Claudia H T Tam1,2,3, Cadmon K P Lim1,2,3, Andrea O Y Luk1,2,3,4, Alex C W Ng1, Heung-Man Lee1,2, Guozhi Jiang1, Eric S H Lau1, Baoqi Fan1, Raymond Wan1, Alice P S Kong1,2,4, Wing-Hung Tam5, Risa Ozaki1, Elaine Y K Chow1,2, Ka-Fai Lee6, Shing-Chung Siu7, Grace Hui7, Chiu-Chi Tsang8, Kam-Piu Lau9, Jenny Y Y Leung10, Man-Wo Tsang11, Grace Kam11, Ip-Tim Lau12, June K Y Li13, Vincent T F Yeung14, Emmy Lau15, Stanley Lo15, Samuel Fung16, Yuk-Lun Cheng17, Chun-Chung Chow1, Miao Hu1, Weichuan Yu18, Stephen K W Tsui19, Yu Huang19, Huiyao Lan1,4, Cheuk-Chun Szeto1, Nelson L S Tang4,20, Maggie C Y Ng21, Wing-Yee So1,2, Brian Tomlinson1,22, Juliana C N Chan1,2,3,4, Ronald C W Ma23,24,25,26. 1. Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China. 2. Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China. 3. CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong, China. 4. Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China. 5. Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Hong Kong, China. 6. Department of Medicine and Geriatrics, Kwong Wah Hospital, Yau Ma Tei, Hong Kong, China. 7. Diabetes Centre, Tung Wah Eastern Hospital, Causeway Bay, Hong Kong, China. 8. Diabetes and Education Centre, Alice Ho Miu Ling Nethersole Hospital, Tai Po, Hong Kong, China. 9. North District Hospital, Sheung Shui, Hong Kong, China. 10. Department of Medicine and Geriatrics, Ruttonjee Hospital, Wan Chai, Hong Kong, China. 11. Department of Medicine and Geriatrics, United Christian Hospital, Kwun Tong, Hong Kong, China. 12. Tseung Kwan O Hospital, Tseung Kwan O, Hong Kong, China. 13. Department of Medicine, Yan Chai Hospital, Tsuen Wan, Hong Kong, China. 14. Centre for Diabetes Education and Management, Our Lady of Maryknoll Hospital, Wong Tai Sin, Hong Kong, China. 15. Department of Medicine, Pamela Youde Nethersole Eastern Hospital, Chai Wan, Hong Kong, China. 16. Department of Medicine and Geriatrics, Princess Margaret Hospital, Lai Chi Kok, Hong Kong, China. 17. Department of Medicine, Alice Ho Miu Ling Nethersole Hospital, Tai Po, Hong Kong, China. 18. Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China. 19. School of Biomedical Sciences, The Chinese University of Hong Kong, Ma Liu Shui, Hong Kong, China. 20. Department of Chemical Pathology, The Chinese University of Hong Kong, Hong Kong, China. 21. Department of Medicine, Vanderbilt University Medical Center, Nashville, USA. 22. Faculty of Medicine, Macau University of Science and Technology, Taipa, Macau, China. 23. Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China. rcwma@cuhk.edu.hk. 24. Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China. rcwma@cuhk.edu.hk. 25. CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong, China. rcwma@cuhk.edu.hk. 26. Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China. rcwma@cuhk.edu.hk.
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.
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.
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