The Precision of Cardiovascular Disease Prevention Begins With a Zip Code.
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ABSTRACT:
SUBMITTER: Obuobi S
PROVIDER: S-EPMC8311274 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundArea-level social determinants of health (SDOH) based on patients' ZIP codes or census tracts have been commonly used in research instead of individual SDOHs. To our knowledge, whether machine learning (ML) could be used to derive individual SDOH measures, specifically individual educational attainment, is unknown.MethodsThis is a retrospective study using data from the Mount Sinai BioMe Biobank. We included participants that completed a validated questionnaire on educational attainment and had home addresses in New York City. ZIP code-level education was derived from the American Community Survey matched for the participant's gender and race/ethnicity. We tested several algorithms to predict individual educational attainment from routinely collected clinical and demographic data. To evaluate how using different measures of educational attainment will impact model performance, we developed three distinct models for predicting cardiovascular (CVD) hospitalization. Educational attainment was imputed into models as either survey-derived, ZIP code-derived, or ML-predicted educational attainment.ResultsA total of 20,805 participants met inclusion criteria. Concordance between survey and ZIP code-derived education was 47%, while the concordance between survey and ML model-predicted education was 67%. A total of 13,715 patients from the cohort were included into our CVD hospitalization prediction models, of which 1,538 (11.2%) had a history of CVD hospitalization. The AUROC of the model predicting CVD hospitalization using survey-derived education was significantly higher than the model using ZIP code-level education (0.77 versus 0.72; p < 0.001) and the model using ML model-predicted education (0.77 versus 0.75; p < 0.001). The AUROC for the model using ML model-predicted education was also significantly higher than that using ZIP code-level education (p = 0.003).ConclusionThe concordance of survey and ZIP code-level educational attainment in NYC was low. As expected, the model utilizing survey-derived education achieved the highest performance. The model incorporating our ML model-predicted education outperformed the model relying on ZIP code-derived education. Implementing ML techniques can improve the accuracy of SDOH data and consequently increase the predictive performance of outcome models.
| S-EPMC10852236 | biostudies-literature
Project description:Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, and is among the most aggressive and still incurable cancers. Innovative and successful therapeutic strategies are extremely needed. Peptides represent a versatile and promising tool to achieve tumor targeting, thanks to their ability to recognize specific target proteins (over)expressed on the surface of cancer cells. A7R is one such peptide, binding neuropilin-1 (NRP-1) and VEGFR2. Since PDAC expresses these receptors, the aim of this study was to test if A7R-drug conjugates could represent a PDAC-targeting strategy. PAPTP, a promising mitochondria-targeted anticancer compound, was selected as the cargo for this proof-of-concept study. Derivatives were designed as prodrugs, using a bioreversible linker to connect PAPTP to the peptide. Both the retro-inverso (DA7R) and the head-to-tail cyclic (cA7R) protease-resistant analogs of A7R were tested, and a tetraethylene glycol chain was introduced to improve solubility. Uptake of a fluorescent DA7R conjugate, as well as of the PAPTP-DA7R derivative into PDAC cell lines was found to be related to the expression levels of NRP-1 and VEGFR2. Conjugation of DA7R to therapeutically active compounds or nanovehicles might allow PDAC-targeted drug delivery, improving the efficacy of the therapy and reducing off-target effects.
| S-EPMC10221132 | biostudies-literature
Project description:The purpose of this review is to describe novel pharmacologic and nonpharmacologic preventive therapies, as well as new strategies to improve delivery of available therapies. Cardiovascular disease (CVD) is the leading cause of death worldwide, and prevention plays a critical role in curbing the global epidemic. Despite available treatment for tobacco addiction, platelet inhibition, blood pressure, and lipid lowering for reduction of atherosclerotic disease, significant gaps in treatment of total CVD remain. We review a range of new preventive treatment options, including drugs for tobacco cessation, platelet/thrombotic inhibition, lipid- and blood pressure-lowering; nonpharmacologic options such as left atrial appendage closure devices and caloric restriction; and strategies such as fixed-dose combination drugs, laboratory screening for drug tailoring, and community-based prevention programs. CVD preventive research continues to evolve and provide clinicians and patients with novel pharmacologic and nonpharmacologic therapies, including new preventive strategies.
