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A Mendelian Randomization Study Zhifa Han1†, Rui Tian1†, Peng Ren1, Wenyang Zhou1, Pingping Wang1, Meng Luo1, Shuilin Jin2* and Qinghua Jiang1*

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A Mendelian Randomization Study Zhifa Han1†, Rui Tian1†, Peng Ren1, Wenyang Zhou1, Pingping Wang1, Meng Luo1, Shuilin Jin2* and Qinghua Jiang1* Han et al. BMC Medical Genetics 2018, 19(Suppl 1):0 https://doi.org/10.1186/s12881-018-0721-7 RESEARCH Open Access Parkinson’s disease and Alzheimer’s disease: a Mendelian randomization study Zhifa Han1†, Rui Tian1†, Peng Ren1, Wenyang Zhou1, Pingping Wang1, Meng Luo1, Shuilin Jin2* and Qinghua Jiang1* From 29th International Conference on Genome Informatics Yunnan, China. 3-5 December 2018 Abstract Background: Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the top two common neurodegenerative diseases in elderly. Recent studies found the α-synuclein have a key role in AD. Although many clinical and pathological features between AD and PD are shared, the genetic association between them remains unclear, especially whether α-synuclein in PD genetically alters AD risk. Results: We did not obtain any significant result (OR = 0.918, 95% CI: 0.782–1.076, P = 0.291) in MR analysis between PD and AD risk. In MR between α-synuclein in PD with AD risk, we only extracted rs356182 as the IV through a strict screening process. The result indicated a significant association based on IVW method (OR = 0. 638, 95% CI: 0.485–0.838, P = 1.20E-03). In order to examine the robustness of the IVW method, we used other three complementary analytical methods and also obtained consistent results. Conclusion: The overall PD genetic risk factors did not predict AD risk, but the α-synuclein susceptibility genetic variants in PD reduce the AD risk. We believe that our findings may help to understand the association between them, which may be useful for future genetic studies for both diseases. Keywords: Alzheimer’s disease, Parkinson’sdisease,α-synuclein, Mendelian randomization, Genetic association Background progressive degeneration of dopaminergic neurons in Alzheimer’s disease (AD) and Parkinson’s disease (PD) the substantia nigra and the presence of Lewy bodies, are the top two common neurodegenerative diseases [1]. which are made of abnormal filaments composed of In 2015, AD and PD respectively affected about 29.8 α-synuclein [7, 8]. million and 6.2 million people worldwide [2]. AD is The two neurodegenerative diseases share many clin- characterized by a progressive decline in memory, lan- ical and pathological features. Because of the toxicity of guage, problem solving and other cognitive functions the α-synuclein or Aβ42 and tau proteins, so many simi- [3]. The neuropathological changes of AD are mainly lar cascades of neuronal reactions leading to progressive manifested as brain atrophy and the accumulation of neurodegeneration occur in PD and AD patients. The abundant extracellular Aβ plaques and intraneuronal overlapping pathological changes of AD and PD include neurofibrillary tau tangles [4, 5]. The patients suffering activation of glycogen synthase kinase-3 beta, mitogen- from PD show slow movements, tremor, gait and activated protein kinases, cell cycle reentry and oxidative balance disturbances and other behavioral problems [6]. stress, etc. [9]. As we all know, mild cognitive impair- The main pathological characteristics of PD are the ment (MCI) is associated with the risk of progression to AD. However, MCI was recently also recognized as a * Correspondence: [email protected]; [email protected] kind of subtype predicting progression to PD [10, 11]. †Zhifa Han and Rui Tian contributed equally to this work. About 25% of non-demented patients with PD meet 2 Department of Mathematics, Harbin Institute of Technology, Harbin, China neuropsychological test criteria for MCI [12]and 1School of Life Science and Technology, Harbin Institute of Technology, Harbin, China more than 50% of them eventually develop dementia [11]. © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Han et al. BMC Medical Genetics 2018, 19(Suppl 1):0 Page 2 of 31 All of these suggest that the two neurodegenerative dis- These genetic variants are largely not associated with eases are probably the risk factor of each other. confounders and can be used as IVs to estimate the In addition to the similarities between AD and PD, causal association of exposures (PD, α-synuclein in PD) some potential mechanisms linking these two neurode- with an outcome (AD) [18, 19]. The MR is based on generative diseases were found recently, especially the three principal assumptions (Fig. 1), which have been α-synuclein and Lewy pathology in AD. Several studies widely described in recent studies [18, 19]. First, the found that up to 50% AD patients exhibited extra