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1,357 results on '"Chan, Juliana C. N."'

2. A polygenic risk score derived from common variants of monogenic diabetes genes is associated with young-onset type 2 diabetes and cardiovascular–kidney complications

Author

O, Chun-Kwan, Fan, Baoqi, Tsoi, Sandra T. F., Tam, Claudia H. T., Wan, Raymond, Lau, Eric S. H., Shi, Mai, Lim, Cadmon K. P., Yu, Gechang, Ho, Jane P. Y., Chow, Elaine Y. K., Kong, Alice P. S., Ozaki, Risa, So, Wing Yee, Ma, Ronald C. W., Luk, Andrea O. Y., and Chan, Juliana C. N.

Published
2024
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3. Type 2 diabetes pathway-specific polygenic risk scores elucidate heterogeneity in clinical presentation, disease progression and diabetic complications in 18,217 Chinese individuals with type 2 diabetes

Author

Yu, Gechang, Tam, Claudia H. T., Lim, Cadmon K. P., Shi, Mai, Lau, Eric S. H., Ozaki, Risa, Lee, Heung-man, Ng, Alex C. W., Hou, Yong, Fan, Baoqi, Huang, Chuiguo, Wu, Hongjiang, Yang, Aimin, Cheung, Hoi Man, Lee, Ka Fai, Siu, Shing Chung, Hui, Grace, Tsang, Chiu Chi, Lau, Kam Piu, Leung, Jenny Y. Y., Cheung, Elaine Y. N., Tsang, Man Wo, Kam, Grace, Lau, Ip Tim, Li, June K. Y., Yeung, Vincent T. F., Lau, Emmy, Lo, Stanley, Fung, Samuel, Cheng, Yuk Lun, Szeto, Cheuk Chun, Chow, Elaine, Kong, Alice P. S., Tam, Wing Hung, Luk, Andrea O. Y., Weedon, Michael N., So, Wing-yee, Chan, Juliana C. N., Oram, Richard A., and Ma, Ronald C. W.

Published
2024
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5. Integrated image-based deep learning and language models for primary diabetes care

Author

Li, Jiajia, Guan, Zhouyu, Wang, Jing, Cheung, Carol Y., Zheng, Yingfeng, Lim, Lee-Ling, Lim, Cynthia Ciwei, Ruamviboonsuk, Paisan, Raman, Rajiv, Corsino, Leonor, Echouffo-Tcheugui, Justin B., Luk, Andrea O. Y., Chen, Li Jia, Sun, Xiaodong, Hamzah, Haslina, Wu, Qiang, Wang, Xiangning, Liu, Ruhan, Wang, Ya Xing, Chen, Tingli, Zhang, Xiao, Yang, Xiaolong, Yin, Jun, Wan, Jing, Du, Wei, Quek, Ten Cheer, Goh, Jocelyn Hui Lin, Yang, Dawei, Hu, Xiaoyan, Nguyen, Truong X., Szeto, Simon K. H., Chotcomwongse, Peranut, Malek, Rachid, Normatova, Nargiza, Ibragimova, Nilufar, Srinivasan, Ramyaa, Zhong, Pingting, Huang, Wenyong, Deng, Chenxin, Ruan, Lei, Zhang, Cuntai, Zhang, Chenxi, Zhou, Yan, Wu, Chan, Dai, Rongping, Koh, Sky Wei Chee, Abdullah, Adina, Hee, Nicholas Ken Yoong, Tan, Hong Chang, Liew, Zhong Hong, Tien, Carolyn Shan-Yeu, Kao, Shih Ling, Lim, Amanda Yuan Ling, Mok, Shao Feng, Sun, Lina, Gu, Jing, Wu, Liang, Li, Tingyao, Cheng, Di, Wang, Zheyuan, Qin, Yiming, Dai, Ling, Meng, Ziyao, Shu, Jia, Lu, Yuwei, Jiang, Nan, Hu, Tingting, Huang, Shan, Huang, Gengyou, Yu, Shujie, Liu, Dan, Ma, Weizhi, Guo, Minyi, Guan, Xinping, Yang, Xiaokang, Bascaran, Covadonga, Cleland, Charles R., Bao, Yuqian, Ekinci, Elif I., Jenkins, Alicia, Chan, Juliana C. N., Bee, Yong Mong, Sivaprasad, Sobha, Shaw, Jonathan E., Simó, Rafael, Keane, Pearse A., Cheng, Ching-Yu, Tan, Gavin Siew Wei, Jia, Weiping, Tham, Yih-Chung, Li, Huating, Sheng, Bin, and Wong, Tien Yin

Published
2024
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9. Circulating metabolomic markers linking diabetic kidney disease and incident cardiovascular disease in type 2 diabetes: analyses from the Hong Kong Diabetes Biobank

Author

Jin, Qiao, Lau, Eric S. H., Luk, Andrea O., Tam, Claudia H. T., Ozaki, Risa, Lim, Cadmon K. P., Wu, Hongjiang, Chow, Elaine Y. K., Kong, Alice P. S., Lee, Heung Man, Fan, Baoqi, Ng, Alex C. W., Jiang, Guozhi, Lee, Ka Fai, Siu, Shing Chung, Hui, Grace, Tsang, Chiu Chi, Lau, Kam Piu, Leung, Jenny Y., Tsang, Man-wo, Cheung, Elaine Y. N., Kam, Grace, Lau, Ip Tim, Li, June K., Yeung, Vincent T. F., Lau, Emmy, Lo, Stanley, Fung, Samuel, Cheng, Yuk Lun, Chow, Chun Chung, Yu, Weichuan, Tsui, Stephen K. W., Tomlinson, Brian, Huang, Yu, Lan, Hui-yao, Szeto, Cheuk Chun, So, Wing Yee, Jenkins, Alicia J., Fung, Erik, Muilwijk, Mirthe, Blom, Marieke T., ‘t Hart, Leen M., Chan, Juliana C. N., and Ma, Ronald C. W.

Published
2024
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10. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Author

