scholarly journals Primary fatty amides in plasma associated with brain amyloid burden, hippocampal volume, and memory in the European Medical Information Framework for Alzheimer's Disease biomarker discovery cohort

2019 ◽  
Vol 15 (6) ◽  
pp. 817-827 ◽  
Author(s):  
Min Kim ◽  
Stuart Snowden ◽  
Tommi Suvitaival ◽  
Ashfaq Ali ◽  
David J. Merkler ◽  
...  
2017 ◽  
Vol 13 (7S_Part_14) ◽  
pp. P691-P692 ◽  
Author(s):  
Isabelle Bos ◽  
Stephanie J.B. Vos ◽  
Rik Vandenberghe ◽  
Philip Scheltens ◽  
Sebastiaan Engelborghs ◽  
...  

Biomedicines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1610
Author(s):  
Jin Xu ◽  
Rebecca Green ◽  
Min Kim ◽  
Jodie Lord ◽  
Amera Ebshiana ◽  
...  

Background: physiological differences between males and females could contribute to the development of Alzheimer's Disease (AD). Here, we examined metabolic pathways that may lead to precision medicine initiatives. Methods: We explored whether sex modifies the association of 540 plasma metabolites with AD endophenotypes including diagnosis, cerebrospinal fluid (CSF) biomarkers, brain imaging, and cognition using regression analyses for 695 participants (377 females), followed by sex-specific pathway overrepresentation analyses, APOE ε4 stratification and assessment of metabolites’ discriminatory performance in AD. Results: In females with AD, vanillylmandelate (tyrosine pathway) was increased and tryptophan betaine (tryptophan pathway) was decreased. The inclusion of these two metabolites (area under curve (AUC) = 0.83, standard error (SE) = 0.029) to a baseline model (covariates + CSF biomarkers, AUC = 0.92, SE = 0.019) resulted in a significantly higher AUC of 0.96 (SE = 0.012). Kynurenate was decreased in males with AD (AUC = 0.679, SE = 0.046). Conclusions: metabolic sex-specific differences were reported, covering neurotransmission and inflammation pathways with AD endophenotypes. Two metabolites, in pathways related to dopamine and serotonin, were associated to females, paving the way to personalised treatment.


2020 ◽  
Vol 74 (1) ◽  
pp. 213-225 ◽  
Author(s):  
Sarah Westwood ◽  
Alison L. Baird ◽  
Sneha N. Anand ◽  
Alejo J. Nevado-Holgado ◽  
Andrey Kormilitzin ◽  
...  

2006 ◽  
Vol 14 (7S_Part_22) ◽  
pp. P1161-P1161
Author(s):  
Min Kim ◽  
Stuart G. Snowden ◽  
Tahmina Ahmad ◽  
Sarah Westwood ◽  
Alison L. Baird ◽  
...  

2019 ◽  
Author(s):  
Daniel Stamate ◽  
Min Kim ◽  
Petroula Proitsi ◽  
Sarah Westwood ◽  
Alison Baird ◽  
...  

AbstractINTRODUCTIONMachine learning (ML) may harbor the potential to capture the metabolic complexity in Alzheimer’s Disease (AD). Here we set out to test the performance of metabolites in blood to categorise AD when compared to CSF biomarkers.METHODSThis study analysed samples from 242 cognitively normal (CN) people and 115 with AD-type dementia utilizing plasma metabolites (n=883). Deep Learning (DL), Extreme Gradient Boosting (XGBoost) and Random Forest (RF) were used to differentiate AD from CN. These models were internally validated using Nested Cross Validation (NCV).RESULTSOn the test data, DL produced the AUC of 0.85 (0.80-0.89), XGBoost produced 0.88 (0.86-0.89) and RF produced 0.85 (0.83-0.87). By comparison, CSF measures of amyloid, p-tau and t-tau (together with age and gender) produced with XGBoost the AUC values of 0.78, 0.83 and 0.87, respectively.DISCUSSIONThis study showed that plasma metabolites have the potential to match the AUC of well-established AD CSF biomarkers in a relatively small cohort. Further studies in independent cohorts are needed to validate whether this specific panel of blood metabolites can separate AD from controls, and how specific it is for AD as compared with other neurodegenerative disorders


2020 ◽  
Vol 78 (2) ◽  
pp. 721-734
Author(s):  
Cynthia M. Stonnington ◽  
Stefanie N. Velgos ◽  
Yinghua Chen ◽  
Sameena Syed ◽  
Matt Huentelman ◽  
...  

Background: Whether brain-derived neurotrophic factor (BDNF) Met carriage impacts the risk or progression of Alzheimer’s disease (AD) is unknown. Objective: To evaluate the interaction of BDNF Met and APOE4 carriage on cerebral metabolic rate for glucose (CMRgl), amyloid burden, hippocampus volume, and cognitive decline among cognitively unimpaired (CU) adults enrolled in the Arizona APOE cohort study. Methods: 114 CU adults (mean age 56.85 years, 38% male) with longitudinal FDG PET, magnetic resonance imaging, and cognitive measures were BDNF and APOE genotyped. A subgroup of 58 individuals also had Pittsburgh B (PiB) PET imaging. We examined baseline CMRgl, PiB PET amyloid burden, CMRgl, and hippocampus volume change over time, and rate of change in cognition over an average of 15 years. Results: Among APOE4 carriers, BDNF Met carriers had significantly increased amyloid deposition and accelerated CMRgl decline in regions typically affected by AD, but without accompanying acceleration of cognitive decline or hippocampal volume changes and with higher baseline frontal CMRgl and slower frontal decline relative to the Val/Val group. The BDNF effects were not found among APOE4 non-carriers. Conclusion: Our preliminary studies suggest that there is a weak interaction between BDNF Met and APOE4 on amyloid-β plaque burden and longitudinal PET measurements of AD-related CMRgl decline in cognitively unimpaired late-middle-aged and older adults, but with no apparent effect upon rate of cognitive decline. We suggest that cognitive effects of BDNF variants may be mitigated by compensatory increases in frontal brain activity—findings that would need to be confirmed in larger studies.


2014 ◽  
Vol 10 (6) ◽  
pp. 724-734 ◽  
Author(s):  
Martina Sattlecker ◽  
Steven J. Kiddle ◽  
Stephen Newhouse ◽  
Petroula Proitsi ◽  
Sally Nelson ◽  
...  

Data in Brief ◽  
2021 ◽  
pp. 106923
Author(s):  
Mostafa J. Khan ◽  
Heather Desaire ◽  
Oscar L. Lopez ◽  
M. Ilyas Kamboh ◽  
Renã A.S. Robinson

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