Magnitude and kinetics of a set of neuroanatomic volume and thickness together with white matter hyperintensity is definitive of cognitive status and brain age

Even among the subjects classified as cognitively normal, there exists a subset of individuals at a given chronological age (CA) who harbor white matter hyperintensity (WMH) while another subset presents with low or undetectable WMH. Here, we conducted a comprehensive MRI segmentation of neuroanatomic structures along with WMH quantification in groups of cognitively normal (CN), cognitively impaired (CI) individuals, and individuals with an etiological diagnosis of cognitive impairment owing to Alzheimer's Disease (CI-AD) across the early (50-64 years), intermediate (65-79 years), and late (≥80 years) age groups from the NACC cohort. Neuroanatomic volumetry quantification revealed that thinning of the parahippocampal gyrus in the early (p = 0.016) and intermediate age groups (p = 0.0001) along with an increase in CSF (p = 0.0009) delineates between CI and CI-AD subjects. Although, a significant loss of ~5-10% in volume of gray matter (p<sub>(CN vs CI)</sub> < 0.0001, p<sub>(CN vs CI-AD)</sub> < 0.0001), white matter (p<sub>(CN vs CI)</sub> = 0.002, p<sub>(CN vs CI-AD)</sub> = 0.0003) and hippocampus (p<sub>(CN vs CI)</sub> = 0.007, p<sub>(CN vs CI-AD)</sub> < 0.0001) was evident at the early age groups in the CI and CI-AD compared to CN but it was not distinct between CI and CI-AD. Using the neuroanatomic and WMH volume, and the supervised decision tree-based ML modeling, we have established that a minimum set of Three brain quantities; Total brain (GM + WM), CSF, and WMH volume, provide the Optimal quantitative features discriminative of cognitive status as CN, CI, and CI-AD. Furthermore, using the volume/thickness of 178 neuroanatomic structures, periventricular and deep WMH volume quantification for the 819 CN subjects, we have developed a quantitative index as 'Brain Age' (BA) depictive of neuroanatomic health at a given CA. Subjects with elevated WMH load (5-10 ml) had increased BA ( + 0.6 to +4 years) than the CA. Increased BA in the subjects with elevated WMH is suggestive of WMH-induced vascular insult leading to accelerated and early structural loss than expected for a given CA. Henceforth, this study establishes that quantification of WMH together with an optimal number of neuroanatomic features is mandatory to delve into the biological underpinning of aging and aging-associated cognitive disorders.

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Publication Details

Journal
Translational Psychiatry
Published
2024-09-27
DOI
https://doi.org/10.1038/s41398-024-03097-2
Citations
2
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
0.69

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article

Magnitude and kinetics of a set of neuroanatomic volume and thickness together with white matter hyperintensity is definitive of cognitive status and brain age

Neha Yadav, Darshit Thakar, Vivek Tiwari, Niraj Kumar Gupta
2 citations
Translational Psychiatry
Functional Brain Connectivity Studies
0.69
article

Magnitude and kinetics of a set of neuroanatomic volume and thickness together with white matter hyperintensity is definitive of cognitive status and brain age

Neha Yadav, Darshit Thakar, Vivek Tiwari, Niraj Kumar Gupta
article en
2 citations

Abstract

Even among the subjects classified as cognitively normal, there exists a subset of individuals at a given chronological age (CA) who harbor white matter hyperintensity (WMH) while another subset presents with low or undetectable WMH. Here, we conducted a comprehensive MRI segmentation of neuroanatomic structures along with WMH quantification in groups of cognitively normal (CN), cognitively impaired (CI) individuals, and individuals with an etiological diagnosis of cognitive impairment owing to Alzheimer's Disease (CI-AD) across the early (50-64 years), intermediate (65-79 years), and late (≥80 years) age groups from the NACC cohort. Neuroanatomic volumetry quantification revealed that thinning of the parahippocampal gyrus in the early (p = 0.016) and intermediate age groups (p = 0.0001) along with an increase in CSF (p = 0.0009) delineates between CI and CI-AD subjects. Although, a significant loss of ~5-10% in volume of gray matter (p<sub>(CN vs CI)</sub> < 0.0001, p<sub>(CN vs CI-AD)</sub> < 0.0001), white matter (p<sub>(CN vs CI)</sub> = 0.002, p<sub>(CN vs CI-AD)</sub> = 0.0003) and hippocampus (p<sub>(CN vs CI)</sub> = 0.007, p<sub>(CN vs CI-AD)</sub> < 0.0001) was evident at the early age groups in the CI and CI-AD compared to CN but it was not distinct between CI and CI-AD. Using the neuroanatomic and WMH volume, and the supervised decision tree-based ML modeling, we have established that a minimum set of Three brain quantities; Total brain (GM + WM), CSF, and WMH volume, provide the Optimal quantitative features discriminative of cognitive status as CN, CI, and CI-AD. Furthermore, using the volume/thickness of 178 neuroanatomic structures, periventricular and deep WMH volume quantification for the 819 CN subjects, we have developed a quantitative index as 'Brain Age' (BA) depictive of neuroanatomic health at a given CA. Subjects with elevated WMH load (5-10 ml) had increased BA ( + 0.6 to +4 years) than the CA. Increased BA in the subjects with elevated WMH is suggestive of WMH-induced vascular insult leading to accelerated and early structural loss than expected for a given CA. Henceforth, this study establishes that quantification of WMH together with an optimal number of neuroanatomic features is mandatory to delve into the biological underpinning of aging and aging-associated cognitive disorders.

Translational PsychiatryVol. 14(1)
Indian Institute of Science Education and Research Berhampur (IN)
U.S. Department of Defense, Alzheimer's Association, Bristol-Myers Squibb, Eli Lilly and Company, Pfizer, Biogen, University of Southern California, Meso Scale Diagnostics, Alzheimer's Disease Neuroimaging Initiative, BioClinica, Novartis Pharmaceuticals Corporation, Northern California Institute for Research and Education, Eisai, Servier, H. Lundbeck A/S, IXICO, National Institutes of Health, Genentech, Canadian Institutes of Health Research, National Institute on Aging
Openalex Percentile: Top 31%
Functional Brain Connectivity Studies
0.69
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