Genome-wide association study of borderline personality disorder reveals genetic overlap with bipolar disorder, major depression and schizophrenia

Borderline personality disorder (BOR) is determined by environmental and genetic factors, and characterized by affective instability and impulsivity, diagnostic symptoms also observed in manic phases of bipolar disorder (BIP). Up to 20% of BIP patients show comorbidity with BOR. This report describes the first case-control genome-wide association study (GWAS) of BOR, performed in one of the largest BOR patient samples worldwide. The focus of our analysis was (i) to detect genes and gene sets involved in BOR and (ii) to investigate the genetic overlap with BIP. As there is considerable genetic overlap between BIP, major depression (MDD) and schizophrenia (SCZ) and a high comorbidity of BOR and MDD, we also analyzed the genetic overlap of BOR with SCZ and MDD. GWAS, gene-based tests and gene-set analyses were performed in 998 BOR patients and 1545 controls. Linkage disequilibrium score regression was used to detect the genetic overlap between BOR and these disorders. Single marker analysis revealed no significant association after correction for multiple testing. Gene-based analysis yielded two significant genes: DPYD (P=4.42 × 10-7) and PKP4 (P=8.67 × 10-7); and gene-set analysis yielded a significant finding for exocytosis (GO:0006887, PFDR=0.019; FDR, false discovery rate). Prior studies have implicated DPYD, PKP4 and exocytosis in BIP and SCZ. The most notable finding of the present study was the genetic overlap of BOR with BIP (rg=0.28 [P=2.99 × 10-3]), SCZ (rg=0.34 [P=4.37 × 10-5]) and MDD (rg=0.57 [P=1.04 × 10-3]). We believe our study is the first to demonstrate that BOR overlaps with BIP, MDD and SCZ on the genetic level. Whether this is confined to transdiagnostic clinical symptoms should be examined in future studies.

Evidence for genetic heterogeneity between clinical subtypes of bipolar disorder

We performed a genome-wide association study of 6447 bipolar disorder (BD) cases and 12 639 controls from the International Cohort Collection for Bipolar Disorder (ICCBD). Meta-analysis was performed with prior results from the Psychiatric Genomics Consortium Bipolar Disorder Working Group for a combined sample of 13 902 cases and 19 279 controls. We identified eight genome-wide significant, associated regions, including a novel associated region on chromosome 10 (rs10884920; P=3.28 × 10-8) that includes the brain-enriched cytoskeleton protein adducin 3 (ADD3), a non-coding RNA, and a neuropeptide-specific aminopeptidase P (XPNPEP1). Our large sample size allowed us to test the heritability and genetic correlation of BD subtypes and investigate their genetic overlap with schizophrenia and major depressive disorder. We found a significant difference in heritability of the two most common forms of BD (BD I SNP-h2=0.35; BD II SNP-h2=0.25; P=0.02). The genetic correlation between BD I and BD II was 0.78, whereas the genetic correlation was 0.97 when BD cohorts containing both types were compared. In addition, we demonstrated a significantly greater load of polygenic risk alleles for schizophrenia and BD in patients with BD I compared with patients with BD II, and a greater load of schizophrenia risk alleles in patients with the bipolar type of schizoaffective disorder compared with patients with either BD I or BD II. These results point to a partial difference in the genetic architecture of BD subtypes as currently defined.

Genome-wide association study identifies SESTD1 as a novel risk gene for lithium-responsive bipolar disorder

This corrects the article DOI: 10.1038/mp.2015.165.

Genetic variants in the region of the C1q genes are associated with rheumatoid arthritis

Rodent models for arthritis implicate a role for complement in disease development and progression. In humans, complement deposition has been observed in inflamed synovia of rheumatoid arthritis (RA) patients. In this study we analysed whether genetic variants of complement component C1q predispose to RA. We genotyped single nucleotide polymorphisms (SNPs) in and around the C1q genes, C1qA, C1qB and C1qC, in a Dutch set of 845 RA cases and 1046 controls. Replication was sought in a sample set from North America (868 cases/1193 controls), and a meta-analysis was performed in a combined samples set of 8000 cases and 23 262 controls of European descent. We determined C1q serum levels in relation to C1q genotypes. In the discovery phase, five of the 13 SNPs tested in the C1q genes showed a significant association with RA. Additional analysis of the genomic area around the C1q genes revealed that the strongest associating SNPs were confined to the C1q locus. Within the C1q locus we observed no additional signal independent of the strongest associating SNP, rs292001 [odds ratio (OR) = 0·72 (0·58-0·88), P = 0·0006]. The variants of this SNP were associated with different C1q serum levels in healthy controls (P = 0·006). Interestingly, this SNP was also associated significantly in genome-wide association studies (GWAS) from the North American Rheumatoid Arthritis Consortium study, confirming the association with RA [OR = 0·83 (0·69-1·00), P = 0·043]. Combined analysis, including integrated data from six GWAS studies, provides support for the genetic association. Genetic variants in C1q are correlated with C1q levels and may be a risk for the development of RA.

