Digenic and multigenic heterozygous FHL genotypes are common but clinically silent in the general population.

AbstractPrimary hemophagocytic lymphohistiocytosis (HLH) is mainly caused by biallelic variants in genes disrupting cytotoxic natural killer (NK) cell and T-cell function (PRF1, UNC13D, STX11, STXBP2, RAB27A, and LYST). A "pathway defect accumulation" model proposes that heterozygous variants in multiple familial hemophagocytic lymphohistiocytosis (FHL) genes (digenic or multigenic inheritance) may increase susceptibility, but its significance remains debated. We assessed the prevalence and clinical relevance of digenic/multigenic FHL genotypes in a German FHL cohort (1987-2023) and the UK Biobank (UKB; 469 589 participants). We analyzed (1) variants classified as disease mutations in the Human Gene Mutation database (HGMD); (2) common variants such as PRF1 p.Ala91Val and p.Asn252Ser; and (3) additional variants previously reported in digenic HLH and explored phenotypic associations using codes of the International Classification of Diseases, 10th Revision for possible HLH-related conditions. In the German cohort, among 635 individuals sequenced for >1 FHL gene, no symptomatic patient with abnormal NK/cytotoxic T-lymphocyte degranulation carried digenic/multigenic heterozygous variants. In UKB, 575 individuals carried digenic FHL genotypes (0.1% prevalence), without enrichment for HLH-associated phenotypes (odds ratio, 0.95; P = 1). Four individuals carried trigenic genotypes; none had HLH-related diagnoses. Several HGMD-labeled pathogenic variants were observed biallelically in asymptomatic adults, suggesting potential misclassification. Including PRF1 p.Ala91Val and p.Asn252Ser increased digenic variant carriers to 2590 but did not cause phenotype enrichment. Digenic heterozygous FHL variants are relatively common in the general population but do not confer increased FHL risk. Many reported pathogenic FHL variants may be benign. These findings argue against classifying multigenic heterozygous carriers as at risk and support integrating population data into variant interpretation.