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2. Periodontitis and Outer Retinal Thickness: a Cross-Sectional Analysis of the United Kingdom Biobank Cohort

Author

Allen, Naomi, Aslam, Tariq, Atan, Denize, Balaskas, Konsantinos, Barman, Sarah A., Barrett, Jenny H., Bishop, Paul, Black, Graeme, Braithwaite, Tasanee, Carare, Roxana O., Chakravarthy, Usha, Chan, Michelle, Chua, Sharon Y.L., Day, Alexander, Desai, Parul, Dhillon, Bal, Dick, Andrew D., Doney, Alexander, Egan, Cathy, Ennis, Sarah, Foster, Paul, Fruttiger, Marcus, Gallacher, John E.J., Garway-Heath, David F., Gibson, Jane, Guggenheim, Jeremy A., Hammond, Chris J., Hardcastle, Alison, Harding, Simon P., Hogg, Ruth E., Hysi, Pirro, Keane, Pearse A., Khaw, Sir Peng T., Khawaja, Anthony P., Lascaratos, Gerassimos, Littlejohns, Thoams, Lotery, Andrew J., Luben, Robert, Luthert, Phil, Macgillivray, Tom, Mackie, Sarah, McGuinness, Bernadette, McKay, Gareth J., McKibbin, Martin, Moore, Tony, Morgan, James E., O’Sullivan, Eoin, Oram, Richard, Owen, Chris G., Patel, Praveen, Paterson, Euan, Peto, Tunde, Petzold, Axel, Rahi, Jugnoo S., Rudnikca, Alicja R., Sattar, Naveed, Self, Jay, Sergouniotis, Panagiotis, Sivaprasad, Sobha, Steel, David, Stratton, Irene, Strouthidis, Nicholas, Sudlow, Cathie, Sun, Zihan, Tapp, Robyn, Thomas, Dhanes, Trucco, Emanuele, Tufail, Adnan, Vitart, Veronique, Viswanathan, Ananth C., Weedon, Mike, Williams, Cathy, Williams, Katie, Woodside, Jayne V., Yates, Max M., Yip, Jennifer, Zheng, Yalin, Wagner, Siegfried K., Patel, Praveen J., Huemer, Josef, Khalid, Hagar, Stuart, Kelsey V., Chu, Colin J., Williamson, Dominic J., Struyven, Robbert R., Romero-Bascones, David, Foster, Paul J., Balaskas, Konstantinos, Cortina-Borja, Mario, Chapple, Iain, Dietrich, Thomas, and Denniston, Alastair K.

Published
2024
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4. Associations between unilateral amblyopia in childhood and cardiometabolic disorders in adult life: a cross-sectional and longitudinal analysis of the UK Biobank

Author

Allen, Naomi, Aslam, Tariq, Atan, Denize, Balaskas, Konstantinos, Barman, Sarah, Barrett, Jenny, Bishop, Paul, Black, Graeme, Braithwaite, Tasanee, Carare, Roxana, Chakravarthy, Usha, Chan, Michelle, Chua, Sharon, Day, Alexander, Desai, Parul, Dhillon, Bal, Dick, Andrew, Doney, Alexander, Egan, Cathy, Ennis, Sarah, Foster, Paul, Fruttiger, Marcus, Gallacher, John, Garway-heath, David (Ted), Gibson, Jane, Guggenheim, Jeremy, Hammond, Chris, Hardcastle, Alison, Harding, Simon, Hogg, Ruth, Hysi, Pirro, Keane, Pearse, Tee Khaw, Sir Peng, Khawaja, Anthony, Lascaratos, Gerassimos, Littlejohns, Thomas, Lotery, Andrew, Luben, Robert, Luthert, Phil, Macgillivray, Tom, Mackie, Sarah, Madhusudhan, Savita, Mcguinness, Bernadette, Mckay, Gareth, Mckibbin, Martin, Moore, Tony, Morgan, James, O'sullivan, Eoin, Oram, Richard, Owen, Chris, Patel, Praveen, Paterson, Euan, Peto, Tunde, Petzold, Axel, Pontikos, Nikolas, Rahi, Jugnoo, Rudnicka, Alicja, Sattar, Naveed, Self, Jay, Sergouniotis, Panagiotis, Sivaprasad, Sobha, Steel, David, Stratton, Irene, Strouthidis, Nicholas, Sudlow, Cathie, Sun, Zihan, Tapp, Robyn, Thomas, Dhanes, Trucco, Emanuele, Tufail, Adnan, Viswanathan, Ananth, Vitart, Veronique, Weedon, Mike, Williams, Katie, Williams, Cathy, Woodside, Jayne, Yates, Max, Zheng, Yalin, Thomas, Mervyn, Wagner, Siegfried Karl, Bountziouka, Vasiliki, and Rahi, Jugnoo Sangeeta

