scholarly journals Characterization of direct and/or indirect genetic associations for multiple traits in longitudinal studies of disease progression

2021 ◽  
Author(s):  
Myriam Brossard ◽  
Andrew D. Paterson ◽  
Osvaldo Espin-Garcia ◽  
Radu V. Craiu ◽  
Shelley B. Bull
Keyword(s):  
Risk Factors ◽  
Disease Progression ◽  
Complex Traits ◽  
Measurement Errors ◽  
Joint Model ◽  
Alternative Methods ◽  
Joint Analysis ◽  
Multiple Time ◽  
Time To Event ◽  
Subject Specific

When quantitative longitudinal traits are risk factors for disease progression, endogenous, and/or subject to random errors, joint model specification of multiple time-to-event and multiple longitudinal traits can effectively identify direct and/or indirect genetic association of single nucleotide polymorphisms (SNPs) with time-to-event traits. Here, we present a joint model that integrates: i) a linear mixed model describing the trajectory of each longitudinal trait as a function of time, SNP effects and subject-specific random effects, and ii) a frailty Cox survival model that depends on SNPs, longitudinal trajectory effects, and a subject-specific frailty term accounting for unexplained dependency between time-to-event traits. Inference is based on a two-stage approach with bootstrap joint covariance estimation. We develop a hypothesis testing procedure to identify direct and/or indirect SNP association with each time-to-event trait. Motivated by complex genetic architecture of type 1 diabetes complications (T1DC) observed in the Diabetes Control and Complications Trial (DCCT), we show by realistic simulation study that joint modelling of two time-to-T1DC (retinopathy, nephropathy) and two longitudinal risk factors (HbA1c, systolic blood pressure) reduces bias and improves identification of direct and/or indirect SNP associations, compared to alternative methods ignoring measurement errors in intermediate risk factors. Through analysis of DCCT, we identify two SNPs with indirect associations with multiple time-to-T1DC traits and obtain similar conclusions using alternative formulations of time-dependent HbA1c effects on T1DC. In total, joint analysis of multiple longitudinal and multiple time-to-event traits provides insight into etiology of complex traits.

scholarly journals Association between CD4, CD4/CD8 ratio and viral blips among virally suppressed HIV patients – a joint disease progression and time-to-event model

2021 ◽  
Author(s):  
Ngah Kuan Chow ◽  
Sabariah Noor Harun ◽  
Amer Hayat Khan
Keyword(s):  
Risk Factors ◽  
Disease Progression ◽  
Recovery Rate ◽  
Significant Risk ◽  
Hiv Treatment ◽  
Joint Disease ◽  
Care Plan ◽  
Hiv Positive ◽  
Time To Event ◽  
Term Care

Aim Viral blips that occur among virally suppressed HIV-positive patients suggest immune activation and inflammation and associated with slower CD4 count and CD4/CD8 ratio normalisation. With the advances in HIV treatment, lifestyle and comorbidities begin to be a concern despite successful antiretroviral therapy. We reported a study incorporating the effect of CD4 and CD4/CD8 ratio normalisation on viral blips in joint disease progression (DP) and time-to-event (TTE) model. Methods A total of 152 HIV-positive patients receiving efavirenz therapy were recruited. Joint DP and TTE models on viral blip were developed for CD4 and CD4/CD8 ratio separately. Risk factors, such as smoking status, pack-year and comorbidity scores, were included in the analysis. Results Gompertz model best described the CD4 and CD4/CD8 ratio DP models, while viral blips data were fitted with the Cox proportional hazard model. History of opportunistic infections and changing of antiretroviral regimen significantly affect the baseline CD4 and CD4/CD8 ratio. Comorbidity score was significant in both CD4 (asymptote CD4) and CD4/CD8 ratio DP model (recovery rate). Increase in cumulative pack-year resulted in lower CD4/CD8 ratio recovery rate (β -0.02, 95%CI: -0.03 to -0.01; p<0.001). Active smokers with slow CD4 or CD4/CD8 ratio normalisation associated with more viral blips. Conclusion CD4 and CD4/CD8 ratio are significant risk factors of viral blips and potential markers of non-AIDS related morbidities in virally suppressed patients. Early identification of high-risk group with repeated viral load testing, lifestyle modification and comorbidities management should be emphasised in the HIV treatment long-term care plan.

