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Ma J, Huang A, Yan K, Li Y, Sun X, Joehanes R, Huan T, Levy D, Liu C. Blood transcriptomic biomarkers of alcohol consumption and cardiovascular disease risk factors: the Framingham Heart Study. Hum Mol Genet 2023; 32:649-658. [PMID: 36130209 PMCID: PMC9896471 DOI: 10.1093/hmg/ddac237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 08/19/2022] [Accepted: 09/15/2022] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The relations of alcohol consumption and gene expression remain to be elucidated. MATERIALS AND METHODS We examined cross-sectional associations between alcohol consumption and whole blood derived gene expression levels and between alcohol-associated genes and obesity, hypertension, and diabetes in 5531 Framingham Heart Study (FHS) participants. RESULTS We identified 25 alcohol-associated genes. We further showed cross-sectional associations of 16 alcohol-associated genes with obesity, nine genes with hypertension, and eight genes with diabetes at P < 0.002. For example, we observed decreased expression of PROK2 (β = -0.0018; 95%CI: -0.0021, -0.0007; P = 6.5e - 5) and PAX5 (β = -0.0014; 95%CI: -0.0021, -0.0007; P = 6.5e - 5) per 1 g/day increase in alcohol consumption. Consistent with our previous observation on the inverse association of alcohol consumption with obesity and positive association of alcohol consumption with hypertension, we found that PROK2 was positively associated with obesity (OR = 1.42; 95%CI: 1.17, 1.72; P = 4.5e - 4) and PAX5 was negatively associated with hypertension (OR = 0.73; 95%CI: 0.59, 0.89; P = 1.6e - 3). We also observed that alcohol consumption was positively associated with expression of ABCA13 (β = 0.0012; 95%CI: 0.0007, 0.0017; P = 1.3e - 6) and ABCA13 was positively associated with diabetes (OR = 2.57; 95%CI: 1.73, 3.84; P = 3.5e - 06); this finding, however, was inconsistent with our observation of an inverse association between alcohol consumption and diabetes. CONCLUSIONS We showed strong cross-sectional associations between alcohol consumption and expression levels of 25 genes in FHS participants. Nonetheless, complex relationships exist between alcohol-associated genes and CVD risk factors.
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Affiliation(s)
- Jiantao Ma
- Division of Nutrition Epidemiology and Data Science, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA 02111, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Allen Huang
- Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA 02142, USA
| | - Kaiyu Yan
- Department of Biostatistics, Boston University, Boston, MA 02118, USA
| | - Yi Li
- Department of Biostatistics, Boston University, Boston, MA 02118, USA
| | - Xianbang Sun
- Department of Biostatistics, Boston University, Boston, MA 02118, USA
| | - Roby Joehanes
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Tianxiao Huan
- Department of Ophthalmology and Visual Sciences, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
- Boston University’s and National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA 01702, USA
| | - Chunyu Liu
- Department of Biostatistics, Boston University, Boston, MA 02118, USA
- Boston University’s and National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA 01702, USA
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Zhang Z, Wang F, Xiao B, Ma J, Yang F. A new remote web-based MDSplus data visualization system for EAST. Fusion Engineering and Design 2023. [DOI: 10.1016/j.fusengdes.2022.113337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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103
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Zheng X, Zhang K, Ma J. The Longitudinal Relationship between Frailty, Loneliness and Cardiovascular Disease: A Prospective Cohort Study. J Nutr Health Aging 2023; 27:1212-1218. [PMID: 38151872 DOI: 10.1007/s12603-023-2037-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 10/25/2023] [Indexed: 12/29/2023]
Abstract
OBJECTIVES Previous studies had reported that frailty and loneliness were associated with increased risk of cardiovascular disease (CVD). The aim of present study was to evaluate the combined effect of frailty and loneliness on the risk of CVD. METHODS A total of 9,674 participants from the China Health and Retirement Longitudinal Study were included. Multivariate Cox proportional hazards regression model was used to explore the associations between frailty, loneliness and new-onset CVD, stroke and cardiac events. RESULTS During the 7-year follow-up, a total of 1,758 respondents experienced CVD (including 584 stroke and 1,324 cardiac events). Compared to those without loneliness or frailty, individuals with loneliness alone, or with frailty alone, or with both loneliness and frailty were significantly associated with increased risk of CVD, with corresponding HRs (95%CIs) were 1.21(1.07-1.37), 1.57(1.32-1.86) and 1.78(1.52-2.10), respectively. Similarly, participants with loneliness alone, or with frailty alone, or with both loneliness and frailty were associated with higher risk of cardiac events. The significant associations were consistent in age subgroups (participants aged less or more than 60 years). CONCLUSION Our study indicated that there was a combined effect of effect of frailty and loneliness on the risk of CVD, stroke and cardiac events. These findings highlighted the importance of identifying loneliness and frailty, and intervening much earlier both in older and younger population.
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Affiliation(s)
- X Zheng
- Jiawei Ma, MD, Department of Critical Care Medicine, Jiangnan University Medical Center, Wuxi, Jiangsu, 214122, China. E-mail:
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104
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Zhu Z, Yu P, Wu Y, Wu Y, Tan Z, Ling J, Ma J, Zhang J, Zhu W, Liu X. Sex Specific Global Burden of Osteoporosis in 204 Countries and Territories, from 1990 to 2030: An Age-Period-Cohort Modeling Study. J Nutr Health Aging 2023; 27:767-774. [PMID: 37754217 DOI: 10.1007/s12603-023-1971-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Accepted: 07/26/2023] [Indexed: 09/28/2023]
Abstract
BACKGROUND Osteoporosis is a highly prevalent disease with distinct sex pattern. We aimed to estimate the sex specific incidence, prevalence, and disability-adjusted life (DALYs) years of osteoporosis between 1990 and 2019, with additional predictions from 2020 to 2034. METHODS We collected osteoporosis disease burden data from the Global Burden of Disease study covering the years 1990 through 2019 in 204 countries and territories. The data included information on the number of incident cases of osteoporosis, DALYs, age-standardized incidence rates (ASIR), age-standardized prevalence rates (ASPR) and age-standardized DALYs rates. Additionally, we performed an age-period-cohort analysis to forecast the burden of osteoporosis. RESULTS The global number of incidence cases of osteoporosis, in 2019, reached 41.5 million cases. From 1990 to 2019, the low-middle socio-demographic index (SDI) region had the highest estimated annual percentage change in the world. Compared to males, female's ASIR and ASPR were all about 1.5 times higher than males for the same years in the same SDI regions. The projected global total number of incidence cases for osteoporosis between 2030 and 2034 is estimated to reach 263.2 million (154.4 million for females and 108.8 for males). Additionally, the burden in terms of DALYs is predicted to be 128.7 million (with 78.4 million for females and 50.3 million for males). CONCLUSION The global burden of osteoporosis is still increasing, mainly observed in high SDI countries. Females bear a burden 1.5 times higher than males in terms of incidence and DALYs. Steps should be taken to reduce the osteoporosis burden, especially in high SDI countries.
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Affiliation(s)
- Z Zhu
- Jing Zhang, Department of Anesthesiology, The Second Affiliated Hospital of Nanchang University, 1st Minde Road, Nanchang, Jiangxi, 330006, China, E-mail: ; Xiao Liu, Department of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, 510080, Guangdong, China, E-mail:
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105
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Chen L, Zhang Y, Chen MM, Ma T, Ma Q, Liu JY, Dong YH, Song Y, Ma J. [Prevalence of unhealthy lifestyle among children and adolescents of Han nationality in China]. Zhonghua Xin Xue Guan Bing Za Zhi 2022; 50:1177-1185. [PMID: 36517438 DOI: 10.3760/cma.j.cn112148-20220826-00648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Objective: To explore the epidemiological characteristics and geographical distribution of unhealthy lifestyle among children and adolescents of Han nationality in China and obtain evidence for proposing the related strategies to improve the well-being of this population. Methods: Students aged 6-22 years old were selected from the Chinese National Survey on Students Constitution and Health in 2019. The prevalence of unhealthy lifestyles (physical inactivity, lack of outdoor activity, sedentary behavior, excessive screen time, sleep insufficiency, unhealthy eating behavior) between sex, residence, and age groups was calculated and compared. Multilevel logistic regression was used to explore the influencing factors of unhealthy lifestyle. Results: The prevalence of moderate-to-vigorous physical activity less than 1 h/d or 30 min/d were 82.06% and 54.69%, respectively. The prevalence of less than 2 h/d or 3 h/d of outdoor activities were 95.20% and 83.26%, respectively. The prevalence of more than 2 h/d or 3 h/d of sitting time were 50.64% and 31.92%, respectively. The prevalence of more than 2 h/d or 3 h/d of screen time were 42.02% and 27.79%, respectively. The prevalence of sleep insufficiency, excessive sugary beverages consumption (≥ 1 time/d), and insufficient consumption of eggs, milk, and breakfast (<7 d/week) were 66.49%, 20.97%, 83.36%, 70.71%, and 34.34%, respectively. The prevalence of severe sleep insufficiency, excessive sugary beverages consumption (≥ 3 times/d), and insufficient consumption of eggs, milk, and breakfast (≤2 d/week) were 27.77%, 8.21%, 47.21%, 32.36% and 9.73%, respectively. Conclusion: In 2019, unhealthy lifestyle is common among Han students aged 6-22 years in China. It is of importance to propose policies to strengthen the health education and initiatives to support healthy behaviors in Han children and adolescents. Jointly promotion on the creation of a healthy environment for Han children and adolescents, and formulation of targeted improvement measures in accordance with the epidemic characteristics in various regions are essential to improve the healthy lifestyle of this population.
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Affiliation(s)
- L Chen
- School of Public Health & Institute of Child and Adolescent Health, Peking University, Beijing 100191, China
| | - Y Zhang
- School of Public Health & Institute of Child and Adolescent Health, Peking University, Beijing 100191, China
| | - M M Chen
- School of Public Health & Institute of Child and Adolescent Health, Peking University, Beijing 100191, China
| | - T Ma
- School of Public Health & Institute of Child and Adolescent Health, Peking University, Beijing 100191, China
| | - Q Ma
- School of Public Health & Institute of Child and Adolescent Health, Peking University, Beijing 100191, China
| | - J Y Liu
- School of Public Health & Institute of Child and Adolescent Health, Peking University, Beijing 100191, China
| | - Y H Dong
- School of Public Health & Institute of Child and Adolescent Health, Peking University, Beijing 100191, China
| | - Y Song
- School of Public Health & Institute of Child and Adolescent Health, Peking University, Beijing 100191, China
| | - J Ma
- School of Public Health & Institute of Child and Adolescent Health, Peking University, Beijing 100191, China
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106
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Han G, Bi J, Ma J, Yuan M, Li Y, Pi G, Li Y, Hu D. 146P Stereotactic body radiotherapy plus anlotinib ± toripalimab in untreated oligometastatic brain metastases NSCLC patients. Immuno-Oncology and Technology 2022. [DOI: 10.1016/j.iotech.2022.100258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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107
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Huang Y, Wang P, Luo Q, Ma J. Association of BST1 polymorphism with idiopathic restless legs syndrome in Chinese population. Sleep Med 2022. [DOI: 10.1016/j.sleep.2022.05.407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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108
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Lee M, Joehanes R, McCartney DL, Kho M, Hüls A, Wyss AB, Liu C, Walker RM, R Kardia SL, Wingo TS, Burkholder A, Ma J, Campbell A, Wingo AP, Huan T, Sikdar S, Keshawarz A, Bennett DA, Smith JA, Evans KL, Levy D, London SJ. Opioid medication use and blood DNA methylation: epigenome-wide association meta-analysis. Epigenomics 2022; 14:1479-1492. [PMID: 36700736 PMCID: PMC9979153 DOI: 10.2217/epi-2022-0353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 01/13/2023] [Indexed: 01/27/2023] Open
Abstract
Aim: To identify differential methylation related to prescribed opioid use. Methods: This study examined whether blood DNA methylation, measured using Illumina arrays, differs by recent opioid medication use in four population-based cohorts. We meta-analyzed results (282 users; 10,560 nonusers) using inverse-variance weighting. Results: Differential methylation (false discovery rate <0.05) was observed at six CpGs annotated to the following genes: KIAA0226, CPLX2, TDRP, RNF38, TTC23 and GPR179. Integrative epigenomic analyses linked implicated loci to regulatory elements in blood and/or brain. Additionally, 74 CpGs were differentially methylated in males or females. Methylation at significant CpGs correlated with gene expression in blood and/or brain. Conclusion: This study identified DNA methylation related to opioid medication use in general populations. The results could inform the development of blood methylation biomarkers of opioid use.
