Composite Risk Score Research Articles

Multigene Copy Number Alteration Risk Score Biomarker-Based Enrichment Study Designs in Metastatic Castrate-Resistant Prostate Cancer.

A composite multigene risk score derived from tumor-biology alterations specific to metastatic castrate-resistant prostate cancer (mCRPC) state was evaluated as a classifier to design biomarker-based enrichment clinical trials. A plasma cell-free DNA copy number alteration risk score based on alterations in 24 genes was simulated to develop a biomarker classifier-based clinical trial design enriched for high-risk patients to detect a survival advantage of a novel treatment (hazard ratio of 0.70 with 80% power). We determined the design trade-offs between the number of patients screened and enrolled when varying the type of patients to enrich and the extent of enrichment needed. For a 2-year overall survival end point in mCRPC state, fully enriching patients with mCRPC having a high-risk score of 3 or more (the 95th percentile of a range of risk scores in patients with mCRPC) was determined to require screening to a maximum of 4,149 patients to enroll 259 patients for the targeted effect size. A nonenriched trial was determined to require enrolling 689 patients to be equivalently powered. We identified a pragmatic alternative, which is to enrich patients with mCRPC with a risk score of 1 or more (the 67th percentile) and an enrichment fraction of 0.25. This would require screening 658 patients to enroll 584 patients, and it maximizes the ability to detect a difference in treatment effect by risk score. A plasma multi-CNA risk score classifier can feasibly be leveraged to design an enrichment trial in mCRPC. Enriching 25% of patients screened with a risk score >1 was observed to be optimal for obtaining an adequately powered, biomarker-based mCRPC-enriched clinical trial.

Abstract 4123804: Joint associations of sleep and daily step count with cardiometabolic health markers: a pooled analysis of the ProPASS consortium

Background: Poor sleep and physical inactivity are lifestyle-related behaviors that impact cardiometabolic health, but there is limited insight into their combined association with cardiometabolic markers. Aims: This study investigated the joint association of device-measured sleep patterns (regularity and duration) and daily step counts with cardiometabolic biomarkers. Methods: Harmonized individual participant data of 12,223 adults (mean±SD age:54.6±9.5 years; 54.8% female) from the pooled Prospective Physical Activity, Sitting and Sleep consortium (ProPASS), comprising six cohorts with thigh-worn accelerometry data were analysed. Sleep regularity was assessed using the validated Sleep Regularity Index (SRI, range 0-100), quantifying day-to-day sleep consistency. We used generalized linear models to examine cross-sectional joint associations between sleep patterns, regularity (SRI tertiles ≤75.8, low; 75.8-84.5, medium; >84.5, high) and duration (<7h, short; 7-8h, adequate; >8h, long), and daily step counts (step tertiles <8488, low; 8488-11601, medium; >11601, high steps/day) with a composite cardiometabolic health score and individual biomarkers, including BMI, waist circumference, total cholesterol, HDL cholesterol, triglycerides, and HbA1c. Results: Lower sleep regularity, deviation from adequate sleep, along with lower step counts were adversely associated with the composite cardiometabolic health risk score. Compared to optimal sleep patterns (SRI>84.5 or 7-8h/day) and high step groups, low sleep regularity and short sleep duration were separately associated with the least favourable composite cardiometabolic health (z-score [95%CI] 0.32 [0.28,0.37] and 0.25 [0.21,0.29], respectively) among participants with low volume of steps. Low sleep regularity and low daily steps were jointly associated with higher BMI (2.98 [2.67,3.29] kg/m 2 ), waist circumference (8.61 [7.81,9.4] cm), total cholesterol (0.15 [0.08,0.23] mmol/L), and lower HDL levels (0.17 [0.14,0.2] mmol/L), regardless of sleep duration. For short/long sleep duration and low daily step count, such associations were only evident in BMI and waist circumference. Conclusions: Our findings suggest that the potential deleterious associations of irregular or inadequate sleep duration with cardiometabolic health outcomes may be exaggerated by lower daily step counts. Future studies should examine the prospective joint association of sleep patterns and physical activity on cardiometabolic health.

RADT-03. CONTRAST-ENHANCING LESIONS INDUCED BY CNS-DIRECTED INTENSITY MODULATED PROTON THERAPY: DEMOGRAPHIC AND CARDIOVASCULAR RISK FACTORS ANALYSIS

