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Genetic epidemiology and functional study of LRRK2 gene in the pathogenesis of Parkinson’s Disease by using Drosophila as a model system
No full text研究背景及目的
巴金森氏症(巴病)為一重要的神經退化性疾病，截至西元2010年為止，已有11個基因的突變是引起少數遺傳性巴病的致病因。其中，LRRK2 (Leucine-rich repat kinase)是引起顯性遺傳以及老年型巴病病患最重要的ㄧ個基因。LRRK2主要分布在細胞質中，具有5個重要的功能區塊，包括ankyrin、LRR （Leucine-rich repeat）、ROC（Ras of complex protein）、COR（C-terminal of Ras）、kinase 以及WD40等區塊。過去在白種人的研究中發現，LRRK2基因上的G2019S為巴病病患的突變熱點，若是帶有此ㄧ突變，幾乎都會罹患此病症(penetrance >95%)。G2019S位點座落在LRRK2 kinase 區塊上，過去許多研究已經證實G2019S會導致LRRK2 蛋白的激脢活性增加，因此導致帶G2019S突變的神經細胞比帶正常LRRK2的神經細胞提早死亡。相對而言，在亞洲人的研究中卻都沒有發現這些突變﹔相反的，我們在exon48上發現了會顯著增加亞洲人罹病危險性的變異點- G2385R。雖然目前為止對於LRRK2基因在不同種族的變異分析的臨床研究甚多，但是LRRK2基因在神經細胞中究竟扮演何種功能以及其確切的致病機轉目前尚未被證實。因此，本研究欲探討LRRK2基因突變對神經細胞所產生的功能性變化，同時建立基因轉植果蠅動物模式，以了解LRRK2基因突變對於神經細胞的影響。
研究材料與方法
本研究分兩階段進行：第一階段為探討在台灣人遺傳性巴病患者中LRRK2
基因突變之基因流行病學研究，本研究由台大醫院巴金森氏症暨動作障礙中心中的病患基因檢體庫中，研究台灣漢人巴金森症患者LRRK2基因突變的流行病學；第二階段則以果蠅 (Drosophila melanogaster)為動物模式，以基因轉植(transgenic)的方式，分別建立野生型與突變型的基因轉植果蠅，以比較突變型的果蠅表現型(phenotype)的變化以及LRRK2蛋白其在果蠅神經細胞中的表現是否有改變，以及是否會影響神經細胞的存活，同時進一部探討LRRK2導致神經細胞死亡的分子機轉。
研究結果
在第一階段的臨床研究中，我們初步篩檢了27位遺傳性巴病病患，其中只有1位是R1441H基因突變(3.7%)，而有6位是G2385R基因變異者(22.2%)。此外，為了進一步探討這些基因變異的功能性意義，我們利用EB virus transform LRRK2
變病患以及帶有G2385R病患的白血球細胞株進行進ㄧ步的in vitro實驗，我們發現，對於低濃度MG-132毒物處理，帶有R1441H的細胞株比起同年齡的對照組細胞株而言有顯著增加的細胞凋亡率以及細胞內氧化自由基的累積﹔但是帶有G2385R的細胞株則需接觸到高濃度的MG-132才會產生細胞毒性。我們因此在第二階段的基礎研究中建立in vivo的基因轉殖果蠅模式，我們發現LRRK2 G2019S 以及R1441C會顯著的導致果蠅周邊神經以及多巴胺神經細胞的樹突退化萎縮(特別是G2019S)，而這種導致樹突萎縮的作用取決於LRRK2 kinase activity的大小，接下來我們以果蠅周邊神經樹突分支神經系(dendritic arborization neurons)為模式，我們發現LRRK2 G2019S之所以會導致神經樹突退化萎縮的其中之一的機轉為藉由調控Glycogen Synthase Kinase 3 beta (GSK3β)而增加 phospho-tau (T212 of tau)的產生，並將之由軸突不正常的運送到樹突，因而導致樹突中microtubule的不穩定及崩解。我們在LRRK2果蠅模式中觀察到的現象進一步驗證了在LRRK2病人死後腦組織切片中發現的大量tau蛋白沉積，並且重現了多巴胺神經細胞隨著老化而死亡的病理特徵。
結論
本研究延續過去台大醫院巴金森氏症暨動作障礙中心過去幾年來所進行的巴金森氏症之基因流行病學研究，使我們對於台灣漢人巴金森氏症之常見基因變異、基因型與表現型之關連性、以及其致病機制，有了基本的了解。本研究同時也證實了LRRK2果蠅模式可以重現許多重要的疾病病理特徵，此現象增加了運用LRRK2果蠅模式來治療巴金森氏症的可能性。Background
Parkinson’s disease (PD) is one of the most common neurodegenerative disorders,
with a prevalence close to 1% after age 65. Causal genes for Mendelian-inherited PD
have been reported. The recent discovery of LRRK2 (Leucine-rich repeat kianse 2) as a causative PD gene has provided insights into the pathophysiology of the disease. Because the clinical phenotype of LRRK2 mutations resembles idiopathic PD, LRRK2 has emerged as the most relevant player in PD pathogenesis identified to date. Many LRRK2 gene mutations have been reported. The G2019S mutation is the hot spot mutation in Caucasians and the G2385R polymorphism is reported to be a genetic risk factor in Easten populations. Mutant Lrrk2 carrying human dominant mutations has enhanced kinase activity, resulting in cell toxicity and neurite shrinkage. Knock-down or ablation of LRRK2 in mammalian cultured neurons promotes neurite outgrowth through actin cytoskeletal rearrangment. However, the information regarding the LRRK2 mutation