A genome-wide association study implicates diacylglycerol kinase eta (DGKH) and several other genes in the etiology of bipolar disorder

Abstract

The genetic basis of bipolar disorder has long been thought to be complex, with the potential involvement of multiple genes, but methods to analyze populations with respect to this complexity have only recently become available. We have carried out a genome-wide association study of bipolar disorder by genotyping over 550,000 single-nucleotide polymorphisms (SNPs) in two independent case-control samples of European origin. The initial association screen was performed using pooled DNA, and selected SNPs were confirmed by individual genotyping. While DNA pooling reduces power to detect genetic associations, there is a substantial cost saving and gain in efficiency. A total of 88 SNPs, representing 80 different genes, met the prior criteria for replication in both samples. Effect sizes were modest: no single SNP of large effect was detected. Of 37 SNPs selected for individual genotyping, the strongest association signal was detected at a marker within the first intron of diacylglycerol kinase eta (DGKH; P=1.5 x 10(-8), experiment-wide P<0.01, OR=1.59). This gene encodes DGKH, a key protein in the lithium-sensitive phosphatidyl inositol pathway. This first genome-wide association study of bipolar disorder shows that several genes, each of modest effect, reproducibly influence disease risk. Bipolar disorder may be a polygenic disease.

Figure 1

Probability plots of expected (line) vs observed (+) p-values derived from pooled DNA in the a) NIMH and b) German samples. X-axis: −ln(expected p-value); Y-axis: −ln(observed p-value).

Figure 1

Probability plots of expected (line) vs observed (+) p-values derived from pooled DNA in the a) NIMH and b) German samples. X-axis: −ln(expected p-value); Y-axis: −ln(observed p-value).

Figure 2

Distribution of risk alleles among cases and controls in the combined sample (a), and relationship of prevalence ratio to risk allele burden (b). Data from ten individually genotyped SNPs (rs4411993, rs7683874, rs10937823, rs942518, rs11021955, rs10120953, rs1170191, rs9315885, rs9513877, rs2360111) are plotted. Cases are indicated in black, controls in gray. An exponential function provides a good fit to the data (R² = 0.82).

Figure 3

Pooling-derived association results for SNPs in the gene DGKH (181 kb). The graphic was produced by UCSC Genome Browser, using the May 2004 build and the custom tracks option. SNPs associated at the p<0.05 level are shown in the NIMH and German tracks, and SNPs genotyped by the HumanHap550 are shown directly above the gene track. Red SNPs were significant at p < 0.05 in both samples, blue SNPs had p < 0.05 in only one sample. There is substantial linkage disequilibrium across the region, according to the HapMap CEPH-European data (not shown).

Figure 4

Graphic illustrating the roles of 8 genes implicated in the present study in lithium-sensitive signaling pathways. Green lines denote enzymatic transformations or cofactor activations, red lines confirmed inhibitory actions, blue lines protein interactions of unknown nature from Lim et al (54) or hypothetical interactions. All colored genes contain at least one replicated SNP based on individual genotyping (teal) or pooled (yellow) data. G-protein coupled receptors (such as GPC51) activate the phosphatidyl inositol signaling pathway via G-protein (G) activation of phospholipase C (PLC, such as PLCG2). PLC cleaves PIP2 into IP3 and diacylglycerol (DAG). DAG is metabolized by DAG kinases (such as DGKH). DAG is a necessary cofactor for activation of most protein kinase C (PKC) isoforms. PKC cross-talks via disheveled (Dvl) with the Wnt/B-catenin signaling pathway. Dvl is activated by Wnt receptors (such as FZD2) and directly inhibited by nucleoredoxin (NXN) by binding the PDZ domain. A2BP1 also binds Dvl. Dvl inhibits glycogen synthase kinase-3 beta (GSK3B), which itself inhibits β-catenin. β-catenin is activitated by whirlin (DFNB31) via the Usher protein complex. Since it also contains PDZ domains, DFNB31 may also bind nucleoredoxin and Dvl. In the nucleus, β-catenin modulates the activity of TCF/LEF transcription factors (such as TCF7L1), which ultimately effects the expression of a large number of target genes. Lithium (Li+) lowers intracellular myo-inositol levels, reducing production of PIP2, and increases β–catenin signaling through inhibition of GSK3B.