Abstract
Higher plasma cholesterol levels are associated with lower Parkinson’s disease (PD) risk. Apolipoprotein A-1 (ApoA-1) is a surface marker of brain HDL-like particles associated with the time of PD onset. Clinical correlates of serum Apolipoprotein A1 levels with structural brain connectivity in PD-related disorders remains unclear. Here, we applied a novel diffusion-weighted imaging approach [Diffusion Magnetic Resonance Imaging (MRI) Connectometry] to explore the association between ApoA-1 and structural brain connectivity in PD. Participants involved in this research were recruited from Parkinson’s Progression Markers Initiative (PPMI). Diffusion MRI connectometry was conducted using a multiple regression against apoA-1 for 36 patients with DTI measurements available in the baseline visit. Fiber results of the connectometry were then reconstructed for each patient, and diffusion parameters were extracted and regressed against apoA-1 levels. Connectometry results revealed the subgenual cingulum to be associated with ApoA-1, with different FDR yields. This result was further supported by significant negative correlation of Quantitative Anisotropic (QA) of left subgenual cingulum (Pearson’s coefficient = −0.398, p = 0.020) and Generalized Fractional Anisotropic (GFA) of right subgenual cingulum (Pearson’s coefficient −0.457, p = 0.007) with plasma apoA-1 levels, in a multiple regression model with age and sex. The subgenual cingulum encompasses fibers from the anterior cingulate cortex and anterior thalamus. These structures are involved in PD-associated psychosis and executive cognitive decline. We demonstrated for the first time that apoA-1, as a blood marker, can predict microstructural changes in white matter regions in PD patients with undisturbed cognition and mild motor disability.
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References
Hottman DA, Chernick D, Cheng S, Wang Z, Li L (2014) HDL and cognition in neurodegenerative disorders. Neurobiology of disease 72 Pt A:22–36. doi:10.1016/j.nbd.2014.07.015
Ikeda K, Nakamura Y, Kiyozuka T, Aoyagi J, Hirayama T, Nagata R, Ito H, Iwamoto K, Murata K, Yoshii Y, Kawabe K, Iwasaki Y (2011) Serological profiles of urate, paraoxonase-1, ferritin and lipid in Parkinson’s disease: changes linked to disease progression. Neuro-Degener Dis 8(4):252–258. doi:10.1159/000323265
Guo X, Song W, Chen K, Chen X, Zheng Z, Cao B, Huang R, Zhao B, Wu Y, Shang HF (2015) The serum lipid profile of Parkinson’s disease patients: a study from China. Int J Neurosci 125(11):838–844. doi:10.3109/00207454.2014.979288
Singh NK, Banerjee BD, Bala K, Mitrabasu, Dung Dung AA, Chhillar N (2014) APOE and LRPAP1 gene polymorphism and risk of Parkinson’s disease. Neurol Sci Off J Italian Neurol Soc Italian Soc Clin Neurophysiol 35(7):1075–1081. doi:10.1007/s10072-014-1651-6
Vitali C, Wellington CL, Calabresi L (2014) HDL and cholesterol handling in the brain. Cardiovasc Res 103(3):405–413. doi:10.1093/cvr/cvu148
Friedman B, Lahad A, Dresner Y, Vinker S (2013) Long-term statin use and the risk of Parkinson’s disease. Am J Manag Care 19(8):626–632
Huang X, Alonso A, Guo X, Umbach DM, Lichtenstein ML, Ballantyne CM, Mailman RB, Mosley TH, Chen H (2015) Statins, plasma cholesterol, and risk of Parkinson’s disease: a prospective study. Mov Dis Off J Mov Dis Soc 30(4):552–559. doi:10.1002/mds.26152
