Exploring how genetic variation within Aquaporin‐4, influences the relationship between sleep and amyloid beta Article Swipe
Tenielle Porter
,
Ayeisha Milligan Armstrong
,
Vincent Doré
,
Eleanor K. O’Brien
,
Pierrick Bourgeat
,
Paul Maruff
,
Christopher C. Rowe
,
Stephanie R. Rainey‐Smith
,
Victor L. Villemagne
,
Simon M. Laws
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1002/alz.092408
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1002/alz.092408
Background The glymphatic system has been suggested as an important clearance mechanism for amyloid‐β (Aβ) during sleep. Animal and cellular models have suggested this clearance mechanism involves the water‐channel protein, Aquaporin‐4 (encoded by the AQP4 gene), located primarily in the astrocytic end‐feet. We have previously reported on the interaction between genetic variants within AQP4 , sleep and cross‐sectional cortical amyloid‐β (Aβ) burden. This study investigated how the relationship between AQP4 genetic variants and sleep may further influence changes in cortical Aβ levels. Methods The current study assessed cognitively unimpaired individuals enrolled in the Australian Imaging, Biomarker and Lifestyle (AIBL) Study of Ageing, who were considered Aβ accumulators (n = 319). Aβ accumulators were defined as those who had a high baseline level of cortical Aβ (centiloid ³20), or a positive rate of change in cortical Aβ, calculated using a minimum of 3 study time‐points. 13 AQP4 gene variants were selected for analysis based on fine mapping of the gene region, and sleep was assessed using measures calculated from the Pittsburgh Sleep Quality Index (PSQI) questionnaire. The relationship between AQP4 gene variants and rate of Aβ accumulation was investigated using linear regressions. Additional linear regression models with AQP4 variant x sleep measure interaction terms and post‐hoc simple slopes were analysed to assess how these relationships may influence Aβ accumulation. Results AQP4 ‐rs68006382 was associated with Aβ accumulation, where minor allele carriers/homozygotes were observed to have a higher rate of accumulation when compared to major allele homozygotes. Linear regressions with AQP4 variant x sleep measure interaction terms revealed that in AQP4 ‐rs68006382 minor allele carriers there was a significant relationship between Aβ accumulation and sleep quality. Additionally, interaction analysis revealed a relationship between Aβ accumulation and sleep latency in AQP4 ‐rs3875089 minor allele carriers. Conclusion The results of this study confirm our previous findings and suggests that interactions between AQP4 genotypes and sleep measures are also associated with the rate of Aβ accumulation.
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Metadata
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4406051155Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1002/alz.092408Digital Object Identifier
- Title
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Exploring how genetic variation within Aquaporin‐4, influences the relationship between sleep and amyloid betaWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-12-01Full publication date if available
- Authors
-
Tenielle Porter, Ayeisha Milligan Armstrong, Vincent Doré, Eleanor K. O’Brien, Pierrick Bourgeat, Paul Maruff, Christopher C. Rowe, Stephanie R. Rainey‐Smith, Victor L. Villemagne, Simon M. LawsList of authors in order
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https://doi.org/10.1002/alz.092408Publisher landing page
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1002/alz.092408Direct OA link when available
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Glymphatic system, Sleep (system call), Amyloid (mycology), Internal medicine, Aquaporin 4, Biology, Medicine, Psychology, Pathology, Cerebrospinal fluid, Computer science, Operating systemTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.models | 21, 195 |
| abstract_inverted_index.simple | 206 |
| abstract_inverted_index.sleep. | 17 |
| abstract_inverted_index.slopes | 207 |
| abstract_inverted_index.system | 4 |
| abstract_inverted_index.within | 53 |
| abstract_inverted_index.³20), | 127 |
| abstract_inverted_index.Ageing, | 102 |
| abstract_inverted_index.Methods | 83 |
| abstract_inverted_index.Quality | 172 |
| abstract_inverted_index.Results | 219 |
| abstract_inverted_index.between | 50, 69, 178, 269, 281, 307 |
| abstract_inverted_index.burden. | 62 |
| abstract_inverted_index.changes | 78 |
