Independent morphological variables correlate with Aging, Mild Cognitive Impairment, and Alzheimer’s Disease

Abstract

This manuscript presents a study with recruited volunteers that comprehends three sorts of events present in Alzheimer's Disease (AD) evolution (structural, biochemical, and cognitive) to propose an update in neurodegeneration biomarkers for AD. The novel variables, K, I, and S, suggested based on physics properties and empirical evidence, are defined by power-law relations between cortical thickness, exposed and total area, and natural descriptors of brain morphology. Our central hypothesis is that variable K, almost constant in healthy human subjects, is a better discriminator of a diseased brain than the current morphological biomarker, Cortical Thickness, due to its aggregated information. We extracted morphological features from 3T MRI T1w images of 123 elderly subjects: 77 Healthy Cognitive Unimpaired Controls (CTL), 33 Mild Cognitive Impairment (MCI) patients, and 13 Alzheimer's Disease (AD) patients. Moreover, Cerebrospinal Fluid (CSF) biomarkers and clinical data scores were correlated with K, intending to characterize health and disease in the cortex with morphological criteria and cognitive-behavioral profiles. K distinguishes Alzheimer's Disease, Mild Cognitive Impairment, and Healthy Cognitive Unimpaired Controls globally and locally with reasonable accuracy (CTL-AD, 0.82; CTL-MCI, 0.58). Correlations were found between global and local K associated with clinical behavioral data (executive function and memory assessments) and CSF biomarkers (t-Tau, Aβ-40, and Aβ-42). The results suggest that the cortical folding component, K, is a premature discriminator of healthy aging, Mild Cognitive Impairment, and Alzheimer's Disease, with significant differences within diagnostics. Despite the non-concomitant events, we found correlations between brain structural degeneration (K), cognitive tasks, and biochemical markers.

Establishing a baseline for human cortical folding morphological variables: a multicenter study

“…We included ROI as a fixed effect in the linear mixed model equation with harmonized variables: Variable ∼ Age × Diagnostic × ROI + (1 Sample : Diagnostic : ROI ). Rates are summarized in Supplementary Material C. We discriminated AD and healthy aging (CTL) trends with K at the Frontal (p adj < 0.0001), Occipital (p adj < 0.0001), Parietal (p adj < 0.0001), and Temporal lobes (p adj < 0.0001), as expected from [20]. Despite the rates being smaller for AD than CTL, the results mimic the whole brain with Alzheimer’s Disease trajectories appearing as a plateau during aging.…”

“…The natural expansion of this work is to include Mild Cognitive Impairment (MCI) subjects. As seen before, the MCI is an intermediary step between healthy aging and AD in the disease progression, cognitive impairment, and structural changes [20, 36, 37]. Also, we intend to continue this work by applying this approach to a longitudinal dataset composed of MRI structural images with MCI subjects that eventually convert to AD and compare to the cortical folding components of non-converters.…”

“…Participants and data included in this analysis were either acquired by the D’Or Institute for Research and Education (IDOR), Rio de Janeiro, RJ, Brazil, used by [20] (approved by the Hospital Copa D’Or Research Ethics Committee under protocol number CAAE 47163715.0.0000.5249), published by Wang et al [11, 12] or from open-access databases, as AHEAD [21] and AOMIC (PIOP01 and PIOP02) [22]. The total number of subjects is 3095 healthy controls from 4 to 96 years old and 555 Alzheimer’s Disease subjects from 56 to 92 years old.…”

“…Data from previous publications are available from their repositories: Wang et al, 2016 [11] and Wang et al, 2019 [12]. Data from AHEAD [21] and AOMIC [22] datasets with the cortical folding variables extracted by these authors are available [32]. Data acquired at IDOR does not have clearance for public sharing patients’ information that could lead to identification due to local Ethics Committee approval restrictions but will be shared upon request.…”

“…A robust estimation framework of a baseline time function is important to provide future clinical studies enough information to compare brain structure trajectories in case of a pathological investigation. We then, as a clinical application and extension of de Moraes et al [20], and Wang et al [12], verify if Alzheimer’s Disease (AD) is similar to a premature accelerated aging brain in terms of the independent morphological variables, K, S, and I, by comparing their rates. Finally, we have determined the time evolution of the fractal dimension α proposed in Mota & Herculano-Houzel’s model [10], interpreting all results within the framework of this theory.…”