Abstract INTRODUCTION Lesions exhibiting radiation-induced contrast enhancement (RICE) may develop following cranial intensity modulated proton therapy (IMPT). The mechanisms underlying their development may be shared or amplified by existing patient comorbidities. The objective of this study was to assess a potential relationship between individual or composite cardiovascular risk criteria and RICE development, independent of dosimetric considerations. METHODS Data were reviewed for patients treated at a single tertiary care institution between 2017-2023. Time to RICE development was assessed using Kaplan-Meier. Cox regression analysis was used to determine hazard ratios (HRs) with 95% confidence intervals (CIs). Host-related risk factors for RICE development were assessed in a univariable analysis (UVA). A binary logistic regression model was built to ascertain the effects of age and cardiovascular risk factors on the likelihood of developing RICE (expressed as QRISK3 relative risk). RESULTS The study cohort included 137 patients; the median age was 40 years (range: 1-85), 51% female, and 53% Hispanic. Cardiovascular risk factors included smoking (18% past, 6% current), diabetes (7%), hypertension (22%), dyslipidemia (15%) and high body mass index (BMI, 50% were obese with BMI>25). At a median follow-up of 3 years, RICE developed in 36 (26%) patients. On UVA, RICE development was only associated with age ≥18 compared to <18 (HR 3.3, 95% CI: 1.2-9.4, p=0.024). None of the other evaluated risk factors were significantly associated with RICE (p>0.05). Additionally, logistic regression analysis showed increasing age was associated with likelihood of developing RICE (χ2=6.95, p=0.031), while QRISK3 score was not. CONCLUSIONS In this contemporary series of patients treated with IMPT, age was the only host factor associated with RICE, while other cardiovascular risk factors, evaluated individually or using established composite risk scores (QRISK3) were not associated with RICE. Additional research is needed to identify potential patient characteristics associated with RICE.

The impact of maternal vulnerability on stress biomarkers and first-trimester growth: the Rotterdam Periconceptional Cohort (Predict Study).

Is the degree of maternal vulnerability positively associated with stress biomarkers (stress hormones, C-reactive protein, tryptophan metabolites, and one-carbon metabolites), and does long-term exposure to stress hormones reduce first-trimester growth? The maternal vulnerability risk score is positively associated with concentrations of hair cortisol and cortisone and negatively with tryptophan, while higher hair cortisol concentrations are associated with reduced first-trimester growth without mediation of tryptophan. A high degree of maternal vulnerability during the periconception period is associated with impaired first-trimester growth and pregnancy complications, with consequences for long-term health of the child and future life course. However, due to the challenges of early identification of vulnerable women, the uptake of periconception care is low in this target group. Between June 2022 and June 2023, this study was conducted in a sub-cohort of 160 pregnant women participating in the Rotterdam Periconceptional Cohort (Predict Study), an ongoing prospective tertiary hospital-based cohort. One hundred and thirty-two women with ongoing pregnancies and available stress biomarker data were included in the analysis. Data on periconceptional social, lifestyle, and medical risk factors were collected via self-administered questionnaires, and these factors were used for the development of a composite maternal vulnerability risk score. Stress biomarkers, including stress hormones (hair cortisol and cortisone) and inflammatory and oxidative stress biomarkers (C-reactive protein, total homocysteine, and tryptophan metabolites) were determined in the first trimester of pregnancy. First-trimester growth was assessed by crown-rump length (CRL) and embryonic volume (EV) measurements at 7, 9, and 11 weeks gestation by making use of an artificial intelligence algorithm and virtual reality techniques using 3D ultrasound data sets. The associations between the maternal vulnerability risk score and stress biomarkers were identified using linear regression models, and between stress hormones and CRL- and EV-trajectories using mixed models. A mediation analysis was performed to assess the contribution of tryptophan. All associations were adjusted for potential confounders, which were identified using a data-driven approach. Several sensitivity analyses were performed to check the robustness of the findings. The maternal vulnerability risk score was positively associated with concentrations of hair cortisol and cortisone (pg/mg) (β = 0.366, 95% CI = 0.010-0.722; β = 0.897, 95% CI = 0.102-1.691, respectively), and negatively with tryptophan concentrations (µmol/L) (β = -1.637, 95% CI = -2.693 to -0.582). No associations revealed for C-reactive protein and total homocysteine. Higher hair cortisol concentrations were associated with reduced EV-trajectories (3√EV: β = -0.010, 95% CI = -0.017 to -0.002), while no associations were found with CRL-trajectories. Mediation by tryptophan was not shown. Residual confounding cannot be ruled out, and the external validity may be limited due to the study's single-center observational design in a tertiary hospital. There is mounting evidence that a high degree of maternal vulnerability negatively affects maternal and perinatal health, and that of the future life course. The results of our study emphasize the need to identify highly vulnerable women as early as possible, at least before conception. Our findings suggest that the chronic stress response and alterations of the maternal tryptophan metabolism are involved in maternal vulnerability, affecting first-trimester growth, with potential impact on the long-term health of the offspring. This study was funded by the Departments of Obstetrics and Gynecology and Clinical Chemistry of the Erasmus MC, University Medical Center, Rotterdam, the Netherlands, and the Junior Award granted by the De Snoo-van 't Hoogerhuijs Foundation in March 2022. There are no conflicts of interest. N/A.

Genetic Risk, Health-Associated Lifestyle, and Risk of Early-onset Total Cancer and Breast Cancer.

