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Health and Liver Diagnostic Markers Influencing Glycemia in Subjects with Prediabetes: Preview Study

Omar Ramos-Lopez Orcid Logo, Diego Martinez-Urbistondo Orcid Logo, Santiago Navas-Carretero Orcid Logo, Ruixin Zhu, Maija Huttunen-Lenz Orcid Logo, Gareth Stratton Orcid Logo, Teodora Handjieva-Darlenska, Svetoslav Handjiev, Jouko Ensio Sundvall, Marta P. Silvestre Orcid Logo, Elli Jalo Orcid Logo, Kirsi H. Pietiläinen Orcid Logo, Tanja C. Adam, Margriet Westerterp-Plantenga Orcid Logo, Elizabeth Simpson, Ian MacDonald, Moira A. Taylor Orcid Logo, Sally D. Poppitt Orcid Logo, Wolfgang Schlicht Orcid Logo, Jennie Brand-Miller Orcid Logo, Mikael Fogelholm Orcid Logo, Anne Raben Orcid Logo, J. Alfredo Martinez

Diagnostics, Volume: 14, Issue: 24, Start page: 2895

Swansea University Author: Gareth Stratton Orcid Logo

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DOI (Published version): 10.3390/diagnostics14242895

Abstract

Introduction: Glucose homeostasis may be dependent on liver conditions and influence health-related markers and quality of life (QoL) objective measurements. This study aimed to analyze the interactions of glycemia with liver and health status in a prediabetic population. Subjects and methods: This...

