Literature DB >> 23707675

Genetics of the connectome.

Paul M Thompson1, Tian Ge, David C Glahn, Neda Jahanshad, Thomas E Nichols.   

Abstract

Connectome genetics attempts to discover how genetic factors affect brain connectivity. Here we review a variety of genetic analysis methods--such as genome-wide association studies (GWAS), linkage and candidate gene studies--that have been fruitfully adapted to imaging data to implicate specific variants in the genome for brain-related traits. Studies that emphasized the genetic influences on brain connectivity. Some of these analyses of brain integrity and connectivity using diffusion MRI, and others have mapped genetic effects on functional networks using resting state functional MRI. Connectome-wide genome-wide scans have also been conducted, and we review the multivariate methods required to handle the extremely high dimension of the genomic and network data. We also review some consortium efforts, such as ENIGMA, that offer the power to detect robust common genetic associations using phenotypic harmonization procedures and meta-analysis. Current work on connectome genetics is advancing on many fronts and promises to shed light on how disease risk genes affect the brain. It is already discovering new genetic loci and even entire genetic networks that affect brain organization and connectivity.
Copyright © 2013 Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2013        PMID: 23707675      PMCID: PMC3905600          DOI: 10.1016/j.neuroimage.2013.05.013

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  104 in total

1.  Altered structural brain connectivity in healthy carriers of the autism risk gene, CNTNAP2.

Authors:  Emily L Dennis; Neda Jahanshad; Jeffrey D Rudie; Jesse A Brown; Kori Johnson; Katie L McMahon; Greig I de Zubicaray; Grant Montgomery; Nicholas G Martin; Margaret J Wright; Susan Y Bookheimer; Mirella Dapretto; Arthur W Toga; Paul M Thompson
Journal:  Brain Connect       Date:  2011

2.  Significant correlation between a set of genetic polymorphisms and a functional brain network revealed by feature selection and sparse Partial Least Squares.

Authors:  Edith Le Floch; Vincent Guillemot; Vincent Frouin; Philippe Pinel; Christophe Lalanne; Laura Trinchera; Arthur Tenenhaus; Antonio Moreno; Monica Zilbovicius; Thomas Bourgeron; Stanislas Dehaene; Bertrand Thirion; Jean-Baptiste Poline; Edouard Duchesnay
Journal:  Neuroimage       Date:  2012-07-08       Impact factor: 6.556

3.  A unified statistical approach for determining significant signals in images of cerebral activation.

Authors:  K J Worsley; S Marrett; P Neelin; A C Vandal; K J Friston; A C Evans
Journal:  Hum Brain Mapp       Date:  1996       Impact factor: 5.038

4.  Semiparametric regression of multidimensional genetic pathway data: least-squares kernel machines and linear mixed models.

Authors:  Dawei Liu; Xihong Lin; Debashis Ghosh
Journal:  Biometrics       Date:  2007-12       Impact factor: 2.571

5.  Applying tensor-based morphometry to parametric surfaces can improve MRI-based disease diagnosis.

Authors:  Yalin Wang; Lei Yuan; Jie Shi; Alexander Greve; Jieping Ye; Arthur W Toga; Allan L Reiss; Paul M Thompson
Journal:  Neuroimage       Date:  2013-02-20       Impact factor: 6.556

6.  Hierarchical topological network analysis of anatomical human brain connectivity and differences related to sex and kinship.

Authors:  Julio M Duarte-Carvajalino; Neda Jahanshad; Christophe Lenglet; Katie L McMahon; Greig I de Zubicaray; Nicholas G Martin; Margaret J Wright; Paul M Thompson; Guillermo Sapiro
Journal:  Neuroimage       Date:  2011-11-12       Impact factor: 6.556

7.  Plasma brain-derived neurotrophic factor and prefrontal white matter integrity in late-onset depression and normal aging.

