Circulating miR-21, miR-29a, and miR-126 are associated with premature death risk due to cancer and cardiovascular disease: the JACC Study

AbstractPrimary prevention of premature death is a public health concern worldwide. Circulating microRNAs (miRNAs) have been described as potential diagnostic biomarkers for diseases as cancer and cardiovascular disease (CVD). This case-cohort study aimed to investigate the potential relationship between circulating miRNAs and the risk of premature death. A total of 39,242 subjects provided baseline serum samples in 1988–1990. Of these, 345 subjects who died of intrinsic disease (< 65 years old) and for which measurable samples were available were included in this study. We randomly selected a sub-cohort of 879 subjects. Circulatring miR-21, miR-29a, and miR-126 were determined using qRT-PCR. Conditional logistic regression models were used to analyse the data with respect to stratified miRNA levels. Multivariable logistic regression revealed that subjects with high circulating miR-21 and miR-29a individual levels had a significantly higher risk of total death, cancer death, and CVD death than those with medium miR-21 and miR-29a individual levels. Conversely, subjects with low circulating miR-126 levels had a significantly higher risk of total death than those with medium levels. This suggests that circulating miRNAs are associated with the risk of premature death from cancer and CVD, identifying them as potential biomarkers for early detection of high-risk individuals.

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Identifying Household Level Risk Factors for Unintentional House Fire Incidents, Injuries and Fatalities

International Journal for Population Data Science ◽

10.23889/ijpds.v1i1.336 ◽

2017 ◽

Vol 1 (1) ◽

Author(s):

Samantha Turner ◽

Sarah Rodgers ◽

Ronan Lyons

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Large Scale ◽

Conditional Logistic Regression ◽

Household Composition ◽

Health Concern ◽

Logistic Regression Models ◽

Household Level ◽

Increased Risk ◽

The Uk

ABSTRACTObjectivesUnintentional house fire incidents, injuries and deaths are a serious public health concern in the UK, which disproportionally affect certain groups in the population. Whilst house fires have decreased in recent years; growing financial pressures in the Fire and Rescue Services (FRSs) have resulted in funds dedicated to fire preventative activities becoming increasingly limited. To ensure ever limiting resources are targeted towards those households at greatest risk, it is essential the FRSs’ are accurately informed about the types of household at increased risk. The aim of this project is to undertake a large-scale case-control study, to identify the distinguishing household level risk factors associated with unintentional house fire incidents, injuries and deaths. ApproachUnintentional house fire incidents reported to the Welsh FRS between the years 2003-2008, were anonymised and incorporated into the Secure Anonymised Information Linkage (SAIL) Databank at the Farr Institute, Swansea University. 6943 case households (households which reported a fire to the FRS) were time-matched to 347,150 control households (case:control ratio 1:50). Individuals registered as living at these properties on the date of the fire were established using the Welsh Demographic Service (WDS) dataset. Household level variables will be created by linking case and control households to other demographic, health, educational and environmental datasets in SAIL. Conditional Logistic Regression will be used to estimate matched odds ratios and 95% confidence intervals. ResultsPotential risk factor variables were selected on the basis of a systematic review and theoretically plausible variables. Covariates include: household composition (e.g. age and gender of residents), socioeconomic status, educational attainment, smoking, alcohol consumption, mental health conditions, other health related conditions, mobility and sensory impairments and property related characteristics. Fire related circumstances (e.g. fire ignition source, presence of a smoke alarm) will also be investigated in logistic regression models exploring risk factors for injury and death. Results will be presented at the conference. ConclusionThis is the first large-scale analysis of risk factors for unintentional house fire incidents, injuries and deaths. The findings from this project will be translated into comprehensible infographics, designed to support the FRSs, other partner organisations and the general public, recognise high risk households in need of preventative interventions.

