Development of genome-wide polygenic risk scores for lipid traits and clinical applications for dyslipidemia, subclinical atherosclerosis, and diabetes cardiovascular complications among East Asians
Authors:   The Hong Kong Diabetes Register TRS Study Group, Tam Claudia H. T. ,   The Hong Kong Diabetes Biobank Study Group, Lim Cadmon K. P. , Luk Andrea O. Y. , Ng Alex C. W. , Lee Heung-man , Jiang Guozhi , Lau Eric S. H. , Fan Baoqi , Wan Raymond , Kong Alice P. S. , Tam Wing-hung , Ozaki Risa , Chow Elaine Y. K. , Lee Ka-fai , Siu Shing-chung , Hui Grace , Tsang Chiu-chi , Lau Kam-piu , Leung Jenny Y. Y. , Tsang Man-wo , Kam Grace , Lau Ip-tim , Li June K. Y. , Yeung Vincent T. F. , Lau Emmy , Lo Stanley , Fung Samuel , Cheng Yuk-lun , Chow Chun-chung , Hu Miao , Yu Weichuan , Tsui Stephen K. W. , Huang Yu , Lan Huiyao , Szeto Cheuk-chun , Tang Nelson L. S. , Ng Maggie C. Y. , So Wing-yee , Tomlinson Brian , Chan Juliana C. N. , Ma Ronald C. W. 
Published: February 2021

Abstract
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− 103 < P < 1.3 × 10− 75) and 3-year lipid changes (1.4 × 10− 6 < 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− 3 < P < 0.0400) and 0.029–0.069 in T2D patients (2.1 × 10− 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, Ptrend = 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− 4 < 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.