| S-EPMC3911909 | biostudies-other
Project description:Precision medicine is an integrative approach to cardiovascular disease prevention and treatment that considers an individual's genetics, lifestyle, and exposures as determinants of their cardiovascular health and disease phenotypes. This focus overcomes the limitations of reductionism in medicine, which presumes that all patients with the same signs of disease share a common pathophenotype and, therefore, should be treated similarly. Precision medicine incorporates standard clinical and health record data with advanced panomics (ie, transcriptomics, epigenomics, proteomics, metabolomics, and microbiomics) for deep phenotyping. These phenotypic data can then be analyzed within the framework of molecular interaction (interactome) networks to uncover previously unrecognized disease phenotypes and relationships between diseases, and to select pharmacotherapeutics or identify potential protein-drug or drug-drug interactions. In this review, we discuss the current spectrum of cardiovascular health and disease, population averages and the response of extreme phenotypes to interventions, and population-based versus high-risk treatment strategies as a pretext to understanding a precision medicine approach to cardiovascular disease prevention and therapeutic interventions. We also consider the search for resilience and Mendelian disease genes and argue against the theory of a single causal gene/gene product as a mediator of the cardiovascular disease phenotype, as well as an Erlichian magic bullet to solve cardiovascular disease. Finally, we detail the importance of deep phenotyping and interactome networks and the use of this information for rational polypharmacy. These topics highlight the urgent need for precise phenotyping to advance precision medicine as a strategy to improve cardiovascular health and prevent disease.
| S-EPMC6021027 | biostudies-literature
Project description:We assessed the added value and limitations of generating directly estimated ZIP Code-level estimates by aggregating 5 years of data from an annual cross-sectional survey, the New York City Community Health Survey (n = 44,886) from 2009 to 2013, that were designed to provide reliable estimates only of larger geographies. Survey weights generated directly-observed ZIP Code (n = 128) level estimates. We assessed the heterogeneity of ZIP Code-level estimates within coarser United Hospital Fund (UHF) neighborhood areas (n = 34) by using the Rao-Scott Chi-Square test and one-way ANOVA. Orthogonal linear contrasts assessed whether there were linear trends at the UHF level from 2009 to 2013. 22 of 37 health indicators were reliable in over 50% of ZIP Codes. 14 of the 22 variables showed heterogeneity in ≥4 UHFs. Variables for drinking, nutrition, and HIV testing showed heterogeneity in the most UHFs (9-24 UHFs). In half of the 32 UHFs, >20% variables had within-UHF heterogeneity. Flu vaccination and sugary beverage consumption showed significant time trends in the largest number of UHFs (12 or more UHFs). Overall, heterogeneity of ZIP Code-level estimates suggests that there is value in aggregating 5 years of data to make direct small area estimates.
| S-EPMC7392987 | biostudies-literature
Project description:ImportanceThere has been large geographic inequity in vaccination coverage across Chicago, Illinois, with higher vaccination rates in zip codes with residents who predominantly have high incomes and are White.ObjectiveTo determine the association between inequitable zip code-level vaccination coverage and COVID-19 mortality in Chicago.Design, setting, and participantsThis retrospective cohort study used Chicago Department of Public Health vaccination and mortality data and Cook County Medical Examiner mortality data from March 1, 2020, through November 6, 2021, to assess the association of COVID-19 mortality with zip code-level vaccination rates. Data were analyzed from June 1, 2021, to April 13, 2022.ExposuresZip code-level first-dose vaccination rates before the Alpha and Delta waves of COVID-19.Main outcomes and measuresThe primary outcome was deaths from COVID-19 during the Alpha and Delta waves. The association of a marginal increase in zip code-level vaccination rate with weekly mortality rates was estimated with a mixed-effects Poisson regression model, and the total number of preventable deaths in the least vaccinated quartile of zip codes was estimated with a linear difference-in-difference design.ResultsThe study population was 2 686 355 Chicago residents in 52 zip codes (median [IQR] age 34 [32-38] years; 1 378 658 [51%] women; 773 938 Hispanic residents [29%]; 783 916 non-Hispanic Black residents [29%]; 894 555 non-Hispanic White residents [33%]). Among residents in the least vaccinated quartile, 80% were non-Hispanic Black, compared with 8% of residents identifying as non-Hispanic Black in the most vaccinated quartile (P < .001). After controlling for age distribution and recovery from COVID-19, a 10-percentage point increase in zip code-level vaccination 6 weeks before the peak of the Alpha wave was associated with a 39% lower relative risk of death from COVID-19 (incidence rate ratio [IRR], 0.61 [95% CI, 0.52-0.72]). A 10-percentage point increase in zip code vaccination rate 6 weeks before the peak of the Delta wave was associated with a 24% lower relative risk of death (IRR, 0.76 [95% CI, 0.66-0.87]). The difference-in-difference estimate was that 119 Alpha wave deaths (72% [95% CI, 63%-81%]) and 108 Delta wave deaths (75% [95% CI, 66%-84%]) might have been prevented in the least vaccinated quartile of zip codes if it had had the vaccination coverage of the most vaccinated quartile.Conclusions and relevanceThese findings suggest that low zip code-level vaccination rates in Chicago were associated with more deaths during the Alpha and Delta waves of COVID-19 and that inequitable vaccination coverage exacerbated existing racial and ethnic disparities in COVID-19 deaths.
