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Alzheimer’s disease biomarker profiling in a memory clinic cohort without common comorbidities
Brain Communications, Volume: 5, Issue: 5
Swansea University Authors: William Griffiths , Yuqin Wang , Manuela Pacciarini
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DOI (Published version): 10.1093/braincomms/fcad228
Abstract
Alzheimer’s disease is a multifactorial disorder with large heterogeneity. Comorbidities such as hypertension, hypercholesterolemia and diabetes are known contributors to the disease progression. However, less is known on their mechanistic contribution to Alzheimer’s pathology and neurodegeneration....
Published in: | Brain Communications |
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ISSN: | 2632-1297 |
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Oxford University Press (OUP)
2023
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Comorbidities such as hypertension, hypercholesterolemia and diabetes are known contributors to the disease progression. However, less is known on their mechanistic contribution to Alzheimer’s pathology and neurodegeneration. The aim of this study was to investigate the relationship of several biomarkers related to risk mechanisms in Alzheimer’s disease with the well-established Alzheimer’s disease markers in a memory clinic population without common comorbidities. We investigated 13 molecular markers representing key mechanisms underlying Alzheimer’s disease pathogenesis in CSF from memory clinic patients without diagnosed hypertension, hypercholesterolemia, or diabetes nor other neurodegenerative disorder. Analysis of 21 covariance (ANCOVA) was used to compare biomarker levels between clinical groups. Associations were analyzed by linear regression. Two-step cluster analysis was used to determine patient clusters. Two key markers were analyzed by immunofluorescence staining in hippocampus from non-demented control and Alzheimer’s disease individuals. CSF samples from a total of 90 participants were enrolled included in this study; 30 with from patients with subjective cognitive decline (age 62.4 4.38, female 60%) 30 with mild cognitive impairment (age 65.6 7.48, female 50%), and 30 with Alzheimer’s disease (age 68.2 7.86, female 50%). Angiotensinogen, thioredoxin-1, and interleukin-15 had the most prominent associations with Alzheimer’s disease pathology, synaptic and axonal damage markers. Synaptosomal-associated protein 25 kDa (SNAP-25) and neurofilament light chain (NFL) were increased in mild cognitive impairment and Alzheimer’s disease cases. Grouping biomarkers by biological function, showed that inflammatory and survival components were associated with Alzheimer’s disease pathology, synaptic dysfunction and axonal damage. Moreover, a vascular/metabolic component was associated with synaptic dysfunction. In the data-driven analysis, two patient clusters were identified; cluster 1 had increased CSF markers of oxidative stress, vascular pathology and neuroinflammation and was characterized by elevated synaptic and axonal damage, compared to cluster 2. Clinical groups were evenly distributed between the clusters. Analysis of post-mortem hippocampal tissue, showed that, compared to non-demented controls, angiotensinogen staining was higher in Alzheimer’s disease and co-localized with phosphorylated-tau. The identification of biomarker-driven endophenotypes in cognitive disorder patients, further highlights the biological heterogeneity of Alzheimer’s disease and the importance of tailored prevention and treatment strategies.