More than 90% of common variants associated with complex traits do not affect 
proteins directly, but instead the circuits that control gene expression. This 
has increased the urgency of understanding the regulatory genome as a key 
component for translating genetic results into mechanistic insights and 
ultimately therapeutics. To address this challenge, we developed HaploReg 
(http://compbio.mit.edu/HaploReg) to aid the functional dissection of 
genome-wide association study (GWAS) results, the prediction of putative causal 
variants in haplotype blocks, the prediction of likely cell types of action, and 
the prediction of candidate target genes by systematic mining of comparative, 
epigenomic and regulatory annotations. Since first launching the website in 
2011, we have greatly expanded HaploReg, increasing the number of chromatin 
state maps to 127 reference epigenomes from ENCODE 2012 and Roadmap Epigenomics, 
incorporating regulator binding data, expanding regulatory motif disruption 
annotations, and integrating expression quantitative trait locus (eQTL) variants 
and their tissue-specific target genes from GTEx, Geuvadis, and other recent 
studies. We present these updates as HaploReg v4, and illustrate a use case of 
HaploReg for attention deficit hyperactivity disorder (ADHD)-associated SNPs 
with putative brain regulatory mechanisms.