Published
2024
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5. The Association of Urinary Sodium Excretion with Glaucoma and Related Traits in a Large United Kingdom Population

Author

Aschard, Hugues, Chia, Mark, Chua, Sharon, Do, Ron, Foster, Paul, Kang, Jae, Kastner, Alan, Khawaja, Anthony, Kim, Jihye, Lentjes, Marleen, Luben, Robert, Madjedi, Kian, Montesano, Giovanni, Pasquale, Louis, Stuart, Kelsey, Warwick, Alasdair, Wiggs, Janey, Allen, Naomi, Aslam, Tariq, Atan, Denize, Barman, Sarah, Barrett, Jenny, Bishop, Paul, Black, Graeme, Braithwaite, Tasanee, Carare, Roxana, Chakravarthy, Usha, Chan, Michelle, Day, Alexander, Desai, Parul, Dhillon, Bal, Dick, Andrew, Doney, Alexander, Egan, Cathy, Ennis, Sarah, Fruttiger, Marcus, Garway-Heath, David (Ted), Gibson, Jane, Guggenheim, Jeremy, Hammond, Chris, Hardcastle, Alison, Harding, Simon, Hogg, Ruth, Hysi, Pirro, Keane, Pearse, Khaw, Peng Tee, Lascaratos, Gerassimos, Littlejohns, Thomas, Lotery, Andrew, Luthert, Phil, MacGillivray, Tom, Mackie, Sarah, McGuinness, Bernadette, McKay, Gareth, McKibbin, Martin, Moore, Tony, Morgan, James, O'Sullivan, Eoin, Oram, Richard, Owen, Chris, Patel, Praveen, Paterson, Euan, Peto, Tunde, Petzold, Axel, Pontikos, Nikolas, Rahi, Jugnoo, Rudnicka, Alicja, Sattar, Naveed, Self, Jay, Sergouniotis, Panagiotis, Sivaprasad, Sobha, Steel, David, Stratton, Irene, Strouthidis, Nicholas, Sudlow, Cathie, Sun, Zihan, Tapp, Robyn, Thomas, Dhanes, Trucco, Emanuele, Tufail, Adnan, Viswanathan, Ananth, Vitart, Veronique, Weedon, Mike, Williams, Katie, Williams, Cathy, Woodside, Jayne, Yates, Max, Yip, Jennifer, Zheng, Yalin, Aung, Tin, Burdon, Kathryn, Chen, Li, Cheng, Ching-Yu, Craig, Jamie, Cree, Angela, de Vries, Victor, Driessen, Sjoerd, Fingert, John, Gharahkhani, Puya, Hammond, Christopher, Hayward, Caroline, Hewitt, Alex, Jansonius, Nomdo, Jonansson, Fridbert, Jonas, Jost, Kass, Michael, Khor, Chiea, Klaver, Caroline, Koh, Jacyline, MacGregor, Stuart, Mackey, David, Mitchell, Paul, Pang, Calvin, Pasutto, Francesca, Pfeiffer, Norbert, Polašek, Ozren, Ramdas, Wishal, Schuster, Alexander, Segrè, Ayellet, Stefansson, Einer, Stefánsson, Kári, Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, van Duijn, Cornelia, Vergroesen, Joëlle, Vithana, Eranga, Wilson, James, Wojciechowski, Robert, Wong, Tien, Young, Terri, Stuart, Kelsey V., Biradar, Mahantesh I., Luben, Robert N., Dhaun, Neeraj, Wagner, Siegfried K., Warwick, Alasdair N., Madjedi, Kian M., Pasquale, Louis R., Wiggs, Janey L., Kang, Jae H., Lentjes, Marleen A.H., Foster, Paul J., and Khawaja, Anthony P.

Published
2024
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6. The Association of Urinary Sodium Excretion with Glaucoma and Related Traits in a Large United Kingdom Population