Suzuki, Ken, Hatzikotoulas, Konstantinos, Southam, Lorraine, Taylor, Henry J., Yin, Xianyong, Lorenz, Kim M., Mandla, Ravi, Huerta-Chagoya, Alicia, Melloni, Giorgio E. M., Kanoni, Stavroula, Rayner, Nigel W., Bocher, Ozvan, Arruda, Ana Luiza, Sonehara, Kyuto, Namba, Shinichi, Lee, Simon S. K., Preuss, Michael H., Petty, Lauren E., Schroeder, Philip, Vanderwerff, Brett, Kals, Mart, Bragg, Fiona, Lin, Kuang, Guo, Xiuqing, Zhang, Weihua, Yao, Jie, Kim, Young Jin, Graff, Mariaelisa, Takeuchi, Fumihiko, Nano, Jana, Lamri, Amel, Nakatochi, Masahiro, Moon, Sanghoon, Scott, Robert A., Cook, James P., Lee, Jung-Jin, Pan, Ian, Taliun, Daniel, Parra, Esteban J., Chai, Jin-Fang, Bielak, Lawrence F., Tabara, Yasuharu, Hai, Yang, Thorleifsson, Gudmar, Grarup, Niels, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloé, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Kwak, Soo-Heon, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Nongmaithem, Suraj S., Noordam, Raymond, Lim, Victor J. Y., Tam, Claudia H. T., Joo, Yoonjung Yoonie, Chen, Chien-Hsiun, Raffield, Laura M., Prins, Bram Peter, Nicolas, Aude, Yanek, Lisa R., Chen, Guanjie, Brody, Jennifer A., Kabagambe, Edmond, An, Ping, Xiang, Anny H., Choi, Hyeok Sun, Cade, Brian E., Tan, Jingyi, Broadaway, K. Alaine, Williamson, Alice, Kamali, Zoha, Cui, Jinrui, Thangam, Manonanthini, Adair, Linda S., Adeyemo, Adebowale, Aguilar-Salinas, Carlos A., Ahluwalia, Tarunveer S., Anand, Sonia S., Bertoni, Alain, Bork-Jensen, Jette, Brandslund, Ivan, Buchanan, Thomas A., Burant, Charles F., Butterworth, Adam S., Canouil, Mickaël, Chan, Juliana C. N., Chang, Li-Ching, Chee, Miao-Li, Chen, Ji, Chen, Shyh-Huei, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, Cushman, Mary, Danesh, John, Das, Swapan K., de Silva, H. Janaka, Dedoussis, George, Dimitrov, Latchezar, Doumatey, Ayo P., Du, Shufa, Duan, Qing, Eckardt, Kai-Uwe, Emery, Leslie S., Evans, Daniel S., Evans, Michele K., Fischer, Krista, Floyd, James S., Ford, Ian, Franco, Oscar H., Frayling, Timothy M., Freedman, Barry I., Genter, Pauline, Gerstein, Hertzel C., Giedraitis, Vilmantas, González-Villalpando, Clicerio, González-Villalpando, Maria Elena, Gordon-Larsen, Penny, Gross, Myron, Guare, Lindsay A., Hackinger, Sophie, Hakaste, Liisa, Han, Sohee, Hattersley, Andrew T., Herder, Christian, Horikoshi, Momoko, Howard, Annie-Green, Hsueh, Willa, Huang, Mengna, Huang, Wei, Hung, Yi-Jen, Hwang, Mi Yeong, Hwu, Chii-Min, Ichihara, Sahoko, Ikram, Mohammad Arfan, Ingelsson, Martin, Islam, Md. Tariqul, Isono, Masato, Jang, Hye-Mi, Jasmine, Farzana, Jiang, Guozhi, Jonas, Jost B., Jørgensen, Torben, Kamanu, Frederick K., Kandeel, Fouad R., Kasturiratne, Anuradhani, Katsuya, Tomohiro, Kaur, Varinderpal, Kawaguchi, Takahisa, Keaton, Jacob M., Kho, Abel N., Khor, Chiea-Chuen, Kibriya, Muhammad G., Kim, Duk-Hwan, Kronenberg, Florian, Kuusisto, Johanna, Läll, Kristi, Lange, Leslie A., Lee, Kyung Min, Lee, Myung-Shik, Lee, Nanette R., Leong, Aaron, Li, Liming, Li, Yun, Li-Gao, Ruifang, Ligthart, Symen, Lindgren, Cecilia M., Linneberg, Allan, Liu, Ching-Ti, Liu, Jianjun, Locke, Adam E., Louie, Tin, Luan, Jian’an, Luk, Andrea O., Luo, Xi, Lv, Jun, Lynch, Julie A., Lyssenko, Valeriya, Maeda, Shiro, Mamakou, Vasiliki, Mansuri, Sohail Rafik, Matsuda, Koichi, Meitinger, Thomas, Melander, Olle, Metspalu, Andres, Mo, Huan, Morris, Andrew D., Moura, Filipe A., Nadler, Jerry L., Nalls, Michael A., Nayak, Uma, Ntalla, Ioanna, Okada, Yukinori, Orozco, Lorena, Patel, Sanjay R., Patil, Snehal, Pei, Pei, Pereira, Mark A., Peters, Annette, Pirie, Fraser J., Polikowsky, Hannah G., Porneala, Bianca, Prasad, Gauri, Rasmussen-Torvik, Laura J., Reiner, Alexander P., Roden, Michael, Rohde, Rebecca, Roll, Katheryn, Sabanayagam, Charumathi, Sandow, Kevin, Sankareswaran, Alagu, Sattar, Naveed, Schönherr, Sebastian, Shahriar, Mohammad, Shen, Botong, Shi, Jinxiu, Shin, Dong Mun, Shojima, Nobuhiro, Smith, Jennifer A., So, Wing Yee, Stančáková, Alena, Steinthorsdottir, Valgerdur, Stilp, Adrienne M., Strauch, Konstantin, Taylor, Kent D., Thorand, Barbara, Thorsteinsdottir, Unnur, Tomlinson, Brian, Tran, Tam C., Tsai, Fuu-Jen, Tuomilehto, Jaakko, Tusie-Luna, Teresa, Udler, Miriam S., Valladares-Salgado, Adan, van Dam, Rob M., van Klinken, Jan B., Varma, Rohit, Wacher-Rodarte, Niels, Wheeler, Eleanor, Wickremasinghe, Ananda R., van Dijk, Ko Willems, Witte, Daniel R., Yajnik, Chittaranjan S., Yamamoto, Ken, Yamamoto, Kenichi, Yoon, Kyungheon, Yu, Canqing, Yuan, Jian-Min, Yusuf, Salim, Zawistowski, Matthew, Zhang, Liang, Zheng, Wei, Raffel, Leslie J., Igase, Michiya, Ipp, Eli, Redline, Susan, Cho, Yoon Shin, Lind, Lars, Province, Michael A., Fornage, Myriam, Hanis, Craig L., Ingelsson, Erik, Zonderman, Alan B., Psaty, Bruce M., Wang, Ya-Xing, Rotimi, Charles N., Becker, Diane M., Matsuda, Fumihiko, Liu, Yongmei, Yokota, Mitsuhiro, Kardia, Sharon L. R., Peyser, Patricia A., Pankow, James S., Engert, James C., Bonnefond, Amélie, Froguel, Philippe, Wilson, James G., Sheu, Wayne H. H., Wu, Jer-Yuarn, Hayes, M. Geoffrey, Ma, Ronald C. W., Wong, Tien-Yin, Mook-Kanamori, Dennis O., Tuomi, Tiinamaija, Chandak, Giriraj R., Collins, Francis S., Bharadwaj, Dwaipayan, Paré, Guillaume, Sale, Michèle M., Ahsan, Habibul, Motala, Ayesha A., Shu, Xiao-Ou, Park, Kyong-Soo, Jukema, J. Wouter, Cruz, Miguel, Chen, Yii-Der Ida, Rich, Stephen S., McKean-Cowdin, Roberta, Grallert, Harald, Cheng, Ching-Yu, Ghanbari, Mohsen, Tai, E-Shyong, Dupuis, Josee, Kato, Norihiro, Laakso, Markku, Köttgen, Anna, Koh, Woon-Puay, Bowden, Donald W., Palmer, Colin N. A., Kooner, Jaspal S., Kooperberg, Charles, Liu, Simin, North, Kari E., Saleheen, Danish, Hansen, Torben, Pedersen, Oluf, Wareham, Nicholas J., Lee, Juyoung, Kim, Bong-Jo, Millwood, Iona Y., Walters, Robin G., Stefansson, Kari, Ahlqvist, Emma, Goodarzi, Mark O., Mohlke, Karen L., Langenberg, Claudia, Haiman, Christopher A., Loos, Ruth J. F., Florez, Jose C., Rader, Daniel J., Ritchie, Marylyn D., Zöllner, Sebastian, Mägi, Reedik, Marston, Nicholas A., Ruff, Christian T., van Heel, David A., Finer, Sarah, Denny, Joshua C., Yamauchi, Toshimasa, Kadowaki, Takashi, Chambers, John C., Ng, Maggie C. Y., Sim, Xueling, Below, Jennifer E., Tsao, Philip S., Chang, Kyong-Mi, McCarthy, Mark I., Meigs, James B., Mahajan, Anubha, Spracklen, Cassandra N., Mercader, Josep M., Boehnke, Michael, Rotter, Jerome I., Vujkovic, Marijana, Voight, Benjamin F., Morris, Andrew P., and Zeggini, Eleftheria

