Combined Risk Score Research Articles

Optimized risk stratification strategy for glioma patients based on the feature genes of poor immune cell infiltration patterns.

Gliomas, originating from glial cells within the brain or spinal cord, are common central nervous system tumors with varying degrees of malignancy that influence the complexity and difficulty of treatment. The current strategies, including traditional surgery, radiotherapy, chemotherapy, and emerging immunotherapies, have yielded limited results. As such, our study aims to optimize risk stratification for a more precise treatment approach. We primarily identify feature genes associated with poor immune cell infiltration patterns through various omics algorithms and categorize glioma patients based on these genes to enhance the accuracy of patient prognosis assessment. This approach can underpin individualized treatment strategies and facilitate the discovery of new therapeutic targets. We procured datasets of gliomas and normal brain tissues from TCGA, CGGA, and GTEx databases. Clustering was conducted using the input of 287 immune cell feature genes. Hub genes linked with the poor prognosis subtype (C1) were filtered through WGCNA. The TCGA dataset served as the discovery cohort and the CGGA dataset as the external validation cohort. We constructed a prognostic model related to feature genes from poor immune cell infiltration patterns utilizing LASSO-Cox regression. Comprehensive analyses of genomic heterogeneity, tumor stemness, pathway relevance, immune infiltration patterns, treatment response, and potential drugs were conducted for different risk groups. Gene expression validation was performed using immunohistochemistry (IHC) on 98 glioma samples and 11 normal brain tissue samples. Using the filtered immune cell-related genes, glioma patients were stratified into C1 and C2 subtypes through clustering. The C1 subtype exhibited a worse prognosis, with upregulated genes primarily enriched in immune response, extracellular matrix, etc., and downregulated genes predominantly enriched in neural signal transduction and neural pathway-related aspects. Seven advanced algorithms were used to elucidate immune cell infiltration patterns of different subtypes. In addition, WGCNA identified hub genes from poor immune infiltration patterns, and a prognostic model was constructed accordingly. High-risk patients demonstrated shorter survival times and higher risk scores as compared to low-risk patients. Multivariate Cox regression analysis revealed that, after adjusting for confounding clinical factors, risk score was a vital independent predictor of overall survival (OS) (P < 0.001). The established nomogram, which combined risk scores with WHO grade and age, accurately predicted glioma patient survival rates at 1, 3, and 5 years, with AUCs of 0.908, 0.890, and 0.812, respectively. This risk score enhanced the nomogram's reliability and informed clinical decision-making. We also comprehensively analyzed genomic heterogeneity, tumor stemness, pathway relevance, immune infiltration patterns, treatment response, and potential drugs for different risk groups. In addition, we conducted preliminary validation of the potential PLSCR1 gene using IHC with a large sample of gliomas and normal brain tissues. Our optimized risk stratification strategy for glioma patients has the potential to improve the accuracy of prognosis assessment. The findings from our omics research not only enhance the understanding of the functions of feature genes related to poor immune cell infiltration patterns but also offer valuable insights for the study of glioma prognostic biomarkers and the development of individualized treatment strategies.

Stratified genome-wide association analysis of type 2 diabetes reveals subgroups with genetic and environmental heterogeneity.

Type 2 diabetes (T2D) is a heterogeneous illness caused by genetic and environmental factors. Previous genome wide association studies (GWAS) have identified many genetic variants associated with T2D and found evidence of differing genetic profiles by age-at-onset. This study seeks to explore further the genetic and environmental drivers of T2D by analysing subgroups based on age-at-onset of diabetes and body mass index (BMI). In UK Biobank, 36 494 T2D cases were stratified into 3 subgroups and GWAS performed for all T2D cases and for each subgroup relative to 421 021 controls. Altogether, 18 SNPs significantly associated genome-wide with T2D in one or more subgroups also showed evidence of heterogeneity between the subgroups, (Cochrane's Q p < 0.01) with 2 remaining significant after multiple testing (in CDKN2B and CYTIP). Combined risk scores, based on genetic profile, BMI and age, resulted in excellent diabetes prediction (AUC = 0.92). A modest improvement in prediction (AUC = 0.93) was seen when the contribution of genetic and environmental factors was evaluated separately for each subgroup. Increasing sample sizes of genetic studies enables us to stratify disease cases into subgroups which have sufficient power to highlight areas of genetic heterogeneity. Despite some evidence that optimising combined risk scores by subgroup improves prediction, larger sample sizes are likely needed for prediction when using a stratification approach.

Risk assessment and stratification of mild cognitive impairment among the Chinese elderly: attention to modifiable risk factors

BackgroundThe early identification of individuals at risk of mild cognitive impairment (MCI) has major public health implications for Alzheimer’s disease prevention.ObjectiveThis study aims to develop and validate a risk assessment...

The role of polygenic risk scores in breast cancer risk perception and decision-making.