Du G, Lewis MM, Shaffer ML, Chen H, Yang QX, Mailman RB, Huang X (2012) Serum cholesterol and nigrostriatal R2* values in Parkinson’s disease. PLoS One 7(4):e35397. doi:10.1371/journal.pone.0035397
Swanson CR, Berlyand Y, Xie SX, Alcalay RN, Chahine LM, Chen-Plotkin AS (2015) Plasma apolipoprotein A1 associates with age at onset and motor severity in early Parkinson’s disease patients. Mov Disord Off J Mov Disord Soc 30(12):1648–1656. doi:10.1002/mds.26290
Qiang JK, Wong YC, Siderowf A, Hurtig HI, Xie SX, Lee VM, Trojanowski JQ, Yearout D, Leverenz JB, Montine TJ, Stern M, Mendick S, Jennings D, Zabetian C, Marek K, Chen-Plotkin AS (2013) Plasma apolipoprotein A1 as a biomarker for Parkinson disease. Ann Neurol 74(1):119–127. doi:10.1002/ana.23872
Marek K, Jennings D, Lasch S, Siderowf A, Tanner C, Simuni T, Coffey C, Kieburtz K, Flagg E, Chowdhury S (2011) The parkinson progression marker initiative (PPMI). Prog Neurobiol 95(4):629–635
Yeh FC, Badre D, Verstynen T (2015) Connectometry: a statistical approach harnessing the analytical potential of the local connectome. NeuroImage. doi:10.1016/j.neuroimage.2015.10.053
Jones DK, Christiansen KF, Chapman RJ, Aggleton JP (2013) Distinct subdivisions of the cingulum bundle revealed by diffusion MRI fibre tracking: implications for neuropsychological investigations. Neuropsychologia 51(1):67–78. doi:10.1016/j.neuropsychologia.2012.11.018
Martinez-Martin P, Rodriguez-Blazquez C, Mario A, Arakaki T, Arillo VC, Chana P, Fernandez W, Garretto N, Martinez-Castrillo JC, Rodriguez-Violante M, Serrano-Duenas M, Ballesteros D, Rojo-Abuin JM, Chaudhuri KR, Merello M (2015) Parkinson’s disease severity levels and MDS-Unified Parkinson’s Disease Rating Scale. Parkinsonism Relat Disord 21(1):50–54. doi:10.1016/j.parkreldis.2014.10.026
Li C, Huang B, Zhang R, Ma Q, Yang W, Wang L, Wang L, Xu Q, Feng J, Liu L, Zhang Y, Huang R (2016) Impaired topological architecture of brain structural networks in idiopathic Parkinson’s disease: a DTI study. Brain Imaging Behav. doi:10.1007/s11682-015-9501-6
Duncan GW, Firbank MJ, Yarnall AJ, Khoo TK, Brooks DJ, Barker RA, Burn DJ, O’Brien JT (2015) Gray and white matter imaging: A biomarker for cognitive impairment in early Parkinson’s disease? Mov Disord 31(1):103–110. doi:10.1002/mds.26312
Vergani F, Martino J, Morris C, Attems J, Ashkan K, Dell’Acqua F (2016) Anatomic connections of the subgenual cingulate region. Neurosurgery 79(3):465–472. doi:10.1227/neu.0000000000001315
Munhoz RP, Moro A, Silveira-Moriyama L, Teive HA (2015) Non-motor signs in Parkinson’s disease: a review. Arq Neuropsiquiatr 73(5):454–462. doi:10.1590/0004-282x20150029
Nigro S, Riccelli R, Passamonti L, Arabia G, Morelli M, Nistico R, Novellino F, Salsone M, Barbagallo G, Quattrone A (2016) Characterizing structural neural networks in de novo Parkinson disease patients using diffusion tensor imaging. Hum Brain Mapp 37(12):4500–4510. doi:10.1002/hbm.23324
Ansari M, Rahmani F, Dolatshahi M, Pooyan A, Aarabi MH (2016) Brain pathway differences between Parkinson’s disease patients with and without REM sleep behavior disorder. Sleep Breathing Schlaf Atmung. doi:10.1007/s11325-016-1435-8