</abstract><type>Journal Article</type><journal>Brain Communications</journal><volume>5</volume><journalNumber>5</journalNumber><paginationStart/><paginationEnd/><publisher>Oxford University Press (OUP)</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>2632-1297</issnElectronic><keywords>Alzheimer’s disease, biomarkers, metabolic disorders, clustering, cerebrospinal fluid</keywords><publishedDay>31</publishedDay><publishedMonth>8</publishedMonth><publishedYear>2023</publishedYear><publishedDate>2023-08-31</publishedDate><doi>10.1093/braincomms/fcad228</doi><url>http://dx.doi.org/10.1093/braincomms/fcad228</url><notes/><college>COLLEGE NANME</college><department>Biomedical Sciences</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>BMS</DepartmentCode><institution>Swansea University</institution><apcterm>Another institution paid the OA fee</apcterm><funders>BBSRC</funders><projectreference>BB/L001942/1, BB/S019588/1</projectreference><lastEdited>2023-10-23T14:51:49.2426210</lastEdited><Created>2023-06-13T10:40:11.1443042</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Medicine</level></path><authors><author><firstname>Makrina</firstname><surname>Daniilidou</surname><orcid>0000-0002-5460-9802</orcid><order>1</order></author><author><firstname>Francesca</firstname><surname>Eroli</surname><order>2</order></author><author><firstname>Vilma</firstname><surname>Alanko</surname><order>3</order></author><author><firstname>Julen</firstname><surname>Goikolea</surname><order>4</order></author><author><firstname>Maria</firstname><surname>Latorre-Leal</surname><order>5</order></author><author><firstname>Patricia</firstname><surname>Rodriguez-Rodriguez</surname><orcid>0000-0002-2438-3515</orcid><order>6</order></author><author><firstname>William</firstname><surname>Griffiths</surname><orcid>0000-0002-4129-6616</orcid><order>7</order></author><author><firstname>Yuqin</firstname><surname>Wang</surname><orcid>0000-0002-3063-3066</orcid><order>8</order></author><author><firstname>Manuela</firstname><surname>Pacciarini</surname><order>9</order></author><author><firstname>Ann</firstname><surname>Brinkmalm</surname><order>10</order></author><author><firstname>Henrik</firstname><surname>Zetterberg</surname><orcid>0000-0003-3930-4354</orcid><order>11</order></author><author><firstname>Kaj</firstname><surname>Blennow</surname><order>12</order></author><author><firstname>Anna</firstname><surname>Rosenberg</surname><order>13</order></author><author><firstname>Nenad</firstname><surname>Bogdanovic</surname><order>14</order></author><author><firstname>Bengt</firstname><surname>Winblad</surname><order>15</order></author><author><firstname>Miia</firstname><surname>Kivipelto</surname><order>16</order></author><author><firstname>Delphine</firstname><surname>Ibghi</surname><order>17</order></author><author><firstname>Angel</firstname><surname>Cedazo-Minguez</surname><order>18</order></author><author><firstname>Silvia</firstname><surname>Maioli</surname><order>19</order></author><author><firstname>Anna</firstname><surname>Matton</surname><orcid>0000-0002-7819-0495</orcid><order>20</order></author></authors><documents><document><filename>63624__28855__38e0d2669cbd4c34a335e5f06443d727.pdf</filename><originalFilename>63624.VOR.pdf</originalFilename><uploaded>2023-10-23T14:49:53.2579906</uploaded><type>Output</type><contentLength>2046023</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>© The Author(s) 2023. 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v2 63624 2023-06-13 Alzheimer’s disease biomarker profiling in a memory clinic cohort without common comorbidities 3316b1d1b524be1831790933eed1c26e 0000-0002-4129-6616 William Griffiths William Griffiths true false c92729b58622f9fdf6a0e7d8f4ce5081 0000-0002-3063-3066 Yuqin Wang Yuqin Wang true false 97e7258d0fe568df57f24c043f5f90cb Manuela Pacciarini Manuela Pacciarini true false 2023-06-13 BMS Alzheimer’s disease is a multifactorial disorder with large heterogeneity. Comorbidities such as hypertension, hypercholesterolemia and diabetes are known contributors to the disease progression. However, less is known on their mechanistic contribution to Alzheimer’s pathology and neurodegeneration. The aim of this study was to investigate the relationship of several biomarkers related to risk mechanisms in Alzheimer’s disease with the well-established Alzheimer’s disease markers in a memory clinic population without common comorbidities. We investigated 13 molecular markers representing key mechanisms underlying Alzheimer’s disease pathogenesis in CSF from memory clinic patients without diagnosed hypertension, hypercholesterolemia, or diabetes nor other neurodegenerative disorder. Analysis of 21 covariance (ANCOVA) was used to compare biomarker