Author

Stuart, Kelsey V., primary, Biradar, Mahantesh I., additional, Luben, Robert N., additional, Dhaun, Neeraj, additional, Wagner, Siegfried K., additional, Warwick, Alasdair N., additional, Sun, Zihan, additional, Madjedi, Kian M., additional, Pasquale, Louis R., additional, Wiggs, Janey L., additional, Kang, Jae H., additional, Lentjes, Marleen A.H., additional, Aschard, Hugues, additional, Kim, Jihye, additional, Foster, Paul J., additional, Khawaja, Anthony P., additional, Chia, Mark, additional, Chua, Sharon, additional, Do, Ron, additional, Foster, Paul, additional, Kang, Jae, additional, Kastner, Alan, additional, Khawaja, Anthony, additional, Lentjes, Marleen, additional, Luben, Robert, additional, Madjedi, Kian, additional, Montesano, Giovanni, additional, Pasquale, Louis, additional, Stuart, Kelsey, additional, Warwick, Alasdair, additional, Wiggs, Janey, additional, Allen, Naomi, additional, Aslam, Tariq, additional, Atan, Denize, additional, Barman, Sarah, additional, Barrett, Jenny, additional, Bishop, Paul, additional, Black, Graeme, additional, Braithwaite, Tasanee, additional, Carare, Roxana, additional, Chakravarthy, Usha, additional, Chan, Michelle, additional, Day, Alexander, additional, Desai, Parul, additional, Dhillon, Bal, additional, Dick, Andrew, additional, Doney, Alexander, additional, Egan, Cathy, additional, Ennis, Sarah, additional, Fruttiger, Marcus, additional, Garway-Heath, David (Ted), additional, Gibson, Jane, additional, Guggenheim, Jeremy, additional, Hammond, Chris, additional, Hardcastle, Alison, additional, Harding, Simon, additional, Hogg, Ruth, additional, Hysi, Pirro, additional, Keane, Pearse, additional, Khaw, Peng Tee, additional, Lascaratos, Gerassimos, additional, Littlejohns, Thomas, additional, Lotery, Andrew, additional, Luthert, Phil, additional, MacGillivray, Tom, additional, Mackie, Sarah, additional, McGuinness, Bernadette, additional, McKay, Gareth, additional, McKibbin, Martin, additional, Moore, Tony, additional, Morgan, James, additional, O'Sullivan, Eoin, additional, Oram, Richard, additional, Owen, Chris, additional, Patel, Praveen, additional, Paterson, Euan, additional, Peto, Tunde, additional, Petzold, Axel, additional, Pontikos, Nikolas, additional, Rahi, Jugnoo, additional, Rudnicka, Alicja, additional, Sattar, Naveed, additional, Self, Jay, additional, Sergouniotis, Panagiotis, additional, Sivaprasad, Sobha, additional, Steel, David, additional, Stratton, Irene, additional, Strouthidis, Nicholas, additional, Sudlow, Cathie, additional, Tapp, Robyn, additional, Thomas, Dhanes, additional, Trucco, Emanuele, additional, Tufail, Adnan, additional, Viswanathan, Ananth, additional, Vitart, Veronique, additional, Weedon, Mike, additional, Williams, Katie, additional, Williams, Cathy, additional, Woodside, Jayne, additional, Yates, Max, additional, Yip, Jennifer, additional, Zheng, Yalin, additional, Aung, Tin, additional, Burdon, Kathryn, additional, Chen, Li, additional, Cheng, Ching-Yu, additional, Craig, Jamie, additional, Cree, Angela, additional, de Vries, Victor, additional, Driessen, Sjoerd, additional, Fingert, John, additional, Gharahkhani, Puya, additional, Hammond, Christopher, additional, Hayward, Caroline, additional, Hewitt, Alex, additional, Jansonius, Nomdo, additional, Jonansson, Fridbert, additional, Jonas, Jost, additional, Kass, Michael, additional, Khor, Chiea, additional, Klaver, Caroline, additional, Koh, Jacyline, additional, MacGregor, Stuart, additional, Mackey, David, additional, Mitchell, Paul, additional, Pang, Calvin, additional, Pasutto, Francesca, additional, Pfeiffer, Norbert, additional, Polašek, Ozren, additional, Ramdas, Wishal, additional, Schuster, Alexander, additional, Segrè, Ayellet, additional, Stefansson, Einer, additional, Stefánsson, Kári, additional, Thorleifsson, Gudmar, additional, Thorsteinsdottir, Unnur, additional, van Duijn, Cornelia, additional, Vergroesen, Joëlle, additional, Vithana, Eranga, additional, Wilson, James, additional, Wojciechowski, Robert, additional, Wong, Tien, additional, and Young, Terri, additional

Published
2024
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7. Associations between unilateral amblyopia in childhood and cardiometabolic disorders in adult life: a cross-sectional and longitudinal analysis of the UK Biobank