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Published in: Diagnostics
ISSN: 2075-4418
Published: MDPI AG 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa68638
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Anthropometrics; clinical, metabolic and other health-related markers; and QoL variables were analyzed. Univariate and multilinear-adjusted regression models were run to explain the interrelationships and effect modification between glycemia, health-related QoL (applying SF-12) and metabolic/liver health (using the HSI, a putative marker of fatty liver). Results: Relevant age/sex interactions were found concerning the levels of insulin, HOMA-IR, C peptide and transaminases in this prediabetic population. Multivariate models identified age, sex, glucose, WC and QoL as important predictors of HSI variability (adj. R value = 0.1393, p &amp;lt; 0.001), whereas the QoL status was statistically related to age, sex, HOMA-IR and HSI (adj. R value = 0.1130, p &amp;lt; 0.001) in this glycemia-impaired group. Furthermore, the QoL values declined with increased HSI scores, where a significant interaction was found (p = 0.011) when the data were analyzed when comparing lower glycemia vs. higher glycemia in prediabetics. Indeed, an effect modification was featured depending on the glycemia levels concerning the QoL and HSI worsening. Conclusion: Glycemia associations with the QoL status and liver metabolism markers were evidenced, with clinical implications for diabetes and liver disease precision management given the modification of the QoL outcomes depending on the liver status and glycemia concentrations. Notably, independent associations of circulating glucose with age, sex, adiposity, inflammation and C peptide levels were found.</abstract><type>Journal Article</type><journal>Diagnostics</journal><volume>14</volume><journalNumber>24</journalNumber><paginationStart>2895</paginationStart><paginationEnd/><publisher>MDPI AG</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>2075-4418</issnElectronic><keywords>Prediabetes; adiposity; fatty liver; quality of life</keywords><publishedDay>23</publishedDay><publishedMonth>12</publishedMonth><publishedYear>2024</publishedYear><publishedDate>2024-12-23</publishedDate><doi>10.3390/diagnostics14242895</doi><url/><notes/><college>COLLEGE NANME</college><department>Engineering and Applied Sciences School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>EAAS</DepartmentCode><institution>Swansea University</institution><apcterm>Another institution paid the OA fee</apcterm><funders>This research was supported by the EU Seventh Framework Programme (FP7; 2007&#x2013;2013) (grant no. 312057), National Health and Medical Research Council (EU Collaborative Grant AUS 8, ID 1067711), Glycemic Index Foundation Australia through royalties to the University of Sydney, Health Research Council of New Zealand (grant no. 14/191), University of Auckland Faculty Research Development Fund, Cambridge Weight Plan, Danish Agriculture and Food Council, Danish Meat Research Institute, National Institute for Health Research Biomedical Research Centre (NIHR BRC) (UK), Biotechnology and Biological Sciences Research Council (BBSRC) (UK), Engineering and Physical Sciences Research Council (EPSRC) (UK), Nutritics (Dublin), Juho Vainio Foundation (Finland), Academy of Finland (grants no. 272376, 314383, 266286 and 314135), Finnish Medical Foundation, Gyllenberg Foundation (Finland), Novo Nordisk Foundation, Finnish Diabetes Research Foundation, University of Helsinki, Government Research Funds for Helsinki University Hospital, Jenny and Antti Wihuri Foundation (Finland), Emil Aaltonen Foundation (Finland) and China Scholarship Council.</funders><projectreference/><lastEdited>2025-01-31T10:27:04.9783365</lastEdited><Created>2025-01-02T15:15:07.8827298</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Engineering and Applied Sciences - Sport and Exercise Sciences</level></path><authors><author><firstname>Omar</firstname><surname>Ramos-Lopez</surname><orcid>0000-0002-2505-1555</orcid><order>1</order></author><author><firstname>Diego</firstname><surname>Martinez-Urbistondo</surname><orcid>0000-0002-0530-7349</orcid><order>2</order></author><author><firstname>Santiago</firstname><surname>Navas-Carretero</surname><orcid>0000-0002-5163-2230</orcid><order>3</order></author><author><firstname>Ruixin</firstname><surname>Zhu</surname><order>4</order></author><author><firstname>Maija</firstname><surname>Huttunen-Lenz</surname><orcid>0000-0002-1034-1613</orcid><order>5</order></author><author><firstname>Gareth</firstname><surname>Stratton</surname><orcid>0000-0001-5618-0803</orcid><order>6</order></author><author><firstname>Teodora</firstname><surname>Handjieva-Darlenska</surname><order>7</order></author><author><firstname>Svetoslav</firstname><surname>Handjiev</surname><order>8</order></author><author><firstname>Jouko Ensio</firstname><surname>Sundvall</surname><order>9</order></author><author><firstname>Marta P.