Title: Age-dependent differences in brain tissue microstructure assessed with neurite orientation dispersion and density imaging
Legend: Healthy brain aging involves substantial changes to the structures that “wire up” the brain, including myelinated axons and dendritic connections. However, these changes and their impact on memory and other thinking skills are often difficult to measure in living humans Together with our collaborators, including Dr. Andy Alexander at the Waisman Center, graduate student Andrew Merluzzi used multi-shell diffusion-weighted imaging to take a closer look at age-related brain changes in late-middle-aged adults (ages 45-72 years). Using recently developed imaging techniques and new methods for modeling the diffusion of water molecules in the brain, we were able to identify brain regions that show age-related changes. Interestingly, measurements representing “neurite density” in the brain were associated with cognitive performance (even when controlling for age, sex, years of education, and factors that increase risk for dementia). As shown here, (A) Lower neurite density (NDI) in left frontal superior white matter (WM) was associated with poorer learning performance on a word learning test [Rey Auditory Verbal Learning Test (RAVLT)]. (B) Lower NDI in right frontal superior WM was associated with poorer performance on a measure of speed and executive performance [trail-making test (TMT) part B]. (C) Lower NDI in left frontal inferior WM was associated with poorer performance on the learning portion of the RAVLT. (D) Lower NDI in right frontal inferior WM was associated with poorer performance on the learning portion of the RAVLT. Corresponding statistical brain maps in the transverse plane are presented to the right of the scatterplots, with highlighted regions in which NDI is reduced with age in bilateral dorsomedial (top) and ventromedial (bottom) frontal cortex. The bottom line is that greater neurite density (AKA “denser wiring”) is associated with better cognitive function!
Citation:
Merluzzi AP, Dean DC 3rd, Adluru N, Suryawanshi GS, Okonkwo OC, Oh JM, Hermann BP, Sager MA, Asthana S, Zhang H, Johnson SC, Alexander AL, Bendlin BB. (2016). Age-dependent differences in brain tissue microstructure assessed with neurite orientation dispersion and density imaging. Neurobiology of Aging, 43:79-88. doi: 10.1016/j.neurobiolaging.2016.03.026.
Abstract: Human aging is accompanied by progressive changes in executive function and memory, but the biological mechanisms underlying these phenomena are not fully understood. Using neurite orientation dispersion and density imaging, we sought to examine the relationship between age, cellular microstructure, and neuropsychological scores in 116 late middle-aged, cognitively asymptomatic participants. Results revealed widespread increases in the volume fraction of isotropic diffusion and localized decreases in neurite density in frontal white matter regions with increasing age. In addition, several of these microstructural alterations were associated with poorer performance on tests of memory and executive function. These results suggest that neurite orientation dispersion and density imaging is capable of measuring age-related brain changes and the neural correlates of poorer performance on tests of cognitive functioning, largely in accordance with published histological findings and brain-imaging studies of people of this age range. Ultimately, this study sheds light on the processes underlying normal brain development in adulthood, knowledge that is critical for differentiating healthy aging from changes associated with dementia.
About the investigator: Bendlin’s work focuses on brain structure and function in middle and late age, especially in people with increased risk of developing AD due to parental family history, genotype and vascular risk factors. Understanding early brain changes in people who may go on to develop AD is expected to lead to earlier diagnosis, prevention, and the development of new therapies for AD. Her current projects use MRI as a tool to understand the effect of risk factors (parental family history, genotype, Metabolic Syndrome) on brain blood flow and structure. Additionally, she is funded to examine the relationship between cerebrospinal fluid biomarkers and brain structure to learn more about early mechanisms of brain damage in AD.