Author

Wagner, Siegfried Karl, primary, Bountziouka, Vasiliki, additional, Hysi, Pirro, additional, Rahi, Jugnoo Sangeeta, additional, Allen, Naomi, additional, Aslam, Tariq, additional, Atan, Denize, additional, Balaskas, Konstantinos, additional, Barman, Sarah, additional, Barrett, Jenny, additional, Bishop, Paul, additional, Black, Graeme, additional, Braithwaite, Tasanee, additional, Carare, Roxana, additional, Chakravarthy, Usha, additional, Chan, Michelle, additional, Chua, Sharon, additional, Day, Alexander, additional, Desai, Parul, additional, Dhillon, Bal, additional, Dick, Andrew, additional, Doney, Alexander, additional, Egan, Cathy, additional, Ennis, Sarah, additional, Foster, Paul, additional, Fruttiger, Marcus, additional, Gallacher, John, additional, Garway-heath, David (Ted), additional, Gibson, Jane, additional, Guggenheim, Jeremy, additional, Hammond, Chris, additional, Hardcastle, Alison, additional, Harding, Simon, additional, Hogg, Ruth, additional, Keane, Pearse, additional, Tee Khaw, Sir Peng, additional, Khawaja, Anthony, additional, Lascaratos, Gerassimos, additional, Littlejohns, Thomas, additional, Lotery, Andrew, additional, Luben, Robert, additional, Luthert, Phil, additional, Macgillivray, Tom, additional, Mackie, Sarah, additional, Madhusudhan, Savita, additional, Mcguinness, Bernadette, additional, Mckay, Gareth, additional, Mckibbin, Martin, additional, Moore, Tony, additional, Morgan, James, additional, O'sullivan, Eoin, additional, Oram, Richard, additional, Owen, Chris, additional, Patel, Praveen, additional, Paterson, Euan, additional, Peto, Tunde, additional, Petzold, Axel, additional, Pontikos, Nikolas, additional, Rahi, Jugnoo, additional, Rudnicka, Alicja, additional, Sattar, Naveed, additional, Self, Jay, additional, Sergouniotis, Panagiotis, additional, Sivaprasad, Sobha, additional, Steel, David, additional, Stratton, Irene, additional, Strouthidis, Nicholas, additional, Sudlow, Cathie, additional, Sun, Zihan, additional, Tapp, Robyn, additional, Thomas, Dhanes, additional, Trucco, Emanuele, additional, Tufail, Adnan, additional, Viswanathan, Ananth, additional, Vitart, Veronique, additional, Weedon, Mike, additional, Williams, Katie, additional, Williams, Cathy, additional, Woodside, Jayne, additional, Yates, Max, additional, Zheng, Yalin, additional, and Thomas, Mervyn, additional

Published
2024
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8. New role of fat-free mass in cancer risk linked with genetic predisposition

Author

Harris, Benjamin H. L., primary, Di Giovannantonio, Matteo, additional, Zhang, Ping, additional, Harris, David A., additional, Lord, Simon R., additional, Allen, Naomi E., additional, Maughan, Tim S., additional, Bryant, Richard J., additional, Harris, Adrian L., additional, Bond, Gareth L., additional, and Buffa, Francesca M., additional

Published
2024
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9. Prospective evaluation of the relevance of Epstein–Barr virus antibodies for early detection of nasopharyngeal carcinoma in Chinese adults.

Author

Yang, Ling, Kartsonaki, Christiana, Simon, Julia, Yao, Pang, Guo, Yu, Lv, Jun, Walters, Robin G, Chen, Yiping, Fry, Hannah, Avery, Daniel, Yu, Canqing, Jin, Jianrong, Mentzer, Alexander J, Allen, Naomi, Butt, Julia, Hill, Michael, Li, Liming, Millwood, Iona Y, Waterboer, Tim, and Chen, Zhengming

Abstract

Background Epstein–Barr virus (EBV) is a major cause of nasopharyngeal carcinoma (NPC) and measurement of different EBV antibodies in blood may improve early detection of NPC. Prospective studies can help assess the roles of different EBV antibodies in predicting NPC risk over time. Methods A case-cohort study within the prospective China Kadoorie Biobank of 512 715 adults from 10 (including two NPC endemic) areas included 295 incident NPC cases and 745 subcohort participants. A multiplex serology assay was used to quantify IgA and IgG antibodies against 16 EBV antigens in stored baseline plasma samples. Cox regression was used to estimate adjusted hazard ratios (HRs) for NPC and C-statistics to assess the discriminatory ability of EBV-markers, including two previously identified EBV-marker combinations, for predicting NPC. Results Sero-positivity for 15 out of 16 EBV-markers was significantly associated with higher NPC risk. Both IgA and IgG antibodies against the same three EBV-markers showed the most extreme HRs, i.e. BGLF2 (IgA: 124.2 (95% CI: 63.3–243.9); IgG: 8.6 (5.5–13.5); LF2: [67.8 (30.0–153.1), 10.9 (7.2–16.4)]); and BFRF1: 26.1 (10.1–67.5), 6.1 (2.7–13.6). Use of a two-marker (i.e. LF2/BGLF2 IgG) and a four-marker (i.e. LF2/BGLF2 IgG and LF2/EA-D IgA) combinations yielded C-statistics of 0.85 and 0.84, respectively, which persisted for at least 5 years after sample collection in both endemic and non-endemic areas. Conclusions In Chinese adults, plasma EBV markers strongly predict NPC occurrence many years before clinical diagnosis. LF2 and BGLF2 IgG could identify NPC high-risk individuals to improve NPC early detection in community and clinical settings. [ABSTRACT FROM AUTHOR]

Published
2024
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10. Association of Metabolic Syndrome With Neuroimaging and Cognitive Outcomes in the UK Biobank.

