Bioinformatics Uncovers Pathological Synuclein RNA

Rarely do genetics, biology, and pathogenesis converge in a single study as they do in the September 25 Nature Communications. An unusually long α-synuclein mRNA identified by Asa Abeliovich and colleagues at Columbia University, New York, brandishes an extended 3’ untranslated region (UTR) and thrives in the presence of dopamine and PD-linked gene variants. It also seems to steer synuclein protein away from synaptic terminals and toward mitochondria, where it accumulates, mimicking PD pathology. Synuclein is the major component of Lewy bodies, dense protein aggregates found in the brains of people with PD and related neurodegenerative diseases. The latest findings highlight a new mechanism for controlling α-synuclein and suggest that selective downregulation of the long isoforms could hold therapeutic value. “The manuscript and its data are outstanding,” noted Jörg Schulz of University Aachen, Germany, in an e-mail to Alzforum. “I believe it will change our view of the pathogenesis of Parkinson’s disease.”

Researchers have worked for decades to determine what drives sporadic PD. Though they have discovered genetic and environmental risk factors, how they provoke disease has been unclear. The new work now links both risk factors to a major hallmark of PD pathology.

To identify molecular pathways driving PD pathogenesis, the Columbia scientists initially tried genomewide expression analyses on patient brain tissue. “We could see it was going to be a rough road,” Abeliovich said. “The data we got were what you would expect with loss of dopamine neurons. They reflected 30 years of disease rather than telling us something about how the disease started.”

To distinguish secondary changes from causal events, first author Herve Rhinn and colleagues analyzed gene expression data using a new computational technique they call differential coexpression analysis (DCA), which is based on a method termed differential wiring that has been applied in cancer research (Hudson et al., 2009). Instead of simply looking for transcripts that go up or down in PD versus normal tissue, as is done in conventional whole-transcriptome analyses, they used bioinformatics to find “master regulator” transcripts that control expression of groups of downstream transcripts. The authors worked on the premise that when a master regulator goes awry, the whole network falls apart, and therefore the regulator likely represents a primary rather than a secondary event in disease. “We looked for the network that was most different between controls and patients. Then we looked for the center of that network,” Abeliovich said.

Using the bioinformatics method to analyze several independent datasets of PD patients and age-matched elderly, the researchers found that “center” to be an α-synuclein transcript with a long 3’UTR. Among 22 human brain regions analyzed, this isoform is expressed most abundantly in the substantia nigra of the midbrain, and people with PD had more of this extended transcript, relative to shorter α-synuclein species, than did age-matched controls. The ratio of the long transcript to total synuclein mRNA increased further in brain tissue from people with common variants in the 3’UTR that raise the risk of getting Parkinson’s. Even in unaffected individuals, risk variants boosted the ratio in a dose-dependent way. Abeliovich saw that as “overwhelming evidence that [the change] is not secondary to disease.”

More than genetics governs the production of this mRNA isoform. Environmental toxins, which are known risk factors for PD, also drove up expression of the long α-synuclein transcript—as did dopamine, whether exogenously applied to cultured rat neurons or injected into mice. Previous studies suggested that dopamine raises synuclein levels, but had not shown how, Abeliovich said.

Rhinn and colleagues also found that upregulation of the extended α-synuclein transcript, in turn, caused accumulation of synuclein protein—preferentially in mitochondria—as occurs in disease. In addition, they identified an miR-34b binding site in the 3’UTR of the α-synuclein long isoform, but not in shorter transcripts. Based on luciferase assays in SH-SY5Y cells transfected with the long synuclein isoform, miR-34b seems to drive translation of the transcript. However, the α-synuclein gene has PD risk variants and sites for binding other miRNAs, which likely add further complexity to the mechanisms regulating mRNA and protein expression, noted Owen Ross of the Mayo Clinic in Jacksonville, Florida (see comment below). Indeed, a recent microRNA profiling study found a dearth of miR-34b/c in PD brains, triggering transcript changes that underlie mitochondrial dysfunction and oxidative stress (Miñones-Moyano et al., 2011).

The findings “highlight the importance of abnormal RNA processing in PD research,” wrote Jesse McLean and Ole Isacson of McLean Hospital, Belmont, Massachusetts, in an e-mail to Alzforum (see full comment below). A prior analysis identified α-synuclein mRNA isoforms with alternatively spliced exons 3 and/or 5 (Beyer et al., 2008). “It would be interesting to know if these coding isoforms correlate with the 3’UTR isoforms in terms of expression,” noted Ross.

Abeliovich sees the extended 3’UTR as a “convergent point for environmental and genetic regulation of α-synuclein.” Compounds that preferentially curb expression of the long transcript may have therapeutic benefits, he suggested. The ratio of the long transcript to total synuclein also appears elevated in patient blood samples, compared to unaffected controls, suggesting it could serve as a disease biomarker, Abeliovich said.—Esther Landhuis

Comments

  1. This article of Rhinn and colleagues is interesting. They are suggesting that alternative 3’UTR lengths in the α-synuclein gene (SNCA) determine protein expression, accumulation, and localization, which can all alter the risk of Parkinson’s disease. Their idea that specific 3’UTR length (and genetic variation therein) can affect protein expression and localization is intriguing. The underlying disease mechanism at the SNCA locus is a major area of research and may well determine future therapeutic intervention strategies. This work also highlights the need for careful consideration of potential knockdown therapies, as it may be a specific transcript of SNCA that is toxic, limiting a general knockdown strategy.

    The authors highlight the two predominant transcripts, but there are a number of other species that may be of interest, and determining the reason for altered 3’UTR expression may be important.

