Microglial activation in Parkinson’s disease using [18F]-FEPPA

Abstract Background Neuroinflammatory processes including activated microglia have been reported to play an important role in Parkinson’s disease (PD). Increased expression of translocator protein (TSPO) has been observed after brain injury and inflammation in neurodegenerative diseases. Positron emission tomography (PET) radioligand targeting TSPO allows for the quantification of neuroinflammation in vivo. Methods Based on the genotype of the rs6791 polymorphism in the TSPO gene, we included 25 mixed-affinity binders (MABs) (14 PD patients and 11 age-matched healthy controls (HC)) and 27 high-affinity binders (HABs) (16 PD patients and 11 age-matched HC) to assess regional differences in the second-generation radioligand [18F]-FEPPA between PD patients and HC. FEPPA total distribution volume (V T) values in cortical as well as subcortical brain regions were derived from a two-tissue compartment model with arterial plasma as an input function. Results Our results revealed a significant main effect of genotype on [18F]-FEPPA V T in every brain region, but no main effect of disease or disease × genotype interaction in any brain region. The overall percentage difference of the mean FEPPA V T between HC-MABs and HC-HABs was 32.6% (SD = 2.09) and for PD-MABs and PD-HABs was 43.1% (SD = 1.21). Conclusions Future investigations are needed to determine the significance of [18F]-FEPPA as a biomarker of neuroinflammation as well as the importance of the rs6971 polymorphism and its clinical consequence in PD

Feasibility study of TSPO quantification with [18F]FEPPA using population-based input function.

The input function (IF) is a core element in the quantification of Translocator protein 18 kDa with positron emission tomography (PET), as no suitable reference region with negligible binding has been identified. Arterial blood sampling is indeed needed to create the IF (ASIF). In the present manuscript we study individualization of a population based input function (PBIF) with a single arterial manual sample to estimate total distribution volume (VT) for [18F]FEPPA and to replicate previously published clinical studies in which the ASIF was used.The data of 3 previous [18F]FEPPA studies (39 of healthy controls (HC), 16 patients with Parkinson's disease (PD) and 18 with Alzheimer's disease (AD)) was reanalyzed with the new approach. PBIF was used with the Logan graphical analysis (GA) neglecting the vascular contribution to estimate VT. Time of linearization of the GA was determined with the maximum error criteria. The optimal calibration of the PBIF was determined based on the area under the curve (AUC) of the IF and the agreement range of VT between methods. The shape of the IF between groups was studied while taking into account genotyping of the polymorphism (rs6971).PBIF scaled with a single value of activity due to unmetabolized radioligand in arterial plasma, calculated as the average of a sample taken at 60 min and a sample taken at 90 min post-injection, yielded a good interval of agreement between methods and optimized the area under the curve of IF. In HC, gray matter VTs estimated by PBIF highly correlated with those using the standard method (r2 = 0.82, p = 0.0001). Bland-Altman plots revealed PBIF slightly underestimates (~1 mL/cm3) VT calculated by ASIF (including a vascular contribution). It was verified that the AUC of the ASIF were independent of genotype and disease (HC, PD, and AD). Previous clinical results were replicated using PBIF but with lower statistical power.A single arterial blood sample taken 75 minute post-injection contains enough information to individualize the IF in the groups of subjects studied; however, the higher variability produced requires an increase in sample size to reach the same effect size

Imaging Markers of Progression in Parkinson's Disease

BackgroundParkinson’s disease (PD) is the second‐most common neurodegenerative disorder after Alzheimer’s disease; however, to date, there is no approved treatment that stops or slows down disease progression. Over the past decades, neuroimaging studies, including molecular imaging and MRI are trying to provide insights into the mechanisms underlying PD.MethodsThis work utilized a literature review.ResultsIt is now becoming clear that these imaging modalities can provide biomarkers that can objectively detect brain changes related to PD and monitor these changes as the disease progresses, and these biomarkers are required to establish a breakthrough in neuroprotective or disease‐modifying therapeutics.ConclusionsHere, we provide a review of recent observations deriving from PET, single‐positron emission tomography, and MRI studies exploring PD and other parkinsonian disorders.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147080/1/mdc312673_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147080/2/mdc312673.pd

Comparison of the AUC of the PBIF and ASIF at 60 and 120 min as a function of the time-sample used to rescale.

