Identifying the genetic lesions that cause monogenic forms of disease has been enormously important in our efforts to understand the molecular basis of this complex disorder. In addition to this work, there has long been an attempt to find genetic variability that alters risk for, rather than causes, disease. In this section we will discuss the route to identifying risk loci in this complex disease.
Candidate Gene Association Studies
The majority of efforts in the 1990’s through to 2006 centered on simple, and generally small, case control candidate gene analyses. In this design a cohort of cases and controls, usually ~100–200 subjects in size was typed for a single polymorphism in a candidate gene to determine if a variant was more common in cases than controls. The genes selected were usually functional candidates, and the variant selected for typing was most often one that altered an amino acid. This effort was largely unsuccessful, with the some notable exceptions.
The first indication that SNCA
contained risk variants came from this type of work, with the publication of a nominal association between alleles of the REP1
polymorphism in the promoter region of SNCA
and risk for disease.46
While this initial work was intriguing, a large number of follow up studies failed to produce a clear picture of whether this was a genuine risk locus, providing both support for and against this association. Clarity only came to this issue with the publication of a large collaborative analysis of ~5000 samples, which showed a clear association between increased risk and the long REP1
This work suggests that the disease-linked alleles are associated with a 1.4 fold increase in risk for PD. As is discussed later, this story became more complicated with the advent of genome wide association (GWA) studies.
The identification of GBA
mutations as risk alleles for PD can possibly be thought of as the result of a candidate gene association study, although it is more appropriate to describe this as an association that was borne of careful and astute clinical observation. The autosomal recessive disorder Gaucher disease is a lysosomal storage disorder that is caused by mutation of the gene encoding glucocerebrosidase, GBA.
An initial report indicated that Gaucher disease patients may also display signs and symptoms of parkinsonism, albeit infrequently.48
This was followed by the observation that carriers of a single GBA
mutation appeared to be at a much higher risk for PD.49
Despite the strong initial association, it took many years to build a convincing argument for single GBA
mutations as a risk factor for typical PD. This was eventually achieved with a large meta-analysis of sequencing studies that showed clearly that a single GBA
mutation increases risk for PD ~5 fold.50
As with SNCA
, the identification of LRRK2
mutations as a cause of PD created intense activity around assessing the range of genetic variability in this gene, and the role of these variants in disease.8, 9
Early in this process an apparent mutation, p.G2385R, was described to segregate with PD in a small Taiwanese family.51
As sequence and genotype data began to accumulate it became clear that this variant was relatively common in the general Asian population, and that this was strongly associated with a ~2 fold increase in risk for PD.14
A meta analysis of these studies, performed in a wide variety of Asian cohorts, has shown this mutation to be present in ~4% of controls, and ~9% of cases.52
While a similar magnitude risk effect has been reported for an additional variant, p.R1628P, again in Asia, the supportive evidence for this is less clear than with p.G2385R.53, 54
Genome Wide Association Studies
A large number of GWA studies have now been performed in PD.55–66
In contrast to candidate gene association studies, GWA attempts an unbiased and comprehensive survey of the genome to identify loci that contain common genetic variability conferring risk for disease. As GWA data have accumulated so too have the number of loci implicated in risk for PD. The most recent analysis includes data on more than 12,000 cases and 20,000 controls, and provides evidence for 16 independent risk loci.57, 67
Individually, alleles at each of the loci represent small risk or protective factors, conferring 1.1 to 1.4 fold increases and 0.95 to 0.7 fold decreases in risk respectively. The basis for GWA studies is the common disease common variant hypothesis, which posits that for common diseases, risk is likely to be conferred by a collection of common variants that individually increase risk only a small amount. Because of this it is perhaps informative to view the risk conferred by the identified loci collectively, i.e. as a risk profile. In this context, when ordering a population based on the collective burden of genetic risk that each individual carries (and using only these 16 loci), the individuals in the highest quintile of genetic risk are 3 times as likely to have PD as those in the lowest quintile of genetic risk.67
Interestingly when using deciles of risk burden, this differential increases to 4 fold (data not shown).
We will not describe each of the loci identified here, but rather show a summary (), and comment on a few loci that are of particular interest.
Table 1 Risk loci for Parkinson’s disease, indicating location, minor allele frequency (MAF) and odds ratio (OR), primarily calculated under an additive model. Included are references to papers that initially implicated these loci, and those that proved (more ...)