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Affiliation(s)
- Mikyeong Lee
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Roby Joehanes
- Department of Health and Human Services, Framingham Heart Study, National Heart, Lung, and Blood Institute, National Institutes of Health, Framingham, MA 01702, USA
| | - Daniel L McCartney
- Centre for Genomic & Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, UK
| | - Minjung Kho
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Anke Hüls
- Department of Epidemiology & Gangarosa, Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Annah B Wyss
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Chunyu Liu
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA 02215, USA
- Framingham Heart Study, Boston University, Framingham, MA 01702, USA
| | - Rosie M Walker
- Centre for Clinical Brain Science, Chancellor's Building, 49 Little France Crescent, Edinburgh Bioquarter, Edinburgh, UK
- School of Psychology, University of Exeter, Exeter, UK
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Thomas S Wingo
- Department of Neurology & Human Genetics, Emory University, Atlanta, GA 30322, USA
| | - Adam Burkholder
- Office of Environmental Science Cyberinfrastructure, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
| | - Jiantao Ma
- Department of Health and Human Services, Framingham Heart Study, National Heart, Lung, and Blood Institute, National Institutes of Health, Framingham, MA 01702, USA
| | - Archie Campbell
- Centre for Genomic & Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, UK
| | - Aliza P Wingo
- Department of Psychiatry & Behavioral Sciences, Emory University, Atlanta, GA 30322, USA
| | - Tianxiao Huan
- Department of Health and Human Services, Framingham Heart Study, National Heart, Lung, and Blood Institute, National Institutes of Health, Framingham, MA 01702, USA
- Department of Ophthalmology, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Sinjini Sikdar
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
- Department of Mathematics & Statistics, Old Dominion University, Norfolk, VA 23529, USA
| | - Amena Keshawarz
- Framingham Heart Study, Framingham, MA 01702, USA
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Kathryn L Evans
- Centre for Genomic & Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, UK
| | - Daniel Levy
- Department of Health and Human Services, Framingham Heart Study, National Heart, Lung, and Blood Institute, National Institutes of Health, Framingham, MA 01702, USA
| | - Stephanie J London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
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109
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Wang P, Huang Y, Ma J. Late-onset congenital central hypoventilation syndrome :a case with RET gene mutation. Sleep Med 2022. [DOI: 10.1016/j.sleep.2022.05.693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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110
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Huang Y, Wang P, Morales R, Luo Q, Ma J. Map2k5 deficient mice manifest phenotypes and pathological changes of dopamine deficiency in the central nervous system. Sleep Med 2022. [DOI: 10.1016/j.sleep.2022.05.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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111
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Saunders GRB, Wang X, Chen F, Jang SK, Liu M, Wang C, Gao S, Jiang Y, Khunsriraksakul C, Otto JM, Addison C, Akiyama M, Albert CM, Aliev F, Alonso A, Arnett DK, Ashley-Koch AE, Ashrani AA, Barnes KC, Barr RG, Bartz TM, Becker DM, Bielak LF, Benjamin EJ, Bis JC, Bjornsdottir G, Blangero J, Bleecker ER, Boardman JD, Boerwinkle E, Boomsma DI, Boorgula MP, Bowden DW, Brody JA, Cade BE, Chasman DI, Chavan S, Chen YDI, Chen Z, Cheng I, Cho MH, Choquet H, Cole JW, Cornelis MC, Cucca F, Curran JE, de Andrade M, Dick DM, Docherty AR, Duggirala R, Eaton CB, Ehringer MA, Esko T, Faul JD, Fernandes Silva L, Fiorillo E, Fornage M, Freedman BI, Gabrielsen ME, Garrett ME, Gharib SA, Gieger C, Gillespie N, Glahn DC, Gordon SD, Gu CC, Gu D, Gudbjartsson DF, Guo X, Haessler J, Hall ME, Haller T, Harris KM, He J, Herd P, Hewitt JK, Hickie I, Hidalgo B, Hokanson JE, Hopfer C, Hottenga J, Hou L, Huang H, Hung YJ, Hunter DJ, Hveem K, Hwang SJ, Hwu CM, Iacono W, Irvin MR, Jee YH, Johnson EO, Joo YY, Jorgenson E, Justice AE, Kamatani Y, Kaplan RC, Kaprio J, Kardia SLR, Keller MC, Kelly TN, Kooperberg C, Korhonen T, Kraft P, Krauter K, Kuusisto J, Laakso M, Lasky-Su J, Lee WJ, Lee JJ, Levy D, Li L, Li K, Li Y, Lin K, Lind PA, Liu C, Lloyd-Jones DM, Lutz SM, Ma J, Mägi R, Manichaikul A, Martin NG, Mathur R, Matoba N, McArdle PF, McGue M, McQueen MB, Medland SE, Metspalu A, Meyers DA, Millwood IY, Mitchell BD, Mohlke KL, Moll M, Montasser ME, Morrison AC, Mulas A, Nielsen JB, North KE, Oelsner EC, Okada Y, Orrù V, Palmer ND, Palviainen T, Pandit A, Park SL, Peters U, Peters A, Peyser PA, Polderman TJC, Rafaels N, Redline S, Reed RM, Reiner AP, Rice JP, Rich SS, Richmond NE, Roan C, Rotter JI, Rueschman MN, Runarsdottir V, Saccone NL, Schwartz DA, Shadyab AH, Shi J, Shringarpure SS, Sicinski K, Skogholt AH, Smith JA, Smith NL, Sotoodehnia N, Stallings MC, Stefansson H, Stefansson K, Stitzel JA, Sun X, Syed M, Tal-Singer R, Taylor AE, Taylor KD, Telen MJ, Thai KK, Tiwari H, Turman C, Tyrfingsson T, Wall TL, Walters RG, Weir DR, Weiss ST, White WB, Whitfield JB, Wiggins KL, Willemsen G, Willer CJ, Winsvold BS, Xu H, Yanek LR, Yin J, Young KL, Young KA, Yu B, Zhao W, Zhou W, Zöllner S, Zuccolo L, Batini C, Bergen AW, Bierut LJ, David SP, Gagliano Taliun SA, Hancock DB, Jiang B, Munafò MR, Thorgeirsson TE, Liu DJ, Vrieze S. Genetic diversity fuels gene discovery for tobacco and alcohol use. Nature 2022; 612:720-724. [PMID: 36477530 PMCID: PMC9771818 DOI: 10.1038/s41586-022-05477-4] [Citation(s) in RCA: 84] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 10/25/2022] [Indexed: 12/12/2022]
Abstract
Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.
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Affiliation(s)
| | - Xingyan Wang
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Fang Chen
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Seon-Kyeong Jang
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Mengzhen Liu
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Chen Wang
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Shuang Gao
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Yu Jiang
- Department of Epidemiology & Population Health at Stanford University, Stanford, CA, USA
| | | | - Jacqueline M Otto
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Clifton Addison
- Jackson Heart Study (JHS) Graduate Training and Education Center (GTEC), Department of Epidemiology and Biostatistics, School of Public Health, Jackson State University, Jackson, MS, USA
| | - Masato Akiyama
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Ocular Pathology and Imaging Science, Kyushu University Graduate School of Medical Sciences, Fukuoka, Japan
| | - Christine M Albert
- Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Fazil Aliev
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, USA
| | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Donna K Arnett
- Dean's Office and Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Allison E Ashley-Koch
- Department of Medicine and Duke Comprehensive Sickle Cell Center, Duke University School of Medicine, Durham, NC, USA
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, USA
| | - Aneel A Ashrani
- Division of Hematology, Department of Medicine, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - Kathleen C Barnes
- Division of Biomedical Informatics & Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Tempus, Chicago, IL, USA
| | - R Graham Barr
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Diane M Becker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Emelia J Benjamin
- Department of Medicine, Boston Medical Center, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | | | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | | | - Jason D Boardman
- Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Dorret I Boomsma
- Netherlands Twin Register, Dept Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Meher Preethi Boorgula
- Division of Biomedical Informatics & Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Brian E Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Sameer Chavan
- Division of Biomedical Informatics & Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Cheng
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Hélène Choquet
- Kaiser Permanente Northern California (KPNC), Division of Research, Oakland, CA, USA
| | - John W Cole
- Department of Neurology, Baltimore Veterans Affairs Medical Center, Baltimore, MD, USA
- Division of Vascular Neurology, Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Marilyn C Cornelis
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Mariza de Andrade
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - Danielle M Dick
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, USA
| | - Anna R Docherty
- Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, USA
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Virginia, USA
- Huntsman Mental Health Institute, Salt Lake City, UT, USA
| | - Ravindranath Duggirala
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Charles B Eaton
- Department of Family Medicine, Brown University, Providence, RI, USA
| | - Marissa A Ehringer
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA
| | - Tõnu Esko
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Lilian Fernandes Silva
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Edoardo Fiorillo
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Italy
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Barry I Freedman
- Department of Internal Medicine-Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Maiken E Gabrielsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Melanie E Garrett
- Department of Medicine and Duke Comprehensive Sickle Cell Center, Duke University School of Medicine, Durham, NC, USA
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, USA
| | - Sina A Gharib
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, University of Washington, Seattle, WA, USA
- Center for Lung Biology, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Nathan Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Virginia, USA
| | - David C Glahn
- Department of Psychiatry & Behavioral Sciences, Boston Children's Hospital & Harvard Medical School, Boston, MA, USA
| | - Scott D Gordon
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Charles C Gu
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Dongfeng Gu
- Department of Epidemiology and Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jeffrey Haessler
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Michael E Hall
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Toomas Haller
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Kathleen Mullan Harris
- Department of Sociology and the Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
| | - Jiang He
- Department of Epidemiology, Tulane University, New Orleans, LA, USA
- Translational Sciences Institute, Tulane University, New Orleans, LA, USA
| | - Pamela Herd
- McCourt School of Public Policy, Georgetown University, Washington, DC, USA
| | - John K Hewitt
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Department Of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Ian Hickie
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Bertha Hidalgo
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - John E Hokanson
- Department of Epidemiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Christian Hopfer
- Department of Psychiatry, University of Colorado Anschutz Medical Center, Denver, CO, USA
| | - JoukeJan Hottenga
- Netherlands Twin Register, Dept Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Hongyan Huang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yi-Jen Hung
- Institute of Preventive Medicine, National Defense Medical Center, New Taipei City, Taiwan
| | - David J Hunter
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Center, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Research, Innovation and Education, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Shih-Jen Hwang
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Chii-Min Hwu
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
| | - William Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Yon Ho Jee
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Eric O Johnson
- GenOmics, Bioinformatics, and Translational Research Center, RTI International, Research Triangle Park, NC, USA
- Fellow Program, RTI International, Research Triangle Park, NC, USA
| | - Yoonjung Y Joo
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Institute of Data Science, Korea University, Seoul, South Korea
| | | | - Anne E Justice
- Department of Population Health Sciences, Geisinger, Danville, PA, USA
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yoichiro Kamatani
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Robert C Kaplan
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland - FIMM, University of Helsinki, Helsinki, Finland
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Matthew C Keller
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Department Of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Tanika N Kelly
- Department of Epidemiology, Tulane University, New Orleans, LA, USA
- Translational Sciences Institute, Tulane University, New Orleans, LA, USA
| | - Charles Kooperberg
- Department of Biostatistics, University of Washington, Seattle, WA, USA
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Tellervo Korhonen
- Institute for Molecular Medicine Finland - FIMM, University of Helsinki, Helsinki, Finland
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Kenneth Krauter
- Department of Molecular, Cellular and Developmental Biology, University of Colorado, Boulder, CO, USA
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
- Center for Medicine and Clinical Research, Kuopio University Hospital, Kuopio, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Jessica Lasky-Su
- Brigham and Women's Hospital, Department of Medicine, Channing Division of Network Medicine, Boston, MA, USA
| | - Wen-Jane Lee
- Department of Medical Research, Taichung Veterans General Hospital, Taichung City, Taiwan
| | - James J Lee
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Kevin Li
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Yuqing Li
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA
| | - Kuang Lin
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Penelope A Lind
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, Australia
- School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Donald M Lloyd-Jones
- Departments of Preventive Medicine, Medicine, and Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Sharon M Lutz
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Department of Biostatics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jiantao Ma
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Division of Nutrition Epidemiology and Data Science, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Reedik Mägi
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA
| | - Ani Manichaikul
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Ravi Mathur
- GenOmics, Bioinformatics, and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Nana Matoba
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Genetics, UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Patrick F McArdle
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Matthew B McQueen
- Department of Integrative Physiology, University of Colorado, Boulder, CO, USA
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | | | | | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Braxton D Mitchell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Matthew Moll
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - May E Montasser
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Antonella Mulas
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Italy
| | - Jonas B Nielsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Elizabeth C Oelsner
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Yukinori Okada
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
| | - Valeria Orrù
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Italy
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland - FIMM, University of Helsinki, Helsinki, Finland
| | - Anita Pandit
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - S Lani Park
- Population Sciences of the Pacific Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig Maximilians University Munich, Munich, Germany
- German Centre for Cardiovascular Research, DZHK, Partner Site Munich, Munich, Germany
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Tinca J C Polderman
- Department of Clinical Developmental Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- Department of Child and Adolescent Psychiatry, Amsterdam UMC, Amsterdam, The Netherlands
| | - Nicholas Rafaels
- Division of Biomedical Informatics & Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Robert M Reed
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alex P Reiner
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - John P Rice
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Nicole E Richmond
- Department of Epidemiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Carol Roan
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Michael N Rueschman
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Nancy L Saccone
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - David A Schwartz
- Division of Pulmonary Sciences and Critical Care Medicine; Department of Medicine and Immunology, University of Colorado, Aurora, CO, USA
| | - Aladdin H Shadyab
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, USA
| | | | | | - Kamil Sicinski
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI, USA
| | - Anne Heidi Skogholt
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas L Smith
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, USA
- Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, WA, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Division of Cardiology, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Michael C Stallings
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Department Of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | | | - Kari Stefansson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Jerry A Stitzel
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
| | - Xiao Sun
- Department of Epidemiology, Tulane University, New Orleans, LA, USA
| | - Moin Syed
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | | | - Amy E Taylor
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, UK
- National Institute for Health Research Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Marilyn J Telen
- Department of Medicine and Duke Comprehensive Sickle Cell Center, Duke University School of Medicine, Durham, NC, USA
| | - Khanh K Thai
- Kaiser Permanente Northern California (KPNC), Division of Research, Oakland, CA, USA
| | - Hemant Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Constance Turman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Tamara L Wall
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Scott T Weiss
- Brigham and Women's Hospital, Department of Medicine, Channing Division of Network Medicine, Boston, MA, USA
| | - Wendy B White
- Jackson Heart Study Undergraduate Training and Education Center, Tougaloo College, Tougaloo, MS, USA
| | - John B Whitfield
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Kerri L Wiggins
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Gonneke Willemsen
- Netherlands Twin Register, Dept Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Cristen J Willer
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Bendik S Winsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Huichun Xu
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Lisa R Yanek
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jie Yin
- Kaiser Permanente Northern California (KPNC), Division of Research, Oakland, CA, USA
| | - Kristin L Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kendra A Young
- Department of Epidemiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Bing Yu
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Wei Zhou
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Sebastian Zöllner
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Luisa Zuccolo
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Health Data Science Centre, Fondazione Human Technopole, Milan, Italy
| | - Chiara Batini
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Andrew W Bergen
- Oregon Research Institute, Springfield, OR, USA
- BioRealm, LLC, Walnut, CA, USA
| | - Laura J Bierut
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Sean P David
- Outcomes Research Network & Department of Family Medicine, NorthShore University HealthSystem, Evanston, IL, USA
- Department of Family Medicine, University of Chicago, Chicago, IL, USA
| | - Sarah A Gagliano Taliun
- Department of Medicine, Université de Montréal, Montréal, Québec, Canada
- Department of Neurosciences, Université de Montréal, Montréal, Québec, Canada
- Research Centre, Montréal Heart Institute, Montréal, Québec, Canada
| | - Dana B Hancock
- GenOmics, Bioinformatics, and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Bibo Jiang
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Marcus R Munafò
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, UK
- National Institute for Health Research Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | | | - Dajiang J Liu
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA.