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Abstract 17220: Risk Factors for Recurrent Peripartum Cardiomyopathy in 783 Women in California

Circulation ◽

10.1161/circ.138.suppl_1.17220 ◽

2018 ◽

Vol 138 (Suppl_1) ◽

Author(s):

Punag Divanji ◽

Gregory Nah ◽

Ian Harris ◽

Anu Agarwal ◽

Nisha I Parikh

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

Logistic Regression ◽

Regression Models ◽

Subsequent Pregnancy ◽

Peripartum Cardiomyopathy ◽

Lv Function ◽

Logistic Regression Models ◽

Grand Multiparity ◽

Adjusted Logistic Regression

Introduction: Characterized by significant left ventricular (LV) dysfunction and clinical heart failure (HF), peripartum cardiomyopathy (PPCM) has an incidence of approximately 1/2200 live births (0.04%). Prior studies estimate that approximately 25% of those with recovered LV function will have recurrent clinical PPCM during subsequent pregnancies, compared to 50% of those without recovered LV function. Specific predictors of recurrent PPCM have not been studied in cohorts with large numbers. Methods: From 2005-2011, we identified 1,872,227 pregnancies by International Classification of Diseases, 9th Revision (ICD-9) codes in the California Healthcare Cost and Utilization Project (HCUP) database, which captures over 95% of the California hospitalized population. Excluding 15,765 women with prior cardiovascular disease (myocardial infarction, coronary artery disease, stroke, HF, valve disease, or congenital heart disease), yielded n=1,856,462 women. Among women without prior cardiovascular disease, we identified index and subsequent pregnancies with PPCM to determine episodes of recurrent PPCM. We considered the following potential predictors of PPCM recurrence in both univariate and age-adjusted logistic regression models: age, race, hypertension, diabetes, smoking, obesity, chronic kidney disease, family history, pre-eclampsia, ectopic pregnancy, income, and insurance status. Results: In HCUP, n=783 women had pregnancies complicated by PPCM (mean age=30.8 years). Among these women, n=133 had a subsequent pregnancy (17%; mean age=28.1 years), with a mean follow-up of 4.34 years (±1.71 years). In this group of 133 subsequent pregnancies, n=14 (10.5%) were complicated by recurrent PPCM, with a mean time-to-event of 2.2 years (±1.89 years). Among the risk factors studied, the only univariate predictor of recurrent PPCM was grand multiparity, defined as ≥ 5 previous deliveries (odds ratio: 22; 95% confidence interval 4.43-118.22). The other predictors we studied were not significantly associated with recurrent PPCM in either univariate or multivariable models. Conclusion: In a large population database in California with 783 cases of PPCM over a 6-year period, 17% of women had a subsequent pregnancy, of which 10.5% had recurrent PPCM. In age-adjusted logistic regression models, grand multiparity was the only statistically significant predictor of recurrent PPCM.

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BAFF Predicts Immunogenicity in Older Patients With Rheumatoid Arthritis Treated With TNF Inhibitors

10.21203/rs.3.rs-74233/v1 ◽

2020 ◽

Author(s):

Borja Hernández-Breijo ◽

Victoria Navarro-Compán ◽

Chamaida Plasencia-Rodríguez ◽

Ioannis Parodis ◽

Johanna E. Gehin ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Older Patients ◽

Operating Characteristic ◽

Certolizumab Pegol ◽

Positive Likelihood Ratio ◽

Characteristic Analysis ◽

Serum Samples ◽

Chi Square ◽

Baseline Serum ◽

Logistic Regression Models

Abstract Background: Immunogenicity related to treatment with TNF inhibitors (TNFi) is one of the causes for the decreased attainment of clinical response in patients with rheumatoid arthritis (RA). The B-cell activating factor (BAFF) may be playing a role in the development of immunogenicity. The objective of this study was to analyse the association of baseline concentration of serum BAFF with immunogenicity after 6 months of TNFi treatment.Methods: A total of 139 patients with RA starting a TNFi (infliximab, adalimumab, certolizumab pegol or golimumab) were followed-up for 6 months. Serum samples were obtained at baseline and at 6 months and anti-drug antibody (ADA) and BAFF concentrations were measured. Logistic regression models were employed in order to analyse the association between BAFF concentrations and immunogenicity. Receiver operating characteristic analysis was performed to determine the BAFF concentrations with a greater likelihood of showing immunogenicity association.Results: At 6 months, 39 patients (28%) developed ADA. A significant interaction between the age and baseline BAFF concentration was found for the development of ADA (Wald chi-square value=5.30; p=0.02); therefore, subsequent results were stratified according to mean age (≤/>55 years). Baseline serum BAFF concentration was independently associated with ADA development only in patients over 55 years (OR=1.55; 95% CI: 1.03-2.12). Baseline serum BAFF≥1034pg/mL predicted the presence of ADA at 6 months (positive likelihood ratio=3.7).Conclusions: Our results suggest that the association of BAFF concentration and immunogenicity depends on the patient’s age. Baseline serum BAFF concentration predicts the presence of ADA within 6 months of TNFi therapy in older patients with RA.