levels between clinical groups. Associations were analyzed by linear regression. Two-step cluster analysis was used to determine patient clusters. Two key markers were analyzed by immunofluorescence staining in hippocampus from non-demented control and Alzheimer’s disease individuals. CSF samples from a total of 90 participants were enrolled included in this study; 30 with from patients with subjective cognitive decline (age 62.4 4.38, female 60%) 30 with mild cognitive impairment (age 65.6 7.48, female 50%), and 30 with Alzheimer’s disease (age 68.2 7.86, female 50%). Angiotensinogen, thioredoxin-1, and interleukin-15 had the most prominent associations with Alzheimer’s disease pathology, synaptic and axonal damage markers. Synaptosomal-associated protein 25 kDa (SNAP-25) and neurofilament light chain (NFL) were increased in mild cognitive impairment and Alzheimer’s disease cases. Grouping biomarkers by biological function, showed that inflammatory and survival components were associated with Alzheimer’s disease pathology, synaptic dysfunction and axonal damage. Moreover, a vascular/metabolic component was associated with synaptic dysfunction. In the data-driven analysis, two patient clusters were identified; cluster 1 had increased CSF markers of oxidative stress, vascular pathology and neuroinflammation and was characterized by elevated synaptic and axonal damage, compared to cluster 2. Clinical groups were evenly distributed between the clusters. Analysis of post-mortem hippocampal tissue, showed that, compared to non-demented controls, angiotensinogen staining was higher in Alzheimer’s disease and co-localized with phosphorylated-tau. The identification of biomarker-driven endophenotypes in cognitive disorder patients, further highlights the biological heterogeneity of Alzheimer’s disease and the importance of tailored prevention and treatment strategies. Journal Article Brain Communications 5 5 Oxford University Press (OUP) 2632-1297 Alzheimer’s disease, biomarkers, metabolic disorders, clustering, cerebrospinal fluid 31 8 2023 2023-08-31 10.1093/braincomms/fcad228 http://dx.doi.org/10.1093/braincomms/fcad228 COLLEGE NANME Biomedical Sciences COLLEGE CODE BMS Swansea University Another institution paid the OA fee BBSRC BB/L001942/1, BB/S019588/1 2023-10-23T14:51:49.2426210 2023-06-13T10:40:11.1443042 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Makrina Daniilidou 0000-0002-5460-9802 1 Francesca Eroli 2 Vilma Alanko 3 Julen Goikolea 4 Maria Latorre-Leal 5 Patricia Rodriguez-Rodriguez 0000-0002-2438-3515 6 William Griffiths 0000-0002-4129-6616 7 Yuqin Wang 0000-0002-3063-3066 8 Manuela Pacciarini 9 Ann Brinkmalm 10 Henrik Zetterberg 0000-0003-3930-4354 11 Kaj Blennow 12 Anna Rosenberg 13 Nenad Bogdanovic 14 Bengt Winblad 15 Miia Kivipelto 16 Delphine Ibghi 17 Angel Cedazo-Minguez 18 Silvia Maioli 19 Anna Matton 0000-0002-7819-0495 20 63624__28855__38e0d2669cbd4c34a335e5f06443d727.pdf 63624.VOR.pdf 2023-10-23T14:49:53.2579906 Output 2046023 application/pdf Version of Record true © The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain. Distributed under the terms of a Creative Commons Attribution 4.0 License (CC BY 4.0). true eng https://creativecommons.org/licenses/by/4.0/ 208 Anna Matton 0000-0002-7819-0495 anna.matton@ki.se false 4 |
title |
Alzheimer’s disease biomarker profiling in a memory clinic cohort without common comorbidities |
spellingShingle |
Alzheimer’s disease biomarker profiling in a memory clinic cohort without common comorbidities William Griffiths Yuqin Wang Manuela Pacciarini |
title_short |
Alzheimer’s disease biomarker profiling in a memory clinic cohort without common comorbidities |
title_full |
Alzheimer’s disease biomarker profiling in a memory clinic cohort without common comorbidities |
title_fullStr |
Alzheimer’s disease biomarker profiling in a memory clinic cohort without common comorbidities |
title_full_unstemmed |
Alzheimer’s disease biomarker profiling in a memory clinic cohort without common comorbidities |
title_sort |
Alzheimer’s disease biomarker profiling in a memory clinic cohort without common comorbidities |