| | - Scott Vrieze
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA.
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Wang L, Zhao YB, Ding JG, Han JJ, Ma YY, Wu X, Wang TH, Ma J, Zhang ZY, Li ZD, Bu XQ, Su AW, Wu A. [Enterostomy based on abdominal wall tension and fascial locking: a theory of preventing stoma complications and parahernia]. Zhonghua Wei Chang Wai Ke Za Zhi 2022; 25:1025-1028. [PMID: 36396379 DOI: 10.3760/cma.j.cn441530-20220307-00088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
No consensus on standardized technique of enterostomy creation has been made meanwhile high heterogeneity of surgical procedure exists in 'stoma creation' chapters of textbooks or atlases of colorectal surgery. The present article reviews the anatomy of tendinous aponeurotic fibers which is crucial for abdominal wall tension and integrity. Through empirical practice we hypothesize a procedure of enterostomy creation basied on abdominal wall tension plus anchor suture for fascia fixation which could theoretically decrease short-term stoma complication rates and long-term parastomal hernia rates. Surgical techniques are as followed: (1) preoperative stoma site mark for de-functioning ileostomy should be positioned at the lateral border of rectus abdominis muscle (RAM) to decrease the difficulty of stoma reversal and for permanent colostomy should be placed overlying the RAM to promote adhesion; (2)Optimal circular removal or lineal opening of skin, and avoid dissection of subcutaneous tissue; (3) Lineal dissection of natural strong fascia (rectus sheath) at stoma site and blunt separation of muscular fibers. The tunnel of the fascia should be made with appropriate size without undue tension. To prevent the formation of dead space, additional suturing at fascia layer is unnecessary. (4) Anchor suture for fascia fixation at two ends of fascia opening could be considered to avoid delayed fascia disruption and parastomal hernia. (5) After pull-through of ileum or colon loop, 4-8 interrupted seromuscular sutures could be placed to attach loop to skin. For ileostomy, self-eversion of mucosa can be successful in vast majority of cases and a Brooke ileostomy is not necessary. The efficacy and safety of this procedure should be tested in future trials.
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Affiliation(s)
- L Wang
- Gastrointestinal Cancer Center, Unit III, Peking University Cancer Hospital &Institute, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Beijing 100142, China
| | - Y B Zhao
- Department of General Surgery, the Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou 450008, China
| | - J G Ding
- Department of General Surgery, The First Affiliated Hospital, Nanjing Medical University, Nanjing 210029, China
| | - J J Han
- Department of General Surgery, Beijing Chaoyang Hosptial, Capital Medical University, Beijing 100020, China
| | - Y Y Ma
- Department of General Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine/Shanghai Clinical Medical Center for Minimally Invasive Surgery, Shanghai 200025, China
| | - X Wu
- Department of Gastrointestinal Surgery, Second Affiliated Hospital of Soochow University, Suzhou 215004, China
| | - T H Wang
- Department of General Surgery, Peking University First Hospital, Beijing 100034, China
| | - J Ma
- Department of Colorectal Surgery, Division of Radiation Enterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China
| | - Z Y Zhang
- Gastrointestinal Cancer Center, Unit III, Peking University Cancer Hospital &Institute, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Beijing 100142, China
| | - Z D Li
- Gastrointestinal Cancer Center, Unit III, Peking University Cancer Hospital &Institute, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Beijing 100142, China
| | - X Q Bu
- Gastrointestinal Cancer Center, Unit III, Peking University Cancer Hospital &Institute, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Beijing 100142, China
| | - A W Su
- Gastrointestinal Cancer Center, Unit III, Peking University Cancer Hospital &Institute, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Beijing 100142, China
| | - Aiwen Wu
- Gastrointestinal Cancer Center, Unit III, Peking University Cancer Hospital &Institute, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Beijing 100142, China
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Zhou XQ, Ma J, Wang RY, Wang RH, Wu YQ, Yang XY, Chen YJ, Tang XN, Sun ET. [Bacterial community diversity in Dermatophagoides farinae using high-throughput sequencing]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2022; 34:630-634. [PMID: 36642905 DOI: 10.16250/j.32.1374.2022105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
OBJECTIVE To investigate the bacterial community diversity in Dermatophagoides farinae. METHODS Laboratory-cultured D. farinae was collected, and the composition of microbial communities was determined by sequence analyses of the V4 region in the bacterial 16S ribosomal RNA (16S rRNA) gene on an Illumina PE250 high-throughput sequencing platform. Following quality control and filtering of the raw sequence files, valid reads were obtained and subjected to operational taxonomic units (OTU) clustering and analysis of the composition of microbial communities and alpha diversity index using the Usearch software, Silva database, and Mothur software. RESULTS A total of 187 616 valid reads were obtained, and 469 OTUs were clustered based on a sequence similarity of more than 97%. OTU annotation showed that the bacteria in D. farinae belonged to 26 phyla, 43 classes, 100 orders, 167 families and 284 genera. The bacteria in D. farinae were mainly annotated to five phyla of Proteobacteria, Firmicutes, Bacteroidota, Actinobacteriota, and Acidobacteriota, with Proteobacteria as the dominant phylum, and mainly annotated to five dominant genera of Ralstonia, norank-f-Mitochondria, Staphylococcus and Sphingomonas, with Wolbachia identified in the non-dominant genus. CONCLUSIONS A high diversity is identified in the composition of the bacterial community in D. farinae, and there are differences in bacterial community diversity and abundance among D. farinae.
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Affiliation(s)
- X Q Zhou
- Department of Medical Parasitology, Wannan Medical College, Wuhu, Anhui 241002, China
| | - J Ma
- Department of Health Inspection and Quarantine, Wannan Medical College, Wuhu, Anhui 241002, China
| | - R Y Wang
- Department of Environmental Hygiene and Occupational Health, School of Public Health, Wannan Medical College, China
| | - R H Wang
- Department of Health Inspection and Quarantine, Wannan Medical College, Wuhu, Anhui 241002, China
| | - Y Q Wu
- Department of Health Inspection and Quarantine, Wannan Medical College, Wuhu, Anhui 241002, China
| | - X Y Yang
- Department of Health Inspection and Quarantine, Wannan Medical College, Wuhu, Anhui 241002, China
| | - Y J Chen
- Department of Environmental Hygiene and Occupational Health, School of Public Health, Wannan Medical College, China
| | - X N Tang
- Department of Medical Parasitology, Wannan Medical College, Wuhu, Anhui 241002, China
| | - E T Sun
- Department of Health Inspection and Quarantine, Wannan Medical College, Wuhu, Anhui 241002, China
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Zhu XJ, Ma JY, Chen ZP, Xie XJ, Zhang JL, Ma J, Yao JF, Zhang LQ, Wu RH. [Comparison of the efficacy and safety of 2 low-dose rituximab regimens in the second-line treatment of primary immune thrombocytopenia in children]. Zhonghua Er Ke Za Zhi 2022; 60:1185-1190. [PMID: 36319155 DOI: 10.3760/cma.j.cn112140-20220418-00340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Objective: To compare the efficacy and safety of 2 low-dose rituximab regimens in the treatment of children with primary immune thrombocytopenia (ITP). Methods: A total of 90 ITP children admitted to the Hematology Oncology Center of Beijing Children's Hospital from January 2018 to March 2021 were enrolled in this prospective cohort study. In the single-dose group, rituximab was given with a single dose of 375 mg/m2 (maximum dose 600 mg). In the 4-dose group, rituximab was given with a dose of 100 mg weekly (if body weight of the patient ≥ 30 kg, increase dosage to 200 mg weekly) for 4 weeks. Wilcoxon Mann-Whitney test, Chi-square test and Fisher's exact test were used to analyze the difference in efficacy, safety and treatment burden between two groups. Results: Among the 90 children, 41 were male and 49 were female, and the age of medication was 6.8 (4.1,10.0) years. There were 27 cases in the single-dose group and 63 cases in the 4-dose group.There were no significant differences in overall response rate, complete response rate and partial response rate between the single-dose group and 4-dose group (41% (11/27) vs. 33% (21/63), 26% (7/27) vs. 19% (12/63), 15% (4/27) vs. 14%(9/63), χ2=0.45, 0.54, 0.00, all P>0.05). The single-dose group was earlier to get overall response than the 4-dose group (1 (1, 1) vs. 3 (2, 6) weeks, Z=-3.24, P=0.001). There were no significant differences in the sustained response rate, the overall response rate in 1 year, the complete response rate in 1 year, and the partial response rate in 1 year between the single-dose group and the 4-dose group (33% (9/27) vs. 30% (19/63), 30% (8/27) vs. 24% (15/63), 19% (5/27) vs. 14% (9/63), 11% (3/27) vs. 10% (6/63), χ2=0.09, 0.34, 0.04, 0.00, all P>0.05). There were no significant differences in the duration of overall response, recurrence rate within half a year and one year, recurrence time and rate of adverse events between the single-dose group and 4-dose group (all P>0.05). The number of hospitalizations, the duration of hospital stays and the dosage of the single-dose group were significantly lower than those of the 4-dose group (1 (1, 1) vs. 4 (4, 4) times, 5 (4, 7) vs. 8 (5, 8) d, 400 (250, 500) vs. 400 (400, 800) mg, Z=-8.67, -3.03, -4.05, all P<0.05). Conclusions: The single-dose rituximab regimen is comparable to 4-dose rituximab regimen in effectiveness and safety for treatment of children ITP, but more economical and convenient. The single-dose rituximab regimen is more suitable for the second-line treatment of children ITP.