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Circulating microRNAs in Fabry Disease

Scientific Reports ◽

10.1038/s41598-019-51805-6 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 5

Author(s):

Ke Xiao ◽

Dongchao Lu ◽

Jeannine Hoepfner ◽

Laura Santer ◽

Shashi Gupta ◽

...

Keyword(s):

Fabry Disease ◽

Premature Death ◽

Circulating Mirnas ◽

Serum Samples ◽

Significant Differential Expression ◽

Enzyme Replacement ◽

Beneficial Effects ◽

Mirna Sequencing ◽

Continuous Progress ◽

Alpha Galactosidase

Abstract Fabry disease is an X-linked deficiency of the lysosomal hydrolase alpha-galactosidase A (alpha-Gal). This results in an accumulation of globotriaosylceramide (GL-3/Gb3) in a variety of cells with subsequent functional impairment. The continuous progress of FD often leads to decreased quality of life and premature death caused by multi-organic complications. The overall aim of our study was to determine the amount of circulating miRNAs in Fabry patients and to test whether ERT would alter the level of individual circulating miRNAs. We used miRNA sequencing by the HTG EdgeSeq System to identify the circulating miRNA pool from Fabry patients with and without enzyme replacement therapy (n = 6). In total, 296 miRNAs in serum of patients were identified. Among them 9 miRNAs were further evaluated in extra serum samples (n = 31) using real-time qPCR and 6 of them showed significant differential expression. The resulting miRNA pattern may help to better understand mechanisms involved in the beneficial effects of ERT and these new miRNA markers could help to estimate the efficacy of ERT or to identify Fabry patients with specific need for ERT.

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On marginal and conditional parameters in logistic regression models

Biometrika ◽

10.1093/biomet/asz019 ◽

2019 ◽

Vol 106 (3) ◽

pp. 732-739

Author(s):

Elena Stanghellini ◽

Marco Doretti

Keyword(s):

Logistic Regression ◽

Regression Models ◽

Conditional Logistic Regression ◽

Exact Formula ◽

Logistic Regression Models ◽

Conditional Models ◽

Data Generating Process ◽

Binary Random Variables ◽

Intermediate Variables ◽

Relevant Covariates

Summary We derive the exact formula linking the parameters of marginal and conditional logistic regression models with binary mediators when no conditional independence assumptions can be made. The formula has the appealing property of being the sum of terms that vanish whenever parameters of the conditional models vanish, thereby recovering well-known results as particular cases. It also permits the disentangling of direct and indirect effects as well as quantifying the distortion induced by the omission of relevant covariates, opening the way to sensitivity analysis. As the parameters of the conditional models are multiplied by terms that are always bounded, the derivations may also be used to construct reasonable bounds on the parameters of interest when relevant intermediate variables are unobserved. We assume that, conditionally on a set of covariates, the data-generating process can be represented by a directed acyclic graph. We also show how the results presented here lead to the extension of path analysis to a system of binary random variables.

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The impact of diabetes on multiple avoidable admissions: a cross-sectional study

BMC Health Services Research ◽

10.1186/s12913-019-4840-4 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 1

Author(s):

Joana Seringa ◽

Ana Patrícia Marques ◽

Bruno Moita ◽

Cátia Gaspar ◽

João Filipe Raposo ◽

...

Keyword(s):

