Linkage studies, as previously discussed, are best suited for detecting genetic variants (including rare variants) of strong effect and with a clear pattern of Mendelian transmission. Association studies, in contrast, are better suited to detecting multiple variants of modest effect, and perform best when the variants being studied are relatively common in the general population. When association studies are focused on particular candidate genes, they are constrained by the limits of investigator imagination and the body of previously accumulated evidence (which may not be sizeable). With the advent of multi-center genomics initiatives such as the International HapMap Project
45 and of improved genotyping technologies for higher throughput analysis, a new type of association study, the genome-wide association study (GWAS), exploded onto the scene. GWAS, presaged in an exposition by Risch and Merikangas
46, typically interrogate hundreds of thousands to upwards of one million biallelic SNPs located throughout the genome. They represent an advance in human genetics because they are more comprehensive and less biased than candidate studies. Because of the unprecedented amount of hypothesis testing (and the resultant inflation of type I error), the standard in the field has been to set ‘genome-wide significance’ at P ≤ 5.0 × 10
−8 (or 0.05 divided by one million, the predicted number of independent common DNA variants in the human genome). This raises interesting theoretical questions about how to evaluate single candidate gene association papers achieving P-values on the order of 10
−2 or 10
−3 even if the history of a sample or a given locus does not include the execution of a GWAS.
GWAS have already advanced our understanding of mechanisms underlying general medical illnesses such as diabetes, Crohn’s disease, and rheumatoid arthritis—as exemplified by a seminal paper published by the Wellcome Trust
47. For MDD, there are now four published GWAS.
The first of these, by Sullivan et al
48, was facilitated by the Genetic Association Information Network (GAIN) and utilized a semi-community-based sample of 1,738 cases and 1,802 controls from the Netherlands. The authors examined 435,291 SNPs and found their top signal to be at rs1558477 (trend-test p-value of 1 × 10
−6), 12.4 kb downstream of
ADCYAP1R1, or adenylate cyclase-activating polypeptide 1 (pituitary) receptor type I. They focused their subsequent efforts, however, on a set of 11 clustered association signals (within their top 200 findings) localized to
PCLO (or Piccolo), a presynpatic protein which is also known as Aczonin. The authors pursued this finding with an expanded collection of close to 12,000 independent subjects, but were unable to replicate their
PCLO findings. A retrospective analysis suggested that the
PCLO-MDD association may only be optimally detected in population-based (as opposed to clinically-obtained) case samples such as the original GAIN MDD sample and only one of their replication samples. Although this hypothesis has not yet been tested,
PCLO remains an intriguing candidate. Beyond a possible role in facilitating dopamine transporter internalization
49, PCLO appears to more generally negatively regulate synaptic vesicle exocytosis by decreasing transport of vesicles from reserve pools to readily-releasable pools through an action on synapsin
50.
PCLO is also expressed outside the CNS at such diverse locations as the neuromuscular junction
51 and in pancreatic beta cells (where it helps regulate insulin release)
52, though these are less likely to have relevance to MDD.
The second published GWAS of MDD, by Muglia et al
53, utilized a German clinic-based sample of 1,022 recurrent depression (MDD-R) cases and 1,000 controls and interrogated 494,678 SNPs. As in the Sullivan et al study, there were no genome-wide significant findings. Muglia et al performed a meta-analysis combining the first sample with a second population-based sample of Swiss origin (494 cases and 1,052 controls), and found their best signal at rs4238010 (P = 5.8 × 10
−6), 260 kb from the closest gene (
CCND2, or cyclin D2). A gene-based analysis obtained results generally similar to those of their original SNP-based analysis. These authors then carried out a more focused examination of SNPs in the vicinity of a number of previously published MDD and bipolar disorder candidate loci, where they found that their most significant association lay in
GRM7 (metabotropic glutamate receptor 7) at rs162209, though this is not in linkage disequilibrium with rs1485171, the SNP previously identified by the Wellcome Trust as moderately associated with bipolar disorder at a p-value of 9.7 × 10
−5.
Additional GWAS of MDD, one derived from GenRED
54 and another from STAR*D
55, have followed. For simplification, we will focus on the results of a meta-analysis by Shyn et al
55, which combined results from GenRED, STAR*D, and the GAIN MDD study (i.e., Sullivan et al). The GenRED GWAS consisted of 1,020 MDD-REO cases while the STAR*D GWAS consisted of 1,221 MDD cases. Both were sampled from North American individuals of European ancestry and both shared a common set of 1,636 controls. By including subjects contributed from the publicly available GAIN MDD GWAS, there were a total of 3,956 cases and 3,428 controls in this three-sample meta-analysis. Using imputation (a method that takes known correlations between individual markers to probabilistically ‘fill-in’ genotypes missing in one, two, or all three studies), a total of 2,339,408 autosomal and 51,795 chromosome X SNPs were analyzed. The model was a broadly inclusive one, and treated as cases all patients with DSM-IV-defined MDD. Additional exploratory analyses, however, were also examined and included a ‘narrow’ analysis (MDD-REO only) and sex-specific analyses. Disappointingly, there were no genome-wide significant findings in either the primary analysis or any of the secondary analyses. Intronic markers from three genes, however, achieved meta-analysis P-values of better than 10
−6:
ATP6V1B2,
GRM7, and
SP4. ATP6V1B2 encodes a vacuolar protein pump ATPase subunit, and has a potentially related finding in bipolar disorder: Sklar et al
56 obtained a p-value of approximately 10
−5 in a SNP in
ATP6V1G1, a gene which contributes a distinct subunit to the same molecular complex. Additionally, it remains possible that the implicated
ATP6V1B2 SNP in the MDD GWAS meta-analysis may affect the adjacent gene
VMAT1 (or vesicular monoamine transporter 1).
GRM7, which was additionally highlighted in Muglia et al (and also mentioned briefly in Sullivan et al), is perhaps the most promising finding since there is a significant body of literature linking GRM7 to the mechanistic action of mood stabilizers and antidepressants
57–59. As a cell surface receptor, GRM7 would represent a highly tractable target for novel therapeutic agents, should subsequent studies continue to suggest a prominent role for this receptor in mood regulation. Finally,
SP4 encodes a brain-specific zinc-finger transcription factor. Most notable for
SP4, so far, are studies demonstrating an association between bipolar disorder and
SP460 and an Sp4-binding site in
GRK3 (G-protein receptor kinase 3)
61, as well as a series of murine studies demonstrating that mice with
SP4 deleted have deficits in hippocampal granule cell density in the dentate gyrus
62 and in hippocampal integrity (with resultant phenotypes in contextual memory)
63. Adult neurogenesis of hippocampal granule cells has been linked to depression and to antidepressant action
64, and so the locus of these
SP4 mutant phenotypes is intriguing. See for a summary of published MDD GWAS to date.
| Table 2Summary of published MDD GWAS results |
Although the results of each individual GWAS and the three-study GAIN/GenRED/STAR*D meta-analysis did not reach the desired level of statistical significance, these studies do support interesting candidate genes and genomic regions for further study. Additionally, pooled analysis of multiple GWAS samples has yielded findings for other complex traits that were not apparent in any single GWAS
13, 65, 66. With this in mind, a meta-analysis of MDD utilizing over 12,000 cases and nearly 10,000 controls is underway
67.