Published
2024
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13. A novel electronic health record-based, machine-learning model to predict severe hypoglycemia leading to hospitalizations in older adults with diabetes: A territory-wide cohort and modeling study

Author

Shi, Mai, Yang, Aimin, Lau, Eric S. H., Luk, Andrea O. Y., Ma, Ronald C. W., Kong, Alice P. S., Wong, Raymond S. M., Chan, Jones C. M., Chan, Juliana C. N., and Chow, Elaine

Subjects
Hospitals -- Emergency service, Medical records, Blood sugar, Machine learning, Electronic records, Diabetics, Neural networks, Type 2 diabetes, Algorithms, Neural network, Algorithm, Biological sciences
Abstract

Background Older adults with diabetes are at high risk of severe hypoglycemia (SH). Many machine-learning (ML) models predict short-term hypoglycemia are not specific for older adults and show poor precision-recall. We aimed to develop a multidimensional, electronic health record (EHR)-based ML model to predict one-year risk of SH requiring hospitalization in older adults with diabetes. Methods and findings We adopted a case-control design for a retrospective territory-wide cohort of 1,456,618 records from 364,863 unique older adults (age [greater than or equal to]65 years) with diabetes and at least 1 Hong Kong Hospital Authority attendance from 2013 to 2018. We used 258 predictors including demographics, admissions, diagnoses, medications, and routine laboratory tests in a one-year period to predict SH events requiring hospitalization in the following 12 months. The cohort was randomly split into training, testing, and internal validation sets in a 7:2:1 ratio. Six ML algorithms were evaluated including logistic-regression, random forest, gradient boost machine, deep neural network (DNN), XGBoost, and Rulefit. We tested our model in a temporal validation cohort in the Hong Kong Diabetes Register with predictors defined in 2018 and outcome events defined in 2019. Predictive performance was assessed using area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC) statistics, and positive predictive value (PPV). We identified 11,128 SH events requiring hospitalization during the observation periods. The XGBoost model yielded the best performance (AUROC = 0.978 [95% CI 0.972 to 0.984]; AUPRC = 0.670 [95% CI 0.652 to 0.688]; PPV = 0.721 [95% CI 0.703 to 0.739]). This was superior to an 11-variable conventional logistic-regression model comprised of age, sex, history of SH, hypertension, blood glucose, kidney function measurements, and use of oral glucose-lowering drugs (GLDs) (AUROC = 0.906; AUPRC = 0.085; PPV = 0.468). Top impactful predictors included non-use of lipid-regulating drugs, in-patient admission, urgent emergency triage, insulin use, and history of SH. External validation in the HKDR cohort yielded AUROC of 0.856 [95% CI 0.838 to 0.873]. Main limitations of this study included limited transportability of the model and lack of geographically independent validation. Conclusions Our novel-ML model demonstrated good discrimination and high precision in predicting one-year risk of SH requiring hospitalization. This may be integrated into EHR decision support systems for preemptive intervention in older adults at highest risk., Author(s): Mai Shi 1,2, Aimin Yang 1,3, Eric S. H. Lau 1,2, Andrea O. Y. Luk 1,2,3, Ronald C. W. Ma 1,2,3, Alice P. S. Kong 1,2,3, Raymond S. M. [...]

Published
2024
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17. 1-year weight change after diabetes diagnosis and long-term incidence and sustainability of remission of type 2 diabetes in real-world settings in Hong Kong: An observational cohort study

Author

Wu, Hongjiang, Yang, Aimin, Lau, Eric S. H., Zhang, Xinge, Fan, Baoqi, Ma, Ronald C. W., Kong, Alice P. S., Chow, Elaine, So, Wing-Yee, Chan, Juliana C. N., and Luk, Andrea O. Y.

Subjects
Glycosylated hemoglobin -- Measurement -- Health aspects, Obesity -- Surgery, Type 2 diabetes -- Diagnosis -- Care and treatment, Health risk assessment -- Methods, Biological sciences
Abstract

Background Clinical trials have demonstrated that remission of type 2 diabetes can be achieved following sustained weight loss. However, the feasibility of achieving diabetes remission through weight management in real-world settings remains unclear. In this study, we aimed to examine the association of weight change at 1 year after diabetes diagnosis with long-term incidence and sustainability of type 2 diabetes remission in real-world settings in Hong Kong. Methods and findings This was a population-based observational cohort study. The territory-wide Risk Assessment and Management Programme for Diabetes Mellitus (RAMP-DM) provides regular comprehensive assessments of metabolic control and complication screening for people with diabetes in Hong Kong. We included 37,326 people with newly diagnosed type 2 diabetes who were enrolled in the RAMP-DM between 2000 and 2017, followed until 2019. Diabetes remission was defined as 2 consecutive HbA1c Conclusions In this study, greater weight loss within the first year of diabetes diagnosis was associated with an increased likelihood of achieving diabetes remission and a decreased risk of returning to hyperglycaemia among those who had achieved diabetes remission. However, both the incidence of diabetes remission and the probability of its long-term sustainability were low with conventional management in real-world settings, in an era when the importance of weight loss was not fully appreciated. Our study provides evidence for policymakers to design and implement early weight management interventions and diabetes remission initiatives., Author(s): Hongjiang Wu 1, Aimin Yang 1,2, Eric S. H. Lau 1, Xinge Zhang 1, Baoqi Fan 1, Ronald C. W. Ma 1,2,3, Alice P. S. Kong 1,2,3, Elaine Chow [...]