Author

Qureshi, Danial, Topiwala, Anya, Al Abid, Shehab Uddin, Allen, Naomi E., Kuźma, Elżbieta, and Littlejohns, Thomas J.

Subjects
METABOLIC syndrome, COGNITIVE testing, EXECUTIVE function, COGNITION, VERBAL memory, VERBAL learning, VASCULAR dementia, EXPLICIT memory
Abstract

OBJECTIVE: Metabolic syndrome (MetS) has been linked to dementia. In this study, we examined the association of MetS with neuroimaging and cognition in dementia-free adults, offering insight into the impact of MetS on brain health prior to dementia onset. RESEARCH DESIGN AND METHODS: We included 37,395 dementia-free adults from the UK Biobank database. MetS was defined as having at least three of the following components: larger waist circumference; elevated levels of triglycerides, blood pressure, HbA1c; or reduced HDL cholesterol levels. Multivariable-adjusted linear regression was used to assess associations of MetS with structural neuroimaging and cognitive domains. RESULTS: MetS was associated with lower total brain (standardized β: −0.06; 95% CI −0.08, −0.04), gray matter (β: −0.10; 95% CI −0.12, −0.08) and hippocampal (for left side, β: −0.03, 95% CI −0.05, −0.01; for right side, β: −0.04, 95% CI −0.07, −0.02) volumes, and greater white matter hyperintensity (WMH) volume (β: 0.08; 95% CI 0.06, 0.11). Study participants with MetS performed poorer on cognitive tests of working memory (β: −0.10; 95% CI −0.13, −0.07), verbal declarative memory (β: −0.08; 95% CI −0.11, −0.05), processing speed (β: −0.06; 95% CI −0.09, −0.04), verbal and numerical reasoning (β: −0.07; 95% CI −0.09, −0.04), nonverbal reasoning (β: −0.03; 95% CI −0.05, −0.01), and on tests of executive function, where higher scores indicated poorer performance (β: 0.05; 95% CI 0.03, 0.08). More MetS components were also associated with less brain volume, greater WMH, and poorer cognition across all domains. CONCLUSIONS: MetS was associated poorer brain health in dementia-free adults, characterized by less brain volume, greater vascular pathology, and poorer cognition. Further research is necessary to understand whether reversal or improvement of MetS can improve brain health. [ABSTRACT FROM AUTHOR]

Published
2024
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11. Plasma proteomic evidence for increased Alzheimer’s disease-related brain pathology after SARS-CoV-2 infection

Author

Duff, Eugene P, primary, Zetterberg, Henrik, additional, Heslegrave, Amanda, additional, Dehghan, Abbas, additional, Elliott, Paul, additional, Allen, Naomi, additional, Runz, Heiko, additional, Laban, Rhiannon, additional, Veleva, Elena, additional, Whelan, Christopher D, additional, Sun, Benjamin B, additional, and Matthews, Paul M, additional

Published
2024
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13. Prospective study design and data analysis in UK Biobank

Author

Allen, Naomi E., primary, Lacey, Ben, additional, Lawlor, Deborah A., additional, Pell, Jill P., additional, Gallacher, John, additional, Smeeth, Liam, additional, Elliott, Paul, additional, Matthews, Paul M., additional, Lyons, Ronan A., additional, Whetton, Anthony D., additional, Lucassen, Anneke, additional, Hurles, Matthew E., additional, Chapman, Michael, additional, Roddam, Andrew W., additional, Fitzpatrick, Natalie K., additional, Hansell, Anna L., additional, Hardy, Rebecca, additional, Marioni, Riccardo E., additional, O’Donnell, Valerie B., additional, Williams, Julie, additional, Lindgren, Cecilia M., additional, Effingham, Mark, additional, Sellors, Jonathan, additional, Danesh, John, additional, and Collins, Rory, additional

Published
2024
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14. Periodontitis and outer retinal thickness: A cross-sectional analysis of the UK Biobank cohort