A Joint Model for Longitudinal and Time-to-event Data in Social and Life Course Research: Employment Status and Time to Retirement

2021 ◽  
pp. 004912412110557
Author(s):  
Jolien Cremers ◽  
Laust Hvas Mortensen ◽  
Claus Thorn Ekstrøm
Keyword(s):  
Event History Analysis ◽  
Social Research ◽  
Joint Model ◽  
Event History ◽  
Multiple Time ◽  
Time To Event ◽  
Joint Models ◽  
Longitudinal Outcome ◽  
Endogenous Covariates ◽  
Association Structure

Longitudinal studies including a time-to-event outcome in social research often use a form of event history analysis to analyse the influence of time-varying endogenous covariates on the time-to-event outcome. Many standard event history models however assume the covariates of interest to be exogenous and inclusion of an endogenous covariate may lead to bias. Although such bias can be dealt with by using joint models for longitudinal and time-to-event outcomes, these types of models are underused in social research. In order to fill this gap in the social science modelling toolkit, we introduce a novel Bayesian joint model in which a multinomial longitudinal outcome is modelled simultaneously with a time-to-event outcome. The methodological novelty of this model is that it concerns a correlated random effects association structure that includes a multinomial longitudinal outcome. We show the use of the joint model on Danish labour market data and compare the joint model to a standard event history model. The joint model has three advantages over a standard survival model. It decreases bias, allows us to explore the relation between exogenous covariates and the longitudinal outcome and can be flexibly extended with multiple time-to-event and longitudinal outcomes.

scholarly journals The hemocyte counts as a potential biomarker for predicting disease progression in COVID-19: a retrospective study

2020 ◽  
Vol 58 (7) ◽  
pp. 1106-1115 ◽  
Author(s):  
Yufen Zheng ◽  
Ying Zhang ◽  
Hongbo Chi ◽  
Shiyong Chen ◽  
Minfei Peng ◽  
...  
Keyword(s):  
Risk Factors ◽  
Platelet Count ◽  
Disease Progression ◽  
Neutrophil Count ◽  
Calibration Curve ◽  
Lymphocyte Count ◽  
Severe Disease ◽  
Clinical Impact ◽  
Predictive Tool ◽  
Potential Biomarker

AbstractObjectivesIn December 2019, there was an outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China, and since then, the disease has been increasingly spread throughout the world. Unfortunately, the information about early prediction factors for disease progression is relatively limited. Therefore, there is an urgent need to investigate the risk factors of developing severe disease. The objective of the study was to reveal the risk factors of developing severe disease by comparing the differences in the hemocyte count and dynamic profiles in patients with severe and non-severe COVID-19.MethodsIn this retrospectively analyzed cohort, 141 confirmed COVID-19 patients were enrolled in Taizhou Public Health Medical Center, Taizhou Hospital, Zhejiang Province, China, from January 17, 2020 to February 26, 2020. Clinical characteristics and hemocyte counts of severe and non-severe COVID patients were collected. The differences in the hemocyte counts and dynamic profiles in patients with severe and non-severe COVID-19 were compared. Multivariate Cox regression analysis was performed to identify potential biomarkers for predicting disease progression. A concordance index (C-index), calibration curve, decision curve and the clinical impact curve were calculated to assess the predictive accuracy.ResultsThe data showed that the white blood cell count, neutrophil count and platelet count were normal on the day of hospital admission in most COVID-19 patients (87.9%, 85.1% and 88.7%, respectively). A total of 82.8% of severe patients had lymphopenia after the onset of symptoms, and as the disease progressed, there was marked lymphopenia. Multivariate Cox analysis showed that the neutrophil count (hazard ratio [HR] = 4.441, 95% CI = 1.954–10.090, p = 0.000), lymphocyte count (HR = 0.255, 95% CI = 0.097–0.669, p = 0.006) and platelet count (HR = 0.244, 95% CI = 0.111–0.537, p = 0.000) were independent risk factors for disease progression. The C-index (0.821 [95% CI, 0.746–0.896]), calibration curve, decision curve and the clinical impact curve showed that the nomogram can be used to predict the disease progression in COVID-19 patients accurately. In addition, the data involving the neutrophil count, lymphocyte count and platelet count (NLP score) have something to do with improving risk stratification and management of COVID-19 patients.ConclusionsWe designed a clinically predictive tool which is easy to use for assessing the progression risk of COVID-19, and the NLP score could be used to facilitate patient stratification management.

scholarly journals THU0070 DEFINING SYNOVIAL SIGNATURES IN THE RAT CIA MODEL: WHAT CAN WE LEARN ABOUT RA PROGRESSION?

