Difference between revisions of "Genetics"

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The idea that the symptoms of ASD is a result of the interaction of many different genes has been supported by linkage studies, and the fact that although many genes have been identified with causing ASD symptoms, each of these individual genes do not cause more than 1-2% of all ASD cases.  However, data mining techniques such as hierarchical clustering and principle components analysis find that it is highly likely that there is 1 continuously distributed factor contributing to many aspects of ASD, thereby validating the existence of the second hypothesis.  Additionally, statistical analysis of ASD family data suggest a large portion of ASDs may be the result of dominant de novo mutations that have reduced penetrance in families.  
 
The idea that the symptoms of ASD is a result of the interaction of many different genes has been supported by linkage studies, and the fact that although many genes have been identified with causing ASD symptoms, each of these individual genes do not cause more than 1-2% of all ASD cases.  However, data mining techniques such as hierarchical clustering and principle components analysis find that it is highly likely that there is 1 continuously distributed factor contributing to many aspects of ASD, thereby validating the existence of the second hypothesis.  Additionally, statistical analysis of ASD family data suggest a large portion of ASDs may be the result of dominant de novo mutations that have reduced penetrance in families.  
 
Some areas of investigation include
 
 
#[[Methylation]]
 
  
 
[[Genetics2| Genetics-Etiology]]
 
[[Genetics2| Genetics-Etiology]]
==Etiology==
 
 
Recent studies have suggested that ASD in families where multiple members are affected by autistic traits may be caused more by genetic predisposition.  In contrast, ASD in families where only one member displays autistic traits are more likely to be caused by rare gene mutations which have a large effect or by copy number variations.  One way of studying this difference is by comparing autistic traits in unaffected family members from multiplex autism families to simplex autism families.<sup>5</sup>
 
 
'''Linkage and Association Studies'''
 
 
Successful linkage studies in the past have been mostly based on affected sibling-pair designs in multiplex families.  However, there were no genome wide significant results probably because of small effect sizes that were a result of any single gene.  Even large scale studies showed only minor overlap, likely because of variety of phenotypes in ASD.  Recently though, use of endophenotypes and [[QTL mapping]] have increased the power of linkage and association studies.
 
 
Endophenotypes can help genetic studies by defining more etiologically homogenous subgroups.  Furthermore, endophenotypes are measurable in both affected and control groups, thus allowing for larger sample sizes.  Language phenotypes such as the age at which the child speaks their first word, are very promising endophenotypes because they show significant linkage in many samples and the support has been lent at implicating the 7q region to this language development, thereby raising hypothesis that the 7q region is home to other loci that are associated with the autism language phenotype<sup>3</sup>.
 
 
[[Copy-Number Variation]]
 
 
 
 
<div style="float:right; padding:10px; background:yellow; border:2px solid black;font-size:large;"><b>[[Autism Spectrum Disorders| Main Page]]</b></div>
 
  
<div style="float:left; padding:10px; background:yellow; border:2px solid black;font-size:large;"><b>[[Genetics| Back]]</b></div>
 
<br><br><br>
 
 
===Analytical Techniques===
 
===Analytical Techniques===
 
*[[QTL mapping]]
 
*[[QTL mapping]]

Revision as of 14:09, 1 April 2010

Genetics

Want more information about a
specific gene or gene group? Pick one of the categories below!
CadherinsNeuroligins/Neurexins/Shank3
METCNVs
ERK and P13KUbiquitin
RELNNeurotrophins
CNTNAP-2Serotoninergic, GABAergic,
and glutamatergic pathways
EIF4EPTEN
NeurotrophinsOxytocin and AVP
Cav1.2NCAM2
Anaphase IF.gif


A host of genes of interest have been identified through gene association studies, resequencing and, recently, the assessment of copy number variation (CNV).In particular, given the pathology of ASD, genes dealing with electrical conductance and neural transmission have been popular sites of study since synaptic dysfunction has been suggested as a unifying theme behind the various disorders in ASD. It has been difficult to find a specific gene mutation that is present in all cases of ASD, probably because of the heterogeneity of the ASD population. However, one group found that when they stratified an ASD group into subgroups based off of severity of symptoms and applied cluster analysis and various genetic profiling techniques, there were 20 novel genes that were shared by all three ASD subgroups. Additionally, most of the highly significantly differentially expressed genes in the ASD group that was found in the study are differentially regulated within the context of androgen insensitivity. This supports one hypothesis that higher levels of fetal testosterone are a risk factor for ASD.1

The high occurrence of differential expression profiles for 15 clock genes only for those in the severely affected ASD subgroup suggest that the severity of symptoms may be a connected with the dysregulation of the circadian rhythm. Scientists have demonstrated a genetic association of PER1 and NPAS2 with autistic disorder, and other theories have been proposed interplays between Fragile-X related proteins and synaptic genes with circadian rhythm genes.1

Most approaches to finding loci of interest are under one of two assumptions:

  1. ASD is a result of interplay between many genes
  2. There is one principle gene which contributes to many aspects of the disease.

The idea that the symptoms of ASD is a result of the interaction of many different genes has been supported by linkage studies, and the fact that although many genes have been identified with causing ASD symptoms, each of these individual genes do not cause more than 1-2% of all ASD cases. However, data mining techniques such as hierarchical clustering and principle components analysis find that it is highly likely that there is 1 continuously distributed factor contributing to many aspects of ASD, thereby validating the existence of the second hypothesis. Additionally, statistical analysis of ASD family data suggest a large portion of ASDs may be the result of dominant de novo mutations that have reduced penetrance in families.

Genetics-Etiology

Analytical Techniques

Citations

1. Schmitz C. Autism: neuropathology, alterations of the GABAergic system, and animal models.Int Rev Neurobiol. 2005;71:1-26. PMID 16512344

2. Jones, J.R. et. al. Hypothesis: Dysregulation of Methylation of Brain-Expressed Genes on the X Chromosome and Autism Spectrum Disorders. American Journal of Medical Genetics Part A 146A:2213-2220 (2008). PMID 18698615

3. Lush, Molly et. al. Current Developments in the Genetics of Autism: From Phenome to Genome. J Neuropathol Exp Neurol. 2008 September; 67(9):829-837. PMID 18716561

4. Cook, E.H. and S. W. Scherer. Copy-number variations associated wtih neuropsychiatric conditions. Nature.2008 October;455(16) 919-23. PMID 18923514

5. Hoekstra RA, et. al. Autistic traits in simplex and multiplex autism families: Focus on unaffected relatives.Am J Med Genet B Neuropsychiatr Genet. 2010 Jan 5;153B(1):356-8. PMID 19367575