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1. Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Author: Kentistou, KA, Kaisinger, LR, Stankovic, S, Vaudel, M, Mendes de Oliveira, E, Messina, A, Walters, RG, Liu, X, Busch, AS, Helgason, H, Thompson, DJ, Santoni, F, Petricek, KM, Zouaghi, Y, Huang-Doran, I, Gudbjartsson, DF, Bratland, E, Lin, K, Gardner, EJ, Zhao, Y, Jia, RY, Terao, C, Riggan, MJ, Bolla, MK, Yazdanpanah, M, Yazdanpanah, N, Bradfield, JP, Broer, L, Campbell, A, Chasman, DI, Cousminer, DL, Franceschini, N, Franke, LH, Girotto, G, He, C, Järvelin, M-R, Joshi, PK, Kamatani, Y, Karlsson, R, Luan, J, Lunetta, KL, Mägi, R, Mangino, M, Medland, SE, Meisinger, C, Noordam, R, Nutile, T, Concas, MP, Polašek, O, Porcu, E, Ring, SM, Sala, C, Smith, AV, Tanaka, T, van der Most, PJ, Vitart, V, Wang, CA, Willemsen, G, Zygmunt, M, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Auer, PL, Barnes, CLK, Beckmann, MW, Berrington de Gonzalez, A, Bogdanova, NV, Bojesen, SE, Brenner, H, Buring, JE, Canzian, F, Chang-Claude, J, Couch, FJ, Cox, A, Crisponi, L, Czene, K, Daly, MB, Demerath, EW, Dennis, J, Devilee, P, De Vivo, I, Dörk, T, Dunning, AM, Dwek, M, Eriksson, JG, Fasching, PA, Fernandez-Rhodes, L, Ferreli, L, Fletcher, O, Gago-Dominguez, M, García-Closas, M, García-Sáenz, JA, González-Neira, A, Grallert, H, Guénel, P, Haiman, CA, Hall, P, Hamann, U, Hakonarson, H, Hart, RJ, Hickey, M, Hooning, MJ, Hoppe, R, Hopper, JL, Hottenga, J-J, Hu, FB, Huebner, H, Hunter, DJ, ABCTB Investigators, Jernström, H, John, EM, Karasik, D, Khusnutdinova, EK, Kristensen, VN, Lacey, JV, Lambrechts, D, Launer, LJ, Lind, PA, Lindblom, A, Magnusson, PKE, Mannermaa, A, McCarthy, MI, Meitinger, T, Menni, C, Michailidou, K, Millwood, IY, Milne, RL, Montgomery, GW, Nevanlinna, H, Nolte, IM, Nyholt, DR, Obi, N, O'Brien, KM, Offit, K, Oldehinkel, AJ, Ostrowski, SR, Palotie, A, Pedersen, OB, Peters, A, Pianigiani, G, Plaseska-Karanfilska, D, Pouta, A, Pozarickij, A, Radice, P, Rennert, G, Rosendaal, FR, Ruggiero, D, Saloustros, E, Sandler, DP, Schipf, S, Schmidt, CO, Schmidt, MK, Small, K, Spedicati, B, Stampfer, M, Stone, J, Tamimi, RM, Teras, LR, Tikkanen, E, Turman, C, Vachon, CM, Wang, Q, Winqvist, R, Wolk, A, Zemel, BS, Zheng, W, van Dijk, KW, Alizadeh, BZ, Bandinelli, S, Boerwinkle, E, Boomsma, DI, Ciullo, M, Chenevix-Trench, G, Cucca, F, Esko, T, Gieger, C, Grant, SFA, Gudnason, V, Hayward, C, Kolčić, I, Kraft, P, Lawlor, DA, Martin, NG, Nøhr, EA, Pedersen, NL, Pennell, CE, Ridker, PM, Robino, A, Snieder, H, Sovio, U, Spector, TD, Stöckl, D, Sudlow, C, Timpson, NJ, Toniolo, D, Uitterlinden, A, Ulivi, S, Völzke, H, Wareham, NJ, Widen, E, Wilson, JF, Lifelines Cohort Study, Danish Blood Donor Study, Ovarian Cancer Association Consortium, Breast Cancer Association Consortium, Biobank Japan Project, China Kadoorie Biobank Collaborative Group, Pharoah, PDP, Li, L, Easton, DF, Njølstad, PR, Sulem, P, Murabito, JM, Murray, A, Manousaki, D, Juul, A, Erikstrup, C, Stefansson, K, Horikoshi, M, Chen, Z, Farooqi, IS, Pitteloud, N, Johansson, S, Day, FR, Perry, JRB, Ong, KK, Kentistou, KA, Kaisinger, LR, Stankovic, S, Vaudel, M, Mendes de Oliveira, E, Messina, A, Walters, RG, Liu, X, Busch, AS, Helgason, H, Thompson, DJ, Santoni, F, Petricek, KM, Zouaghi, Y, Huang-Doran, I, Gudbjartsson, DF, Bratland, E, Lin, K, Gardner, EJ, Zhao, Y, Jia, RY, Terao, C, Riggan, MJ, Bolla, MK, Yazdanpanah, M, Yazdanpanah, N, Bradfield, JP, Broer, L, Campbell, A, Chasman, DI, Cousminer, DL, Franceschini, N, Franke, LH, Girotto, G, He, C, Järvelin, M-R, Joshi, PK, Kamatani, Y, Karlsson, R, Luan, J, Lunetta, KL, Mägi, R, Mangino, M, Medland, SE, Meisinger, C, Noordam, R, Nutile, T, Concas, MP, Polašek, O, Porcu, E, Ring, SM, Sala, C, Smith, AV, Tanaka, T, van der Most, PJ, Vitart, V, Wang, CA, Willemsen, G, Zygmunt, M, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Auer, PL, Barnes, CLK, Beckmann, MW, Berrington de Gonzalez, A, Bogdanova, NV, Bojesen, SE, Brenner, H, Buring, JE, Canzian, F, Chang-Claude, J, Couch, FJ, Cox, A, Crisponi, L, Czene, K, Daly, MB, Demerath, EW, Dennis, J, Devilee, P, De Vivo, I, Dörk, T, Dunning, AM, Dwek, M, Eriksson, JG, Fasching, PA, Fernandez-Rhodes, L, Ferreli, L, Fletcher, O, Gago-Dominguez, M, García-Closas, M, García-Sáenz, JA, González-Neira, A, Grallert, H, Guénel, P, Haiman, CA, Hall, P, Hamann, U, Hakonarson, H, Hart, RJ, Hickey, M, Hooning, MJ, Hoppe, R, Hopper, JL, Hottenga, J-J, Hu, FB, Huebner, H, Hunter, DJ, ABCTB Investigators, Jernström, H, John, EM, Karasik, D, Khusnutdinova, EK, Kristensen, VN, Lacey, JV, Lambrechts, D, Launer, LJ, Lind, PA, Lindblom, A, Magnusson, PKE, Mannermaa, A, McCarthy, MI, Meitinger, T, Menni, C, Michailidou, K, Millwood, IY, Milne, RL, Montgomery, GW, Nevanlinna, H, Nolte, IM, Nyholt, DR, Obi, N, O'Brien, KM, Offit, K, Oldehinkel, AJ, Ostrowski, SR, Palotie, A, Pedersen, OB, Peters, A, Pianigiani, G, Plaseska-Karanfilska, D, Pouta, A, Pozarickij, A, Radice, P, Rennert, G, Rosendaal, FR, Ruggiero, D, Saloustros, E, Sandler, DP, Schipf, S, Schmidt, CO, Schmidt, MK, Small, K, Spedicati, B, Stampfer, M, Stone, J, Tamimi, RM, Teras, LR, Tikkanen, E, Turman, C, Vachon, CM, Wang, Q, Winqvist, R, Wolk, A, Zemel, BS, Zheng, W, van Dijk, KW, Alizadeh, BZ, Bandinelli, S, Boerwinkle, E, Boomsma, DI, Ciullo, M, Chenevix-Trench, G, Cucca, F, Esko, T, Gieger, C, Grant, SFA, Gudnason, V, Hayward, C, Kolčić, I, Kraft, P, Lawlor, DA, Martin, NG, Nøhr, EA, Pedersen, NL, Pennell, CE, Ridker, PM, Robino, A, Snieder, H, Sovio, U, Spector, TD, Stöckl, D, Sudlow, C, Timpson, NJ, Toniolo, D, Uitterlinden, A, Ulivi, S, Völzke, H, Wareham, NJ, Widen, E, Wilson, JF, Lifelines Cohort Study, Danish Blood Donor Study, Ovarian Cancer Association Consortium, Breast Cancer Association Consortium, Biobank Japan Project, China Kadoorie Biobank Collaborative Group, Pharoah, PDP, Li, L, Easton, DF, Njølstad, PR, Sulem, P, Murabito, JM, Murray, A, Manousaki, D, Juul, A, Erikstrup, C, Stefansson, K, Horikoshi, M, Chen, Z, Farooqi, IS, Pitteloud, N, Johansson, S, Day, FR, Perry, JRB, and Ong, KK
Abstract: Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease.
Published: 2024

2. Associations of alcohol intake with subclinical carotid atherosclerosis in 22,000 Chinese adults

Author: Zhou, T, Im, PK, Hariri, P, Du, H, Guo, Y, Lin, K, Yang, L, Yu, C, Chen, Y, Sohoni, R, Avery, D, Guan, M, Yang, M, Lv, J, Clarke, R, Li, L, Walters, RG, Chen, Z, Millwood, IY, and Group, China Kadoorie Biobank
Abstract: Background and aims We investigated the causal relevance of alcohol intake with measures of carotid artery thickness and atherosclerosis in Chinese adults. Methods The study included 22,384 adults from the China Kadoorie Biobank, with self-reported alcohol use at baseline and resurvey, carotid artery ultrasound measurements, and genotyping data for ALDH2-rs671 and ADH1B-rs1229984. Associations of carotid intima media thickness (cIMT), any carotid plaque, and total plaque burden (derived from plaque number and size) with self-reported (conventional analyses) and genotype-predicted mean alcohol intake (Mendelian randomisation) were assessed using linear and logistic regression models. Results Overall 34.2% men and 2.1% women drank alcohol regularly at baseline. Mean cIMT was 0.70 mm in men and 0.64 mm in women, with 39.1% and 26.5% having carotid plaque, respectively. Among men, cIMT was not associated with self-reported or genotype-predicted mean alcohol intake. The risk of plaque increased significantly with self-reported intake among current drinkers (odds ratio 1.42 [95% CI 1.14–1.76] per 280 g/week), with directionally consistent findings with genotype-predicted mean intake (1.21 [0.99–1.49]). Higher alcohol intake was significantly associated with higher carotid plaque burden in both conventional (0.19 [0.10–0.28] mm higher per 280 g/week) and genetic analyses (0.09 [0.02–0.17]). Genetic findings in women suggested the association of genotype-predicted alcohol with carotid plaque burden in men was likely to due to alcohol itself, rather than pleiotropic genotypic effects. Conclusion Higher alcohol intake was associated with a higher carotid plaque burden, but not with cIMT, providing support for a potential causal association of alcohol intake with carotid atherosclerosis.
Published: 2023

3. Minimal improvement in coronary artery disease risk prediction in Chinese population using polygenic risk scores: Evidence from the China Kadoorie Biobank

Author: Yang, S, Sun, D, Sun, Z, Yu, C, Guo, Y, Si, J, Pang, Y, Pei, P, Yang, L, Millwood, IY, G Walters, R, Chen, Y, Du, H, Pang, Z, Schmidt, D, Stevens, R, Clarke, R, Chen, J, Chen, Z, Lv, J, and Li, L
Subjects: General Medicine
Abstract: Background: Several studies have reported that polygenic risk scores (PRSs) can enhance risk prediction of coronary artery disease (CAD) in European populations. However, research on this topic is far from sufficient in non-European countries, including China. We aimed to evaluate the potential of PRS for predicting CAD for primary prevention in the Chinese population. Methods: Participants with genome-wide genotypic data from the China Kadoorie Biobank were divided into training (n = 28,490) and testing sets (n = 72,150). Ten previously developed PRSs were evaluated, and new ones were developed using clumping and thresholding or LDpred method. The PRS showing the strongest association with CAD in the training set was selected to further evaluate its effects on improving the traditional CAD risk-prediction model in the testing set. Genetic risk was computed by summing the product of the weights and allele dosages across genome-wide single-nucleotide polymorphisms. Prediction of the 10-year first CAD events was assessed using hazard ratios (HRs) and measures of model discrimination, calibration, and net reclassification improvement (NRI). Hard CAD (nonfatal I21–I23 and fatal I20–I25) and soft CAD (all fatal or nonfatal I20–I25) were analyzed separately. Results: In the testing set, 1214 hard and 7201 soft CAD cases were documented during a mean follow-up of 11.2 years. The HR per standard deviation of the optimal PRS was 1.26 (95% CI:1.19–1.33) for hard CAD. Based on a traditional CAD risk prediction model containing only non-laboratory-based information, the addition of PRS for hard CAD increased Harrell's C index by 0.001 (–0.001 to 0.003) in women and 0.003 (0.001 to 0.005) in men. Among the different high-risk thresholds ranging from 1% to 10%, the highest categorical NRI was 3.2% (95% CI: 0.4–6.0%) at a high-risk threshold of 10.0% in women. The association of the PRS with soft CAD was much weaker than with hard CAD, leading to minimal or no improvement in the soft CAD model. Conclusions: In this Chinese population sample, the current PRSs minimally changed risk discrimination and offered little to no improvement in risk stratification for soft CAD. Therefore, this may not be suitable for promoting genetic screening in the general Chinese population to improve CAD risk prediction.
Published: 2023
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4. Helicobacter pylorimultiplex serology and risk of non-cardia and cardia gastric cancer: a case-cohort study and meta-analysis

Author: Yao, P, Kartsonaki, C, Butt, J, Jeske, R, de Martel, C, Plummer, M, Guo, Y, Clark, S, Walters, RG, Chen, Y, Avery, D, Lv, J, Yu, C, Wang, H, Hill, M, Peto, R, Li, L, Waterboer, T, Chen, Z, Millwood, IY, and Yang, L
Subjects: Epidemiology, General Medicine
Abstract: BackgroundHelicobacter pylori infection is a major cause of non-cardia gastric cancer (NCGC), but uncertainty remains about the associations between sero-positivity to different H. pylori antigens and risk of NCGC and cardia gastric cancer (CGC) in different populations.MethodsA case-cohort study in China included ∼500 each of incident NCGC and CGC cases and ∼2000 subcohort participants. Sero-positivity to 12 H. pylori antigens was measured in baseline plasma samples using a multiplex assay. Hazard ratios (HRs) of NCGC and CGC for each marker were estimated using Cox regression. These were further meta-analysed with studies using same assay.ResultsIn the subcohort, sero-positivity for 12 H. pylori antigens varied from 11.4% (HpaA) to 70.8% (CagA). Overall, 10 antigens showed significant associations with risk of NCGC (adjusted HRs: 1.33 to 4.15), and four antigens with CGC (HRs: 1.50 to 2.34). After simultaneous adjustment for other antigens, positive associations remained significant for NCGC (CagA, HP1564, HP0305) and CGC (CagA, HP1564, HyuA). Compared with CagA sero-positive only individuals, those who were positive for all three antigens had an adjusted HR of 5.59 (95% CI 4.68–6.66) for NCGC and 2.17 (95% CI 1.54–3.05) for CGC. In the meta-analysis of NCGC, the pooled relative risk for CagA was 2.96 (95% CI 2.58–3.41) [Europeans: 5.32 (95% CI 4.05–6.99); Asians: 2.41 (95% CI 2.05–2.83); PheterogeneityConclusionsSero-positivity to several H. pylori antigens was significantly associated with an increased risk of NCGC and CGC, with varying effects between Asian and European populations.
Published: 2023
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5. COPD and its association with smoking in the Mainland China: a cross-sectional analysis of 0.5 million men and women from ten diverse areas

Author: Kurmi OP, Li L, Wang J, Millwood IY, Chen J, Collins R, Guo Y, Bian Z, Li J, Chen B, Xie K, Jia W, Gao Y, Peto R, and Chen Z
Subjects: Diseases of the respiratory system, RC705-779
Abstract: Om P Kurmi,1 Liming Li,2,3 Jenny Wang,1 Iona Y Millwood,1 Junshi Chen,4 Rory Collins,1 Yu Guo,2 Zheng Bian,2 Jiangtao Li,5 Biyun Chen,6 Kaixu Xie,7 Weifan Jia,8 Yali Gao,9 Richard Peto,1 Zhengming Chen1 On behalf of the China Kadoorie Biobank Collaborative Group 1Nuffield Department of Population Health, Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), University of Oxford, Oxford, UK; 2Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 3Chinese Academy of Medical Sciences, Dong Cheng District, 4China National Center for Food Safety Risk Assessment, Beijing, 5NCDs Prevention and Control Department, Huixian CDC, Huixian, Henan, 6NCDs Prevention and Control Department, Hunan CDC, Changsha, 7NCDs Prevention and Control Department, Tongxiang CDC, Zhejiang, 8NCDs Prevention and Control Department, Liuyang CDC, Baiyikengdao, Liuyang, Changsha, Hunan, 9NCDs Prevention and Control Department, Sichuan CDC, Sichuan, Mainland China Purpose: In adult Chinese men, smoking prevalence is high, but little is known about its association with chronic respiratory disease, which is still poorly diagnosed and managed. Methods: A nationwide study recruited 0.5 million men and women aged 30–79 years during 2004–2008 from ten geographically diverse areas across the Mainland China. Information was collected from each participant regarding smoking and self-reported physician diagnosis of chronic bronchitis/emphysema (CB/E), along with measurement of lung function indices. Logistic regression was used to yield sex-specific odds ratios (ORs) relating smoking to airflow obstruction (AFO), defined as forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC)
Published: 2015

6. Liver biomarkers, genetic and lifestyle risk factors in relation to risk of cardiovascular disease in Chinese

Author: Wang, X, Cheng, S, Lv, J, Yu, C, Guo, Y, Pei, P, Yang, L, Millwood, IY, Walters, R, Chen, Y, Du, H, Duan, H, Gilbert, S, Avery, D, Chen, J, Pang, Y, Chen, Z, Li, L, and Group, China Kadoorie Biobank Collaborative
Subjects: Cardiology and Cardiovascular Medicine
Abstract: Background and aimsLiver biomarkers and metabolic associated fatty liver disease (MAFLD) have been shown to be associated with cardiovascular disease (CVD). However, there is limited evidence on CVD subtypes [myocardial infarction (MI), ischemic stroke (IS), and intracerebral hemorrhage (ICH)], especially in the Chinese population. We examined these associations overall, by genetic predisposition to non-alcoholic fatty liver disease (NAFLD), and by lifestyle risk factors.Approach and resultsThis is a nested case-control study of CVD (10,298 cases and 5,388 controls) within the China Kadoorie Biobank. Cox regression was used to estimate adjusted hazard ratios (HRs) for CVD associated with liver biomarkers and MAFLD and by stratum of genetic risk and a combined high-risk lifestyle score. For liver enzymes, there were positive associations with MI and IS, but no associations with ICH or carotid plaque. There were positive associations of NAFLD with risks of MI, IS, and ICH (HR 1.43 [95% CI 1.30–1.57], 1.25 [1.16–1.35], and 1.12 [1.02–1.23]) as well as carotid plaque (odds ratio 2.36 [1.12–4.96]). The associations of NAFLD with CVD and carotid plaque were stronger among individuals with a high genetic risk (ICH: p-interaction < 0.05), while the associations with stroke were stronger among those with a favorable lifestyle (p-interaction < 0.05). The results for MAFLD mirrored those for NAFLD.ConclusionIn Chinese adults, liver biomarkers and MAFLD were associated with risk of CVD, with different magnitudes of associations by CVD subtypes. Genetic predisposition to NAFLD and lifestyle factors modified the associations of fatty liver with stroke.
Published: 2022