Polygenic risk scores (PRS) have the potential to improve the accuracy of clinical risk assessments, yet questions about their clinical validity and readiness for clinical implementation persist. Understanding how individuals integrate and act on the information provided by PRS is critical for their effective integration into routine clinical care, yet few studies have examined how individuals respond to the receipt of polygenic risk information. We conducted an embedded Ethical, Legal, and Social Implications (ELSI) study to examine if and how unaffected participants in a US population breast cancer screening trial understood and utilized PRS, as part of a multifactorial risk score combining traditional risk factors with a genetic risk assessment, to make screening and risk-reduction decisions. Semi-structured qualitative interviews were conducted with 24 trial participants who were designated at elevated risk for breast cancer due to their combined risk score. Interviews were analyzed using a grounded theory approach. Participants understood PRS conceptually and accepted it as one of many risk factors to consider, yet the value and meaning they ascribed to this risk estimate varied. Most participants reported financial and insurance barriers to enhanced screening with MRI and were not interested in taking risk-reducing medications. These findings contribute to our understanding of how PRS may be best translated from research to clinical care. Furthermore, they illuminate ethical concerns about identifying risk and making recommendations based on polygenic risk in a population screening context where many may have trouble accessing appropriate care.

Morphology-Voltage-P-wave-duration (MVP) score to select patients for continuous atrial fibrillation screening to prevent stroke

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): The LOOP Study was funded by Innovation Fund Denmark [grant number 12-1352259], The Research Foundation for the Capital Region of Denmark, The Danish Heart Foundation [grant number 11-04-R83-A3363-22625], Aalborg University Talent Management Program, Arvid Nilssons Fond, Skibsreder Per Henriksen, R og Hustrus Fond, the European Union’s Horizon 2020 program [grant number 847770], Læge Sophus Carl Emil Friis og hustru Olga Doris Friis’ Legat, and an unrestricted grant from Medtronic. Background It is well known that atrial fibrillation (AF) confers a substantially increased risk of ischemic stroke, but data on health benefits from AF screening are scarce. The newly proposed MVP risk score combining the duration, voltage and morphology of P-wave has been demonstrated to be predictive of AF and might therefore also be useful in risk-stratifying individuals for AF screening and subsequent treatment. Purpose The present study sought to examine MVP risk score and its P-wave components for prediction of AF screening effects. Methods The LOOP Study randomized AF-naïve individuals aged 70-90 years with additional stroke risk factors to either continuous AF screening with implantable loop recorder (ILR) and subsequent anticoagulation initiation upon detection of AF episode ≥6 minutes, or usual care. In this secondary analysis, the LOOP participants with a baseline 12-lead electrocardiogram (ECG) suitable for P-wave measurement were included. Results Of 5759 participants included, 265 (4.6%) had had ischemic stroke during follow-up: 213 (4.9%) of 4311 in the control group versus 64 (3.6%) of 1448 in the ILR group. Among the participants in the control group, a significantly increased risk of ischemic stroke was observed for MVP score 5-6 versus score 0-2 (hazard ratio (HR) 1.66 [95% confidence interval (CI): 1.01-2.75]) and for the presence of interatrial block (IAB) versus no IAB (HR 1.85 [95% CI: 1.19-2.86]), whereas a P-wave voltage in lead I (PWVI) &amp;lt;100 µV was associated with risk reduction compared to higher voltage (HR 0.65 [95% CI: 0.45-0.93]). Further spline analysis revealed longer P-wave duration (PWD) to also be correlated with higher stroke risk (HR 1.49 [95% CI: 1.11-2.00] for &amp;gt;110 versus ≤110 ms). Compared with usual care, ILR screening did not significantly reduce the stroke risk regardless of MVP risk score, PWD, PWVI, or IAB pattern at baseline. Conclusions In an elderly population with additional stroke risk factors, both the P-wave parameters and the combined MVP risk score based on 12-lead ECG were associated with ischemic stroke, but these did not successfully demonstrate an association with effects of AF screening on stroke prevention.

A Probiotic Formula for Modulation of Colorectal Cancer Risk via Reducing CRC-Associated Bacteria.

Gut microbiota dysbiosis with increased pathogenic bacteria and decreased beneficial bacteria is associated with colorectal cancer (CRC) development. This study examined the effect of a newly developed probiotic formula in modulating CRC-related bacteria. We developed a probiotic formula containing three bifidobacteria (B. adolescentis, B. longum, and B. bifidum) based on the identification of bacterial species that showed significant correlations with CRC-related bacteria including Fusobacterium nucleatum (Fn), Lachnoclostridium sp. m3, Clostridium hathewayi (Ch), and Bacteroides clarus (Bc). We co-cultured Fn with each bifidobacterium or the combined formula and examined the growth of Fn by qPCR. The three individual bifidobacteria significantly inhibited the growth of Fn compared to the control treatment (24~65% inhibition; all p < 0.001). The combination of the three bifidobacteria showed a greater inhibitory effect on Fn growth (70% inhibition) than the individual bifidobacteria (all p < 0.05). We further examined the effect of the probiotic formula in a pilot study of 72 subjects (40 on probiotics; 32 with no intervention) for 4 weeks and followed them up for 12 weeks. The relative fecal abundances of the bifidobacteria in the formula and the CRC-related markers (Fn, m3, Ch, and Bc) were quantitated by qPCR before and after the intervention, and the combined CRC risk score (4Bac; Fn, m3, Ch, and Bc) was evaluated. Subjects with probiotics intervention showed significantly increased abundances of the bifidobacteria from week 2 to week 5 compared to baseline (p < 0.05), and the abundances dropped to baseline levels after the cessation of the intervention. There were significant decreases in the levels of CRC-related markers (Fn and m3) and the CRC risk score (4Bac) from week 2 to week 12 compared to baseline levels (p < 0.05) in the intervention group but not in the control group. A novel probiotic formula containing B. adolescentis, B. longum, and B. bifidum was effective in inhibiting the growth of F. nucleatum in vitro and improving the gut microbial environment against CRC development.

