scholarly journals %polynova_2way: A SAS macro for implementation of mixed models for metabolomics data

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0244013
Author(s):  
Rodrigo Manjarin ◽  
Magdalena A. Maj ◽  
Michael R. La Frano ◽  
Hunter Glanz
Keyword(s):  
Least Squares ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
P Value ◽  
Data Sets ◽  
Metabolomics Data ◽  
Bonferroni Procedure ◽  
Design Structure ◽  
Metabolomic Data ◽  
Mean Differences

The generation of large metabolomic data sets has created a high demand for software that can fit statistical models to one-metabolite-at-a-time on hundreds of metabolites. We provide the %polynova_2way macro in SAS to identify metabolites differentially expressed in study designs with a two-way factorial treatment and hierarchical design structure. For each metabolite, the macro calculates the least squares means using a linear mixed model with fixed and random effects, runs a 2-way ANOVA, corrects the P-values for the number of metabolites using the false discovery rate or Bonferroni procedure, and calculate the P-value for the least squares mean differences for each metabolite. Finally, the %polynova_2way macro outputs a table in excel format that combines all the results to facilitate the identification of significant metabolites for each factor. The macro code is freely available in the Supporting Information.

P0786CLINICAL SIGNIFICANCE AND RELATED FACTORS OF GFR SLOPE IN A LARGE MULTICENTER OBSERVATIONAL STUDY IN JAPAN

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Yuji Kamijo ◽  
Koji Hashimoto ◽  
Yosuke Yamada ◽  
Makoto Harada ◽  
Masatsugu Aida ◽  
...  
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Clinical Significance ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Surrogate Marker ◽  
Hazard Ratio ◽  
Related Factors ◽  
Ckd Stage ◽  
Egfr Decline

Abstract Background and Aims Recently, glomerular filtration rate (GFR) slope has attracted attention as an important surrogate marker for the prognosis of chronic kidney disease (CKD), with a reduction in slope of eGFR decline by 0.75 mL/min/1.73 m2 per year reportedly having clinical significance. As few large clinical studies on Japanese CKD patients exist, this investigation addresses the clinical significance of GFR slope and its related factors. Method To evaluate the clinical impact of GFR slope, we conducted a prognostic investigation of CKD patients in Japan by means of a large, multicenter, retrospective, observational study. Patients with CKD who were seen at among 15 general hospitals between January and March 2014 were surveyed using medical records. The selection criteria were age ≥20 years, estimated GFR (eGFR) <60 mL/min/1.73 m2, and receiving medical treatment for CKD. Baseline patient characteristics, eGFR changes, and hard endpoints (death or end-stage kidney disease requiring renal replacement therapy) during observation were analysed. We calculated GFR slope using GFR data of 2 years following the observation start point by 2 calculation methods, the linear mixed model and least squares linear regression, and examined the relationship of GFR slope with the hazard ratio of the composite hard endpoints. The factors related to GFR slope were also assessed by multiple regression analysis. Results Among a total of 11233 collected patients, we analyzed the data of 7490 CKD G3 and G4 patients whose GFR data during 2 years could be obtained (60% male, mean age: 71 years, CKD G3a: 55%, G3b: 30%, G4: 15%, mean eGFR: 44.1 mL/min/1.73 m2, urine protein positive: 51%, diabetes mellitus: 49%, use of RAS inhibitors: 57%). The mean observation period was 1040 days. Hard endpoints after the GFR slope measurement period occurred in 301 subjects. The GFR slope of the cohort was -0.948 mL/min/1.73 m2 per year (95% confidence interval [CI] -1.016, -0.880) in the linear mixed model and -0.982 mL/min/1.73 m2 per year (95% CI -1.075, -0.889) according to least squares linear regression. Both calculated GFR slopes were significantly related to the hazard ratio of the composite hard endpoints. Hazard ratio decreased by 0.85 (linear mixed model) and 0.9 (least squares linear regression) times in case of a reduction in slope of eGFR decline by 0.75 mL/min/1.73 m2 per year. Multiple regression analysis revealed strongly significant associations for GFR slope with urine protein and CKD stage and undetectable relationships for GFR slope with diabetes and age. Conclusion This study demonstrated the clinical significance of GFR slope as a surrogate marker for renal prognosis in Japanese CKD patients. In order to reduce slope of eGFR decline, active intervention for proteinuria before the progression to an advanced CKD stage appears to be effective.

