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1. CYP1B1-RMDN2 Alzheimer’s disease endophenotype locus identified for cerebral tau PET

Author

Nho, Kwangsik, Risacher, Shannon L., Apostolova, Liana G., Bice, Paula J., Brosch, Jared R., Deardorff, Rachael, Faber, Kelley, Farlow, Martin R., Foroud, Tatiana, Gao, Sujuan, Rosewood, Thea, Kim, Jun Pyo, Nudelman, Kelly, Yu, Meichen, Aisen, Paul, Sperling, Reisa, Hooli, Basavaraj, Shcherbinin, Sergey, Svaldi, Diana, Jack, Jr., Clifford R., Jagust, William J., Landau, Susan, Vasanthakumar, Aparna, Waring, Jeffrey F., Doré, Vincent, Laws, Simon M., Masters, Colin L., Porter, Tenielle, Rowe, Christopher C., Villemagne, Victor L., Dumitrescu, Logan, Hohman, Timothy J., Libby, Julia B., Mormino, Elizabeth, Buckley, Rachel F., Johnson, Keith, Yang, Hyun-Sik, Petersen, Ronald C., Ramanan, Vijay K., Ertekin-Taner, Nilüfer, Vemuri, Prashanthi, Cohen, Ann D., Fan, Kang-Hsien, Kamboh, M. Ilyas, Lopez, Oscar L., Bennett, David A., Ali, Muhammad, Benzinger, Tammie, Cruchaga, Carlos, Hobbs, Diana, De Jager, Philip L., Fujita, Masashi, Jadhav, Vaishnavi, Lamb, Bruce T., Tsai, Andy P., Castanho, Isabel, Mill, Jonathan, Weiner, Michael W., and Saykin, Andrew J.

Published
2024
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3. An IL1RL1 genetic variant lowers soluble ST2 levels and the risk effects of APOE-ε4 in female patients with Alzheimer's disease.

Author

Jiang, Yuanbing, Zhou, Xiaopu, Wong, Hiu Yi, Ouyang, Li, Ip, Fanny CF, Chau, Vicky MN, Lau, Shun-Fat, Wu, Wei, Wong, Daniel YK, Seo, Heukjin, Fu, Wing-Yu, Lai, Nicole CH, Chen, Yuewen, Chen, Yu, Tong, Estella PS, Alzheimer’s Disease Neuroimaging Initiative, Mok, Vincent CT, Kwok, Timothy CY, Mok, Kin Y, Shoai, Maryam, Lehallier, Benoit, Losada, Patricia Morán, O'Brien, Eleanor, Porter, Tenielle, Laws, Simon M, Hardy, John, Wyss-Coray, Tony, Masters, Colin L, Fu, Amy KY, and Ip, Nancy Y

Subjects
Alzheimer’s Disease Neuroimaging Initiative, Animals, Humans, Mice, Alzheimer Disease, Female, Apolipoprotein E4, Genome-Wide Association Study, Amyloid beta-Peptides, Interleukin-1 Receptor-Like 1 Protein, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Human Genome, Brain Disorders, Dementia, Neurosciences, Alzheimer's Disease, Aging, Neurodegenerative, Genetics, Acquired Cognitive Impairment, Aetiology, 2.1 Biological and endogenous factors, Neurological
Abstract

Changes in the levels of circulating proteins are associated with Alzheimer's disease (AD), whereas their pathogenic roles in AD are unclear. Here, we identified soluble ST2 (sST2), a decoy receptor of interleukin-33-ST2 signaling, as a new disease-causing factor in AD. Increased circulating sST2 level is associated with more severe pathological changes in female individuals with AD. Genome-wide association analysis and CRISPR-Cas9 genome editing identified rs1921622 , a genetic variant in an enhancer element of IL1RL1, which downregulates gene and protein levels of sST2. Mendelian randomization analysis using genetic variants, including rs1921622 , demonstrated that decreased sST2 levels lower AD risk and related endophenotypes in females carrying the Apolipoprotein E (APOE)-ε4 genotype; the association is stronger in Chinese than in European-descent populations. Human and mouse transcriptome and immunohistochemical studies showed that rs1921622 /sST2 regulates amyloid-beta (Aβ) pathology through the modulation of microglial activation and Aβ clearance. These findings demonstrate how sST2 level is modulated by a genetic variation and plays a disease-causing role in females with AD.

