Summary of Chapter

In summary, this Chapter has demonstrated that in a working memory task, there is less deactivation in the PCC ROI to increasing working memory load when the stimuli are scenes (3D rooms) compared to when they are 2D shapes. This is in support of the findings of Chapter 3 that the BOLD response in the PCC ROI shows category sensitivity. Also consistent with Chapter 3, no significant BOLD-behaviour correlations were detected. This finding challenges previous studies that suggest PCC deactivation has a relationship with task difficulty, and instead, could imply that it may be a property of viewing scenes that is associated with the different pattern of deactivation across scenes and shapes. Similar to the tNAA-BOLD relationship identified in Chapter 3, individual differences in the magnitude of this deactivation to scenes, but not to shapes, was related to individual differences in PCC tNAA. This suggests there may be a category sensitive PCC BOLD-PCC tNAA relationship for scene working memory, as well as a category sensitive PCC BOLD-PCC tNAA relationship for scene perception, as indicated in Chapter 3. PCC tNAA was the only metabolite that appeared to show a category-sensitive relationship for scenes, as the region within the PCC that showed a correlation between GABA+ and BOLD for scenes was highly similar to a region that showed a correlation between GABA+ and shapes. This adds new knowledge to the MRS-BOLD literature, as category sensitivity in working memory studies has not previously been assessed. The complementary findings of a PCC tNAA-PCC scene BOLD relationship on the two paradigms that young APOE-E4 carriers showed an altered pattern of activity in the PCC ROI (less deactivation) (Shine et al., 2015) provide support for the hypothesis that the alteration in PCC BOLD in the APOE-E4 carriers could be associated with an alteration in

PCC MRS, with a tNAA now being the strongest candidate for a potential metabolite alteration. The next Chapter will investigate this question, asking whether young APOE- E4 carriers and non-carriers show different profiles of tNAA concentration in the PCC.

5 Chapter 5: Investigating metabolite

differences between young APOE-E4

carriers and non-carriers in posterior

cingulate cortex using MRS

5.1 Introduction

The purpose of this final experimental Chapter was to investigate whether there are differences in MRS metabolites in the PCC of young APOE-E4 carriers compared to non-carriers. The rationale for testing MRS in these groups was, as introduced in Chapter 1, that such an approach allows us to investigate potential biochemical differences in a key brain region implicated in AD pathogenesis, in order to gain insight into how and why this disease may develop in some at risk individuals. Several neuroimaging studies have adopted this strategy to study the impact of the APOE-E4 allele in young people in the PCC; these suggest alterations in PCC resting state fMRI activity (Filippini, MacIntosh, et al., 2009), task-related fMRI activity (Shine et al., 2015), functional connectivity (measured using fMRI) (Dennis et al., 2010), and glucose metabolism (measured using FDG-PET) in APOE-E4 carriers (Reiman et al., 2004). A question that has not yet been addressed in this age group is whether there are also biochemical differences in the PCC region measured using MRS.

MRS is a valuable neuroimaging technique to apply here, as it can provide additional biochemical information to augment the findings from fMRI and FDG-PET studies, as outlined in Chapters 1 and 2. FMRI tells us about spatial specificity of any activity differences between E4 carriers and non-carriers, but it does not tell us very much about the biological mechanisms behind why brain regions are more active. If we can better understand the biological pathways behind the altered brain activity in these individuals, it could provide clues as to what biological pathways, potentially linked to risk genes, may pre-dispose an individual to develop AD later in life. FDG-PET is another technique that provides biochemical information as this tells us about glucose metabolism, however MRS can augment the information gleaned using this research

technique as it provides extra biochemical information on different biological markers, such as markers of inflammation, energy metabolism and neuronal density (Rae, 2014). Furthermore, MRS is more appealing than FDG-PET, since MRS is a non-invasive technique and can be performed in a standard MRI scanner, whereas FDG-PET involves radioactive isotopes and is more expensive (Johnson, Fox, Sperling, & Klunk, 2012). Another method to assess biochemistry is post-mortem histology studies, but such studies are very rare thus are not an optimal method of investigation (despite being incredibly informative, e.g. Perkins et al., 2016, Valla et al., 2010, a point which will be further discussed later in this introduction).

