Gerard Schellenberg and colleagues report a genome-wide association study of late-onset Alzheimer's disease (LOAD), as part of the Alzheimer Disease Genetics Consortium. They identify common variants in MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 associated with LOAD. The Alzheimer Disease Genetics Consortium (ADGC) performed a genome-wide association study of late-onset Alzheimer disease using a three-stage design consisting of a discovery stage (stage 1) and two replication stages (stages 2 and 3). Both joint analysis and meta-analysis approaches were used. We obtained genome-wide significant results at MS4A4A (rs4938933; stages 1 and 2, meta-analysis P (PM) = 1.7 × 10−9, joint analysis P (PJ) = 1.7 × 10−9; stages 1, 2 and 3, PM = 8.2 × 10−12), CD2AP (rs9349407; stages 1, 2 and 3, PM = 8.6 × 10−9), EPHA1 (rs11767557; stages 1, 2 and 3, PM = 6.0 × 10−10) and CD33 (rs3865444; stages 1, 2 and 3, PM = 1.6 × 10−9). We also replicated previous associations at CR1 (rs6701713; PM = 4.6 × 10−10, PJ = 5.2 × 10−11), CLU (rs1532278; PM = 8.3 × 10−8, PJ = 1.9 × 10−8), BIN1 (rs7561528; PM = 4.0 × 10−14, PJ = 5.2 × 10−14) and PICALM (rs561655; PM = 7.0 × 10−11, PJ = 1.0 × 10−10), but not at EXOC3L2, to late-onset Alzheimer's disease susceptibility1,2,3.

Systemic lupus erythematosus (SLE) is a clinically heterogeneous disease in which the risk of disease is influenced by complex genetic and environmental contributions. Alleles of HLA-DRB1, IRF5, and STAT4 are established susceptibility genes; there is strong evidence for the existence of additional risk loci. We genotyped more than 500,000 single-nucleotide polymorphisms (SNPs) in DNA samples from 1311 case subjects with SLE and 1783 control subjects; all subjects were North Americans of European descent. Genotypes from 1557 additional control subjects were obtained from public data repositories. We measured the association between the SNPs and SLE after applying strict quality-control filters to reduce technical artifacts and to correct for the presence of population stratification. Replication of the top loci was performed in 793 case subjects and 857 control subjects from Sweden. Genetic variation in the region upstream from the transcription initiation site of the gene encoding B lymphoid tyrosine kinase (BLK) and C8orf13 (chromosome 8p23.1) was associated with disease risk in both the U.S. and Swedish case–control series (rs13277113; odds ratio, 1.39; P=1×10⁻¹⁰) and also with altered levels of messenger RNA in B-cell lines. In addition, variants on chromosome 16p11.22, near the genes encoding integrin alpha M (ITGAM, or CD11b) and integrin alpha X (ITGAX), were associated with SLE in the combined sample (rs11574637; odds ratio, 1.33; P=3×10⁻¹¹). We identified and then confirmed through replication two new genetic loci for SLE: a promoter-region allele associated with reduced expression of BLK and increased expression of C8orf13 and variants in the ITGAM–ITGAX region.

Alzheimer's disease (AD) is a complex genetic disorder with no effective treatments. More than 20 common markers have been identified, which are associated with AD. Recently, several rare variants have been identified in Amyloid Precursor Protein (APP), Triggering Receptor Expressed On Myeloid Cells 2 (TREM2) and Unc-5 Netrin Receptor C (UNC5C) that affect risk for AD. Despite the many successes, the genetic architecture of AD remains unsolved. We used Genome-wide Complex Trait Analysis to (1) estimate phenotypic variance explained by genetics; (2) calculate genetic variance explained by known AD single nucleotide polymorphisms (SNPs); and (3) identify the genomic locations of variation that explain the remaining unexplained genetic variance. In total, 53.24% of phenotypic variance is explained by genetics, but known AD SNPs only explain 30.62% of the genetic variance. Of the unexplained genetic variance, approximately 41% is explained by unknown SNPs in regions adjacent to known AD SNPs, and the remaining unexplained genetic variance outside these regions.