Published
2022

4. Alzheimer’s disease genetic risk and cognitive reserve in relationship to long-term cognitive trajectories among cognitively normal individuals

Author

Pettigrew, Corinne, Nazarovs, Jurijs, Soldan, Anja, Singh, Vikas, Wang, Jiangxia, Hohman, Timothy, Dumitrescu, Logan, Libby, Julia, Kunkle, Brian, Gross, Alden L., Johnson, Sterling, Lu, Qiongshi, Engelman, Corinne, Masters, Colin L., Maruff, Paul, Laws, Simon M., Morris, John C., Hassenstab, Jason, Cruchaga, Carlos, Resnick, Susan M., Kitner-Triolo, Melissa H., An, Yang, and Albert, Marilyn

Published
2023
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5. Large multi-ethnic genetic analyses of amyloid imaging identify new genes for Alzheimer disease

Author

Ali, Muhammad, Archer, Derek B., Gorijala, Priyanka, Western, Daniel, Timsina, Jigyasha, Fernández, Maria V., Wang, Ting-Chen, Satizabal, Claudia L., Yang, Qiong, Beiser, Alexa S., Wang, Ruiqi, Chen, Gengsheng, Gordon, Brian, Benzinger, Tammie L. S., Xiong, Chengjie, Morris, John C., Bateman, Randall J., Karch, Celeste M., McDade, Eric, Goate, Alison, Seshadri, Sudha, Mayeux, Richard P., Sperling, Reisa A., Buckley, Rachel F., Johnson, Keith A., Won, Hong-Hee, Jung, Sang-Hyuk, Kim, Hang-Rai, Seo, Sang Won, Kim, Hee Jin, Mormino, Elizabeth, Laws, Simon M., Fan, Kang-Hsien, Kamboh, M. Ilyas, Vemuri, Prashanthi, Ramanan, Vijay K., Yang, Hyun-Sik, Wenzel, Allen, Rajula, Hema Sekhar Reddy, Mishra, Aniket, Dufouil, Carole, Debette, Stephanie, Lopez, Oscar L., DeKosky, Steven T., Tao, Feifei, Nagle, Michael W., Hohman, Timothy J., Sung, Yun Ju, Dumitrescu, Logan, and Cruchaga, Carlos

Published
2023
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6. Alzheimer's disease research progress in Australia: The Alzheimer's Association International Conference Satellite Symposium in Sydney

Author

Sexton, Claire E, Anstey, Kaarin J, Baldacci, Filippo, Barnum, CJ, Barron, Anna M, Blennow, Kaj, Brodaty, Henry, Burnham, Samantha, Elahi, Fanny M, Götz, Jürgen, Jeon, Yun‐Hee, Koronyo‐Hamaoui, Maya, Landau, Susan M, Lautenschlager, Nicola T, Laws, Simon M, Lipnicki, Darren M, Lu, Hanzhang, Masters, Colin L, Moyle, Wendy, Nakamura, Akinori, Pasinetti, Giulio Maria, Rao, Naren, Rowe, Christopher, Sachdev, Perminder S, Schofield, Peter R, Sigurdsson, Einar M, Smith, Kate, Srikanth, Velandai, Szoeke, Cassandra, Tansey, Malú G, Whitmer, Rachel, Wilcock, Donna, Wong, Tien Y, Bain, Lisa J, and Carrillo, Maria C