aggre- genetic variants selected to be IVs should be associated gation of α-synuclein into Lewy bodies [13, 14]. Statistic with the exposures (PD, α-synuclein in PD) (assumption 1 test did not identify any significant difference of in Fig. 1) 20,22. Second, the genetic variants should not be α-synuclein levels in cerebrospinal fluid between AD associated with confounders (assumption 2 in Fig. 1)[18, and PD patients [15]. In transgenic mice, the accumula- 19]. Third, genetic variants should affect the risk of the tion of α-synuclein could significantly disrupt cognition outcome (AD) only through the exposure (PD or [14]. A similar study found that the α-synuclein in the α-synuclein in PD) (assumption 3 in Fig. 1) 20,22.The transgenic mice could also massive increase apolipopro- second and third assumptions are collectively known tein E (ApoE) levels and accelerate the accumulation of as independence from pleiotropy [18, 19]. This study insoluble mouse Aβ [16]. Furthermore, the cerebrospinal is based on the publicly available, large-scale GWAS fluid total α-synuclein levels contributed to the differen- summary datasets, and the genetic variants are SNPs. tial diagnosis of AD versus other dementias [17]. In the All participants gave informed consent in all these familial AD patients with presenilin 1 (PSEN1) mutations, corresponding original studies. which is most commonly associated with familial forms of AD, the notable interaction between α-synuclein and PD GWAS dataset PSEN1 was identified in post-mortem brain tissue [9]. Our Here, we first used PD susceptibility SNPs as the IVs previously study conducted an interaction network using that from the most large-scale PD GWAS dataset [20]. genome-wide association studies (GWASs) data and found This GWAS included 428,235 individuals (26,035 PD the significant interaction among AD and PD susceptibility cases and 403,190 controls) consisting of 416,518 indi- genes [7]. All of these evidences suggest a further investiga- viduals in discovery stage and 21,679 individuals in repli- tion for the potential genetic mechanisms linking PD to cation stage [20]. The final joint analysis identified 17 AD, particularly the role that the α-synuclein plays in AD. novel loci associated with PD with the genome-wide sig- In recent years, large-scale GWAS identified some nificance (P < 5.00E-08) [20]. We extracted lead SNPs in- common genetic variants and provided insights into the formation of each locus from the joint analysis results genetics of AD and PD, including α-synuclein coding except rs601999, which did not provide sufficient data. gene Synuclein Alpha (SNCA) 18,19. The large-scale We also obtained 27 genome-wide significant loci from GWAS datasets provide tremendous support for investi- other more earlier GWASs23,24. But the basic lead SNPs gating the potential genetic association between PD and information of these 27 loci were extracted from the dis- AD risk by Mendelian randomization analytical method covery stage of the most large-scale GWAS [19]. All (MR). MR is conceptually similar to randomized con- these 43 lead SNPs were independent [20]. trolled trials (RCT) and can be applied to investigate the causality of biomarkers in disease etiology based on Reported SNCA mutations in PD GWAS summary data20,21. In our study, we conducted a We acquired the PD susceptibility SNCA lead SNPs MR analysis with the lead single nucleotide polymor- through a rigorous screening process. We first searched phisms (lead SNPs, which showed the strongest associ- all previous GWASs which reported SNCA as a PD sus- ation in GWAS) from PD susceptibility loci. Here, these ceptibility locus. Afterwards, we obtained the lead SNPs lead SNPs defined as instrumental variable (IV). In the from each GWAS. However, we would exclude the lead results of sensitivity analysis of the MR between PD and SNP when they were not reported by GWAS of European AD risk, we found that the absence of SNCA lead SNP ethnicity. When a lead SNP is reported by more than one would massive decrease the statistical significance. Con- GWAS, we would extract the summary statistics from the sidering the reported role of α-synuclein in AD path- most large-scale GWAS because of its greater statistic ology, we further performed a MR to investigate the power. When several lead SNPs were in linkage disequilib- genetic association of the α-synuclein and AD risk. rium (LD), we would choose the one from the most large-scale GWAS. We searched the LD information by Materials and methods using the HaploReg v4.1, which based on LD data from Study design 1000 Genomes Project (CEU) [21]. MR is based on the premise that the human genetic var- Finally, we only selected one lead SNP from 7 undupli- iants are randomly distributed in the population [18, 19]. cated lead SNPs.
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