7. Association of Red Meat Consumption, Metabolic Markers, and Risk of Cardiovascular Diseases

Author: Pan, L, Chen, L, Lv, J, Pang, Y, Guo, Y, Pei, P, Sansome, S, Millwood, IY, Du, H, Sohoni, R, Yang, L, Chen, Y, Walters, RG, Hua, Y, Chen, J, Yu, C, Chen, Z, and Li, L
Subjects: Nutrition and Dietetics, Endocrinology, Diabetes and Metabolism, Food Science
Abstract: ObjectiveThe metabolic mechanism of harmful effects of red meat on the cardiovascular system is still unclear. The objective of the present study is to investigate the associations of self-reported red meat consumption with plasma metabolic markers, and of these markers with the risk of cardiovascular diseases (CVD).MethodsPlasma samples of 4,778 participants (3,401 CVD cases and 1,377 controls) aged 30–79 selected from a nested case-control study based on the China Kadoorie Biobank were analyzed by using targeted nuclear magnetic resonance to quantify 225 metabolites or derived traits. Linear regression was conducted to evaluate the effects of self-reported red meat consumption on metabolic markers, which were further compared with the effects of these markers on CVD risk assessed by logistic regression.ResultsOut of 225 metabolites, 46 were associated with red meat consumption. Positive associations were observed for intermediate-density lipoprotein (IDL), small high-density lipoprotein (HDL), and all sizes of low-density lipoprotein (LDL). Cholesterols, phospholipids, and apolipoproteins within various lipoproteins, as well as fatty acids, total choline, and total phosphoglycerides, were also positively associated with red meat consumption. Meanwhile, 29 out of 46 markers were associated with CVD risk. In general, the associations of metabolic markers with red meat consumption and of metabolic markers with CVD risk showed consistent direction.ConclusionsIn the Chinese population, red meat consumption is associated with several metabolic markers, which may partially explain the harmful effect of red meat consumption on CVD.
Published: 2022
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8. Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects

Author: Howe, LJ, Nivard, MG, Morris, TT, Hansen, AF, Rasheed, H, Cho, Y, Chittoor, G, Ahlskog, R, Lind, PA, Palviainen, T, van der Zee, MD, Cheesman, R, Mangino, M, Wang, Y, Li, S, Klaric, L, Ratliff, SM, Bielak, LF, Nygaard, M, Giannelis, A, Willoughby, EA, Reynolds, CA, Balbona, JV, Andreassen, OA, Ask, H, Baras, A, Bauer, CR, Boomsma, DI, Campbell, A, Campbell, H, Chen, Z, Christofidou, P, Corfield, E, Dahm, CC, Dokuru, DR, Evans, LM, de Geus, EJC, Giddaluru, S, Gordon, SD, Harden, KP, Hill, WD, Hughes, A, Kerr, SM, Kim, Y, Kweon, H, Latvala, A, Lawlor, DA, Li, L, Lin, K, Magnus, P, Magnusson, PKE, Mallard, TT, Martikainen, P, Mills, MC, Njolstad, PR, Overton, JD, Pedersen, NL, Porteous, DJ, Reid, J, Silventoinen, K, Southey, MC, Stoltenberg, C, Tucker-Drob, EM, Wright, MJ, Hewitt, JK, Keller, MC, Stallings, MC, Lee, JJ, Christensen, K, Kardia, SLR, Peyser, PA, Smith, JA, Wilson, JF, Hopper, JL, Hagg, S, Spector, TD, Pingault, J-B, Plomin, R, Havdahl, A, Bartels, M, Martin, NG, Oskarsson, S, Justice, AE, Millwood, IY, Hveem, K, Naess, O, Willer, CJ, Asvold, BO, Koellinger, PD, Kaprio, J, Medland, SE, Walters, RG, Benjamin, DJ, Turley, P, Evans, DM, Smith, GD, Hayward, C, Brumpton, B, Hemani, G, Davies, NM, Howe, LJ, Nivard, MG, Morris, TT, Hansen, AF, Rasheed, H, Cho, Y, Chittoor, G, Ahlskog, R, Lind, PA, Palviainen, T, van der Zee, MD, Cheesman, R, Mangino, M, Wang, Y, Li, S, Klaric, L, Ratliff, SM, Bielak, LF, Nygaard, M, Giannelis, A, Willoughby, EA, Reynolds, CA, Balbona, JV, Andreassen, OA, Ask, H, Baras, A, Bauer, CR, Boomsma, DI, Campbell, A, Campbell, H, Chen, Z, Christofidou, P, Corfield, E, Dahm, CC, Dokuru, DR, Evans, LM, de Geus, EJC, Giddaluru, S, Gordon, SD, Harden, KP, Hill, WD, Hughes, A, Kerr, SM, Kim, Y, Kweon, H, Latvala, A, Lawlor, DA, Li, L, Lin, K, Magnus, P, Magnusson, PKE, Mallard, TT, Martikainen, P, Mills, MC, Njolstad, PR, Overton, JD, Pedersen, NL, Porteous, DJ, Reid, J, Silventoinen, K, Southey, MC, Stoltenberg, C, Tucker-Drob, EM, Wright, MJ, Hewitt, JK, Keller, MC, Stallings, MC, Lee, JJ, Christensen, K, Kardia, SLR, Peyser, PA, Smith, JA, Wilson, JF, Hopper, JL, Hagg, S, Spector, TD, Pingault, J-B, Plomin, R, Havdahl, A, Bartels, M, Martin, NG, Oskarsson, S, Justice, AE, Millwood, IY, Hveem, K, Naess, O, Willer, CJ, Asvold, BO, Koellinger, PD, Kaprio, J, Medland, SE, Walters, RG, Benjamin, DJ, Turley, P, Evans, DM, Smith, GD, Hayward, C, Brumpton, B, Hemani, G, and Davies, NM
Abstract: Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects.
Published: 2022

9. Stroke genetics informs drug discovery and risk prediction across ancestries

Author: Mishra, A, Malik, R, Hachiya, T, Jurgenson, T, Namba, S, Posner, DC, Kamanu, FK, Koido, M, Le Grand, Q, Shi, M, He, Y, Georgakis, MK, Caro, I, Krebs, K, Liaw, Y-C, Vaura, FC, Lin, K, Winsvold, BS, Srinivasasainagendra, V, Parodi, L, Bae, H-J, Chauhan, G, Chong, MR, Tomppo, L, Akinyemi, R, Roshchupkin, GV, Habib, N, Jee, YH, Thomassen, JQ, Abedi, V, Carcel-Marquez, J, Nygaard, M, Leonard, HL, Yang, C, Yonova-Doing, E, Knol, MJ, Lewis, AJ, Judy, RL, Ago, T, Amouyel, P, Armstrong, ND, Bakker, MK, Bartz, TM, Bennett, DA, Bis, JC, Bordes, C, Borte, S, Cain, A, Ridker, PM, Cho, K, Chen, Z, Cruchaga, C, Cole, JW, de Jager, PL, de Cid, R, Endres, M, Ferreira, LE, Geerlings, MI, Gasca, NC, Gudnason, V, Hata, J, He, J, Heath, AK, Ho, Y-L, Havulinna, AS, Hopewell, JC, Hyacinth, HI, Inouye, M, Jacob, MA, Jeon, CE, Jern, C, Kamouchi, M, Keene, KL, Kitazono, T, Kittner, SJ, Konuma, T, Kumar, A, Lacaze, P, Launer, LJ, Lee, K-J, Lepik, K, Li, J, Li, L, Manichaikul, A, Markus, HS, Marston, NA, Meitinger, T, Mitchell, BD, Montellano, FA, Morisaki, T, Mosley, TH, Nalls, MA, Nordestgaard, BG, O'Donnell, MJ, Okada, Y, Onland-Moret, NC, Ovbiagele, B, Peters, A, Psaty, BM, Rich, SS, Rosand, J, Sabatine, MS, Sacco, RL, Saleheen, D, Sandset, EC, Salomaa, V, Sargurupremraj, M, Sasaki, M, Satizabal, CL, Schmidt, CO, Shimizu, A, Smith, NL, Sloane, KL, Sutoh, Y, Sun, YV, Tanno, K, Tiedt, S, Tatlisumak, T, Torres-Aguila, NP, Tiwari, HK, Tregouet, D-A, Trompet, S, Tuladhar, AM, Tybjaerg-Hansen, A, van Vugt, M, Vibo, R, Verma, SS, Wiggins, KL, Wennberg, P, Woo, D, Wilson, PWF, Xu, H, Yang, Q, Yoon, K, Millwood, IY, Gieger, C, Ninomiya, T, Grabe, HJ, Jukema, JW, Rissanen, IL, Strbian, D, Kim, YJ, Chen, P-H, Mayerhofer, E, Howson, JMM, Irvin, MR, Adams, H, Wassertheil-Smoller, S, Christensen, K, Ikram, MA, Rundek, T, Worrall, BB, Lathrop, GM, Riaz, M, Simonsick, EM, Korv, J, Franca, PHC, Zand, R, Prasad, K, Frikke-Schmidt, R, de Leeuw, F-E, Liman, T, Haeusler, KG, Ruigrok, YM, Heuschmann, PU, Longstreth, WT, Jung, KJ, Bastarache, L, Pare, G, Damrauer, SM, Chasman, DI, Rotter, JI, Anderson, CD, Zwart, J-A, Niiranen, TJ, Fornage, M, Liaw, Y-P, Seshadri, S, Fernandez-Cadenas, I, Walters, RG, Ruff, CT, Owolabi, MO, Huffman, JE, Milani, L, Kamatani, Y, Dichgans, M, Debette, S, Lee, J-M, Cheng, Y-C, Meschia, JF, Chen, WM, Sale, MM, Zonderman, AB, Evans, MK, Wilson, JG, Correa, A, Traylor, M, Lewis, CM, Reiner, A, Haessler, J, Langefeld, CD, Gottesman, RF, Yaffe, K, Liu, YM, Kooperberg, C, Lange, LA, Furie, KL, Arnett, DK, Benavente, OR, Grewal, RP, Peddareddygari, LR, Hveem, K, Lindstrom, S, Wang, L, Smith, EN, Gordon, W, Vlieg, AVH, de Andrade, M, Brody, JA, Pattee, JW, Brumpton, BM, Suchon, P, Chen, M-H, Frazer, KA, Turman, C, Germain, M, MacDonald, J, Braekkan, SK, Armasu, SM, Pankratz, N, Jackson, RD, Nielsen, JB, Giulianin, F, Puurunen, MK, Ibrahim, M, Heckbert, SR, Bammler, TK, McCauley, BM, Taylor, KD, Pankow, JS, Reiner, AP, Gabrielsen, ME, Deleuze, J-F, O'Donnell, CJ, Kim, J, McKnight, B, Kraft, P, Hansen, J-B, Rosendaal, FR, Heit, JA, Tang, W, Morange, P-E, Johnson, AD, Kabrhel, C, van Dijk, EJ, Koudstaal, PJ, Luijckx, G-J, Nederkoorn, PJ, van Oostenbrugge, RJ, Visser, MC, Wermer, MJH, Kappelle, LJ, Esko, T, Metspalu, A, Magi, R, Nelis, M, Levi, CR, Maguire, J, Jimenez-Conde, J, Sharma, P, Sudlow, CLM, Rannikmae, K, Schmidt, R, Slowik, A, Pera, J, Thijs, VNS, Lindgren, AG, Ilinca, A, Melander, O, Engstrom, G, Rexrode, KM, Rothwell, PM, Stanne, TM, Johnson, JA, Danesh, J, Butterworth, AS, Heitsch, L, Boncoraglio, GB, Kubo, M, Pezzini, A, Rolfs, A, Giese, A-K, Weir, D, Ross, OA, Lemmons, R, Soderholm, M, Cushman, M, Jood, K, McDonough, CW, Bell, S, Linkohr, B, Lee, T-H, Putaala, J, Lopez, OL, Carty, CL, Jian, X, Schminke, U, Cullell, N, Delgado, P, Ibanez, L, Krupinski, J, Lioutas, V, Matsuda, K, Montaner, J, Muino, E, Roquer, J, Sarnowski, C, Sattar, N, Sibolt, G, Teumer, A, Rutten-Jacobs, L, Kanai, M, Gretarsdottir, S, Rost, NS, Yusuf, S, Almgren, P, Ay, H, Bevan, S, Brown, RD, Carrera, C, Buring, JE, Chen, W-M, Cotlarciuc, I, de Bakker, PIW, DeStefano, AL, den Hoed, M, Duan, Q, Engelter, ST, Falcone, GJ, Gustafsson, S, Hassan, A, Holliday, EG, Howard, G, Hsu, F-C, Ingelsson, E, Harris, TB, Kissela, BM, Kleindorfer, DO, Langenberg, C, Leys, D, Lin, W-Y, Lorentzen, E, Magnusson, PK, McArdle, PF, Pulit, SL, Rice, K, Sakaue, S, Sapkota, BR, Tanislav, C, Thorleifsson, G, Thorsteinsdottir, U, Tzourio, C, van Duijn, CM, Walters, M, Wareham, NJ, Amin, N, Aparicio, HJ, Attia, J, Beiser, AS, Berr, C, Bustamante, M, Caso, V, Choi, SH, Chowhan, A, Dartigues, J-F, Delavaran, H, Dorr, M, Ford, I, Gurpreet, WS, Hamsten, A, Hozawa, A, Ingelsson, M, Iwasaki, M, Kaffashian, S, Kalra, L, Kjartansson, O, Kloss, M, Labovitz, DL, Laurie, CC, Lind, L, Lindgren, CM, Makoto, H, Minegishi, N, Morris, AP, Mueller-Nurasyid, M, Norrving, B, Ogishima, S, Parati, EA, Pedersen, NL, Perola, M, Jousilahti, P, Pileggi, S, Rabionet, R, Riba-Llena, I, Ribases, M, Romero, JR, Rudd, AG, Sarin, A-P, Sarju, R, Satoh, M, Sawada, N, Sigurdsson, A, Smith, A, Stine, OC, Stott, DJ, Strauch, K, Takai, T, Tanaka, H, Touze, E, Tsugane, S, Uitterlinden, AG, Valdimarsson, EM, van der Lee, SJ, Wakai, K, Williams, SR, Wolfe, CDA, Wong, Q, Yamaji, T, Sanghera, DK, Stefansson, K, Martinez-Majander, N, Sobue, K, Soriano-Tarraga, C, Volzke, H, Akpa, O, Sarfo, FS, Akpalu, A, Obiako, R, Wahab, K, Osaigbovo, G, Owolabi, L, Komolafe, M, Jenkins, C, Arulogun, O, Ogbole, G, Adeoye, AM, Akinyemi, J, Agunloye, A, Fakunle, AG, Uvere, E, Olalere, A, Adebajo, OJ, Chen, J, Clarke, R, Collins, R, Guo, Y, Wang, C, Lv, J, Peto, R, Chen, Y, Fairhurst-Hunter, Z, Hill, M, Pozarickij, A, Schmidt, D, Stevens, B, Turnbull, I, Yu, C, Nagai, A, Murakami, Y, Shiroma, EJ, Sigurdsson, S, Ghanbari, M, Boerwinkle, E, Fongang, B, Wang, R, Ikram, MK, Volker, U, de Laat, KF, van Norden, AGW, de Kort, PL, Vermeer, SE, Brouwers, PJAM, Gons, RAR, den Heijer, T, van Dijk, GW, van Rooij, FGW, Aamodt, AH, Skogholt, AH, Willer, CJ, Heuch, I, Hagen, K, Fritsche, LG, Pedersen, LM, Ellekjaer, H, Zhou, W, Martinsen, AE, Kristoffersen, ES, Thomas, LF, Kleinschnitz, C, Frantz, S, Ungethum, K, Gallego-Fabrega, C, Lledos, M, Llucia-Carol, L, Sobrino, T, Campos, F, Castillo, J, Freijo, M, Arenillas, JF, Obach, V, Alvarez-Sabin, J, Molina, CA, Ribo, M, Munoz-Narbona, L, Lopez-Cancio, E, Millan, M, Diaz-Navarro, R, Vives-Bauza, C, Serrano-Heras, G, Segura, T, Dhar, R, Delgado-Mederos, R, Prats-Sanchez, L, Camps-Renom, P, Blay, N, Sumoy, L, Marti-Fabregas, J, Schnohr, P, Jensen, GB, Benn, M, Afzal, S, Kamstrup, PR, van Setten, J, van der Laan, SW, Vonk, JMJ, Kim, B-J, Curtze, S, Tiainen, M, Kinnunen, J, Menon, V, Sung, YJ, Saillour-Glenisson, F, Gravel, S, Mishra, A, Malik, R, Hachiya, T, Jurgenson, T, Namba, S, Posner, DC, Kamanu, FK, Koido, M, Le Grand, Q, Shi, M, He, Y, Georgakis, MK, Caro, I, Krebs, K, Liaw, Y-C, Vaura, FC, Lin, K, Winsvold, BS, Srinivasasainagendra, V, Parodi, L, Bae, H-J, Chauhan, G, Chong, MR, Tomppo, L, Akinyemi, R, Roshchupkin, GV, Habib, N, Jee, YH, Thomassen, JQ, Abedi, V, Carcel-Marquez, J, Nygaard, M, Leonard, HL, Yang, C, Yonova-Doing, E, Knol, MJ, Lewis, AJ, Judy, RL, Ago, T, Amouyel, P, Armstrong, ND, Bakker, MK, Bartz, TM, Bennett, DA, Bis, JC, Bordes, C, Borte, S, Cain, A, Ridker, PM, Cho, K, Chen, Z, Cruchaga, C, Cole, JW, de Jager, PL, de Cid, R, Endres, M, Ferreira, LE, Geerlings, MI, Gasca, NC, Gudnason, V, Hata, J, He, J, Heath, AK, Ho, Y-L, Havulinna, AS, Hopewell, JC, Hyacinth, HI, Inouye, M, Jacob, MA, Jeon, CE, Jern, C, Kamouchi, M, Keene, KL, Kitazono, T, Kittner, SJ, Konuma, T, Kumar, A, Lacaze, P, Launer, LJ, Lee, K-J, Lepik, K, Li, J, Li, L, Manichaikul, A, Markus, HS, Marston, NA, Meitinger, T, Mitchell, BD, Montellano, FA, Morisaki, T, Mosley, TH, Nalls, MA, Nordestgaard, BG, O'Donnell, MJ, Okada, Y, Onland-Moret, NC, Ovbiagele, B, Peters, A, Psaty, BM, Rich, SS, Rosand, J, Sabatine, MS, Sacco, RL, Saleheen, D, Sandset, EC, Salomaa, V, Sargurupremraj, M, Sasaki, M, Satizabal, CL, Schmidt, CO, Shimizu, A, Smith, NL, Sloane, KL, Sutoh, Y, Sun, YV, Tanno, K, Tiedt, S, Tatlisumak, T, Torres-Aguila, NP, Tiwari, HK, Tregouet, D-A, Trompet, S, Tuladhar, AM, Tybjaerg-Hansen, A, van Vugt, M, Vibo, R, Verma, SS, Wiggins, KL, Wennberg, P, Woo, D, Wilson, PWF, Xu, H, Yang, Q, Yoon, K, Millwood, IY, Gieger, C, Ninomiya, T, Grabe, HJ, Jukema, JW, Rissanen, IL, Strbian, D, Kim, YJ, Chen, P-H, Mayerhofer, E, Howson, JMM, Irvin, MR, Adams, H, Wassertheil-Smoller, S, Christensen, K, Ikram, MA, Rundek, T, Worrall, BB, Lathrop, GM, Riaz, M, Simonsick, EM, Korv, J, Franca, PHC, Zand, R, Prasad, K, Frikke-Schmidt, R, de Leeuw, F-E, Liman, T, Haeusler, KG, Ruigrok, YM, Heuschmann, PU, Longstreth, WT, Jung, KJ, Bastarache, L, Pare, G, Damrauer, SM, Chasman, DI, Rotter, JI, Anderson, CD, Zwart, J-A, Niiranen, TJ, Fornage, M, Liaw, Y-P, Seshadri, S, Fernandez-Cadenas, I, Walters, RG, Ruff, CT, Owolabi, MO, Huffman, JE, Milani, L, Kamatani, Y, Dichgans, M, Debette, S, Lee, J-M, Cheng, Y-C, Meschia, JF, Chen, WM, Sale, MM, Zonderman, AB, Evans, MK, Wilson, JG, Correa, A, Traylor, M, Lewis, CM, Reiner, A, Haessler, J, Langefeld, CD, Gottesman, RF, Yaffe, K, Liu, YM, Kooperberg, C, Lange, LA, Furie, KL, Arnett, DK, Benavente, OR, Grewal, RP, Peddareddygari, LR, Hveem, K, Lindstrom, S, Wang, L, Smith, EN, Gordon, W, Vlieg, AVH, de Andrade, M, Brody, JA, Pattee, JW, Brumpton, BM, Suchon, P, Chen, M-H, Frazer, KA, Turman, C, Germain, M, MacDonald, J, Braekkan, SK, Armasu, SM, Pankratz, N, Jackson, RD, Nielsen, JB, Giulianin, F, Puurunen, MK, Ibrahim, M, Heckbert, SR, Bammler, TK, McCauley, BM, Taylor, KD, Pankow, JS, Reiner, AP, Gabrielsen, ME, Deleuze, J-F, O'Donnell, CJ, Kim, J, McKnight, B, Kraft, P, Hansen, J-B, Rosendaal, FR, Heit, JA, Tang, W, Morange, P-E, Johnson, AD, Kabrhel, C, van Dijk, EJ, Koudstaal, PJ, Luijckx, G-J, Nederkoorn, PJ, van Oostenbrugge, RJ, Visser, MC, Wermer, MJH, Kappelle, LJ, Esko, T, Metspalu, A, Magi, R, Nelis, M, Levi, CR, Maguire, J, Jimenez-Conde, J, Sharma, P, Sudlow, CLM, Rannikmae, K, Schmidt, R, Slowik, A, Pera, J, Thijs, VNS, Lindgren, AG, Ilinca, A, Melander, O, Engstrom, G, Rexrode, KM, Rothwell, PM, Stanne, TM, Johnson, JA, Danesh, J, Butterworth, AS, Heitsch, L, Boncoraglio, GB, Kubo, M, Pezzini, A, Rolfs, A, Giese, A-K, Weir, D, Ross, OA, Lemmons, R, Soderholm, M, Cushman, M, Jood, K, McDonough, CW, Bell, S, Linkohr, B, Lee, T-H, Putaala, J, Lopez, OL, Carty, CL, Jian, X, Schminke, U, Cullell, N, Delgado, P, Ibanez, L, Krupinski, J, Lioutas, V, Matsuda, K, Montaner, J, Muino, E, Roquer, J, Sarnowski, C, Sattar, N, Sibolt, G, Teumer, A, Rutten-Jacobs, L, Kanai, M, Gretarsdottir, S, Rost, NS, Yusuf, S, Almgren, P, Ay, H, Bevan, S, Brown, RD, Carrera, C, Buring, JE, Chen, W-M, Cotlarciuc, I, de Bakker, PIW, DeStefano, AL, den Hoed, M, Duan, Q, Engelter, ST, Falcone, GJ, Gustafsson, S, Hassan, A, Holliday, EG, Howard, G, Hsu, F-C, Ingelsson, E, Harris, TB, Kissela, BM, Kleindorfer, DO, Langenberg, C, Leys, D, Lin, W-Y, Lorentzen, E, Magnusson, PK, McArdle, PF, Pulit, SL, Rice, K, Sakaue, S, Sapkota, BR, Tanislav, C, Thorleifsson, G, Thorsteinsdottir, U, Tzourio, C, van Duijn, CM, Walters, M, Wareham, NJ, Amin, N, Aparicio, HJ, Attia, J, Beiser, AS, Berr, C, Bustamante, M, Caso, V, Choi, SH, Chowhan, A, Dartigues, J-F, Delavaran, H, Dorr, M, Ford, I, Gurpreet, WS, Hamsten, A, Hozawa, A, Ingelsson, M, Iwasaki, M, Kaffashian, S, Kalra, L, Kjartansson, O, Kloss, M, Labovitz, DL, Laurie, CC, Lind, L, Lindgren, CM, Makoto, H, Minegishi, N, Morris, AP, Mueller-Nurasyid, M, Norrving, B, Ogishima, S, Parati, EA, Pedersen, NL, Perola, M, Jousilahti, P, Pileggi, S, Rabionet, R, Riba-Llena, I, Ribases, M, Romero, JR, Rudd, AG, Sarin, A-P, Sarju, R, Satoh, M, Sawada, N, Sigurdsson, A, Smith, A, Stine, OC, Stott, DJ, Strauch, K, Takai, T, Tanaka, H, Touze, E, Tsugane, S, Uitterlinden, AG, Valdimarsson, EM, van der Lee, SJ, Wakai, K, Williams, SR, Wolfe, CDA, Wong, Q, Yamaji, T, Sanghera, DK, Stefansson, K, Martinez-Majander, N, Sobue, K, Soriano-Tarraga, C, Volzke, H, Akpa, O, Sarfo, FS, Akpalu, A, Obiako, R, Wahab, K, Osaigbovo, G, Owolabi, L, Komolafe, M, Jenkins, C, Arulogun, O, Ogbole, G, Adeoye, AM, Akinyemi, J, Agunloye, A, Fakunle, AG, Uvere, E, Olalere, A, Adebajo, OJ, Chen, J, Clarke, R, Collins, R, Guo, Y, Wang, C, Lv, J, Peto, R, Chen, Y, Fairhurst-Hunter, Z, Hill, M, Pozarickij, A, Schmidt, D, Stevens, B, Turnbull, I, Yu, C, Nagai, A, Murakami, Y, Shiroma, EJ, Sigurdsson, S, Ghanbari, M, Boerwinkle, E, Fongang, B, Wang, R, Ikram, MK, Volker, U, de Laat, KF, van Norden, AGW, de Kort, PL, Vermeer, SE, Brouwers, PJAM, Gons, RAR, den Heijer, T, van Dijk, GW, van Rooij, FGW, Aamodt, AH, Skogholt, AH, Willer, CJ, Heuch, I, Hagen, K, Fritsche, LG, Pedersen, LM, Ellekjaer, H, Zhou, W, Martinsen, AE, Kristoffersen, ES, Thomas, LF, Kleinschnitz, C, Frantz, S, Ungethum, K, Gallego-Fabrega, C, Lledos, M, Llucia-Carol, L, Sobrino, T, Campos, F, Castillo, J, Freijo, M, Arenillas, JF, Obach, V, Alvarez-Sabin, J, Molina, CA, Ribo, M, Munoz-Narbona, L, Lopez-Cancio, E, Millan, M, Diaz-Navarro, R, Vives-Bauza, C, Serrano-Heras, G, Segura, T, Dhar, R, Delgado-Mederos, R, Prats-Sanchez, L, Camps-Renom, P, Blay, N, Sumoy, L, Marti-Fabregas, J, Schnohr, P, Jensen, GB, Benn, M, Afzal, S, Kamstrup, PR, van Setten, J, van der Laan, SW, Vonk, JMJ, Kim, B-J, Curtze, S, Tiainen, M, Kinnunen, J, Menon, V, Sung, YJ, Saillour-Glenisson, F, and Gravel, S
Abstract: Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.
Published: 2022