Early-onset cancer (diagnosed under age 50) generally manifests as an aggressive disease phenotype. The association between healthy lifestyle and early-onset cancer and whether it varies by common genetic variants remains unclear. We analyzed a prospective cohort of 66,308 participants who were under age 50 and free of cancer at baseline in the UK Biobank. Using Cox regression, we estimated Hazard ratios (HRs) and 95% confidence intervals (CIs) for early-onset total and breast cancer based on sex-specific composite total cancer polygenic risk scores (PRSs), a breast cancer-specific PRS, and sex-specific health-associated lifestyle scores (HLSs). In multivariable-adjusted analyses with 2-year latency, higher genetic risk (highest vs lowest tertile of PRS) was associated with significantly increased risks of early-onset total cancer in females (HR, 95% CI: 1.83, 1.49-2.26) and males (2.03, 1.51-2.73) as well as early-onset breast cancer in females (3.06, 2.20-4.26). An unfavorable lifestyle (highest vs lowest category of HLS) was associated with higher risk of total cancer and breast cancer in females across genetic risk categories; the association with total cancer and breast cancer was stronger in the highest genetic risk category than the lowest: HRs (95% CIs) were 1.55 (1.12, 2.14) and 1.69 (1.11, 2.57) in the highest genetic risk category and 1.03 (0.64, 1.67) and 0.81 (0.36, 1.85) in the lowest. Genetic and lifestyle factors were independently associated with early-onset total and breast cancer risk. Individuals with a high genetic risk may benefit more from adopting a healthy lifestyle in preventing early-onset cancer.

Associations between habitual sleep characteristics and cardiometabolic disease risk in corporate executives

ObjectivesCorporate executive job demands may lead to poor sleep habits, increasing their risk for cardiometabolic disease. This study aimed to describe and explore associations between objectively measured habitual sleep characteristics and cardiometabolic disease risk of corporate executives, while accounting for occupational, psychological, and lifestyle factors. MethodsHabitual sleep was measured using wrist-worn actigraphy and a sleep diary over seven consecutive days in 61 (68.3% men) corporate executives aged 46.4 ± 8.7years. A composite cardiometabolic disease risk score was determined using body mass index, waist circumference, blood pressure and fasting glucose and lipid concentrations. Prediction models were built using a backward stepwise selection approach to explore associations between sleep characteristics and cardiometabolic disease risk factors adjusting for occupational, psychological, and lifestyle covariates. ResultsAverage total sleep time was 6.60 ± 0.75 hours, with 51.7% of participants reporting poor sleep quality and 26.2% extending their weekend sleep. Adjusted models showed that lower sleep efficiency (β = −0.25, 95%CI: −0.43; −0.08, P = .006), shorter weekday total sleep time (β = −1.37, 95% CI: −2.41, −0.32; P = .011) and catch-up sleep (β = 0.84, 95%CI: 0.08, 1.60, P = .002) were associated with higher cardiometabolic disease risk scores. Adjusted models also found that shorter average time-in-bed (ß=−2.00, 95%CI: −3.76; −0.18, P = .031), average total sleep time (ß=1.98, 95%CI: −3.70; −0.25, P = .025) and weekday total sleep time (β = −2.13, 95%CI: −3.56; −0.69, P = .025) as well as catch-up sleep (β = 1.67, 95% CI: 0.52; 2.83; P = .012) were all associated with a higher body mass index. ConclusionCorporate executives who compromise sleep duration during the working week may increase their risk for obesity and future cardiometabolic disease.

A genome-wide association study identifies novel loci of vertigo in an Asian population-based cohort

The contributing genetic factors of vertigo remain poorly characterized, particularly in individuals of non-European ancestries. Here we show the genetic landscape of vertigo in an Asian population-based cohort. In a two-stage genome-wide association study (Ncase = 6199; Ncontrol = 54,587), we identify vertigo-associated genomic loci in DROSHA and ZNF91/LINC01224, with the latter replicating the findings in European ancestries. Gene-based association testing corroborates these findings. Interestingly, both genes are enriched in cerebellum, a key structure receiving sensory input from the vestibular system. Subjects carrying risk alleles from lead SNPs of DROSHA and ZNF91 incur a 1.74-fold risk of vertigo than those without. Moreover, composite clinical-polygenic risk scores allow differentiation between patients and controls, yielding an area under receiver operating characteristic curve of 0.69. This study identified novel genomic loci for vertigo in an Asian population-based cohort, which may help identifying high risk subjects and provide mechanistic insight in understanding the pathogenesis of vertigo.

Cardiac Biomarkers are Associated with Incident Fracture Risk in Advanced Chronic Kidney Disease

Cardiovascular disease is associated with increased fracture risk in the general population. Few data exist on the association between cardiovascular health and incident fracture risk in patients with advanced CKD, a high-risk population for fractures. We aimed to assess the link between fracture risk and cardiovascular health in a prospective cohort of 210 patients with CKD stage G4–5. Incident fractures were recorded during a prospective follow-up of 5 years. Laboratory parameters, abdominal aortic calcification score, echocardiography, ultrasound assessment of brachial artery flow-mediated dilatation and carotid intima-media thickness, and maximal stress ergometry were obtained at baseline. A total of 51 fractures were observed in 40 (19%) patients during follow-up. In separate multivariable Cox proportional hazards models adjusted for age, gender, and baseline eGFR, TnT (HR 1.007, CI 95% 1.003–1.010, p < 0.001) and ProBNP (HR 1.000, CI 95% 1.000–1.000, p = 0.017) were associated with incident fractures and the association persisted after adjusting for coronary artery disease (CAD). The patients unable to perform the ergometry test had a higher risk of incident fractures compared to others (36.1% vs 15.5%, p = 0.009). A cardiovascular composite risk score summarizing TnT, ProBNP, and ergometry data was independently associated with incident fractures in a multivariable Cox model (HR 1.373, CI 95% 1.180–1.599, p < 0.001). Patients with the lowest score were observed with no fractures, while patients with the highest score were observed with a fracture risk of 40.5% during follow-up. Risk of incident fractures is associated with biomarkers of cardiovascular health and a composite cardiovascular risk score in patients with advanced CKD.