scholarly journals Exome-wide association studies in general and long-lived populations identify genetic variants related to human age

2020 ◽  
Author(s):  
Patrick Sin-Chan ◽  
Nehal Gosalia ◽  
Chuan Gao ◽  
Cristopher V. Van Hout ◽  
Bin Ye ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Large Scale ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Association Studies ◽  
Model Systems ◽  
P Value ◽  
Ashkenazi Jews ◽  
Association Analyses ◽  
Age Related

SUMMARYAging is characterized by degeneration in cellular and organismal functions leading to increased disease susceptibility and death. Although our understanding of aging biology in model systems has increased dramatically, large-scale sequencing studies to understand human aging are now just beginning. We applied exome sequencing and association analyses (ExWAS) to identify age-related variants on 58,470 participants of the DiscovEHR cohort. Linear Mixed Model regression analyses of age at last encounter revealed variants in genes known to be linked with clonal hematopoiesis of indeterminate potential, which are associated with myelodysplastic syndromes, as top signals in our analysis, suggestive of age-related somatic mutation accumulation in hematopoietic cells despite patients lacking clinical diagnoses. In addition to APOE, we identified rare DISP2 rs183775254 (p = 7.40×10−10) and ZYG11A rs74227999 (p = 2.50×10−08) variants that were negatively associated with age in either both sexes combined and females, respectively, which were replicated with directional consistency in two independent cohorts. Epigenetic mapping showed these variants are located within cell-type-specific enhancers, suggestive of important transcriptional regulatory functions. To discover variants associated with extreme age, we performed exome-sequencing on persons of Ashkenazi Jewish descent ascertained for extensive lifespans. Case-Control analyses in 525 Ashkenazi Jews cases (Males ≥ 92 years, Females ≥ 95years) were compared to 482 controls. Our results showed variants in APOE (rs429358, rs6857), and TMTC2 (rs7976168) passed Bonferroni-adjusted p-value, as well as several nominally-associated population-specific variants. Collectively, our Age-ExWAS, the largest performed to date, confirmed and identified previously unreported candidate variants associated with human age.

Migration Patterns and Marriage Equality

2017 ◽  
Vol 42 (3) ◽  
pp. 325-343 ◽  
Author(s):  
Carol S. Walther ◽  
Dennis F. Corbin
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
General Social Survey ◽  
Generalized Linear Mixed Model ◽  
Future Research ◽  
Data Sets ◽  
Marriage Equality ◽  
Social Survey ◽  
Migration Patterns ◽  
Attitudes Toward Marriage

Attitudes toward marriage equality have gradually become more accepting as more and more states have passed legislation that acknowledged full or partial recognition of marriage equality. Given the traditionally conservative behavior of the South, this article analyzes how regional migration patterns and time affect attitudes toward marriage equality from the 1988 and the 2004 to 2014 General Social Survey data sets using a generalized linear mixed model. We find that migrant southerners, migrant northerners, and native northerners are more likely to support marriage equality than native southerners are. Furthermore, time seems to also play a significant role in understanding trends in attitudes toward marriage equality. We conclude by suggesting future research.

scholarly journals PSVIII-10 Effects of enzyme supplementation in corn distiller’s dried grains with solubles (DDGS) diets on growth performance in broilers: a meta-analysis

2020 ◽  
Vol 98 (Supplement_3) ◽  
pp. 211-211
Author(s):  
Jae-Cheol Jang ◽  
Zhikai Zeng ◽  
Pedro E Urriola ◽  
Gerald C Shurson
Keyword(s):  
Growth Performance ◽  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Meta Analysis ◽  
Growth Responses ◽  
Exogenous Enzymes ◽  
The Mean ◽  
Enzyme Supplementation ◽  
Mean Differences

