|ERK and P13K||Ubiquitin|
and glutamatergic pathways
|Social Deficit/Emotional Circuits|
|MET||ERK and P13K|
|Neurotrophins||Oxytocin and AVP|
|MET||ERK and P13K|
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:
- ASD is a result of interplay between many genes
- 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.