Early pregnancy HbA1c as the first screening test for gestational diabetes: results from three prospective cohorts

More than 90% of gestational diabetes cases are estimated to occur in low-income and middle-income countries (LMICs). Most current guidelines recommend an oral glucose tolerance test (OGTT) at 24-28 weeks of gestation. The OGTT is burdensome, especially in LMICs, resulting in a high proportion of women not being screened. We aimed to develop a simple and effective screening strategy for gestational diabetes. STRiDE, a prospective cohort study, was set up in seven centres in south India and seven centres in western Kenya, and included pregnant women aged 18-50 years of age and at less than 16 weeks of gestation (<20 weeks in Kenya), confirmed by dating ultrasound. We assessed the efficacy of early pregnancy HbA1c (venous and capillary point-of-care), either alone or as part of a composite risk score with age, BMI, and family history of diabetes, in predicting gestational diabetes at 24-28 weeks of gestation, in two LMICs (India and Kenya) and in a UK multi-ethnic population from the PRiDE study. A key secondary outcome was to assess whether an early pregnancy composite risk score can reduce the need for OGTTs. Gestational diabetes was diagnosed using current WHO criteria. Between Feb 15, 2016, Dec 13, 2019, we enrolled 3070 participants in India and 4104 in Kenya. 4320 participants were included from the PRiDE cohort. Gestational diabetes prevalence by OGTT at 24-28 weeks was 19·2% in India, 3·0% in Kenya, and 14·5% in the UK. Early pregnancy HbA1c was independently associated with incidence of gestational diabetes at 24-28 weeks of gestation. Adjusted risk ratios were 1·60 (95% CI 1·19-2·16) in India, 3·49 (2·8-4·34) in Kenya, and 4·72 (3·82-5·82) in the UK. Composite risk score models that combined venous or point-of-care HbA1c with age, BMI, and family history of diabetes best predicted testing positive for gestational diabetes. A population-specific, two-threshold screening strategy of rule-in and rule-out gestational diabetes using early pregnancy composite risk score could reduce the requirement of OGTTs by 50-64%. For the HbA1c-alone model, the thresholds were 5·4% (rule in) and 4·9% (rule out) in India, 6·0% (rule in) and 5·2% (rule out) in Kenya, and 5·6% (rule in) and 5·2% (rule out) in the UK. Early pregnancy HbA1c offers a simple screening test for gestational diabetes, allowing those at highest risk to receive early intervention and greatly reduce the need for OGTTs. This can also be carried out using point-of-care HbA1c in LMICs. UK Medical Research Council and the Indian Department of Biotechnology.

Socioeconomic Status and Clinical Outcomes in Chronic Kidney Disease: Bootstrap Validation of a Simple Indicator.

Background: Chronic Kidney Disease (CKD) is a complex health condition that interacts significantly with socioeconomic determinants, particularly income status and education. This study developed a simple indicator of socioeconomic status (SES), which is composed of income status and education in CKD patients, and evaluated its impact on health outcomes in this population. Methods: This study was conducted on 561 CKD patients, stages 2-5. The composite SES score was developed by combining the regression coefficients of income and education as predictors of the study endpoint in a multivariable Cox model, normalizing these coefficients to derive weights, and then using these weights to calculate an individual percentage score based on each person's income and education. The composed SES indicator was internally validated through bootstrap analysis. Over a median follow-up time of 36 months, we tracked all-cause death and non-fatal cardiovascular events. Results: Both lack of income (p = 0.020) and low educational level (p = 0.034) were independently related to the combined endpoint. Based on these covariates' regression coefficients, a composite socioeconomic score considering income and educational level was generated. In a Cox regression model, a 10% increase in this composite risk score entailed a 25% increase in the hazard ratio (HR) of the combined endpoint [HR (10% increase): 1.25], and the internally validated 95% CI ranged from 1.14 to 1.41 (p < 0.001). Conclusions: This study underscores the significant impact of a simple, bootstrap-validated composite SES indicator on CKD patients' health outcomes. These findings highlight the importance of considering education and socioeconomic factors in managing and treating CKD patients and inform future research and policy considerations for this population.

Protocol for a Study Investigating Context-Specific Sedentary Behaviors and Cardiometabolic Health in College-Based Young Adults (CONTEXT-SB).