Logistic Regression ◽

Age Groups ◽

Health Care Expenditures ◽

Cross Sectional Study ◽

Health Concern ◽

Diabetes Diagnosis ◽

Cross Sectional ◽

Younger Adults ◽

Logistic Regression Models ◽

The Impact

Abstract Background Multiple admissions for ambulatory care sensitive conditions (ACSC) are responsible for an important proportion of health care expenditures. Diabetes is one of the conditions consensually classified as an ACSC being considered a major public health concern. The aim of this study was to analyse the impact of diabetes on the occurrence of multiple admissions for ACSC. Methods We analysed inpatient data of all public Portuguese NHS hospitals from 2013 to 2015 on multiple admissions for ACSC among adults aged 18 or older. Multiple ACSC users were identified if they had two or more admissions for any ACSC during the period of analysis. Two logistic regression models were computed. A baseline model where a logistic regression was performed to assess the association between multiple admissions and the presence of diabetes, adjusting for age and sex. A full model to test if diabetes had no constant association with multiple admissions by any ACSC across age groups. Results Among 301,334 ACSC admissions, 144,209 (47.9%) were classified as multiple admissions and from those, 59,436 had diabetes diagnosis, which corresponded to 23,692 patients. Patients with diabetes were 1.49 times (p < 0,001) more likely to be admitted multiple times for any ACSC than patients without diabetes. Younger adults with diabetes (18–39 years old) were more likely to become multiple users. Conclusion Diabetes increases the risk of multiple admissions for ACSC, especially in younger adults. Diabetes presence is associated with a higher resource utilization, which highlights the need for the implementation of adequate management of chronic diseases policies.

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1400Central but not general obesity is positively associated with risk of hyperhomocysteinemia in middle-aged women

International Journal of Epidemiology ◽

10.1093/ije/dyab168.696 ◽

2021 ◽

Vol 50 (Supplement_1) ◽

Author(s):

Yingying Wang

Keyword(s):

Cardiovascular Disease ◽

Logistic Regression ◽

Regression Models ◽

Central Obesity ◽

Multiple Logistic Regression ◽

Obese Women ◽

General Obesity ◽

Middle Aged ◽

Logistic Regression Models ◽

The Relationship

Abstract Background Obesity and homocysteine (Hcy) are two important risk factors for cardiovascular disease (CVD); however, there were conflicting results for the relationship between them. Our study is to explore the associations of general and central obesity with hyperhomocysteinemia (HHcy) in middle-aged women. Methods The current analysis was based on data from 11007 women aged 40-60 years. Height, weight, and waist circumference (WC) were measured and serum homocysteine was determined. Multiple logistic regression models were used to assess the associations of the risk of hyperhomocysteinemia (HHcy, Hcy>15μmol/L) with BMI and WC. Results 13.71% women had HHcy. The prevalences of BMI-based general obesity and WC-based central obesity were 11.17% and 22.88%, respectively. Compared with non-obese women, the mean serum Hcy concentration was significantly higher in WC-based central obese women (P = 0.002), but not in BMI-based general obese women (P > 0.05). In the multiple logistic regression models, central obesity was positively related to the risk of HHcy (OR = 1.30, 95%CI=1.10 to 1.52), while general obesity was inversely related to the risk of HHcy (OR = 0.82, 95%CI=0.72 to 0.93 and OR = 0.71,95% CI = 0.57 to 0.89). Conclusions Central obesity was positively, while general obesity was negatively related to the risk of HHcy. Menopause showed no effect modification on these associations. Key messages Homocysteine; Central obesity; Menopause; Cardiovascular Disease

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Persistent organic pollutants distribution in plasma lipoprotein fractions

Brazilian Journal of Biology ◽

10.1590/1519-6984.248910 ◽

2023 ◽

Vol 83 ◽

Author(s):

S. Khwaja ◽

S. I. Hussain ◽

M. Zahid ◽

Z. Aziz ◽

A. Akram ◽

...

Keyword(s):

Blood Pressure ◽

Cardiovascular Disease ◽

Logistic Regression ◽

Regression Model ◽

Lipid Profile ◽

Organic Pollutants ◽

Persistent Organic Pollutants ◽

Logistic Regression Model ◽

Serum Samples ◽

Binary Logistic Regression Model

Abstract This study determines the associations among serum lipid profiles, risk of cardiovascular disease, and persistent organic pollutants. Using Gas chromatography technique, the intensity of toxic pollutant residues in serum samples of Hypertensive patients were measured. Based on statistical analysis, the effects of different covariates namely pesticides, age, systolic blood pressure, diastolic blood pressure, and lipid profile duration was checked using the logistic regression model. Statistical computation was performed on SPSS 22.0. The P-values of F-Statistic for each lipid profile class are greater than 0.01 (1%), therefore we cannot reject the null hypothesis for all cases. The estimated coefficients, their standard errors, Wald Statistic, and odds ratio of the binary logistic regression model for different lipid profile parameters indicate if pesticides increase then the logit value of different lipid profile parameters changes from -0.46 to -0.246 except LDL which increases by 0.135. The study reports a significantly increased threat of cardiovascular disease with increased concentrations of toxic pollutants.

