Neurogenetic disorders across the lifespan: from aberrant development to degeneration

Author(s):  
Richard A. Hickman ◽  
Sarah A. O’Shea ◽  
Mark F. Mehler ◽  
Wendy K. Chung
2019 ◽  
Vol 35 (17) ◽  
pp. 3092-3101 ◽  
Author(s):  
Hideko Kawakubo ◽  
Yusuke Matsui ◽  
Itaru Kushima ◽  
Norio Ozaki ◽  
Teppei Shimamura

Abstract Motivation Recent sequence-based analyses have identified a lot of gene variants that may contribute to neurogenetic disorders such as autism spectrum disorder and schizophrenia. Several state-of-the-art network-based analyses have been proposed for mechanical understanding of genetic variants in neurogenetic disorders. However, these methods were mainly designed for modeling and analyzing single networks that do not interact with or depend on other networks, and thus cannot capture the properties between interdependent systems in brain-specific tissues, circuits and regions which are connected each other and affect behavior and cognitive processes. Results We introduce a novel and efficient framework, called a ‘Network of Networks’ approach, to infer the interconnectivity structure between multiple networks where the response and the predictor variables are topological information matrices of given networks. We also propose Graph-Oriented SParsE Learning, a new sparse structural learning algorithm for network data to identify a subset of the topological information matrices of the predictors related to the response. We demonstrate on simulated data that propose Graph-Oriented SParsE Learning outperforms existing kernel-based algorithms in terms of F-measure. On real data from human brain region-specific functional networks associated with the autism risk genes, we show that the ‘Network of Networks’ model provides insights on the autism-associated interconnectivity structure between functional interaction networks and a comprehensive understanding of the genetic basis of autism across diverse regions of the brain. Availability and implementation Our software is available from https://github.com/infinite-point/GOSPEL. Supplementary information Supplementary data are available at Bioinformatics online.


Neurogenetics ◽  
2012 ◽  
pp. 6-16 ◽  
Author(s):  
David Craufurd ◽  
Peter S. Harper ◽  
Nicholas Wood

Neurology ◽  
2019 ◽  
Vol 93 (16) ◽  
pp. e1535-e1542 ◽  
Author(s):  
Benjamin T. Cocanougher ◽  
Lauren Flynn ◽  
Pomi Yun ◽  
Minal Jain ◽  
Melissa Waite ◽  
...  

ObjectiveTo better characterize adult myotubularin 1 (MTM1)–related myopathy carriers and recommend a phenotypic classification.MethodsThis cohort study was performed at the NIH Clinical Center. Participants were required to carry a confirmed MTM1 mutation and were recruited via the Congenital Muscle Disease International Registry (n = 8), a traveling local clinic of the Neuromuscular and Neurogenetic Disorders of Childhood Section, National Institute of Neurological Disorders and Stroke, NIH and Cure CMD (n = 1), and direct physician referral (n = 1). Neuromuscular examinations, muscle MRI, dynamic breathing MRI, cardiac MRI, pulmonary function tests (PFTs), physical therapy assessments including the Motor Function Measure 32 (MFM-32) scale, and X chromosome inactivation (XCI) studies were performed.ResultsPhenotypic categories were proposed based on ambulatory status and muscle weakness. Carriers were categorized as severe (nonambulatory; n = 1), moderate (minimal independent ambulation/assisted ambulation; n = 3), mild (independent ambulation but with evidence of muscle weakness; n = 4), and nonmanifesting (no evidence of muscle weakness; n = 2). Carriers with more severe muscle weakness exhibited greater degrees of respiratory insufficiency and abnormal signal on muscle imaging. Skeletal asymmetries were evident in both manifesting and nonmanifesting carriers. Skewed XCI did not explain phenotypic severity.ConclusionThis work illustrates the phenotypic range of MTM1-related myopathy carriers in adulthood and recommends a phenotypic classification. This classification, defined by ambulatory status and muscle weakness, is supported by muscle MRI, PFT, and MFM-32 scale composite score findings, which may serve as markers of disease progression and outcome measures in future gene therapy or other clinical trials.


Author(s):  
Nicolas Dupré ◽  
Jean-Pierre Bouchard ◽  
Bernard Brais ◽  
Guy A. Rouleau

ABSTRACT:Historical events have shaped the various regional gene pools of the French-Canadian (FC) population, leading to increased prevalence of some rare diseases. The first studies of these founder effects were performed in large part by astute clinicians such as André Barbeau. In collaboration with others, he contributed greatly to the delineation of phenotypic subtypes of these conditions. As such, the following neurogenetic disorders were first identified in patients of FC origin: AOA2, ARSACS, HSAN2, RAB, and HMSN/ACC. We have summarized our current knowledge of the main hereditary ataxias, spastic parapareses and neuropathies that are particular to the FC population. The initial genetic characterization of the more common and homogeneous of these diseases has been largely completed. We predict that the regional populations of Canada will allow the identification of new rare forms of hereditary ataxias, spastic parapareses and neuropathies, and contribute to the unravelling of the genetic basis of these entities.


2012 ◽  
Vol 2012 ◽  
pp. 1-3 ◽  
Author(s):  
Hansen Wang ◽  
Cara J. Westmark ◽  
Emma Frost ◽  
Laurie C. Doering

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