Jennifer A. Brody

Systematic Localization of Common Disease-Associated Variation in Regulatory DNA

Predictions of Genetic Disease Many genome-wide association studies (GWAS) have identified loci and variants associated with disease, but the ability to predict disease on the basis of these genetic variants remains small. Maurano et al. (p. 1190; see the Perspective by Schadt and Chang; see the cover) characterize the location of GWAS variants in the genome with respect to their proximity to regulatory DNA [marked by deoxyribonuclease I (DNase I) hypersensitive sites] by tissue type, disease, and enrichments in physiologically relevant transcription factor binding sites and networks. They found many noncoding disease associations in regulatory DNA, indicating tissue and developmental-specific regulatory roles for many common genetic variants and thus enabling links to be made between gene regulation and adult-onset disease. Genetic variants that have been associated with diseases are concentrated in regulatory regions of the genome. Genome-wide association studies have identified many noncoding variants associated with common diseases and traits. We show that these variants are concentrated in regulatory DNA marked by deoxyribonuclease I (DNase I) hypersensitive sites (DHSs). Eighty-eight percent of such DHSs are active during fetal development and are enriched in variants associated with gestational exposure–related phenotypes. We identified distant gene targets for hundreds of variant-containing DHSs that may explain phenotype associations. Disease-associated variants systematically perturb transcription factor recognition sequences, frequently alter allelic chromatin states, and form regulatory networks. We also demonstrated tissue-selective enrichment of more weakly disease-associated variants within DHSs and the de novo identification of pathogenic cell types for Crohn’s disease, multiple sclerosis, and an electrocardiogram trait, without prior knowledge of physiological mechanisms. Our results suggest pervasive involvement of regulatory DNA variation in common human disease and provide pathogenic insights into diverse disorders.

Systematic identification of trans eQTLs as putative drivers of known disease associations

Identifying the downstream effects of disease-associated SNPs is challenging. To help overcome this problem, we performed expression quantitative trait locus (eQTL) meta-analysis in non-transformed peripheral blood samples from 5,311 individuals with replication in 2,775 individuals. We identified and replicated trans eQTLs for 233 SNPs (reflecting 103 independent loci) that were previously associated with complex traits at genome-wide significance. Some of these SNPs affect multiple genes in trans that are known to be altered in individuals with disease: rs4917014, previously associated with systemic lupus erythematosus (SLE), altered gene expression of C1QB and five type I interferon response genes, both hallmarks of SLE. DeepSAGE RNA sequencing showed that rs4917014 strongly alters the 3′ UTR levels of IKZF1 in cis, and chromatin immunoprecipitation and sequencing analysis of the trans-regulated genes implicated IKZF1 as the causal gene. Variants associated with cholesterol metabolism and type 1 diabetes showed similar phenomena, indicating that large-scale eQTL mapping provides insight into the downstream effects of many trait-associated variants.

Novel genetic markers associate with atrial fibrillation risk in Europeans and Japanese

OBJECTIVES This study sought to identify nonredundant atrial fibrillation (AF) genetic susceptibility signals and examine their cumulative relations with AF risk. BACKGROUND AF-associated loci span broad genomic regions that may contain multiple susceptibility signals. Whether multiple signals exist at AF loci has not been systematically explored. METHODS We performed association testing conditioned on the most significant, independently associated genetic markers at 9 established AF loci using 2 complementary techniques in 64,683 individuals of European ancestry (3,869 incident and 3,302 prevalent AF cases). Genetic risk scores were created and tested for association with AF in Europeans and an independent sample of 11,309 individuals of Japanese ancestry (7,916 prevalent AF cases). RESULTS We observed at least 4 distinct AF susceptibility signals on chromosome 4q25 upstream of PITX2, but not at the remaining 8 AF loci. A multilocus score comprised 12 genetic markers demonstrated an estimated 5-fold gradient in AF risk. We observed a similar spectrum of risk associated with these markers in Japanese. Regions containing AF signals on chromosome 4q25 displayed a greater degree of evolutionary conservation than the remainder of the locus, suggesting that they may tag regulatory elements. CONCLUSIONS The chromosome 4q25 AF locus is architecturally complex and harbors at least 4 AF susceptibility signals in individuals of European ancestry. Similar polygenic AF susceptibility exists between Europeans and Japanese. Future work is necessary to identify causal variants, determine mechanisms by which associated loci predispose to AF, and explore whether AF susceptibility signals classify individuals at risk for AF and related morbidity.

Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci

Meta-analyses of association results for blood pressure using exome-centric single-variant and gene-based tests identified 31 new loci in a discovery stage among 146,562 individuals, with follow-up and meta-analysis in 180,726 additional individuals (total n = 327,288). These blood pressure–associated loci are enriched for known variants for cardiometabolic traits. Associations were also observed for the aggregation of rare and low-frequency missense variants in three genes, NPR1, DBH, and PTPMT1. In addition, blood pressure associations at 39 previously reported loci were confirmed. The identified variants implicate biological pathways related to cardiometabolic traits, vascular function, and development. Several new variants are inferred to have roles in transcription or as hubs in protein–protein interaction networks. Genetic risk scores constructed from the identified variants were strongly associated with coronary disease and myocardial infarction. This large collection of blood pressure–associated loci suggests new therapeutic strategies for hypertension, emphasizing a link with cardiometabolic risk.

Engineering of stable bispecific antibodies targeting IL-17A and IL-23

Bispecific antibodies (bsAbs) present an attractive opportunity to combine the additive and potentially synergistic effects exhibited by combinations of monoclonal antibodies (mAbs). Current challenges for engineering bsAbs include retention of the binding affinity of the parent mAb or antibody fragment, the ability to bind both targets simultaneously, and matching valency with biology. Other factors to consider include structural stability and expression of the recombinant molecule, both of which may have significant impact on its development as a therapeutic. Here, we incorporate selection of stable, potent single-chain variable fragments (scFvs) early in the engineering process to assemble bsAbs for therapeutic applications targeting the cytokines IL-17A/A and IL-23. Stable scFvs directed against human cytokines IL-23p19 and IL-17A/A were isolated from a human Fab phage display library via batch conversion of panning output from Fabs to scFvs. This strategy integrated a step for shuffling V regions during the conversion and permitted the rescue of scFv molecules in both the V(H)V(L) and the V(L)V(H) orientations. Stable scFvs were identified and assembled into several bispecific formats as fusions to the Fc domain of human IgG1. The engineered bsAbs are potent neutralizers of the biological activity of both cytokines (IC(50) < 1 nM), demonstrate the ability to bind both target ligands simultaneously and display stability and productivity advantageous for successful manufacture of a therapeutic molecule. Pharmacokinetic analysis of the bsAbs in mice revealed serum half-lives similar to human mAbs. Assembly of bispecific molecules using stable antibody fragments offers an alternative to reformatting mAbs and minimizes subsequent structure-related and manufacturing concerns.

A dual-targeting PDGFRβ/VEGF-A molecule assembled from stable antibody fragments demonstrates anti-angiogenic activity in vitro and in vivo

Targeting angiogenesis is a promising approach to the treatment of solid tumors and age-related macular degeneration (AMD). Inhibition of vascularization has been validated by the successful marketing of monoclonal antibodies (mAbs) that target specific growth factors or their receptors, but there is considerable room for improvement in existing therapies. Combination of mAbs targeting both the VEGF and PDGF pathways has the potential to increase the efficacy of anti-angiogenic therapy without the accompanying toxicities of tyrosine kinase inhibitors and the inability to combine efficiently with traditional chemotherapeutics. However, development costs and regulatory issues have limited the use of combinatorial approaches for the generation of more efficacious treatments. The concept of mediating disease pathology by targeting two antigens with one therapeutic was proposed over two decades ago. While mAbs are particularly suitable candidates for a dual-targeting approach, engineering bispecificity into one molecule can be difficult due to issues with expression and stability, which play a significant role in manufacturability. Here, we address these issues upstream in the process of developing a bispecific antibody (bsAb). Single-chain antibody fragments (scFvs) targeting PDGFRβ and VEGF-A were selected for superior stability. The scFvs were fused to both termini of human Fc to generate a bispecific, tetravalent molecule. The resulting molecule displays potent activity, binds both targets simultaneously, and is stable in serum. The assembly of a bsAb using stable monomeric units allowed development of an anti-PDGFRB/VEGF-A antibody capable of attenuating angiogenesis through two distinct pathways and represents an efficient method for rapid engineering of dual-targeting molecules.

DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases

BackgroundChronic low-grade inflammation reflects a subclinical immune response implicated in the pathogenesis of complex diseases. Identifying genetic loci where DNA methylation is associated with chronic low-grade inflammation may reveal novel pathways or therapeutic targets for inflammation.ResultsWe performed a meta-analysis of epigenome-wide association studies (EWAS) of serum C-reactive protein (CRP), which is a sensitive marker of low-grade inflammation, in a large European population (n = 8863) and trans-ethnic replication in African Americans (n = 4111). We found differential methylation at 218 CpG sites to be associated with CRP (P < 1.15 × 10–7) in the discovery panel of European ancestry and replicated (P < 2.29 × 10–4) 58 CpG sites (45 unique loci) among African Americans. To further characterize the molecular and clinical relevance of the findings, we examined the association with gene expression, genetic sequence variants, and clinical outcomes. DNA methylation at nine (16%) CpG sites was associated with whole blood gene expression in cis (P < 8.47 × 10–5), ten (17%) CpG sites were associated with a nearby genetic variant (P < 2.50 × 10–3), and 51 (88%) were also associated with at least one related cardiometabolic entity (P < 9.58 × 10–5). An additive weighted score of replicated CpG sites accounted for up to 6% inter-individual variation (R2) of age-adjusted and sex-adjusted CRP, independent of known CRP-related genetic variants.ConclusionWe have completed an EWAS of chronic low-grade inflammation and identified many novel genetic loci underlying inflammation that may serve as targets for the development of novel therapeutic interventions for inflammation.

A DNA methylation biomarker of alcohol consumption

The lack of reliable measures of alcohol intake is a major obstacle to the diagnosis and treatment of alcohol-related diseases. Epigenetic modifications such as DNA methylation may provide novel biomarkers of alcohol use. To examine this possibility, we performed an epigenome-wide association study of methylation of cytosine-phosphate-guanine dinucleotide (CpG) sites in relation to alcohol intake in 13 population-based cohorts (ntotal=13 317; 54% women; mean age across cohorts 42–76 years) using whole blood (9643 European and 2423 African ancestries) or monocyte-derived DNA (588 European, 263 African and 400 Hispanic ancestry) samples. We performed meta-analysis and variable selection in whole-blood samples of people of European ancestry (n=6926) and identified 144 CpGs that provided substantial discrimination (area under the curve=0.90–0.99) for current heavy alcohol intake (⩾42 g per day in men and ⩾28 g per day in women) in four replication cohorts. The ancestry-stratified meta-analysis in whole blood identified 328 (9643 European ancestry samples) and 165 (2423 African ancestry samples) alcohol-related CpGs at Bonferroni-adjusted P<1 × 10−7. Analysis of the monocyte-derived DNA (n=1251) identified 62 alcohol-related CpGs at P<1 × 10-7. In whole-blood samples of people of European ancestry, we detected differential methylation in two neurotransmitter receptor genes, the γ-Aminobutyric acid-A receptor delta and γ-aminobutyric acid B receptor subunit 1; their differential methylation was associated with expression levels of a number of genes involved in immune function. In conclusion, we have identified a robust alcohol-related DNA methylation signature and shown the potential utility of DNA methylation as a clinically useful diagnostic test to detect current heavy alcohol consumption.

Sequence kernel association test for survival traits.

Rare variant tests have been of great interest in testing genetic associations with diseases and disease‐related quantitative traits in recent years. Among these tests, the sequence kernel association test (SKAT) is an omnibus test for effects of rare genetic variants, in a linear or logistic regression framework. It is often described as a variance component test treating the genotypic effects as random. When the linear kernel is used, its test statistic can be expressed as a weighted sum of single‐marker score test statistics. In this paper, we extend the test to survival phenotypes in a Cox regression framework. Because of the anticonservative small‐sample performance of the score test in a Cox model, we substitute signed square‐root likelihood ratio statistics for the score statistics, and confirm that the small‐sample control of type I error is greatly improved. This test can also be applied in meta‐analysis. We show in our simulation studies that this test has superior statistical power except in a few specific scenarios, as compared to burden tests in a Cox model. We also present results in an application to time‐to‐obesity using genotypes from Framingham Heart Study SNP Health Association Resource.

Analysis of loss-of-function variants and 20 risk factor phenotypes in 8,554 individuals identifies loci influencing chronic disease

A typical human exome harbors dozens of loss-of-function (LOF) variants, which can lower disease risk factor levels and affect drug efficacy. We hypothesized that LOF variants are enriched in genes influencing risk factor levels and the onset of common chronic diseases, such as cardiovascular disease and diabetes. To test this hypothesis, we sequenced the exomes of 8,554 individuals and analyzed the effects of predicted LOF variants on 20 chronic disease risk factor phenotypes. Analysis of this sample as discovery and replication strata of equal size verified two relationships in well-studied genes (PCSK9 and APOC3) and identified eight new loci. Previously unknown relationships included elevated fasting glucose in carriers of heterozygous LOF variation in TXNDC5, which encodes a biomarker for type 1 diabetes progression, and apparent recessive effects of C1QTNF8 on serum magnesium levels. These data demonstrate the utility of functional-variant annotation within a large sample of deeply phenotyped individuals for gene discovery.