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Affiliation(s)
- X J Zhu
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing Key Laboratory of Pediatric Hematology Oncology, National Key Discipline of Pediatrics, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing 100045, China
| | - J Y Ma
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing Key Laboratory of Pediatric Hematology Oncology, National Key Discipline of Pediatrics, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing 100045, China
| | - Z P Chen
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Hematologic Disease Laboratory, Beijing Pediatric Research Institute, Beijing 100045, China
| | - X J Xie
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing Key Laboratory of Pediatric Hematology Oncology, National Key Discipline of Pediatrics, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing 100045, China
| | - J L Zhang
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing Key Laboratory of Pediatric Hematology Oncology, National Key Discipline of Pediatrics, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing 100045, China
| | - J Ma
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing Key Laboratory of Pediatric Hematology Oncology, National Key Discipline of Pediatrics, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing 100045, China
| | - J F Yao
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing Key Laboratory of Pediatric Hematology Oncology, National Key Discipline of Pediatrics, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing 100045, China
| | - L Q Zhang
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing Key Laboratory of Pediatric Hematology Oncology, National Key Discipline of Pediatrics, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing 100045, China
| | - R H Wu
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing Key Laboratory of Pediatric Hematology Oncology, National Key Discipline of Pediatrics, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing 100045, China
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Sun H, Wang Q, Wang Y, Zhang Y, Zhang W, Shen W, Zhao L, Ge X, Yang N, Tan B, Su X, Ma J, Wang F, Dong W, Zhang J, Sun D, Liu T, Zhang Q, Li B, Huang W. Treatment Strategies for Limited-Stage Primary Small Cell Carcinoma of the Esophagus: A Multicenter Retrospective Trial from China. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
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Hobbis D, Yaddanapudi S, Brooks J, Pafundi D, Jackson A, Tryggestad E, Moseley D, Routman D, Stish B, Lucido J, Ma J, Fatyga M, Anand A, Rong Y, Foote R, Patel S. Comparisons of Clinical and Reference Standard Contours to AI Auto-Segmentation: An Evaluation of 5 Commercial Models in Head and Neck Organ at Risk Delineation. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.888] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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117
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Mao Y, Wang S, Gao T, Zhang N, Liang X, Tang L, Zhou G, Guo R, Zhang Y, Chen L, Luo W, Li Y, Liang S, Lin L, Li W, Liu X, Xu C, Lv J, Liu L, Li J, Xie F, Sun Y, Ma J. Sparing Irradiation vs. Conventional Irradiation to the Medial Retropharyngeal Space in Patients with Nasopharyngeal Carcinoma: An Open-Label, Non-Inferiority, Multicenter, Randomized Phase III Trial. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Prezelski K, Hsu D, del Balzo L, Ma J, Pike L, Ballangrud A, Aristophanous M. Artificial Intelligence-Driven Measurement of Brain Metastases' SRS Response – A Comparison with Current Standards for Assessment. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Li J, Liu N, Ma J. Tumor Cell-Intrinsic E3 Ligase TRIM21 Restrains Radiation-Induced Antitumor Immunity by Decreasing Mitochondrial DNA Release from VDAC2 Oligomers. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.2082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Ma J, Guo R, Lin J, Xu C, Li J, Wu Y, Zhang X, Tang L, Sun Y. Long-Term Outcome Following Intensity-Modulated Radiotherapy Delivered Using Individualized Clinical Target Volume Delineation Based on Stepwise Spread Pattern of Nasopharyngeal Carcinoma. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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121
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Ma J, Yu H, Gelblum D, Kroen E, Shaverdian N, Tsai C, Yang J, Rimner A, Huang J, Gomez D. Factors Associated with Outcomes in Patients with Metastatic NSCLC Receiving Osimertinib and Consolidative Radiation Therapy. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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122
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Tian Y, Ma J, Zhu H, Yu J. Outcomes of First-Line Anti-PD-L1 Blockades Combined with Brain Radiotherapy (BRT) for Extensive-Stage Small-Cell Lung Cancer (ES-SCLC) with Brain Metastases (BM). Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
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Park WY, Yiannakou I, Petersen JM, Hoffmann U, Ma J, Long MT. Sugar-Sweetened Beverage, Diet Soda, and Nonalcoholic Fatty Liver Disease Over 6 Years: The Framingham Heart Study. Clin Gastroenterol Hepatol 2022; 20:2524-2532.e2. [PMID: 34752964 PMCID: PMC9236136 DOI: 10.1016/j.cgh.2021.11.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 10/22/2021] [Accepted: 11/01/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND & AIMS Nonalcoholic fatty liver disease (NAFLD) is associated with sugar-sweetened beverage (SSB) consumption in cross-sectional studies. In a prospective cohort, we examined the association of beverage consumption (SSB and diet soda) with incident NAFLD and changes in hepatic fat in the Framingham Heart Study (FHS). METHODS We conducted a prospective observational study of participants from the FHS Third Generation and Offspring cohorts who participated in computed tomography sub-studies. Participants were classified according to their average SSB or diet soda consumption, which was derived from baseline and follow-up food frequency questionnaires: non-consumers (0-<1/month), occasional consumers (1/month-<1/week), and frequent consumers (≥1/week-≥1/day). Hepatic fat was quantified by the liver fat attenuation measurements on computed tomography scan. The primary dependent variable was incident NAFLD; secondarily, we investigated change in liver fat. RESULTS The cohorts included 691 Offspring (mean age, 62.8 ± 8.2 years; 57.7% women) and 945 Third Generation participants (mean age, 48.4 ± 6.3 years; 46.6% women). In the Offspring cohort, there was a dose-response relationship with SSB consumption and incident NAFLD. Frequent SSB consumers had 2.53 times increased odds of incident NAFLD compared with non-consumers (95% confidence interval, 1.36-4.7) after multivariable analysis. For Offspring cohort participants, occasional and frequent consumers of SSB had a more adverse increase in liver fat compared with non-consumers. CONCLUSIONS Higher average SSB intake is associated with increase in liver fat over 6 years of follow-up and increased odds of incident NAFLD especially among the older cohort, whereas no consistent association was observed for the younger Third Generation cohort.
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Affiliation(s)
- William Y Park
- Department of Medicine, Boston Medical Center, Boston University School of Medicine, Boston
| | - Ioanna Yiannakou
- Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston; PhD in Biomedical Science, Nutrition and Metabolism, Boston University School of Medicine, Boston
| | - Julie M Petersen
- Department of Epidemiology, Boston University School of Public Health, Boston
| | - Udo Hoffmann
- Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Jiantao Ma
- National Heart, Lung, and Blood Institute's Framingham Heart Study and Population Sciences Branch, Framingham
| | - Michelle T Long
- Department of Medicine, Boston Medical Center, Boston University School of Medicine, Boston; Section of Gastroenterology, Boston Medical Center, Boston University School of Medicine, Boston, Massachusetts.
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Li X, Ma J, Liu S, Huang P, Chen B, Wei D, Liu J. Efficient second harmonic generation by harnessing bound states in the continuum in semi-nonlinear etchless lithium niobate waveguides. Light Sci Appl 2022; 11:317. [PMID: 36316306 PMCID: PMC9622896 DOI: 10.1038/s41377-022-01017-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 10/08/2022] [Accepted: 10/12/2022] [Indexed: 05/16/2023]
Abstract
Integrated photonics provides unprecedented opportunities to pursue advanced nonlinear light sources with low-power consumptions and small footprints in a scalable manner, such as microcombs, chip-scale optical parametric oscillators and integrated quantum light sources. Among a variety of nonlinear optical processes, high-efficiency second harmonic generation (SHG) on-chip is particularly appealing and yet challenging. In this work, we present efficient SHG in highly engineerable semi-nonlinear waveguides consisting of electron-beam resist waveguides and thin-film silicon nitride (SiN)/lithium niobate (LN). By carefully designing octave-separating bound states in the continuum (BICs) for the nonlinear interacting waves in such a hybrid structure, we have simultaneously optimized the losses for both fundamental frequency (FF) and second harmonic (SH) waves and achieved modal phasing matching and maximized the nonlinear modal overlap between the FF and SH waves, which results in an experimental conversion efficiency up to 4.05% W-1cm-2. Our work provides a versatile and fabrication-friendly platform to explore on-chip nonlinear optical processes with high efficiency in the context of nanophotonics and quantum optics.
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Affiliation(s)
- Xueshi Li
- State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics, Sun Yat-Sen University, 510275, Guangzhou, China
| | - Jiantao Ma
- State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics, Sun Yat-Sen University, 510275, Guangzhou, China
| | - Shunfa Liu
- State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics, Sun Yat-Sen University, 510275, Guangzhou, China
| | - Peinian Huang
- State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics, Sun Yat-Sen University, 510275, Guangzhou, China
| | - Bo Chen
- State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics, Sun Yat-Sen University, 510275, Guangzhou, China
| | - Dunzhao Wei
- State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics, Sun Yat-Sen University, 510275, Guangzhou, China.
| | - Jin Liu
- State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics, Sun Yat-Sen University, 510275, Guangzhou, China.
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Tian YX, Guo X, Ma J, Liu QY, Li SJ, Wu YH, Zhao WH, Ma SY, Chen HY, Guo F. Characterization of biochar-derived organic matter extracted with solvents of differing polarity via ultrahigh-resolution mass spectrometry. Chemosphere 2022; 307:135785. [PMID: 35870614 DOI: 10.1016/j.chemosphere.2022.135785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 06/10/2022] [Accepted: 07/17/2022] [Indexed: 06/15/2023]
Abstract
In recent years, biochar, a porous carbon-based material, has gained attention for its application prospects in contaminated soil remediation and soil improvement. Biochar-derived organic matter has a key role in influencing the migration and transformation of soil elements and pollutants. However, existing research concerning the molecular characteristics of biochar-derived organic matter is limited. Here, we used four polar solvents - dichloromethane (CH2Cl2), acetone (CH3COCH3), methanol (CH3OH), and distilled water (H2O) - to extract organic matter from soybean straw biochar and wheat straw biochar by accelerated solvent extraction (ASE). We characterized the extracts using Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). We found considerable differences in organic matter according to the extraction solvents; such differences were related to the polarity of the solvent, as well as intermolecular forces between the solvent and organic matter. CH3OH extracted the most biochar-extractable organic matter components because CH3OH can weaken or destroy oxygen bridge bonds in biochar and form hydrogen bonds with small-molecule organic compounds. CH3OH and H2O have strong extraction capacity for compounds containing heteroatoms. CH2Cl2-extractable organic matter is relatively labile and bioavailable, while CH3OH- and H2O-extractable organic matters are relatively stable. In addition, the binding capacity of biochar-derived organic matter for minerals and pollutants differed among fractions, in part because of differences in molecular weight, atomic O/C and H/C ratios, heteroatom distribution, and biomolecular compounds present in biochar-derived organic matter. The findings in this study help to select appropriate extractants to analyze biochar-derived organic matter for various research purposes, and provides a theoretical basis for biochar-based remediation of contaminated soil.
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Affiliation(s)
- Y X Tian
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - X Guo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; School of Environmental, Liaoning University, Shenyang, 110036, China
| | - J Ma
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Q Y Liu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; School of Earth Science and Engineering, Sun Yat-Sen University, Guangzhou, 510275, China
| | - S J Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; School of Environmental, Liaoning University, Shenyang, 110036, China
| | - Y H Wu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - W H Zhao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - S Y Ma
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; College of Environmental and Resource Sciences, Shan Xi University, Shan Xi, 030006, China
| | - H Y Chen
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
| | - F Guo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
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Ma T, Li YH, Chen MM, Ma Y, Gao D, Chen L, Ma Q, Zhang Y, Liu JY, Wang XX, Dong YH, Ma J. [Associations between early onset of puberty and obesity types in children: Based on both the cross-sectional study and cohort study]. Beijing Da Xue Xue Bao Yi Xue Ban 2022; 54. [PMID: 36241240 PMCID: PMC9568395 DOI: 10.19723/j.issn.1671-167x.2022.05.025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
OBJECTIVE To explore and analyze the relationship between early onset of puberty and different types of obesity in children, by combining large sample cross-sectional survey data with long-term longitudinal cohort data, so as to provide clues for further clarifying the health hazards of early onset of puberty and obesity prevention and control. METHODS The research data were from the cross-sectional survey data of seven provinces(autonomous regions, municipalities) in China and the cohort data of adolescent development in Xiamen. The study first found the association between early onset of puberty and obesity by Logistic regression on the cross-sectional data, and then used Poisson regression to analyze the association between early puberty initiation and various types of obesity risk. RESULTS In the study, 43 137 and 1 266 children were included in the cross-sectional survey and cohort survey respectively. The cross-sectional study found that among the girls aged 10-13 years, compared with the girls of the same age who did not start puberty, the body mass index (BMI)-Z score of the girls in the puberty start group was 0.5-0.8 higher, and the waist circumference Z score was 0.4-0.7 higher, and the risk of various types of obesity was higher. At the same time, the early onset of puberty was positively correlated with simple obesity, central obesity and compound obesity, the OR (95%CI) were 1.86 (1.42-2.44), 1.95 (1.65-2.32) and 1.86 (1.41-2.45), respectively. No significant association was found in boys. According to the cohort data, in girls, the risk of simple obesity was 6.00 times [RR (95%CI): 6.00 (1.07-33.60)], the risk of central obesity was 3.30 times [RR (95%CI): 3.30 (1.22-8.92)], and the risk of compound obesity was 5.76 times [RR (95%CI): 5.76 (1.03-32.30)], compared with the group without early puberty initiation, while no association between early puberty initiation and obesity was found in boys. CONCLUSION Based on the cross-sectional survey and longitudinal cohort survey, it is confirmed that the early onset of puberty in girls may increase the risk of simple obesity, central obesity and compound obesity, while there is no significant correlation between puberty onset and obesity in boys.