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3316b1d1b524be1831790933eed1c26e c92729b58622f9fdf6a0e7d8f4ce5081 97e7258d0fe568df57f24c043f5f90cb |
author_id_fullname_str_mv |
3316b1d1b524be1831790933eed1c26e_***_William Griffiths c92729b58622f9fdf6a0e7d8f4ce5081_***_Yuqin Wang 97e7258d0fe568df57f24c043f5f90cb_***_Manuela Pacciarini |
author |
William Griffiths Yuqin Wang Manuela Pacciarini |
author2 |
Makrina Daniilidou Francesca Eroli Vilma Alanko Julen Goikolea Maria Latorre-Leal Patricia Rodriguez-Rodriguez William Griffiths Yuqin Wang Manuela Pacciarini Ann Brinkmalm Henrik Zetterberg Kaj Blennow Anna Rosenberg Nenad Bogdanovic Bengt Winblad Miia Kivipelto Delphine Ibghi Angel Cedazo-Minguez Silvia Maioli Anna Matton |
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Brain Communications |
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Swansea University |
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2632-1297 |
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10.1093/braincomms/fcad228 |
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Oxford University Press (OUP) |
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Faculty of Medicine, Health and Life Sciences |
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description |
Alzheimer’s disease is a multifactorial disorder with large heterogeneity. Comorbidities such as hypertension, hypercholesterolemia and diabetes are known contributors to the disease progression. However, less is known on their mechanistic contribution to Alzheimer’s pathology and neurodegeneration. The aim of this study was to investigate the relationship of several biomarkers related to risk mechanisms in Alzheimer’s disease with the well-established Alzheimer’s disease markers in a memory clinic population without common comorbidities. We investigated 13 molecular markers representing key mechanisms underlying Alzheimer’s disease pathogenesis in CSF from memory clinic patients without diagnosed hypertension, hypercholesterolemia, or diabetes nor other neurodegenerative disorder. Analysis of 21 covariance (ANCOVA) was used to compare biomarker levels between clinical groups. Associations were analyzed by linear regression. Two-step cluster analysis was used to determine patient clusters. Two key markers were analyzed by immunofluorescence staining in hippocampus from non-demented control and Alzheimer’s disease individuals. CSF samples from a total of 90 participants were enrolled included in this study; 30 with from patients with subjective cognitive decline (age 62.4 4.38, female 60%) 30 with mild cognitive impairment (age 65.6 7.48, female 50%), and 30 with Alzheimer’s disease (age 68.2 7.86, female 50%). Angiotensinogen, thioredoxin-1, and interleukin-15 had the most prominent associations with Alzheimer’s disease pathology, synaptic and axonal damage markers. Synaptosomal-associated protein 25 kDa (SNAP-25) and neurofilament light chain (NFL) were increased in mild cognitive impairment and Alzheimer’s disease cases. Grouping biomarkers by biological function, showed that inflammatory and survival components were associated with Alzheimer’s disease pathology, synaptic dysfunction and axonal damage. Moreover, a vascular/metabolic component was associated with synaptic dysfunction. In the data-driven analysis, two patient clusters were identified; cluster 1 had increased CSF markers of oxidative stress, vascular pathology and neuroinflammation and was characterized by elevated synaptic and axonal damage, compared to cluster 2. Clinical groups were evenly distributed between the clusters. Analysis of post-mortem hippocampal tissue, showed that, compared to non-demented controls, angiotensinogen staining was higher in Alzheimer’s disease and co-localized with phosphorylated-tau. The identification of biomarker-driven endophenotypes in cognitive disorder patients, further highlights the biological heterogeneity of Alzheimer’s disease and the importance of tailored prevention and treatment strategies. |
published_date |
2023-08-31T14:51:50Z |
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1780554515658833920 |
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11.014067 |