Dataset Information

F9 missense mutations impairing factor IX activation are associated with pleiotropic plasma phenotypes.

ABSTRACT:

Background

Circulating dysfunctional factor IX (FIX) might modulate distribution of infused FIX in hemophilia B (HB) patients. Recurrent substitutions at FIX activation sites (R191-R226, >300 patients) are associated with variable FIX activity and antigen (FIXag) levels.

Objectives

To investigate the (1) expression of a complete panel of missense mutations at FIX activation sites and (2) contribution of F9 genotypes on the FIX pharmacokinetics (PK).

Methods

We checked FIX activity and antigen and activity assays in plasma and after recombinant expression of FIX variants and performed an analysis of infused FIX PK parameters in patients (n = 30), mostly enrolled in the F9 Genotype and PK HB Italian Study (GePKHIS; EudraCT ID2017-003902-42).

Results

The variable FIXag amounts and good relation between biosynthesis and activity of multiple R191 variants results in graded moderate-to-mild severity of the R191C>L>P>H substitutions. Recombinant expression may predict the absence in the HB mutation database of the benign R191Q/W/K and R226K substitutions. Equivalent changes at R191/R226 produced higher FIXag levels for R226Q/W/P substitutions, as also observed in p.R226W female carrier plasma. Pharmacokinetics analysis in patients suggested that infused FIX Alpha distribution and Beta elimination phases positively correlated with endogenous FIXag levels. Mean residence time was particularly prolonged (79.4 h, 95% confidence interval 44.3-114.5) in patients (n = 7) with the R191/R226 substitutions, which in regression analysis were independent predictors (β coefficient 0.699, P = .004) of Beta half-life, potentially prolonged by the increasing over time ratio between endogenous and infused FIX.

Conclusions

FIX activity and antigen levels and specific features of the dysfunctional R191/R226 variants may exert pleiotropic effects both on HB patients' phenotypes and substitutive treatment.

SUBMITTER: Branchini A

PROVIDER: S-EPMC9298354 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background Factor IX (FIX) plays a critical role in blood coagulation. Complete deletion of F9 results in severe hemophilia B, whereas the clinical implications of complete F9 duplication and triplication remain understudied.Objective To investigate the rearrangement mechanisms underlying complete F9 deletion (cases 1 and 2), duplication (cases 3 and 4), and triplication (case 5), and to explore their association with FIX expression levels and clinical impacts.Methods Plasma FIX levels were detected using antigen and activity assays. CNVplex technology, optical genome mapping, and long-distance polymerase chain reaction were employed to characterize the breakpoints of the chromosomal rearrangements.Results Cases 1 and 2 exhibited FIX activities below 1%. Case 3 displayed FIX activities within the reference range. However, cases 4 and 5 showed a significant increase in FIX activities. Alu-mediated nonallelic homologous recombination was identified as the cause of F9 deletion in case 1; FoSTeS/MMBIR (Fork Stalling and Template Switching/microhomology-mediated break-induced replication) contributed to both F9 deletion and tandem duplication observed in cases 2 and 3; BIR/MMBIR (break-induced replication/microhomology-mediated break-induced replication) mediated by the same pair of low-copy repeats results in similar duplication-triplication/inversion-duplication (DUP-TRP/INV-DUP) rearrangements in cases 4 and 5, leading to complete F9 duplication and triplication, respectively.Conclusion Large deletions involving the F9 gene exhibit no apparent pattern, and the extra-hematologic clinical phenotypes require careful analysis of other genes within the deletion. The impact of complete F9 duplication and triplication on FIX expression might depend on the integrity of the F9 upstream sequence and the specific rearrangement mechanisms. Notably, DUP-TRP/INV-DUP rearrangements significantly elevate FIX activity and are closely associated with thrombotic phenotypes.

Project description:BackgroundMissense mutations in the first five exons of F9, which encodes factor FIX, represent 40% of all mutations that cause hemophilia B. To address the ongoing debate regarding in silico identification of disease-causing mutations at these exons, we analyzed 215 missense mutations from www.factorix.org using six in silico prediction tools, which are the most common used programs for analysis prediction of impact of mutations on the protein structure and function, with further advantage of using similar approaches. We developed different algorithms to integrate multiple predictions from such tools. In order to approach a structural analysis on FIX we performed a modeling of five selected pathogenic mutations.ResultsSIFT, PolyPhen-2 HumDiv, SNAP2, and MutationAssessor were the most successful in identifying true non-causative and causative mutations. A proposed function integrating these algorithms (wgP4) was the most sensitive (90.1%), specific (22.6%), and accurate (87%) than similar functions, and identified 187 variants as deleterious. Clinical phenotype was significantly associated with predicted causative mutations at all five exons. However, PolyPhen-2 HumDiv was more successful in linking clinical severity to specific exons, while functions that integrate 4-6 predictions were more successful in linking phenotype to genotypes at the light chain (exons 3-5). The most important value of integrating multiple predictions is the inclusion of scores derived from different approaches. Modeling of protein structure showed the effects of pathogenic nsSNPs on structure and function of FIX.ConclusionsA simple function that integrates information from different in silico programs yields the best prediction of mutated phenotypes. However, the specificity, sensitivity, and accuracy of genotype-phenotype predictions depend on specific characteristics of the protein domain and the disease of interest as we validated by the structural analysis of selected pathogenic F9 mutations. The proposed function integrating algorithm (wgP4) might be useful for the analysis of nsSNPs impact on other genes.