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Table 3 Association between quintiles of polygenic risk scores and carotid intima-media thickness in adult women (n = 781)

From: Development of genome-wide polygenic risk scores for lipid traits and clinical applications for dyslipidemia, subclinical atherosclerosis, and diabetes cardiovascular complications among East Asians

Polygenic risk score Cohorts of adult women Quintile of polygenic score   Model 1 Model 2
Q1 Q2 Q3 Q4 Q5 Test Pmodel 1 PQ Pmodel 2 PQ
PRSTC Cohort 1 0.0481 (0.0466–0.0497) 0.0496 (0.0482–0.0511) 0.0503 (0.0487–0.0520) 0.0501 (0.0486–0.0516) 0.0497 (0.0482–0.0514) Linear trend 0.0534   0.1003  
Cohort 2 0.0481 (0.0450–0.0515) 0.0504 (0.0453–0.0561) 0.0529 (0.0479–0.0584) 0.0550 (0.0496–0.0610) 0.0512 (0.0479–0.0547) Linear trend 0.1032   0.0758  
       Meta-analysis 0.0182 0.3547 0.0315 0.2560
Cohort 1 0.0495 (0.0488–0.0503) 0.0497 (0.0482–0.0514) Top 20% vs others 0.6893   0.7445  
Cohort 2 0.0518 (0.0493–0.0544) 0.0512 (0.0479–0.0547) Top 20% vs others 0.8236   0.9732  
       Meta-analysis 0.7591 0.7336 0.7667 0.8891
PRSTG Cohort 1 0.0499
(0.0485–0.0514)
0.0498
(0.0481–0.0515)
0.0491
(0.0475–0.0507)
0.0494
(0.0481–0.0507)
0.0498
(0.0480–0.0516)
Linear trend 0.7416   0.7173  
Cohort 2 0.0515
(0.0471–0.0563)
0.0514
(0.0481–0.0548)
0.0512
(0.0477–0.0549)
0.0542
(0.0457–0.0643)
0.0507
(0.0469–0.0548)
Linear trend 0.6197   0.9116  
       Meta-analysis 0.6430 0.7068 0.7048 0.9963
Cohort 1 0.0495 (0.0488–0.0503) 0.0498 (0.0480–0.0516) Top 20% vs others 0.9536   0.9879  
Cohort 2 0.0518 (0.0495–0.0542) 0.0507 (0.0469–0.0548) Top 20% vs others 0.4509   0.9879  
       Meta-analysis 0.8786 0.4574 0.9917 0.9849
PRSHDL Cohort 1 0.0512
(0.0497–0.0527)
0.0490
(0.0475–0.0505)
0.0496
(0.0479–0.0513)
0.0483
(0.0469–0.0498)
0.0498
(0.0482–0.0514)
Linear trend 0.3786   0.3242  
  Cohort 2 0.0511
(0.0470–0.0556)
0.0542
(0.0466–0.0630)
0.0498
(0.0459–0.0539)
0.0532
(0.0491–0.0576)
0.0508
(0.0475–0.0542)
Linear trend 0.9307   0.8528  
        Meta-analysis 0.4194 0.7165 0.3205 0.8838
  Cohort 1 0.0512
(0.0497–0.0527)
0.0492 (0.0484–0.0500) Bottom 20% vs others 0.0212   0.0160  
  Cohort 2 0.0511
(0.0470–0.0556)
0.0518 (0.0495–0.0542) Bottom 20% vs others 0.4012   0.4524  
        Meta-analysis 0.0533 0.1286 0.0405 0.1373
PRSLDL Cohort 1 0.0481
(0.0467–0.0495)
0.0498
(0.0484–0.0513)
0.0489
(0.0475–0.0503)
0.0514
(0.0494–0.0536)
0.0495
(0.0482–0.0509)
Linear trend 0.0485   0.0954  
  Cohort 2 0.0509
(0.0452–0.0574)
0.0516
(0.0458–0.0581)
0.0533
(0.0485–0.0585)
0.0545
(0.0504–0.0590)
0.0490
(0.0465–0.0517)
Linear trend 0.9030   0.7916  
        Meta-analysis 0.0570 0.5840 0.0972 0.7430
  Cohort 1 0.0496 (0.0488–0.0504) 0.0495
(0.0482–0.0509)
Top 20% vs others 0.7463   0.7438  
  Cohort 2 0.0526 (0.0500–0.0553) 0.0490
(0.0465–0.0517)
Top 20% vs others 0.2775   0.3636  
        Meta-analysis 0.9340 0.2564 0.9800 0.3328
  1. Data are presented as geometric mean (95% CI) stratified by quintile categories of polygenic risk score. Intima-media thickness was natural log (ln) transformed. Pmodel 1 and Pmodel 2 values were obtained from linear regression with the adjustment for covariates included in models 1 and 2, respectively. Model 1: principal components and age. Model 2: principal components, age, body mass index, and systolic blood pressure. Results from individual cohorts were meta-analyzed using a fixed effects model. PQ refers to the p value of Cochran’s Q-statistics in heterogeneity test. Associations between PRSs and carotid intima-media thickness were examined in two different ways: (1) we examined a linear trend across the quintile categories. (2) We tested a hypothesis that a high PRS for TC, TG, and LDL-C (a low PRS for HDL-C) was associated with intima media thickness by comparing the top (bottom) 20% with the remaining 80% of the PRS distribution