Melanoma risk prediction based on a polygenic risk score and clinical risk factors.

Melanoma is one of the most commonly diagnosed cancers in the Western world: third in Australia, fifth in the USA and sixth in the European Union. Predicting an individual's personal risk of developing melanoma may aid them in undertaking effective risk reduction measures. The objective of this study was to use the UK Biobank to predict the 10-year risk of melanoma using a newly developed polygenic risk score (PRS) and an existing clinical risk model. We developed the PRS using a matched case-control training dataset ( N = 16 434) in which age and sex were controlled by design. The combined risk score was developed using a cohort development dataset ( N = 54 799) and its performance was tested using a cohort testing dataset ( N = 54 798). Our PRS comprises 68 single-nucleotide polymorphisms and had an area under the receiver operating characteristic curve of 0.639 [95% confidence interval (CI) = 0.618-0.661]. In the cohort testing data, the hazard ratio per SD of the combined risk score was 1.332 (95% CI = 1.263-1.406). Harrell's C-index was 0.685 (95% CI = 0.654-0.715). Overall, the standardized incidence ratio was 1.193 (95% CI = 1.067-1.335). By combining a PRS and a clinical risk score, we have developed a risk prediction model that performs well in terms of discrimination and calibration. At an individual level, information on the 10-year risk of melanoma can motivate people to take risk-reduction action. At the population level, risk stratification can allow more effective population-level screening strategies to be implemented.

Highlights of Cardiovascular Disease Prevention Studies Presented at the 2023 American College of Cardiology Conference.

To summarize selected late-breaking science on cardiovascular (CV) disease prevention presented at the 2023 American College of Cardiology (ACC) conference. The CLEAR outcomes randomized control trial (RCT) compared bempedoic acid to placebo in patients at high-risk of cardiovascular disease (CVD) or prevalent CVD and statin intolerance for CV outcomes. The YELLOW III was a single-arm study that evaluated the effect of Evolocumab on coronary plaque characteristics in patients with stable coronary artery disease (CAD). A cohort evaluated the association between a self-reported low-carbohydrate high-fat (ketogenic) diet and serum lipid levels as compared to a standard diet. The LOADSTAR trial compared CV outcomes with targeted low-density lipoprotein cholesterol (LDL-C) approach vs. high-intensity statin in patients with CAD. The PCDS statin cluster randomized trial compared the effectiveness of an electronic reminder to the clinician on a high-intensity statin use among patients with a history of ASCVD as compared to no reminder. A prospective cohort study compared the extent of coronary atherosclerosis among lifelong endurance athletes and healthy non-athletes. A causal artificial intelligence study combined polygenic risk scores with data from large CV prevention RCTs to guide systolic blood pressure and LDL-C reduction targets to reach average CV risk. The ACCESS trial evaluated the impact of eliminating copayment for low-income older adults in Canada with chronic CV diseases on composite CV outcomes. A pooled analysis of 3 large RCTs evaluated the association between residual inflammatory risk and CV outcomes, as compared to residual elevated cholesterol risk in patients receiving statin therapy. A Phase 2B RCT compared the efficacy of an oral PCSK9i, MK-0616, in reducing LDL-C as compared to a placebo. The late-breaking clinical science presented at the 2023 conference of the ACC paves the way for an evidence-based alternative to statin therapy and provides data on several common clinical scenarios encountered in daily practice.

