GRADIENT protocol “InteGRAted DIagnostic framework and ENThorinal cortex atrophy assessment in MCI patients”: towards an integrated early diagnosis for Mild Cognitive Impairment

We will present the research protocol developed as part of the 40th Cycle Doctoral Program in Scienze e Tecnologie Biologiche e Ambientali, and conducted at the Laboratorio Inspire, Professor S. Invitto, lecturer at Unisalento; PhD student Anna Zito, nephrologist at the Lecce Local Health Authority.

The working hypothesis arose from the need to identify an integrated diagnostic algorithm for the early diagnosis of Mild Cognitive Impairment, a neurological condition that can precede the development of full-blown dementia, which is increasingly common in today's society, characterized by an elderly population with multiple pathologies.

The project will be presented in poster form.

INTRODUCTION

Mild cognitive impairment (MCI) is a clinical condition resembling the transitional phase between normal cognitive function and Alzheimer’s disease (AD). MCI diagnosis is often challenging due to its heterogeneous nature, blurred symptomatology, and overlapping traits with normal aging and early-stage dementia. 

In MCI, mild degenerative changes are detectable in medial temporal lobe structures, specifically in the perientorhinal cortex and hippocampus. Interestingly, the same structures are crucial in integrating sensory information, particularly from the olfactory system. Since olfactory impairment emerges in patients at early stages of AD and/or MCI, studies suggest that olfactory function serves as an early biomarker in neurodegenerative diseases. Additionally, olfactory deficits have been linked to depressive disorders, reflecting broader disruptions in neural circuits related to emotion and cognition. 

Identifying sensitive and early integrated diagnostic tools may offer a promising psychophysiological approach to detecting presymptomatic AD stages and possibly delaying the onset of the overt disease. Our previous work has demonstrated how, in MCI patients, entorhinal cortex atrophy, assessed through ERICA scores, is primarily related to anxiety scores.

Indeed, prolonged stress and anxiety can contribute to neurodegenerative processes by inducing chronic stress and inflammation in the brain, via their effects on the hypothalamic–pituitary–adrenal axis and the dysregulated release of stress hormones such as cortisol. Since saliva is a non-invasive and widely accessible biological fluid, measuring cortisol may be useful for early diagnosis. Thus, the proposed project aims to design and validate an integrated, multilevel diagnostic panel to identify early and reliable hallmarks of MCI.

METHODS 

We designed a study protocol named “GRADIENT MCI” (InteGRAted DIagnostic framework and ENThorinal cortex atrophy assessment in MCI patients). We will perform an overall evaluation of 30 subjects with MCI, selected based on a clinical suspicion in the Alzheimer Assessment Unit (UVA Lecce) of the Vito Fazzi Hospital, Lecce ASL, Puglia, Italy. The assessment will include: -neurological assessment, neuroimaging (i.e, ERICA score); -neuropsychological and psychological evaluation; -psychophysical (i.e, Sniffing Stick test) and psychophysiological olfactory assessment (i.e, OERP);  and levels of a biomarker (cortisol) in saliva. 

This study will examine the correlation between the degree of perientorhinal and hippocampal atrophy as assessed by MRI imaging, levels of cortisol in saliva, OERP components, and neuropsychological variables in a sample of multidomain MCI patients, as assessed through a comprehensive neuropsychological and psychophysiological evaluation. A predictive inferential model will be built on the variables put into the system.

CONCLUSION 

By focusing on medial temporal lobe structures—particularly the entorhinal cortex and hippocampus—and incorporating olfactory function and salivary biomarkers such as cortisol, this study aims to construct a multidimensional diagnostic framework. Ultimately, we aim to develop a predictive model that identifies early hallmarks of cognitive decline, facilitating earlier interventions. This multidisciplinary methodology enriches our understanding of MCI and lays the groundwork for a more sensitive, accessible, and non-invasive diagnostic tool in clinical practice.