This calculator is to estimate the risk of new onset diabetes within first year post transplant among liver transplant recipients who had no past medical history of diabetes before transplant.
Recipient's T2D-PRS, z-score i Assuming Si is the summary statistic for the effective allele for the ith SNP and Gij is the number of the effective allele of the ith SNP observed in the jth individual, PRS for the jth individual (PRSj) can be calculated as $$PRS_{j}=\sum_{i}S_{i}\times G_{ij}$$ For the T2D-PRS, summary statistics for the top 403 GWAS-significant SNPs were obtained from this source. Of these 403 SNPs, 361 passed the quality control (QC) criteria in our liver transplant study cohorts, which included an imputation info score > 0.8, a minor allele frequency > 0.01, and a Hardy-Weinberg Equilibrium (HWE) P-value > 1E-6. These 361 SNPs were used in the T2D-PRS calculations.
The T2D-PRS can be calculated for both donors and recipients using the PRSice software (available here), with SNP genotype data and SNP summary statistics, as outlined in the formula above. The T2D-PRS z-score, which serves as the required input for this calculator, can then be derived by standardizing the T2D-PRS using a population mean of 19.75 and a standard deviation (SD) of 0.724.
For more details, please see notes at the bottom of the page.
Donor's T2D-PRS, z-score i Assuming Si is the summary statistic for the effective allele for the ith SNP and Gij is the number of the effective allele of the ith SNP observed in the jth individual, PRS for the jth individual (PRSj) can be calculated as $$PRS_{j}=\sum_{i}S_{i}\times G_{ij}$$ For the T2D-PRS, summary statistics for the top 403 GWAS-significant SNPs were obtained from this source. Of these 403 SNPs, 361 passed the quality control (QC) criteria in our liver transplant study cohorts, which included an imputation info score > 0.8, a minor allele frequency > 0.01, and a Hardy-Weinberg Equilibrium (HWE) P-value > 1E-6. These 361 SNPs were used in the T2D-PRS calculations.
The T2D-PRS can be calculated for both donors and recipients using the PRSice software (available here), with SNP genotype data and SNP summary statistics, as outlined in the formula above. The T2D-PRS z-score, which serves as the required input for this calculator, can then be derived by standardizing the T2D-PRS using a population mean of 19.75 and a standard deviation (SD) of 0.724.
For more details, please see notes at the bottom of the page.
Recipient Age
Recipient's age at transplant
Recipient BMI
Recipient's body mass index (BMI) at transplant
Recipient Sex
Probability of PTDM within first year post-transplant
% PTDM Risk
This calculator is for research only.
A z-score quantifies how far a specific value deviates from the average (mean) of a group, measured in terms of standard deviations, which indicates the spread of the data. A positive z-score signifies that the value is above the average, a negative z-score indicates it is below average, and a z-score of 0 means the value is equal to the average. In our PTDM study cohort, the average T2D-PRS is 19.75, with a standard deviation (SD) of 0.724. The z-scores for T2D-PRS in this cohort range from approximately -4 to 4, indicating that some donors or recipients have T2D-PRS scores that are four standard deviations above or below the mean. In other cohorts or future recruitment of recipients and donors, T2D-PRS z-scores could potentially fall well outside this range, such as 10 or -10. However, it's important to note that these extreme values were not tested in our prediction model and may not exhibit the same behavior as scores closer to the average.