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Dementia, Neurodegenerative, Acquired Cognitive Impairment, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Alzheimer's Disease, Aging, Brain Disorders, Behavioral and Social Science, Neurological, Alzheimer Disease, Australia, Biomarkers, Biomedical Research, Cognitive Dysfunction, Disease Progression, Humans, Life Style, Positron-Emission Tomography, Prodromal Symptoms, Alzheimer&apos, s, dementia, behavioral symptoms, biomarkers, prevention, Alzheimer's, Geriatrics, Clinical sciences, Biological psychology
Abstract

The Alzheimer's Association International Conference held its sixth Satellite Symposium in Sydney, Australia in 2019, highlighting the leadership of Australian researchers in advancing the understanding of and treatment developments for Alzheimer's disease (AD) and other dementias. This leadership includes the Australian Imaging, Biomarker, and Lifestyle Flagship Study of Ageing (AIBL), which has fueled the identification and development of many biomarkers and novel therapeutics. Two multimodal lifestyle intervention studies have been launched in Australia; and Australian researchers have played leadership roles in other global studies in diverse populations. Australian researchers have also played an instrumental role in efforts to understand mechanisms underlying vascular contributions to cognitive impairment and dementia; and through the Women's Healthy Aging Project have elucidated hormonal and other factors that contribute to the increased risk of AD in women. Alleviating the behavioral and psychological symptoms of dementia has also been a strong research and clinical focus in Australia.

Published
2022

7. Polygenic resilience scores capture protective genetic effects for Alzheimer’s disease

Author

Hou, Jiahui, Hess, Jonathan L, Armstrong, Nicola, Bis, Joshua C, Grenier-Boley, Benjamin, Karlsson, Ida K, Leonenko, Ganna, Numbers, Katya, O’Brien, Eleanor K, Shadrin, Alexey, Thalamuthu, Anbupalam, Yang, Qiong, Andreassen, Ole A, Brodaty, Henry, Gatz, Margaret, Kochan, Nicole A, Lambert, Jean-Charles, Laws, Simon M, Masters, Colin L, Mather, Karen A, Pedersen, Nancy L, Posthuma, Danielle, Sachdev, Perminder S, Williams, Julie, Fan, Chun Chieh, Faraone, Stephen V, Fennema-Notestine, Christine, Lin, Shu-Ju, Escott-Price, Valentina, Holmans, Peter, Seshadri, Sudha, Tsuang, Ming T, Kremen, William S, and Glatt, Stephen J

Subjects
Genetics, Alzheimer's Disease, Brain Disorders, Human Genome, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Genetic Testing, Neurodegenerative, Prevention, Dementia, Aging, Acquired Cognitive Impairment, Aetiology, 2.1 Biological and endogenous factors, Alzheimer Disease, Apolipoprotein E4, Apolipoproteins E, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Multifactorial Inheritance, Risk Factors, Alzheimer’s Disease Neuroimaging Initiative, Clinical Sciences, Public Health and Health Services, Psychology
Abstract

Polygenic risk scores (PRSs) can boost risk prediction in late-onset Alzheimer's disease (LOAD) beyond apolipoprotein E (APOE) but have not been leveraged to identify genetic resilience factors. Here, we sought to identify resilience-conferring common genetic variants in (1) unaffected individuals having high PRSs for LOAD, and (2) unaffected APOE-ε4 carriers also having high PRSs for LOAD. We used genome-wide association study (GWAS) to contrast "resilient" unaffected individuals at the highest genetic risk for LOAD with LOAD cases at comparable risk. From GWAS results, we constructed polygenic resilience scores to aggregate the addictive contributions of risk-orthogonal common variants that promote resilience to LOAD. Replication of resilience scores was undertaken in eight independent studies. We successfully replicated two polygenic resilience scores that reduce genetic risk penetrance for LOAD. We also showed that polygenic resilience scores positively correlate with polygenic risk scores in unaffected individuals, perhaps aiding in staving off disease. Our findings align with the hypothesis that a combination of risk-independent common variants mediates resilience to LOAD by moderating genetic disease risk.

