OBJECTIVE: The aim of this study was to identify the clinical features that affect age at diagnosis (AD) and time to the diagnosis of SCID.
METHODS: From 2005 to 2016, 147 SCID patients were referred to the Asian Primary Immunodeficiency Network. Patients with genetic diagnosis, age at presentation (AP), and AD were selected for study.
RESULTS: A total of 88 different SCID gene mutations were identified in 94 patients, including 49 IL2RG mutations, 12 RAG1 mutations, 8 RAG2 mutations, 7 JAK3 mutations, 4 DCLRE1C mutations, 4 IL7R mutations, 2 RFXANK mutations, and 2 ADA mutations. A total of 29 mutations were previously unreported. Eighty-three of the 94 patients fulfilled the selection criteria. Their median AD was 4 months, and the time to diagnosis was 2 months. The commonest SCID was X-linked (n = 57). A total of 29 patients had a positive FH. Candidiasis (n = 27) and bacillus Calmette-Guérin (BCG) vaccine infection (n = 19) were the commonest infections. The median age for candidiasis and BCG infection documented were 3 months and 4 months, respectively. The median absolute lymphocyte count (ALC) was 1.05 × 10(9)/L with over 88% patients below 3 × 10(9)/L. Positive FH was associated with earlier AP by 1 month (p = 0.002) and diagnosis by 2 months (p = 0.008), but not shorter time to diagnosis (p = 0.494). Candidiasis was associated with later AD by 2 months (p = 0.008) and longer time to diagnosis by 0.55 months (p = 0.003). BCG infections were not associated with age or time to diagnosis.
CONCLUSION: FH was useful to aid earlier diagnosis but was overlooked by clinicians and not by parents. Similarly, typical clinical features of SCID were not recognized by clinicians to shorten the time to diagnosis. We suggest that lymphocyte subset should be performed for any infant with one or more of the following four clinical features: FH, candidiasis, BCG infections, and ALC below 3 × 10(9)/L.
METHODS: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls).
RESULTS: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network.
CONCLUSION: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development.
IMPACT: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization.
SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.