We believe that this is the first study to investigate the effect of the PARK16 rs11240572 variant on the GMV of the whole brain in PD patients by VBM analysis. Our results showed that patients with the variant had a different brain structure to a control group in a Chinese PD cohort. The differences of brain structure were located at basal ganglia and temporoparietal cortex, hinting that it might play a key role in the pathogenesis of PD.
PARK16 is located on chromosome 1q32, and seven of its SNPs (rs16856139, rs823128, rs823122, rs947211, rs823156, rs708730 and rs11240572) were found to be risk factors for PD in a Japanese cohort (Satake et al., 2009). However, subsequent studies demonstrated that some SNPs, including rs11240572, were in fact associated with PD risk reduction in a Chinese population (Chang et al., 2013; Tan et al., 2010; Yan et al., 2011). The SNP rs11240572 is located in the peptidase M20-domain-containing protein 1 (PM20D1) gene, which is associated with metal ion binding and peptidase activity (Kimura et al., 2006). Brain iron deposition is closely related to PD, as the accumulation of iron in the substantia nigra has been recognized as a major characteristic of PD (Guan et al., 2017; Sanchez-Mut et al., 2018). However, whether rs11240572 also affects iron homeostasis in the brain need to be further elucidated.
Our study found that PARK16 rs11240572-A variant carriers had increased GMV of basal ganglia, along with better motor and cognitive scores. These results suggest that the rs11240572-A variant may slow down the progression of PD, consistent with previous reports suggesting that it has a protective function (Chang et al., 2013; Tan et al., 2010; Yan et al., 2011). The pathogenesis of PD involves the basal ganglia, including the caudate nucleus and putamen, resulting in impaired movement control (Fang et al. 2020) as well as poor cognition such as impaired learning, planning, memory, and emotion (Obeso et al., 2008; Gao et al., 2017). Previous studies have found that PD patients have a variable GMV in the putamen, caudate nucleus, cerebellum and cerebral cortex. Brockmann et al. (2011) reported a decreased basal ganglia GMV, especially in the putamen of LRRK2 mutation patients. Similarly, Reetz et al. (2009) showed that subjects with a parkin gene mutation had decreased basal ganglia GMV. In contrast, two studies (Burciu et al., 2018; Vilas et al., 2016) found no change in the brain structure of patients with either a LRRK2 mutation or a SNCA variant. We use a preliminary threshold with GRF correction of voxel p = 0.005 and cluster p = 0.05. Previous study has reported positive results of VBM using volumetric threshold of p < 0.005 and cluster level of p < 0.05. (Engelhardt, Boulat et al. 2020). No findings survived with a threshold of voxel p < 0.001 and cluster p < 0.05.
In the non-carrier group, we also found left basal ganglia GMV was positively correlated with UPDRS III and bradykinesia, but negatively correlated with MMSE using correlation analysis. Several studies has found similar results and explained these phenomena as plasticity compensation of neurons (Binkofski et al. 2007, Brockmann et al. 2011).Changes in GM signal extracted from MRI images can reflect various processes, such as changes in the number of synapses, the number of glial cells, the number of neurons, dendritic structure, vasculature, blood volume and circulation, and myelination. (Spruston et al.,2008, Hoekzema et al., 2017). In the structure of neurons, dendrites are key sites for synaptic integration and neuronal connectivity in the brain. Kassem et al.(2013) demonstrated that grey matter loss determined by MRI is primarily due to loss of dendrites and their synapses in stressed mice. Therefore, we hypothesized that the increase in GMV in the basal ganglia, indicating the upregulation of functional dendrites and synapses, may be a compensatory alteration secondary to the dopamine depletion in this region in a special disease stage, and probably in the following years the volume would be decreased with the exhaustion of the ability to maintain the brain function. Of course, there are many studies demonsrtated that the smaller the gray matter volume is, the greater the damage is, and the worse the disease is. However, no correlation was found between the altered GMV and clinical features in rs11240572-A carriers. Inconsistencies in results may be due to differences in sample size, research group, and disease stage. In order to figure out the effect of group size on our correlation result, we reduced the sample size to the level of the carrier sample and still found the same correlations in the non-carrier group, which strengthen the speculation about a meaningful group difference between correlation findings of both groups.
Previous studies suggested that PD patients with mild cognitive impairment might suffer from atrophy of the temporal and parietal areas (Pereira et al., 2014; Zhang et al., 2018). In contrast, Binudo et al. (2013) demonstrated that mild cognitive impairment in PD was associated with significant regional thickening in the left temporal-occipital lobe and the thickening has been explained by compensatory neuroplasticity. The association between temporal GMV and cognition impairment in PD is therefore still controversial. Our study showed decreased GMV of both the left superior temporal gyrus and supramarginal gyrus was negatively associated with cognitive function in rs11240572-A non-carriers, which might indicate the compensatory neuroplasticity.
In addition, instead of bilaterally symmetrical GMV alterations, our study showed differences in the left basal ganglia and left temporoparietal cortex between the two groups of patients. Recently, Garrido et al. (2020) reported the left hemispheric predominance of nigrostriatal deficit in right-handed PD. Thus, it might be account of the fact that most of our subjects were right-handed or the limited sample size. Further studies will be needed to address the issues.
There were several limitations in the present study. First, because of the difficulty in acquiring genetic and imaging data from the same participants, the sample size recruited in the present study is relatively small. We subdivided the patients according to their genetic profiles, which may lead to the different group sizes. Due to the limited sample size, the results should be interpreted cautiously and larger studies are needed to validate and further our findings. Secondly, participants were only estimated by VBM, which can lack accuracy. Therefore a variety of neuroimaging approaches, such as functional MRI and quantitative susceptibility mapping, should be incorporated into future work to elucidate the genetic effect in PD. In spite of these limitations, our study provides novel clues for future efforts to explore the possible pathological mechanism underlying PARK16-related PD.