Sedentary behavior (SB) is detrimental to cardiometabolic disease (CMD) risk, which can begin in young adulthood. To devise effective SB-CMD interventions in young adults, it is important to understand which context-specific sedentary behaviors (CS-SB) are most detrimental for CMD risk, the lifestyle behaviors that co-exist with CS-SBs, and the socioecological predictors of CS-SB. This longitudinal observational study will recruit 500 college-aged (18-24 years) individuals. Two laboratory visits will occur, spaced 12 months apart, where a composite CMD risk score (e.g., arterial stiffness, metabolic and inflammatory biomarkers, heart rate variability, and body composition) will be calculated, and questionnaires to measure lifestyle behaviors and different levels of the socioecological model will be administered. After each visit, total SB (activPAL) and CS-SB (television, transportation, academic/ occupational, leisure computer, "other"; ecological momentary assessment) will be measured across seven days. It is hypothesized that certain CS-SB will show stronger associations with CMD risk, compared to T-SB, even after accounting for coexisting lifestyle behaviors. It is expected that a range of intra-individual, inter-individual, and physical environment socioecological factors will predict CS-SB. The findings from this study will support the development of an evidence-based, multi-level intervention to target SB reduction and mitigate CMD risk in CBYA.

Associations between obesity, a composite risk score for probable long COVID, and sleep problems in SARS-CoV-2 vaccinated individuals

BackgroundPreliminary data suggests that obesity might hasten the decline in mRNA vaccine-induced immunity against SARS-CoV-2. However, whether this renders individuals with obesity more susceptible to long COVID symptoms post-vaccination remains uncertain. Given sleep’s critical role in immunity, exploring the associations between obesity, probable long COVID symptoms, and sleep disturbances is essential.MethodsWe analyzed data from a survey of 5919 adults aged 18 to 89, all of whom received two SARS-CoV-2 mRNA vaccinations. Participants were categorized into normal weight, overweight, and obesity groups based on ethnicity-specific BMI cutoffs. The probability of long COVID was evaluated using the Post-Acute Sequelae of SARS-CoV-2 (PASC) score, as our survey did not permit confirmation of acute SARS-CoV-2 infection through methods such as antibody testing. Additionally, sleep patterns were assessed through questionnaires.ResultsParticipants with obesity exhibited a significantly higher adjusted odds ratio (OR) of having a PASC score of 12 or higher, indicative of probable long COVID in our study, compared to those with normal weight (OR: 1.55, 95% CI: 1.05, 2.28). No significant difference was observed for overweight individuals (OR: 0.92 [95% CI: 0.63, 1.33]). Both obesity and probable long COVID were associated with increased odds of experiencing a heightened sleep burden, such as the presence of obstructive sleep apnea or insomnia (P < 0.001). However, no significant interaction between BMI and probable long COVID status was found.ConclusionsEven post-vaccination, individuals with obesity may encounter a heightened risk of experiencing prolonged COVID-19 symptoms. However, confirming our observations necessitates comprehensive studies incorporating rigorous COVID infection testing, such as antibody assays - unavailable in our anonymous survey. Additionally, it is noteworthy that the correlation between probable long COVID and sleep disturbances appears to be independent of BMI.

Exploring associations between eating habits, gastrointestinal health and perceived stress and anxiety symptoms in adults

Gastrointestinal (GI) disorders are becoming increasingly common in young people in India and globally (1). Diet (eating habits, nutrient intake, and dietary diversity) and mental health (stress and anxiety levels) factors can independently and synergistically regulate gut health through dietary modulation of gut microbiota composition and gut-brain axis-related mechanistic pathways (2-3). However, few studies have investigated the associations between diet, mental health, and GI-related disturbances. Hence, this observational study was conducted to explore the possible effects of eating behaviors and stress and anxiety symptoms on self-reported measures of gastrointestinal health among 18-45-year-old adults in India.A purposive cluster sampling method guided the recruitment of participants (n=407). Two non- consecutive day 24-hour diet recalls were conducted to estimate nutrient intakes and calculate Individual Diet Diversity (IDD) and Food Variety Scores (FVS). Gastrointestinal health was assessed using a validated instrument comprising 35 items related to gastric, small intestine, and colon function, and GI inflammation. Perceived Stress Scale (PSS-10 scores 0 to 40 with higher scores representing higher levels of stress), and Generalized Anxiety Disorder Scale (GAD-7 scores &gt;5 (mild), &gt;10 (moderate), and &gt;15 (severe)) were used to evaluate perceived stress and anxiety (4-5). Socioeconomic status and eating habits were self-reported and the anthropometry measurements were recorded. Multivariable logistic regression analysis was performed using sociodemographic characteristics, anthropometry measurements, eating habits, and stress and anxiety levels as independent (predictor) variables, and composite gastrointestinal health risk scores as the dependent variables.Participants reported mild anxiety (mean (M) = 7.09, standard deviation (SD)= 3.25) and moderate stress (M=18.44; SD= 9.89) with preponderance among females, higher age groups (&gt; 35 years), and lower socioeconomic status. Overall, 38.8% and 45.3% were at high-risk score categories for gastric function and GI inflammation respectively. Higher energy and fat consumption, frequent breakfast skipping, and lower IDDS and FVS scores were associated with higher scores for stress and anxiety. Moreover, participants having moderate to severe anxiety reported a higher frequency of GI symptoms such as indigestion (M= 3.23 SD= 2.1-4.6, p= 0.023), excessive belching (M= 2.36 SD =1.21, p=0.043), and post-meal lower abdominal discomfort and cramps (M= 3.07, SD = 2.22, p &lt; 0.001) as compared to those having nominal/mild anxiety. Age-adjusted regression models showed higher waist circumference (OR= 4.69, 95% CI =1.33- 7.28, p= 0.034), and stress scores (OR= 1.66, 95% CI= 1.32-1.90, p = 0.042), lower IDDS (OR= 2.34, 95% CI=1.80- 2.91, p &lt;0.001) and presence of &gt; 2 co-morbid conditions (OR= 8.12, 95% CI = 5.34- 11.21, p &lt; 0.001) as predictors of higher GI disorder risk scores.The preliminary findings of the study highlight associations between diet, stress, and GI health, presenting opportunities to modulate diet and optimize mental health to prevent and reduce the severity of GI disorders.