Integrated bioinformatic analysis of mitochondrial metabolism-related genes in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a common hematologic malignancy characterized by poor prognoses and high recurrence rates. Mitochondrial metabolism has been increasingly recognized to be crucial in tumor progression and treatment resistance. The purpose of this study was to examined the role of mitochondrial metabolism in the immune regulation and prognosis of AML. In this study, mutation status of 31 mitochondrial metabolism-related genes (MMRGs) in AML were analyzed. Based on the expression of 31 MMRGs, mitochondrial metabolism scores (MMs) were calculated by single sample gene set enrichment analysis. Differential analysis and weighted co-expression network analysis were performed to identify module MMRGs. Next, univariate Cox regression and the least absolute and selection operator regression were used to select prognosis-associated MMRGs. A prognosis model was then constructed using multivariate Cox regression to calculate risk score. We validated the expression of key MMRGs in clinical specimens using immunohistochemistry (IHC). Then differential analysis was performed to identify differentially expressed genes (DEGs) between high- and low-risk groups. Functional enrichment, interaction networks, drug sensitivity, immune microenvironment, and immunotherapy analyses were also performed to explore the characteristic of DEGs. Given the association of MMs with prognosis of AML patients, a prognosis model was constructed based on 5 MMRGs, which could accurately distinguish high-risk patients from low-risk patients in both training and validation datasets. IHC results showed that MMRGs were highly expressed in AML samples compared to normal samples. Additionally, the 38 DEGs were mainly related to mitochondrial metabolism, immune signaling, and multiple drug resistance pathways. In addition, high-risk patients with more immune-cell infiltration had higher Tumor Immune Dysfunction and Exclusion scores, indicating poor immunotherapy response. mRNA-drug interactions and drug sensitivity analyses were performed to explore potential druggable hub genes. Furthermore, we combined risk score with age and gender to construct a prognosis model, which could predict the prognosis of AML patients. Our study provided a prognostic predictor for AML patients and revealed that mitochondrial metabolism is associated with immune regulation and drug resistant in AML, providing vital clues for immunotherapies.

Association between hemoglobin glycation index and diabetic kidney disease in type 2 diabetes mellitus in China: A cross- sectional inpatient study.

To investigate the association between Hemoglobin Glycation Index (HGI) and Diabetic Kidney Disease (DKD) in Chinese type 2 diabetic individuals and to construct a risk score based on HGI to predict a person's risk of DKD. We retrospectively analyzed 1622 patients with type 2 diabetes mellitus (T2DM). HGI was obtained by calculating the fasting plasma glucose (FPG) level into the formula, and they were grouped into low HGI group (L-HGI), medium HGI group (H-HGI) and high HGI group (H-HGI) according to tri-sectional quantile of HGI. The occurrence of DKD was analyzed in patients with different levels of HGI. Multivariate logistics regression analysis was used to analyze the risk factors of DKD in patients with T2DM. A total of 1622 patients with T2DM were enrolled in the study. Among them, 390 cases were DKD. The prevalence of DKD among the three groups was 16.6%, 24.2% and 31.3%. The difference was statistically significant (P = 0.000). There were significant differences in age (P=0.033), T2DM duration (P=0.005), systolic blood pressure (SBP) (P=0.003), glycosylated hemoglobin (HbA1c) (P=0.000), FPG (P=0.032), 2-hour postprandial plasma glucose (2h-PPG) (P=0.000), fasting C-peptide FCP (P=0.000), 2-hour postprandial C-peptide (2h-CP) (P=0.000), total cholesterol (TC) (P=0.003), low density lipoprotein cholesterol (LDL-C) (P=0.000), serum creatinine (sCr) (P=0.001), estimated glomerular filtration rate (eGFR) (P=0.000) among the three groups. Mantel-Haenszel chi-square test showed that there was a linear relationship between HGI and DKD (x2=177.469, p < 0.001). Pearson correlation analysis showed that with the increase of HGI level the prevalence of DKD was increasing (R= 0.445, P=0.000). It was indicated by univariate logistic regression analysis that individuals in H-HGI was more likely to develop DKD (OR: 2.283, 95% CI: 1.708~ 3.052) when compared with L-HGI. Adjusted to multiple factors, this trend still remained significant (OR: 2.660, 95% CI: 1.935~ 3.657). The combined DKD risk score based on HGI resulted in an area under the receiver operator characteristic curve (AUROC) of 0.702. High HGI is associated with an increased risk of DKD. DKD risk score may be used as one of the risk predictors of DKD in type 2 diabetic population.

Abstract PD14-05: PD14-05 Prospective longitudinal validation of a breast cancer risk prediction model in a cohort of 130,058 women