10. A saturated map of common genetic variants associated with human height

Author: Yengo, L, Vedantam, S, Marouli, E, Sidorenko, J, Bartell, E, Sakaue, S, Graff, M, Eliasen, AU, Jiang, Y, Raghavan, S, Miao, J, Arias, JD, Graham, SE, Mukamel, RE, Spracklen, CN, Yin, X, Chen, S-H, Ferreira, T, Highland, HH, Ji, Y, Karaderi, T, Lin, K, Lull, K, Malden, DE, Medina-Gomez, C, Machado, M, Moore, A, Rueger, S, Sim, X, Vrieze, S, Ahluwalia, TS, Akiyama, M, Allison, MA, Alvarez, M, Andersen, MK, Ani, A, Appadurai, V, Arbeeva, L, Bhaskar, S, Bielak, LF, Bollepalli, S, Bonnycastle, LL, Bork-Jensen, J, Bradfield, JP, Bradford, Y, Braund, PS, Brody, JA, Burgdorf, KS, Cade, BE, Cai, H, Cai, Q, Campbell, A, Canadas-Garre, M, Catamo, E, Chai, J-F, Chai, X, Chang, L-C, Chang, Y-C, Chen, C-H, Chesi, A, Choi, SH, Chung, R-H, Cocca, M, Concas, MP, Couture, C, Cuellar-Partida, G, Danning, R, Daw, EW, Degenhard, F, Delgado, GE, Delitala, A, Demirkan, A, Deng, X, Devineni, P, Dietl, A, Dimitriou, M, Dimitrov, L, Dorajoo, R, Ekici, AB, Engmann, JE, Fairhurst-Hunter, Z, Farmaki, A-E, Faul, JD, Fernandez-Lopez, J-C, Forer, L, Francescatto, M, Freitag-Wolf, S, Fuchsberger, C, Galesloot, TE, Gao, Y, Gao, Z, Geller, F, Giannakopoulou, O, Giulianini, F, Gjesing, AP, Goel, A, Gordon, SD, Gorski, M, Grove, J, Guo, X, Gustafsson, S, Haessler, J, Hansen, TF, Havulinna, AS, Haworth, SJ, He, J, Heard-Costa, N, Hebbar, P, Hindy, G, Ho, Y-LA, Hofer, E, Holliday, E, Horn, K, Hornsby, WE, Hottenga, J-J, Huang, H, Huang, J, Huerta-Chagoya, A, Huffman, JE, Hung, Y-J, Huo, S, Hwang, MY, Iha, H, Ikeda, DD, Isono, M, Jackson, AU, Jager, S, Jansen, IE, Johansson, I, Jonas, JB, Jonsson, A, Jorgensen, T, Kalafati, I-P, Kanai, M, Kanoni, S, Karhus, LL, Kasturiratne, A, Katsuya, T, Kawaguchi, T, Kember, RL, Kentistou, KA, Kim, H-N, Kim, YJ, Kleber, ME, Knol, MJ, Kurbasic, A, Lauzon, M, Le, P, Lea, R, Lee, J-Y, Leonard, HL, Li, SA, Li, X, Liang, J, Lin, H, Lin, S-Y, Liu, J, Liu, X, Lo, KS, Long, J, Lores-Motta, L, Luan, J, Lyssenko, V, Lyytikainen, L-P, Mahajan, A, Mamakou, V, Mangino, M, Manichaikul, A, Marten, J, Mattheisen, M, Mavarani, L, McDaid, AF, Meidtner, K, Melendez, TL, Mercader, JM, Milaneschi, Y, Miller, JE, Millwood, IY, Mishra, PP, Mitchell, RE, Mollehave, LT, Morgan, A, Mucha, S, Munz, M, Nakatochi, M, Nelson, CP, Nethander, M, Nho, CW, Nielsen, AA, Nolte, IM, Nongmaithem, SS, Noordam, R, Ntalla, I, Nutile, T, Pandit, A, Christofidou, P, Parna, K, Pauper, M, Petersen, ERB, Petersen, L, Pitkanen, N, Polasek, O, Poveda, A, Preuss, MH, Pyarajan, S, Raffield, LM, Rakugi, H, Ramirez, J, Rasheed, A, Raven, D, Rayner, NW, Riveros, C, Rohde, R, Ruggiero, D, Ruotsalainen, SE, Ryan, KA, Sabater-Lleal, M, Saxena, R, Scholz, M, Sendamarai, A, Shen, B, Shi, J, Shin, JH, Sidore, C, Sitlani, CM, Slieker, RKC, Smit, RAJ, Smith, A, Smith, JA, Smyth, LJ, Southam, LE, Steinthorsdottir, V, Sun, L, Takeuchi, F, Tallapragada, D, Taylor, KD, Tayo, BO, Tcheandjieu, C, Terzikhan, N, Tesolin, P, Teumer, A, Theusch, E, Thompson, DJ, Thorleifsson, G, Timmers, PRHJ, Trompet, S, 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Walters, RG, Winkler, TW, Young, KL, Loh, P-R, Esko, T, Assimes, TL, Auton, A, Abecasis, GR, Willer, CJ, Locke, AE, Berndt, S, Lettre, G, Frayling, TM, Okada, Y, Wood, AR, Visscher, PM, and Hirschhorn, JN
Abstract: Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.
Published: 2022

11. Stroke genetics informs drug discovery and risk prediction across ancestries (vol 611, pg 115, 2022)

Author: Mishra, A, Malik, R, Hachiya, T, Jurgenson, T, Namba, S, Posner, DC, Kamanu, FK, Koido, M, Le Grand, Q, Shi, M, He, Y, Georgakis, MK, Caro, I, Krebs, K, Liaw, Y-C, Vaura, FC, Lin, K, Winsvold, BS, Srinivasasainagendra, V, Parodi, L, Bae, H-J, Chauhan, G, Chong, MR, Tomppo, L, Akinyemi, R, Roshchupkin, GV, Habib, N, Jee, YH, Thomassen, JQ, Abedi, V, Carcel-Marquez, J, Nygaard, M, Leonard, HL, Yang, C, Yonova-Doing, E, Knol, MJ, Lewis, AJ, Judy, RL, Ago, T, Amouyel, P, Armstrong, ND, Bakker, MK, Bartz, TM, Bennett, DA, Bis, JC, Bordes, C, Borte, S, Cain, A, Ridker, PM, Cho, K, Chen, Z, Cruchaga, C, Cole, JW, de Jager, PL, de Cid, R, Endres, M, Ferreira, LE, Geerlings, MI, Gasca, NC, Gudnason, V, Hata, J, He, J, Heath, AK, Ho, Y-L, Havulinna, AS, Hopewell, JC, Hyacinth, IH, Inouye, M, Jacob, MA, Jeon, CE, Jern, C, Kamouchi, M, Keene, KL, Kitazono, T, Kittner, SJ, Konuma, T, Kumar, A, Lacaze, P, Launer, LJ, Lee, K-J, Lepik, K, Li, J, Li, L, Manichaikul, A, Markus, HS, Marston, NA, Meitinger, T, Mitchell, BD, Montellano, FA, Morisaki, T, Mosley, TH, Nalls, MA, Nordestgaard, BG, O'Donnell, MJ, Okada, Y, Onland-Moret, NC, Ovbiagele, B, Peters, A, Psaty, BM, Rich, SS, Rosand, J, Sabatine, MS, Sacco, RL, Saleheen, D, Sandset, EC, Salomaa, V, Sargurupremraj, M, Sasaki, M, Satizabal, CL, Schmidt, CO, Shimizu, A, Smith, NL, Sloane, KL, Sutoh, Y, Sun, YV, Tanno, K, Tiedt, S, Tatlisumak, T, Torres-Aguila, NP, Tiwari, HK, Tregouet, D-A, Trompet, S, Tuladhar, AM, Tybjaerg-Hansen, A, van Vugt, M, Vibo, R, Verma, SS, Wiggins, KL, Wennberg, P, Woo, D, Wilson, PWF, Xu, H, Yang, Q, Yoon, K, Millwood, IY, Gieger, C, Ninomiya, T, Grabe, HJ, Jukema, JW, Rissanen, IL, Strbian, D, Kim, YJ, Chen, P-H, Mayerhofer, E, Howson, JMM, Irvin, MR, Adams, H, Wassertheil-Smoller, S, Christensen, K, Ikram, MA, Rundek, T, Worrall, BB, Lathrop, GM, Riaz, M, Simonsick, EM, Korv, J, Franca, PHC, Zand, R, Prasad, K, Frikke-Schmidt, R, de Leeuw, F-E, Liman, T, Haeusler, KG, Ruigrok, YM, Heuschmann, PU, Longstreth, WT, Jung, KJ, Bastarache, L, Pare, G, Damrauer, SM, Chasman, DI, Rotter, JI, Anderson, CD, Zwart, J-A, Niiranen, TJ, Fornage, M, Liaw, Y-P, Seshadri, S, Fernandez-Cadenas, I, Walters, RG, Ruff, CT, Owolabi, MO, Huffman, JE, Milani, L, Kamatani, Y, Dichgans, M, Debette, S, Mishra, A, Malik, R, Hachiya, T, Jurgenson, T, Namba, S, Posner, DC, Kamanu, FK, Koido, M, Le Grand, Q, Shi, M, He, Y, Georgakis, MK, Caro, I, Krebs, K, Liaw, Y-C, Vaura, FC, Lin, K, Winsvold, BS, Srinivasasainagendra, V, Parodi, L, Bae, H-J, Chauhan, G, Chong, MR, Tomppo, L, Akinyemi, R, Roshchupkin, GV, Habib, N, Jee, YH, Thomassen, JQ, Abedi, V, Carcel-Marquez, J, Nygaard, M, Leonard, HL, Yang, C, Yonova-Doing, E, Knol, MJ, Lewis, AJ, Judy, RL, Ago, T, Amouyel, P, Armstrong, ND, Bakker, MK, Bartz, TM, Bennett, DA, Bis, JC, Bordes, C, Borte, S, Cain, A, Ridker, PM, Cho, K, Chen, Z, Cruchaga, C, Cole, JW, de Jager, PL, de Cid, R, Endres, M, Ferreira, LE, Geerlings, MI, Gasca, NC, Gudnason, V, Hata, J, He, J, Heath, AK, Ho, Y-L, Havulinna, AS, Hopewell, JC, Hyacinth, IH, Inouye, M, Jacob, MA, Jeon, CE, Jern, C, Kamouchi, M, Keene, KL, Kitazono, T, Kittner, SJ, Konuma, T, Kumar, A, Lacaze, P, Launer, LJ, Lee, K-J, Lepik, K, Li, J, Li, L, Manichaikul, A, Markus, HS, Marston, NA, Meitinger, T, Mitchell, BD, Montellano, FA, Morisaki, T, Mosley, TH, Nalls, MA, Nordestgaard, BG, O'Donnell, MJ, Okada, Y, Onland-Moret, NC, Ovbiagele, B, Peters, A, Psaty, BM, Rich, SS, Rosand, J, Sabatine, MS, Sacco, RL, Saleheen, D, Sandset, EC, Salomaa, V, Sargurupremraj, M, Sasaki, M, Satizabal, CL, Schmidt, CO, Shimizu, A, Smith, NL, Sloane, KL, Sutoh, Y, Sun, YV, Tanno, K, Tiedt, S, Tatlisumak, T, Torres-Aguila, NP, Tiwari, HK, Tregouet, D-A, Trompet, S, Tuladhar, AM, Tybjaerg-Hansen, A, van Vugt, M, Vibo, R, Verma, SS, Wiggins, KL, Wennberg, P, Woo, D, Wilson, PWF, Xu, H, Yang, Q, Yoon, K, Millwood, IY, Gieger, C, Ninomiya, T, Grabe, HJ, Jukema, JW, Rissanen, IL, Strbian, D, Kim, YJ, Chen, P-H, Mayerhofer, E, Howson, JMM, Irvin, MR, Adams, H, Wassertheil-Smoller, S, Christensen, K, Ikram, MA, Rundek, T, Worrall, BB, Lathrop, GM, Riaz, M, Simonsick, EM, Korv, J, Franca, PHC, Zand, R, Prasad, K, Frikke-Schmidt, R, de Leeuw, F-E, Liman, T, Haeusler, KG, Ruigrok, YM, Heuschmann, PU, Longstreth, WT, Jung, KJ, Bastarache, L, Pare, G, Damrauer, SM, Chasman, DI, Rotter, JI, Anderson, CD, Zwart, J-A, Niiranen, TJ, Fornage, M, Liaw, Y-P, Seshadri, S, Fernandez-Cadenas, I, Walters, RG, Ruff, CT, Owolabi, MO, Huffman, JE, Milani, L, Kamatani, Y, Dichgans, M, and Debette, S
Published: 2022