Published
2024
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22. Lifetime risk, life expectancy, and years of life lost to type 2 diabetes in 23 high-income jurisdictions: a multinational, population-based study

Author

Tomic, Dunya, Morton, Jedidiah I, Chen, Lei, Salim, Agus, Gregg, Edward W, Pavkov, Meda E, Arffman, Martti, Balicer, Ran, Baviera, Marta, Boersma-van Dam, Elise, Brinks, Ralph, Carstensen, Bendix, Chan, Juliana C N, Cheng, Yiling J, Fosse-Edorh, Sandrine, Fuentes, Sonsoles, Gardiner, Hélène, Gulseth, Hanne L, Gurevicius, Romualdas, Ha, Kyoung Hwa, Hoyer, Annika, Jermendy, György, Kautzky-Willer, Alexandra, Keskimäki, Ilmo, Kim, Dae Jung, Kiss, Zoltán, Klimek, Peter, Leventer-Roberts, Maya, Lin, Chun-Yi, Lopez-Doriga Ruiz, Paz, Luk, Andrea O Y, Ma, Stefan, Mata-Cases, Manel, Mauricio, Dídac, McGurnaghan, Stuart, Imamura, Tomoaki, Paul, Sanjoy K, Peeters, Anna, Pildava, Santa, Porath, Avi, Robitaille, Cynthia, Roncaglioni, Maria Carla, Sugiyama, Takehiro, Wang, Kang-Ling, Wild, Sarah H, Yekutiel, Naama, Shaw, Jonathan E, and Magliano, Dianna J

Published
2022
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23. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

Author

Mahajan, Anubha, Spracklen, Cassandra N., Zhang, Weihua, Ng, Maggie C. Y., Petty, Lauren E., Kitajima, Hidetoshi, Yu, Grace Z., Rüeger, Sina, Speidel, Leo, Kim, Young Jin, Horikoshi, Momoko, Mercader, Josep M., Taliun, Daniel, Moon, Sanghoon, Kwak, Soo-Heon, Robertson, Neil R., Rayner, Nigel W., Loh, Marie, Kim, Bong-Jo, Chiou, Joshua, Miguel-Escalada, Irene, della Briotta Parolo, Pietro, Lin, Kuang, Bragg, Fiona, Preuss, Michael H., Takeuchi, Fumihiko, Nano, Jana, Guo, Xiuqing, Lamri, Amel, Nakatochi, Masahiro, Scott, Robert A., Lee, Jung-Jin, Huerta-Chagoya, Alicia, Graff, Mariaelisa, Chai, Jin-Fang, Parra, Esteban J., Yao, Jie, Bielak, Lawrence F., Tabara, Yasuharu, Hai, Yang, Steinthorsdottir, Valgerdur, Cook, James P., Kals, Mart, Grarup, Niels, Schmidt, Ellen M., Pan, Ian, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloe, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Ahmad, Meraj, Noordam, Raymond, Lim, Victor J. Y., Tam, Claudia H. T., Joo, Yoonjung Yoonie, Chen, Chien-Hsiun, Raffield, Laura M., Lecoeur, Cécile, Prins, Bram Peter, Nicolas, Aude, Yanek, Lisa R., Chen, Guanjie, Jensen, Richard A., Tajuddin, Salman, Kabagambe, Edmond K., An, Ping, Xiang, Anny H., Choi, Hyeok Sun, Cade, Brian E., Tan, Jingyi, Flanagan, Jack, Abaitua, Fernando, Adair, Linda S., Adeyemo, Adebowale, Aguilar-Salinas, Carlos A., Akiyama, Masato, Anand, Sonia S., Bertoni, Alain, Bian, Zheng, Bork-Jensen, Jette, Brandslund, Ivan, Brody, Jennifer A., Brummett, Chad M., Buchanan, Thomas A., Canouil, Mickaël, Chan, Juliana C. N., Chang, Li-Ching, Chee, Miao-Li, Chen, Ji, Chen, Shyh-Huei, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, Cushman, Mary, Das, Swapan K., de Silva, H. Janaka, Dedoussis, George, Dimitrov, Latchezar, Doumatey, Ayo P., Du, Shufa, Duan, Qing, Eckardt, Kai-Uwe, Emery, Leslie S., Evans, Daniel S., Evans, Michele K., Fischer, Krista, Floyd, James S., Ford, Ian, Fornage, Myriam, Franco, Oscar H., Frayling, Timothy M., Freedman, Barry I., Fuchsberger, Christian, Genter, Pauline, Gerstein, Hertzel C., Giedraitis, Vilmantas, González-Villalpando, Clicerio, González-Villalpando, Maria Elena, Goodarzi, Mark O., Gordon-Larsen, Penny, Gorkin, David, Gross, Myron, Guo, Yu, Hackinger, Sophie, Han, Sohee, Hattersley, Andrew T., Herder, Christian, Howard, Annie-Green, Hsueh, Willa, Huang, Mengna, Huang, Wei, Hung, Yi-Jen, Hwang, Mi Yeong, Hwu, Chii-Min, Ichihara, Sahoko, Ikram, Mohammad Arfan, Ingelsson, Martin, Islam, Md Tariqul, Isono, Masato, Jang, Hye-Mi, Jasmine, Farzana, Jiang, Guozhi, Jonas, Jost B., Jørgensen, Marit E., Jørgensen, Torben, Kamatani, Yoichiro, Kandeel, Fouad R., Kasturiratne, Anuradhani, Katsuya, Tomohiro, Kaur, Varinderpal, Kawaguchi, Takahisa, Keaton, Jacob M., Kho, Abel N., Khor, Chiea-Chuen, Kibriya, Muhammad G., Kim, Duk-Hwan, Kohara, Katsuhiko, Kriebel, Jennifer, Kronenberg, Florian, Kuusisto, Johanna, Läll, Kristi, Lange, Leslie A., Lee, Myung-Shik, Lee, Nanette R., Leong, Aaron, Li, Liming, Li, Yun, Li-Gao, Ruifang, Ligthart, Symen, Lindgren, Cecilia M., Linneberg, Allan, Liu, Ching-Ti, Liu, Jianjun, Locke, Adam E., Louie, Tin, Luan, Jian’an, Luk, Andrea O., Luo, Xi, Lv, Jun, Lyssenko, Valeriya, Mamakou, Vasiliki, Mani, K. Radha, Meitinger, Thomas, Metspalu, Andres, Morris, Andrew D., Nadkarni, Girish N., Nadler, Jerry L., Nalls, Michael A., Nayak, Uma, Nongmaithem, Suraj S., Ntalla, Ioanna, Okada, Yukinori, Orozco, Lorena, Patel, Sanjay R., Pereira, Mark A., Peters, Annette, Pirie, Fraser J., Porneala, Bianca, Prasad, Gauri, Preissl, Sebastian, Rasmussen-Torvik, Laura J., Reiner, Alexander P., Roden, Michael, Rohde, Rebecca, Roll, Kathryn, Sabanayagam, Charumathi, Sander, Maike, Sandow, Kevin, Sattar, Naveed, Schönherr, Sebastian, Schurmann, Claudia, Shahriar, Mohammad, Shi, Jinxiu, Shin, Dong Mun, Shriner, Daniel, Smith, Jennifer A., So, Wing Yee, Stančáková, Alena, Stilp, Adrienne M., Strauch, Konstantin, Suzuki, Ken, Takahashi, Atsushi, Taylor, Kent D., Thorand, Barbara, Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, Tomlinson, Brian, Torres, Jason M., Tsai, Fuu-Jen, Tuomilehto, Jaakko, Tusie-Luna, Teresa, Udler, Miriam S., Valladares-Salgado, Adan, van Dam, Rob M., van Klinken, Jan B., Varma, Rohit, Vujkovic, Marijana, Wacher-Rodarte, Niels, Wheeler, Eleanor, Whitsel, Eric A., Wickremasinghe, Ananda R., van Dijk, Ko Willems, Witte, Daniel R., Yajnik, Chittaranjan S., Yamamoto, Ken, Yamauchi, Toshimasa, Yengo, Loïc, Yoon, Kyungheon, Yu, Canqing, Yuan, Jian-Min, Yusuf, Salim, Zhang, Liang, Zheng, Wei, Raffel, Leslie J., Igase, Michiya, Ipp, Eli, Redline, Susan, Cho, Yoon Shin, Lind, Lars, Province, Michael A., Hanis, Craig L., Peyser, Patricia A., Ingelsson, Erik, Zonderman, Alan B., Psaty, Bruce M., Wang, Ya-Xing, Rotimi, Charles N., Becker, Diane M., Matsuda, Fumihiko, Liu, Yongmei, Zeggini, Eleftheria, Yokota, Mitsuhiro, Rich, Stephen S., Kooperberg, Charles, Pankow, James S., Engert, James C., Chen, Yii-Der Ida, Froguel, Philippe, Wilson, James G., Sheu, Wayne H. H., Kardia, Sharon L. R., Wu, Jer-Yuarn, Hayes, M. Geoffrey, Ma, Ronald C. W., Wong, Tien-Yin, Groop, Leif, Mook-Kanamori, Dennis O., Chandak, Giriraj R., Collins, Francis S., Bharadwaj, Dwaipayan, Paré, Guillaume, Sale, Michèle M., Ahsan, Habibul, Motala, Ayesha A., Shu, Xiao-Ou, Park, Kyong-Soo, Jukema, J. Wouter, Cruz, Miguel, McKean-Cowdin, Roberta, Grallert, Harald, Cheng, Ching-Yu, Bottinger, Erwin P., Dehghan, Abbas, Tai, E-Shyong, Dupuis, Josée, Kato, Norihiro, Laakso, Markku, Köttgen, Anna, Koh, Woon-Puay, Palmer, Colin N. A., Liu, Simin, Abecasis, Goncalo, Kooner, Jaspal S., Loos, Ruth J. F., North, Kari E., Haiman, Christopher A., Florez, Jose C., Saleheen, Danish, Hansen, Torben, Pedersen, Oluf, Mägi, Reedik, Langenberg, Claudia, Wareham, Nicholas J., Maeda, Shiro, Kadowaki, Takashi, Lee, Juyoung, Millwood, Iona Y., Walters, Robin G., Stefansson, Kari, Myers, Simon R., Ferrer, Jorge, Gaulton, Kyle J., Meigs, James B., Mohlke, Karen L., Gloyn, Anna L., Bowden, Donald W., Below, Jennifer E., Chambers, John C., Sim, Xueling, Boehnke, Michael, Rotter, Jerome I., McCarthy, Mark I., and Morris, Andrew P.

