A. Pavlova

Genetic risk factors for inhibitors to factors VIII and IX.

Summary.  The formation of alloantibodies against factor VIII (FVIII) or factor IX (FIX) is the most severe complication of replacement therapy in patients with haemophilia. In the last decade, genetic factors have been shown to constitute a decisive risk determinant for the development of inhibitors. In severe haemophilia A and B, mutations that result in an absent or truncated FVIII/FIX protein are associated with a 20–80% risk of inhibitor formation. In mild to moderate haemophilia, missense mutations represent the main mutation type, with an inhibitor prevalence of 5%. These patients synthesize some endogenous, although non‐functional protein that is sufficient to induce immune tolerance. However, in patients with missense mutations clustered in the A2 and C2 domains (C1/C2 junction), the risk of inhibitor formation is fourfold greater than in patients with mutations outside this region, indicating that inhibitor prevalence in missense mutations is also dependent on localization of the mutation. Recently, a significant association between inhibitor formation and polymorphisms in genes coding for cytokines (IL‐10) and other immunoregulatory factors (TNF‐α) has been shown. These genetic factors constitute the individual genetic risk profile of a haemophilic patient. This risk is imprinted and fixed; however, environmental factors such as treatment schedule may increase or decrease the inhibitor risk in an individual patient. Improved understanding of these complex interactions may lead to the development of preventive measures to minimize inhibitor formation.

Impact of polymorphisms of the major histocompatibility complex class II, interleukin-10, tumor necrosis factor-alpha and cytotoxic T-lymphocyte antigen-4 genes on inhibitor development in severe hemophilia A.

Summary.  Background: Approximately 25% of severe hemophilia A (HA) patients develop antibodies to factor VIII protein. Patients: In the present case‐controlled cohort study, 260 severely affected, mutation‐type‐matched HA patients were studied for association of human leukocyte antigen (HLA) class II molecules and polymorphisms in the genes encoding interleukin‐10 (IL‐10), tumor necrosis factor‐α (TNF‐α) and cytotoxic T‐lymphocyte antigen‐4 (CTLA‐4) and development of inhibitors. Results: Our results demonstrate a higher frequency of DRB1*15 and DQB1*0602 alleles as well as of the haplotype DRB1*15/DQB1*0602 in inhibitor patients [odds ratio (OR) 1.9; P < 0.05]. In TNF‐α, the A allele of the −308G>A polymorphism was found with higher frequency in the inhibitor cohort (0.22 vs. 0.13, OR 1.80). This finding was more pronounced for the homozygous A/A genotype (OR 4.7). For IL‐10, the −1082G allele was observed more frequently in patients with inhibitors (0.55 vs. 0.43; P = 0.008). The functional cytokine phenotype was determined for the first time, on the basis of the genetic background, and this showed that 12% of patients with inhibitors were high‐TNF‐α/high‐IL‐10 producers, as compared with 3% of non‐inhibitor patients (OR 4.4). A trend for a lower frequency of the A allele of the CT60 polymorphism in CTLA‐4 was found in inhibitor patients (0.42 vs. 0.50). Conclusions: In conclusion, the reported data clearly highlighted the participation of HLA molecules in inhibitor formation in a large cohort of patients. The higher frequencies of the −308G>A polymorphism in TNF‐α and −1082A>G in IL‐10 in inhibitor patients confirmed the earlier published data. The CT60 single‐nucleotide polymorphism in CTLA‐4 is of apparently less importance.

The polygenic nature of inhibitors in hemophilia A: results from the Hemophilia Inhibitor Genetics Study (HIGS) Combined Cohort.