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 247.2-248
Author(s):  
D. Ruelas ◽  
R. LI ◽  
C. Franci ◽  
V. Lira ◽  
D. Lopez ◽  
...  
Keyword(s):  
Disease Progression ◽  
Synovial Tissue ◽  
Current Knowledge ◽  
Severe Disease ◽  
Unmet Need ◽  
Poor Response ◽  
Multiple Time ◽  
Combination Therapies ◽  
Course Of Disease ◽  
Time Point

Background:Patients showing inadequate or no response to current therapies represent a key unmet need in rheumatoid arthritis (RA). To address this, novel or combination therapies are of high clinical interest. Identification of novel therapeutic targets requires a greater understanding of the pathogenic molecular drivers in the RA synovium. However, our current knowledge of human molecular patterns that emerge as a result of disease progression is complicated by patient-to-patient heterogeneity and access to synovial tissue.Objectives:Here we use the current knowledge of human synovial heterogeneity to conduct a longitudinal study of global molecular responses in the rat collagen-induced arthritis (CIA) model to better understand synovial biology, improve the preclinical modeling of human disease, and discover novel targets for RA.Methods:A rat CIA model was performed as previously described.1RNA-Seq was performed on 56 knee synovial tissues collected at multiple time points throughout the course of disease. Differential gene expression was determined at each individual time point and longitudinally with disease progression. Published human synovial datasets were used to categorize these genes into myeloid, lymphoid, fibroid, and low inflammatory signatures.2Differentially expressed genes (DEGs) at each time point were compared to human synovial datasets of RA patients before and after treatment. In addition, we compared disease-driven genes in CIA to genes in RA patients that are unchanged following therapy to identify possible combination therapies.Results:Disease pathology in the rat CIA natural history study progressed as expected: significant decreases were seen in body weight, as well as increases in ankle diameter, paw weight, and histopathology scores of joints in collagen-injected vs noninjected rats. There were 1900 DEGs identified between diseased and naïve rats over the course of disease, representing disease-induced gene signatures (Fig. 1). Comparing these DEGs to reported human RA synovial signatures, both the lymphoid and myeloid signatures were found to be highly upregulated. Interestingly, there were no significant DEGs representing the human fibroid and low inflammatory synovial signatures identified in the CIA rat model. This suggests that the rat CIA model most closely models RA patients with an immune synovial phenotype. In addition, we examined the overlap between disease-driven genes in CIA and genes in RA patients that are unchanged following therapy to identify signaling pathways that may be of utility in combination therapy. Of genes that were upregulated in CIA, 94% of genes that mapped to extracellular matrix-receptor pathways remained unchanged in the synovial tissue of RA patients following tocilizumab treatment.Conclusion:Previous studies have shown that nearly 30% of treatment-naïve early RA patients exhibit a strong fibroid phenotype that correlates with less severe disease and a relatively poor response to disease-modifying anti-rheumatic drugs.3These data indicate that the synovial biology associated with such patients (fibroid or pauci-immune) is not well captured in CIA, the most common preclinical RA model. To assess potential new therapies targeting these patients, it will be necessary to develop alternative animal models with more intact fibroid signatures. In addition to these findings, we also characterized the global molecular changes that occur with disease progression in the CIA rat and made a comparison to RA patients on treatment, providing an overall understanding of disease-relevant pathways in the synovium that may point to possible combination therapies.References:[1]Trentham DE, et al.J Exp Med. 1977;146(3):857-868.[2]Dennis G Jr, et al.Arthritis Res Ther. 2014;16(2):R90.[3]Humby F, et al.Ann Rheum Dis. 2019;78(6):761-772.Disclosure of Interests:Debbie Ruelas Employee of: Gilead, Ruidong Li Employee of: Gilead, Christian Franci Employee of: Gilead, Victor Lira Employee of: Gilead, David Lopez Employee of: Gilead, Li Li Employee of: Gilead, Gundula Min-Oo Employee of: Gilead, Julie A. Di Paolo Employee of: Gilead

scholarly journals 157. patient to Environment Transmission of Multidrug-resistant Bacteria Within Intensive Care Units

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S207-S208
Author(s):  
Matthew J Ziegler ◽  
Brendan Kelly ◽  
Michael Z David ◽  
Lauren Dutcher ◽  
Pam C Tolomeo ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Multidrug Resistant ◽  
Resistant Bacteria ◽  
Multiple Time ◽  
Extended Spectrum Beta Lactamase ◽  
Environmental Transmission ◽  
Body Culture ◽  
Clinical Culture ◽  
Multiple Time Points