Rahmani F, Ansari M, Pooyan A, Mirbagheri MM, Aarabi MH (eds) (2016) Differences in white matter microstructure between Parkinson's disease patients with and without REM sleep behavior disorder. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Starkstein SE, Brockman S, Hayhow BD (2012) Psychiatric syndromes in Parkinson’s disease. Curr Opin Psychiatry 25(6):468–472. doi:10.1097/YCO.0b013e3283577ed1
Huebl J, Brucke C, Merkl A, Bajbouj M, Schneider GH, Kuhn AA (2016) Processing of emotional stimuli is reflected by modulations of beta band activity in the subgenual anterior cingulate cortex in patients with treatment resistant depression. Soc Cogn Affect Neurosci 11(8):1290–1298. doi:10.1093/scan/nsw038
Keedwell PA, Doidge AN, Meyer M, Lawrence N, Lawrence AD, Jones DK (2016) Subgenual cingulum microstructure supports control of emotional conflict. Cereb Cortex (New York, NY: 1991) 26(6):2850–2862. doi:10.1093/cercor/bhw030
Fox MD, Buckner RL, White MP, Greicius MD, Pascual-Leone A (2012) Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate. Biol Psychiatry 72(7):595–603
Schoene-Bake JC, Parpaley Y, Weber B, Panksepp J, Hurwitz TA, Coenen VA (2010) Tractographic analysis of historical lesion surgery for depression. Neuropsychopharmacol Off Publ Am Coll Neuropsychopharmacol 35(13):2553–2563. doi:10.1038/npp.2010.132
Zheng Z, Shemmassian S, Wijekoon C, Kim W, Bookheimer SY, Pouratian N (2014) DTI correlates of distinct cognitive impairments in Parkinson’s disease. Hum Brain Mapp 35(4):1325–1333. doi:10.1002/hbm.22256
Gattellaro G, Minati L, Grisoli M, Mariani C, Carella F, Osio M, Ciceri E, Albanese A, Bruzzone M (2009) White matter involvement in idiopathic Parkinson disease: a diffusion tensor imaging study. Am J Neuroradiol 30(6):1222–1226
Kim HJ, Kim SJ, Kim HS, Choi CG, Kim N, Han S, Jang EH, Chung SJ, Lee CS (2013) Alterations of mean diffusivity in brain white matter and deep gray matter in Parkinson’s disease. Neurosci Lett 550:64–68. doi:10.1016/j.neulet.2013.06.050
Hall JM, Ehgoetz Martens KA, Walton CC, O’Callaghan C, Keller PE, Lewis SJ, Moustafa AA (2016) Diffusion alterations associated with Parkinson’s disease symptomatology: a review of the literature. Parkinsonism Relat Disord 33:12–26. doi:10.1016/j.parkreldis.2016.09.026
Galantucci S, Agosta F, Stefanova E, Basaia S, van den Heuvel MP, Stojkovic T, Canu E, Stankovic I, Spica V, Copetti M, Gagliardi D, Kostic VS, Filippi M (2016) Structural brain connectome and cognitive impairment in Parkinson disease. Radiology. doi: 10.1148/radiol.2016160274
Rossi ME, Ruottinen H, Saunamaki T, Elovaara I, Dastidar P (2014) Imaging brain iron and diffusion patterns: a follow-up study of Parkinson’s disease in the initial stages. Acad Radiol 21(1):64–71. doi:10.1016/j.acra.2013.09.018
Braak H, Del Tredici K, Rüb U, de Vos RA, Steur ENJ, Braak E (2003) Staging of brain pathology related to sporadic Parkinson’s disease. Neurobiol Aging 24(2):197–211
O’Callaghan C, Bertoux M, Hornberger M (2014) Beyond and below the cortex: the contribution of striatal dysfunction to cognition and behaviour in neurodegeneration. J Neurol Neurosurg Psychiatry 85(4):371–378. doi:10.1136/jnnp-2012-304558
Cooper M, Thapar A, Jones DK (2015) ADHD severity is associated with white matter microstructure in the subgenual cingulum. NeuroImage Clin 7:653–660. doi:10.1016/j.nicl.2015.02.012