12. Adiposity, metabolomic biomarkers and risk of nonalcoholic fatty liver disease: a case-cohort study

Author: Pang, Y, Kartsonaki, C, Lv, J, Millwood, IY, Fairhurst-Hunter, Z, Turnbull, I, Bragg, F, Hill, MR, Yu, C, Guo, Y, Chen, Y, Yang, L, Clarke, R, Walters, RG, Wu, M, Chen, J, Li, L, Chen, Z, and Holmes, MV
Subjects: Adult, Cohort Studies, Nutrition and Dietetics, Non-alcoholic Fatty Liver Disease, Medicine (miscellaneous), Humans, Obesity, Prospective Studies, Biomarkers, Adiposity
Abstract: Background Globally, the burden of obesity and associated nonalcoholic fatty liver disease (NAFLD) are rising, but little is known about the role that circulating metabolomic biomarkers play in mediating their association. Objectives We aimed to examine the observational and genetic associations of adiposity with metabolomic biomarkers and the observational associations of metabolomic biomarkers with incident NAFLD. Methods A case-subcohort study within the prospective China Kadoorie Biobank included 176 NAFLD cases and 180 subcohort individuals and measured 1208 metabolites in stored baseline plasma using a Metabolon assay. In the subcohort the observational and genetic associations of BMI with biomarkers were assessed using linear regression, with adjustment for multiple testing. Cox regression was used to estimate adjusted HRs for NAFLD associated with biomarkers. Results In observational analyses, BMI (kg/m2; mean: 23.9 in the subcohort) was associated with 199 metabolites at a 5% false discovery rate. The effects of genetically elevated BMI with specific metabolites were directionally consistent with the observational associations. Overall, 35 metabolites were associated with NAFLD risk, of which 15 were also associated with BMI, including glutamate (HR per 1-SD higher metabolite: 1.95; 95% CI: 1.48, 2.56), cysteine-glutathione disulfide (0.44; 0.31, 0.62), diaclyglycerol (C32:1) (1.71; 1.24, 2.35), behenoyl dihydrosphingomyelin (C40:0) (1.92; 1.42, 2.59), butyrylcarnitine (C4) (1.91; 1.38, 2.35), 2-hydroxybehenate (1.81; 1.34, 2.45), and 4-cholesten-3-one (1.79; 1.27, 2.54). The discriminatory performance of known risk factors was increased when 28 metabolites were also considered simultaneously in the model (weighted C-statistic: 0.84 to 0.90; P < 0.001). Conclusions Among relatively lean Chinese adults, a range of metabolomic biomarkers are associated with NAFLD risk and these biomarkers may lie on the pathway between adiposity and NAFLD.
Published: 2022
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13. Investigation into the Health Effects of Reduced Chymase Function Using Predicted Loss-of-Function Mutations in CMA1

Author: Fairhurst-Hunter, Z, Walters, RG, Zink, A, Lin, K, Guo, Y, Yu, C, Lv, J, Li, L, Freitag, DF, Chen, Z, and Millwood, IY
Subjects: Heart Failure, Chymases, Mutation, Genetics, Pharmaceutical Science, Molecular Medicine, Humans, Renal Insufficiency, Chronic, Cardiology and Cardiovascular Medicine, Fibrosis, Genetics (clinical)
Abstract: Tissue remodelling and fibrosis which occur in response to injury play a central role in the development of many diseases. Chymase is a key enzyme believed to mediate these pathological processes. As such, chymase inhibitors have been under active development for the treatment of a number of conditions. To investigate the impact of reduced chymase function, we constructed a genetic score from two pLoF mutations in the gene encoding chymase and tested its association with diseases and biomarkers. Our study found no association between the genetically-predicted reduced chymase function score and heart failure, chronic kidney disease or other predefined conditions. We additionally found no association of the score with any physical measurements or biomarkers. Our results provide no evidence in support of chymase inhibition as a novel therapeutic strategy for the treatment or prevention of heart failure, chronic kidney disease or major cardiovascular events, as previously proposed.
Published: 2022

14. GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI

Author: Couto Alves, A, De Silva, NMG, Karhunen, V, Sovio, U, Das, S, Taal, HR, Warrington, NM, Lewin, AM, Kaakinen, M, Cousminer, DL, Thiering, E, Timpson, NJ, Bond, TA, Lowry, E, Brown, CD, Estivill, X, Lindi, V, Bradfield, JP, Geller, F, Speed, D, Coin, LJM, Loh, M, Barton, SJ, Beilin, LJ, Bisgaard, H, Bønnelykke, K, Alili, R, Hatoum, IJ, Schramm, K, Cartwright, R, Charles, M, Salerno, V, Clément, K, Claringbould, AAJ, BIOS Consortium, van Duijn, CM, Moltchanova, E, Eriksson, JG, Elks, C, Feenstra, B, Flexeder, C, Franks, S, Frayling, TM, Freathy, RM, Elliott, P, Widén, E, Hakonarson, H, Hattersley, AT, Rodriguez, A, Banterle, M, Heinrich, J, Heude, B, Holloway, JW, Hofman, A, Hyppönen, E, Inskip, H, Kaplan, LM, Hedman, AK, Läärä, E, Prokisch, H, Grallert, H, Lakka, TA, Lawlor, DA, Melbye, M, Ahluwalia, TS, Marinelli, M, Millwood, IY, Palmer, LJ, Pennell, CE, Perry, JR, Ring, SM, Savolainen, MJ, Rivadeneira, F, Standl, M, Sunyer, J, Tiesler, CMT, Uitterlinden, AG, Schierding, W, O’Sullivan, JM, Prokopenko, I, Herzig, K, Smith, GD, O'Reilly, P, Felix, JF, Buxton, JL, Blakemore, AIF, Ong, KK, Jaddoe, VWV, Grant, SFA, Sebert, S, McCarthy, MI, Järvelin, M., and Early Growth Genetics (EGG) Consortium
Abstract: Copyright © 2019 The Authors. Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here, we combine genome-wide association studies with modeling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score, and colocalization analyses to determine how developmental timings, molecular pathways, and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult body mass index (BMI), with variants associated with adult BMI acting as early as 4 to 6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the LEPR/LEPROT locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies.
Published: 2019

15. GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI

Author: Alves, AC, De Silva, NMG, Karhunen, V, Sovio, U, Das, S, Taal, HR, Warrington, NM, Lewin, AM, Kaakinen, M, Cousminer, DL, Thiering, E, Timpson, NJ, Bond, TA, Lowry, E, Brown, CD, Estivill, X, Lindi, V, Bradfield, JP, Geller, F, Speed, D, Coin, LJM, Loh, M, Barton, SJ, Beilin, LJ, Bisgaard, H, Bonnelykke, K, Alili, R, Hatoum, IJ, Schramm, K, Cartwright, R, Charles, M-A, Salerno, V, Clement, K, Claringbould, AAJ, van Duijn, CM, Moltchanova, E, Eriksson, JG, Elks, C, Feenstra, B, Flexeder, C, Franks, S, Frayling, TM, Freathy, RM, Elliott, P, Widen, E, Hakonarson, H, Hattersley, AT, Rodriguez, A, Banterle, M, Heinrich, J, Heude, B, Holloway, JW, Hofman, A, Hypponen, E, Inskip, H, Kaplan, LM, Hedman, AK, Laara, E, Prokisch, H, Grallert, H, Lakka, TA, Lawlor, DA, Melbye, M, Ahluwalia, TS, Marinelli, M, Millwood, IY, Palmer, LJ, Pennell, CE, Perry, JR, Ring, SM, Savolainen, MJ, Rivadeneira, F, Standl, M, Sunyer, J, Tiesler, CMT, Uitterlinden, AG, Schierding, W, O'Sullivan, JM, Prokopenko, I, Herzig, K-H, Smith, GD, O'Reilly, P, Felix, JF, Buxton, JL, Blakemore, AIF, Ong, KK, Jaddoe, VWV, Grant, SFA, Sebert, S, McCarthy, MI, Jarvelin, M-R, Alves, AC, De Silva, NMG, Karhunen, V, Sovio, U, Das, S, Taal, HR, Warrington, NM, Lewin, AM, Kaakinen, M, Cousminer, DL, Thiering, E, Timpson, NJ, Bond, TA, Lowry, E, Brown, CD, Estivill, X, Lindi, V, Bradfield, JP, Geller, F, Speed, D, Coin, LJM, Loh, M, Barton, SJ, Beilin, LJ, Bisgaard, H, Bonnelykke, K, Alili, R, Hatoum, IJ, Schramm, K, Cartwright, R, Charles, M-A, Salerno, V, Clement, K, Claringbould, AAJ, van Duijn, CM, Moltchanova, E, Eriksson, JG, Elks, C, Feenstra, B, Flexeder, C, Franks, S, Frayling, TM, Freathy, RM, Elliott, P, Widen, E, Hakonarson, H, Hattersley, AT, Rodriguez, A, Banterle, M, Heinrich, J, Heude, B, Holloway, JW, Hofman, A, Hypponen, E, Inskip, H, Kaplan, LM, Hedman, AK, Laara, E, Prokisch, H, Grallert, H, Lakka, TA, Lawlor, DA, Melbye, M, Ahluwalia, TS, Marinelli, M, Millwood, IY, Palmer, LJ, Pennell, CE, Perry, JR, Ring, SM, Savolainen, MJ, Rivadeneira, F, Standl, M, Sunyer, J, Tiesler, CMT, Uitterlinden, AG, Schierding, W, O'Sullivan, JM, Prokopenko, I, Herzig, K-H, Smith, GD, O'Reilly, P, Felix, JF, Buxton, JL, Blakemore, AIF, Ong, KK, Jaddoe, VWV, Grant, SFA, Sebert, S, McCarthy, MI, and Jarvelin, M-R
Abstract: Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here, we combine genome-wide association studies with modeling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score, and colocalization analyses to determine how developmental timings, molecular pathways, and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult body mass index (BMI), with variants associated with adult BMI acting as early as 4 to 6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the LEPR/LEPROT locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies.
Published: 2019

16. Lipids, lipoproteins and metabolites and risk of incident myocardial infarction and stroke subtypes

Author: Holmes, MV, Millwood, IY, Kartsonaki, C, Hill, MR, Bennett, DA, Boxall, R, Guo, Y, Xu, X, Bian, Z, Hu, R, Walters, RG, Chen, J, Ala-Korpela, M, Parish, SE, Clarke, RJ, Peto, R, Collins, RE, Li, L, and Chen, Z
Subjects: lipids (amino acids, peptides, and proteins)
Abstract: Background Blood lipids are established risk factors for myocardial infarction (MI), but uncertainty persists about the relevance of lipids, lipoprotein particles and circulating metabolites for MI and stroke subtypes. Objectives To investigate the associations of plasma metabolic markers with risks of incident MI, ischemic stroke (IS) and intracerebral hemorrhage (ICH). Methods In a nested case-control study (912 MI, 1146 IS, 1138 ICH cases and 1466 common controls) aged 30-79 years in China Kadoorie Biobank, NMR spectroscopy measured 225 metabolic markers in baseline plasma samples. Logistic regression was used to estimate adjusted odds ratios (ORs) for a one standard deviation higher metabolic marker. Results Very-low-, intermediate- and low-density lipoprotein particles were positively associated with MI and IS. HDL particles were inversely associated with MI apart from small HDL. In contrast, no lipoprotein particles associated with ICH. Cholesterol in large HDL was inversely associated with MI and IS (ORs 0.79 and 0.88), whereas cholesterol in small HDL was not (ORs 0.99 and 1.06). Triglycerides within all lipoproteins, including most HDL particles, positively associated with MI, with a similar pattern for IS. Glycoprotein acetyls, ketone bodies, glucose and docosahexaenoic acid associated with all three diseases. The 225 metabolic markers showed concordant associations between MI and IS, but not with ICH. Conclusions Lipoproteins and lipids showed similar associations with MI and IS, but not with ICH. Within HDL particles, cholesterol concentrations were inversely associated, whereas TG concentrations were positively associations with MI. Glycoprotein acetyls and several non-lipid related metabolites associated with all three diseases.
Published: 2017

17. CETP gene variants and risk of vascular and non-vascular diseases in ~150,000 Chinese adults

Author: Millwood, IY, Bennett, D, Holmes, MV, Boxall, R, Guo, Y, Bian, Z, Yang, L, Sansome, GS, Chen, Y, Huaidong, D, Yu, C, Hacker, A, Reilly, D, Tan, Y, Hill, MR, Chen, J, Peto, R, Shen, H, Collins, RE, Clarke, RJ, Li, L, Walters, R, and Chen, Z
Subjects: lipids (amino acids, peptides, and proteins)
Abstract: Importance Raising HDL-cholesterol through pharmacological inhibition of cholesteryl ester transfer protein is a potentially important strategy for prevention and treatment of cardiovascular diseases. Objective To use genetic variants in the CETP gene to assess potential risks and benefits of lifelong lower cholesteryl ester transfer protein activity on cardiovascular diseases and other outcomes. Design A prospective biobank study, with 9-year follow-up through linkage to health insurance records and death and disease registries. Setting Five urban and five rural areas of China. Participants 151,217 individuals aged 30-79 years at baseline with genotype data, 17,854 of whom also had lipid measurements and 4,657 had lipoprotein particle measurements. Exposures Five CETP variants including an East Asian loss-of-function variant (rs2303790), combined in a genetic score weighted to effects on HDL-cholesterol. Main outcomes and measure Baseline lipids and lipoprotein particles, cardiovascular risk factors, and incidence of carotid plaque and pre-defined major vascular and non-vascular diseases and a phenome-wide range of diseases. Results Overall the mean LDL-cholesterol was 91 and HDL-cholesterol was 48 mg/dL. CETP variants were strongly associated with higher concentrations of HDL-cholesterol (e.g. 6.1 mg/dL per rs2303790 allele; P=9.4x10-4766 ), but were not associated with lower LDL-cholesterol. Within HDL particles, cholesterol esters were increased and triglycerides reduced, while within VLDL particles, cholesterol esters were reduced and triglycerides increased. Scaled to 10mg/dL higher HDL-cholesterol, the CETP genetic score was not associated with occlusive cardiovascular disease (18,550 events; OR=0.98 [95%CI 0.91-1.06]), major coronary events (5,767 events; 1.08 [0.95-1.22]), myocardial infarction (3,118 events; 1.14 [0.97-1.34]) ischemic stroke (13,759 events; 0.94 [0.83-1.06]), intracerebral haemorrhage (6,532 events; 0.94 [0.86-1.02]) or other vascular diseases or carotid plaque. Similarly, rs2303790 was not associated with any vascular diseases or plaque. There were no associations with non-vascular diseases other than an increased risk of eye diseases with rs2303790 (4,090 events; 1.43 [1.13-1.80], P=0.0028). Conclusions and relevance CETP variants were associated with altered HDL metabolism but did not lower LDL-cholesterol and had no significant effects on cardiovascular disease risk. These results suggest that in the absence of reduced LDL-cholesterol, increasing HDL-cholesterol by inhibition of cholesteryl ester transfer protein may not confer significant benefits for cardiovascular diseases.
Published: 2017

18. Fresh fruit consumption in relation to incident diabetes and diabetic vascular complications: A 7-y prospective study of 0.5 million Chinese adults

Author: Du, Huaidong, Li, L, Bennett, D, Guo, Y, Turnbull, I, Yang, L, Bragg, F, Bian, Z, Chen, Y-P, Chen, J, Millwood, IY, Sansome, S, Ma, L, Huang, Y, Zhang, N, Zheng, X, Sun, Q, Key, T, Collins, R, Peto, R, Chen, Z-M, and China Kadoorie Biobank study
Subjects: Medicine
Abstract: BACKGROUND: Despite the well-recognised health benefits of fresh fruit consumption, substantial uncertainties remain about its potential effects on incident diabetes and, among those with diabetes, on risks of death and major vascular complications. METHODS AND FINDINGS: Between June 2004 and July 2008, the nationwide China Kadoorie Biobank study recruited 0.5 million adults aged 30-79 (mean 51) y from ten diverse localities across China. During ~7 y of follow-up, 9,504 new diabetes cases were recorded among 482,591 participants without prevalent (previously diagnosed or screen-detected) diabetes at baseline, with an overall incidence rate of 2.8 per 1,000 person-years. Among 30,300 (5.9%) participants who had diabetes at baseline, 3,389 deaths occurred (overall mortality rate 16.5 per 1,000), along with 9,746 cases of macrovascular disease and 1,345 cases of microvascular disease. Cox regression yielded adjusted hazard ratios (HRs) associating each disease outcome with self-reported fresh fruit consumption, adjusting for potential confounders such as age, sex, region, socio-economic status, other lifestyle factors, body mass index, and family history of diabetes. Overall, 18.8% of participants reported consuming fresh fruit daily, and 6.4% never/rarely (non-consumers), with the proportion of non-consumers about three times higher in individuals with previously diagnosed diabetes (18.9%) than in those with screen-detected diabetes (6.7%) or no diabetes (6.0%). Among those without diabetes at baseline, higher fruit consumption was associated with significantly lower risk of developing diabetes (adjusted HR = 0.88 [95% CI 0.83-0.93] for daily versus non-consumers, p < 0.001, corresponding to a 0.2% difference in 5-y absolute risk), with a clear dose-response relationship. Among those with baseline diabetes, higher fruit consumption was associated with lower risks of all-cause mortality (adjusted HR = 0.83 [95% CI 0.74-0.93] per 100 g/d) and microvascular (0.72 [0.61-0.87]) and macrovascular (0.87 [0.82-0.93]) complications (p < 0.001), with similar HRs in individuals with previously diagnosed and screen-detected diabetes; estimated differences in 5-y absolute risk between daily and non-consumers were 1.9%, 1.1%, and 5.4%, respectively. The main limitation of this study was that, owing to its observational nature, we could not fully exclude the effects of residual confounding. CONCLUSION: In this large epidemiological study in Chinese adults, higher fresh fruit consumption was associated with significantly lower risk of diabetes and, among diabetic individuals, lower risks of death and development of major vascular complications.
Published: 2017

19. Interethnic analyses of blood pressure loci in populations of East Asian and European descent.

Author: Takeuchi, F, Akiyama, M, Matoba, N, Katsuya, T, Nakatochi, M, Tabara, Y, Narita, A, Saw, W-Y, Moon, S, Spracklen, CN, Chai, J-F, Kim, Y-J, Zhang, L, Wang, C, Li, H, Wu, J-Y, Dorajoo, R, Nierenberg, JL, Wang, YX, He, J, Bennett, DA, Takahashi, A, Momozawa, Y, Hirata, M, Matsuda, K, Rakugi, H, Nakashima, E, Isono, M, Shirota, M, Hozawa, A, Ichihara, S, Matsubara, T, Yamamoto, K, Kohara, K, Igase, M, Han, S, Gordon-Larsen, P, Huang, W, Lee, NR, Adair, LS, Hwang, MY, Lee, J, Chee, ML, Sabanayagam, C, Zhao, W, Liu, J, Reilly, DF, Sun, L, Huo, S, Edwards, TL, Long, J, Chang, L-C, Chen, C-H, Yuan, J-M, Koh, W-P, Friedlander, Y, Kelly, TN, Bin Wei, W, Xu, L, Cai, H, Xiang, Y-B, Lin, K, Clarke, R, Walters, RG, Millwood, IY, Li, L, Chambers, JC, Kooner, JS, Elliott, P, van der Harst, P, International Genomics of Blood Pressure (iGEN-BP) Consortium, Chen, Z, Sasaki, M, Shu, X-O, Jonas, JB, Heng, C-K, Chen, Y-T, Zheng, W, Lin, X, Teo, Y-Y, Tai, E-S, Cheng, C-Y, Wong, TY, Sim, X, Mohlke, KL, Yamamoto, M, Kim, B-J, Miki, T, Nabika, T, Yokota, M, Kamatani, Y, Kubo, M, Kato, N, Takeuchi, F, Akiyama, M, Matoba, N, Katsuya, T, Nakatochi, M, Tabara, Y, Narita, A, Saw, W-Y, Moon, S, Spracklen, CN, Chai, J-F, Kim, Y-J, Zhang, L, Wang, C, Li, H, Wu, J-Y, Dorajoo, R, Nierenberg, JL, Wang, YX, He, J, Bennett, DA, Takahashi, A, Momozawa, Y, Hirata, M, Matsuda, K, Rakugi, H, Nakashima, E, Isono, M, Shirota, M, Hozawa, A, Ichihara, S, Matsubara, T, Yamamoto, K, Kohara, K, Igase, M, Han, S, Gordon-Larsen, P, Huang, W, Lee, NR, Adair, LS, Hwang, MY, Lee, J, Chee, ML, Sabanayagam, C, Zhao, W, Liu, J, Reilly, DF, Sun, L, Huo, S, Edwards, TL, Long, J, Chang, L-C, Chen, C-H, Yuan, J-M, Koh, W-P, Friedlander, Y, Kelly, TN, Bin Wei, W, Xu, L, Cai, H, Xiang, Y-B, Lin, K, Clarke, R, Walters, RG, Millwood, IY, Li, L, Chambers, JC, Kooner, JS, Elliott, P, van der Harst, P, International Genomics of Blood Pressure (iGEN-BP) Consortium, Chen, Z, Sasaki, M, Shu, X-O, Jonas, JB, Heng, C-K, Chen, Y-T, Zheng, W, Lin, X, Teo, Y-Y, Tai, E-S, Cheng, C-Y, Wong, TY, Sim, X, Mohlke, KL, Yamamoto, M, Kim, B-J, Miki, T, Nabika, T, Yokota, M, Kamatani, Y, Kubo, M, and Kato, N
Abstract: Blood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, we perform a multi-stage genome-wide association study for BP (max N = 289,038) principally in East Asians and meta-analysis in East Asians and Europeans. We report 19 new genetic loci and ancestry-specific BP variants, conforming to a common ancestry-specific variant association model. At 10 unique loci, distinct non-rare ancestry-specific variants colocalize within the same linkage disequilibrium block despite the significantly discordant effects for the proxy shared variants between the ethnic groups. The genome-wide transethnic correlation of causal-variant effect-sizes is 0.898 and 0.851 for systolic and diastolic BP, respectively. Some of the ancestry-specific association signals are also influenced by a selective sweep. Our results provide new evidence for the role of common ancestry-specific variants and natural selection in ethnic differences in complex traits such as BP.
Published: 2018

