Genome-Wide Association Studies (GWAS) have implicated >60 loci in the susceptibility to systemic lupus erythematosus (SLE). However, GWAS reports signals in non-coding genomic regions, not the precise location of culprit genes. Chromatin conformation capture (3C) technologies that detect physical contacts between regions of the genome offer a powerful opportunity to map disease variants to target genes. We developed a massively parallel, high-resolution method to characterize the genome-wide interactomes of 36,691 promoters of protein-coding, noncoding, antisense, snRNA, miRNA, snoRNA and lincRNA genes in any cell type. Using this method, we generated promoter interactomes of primary human T follicular helper (TFH) cells from healthy tonsil, a cell type relevant to SLE as TFH operate upstream of pathogenic autoantibody-producing B cells. These sub-1kb TFH promoter interactome datasets were intersected with maps of TFH open chromatin generated by ATAC-seq and SLE SNPs from the 63 candidate loci, resulting in detection of consistent interactions between genes and accessible SNPs at 48 loci. We find that ~25% of accessible SLE SNPs interact with the nearest gene, e.g. STAT4 and IKZF3, while ~75% of accessible SNPs ‘skip’ the nearest gene to interact with distant genes, e.g. LCLAT1 at the ‘LBH’ locus, and the master TFH transcription factor BCL6 at the ‘LPP-TPRG1’ locus. Gene ontology analysis confirms that genes directly implicated by SNP interactions reside in SLE-relevant networks while ‘nearest to SNP’ genes do not. In conclusion, high-resolution, 3-dimensional promoter interactions with accessible, disease-associated SNPs in disease-relevant tissue connect variants to relevant genes with high apparent accuracy.