Published
2022

11. Using imputation to provide harmonized longitudinal measures of cognition across AIBL and ADNI

Author

Shishegar, Rosita, Cox, Timothy, Rolls, David, Bourgeat, Pierrick, Doré, Vincent, Lamb, Fiona, Robertson, Joanne, Laws, Simon M, Porter, Tenielle, Fripp, Jurgen, Tosun, Duygu, Maruff, Paul, Savage, Greg, Rowe, Christopher C, Masters, Colin L, Weiner, Michael W, Villemagne, Victor L, and Burnham, Samantha C

Subjects
Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Aging, Neurosciences, Acquired Cognitive Impairment, Brain Disorders, Neurodegenerative, Dementia, Biomedical Imaging, Alzheimer's Disease, Aged, Aged, 80 and over, Algorithms, Alzheimer Disease, Amyloid beta-Peptides, Australia, Biomarkers, Cognition, Cognitive Dysfunction, Computational Biology, Data Analysis, Female, Humans, Longitudinal Studies, Male, Neuroimaging, Positron-Emission Tomography, Reproducibility of Results
Abstract

To improve understanding of Alzheimer's disease, large observational studies are needed to increase power for more nuanced analyses. Combining data across existing observational studies represents one solution. However, the disparity of such datasets makes this a non-trivial task. Here, a machine learning approach was applied to impute longitudinal neuropsychological test scores across two observational studies, namely the Australian Imaging, Biomarkers and Lifestyle Study (AIBL) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) providing an overall harmonised dataset. MissForest, a machine learning algorithm, capitalises on the underlying structure and relationships of data to impute test scores not measured in one study aligning it to the other study. Results demonstrated that simulated missing values from one dataset could be accurately imputed, and that imputation of actual missing data in one dataset showed comparable discrimination (p

Published
2021

18. Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease

Author

Cadby, Gemma, Giles, Corey, Melton, Phillip E., Huynh, Kevin, Mellett, Natalie A., Duong, Thy, Nguyen, Anh, Cinel, Michelle, Smith, Alex, Olshansky, Gavriel, Wang, Tingting, Brozynska, Marta, Inouye, Mike, McCarthy, Nina S., Ariff, Amir, Hung, Joseph, Hui, Jennie, Beilby, John, Dubé, Marie-Pierre, Watts, Gerald F., Shah, Sonia, Wray, Naomi R., Lim, Wei Ling Florence, Chatterjee, Pratishtha, Martins, Ian, Laws, Simon M., Porter, Tenielle, Vacher, Michael, Bush, Ashley I., Rowe, Christopher C., Villemagne, Victor L., Ames, David, Masters, Colin L., Taddei, Kevin, Arnold, Matthias, Kastenmüller, Gabi, Nho, Kwangsik, Saykin, Andrew J., Han, Xianlin, Kaddurah-Daouk, Rima, Martins, Ralph N., Blangero, John, Meikle, Peter J., and Moses, Eric K.

Published
2022
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22. Alzheimer's disease genetic risk and changes in brain atrophy and white matter hyperintensities in cognitively unimpaired adults.

Author

Soldan, Anja, Wang, Jiangxia, Pettigrew, Corinne, Davatzikos, Christos, Erus, Guray, Hohman, Timothy J, Dumitrescu, Logan, Bilgel, Murat, Resnick, Susan M, Rivera-Rivera, Leonardo A, Langhough, Rebecca, Johnson, Sterling C, Benzinger, Tammie, Morris, John C, Laws, Simon M, Fripp, Jurgen, Masters, Colin L, and Albert, Marilyn S

Published
2024
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28. A comprehensive multi-omics analysis reveals unique signatures to predict Alzheimer’s disease

Author

Vacher, Michael, Canovas, Rodrigo, Laws, Simon M., Doecke, James D., Vacher, Michael, Canovas, Rodrigo, Laws, Simon M., and Doecke, James D.

