The Association Between Structural Brain Connectivity With Plasma APO-A1 Levels In Parkinson Disease: Connectometry Approach
Farzaneh Rahmani1 and MohammadHadi Aarabi1

1Students'Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran

Synopsis

The basis of Parkinson disease (PD) pathology is accumulation of α-synuclein particles (Lewy bodies) in the presynaptic terminal and perikaria of neocortex, cerebellum, thalamus and SN.

Features of the lipid profile specially cholesterol levels are association with PD risk. However no such data exists on the association of these plasma markers with structural brain changes in PD. The primary site of PD pathology is the nigrostriatal tract which then progresses to the cingulium. The nigrostriatal tract is extensively damaged prior to PD onset. Lower plasma levels of apoA-I is associated with earlier onset of PD and greater putaminal DAT deficit and a more rapid motor decline in PD . However apoA-I levels have never been investigated regarding changes in structural brain connectivity. The our results show that apoA-I levels in drug_naïve patients are associated with structural changes in the even prior to pathologic involvement of cingulium.


Introduction

Features of the lipid profile specially cholesterol levels are association with PD risk. However no such data exists on the association of these plasma markers with structural brain changes in PD. The primary site of PD pathology is the nigrostriatal tract which then progresses to the cingulium. The nigrostriatal tract is extensively damaged prior to PD onset. Lower plasma levels of apoA-I is associated with earlier onset of PD and greater putaminal DAT deficit and a more rapid motor decline in PD [1,2] . However apoA-I levels have never been investigated regarding changes in structural brain connectivity. Here we applied the connectometry framework to analyses structural connectivity in drug-naïve PD patients using a multiple regression model considering cholesterol, non-HDL cholesterol, apoA_I, EGF, LDL, HDL, Age, and Sex and using False Discovery Rate to evaluation our finding.

Methods

We included 39 PPMI subjects Mean age=63.8±8.4) and 23 healthy age-sex matched controls Mean age=63±9) for whom plasma samples and diffusion imaging were available from the baseline visit. Data used in the preparation of this paper was obtained from Parkinson's Progression Markers Initiative (PPMI) database (www.ppmi-info.org/data/) [3]. This dataset was acquired on a 3 Tesla Siemens scanner, producing 64 DWI (repetition time = 7748 ms, echo time = 86 ms; voxel size: 2.0×2.0×2.0 mm3. Plasma levels of apoA-I and a basic lipid panel (comprised of HDL, LDL, total cholesterol, and triglycerides) were measured using a Roche Cobas c501 automated biochemical analyzer (Tina-quant assay, catalog number 03032566-122).The diffusion data were reconstructed in the MNI space using qspace diffeomorphic reconstruction to obtain the spin distribution function by DSI-Studio[4]. A diffusion sampling length ratio of 1.25 was used, and the output resolution was 2 mm . Diffusion MRI connectometry was conducted in a total of 39 subjects using a multiple regression model considering Cholesterol,Non.HDL, apoA-I, EGF, LDL, HDL, Age, and Sex. A percentage threshold of 50 %, 100 % and 200 % were used to select local connectomes correlated with Plasma factors. A deterministic fiber tracking algorithm was conducted to connect the selected local connectomes. A length threshold of 52 mm were used to select tracks. The seeding density was 20 seeds per mm3. To estimate the false discovery rate, a total of 1000, 2000 and 4000 randomized permutations were applied to the group label to obtain the null distribution of the track length.

Result

The analysis showed a significant negative correlation (FDR= 0.04) between Apo_AI of PD (Table 1) and another factors have no association with structural brain network and connectivity in two fiber pathways: 1) Cingulium, 2) Corticospinal Tracts (CST). Also Table 2 shows there is no association between Plasma factors, age and sex in normal cases. Figure 2 shows the significant pathway which areassociated with Apo_A.

Conclusion

The cingulate gyrus is both functionally and structurally disturbed in PD, as a functional part of the limbic system. The cingulate is critical to emotion formation and autonomic function; while playing a key role in response initiation, planning memory, predominant executive dysfunction [5] and visuospatial skills, which are all impaired in early stages of PD [6]. In our study we found that lower quantitative anisotropy in posterior cingulium might be associated with higher plasma level of apoA-I in drug-naïve PD patients (Figure 1). Moreover higher levels of apoA-I might also negatively associated with anisotropy in some areas of midbrain, probably the initial portions of the nigrostriatal fibers, which are considered the primary site of Lewy body pathology in PD (Figure 1). These pathological changes spread to the dorsal vagal nucleus and anterior olfactory nucleus and then involve the limbic system and cinguliumat stage 5 of pathological changes and finally reach the neocortex [7]. Nearly half of the dopaminergic neurons of the nigrostriatal pathway are lost before initiation of PD symptoms [8], however a direct measuring of the pathological progression of the disease is not yet feasible [9].

Acknowledgements

PPMI – a public-private partnership – is funded by the Michael J. Fox Foundation for Parkinson’s Research and funding partners, including [list the full names of all of the PPMI funding partners found at www.ppmi-info.org/fundingpartners. The authors thank Dr.Pasalar for her kindly support of this work.

References

[1] C. R. Swanson, Y. Berlyand, S. X. Xie, R. N. Alcalay, L. M. Chahine, and A. S. Chen-Plotkin, "Plasma apolipoprotein A1 associates with age at onset and motor severity in early Parkinson's disease patients," Mov Disord, vol. 30, pp. 1648-56, Oct 2015.

[2] J. K. Qiang, Y. C. Wong, A. Siderowf, H. I. Hurtig, S. X. Xie, V. M. Lee, et al., "Plasma apolipoprotein A1 as a biomarker for Parkinson disease," Ann Neurol, vol. 74, pp. 119-27, Jul 2013.

[3] "The Parkinson Progression Marker Initiative (PPMI)," Prog Neurobiol, vol. 95, pp. 629-35, Dec 2011. [4] F. C. Yeh, D. Badre, and T. Verstynen, "Connectometry: A statistical approach harnessing the analytical potentialof the local connectome," Neuroimage, Oct 21 2015.

[5] G. Gattellaro, L. Minati, M. Grisoli, C. Mariani, F.Carella, M. Osio, et al., "White matter involvement inidiopathic Parkinson disease: a diffusion tensor imagingstudy," American Journal of Neuroradiology, vol. 30, pp.1222-1226, 2009.

[6] G. W. Duncan, M. J. Firbank, A. J. Yarnall, T. K. Khoo,D. J. Brooks, R. A. Barker, et al., "Gray and white matterimaging: A biomarker for cognitive impairment in earlyParkinson's disease?," Movement Disorders, 2015.

[7] H. Braak and K. Del Tredici, "Invited Article: Nervoussystem pathology in sporadic Parkinson disease,"Neurology, vol. 70, pp. 1916-1925, 2008.

[8] K. Yoshikawa, Y. Nakata, K. Yamada, and M. Nakagawa,"Early pathological changes in the parkinsonian braindemonstrated by diffusion tensor MRI," Journal ofNeurology, Neurosurgery & Psychiatry, vol. 75, pp. 481484,2004.

[9] M. M. Mielke and W. Maetzler, "A'bird's eye'view on thecurrent status and potential benefits of blood biomarkersfor Parkinson's disease," Biomarkers in medicine, vol. 8,p. 225, 2014.

Figures

Table 1

Table 2

Figure 1



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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