20. Age at menarche and risk of major cardiovascular diseases: evidence of birth cohort effects from a prospective study of 300,000 Chinese women

Author: Yang, Ling, Li, LM, Millwood, IY, Peters, SA, Chen, YP, Guo, Y, Bian, Z, Woodward, M, and Chen, ZM
Abstract: Background Previous studies of mostly Western women have reported inconsistent findings on the association between age at menarche and risk of cardiovascular disease (CVD). Little is known about the association in China where there has been a large intergenerational decrease in women's mean age at menarche. Methods The China Kadoorie Biobank recruited 302,632 women aged 30–79 (mean 50.5) years in 2004–8 from 10 diverse regional sites across China. During 7 years follow-up, 14,111 incident cases of stroke, 14,093 of coronary heart disease (CHD), and 3200 CVD deaths were reported among 281,491 women who had no prior history of CVD at baseline. Cox regression yielded adjusted hazard ratios (HRs) relating age at menarche to CVD risks. Results The mean (SD) age of menarche was 15.4 (1.9) years, decreasing from 16.2 (2.0) among women born before 1940 to 14.7 (1.6) for those born during the 1960s–1970s. The patterns of association between age at menarche and CVD risk appeared to differ between different birth cohorts, with null associations in older generations but U-shaped or weak positive associations in younger women, especially those born after the 1960s. After minimizing the potential confounding effects from major CVD risk factors, both early and late menarche, compared with menarche at age 13 years, were associated with increased risk of CVD morbidity and mortality, which was more pronounced in younger generations. Conclusion Among Chinese women the associations between age at menarche and risk of CVD differed by birth cohort, suggesting other factors may underpin the association.
Published: 2016

21. Association between Common Variation at the FTO Locus and Changes in Body Mass Index from Infancy to Late Childhood: The Complex Nature of Genetic Association through Growth and Development

Author: Sovio, U, Mook, Dennis, Warrington, NM, Lawrence, R, Briollais, L, Palmer, CNA, Cecil, J, Sandling, JK, Syvanen, AC, Kaakinen, M, Beilin, LJ, Millwood, IY, Bennett, AJ, Laitinen, J, Pouta, A, Molitor, J, Smith, GD, Ben-Shlomo, Y, Jaddoe, Vincent, Palmer, LJ, Pennell, CE, Cole, TJ, McCarthy, MI, Jarvelin, MR, Timpson, NJ, Sovio, U, Mook, Dennis, Warrington, NM, Lawrence, R, Briollais, L, Palmer, CNA, Cecil, J, Sandling, JK, Syvanen, AC, Kaakinen, M, Beilin, LJ, Millwood, IY, Bennett, AJ, Laitinen, J, Pouta, A, Molitor, J, Smith, GD, Ben-Shlomo, Y, Jaddoe, Vincent, Palmer, LJ, Pennell, CE, Cole, TJ, McCarthy, MI, Jarvelin, MR, and Timpson, NJ
Abstract: An age-dependent association between variation at the FTO locus and BMI in children has been suggested. We meta-analyzed associations between the FTO locus (rs9939609) and BMI in samples, aged from early infancy to 13 years, from 8 cohorts of European ancestry. We found a positive association between additional minor (A) alleles and BMI from 5.5 years onwards, but an inverse association below age 2.5 years. Modelling median BMI curves for each genotype using the LMS method, we found that carriers of minor alleles showed lower BMI in infancy, earlier adiposity rebound (AR), and higher BMI later in childhood. Differences by allele were consistent with two independent processes: earlier AR equivalent to accelerating developmental age by 2.37% (95% CI 1.87, 2.87, p = 10(-20)) per A allele and a positive age by genotype interaction such that BMI increased faster with age (p = 10 223). We also fitted a linear mixed effects model to relate genotype to the BMI curve inflection points adiposity peak (AP) in infancy and AR. Carriage of two minor alleles at rs9939609 was associated with lower BMI at AP (-0.40% (95% CI: -0.74, -0.06), p = 0.02), higher BMI at AR (0.93% (95% CI: 0.22, 1.64), p = 0.01), and earlier AR (-4.72% (-5.81, -3.63), p = 10 217), supporting cross-sectional results. Overall, we confirm the expected association between variation at rs9939609 and BMI in childhood, but only after an inverse association between the same variant and BMI in infancy. Patterns are consistent with a shift on the developmental scale, which is reflected in association with the timing of AR rather than just a global increase in BMI. Results provide important information about longitudinal gene effects and about the role of FTO in adiposity. The associated shifts in developmental timing have clinical importance with respect to known relationships between AR and both later-life BMI and metabolic disease risk.
Published: 2011

22. Genome-Wide Association Study Reveals Multiple Loci Associated with Primary Tooth Development during Infancy

Author: Gibson, G, Pillas, D, Hoggart, CJ, Evans, DM, O'Reilly, PF, Sipila, K, Lahdesmaki, R, Millwood, IY, Kaakinen, M, Netuveli, G, Blane, D, Charoen, P, Sovio, U, Pouta, A, Freimer, N, Hartikainen, A-L, Laitinen, J, Vaara, S, Glaser, B, Crawford, P, Timpson, NJ, Ring, SM, Deng, G, Zhang, W, McCarthy, MI, Deloukas, P, Peltonen, L, Elliott, P, Coin, LJM, Smith, GD, Jarvelin, M-R, Gibson, G, Pillas, D, Hoggart, CJ, Evans, DM, O'Reilly, PF, Sipila, K, Lahdesmaki, R, Millwood, IY, Kaakinen, M, Netuveli, G, Blane, D, Charoen, P, Sovio, U, Pouta, A, Freimer, N, Hartikainen, A-L, Laitinen, J, Vaara, S, Glaser, B, Crawford, P, Timpson, NJ, Ring, SM, Deng, G, Zhang, W, McCarthy, MI, Deloukas, P, Peltonen, L, Elliott, P, Coin, LJM, Smith, GD, and Jarvelin, M-R
Abstract: Tooth development is a highly heritable process which relates to other growth and developmental processes, and which interacts with the development of the entire craniofacial complex. Abnormalities of tooth development are common, with tooth agenesis being the most common developmental anomaly in humans. We performed a genome-wide association study of time to first tooth eruption and number of teeth at one year in 4,564 individuals from the 1966 Northern Finland Birth Cohort (NFBC1966) and 1,518 individuals from the Avon Longitudinal Study of Parents and Children (ALSPAC). We identified 5 loci at P<5x10(-8), and 5 with suggestive association (P<5x10(-6)). The loci included several genes with links to tooth and other organ development (KCNJ2, EDA, HOXB2, RAD51L1, IGF2BP1, HMGA2, MSRB3). Genes at four of the identified loci are implicated in the development of cancer. A variant within the HOXB gene cluster associated with occlusion defects requiring orthodontic treatment by age 31 years.
Published: 2010

23. Genetic Determinants of Height Growth Assessed Longitudinally from Infancy to Adulthood in the Northern Finland Birth Cohort 1966

Author: Gibson, G, Sovio, U, Bennett, AJ, Millwood, IY, Molitor, J, O'Reilly, PF, Timpson, NJ, Kaakinen, M, Laitinen, J, Haukka, J, Pillas, D, Tzoulaki, I, Hoggart, C, Coin, LJM, Whittaker, J, Pouta, A, Hartikainen, A-L, Freimer, NB, Widen, E, Peltonen, L, Elliott, P, McCarthy, MI, Jarvelin, M-R, Gibson, G, Sovio, U, Bennett, AJ, Millwood, IY, Molitor, J, O'Reilly, PF, Timpson, NJ, Kaakinen, M, Laitinen, J, Haukka, J, Pillas, D, Tzoulaki, I, Hoggart, C, Coin, LJM, Whittaker, J, Pouta, A, Hartikainen, A-L, Freimer, NB, Widen, E, Peltonen, L, Elliott, P, McCarthy, MI, and Jarvelin, M-R
Abstract: Recent genome-wide association (GWA) studies have identified dozens of common variants associated with adult height. However, it is unknown how these variants influence height growth during childhood. We derived peak height velocity in infancy (PHV1) and puberty (PHV2) and timing of pubertal height growth spurt from parametric growth curves fitted to longitudinal height growth data to test their association with known height variants. The study consisted of N = 3,538 singletons from the prospective Northern Finland Birth Cohort 1966 with genotype data and frequent height measurements (on average 20 measurements per person) from 0-20 years. Twenty-six of the 48 variants tested associated with adult height (p<0.05, adjusted for sex and principal components) in this sample, all in the same direction as in previous GWA scans. Seven SNPs in or near the genes HHIP, DLEU7, UQCC, SF3B4/SV2A, LCORL, and HIST1H1D associated with PHV1 and five SNPs in or near SOCS2, SF3B4/SV2A, C17orf67, CABLES1, and DOT1L with PHV2 (p<0.05). We formally tested variants for interaction with age (infancy versus puberty) and found biologically meaningful evidence for an age-dependent effect for the SNP in SOCS2 (p = 0.0030) and for the SNP in HHIP (p = 0.045). We did not have similar prior evidence for the association between height variants and timing of pubertal height growth spurt as we had for PHVs, and none of the associations were statistically significant after correction for multiple testing. The fact that in this sample, less than half of the variants associated with adult height had a measurable effect on PHV1 or PHV2 is likely to reflect limited power to detect these associations in this dataset. Our study is the first genetic association analysis on longitudinal height growth in a prospective cohort from birth to adulthood and gives grounding for future research on the genetic regulation of human height during different periods of growth.
Published: 2009

24. Maternal leptin receptor gene variant Gln223Arg is not associated with variation in birth weight or maternal body mass index in UK and South Asian populations

Author: Rand, L, primary, Winchester, EC, additional, Millwood, IY, additional, Penny, MA, additional, and Kessling, AM, additional
Published: 2001
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25. Safety, tolerability, and pharmacokinetics of SPL7013 gel (VivaGel): a dose ranging, phase I study.

Author: O'Loughlin J, Millwood IY, McDonald HM, Price CF, Kaldor JM, Paull JR, O'Loughlin, John, Millwood, Iona Y, McDonald, Helen M, Price, Clare F, Kaldor, John M, and Paull, Jeremy R A
Abstract: Objectives: To evaluate safety, tolerability and systemic pharmacokinetics of escalating doses of SPL7013 Gel in healthy women.Design: : Randomized, double-blind, placebo-controlled dose-escalation trial.Methods: Thirty-seven healthy women were randomized to receive 3.5 g of 0.5% (N = 8), 1% (N = 8), or 3% (N = 9) SPL7013 Gel or placebo gel (N = 12), applied vaginally once daily for 7 consecutive days. Genital toxicity was determined by interview, physical examination, assessment of vaginal microflora and colposcopy. Systemic toxicity was determined by nongenital adverse events (AEs) and laboratory assessments. Plasma was collected for pharmacokinetic analysis.Results: Genital AEs considered potentially product-related were all mild and reported by 5 (20%) women receiving SPL7013 Gel and 2 (17%) women receiving placebo gel. The most common were abdominal pain or discomfort, with no reports of vaginal burning or malodour, or genital-tract pain. There were no clinically significant colposcopic findings, including of genital inflammation or epithelial disruption. Lower concentrations of normal lactobacillary flora occurred during SPL7013 Gel and placebo gel use, with a decrease in anaerobes in the SPL7013 Gel groups. There were no reported cases of bacterial vaginosis, and lactobacilli returned to predose levels in most women after treatment. All nongenital AEs were of mild or moderate severity, expect for a severe tension headache in a woman receiving placebo. There was no absorption of SPL7013 into the systemic circulation.Conclusions: SPL7013 Gel applied vaginally once daily for 7 days at concentrations of 0.5% to 3% was safe and well tolerated in healthy, sexually abstinent women, with no evidence of systemic toxicity or absorption. [ABSTRACT FROM AUTHOR]
Published: 2010
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26. Genome-wide association analyses for lung function and chronic obstructive pulmonary disease identify new loci and potential druggable targets

Author: Wain, LV, Shrine, N, Artigas, MS, Erzurumluoglu, AM, Noyvert, B, Bossini-Castillo, L, Obeidat, M, Henry, AP, Portelli, MA, Hall, RJ, Billington, CK, Rimington, TL, Fenech, AG, John, C, Blake, T, Jackson, VE, Allen, RJ, Prins, BP, Understanding Society Scientific Group, Campbell, A, Porteous, DJ, Jarvelin, M-R, Wielscher, M, James, AL, Hui, J, Wareham, NJ, Zhao, JH, Wilson, JF, Joshi, PK, Stubbe, B, Rawal, R, Schulz, H, Imboden, M, Probst-Hensch, NM, Karrasch, S, Gieger, C, Deary, IJ, Harris, SE, Marten, J, Rudan, I, Enroth, S, Gyllensten, U, Kerr, SM, Polasek, O, Kähönen, M, Surakka, I, Vitart, V, Hayward, C, Lehtimäki, T, Raitakari, OT, Evans, DM, Henderson, AJ, Pennell, CE, Wang, CA, Sly, PD, Wan, ES, Busch, R, Hobbs, BD, Litonjua, AA, Sparrow, DW, Gulsvik, A, Bakke, PS, Crapo, JD, Beaty, TH, Hansel, NN, Mathias, RA, Ruczinski, I, Barnes, KC, Bossé, Y, Joubert, P, Van Den Berge, M, Brandsma, C-A, Paré, PD, Sin, DD, Nickle, DC, Hao, K, Gottesman, O, Dewey, FE, Bruse, SE, Carey, DJ, Kirchner, HL, Geisinger-Regeneron DiscovEHR Collaboration, Jonsson, S, Thorleifsson, G, Jonsdottir, I, Gislason, T, Stefansson, K, Schurmann, C, Nadkarni, G, Bottinger, EP, Loos, RJF, Walters, RG, Chen, Z, Millwood, IY, Vaucher, J, Kurmi, OP, Li, L, Hansell, AL, Brightling, C, Zeggini, E, Cho, MH, Silverman, EK, Sayers, I, Trynka, G, Morris, AP, Strachan, DP, Hall, IP, and Tobin, MD
Subjects: Adult, Aged, 80 and over, Male, Middle Aged, Polymorphism, Single Nucleotide, Asthma, respiratory tract diseases, 3. Good health, Epigenesis, Genetic, Pulmonary Disease, Chronic Obstructive, Genetic Loci, Risk Factors, Humans, Female, Genetic Predisposition to Disease, Lung, Alleles, Aged, Genome-Wide Association Study
Abstract: Chronic obstructive pulmonary disease (COPD) is characterized by reduced lung function and is the third leading cause of death globally. Through genome-wide association discovery in 48,943 individuals, selected from extremes of the lung function distribution in UK Biobank, and follow-up in 95,375 individuals, we increased the yield of independent signals for lung function from 54 to 97. A genetic risk score was associated with COPD susceptibility (odds ratio per 1 s.d. of the risk score (∼6 alleles) (95% confidence interval) = 1.24 (1.20-1.27), P = 5.05 × 10‾⁴⁹), and we observed a 3.7-fold difference in COPD risk between individuals in the highest and lowest genetic risk score deciles in UK Biobank. The 97 signals show enrichment in genes for development, elastic fibers and epigenetic regulation pathways. We highlight targets for drugs and compounds in development for COPD and asthma (genes in the inositol phosphate metabolism pathway and CHRM3) and describe targets for potential drug repositioning from other clinical indications.

27. Phenotypic vs. Genetic Mismatch of BMI and Type 2 Diabetes: Evidence from Two Perspective Cohort Studies.

Author: Li A, Gong S, Yu C, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Yang X, Hou W, Chen J, Chen Z, Lv J, Li L, and Sun D
Abstract: Little is known about the population-based mismatch between phenotypic and genetic BMI (BMI-PGM) and its association with type 2 diabetes. We therefore used data from the China Kadoorie Biobank and UK Biobank and calculated BMI-PGM for each participant as the difference between the percentile for adjusted BMI at baseline and the percentile for adjusted polygenic risk score for BMI. Participants were categorized into discordantly low (BMI-PGM< the 1st quartile), concordant (the 1st quartile ≤BMI-PGM
Published: 2024
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28. Risk prediction of ischemic heart disease using plasma proteomics, conventional risk factors and polygenic scores in Chinese and European adults.

Author: Mazidi M, Wright N, Yao P, Kartsonaki C, Millwood IY, Fry H, Said S, Pozarickij A, Pei P, Chen Y, Wang B, Avery D, Du H, Schmidt DV, Yang L, Lv J, Yu C, Sun D, Chen J, Hill M, Peto R, Collins R, Bennett DA, Walters RG, Li L, Clarke R, and Chen Z
Subjects: Adult, Aged, Female, Humans, Male, Middle Aged, Biomarkers blood, Case-Control Studies, China epidemiology, East Asian People genetics, Europe epidemiology, Risk Assessment, Risk Factors, White People genetics, Genetic Risk Score, Myocardial Ischemia blood, Myocardial Ischemia genetics, Myocardial Ischemia epidemiology, Proteomics
Abstract: Plasma proteomics could enhance risk prediction for multiple diseases beyond conventional risk factors or polygenic scores (PS). To assess utility of proteomics for risk prediction of ischemic heart disease (IHD) compared with conventional risk factors and PS in Chinese and European populations. A nested case-cohort study measured plasma levels of 2923 proteins using Olink Explore panel in ~ 4000 Chinese adults (1976 incident IHD cases and 2001 sub-cohort controls). We used conventional and machine learning (Boruta) methods to develop proteomics-based prediction models of IHD, with discrimination assessed using area under the curve (AUC), C-statistics and net reclassification index (NRI). These were compared with conventional risk factors and PS in Chinese and in 37,187 Europeans. Overall, 446 proteins were associated with IHD (false discovery rate < 0.05) in Chinese after adjustment for conventional cardiovascular disease risk factors. Proteomic risk models alone yielded higher C-statistics for IHD than conventional risk factors or PS (0.855 [95%CI 0.841-0.868] vs. 0.845 [0.829-0.860] vs 0.553 [0.528-0.578], respectively). Addition of 446 proteins to PS improved C-statistics to 0.857 (0.843-0.871) and NRI by 109.1%; and addition to conventional risk factors improved C-statistics to 0.868 (0.854-0.882) and NRI by 86.9%. Boruta analysis identified 30 proteins accounting for ~ 90% of improvement in NRI for IHD conferred by all 2923 proteins. Similar proteomic panels yielded comparable improvements in risk prediction of IHD in Europeans. Plasma proteomics improved risk prediction of IHD beyond conventional risk factors and PS and could enhance precision medicine approaches for primary prevention of IHD., Competing Interests: Declarations. Conflict of interest: None of the authors have any conflicts of interest in relation to this report. Ethical approval: The China Kadoorie Biobank (CKB) complies with all required ethical standards for medical research on human subjects. Ethical approvals were obtained and been maintained by the relevant institutional ethical research committees in the UK and China. Consent to participate/publication: All participants provided written informed consent., (© 2024. The Author(s).)
Published: 2024
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29. DNA Methylation Age Mediates Effect of Metabolic Profile on Cardiovascular and General Aging.

Author: Si J, Ma Y, Yu C, Sun D, Pang Y, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Zheng X, Avery D, Chen J, Chen Z, Liang L, Li L, and Lv J
Subjects: Humans, Female, Male, Middle Aged, Aged, Prospective Studies, Epigenesis, Genetic, Metabolome, Atherosclerosis genetics, Atherosclerosis metabolism, Atherosclerosis epidemiology, Atherosclerosis blood, China epidemiology, Aged, 80 and over, Adult, DNA Methylation, Aging metabolism, Aging genetics, Frailty genetics, Frailty metabolism, Frailty epidemiology
Abstract: Background: Alterations in lipid metabolism and DNA methylation are 2 hallmarks of aging. Connecting metabolomic, epigenomic, and aging outcomes help unravel the complex mechanisms underlying aging. We aimed to assess whether DNA methylation clocks mediate the association of circulating metabolites with incident atherosclerotic cardiovascular disease (ASCVD) and frailty., Methods: The China Kadoorie Biobank is a prospective cohort study with a baseline survey from 2004 to 2008 and a follow-up period until December 31, 2018. We used the Infinium Methylation EPIC BeadChip to measure the methylation levels of 988 participants' baseline blood leukocyte DNA. Metabolite profiles, including lipoprotein particles, lipid constituents, and various circulating metabolites, were measured using quantitative nuclear magnetic resonance. The pace of DNA methylation age acceleration (AA) was calculated using 5 widely used epigenetic clocks (the first generation: Horvath, Hannum, and Li; the second generation: Grim and Pheno). Incident ASCVD was ascertained through linkage with local death and disease registries and national health insurance databases, supplemented by active follow-up. The frailty index was constructed using medical conditions, symptoms, signs, and physical measurements collected at baseline., Results: A total of 508 incident cases of ASCVD were documented during a median follow-up of 9.5 years. The first generation of epigenetic clocks was associated with the risk of ASCVD ( P <0.05). For each SD increment in LiAA, HorvathAA, and HannumAA, the corresponding hazard ratios for ASCVD risk were 1.16 (1.05-1.28), 1.10 (1.00-1.22), and 1.17 (1.04-1.31), respectively. Only LiAA mediated the association of various metabolites (lipids, fatty acids, histidine, and inflammatory biomarkers) with ASCVD, with the mediating proportion reaching up to 15% for the diameter of low-density lipoprotein ( P =1.2×10 -2 ). Regarding general aging, a 1-SD increase in GrimAA was associated with an average increase of 0.10 in the frailty index ( P =2.0×10 -3 ), and a 33% and 63% increased risk of prefrailty and frailty at baseline ( P =1.5×10 -2 and 5.8×10 -2 ), respectively; this association was not observed with other clocks. GrimAA mediated the effect of various lipids, fatty acids, glucose, lactate, and inflammatory biomarkers on the frailty index, with the mediating proportion reaching up to 22% for triglycerides in very small-sized very low-density lipoprotein ( P =6.0×10 -3 )., Conclusions: These findings suggest that epigenomic mechanisms may play a role in the associations between circulating metabolites and the aging process. Different mechanisms underlie the first and second generations of DNA methylation age in cardiovascular and general aging., Competing Interests: None.
Published: 2024
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30. Mosaic loss of chromosome Y, tobacco smoking and risk of age-related lung diseases: insights from two prospective cohorts.

Author: Weng C, Zhao Y, Song M, Shao Z, Pang Y, Yu C, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Chen J, Chen Z, Genovese G, Terao C, Lv J, Li L, and Sun D
Subjects: Humans, Male, Middle Aged, Prospective Studies, Aged, China epidemiology, Lung Diseases epidemiology, Lung Diseases genetics, Mosaicism, Chromosomes, Human, Y, United Kingdom epidemiology, Idiopathic Pulmonary Fibrosis genetics, Idiopathic Pulmonary Fibrosis epidemiology, Risk Factors, Female, Lung Neoplasms genetics, Lung Neoplasms epidemiology, Proportional Hazards Models, Pulmonary Disease, Chronic Obstructive genetics, Pulmonary Disease, Chronic Obstructive epidemiology, Tobacco Smoking adverse effects
Abstract: Background: Little is known about the underlying relationship between mosaic loss of chromosome Y (mLOY), the most common chromosomal alterations in older men, and the risk of age-related lung diseases., Methods: We included 217 780 participants from the UK Biobank (UKB) and 42 859 participants from the China Kadoorie Biobank. The mLOY events were detected using the Mosaic Chromosomal Alterations (MoChA) pipeline. Outcomes included all lung diseases, COPD, lung cancer and idiopathic pulmonary fibrosis (IPF). Cox proportional hazard models were fitted to estimate the hazard ratios and 95% confidence intervals of mLOY with lung diseases in both cohorts. The combined hazard ratios were derived from meta-analysis., Results: Results from the two cohorts showed that expanded mLOY was associated with increased risks of all lung diseases (HR 1.19 (95% CI 1.04-1.36)), COPD (HR 1.20 (95% CI 1.13-1.28)), lung cancer (HR 1.34 (95% CI 1.21-1.48)) and IPF (HR 1.34 (95% CI 1.16-1.56) in the UKB). There was evidence of positive interactions between mLOY and smoking behaviour (relative excess risk due to interaction (97.5% CI) >0). Additionally, we observed that current smokers with expanded mLOY had the highest risk of incident lung diseases in both cohorts., Conclusions: mLOY may be a novel predictor for age-related lung diseases. For current smokers carrying mLOY, adopting quitting smoking behaviour may contribute to substantially reducing their risk of incident lung diseases., Competing Interests: Conflict of interest: The authors have no potential conflicts of interest to disclose., (Copyright ©The authors 2024.)
Published: 2024
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31. Association of autosomal mosaic chromosomal alterations with risk of bladder cancer in Chinese adults: a prospective cohort study.

Author: Song M, Han Y, Zhao Y, Lv J, Yu C, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Yang X, Yao W, Chen J, Chen Z, Genovese G, Terao C, Li L, and Sun D
Subjects: Humans, Male, Female, Middle Aged, Prospective Studies, China epidemiology, Risk Factors, Adult, Aged, Genetic Predisposition to Disease, East Asian People, Urinary Bladder Neoplasms genetics, Urinary Bladder Neoplasms epidemiology, Mosaicism, Chromosome Aberrations
Abstract: Little is known about the prospective association between autosomal mosaic chromosomal alterations (mCAs), a group of large-scale somatic mutations on autosomes, and bladder cancer. Here we utilized data from 99,877 participants who were free of physician-diagnosed cancer at baseline (2004-2008) of the China Kadoorie Biobank to estimate the associations between autosomal mCAs and bladder cancer (ICD-10: C67). A total of 2874 autosomal mCAs events among 2612 carriers (2.6%) were detected. After a median follow-up of 12.4 years, we discovered that participants with all autosomal mCAs exhibited higher risks of bladder cancer, with a multivariable-adjusted hazard ratio (HR) (95% confidence interval [CI]) of 2.60 (1.44, 4.70). The estimate of such association was even stronger for mosaic loss events (HR [95% CI]: 6.68 [2.92, 15.30]), while it was not significant for CN-LOH events. Both expanded (cell fraction ≥10%) and non-expanded autosomal mCAs, as well as mosaic loss, were associated with increased risks of bladder cancer. Of interest, physical activity (PA) significantly modified the associations of autosomal mCAs and mosaic loss (P interaction = 0.038 and 0.012, respectively) with bladder cancer. The increased risks of bladder cancer were only observed with mCAs and mosaic loss among participants with a lower level of PA (HR [95% CI]: 5.11 [2.36, 11.09] and 16.30 [6.06, 43.81]), but not among participants with a higher level of PA. Our findings suggest that peripheral leukocyte autosomal mCAs may represent a novel risk factor for bladder cancer, and PA may serve as a potential intervention target for mCAs carriers., (© 2024. The Author(s).)
Published: 2024
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32. Genome-wide DNA methylation profiling in blood reveals epigenetic signature of incident acute coronary syndrome.

Author: Long P, Si J, Zhu Z, Jiang Y, Wang Y, Jiang Q, Li W, Xu X, You Y, Qu M, Wang H, Mo T, Liu K, Jiang J, Wang Q, Yu C, Guo Y, Millwood IY, Walters RG, He X, Yuan Y, Wang H, Zhang X, He M, Guo H, Chen Z, Li L, Lv J, Wang C, and Wu T
Subjects: Humans, Male, Female, Middle Aged, Case-Control Studies, Prospective Studies, Aged, DNA-Binding Proteins genetics, Transcription Factors genetics, China epidemiology, Mendelian Randomization Analysis, Risk Factors, Biomarkers blood, Acute Coronary Syndrome genetics, Acute Coronary Syndrome blood, DNA Methylation, Epigenesis, Genetic, Genome-Wide Association Study
Abstract: DNA methylation (DNAm) has been implicated in acute coronary syndrome (ACS), but the causality remains unclear in cross-sectional studies. Here, we conduct a prospective epigenome-wide association study of incident ACS in two Chinese cohorts (discovery: 751 nested case-control pairs; replication: 476 nested case-control pairs). We identified and validated 26 differentially methylated positions (DMPs, false discovery rate [FDR] <0.05), including three mapped to known cardiovascular disease genes (PRKCZ, PRDM16, EHBP1L1) and four with causal evidence from Mendelian randomization (PRKCZ, TRIM27, EMC2, EHBP1L1). Two hypomethylated DMPs were negatively correlated with the expression in blood of their mapped genes (PIGG and EHBP1L1), which were further found to overexpress in leukocytes and/or atheroma plaques. Finally, our DMPs could substantially improve the prediction of ACS over traditional risk factors and polygenic scores. These findings demonstrate the importance of DNAm in the pathogenesis of ACS and highlight DNAm as potential predictive biomarkers and treatment targets., (© 2024. The Author(s).)
Published: 2024
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33. Associations of polygenic risk scores with risks of stroke and its subtypes in Chinese.

Author: Yang S, Sun Z, Sun D, Yu C, Guo Y, Sun D, Pang Y, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Lu Y, Burgess S, Avery D, Clarke R, Chen J, Chen Z, Li L, and Lv J
Subjects: Adult, Aged, Female, Humans, Male, Middle Aged, China epidemiology, East Asian People genetics, Genome-Wide Association Study, Incidence, Phenotype, Polymorphism, Single Nucleotide, Predictive Value of Tests, Prognosis, Risk Assessment, Genetic Risk Score, Hemorrhagic Stroke epidemiology, Hemorrhagic Stroke diagnosis, Hemorrhagic Stroke genetics, Ischemic Stroke genetics, Ischemic Stroke epidemiology, Ischemic Stroke diagnosis
Abstract: Background and Purpose: Previous studies, mostly focusing on the European population, have reported polygenic risk scores (PRSs) might achieve risk stratification of stroke. We aimed to examine the association strengths of PRSs with risks of stroke and its subtypes in the Chinese population., Methods: Participants with genome-wide genotypic data in China Kadoorie Biobank were split into a potential training set (n=22 191) and a population-based testing set (n=72 150). Four previously developed PRSs were included, and new PRSs for stroke and its subtypes were developed. The PRSs showing the strongest association with risks of stroke or its subtypes in the training set were further evaluated in the testing set. Cox proportional hazards regression models were used to estimate the association strengths of different PRSs with risks of stroke and its subtypes (ischaemic stroke (IS), intracerebral haemorrhage (ICH) and subarachnoid haemorrhage (SAH))., Results: In the testing set, during 872 919 person-years of follow-up, 8514 incident stroke events were documented. The PRSs of any stroke (AS) and IS were both positively associated with risks of AS, IS and ICH (p<0.05). The HR for per SD increment (HR SD ) of PRS AS was 1.10 (95% CI 1.07 to 1.12), 1.10 (95% CI 1.07 to 1.12) and 1.13 (95% CI 1.07 to 1.20) for AS, IS and ICH, respectively. The corresponding HR SD of PRS IS was 1.08 (95% CI 1.06 to 1.11), 1.08 (95% CI 1.06 to 1.11) and 1.09 (95% CI 1.03 to 1.15). PRS ICH was positively associated with the risk of ICH (HR SD =1.07, 95% CI 1.01 to 1.14). PRS SAH was not associated with risks of stroke and its subtypes. The addition of current PRSs offered little to no improvement in stroke risk prediction and risk stratification., Conclusions: In this Chinese population, the association strengths of current PRSs with risks of stroke and its subtypes were moderate, suggesting a limited value for improving risk prediction over traditional risk factors in the context of current genome-wide association study under-representing the East Asian population., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Published: 2024
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34. The Role of Furin and Its Therapeutic Potential in Cardiovascular Disease Risk.

Author: Fry H, Mazidi M, Kartsonaki C, Clarke R, Walters RG, Chen Z, and Millwood IY
Subjects: Humans, Risk Factors, Animals, Furin metabolism, Furin genetics, Cardiovascular Diseases metabolism, Cardiovascular Diseases genetics
Abstract: Furin is an important proteolytic enzyme, converting several proteins from inactive precursors to their active forms. Recently, proteo-genomic analyses in European and East Asian populations suggested a causal association of furin with ischaemic heart disease, and there is growing interest in its role in cardiovascular disease (CVD) aetiology. In this narrative review, we present a critical appraisal of evidence from population studies to assess furin's role in CVD risk and potential as a drug target for CVD. Whilst most observational studies report positive associations between furin expression and CVD risk, some studies report opposing effects, which may reflect the complex biological roles of furin and its substrates. Genetic variation in FURIN is also associated with CVD and its risk factors. We found no evidence of current clinical development of furin as a drug target for CVD, although several phase 1 and 2 clinical trials of furin inhibitors as a type of cancer immunotherapy have been completed. The growing field of proteo-genomics in large-scale population studies may inform the future development of furin and other potential drug targets to improve the treatment and prevention of CVD.
Published: 2024
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35. Conventional and genetic associations of BMI with major vascular and non-vascular disease incidence and mortality in a relatively lean Chinese population: U-shaped relationship revisited.

Author: Iona A, Bragg F, Fairhurst-Hunter Z, Millwood IY, Wright N, Lin K, Yang L, Du H, Chen Y, Pei P, Cheng L, Schmidt D, Avery D, Yu C, Lv J, Clarke R, Walters R, Li L, Parish S, and Chen Z
Subjects: Humans, Middle Aged, Male, Female, China epidemiology, Adult, Aged, Incidence, Prospective Studies, Cardiovascular Diseases mortality, Cardiovascular Diseases genetics, Risk Factors, Proportional Hazards Models, Thinness genetics, Thinness epidemiology, East Asian People, Body Mass Index, Mendelian Randomization Analysis
Abstract: Background: Higher body mass index (BMI) is associated with higher incidence of cardiovascular and some non-cardiovascular diseases (CVDs/non-CVDs). However, uncertainty remains about its associations with mortality, particularly at lower BMI levels., Methods: The prospective China Kadoorie Biobank recruited >512 000 adults aged 30-79 years in 2004-08 and genotyped a random subset of 76 000 participants. In conventional and Mendelian randomization (MR) analyses, Cox regression yielded adjusted hazard ratios (HRs) associating measured and genetically predicted BMI levels with incident risks of major vascular events (MVEs; conventional/MR 68 431/23 621), ischaemic heart disease (IHD; 50 698/12 177), ischaemic stroke (IS; 42 427/11 897) and intracerebral haemorrhage (ICH; 7644/4712), and with mortality risks of CVD (15 427/6781), non-CVD (26 915/4355) and all causes (42 342/6784), recorded during ∼12 years of follow-up., Results: Overall, the mean BMI was 23.8 (standard deviation: 3.2) kg/m2 and 13% had BMIs of <20 kg/m2. Measured and genetically predicted BMI showed positive log-linear associations with MVE, IHD and IS, but a shallower positive association with ICH in conventional analyses. Adjusted HRs per 5 kg/m2 higher genetically predicted BMI were 1.50 (95% CI 1.41-1.58), 1.49 (1.38-1.61), 1.42 (1.31-1.54) and 1.64 (1.58-1.69) for MVE, IHD, IS and ICH, respectively. These were stronger than associations in conventional analyses [1.21 (1.20-1.23), 1.28 (1.26-1.29), 1.31 (1.29-1.33) and 1.14 (1.10-1.18), respectively]. At BMIs of ≥20 kg/m2, there were stronger positive log-linear associations of BMI with CVD, non-CVD and all-cause mortality in MR than in conventional analyses., Conclusions: Among relatively lean Chinese adults, higher genetically predicted BMI was associated with higher risks of incident CVDs. Excess mortality risks at lower BMI in conventional analyses are likely not causal and may reflect residual reverse causality., (© The Author(s) 2024. Published by Oxford University Press on behalf of the International Epidemiological Association.)
Published: 2024
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36. Publisher Correction: Understanding the genetic complexity of puberty timing across the allele frequency spectrum.

Author: Kentistou KA, Kaisinger LR, Stankovic S, Vaudel M, Mendes de Oliveira E, Messina A, Walters RG, Liu X, Busch AS, Helgason H, Thompson DJ, Santoni F, Petricek KM, Zouaghi Y, Huang-Doran I, Gudbjartsson DF, Bratland E, Lin K, Gardner EJ, Zhao Y, Jia RY, Terao C, Riggan MJ, Bolla MK, Yazdanpanah M, Yazdanpanah N, Bradfield JP, Broer L, Campbell A, Chasman DI, Cousminer DL, Franceschini N, Franke LH, Girotto G, He C, Järvelin MR, Joshi PK, Kamatani Y, Karlsson R, Luan J, Lunetta KL, Mägi R, Mangino M, Medland SE, Meisinger C, Noordam R, Nutile T, Concas MP, Polašek O, Porcu E, Ring SM, Sala C, Smith AV, Tanaka T, van der Most PJ, Vitart V, Wang CA, Willemsen G, Zygmunt M, Ahearn TU, Andrulis IL, Anton-Culver H, Antoniou AC, Auer PL, Barnes CLK, Beckmann MW, Berrington de Gonzalez A, Bogdanova NV, Bojesen SE, Brenner H, Buring JE, Canzian F, Chang-Claude J, Couch FJ, Cox A, Crisponi L, Czene K, Daly MB, Demerath EW, Dennis J, Devilee P, De Vivo I, Dörk T, Dunning AM, Dwek M, Eriksson JG, Fasching PA, Fernandez-Rhodes L, Ferreli L, Fletcher O, Gago-Dominguez M, García-Closas M, García-Sáenz JA, González-Neira A, Grallert H, Guénel P, Haiman CA, Hall P, Hamann U, Hakonarson H, Hart RJ, Hickey M, Hooning MJ, Hoppe R, Hopper JL, Hottenga JJ, Hu FB, Huebner H, Hunter DJ, Jernström H, John EM, Karasik D, Khusnutdinova EK, Kristensen VN, Lacey JV, Lambrechts D, Launer LJ, Lind PA, Lindblom A, Magnusson PKE, Mannermaa A, McCarthy MI, Meitinger T, Menni C, Michailidou K, Millwood IY, Milne RL, Montgomery GW, Nevanlinna H, Nolte IM, Nyholt DR, Obi N, O'Brien KM, Offit K, Oldehinkel AJ, Ostrowski SR, Palotie A, Pedersen OB, Peters A, Pianigiani G, Plaseska-Karanfilska D, Pouta A, Pozarickij A, Radice P, Rennert G, Rosendaal FR, Ruggiero D, Saloustros E, Sandler DP, Schipf S, Schmidt CO, Schmidt MK, Small K, Spedicati B, Stampfer M, Stone J, Tamimi RM, Teras LR, Tikkanen E, Turman C, Vachon CM, Wang Q, Winqvist R, Wolk A, Zemel BS, Zheng W, van Dijk KW, Alizadeh BZ, Bandinelli S, Boerwinkle E, Boomsma DI, Ciullo M, Chenevix-Trench G, Cucca F, Esko T, Gieger C, Grant SFA, Gudnason V, Hayward C, Kolčić I, Kraft P, Lawlor DA, Martin NG, Nøhr EA, Pedersen NL, Pennell CE, Ridker PM, Robino A, Snieder H, Sovio U, Spector TD, Stöckl D, Sudlow C, Timpson NJ, Toniolo D, Uitterlinden A, Ulivi S, Völzke H, Wareham NJ, Widen E, Wilson JF, Pharoah PDP, Li L, Easton DF, Njølstad PR, Sulem P, Murabito JM, Murray A, Manousaki D, Juul A, Erikstrup C, Stefansson K, Horikoshi M, Chen Z, Farooqi IS, Pitteloud N, Johansson S, Day FR, Perry JRB, and Ong KK
Published: 2024
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37. Causal relevance of different blood pressure traits on risk of cardiovascular diseases: GWAS and Mendelian randomisation in 100,000 Chinese adults.