Published
2022
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24. Higher risk of incident diabetes among patients with primary hyperparathyroidism.

Author

Zhang, Yingchai, Wu, Hongjiang, Yang, Aimin, Y.H. Ng, Noel, Zhang, Xinge, Lau, Eric S. H., Chow, Edith W. K., Kong, Alice P. S., Chow, Elaine Y. K., Chan, Juliana C. N., Luk, Andrea O. Y., and Ma, Ronald C. W.

Subjects
PEOPLE with diabetes, MEDIAN (Mathematics), DIABETES, REGRESSION analysis, HYPERCALCEMIA
Abstract

Objectives: There is relatively scarce data regarding the association between primary hyperparathyroidism (PHPT) and incident diabetes in large population‐based longitudinal studies. We aimed to evaluate the risk of incident diabetes in individuals with and without PHPT and investigate the association between serum calcium concentrations and the risk of incident diabetes in patients with PHPT. Methods: We included 2749 PHPT patients and 13,745 age, sex and index year matched non‐PHPT individuals during 2000–2019. We used Cox regression models to compare the risk of incident diabetes in individuals with and without PHPT, and the risk of incident diabetes in PHPT patients with serum calcium concentration above and below the median value. The association between serum calcium concentrations and the risk of incident diabetes was examined by restricted cubic spline analyses in patients with PHPT. Results: During a median follow‐up time of 5.17 years (IQR 2.17, 9.58), 433 patients (15.75%) with PHPT and 2110 individuals (15.35%) without PHPT developed diabetes, respectively. Patients with PHPT had a higher incidence rate of diabetes compared to non‐PHPT individuals (27.60 [95% CI 25.00, 30.30] vs. 23.90 [95% CI 22.80, 24.90] per 1000 person‐years, log‐rank test p =.007]. Crude Cox regression model showed PHPT was associated with a 15% higher risk of incident diabetes (HR 1.15, 95%CI 1.04, 1.28). In patients with PHPT, a 44% higher risk of incident diabetes was found in patients with serum calcium concentrations above the median value (2.63 mmol/L), compared to those below the median value (HR 1.44, 95%CI 1.08, 1.90). Restricted cubic spline analyses confirmed a positive linear association between serum calcium concentrations and the risk of incident diabetes in those with PHPT (p‐value for nonlinear =.751) Conclusions: Patients with PHPT had a higher risk of incident diabetes compared to non‐PHPT individuals. A positive linear association was found between serum calcium concentrations and the risk of incident diabetes in patients with PHPT. [ABSTRACT FROM AUTHOR]

Published
2024
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25. Age- and sex-specific hospital bed-day rates in people with and without type 2 diabetes: A territory-wide population-based cohort study of 1.5 million people in Hong Kong

Author

Wu, Hongjiang, Yang, Aimin, Lau, Eric S. H., Zhang, Xinge, Fan, Baoqi, Shi, Mai, Huang, Chuiguo, Ma, Ronald C. W., Kong, Alice P. S., Chow, Elaine, So, Wing-Yee, Chan, Juliana C. N., and Luk, Andrea O. Y.

Subjects
Age factors in disease -- Analysis, Sex factors in disease -- Analysis, Hospital utilization -- Length of stay, Type 2 diabetes -- Statistics -- Demographic aspects -- Care and treatment, Biological sciences
Abstract

Background Type 2 diabetes affects multiple systems. We aimed to compare age- and sex-specific rates of all-cause and cause-specific hospital bed-days between people with and without type 2 diabetes. Methods and findings Data were provided by the Hong Kong Hospital Authority. We included 1,516,508 one-to-one matched people with incident type 2 diabetes (n = 758,254) and those without diabetes during the entire follow-up period (n = 758,254) between 2002 and 2018, followed until 2019. People with type 2 diabetes and controls were matched for age at index date (±2 years), sex, and index year (±2 years). We defined hospital bed-day rate as total inpatient bed-days divided by follow-up time. We constructed negative binominal regression models to estimate hospital bed-day rate ratios (RRs) by age at diabetes diagnosis and sex. All RRs were stratified by sex and adjusted for age and index year. During a median of 7.8 years of follow-up, 60.5% (n = 459,440) of people with type 2 diabetes and 56.5% (n = 428,296) of controls had a hospital admission for any cause, with a hospital bed-day rate of 3,359 bed-days and 2,350 bed-days per 1,000 person-years, respectively. All-cause hospital bed-day rate increased with increasing age in controls, but showed a J-shaped relationship with age in people with type 2 diabetes, with 38.4% of bed-days in those diagnosed Conclusions In this study, we observed that type 2 diabetes was associated with increased risks of hospital bed-days for a wide range of medical conditions, with an excess burden of mental health disorders in people diagnosed at a young age. Age and sex differences should be considered in planning preventive and therapeutic strategies for type 2 diabetes. Effective control of risk factors with a focus on mental health disorders are urgently needed in young people with type 2 diabetes. Healthcare systems and policymakers should consider allocating adequate resources and developing strategies to meet the mental health needs of young people with type 2 diabetes, including integrating mental health services into diabetes care., Author(s): Hongjiang Wu 1, Aimin Yang 1,2, Eric S. H. Lau 1, Xinge Zhang 1, Baoqi Fan 1, Mai Shi 1, Chuiguo Huang 1, Ronald C. W. Ma 1,2,3, Alice [...]