| S-EPMC9142872 | biostudies-literature
Project description:Canonical fibroblast growth factors (FGFs) activate FGF receptors (FGFRs) through paracrine or autocrine mechanisms in a process that requires cooperation with heparan sulfate proteoglycans, which function as co-receptors for FGFR activation. By contrast, endocrine FGFs (FGF19, FGF21 and FGF23) are circulating hormones that regulate critical metabolic processes in a variety of tissues. FGF19 regulates bile acid synthesis and lipogenesis, whereas FGF21 stimulates insulin sensitivity, energy expenditure and weight loss. Endocrine FGFs signal through FGFRs in a manner that requires klothos, which are cell-surface proteins that possess tandem glycosidase domains. Here we describe the crystal structures of free and ligand-bound β-klotho extracellular regions that reveal the molecular mechanism that underlies the specificity of FGF21 towards β-klotho and demonstrate how the FGFR is activated in a klotho-dependent manner. β-Klotho serves as a primary 'zip code'-like receptor that acts as a targeting signal for FGF21, and FGFR functions as a catalytic subunit that mediates intracellular signalling. Our structures also show how the sugar-cutting enzyme glycosidase has evolved to become a specific receptor for hormones that regulate metabolic processes, including the lowering of blood sugar levels. Finally, we describe an agonistic variant of FGF21 with enhanced biological activity and present structural insights into the potential development of therapeutic agents for diseases linked to endocrine FGFs.
| S-EPMC6594174 | biostudies-literature
Project description:We sought to analyze the impact of socioeconomic status (SES) on in-hospital outcomes, cost of hospitalization, and resource use after acute ischemic stroke.We used the 2003-2011 Nationwide Inpatient Sample database for this analysis. All admissions with a principal diagnosis of acute ischemic stroke were identified by using International Classification of Diseases, Ninth Revision codes. SES was assessed by using median household income of the residential ZIP code for each patient. Quartile 1 and quartile 4 reflect the lowest-income and highest-income SES quartile, respectively. During a 9-year period, 775,905 discharges with acute ischemic stroke were analyzed. There was a progressive increase in the incidence of reperfusion on the first admission day across the SES quartiles (P-trend<0.001). In addition, we observed a significant reduction in discharge to nursing facility, across the SES quartiles (P-trend<0.001). Although we did not observe a significant difference in in-hospital mortality across the SES quartiles in the overall cohort (P-trend=0.22), there was a significant trend toward reduced in-hospital mortality across the SES quartiles in younger patients (<75 years) (P-trend<0.001). The mean length of stay in the lowest-income quartile was 5.75 days, which was significantly higher compared with other SES quartiles. Furthermore, the mean adjusted cost of hospitalization among quartiles 2, 3, and 4, compared with quartile 1, was significantly higher by $621, $1238, and $2577, respectively. Compared with the lowest-income quartile, there was a significantly higher use of echocardiography, invasive angiography, and operative procedures, including carotid endarterectomy, in the highest-income quartile.Patients from lower-income quartiles had decreased reperfusion on the first admission day, compared with patients from higher-income quartiles. The cost of hospitalization of patients from higher-income quartiles was significantly higher than that of patients from lowest-income quartiles, despite longer hospital stays in the latter group. This might be partially attributable to a lower use of key procedures among patients from lowest-income quartile.
| S-EPMC4392443 | biostudies-other
Project description: Not available
| S-EPMC7210201 | biostudies-literature
Project description:Active genes in yeast can be targeted to the nuclear periphery through interaction of cis-acting "DNA zip codes" with the nuclear pore complex. We find that genes with identical zip codes cluster together. This clustering was specific; pairs of genes that were targeted to the nuclear periphery by different zip codes did not cluster together. Insertion of two different zip codes (GRS I or GRS III) at an ectopic site induced clustering with endogenous genes that have that zip code. Targeting to the nuclear periphery and interaction with the nuclear pore is a prerequisite for gene clustering, but clustering can be maintained in the nucleoplasm. Finally, we find that the Put3 transcription factor recognizes the GRS I zip code to mediate both targeting to the NPC and interchromosomal clustering. These results suggest that zip-code-mediated clustering of genes at the nuclear periphery influences the three-dimensional arrangement of the yeast genome.
| S-EPMC3376219 | biostudies-literature