Author: Pozarickij A, Gan W, Lin K, Clarke R, Fairhurst-Hunter Z, Koido M, Kanai M, Okada Y, Kamatani Y, Bennett D, Du H, Chen Y, Yang L, Avery D, Guo Y, Yu M, Yu C, Schmidt Valle D, Lv J, Chen J, Peto R, Collins R, Li L, Chen Z, Millwood IY, and Walters RG
Subjects: Adult, Aged, Female, Humans, Male, Middle Aged, China epidemiology, Genetic Predisposition to Disease, Genome-Wide Association Study, Hypertension genetics, Hypertension epidemiology, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide, Risk Factors, Blood Pressure genetics, Cardiovascular Diseases genetics, Cardiovascular Diseases epidemiology, East Asian People genetics
Abstract: Elevated blood pressure (BP) is major risk factor for cardiovascular diseases (CVD). Genome-wide association studies (GWAS) conducted predominantly in populations of European ancestry have identified >2,000 BP-associated loci, but other ancestries have been less well-studied. We conducted GWAS of systolic, diastolic, pulse, and mean arterial BP in 100,453 Chinese adults. We identified 128 non-overlapping loci associated with one or more BP traits, including 74 newly-reported associations. Despite strong genetic correlations between populations, we identified appreciably higher heritability and larger variant effect sizes in Chinese compared with European or Japanese ancestry populations. Using instruments derived from these GWAS, multivariable Mendelian randomisation demonstrated that BP traits contribute differently to the causal associations of BP with CVD. In particular, only pulse pressure was independently causally associated with carotid plaque. These findings reinforce the need for studies in diverse populations to understand the genetic determinants of BP traits and their roles in disease risk., (© 2024. The Author(s).)
Published: 2024
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38. Understanding the genetic complexity of puberty timing across the allele frequency spectrum.

Author: Kentistou KA, Kaisinger LR, Stankovic S, Vaudel M, Mendes de Oliveira E, Messina A, Walters RG, Liu X, Busch AS, Helgason H, Thompson DJ, Santoni F, Petricek KM, Zouaghi Y, Huang-Doran I, Gudbjartsson DF, Bratland E, Lin K, Gardner EJ, Zhao Y, Jia RY, Terao C, Riggan MJ, Bolla MK, Yazdanpanah M, Yazdanpanah N, Bradfield JP, Broer L, Campbell A, Chasman DI, Cousminer DL, Franceschini N, Franke LH, Girotto G, He C, Järvelin MR, Joshi PK, Kamatani Y, Karlsson R, Luan J, Lunetta KL, Mägi R, Mangino M, Medland SE, Meisinger C, Noordam R, Nutile T, Concas MP, Polašek O, Porcu E, Ring SM, Sala C, Smith AV, Tanaka T, van der Most PJ, Vitart V, Wang CA, Willemsen G, Zygmunt M, Ahearn TU, Andrulis IL, Anton-Culver H, Antoniou AC, Auer PL, Barnes CLK, Beckmann MW, Berrington de Gonzalez A, Bogdanova NV, Bojesen SE, Brenner H, Buring JE, Canzian F, Chang-Claude J, Couch FJ, Cox A, Crisponi L, Czene K, Daly MB, Demerath EW, Dennis J, Devilee P, De Vivo I, Dörk T, Dunning AM, Dwek M, Eriksson JG, Fasching PA, Fernandez-Rhodes L, Ferreli L, Fletcher O, Gago-Dominguez M, García-Closas M, García-Sáenz JA, González-Neira A, Grallert H, Guénel P, Haiman CA, Hall P, Hamann U, Hakonarson H, Hart RJ, Hickey M, Hooning MJ, Hoppe R, Hopper JL, Hottenga JJ, Hu FB, Huebner H, Hunter DJ, Jernström H, John EM, Karasik D, Khusnutdinova EK, Kristensen VN, Lacey JV, Lambrechts D, Launer LJ, Lind PA, Lindblom A, Magnusson PKE, Mannermaa A, McCarthy MI, Meitinger T, Menni C, Michailidou K, Millwood IY, Milne RL, Montgomery GW, Nevanlinna H, Nolte IM, Nyholt DR, Obi N, O'Brien KM, Offit K, Oldehinkel AJ, Ostrowski SR, Palotie A, Pedersen OB, Peters A, Pianigiani G, Plaseska-Karanfilska D, Pouta A, Pozarickij A, Radice P, Rennert G, Rosendaal FR, Ruggiero D, Saloustros E, Sandler DP, Schipf S, Schmidt CO, Schmidt MK, Small K, Spedicati B, Stampfer M, Stone J, Tamimi RM, Teras LR, Tikkanen E, Turman C, Vachon CM, Wang Q, Winqvist R, Wolk A, Zemel BS, Zheng W, van Dijk KW, Alizadeh BZ, Bandinelli S, Boerwinkle E, Boomsma DI, Ciullo M, Chenevix-Trench G, Cucca F, Esko T, Gieger C, Grant SFA, Gudnason V, Hayward C, Kolčić I, Kraft P, Lawlor DA, Martin NG, Nøhr EA, Pedersen NL, Pennell CE, Ridker PM, Robino A, Snieder H, Sovio U, Spector TD, Stöckl D, Sudlow C, Timpson NJ, Toniolo D, Uitterlinden A, Ulivi S, Völzke H, Wareham NJ, Widen E, Wilson JF, Pharoah PDP, Li L, Easton DF, Njølstad PR, Sulem P, Murabito JM, Murray A, Manousaki D, Juul A, Erikstrup C, Stefansson K, Horikoshi M, Chen Z, Farooqi IS, Pitteloud N, Johansson S, Day FR, Perry JRB, and Ong KK
Subjects: Humans, Female, Animals, Multifactorial Inheritance genetics, Mice, Genome-Wide Association Study, Adolescent, Puberty, Precocious genetics, Polymorphism, Single Nucleotide, Receptors, G-Protein-Coupled genetics, Puberty, Delayed genetics, Child, Menarche genetics, Puberty genetics, Gene Frequency
Abstract: Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease., (© 2024. The Author(s).)
Published: 2024
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39. Prospective evaluation of the relevance of Epstein-Barr virus antibodies for early detection of nasopharyngeal carcinoma in Chinese adults.

Author: Yang L, Kartsonaki C, Simon J, Yao P, Guo Y, Lv J, Walters RG, Chen Y, Fry H, Avery D, Yu C, Jin J, Mentzer AJ, Allen N, Butt J, Hill M, Li L, Millwood IY, Waterboer T, and Chen Z
Subjects: Adult, Aged, Female, Humans, Male, Middle Aged, Case-Control Studies, China epidemiology, East Asian People, Herpesvirus 4, Human immunology, Immunoglobulin A blood, Immunoglobulin G blood, Proportional Hazards Models, Prospective Studies, Antibodies, Viral blood, Early Detection of Cancer methods, Epstein-Barr Virus Infections blood, Epstein-Barr Virus Infections epidemiology, Nasopharyngeal Carcinoma blood, Nasopharyngeal Carcinoma epidemiology, Nasopharyngeal Carcinoma virology, Nasopharyngeal Neoplasms blood, Nasopharyngeal Neoplasms epidemiology, Nasopharyngeal Neoplasms virology
Abstract: Background: Epstein-Barr virus (EBV) is a major cause of nasopharyngeal carcinoma (NPC) and measurement of different EBV antibodies in blood may improve early detection of NPC. Prospective studies can help assess the roles of different EBV antibodies in predicting NPC risk over time., Methods: A case-cohort study within the prospective China Kadoorie Biobank of 512 715 adults from 10 (including two NPC endemic) areas included 295 incident NPC cases and 745 subcohort participants. A multiplex serology assay was used to quantify IgA and IgG antibodies against 16 EBV antigens in stored baseline plasma samples. Cox regression was used to estimate adjusted hazard ratios (HRs) for NPC and C-statistics to assess the discriminatory ability of EBV-markers, including two previously identified EBV-marker combinations, for predicting NPC., Results: Sero-positivity for 15 out of 16 EBV-markers was significantly associated with higher NPC risk. Both IgA and IgG antibodies against the same three EBV-markers showed the most extreme HRs, i.e. BGLF2 (IgA: 124.2 (95% CI: 63.3-243.9); IgG: 8.6 (5.5-13.5); LF2: [67.8 (30.0-153.1), 10.9 (7.2-16.4)]); and BFRF1: 26.1 (10.1-67.5), 6.1 (2.7-13.6). Use of a two-marker (i.e. LF2/BGLF2 IgG) and a four-marker (i.e. LF2/BGLF2 IgG and LF2/EA-D IgA) combinations yielded C-statistics of 0.85 and 0.84, respectively, which persisted for at least 5 years after sample collection in both endemic and non-endemic areas., Conclusions: In Chinese adults, plasma EBV markers strongly predict NPC occurrence many years before clinical diagnosis. LF2 and BGLF2 IgG could identify NPC high-risk individuals to improve NPC early detection in community and clinical settings., (© The Author(s) 2024. Published by Oxford University Press on behalf of the International Epidemiological Association.)
Published: 2024
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40. PCSK9 genetic variants and risk of vascular and non-vascular diseases in Chinese and UK populations.

Author: Holmes MV, Kartsonaki C, Boxall R, Lin K, Reeve N, Yu C, Lv J, Bennett DA, Hill MR, Yang L, Chen Y, Du H, Turnbull I, Collins R, Clarke RJ, Tobin MD, Li L, Millwood IY, Chen Z, and Walters RG
Subjects: Humans, China epidemiology, Male, Female, Middle Aged, Aged, United Kingdom epidemiology, Risk Assessment, Prospective Studies, Risk Factors, Cholesterol, LDL blood, Cardiovascular Diseases genetics, Cardiovascular Diseases epidemiology, Biomarkers blood, Phenotype, East Asian People, Proprotein Convertase 9 genetics, Genetic Predisposition to Disease
Abstract: Aims: Lowering low-density lipoprotein cholesterol (LDL-C) through PCSK9 inhibition represents a new therapeutic approach to preventing and treating cardiovascular disease (CVD). Phenome-wide analyses of PCSK9 genetic variants in large biobanks can help to identify unexpected effects of PCSK9 inhibition., Methods and Results: In the prospective China Kadoorie Biobank, we constructed a genetic score using three variants at the PCSK9 locus associated with directly measured LDL-C [PCSK9 genetic score (PCSK9-GS)]. Logistic regression gave estimated odds ratios (ORs) for PCSK9-GS associations with CVD and non-CVD outcomes, scaled to 1 SD lower LDL-C. PCSK9-GS was associated with lower risks of carotid plaque [n = 8340 cases; OR = 0.61 (95% confidence interval: 0.45-0.83); P = 0.0015], major occlusive vascular events [n = 15 752; 0.80 (0.67-0.95); P = 0.011], and ischaemic stroke [n = 11 467; 0.80 (0.66-0.98); P = 0.029]. However, PCSK9-GS was also associated with higher risk of hospitalization with chronic obstructive pulmonary disease [COPD: n = 6836; 1.38 (1.08-1.76); P = 0.0089] and with even higher risk of fatal exacerbations amongst individuals with pre-existing COPD [n = 730; 3.61 (1.71-7.60); P = 7.3 × 10-4]. We also replicated associations for a PCSK9 variant, reported in UK Biobank, with increased risks of acute upper respiratory tract infection (URTI) [pooled OR after meta-analysis of 1.87 (1.38-2.54); P = 5.4 × 10-5] and self-reported asthma [pooled OR of 1.17 (1.04-1.30); P = 0.0071]. There was no association of a polygenic LDL-C score with COPD hospitalization, COPD exacerbation, or URTI., Conclusion: The LDL-C-lowering PCSK9 genetic variants are associated with lower risk of subclinical and clinical atherosclerotic vascular disease but higher risks of respiratory diseases. Pharmacovigilance studies may be required to monitor patients treated with therapeutic PCSK9 inhibitors for exacerbations of respiratory diseases or respiratory tract infections., Lay Summary: Genetic analyses of over 100 000 participants of the China Kadoorie Biobank, mimicking the effect of new drugs intended to reduce cholesterol by targeting the PCSK9 protein, have identified potential severe effects of lower PCSK9 activity in patients with existing respiratory disease.PCSK9 genetic variants that are associated with lower cholesterol and reduced rates of cardiovascular disease are also associated with increased risk of a range of respiratory diseases, including asthma, upper respiratory tract infections, and hospitalization with chronic obstructive pulmonary disease (COPD).These genetic variants are not associated with whether or not individuals have COPD; instead, they are specifically associated with an increase in the chance of those who already have COPD being hospitalized and even dying, suggesting that careful monitoring of such patients should be considered during development of and treatment with anti-PCSK9 medication., Competing Interests: Conflict of interest: The Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford (CTSU) is co-ordinating a PCSK9 phase III cardiovascular outcome trial (ORION 4). M.V.H. has collaborated with Boehringer Ingelheim in research, and in accordance with the policy of CTSU did not accept any personal payment. M.V.H. was at the University of Oxford when this work was conducted and is presently employed by 23andMe and holds stock in 23andMe., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)
Published: 2024
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41. Helicobacter pylori Treatment and Gastric Cancer Risk Among Individuals With High Genetic Risk for Gastric Cancer.

Author: Xu HM, Han Y, Liu ZC, Yin ZY, Wang MY, Yu C, Ma JL, Sun D, Liu WD, Zhang Y, Zhou T, Zhang JY, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Chen Z, You WC, Li L, Pan KF, Lv J, and Li WQ
Subjects: Humans, Female, Male, Middle Aged, China epidemiology, Genome-Wide Association Study, Case-Control Studies, Adult, Risk Factors, Dietary Supplements, Cohort Studies, Aged, Anti-Bacterial Agents therapeutic use, Stomach Neoplasms genetics, Stomach Neoplasms epidemiology, Helicobacter pylori, Helicobacter Infections drug therapy, Helicobacter Infections complications, Genetic Predisposition to Disease
Abstract: Importance: Helicobacter pylori treatment and nutrition supplementation may protect against gastric cancer (GC), but whether the beneficial effects only apply to potential genetic subgroups and whether high genetic risk may be counteracted by these chemoprevention strategies remains unknown., Objective: To examine genetic variants associated with the progression of gastric lesions and GC risk and to assess the benefits of H pylori treatment and nutrition supplementation by levels of genetic risk., Design, Setting, and Participants: This cohort study used follow-up data of the Shandong Intervention Trial (SIT, 1989-2022) and China Kadoorie Biobank (CKB, 2004-2018) in China. Based on the SIT, a longitudinal genome-wide association study was conducted to identify genetic variants for gastric lesion progression. Significant variants were examined for incident GC in a randomly sampled set of CKB participants (set 1). Polygenic risk scores (PRSs) combining independent variants were assessed for GC risk in the remaining CKB participants (set 2) and in an independent case-control study in Linqu., Exposures: H pylori treatment and nutrition supplementation., Main Outcomes and Measures: Primary outcomes were the progression of gastric lesions (in SIT only) and the risk of GC. The associations of H pylori treatment and nutrition supplementation with GC were evaluated among SIT participants with different levels of genetic risk., Results: Our analyses included 2816 participants (mean [SD] age, 46.95 [9.12] years; 1429 [50.75%] women) in SIT and 100 228 participants (mean [SD] age, 53.69 [11.00] years; 57 357 [57.23%] women) in CKB, with 147 GC cases in SIT and 825 GC cases in CKB identified during follow-up. A PRS integrating 12 genomic loci associated with gastric lesion progression and incident GC risk was derived, which was associated with GC risk in CKB (highest vs lowest decile of PRS: hazard ratio [HR], 2.54; 95% CI, 1.80-3.57) and further validated in the analysis of 702 case participants and 692 control participants (mean [SD] age, 54.54 [7.66] years; 527 [37.80%] women; odds ratio, 1.83; 95% CI, 1.11-3.05). H pylori treatment was associated with reduced GC risk only for individuals with high genetic risk (top 25% of PRS: HR, 0.45; 95% CI, 0.25-0.82) but not for those with low genetic risk (HR, 0.81; 95% CI, 0.50-1.34; P for interaction = .03). Such effect modification was not found for vitamin (P for interaction = .93) or garlic (P for interaction = .41) supplementation., Conclusions and Relevance: The findings of this cohort study indicate that a high genetic risk of GC may be counteracted by H pylori treatment, suggesting primary prevention could be tailored to genetic risk for more effective prevention.
Published: 2024
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42. Infectious pathogens and risk of esophageal, gastric and duodenal cancers and ulcers in China: A case-cohort study.

Author: Kartsonaki C, Yao P, Butt J, Jeske R, de Martel C, Plummer M, Sun D, Clark S, Walters RG, Chen Y, Lv J, Yu C, Hill M, Peto R, Li L, Waterboer T, Chen Z, Millwood IY, and Yang L
Subjects: Adult, Humans, Cohort Studies, Ulcer complications, Seroepidemiologic Studies, Herpesvirus 4, Human, Cardia, Duodenal Ulcer epidemiology, Duodenal Ulcer complications, Duodenal Neoplasms, Epstein-Barr Virus Infections complications, Gastrointestinal Neoplasms, Hepatitis C complications, Hepatitis C epidemiology, Helicobacter Infections complications, Helicobacter Infections epidemiology, Helicobacter pylori
Abstract: Infection by certain pathogens is associated with cancer development. We conducted a case-cohort study of ~2500 incident cases of esophageal, gastric and duodenal cancer, and gastric and duodenal ulcer and a randomly selected subcohort of ~2000 individuals within the China Kadoorie Biobank study of >0.5 million adults. We used a bead-based multiplex serology assay to measure antibodies against 19 pathogens (total 43 antigens) in baseline plasma samples. Associations between pathogens and antigen-specific antibodies with risks of site-specific cancers and ulcers were assessed using Cox regression fitted using the Prentice pseudo-partial likelihood. Seroprevalence varied for different pathogens, from 0.7% for Hepatitis C virus (HCV) to 99.8% for Epstein-Barr virus (EBV) in the subcohort. Compared to participants seronegative for the corresponding pathogen, Helicobacter pylori seropositivity was associated with a higher risk of non-cardia (adjusted hazard ratio [HR] 2.73 [95% CI: 2.09-3.58]) and cardia (1.67 [1.18-2.38]) gastric cancer and duodenal ulcer (2.71 [1.79-4.08]). HCV was associated with a higher risk of duodenal cancer (6.23 [1.52-25.62]) and Hepatitis B virus was associated with higher risk of duodenal ulcer (1.46 [1.04-2.05]). There were some associations of antibodies again some herpesviruses and human papillomaviruses with risks of gastrointestinal cancers and ulcers but these should be interpreted with caution. This first study of multiple pathogens with risk of gastrointestinal cancers and ulcers demonstrated that several pathogens are associated with risks of gastrointestinal cancers and ulcers. This will inform future investigations into the role of infection in the etiology of these diseases., (© 2023 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)
Published: 2024
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43. A genome-wide association study based on the China Kadoorie Biobank identifies genetic associations between snoring and cardiometabolic traits.

Author: Zhu Y, Zhuang Z, Lv J, Sun D, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Liu F, Stevens R, Chen J, Chen Z, Li L, and Yu C
Subjects: Humans, Genome-Wide Association Study, Biological Specimen Banks, Blood Pressure genetics, Aldehyde Dehydrogenase, Mitochondrial genetics, Snoring genetics, Snoring epidemiology, Hypertension epidemiology, Hypertension genetics
Abstract: Despite the high prevalence of snoring in Asia, little is known about the genetic etiology of snoring and its causal relationships with cardiometabolic traits. Based on 100,626 Chinese individuals, a genome-wide association study on snoring was conducted. Four novel loci were identified for snoring traits mapped on SLC25A21, the intergenic region of WDR11 and FGFR, NAA25, ALDH2, and VTI1A, respectively. The novel loci highlighted the roles of structural abnormality of the upper airway and craniofacial region and dysfunction of metabolic and transport systems in the development of snoring. In the two-sample bi-directional Mendelian randomization analysis, higher body mass index, weight, and elevated blood pressure were causal for snoring, and a reverse causal effect was observed between snoring and diastolic blood pressure. Altogether, our results revealed the possible etiology of snoring in China and indicated that managing cardiometabolic health was essential to snoring prevention, and hypertension should be considered among snorers., (© 2024. The Author(s).)
Published: 2024
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44. Development and evaluation of a polygenic risk score for lung cancer in never-smoking women: A large-scale prospective Chinese cohort study.

