This study, published online at Nature.com last Wednesday, strikes me as an interesting hybrid of two kinds of studies that are frequently used in autism research: gene-expression studies (where researchers compare patterns of gene expression in tissue samples taken from autistic people to those in samples taken from neurotypical people) and neuroanatomical studies (where researchers look at differences in size, structure or activation patterns of various brain structures between autistic and neurotypical subjects).
In this study, the researchers took samples from three different regions of the brain (the prefrontal cortex, superior temporal gyrus and cerebellar vermis), using brains donated to the Autism Tissue Project and the Harvard brain bank. From both of those sources, they ended up with 58 cortex samples (29 from autistic brains; 29 from non-autistic brains) and 21 cerebellar samples (11 autistic; 10 not).
They looked for differences in gene expression between autistic and control tissue samples by measuring the amount of RNA present in each sample corresponding to a given sequence of genomic DNA. (Since the mid-to-late 1990s, a tool has existed to do this at quite a high resolution: the DNA microarray. This is a glass or silicon chip covered in tiny wells where a short sequence of DNA is anchored --- in this case, the DNA probes are short, synthesized 50-base snippets made to match specific parts of each gene contained in the National Center for Biotechnology Information's RefSeq database --- to which your sample DNA or RNA will bind if it contains a complementary sequence).
(What a microarray looks like)
This type of experimental design doesn't really allow direct comparison between RNA extracts from different tissue samples --- instead, each sample (from the same region of the brain of either an autistic or neurotypical donor, or from different regions within the same brain) hybridizes (i.e., forms a new, DNA-RNA "hybrid" helix when heated) to the DNA probes on its own separate array. Researchers then compare the intensity of the signal created by each well across the two arrays --- the brighter the color, the more (fluorescent-dye-treated) sample RNA is present on the chip.
In this experiment, the researchers found 444 genes that differed significantly between the autistic and control cortex* samples in how much mRNA (the RNA created when DNA is transcribed; used as a template for protein synthesis) there was in a given tissue extract. They decided to concentrate on the 200 most differentially expressed genes for their (more detailed) expression analysis, which included a look into "co-expression networks" of genes whose expression seems to be regulated via the same pathways. They replicated their results by doing a similar microarray experiment on tissue samples from a smaller group of donated brains (nine from autistic donors, five from neurotypical donors), this time taking samples from a different region of the cerebral cortex than either of the cortical regions assayed in the initial experiment.
Figure 1C, in Voineagu et al, 2011 --- scatter plot showing genes found to be up- (red) and down-regulated (green) in both the initial and replication data sets. The bluish lines drawn through each cluster of dots reflects the cutoff for significance; most of the regulation changes are significant, but some aren't. Both axes represent a logarithmic measure of the change from baseline for either data set (Data Set 1, or the initial data, is on the x-axis; Data Set 2, or the replication data, is on the y-axis).
They got additional confirmation of their gene-expression data by using an alternative measure of how much of a given mRNA sequence was present in each tissue extract: for each gene that the microarray experiments identified as being differentially expressed in autistic and non-autistic brain tissues, they made a DNA copy of its array-bound mRNAs, and then amplified those bits of DNA using a process called RT-PCR (real-time polymerase chain reaction). That process uses bacterial enzymes to make huge numbers of copies of a given sequence of DNA, such that the amount of DNA is large enough to be easily quantified. Those amounts could be compared between groups, and thus confirm (or fail to confirm) differences in mRNA production predicted by the microarray experiment.
This figure shows how much more or less mRNA there was from eleven genes whose differential expression levels were validated using PCR:
(Supplementary Figure 2B, in Voineagu et al., 2011 --- top bar graph, in red, shows positive changes in expression of five genes in the tissue samples taken from autistic donors; bottom graph, with green bars, shows the average reduction in expression of six other genes. On both graphs, the numbers on the y-axis represent how many times as much of one kind of mRNA was found in the autistic sample; you can see that the up-regulating produced a more dramatic change --- ten- and twenty-fold, for all but one of the five genes --- than down-regulating, which produced, respectively, one-half, one-fifth, one-eighth, one-third and one-fourth as much mRNA as the control sample).
They found two co-expression modules (networks of genes) whose expression varied in relation to whether the sample came from an autistic or non-autistic donor, and not in relation to any of the other variables they took into account (like age, sex, cause of death, medication history, whether the person also had seizures, and family history of mental illness): M12 and M16.
Here is their drawing of M12, and the relationships between its component genes:
(One of the genes in the middle of this diagram, CNTNAP1, is a close relative of a gene that other genetic studies have tied to autism --- and that I have described on this blog --- CNTNAP2).
... and here is their drawing of M16:
Relative to the samples from neurotypical donors, the brain tissue samples from autistic donors had more mRNA transcripts of genes in M16, and fewer transcripts of genes from M12.
In each of these modules, genes for certain types of proteins predominated: for M12, these are proteins involved in synapse formation, neurotransmission, vesicular transport (importing objects into the cell, or exporting objects from it); while M16 included lots of genes for immune and inflammatory proteins.
One of the major genes in M12, A2BP1, is a splicing regulator. Alternative splicing is one of the ways the cell can make different kinds of proteins from the same mRNA; the mRNA will contain characteristic sequences, called splice sites, where splicing enzymes can bind to it, cut it and put it back together, minus the regions bordered by splice sites.
Like some other instances I've mentioned of proteins playing a role in gene expression themselves being expressed differently in autism, this down-regulation of A2BP1 could have important ramifications for the genes whose transcripts A2BP1 is involved in splicing. The authors of this study thought it would be a good idea to look for A2BP1 splice sites in the RNA samples from those specimens within the autism group with especially low levels of A2BP1 mRNA; to do this, they sequenced all the mRNA from three samples with relatively little A2BP1 mRNA, and also from three control samples with normal A2BP1 expression. They found 212 potential splice sites using this method, which they validated by using RT-PCR (again) to compare relative amounts of various alternatively-spliced mRNAs in autistic and control tissue samples --- first in the same three samples that were sequenced, and then in three other samples from the autism group, which also had low A2BP1 expression. Using this method, they confirmed that the vast majority (85%) of the expected splicing changes were really there in all of the low-A2BP1 samples.
The genes whose alternative splicing depended on A2BP1, and thus whose alternate forms were underexpressed in the low-A2BP1 RNA samples, included a lot of the same genes as the M12 co-expression module. So it looks like, besides finding out that M12 is collectively underexpressed in autism, these researchers have also found at least one of the mechanisms behind this underexpression.
*The cerebellar samples differed significantly in the expression of only two genes, so those data were not included in further analysis.
Irina Voineagu, Xinchen Wang, Patrick Johnston, Jennifer K. Lowe, Yuan Tian, Steve Horvath, Jonathan Mill, Rita M. Cantor, Benjamin J. Blencowe, & Daniel H. Geschwind (2011). Transcriptomic analysis of autistic brain reveals convergent molecular pathology Nature (25 May) : 10.1038/nature10110