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Affiliation(s)
- T Ma
- Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - Y H Li
- Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - M M Chen
- Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - Y Ma
- Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - D Gao
- Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - L Chen
- Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - Q Ma
- Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - Y Zhang
- Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - J Y Liu
- Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - X X Wang
- School of Public Health and Management, Ningxia Medical University, Yinchuan 750004, China
| | - Y H Dong
- Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - J Ma
- Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
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Ma J, Nandalike K, Jhawar S, Kamerman-Kretzmer R, Shi Y. 38 Cutaneous rash with elexacaftor/tezacaftor/ivacaftor in children with cystic fibrosis. J Cyst Fibros 2022. [DOI: 10.1016/s1569-1993(22)00729-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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128
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Ai D, Chen ZP, Li G, Yao JF, Ma JY, Ma J, Zhang LQ, Jiang J, Wu RH. [Three cases of von Willebrand type 2B in children]. Zhonghua Er Ke Za Zhi 2022; 60:943-945. [PMID: 36038307 DOI: 10.3760/cma.j.cn112140-20220220-00133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Affiliation(s)
- D Ai
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Z P Chen
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - G Li
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - J F Yao
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - J Y Ma
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - J Ma
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - L Q Zhang
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - J Jiang
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - R H Wu
- Hematology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
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129
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Xu J, Wang Y, Gao M, Cui C, Liu C, Ma J, Mi JQ. 643P Efficacy of CAR-T therapy for relapse or refractory multiple myeloma in the Chinese population: A systematic literature review and meta-analysis. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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130
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Petrylak D, Azad A, Szmulewitz R, Iguchi T, Shore N, Holzbeierlein J, Alekseev B, El-Chaar N, Rosbrook B, Ma J, Zohren F, Haas G, Stenzl A, Armstrong A. 1398P Overall survival (OS) in patients (pts) with metastatic hormone-sensitive prostate cancer (mHSPC) who received prior androgen deprivation therapy (ADT) and reached low prostate-specific antigen (PSA) levels treated further with enzalutamide (ENZA): Post hoc analyses of ARCHES. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.1884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
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131
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Gao Y, Guo D, Chen S, Han T, Zhao Y, Ma J, Lu G, Deng W, Ding R, Bu F. 295P PIK3CA in Asia: A landscape analysis of 1974 Chinese glioma samples. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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132
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Nazaretski E, Coburn DS, Xu W, Ma J, Xu H, Smith R, Huang X, Yang Y, Huang L, Idir M, Kiss A, Chu YS. A new Kirkpatrick-Baez-based scanning microscope for the Submicron Resolution X-ray Spectroscopy (SRX) beamline at NSLS-II. J Synchrotron Radiat 2022; 29:1284-1291. [PMID: 36073888 PMCID: PMC9455213 DOI: 10.1107/s1600577522007056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Accepted: 07/09/2022] [Indexed: 06/15/2023]
Abstract
The development, construction, and first commissioning results of a new scanning microscope installed at the 5-ID Submicron Resolution X-ray Spectroscopy (SRX) beamline at NSLS-II are reported. The developed system utilizes Kirkpatrick-Baez mirrors for X-ray focusing. The instrument is designed to enable spectromicroscopy measurements in 2D and 3D with sub-200 nm spatial resolution. The present paper focuses on the design aspects, optical considerations, and specifics of the sample scanning stage, summarizing some of the initial commissioning results.
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Affiliation(s)
- E. Nazaretski
- National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - D. S. Coburn
- National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - W. Xu
- National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - J. Ma
- National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - H. Xu
- National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - R. Smith
- National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - X. Huang
- National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - Y. Yang
- National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - L. Huang
- National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - M. Idir
- National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - A. Kiss
- National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - Y. S. Chu
- National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973, USA
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133
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Dai L, Chen KN, Y. Wu, Ma J, Guo S, Tian H, Xiao G, Liu W, He M, Chen C, Shi X, Wang Z, Liu J, Guo W, Cui Y, Dai T, Fu X, Jiao W. 1243P Influence of home nutritional therapy on body weight in patients with esophageal cancer after surgery: A prospective observational study. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.1361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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134
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Salvagiotto G, Fiene R, Ma J, Majewski D, Tomotoshi K, Livingston M, Hilcove S, Carlson C. P12-33 Development of a neural MEA co-culture assay for seizurogenic risk assessment featuring human iPSC-derived cell types. Toxicol Lett 2022. [DOI: 10.1016/j.toxlet.2022.07.512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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135
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Meng DF, Ma J, Fu L. 1328P Association of socioeconomic disparities with nasopharyngeal carcinoma survival in an endemic area, China. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.1461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
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136
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Jinhai Y, Hu H, Bian Z, Ma J, Chen S, Lu G, Deng W, Ding R, Bu F. 123P Correlation between MSI, TMB and BLM gene mutation in solid tumors. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
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137
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Yang W, Zeng X, Petrick JL, Danford CJ, Florio AA, Lu B, Nan H, Ma J, Wang L, Zeng H, Sudenga SL, Campbell PT, Giovannucci E, McGlynn KA, Zhang X. Body mass index trajectories, weight gain and risks of liver and biliary tract cancers. JNCI Cancer Spectr 2022; 6:pkac056. [PMID: 35960613 PMCID: PMC9406603 DOI: 10.1093/jncics/pkac056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Revised: 05/18/2022] [Accepted: 06/06/2022] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Little is known about the role of early obesity or weight change during adulthood in the development of liver cancer and biliary tract cancer (BTC). METHODS We investigated the associations of body mass index (BMI) and weight trajectories with the risk of liver cancer and BTC in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO). BMI was self-reported at ages 20, 50, and at enrollment. BMI trajectories were determined using latent class growth models. Cox regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS During a median follow-up of 15.9 years among 138,922 participants, 170 liver cancer and 143 BTC cases were identified. Compared with those whose BMI does not exceed 25 kg/m2, participants with BMI exceeding 25 kg/m2 at age 20 had increased risks of liver cancer (HR = 2.03, 95% CI: 1.26-3.28) and BTC (HR = 1.99, 95% CI: 1.16-3.39). Compared to participants maintaining normal BMI until enrollment, trajectory of normal weight at age 20 to obesity at enrollment was associated with increased risk for liver cancer (HR = 2.50, 95% CI: 1.55-4.04) and BTC (HR = 1.83, 95% CI: 1.03-3.22). Compared to adults with stable weight (+/-5kg) between age 20 to 50 years, weight gain ≥20 kg between ages 20 to 50 years had higher HRs of 2.24 (95%CI: 1.40-3.58) for liver cancer and 1.86 (95% CI: 1.12-3.09) for BTC. CONCLUSIONS Being overweight/obese at age 20, and BMI trajectories that result in being overweight and/or obese, may increase risk for both liver cancer and BTC.
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Affiliation(s)
- Wanshui Yang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Nutrition, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
| | - Xufen Zeng
- Department of Nutrition, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
| | | | - Christopher J Danford
- Division of Gastroenterology and Hepatology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Andrea A Florio
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Bing Lu
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Hongmei Nan
- Department of Epidemiology, Richard M Fairbanks School of Public Health, Indiana University, and Indiana University Melvin and Bren Simon Cancer Center, Indianapolis, IN, USA
| | - Jiantao Ma
- Framingham Heart Study, Framingham, MA, USA
- Division of Nutrition Data Science, Tufts University Friedman School of Nutrition Science and Policy, Boston, MA, USA
| | - Liang Wang
- Department of Public Health, Robbins College of Health and Human Sciences, Baylor University, TX, USA
| | - Hongmei Zeng
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Staci L Sudenga
- Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Peter T Campbell
- Department of Epidemiology and Population Science, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Edward Giovannucci
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Katherine A McGlynn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Xuehong Zhang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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138
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Ma J, Liu MR, Cui SY, Dai Z, Luo HM. [Progress and policy considerations on the pilot program of standardized training for public health physicians in China]. Zhonghua Yu Fang Yi Xue Za Zhi 2022; 56:1069-1073. [PMID: 35922233 DOI: 10.3760/cma.j.cn112150-20220616-00615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The standardized training for public health physicians plays an important role in exploring the cultivation public health professionals and strengthening the construction of public health service providers. In 2018, the National Health Commission of China launched a pilot program of standardized training for public health physicians in 10 provinces. This paper clarifies the definition of the standardized training for public health physicians, systematically analyzes the status quo of the training in China and other countries, articulates the design and progress of the training in the perspective of Centers for Disease Control and Prevention, and makes some suggestions for the priorities of the pilot training program, so as to provide reference and basis for the better development of the standardized training for public health physicians in China in the future.
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Affiliation(s)
- J Ma
- Department of Education and Training, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - M R Liu
- Department of Education and Training, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - S Y Cui
- Department of Education and Training, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Z Dai
- Department of Education and Training, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - H M Luo
- Department of Education and Training, Chinese Center for Disease Control and Prevention, Beijing 102206, China
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139
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Zhong SG, Mao Y, Shen JY, Ma J. [Research progress in magnetic resonance imaging of primary nocturnal enuresis]. Zhonghua Er Ke Za Zhi 2022; 60:840-843. [PMID: 35922202 DOI: 10.3760/cma.j.cn112140-20220221-00134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Affiliation(s)
- S G Zhong
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Y Mao
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - J Y Shen
- Department of Nephrology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - J Ma
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
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140
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Zheng Y, Joyce B, Hwang SJ, Ma J, Liu L, Allen N, Krefman A, Wang J, Gao T, Nannini D, Zhang H, Jacobs DR, Gross M, Fornage M, Lewis CE, Schreiner PJ, Sidney S, Chen D, Greenland P, Levy D, Hou L, Lloyd-Jones D. Association of Cardiovascular Health Through Young Adulthood With Genome-Wide DNA Methylation Patterns in Midlife: The CARDIA Study. Circulation 2022; 146:94-109. [PMID: 35652342 PMCID: PMC9348746 DOI: 10.1161/circulationaha.121.055484] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Cardiovascular health (CVH) from young adulthood is strongly associated with an individual's future risk of cardiovascular disease (CVD) and total mortality. Defining epigenomic biomarkers of lifelong CVH exposure and understanding their roles in CVD development may help develop preventive and therapeutic strategies for CVD. METHODS In 1085 CARDIA study (Coronary Artery Risk Development in Young Adults) participants, we defined a clinical cumulative CVH score that combines body mass index, blood pressure, total cholesterol, and fasting glucose measured longitudinally from young adulthood through middle age over 20 years (mean age, 25-45). Blood DNA methylation at >840 000 methylation markers was measured twice over 5 years (mean age, 40 and 45). Epigenome-wide association analyses on the cumulative CVH score were performed in CARDIA and compared in the FHS (Framingham Heart Study). We used penalized regression to build a methylation-based risk score to evaluate the risk of incident coronary artery calcification and clinical CVD events. RESULTS We identified 45 methylation markers associated with cumulative CVH at false discovery rate <0.01 (P=4.7E-7-5.8E-17) in CARDIA and replicated in FHS. These associations were more pronounced with methylation measured at an older age. CPT1A, ABCG1, and SREBF1 appeared as the most prominent genes. The 45 methylation markers were mostly located in transcriptionally active chromatin and involved lipid metabolism, insulin secretion, and cytokine production pathways. Three methylation markers located in genes SARS1, SOCS3, and LINC-PINT statistically mediated 20.4% of the total effect between CVH and risk of incident coronary artery calcification. The methylation risk score added information and significantly (P=0.004) improved the discrimination capacity of coronary artery calcification status versus CVH score alone and showed association with risk of incident coronary artery calcification 5 to 10 years later independent of cumulative CVH score (odds ratio, 1.87; P=9.66E-09). The methylation risk score was also associated with incident clinical CVD in FHS (hazard ratio, 1.28; P=1.22E-05). CONCLUSIONS Cumulative CVH from young adulthood contributes to midlife epigenetic programming over time. Our findings demonstrate the role of epigenetic markers in response to CVH changes and highlight the potential of epigenomic markers for precision CVD prevention, and earlier detection of subclinical CVD, as well.