Authors:  R B Dalby; B Elfving; P H P Poulsen; L Foldager; J Frandsen; P Videbech; R Rosenberg
Journal:  Acta Psychiatr Scand       Date:  2013-01-27       Impact factor: 6.392

8.  Genetics of brain fiber architecture and intellectual performance.

Authors:  Ming-Chang Chiang; Marina Barysheva; David W Shattuck; Agatha D Lee; Sarah K Madsen; Christina Avedissian; Andrea D Klunder; Arthur W Toga; Katie L McMahon; Greig I de Zubicaray; Margaret J Wright; Anuj Srivastava; Nikolay Balov; Paul M Thompson
Journal:  J Neurosci       Date:  2009-02-18       Impact factor: 6.167

9.  Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium.

Authors:  L A Farrer; L A Cupples; J L Haines; B Hyman; W A Kukull; R Mayeux; R H Myers; M A Pericak-Vance; N Risch; C M van Duijn
Journal:  JAMA       Date:  1997 Oct 22-29       Impact factor: 56.272

10.  Discovery and Replication of Gene Influences on Brain Structure Using LASSO Regression.

Authors:  Omid Kohannim; Derrek P Hibar; Jason L Stein; Neda Jahanshad; Xue Hua; Priya Rajagopalan; Arthur W Toga; Clifford R Jack; Michael W Weiner; Greig I de Zubicaray; Katie L McMahon; Narelle K Hansell; Nicholas G Martin; Margaret J Wright; Paul M Thompson
Journal:  Front Neurosci       Date:  2012-08-06       Impact factor: 4.677

View more
  75 in total

1.  Integrated multimodal imaging in neurodegenerative disease.

Authors:  Murray Grossman
Journal:  Lancet Neurol       Date:  2015-08-26       Impact factor: 44.182

2.  Adaptive testing for multiple traits in a proportional odds model with applications to detect SNP-brain network associations.

Authors:  Junghi Kim; Wei Pan
Journal:  Genet Epidemiol       Date:  2017-02-13       Impact factor: 2.135

3.  Massively expedited genome-wide heritability analysis (MEGHA).

Authors:  Tian Ge; Thomas E Nichols; Phil H Lee; Avram J Holmes; Joshua L Roffman; Randy L Buckner; Mert R Sabuncu; Jordan W Smoller
Journal:  Proc Natl Acad Sci U S A       Date:  2015-02-09       Impact factor: 11.205

4.  Genome-wide association studies of brain imaging data via weighted distance correlation.

Authors:  Canhong Wen; Yuhui Yang; Quan Xiao; Meiyan Huang; Wenliang Pan
Journal:  Bioinformatics       Date:  2020-12-08       Impact factor: 6.937

5.  Imaging-wide association study: Integrating imaging endophenotypes in GWAS.

Authors:  Zhiyuan Xu; Chong Wu; Wei Pan
Journal:  Neuroimage       Date:  2017-07-20       Impact factor: 6.556

6.  FGWAS: Functional genome wide association analysis.

Authors:  Chao Huang; Paul Thompson; Yalin Wang; Yang Yu; Jingwen Zhang; Dehan Kong; Rivka R Colen; Rebecca C Knickmeyer; Hongtu Zhu
Journal:  Neuroimage       Date:  2017-07-20       Impact factor: 6.556

7.  Heritability analysis with repeat measurements and its application to resting-state functional connectivity.

Authors:  Tian Ge; Avram J Holmes; Randy L Buckner; Jordan W Smoller; Mert R Sabuncu
Journal:  Proc Natl Acad Sci U S A       Date:  2017-05-08       Impact factor: 11.205

8.  The Shared Genetic Basis of Educational Attainment and Cerebral Cortical Morphology.

Authors:  Tian Ge; Chia-Yen Chen; Alysa E Doyle; Richard Vettermann; Lauri J Tuominen; Daphne J Holt; Mert R Sabuncu; Jordan W Smoller
Journal:  Cereb Cortex       Date:  2019-07-22       Impact factor: 5.357

9.  Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaging-genetic applications.

Authors:  Chenyang Tao; Thomas E Nichols; Xue Hua; Christopher R K Ching; Edmund T Rolls; Paul M Thompson; Jianfeng Feng
Journal:  Neuroimage       Date:  2016-09-22       Impact factor: 6.556

10.  A Robust Reduced Rank Graph Regression Method for Neuroimaging Genetic Analysis.

Authors:  Xiaofeng Zhu; Weihong Zhang; Yong Fan
Journal:  Neuroinformatics       Date:  2018-10
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.