Anthropometric Profile, Overweight/Obesity Prevalence, and Socioeconomic Impact in Moroccan Children Aged 6-12 Years Old with Autism Spectrum Disorder.

In addition to the inherent challenges of their condition, children with autism spectrum disorder (ASD) are also susceptible to the global obesity epidemic. However, concerning the prevalence of obesity within the Moroccan ASD pediatric population, data remain scarce. A total of 258 children (boys = 195) aged 6 to 12 years old (mean = 9.4 ± 1.4) diagnosed with ASD participated in this study. Besides the body mass and height, four significant anthropometric markers for assessing obesity were examined: body mass index (BMI), body surface area (BSA), waist circumference (WC), and waist-to-height ratio (WHtR). Each anthropometric marker was categorized into one of three cardiometabolic risk levels based on the Z-scores and their corresponding percentiles. The distribution was as follows: low risk (≤84th percentile), high risk (85th-94th percentile), and very high risk (≥95th percentile). Subsequently, a multiple regression analysis was employed to develop an algorithm that generates a composite risk score. This score incorporates all the anthropometric variables simultaneously, while also weighting their individual contributions to the cardiometabolic risk. Children with ASD exhibit an anthropometric profile that markedly increases their susceptibility to cardiometabolic issues. While roughly 11% of the general Moroccan child population is overweight or obese, this figure soars to nearly 60% among children with ASD when considering the central adiposity markers. Furthermore, children from middle-class socioeconomic backgrounds display a more than threefold greater risk of developing overweight or obesity compared to their counterparts from lower socioeconomic backgrounds. This study has, for the first time, provided an up-to-date overview of the cardiometabolic risk in Moroccan children with ASD using traditional anthropometric measurements. The primary risk factor is clearly linked to central (abdominal) adiposity, which is recognized as the most deleterious. This study highlights the need to include general and central obesity markers. This study underscores the importance of incorporating both general and central adiposity markers for a more comprehensive assessment, and it emphasizes the need for closer monitoring within this high-risk population.

Prenatal Exposure to Chemical Mixtures and Metabolic Syndrome Risk in Children

Prenatal exposure to ubiquitous endocrine-disrupting chemicals (EDCs) may increase the risk of metabolic syndrome (MetS) in children, but few studies have studied chemical mixtures or explored underlying protein and metabolic signatures. To investigate associations of prenatal exposure to EDC mixtures with MetS risk score in children and identify associated proteins and metabolites. This population-based, birth cohort study used data collected between April 1, 2003, and February 26, 2016, from the Human Early Life Exposome cohort based in France, Greece, Lithuania, Norway, Spain, and the UK. Eligible participants included mother-child pairs with measured prenatal EDC exposures and complete data on childhood MetS risk factors, proteins, and metabolites. Data were analyzed between October 2022 and July 2023. Nine metals, 3 organochlorine pesticides, 5 polychlorinated biphenyls, 2 polybrominated diphenyl ethers (PBDEs), 5 perfluoroalkyl substances (PFAS), 10 phthalate metabolites, 3 phenols, 4 parabens, and 4 organophosphate pesticide metabolites measured in urine and blood samples collected during pregnancy. At 6 to 11 years of age, a composite MetS risk score was constructed using z scores of waist circumference, systolic and diastolic blood pressures, triglycerides, high-density lipoprotein cholesterol, and insulin levels. Childhood levels of 44 urinary metabolites, 177 serum metabolites, and 35 plasma proteins were quantified using targeted methods. Associations were assessed using bayesian weighted quantile sum regressions applied to mixtures for each chemical group. The study included 1134 mothers (mean [SD] age at birth, 30.7 [4.9] years) and their children (mean [SD] age, 7.8 [1.5] years; 617 male children [54.4%] and 517 female children [45.6%]; mean [SD] MetS risk score, -0.1 [2.3]). MetS score increased per 1-quartile increase of the mixture for metals (β = 0.44; 95% credible interval [CrI], 0.30 to 0.59), organochlorine pesticides (β = 0.22; 95% CrI, 0.15 to 0.29), PBDEs (β = 0.17; 95% CrI, 0.06 to 0.27), and PFAS (β = 0.19; 95% CrI, 0.14 to 0.24). High-molecular weight phthalate mixtures (β = -0.07; 95% CrI, -0.10 to -0.04) and low-molecular weight phthalate mixtures (β = -0.13; 95% CrI, -0.18 to -0.08) were associated with a decreased MetS score. Most EDC mixtures were associated with elevated proinflammatory proteins, amino acids, and altered glycerophospholipids, which in turn were associated with increased MetS score. This cohort study suggests that prenatal exposure to EDC mixtures may be associated with adverse metabolic health in children. Given the pervasive nature of EDCs and the increase in MetS, these findings hold substantial public health implications.