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Affiliation(s)
- Yinan Zheng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Brian Joyce
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Shih-Jen Hwang
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Jiantao Ma
- Tufts University Friedman School of Nutrition Science and Policy, Boston, Massachusetts, USA
| | - Lei Liu
- Division of Biostatistics, Washington University, St. Louis, Missouri, USA
| | - Norrina Allen
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Amy Krefman
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Jun Wang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Tao Gao
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Drew Nannini
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Haixiang Zhang
- Center for Applied Mathematics, Tianjin University, Tianjin, China
| | - David R. Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Myron Gross
- Department of Laboratory Medicine and Pathology, Medical School, University of Minnesota, Minneapolis, Minnesota, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Cora E. Lewis
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
- Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Pamela J. Schreiner
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Stephen Sidney
- Division of Research, Kaiser Permanente Northern California, Oakland, California, USA
| | - Dongquan Chen
- Department of Medicine, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Philip Greenland
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Donald Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
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Zhang YQ, Sun KG, Lu JY, Ma J, Yao N, Qin ZH, Yao YH. [Efficacy and safety of total neoadjuvant therapy versus neoadjuvant chemoradiotherapy in the treatment of locally advanced rectal cancer: a meta-analysis]. Zhonghua Wei Chang Wai Ke Za Zhi 2022; 25:531-538. [PMID: 35754218 DOI: 10.3760/cma.j.cn441530-20210806-00311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To systematically evaluate the efficacy and safety of total neoadjuvant therapy (TNT) in the comprehensive treatment of locally advanced rectal cancer. Methods: Literatures were screened from PubMed, Embase, Web of Science, Cochrane Library, CBM, Wanfang Data, VIP and CNKI from the inception date to May 2021 to collect the randomized controlled clinical trials (RCTs) of TNT followed by total mesorectal excision (TME) versus neoadjuvant chemotherapy (nCRT) followed by TME in the treatment of locally advanced rectal cancer. The data of overall survival, disease-free survival, R0 radical resection rate, pathological complete response (pCR) rate, T downstaging rate, the incidence of adverse events ≥ grade III, including neutropenia, nausea and vomiting, diarrhea, radiation dermatitis and nervous system toxicity, and the morbidity of complications within postoperative 30 days of the two groups were extracted from the included literatures. Review Manager 5.3 software was utilized for statistical meta-analysis. Results: Nine RCTs were finally enrolled including 2430 patients. Meta-analysis results showed that compared with nCRT group, patients in TNT group had longer overall survival (HR=0.80, 95%CI: 0.65-0.97, P=0.03) and higher pCR rate (RR=1.73, 95%CI: 1.44-2.08, P<0.01) with significant differences. Besides, there were no significant differences between two groups in disease-free survival (HR=0.86, 95%CI:0.71-1.05, P=0.14), R0 radical resection rate (RR=1.02, 95%CI: 0.99-1.06, P=0.17) and T downstaging rate (RR=1.04, 95%CI: 0.89-1.22, P=0.58) between two groups. In terms of treatment safety, the incidence of adverse events ≥ grade III (RR=1.09, 95%CI: 0.70-1.70, P=0.70) and morbidity of complications within postoperative 30 days (RR=1.07, 95%CI: 0.97-1.18, P=0.19) did not significantly differ between two groups. Conclusions: In the treatment of locally advanced rectal cancer, TNT may bring more survival benefits than nCRT and does not increase the incidence of adverse events and postoperative complications. Therefore, TNT could be used as a recommended treatment for patients with locally advanced rectal cancer.
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Affiliation(s)
- Y Q Zhang
- Department of Radiation Oncology, the Affiliated Hospital of Xuzhou Medical University, Xuzhou 221002, China
| | - K G Sun
- Department of Radiation Oncology, the Affiliated Hospital of Xuzhou Medical University, Xuzhou 221002, China
| | - J Y Lu
- Department of Radiation Oncology, the Affiliated Hospital of Xuzhou Medical University, Xuzhou 221002, China
| | - J Ma
- Department of Radiation Oncology, the Affiliated Hospital of Xuzhou Medical University, Xuzhou 221002, China
| | - N Yao
- Department of Radiation Oncology, the Affiliated Hospital of Xuzhou Medical University, Xuzhou 221002, China
| | - Z H Qin
- School of Public Health, Xuzhou Medical University, Xuzhou 221004, China
| | - Y H Yao
- Department of Radiation Oncology, the Affiliated Hospital of Xuzhou Medical University, Xuzhou 221002, China School of Medical Imaging, Xuzhou Medical University, Xuzhou 221004, China
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142
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Abstract
Medical and dental artificial intelligence (AI) require the trust of both users and
recipients of the AI to enhance implementation, acceptability, reach, and maintenance.
Standardization is one strategy to generate such trust, with quality standards pushing for
improvements in AI and reliable quality in a number of attributes. In the present brief
review, we summarize ongoing activities from research and standardization that contribute
to the trustworthiness of medical and, specifically, dental AI and discuss the role of
standardization and some of its key elements. Furthermore, we discuss how explainable AI
methods can support the development of trustworthy AI models in dentistry. In particular,
we demonstrate the practical benefits of using explainable AI on the use case of caries
prediction on near-infrared light transillumination images.
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Affiliation(s)
- J Ma
- Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute, Berlin, Germany
| | - L Schneider
- Department of Oral Diagnostics, Digital Health and Health Services Research, Charité-Universitätsmedizin, Berlin, Germany.,ITU/WHO Focus Group on AI for Health, Topic Group Dental Diagnostics and Digital Dentistry, Geneva, Switzerland
| | - S Lapuschkin
- Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute, Berlin, Germany
| | - R Achtibat
- Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute, Berlin, Germany
| | - M Duchrau
- Department of Oral Diagnostics, Digital Health and Health Services Research, Charité-Universitätsmedizin, Berlin, Germany
| | - J Krois
- Department of Oral Diagnostics, Digital Health and Health Services Research, Charité-Universitätsmedizin, Berlin, Germany.,ITU/WHO Focus Group on AI for Health, Topic Group Dental Diagnostics and Digital Dentistry, Geneva, Switzerland
| | - F Schwendicke
- Department of Oral Diagnostics, Digital Health and Health Services Research, Charité-Universitätsmedizin, Berlin, Germany.,ITU/WHO Focus Group on AI for Health, Topic Group Dental Diagnostics and Digital Dentistry, Geneva, Switzerland
| | - W Samek
- Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute, Berlin, Germany.,BIFOLD-Berlin Institute for the Foundations of Learning and Data, Berlin, Germany
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Zhang W, Liu FQ, Zhang LP, Ding HG, Zhuge YZ, Wang JT, Li L, Wang GC, Wu H, Li H, Cao GH, Lu XF, Kong DR, Sun L, Wu W, Sun JH, Liu JT, Zhu H, Li DL, Guo WH, Xue H, Wang Y, Gengzang CJC, Zhao T, Yuan M, Liu SR, Huan H, Niu M, Li X, Ma J, Zhu QL, Guo WW, Zhang KP, Zhu XL, Huang BR, Li JN, Wang WD, Yi HF, Zhang Q, Gao L, Zhang G, Zhao ZW, Xiong K, Wang ZX, Shan H, Li MS, Zhang XQ, Shi HB, Hu XG, Zhu KS, Zhang ZG, Jiang H, Zhao JB, Huang MS, Shen WY, Zhang L, Xie F, Li ZW, Hou CL, Hu SJ, Lu JW, Cui XD, Lu T, Yang SS, Liu W, Shi JP, Lei YM, Bao JL, Wang T, Ren WX, Zhu XL, Wang Y, Yu L, Yu Q, Xiang HL, Luo WW, Qi XL. [Status of HVPG clinical application in China in 2021]. Zhonghua Gan Zang Bing Za Zhi 2022; 30:637-643. [PMID: 36038326 DOI: 10.3760/cma.j.cn501113-20220302-00093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: The investigation and research on the application status of Hepatic Venous Pressure Gradient (HVPG) is very important to understand the real situation and future development of this technology in China. Methods: This study comprehensively investigated the basic situation of HVPG technology in China, including hospital distribution, hospital level, annual number of cases, catheters used, average cost, indications and existing problems. Results: According to the survey, there were 70 hospitals in China carrying out HVPG technology in 2021, distributed in 28 provinces (autonomous regions and municipalities directly under the central Government). A total of 4 398 cases of HVPG were performed in all the surveyed hospitals in 2021, of which 2 291 cases (52.1%) were tested by HVPG alone. The average cost of HVPG detection was (5 617.2±2 079.4) yuan. 96.3% of the teams completed HVPG detection with balloon method, and most of the teams used thrombectomy balloon catheter (80.3%). Conclusion: Through this investigation, the status of domestic clinical application of HVPG has been clarified, and it has been confirmed that many domestic medical institutions have mastered this technology, but it still needs to continue to promote and popularize HVPG technology in the future.
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Affiliation(s)
- W Zhang
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - F Q Liu
- Department of Interventional Radiology, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - L P Zhang
- Department of Radiology,Third Hospital of Taiyuan, Taiyuan 030012, China
| | - H G Ding
- Liver Disease Digestive Center,Beijing Youan Hospital, Capital Medical University, Beijing 100069, China
| | - Y Z Zhuge
- Digestive Department,Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing 210008, China
| | - J T Wang
- Department of Hepatobiliary Surgery, Xingtai People's Hospital, Xingtai 054001, China
| | - L Li
- Department of Interventional Radiology, the First Hospital of Lanzhou University, Lanzhou 730013, China
| | - G C Wang
- Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - H Wu
- Digestive Department, West China Hospital, Sichuan University, Chengdu 610044, China
| | - H Li
- Institute of Hepatology and Department of Infectious Disease, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - G H Cao
- Department of Radiology, Shulan Hospital, Hangzhou 310022, China
| | - X F Lu
- Digestive Department, West China Hospital, Sichuan University, Chengdu 610044, China
| | - D R Kong
- Digestive Department, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - L Sun
- Department of Gastroenterology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325001, China
| | - W Wu
- Department of Gastroenterology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325001, China
| | - J H Sun
- Hepatobiliary and Pancreatic Intervention Center , the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - J T Liu
- Digestive Department,Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China
| | - H Zhu
- The 1 st Department of Interventional Radiology, the Sixth People's Hospital of Shenyang, Shenyang 110006, China
| | - D L Li
- No. 900 Hospital of the Joint Logistic Support Force, Fuzhou 350025, China
| | - W H Guo
- Department of Interventional Radiology, Meng Chao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350025, China
| | - H Xue
- Digestive Department, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - Y Wang
- Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - C J C Gengzang
- Department of Interventional Radiology, the Fourth People's Hospital of Qinghai Province, Xining 810007, China
| | - T Zhao
- Department of Radiology,Sir Run Shaw Hospital, Zhejiang University, Hangzhou 310016, China
| | - M Yuan
- Department of Interventional Radiology Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China
| | - S R Liu
- Department of Infectious Disease,Qufu People's Hospital, Qufu 273199, China
| | - H Huan
- Digestive Department, Chengdu Office Hospital of Tibet Autonomous Region People's Government, Chengdu 610041, China
| | - M Niu
- Department of Interventional Radiology, the First Affiliated Hospital of China Medical University, Shenyang 110001, China
| | - X Li
- Department of Radiology,Tianjin Second People's Hospital, Tianjin 300192, China
| | - J Ma
- Department of Interventional Vascular Surgerg, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan 750002, China
| | - Q L Zhu
- Digestive Department,the Affiliated Hospital of Southwest Medical University, Luzhou 646099, China
| | - W W Guo
- Department of Interventional Radiology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China
| | - K P Zhang
- Department of Hepatobiliary Surgery, Xingtai People's Hospital, Xingtai 054001, China
| | - X L Zhu
- Department of Surgery, the First Hospital of Lanzhou University, Lanzhou 730013, China
| | - B R Huang
- Department of Interventional Vascular Surgery,Jingzhou First People's Hospital, Jingzhou, China
| | - J N Li
- Liver Diseases Department,Jiamusi Infectious Disease Hospital, Jiamusi 154015, China
| | - W D Wang
- Hepatobiliary, Pancreatic and Spleen Surgery Department,Shunde Hospital, Southern Medical University, Foshan 528427, China
| | - H F Yi
- Digestive Department,Wuhan First Hospital, Wuhan 430030, China
| | - Q Zhang
- Interventional Vascular Surgery Department, Affiliated Zhongda Hospital of Southeast University, Nanjing 210009, China
| | - L Gao
- Oncology and Vascular Interventional Department, First Hospital of Shanxi Medical University, Taiyuan 030001, China
| | - G Zhang
- Digestive Department, the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530016, China
| | - Z W Zhao
- Department of Interventional Radiology, Lishui Municipal Central Hospital, Zhejiang University School of Medicine, Lishui 323030, China
| | - K Xiong
- Digestive Department, the Second Affiliated Hospital of Nanchang University, Nanchang 330008, China
| | - Z X Wang
- Inner Mongolia Medical University Affiliated Hospital, Hohhot 010050, China
