Characterization of DCTN1 genetic variability in neurodegeneration

Objective: Recently, mutations in DCTN1 were found to cause Perry syndrome, a parkinsonian disorder with TDP-43-positive pathology. Previously, mutations in DCTN1 were identified in a family with lower motor neuron disease, in amyotrophic lateral sclerosis (ALS), and in a family with ALS/frontotemporal dementia (FTD), suggesting a central role for DCTN1 in neurodegeneration. Methods: In this study we sequenced all DCTN1 exons and exon-intron boundaries in 286 samples diagnosed with Parkinson disease (PD), frontotemporal lobar degeneration (FTLD), or ALS. Results: This analysis revealed 36 novel variants (9 missense, 5 silent, and 22 noncoding). Segregation analysis in families and association studies in PD, FTLD, and ALS case–control series did not identify any variants segregating with disease or associated with increased disease risk. Conclusions: This study suggests that pathogenic mutations in DCTN1 are rare and do not play a common role in the development of Parkinson disease, frontotemporal lobar degeneration, or amyotrophic lateral sclerosis.

[1]  M. Farrer,et al.  Pallidonigral TDP-43 pathology in Perry syndrome. , 2009, Parkinsonism & related disorders.

[2]  M. Farrer,et al.  DCTN1 mutations in Perry syndrome , 2009, Nature Genetics.

[3]  E. Holzbaur,et al.  Regulation of Dynactin through the Differential Expression of p150Glued Isoforms* , 2008, Journal of Biological Chemistry.

[4]  A. Grierson,et al.  Role of axonal transport in neurodegenerative diseases. , 2008, Annual review of neuroscience.

[5]  Z. Wszolek,et al.  Rapidly progressive familial parkinsonism with central hypoventilation, depression and weight loss (Perry syndrome)--a literature review. , 2008, Parkinsonism & related disorders.

[6]  Anna Akhmanova,et al.  Structure-function relationship of CAP-Gly domains , 2007, Nature Structural &Molecular Biology.

[7]  M. Ikura,et al.  CLIP170 autoinhibition mimics intermolecular interactions with p150Glued or EB1 , 2007, Nature Structural &Molecular Biology.

[8]  E. Holzbaur,et al.  Axonal transport and neurodegenerative disease. , 2006, Biochimica et biophysica acta.

[9]  K. Fischbeck,et al.  A motor neuron disease–associated mutation in p150Glued perturbs dynactin function and induces protein aggregation , 2006, The Journal of cell biology.

[10]  Andrew D. Stephens,et al.  A microtubule-binding domain in dynactin increases dynein processivity by skating along microtubules , 2006, Nature Cell Biology.

[11]  S. Reske,et al.  Heterozygous R1101K mutation of the DCTN1 gene in a family with ALS and FTD , 2005, Annals of neurology.

[12]  M. Farrer,et al.  Lrrk2 pathogenic substitutions in Parkinson's disease , 2005, Neurogenetics.

[13]  K. Fischbeck,et al.  Distal spinal and bulbar muscular atrophy caused by dynactin mutation , 2005, Annals of neurology.

[14]  Allen Newell,et al.  Parallel implementation of OPS5 on the encore multiprocessor: Results and analysis , 2005, International Journal of Parallel Programming.

[15]  Gerald DeJong,et al.  Explanation-Based Learning: An Alternative View , 2005, Machine Learning.

[16]  A. Ludolph,et al.  Point mutations of the p150 subunit of dynactin (DCTN1) gene in ALS , 2004, Neurology.

[17]  Tom M. Mitchell,et al.  Explanation-Based Generalization: A Unifying View , 1986, Machine Learning.

[18]  Allen Newell,et al.  Chunking in Soar: The anatomy of a general learning mechanism , 1985, Machine Learning.

[19]  Shin J. Oh,et al.  Mutant dynactin in motor neuron disease , 2003, Nature Genetics.

[20]  V. Allan,et al.  Dynactin , 2000, Current Biology.

[21]  R. A. Brooks,et al.  Intelligence without Representation , 1991, Artif. Intell..

[22]  Allen Newell,et al.  The effectiveness of task-level parallelism for high-level vision , 1989, PPOPP '90.

[23]  Allen Newell,et al.  Soar/PSM-E: investigating match parallelism in a learning production sytsem , 1988, PPoPP 1988.

[24]  John E. Laird Recovery from Incorrect knowledge in Soar , 1988, AAAI.

[25]  Allen Newell,et al.  SOAR: An Architecture for General Intelligence , 1987, Artif. Intell..

[26]  John E. Laird,et al.  Learning General Search Control from Outside Guidance , 1987, IJCAI.

[27]  Gerald DeJong,et al.  The Classification, Detection and Handling of Imperfect Theory Problems , 1987, IJCAI.

[28]  David Chapman,et al.  Pengi: An Implementation of a Theory of Activity , 1987, AAAI.

[29]  Alberto M. Segre,et al.  Explanation-based learning of generalized robot assembly plans , 1987 .

[30]  L. Suchman Plans and situated actions , 1987 .

[31]  Jaime G. Carbonell,et al.  Learning by Experimentation , 1987 .

[32]  Richard J. Doyle,et al.  Constructing and Refining Causal Explanations from an Inconsistent Domain Theory , 1986, AAAI.

[33]  Alberto M. Segre Explanation-based manipulator learning , 1986 .

[34]  Tom M. Mitchell,et al.  LEAP: A Learning Apprentice for VLSI Design , 1985, IJCAI.

[35]  Michael D. Rychener THE INSTRUCTIBLE PRODUCTION SYSTEM: A RETROSPECTIVE ANALYSIS , 1983 .

[36]  Michael D. Rychener Approaches to Knowledge Acquisition: The Instructable Production System Project , 1980, AAAI.

[37]  Richard Fikes,et al.  Learning and Executing Generalized Robot Plans , 1993, Artif. Intell..