Abstract Background: Personalized breast cancer (BC) risk assessment depends on known traditional risk factors, specific germline mutations, and genome-wide polygenic risk scores (PRS). PRS explains a substantial proportion of genetic BC susceptibility. Accuracy of BC risk prediction may be improved by combining a PRS with traditional risk factors. We recently developed and validated a 149-SNP PRS for women of diverse ancestries using ancestry-informative genetic markers and combined this with version 7 of the Tyrer-Cuzick (TC) model to generate a Combined Risk Score (CRS). Here, we describe a pre-specified prospective longitudinal clinical validation of CRS as a predictor of BC risk. Methods: Women in the U.S. who were referred for clinical genetic testing between January 2017 and February 2019 were matched to medical and hospital claims in an anonymized dataset. Women with a pathogenic mutation in a BC-related gene were excluded from analysis. Follow-up began 4 months after testing and extended to the earliest date of BC diagnosis, censoring at the time of BC preventive treatment, or November 1, 2019. Incident BC events were determined by an ICD10 code of C50.* and confirmed by relevant treatment codes. CRS calibration was evaluated by the ratio of observed (O) to expected (E) incident BCs for the full cohort, and for women split into event-based 5-year CRS risk deciles. Cox proportional hazards models were used to evaluate discriminatory accuracy in terms of hazard ratios (HR) with 95% confidence intervals (CI) and p-values from likelihood ratio chi-squared statistics. Kaplan-Meier analysis was used to examine risk for women split into high- or low-risk groups according to a 3% 5-year CRS risk threshold. Results: 130,058 women with 148,349 total patient years met study eligibility criteria and were matched to claims data. Over a median (range) follow-up of 12.1 (4.0-29.5) months, 340 incident BC events were observed. The CRS was well calibrated in the overall cohort with an O/E ratio of 1.11 (95% CI=0.99-1.23) and within deciles of predicted risk (Table). Importantly, in the highest risk decile, the O/E was 0.91 (95% CI=0.63-1.27) with CRS, but 0.67 (95% CI=0.46-0.94) with TC alone, illustrating the superior calibration of CRS. In a Cox model adjusted for age at testing, PRS had an HR per standard deviation (SD) of 1.48 (95% CI=1.33-1.64, p=2.55×10-13); the HR/SD was 1.43 (95% CI=1.29-1.59, p=1.61×10-11) after adjusting for family history. In a bivariate analysis using both CRS and TC to predict time to BC, CRS added significantly to the model after accounting for TC (HR/SD=2.89, 95% CI=2.12-3.94, p=1.20×10-11), whereas TC did not add significant information after accounting for CRS. 15,986 (12.3%) women were above the CRS high-risk threshold, including 123 with events. A total of 10,248 (7.9%) women were reclassified by the CRS model compared to the TC model. Among women who were classified as high-risk by TC, 32.6% were reclassified as low-risk by CRS; among those classified as low-risk by TC, 4.3% were reclassified as high-risk by CRS. The CRS high-risk group experienced events at over three times the rate of the low-risk group (HR=3.75, 95% CI=3.00-4.68, p=6.39×10-27). Conclusion: The CRS was well-calibrated in predicting BC and significantly improved upon a traditional risk factor model. Clinical use of the CRS may lead to improved BC prevention and screening strategies. Table: Absolute risk calibration by 5-year risk decile Incidence is reported per 1,000 women-years. 34 breast cancers were observed per decile. Citation Format: Brent Mabey, Elisha Hughes, Braden Probst, Holly J. Pederson, Timothy Simmons, Brian Morris, Brooke Hullinger, Susan Domchek, Charis Eng, Monique Gary, Jennifer Klemp, Semanti Mukherjee, Vijai Joseph, Kenneth Offit, Olufunmilayo I. Olopade, Sandhya Pruthi, Allison W. Kurian, Mark E. Robson, Pat Whitworth, Susanne Wagner, Jerry Lanchbury, Thomas Slavin, Alexander Gutin. PD14-05 Prospective longitudinal validation of a breast cancer risk prediction model in a cohort of 130,058 women [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD14-05.

Abstract P2-11-36: Osteopontin splice variants indicate prognosis in premalignant breast lesions

Abstract BACKGROUND: Premalignant breast lesions pose variable risks for transformation, raising the question who should receive treatment to counteract the potential progression to breast cancer. Prognostic indicators will spare low-risk patients the burden of substantial treatment side effects and will enable high-risk patients to comfortably take preemptive action. Osteopontin (OPN) is a secreted mediator of breast cancer progression, which is subject to alternative splicing in transformed tissues and has been known to be a marker for breast cancer aggressiveness. Here, we test the variants OPN-a and OPN-c as potential prognosticators for the transformation of premalignant breast lesions. The presence of spliced Osteopontin-c in these lesions does reflect the risk for cancer development within 5 years. METHODS: By immunohistochemistry, we analyze the association of Osteopontin variant expression in healthy breasts, hyperplasias, radial scars, lobular and ductal carcinomas in situ from 434 women as well as papillomas from 114 women to assess a) staining for OPN exon 4 (present in OPN-a and OPNb) and OPN-c in low-risk to high-risk lesions b) correlations between staining and progression to cancer or survival. RESULTS: The staining intensity for OPN-c correlates with risk, and it is prognostic for ensuing invasive disease and survival. About 10% of OPN-c pathology score 0–1 (intensity), vs. 40% of score 3 experience cancer over 5 years. More than 90% of women, who progress, had pathology scores of 2–3 for OPN-c intensity at the time of initial diagnosis. When combining OPN-c and OPN exon 4 staining, all of the low intensity patients are alive after 5 years, whereas women in the high category have a close to 30% chance to die within 5 years. Of patients who succumb, close to 80% had a high combined score at the time of initial diagnosis. In the papilloma patients, fewer than 5% of OPN-c pathology score 0-1 (intensity), versus almost 18% of score 2-3 experienced cancer in follow-up. 9 of 12 women, who progressed, had pathology scores of 2-3 for OPN-c intensity at the time of initial diagnosis, none had a score of 0. When developing a combined risk score from intensity plus percent positivity for OPN-c, the progression risk for patients with low score was 3.2%, for intermediate score was 5.7%, and for high score was 18.8%. Papillomas in patients, who were later diagnosed with cancer in the contralateral breast, displayed stronger staining positivity than non-progressors. CONCLUSION: The information of OPN-c immunohistochemistry can provide a foundation for very reliable prognostication and has the potential to aid decision making in the treatment or watchful waiting of early breast lesions. The addition of OPN-a refines the prognostication of survival. The staining intensity for OPN variants may also inform on the cancer risk in the unaffected breast, which may reflect a genetic predisposition for Osteopontin expression and splicing. OPN splice variant immunohistochemistry on breast biopsies will allow counseling of the patients on their risk to develop breast cancer at a later time. Citation Format: Georg F. Weber, Piotr Ziolkowski. Osteopontin splice variants indicate prognosis in premalignant breast lesions [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-11-36.