The earliest signals to show up convincingly with GWA were at SNCA
, and LRRK2
Notably these are loci that contain genes linked to autosomal dominant forms of PD. While we cannot be sure that the biological mediator of the risk alleles at these loci are indeed SNCA
, and LRRK2
, because GWA identifies loci, not genes, it does seem likely. The initial association at SNCA,
described above, centers on the REP1
allele about 10kb 5′ to the translational start site of the gene. Interestingly, the initial compelling GWA signals at SNCA
were not in this area of the gene, but rather over the 3′ end of the gene, from intron 4 through till after the 3′ untranslated region. Current data seems to suggest that these signals are distinct, i.e. that there are at least two (and probably more) distinct regions of the SNCA
locus that contain common variants that alter risk for disease.68
This implies that the OR estimate of 1.4 for risk conferred by alleles at SNCA
is an underestimate. Similarly, there appear to be distinct risk effects within the HLA
locus and evidence that there exists more than one risk haplotype across the MAPT
These observations are consistent with the notion of graded haplotype risk, and suggest that the initial association observed at individual risk loci can represent only the dominant signal, and that substantive additional risk is likely to occur at many previously identified risk loci.2, 70
Also of note is that the MAPT
association with PD has only been observed in Caucasian populations, the GWA published to date in Asian cohorts fails to identify a signal at this locus. It is not yet clear whether this represents the substantial divergence of genetic diversity at this locus between populations (i.e. a true lack of association in Asian populations), or a relative lack of informative markers for the Asian population at this locus in current genotyping arrays.71
The association signal at LRRK2
is complex. As discussed above there is at least one established, common, protein-coding risk allele in the Asian population.52
GWA in Asian subject shows a clear and strong association close to LRRK2
but it is not clear whether this represents tagging of the p.G2385R allele or a distinct signal.62
There also exists a clear association close to LRRK2
in the Caucasian population and it is clear that this signal is not being driven by the common p.G2019S mutation.63
A recent report provides evidence of association between a LRRK2
haplotype that contains protein-coding polymorphisms and risk for disease; it is certainly plausible that this is the effect being tagged by GWA signals but this requires more work.54
Certainly it is reasonable to suppose that disease may be associated with both non-coding and coding changes in the same transcript, and this forms the basis of the Pleomorphic Risk Locus hypothesis.2
Therapeutic Implications of Risk Loci
In the early stages of GWA much was made of the rather small effect sizes identified by GWA; and this has been used to suggest that these loci are not important in the pathogenesis or etiology of disease. This is a logical fallacy, much like the old argument that SNCA mutations will tell us little about the disease because they are rare. GWA results provide data on the size of effects of risk alleles, but this tells us nothing about how critical the affected gene is within the molecular process that is PD. Clearly understanding the potential mechanistic implications of these genes is important; particularly whether individual genes are exerting an effect by increasing the likelihood of a disease initiating event or whether they are related to molecular or cellular response to the disease process.
The majority of risk loci identified by GWA cannot be explained by non-synonymous (protein coding) polymorphisms.72
This suggests that such loci must alter risk by altering the biologically relevant transcript in some other way, either by affecting transcript expression levels, altering splicing, or changing sub cellular localization. There already exists data that has attempted to look at this for PD loci, and while these are quite blunt tools some significant correlations have been detected that suggest risk alleles alter expression of proximal transcripts.63, 67, 73
This immediately suggests a potential point of therapeutic intervention lies in modulating expression and that excellent targets in this regard are genes implicated by GWA studies. This is an approach that is already being investigated for SNCA
, although in this case driven by the finding of SNCA
multiplication as a cause of PD.74
What is known about the age-related biology of this protein suggests this is a good target.75
Notably, the risk alleles identified at SNCA
are associated with increased SNCA
expression and this immediately supports the notion that such a therapy may be effective in typical PD as well as rare familial forms.73
There are several considerations that need to be addressed before attempting to convert GWA findings such as those described here to expression-based therapies. The first is to identity the pathobiologically relevant transcript within any single risk locus, and in concert with this, to understand quite how the transcript is affected. One can imagine that this might be through several mechanisms; basal expression levels, expression in response to a stimulus (i.e. induced expression), exon splicing, and sub cellular localization of a transcript. Perhaps a more complex endeavor will be to understand quite how modulating this transcript will manifest in downstream effects. Gene therapy is already being tested for PD and other neurodegenerative diseases, in Phase 1 and 2 clinical trials.76, 77
This is likely to be a hard fought effort, however, the applicability of such an approach to myriad diseases, would suggest that overcoming the practical obstacles to this therapy will be an effort spread across many research fields.
Aside from mechanistic implications, genetics is likely to impact other aspects of therapeutics application in PD. It is conceivable that genetic profiling of individuals could ultimately be used to both predict who is at a high risk for disease and their long term prognosis, in addition to indicating which therapies, and what dosing regimen, is most likely to be effective. Given the relationship between genetic variability and gene expression in the brain,78
a working understanding of how a patients genetic profile will predict response to modulating gene expression, and how this may be used as a covariate in assessing biomarkers of disease progression, are both likely to be important in designing and monitoring personalized, or boutique therapies.
Where are the cures?
A question that is frequently raised, particularly to the enthusiastic geneticist, is “its been a long time since the first mutation was discovered, where are the cures?”. In truth, this is a question borne partly out of hyperbole surrounding many genetic findings, but mostly out of a lack of understanding regarding the process of drug production coupled with a naïve belief that understanding biology is easy. Inherent in the type of etiologic based therapy discussed here, is to identify a process or target for intervention. For the most part this relies on understanding at least part of the pathobiological effect of a mutant protein. This mechanism is usually not self evident – for example, the identification of α-synuclein mutations led quickly to an understanding that α-synuclein accumulated in Lewy Bodies, but the toxic species, and the nature of toxicity is still not apparent. Understanding the pathobiology is clearly very difficult; this is not only illustrated by the enormous amount of ongoing work in this regard in PD, but similar efforts in other complex diseases. Even when a pathobiological mechanism is revealed (or even hinted at), the route to therapy is a long one. The preclinical stage, of identifying efficient and specific drugs or small molecules that appropriately target the pathobiological process, takes many years. Even when this is achieved, the clinical and approval stage takes close to a decade. Perhaps as important as understanding these time limitations, is acknowledging that the vast majority of therapies that transition from preclinical to clinical stages fail to make it to market.
So, given these hurdles, why are we pursuing genetics? Despite these limitations, we truly believe that the best possible route to treating this complex disease is to understand what goes wrong at the molecular level, and to use this knowledge to reverse, halt, or slow this process. Although the first genetic finding was made in PD more than 15 years ago, we still consider this early days in terms of therapeutic design. While there is a long way to go, we are clearly a lot further along the road to a cure than when we started, and the continued addition of new genetic findings can only take us further down this path.