| abstract_inverted_index.confirm | 299 |
| abstract_inverted_index.current | 85 |
| abstract_inverted_index.defined | 114 |
| abstract_inverted_index.further | 76 |
| abstract_inverted_index.genetic | 51, 71 |
| abstract_inverted_index.latency | 286 |
| abstract_inverted_index.levels. | 82 |
| abstract_inverted_index.located | 37 |
| abstract_inverted_index.mapping | 156 |
| abstract_inverted_index.measure | 201, 253 |
| abstract_inverted_index.minimum | 140 |
| abstract_inverted_index.region, | 160 |
| abstract_inverted_index.results | 295 |
| abstract_inverted_index.variant | 198, 250 |
| abstract_inverted_index.(encoded | 32 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Imaging, | 95 |
| abstract_inverted_index.analysed | 209 |
| abstract_inverted_index.analysis | 152, 277 |
| abstract_inverted_index.assessed | 87, 164 |
| abstract_inverted_index.baseline | 121 |
| abstract_inverted_index.carriers | 263 |
| abstract_inverted_index.cellular | 20 |
| abstract_inverted_index.compared | 241 |
| abstract_inverted_index.cortical | 59, 80, 124, 135 |
| abstract_inverted_index.enrolled | 91 |
| abstract_inverted_index.findings | 302 |
| abstract_inverted_index.involves | 27 |
| abstract_inverted_index.measures | 166, 312 |
| abstract_inverted_index.observed | 232 |
| abstract_inverted_index.positive | 130 |
| abstract_inverted_index.previous | 301 |
| abstract_inverted_index.protein, | 30 |
| abstract_inverted_index.quality. | 274 |
| abstract_inverted_index.reported | 46 |
| abstract_inverted_index.revealed | 256, 278 |
| abstract_inverted_index.selected | 150 |
| abstract_inverted_index.suggests | 304 |
| abstract_inverted_index.variants | 52, 72, 148, 181 |
| abstract_inverted_index.Biomarker | 96 |
| abstract_inverted_index.Lifestyle | 98 |
| abstract_inverted_index.carriers. | 292 |
| abstract_inverted_index.clearance | 11, 25 |
| abstract_inverted_index.genotypes | 309 |
| abstract_inverted_index.important | 10 |
| abstract_inverted_index.influence | 77, 216 |
| abstract_inverted_index.mechanism | 12, 26 |
| abstract_inverted_index.primarily | 38 |
| abstract_inverted_index.suggested | 7, 23 |
| abstract_inverted_index.(centiloid | 126 |
| abstract_inverted_index.Additional | 192 |
| abstract_inverted_index.Australian | 94 |
| abstract_inverted_index.Background | 1 |
| abstract_inverted_index.Conclusion | 293 |
| abstract_inverted_index.Pittsburgh | 170 |
| abstract_inverted_index.associated | 223, 315 |
| abstract_inverted_index.astrocytic | 41 |
| abstract_inverted_index.calculated | 137, 167 |
| abstract_inverted_index.considered | 105 |
| abstract_inverted_index.glymphatic | 3 |
| abstract_inverted_index.post‐hoc | 205 |
| abstract_inverted_index.previously | 45 |
| abstract_inverted_index.regression | 194 |
| abstract_inverted_index.unimpaired | 89 |
| abstract_inverted_index.cognitively | 88 |
| abstract_inverted_index.end‐feet. | 42 |
| abstract_inverted_index.individuals | 90 |
| abstract_inverted_index.interaction | 49, 202, 254, 276 |
| abstract_inverted_index.regressions | 247 |
| abstract_inverted_index.significant | 267 |
| abstract_inverted_index.accumulation | 186, 239, 271, 283 |
| abstract_inverted_index.accumulators | 107, 112 |
| abstract_inverted_index.amyloid‐β | 14, 60 |
| abstract_inverted_index.homozygotes. | 245 |
| abstract_inverted_index.interactions | 306 |
| abstract_inverted_index.investigated | 65, 188 |
| abstract_inverted_index.regressions. | 191 |
| abstract_inverted_index.relationship | 68, 177, 268, 280 |
| abstract_inverted_index.‐rs3875089 | 289 |
| abstract_inverted_index.Additionally, | 275 |
| abstract_inverted_index.Aquaporin‐4 | 31 |
| abstract_inverted_index.accumulation, | 226 |
| abstract_inverted_index.accumulation. | 218, 321 |
| abstract_inverted_index.relationships | 214 |
| abstract_inverted_index.‐rs68006382 | 221, 260 |
| abstract_inverted_index.questionnaire. | 175 |
| abstract_inverted_index.time‐points. | 144 |
| abstract_inverted_index.water‐channel | 29 |
| abstract_inverted_index.cross‐sectional | 58 |
| abstract_inverted_index.carriers/homozygotes | 230 |
| cited_by_percentile_year | |
| countries_distinct_count | 2 |
| institutions_distinct_count | 10 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/6 |
| sustainable_development_goals[0].score | 0.4699999988079071 |
| sustainable_development_goals[0].display_name | Clean water and sanitation |
| citation_normalized_percentile.value | 0.32084371 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |