DCR) were 44.8% and 79.3%, respectively. The median progression free survival (mPFS) and median overall survival (mOS) were 4.8 months (95%CI 3.06-6.54) and 11.8 months (95%CI 10.43-13.17). Analysis of baseline ctDNA revealed a notably higher prevalence of EPHB1 mutation in non-responders (PD+increased SD) compared to responders (CR+PR+decreased SD) (21.43% vs. 0%, P=0.022). Pts with EPHB1 mutation showed a significantly increased risk of disease progression (HR 3.86, 95% CI 0.43-34.41, p=0.013) and death (HR 4.49, 95% CI 0.43-46.93, p=0.005) compared to wild-type EPHB1 pts. In contrast to high ctDNA level (mean tumor molecules [MTM] per mL of plasma, cutoff value=2999.7), low ctDNA level demonstrated a significantly reduced risk of disease progression (HR 1.88, 95% CI 1.05-3.37, p=0.034). Dynamic T cell receptor (TCR) diversity analysis during baseline and the initial tumor assessment showed a significant post-treatment increase in the Shannon index within the responder group (P=0.045, median Shannon index change: responder 0.43 vs. non-responder -0.49). An increased Shannon index was correlated with significantly prolonged mPFS (HR 0.44, 95% CI 0.22-0.91, P=0.009), while no significant difference was observed in mOS (HR 0.74, 95% CI 0.36-1.54, P=0.399). A negative correlation between the Shannon index and MTM was observed (R=-0.37, P=0.009). Conclusions: 2L-treatment with sintilimab plus nab-PTX maintains favorable efficacy in advanced G/GEJA pts without prior PD-1/PD-L1 inhibitor treatment. EPHB1 mutation and dynamic change of TCR could serve as potential predictive factors. Further investigation is warranted. Clinical trial information: NCT04140318 .

Molecular characterization and biomarker identification in pediatric B-cell acute lymphoblastic leukemia.

6524 Background: B-cell acute lymphoblastic leukemia (B-ALL) is the most prevalent hematologic malignancy in children and a leading cause of mortality. Despite high cure rates, the management of B-ALL remains challenging due to its high heterogeneity and propensity for relapse. This study aimed to delineate molecular features of pediatric B-ALL and explore the clinical utility of circulating tumor DNA (ctDNA) as a biomarker in B-ALL. Methods: The study analyzed 146 primary pediatric B-ALL patients who were diagnosed from August 2020 to April 2023 and received systemic chemotherapy in Wuhan Children's Hospital. Baseline bone marrow (BM) and plasma samples were collected for next-generation sequencing (NGS) to profile the mutational landscape. BM samples collected on day 19 of the treatment were utilized for minimal residual disease (MRD) testing to assess treatment efficacy. Transcriptomic profiling of baseline BM samples was performed via bulk RNA sequencing. Fisher's exact test and the Wilcoxon rank sum test were utilized to compare categorical and continuous variables between groups, respectively. A two‐tailed P-value&lt;0.05 was considered statistically significant unless indicated otherwise. Results: Transcriptomic analysis revealed that 86.3% of patients (126 out of 146) could be categorized into 13 distinct molecular subtypes, with hyperdiploidy emerging as the predominant subtype. Baseline BM NGS identified gene fusions in 61% of patients, including 37 novel fusions previously unreported in B-ALL. Specifically, the KMT2A-TRIM29 novel fusion was detected and validated in a male child diagnosed with the KMT2A-rearranged subtype. Despite initially responding well to therapy, the patient experienced disease progression after a year, indicating a poor prognosis. We also found that elevated mutant counts and maximum-variant-allele-frequency (maxVAF) in baseline BM were associated with significantly poorer response to chemotherapy ( P=0.0012 and 0.028, respectively). Additionally, MRD-negative patients exhibited upregulated expression of immune-related pathways ( P&lt;0.01) and increased CD8+ T cell infiltration ( P=0.047), indicating a more active immune microenvironment in better responding tumors. Baseline plasma ctDNA, which exhibited high mutational concordance with paired baseline BM samples, also demonstrated significant associations with chemotherapy efficacy, highlighting its potential as a non-invasive tool for disease monitoring and treatment outcome prediction. Conclusions: This study elucidated novel gene fusions and potential biomarkers for treatment response in pediatric B-ALL. Importantly, both baseline plasma ctDNA and BM samples offer promising prognostic insights into chemotherapy responses, paving the way for non-invasive monitoring strategies in the management of pediatric B-ALL.

#814 Inflammatory biomarkers and progression of diabetic kidney disease

Abstract Background and Aims Diabetic kidney disease (DKD) is one of the fastest growing causes of chronic kidney disease and associated morbidity and mortality. Previous studies have demonstrated the involvement of inflammation in the progression of kidney damage. The aim of our study was to evaluate potential therapeutic approaches using inflammatory biomarkers to assess DKD progression. Method A total of 499 patients with DT1 and DT2, aged 34 to 84 years (60 [60;72]), were examined. All patients underwent standard clinical and laboratory examination, with an assessment of the levels of the inflammatory biomarkers (FGF-23, TNF-α, VEGF-A, hsCRP, Il-6) in baseline plasma samples. Renal function was assessed based on the levels of serum creatinine, eGFR and albumin/creatinine ratio. Control group included 65 people the same age without diabetes. Results We divided all patients into two groups according to the presence DKD. The levels of FGF-23 (p &amp;lt; 0.001), TNF-α (p = 0.014), VEGF-A (p = 0.006), hsCRP (p &amp;lt; 0.001), Il-6 (p &amp;lt; 0.001) were significantly higher in patients with DKD than in control group. A predictive model was developed to estimate the probability of DKD depending on VEGF-A, FGF-23, TNF-α, Il-6, hsCRP, age, duration of diabetes, systolic blood pressure, HbA1c, LDL-C, using binary logistic regression. The resulting regression model was statistically significant (p &amp;lt; 0.001). Based on the value of Nagelkerke R², the model explained 79.5% of the observed DKD variance. 1 pmol/l increase of FGF-23 was associated with 1.921 times increase in DKD odds. 1 pg/ml increase of TNF-α was associated with 1.092 times decrease in DKD odds. 1 mg/ml increase of Il-6 was associated with 1.612 times increase in DKD odds. 1 mg/l increase of hsCRP was associated with 1.496 times increase in DKD odds. Conclusion Our study identifies FGF-23, TNF-α, Il-6, hsCRP as promising targets of novel therapeutic interventions in patients with diabetes, which should be investigated in future clinical trials.

#909 Role of cystatin C in the development and progression of chronic heart failure in patients with diabetes

Abstract Background and Aims It has been known that cystatin C is a marker for early prediction of renal function. In recent years, studies have shown that cystatin C plays an important role in predicting new or worsening cardiovascular diseases. The aim of our study was to investigate the role of cystatin C in the development and progression of chronic heart failure (CHF) in patients with diabetes. Method A total of 499 patients with DT1 and DT2, aged 34 to 84 years (60 [60; 72]), were examined. All patients underwent standard clinical and laboratory examination, with an assessment of the levels of the natriuretic peptides (BNP and NTproBNP) in baseline plasma samples. Renal function was assessed based on the levels of serum creatinine and cystatin C. Patients were divided into quartiles according to cystatin C levels: Q1 &amp;lt;0.78 mg/l, Q2 0.78-0.92 mg/l, Q3 0.93-1.38 mg/l, Q4 &amp;gt;1.38 mg/l. Results Significant differences in the levels of BNP and NTproBNP were observed in patients with diabetes with cystine C levels ≥0.93 mg/l (32.20 [19.85; 69.35] pg/ml and 104.25 [57.70; 210.08] ng/l, respectively). There were significant correlations between cystatin C and the levels of BNP (r = 0.56, p &amp;lt; 0.05) and NTproBNP (r = 0.58, p &amp;lt; 0.05). Logistic regression analysis showed the prognostic value of cystatin C, and not creatinine, as a predictor of heart failure in patients with diabetes and GFR&amp;gt;60 ml/min/1.73 m2 (1 mg/l increase of cystatin C was associated with 7.085 times increase in CHF odds). ROC analysis revealed that the level of cystatin C ≥0.96 mg/l with a sensitivity of 84% and specificity of 75% predicted increased BNP and NTproBNP in patients with diabetes (ROC AUC = 0.844). Conclusion Cystatin C level could be used as a predictive indicator of CHF in patients with diabetes and GFR&amp;gt;60 ml/min/1.73 m2.

Plasma pTau181 and pTau217 predict asymptomatic amyloid accumulation equally well as amyloid PET.

The dynamic phase of preclinical Alzheimer's disease, as characterized by accumulating cortical amyloid-β, is a window of opportunity for amyloid-β-lowering therapies to have greater efficacy. Biomarkers that accurately predict amyloid-β accumulation may be of critical importance for participant inclusion in secondary prevention trials and thus enhance development of early Alzheimer's disease therapies. We compared the abilities of baseline plasma pTau181, pTau217 and amyloid-β PET load to predict future amyloid-β accumulation in asymptomatic elderly. In this longitudinal cohort study, baseline plasma pTau181 and pTau217 were quantified using single molecule array assays in cognitively unimpaired elderly selected from the community-recruited F-PACK cohort based on the availability of baseline plasma samples and longitudinal amyloid-β PET data (median time interval = 5 years, range 2-10 years). The predictive abilities of pTau181, pTau217 and PET-based amyloid-β measures for PET-based amyloid-β accumulation were investigated using receiver operating characteristic analyses, correlations and stepwise regression analyses. We included 75 F-PACK subjects (mean age = 70 years, 48% female), of which 16 were classified as amyloid-β accumulators [median (interquartile range) Centiloid rate of change = 3.42 (1.60) Centiloids/year). Plasma pTau181 [area under the curve (95% confidence interval) = 0.72 (0.59-0.86)] distinguished amyloid-β accumulators from non-accumulators with similar accuracy as pTau217 [area under the curve (95% confidence interval) = 0.75 (0.62-0.88) and amyloid-β PET [area under the curve (95% confidence interval) = 0.72 (0.56-0.87)]. Plasma pTau181 and pTau217 strongly correlated with each other (r = 0.93, Pfalse discovery rate < 0.001) and, together with amyloid-β PET, similarly correlated with amyloid-β rate of change (r pTau181 = 0.33, r pTau217 = 0.36, r amyloid-β PET = 0.35, all Pfalse discovery rate ≤ 0.01). Addition of plasma pTau181, plasma pTau217 or amyloid-β PET to a linear demographic model including age, sex and APOE-ε4 carriership similarly improved the prediction of amyloid-β accumulation (ΔAkaike information criterion ≤ 4.1). In a multimodal biomarker model including all three biomarkers, each biomarker lost their individual predictive ability. These findings indicate that plasma pTau181, plasma pTau217 and amyloid-β PET convey overlapping information and therefore predict the dynamic phase of asymptomatic amyloid-β accumulation with comparable performances. In clinical trial recruitment, confirmatory PET scans following blood-based prescreening might thus not provide additional value for detecting participants in these early disease stages who are destined to accumulate cortical amyloid-β. Given the moderate performances, future studies should investigate whether integrating plasma pTau species with other factors can improve performance and thus enhance clinical and research utility.