<p>Samples at 75 min minimize the difference and SD. It should be noted that sample at 52 min is the average between 45and 60 min and 75 is the average between 60 and 90 min. the result is the average between 21 HC, 18 AD and 16 PD.</p

Comparison of total distribution volume (<i>V</i>_<i>T</i>) between healthy controls and PD patients calculated with ASIF and PBIF75 for putamen (left) and caudate (right).

<p>Estimation with PBIF75 led to same conclusion as with the ASIF; that there is no difference from disease (p = 0.2 in Caudate and p = 0.8 in the Putamen using PBIF vs p = 0.4 in Caudate and p = 0.7 in Putamen using ISIF) and that there is a difference due to genotype (p = 0.001 in Caudate and p = 0.002 in Putamen using PBIF vs p = 0.001 in the Caudate and p = 0.0008 in Putamen using ASIF). Images were partial volume effect corrected prior to TAC extraction.</p

Bland-altman plot of <i>V</i>_<i>T</i> assessed by ASIF (2-TCM) and PBIF75 (Logan plot) for 7 regions of interest in healthy controls.

<p>FEPPA <i>V</i>_<i>T</i><i>s</i> derived by Logan PBIF75 plot slightly underestimated (Bias < 1 mL/cm³) those derived with 2-TCM. (A) In MABs (n = 7), the 95% limits of agreement (dashed <i>lines</i>) was between -0.7 to 1.3 mL/cm³ and no systematic bias was observed (r = 0.12, p = 0.6). (B) In HABs (n = 14), the 95% limits of agreement (dashed lines) was between -2.2 to 4.2 mL/cm³ and no systematic bias was observed (r = 0.08, p = 0.7).</p

Total distribution volume (<i>V</i>_<i>T</i>) calculated using ASIF (2-TCM) and PBIF75 (Logan plot).

<p>In Temporal, Prefrontal, Hippocampus, Parietal and Occipital regions stratified as HAB and MAB groups. ASIF showed an average reduction of 29% in <i>V</i>_<i>T</i> across ROIs while PBIF showed a reduction of 26%. 5/7 ROIs survived the multiple region Bonferroni adjustment using ASIF and only 2/7 passed the Bonferroni adjustment using PBIF75. Images were partial volume effect corrected prior to TAC extraction. * p< 0.05, ** p<0.01 *** p< 0.001.</p

Comparison of [¹⁸F]FEPPA regional total distribution volume (<i>V</i>_<i>T</i>) between healthy control subjects and AD patients calculated with PBIF75 for HABs (left) and MABs (right).

<p>(<i>cf</i>. figure 1 in ref [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0177785#pone.0177785.ref007" target="_blank">7</a>]). PBIF75 estimation led to the same conclusion as the previously published with ASIF: [¹⁸F]FEPPA <i>V</i>_<i>T</i> in AD patients is on average 13–48% higher than HC (A Factorial ANOVA with genotype and age as covariate showed: p<0.05 in the Temporal, Prefrontal, Parietal and Occipital and p = 0.4 in the hippocampus). Images were partial volume effect corrected prior to TAC extraction. * p< 0.05 in ANOVA within group.</p

Population based input function.

<p>A) Average (n = 24) time evolution of unmetabolized [¹⁸F]FEPPA in plasma from HC (n = 8), PD (n = 8) and AD (n = 8) subjects. The inner plot shows details of the first 100 seconds post injection. B) The area under the curve of the input functions created from arterial blood sampling did not differ between 21 HC, 18 AD and 16 PD.</p