Application of multimodal imaging brain biomarkers in large cohort studies to understand the mixed cerebral pathologies of the aging brain

• Applicant: Professorin Dr. Stefanie Schreiber
• Subject Area: Clinical Neurology; Neurosurgery and Neuroradiology ; Human Cognitive and Systems Neuroscience
• Term: from 2014 to 2016
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 258735457

The so far commonly accepted hypothetical model of Alzheimers disease (AD) pathology proposes that AD pathology biomarkers become abnormal in a temporally ordered manner. While cerebral amyloid biomarkers (including amyloid positron emission tomography (PET)) become abnormal first, biomarkers of neuronal injury and neurodegeneration become abnormal later, and their abnormalities are more closely related to cognitive symptoms. Recent studies demonstrated the existence of aged control subjects, who show abnormal neurodegeneration in AD like pathology signature regions, including hippocampal volume atrophy and fluorodeoxyglucose (FDG) hypometabolism in cingular and temporal cortices, without having cortical amyloid retention. Those subjects have been entitled as SNAP (Suspected Non AD Pathophysiology) cases, and their existence has challenged the temporal order of the hypothetical AD pathology model. However, there are several controversies about the classification of those SNAP subjects, including the fact that their assignment refers to the dichotomized categorization of neurodegeneration biomarkers as positive or negative, though the chosen neurodegeneration biomarker thresholds have not been validated. There is moreover a lack of knowledge, whether and to what extent non AD etiologies, including cerebral small vessel disease and aging, contribute to the neurodegeneration in those subjects who meet the criteria for SNAP classification. To address those controversies I will analyze various imaging biomarkers derived from ADNI (Alzheimers Disease Neuroimaging Initiative), a large multicenter cohort. I first aim to determine distinct thresholds from different derivation samples (including ADNI AD patients and ADNI patients with mild cognitive impairment (MCI)), (i) to classify neurodegeneration biomarkers (including hippocampal volume atrophy and FDG hypometabolism in AD like pathology signature regions) as positive or negative, and (ii) to subsequently apply those thresholds in an evaluation sample (aged controls from ADNI) to test the thresholds validity to identify SNAP cases. In a second step, I will examine the relationship between SNAP like neurodegeneration and the SNAP subjects genetic status, concomitant diseases and vascular risk profile. To investigate, whether SNAP-like neuronal injury is just part of a more widespread pattern of age-dependent neurodegeneration, I moreover aim to specify the overlap between AD like and SNAP like neuronal degeneration using voxelbased analysis.

• DFG Programme: Research Fellowships
• International Connection: USA
• Host: Professor Dr. William Jagust