Ravi Prakash Reddy Nanga¹, Halvor Juul¹, Narayan Data Soni¹, Blake Benyard¹, Anshuman Swain², Ryan Armbruster¹, Paul Jacobs¹, and Ravinder Reddy^1
1Radiology, Center for Advance Metabolic Imaging in Precision Medicine, Perelman School of Medicine at The University of Pennsylvania, Philadelphia, PA, United States, ²Center for Advance Metabolic Imaging in Precision Medicine, Perelman School of Medicine at The University of Pennsylvania, Philadelphia, PA, United States

In order to probe the metabolism of glutamate and myo-inositol for better understanding of the Alzheimer’s diseases (AD) we have employed the chemical exchange saturation transfer of glutamate (GluCEST) and myoinositol (MICEST) in a fast progressing, 5xFAD mouse model. There were significant differences observed in the GluCEST and MICEST maps of 5XFAD mice when compared to the wild-type (WT) mice for regions of interest drawn on hippocampus and thalamus, which are further supported by the spectroscopy results.

Lars Michels¹, Valerie Treyer^2,3, Anton Gietl⁴, and Ruth O’Gorman Tuura^5
1Department of Neuroradiology, University Hospital Zurich, Zurich, Switzerland, ²Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland, ³Institute of Regenerative Medicine Zurich, University of Zurich, Zurich, Switzerland, ⁴Institute of Regenerative Medicine Zurich., University of Zurich, Zurich, Switzerland, ⁵Center for MR Research, University Children's Hospital, Zurich, Switzerland

Glutathione (GSH) is a brain marker for oxidative stress, which has previously been associated with brain amyloidosis and memory decline. However, to date no study has examined the link between GSH and beta-amyloid in a large cohort of elderly participants. Using simultaneous PET/MRS, we assessed amyloid deposition with amyloid-PET and GSH with MEGAPRESS, in a cohort of 134 healthy elderly and 46 mild cognitively impaired participants. GSH declined with age and showed sex differences, but no significant association between GSH and amyloid status was observed

Michael Wolf¹, Carlos Cruchaga², Jillilan Crocker¹, Priyanka Gorijala², Laura Hemmy³, James Hodges¹, Samira Mafimoghaddam², Silvia Mangia¹, Malgorzata Marjanska¹, Riley McCarten³, Thomas Nichols⁴, Jeromy Thotland¹, Rachel Zilinskas¹, and Melissa Terpstra^5
1University of Minnesota, Minneapolis, MN, United States, ²Washington University School of Medicine, St. Louis, MO, United States, ³Minneapolis VA Health Care System, Minneapolis, MN, United States, ⁴University of Oxford, Oxford, United Kingdom, ⁵University of Missouri, Columbia, MO, United States

Ultra-high field (7T) ultra-short echo time (8 ms STEAM) MRS can consistently provide a 14-neurochemical profile and distinguish aging and AD status. In this project, we generated composite scores from published age- and AD- specific neurochemical profiles and applied them to a typically aging cohort for whom polygenic risk for AD and extensive cognitive performance data were also available. Principal component analysis of the neurochemical profile fully distinguished aging, and AD classification was 58% correct. The largest correlation coefficients (r) were found between MRS and cognition. Correlation between MRS and polygenic risk and between cognition and polygenic risk was smaller.

Leo Cheng¹, Isabella Muti¹, JianXiang Weng¹, Anya Zhong¹, Pia Kivisäkk², Bradley Hyman², and Steven Arnold^2
1Massachusetts General Hospital, Charlestown, MA, United States, ²Massachusetts General Hospital, Boston, MA, United States

Currently, a definitive AD diagnosis can only be achieved at autopsy, through pathology examinations of brain tissue. No non- or less-invasive examination can yet diagnose and characterize AD during the patient’s life, in turn limiting insights into potential strategies for countering AD modes of progression. Here, using HRMAS MRS, we studied human blood plasma samples obtained from AD and non-AD subjects to reveal potential AD-associated metabolomic changes measurable in blood, which may assist with AD diagnosis and, more importantly, contribute to the development of precision treatments. 

Ulrich Pilatus¹, Gunter P. Eckert², Nasir Ludin¹, Silke Matura¹, Johannes Pantel¹, Carmen Silaidos², Lena Wachter², and Elke Hattingen^1
1Goethe-University Frankfurt, Frankfurt, Germany, ²Justus-Liebig-University of Giessen, Giessen, Germany

Combining quantitative (mmol/l) ¹H MRSI and ³¹P MRSI data from the brain of healthy volunteers revealed a choline component (rCho=tCho-(PCho+GPC)) which is visible with ¹H MRSI but missing in ³¹P MRSI. This component, which may account for a fraction of mobile phospholipids, is reduced in young female (mean age 26) subjects.  Lower levels would indicate a  higher integrity of the membrane phospholipids in the brain of young women. A possible reason is the higher estrogen levels in this group.

Marilena M DeMayo^1,2, Jinglei Lv^1,2, Shantel Duffy^3,4, Sharon Naismith^3,4,5, and Fernando Calamante^1,2,6
1School of Biomedical Engineering, University of Sydney, Sydney, Australia, ²Brain and Mind Centre, University of Sydney, Sydney, Australia, ³School of Psychology, University of Sydney, Sydney, Australia, ⁴Healthy Brain Ageing Program, Brain and Mind Centre, University of Sydney, Sydney, Australia, ⁵Centre of Research Excellence to Optimise Sleep in Brain Ageing and Neurodegeneration (CogSleep CRE), Sydney, Australia, ⁶Sydney Imaging, University of Sydney, Sydney, Australia

We investigated the association between two MR markers of Mild Cognitive Impairment (MCI): N-Acetylaspartate (NAA) measured by MR Spectroscopy within the hippocampus; and functional connectivity within the Default Mode Network (DMN). We showed differential relationships between functional coupling/connectivity and NAA in MCI and controls, with an association between these measures in MCI not evident in controls. For those with MCI, we detected 20 connections within the DMN associated with NAA levels, with stronger connectivity associated with lower NAA levels. This suggests change in NAA within the hippocampus is associated with functional change within the DMN for those with MCI.

Moritz Simon Fabian¹, Stefan Hock¹, Angelika Barbara Mennecke¹, Manuel Schmidt¹, Arnd Dörfler¹, and Moritz Zaiß^1,2
1Neuroradiology, University Hospital Erlangen, Erlangen, Germany, ²High-field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany

Differentiation of active multiple sclerosis lesions from non-active ones is done in the clinical environment by using contrast enhanced T1 images. CEST MRI has shown to yield correlations with Gadolinium contrast enhancement in tumors and other pathological tissue. In this work, we are trying to gain more insight in the metabolic information regarding the brain of patients suffering from multiple sclerosis.