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Fig 1.

Flowchart of MR investigating the causal relationship between LTL and PCa.

GIV assumptions: (1) GIVs must be strongly associated with LTL (P < 5×10−8); (2) GIVs must not be correlated with unmeasured confounders of the LTL and PCa relationship; (3) GIVs should only affect the risk of PCa through LTL. SNPs = single-nucleotide polymorphisms; LTL = leukocyte telomere length; PCa = prostate cancer; IVW = inverse-variance-weighted; WM = weighted median.

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Fig 1 Expand

Table 1.

MR results of LTL on the risk of PCa.

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Table 1 Expand

Fig 2.

Scatter plots of LTL with the risk of PCa.

A–D, Effect of LTL-related SNPs on the PCa risk from four different cohorts. Scatter plot demonstrating the effect of each LTL-associated SNP on PCa on the log-odds scale. Slopes of each line represent the causal association for each method. MR = Mendelian randomization; SNP = single-nucleotide polymorphism; LTL = leukocyte telomere length; PCa = prostate cancer.

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Fig 2 Expand

Fig 3.

Density plots of LTL with the risk of PCa.

A–D, Effect of LTL-related SNPs on the PCa risk from four different cohorts. MR = Mendelian randomization; SNP = single nucleotide polymorphism.

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Fig 3 Expand

Fig 4.

Forest plots to visualize the results of the meta-analysis of the four different cohorts.

Forest plots demonstrating the average genetically determined effect of LTL on PCa. Presented OR and CI correspond to the average effects of LTL on PCa. I2 statistic and chi-squared-based Q were used to evaluate the heterogeneity among different studies.

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Fig 4 Expand