Published
2023
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26. Trends in all-cause mortality among people with diagnosed diabetes in high-income settings: a multicountry analysis of aggregate data

Author

Magliano, Dianna J, Chen, Lei, Carstensen, Bendix, Gregg, Edward W, Pavkov, Meda E, Salim, Agus, Andes, Linda J, Balicer, Ran, Baviera, Marta, Chan, Juliana C N, Cheng, Yiling J, Gardiner, Helene, Gulseth, Hanne L, Gurevicius, Romualdas, Ha, Kyoung Hwa, Jermendy, György, Kim, Dae Jung, Kiss, Zoltán, Leventer-Roberts, Maya, Lin, Chun-Yi, Luk, Andrea O Y, Ma, Stefan, Mata-Cases, Manel, Mauricio, Didac, Nichols, Gregory A, Pildava, Santa, Porath, Avi, Read, Stephanie H, Robitaille, Cynthia, Roncaglioni, Maria Carla, Lopez-Doriga Ruiz, Paz, Wang, Kang-Ling, Wild, Sarah H, Yekutiel, Naama, and Shaw, Jonathan E

Published
2022
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27. Relative leucocyte telomere length is associated with incident end-stage kidney disease and rapid decline of kidney function in type 2 diabetes: analysis from the Hong Kong Diabetes Register

Author

Cheng, Feifei, Luk, Andrea O., Wu, Hongjiang, Tam, Claudia H. T., Lim, Cadmon K. P., Fan, Baoqi, Jiang, Guozhi, Carroll, Luke, Yang, Aimin, Lau, Eric S. H., Ng, Alex C. W., Lee, Heung Man, Chow, Elaine, Kong, Alice P. S., Keech, Anthony C., Joglekar, Mugdha V., So, Wing Yee, Hardikar, Anandwardhan A., Chan, Juliana C. N., Jenkins, Alicia J., and Ma, Ronald C. W.

Published
2022
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29. Combined associations of family history and self-management with age at diagnosis and cardiometabolic risk in 86,931 patients with type 2 diabetes: Joint Asia Diabetes Evaluation (JADE) Register from 11 countries

Author

Cheung, Johnny T. K., Lau, Eric, Tsui, Cyrus C. T., Siu, Edmond L. N., Tse, Naomi K. W., Hui, Nicole Y. L., Ma, Ronald C. W., Kong, Alice P. S., Fu, Amy, Lau, Vanessa, Jia, Weiping, Sheu, Wayne H. H., Sobrepena, Leorino, Yoon, K. H., Tan, Alexander T. B., Chia, Yook-Chin, Sosale, Aravind, Saboo, Banshi D., Kesavadev, Jothydev, Goh, Su-Yen, Nguyen, Thy Khue, Thewjitcharoen, Yotsapon, Suwita, Raymond, Luk, Andrea O. Y., Yang, Aimin, Chow, Elaine, Lim, Lee Ling, and Chan, Juliana C. N.

Published
2022
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30. High-density lipoprotein subclasses and cardiovascular disease and mortality in type 2 diabetes: analysis from the Hong Kong Diabetes Biobank

Author

Jin, Qiao, Lau, Eric S. H., Luk, Andrea O., Tam, Claudia H. T., Ozaki, Risa, Lim, Cadmon K. P., Wu, Hongjiang, Chow, Elaine Y. K., Kong, Alice P. S., Lee, Heung Man, Fan, Baoqi, Ng, Alex C. W., Jiang, Guozhi, Lee, Ka Fai, Siu, Shing Chung, Hui, Grace, Tsang, Chiu Chi, Lau, Kam Piu, Leung, Jenny Y., Tsang, Man-wo, Cheung, Elaine Y. N., Kam, Grace, Lau, Ip Tim, Li, June K., Yeung, Vincent T., Lau, Emmy, Lo, Stanley, Fung, Samuel, Cheng, Yuk Lun, Chow, Chun Chung, Yu, Weichuan, Tsui, Stephen K. W., Huang, Yu, Lan, Hui-yao, Szeto, Cheuk Chun, So, Wing Yee, Jenkins, Alicia J., Chan, Juliana C. N., and Ma, Ronald C. W.

Published
2022
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31. Association of dipeptidyl peptidase‐4 inhibitor initiation at glycated haemoglobin <7.5% with reduced major clinical events mediated by low glycated haemoglobin variability

Author

Cheung, Johnny T. K., primary, Yang, Aimin, additional, Wu, Hongjiang, additional, Lau, Eric S. H., additional, Lui, Juliana, additional, Kong, Alice P. S., additional, Ma, Ronald C. W., additional, Luk, Andrea O. Y., additional, Chow, Elaine, additional, and Chan, Juliana C. N., additional

Published
2024
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32. Trends in the incidence of diagnosed diabetes: a multicountry analysis of aggregate data from 22 million diagnoses in high-income and middle-income settings

Author

Magliano, Dianna J, Chen, Lei, Islam, Rakibul M, Carstensen, Bendix, Gregg, Edward W, Pavkov, Meda E, Andes, Linda J, Balicer, Ran, Baviera, Marta, Boersma-van Dam, Elise, Booth, Gillian L, Chan, Juliana C N, Chua, Yi Xian, Fosse-Edorh, Sandrine, Fuentes, Sonsoles, Gulseth, Hanne L, Gurevicius, Romualdas, Ha, Kyoung Hwa, Hird, Thomas R, Jermendy, György, Khalangot, Mykola D, Kim, Dae Jung, Kiss, Zoltán, Kravchenko, Victor I, Leventer-Roberts, Maya, Lin, Chun-Yi, Luk, Andrea O Y, Mata-Cases, Manel, Mauricio, Didac, Nichols, Gregory A, Nielen, Mark M, Pang, Deanette, Paul, Sanjoy K, Pelletier, Catherine, Pildava, Santa, Porath, Avi, Read, Stephanie H, Roncaglioni, Maria Carla, Lopez-Doriga Ruiz, Paz, Shestakova, Marina, Vikulova, Olga, Wang, Kang-Ling, Wild, Sarah H, Yekutiel, Naama, and Shaw, Jonathan E

Published
2021
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35. Age-specific population attributable risk factors for all-cause and cause-specific mortality in type 2 diabetes: An analysis of a 6-year prospective cohort study of over 360,000 people in Hong Kong

Author

Wu, Hongjiang, Lau, Eric S. H., Yang, Aimin, Zhang, Xinge, Fan, Baoqi, Ma, Ronald C. W., Kong, Alice P. S., Chow, Elaine, So, Wing-Yee, Chan, Juliana C. N., and Luk, Andrea O. Y.