Weingarten CP, Sundman MH, Hickey P, Chen NK (2015) Neuroimaging of Parkinson’s disease: expanding views. Neurosci Biobehav Rev 59:16–52. doi:10.1016/j.neubiorev.2015.09.007
Kovari E, Gold G, Herrmann FR, Canuto A, Hof PR, Bouras C, Giannakopoulos P (2003) Lewy body densities in the entorhinal and anterior cingulate cortex predict cognitive deficits in Parkinson’s disease. Acta Neuropathol 106(1):83–88. doi:10.1007/s00401-003-0705-2
Zhang J, Zhang YT, Hu WD, Li L, Liu GY, Bai YP (2015) Gray matter atrophy in patients with Parkinson’s disease and those with mild cognitive impairment: a voxel-based morphometry study. Int J Clin Exp Med 8(9):15383–15392
Lucas-Jiménez O, Díez-Cirard M, Ojeda N, Peña J, Cabrera-Zubizarreta A, Ibarretxe-Bilbao N (2015) Verbal memory in Parkinson’s disease: a combined DTI and fMRI study. J Parkinson’s Dis 5(4):793–804. doi:10.3233/JPD-150623
Mole JP, Subramanian L, Bracht T, Morris H, Metzler-Baddeley C, Linden DE (2016) Increased fractional anisotropy in the motor tracts of Parkinson’s disease suggests compensatory neuroplasticity or selective neurodegeneration. Eur Radiol. doi:10.1007/s00330-015-4178-1
Wen MC, Heng HS, Ng SY, Tan LC, Chan LL, Tan EK (2016) White matter microstructural characteristics in newly diagnosed Parkinson’s disease: an unbiased whole-brain study. Sci Rep 6:35601. doi:10.1038/srep35601
Bezard E, Gross CE, Brotchie JM (2003) Presymptomatic compensation in Parkinson’s disease is not dopamine-mediated. Trends Neurosci 26(4):215–221. doi:10.1016/s0166-2236(03)00038-9
Yeh FC, Badre D, Verstynen T (2016) Connectometry: a statistical approach harnessing the analytical potential of the local connectome. NeuroImage 125:162–171. doi:10.1016/j.neuroimage.2015.10.053
Yeh F-C, Verstynen TD, Wang Y, Fernández-Miranda JC, Tseng W-YI (2013) Deterministic diffusion fiber tracking improved by quantitative anisotropy. PLoS One 8(11):e80713. doi:10.1371/journal.pone.0080713
Acknowledgements
This work was funded by Grants from the Michael J Fox Foundation for Parkinson’s Research, the W Garfield Weston Foundation, and the Alzheimer’s Association, the Canadian Institutes for Health Research, and the Natural Sciences and Engineering Research Council of Canada. We thank Christian Beckmann and Simon Eickhoff for their advice on data analysis. Data used in this article were obtained from the Parkinsons Progression Markers Initiative (PPMI) database (http://www.ppmi-info.org/data). For up-to-date information on the study, visit http://www.ppmi-info.org. PPMI is sponsored and partially funded by the Michael J Fox Foundation for Parkinsons Research and funding partners, including AbbVie, Avid Radiopharmaceuticals, Biogen, Bristol-Myers Squibb, Covance, GE Healthcare, Genentech, GlaxoSmithKline (GSK), Eli Lilly and Company, Lundbeck, Merck, Meso Scale Discovery (MSD), Pfizer, Piramal Imaging, Roche, Servier, and UCB (http://www.ppmi-info.org/fundingpartners).
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Rahmani, F., Aarabi, M.H. Does apolipoprotein A1 predict microstructural changes in subgenual cingulum in early Parkinson?. J Neurol 264, 684–693 (2017). https://doi.org/10.1007/s00415-017-8403-5
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DOI: https://doi.org/10.1007/s00415-017-8403-5