</firstname><surname>Silvestre</surname><orcid>0000-0001-9327-2897</orcid><order>10</order></author><author><firstname>Elli</firstname><surname>Jalo</surname><orcid>0000-0002-9987-1716</orcid><order>11</order></author><author><firstname>Kirsi H.</firstname><surname>Pietil&#xE4;inen</surname><orcid>0000-0002-8522-1288</orcid><order>12</order></author><author><firstname>Tanja C.</firstname><surname>Adam</surname><order>13</order></author><author><firstname>Margriet</firstname><surname>Westerterp-Plantenga</surname><orcid>0000-0002-6326-3102</orcid><order>14</order></author><author><firstname>Elizabeth</firstname><surname>Simpson</surname><order>15</order></author><author><firstname>Ian</firstname><surname>MacDonald</surname><order>16</order></author><author><firstname>Moira A.</firstname><surname>Taylor</surname><orcid>0000-0003-4100-8343</orcid><order>17</order></author><author><firstname>Sally D.</firstname><surname>Poppitt</surname><orcid>0000-0002-2214-8378</orcid><order>18</order></author><author><firstname>Wolfgang</firstname><surname>Schlicht</surname><orcid>0000-0002-2134-2259</orcid><order>19</order></author><author><firstname>Jennie</firstname><surname>Brand-Miller</surname><orcid>0000-0002-6797-8754</orcid><order>20</order></author><author><firstname>Mikael</firstname><surname>Fogelholm</surname><orcid>0000-0001-8110-102X</orcid><order>21</order></author><author><firstname>Anne</firstname><surname>Raben</surname><orcid>0000-0001-5229-4491</orcid><order>22</order></author><author><firstname>J. 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spelling 2025-01-31T10:27:04.9783365 v2 68638 2025-01-02 Health and Liver Diagnostic Markers Influencing Glycemia in Subjects with Prediabetes: Preview Study 6d62b2ed126961bed81a94a2beba8a01 0000-0001-5618-0803 Gareth Stratton Gareth Stratton true false 2025-01-02 EAAS Introduction: Glucose homeostasis may be dependent on liver conditions and influence health-related markers and quality of life (QoL) objective measurements. This study aimed to analyze the interactions of glycemia with liver and health status in a prediabetic population. Subjects and methods: This study included 2220 overweight/obese prediabetics from the multinational PREVIEW project. Anthropometrics; clinical, metabolic and other health-related markers; and QoL variables were analyzed. Univariate and multilinear-adjusted regression models were run to explain the interrelationships and effect modification between glycemia, health-related QoL (applying SF-12) and metabolic/liver health (using the HSI, a putative marker of fatty liver). Results: Relevant age/sex interactions were found concerning the levels of insulin, HOMA-IR, C peptide and transaminases in this prediabetic population. Multivariate models identified age, sex, glucose, WC and QoL as important predictors of HSI variability (adj. R value = 0.1393, p &lt; 0.001), whereas the QoL status was statistically related to age, sex, HOMA-IR and HSI (adj. R value = 0.1130, p &lt; 0.001) in this glycemia-impaired group. Furthermore, the QoL values declined with increased HSI scores, where a significant interaction was found (p = 0.011) when the data were analyzed when comparing lower glycemia vs. higher glycemia in prediabetics. Indeed, an effect modification was featured depending on the glycemia levels concerning the QoL and HSI worsening. Conclusion: Glycemia associations with the QoL status and liver metabolism markers were evidenced, with clinical implications for diabetes and liver disease precision management given the modification of the QoL outcomes depending on the liver status and glycemia concentrations. Notably, independent associations of circulating glucose with age, sex, adiposity, inflammation and C peptide levels were found. Journal Article Diagnostics 14 24 2895 MDPI AG 2075-4418 Prediabetes; adiposity; fatty liver; quality of life 23 12 2024 2024-12-23 10.3390/diagnostics14242895 COLLEGE NANME Engineering and Applied Sciences School COLLEGE CODE EAAS Swansea University Another institution paid the OA fee This research was supported by the EU Seventh Framework Programme (FP7; 2007–2013) (grant no. 312057), National Health and Medical Research Council (EU Collaborative Grant AUS 8, ID 1067711), Glycemic Index Foundation Australia through royalties to the University of Sydney, Health Research Council of New Zealand (grant no. 14/191), University of Auckland Faculty Research Development Fund, Cambridge Weight Plan, Danish Agriculture and Food Council, Danish Meat Research Institute, National Institute for Health Research Biomedical Research Centre (NIHR BRC) (UK), Biotechnology and Biological Sciences Research Council (BBSRC) (UK), Engineering and Physical Sciences Research Council (EPSRC) (UK), Nutritics (Dublin), Juho Vainio Foundation (Finland), Academy of Finland (grants no. 272376, 314383, 266286 and 314135), Finnish Medical Foundation, Gyllenberg Foundation (Finland), Novo Nordisk Foundation, Finnish Diabetes Research Foundation, University of Helsinki, Government Research Funds for Helsinki University Hospital, Jenny and Antti Wihuri Foundation (Finland), Emil Aaltonen Foundation (Finland) and China Scholarship Council. 