Author: Wei X, Sun D, Gao J, Zhang J, Zhu M, Yu C, Ma Z, Fu Y, Ji C, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Jin G, Chen Z, Hu Z, Li L, Shen H, Lv J, and Ma H
Subjects: Humans, Female, Genetic Risk Score, Genetic Predisposition to Disease, Cohort Studies, Prospective Studies, Genome-Wide Association Study, Risk Factors, Smoking genetics, Smoking epidemiology, China, Lung Neoplasms epidemiology, Lung Neoplasms genetics
Abstract: The proportion of lung cancer in never smokers is rising, especially among Asian women, but there is no effective early detection tool. Here, we developed a polygenic risk score (PRS), which may help to identify the population with higher risk of lung cancer in never-smoking women. We first performed a large GWAS meta-analysis (8595 cases and 8275 controls) to systematically identify the susceptibility loci for lung cancer in never-smoking Asian women and then generated a PRS using GWAS datasets. Furthermore, we evaluated the utility and effectiveness of PRS in an independent Chinese prospective cohort comprising 55 266 individuals. The GWAS meta-analysis identified eight known loci and a novel locus (5q11.2) at the genome-wide statistical significance level of P < 5 × 10 -8 . Based on the summary statistics of GWAS, we derived a polygenic risk score including 21 variants (PRS-21) for lung cancer in never-smoking women. Furthermore, PRS-21 had a hazard ratio (HR) per SD of 1.29 (95% CI = 1.18-1.41) in the prospective cohort. Compared with participants who had a low genetic risk, those with an intermediate (HR = 1.32, 95% CI: 1.00-1.72) and high (HR = 2.09, 95% CI: 1.56-2.80) genetic risk had a significantly higher risk of incident lung cancer. The addition of PRS-21 to the conventional risk model yielded a modest significant improvement in AUC (0.697 to 0.711) and net reclassification improvement (24.2%). The GWAS-derived PRS-21 significantly improves the risk stratification and prediction accuracy for incident lung cancer in never-smoking Asian women, demonstrating the potential for identification of high-risk individuals and early screening., (© 2023 UICC.)
Published: 2024
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45. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Author: Suzuki K, Hatzikotoulas K, Southam L, Taylor HJ, Yin X, Lorenz KM, Mandla R, Huerta-Chagoya A, Melloni GEM, Kanoni S, Rayner NW, Bocher O, Arruda AL, Sonehara K, Namba S, Lee SSK, Preuss MH, Petty LE, Schroeder P, Vanderwerff B, Kals M, Bragg F, Lin K, Guo X, Zhang W, Yao J, Kim YJ, Graff M, Takeuchi F, Nano J, Lamri A, Nakatochi M, Moon S, Scott RA, Cook JP, Lee JJ, Pan I, Taliun D, Parra EJ, Chai JF, Bielak LF, Tabara Y, Hai Y, Thorleifsson G, Grarup N, Sofer T, Wuttke M, Sarnowski C, Gieger C, Nousome D, Trompet S, Kwak SH, Long J, Sun M, Tong L, Chen WM, Nongmaithem SS, Noordam R, Lim VJY, Tam CHT, Joo YY, Chen CH, Raffield LM, Prins BP, Nicolas A, Yanek LR, Chen G, Brody JA, Kabagambe E, An P, Xiang AH, Choi HS, Cade BE, Tan J, Broadaway KA, Williamson A, Kamali Z, Cui J, Thangam M, Adair LS, Adeyemo A, Aguilar-Salinas CA, Ahluwalia TS, Anand SS, Bertoni A, Bork-Jensen J, Brandslund I, Buchanan TA, Burant CF, Butterworth AS, Canouil M, Chan JCN, Chang LC, Chee ML, Chen J, Chen SH, Chen YT, Chen Z, Chuang LM, Cushman M, Danesh J, Das SK, de Silva HJ, Dedoussis G, Dimitrov L, Doumatey AP, Du S, Duan Q, Eckardt KU, Emery LS, Evans DS, Evans MK, Fischer K, Floyd JS, Ford I, Franco OH, Frayling TM, Freedman BI, Genter P, Gerstein HC, Giedraitis V, González-Villalpando C, González-Villalpando ME, Gordon-Larsen P, Gross M, Guare LA, Hackinger S, Hakaste L, Han S, Hattersley AT, Herder C, Horikoshi M, Howard AG, Hsueh W, Huang M, Huang W, Hung YJ, Hwang MY, Hwu CM, Ichihara S, Ikram MA, Ingelsson M, Islam MT, Isono M, Jang HM, Jasmine F, Jiang G, Jonas JB, Jørgensen T, Kamanu FK, Kandeel FR, Kasturiratne A, Katsuya T, Kaur V, Kawaguchi T, Keaton JM, Kho AN, Khor CC, Kibriya MG, Kim DH, Kronenberg F, Kuusisto J, Läll K, Lange LA, Lee KM, Lee MS, Lee NR, Leong A, Li L, Li Y, Li-Gao R, Ligthart S, Lindgren CM, Linneberg A, Liu CT, Liu J, Locke AE, Louie T, Luan J, Luk AO, Luo X, Lv J, Lynch JA, Lyssenko V, Maeda S, Mamakou V, Mansuri SR, Matsuda K, Meitinger T, Melander O, Metspalu A, Mo H, Morris AD, Moura FA, Nadler JL, Nalls MA, Nayak U, Ntalla I, Okada Y, Orozco L, Patel SR, Patil S, Pei P, Pereira MA, Peters A, Pirie FJ, Polikowsky HG, Porneala B, Prasad G, Rasmussen-Torvik LJ, Reiner AP, Roden M, Rohde R, Roll K, Sabanayagam C, Sandow K, Sankareswaran A, Sattar N, Schönherr S, Shahriar M, Shen B, Shi J, Shin DM, Shojima N, Smith JA, So WY, Stančáková A, Steinthorsdottir V, Stilp AM, Strauch K, Taylor KD, Thorand B, Thorsteinsdottir U, Tomlinson B, Tran TC, Tsai FJ, Tuomilehto J, Tusie-Luna T, Udler MS, Valladares-Salgado A, van Dam RM, van Klinken JB, Varma R, Wacher-Rodarte N, Wheeler E, Wickremasinghe AR, van Dijk KW, Witte DR, Yajnik CS, Yamamoto K, Yamamoto K, Yoon K, Yu C, Yuan JM, Yusuf S, Zawistowski M, Zhang L, Zheng W, Raffel LJ, Igase M, Ipp E, Redline S, Cho YS, Lind L, Province MA, Fornage M, Hanis CL, Ingelsson E, Zonderman AB, Psaty BM, Wang YX, Rotimi CN, Becker DM, Matsuda F, Liu Y, Yokota M, Kardia SLR, Peyser PA, Pankow JS, Engert JC, Bonnefond A, Froguel P, Wilson JG, Sheu WHH, Wu JY, Hayes MG, Ma RCW, Wong TY, Mook-Kanamori DO, Tuomi T, Chandak GR, Collins FS, Bharadwaj D, Paré G, Sale MM, Ahsan H, Motala AA, Shu XO, Park KS, Jukema JW, Cruz M, Chen YI, Rich SS, McKean-Cowdin R, Grallert H, Cheng CY, Ghanbari M, Tai ES, Dupuis J, Kato N, Laakso M, Köttgen A, Koh WP, Bowden DW, Palmer CNA, Kooner JS, Kooperberg C, Liu S, North KE, Saleheen D, Hansen T, Pedersen O, Wareham NJ, Lee J, Kim BJ, Millwood IY, Walters RG, Stefansson K, Ahlqvist E, Goodarzi MO, Mohlke KL, Langenberg C, Haiman CA, Loos RJF, Florez JC, Rader DJ, Ritchie MD, Zöllner S, Mägi R, Marston NA, Ruff CT, van Heel DA, Finer S, Denny JC, Yamauchi T, Kadowaki T, Chambers JC, Ng MCY, Sim X, Below JE, Tsao PS, Chang KM, McCarthy MI, Meigs JB, Mahajan A, Spracklen CN, Mercader JM, Boehnke M, Rotter JI, Vujkovic M, Voight BF, Morris AP, and Zeggini E
Subjects: Humans, Adipocytes metabolism, Chromatin genetics, Chromatin metabolism, Coronary Artery Disease complications, Coronary Artery Disease genetics, Diabetic Nephropathies complications, Diabetic Nephropathies genetics, Endothelial Cells metabolism, Enteroendocrine Cells, Epigenomics, Islets of Langerhans metabolism, Multifactorial Inheritance genetics, Peripheral Arterial Disease complications, Peripheral Arterial Disease genetics, Single-Cell Analysis, Diabetes Mellitus, Type 2 classification, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 genetics, Diabetes Mellitus, Type 2 pathology, Diabetes Mellitus, Type 2 physiopathology, Disease Progression, Genetic Predisposition to Disease genetics, Genome-Wide Association Study
Abstract: Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes 1,2 and molecular mechanisms that are often specific to cell type 3,4 . Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10 -8 ) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores 5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care., (© 2024. The Author(s).)
Published: 2024
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46. Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference.

Author: Meng X, Navoly G, Giannakopoulou O, Levey DF, Koller D, Pathak GA, Koen N, Lin K, Adams MJ, Rentería ME, Feng Y, Gaziano JM, Stein DJ, Zar HJ, Campbell ML, van Heel DA, Trivedi B, Finer S, McQuillin A, Bass N, Chundru VK, Martin HC, Huang QQ, Valkovskaya M, Chu CY, Kanjira S, Kuo PH, Chen HC, Tsai SJ, Liu YL, Kendler KS, Peterson RE, Cai N, Fang Y, Sen S, Scott LJ, Burmeister M, Loos RJF, Preuss MH, Actkins KV, Davis LK, Uddin M, Wani AH, Wildman DE, Aiello AE, Ursano RJ, Kessler RC, Kanai M, Okada Y, Sakaue S, Rabinowitz JA, Maher BS, Uhl G, Eaton W, Cruz-Fuentes CS, Martinez-Levy GA, Campos AI, Millwood IY, Chen Z, Li L, Wassertheil-Smoller S, Jiang Y, Tian C, Martin NG, Mitchell BL, Byrne EM, Awasthi S, Coleman JRI, Ripke S, Sofer T, Walters RG, McIntosh AM, Polimanti R, Dunn EC, Stein MB, Gelernter J, Lewis CM, and Kuchenbaecker K
Subjects: Humans, Genetic Predisposition to Disease, Depression, Chromosome Mapping, Polymorphism, Single Nucleotide genetics, Genome-Wide Association Study, Depressive Disorder, Major genetics
Abstract: Most genome-wide association studies (GWAS) of major depression (MD) have been conducted in samples of European ancestry. Here we report a multi-ancestry GWAS of MD, adding data from 21 cohorts with 88,316 MD cases and 902,757 controls to previously reported data. This analysis used a range of measures to define MD and included samples of African (36% of effective sample size), East Asian (26%) and South Asian (6%) ancestry and Hispanic/Latin American participants (32%). The multi-ancestry GWAS identified 53 significantly associated novel loci. For loci from GWAS in European ancestry samples, fewer than expected were transferable to other ancestry groups. Fine mapping benefited from additional sample diversity. A transcriptome-wide association study identified 205 significantly associated novel genes. These findings suggest that, for MD, increasing ancestral and global diversity in genetic studies may be particularly important to ensure discovery of core genes and inform about transferability of findings., (© 2024. The Author(s).)
Published: 2024
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47. Associations of diabetes, circulating protein biomarkers, and risk of pancreatic cancer.

Author: Pang Y, Lv J, Wu T, Yu C, Guo Y, Chen Y, Yang L, Millwood IY, Walters RG, Yang X, Stevens R, Clarke R, Chen J, Li L, Chen Z, and Kartsonaki C
Subjects: Humans, Female, Middle Aged, Male, Risk Factors, Interleukin-10 genetics, Interleukin-6 genetics, Insulin, Biomarkers, Diabetes Mellitus, Type 2, Insulin Resistance, Pancreatic Neoplasms genetics
Abstract: Background: Type 2 diabetes (T2D) is associated with higher risk of pancreatic cancer (PC), but the underlying mechanisms are not fully understood., Methods: We conducted a case-subcohort study involving 610 PC cases and 623 subcohort participants with 92 protein biomarkers measured in baseline plasma samples. Genetically-instrumented T2D was derived using 86 single-nucleotide polymorphisms (SNPs), including insulin resistance (IR) SNPs., Results: In observational analyses of 623 subcohort participants (mean age, 52 years; 61% women), T2D was positively associated with 13 proteins (SD difference: IL6: 0.52 [0.23-0.81]; IL10: 0.41 [0.12-0.70]), of which 8 were nominally associated with incident PC. The 8 proteins potentially mediated 36.9% (18.7-75.0%) of the association between T2D and PC. In MR, no associations were observed for genetically-determined T2D with proteins, but there were positive associations of genetically-determined IR with IL6 and IL10 (SD difference: 1.23 [0.05-2.41] and 1.28 [0.31-2.24]). In two-sample MR, fasting insulin was associated with both IL6 and PC, but no association was observed between IL6 and PC., Conclusions: Proteomics were likely to explain the association between T2D and PC, but were not causal mediators. Elevated fasting insulin driven by insulin resistance might explain the associations of T2D, proteomics, and PC., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)
Published: 2024
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48. Causal association between snoring and stroke: a Mendelian randomization study in a Chinese population.

Author: Zhu Y, Zhuang Z, Lv J, Sun D, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Wu X, Schmidt D, Avery D, Chen J, Chen Z, Li L, and Yu C
Abstract: Background: Previous observational studies established a positive relationship between snoring and stroke. We aimed to investigate the causal effect of snoring on stroke., Methods: Based on 82,339 unrelated individuals with qualified genotyping data of Asian descent from the China Kadoorie Biobank (CKB), we conducted a Mendelian randomization (MR) analysis of snoring and stroke. Genetic variants identified in the genome-wide association analysis (GWAS) of snoring in CKB and UK Biobank (UKB) were selected for constructing genetic risk scores (GRS). A two-stage method was applied to estimate the associations of the genetically predicted snoring with stroke and its subtypes. Besides, MR analysis among the non-obese group (body mass index, BMI <24.0 kg/m 2 ), as well as multivariable MR (MVMR), were performed to control for potential pleiotropy from BMI. In addition, the inverse-variance weighted (IVW) method was applied to estimate the causal association with genetic variants identified in CKB GWAS., Findings: Positive associations were found between snoring and total stroke, hemorrhagic stroke (HS), and ischemic stroke (IS). With GRS of CKB, the corresponding HRs (95% CIs) were 1.56 (1.15, 2.12), 1.50 (0.84, 2.69), 2.02 (1.36, 3.01), and the corresponding HRs (95% CIs) using GRS of UKB were 1.78 (1.30, 2.43), 1.94 (1.07, 3.52), and 1.74 (1.16, 2.61). The associations remained stable in the MR among the non-obese group, MVMR analysis, and MR analysis using the IVW method., Interpretation: This study suggests that, among Chinese adults, genetically predicted snoring could increase the risk of total stroke, IS, and HS, and the causal effect was independent of BMI., Funding: National Natural Science Foundation of China, Kadoorie Charitable Foundation Hong Kong, UK Wellcome Trust, National Key R&D Program of China, Chinese Ministry of Science and Technology., Competing Interests: The authors have no relevant financial or non-financial interests to disclose., (© 2023 The Author(s).)
Published: 2024
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49. MTHFR and risk of stroke and heart disease in a low-folate population: a prospective study of 156 000 Chinese adults.

Author: Bennett DA, Parish S, Millwood IY, Guo Y, Chen Y, Turnbull I, Yang L, Lv J, Yu C, Davey Smith G, Wang Y, Wang Y, Peto R, Collins R, Walters RG, Li L, Chen Z, and Clarke R
Subjects: Adult, Humans, Methylenetetrahydrofolate Reductase (NADPH2) genetics, Prospective Studies, Folic Acid, Genotype, Homocysteine genetics, Brain Ischemia, Stroke epidemiology, Stroke genetics, Coronary Artery Disease
Abstract: Background: The relevance of folic acid for stroke prevention in low-folate populations such as in China is uncertain. Genetic studies of the methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism, which increases plasma homocysteine (tHcy) levels, could clarify the causal relevance of elevated tHcy levels for stroke, ischaemic heart disease (IHD) and other diseases in populations without folic acid fortification., Methods: In the prospective China Kadoorie Biobank, 156 253 participants were genotyped for MTHFR and 12 240 developed a stroke during the 12-year follow-up. Logistic regression was used to estimate region-specific odds ratios (ORs) for total stroke and stroke types, IHD and other diseases comparing TT genotype for MTHFR C677T (two thymine alleles at position 677 of MTHFR C677T polymorphism) vs CC (two cytosine alleles) after adjustment for age and sex, and these were combined using inverse-variance weighting., Results: Overall, 21% of participants had TT genotypes, but this varied from 5% to 41% across the 10 study regions. Individuals with TT genotypes had 13% (adjusted OR 1.13, 95% CI 1.09-1.17) higher risks of any stroke [with a 2-fold stronger association with intracerebral haemorrhage (1.24, 1.17-1.32) than for ischaemic stroke (1.11, 1.07-1.15)] than the reference CC genotype. In contrast, MTHFR C677T was unrelated to risk of IHD or any other non-vascular diseases, including cancer, diabetes and chronic obstructive lung disease., Conclusions: In Chinese adults, the MTHFR C677T polymorphism was associated with higher risks of stroke. The findings warrant corroboration by further trials of folic acid and implementation of mandatory folic acid fortification programmes for stroke prevention in low-folate populations., (© The Author(s) 2023. Published by Oxford University Press on behalf of the International Epidemiological Association.)
Published: 2023
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50. Ethnic differences of genetic risk and smoking in lung cancer: two prospective cohort studies.

Author: Zhu M, Lv J, Huang Y, Ma H, Li N, Wei X, Ji M, Ma Z, Song C, Wang C, Dai J, Tan F, Guo Y, Walters R, Millwood IY, Hung RJ, Christiani DC, Yu C, Jin G, Chen Z, Wei Q, Amos CI, Hu Z, Li L, and Shen H
Subjects: Humans, Prospective Studies, Smoking adverse effects, Smoking genetics, Risk Factors, Tobacco Smoking, Genetic Risk Score, Lung Neoplasms epidemiology, Lung Neoplasms genetics
Abstract: Background: The role of genetic background underlying the disparity of relative risk of smoking and lung cancer between European populations and East Asians remains unclear., Methods: To assess the role of ethnic differences in genetic factors associated with smoking-related risk of lung cancer, we first constructed ethnic-specific polygenic risk scores (PRSs) to quantify individual genetic risk of lung cancer in Chinese and European populations. Then, we compared genetic risk and smoking as well as their interactions on lung cancer between two cohorts, including the China Kadoorie Biobank (CKB) and the UK Biobank (UKB). We also evaluated the absolute risk reduction over a 5-year period., Results: Differences in compositions and association effects were observed between the Chinese-specific PRSs and European-specific PRSs, especially for smoking-related loci. The PRSs were consistently associated with lung cancer risk, but stronger associations were observed in smokers of the UKB [hazard ratio (HR) 1.26 vs 1.15, P = 0.028]. A significant interaction between genetic risk and smoking on lung cancer was observed in the UKB (RERI, 11.39 (95% CI, 7.01-17.94)], but not in the CKB. Obvious higher absolute risk was observed in nonsmokers of the CKB, and a greater absolute risk reduction was found in the UKB (10.95 vs 7.12 per 1000 person-years, P <0.001) by comparing heavy smokers with nonsmokers, especially for those at high genetic risk., Conclusions: Ethnic differences in genetic factors and the high incidence of lung cancer in nonsmokers of East Asian ethnicity were involved in the disparity of smoking-related risk of lung cancer., (© The Author(s) 2023; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)
Published: 2023
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