Abstract MP38: Higher Childhood Cardiovascular Risk Score is Associated With Worse Physical, Social and Emotional Functioning in Adulthood

Introduction: Childhood cardiovascular risk factors have been associated with increased risk of adult cardiovascular disease, but how they are associated with adult physical, emotional and social functioning is not well understood. Hypothesis: We addressed the hypothesis that the International Childhood Cardiovascular Cohort (i3C) Consortium childhood risk score would be associated with worse physical, social and emotional functioning in adulthood. Methods: The i3C childhood combined risk score is the average of five childhood risk factors (body mass index, systolic blood pressure, youth smoking, total cholesterol and triglycerides) on the z-score scale. Self-reported measures of physical (e.g., pain, functioning, fatigue), social (e.g., social isolation, satisfaction with social role) and emotional functioning (e.g., anxiety, depression) were assessed in adulthood in a subset of two i3C cohorts, the NHLBI Growth and Health Study (NGHS) and the Princeton Lipid Research Study (PLRS). Potential covariates included cohort (as a proxy for age, given no overlap in ages between cohorts), sex, race (Black vs. White), own education, parental education, marital status, and self-reported hypertension, diabetes and cancer. Interactions between the i3C risk score and cohort (age) were evaluated. Results: Ninety-two NGHS (100% female, 46% Black, mean±SD age 44.5±0.6 years) and 75 PLRS (77% female, 31% Black, 60.6±3.4 years) participants were included in analyses. In adjusted models, a higher i3C risk score was associated with worse physical functioning, global pain score, pain interference with everyday activities, and fatigue in the older PLRS participants, but only with global pain score in the younger NGHS participants (all p[int]&lt;0.05 except global pain). Higher i3C childhood risk score was associated with greater sleep-related impairment in PLRS, but with less impairment in NGHS participants (p[int]=0.03). Higher i3C childhood risk score was also associated with higher depression scores and less satisfaction with social roles in PLRS participants but not NGHS participants (p[int]=0.02 and 0.04, respectively). There was no significant relationship of i3C risk score with sleep quality, friendships, social isolation or anxiety. Conclusions: In conclusion, higher childhood cardiovascular risk factors are associated with worse physical, social and emotional health in adulthood, even in this limited sample of predominantly Black and White women followed from childhood. These effects are more prominent in older than younger adults, when issues such as pain and sleep problems become more prevalent.

Health behavior of young patients with ischemic stroke in Estonia: A score of five factors.

Behavioral risk factors are common among young patients with stroke. This study aimed to compare the health behavior of patients and healthy controls and develop a combined risk score of health behavior. The health behavior of patients aged 18-54 years who suffered an ischemic stroke from 2013 to 2020 in Estonia was compared to the Health Behavior among Estonian Adult Population 2014 study sample. We chose five risk factors for comparison: smoking status, body mass index, physical exercise, diet (salt use and vegetable consumption), alcohol intake (quantity and frequency), and composed a summary score. Comparing 342 patients and 1789 controls, daily smoking (49.0%vs. 22.7%), obesity (33.4%vs. 15.9%), low physical activity(<twice/week) (72.2%vs. 60.5%), excessive salt use (8.6%vs. 4.5%), and frequent alcohol use (≥ weekly) (39.9%vs. 34.0%) were more prevalent among patients. The differences in infrequent vegetable consumption(<6 days/week) and excessive alcohol consumption (7 days,>8 units/females,>16 units/males) were not significant. The observed differences were similar for age groups 18-44 years and 45-54 years. The average Health Behavior Stroke Risk Score (0-10) was 4.6 points (CI 4.4-4.8, SD±1.97) for patients and 3.5 points (CI 3.4-3.6, SD±1.90) for controls. Before stroke, young patients displayed significantly worse health behavior than the general population. The largest differences were found for smoking and obesity, and a cumulation of risk factors was observed via the HBSR score.

An immune genes signature for predicting mortality in sepsis patients.