| | - H Shan
- Interventional Medicine Center, the Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai 519000, China
| | - M S Li
- Department of Endovascular Surgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - X Q Zhang
- Digestive Department, the Second Hospital of Hebei Medical University, Shijiazhuang 050004, China
| | - H B Shi
- Department of Interventional Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - X G Hu
- Interventional Radiology Department,Jinhua Municipal Central Hospital, Jinhua 321099, China
| | - K S Zhu
- Interventional Radiology Department, the Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou 510260, China
| | - Z G Zhang
- Department of Liver Surgery,Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430014, China
| | - H Jiang
- Infectious Disease Department,Second Affiliated Hospital, Military Medical University of the Air Force, Xi'an 710038, China
| | - J B Zhao
- Department of Vascular and Interventional Radiology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - M S Huang
- Interventional Radiology Department, the Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510000, China
| | - W Y Shen
- Digestive Department,Fuling Hospital Affiliated to Chongqing University, Chongqing 400030, China
| | - L Zhang
- Hepatobiliary Pancreatic Center,Tsinghua Changgung Hospital, Beijing 102200, China
| | - F Xie
- Function Department,Lanzhou Second People's Hospital, Lanzhou 730030, China
| | - Z W Li
- Hepatobiliary Surgery Department,Shenzhen Third People's Hospital, Shenzhen518112, China
| | - C L Hou
- Department of Interventional Radiology, the First Affiliated Hospital of USTC, Hefei 230001, China
| | - S J Hu
- Digestive Department,People's Hospital of Ningxia Hui Autonomous Region, Yinchuan 750002, China
| | - J W Lu
- Department of Interventional Radiology, Qufu People's Hospital, Qufu 273199, China
| | - X D Cui
- Department of Interventional Radiology, the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530016, China
| | - T Lu
- Department of Gastroenterology, Yangquan Third People's Hospital, Yangquan 045099,China
| | - S S Yang
- Department of Gastroenterology, General Hospital of Ningxia Medical University , Yinchuan 750003, China
| | - W Liu
- Department of Interventional Radiology, Lishui People's Hospital, Zhejiang Province, Lishui 323050, China
| | - J P Shi
- Department of Liver Diseases, Affiliated Hospital of Hangzhou Normal University, Hangzhou 310015, China
| | - Y M Lei
- Interventional Radiology Department, People's Hospital of Tibet Autonomous Region, Lhasa 850001, China
| | - J L Bao
- Department of Gastroenterology, Shannan people's Hospital,Shannan 856004, China
| | - T Wang
- Department of Interventional Radiology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai 264099,China
| | - W X Ren
- Interventional Treatment Center, the First Affiliated Hospital of Xinjiang Medical University, Urumqi 830011,China
| | - X L Zhu
- Interventional Radiology Department, the First Affiliated Hospital of Suzhou University, Suzhou 215006, China
| | - Y Wang
- Department of Interventional Vascular Surgery, the Second Affiliated Hospital of Hainan Medical College, Haikou 570216, China
| | - L Yu
- Department of Interventional Radiology, Sanming First Hospital Affiliated to Fujian Medical University,Sanming 365001,China
| | - Q Yu
- Interventional Radiology Department, Fifth Medical Center of PLA General Hospital, Beijing 100039, China
| | - H L Xiang
- Department of Gastroenterology, Tianjin Third Central Hospital, Tianjin 300170, China
| | - W W Luo
- Deparment of Infectious Diseases, the Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
| | - X L Qi
- Center of Portal Hypertension Department of Radiology, Zhongda Hospital of Southeast University, Nanjing 210009, China
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144
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He F, Wang Y, Tao X, Zhu M, Hong Z, Bian Z, Ma J. [Low-dose helical CT projection data restoration using noise estimation]. Nan Fang Yi Ke Da Xue Xue Bao 2022; 42:849-859. [PMID: 35790435 DOI: 10.12122/j.issn.1673-4254.2022.06.08] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
OBJECTIVE To build a helical CT projection data restoration model at random low-dose levels. METHODS We used a noise estimation module to achieve noise estimation and obtained a low-dose projection noise variance map, which was used to guide projection data recovery by the projection data restoration module. A filtering back-projection algorithm (FBP) was finally used to reconstruct the images. The 3D wavelet group residual dense network (3DWGRDN) was adopted to build the network architecture of the noise estimation and projection data restoration module using asymmetric loss and total variational regularization. For validation of the model, 1/10 and 1/15 of normal dose helical CT images were restored using the proposed model and 3 other restoration models (IRLNet, REDCNN and MWResNet), and the results were visually and quantitatively compared. RESULTS Quantitative comparisons of the restored images showed that the proposed helical CT projection data restoration model increased the structural similarity index by 5.79% to 17.46% compared with the other restoration algorithms (P < 0.05). The image quality scores of the proposed method rated by clinical radiologists ranged from 7.19% to 17.38%, significantly higher than the other restoration algorithms (P < 0.05). CONCLUSION The proposed method can effectively suppress noises and reduce artifacts in the projection data at different low-dose levels while preserving the integrity of the edges and fine details of the reconstructed CT images.
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Affiliation(s)
- F He
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.,Pazhou Lab, Guangzhou, 510330, China
| | - Y Wang
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.,Pazhou Lab, Guangzhou, 510330, China
| | - X Tao
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| | - M Zhu
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.,Pazhou Lab, Guangzhou, 510330, China
| | - Z Hong
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.,Pazhou Lab, Guangzhou, 510330, China
| | - Z Bian
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| | - J Ma
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
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145
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Zhu Q, Wang Y, Zhu M, Tao X, Bian Z, Ma J. [An adaptive CT metal artifact reduction algorithm that combines projection interpolation and physical correction]. Nan Fang Yi Ke Da Xue Xue Bao 2022; 42:832-839. [PMID: 35790433 DOI: 10.12122/j.issn.1673-4254.2022.06.06] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
OBJECTIVE To propose an adaptive weighted CT metal artifact reduce algorithm that combines projection interpolation and physical correction. METHODS A normalized metal projection interpolation algorithm was used to obtain the initial corrected projection data. A metal physical correction model was then introduced to obtain the physically corrected projection data. To verify the effectiveness of the method, we conducted experiments using simulation data and clinical data. For the simulation data, the quantitative indicators PSNR and SSIM were used for evaluation, while for the clinical data, the resultant images were evaluated by imaging experts to compare the artifact-reducing performance of different methods. RESULTS For the simulation data, the proposed method improved the PSNR value by at least 0.2 dB and resulted in the highest SSIM value among the methods for comparison. The experiment with the clinical data showed that the imaging experts gave the highest scores of 3.616±0.338 (in a 5-point scale) to the images processed using the proposed method, which had significant better artifact-reducing performance than the other methods (P < 0.001). CONCLUSION The metal artifact reduction algorithm proposed herein can effectively reduce metal artifacts while preserving the tissue structure information and reducing the generation of new artifacts.
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Affiliation(s)
- Q Zhu
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.,Pazhou Lab, Guangzhou 510330, China
| | - Y Wang
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.,Pazhou Lab, Guangzhou 510330, China
| | - M Zhu
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.,Pazhou Lab, Guangzhou 510330, China
| | - X Tao
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.,Pazhou Lab, Guangzhou 510330, China
| | - Z Bian
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| | - J Ma
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
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146
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Gervis J, Ma J, Chui K, Lichtenstein A. Association of Taste-Related Genes With Diet Quality and Cardiometabolic Risk Factors Among Community-Dwelling Adults – The Framingham Heart Study. Curr Dev Nutr 2022. [PMCID: PMC9194398 DOI: 10.1093/cdn/nzac078.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Objectives Understanding the individual-level drivers of food choices is critical for designing personalized nutrition guidance. Taste perception is one factor, yet the effects of genetic variants (SNPs) related to taste perception on diet quality and cardiometabolic risk factors (CRFs) are unknown. Thus, our aims were to determine the associations of taste-related SNPs, combined as polygenic risk scores (PRS), with diet quality, and CRFs (waist circumference, glucose, systolic and diastolic blood pressure [SBP and DBP], and log[triglyceride] [TG] and HDL levels). Methods Cross-sectional analyses were conducted in 6,230 Framingham Heart Study Offspring (1998–2001) and Third Generation (2002–05) participants (mean age ± SD: 50 ± 14 y; 54% female). Diet quality was estimated using food group intakes (log[sev/wk]) derived from food frequency questionnaires. Weighted PRS were derived for tastes with ≥ 2 SNPs identified from prior GWAS (32 SNPs; 19 sweet, 9 bitter, 2 umami, 1 salt, 1 sour). Higher PRS indicated more alleles for higher taste perception. Associations were assessed via linear mixed models adjusted for age, sex, population stratification and energy intake. Results PRS were built for sweet, bitter, and umami perception (mean PRS ± SD: 19.5 ± 2.5, 5.3 ± 1.6, and 3.1 ± 0.8, respectively). Inverse associations were identified for PRSbitter and whole grains, PRSumami and vegetables, and PRSsweet and TG levels (β [95% CI] = −0.03 [−0.05, −0.02], −0.03 [−0.06, −0.01], and −0.008 [−0.014, −0.003], respectively) (all FDR <0.05). Exploratory analyses of individual SNPs identified associations (FDR <0.05) of sweet-related SNPs with higher fish/seafood and HDL levels, and lower TG levels; umami-related SNPs with lower vegetables; and a bitter-related SNP with lower SBP and DBP. Novel SNP-diet interactions were also identified; for example, higher fish/seafood intake was associated with lower TG levels for those with GG for salt-related SNP rs10134414 (G>A; G = higher perception), but higher TG levels for those with AA/AG (P=0.002). Conclusions Among community-dwelling adults, sweet-, bitter- and umami-related genes were associated with diet quality and CRFs, suggesting that taste-related genes impact food choices and may be beneficial to consider when personalizing risk reduction dietary guidance. Funding Sources AHA pre-doctoral fellowship #837,466 (JEG).
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Affiliation(s)
- Julie Gervis
- JM USDA Human Nutrition Research Center on Aging, Tufts University
| | - Jiantao Ma
- Friedman School of Nutrition Science and Policy, Tufts University
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147
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Huan T, Nguyen S, Colicino E, Ochoa‐Rosales C, Hill WD, Brody JA, Soerensen M, Zhang Y, Baldassari A, Elhadad MA, Toshiko T, Zheng Y, Domingo‐Relloso A, Lee DH, Ma J, Yao C, Liu C, Hwang S, Joehanes R, Fornage M, Bressler J, van Meurs JB, Debrabant B, Mengel‐From J, Hjelmborg J, Christensen K, Vokonas P, Schwartz J, Gahrib SA, Sotoodehnia N, Sitlani CM, Kunze S, Gieger C, Peters A, Waldenberger M, Deary IJ, Ferrucci L, Qu Y, Greenland P, Lloyd‐Jones DM, Hou L, Bandinelli S, Voortman T, Hermann B, Baccarelli A, Whitsel E, Pankow JS, Levy D. Integrative analysis of clinical and epigenetic biomarkers of mortality. Aging Cell 2022; 21:e13608. [PMID: 35546478 PMCID: PMC9197414 DOI: 10.1111/acel.13608] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 03/03/2022] [Accepted: 03/24/2022] [Indexed: 01/28/2023] Open
Abstract
DNA methylation (DNAm) has been reported to be associated with many diseases and with mortality. We hypothesized that the integration of DNAm with clinical risk factors would improve mortality prediction. We performed an epigenome-wide association study of whole blood DNAm in relation to mortality in 15 cohorts (n = 15,013). During a mean follow-up of 10 years, there were 4314 deaths from all causes including 1235 cardiovascular disease (CVD) deaths and 868 cancer deaths. Ancestry-stratified meta-analysis of all-cause mortality identified 163 CpGs in European ancestry (EA) and 17 in African ancestry (AA) participants at p < 1 × 10-7 , of which 41 (EA) and 16 (AA) were also associated with CVD death, and 15 (EA) and 9 (AA) with cancer death. We built DNAm-based prediction models for all-cause mortality that predicted mortality risk after adjusting for clinical risk factors. The mortality prediction model trained by integrating DNAm with clinical risk factors showed an improvement in prediction of cancer death with 5% increase in the C-index in a replication cohort, compared with the model including clinical risk factors alone. Mendelian randomization identified 15 putatively causal CpGs in relation to longevity, CVD, or cancer risk. For example, cg06885782 (in KCNQ4) was positively associated with risk for prostate cancer (Beta = 1.2, PMR = 4.1 × 10-4 ) and negatively associated with longevity (Beta = -1.9, PMR = 0.02). Pathway analysis revealed that genes associated with mortality-related CpGs are enriched for immune- and cancer-related pathways. We identified replicable DNAm signatures of mortality and demonstrated the potential utility of CpGs as informative biomarkers for prediction of mortality risk.