in the Asian population is rare and the functional relevance of these mutations (such as G2019S) or risk variant (G2385R) are unclear. In addition, very recently, aother gene for early onset-PD (PARK9/ATP13A2) was identified. The phenotype of affected individuals is juvenile onset of PD and may combine the phenotypes of dementia and pyramidal degeneration. The ATP13A2 protein is assumed to be the neuronal P-type ATPase and the intracellylar location is primarily in the lysosome. The mechanism by which loss of ATP13A2 causes parkinsonism and the possible function is unclear. To date there have been few studies examining the frequency of ATP13A2 mutations in parkinsonism, nor in different populations. The data in Asian populations are lack.
Purpose
We propose this research proposal with the following aims to evaluate the the frequency and functional significance of LRRK2 and ATP13A2 mutations in patients with PD in Taiwanese.
1. To determine the frequency of mutations of the ATP13A2 gene in PD patients of Taiwanese.
2. To determine the frequency of mutations of the LRRK2 gene in PD patients of Taiwanese.
3. To elucidate the functional relevance of LRRK2 genetic substitutions using lymphoblastoid cell lines derived from patients with LRRK2 substitutions.
4. Employing Drosophila da neurons as a model system, we aim to characterize the role of LRRK2 mutations in Drosophila dendrite morphogenesis by creating transgenic Drosophila models.
Materials and methods
We recruit more than 500 PD patients and control subjects to evaluate the frequency of ATP13A2 and LRRK2 mutations in Taiwanese populations using the method of direct sequencing in the first set of the study. In the second part, we use EBV transformed lymphoblastoid cell lines derived from patients carring LRRK2 mutations to elucidate the possible molecular functional changes. We also create transgenic Drosophila models carrying wild type LRRK2, G2019S, R1441C and G2385R to elucidate the molecular effects of these LRRK2 mutatuins in the in vivo model system.
Results
We identified one novel missense variant, Ala746Thr, in a single heterozygous state
in three patients (1.7% in EOPD). The variant was not observed in 589 ethnicity matched controls. The frequency of this variant was significantly higher in PD cases than controls (p=0.01, relative risk 4.3, 95%CI 1.9-4.3). The clinical phenotype and 18F-dopa PET image of ATP13A2 Ala78Thr carriers are similar to that seen in idiopathic PD. The variant is located between the highly conserved phosphorylation region and the 5th transmembrane domain of the ATP13A2 protein. We also found the frequencies of R1441H and G2385R in familial PD patients were 3.7% and 22.2%, respectively. The clinical phenotypes and [18F]-dopa PET findings for subjects with R1441H or G2385R resembled those of patients with idiopathic PD; however, their lymphoblastoid cell lines showed increased apoptosis following exposure to a proteosome inhibitor. Thus, LRRK2 mutations are rare in Taiwanese with familial PD.