A growing body of evidence indicates that the immune system plays a central role in sepsis. By analyzing immune genes, we sought to establish a robust gene signature and develop a nomogram that could predict mortality in patients with sepsis. Herein, data were extracted from the Gene Expression Omnibus and Biological Information Database of Sepsis (BIDOS) databases. We enrolled 479 participants with complete survival data using the GSE65682 dataset, and grouped them randomly into training (n = 240) and internal validation (n = 239) sets based on a 1:1 proportion. GSE95233 was set as the external validation dataset (n=51). We validated the expression and prognostic value of the immune genes using the BIDOS database. We established a prognostic immune genes signature (including ADRB2, CTSG, CX3CR1, CXCR6, IL4R, LTB, and TMSB10) via LASSO and Cox regression analyses in the training set. Based on the training and validation sets, the Receiver Operating Characteristic curves and Kaplan-Meier analysis revealed that the immune risk signature has good predictive power in predicting sepsis mortality risk. The external validation cases also showed that mortality rates in the high-risk group were higher than those in the low-risk group. Subsequently, a nomogram integrating the combined immune risk score and other clinical features was developed. Finally, a web-based calculator was built to facilitate a convenient clinical application of the nomogram. In summary, the signature based on the immune gene holds potential as a novel prognostic predictor for sepsis.

The prognostic value of the GPAT/AGPAT gene family in hepatocellular carcinoma and its role in the tumor immune microenvironment.

Liver cancer is the sixth most commonly diagnosed cancer and the third leading cause of cancer-related death worldwide. Hepatocellular carcinoma accounts for an estimated 90% of all liver cancers. Many enzymes of the GPAT/AGPAT family are required for the synthesis of triacylglycerol. Expression of AGPAT isoenzymes has been reported to be associated with an increased risk of tumorigenesis or development of aggressive phenotypes in a variety of cancers. However, whether members of the GPAT/AGPAT gene family also influence the pathophysiology of HCC is unknown. Hepatocellular carcinoma datasets were obtained from the TCGA and ICGC databases. Predictive models related to the GPAT/AGPAT gene family were constructed based on LASSO-Cox regression using the ICGC-LIRI dataset as an external validation cohort. Seven immune cell infiltration algorithms were used to analyze immune cell infiltration patterns in different risk groups. IHC, CCK-8, Transwell assay, and Western blotting were used for in vitro validation. Compared with low-risk patients, high-risk patients had shorter survival and higher risk scores. Multivariate Cox regression analysis showed that risk score was a significant independent predictor of overall survival (OS) after adjustment for confounding clinical factors (p < 0.001). The established nomogram combined risk score and TNM staging to accurately predict survival at 1, 3, and 5 years in patients with HCC with AUC values of 0.807, 0.806, and 0.795, respectively. This risk score improved the reliability of the nomogram and guided clinical decision-making. In addition, we comprehensively analyzed immune cell infiltration (using seven algorithms), response to immune checkpoint blockade, clinical relevance, survival, mutations, mRNA expression-based stemness index, signaling pathways, and interacting proteins related to the three core genes of the prognostic model (AGPAT5, LCLAT1, and LPCAT1). We also performed preliminary validation of the differential expression, oncological phenotype, and potential downstream pathways of the three core genes by IHC, CCK-8, Transwell assay, and Western blotting. These results improve our understanding of the function of GPAT/AGPAT gene family members and provide a reference for prognostic biomarker research and individualized treatment of HCC.

Genetic Risk Score Improves Risk Stratification for Anticoagulation-Related Intracerebral Hemorrhage.

Intracerebral hemorrhage (ICH) is the most devastating adverse outcome for patients on anticoagulants. Clinical risk scores that quantify bleeding risk can guide decision-making in situations when indication or duration for anticoagulation is uncertain. We investigated whether integration of a genetic risk score into an existing risk factor-based CRS could improve risk stratification for anticoagulation-related ICH. We constructed 153 genetic risk scores from genome-wide association data of 1545 ICH cases and 1481 controls and validated them in 431 ICH cases and 431 matched controls from the population-based UK Biobank. The score that explained the largest variance in ICH risk was selected and tested for prediction of incident ICH in an independent cohort of 5530 anticoagulant users. A CRS for major anticoagulation-related hemorrhage, based on 8/9 components of the HAS-BLED score, was compared with a combined clinical and genetic risk score incorporating an additional point for high genetic risk for ICH. Among anticoagulated individuals, 94 ICH occurred over a mean follow-up of 11.9 years. Compared with the lowest genetic risk score tertile, being in the highest tertile was associated with a two-fold increased risk for incident ICH (hazard ratio, 2.08 [95% CI, 1.22-3.56]). Although the CRS predicted incident ICH with a hazard ratio of 1.24 per 1-point increase (95% CI [1.01-1.53]), adding a point for high genetic ICH risk led to a stronger association (hazard ratio of 1.33 per 1-point increase [95% CI, 1.11-1.59]) with improved risk stratification (C index 0.57 versus 0.53) and maintained calibration (integrated calibration index 0.001 for both). The new clinical and genetic risk score showed 19% improvement in high-risk classification among individuals with ICH and a net reclassification improvement of 0.10. Among anticoagulant users, a prediction score incorporating genomic information is superior to a clinical risk score alone for ICH risk stratification and could serve in clinical decision-making.

