Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China.
Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China.
Genome Med. 2021 Feb 19;13(1):29. doi: 10.1186/s13073-021-00831-z.
BACKGROUND: The clinical utility of personal genomic information in identifying individuals at increased risks for dyslipidemia and cardiovascular diseases remains unclear. METHODS: We used data from Biobank Japan (n = 70,657-128,305) and developed novel East Asian-specific genome-wide polygenic risk scores (PRSs) for four lipid traits. We validated (n = 4271) and subsequently tested associations of these scores with 3-year lipid changes in adolescents (n = 620), carotid intima-media thickness (cIMT) in adult women (n = 781), dyslipidemia (n = 7723), and coronary heart disease (CHD) (n = 2374 cases and 6246 controls) in type 2 diabetes (T2D) patients. RESULTS: Our PRSs aggregating 84-549 genetic variants (0.251 < correlation coefficients (r) < 0.272) had comparably stronger association with lipid variations than the typical PRSs derived based on the genome-wide significant variants (0.089 < r < 0.240). Our PRSs were robustly associated with their corresponding lipid levels (7.5 × 10 < P < 1.3 × 10) and 3-year lipid changes (1.4 × 10 < P < 0.0130) which started to emerge in childhood and adolescence. With the adjustments for principal components (PCs), sex, age, and body mass index, there was an elevation of 5.3% in TC (β ± SE = 0.052 ± 0.002), 11.7% in TG (β ± SE = 0.111 ± 0.006), 5.8% in HDL-C (β ± SE = 0.057 ± 0.003), and 8.4% in LDL-C (β ± SE = 0.081 ± 0.004) per one standard deviation increase in the corresponding PRS. However, their predictive power was attenuated in T2D patients (0.183 < r < 0.231). When we included each PRS (for TC, TG, and LDL-C) in addition to the clinical factors and PCs, the AUC for dyslipidemia was significantly increased by 0.032-0.057 in the general population (7.5 × 10 < P < 0.0400) and 0.029-0.069 in T2D patients (2.1 × 10 < P < 0.0428). Moreover, the quintile of TC-related PRS was moderately associated with cIMT in adult women (β ± SE = 0.011 ± 0.005, P = 0.0182). Independent of conventional risk factors, the quintile of PRSs for TC [OR (95% CI) = 1.07 (1.03-1.11)], TG [OR (95% CI) = 1.05 (1.01-1.09)], and LDL-C [OR (95% CI) = 1.05 (1.01-1.09)] were significantly associated with increased risk of CHD in T2D patients (4.8 × 10 < P < 0.0197). Further adjustment for baseline lipid drug use notably attenuated the CHD association. CONCLUSIONS: The PRSs derived and validated here highlight the potential for early genomic screening and personalized risk assessment for cardiovascular disease.
背景:个人基因组信息在识别血脂异常和心血管疾病风险增加的个体方面的临床应用尚不清楚。
方法:我们使用了来自 Biobank Japan 的数据(n=70657-128305),并开发了新的东亚特异性全基因组多基因风险评分(PRS),用于四种血脂特征。我们对(n=4271)进行了验证,并随后测试了这些评分与青少年(n=620)三年内血脂变化、成年女性颈动脉内膜中层厚度(cIMT)(n=781)、血脂异常(n=7723)和 2 型糖尿病(T2D)患者的冠心病(CHD)(n=2374 例病例和 6246 例对照)之间的关联。
结果:我们的 PRS 聚集了 84-549 个遗传变异(0.251<r<0.272),与血脂变化的相关性比基于全基因组显著变异(0.089<r<0.240)得出的典型 PRS 更强。我们的 PRS 与相应的血脂水平(7.5×10< P<1.3×10)和 3 年内的血脂变化(1.4×10< P<0.0130)稳健相关,这些变化从儿童和青少年时期就开始出现。在调整主成分(PCs)、性别、年龄和体重指数后,TC 升高 5.3%(β±SE=0.052±0.002),TG 升高 11.7%(β±SE=0.111±0.006),HDL-C 升高 5.8%(β±SE=0.057±0.003),LDL-C 升高 8.4%(β±SE=0.081±0.004),PRS 相应增加一个标准差。然而,在 T2D 患者中,其预测能力减弱(0.183<r<0.231)。当我们在一般人群(7.5×10< P<0.0400)和 T2D 患者(2.1×10< P<0.0428)中除了临床因素和 PCs 之外,还纳入每个 PRS(用于 TC、TG 和 LDL-C)时,血脂异常的 AUC 显著增加了 0.032-0.057。此外,TC 相关 PRS 的五分位数与成年女性的 cIMT 中度相关(β±SE=0.011±0.005,P=0.0182)。独立于传统危险因素,TC [OR(95%CI)=1.07(1.03-1.11)]、TG [OR(95%CI)=1.05(1.01-1.09)]和 LDL-C [OR(95%CI)=1.05(1.01-1.09)]的 PRS 五分位数与 T2D 患者的 CHD 风险增加显著相关(4.8×10< P<0.0197)。进一步调整基线血脂药物使用后,显著减弱了 CHD 相关性。
结论:这里得出和验证的 PRS 突出了心血管疾病早期基因组筛查和个性化风险评估的潜力。
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