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Affiliation(s)
- Tianxiao Huan
- The Framingham Heart StudyFraminghamMassachusettsUSA
- The Population Sciences BranchDivision of Intramural ResearchNational Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMarylandUSA
- Department of Ophthalmology and Visual SciencesUniversity of Massachusetts Medical SchoolWorcesterMassachusettsUSA
| | - Steve Nguyen
- Division of Epidemiology & Community HealthSchool of Public HealthUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Elena Colicino
- Icahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Carolina Ochoa‐Rosales
- Department of EpidemiologyErasmus University Medical CenterRotterdamthe Netherlands
- Centro de Vida Saludable de la Universidad de ConcepciónConcepciónChile
| | - W. David Hill
- Department of PsychologyLothian Birth CohortsUniversity of EdinburghEdinburghUK
| | - Jennifer A. Brody
- Cardiovascular Health Research UnitDepartment of MedicineUniversity of WashingtonSeattleWashingtonUSA
| | - Mette Soerensen
- Department of Public HealthEpidemiology, Biostatistics and BiodemographyUniversity of Southern DenmarkOdense CDenmark
- Department of Clinical Biochemistry and PharmacologyCenter for Individualized Medicine in Arterial DiseasesOdense University HospitalOdense CDenmark
- Department of Clinical GeneticsOdense University HospitalOdense CDenmark
| | - Yan Zhang
- Division of Clinical Epidemiology & Aging ResearchGerman Cancer Rsrch Ctr (DKFZ)HeidelbergGermany
| | - Antoine Baldassari
- Department of EpidemiologyGillings School of Global Public HealthUniversity of North CarolinaChapel HillNorth CarolinaUSA
| | - Mohamed Ahmed Elhadad
- Research Unit of Molecular EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- Institute of EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- German Research Center for Cardiovascular Disease (DZHK)Partner Site Munich Heart AllianceMunichGermany
| | - Tanaka Toshiko
- Translational Gerontology BranchNational Institute on AgingBaltimoreMarylandUSA
| | - Yinan Zheng
- Department of Preventive MedicineNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Arce Domingo‐Relloso
- Department of Chronic Diseases EpidemiologyNational Center for EpidemiologyCarlos III Health InstituteMadridSpain
- Department of Environmental Health SciencesColumbia University Mailman School of Public HealthNew YorkNew YorkUSA
- Department of Statistics and Operations ResearchUniversity of ValenciaValenciaSpain
| | - Dong Heon Lee
- The Framingham Heart StudyFraminghamMassachusettsUSA
- The Population Sciences BranchDivision of Intramural ResearchNational Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Jiantao Ma
- The Framingham Heart StudyFraminghamMassachusettsUSA
- The Population Sciences BranchDivision of Intramural ResearchNational Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMarylandUSA
- Nutrition Epidemiology and Data ScienceFriedman School of Nutrition Science and PolicyTufts UniversityBostonMassachusettsUSA
| | - Chen Yao
- The Framingham Heart StudyFraminghamMassachusettsUSA
- The Population Sciences BranchDivision of Intramural ResearchNational Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Chunyu Liu
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
| | - Shih‐Jen Hwang
- The Framingham Heart StudyFraminghamMassachusettsUSA
- The Population Sciences BranchDivision of Intramural ResearchNational Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Roby Joehanes
- The Framingham Heart StudyFraminghamMassachusettsUSA
- The Population Sciences BranchDivision of Intramural ResearchNational Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Myriam Fornage
- Human Genetics CenterSchool of Public HealthUniversity of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Jan Bressler
- Department of Internal MedicineErasmusRotterdamthe Netherlands
| | | | - Birgit Debrabant
- Department of Public HealthEpidemiology, Biostatistics and BiodemographyUniversity of Southern DenmarkOdense CDenmark
| | - Jonas Mengel‐From
- Department of Public HealthEpidemiology, Biostatistics and BiodemographyUniversity of Southern DenmarkOdense CDenmark
- Department of Clinical GeneticsOdense University HospitalOdense CDenmark
| | - Jacob Hjelmborg
- Department of Public HealthEpidemiology, Biostatistics and BiodemographyUniversity of Southern DenmarkOdense CDenmark
| | - Kaare Christensen
- Department of Public HealthEpidemiology, Biostatistics and BiodemographyUniversity of Southern DenmarkOdense CDenmark
- Department of Clinical GeneticsOdense University HospitalOdense CDenmark
| | - Pantel Vokonas
- Veterans AffairsNormative Aging StudyBostonMassachusettsUSA
- Veterans AffairsBoston Healthcare SystemBostonMassachusettsUSA
- Boston University School of Public HealthBostonMassachusettsUSA
| | - Joel Schwartz
- Departments of Environmental Health and EpidemiologyHarvard TH Chan School of Public HealthBostonMassachusettsUSA
| | - Sina A. Gahrib
- Cardiovascular Health Research UnitDepartment of MedicineUniversity of WashingtonSeattleWashingtonUSA
- Department of PsychologyUniv of EdinburghEdinburghUK
| | - Nona Sotoodehnia
- Cardiovascular Health Research UnitDepartment of MedicineUniversity of WashingtonSeattleWashingtonUSA
| | - Colleen M. Sitlani
- Cardiovascular Health Research UnitDepartment of MedicineUniversity of WashingtonSeattleWashingtonUSA
| | - Sonja Kunze
- Research Unit of Molecular EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- Institute of EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
| | - Christian Gieger
- Research Unit of Molecular EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- Institute of EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- German Research Center for Cardiovascular Disease (DZHK)Partner Site Munich Heart AllianceMunichGermany
| | - Annette Peters
- Institute of EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- German Research Center for Cardiovascular Disease (DZHK)Partner Site Munich Heart AllianceMunichGermany
- German Center for Diabetes Research (DZD)München‐Neuherberg, NeuherbergGermany
- Institute of Medical Information Sciences, Biometry and EpidemiologyLudwig‐Maximilians‐UniversityMunichGermany
| | - Melanie Waldenberger
- Research Unit of Molecular EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- Institute of EpidemiologyHelmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherbergGermany
- German Research Center for Cardiovascular Disease (DZHK)Partner Site Munich Heart AllianceMunichGermany
| | - Ian J. Deary
- Division of PulmonaryCritical Care and Sleep MedicineCenter for Lung BiologyUniversity of WashingtonSeattleWashingtonUSA
| | - Luigi Ferrucci
- Translational Gerontology BranchNational Institute on AgingBaltimoreMarylandUSA
| | - Yishu Qu
- Department of Preventive MedicineNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Philip Greenland
- Department of Preventive MedicineNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Donald M. Lloyd‐Jones
- Department of Preventive MedicineNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Lifang Hou
- Department of Preventive MedicineNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | | | - Trudy Voortman
- Department of EpidemiologyErasmus University Medical CenterRotterdamthe Netherlands
| | - Brenner Hermann
- Division of Clinical Epidemiology & Aging ResearchGerman Cancer Rsrch Ctr (DKFZ)HeidelbergGermany
- Network Aging Research (NAR)University of HeidelbergHeidelbergGermany
| | - Andrea Baccarelli
- Precision Medicine ProgramDepartment of Environmental Health SciencesMailman School of Public HealthColumbia UniversityNew YorkNew YorkUSA
| | - Eric Whitsel
- Department of EpidemiologyGillings School of Global Public HealthUniversity of North CarolinaChapel HillNorth CarolinaUSA
- Department of MedicineSchool of MedicineUniversity of North CarolinaChapel HillNorth CarolinaUSA
| | - James S. Pankow
- Division of Epidemiology & Community HealthSchool of Public HealthUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Daniel Levy
- The Framingham Heart StudyFraminghamMassachusettsUSA
- The Population Sciences BranchDivision of Intramural ResearchNational Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMarylandUSA
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148
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Liu C, Joehanes R, Ma J, Wang Y, Sun X, Keshawarz A, Sooda M, Huan T, Hwang SJ, Bui H, Tejada B, Munson PJ, Cumhur D, Heard-Costa NL, Pitsillides AN, Peloso GM, Feolo M, Sharopova N, Vasan RS, Levy D. Whole Genome DNA and RNA Sequencing of Whole Blood Elucidates the Genetic Architecture of Gene Expression Underlying a Wide Range of Diseases. Res Sq 2022:rs.3.rs-1598646. [PMID: 35664994 PMCID: PMC9164515 DOI: 10.21203/rs.3.rs-1598646/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
To create a scientific resource of expression quantitative trail loci (eQTL), we conducted a genome-wide association study (GWAS) using genotypes obtained from whole genome sequencing (WGS) of DNA and gene expression levels from RNA sequencing (RNA-seq) of whole blood in 2622 participants in Framingham Heart Study. We identified 6,778,286 cis -eQTL variant-gene transcript (eGene) pairs at p < 5x10 - 8 (2,855,111 unique cis -eQTL variants and 15,982 unique eGenes) and 1,469,754 trans -eQTL variant-eGene pairs at p < 1e-12 (526,056 unique trans -eQTL variants and 7,233 unique eGenes). In addition, 442,379 cis -eQTL variants were associated with expression of 1518 long non-protein coding RNAs (lncRNAs). Gene Ontology (GO) analyses revealed that the top GO terms for cis- eGenes are enriched for immune functions (FDR < 0.05). The cis -eQTL variants are enriched for SNPs reported to be associated with 815 traits in prior GWAS, including cardiovascular disease risk factors. As proof of concept, we used this eQTL resource in conjunction with genetic variants from public GWAS databases in causal inference testing (e.g., COVID-19 severity). After Bonferroni correction, Mendelian randomization analyses identified putative causal associations of 60 eGenes with systolic blood pressure, 13 genes with coronary artery disease, and seven genes with COVID-19 severity. This study created a comprehensive eQTL resource via BioData Catalyst that will be made available to the scientific community. This will advance understanding of the genetic architecture of gene expression underlying a wide range of diseases.
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149
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Wang L, Wang Y, Bian Z, Ma J, Huang J. [A nonlocal spectral similarity-induced material decomposition method for noise reduction of dual-energy CT images]. Nan Fang Yi Ke Da Xue Xue Bao 2022; 42:724-732. [PMID: 35673917 DOI: 10.12122/j.issn.1673-4254.2022.05.14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
OBJECTIVE To propose a nonlocal spectral similarity-induced material decomposition network (NSSD-Net) to reduce the correlation noise in the low-dose spectral CT decomposed images. METHODS We first built a model-driven iterative decomposition model for dual-energy CT, optimized the objective function solving process using the iterative shrinking threshold algorithm (ISTA), and cast the ISTA decomposition model into the deep learning network. We then developed a novel cost function based on the nonlocal spectral similarity to constrain the training process. To validate the decomposition performance, we established a material decomposition dataset by real patient dual-energy CT data. The NSSD-Net was compared with two traditional model-driven material decomposition methods, one data-based material decomposition method and one data-model coupling-driven material decomposition supervised learning method. RESULTS The quantitative results showed that compared with the two traditional methods, the NSSD-Net method obtained the highest PNSR values (31.383 and 31.444) and SSIM values (0.970 and 0.963) and the lowest RMSE values (2.901 and 1.633). Compared with the datamodel coupling-driven supervised decomposition method, the NSSD-Net method obtained the highest SSIM values on water and bone decomposed results. The results of subjective image quality assessment by clinical experts showed that the NSSD-Net achieved the highest image quality assessment scores on water and bone basis material (8.625 and 8.250), showing significant differences from the other 4 decomposition methods (P < 0.001). CONCLUSION The proposed method can achieve high-precision material decomposition and avoid training data quality issues and model unexplainable issues.
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Affiliation(s)
- L Wang
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.,Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Guangzhou 510515, China
| | - Y Wang
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.,Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Guangzhou 510515, China
| | - Z Bian
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.,Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Guangzhou 510515, China
| | - J Ma
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.,Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Guangzhou 510515, China
| | - J Huang
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.,Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Guangzhou 510515, China
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150
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Ali N, Tian H, Thabane L, Ma J, Wu H, Zhong Q, Gao Y, Sun C, Zhu Y, Wang T. The Effects of Dual-Task Training on Cognitive and Physical Functions in Older Adults with Cognitive Impairment; A Systematic Review and Meta-Analysis. J Prev Alzheimers Dis 2022; 9:359-370. [PMID: 35543010 DOI: 10.14283/jpad.2022.16] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
BACKGROUND AND OBJECTIVE Individuals with Alzheimer disease and dementia experience cognitive decline and reduction in physical capabilities. Engaging in cognitive challenges and physical exercises is effective in reducing age-related cognitive and physical decline. It is believed that physical activity in the context of cognitive challenges might enhance the process of neurogenesis in the adult brain, but how effective are such interventions? Is there enough evidence to support that dual-task training is more effective than cognitive or physical training alone? To what extent can such training improve cognitive and physical functions in patients at various stages of cognitive decline? METHODOLOGY This systematic review with meta-analysis summarizes the emerging evidence of dual-task training for enhancing cognitive and physical functions in older individuals with cognitive impairment, dementia or Alzheimer's disease. A systematic search was carried out in MEDLINE, PubMed, EMBASE, and Cochrane Library with the following search terms: randomized control trials, dual-task training, SCD, MCI, dementia, and Alzheimer's disease. RESULTS A total of 21 studies with 2,221 participants were identified. The results of dual-task tanning intervention are summarized as change in global cognitive function; SMD = 0.24, (P= 0.002), memory; SMD = 0.28, (P = 0.000), executive function; SMD = 0.35, (P = 0.000), attention; SMD = -0.19, (P = 0.1), gait speed; SMD = 0.26, (P = 0.007), dual-task cost; SMD 0.56, (P = 0.000), and balance; SMD 0.36, (P = 0.004). CONCLUSION Primary analysis showed a small-to-medium positive effect of dual-task training interventions on cognitive functions and medium-to-large positive effect on gait functions and balance.
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Affiliation(s)
- N Ali
- Tong Wang, Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, No. 300 of Guangzhou Road, Nanjing, Jiangsu 210029, China. Tel: +86 13951680478, fax: +862583318752. E-mail: ; Yi Zhu, Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, No. 300 of Guangzhou Road, Nanjing, Jiangsu 210029, China. Tel: +86 13705164030, fax: +862583318752. E-mail:
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