Abstract

Background: Complex disorders, such as Alzheimer’s disease (AD), result from the combined influence of multiple biological and environmental factors. The integration of high-throughput data from multiple omics platforms can provide system overviews, improving our understanding of complex biological processes underlying human disease. In this study, integrated data from four omics platforms were used to characterise biological signatures of AD. Method: The study cohort consists of 455 participants (Control:148, Cases:307) from the Religious Orders Study and Memory and Aging Project (ROSMAP). Genotype (SNP), methylation (CpG), RNA and proteomics data were collected, quality-controlled and pre-processed (SNP = 130; CpG = 83; RNA = 91; Proteomics = 119). Using a diagnosis of Mild Cognitive Impairment (MCI)/AD combined as the target phenotype, we first used Partial Least Squares Regression as an unsupervised classification framework to assess the prediction capabilities for each omics dataset individually. We then used a variation of the sparse generalized canonical correlation analysis (sGCCA) to assess predictions of the combined datasets and identify multi-omics signatures characterising each group of participants. Results: Analysing datasets individually we found methylation data provided the best predictions with an accuracy of 0.63 (95%CI = [0.54–0.71]), followed by RNA, 0.61 (95%CI = [0.52–0.69]), SNP, 0.59 (95%CI = [0.51–0.68]) and proteomics, 0.58 (95%CI = [0.51–0.67]). After integration of the four datasets, predictions were dramatically improved with a resulting accuracy of 0.95 (95% CI = [0.89–0.98]). Conclusion: The integration of data from multiple platforms is a powerful approach to explore biological systems and better characterise the biological signatures of AD. The results suggest that integrative methods can identify biomarker panels with improved predictive performance compared to individual platforms alone. Further validation in independent cohorts

Published
2024

29. Investigating Genetic Overlap between Alzheimer's Disease, Lipids, and Coronary Artery Disease: A Large-Scale Genome-Wide Cross Trait Analysis.

Author

Kirby, Artika, Porter, Tenielle, Adewuyi, Emmanuel O., and Laws, Simon M.

Subjects
MYOCARDIAL ischemia, CORONARY artery disease, CORONARY disease, LOW density lipoproteins, ALZHEIMER'S disease
Abstract

There is evidence to support a link between abnormal lipid metabolism and Alzheimer's disease (AD) risk. Similarly, observational studies suggest a comorbid relationship between AD and coronary artery disease (CAD). However, the intricate biological mechanisms of AD are poorly understood, and its relationship with lipids and CAD traits remains unresolved. Conflicting evidence further underscores the ongoing investigation into this research area. Here, we systematically assess the cross-trait genetic overlap of AD with 13 representative lipids (from eight classes) and seven CAD traits, leveraging robust analytical methods, well-powered large-scale genetic data, and rigorous replication testing. Our main analysis demonstrates a significant positive global genetic correlation of AD with triglycerides and all seven CAD traits assessed—angina pectoris, cardiac dysrhythmias, coronary arteriosclerosis, ischemic heart disease, myocardial infarction, non-specific chest pain, and coronary artery disease. Gene-level analyses largely reinforce these findings and highlight the genetic overlap between AD and three additional lipids: high-density lipoproteins (HDLs), low-density lipoproteins (LDLs), and total cholesterol. Moreover, we identify genome-wide significant genes (Fisher's combined p value [FCPgene] < 2.60 × 10−6) shared across AD, several lipids, and CAD traits, including WDR12, BAG6, HLA-DRA, PHB, ZNF652, APOE, APOC4, PVRL2, and TOMM40. Mendelian randomisation analysis found no evidence of a significant causal relationship between AD, lipids, and CAD traits. However, local genetic correlation analysis identifies several local pleiotropic hotspots contributing to the relationship of AD with lipids and CAD traits across chromosomes 6, 8, 17, and 19. Completing a three-way analysis, we confirm a strong genetic correlation between lipids and CAD traits—HDL and sphingomyelin demonstrate negative correlations, while LDL, triglycerides, and total cholesterol show positive correlations. These findings support genetic overlap between AD, specific lipids, and CAD traits, implicating shared but non-causal genetic susceptibility. The identified shared genes and pleiotropic hotspots are valuable targets for further investigation into AD and, potentially, its comorbidity with CAD traits. [ABSTRACT FROM AUTHOR]

Published
2024
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30. The relationships between multidimensional sleep health and work productivity in individuals with neurological conditions.