Author

Wagner, Siegfried K., primary, Patel, Praveen J., additional, Huemer, Josef, additional, Khalid, Hagar, additional, Stuart, Kelsey V., additional, Chu, Colin J., additional, Williamson, Dominic J., additional, Struyven, Robbert R., additional, Romero-Bascones, David, additional, Foster, Paul J., additional, Khawaja, Anthony P., additional, Petzold, Axel, additional, Balaskas, Konstantinos, additional, Cortina-Borja, Mario, additional, Chapple, Iain, additional, Dietrich, Thomas, additional, Rahi, Jugnoo S., additional, Denniston, Alastair K., additional, Keane, Pearse A., additional, Allen, Naomi, additional, Aslam, Tariq, additional, Atan, Denize, additional, Balaskas, Konsantinos, additional, Barman, Sarah A., additional, Barrett, Jenny H., additional, Bishop, Paul, additional, Black, Graeme, additional, Braithwaite, Tasanee, additional, Carare, Roxana O., additional, Chakravarthy, Usha, additional, Chan, Michelle, additional, Chua, Sharon Y.L., additional, Day, Alexander, additional, Desai, Parul, additional, Dhillon, Bal, additional, Dick, Andrew D., additional, Doney, Alexander, additional, Egan, Cathy, additional, Ennis, Sarah, additional, Foster, Paul, additional, Fruttiger, Marcus, additional, Gallacher, John E.J., additional, Garway-Heath, David F., additional, Gibson, Jane, additional, Guggenheim, Jeremy A., additional, Hammond, Chris J., additional, Hardcastle, Alison, additional, Harding, Simon P., additional, Hogg, Ruth E., additional, Hysi, Pirro, additional, Khaw, Sir Peng T., additional, Lascaratos, Gerassimos, additional, Littlejohns, Thoams, additional, Lotery, Andrew J., additional, Luben, Robert, additional, Luthert, Phil, additional, Macgillivray, Tom, additional, Mackie, Sarah, additional, McGuinness, Bernadette, additional, McKay, Gareth J., additional, McKibbin, Martin, additional, Moore, Tony, additional, Morgan, James E., additional, O’Sullivan, Eoin, additional, Oram, Richard, additional, Owen, Chris G., additional, Patel, Praveen, additional, Paterson, Euan, additional, Peto, Tunde, additional, Rudnikca, Alicja R., additional, Sattar, Naveed, additional, Self, Jay, additional, Sergouniotis, Panagiotis, additional, Sivaprasad, Sobha, additional, Steel, David, additional, Stratton, Irene, additional, Strouthidis, Nicholas, additional, Sudlow, Cathie, additional, Sun, Zihan, additional, Tapp, Robyn, additional, Thomas, Dhanes, additional, Trucco, Emanuele, additional, Tufail, Adnan, additional, Vitart, Veronique, additional, Viswanathan, Ananth C., additional, Weedon, Mike, additional, Williams, Cathy, additional, Williams, Katie, additional, Woodside, Jayne V., additional, Yates, MaxM., additional, Yip, Jennifer, additional, and Zheng, Yalin, additional

Published
2024
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15. Use of Sex-Specific Body Mass Index to Optimize Low Correlation With Height and High Correlation With Fatness: A UK Biobank Study.

Author

Feng, Qi, Kim, Jean H, Xie, Junqing, Bešević, Jelena, Conroy, Megan, Omiyale, Wemimo, Wu, Yushan, Woodward, Mark, Lacey, Ben, and Allen, Naomi

Subjects
STATURE, BODY composition, RESEARCH, BODY weight, MORTALITY, DESCRIPTIVE statistics, BODY mass index, STATISTICAL correlation, STATISTICAL sampling, RECEIVER operating characteristic curves, SENSITIVITY & specificity (Statistics), PREDICTION models, GENDER specific care, ADIPOSE tissues
Abstract

Body mass index (BMI; weight (kg)/height (m)2) is commonly used to measure general adiposity. However, evidence of its appropriateness for males and females remains inconsistent. We aimed to identify the most appropriate sex-specific power value that height should be raised to in the formula and the value that would make it achieve height independency and body fatness dependency. We randomly assigned UK Biobank participants recruited in the United Kingdom between 2006 and 2010 (n  = 489,873; mean age = 56.5 years; 94.2% White) to training and testing sets (80%:20%). Using height raised to the power of −50.00 to 50.00, we identified the optimal power value that either minimized correlation with height or maximized correlation with body fat percentage, using age-adjusted correlations. The optimal power values for height were 1.77 for males and 1.39 for females. The new formulas resulted in 4.5% of females and 2.4% of males being reclassified into a different BMI category. The formulas did not show significant improvement (in terms of area under the receiver operating characteristic curve, sensitivity, and specificity) in identifying individuals with excessive body fat percentage or in predicting risk of all-cause mortality. Therefore, the conventional BMI formula is still valuable in research and disease screening for both sexes. [ABSTRACT FROM AUTHOR]

Published
2024
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16. Association between metabolic syndrome and risk of incident dementia in UK Biobank.

Author

Qureshi, Danial, Collister, Jennifer, Allen, Naomi E., Kuźma, Elżbieta, and Littlejohns, Thomas