    SNCA is located in a large linkage disequilibrium block with risk variants along the length of the gene; hence, in the past, promoter variants such as the REP1 repeat have also been shown to affect SNCA expression. Therefore, given the complexity of mechanisms regulating synuclein gene and protein expression, the modest effect of this 3’UTR-directed risk may well be confounded by others. For example, studies of patient tissue have shown reduced SNCA gene expression, although that is not examining specific transcripts. Furthermore, the authors note that they observe the same SNCA 3’UTR transcript expression pattern in cerebral cortex tissue, which perhaps questions the direct role of this mechanism in the cell death that characterizes Parkinson’s disease.

    There are a number of SNCA mRNA transcripts reported with alternative splicing of exon 3 and/or exon 5 (see Beyer et al., 2008). It would be interesting to know if these coding transcripts correlate with the 3’UTR transcripts from the expression point of view. In addition, the authors mention miR34b, but there are several miRNA binding sites, and it is not clear how the others are affected within the setting of alternate 3’UTR lengths.

    I think, as with many similar studies, this work raises more questions regarding the complexity of the genetic risk observed in sporadic patients for the SNCA locus. Teasing out the underlying functional genetic variants and then characterizing them will be crucial steps in developing SNCA-based drugs.

    References:

    Beyer K, Domingo-Sàbat M, Humbert J, Carrato C, Ferrer I, Ariza A. Differential expression of alpha-synuclein, parkin, and synphilin-1 isoforms in Lewy body disease. Neurogenetics. 2008 Jul;9(3):163-72. PubMed.

    View all comments by Owen Ross

  2. The manuscript and its data are outstanding. I believe it will change our view of the pathogenesis of Parkinson's disease. The authors make use of intelligent bioinformatic approaches (differential coexpression analysis) to identify a specific transcript isoform of α-synuclein with a long 3′ untranslated region (UTR), termed aSynL, that is highly altered in coexpression correlation in the context of PD tissue. Without describing their whole approach, their new data allow the authors to integrate current knowledge of genetic risk variants, explain the vulnerability of dopaminergic midbrain neurons, integrate mechanisms of known toxins, describe effects of L-DOPA, and explain mislocalization of α-synuclein to mitochondria, which has been a focus in the field (including ours) during the last years.

    It will take some time to really appreciate all the details that are given here and to give full credit to the authors. Of course, the data will need replication. However, based on the detailed descriptions in the manuscript, I have not much doubt that the story will hold true.

    View all comments by Jorg Schulz

  3. These authors used an emerging bioinformatics technique (differential coexpression) to identify a mature α-synuclein mRNA transcript that retains an elongated 3’UTR (aSynL) as a potential common pathogenic mechanism for Parkinson's disease (PD).

    By applying differential coexpression analysis, aSynL was identified as a potential convergent mechanism of several biological pathways reconfigured in association with PD genetic and environmental risk factors. Their findings highlight the importance of abnormal RNA processing in PD research, particularly since the authors show that aSynL transcripts show pathological significance.

    These set-wise, coexpression changes as causal should, however, be approached with caution. For example, coexpression changes found in postmortem PD neurons may not represent causal pathological processes, but rather, may represent a reconfiguration of the existing neuron towards a survival state.

    View all comments by Jesse McLean

  4. I must say that this is a beautiful and incredibly extensive study that ties together many of the loose ends of the α-synuclein story. It is a scholarly example of how one and the same gene can either contribute 100 percent to disease causality or increase relative risk for that same disease. It demonstrates well the use of public databases and bioinformatics analysis of expression data. Data are also extensively validated using brain material of patients and control individuals, primary cells, transgenic animals, etc. Ultimately, the study provides evidence for the higher sensitivity of midbrain dopaminergic neurons for underlying disease processes.

    I believe that this is a milestone paper in our quest for more understanding of the complex brain pathology observed in neurodegenerative brain diseases.

    View all comments by Christine Van Broeckhoven

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References

Paper Citations

  1. Hudson NJ, Reverter A, Dalrymple BP. A differential wiring analysis of expression data correctly identifies the gene containing the causal mutation. PLoS Comput Biol. 2009 May;5(5):e1000382. PubMed.
  2. Miñones-Moyano E, Porta S, Escaramís G, Rabionet R, Iraola S, Kagerbauer B, Espinosa-Parrilla Y, Ferrer I, Estivill X, Martí E. MicroRNA profiling of Parkinson's disease brains identifies early downregulation of miR-34b/c which modulate mitochondrial function. Hum Mol Genet. 2011 Aug 1;20(15):3067-78. PubMed.
  3. Beyer K, Domingo-Sàbat M, Humbert J, Carrato C, Ferrer I, Ariza A. Differential expression of alpha-synuclein, parkin, and synphilin-1 isoforms in Lewy body disease. Neurogenetics. 2008 Jul;9(3):163-72. PubMed.

Further Reading

Papers

  1. Miñones-Moyano E, Porta S, Escaramís G, Rabionet R, Iraola S, Kagerbauer B, Espinosa-Parrilla Y, Ferrer I, Estivill X, Martí E. MicroRNA profiling of Parkinson's disease brains identifies early downregulation of miR-34b/c which modulate mitochondrial function. Hum Mol Genet. 2011 Aug 1;20(15):3067-78. PubMed.
  2. Beyer K, Domingo-Sàbat M, Humbert J, Carrato C, Ferrer I, Ariza A. Differential expression of alpha-synuclein, parkin, and synphilin-1 isoforms in Lewy body disease. Neurogenetics. 2008 Jul;9(3):163-72. PubMed.

Primary Papers

  1. Rhinn H, Qiang L, Yamashita T, Rhee D, Zolin A, Vanti W, Abeliovich A. Alternative α-synuclein transcript usage as a convergent mechanism in Parkinson's disease pathology. Nat Commun. 2012;3:1084. PubMed.

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