Author

Turner, Mitchell, Laws, Manja, Griffiths, Madeline, Turner, Kate, Dempsey, Leah, Laws, Simon M., and Cruickshank, Travis

Subjects
LABOR productivity, NEUROLOGICAL disorders, SLEEP quality, SLEEP hygiene, SLEEP, SLEEP duration, HYGIENE
Abstract

Summary: Numerous studies have reported the negative impacts of poor sleep on work productivity in the general population. However, despite the known sleep issues that individuals living with neurological conditions experience, no study has explored its impact on their work productivity. Sleep health is a concept that includes multiple domains of sleep, measured with a combination of objective and subjective measures. Therefore, this study aimed to ascertain the associations between sleep health and its domains and work productivity in individuals with neurological conditions. Sleep health domains were determined through actigraphy data collected over 1 week and sleep questionnaires. Work productivity was assessed via the Work Productivity and Activity Impairment Questionnaire. A comparison of sleep health scores between demographic variables was performed using Mann–Whitney U and Kruskal–Wallis tests. Associations between the sleep health domains and work productivity were performed using linear regression models. There were no significant differences in sleep health scores between sex, smoking status, education level, employment status or any work productivity domain. Individuals with non‐optimal sleep timing had greater absenteeism (22.99%) than the optimal group. Individuals with non‐optimal sleep quality had an increase in presenteeism (30.85%), work productivity loss (26.44%) and activity impairment (25.81%) compared to those in the optimal group. The findings from this study highlight that self‐reported sleep quality has the largest impact on work productivity. Improving individuals' sleep quality through triage for potential sleep disorders or improving their sleep hygiene (sleep behaviour and environment) may positively impact work productivity. [ABSTRACT FROM AUTHOR]

Published
2024
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34. Alzheimer's Disease biological PET staging using plasma p217+tau

Author

Feizpour, Azadeh, primary, Dore, Vincent, additional, Krishnadas, Natasha, additional, Bourgeat, Pierrick, additional, Doecke, James D., additional, Saad, Ziad, additional, Triana-Baltzer, Gallen, additional, Laws, Simon M., additional, Shishegar, Rosita, additional, Huang, Kun, additional, Fowler, Christopher, additional, Ward, Larry, additional, Masters, Colin L., additional, Mejan-Fripp, Jurgen, additional, Kolb, Hartmuth C., additional, Villemagne, Victor L., additional, and Rowe, Christopher C., additional

Published
2024
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35. Accurate Detection and Staging of Alzheimer's Disease by Plasma Ptau217 on a High Throughput Immunoassay Platform

Author

Feizpour, Azadeh, primary, Doecke, James D., additional, Doré, Vincent, additional, Krishnadas, Natasha, additional, Huang, Kun, additional, Bourgeat, Pierrick, additional, Laws, Simon M., additional, Fowler, Christopher, additional, Robertson, Joanne, additional, Mackintosh, Lucy, additional, Ayton, Scott, additional, Martins, Ralph N., additional, Rainey-Smith, Stephanie R., additional, Taddei, Kevin, additional, Ward, Larry, additional, Stage, Eddie, additional, Bannon, Anthony W., additional, Masters, colin, additional, Fripp, Jurgen, additional, Villemagne, Victor L., additional, and Rowe, Christopher C., additional

Published
2024
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36. When Does Alzheimer's Disease Start? Robust Estimates Based on Longitudinal Aβ-Amyloid-PET in Three Large International Cohorts