Abstract The objective of this study was to conduct a meta-analysis to quantitatively summarize the growth responses of broilers fed cDDGS and the efficacy of various types of dietary enzyme supplementation. A total of 12 publications with 69 observations were included in the database. Individual observations were analyzed using a multivariable linear mixed model. The mean differences (MD) of BWG, FI, and gain efficiency (G/F) were calculated by subtracting either the enzyme response in corn-soybean meal (CSB) or CSB+cDDGS based diets to the control, and was expressed as a percentage (MD = (enzyme – control)/control ×100%). A type of exogenous enzymes (xylanase; protease; carbohydrases; cocktail = proteases + carbohydrases), and feeding phase (starter = d 0 to d 21; finisher = d 21 to d 42 or 49; overall = d 0 to d 42 or more) were included as fixed effects. Dietary enzyme inclusion showed significant improvement on BWG (3.19%, P < 0.01) and G/F (5.69%, P < 0.01) in broilers fed cDDGS diet. However, no significant enzyme responses were observed in broilers fed CSB diet on growth performance. Broilers fed cDDGS diet had increased (P < 0.01) BWG with the addition of protease (3.32 %) and cocktail (3.27 %), whereas addition of xylanased improved (P < 0.01) G/F by (3.56 %) and carbohydrases (1.90 %). Broilers fed cDDGS diet with enzyme supplementation showed greater improvement in BWG (3.71 %, P < 0.01) and G/F (3.78 %, P < 0.01) at finisher phase compared with starter phase. Likewise, Broilers fed CSB diet with enzyme supplementation increased BWG (9.40 %, P < 0.01) and G/F (3.11 %, P < 0.01) at finisher phase. In conclusion, supplementation of xylanase and carbohydrases in cDDGS diet improved G/F, and the enzyme response can be maximized when fed during the finisher phase diet compared with the starter phase diet.

scholarly journals Sparse Unmixing for Hyperspectral Image with Nonlocal Low-Rank Prior

2019 ◽  
Vol 11 (24) ◽  
pp. 2897 ◽  
Author(s):  
Yuhui Zheng ◽  
Feiyang Wu ◽  
Hiuk Jae Shim ◽  
Le Sun
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Spatial Information ◽  
Hyperspectral Image ◽  
Simulated Data ◽  
Hyperspectral Data ◽  
Low Rank ◽  
Data Sets ◽  
Self Similarity ◽  
Model Framework

Hyperspectral unmixing is a key preprocessing technique for hyperspectral image analysis. To further improve the unmixing performance, in this paper, a nonlocal low-rank prior associated with spatial smoothness and spectral collaborative sparsity are integrated together for unmixing the hyperspectral data. The proposed method is based on a fact that hyperspectral images have self-similarity in nonlocal sense and smoothness in local sense. To explore the spatial self-similarity, nonlocal cubic patches are grouped together to compose a low-rank matrix. Then, based on the linear mixed model framework, the nuclear norm is constrained to the abundance matrix of these similar patches to enforce low-rank property. In addition, the local spatial information and spectral characteristic are also taken into account by introducing TV regularization and collaborative sparse terms, respectively. Finally, the results of the experiments on two simulated data sets and two real data sets show that the proposed algorithm produces better performance than other state-of-the-art algorithms.

scholarly journals Prediction of Missing Values in Microarray and Use of Mixed Models to Evaluate the Predictors

2005 ◽  
Vol 4 (1) ◽  
Author(s):  
Guri Feten ◽  
Trygve Almøy ◽  
Are H. Aastveit
Keyword(s):  
Gene Expression ◽  
Missing Values ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Correlation Structure ◽  
Data Sets ◽  
Data Set ◽  
Nearest Neighbours ◽  
Complete Matrix ◽  
The Ideal

Gene expression microarray experiments generate data sets with multiple missing expression values. In some cases, analysis of gene expression requires a complete matrix as input. Either genes with missing values can be removed, or the missing values can be replaced using prediction. We propose six imputation methods. A comparative study of the methods was performed on data from mice and data from the bacterium Enterococcus faecalis, and a linear mixed model was used to test for differences between the methods. The study showed that different methods' capability to predict is dependent on the data, hence the ideal choice of method and number of components are different for each data set. For data with correlation structure methods based on K-nearest neighbours seemed to be best, while for data without correlation structure using the average of the gene was to be preferred.