Abstract

INTRODUCTION: The association between metabolic syndrome (MetS) and incident dementia remains inconclusive. METHODS: In 176,249 dementia‐free UK Biobank participants aged ≥60 years at baseline, Cox proportional‐hazards models were used to investigate the association between MetS and incident dementia. MetS was defined as the presence of ≥3 of the following: elevated waist circumference, triglycerides, blood pressure, blood glucose, and reduced high‐density lipoprotein cholesterol. RESULTS: Over 15 years of follow‐up (median = 12.3), 5255 participants developed dementia. MetS was associated with an increased risk of incident dementia (hazard ratio [HR]: 1.12, 95% confidence interval [CI]: 1.06, 1.18). The association remained consistent when restricting to longer follow‐up intervals: >5 to 10 years (HR: 1.17, 95% CI: 1.07, 1.27) and >10 years (HR: 1.22, 95% CI: 1.12, 1.32). Stronger associations were observed in those with ≥4 MetS components and in apolipoprotein‐E (APOE)‐ε4 non‐carriers. DISCUSSION: In this large population‐based prospective cohort, MetS was associated with an increased risk of dementia. Highlights: MetS was associated with a 12% increased risk of incident all‐cause dementia.Associations remained similar after restricting the analysis to those with longer follow‐up.The presence of four or five MetS components was significantly associated with dementia.Stronger associations were observed in those with a low genetic risk for dementia. [ABSTRACT FROM AUTHOR]

Published
2024
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17. Social determinants of ethnic disparities in SARSCoV-2 infection: UK Biobank SARS-CoV-2 Serology Study.

Author

Omiyale, Wemimo, Holliday, Jo, Doherty, Nicola, Callen, Howard, Wood, Natasha, Horn, Edward, Burnett, Frances, Young, Allen, Lewington, Sarah, Fry, Dan, Bešević, Jelena, Conroy, Megan, Sheard, Simon, Qi Feng, Welsh, Samantha, Effingham, Mark, Young, Alan, Collins, Rory, Lacey, Ben, and Allen, Naomi

Subjects
COVID-19, SOCIAL determinants of health, CONFIDENCE intervals, BLOOD collection, RISK assessment, DESCRIPTIVE statistics, RESEARCH funding, HEALTH equity, LOGISTIC regression analysis, ODDS ratio, COVID-19 pandemic
Published
2024
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18. Social determinants of ethnic disparities in SARS-CoV-2 infection: UK Biobank SARS-CoV-2 Serology Study

Author

Omiyale, Wemimo, Holliday, Jo, Doherty, Nicola, Callen, Howard, Wood, Natasha, Horn, Edward, Burnett, Frances, Young, Allen, Lewington, Sarah, Fry, Dan, Bešević, Jelena, Conroy, Megan, Sheard, Simon, Feng, Qi, Welsh, Samantha, Effingham, Mark, Young, Alan, Collins, Rory, Lacey, Ben, and Allen, Naomi

Abstract

BackgroundThe social determinants of ethnic disparities in risk of SARS-CoV-2 infection during the first wave of the pandemic in the UK remain unclear.MethodsIn May 2020, a total of 20 195 adults were recruited from the general population into the UK Biobank SARS-CoV-2 Serology Study. Between mid-May and mid-November 2020, participants provided monthly blood samples. At the end of the study, participants completed a questionnaire on social factors during different periods of the pandemic. Logistic regression yielded ORs for the association between ethnicity and SARS-CoV-2 immunoglobulin G antibodies (indicating prior infection) using blood samples collected in July 2020, immediately after the first wave.ResultsAfter exclusions, 14 571 participants (mean age 56; 58% women) returned a blood sample in July, of whom 997 (7%) had SARS-CoV-2 antibodies. Seropositivity was strongly related to ethnicity: compared with those of White ethnicity, ORs (adjusted for age and sex) for Black, South Asian, Chinese, Mixed and Other ethnic groups were 2.66 (95% CI 1.94–3.60), 1.66 (1.15–2.34), 0.99 (0.42–1.99), 1.42 (1.03–1.91) and 1.79 (1.27–2.47), respectively. Additional adjustment for social factors reduced the overall likelihood ratio statistics for ethnicity by two-thirds (67%; mostly from occupational factors and UK region of residence); more precise measurement of social factors may have further reduced the association.ConclusionsThis study identifies social factors that are likely to account for much of the ethnic disparities in SARS-CoV-2 infection during the first wave in the UK, and highlights the particular relevance of occupation and residential region in the pathway between ethnicity and SARS-CoV-2 infection.

Published
2024
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19. Persistence of SARS-CoV-2 antibodies over 18 months following infection: UK Biobank COVID-19 Serology Study

Author

Bešević, Jelena, Lacey, Ben, Callen, Howard, Omiyale, Wemimo, Conroy, Megan, Feng, Qi, Crook, Derrick W, Doherty, Nicola, Ebner, Daniel, Eyre, David W, Fry, Dan, Horn, Edward, Jones, E Yvonne, Marsden, Brian D, Peto, Tim E A, Starkey, Fenella, Stuart, David, Welsh, Samantha, Wood, Natasha, Young, Alan, Young, Allen, Effingham, Mark, Collins, Rory, Holliday, Jo, and Allen, Naomi

Abstract

BackgroundLittle is known about the persistence of antibodies after the first year following SARS-CoV-2 infection. We aimed to determine the proportion of individuals that maintain detectable levels of SARS-CoV-2 antibodies over an 18-month period following infection.MethodsPopulation-based prospective study of 20 000 UK Biobank participants and their adult relatives recruited in May 2020. The proportion of SARS-CoV-2 cases testing positive for immunoglobulin G (IgG) antibodies against the spike protein (IgG-S), and the nucleocapsid protein (IgG-N), was calculated at varying intervals following infection.ResultsOverall, 20 195 participants were recruited. Their median age was 56 years (IQR 39–68), 56% were female and 88% were of white ethnicity. The proportion of SARS-CoV-2 cases with IgG-S antibodies following infection remained high (92%, 95% CI 90%–93%) at 6 months after infection. Levels of IgG-N antibodies following infection gradually decreased from 92% (95% CI 88%–95%) at 3 months to 72% (95% CI 70%–75%) at 18 months. There was no strong evidence of heterogeneity in antibody persistence by age, sex, ethnicity or socioeconomic deprivation.ConclusionThis study adds to the limited evidence on the long-term persistence of antibodies following SARS-CoV-2 infection, with likely implications for waning immunity following infection and the use of IgG-N in population surveys.

Published
2024
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21. Comparison of body composition measures assessed by bioelectrical impedance analysis versus dual-energy X-ray absorptiometry in the United Kingdom Biobank.

Author

Feng Q, Bešević J, Conroy M, Omiyale W, Lacey B, and Allen N

Abstract

Background: Bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA) serves as common modalities for body composition assessment. This study was aimed to evaluate the agreement between BIA and DXA measures in UK Biobank., Methods: UK Biobank participants with body fat mass (FM) and fat-free mass (FFM) estimates obtained through BIA (Tanita BC418MA) and DXA concurrently were included. Correlation between BIA and DXA-derived estimates were assessed with Lin's concordance correlation coefficients. Bland-Altman and Passing-Boblok analyses were performed to quantify the difference and agreement between BIA and DXA. Multivariable linear regression was used to identify predictors influencing the differences. Finally, prediction models were developed to calibrate BIA measures against DXA., Results: The analysis included 34437 participants (female 51.4%, mean age 64.1 years at imaging assessment). BIA and DXA measurements were highly correlated (Lin's concordance correlation coefficient 0.94 for FM and 0.94 for FFM). BIA (Tanita BC418MA) underestimates FM overall by 1.84 kg (23.77 vs. 25.61, p < 0.01), and overestimated FFM overall by 2.56 kg (52.49 vs. 49.93, p < 0.01). The BIA-DXA differences were associated with FM, FFM, BMI and waist circumference. The developed prediction models showed overall good performance in calibrating BIA data., Conclusion: Our analysis exhibited strong correlation between BIA (Tanita BC418MA)- and DXA-derived body composition measures at a population level in UK Biobank. However, the BIA-DXA differences were observed at individual level and associated with individual anthropometric measures. Future studies may explore the use of prediction models to enhance the calibration of BIA measures for more accurate assessments in UK Biobank., Competing Interests: Declaration of competing interest There is no conflict of interest., (Copyright © 2024. Published by Elsevier Ltd.)

Published
2024
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22. Association between metabolic syndrome and risk of incident dementia in UK Biobank.

Author

Qureshi D, Collister J, Allen NE, Kuźma E, and Littlejohns T

Subjects
Humans, Prospective Studies, Biological Specimen Banks, UK Biobank, Risk Factors, Incidence, Metabolic Syndrome epidemiology, Metabolic Syndrome complications, Dementia epidemiology, Dementia complications
Abstract

Introduction: The association between metabolic syndrome (MetS) and incident dementia remains inconclusive., Methods: In 176,249 dementia-free UK Biobank participants aged ≥60 years at baseline, Cox proportional-hazards models were used to investigate the association between MetS and incident dementia. MetS was defined as the presence of ≥3 of the following: elevated waist circumference, triglycerides, blood pressure, blood glucose, and reduced high-density lipoprotein cholesterol., Results: Over 15 years of follow-up (median = 12.3), 5255 participants developed dementia. MetS was associated with an increased risk of incident dementia (hazard ratio [HR]: 1.12, 95% confidence interval [CI]: 1.06, 1.18). The association remained consistent when restricting to longer follow-up intervals: >5 to 10 years (HR: 1.17, 95% CI: 1.07, 1.27) and >10 years (HR: 1.22, 95% CI: 1.12, 1.32). Stronger associations were observed in those with ≥4 MetS components and in apolipoprotein-E (APOE)-ε4 non-carriers., Discussion: In this large population-based prospective cohort, MetS was associated with an increased risk of dementia., Highlights: MetS was associated with a 12% increased risk of incident all-cause dementia. Associations remained similar after restricting the analysis to those with longer follow-up. The presence of four or five MetS components was significantly associated with dementia. Stronger associations were observed in those with a low genetic risk for dementia., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Published
2024
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