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Abstract P879: Differences in Statistical Performance of Polygenic Risk Scores for Cardiovascular Disease Across Different Race/Ethnicities

Stroke ◽

10.1161/str.52.suppl_1.p879 ◽

2021 ◽

Vol 52 (Suppl_1) ◽

Author(s):

Julian N Acosta ◽

Cameron Both ◽

Natalia Szejko ◽

Stacy Brown ◽

Kevin N Sheth ◽

...

Keyword(s):

Cardiovascular Disease ◽

Logistic Regression ◽

Genetic Risk ◽

Regression Models ◽

Risk Scores ◽

Uk Biobank ◽

Polygenic Risk ◽

Logistic Regression Models ◽

The Uk ◽

Significant Health

Introduction: Genome-wide association studies have identified numerous genetic risk variants for stroke and myocardial infarction (MI) in Europeans. However, the limited applicability of these results to non-Europeans due to racial/ethnic differences in the genetic architecture of cardiovascular disease (CVD), coupled with the limited availability of genomic data in non-Europeans, may create significant health disparities now that genomic-based precision medicine is a reality. We tested the hypothesis that the performance of polygenic risk scores (PRS) for CVD differ in Europeans versus non-Europeans. Methods: We conducted a nested study within the UK Biobank, a prospective, population-based study that enrolled ~500,000 participants across the UK. For this study, we identified self-reported black participants and randomly matched them 1:1 by age and sex with white participants. We created a PRS using previously discovered loci for stroke and MI. We then tested whether this PRS representing the aggregate polygenic susceptibility to CVD yielded similar precision in black versus white participants in logistic regression models. Results: Of the 502,536 participants enrolled in the UK Biobank, 8,061 were self-reported blacks, with 7,644 having available data for our analyses. We randomly matched these participants with white individuals, leading to a total sample size of 15,288 (mean age 51.9 [SD 8.1], female 8,722 [57%]). The total number of events was 741 overall, with 363 happening in blacks and 378 happening in whites. In logistic regression models including age, sex, and 5 principal components, the statistical precision (e.g. narrower confidence intervals) for the PRS was substantially higher for whites (OR 1.22, 95%CI 1.08 - 1.37; p<0.0001) compared to blacks (OR 1.24, 95%CI 1.05-1.47; p=0.01). Secondary analyses using genetically-determined ancestry yielded similar results. Conclusion: Because CVD-related PRSs are derived mainly using genetic risk factors identified in populations of European ancestry, their statistical performance is lower in non-European populations. This asymmetry can lead to significant health disparities now that these tools are being evaluated in multiple precision medicine approaches.

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Evaluation of female breast cancer risk among the betel quid chewer: A bio-statistical assessment in Assam, India

Nepal Journal of Epidemiology ◽

10.3126/nje.v5i2.12832 ◽

2015 ◽

Vol 5 (2) ◽

pp. 494-498 ◽

Cited By ~ 1

Author(s):

Nijara Rajbongshi ◽

Lipi B Mahanta ◽

Dilip C Nath

Keyword(s):

Breast Cancer ◽

Logistic Regression ◽

Family Income ◽

Conditional Logistic Regression ◽

Female Breast Cancer ◽

Betel Quid ◽

P Value ◽

Female Population ◽

Logistic Regression Models ◽

Matched Case

Background: Breast cancer is the most commonly diagnosed cancer among the female population of Assam, India. Chewing of betel quid with or without tobacco is common practice among female population of this region. Moreoverthe method of preparing the betel quid is different from other parts of the country.So matched case control study is conducted to analyse whetherbetel quid chewing plays a significant role in the high incidence of breast cancer occurrences in Assam. Methods and Material: Here, controls are matched to the cases by age at diagnosis (±5 years), family income and place of residence with matching ratio 1:1. Conditional logistic regression models and odd ratios (OR) was used to draw conclusions. Results: It is observed that cases are more habituated to chewing habits than the controls.Further the conditional logistic regression analysis reveals that betel quid chewer faces 2.353 times more risk having breast cancer than the non-chewer with p value 0.0003 (95% CI 1.334-4.150). Conclusion:Though the female population in Assam usually does not smoke, the addictive habits typical to this region have equal effect on the occurrence of breast cancer.DOI: http://dx.doi.org/10.3126/nje.v5i2.12832Nepal J Epidemiol. 2015;5(2); 494-498.

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