2025-01-31T10:27:04.9783365 2025-01-02T15:15:07.8827298 Faculty of Science and Engineering School of Engineering and Applied Sciences - Sport and Exercise Sciences Omar Ramos-Lopez 0000-0002-2505-1555 1 Diego Martinez-Urbistondo 0000-0002-0530-7349 2 Santiago Navas-Carretero 0000-0002-5163-2230 3 Ruixin Zhu 4 Maija Huttunen-Lenz 0000-0002-1034-1613 5 Gareth Stratton 0000-0001-5618-0803 6 Teodora Handjieva-Darlenska 7 Svetoslav Handjiev 8 Jouko Ensio Sundvall 9 Marta P. Silvestre 0000-0001-9327-2897 10 Elli Jalo 0000-0002-9987-1716 11 Kirsi H. Pietiläinen 0000-0002-8522-1288 12 Tanja C. Adam 13 Margriet Westerterp-Plantenga 0000-0002-6326-3102 14 Elizabeth Simpson 15 Ian MacDonald 16 Moira A. Taylor 0000-0003-4100-8343 17 Sally D. Poppitt 0000-0002-2214-8378 18 Wolfgang Schlicht 0000-0002-2134-2259 19 Jennie Brand-Miller 0000-0002-6797-8754 20 Mikael Fogelholm 0000-0001-8110-102X 21 Anne Raben 0000-0001-5229-4491 22 J. Alfredo Martinez 23 68638__33235__75e0c4f4f59f4bd6b3778c6eca6504cc.pdf 68638.VOR.pdf 2025-01-02T15:18:28.5028242 Output 725205 application/pdf Version of Record true © 2024 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. true eng https://creativecommons.org/licenses/by/4.0/
title Health and Liver Diagnostic Markers Influencing Glycemia in Subjects with Prediabetes: Preview Study
spellingShingle Health and Liver Diagnostic Markers Influencing Glycemia in Subjects with Prediabetes: Preview Study
Gareth Stratton
title_short Health and Liver Diagnostic Markers Influencing Glycemia in Subjects with Prediabetes: Preview Study
title_full Health and Liver Diagnostic Markers Influencing Glycemia in Subjects with Prediabetes: Preview Study
title_fullStr Health and Liver Diagnostic Markers Influencing Glycemia in Subjects with Prediabetes: Preview Study
title_full_unstemmed Health and Liver Diagnostic Markers Influencing Glycemia in Subjects with Prediabetes: Preview Study
title_sort Health and Liver Diagnostic Markers Influencing Glycemia in Subjects with Prediabetes: Preview Study
author_id_str_mv 6d62b2ed126961bed81a94a2beba8a01
author_id_fullname_str_mv 6d62b2ed126961bed81a94a2beba8a01_***_Gareth Stratton
author Gareth Stratton
author2 Omar Ramos-Lopez
Diego Martinez-Urbistondo
Santiago Navas-Carretero
Ruixin Zhu
Maija Huttunen-Lenz
Gareth Stratton
Teodora Handjieva-Darlenska
Svetoslav Handjiev
Jouko Ensio Sundvall
Marta P. Silvestre
Elli Jalo
Kirsi H. Pietiläinen
Tanja C. Adam
Margriet Westerterp-Plantenga
Elizabeth Simpson
Ian MacDonald
Moira A. Taylor
Sally D. Poppitt
Wolfgang Schlicht
Jennie Brand-Miller
Mikael Fogelholm
Anne Raben
J. Alfredo Martinez
format Journal article
container_title Diagnostics
container_volume 14
container_issue 24
container_start_page 2895
publishDate 2024
institution Swansea University
issn 2075-4418
doi_str_mv 10.3390/diagnostics14242895
publisher MDPI AG
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Sport and Exercise Sciences{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Sport and Exercise Sciences
document_store_str 1
active_str 0
description Introduction: Glucose homeostasis may be dependent on liver conditions and influence health-related markers and quality of life (QoL) objective measurements. This study aimed to analyze the interactions of glycemia with liver and health status in a prediabetic population. Subjects and methods: This study included 2220 overweight/obese prediabetics from the multinational PREVIEW project. Anthropometrics; clinical, metabolic and other health-related markers; and QoL variables were analyzed. Univariate and multilinear-adjusted regression models were run to explain the interrelationships and effect modification between glycemia, health-related QoL (applying SF-12) and metabolic/liver health (using the HSI, a putative marker of fatty liver). Results: Relevant age/sex interactions were found concerning the levels of insulin, HOMA-IR, C peptide and transaminases in this prediabetic population. Multivariate models identified age, sex, glucose, WC and QoL as important predictors of HSI variability (adj. R value = 0.1393, p &lt; 0.001), whereas the QoL status was statistically related to age, sex, HOMA-IR and HSI (adj. R value = 0.1130, p &lt; 0.001) in this glycemia-impaired group. Furthermore, the QoL values declined with increased HSI scores, where a significant interaction was found (p = 0.011) when the data were analyzed when comparing lower glycemia vs. higher glycemia in prediabetics. Indeed, an effect modification was featured depending on the glycemia levels concerning the QoL and HSI worsening. Conclusion: Glycemia associations with the QoL status and liver metabolism markers were evidenced, with clinical implications for diabetes and liver disease precision management given the modification of the QoL outcomes depending on the liver status and glycemia concentrations. Notably, independent associations of circulating glucose with age, sex, adiposity, inflammation and C peptide levels were found.
published_date 2024-12-23T05:24:49Z
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