By using Drosophila as a model system, we found that expression of G2019S mutant
in Drosophila dendritic arborization neurons induces mislocalization of the axonal protein tau in dendrites and causes dendrite degeneration. G2019S-induced dendrite degeneration is suppressed by reducing the level of tau protein and aggravated by tau coexpression. Further genetic analyses suggest that G2019S and Tau function synergistically to cause microtubule fragmentation, inclusion formation and dendrite degeneration. Mechanistically, hyperactivated G2019S promotes tau phosphorylation at the T212 site by the Drosophila GSK3β homolog Shaggy (Sgg). G2019S increases the recruitment of autoactivated Sgg, thus inducing hyperphosphorylation and mislocalization of tau with resultant dendrite degeneration.
Conclusions
Our study not only provides a genetic epidemiology information regarding the muattaion frequency of ATP13A2 and LRRK2 in Taiwnaese PD patients but also provide a molecular and cellular mechanism in understanding the regulation of neurite degeneration by LRRK2. Our restuls will be stretched to understand the pathomechanism of LRRK2-linked PD and the transgenic LRRK2 Drosophila model could be a plateform for further drug screening
Design of Cost Efficient FEQ for IEEE802.16a OFDM System
No full text在這個論文中，提出一些應用於IEEE802.16a 正交分頻多工調變系統的設計，像是低功率的頻域等化器，利用DC次載波偵測去找到整數倍載波飄移和通道內插的分析。
低功率頻域等化器是根據strength-reduced 複數乘法器的觀念去設計，讓整個硬體上的需求降低，提出的低功率等化器比傳統的架構節省了將近19%的運算量。由於在作通道估計時需要用到ROM去儲存已知的前置碼，為了降低硬體成本，一個藉由控制MUX 來取代大量ROM 的方法被應用在系統。除此之外，選擇single port RAM 代替dual ports RAM來存取在LMS adaptation會被讀寫的訊號，並且利用合併的技巧，將兩個獨立的RAM合成一塊，使控制訊號只要一組就足夠。使用以上技巧，在ROM方面：面積可以省70%，而在功率消耗量上可節省53%。就RAM 而言，面積省20%，功率消耗量節省18.4%。
整數倍載波飄移的設計，用DC次載波找飄移量比傳統用matched-filter 來找，就硬體成本而言節省了88.6%，功率消耗量方面省了85%。
在802.16a 正交分頻多工調變系統，由於通道估計只能在偶數次載波上通道資訊，在奇數次載波就必須利用已知的通道去作內插估計。越複雜的內插方法雖然會有比較好的精準度，但所需實現的硬體需求也相對較高。在此論文中，針對MSE 對Linear 與Piecewise-Parabolic 內插提出一套完整的分析，根據分析、模擬結果與系統的考量，最後選擇Linear 內插來作奇數次載波上通道的估測。最後有對低功率頻域等化器作c code 浮點數symbol error rate 的模擬，由分析可看出這樣的設計符合系統的要求。In this thesis, the design of IEEE 802.16a OFDM-based WiMAX systems is presented. The system design includes the cost efficient FEQ, dc-tone power detection integer CFO estimation, channel interpolation analysis and the CFO tracking loop.
According to strength-reduced complex-value multiplier, the cost efficient FEQ is proposed to decrease the hardware cost. The hardware cost of proposed FEQ is reduced 19% compared with the conventional FEQ. On the other hand, in order to reduce the ROM size in the channel estimation to store the preamble data, the control-MUX method is proposed. In addition, considering the storage
of the channel coefficient and decision error in the LMS adaptation, the single port RAM is selected to decrease the RAM size requirements. Furthermore, combing the two RAM blocks, channel coefficient RAM and decision error RAM, to a single RAM is applied to the cost efficient FEQ design. Consequently, the total size for
the ROM and RAM can be reduced by 70% and 20% respectively.
Besides, the power consumption is also saved by 53% and 18.4% individually.
Considering integer CFO estimation, the dc-tone power detection in the frequency-domain is proposed to achieve the low-computing estimation. Therefore, the approach can save 85% power and 88.6% hardware cost compared with the matched-filter based integer CFO estimation.
The channel interpolation is necessary in WiMAX systems to obtain the channel information on the odd tones since the preamble only provide the even tones information. Although the complicated interpolation method, Raised-Cosine interpolation, can minimize the estimation error, the method results in the higher hardware cost simultaneously. Therefore, in order to acquire the best trade-off between performance and hardware cost, the estimation error of the
Linear and Piecewise-Parabolic channel is analyzed based on the MSE criterion. According to the analysis results, the Linear and Piecewise-Parabolic interpolation satisfy to system requirement. From the hardware cost point of view, the Linear channel interpolation is adopted for the cost efficient FEQ. Finally, the floating and fixed point SER simulations are presented to meet the system requirements.1 Introduction 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3 Thesis Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2 Wireless MAN System and Background Knowledge 7
2.1 Wireless MAN Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.2 OFDM Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.2.1 OFDM Signal Modeling . . . . . . . . . . . . . . . . . . . . . . . 9
2.2.2 Guard Interval and Cyclic Pre . . . . . . . . . . . . . . . . . . 13
2.3 IEEE 802.16 Standard and Specications for OFDM Mode . . . . . . . . 13
2.3.1 Main Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.3.2 Preamble Format . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.3.3 Structure of the down-link frame . . . . . . . . . . . . . . . . . . 17
2.3.4 Adaptive Modulation and Forward Error Correction . . . . . . . . 18
2.3.5 Pilot Modulation . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3 OFDM System and Wireless Channel Model 21
3.1 OFDM System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3.2 Wireless Channel Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2.1 Path Loss(PL) and Shadowing . . . . . . . . . . . . . . . . . . . . 23
3.2.2 Multipath Fading . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3.2.3 Power Amplier Nonlinearity . . . . . . . . . . . . . . . . . . . . 25
3.2.4 Power Delay Prole (PDP) . . . . . . . . . . . . . . . . . . . . . . 25
3.2.5 Time Dispersion . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3.2.6 Coherence Bandwidth . . . . . . . . . . . . . . . . . . . . . . . . 28
3.2.7 Doppler Shift . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.2.8 Coherence Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.2.9 Rayleigh Fading and Ricean Fading . . . . . . . . . . . . . . . . . 30
3.2.10 Channel Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
4 Synchronization Techniques in OFDM Systems 33
4.1 Symbol Boundary O set . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
4.1.1 Delay Correlator (Coarse Symbol Boundary Detection) . . . . . . 35
4.1.2 Matched Filter (Fine Symbol Boundary Detection) . . . . . . . . 36
4.2 Carrier Frequency O set . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
4.2.1 Fractional CFO Estimation (Correlator) . . . . . . . . . . . . . . 38
4.2.2 Integer CFO Estimation . . . . . . . . . . . . . . . . . . . . . . . 39
4.2.3 CFO Tracking Loop . . . . . . . . . . . . . . . . . . . . . . . . . 45
5 Equalization 51
5.1 Channel E ects in Time Domain and Frequency Domain . . . . . . . . . 51
5.2 Equalization of the OFDM system . . . . . . . . . . . . . . . . . . . . . . 52
5.2.1 Channel Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . 53
5.2.2 Interpolation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
5.2.3 Interpolation Analysis . . . . . . . . . . . . . . . . . . . . . . . . 56
5.2.4 Adaptive . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
6 FEQ Design 71
6.1 Conventional FEQ and Cost E cient FEQ . . . . . . . . . . . . . . . . . 72
6.1.1 Filtering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
6.1.2 Updating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
6.1.3 Channel Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . 75
6.1.4 Comparisons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
6.2 Hardware Design for Cost E cient FEQ . . . . . . . . . . . . . . . . . . 80
6.2.1 Simulation for Signal Word length . . . . . . . . . . . . . . . . . . 80
6.2.2 Channel Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . 84
6.2.3 Slicer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
6.2.4 Updating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
6.3 FPGA Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
7 MISO 99
7.1 Transmitter Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
7.2 Channel Estimation for MISO system . . . . . . . . . . . . . . . . . . . . 100
8 Conclusion 103
Bibliography 10
Lack of evidence for association of a parkin promoter polymorphism with early-onset Parkinson’s disease in a Chinese population
No full text
Feeling-of-Knowing in Episodic Memory in Patients with Parkinson's Disease with Various Motor Symptoms
No full textMinimal Detectable Change of the Timed “Up & Go” Test and the Dynamic Gait Index in People With Parkinson Disease
No full text
Novel variant Pro143Ala in HTRA2 contributes to Parkinson’s disease by inducing hyperphosphorylation of HTRA2 protein in mitochondria
No full text- …