Author

Burnham, Samantha Claire, primary, Cox, Timothy, additional, Benzinger, Tammie, additional, Bourgeat, Pierrick, additional, Cruchaga, Carlos, additional, Doecke, James D., additional, Doré, Vincent, additional, Fowler, Christopher, additional, Goyal, Manu S., additional, Jin, Liang, additional, Laws, Simon M., additional, Hassenstab, Jason, additional, Maruff, Paul, additional, Williams, Rob, additional, Porter, Tenielle, additional, Saykin, Andrew J., additional, Shishegar, Rosita, additional, Sohrabi, Hamid R., additional, Petersen, Ronald C., additional, Tosun, Duygu, additional, Fripp, Jurgen, additional, Rowe, Christopher C., additional, Morris, John C., additional, Weiner, Michael, additional, Masters, colin, additional, and Villemagne, Victor L., additional

Published
2024
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38. Self‐reported physical activity levels do not predict brain beta amyloid levels in older cognitively normal adults over time

Author

Slee, Michael, primary, Rainey‐Smith, Stephanie R, additional, Villemagne, Victor L, additional, Sohrabi, Hamid R, additional, Taddei, Kevin, additional, Ames, David, additional, Dore, Vincent, additional, Maruff, Paul, additional, Laws, Simon M, additional, Masters, Colin L, additional, Rowe, Christopher C, additional, Martins, Ralph N, additional, Erickson, Kirk I., additional, and Brown, Belinda M, additional

Published
2023
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39. A comparison of machine learning based‐composite cognitive test scores to track cognitive decline in early stages of Alzheimer’s disease dementia: ADOPIC study

Author

Shishegar, Rosita, primary, Lee, Matthew, additional, Cox, Timothy, additional, Chai, Tze Young, additional, Dore, Vincent, additional, Bourgeat, Pierrick, additional, Fripp, Jurgen, additional, Burnham, Samantha C., additional, Lamb, Fiona, additional, Robertson, Joanne, additional, Laws, Simon M, additional, Porter, Tenielle, additional, Savage, Greg, additional, Hassenstab, Jason J., additional, Morris, John C, additional, Aschenbrenner, Andrew J., additional, Weiner, Michael S. W., additional, Masters, Colin L, additional, Rowe, Christopher C, additional, Villemagne, Victor L, additional, Lim, Yen Ying, additional, Doecke, James D, additional, Sohrabi, Hamid R, additional, and Maruff, Paul, additional

Published
2023
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43. Rates of age- and amyloid β-associated cortical atrophy in older adults with superior memory performance

Author

Chambers, Brian, Chiu, Edmond, Clarnette, Roger, Darby, David, Davison, Mary, Drago, John, Drysdale, Peter, Gilbert, Jacqueline, Lim, Kwang, Lautenschlager, Nicola, LoGiudice, Dina, McCardle, Peter, McFarlane, Steve, Mander, Alastair, Merory, John, O'Connor, Daniel, Scholes, Ron, Samuel, Mathew, Trivedi, Darshan, Woodward, Michael, Dang, Christa, Yassi, Nawaf, Harrington, Karra D., Xia, Ying, Lim, Yen Ying, Ames, David, Laws, Simon M., Hickey, Martha, Rainey-Smith, Stephanie, Sohrabi, Hamid R., Doecke, James D., Fripp, Jurgen, Salvado, Olivier, Snyder, Peter J., Weinborn, Michael, Villemagne, Victor L., Rowe, Christopher C., Masters, Colin L., and Maruff, Paul

Published
2019
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48. Suboptimal self‐reported sleep efficiency and duration are associated with faster accumulation of brain amyloid beta in cognitively unimpaired older adults.

Author

Pivac, Louise N., Brown, Belinda M., Sewell, Kelsey R., Doecke, James D., Villemagne, Victor L., Doré, Vincent, Weinborn, Michael, Sohrabi, Hamid R., Gardener, Samantha L., Bucks, Romola S., Laws, Simon M., Taddei, Kevin, Maruff, Paul, Masters, Colin L., Rowe, Christopher, Martins, Ralph N., and Rainey‐Smith, Stephanie R.