In the general introduction Chapter, I hypothesised that alterations in PCC MRS metabolites in APOE-E4 carriers (compared to non-carriers) might underlie the differences in PCC fMRI activity evident between these groups in Shine et al. (2015). In support of this hypothesis, biochemical alterations have been detected in young APOE-E4 carriers compared to non-carriers, using FDG-PET (Reiman et al., 2004) and in post- mortem studies of young APOE-E4 carriers (Perkins et al., 2016; Valla et al., 2010); MRS metabolite alterations also exist in AD, MCI, older APOE-E4 carriers, as well as pre- symptomatic FAD mutation carriers (e.g. Bai et al., 2014; Fayed, Modrego, Rojas-Salinas, & Aguilar, 2011; Godbolt et al., 2006; K. Kantarci et al., 2000; Kejal Kantarci et al., 2007; Laakso et al., 2003; Walecki, Barcikowska, Ćwikła, & Gabryelewicz, 2011).

Important for my hypothesis, however, is that it is possible for scene-sensitive BOLD-MRS relationships to exist. Chapters 3 and 4 provided novel information that PCC BOLD for just the scene conditions of a perception task and a working memory task (which were the same or similar to the tasks in Shine et al., (2015)) were indeed related to PCC MRS metabolites, thus addressing this missing link in support of my hypothesis. More specifically, a region towards the superior medial surface of the PCC had a positive relationship with PCC tNAA. As tNAA was positively correlated with PCC BOLD during the scene conditions of these two tasks, and APOE-E4 carriers showed a more positive BOLD response to both scene conditions of these tasks in Shine et al. (2015), then the next question is whether APOE-E4 carriers have a higher concentration of tNAA which could underlie their higher PCC BOLD response to scenes.

The rationale and approach applied here to link altered fMRI activity (during a task sensitive to behavioural impairments in a disease) with altered MRS biochemistry is similar to that an approach that has been successfully used in schizophrenia research.

First, it was established that schizophrenia patients show behavioural impairment in cognitive control, which is defined as the ability to flexibly switch between different thoughts and actions (Dreisbach, 2012). An example of this is that patients show poorer performance than healthy controls in the Stroop task, which requires the ability to inhibit reading the colour in which a word is printed (Hepp, Maier, Hermle, & Spitzer, 1996). Next, fMRI was used in healthy controls to investigate which brain regions are important for cognitive control. This revealed that the ACC is involved in cognitive control tasks, as evidenced by increased activity in this brain region during conditions of high compared to low cognitive control demands (Falkenberg, Specht, & Westerhausen, 2011). Third, a metabolite that was most likely to be altered in schizophrenia was selected to be studied (glutamate, given the glutamatergic imbalance hypothesis behind schizophrenia pathogenesis (Moghaddam & Javitt, 2012)). Then MRS was used to measure ACC Glx in healthy controls; this was found to be correlated with fMRI activity during an auditory cognitive control task (Falkenberg et al., 2012). Fourth, the researchers then studied schizophrenia patients to investigate whether ACC Glx was different in patients compared to healthy controls (Falkenberg et al., 2014; Reid et al., 2010). Finally, this study assessed whether the Glx-BOLD relationship evident during cognitive control tasks was the same as that found in healthy controls or whether it was altered (Falkenberg et al., 2014). Aligned to this series of studies in schizophrenia, the MRS study in this Chapter represents the fourth step in this series. It aimed to investigate whether the metabolite that has been associated with the BOLD response during scene processing tasks sensitive to impairment in AD, and which shows altered activity in young APOE-E4 carriers, is different in APOE-E4 participants compared to non-carriers.