Subjects
Comorbidity -- Risk factors -- Demographic aspects -- Patient outcomes, Type 2 diabetes -- Demographic aspects -- Patient outcomes, Biological sciences
Abstract

Background The prevalence of type 2 diabetes has increased in both young and old people. We examined age-specific associations and population attributable fractions (PAFs) of risk factors for all-cause and cause-specific mortality in people with type 2 diabetes. Methods and findings We analysed data from 360,202 Chinese with type 2 diabetes who participated in a territory-wide diabetes complication screening programme in Hong Kong between January 2000 and December 2019. We compared the hazard ratios and PAFs of eight risk factors, including three major comorbidities (cardiovascular disease [CVD], chronic kidney disease [CKD], all-site cancer) and five modifiable risk factors (suboptimal HbA1c, suboptimal blood pressure, suboptimal low-density lipoprotein cholesterol, smoking, and suboptimal weight), for mortality across four age groups (18 to 54, 55 to 64, 65 to 74, and [greater than or equal to]75 years). During a median 6.0 years of follow-up, 44,396 people died, with cancer, CVD, and pneumonia being the leading causes of death. Despite a higher absolute mortality risk in older people (crude all-cause mortality rate: 59.7 versus 596.2 per 10,000 person-years in people aged 18 to 54 years versus those aged [greater than or equal to]75 years), the relative risk of all-cause and cause-specific mortality associated with most risk factors was higher in younger than older people, after mutually adjusting for the eight risk factors and other potential confounders including sex, diabetes duration, lipid profile, and medication use. The eight risk factors explained a larger proportion of mortality events in the youngest (PAF: 51.6%, 95% confidence interval [CI] [39.1%, 64.0%], p < 0.001) than the oldest (PAF: 35.3%, 95% CI [27.2%, 43.4%], p < 0.001) age group. Suboptimal blood pressure (PAF: 16.9%, 95% CI [14.7%, 19.1%], p < 0.001) was the leading attributable risk factor for all-cause mortality in the youngest age group, while CKD (PAF: 15.2%, 95% CI [14.0%, 16.4%], p < 0.001) and CVD (PAF: 9.2%, 95% CI [8.3%, 10.1%], p < 0.001) were the leading attributable risk factors in the oldest age group. The analysis was restricted to Chinese, which might affect the generalisability to the global population with differences in risk profiles. Furthermore, PAFs were estimated under the assumption of a causal relationship between risk factors and mortality. However, reliable causality was difficult to establish in the observational study. Conclusions Major comorbidities and modifiable risk factors were associated with a greater relative risk for mortality in younger than older people with type 2 diabetes and their associations with population mortality burden varied substantially by age. These findings highlight the importance of early control of blood pressure, which could reduce premature mortality in young people with type 2 diabetes and prevent the onset of later CKD and related mortality at older ages., Author(s): Hongjiang Wu 1, Eric S. H. Lau 1, Aimin Yang 1,2, Xinge Zhang 1, Baoqi Fan 1, Ronald C. W. Ma 1,2,3, Alice P. S. Kong 1,2,3, Elaine Chow [...]

Published
2023
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39. Effects of intensive treatment of Chinese women with gestational diabetes on the risk of offspring being overweight from 3 to 8 years of age.

Author

Li, Jing, Zhang, Rui, Zhang, Cuiping, Liu, Gongshu, Li, Weiqin, Wang, Hui, Qiao, Yijuan, Yu, Zhijie, Hu, Gang, Chan, Juliana C. N., Leng, Junhong, and Yang, Xilin

Subjects
HIGH-risk pregnancy, OVERWEIGHT children, GESTATIONAL diabetes, MATERNAL age, DIASTOLIC blood pressure, MEDICAL personnel, CHI-squared test
Abstract

A study published in the journal Diabetes, Obesity & Metabolism found that children born to mothers with gestational diabetes have an increased risk of being overweight as they grow up. The study also found that intensive treatment of gestational diabetes during pregnancy improved outcomes for both mother and baby, but did not reduce the risk of childhood obesity. The researchers suggest that prevention and intensive management of gestational diabetes are important in reducing the risk of childhood obesity. They also recommend that children from gestational diabetes pregnancies adopt a healthy lifestyle from an early age to reduce the risk of future health problems. Further research is needed to better understand these relationships and develop effective health management strategies for women with gestational diabetes and their children. [Extracted from the article]

Published
2024
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40. Current type 2 diabetes guidelines: Individualized treatment and how to make the most of metformin.

Author

Chan, Juliana C. N., Yang, Aimin, Chu, Natural, and Chow, Elaine

Subjects
*VITAMIN B12 deficiency, *TYPE 2 diabetes, *MEDICAL personnel, *SODIUM-glucose cotransporters, *MEDICAL quality control, *PEOPLE with diabetes
Abstract

Evidence‐based guidelines provide the premise for the delivery of quality care to preserve health and prevent disabilities and premature death. The systematic gathering of observational, mechanistic and experimental data contributes to the hierarchy of evidence used to guide clinical practice. In the field of diabetes, metformin was discovered more than 100 years ago, and with 60 years of clinical use, it has stood the test of time regarding its value in the prevention and management of type 2 diabetes. Although some guidelines have challenged the role of metformin as the first‐line glucose‐lowering drug, it is important to point out that the cardiovascular‐renal protective effects of sodium‐glucose co‐transporter‐2 inhibitors and glucagon‐like peptide‐1 receptor agonists were gathered from patients with type 2 diabetes, the majority of whom were treated with metformin. Most national, regional and international guidelines recommend metformin as a foundation therapy with emphasis on avoidance of therapeutic inertia and early attainment of multiple treatment goals. Moreover, real‐world evidence has confirmed the glucose‐lowering and cardiovascular‐renal benefits of metformin accompanied by an extremely low risk of lactic acidosis. In patients with type 2 diabetes and advanced chronic kidney disease (estimated glomerular filtration rate 15‐30 mL/min/1.73m2), metformin discontinuation was associated with an increased risk of cardiovascular‐renal events compared with metformin persistence. Meanwhile, it is understood that microbiota, nutrients and metformin can interact through the gut‐brain‐kidney axis to modulate homeostasis of bioactive molecules, systemic inflammation and energy metabolism. While these biological changes contribute to the multisystem effects of metformin, they may also explain the gastrointestinal side effects and vitamin B12 deficiency associated with metformin intolerance. By understanding the interactions between metformin, foods and microbiota, healthcare professionals are in a better position to optimize the use of metformin and mitigate potential side effects. The United Kingdom Prospective Diabetes Study and the Da Qing Diabetes Prevention Program commenced 40 years ago provided the first evidence that type 2 diabetes is preventable and treatable. To drive real‐world impact from this evidence, payors, practitioners and planners need to co‐design and implement an integrated, data‐driven, metformin‐based programme to detect people with undiagnosed diabetes and prediabetes (intermediate hyperglycaemia), notably impaired glucose tolerance, for early intervention. The systematic data collection will create real‐world evidence to bring out the best of metformin and make healthcare sustainable, affordable and accessible. [ABSTRACT FROM AUTHOR]

Published
2024
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41. Monogenic diabetes in a Chinese population with young‐onset diabetes: A 17‐year prospective follow‐up study in Hong Kong.

Author

Tsoi, Sandra T. F., Lim, Cadmon, Ma, Ronald C. W., Lau, Eric S. H., Fan, Baoqi, Chow, Elaine, Kong, Alice P. S., Chan, Juliana C. N., and Luk, Andrea O. Y.