Subjects
SLEEP duration, OLDER people, AMYLOID, SLEEP quality, APOLIPOPROTEIN E, MIND-wandering, SLEEP
Abstract

INTRODUCTION: This study investigated whether self‐reported sleep quality is associated with brain amyloid beta (Aβ) accumulation. METHODS: Linear mixed effect model analyses were conducted for 189 cognitively unimpaired (CU) older adults (mean ± standard deviation 74.0 ± 6.2; 53.2% female), with baseline self‐reported sleep data, and positron emission tomography‐determined brain Aβ measured over a minimum of three time points (range 33.3–72.7 months). Analyses included random slopes and intercepts, interaction for apolipoprotein E (APOE) ε4 allele status, and time, adjusting for sex and baseline age. RESULTS: Sleep duration <6 hours, in APOE ε4 carriers, and sleep efficiency <65%, in the whole sample and APOE ε4 non‐carriers, is associated with faster accumulation of brain Aβ. DISCUSSION: These findings suggest a role for self‐reported suboptimal sleep efficiency and duration in the accumulation of Alzheimer's disease (AD) neuropathology in CU individuals. Additionally, poor sleep efficiency represents a potential route via which individuals at lower genetic risk may progress to preclinical AD. Highlights: In cognitively unimpaired older adults self‐report sleep is associated with brain amyloid beta (Aβ) accumulation.Across sleep characteristics, this relationship differs by apolipoprotein E (APOE) genotype.Sleep duration <6 hours is associated with faster brain Aβ accumulation in APOE ε4 carriers.Sleep efficiency < 65% is associated with faster brain Aβ accumulation in APOE ε4 non‐carriers.Personalized sleep interventions should be studied for potential to slow Aβ accumulation. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Physical activity and brain amyloid beta: A longitudinal analysis of cognitively unimpaired older adults

Author

Slee, Michael G., primary, Rainey‐Smith, Stephanie R., additional, Villemagne, Victor L., additional, Doecke, James D., additional, Sohrabi, Hamid R., additional, Taddei, Kevin, additional, Ames, David, additional, Dore, Vincent, additional, Maruff, Paul, additional, Laws, Simon M., additional, Masters, Colin L., additional, Rowe, Christopher C., additional, Martins, Ralph N., additional, Erickson, Kirk I., additional, and Brown, Belinda M., additional

Published
2023
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50. Transferability of a European-derived Alzheimer’s Disease Genetic Risk Score across Multi-Ancestry Populations

Author

Nicolas, Aude, primary, Grenier-Boley, Benjamin, additional, Sherva, Richard, additional, Kim, Yoontae, additional, Kikuchi, Masataka, additional, de Rojas, Itziar, additional, Dalmasso, Carolina, additional, Zhou, Xiaopu, additional, Guen, Yann Le, additional, Arboleda-Bustos, Carlos E, additional, Camargos Bicalho, Maria Aparecida, additional, Guerchet, Maëlenn, additional, van der Lee, Sven, additional, Goss, Monica, additional, Castillo, Atahualpa, additional, Bellenguez, Céline, additional, Küçükali, Fahri, additional, Satizabal Barrera, Claudia, additional, Fongang, Bernard, additional, yang, Qiong, additional, Peters, Oliver, additional, Schneider, Anja, additional, Dichgans, Martin, additional, Rujescu, Dan, additional, Scherbaum, Norbert, additional, Deckert, Jürgen, additional, Riedel-Heller, Steffi, additional, Hausner, Lucrezia, additional, Molina Porcel, Laura, additional, Düzel, Emrah, additional, Grimmer, Timo, additional, Wiltfang, Jens, additional, Heilmann-Heimbach, Stefanie, additional, Moebus, Susanne, additional, Tegos, Thomas, additional, Scarmeas, Nikolaos, additional, Dols-Icardo, Oriol, additional, Moreno, Fermin, additional, Pérez-Tur, Jordi, additional, Bullido, María J., additional, Pastor, Pau, additional, Sánchez-Valle, Raquel, additional, Álvarez, Victoria, additional, Cao, Han, additional, Ip, Nancy Y., additional, Fu, Amy K. Y., additional, Ip, Fanny C. 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2023
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