Graphical abstract

Figure 1. Genetic testing reveals diverse pathogenic mechanisms in patients with HLH. (A) Summary of workflow for 48 subjects who underwent research-based WES analyses. (B) Genetic profiles for 101 subjects who met the HLH-2004 criteria and received genetic testing. (C) Dominant NLRC4 and NLRP12 variants and recessive NLRP4, NLRC3, and NLRP13 variants are significantly associated with development of HLH. The number of alleles containing potential protein-altering variants (frameshift insertions/deletions, stop gain/stop loss, splicing defects, nonframeshift insertions/deletions, and missense variants) in NLRC4, NLRP12, NLRP4, NLRP13, and NLRC3 in HLH-affected cases (n = 48) was compared with the number in other samples in the Baylor-Hopkins Center for Mendelian Genomics database (total n = 6677; analyzed n = 5981), which contains exomes from well-phenotyped diseased and healthy individuals (recorded within the PhenoDB database) collected among more than 380 phenotypic cohorts. Unaffected relatives in the HLH cohort (n = 51) and individuals in the Immunodeficiency cohort (n = 645) were excluded from the analysis. Differences in allelic counts between HLH cases and controls (n = 5981) were tested by random sampling without replacement (100 000 iterations).

Figure 2. Features of clinical presentation correlate with genetic findings. (A) HLH-associated trigger by genetic profile. Primary triggers for the presenting HLH episode of 122 subjects were defined as infection (blue), malignancy (green), autoimmune disease (red), or no associated trigger (orange). A trigger was identified in 74% of subjects. (B) HLH-associated trigger by age at diagnosis. Subjects (n = 122) were separated into 4 groups by age in years (x-axis) and analyzed by HLH-triggering event. A two-sample test of proportions with a 95% confidence level for each comparison was used to analyze proportional differences in trigger by age. (C) HLH genetic profile by age at diagnosis. Subjects were placed into the same 4 groups by age in years (x-axis), excluding subjects with potential disease-causing variants in PIDD and DIAP genes (n = 3). A two-sample test of proportions with a 95% confidence level for each comparison was used to analyze proportional differences in genetic profile by age (total n = 119). (D) Biallelic fHLH variants are enriched in subjects younger than 1 year. A two-sample test of proportions with a 95% confidence level was used to analyze the proportional difference between fHLH cases diagnosed at younger than 1 year and older than 1 year of age (total n = 122).

Figure 3. Outcome data for HLH subject cohort (Kaplan-Meier survival curves). (A) Overall survival estimate from HLH diagnosis to date of death or last contact in years (n = 122). (B) Survival estimates from HLH diagnosis to date of death or last contact in years by genetic profile (total n = 119). (C) Survival estimates from HLH diagnosis to date of death or last contact in years by associated trigger (n = 122).

Figure 4. Proposed algorithm for testing of critically ill children. *Decision regarding further evaluation requires clinical judgment. **Strongly recommended in children younger than 1 year. Abbreviations: BIRC4, baculoviral inhibitor of apoptosis repeat-containing protein 4; SAP, signaling lymphocytic activation molecule-associated protein.