Predicting 10-Year Risk of Pancreatic Cancer Using a Combined Genetic and Clinical Model.

Pancreatic cancer has the poorest 5-year survival rate of any major solid tumor, but when diagnosed at an early stage, survival rates improve. Population screening is impractical because pancreatic cancer is rare with a lifetime risk of 1.7%, but accurate risk stratification in the general population could enable health care providers to focus early detection strategies to at-risk individuals. Here, we validate a combined risk prediction model that integrates a polygenic risk score and a clinical risk model. Using the UK Biobank, we conducted a prospective cohort study assessing 10-year pancreatic cancer risks based on a polygenic risk score, a clinical risk score, and a combined risk score. We assessed the association, discrimination, calibration, cumulative hazards, and standardized incidence ratios compared to population incidence rates for the risk scores. We also conducted net reclassification analyses. While all of the risk scores discriminated well between affected and unaffected participants, the combined risk score - with a Harrell's C-index of 0.714 (95% confidence interval [CI]= 0.698, 0.730) - discriminated better than both the polygenic risk score (P= .001) and the clinical risk score (P= .02). In terms of calibration, there was no problem with dispersion for the combined risk score (β= 0.952, 95% CI= 0.865-1.039, P= .3) and overall there was a small overestimation of risk (α=-0.089, 95% CI=-0.156 to-0.021, P= .009). Participants in the top decile of 10-year risk were at 1.413 (95% CI= 1.242-1.607) times population risk. The combined risk score was able to identify individuals at substantially increased risk of pancreatic cancer and to whom targeted screening could be useful.

ALTERNATIVE FISTULA RISK SCORE AND FIRST POSTOPERATIVE DAY DRAIN FLUID AMYLASE AS PREDICTORS OF PANCREATIC FISTULA AFTER PANCREATICODUODENECTOMY.

The high morbidity and mortality rates of pancreaticoduodenectomy are mainly associated with pancreaticojejunal anastomosis, the most fragile and susceptible to complications such as clinically relevant postoperative pancreatic fistula. The alternative fistula risk score and the first postoperative day drain fluid amylase are predictors of the occurrence of clinically relevant postoperative pancreatic fistula. No consensus has been reached on which of the scores is a better predictor; moreover, their combined predictive power remains unclear. To the best of our knowledge, this association had not yet been studied. This study assessed the predictive effect of alternative fistula risk score and/or drain fluid amylase on clinically relevant postoperative pancreatic fistula in a retrospective cohort of 58 patients following pancreaticoduodenectomy. The Shapiro-Wilk and Mann-Whitney tests were applied for assessing the distribution of the samples and for comparing the medians, respectively. The receiver operating characteristics curve and the confusion matrix were used to analyze the predictive models. The alternative fistula risk score values were not statistically different between patients in the clinically relevant postoperative pancreatic fistula and non- clinically relevant postoperative pancreatic fistula groups (Mann-Whitney U test 59.5, p=0.12). The drain fluid amylase values were statistically different between clinically relevant postoperative pancreatic fistula and non- clinically relevant postoperative pancreatic fistula groups (Mann-Whitney U test 27, p=0.004). The alternative fistula risk score and drain fluid amylase were independently less predictive for clinically relevant postoperative pancreatic fistula, compared to combined alternative fistula risk score + drain fluid amylase. The combined model involving alternative fistula risk score >20% + drain fluid amylase=5,000 U/L was the most effective predictor of clinically relevant postoperative pancreatic fistula occurrence following pancreaticoduodenectomy.

RISK SCORE MODEL FOR PREDICTING CARDIOTOXICITY IN BREAST CANCER: DIAGNOSTIC VALUE OF HIGH-SENSITIVITY CARDIAC TROPONIN T.

to develop a risk score model for cardiovascular toxicity (CT) predicting, based on cardiovascular risk factors (RFs), RFs associated with cancer therapy, and troponin levels. The study included 76 BC patients with a prospective analysis of their clinical and treatment data, RFs, echocardiographic indicators before the start of treatment and after 6 months, and an increase in troponin level. Among all RFs, the most significant RFs of CT were: radiation therapy, treatment with anthracyclines, and cardiovascular diseases. Based on the obtained results, a combined CT risk score was developed and proposed.According to the sum of points, patients were divided into groups: group 1 - with a low risk of CT development, the sum of points < 5; group 2 - moderate risk, 6-7 points; group 3 - high risk, > 8 points. In a pilot prospective study, an analysis of the RFs of CT was provided, compared to echocardiography data and the degree of troponin increase in dynamic observation; the risk score model for the CT prediction was developed for BC patients stratification. According to the developed score, BC patients with a total of > 8 points are considered to have a high risk of CT complications. The use of the proposed risk model score with calculation of the RFs of CT along with high-sensitivity troponin increase during cancer treatment allows predicting the risk of CT developing at the early stages - before the onset of clinical manifestations. Accordingly, these BC patients have a high risk of CT, and the use of personalized cardiac monitoring together with cardioprotective therapy can prevent cardiovascular complications.