Traumatic brain injury (TBI) is a potentially dangerous medical condition which occurs when a violent external force – such as a fall or blow to the head – injures the brain. Alzheimer's disease (AD) is an incurable brain disease which usually starts slowly and worsens over time, leading to memory loss, confusion, and to other forms of mental disability. Though TBI victims are more likely to develop AD, it can be very difficult for both scientists and clinicians to accurately estimate the likelihood that any particular TBI patient will develop AD. In addition, the AD manifestations of TBI survivors may differ from those of typical AD patients in poorly understood ways which could make the clinical care of such patients more challenging. For such reasons, it would be extremely useful to understand how TBI may lead to AD and to identify new ways to predict how likely it is for a TBI victim to develop AD.

The purpose of this scientific study is to shed light on this by using sophisticated methods to study the brains of older adults who are either healthy, TBI survivors, AD patients, or both. The main hypothesis of the study is that the TBI-affected brain has certain anatomic properties which, if known, could help scientists to predict the likelihood of AD after TBI with high accuracy. The secondary hypothesis of the study is that at least some of these properties are different from those which are already known to be risk factors for AD (e.g., obesity, smoking, a history of high blood pressure, or certain inherited traits).

To accomplish the goals of the project, we propose to use a technique for imaging the brain called magnetic resonance imaging (MRI), which is a powerful and safe technology being used routinely by clinicians worldwide. When used together with sophisticated scientific methods for brain image analysis, MRI will allow us to compare against one another four groups of individuals: (1) healthy older adults, (2) older adults who have survived TBI and who did not have AD at the time of the study, (3) older adults with no history of TBI but who had been diagnosed with AD by the time of the study, and (4) older adults who are both TBI survivors and who had been diagnosed with AD by the time of the study. The brain images of each volunteer will be analyzed to quantify the structural properties of various brain regions as well as the properties of the brain circuitry connections between every pair of such regions. All these properties will be compared to identify brain features that distinguish groups from one another to an extent which is very unlikely to be due to chance alone. Very importantly, such comparisons may allow us to find properties of the TBI-affected brain whose characteristics are commensurate with the likelihood of TBI survivors to develop AD.

Though several risk factors for AD are already known to science, few of them can assist with evaluating AD risk in TBI survivors above and beyond the extent to which this can already be done in individuals without TBI. Partly for this reason, this proposed project to identify novel AD risk factors that are specific to the TBI population can be of substantial clinical benefit. Specifically, (1) having the ability to accurately identify TBI victims at high risk for AD could have substantial consequences for the healthcare of such individuals, and (2) understanding the relationship between TBI and AD could advance our scientific and clinical knowledge regarding these two conditions.