#1985 Tocilizumab in chronic active antibody-mediated rejection: a randomized controlled open-label multi-center trial (INTERCEPT study)

Abstract Background and Aims Chronic active antibody mediated graft rejection (caAMR) caused by immune-mediated injury is the leading cause of long-term graft loss in kidney transplant recipients. Nevertheless, no effective treatment exists for caAMR to date, highlighting a great unmet need for evaluation of novel treatment options. Recently, tocilizumab (TCZ), a monoclonal antibody directed against the human interleukin-6 (IL-6) receptor, by antagonizing IL-6-triggered inflammation and B cell/plasma cell-driven immune activation, has shown promise in the treatment of caAMR. However, TCZ has not been assessed systematically in a randomized study. The INTERCEPT study aims to evaluate the efficacy of addition of TCZ to standard of treatment (SOC) as compared to SOC alone in reducing the decline of graft function from baseline at 24 months after start of treatment as assessed by estimated glomerular filtration rate (eGFR) in kidney transplant recipients with caAMR. Method This ongoing randomized controlled open-label multi-center investigator-initiated trial plans to include a total of 50 adult kidney transplant recipients with biopsy-proven caAMR using Banff 2019 criteria at least 12 months after transplantation and eGFR ≥20 ml/min/1.73 m2. Any subject who underwent kidney transplantation in Sweden or is currently living in Sweden and being followed up at any of the Swedish transplant centers or their affiliated regional centers can be considered for participation. Participants are randomized to receive either TCZ (n=25) added to our standard of care (SOC) maintenance treatment or SOC alone (n=25) for a period of 24 months and followed for additional 12 months after cessation of the study medication. After the inclusion transplant biopsy at baseline, protocol biopsies are performed at 12 and 24 months. The study design flow-chart is shown in the Figure. The primary endpoint is the slope of eGFR at 24 months after start of treatment. The eGFR is assessed using Modification of Diet in Renal Disease (MDRD) formula. The secondary endpoints include assessment of the following at 12, 24 and 36 months: composite risk score iBox, safety, evolution and characteristics of donor-specific antibodies (DSA), graft histology, proteinuria, kidney function assessed by measured GFR (mGFR), patient- and death-censored graft survival, patient-reported outcomes that include transplant-specific well-being, adherence to immunosuppressive medications and perceived threat of the risk of graft rejection. Results We expect that addition of TCZ to SOC will slow down the decline of graft function in kidney transplant recipients with caAMR. Conclusion Currently there is no effective treatment for caAMR. Based on the hypothesis that inhibition of IL-6 by TCZ will reduce antibody production and reduce antibody-mediated damage, our randomized trial has a potential to provide evidence for a novel treatment strategy for caAMR. If TCZ is found to be effective, our study has the potential to improve long-term graft survival and quality of life, reduce morbidity and mortality in kidney transplant patients as well as lower the health care costs.

Abstract PS04-08: Sociodemographic Risk Factors and Prediction of Aromatase Inhibitor Non-Adherence in Women with Breast Cancer Enrolled in SWOG S1105

Abstract Background: Non-adherence to aromatase inhibitors (AIs) for breast cancer is common and increases risk of recurrence. Few prospective studies have systematically evaluated non-adherence and non-clinical factors associated with it. We analyzed baseline sociodemographic characteristics and financial factors associated with non-adherence to create a baseline composite risk-score for AI non-adherence. Methods: Patients enrolled in S1105 were required to have been on an AI for ≥30 days at enrollment. Patients were assessed for non-adherence of AIs every 3 months for 36 months, with non-adherence defined as urine AI metabolite assay results satisfying any of the following: &amp;lt; 10 ng/mL, undetectable, specimen submitted outside of the ± 21-day follow-up appointment window, or no submitted specimen. Factors included race, Hispanic ethnicity, age, education, income, health insurance type, and prescription cost. We also included socioeconomic deprivation and rural or urban residence using trial participants’ residential zip codes linked to the Area Deprivation Index (ADI) and Rural Urban Continuum codes (RUCC) respectively. For numeric factors and categorical factors with more than two levels, we used cutpoint analysis to determine the highest risk range by optimizing the Chi-squared statistic. For each resulting binary factor, we performed a logistic regression, adjusting for the study stratification factors and stratifying by treatment arm. Factors associated with adherence at the alpha=0.10 level were combined into a composite risk score, with study participants given one point for each baseline adverse risk factor. Secondarily, we examined a composite risk score including all factors, regardless of statistical significance. Results: In total, 724 patients were registered from 40 institutions between May 2012 and September 2013. The median age was 60.9 years, and 64.5% were on AI &amp;lt; 12 months prior to registration. Only 8% had out of pocket (OOP) cost &amp;gt;$30. Observed adherence at 36 months was 35.9%. Patients living in metro areas with populations ≥ 250,000 (RUCC ≤ 3) were more likely to be non-adherent (37.5% vs 28.3%, OR=1.50, p=.08); as were those who were younger, those without a college education, and those with limited (≤$5) OOP cost. ADI, race and ethnicity were not associated with non-adherence. The composite risk score was strongly associated with 36-month adherence. For each 1 unit increase in risk level, the risk of non-adherence increased 47% (OR=1.47, p&amp;lt; .001); the risk increased 64% for those with &amp;gt;2 vs. ≤2 risk factors (OR=1.64, p=.002). Results using all factors regardless of statistical significance were consistent. Conclusions: A composite model comprised of sociodemographic risk factors can identify patients on AI’s at much greater risk of long-term AI non-adherence. In addition to mitigating side effects, targeted interventions to improve adherence should focus on structural barriers among those at highest risk. Non-adherence (+/- 6 months) = factor + AI duration + AI type, stratified by arm Citation Format: Dawn Hershman, Anna Moseley, Kathryn Arnold, Julie Gralow, Alfred Neugut, Scott Ramsey, N. Lynn Henry, Joseph Unger. Sociodemographic Risk Factors and Prediction of Aromatase Inhibitor Non-Adherence in Women with Breast Cancer Enrolled in SWOG S1105 [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS04-08.