On Total Least Squares Estimation for Longitudinal Errors-in-Variables Models

2021 ◽  
pp. 359-380
Author(s):  
Rauf Ahmad ◽  
Silvelyn Zwanzig
Keyword(s):  
Least Squares ◽  
Repeated Measures ◽  
Measurement Errors ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Total Least Squares ◽  
Special Focus ◽  
Design Matrix ◽  
Fixed Part ◽  
Set Up

The objective of this study is to evaluate the total least squares (TLS) estimator for the linear mixed model when the design matrix is subject to measurement errors, with special focus on models for longitudinal or repeated-measures data. We consider measurement errors only in the design matrix concerning the fixed part of the model and estimate its corresponding parameter vector under the TLS set up. After treating two variants of the general case, the random coefficient model is discussed as a special case. We evaluate conditions, on the design matrices as well as on variance component parameters, under which a reasonable TLS estimator can be expected in such models. Analysis of a real data example is also provided.

scholarly journals Statistical models for longitudinal zero-inflated count data: application to seizure attacks

2019 ◽  
Vol 19 (3) ◽  
pp. 2555-2564
Author(s):  
Fenta Haile Mekonnen ◽  
Workie Demeke Lakew ◽  
Zike Dereje Tesfaye ◽  
Prafulla Kumar Swain
Keyword(s):  
Risk Factors ◽  
Epileptic Seizure ◽  
Count Data ◽  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Negative Binomial ◽  
P Value ◽  
Longitudinal Outcome ◽  
Seizure Attacks

Background: Chronic non-communicable diseases:- such as epilepsy, are increasingly recognized as public health problems in developing and African countries. This study aimed at finding determinants of the number of epileptic seizure attacks using different count data modeling techniques.Methods: Four common fixed-effects Poisson family models were reviewed to analyze the count data with a high proportion of zeros in longitudinal outcome, i.e., the number of seizure attacks in epilepsy patients. This is because, in addition to the problem of extra zeros, the correlation between measurements upon the same patient at different occasions needs to be taken into consideration.Results: The investigation remarkably identified some important factors associated with epileptic seizure attacks. As people grow old , the number of seizure attacks increased and male patients had more seizures than their female counterparts. In general, a patient’s age, sex, monthly income, family history of epilepsy andservice satisfaction were some of the significant factors responsible for the frequency of seizure attacks (P value<0.05).Conclusion: This study suggests that zero-inflated negative binomial is the best model for predicting and describing the number of seizure attacks as well as identifying the potential risk factors. Addressing these risk factors will definitely contain the progression of seizure attack.Keywords: linear mixed model, hurdle model, seizure attacks, zero-inflated models.

scholarly journals Secondary Genome-Wide Association Study Using Novel Analytical Strategies Disentangle Genetic Components of Cleft Lip and/or Cleft Palate in 1q32.2

Genes ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1280
Author(s):  
Yunju Yang ◽  
Akiko Suzuki ◽  
Junichi Iwata ◽  
Goo Jun
Keyword(s):  
Association Study ◽  
Cleft Lip ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Genome Wide Association Study ◽  
P Value ◽  
Genetic Components ◽  
Genome Wide ◽  
Analytical Strategies ◽  
Project Data

Orofacial cleft (OFC) is one of the most prevalent birth defects, leading to substantial and long-term burdens in a newborn’s quality of life. Although studies revealed several genetic variants associated with the birth defect, novel approaches may provide additional clues about its etiology. Using the Center for Craniofacial and Dental Genetics project data (n = 10,542), we performed linear mixed-model analyses to study the genetic compositions of OFC and investigated the dependence among identified loci using conditional analyses. To identify genes associated with OFC, we conducted a transcriptome-wide association study (TWAS) based on predicted expression levels. In addition to confirming the previous findings at four loci, 1q32.2, 8q24, 2p24.2 and 17p13.1, we untwined two independent loci at 1q32.2, TRAF3IP3 and IRF6. The sentinel SNP in TRAF3IP3 (rs2235370, p-value = 5.15 × 10−9) was independent of the sentinel SNP at IRF6 (rs2235373, r2 < 0.3). We found that the IRF6 effect became nonsignificant once the 8q24 effect was conditioned, while the TRAF3IP3 effect remained significant. Furthermore, we identified nine genes associated with OFC in TWAS, implicating a glutathione synthesis and drug detoxification pathway. We identified some meaningful additions to the OFC etiology using novel statistical methods in the existing data.

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