The major risk alleles of age-related macular degeneration (AMD) in CFH do not play a major role in rheumatoid arthritis (RA)

Because activation of the alternative pathway (AP) of the complement system is an important aspect of both age-related macular degeneration (AMD) and rheumatoid arthritis (RA), we wished to address the question whether genetic risk factors of the AP inhibitor complement factor H (CFH) for AMD would also be risk factors for RA. For this purpose we genotyped single nucleotide polymorphisms (SNPs) in a Dutch set of RA patients and controls. Similarly, a meta-analysis using a Spanish cohort of RA as well as six large genome-wide association studies (GWAS) studies was performed. For these SNPs we analysed more than 6000 patients and 20,000 controls. The CFH variants, I62V, Y402H, IVS1 and IVS10, known to associate strongly with AMD, did not show a significant association with the risk of developing RA despite a strong statistical power to detect such differences. In conclusion, the major risk alleles of AMD in CFH do not have a similar effect on developing RA.

Distribution of genetic variation within and among local populations of Arabidopsis thaliana over its species range

A detailed description of local population structure in Arabidopsis thaliana is presented, including an assessment of the genetic relatedness of individuals collected from the same field. A hierarchical sample of four individuals from 37 local populations, including North America, England, Eastern and Western Europe, and Asia, and a selection of ecotypes, were analysed for variation in Adh, ChiA, FAH1, F3H, Rpm1, Rps5, and five microsatellite loci. Twenty-eight of the 37 population samples contained individuals with identical multilocus haplotypes, 12 of which were fixed for a single haplotype. These monomorphic populations were evenly distributed over the species range. Only in North America did we find a single multilocus haplotype shared among different populations, perhaps indicating a continental founder event. Despite the occurrence of local inbreeding, a considerable amount of genetic variation was found segregating within and among local populations. A novel analysis of haplotype differences reveals that genetic differentiation occurs at every geographic scale in A. thaliana, where we find a surprising under-representation of recent migrants between local populations. This leads us to hypothesize that most dispersal between A. thaliana populations is by pollen rather than seed. Based on the structure of A. thaliana populations, it appears that regional groups of local populations may provide the most appropriate genetic material for linkage disequilibrium mapping of adaptive traits.

Evolutionary dynamics of plant R-genes

Plant R-genes involved in gene-for-gene interactions with pathogens are expected to undergo coevolutionary arms races in which plant specificity and pathogen virulence continually adapt in response to each other. Lending support to this idea, the solvent-exposed amino acid residues of leucine-rich repeats, a region of R-genes involved in recognizing pathogens, often evolve at unusually fast rates. But within-species polymorphism is also common in R-genes, implying that the adaptive substitution process is not simply one of successive selective sweeps. Here we document these features in available data and discuss them in light of the evolutionary dynamics they likely reflect.

Plant-pathogen arms races at the molecular level

Advances in research into the genetics of plant-pathogen interactions include an embracing of evolutionary ideas and methodologies. Recent studies reveal positive selection and selective maintenance of variation in plant resistance and defense-related genes. Coevolution between plants and their enemies involves many interactions at the molecular level.

Dynamics of disease resistance polymorphism at the Rpm1 locus of Arabidopsis

The co-evolutionary 'arms race' is a widely accepted model for the evolution of host-pathogen interactions. This model predicts that variation for disease resistance will be transient, and that host populations generally will be monomorphic at disease-resistance (R-gene) loci. However, plant populations show considerable polymorphism at R-gene loci involved in pathogen recognition. Here we have tested the arms-race model in Arabidopsis thaliana by analysing sequences flanking Rpm1, a gene conferring the ability to recognize Pseudomonas pathogens carrying AvrRpm1 or AvrB. We reject the arms-race hypothesis: resistance and susceptibility alleles at this locus have co-existed for millions of years. To account for the age of alleles and the relative levels of polymorphism within allelic classes, we use coalescence theory to model the long-term accumulation of nucleotide polymorphism in the context of the short-term ecological dynamics of disease resistance. This analysis supports a 'trench warfare' hypothesis, in which advances and retreats of resistance-allele frequency maintain variation for disease resistance as a dynamic polymorphism.