In addition to apolipoprotein E (APOE), recent large genome-wide association studies (GWASs) have identified nine other genes/loci (CR1, BIN1, CLU, PICALM, MS4A4/MS4A6E, CD2AP, CD33, EPHA1 and ABCA7) for late-onset Alzheimer's disease (LOAD). However, the genetic effect attributable to known loci is about 50%, indicating that additional risk genes for LOAD remain to be identified. In this study, we have used a new GWAS data set from the University of Pittsburgh (1291 cases and 938 controls) to examine in detail the recently implicated nine new regions with Alzheimer's disease (AD) risk, and also performed a meta-analysis utilizing the top 1% GWAS single-nucleotide polymorphisms (SNPs) with P<0.01 along with four independent data sets (2727 cases and 3336 controls) for these SNPs in an effort to identify new AD loci. The new GWAS data were generated on the Illumina Omni1-Quad chip and imputed at ∼2.5 million markers. As expected, several markers in the APOE regions showed genome-wide significant associations in the Pittsburg sample. While we observed nominal significant associations (P<0.05) either within or adjacent to five genes (PICALM, BIN1, ABCA7, MS4A4/MS4A6E and EPHA1), significant signals were observed 69–180 kb outside of the remaining four genes (CD33, CLU, CD2AP and CR1). Meta-analysis on the top 1% SNPs revealed a suggestive novel association in the PPP1R3B gene (top SNP rs3848140 with P=3.05E–07). The association of this SNP with AD risk was consistent in all five samples with a meta-analysis odds ratio of 2.43. This is a potential candidate gene for AD as this is expressed in the brain and is involved in lipid metabolism. These findings need to be confirmed in additional samples.

Systemic lupus erythematosus (SLE) is a clinically heterogeneous, systemic autoimmune disease characterized by autoantibody formation. Previously published genome-wide association studies (GWAS) have investigated SLE as a single phenotype. Therefore, we conducted a GWAS to identify genetic factors associated with anti–dsDNA autoantibody production, a SLE–related autoantibody with diagnostic and clinical importance. Using two independent datasets, over 400,000 single nucleotide polymorphisms (SNPs) were studied in a total of 1,717 SLE cases and 4,813 healthy controls. Anti–dsDNA autoantibody positive (anti–dsDNA +, n = 811) and anti–dsDNA autoantibody negative (anti–dsDNA –, n = 906) SLE cases were compared to healthy controls and to each other to identify SNPs associated specifically with these SLE subtypes. SNPs in the previously identified SLE susceptibility loci STAT4, IRF5, ITGAM, and the major histocompatibility complex were strongly associated with anti–dsDNA + SLE. Far fewer and weaker associations were observed for anti–dsDNA – SLE. For example, rs7574865 in STAT4 had an OR for anti–dsDNA + SLE of 1.77 (95% CI 1.57–1.99, p = 2.0E-20) compared to an OR for anti–dsDNA – SLE of 1.26 (95% CI 1.12–1.41, p = 2.4E-04), with p_{heterogeneity}<0.0005. SNPs in the SLE susceptibility loci BANK1, KIAA1542, and UBE2L3 showed evidence of association with anti–dsDNA + SLE and were not associated with anti–dsDNA – SLE. In conclusion, we identified differential genetic associations with SLE based on anti–dsDNA autoantibody production. Many previously identified SLE susceptibility loci may confer disease risk through their role in autoantibody production and be more accurately described as autoantibody propensity loci. Lack of strong SNP associations may suggest that other types of genetic variation or non-genetic factors such as environmental exposures have a greater impact on susceptibility to anti–dsDNA – SLE. Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that can involve virtually any organ system. SLE patients produce antibodies that bind to their own cells and proteins (autoantibodies) which can cause irreversible organ damage. One particular SLE–related autoantibody directed at double-stranded DNA (anti–dsDNA) is associated with kidney involvement and more severe disease. Previous genome-wide association studies (GWAS) in SLE have studied SLE itself, not particular SLE manifestations. Therefore, we conducted this GWAS of anti–dsDNA autoantibody production to identify genetic associations with this clinically important autoantibody. We found that many previously identified SLE–associated genes are more strongly associated with anti–dsDNA autoantibody production than SLE itself, and they may be more accurately described as autoantibody propensity genes. No strong genetic associations were observed for SLE patients who do not produce anti–dsDNA autoantibodies, suggesting that other factors may have more influence in developing this type of SLE. Further investigation of these autoantibody propensity genes may lead to greater insight into the causes of autoantibody production and organ damage in SLE.