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Function to compute the T2D score made by Ahola Olli et al. on Nightingale metabolomics data-set.
comp.T2D_Ahola_Olli(met, phen, betas, quiet = FALSE)data-frame containing the value of the T2D-score on the uploaded data-set
numeric data-frame with Nightingale-metabolomics
data-frame containing phenotypic information of the samples (in particular: sex, age, BMI and the clinically measured glucose)
The betas of the linear regression composing the T2D-score
logical to suppress the messages in the console
This metabolomics-based score is associated with incident Type 2 Diabetes, made by Ahola-Olli et al. It is constructed using phe, l_vldl_ce_percentage and l_hdl_fc quantified by Nightingale Health, and some phenotypic information: sex, age, BMI, fasting glucose. It was trained using a stepwise logistic regression on 3 cohorts.
This function is constructed to be able to apply the T2D-score as described in: Ahola-Olli,A.V. et al. (2019) Circulating metabolites and the risk of type 2 diabetes: a prospective study of 11,896 young adults from four Finnish cohorts. Diabetologia, 62, 2298-2309, doi:10.1007/s00125-019-05001-w
prep_met_for_scores, Ahola_Olli_betas, comp.mort_score, comp.CVD_score
library(MiMIR)
#load the dataset
met <- synthetic_metabolic_dataset
phen<-synthetic_phenotypic_dataset
#Prepare the metabolic features fo the mortality score
T2Dscore<-comp.T2D_Ahola_Olli(met= met, phen=phen,betas=MiMIR::Ahola_Olli_betas, quiet=TRUE)
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