Cohort profile: the Adverse Childhood Experiences cohort of the Malawi Longitudinal Study of Families and Health

PurposeThe Adverse Childhood Experiences (ACE) cohort of the Malawi Longitudinal Study of Families and Health (MLSFH-ACE) is a study of adolescents surveyed during 2017–2021. It provides an important opportunity to...

Association of monocyte to HDL cholesterol ratio and a composite risk score with left ventricular aneurysm formation in patients with acute ST-segment elevation myocardial infarction.

Left ventricular aneurysm (LVA) is an important complication of acute myocardial infarction. This study aimed to investigate the potential predictive value of the monocyte count to high-density lipoprotein cholesterol ratio (MHR) and a composite risk score in determining the formation of LVA in patients with acute ST-segment elevation myocardial infarction (STEMI) who underwent primary percutaneous coronary intervention. We recruited 1005 consecutive patients with STEMI. Multivariable logistic regression analysis was conducted identify the independent risk factors for LVA formation. Predictive power of MHR and composite risk score for LVA formation were assessed using receiver operating characteristic curve analysis. The MHR was significantly higher among patients with LVA compared to those without LVA [6.6 (3.8-10.8) vs. 4.6 (3.3-6.3), P < 0.001]. Univariable logistic regression analysis revealed that MHR (OR = 3.866, 95% CI = 2.677-5.582, P < 0.001) was associated with the risk of LVA formation. The predictive value of MHR remained significant even after multivariate logistic regression analysis [odds ratio (OR) = 4.801, 95% confidence interval (CI) = 2.672-8.629, P < 0.001]. The discriminant power of MHR for LVA is 0.712, which is superior to both monocyte ( C statistic = 0.553) and high-density lipoprotein cholesterol ( C statistic = 0.654). The composite risk score including MHR, gender, LVEF, hemoglobin, lymphocyte and left anterior descending artery as the culprit vessel could significantly increase the predictive ability ( C statistic = 0.920). A higher MHR could effectively identify individuals at high risk of LVA formation, especially when combined with gender, LVEF, hemoglobin, lymphocyte and left anterior descending artery as the culprit vessel.

DEep LearnIng-based QuaNtification of epicardial adipose tissue predicts MACE in patients undergoing stress CMR

Background and aimsThis study investigated the additional prognostic value of epicardial adipose tissue (EAT) volume for major adverse cardiovascular events (MACE) in patients undergoing stress cardiac magnetic resonance (CMR) imaging. Methods730 consecutive patients [mean age: 63 ± 10 years; 616 men] who underwent stress CMR for known or suspected coronary artery disease were randomly divided into derivation (n = 365) and validation (n = 365) cohorts. MACE was defined as non-fatal myocardial infarction and cardiac deaths. A deep learning algorithm was developed and trained to quantify EAT volume from CMR. EAT volume was adjusted for height (EAT volume index). A composite CMR-based risk score by Cox analysis of the risk of MACE was created. ResultsIn the derivation cohort, 32 patients (8.7 %) developed MACE during a follow-up of 2103 days. Left ventricular ejection fraction (LVEF) < 35 % (HR 4.407 [95 % CI 1.903–10.202]; p<0.001), stress perfusion defect (HR 3.550 [95 % CI 1.765–7.138]; p<0.001), late gadolinium enhancement (LGE) (HR 4.428 [95%CI 1.822–10.759]; p = 0.001) and EAT volume index (HR 1.082 [95 % CI 1.045–1.120]; p<0.001) were independent predictors of MACE. In a multivariate Cox regression analysis, adding EAT volume index to a composite risk score including LVEF, stress perfusion defect and LGE provided additional value in MACE prediction, with a net reclassification improvement of 0.683 (95%CI, 0.336–1.03; p<0.001). The combined evaluation of risk score and EAT volume index showed a higher Harrel C statistic as compared to risk score (0.85 vs. 0.76; p<0.001) and EAT volume index alone (0.85 vs.0.74; p<0.001). These findings were confirmed in the validation cohort. ConclusionsIn patients with clinically indicated stress CMR, fully automated EAT volume measured by deep learning can provide additional prognostic information on top of standard clinical and imaging parameters.