Subjects
CHINESE people, MATURITY onset diabetes of the young, CHRONIC kidney failure, DIABETES, DIABETES complications, CARDIOVASCULAR diseases
Abstract

Aims: Asians have a high prevalence of young‐onset diabetes, but the pattern of monogenic diabetes is unknown. We aimed to determine the prevalence of monogenic diabetes in Chinese patients with young‐onset diabetes and compare the clinical characteristics and outcome between patients with and without monogenic diabetes. Materials and Methods: We sequenced a targeted panel of 33 genes related to monogenic diabetes in 1021 Chinese patients with non‐type 1 diabetes diagnosed at age ≤40 years. Incident complications including cardiovascular disease (CVD), end‐stage kidney disease (ESKD) and all‐cause death were captured since enrolment (1995–2012) until 2019. Results: In this cohort (mean ± SD age at diagnosis: 33.0 ± 6.0 years, median[IQR] diabetes duration 7.0[1.0–15.0] years at baseline, 44.9% men), 22(2.2%, 95% confidence interval[CI] 1.4%–3.2%) had monogenic diabetes. Pathogenic (P) or likely pathogenic (LP) variants were detected in GCK (n = 6), HNF1A (n = 9), HNF4A (n = 1), PLIN1 (n = 1) and PPARG (n = 2), together with copy number variations in HNF1B (n = 3). Over a median follow‐up of 17.1 years, 5(22.7%) patients with monogenic diabetes (incidence rate 12.3[95% CI 5.1–29.4] per 1000 person‐years) versus 254(25.4%) without monogenic diabetes (incidence rate 16.7[95% CI 14.8–18.9] per 1000 person‐years) developed the composite outcome of CVD, ESKD and/or death (p = 0.490). The multivariable Cox model did not show any difference in hazards for composite events between groups. Conclusions: In Chinese with young‐onset non‐type 1 diabetes, at least 2% of cases were contributed by monogenic diabetes, over 80% of which were accounted for by P/LP variants in common MODY genes. The incidence of diabetes complications was similar between patients with and without monogenic diabetes. [ABSTRACT FROM AUTHOR]

Published
2024
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42. The Therapeutic Potential of the Specific Intestinal Microbiome (SIM) Diet on Metabolic Diseases.

Author

Chu, Natural H. S., Chow, Elaine, and Chan, Juliana C. N.

Subjects
GUT microbiome, HIGH-fiber diet, SHORT-chain fatty acids, FATTY liver, MEDITERRANEAN diet, PREBIOTICS
Abstract

Simple Summary: Prebiotics, essential for humans and our gut microbiome, maintain the ecosystem's homeostasis in a mutual relationship with the host and microbiome. As a gut microbiome modulator, poorly absorbed or indigestible carbohydrates interact with the gut microbiome, and its metabolites promote immune health. However, there is limited discussion of a habitual diet in metabolic diseases. Exploring the intricate crosstalk between dietary prebiotics and the specific intestinal microbiome (SIM) is intriguing to gain deeper insights into their therapeutic implications. Exploring the intricate crosstalk between dietary prebiotics and the specific intestinal microbiome (SIM) is intriguing in explaining the mechanisms of current successful dietary interventions, including the Mediterranean diet and high-fiber diet. This knowledge forms a robust basis for developing a new natural food therapy. The SIM diet can be measured and evaluated to establish a reliable basis for the management of metabolic diseases, such as diabetes, metabolic (dysfunction)-associated fatty liver disease (MAFLD), obesity, and metabolic cardiovascular disease. This review aims to delve into the existing body of research to shed light on the promising developments of possible dietary prebiotics in this field and explore the implications for clinical practice. The exciting part is the crosstalk of diet, microbiota, and gut–organ interactions facilitated by producing short-chain fatty acids, bile acids, and subsequent metabolite production. These metabolic-related microorganisms include Butyricicoccus, Akkermansia, and Phascolarctobacterium. The SIM diet, rather than supplementation, holds the promise of significant health consequences via the prolonged reaction with the gut microbiome. Most importantly, the literature consistently reports no adverse effects, providing a strong foundation for the safety of this dietary therapy. [ABSTRACT FROM AUTHOR]

Published
2024
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43. The Lancet Commission on diabetes: using data to transform diabetes care and patient lives

Author

Chan, Juliana C N, Lim, Lee-Ling, Wareham, Nicholas J, Shaw, Jonathan E, Orchard, Trevor J, Zhang, Ping, Lau, Eric S H, Eliasson, Björn, Kong, Alice P S, Ezzati, Majid, Aguilar-Salinas, Carlos A, McGill, Margaret, Levitt, Naomi S, Ning, Guang, So, Wing-Yee, Adams, Jean, Bracco, Paula, Forouhi, Nita G, Gregory, Gabriel A, Guo, Jingchuan, Hua, Xinyang, Klatman, Emma L, Magliano, Dianna J, Ng, Boon-Peng, Ogilvie, David, Panter, Jenna, Pavkov, Meda, Shao, Hui, Unwin, Nigel, White, Martin, Wou, Constance, Ma, Ronald C W, Schmidt, Maria I, Ramachandran, Ambady, Seino, Yutaka, Bennett, Peter H, Oldenburg, Brian, Gagliardino, Juan José, Luk, Andrea O Y, Clarke, Philip M, Ogle, Graham D, Davies, Melanie J, Holman, Rury R, and Gregg, Edward W

Published
2020
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44. Enhanced prediction of abnormal glucose tolerance using an extended non-invasive risk score incorporating routine renal biochemistry

Author

He, Jie, primary, Fan, Baoqi, additional, Lau, Eric S H, additional, Chu, Natural, additional, Ng, Noel Yat Hey, additional, Leung, Kathy Ho Ting, additional, Poon, Emily W M, additional, Kong, Alice Pik Shan, additional, Ma, Ronald Ching Wan, additional, Luk, Andrea O Y, additional, Chan, Juliana C N, additional, and Chow, Elaine, additional

Published
2024
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45. Age at Type 2 Diabetes Diagnosis and Risk of Cancer: Cohort Study in Over 1 Million Individuals from the TriNetX US Collaborative Network

Author

Slater, Tommy, primary, Hernández Ibarburu, Gema, additional, Drebert, Zuzanna, additional, Henson, Joseph, additional, Zaccardi, Francesco, additional, Sargeant, Jack A., additional, Brown, Karen, additional, Webb, David R., additional, Papamargaritis, Dimitris, additional, Chan, Juliana C. N., additional, W. Gregg, Edward, additional, Khunti, Kamlesh, additional, Davies, Melanie J., additional, and Yates, Tom, additional

Published
2024
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46. Impact of age at type 2 diabetes mellitus diagnosis on mortality and vascular complications: systematic review and meta-analyses

Author

Nanayakkara, Natalie, Curtis, Andrea J., Heritier, Stephane, Gadowski, Adelle M., Pavkov, Meda E., Kenealy, Timothy, Owens, David R., Thomas, Rebecca L., Song, Soon, Wong, Jencia, Chan, Juliana C.-N., Luk, Andrea O.-Y., Penno, Giuseppe, Ji, Linong, Mohan, Viswanathan, Amutha, Anandakumar, Romero-Aroca, Pedro, Gasevic, Danijela, Magliano, Dianna J., Teede, Helena J., Chalmers, John, and Zoungas, Sophia

Published
2021
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