Abstract Background Identifying risk factors for environmental contamination with multidrug-resistant organisms (MDROs) is essential to prioritize methods for prevention of hospital transmission. Methods Patients admitted to an ICU with an MDRO detected on clinical culture in the prior 30 days were enrolled. Patients (4 body sites) and high-touch objects (HTO) (3 composite sites) in ICU rooms were sampled. Environmental transmission was defined by shared MDRO species cultured on patient and HTO cultures obtained on multiple time points during the patient’s stay. Risk factors for environmental transmission were identified with logistic regression. Results Forty-five patients were included (median 2 days of longitudinal sampling [IQR 1–4 days]). Enrollment anatomic cultures included extended-spectrum beta-lactamase-producing Enterobacterales (ESBLE) (n=12, 27%), carbapenem-resistant organisms (CRO) (n=4, 9%), methicillin-resistant S.aureus (MRSA) (n=11, 24%), vancomycin-resistant Enterococci (VRE) (n=4, 9%), and C.difficile (CDIFF) (n=14, 31%). Patient colonization during serial sampling was common with CRO (n=21, 47%), ESBLE (n=16, 36%), and VRE (n=16, 36%) and less so with MRSA (n=7, 16%) and CDIFF (n=5, 11%). Detection of MDROs on environmental surfaces was also common with identification of CRO in 47% of patient rooms (n=21) and ESBLE in 29% (n=13); MRSA (n=2, 4%), VRE (n=9, 20%), and CDIFF (n=3, 7%) were rarer. Patient to environment transmission was observed in 40% of rooms (n=18). Thirteen (29%) rooms had foreign MDRO contamination (i.e., one not detected on a body culture), most (n=10) with CRO. Environmental MDROs were most common in bathroom/sinks (n=22), followed by surfaces near the patient (n=10), and least common surfaces often touched by staff within the room (n=6). On multivariable logistic regression, naïve to clustering by patient, recent receipt of a proton pump inhibitor (OR 2.35, 95% CI 1.00 – 5.52, P=0.049) and presence of one or more wounds (OR 2.56, 95% CI 1.05 – 6.26, P=0.038) were significantly associated with environmental transmission (OR 1.56, 95% CI 1.01 – 2.43, P=0.046) (Table 1). Conclusion MDRO contamination of patient rooms is common with detection of organisms attributed to, and foreign to, the occupant. Disclosures Michael Z. David, MD PhD, GSK (Consultant)

P146 Disease progression in del (5q) MDS patients treated with lenalidomide: analysis of risk factors and long-term outcome in 44 patients

2007 ◽  
Vol 31 ◽  
pp. S120-S121
Author(s):  
A.A.N. Giagounidis ◽  
S. Haase ◽  
V. Lohrbacher ◽  
M. Heinsch ◽  
B. Schuran ◽  
...  
Keyword(s):  
Risk Factors ◽  
Disease Progression ◽  
Term Outcome ◽  
Long Term Outcome

Gait Risk Factors for Disease Progression Differ Between Non-traumatic and Post-traumatic Knee Osteoarthritis

2021 ◽  
Author(s):  
Shawn M. Robbins ◽  
Jean-Pierre Pelletier ◽  
François Abram ◽  
Mathieu Boily ◽  
John Antoniou ◽  
...  
Keyword(s):  
Risk Factors ◽  
Knee Osteoarthritis ◽  
Disease Progression ◽  
Post Traumatic

scholarly journals Toward a Comprehensive Developmental Model for Alcohol Use Disorders in Men

2011 ◽  
Vol 14 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Kenneth S. Kendler ◽  
Charles O. Gardner ◽  
Carol A. Prescott
Keyword(s):  
Risk Factors ◽  
Alcohol Use ◽  
Social Factors ◽  
Complex Traits ◽  
Internalizing Symptoms ◽  
Peer Group ◽  
Alcohol Use Disorders ◽  
Developmental Model ◽  
Minor Role ◽  
Late Adolescent

The multiple risk factors for alcohol use (AU) and alcohol use disorders (AUDs) are interrelated through poorly understood pathways, many of which begin in childhood. In this report, the authors seek to develop an empirical, broad-based developmental model for the etiology of AU and AUDs in men. We assessed 15 risk factors in four developmental tiers in 1,794 adult male twins from the Virginia population based twin registry. The best fitting model explained 39% of the variance in late adolescent AU, and 30% of the liability to lifetime symptoms of AUD. AU and AUDs can be best understood as arising from the action and interaction of two pathways reflecting externalizing genetic/temperamental and familial/social factors. Peer group deviance was important in each pathway. Internalizing symptoms played a more minor role. Familial/social factors were especially important influences on AU, while genetic/temperamental factors were more critical for AUDs. We conclude that AU and AUDs in men are complex traits influenced by genetic, family, temperamental, and social factors, acting and interacting over developmental time.

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