Studies of determinants of development of inhibitory Abs to factor VIII in people with hemophilia A indicate a complex process involving multiple factors. The Hemophilia Inhibitor Genetics Study (HIGS) Combined Cohort was formed to extend our understanding of the genetic background of risk. The study group contains 833 subjects from 3 independent cohorts: brother pairs and singletons with and without a history of inhibitors, as well as 104 brother pairs discordant for inhibitor status. Using an Illumina iSelect platform, 13 331 single-nucleotide polymorphisms from 1081 genes, primarily immune response and immune modifier genes, were typed. Each cohort was analyzed separately with results combined using a meta-analytic technique. After adjustment for potential confounders, 53 single-nucleotide polymorphisms were found to be significant predictors of inhibitor status using the criteria of odds ratios in the same direction in all cohorts or allowing for a 20% interval around an odds ratio = 1 in 1 of the 3 and significant in at least 2. Of the 53 markers, 13 had meta P < .001. Eight of the 53 were significant predictors among the discordant pairs. Results support the complexity of the immune response and encourage further research with the goal of understanding the pathways involved.

Molecular basis of antithrombin deficiency

Antithrombin (AT) is the most important physiological inhibitor of coagulation proteases. It is activated by glycosaminoglycans such as heparin. Hereditary antithrombin deficiency is a rare disease that is mainly associated with venous thromboembolism. So far, more than 200 different mutations in the antithrombin gene (SERPINC1) have been described. The aim of our study was to characterise the molecular background in a large cohort of patients with AT deficiency. Mutation analysis was performed by direct sequencing of SERPINC1 in 272 AT-deficient patients. Large deletions were identified by multiplex PCR coupled with liquid chromatography or multiplex ligation-dependent probe amplification (MLPA) analysis. To predict the effect of SERPINC1 sequence variations on the pathogenesis of AT deficiency, in silico assessments, multiple sequence alignment, and molecular graphic imaging were performed. The mutation profile consisted of 59% missense, 10% nonsense, 8% splice site mutations, 15% small deletions/insertions/duplications, and 8% large deletions. Altogether 87 different mutations, including 42 novel mutations (22 missense and 20 null mutations), were identified. Of the novel missense mutations, nine are suspected to impair the conformational changes that are needed for AT activation, two to affect the central reactive loop or the heparin binding site, and six to impair the structural integrity of the molecule. Despite the heterogeneous background of AT deficiency, 10 AT variants occurred in multiple index patients. Characterisation of the SERPINC1 mutation profile in large cohorts of patients may help to further elucidate the pathogenesis of AT deficiency and to establish genotype-phenotype associations.

Deficiencies of antithrombin, protein C and protein S – Practical experience in genetic analysis of a large patient cohort

Deficiencies of natural anticoagulant proteins including antithrombin (AT), protein C (PC) and protein S (PS) are important causes of inherited thrombophilia. This study aimed to report on the practical experience gained in performing genetic analyses of a large cohort of patients with AT, PC and PS deficiencies and to relate this knowledge to clinical application. We genotyped a large cohort of 709 unrelated patients with AT (231), PC (234) and PS (244) deficiencies referred to us by physicians throughout Germany. Mutations were detected by direct sequencing and multiplex ligation-dependent probe amplification (MLPA). The highest mutation detection rate (MDR) was found for the SERPINC1 gene (83.5%), followed by the PROC (69%) and PROS1 (43%) genes. Even at AT activities close to the normal range (75%), the MDR was 70%. Contrastingly, for PC and PS deficiencies, the MDR dropped significantly and mildly lowered to subnormal values. At PS activities >55% for PS no mutations were detected. Mutation profiles of all three genes were similar with the highest prevalence for missense mutations (63-78%), followed by nonsense (7-11%), splice-site mutations (7-13%), small deletions (1-8%), small insertions/duplications (1-4%) and large deletions (3-6%). In conclusion, genetic testing is a useful diagnostic tool for diagnosing thrombophilia. Based on our data, genetic analysis for patients with AT deficiency is indicated for all subnormal activities. In contrast, genotyping is not advisable for PC activities >70% and for PS activities >55%.

Molecular mechanisms underlying hemophilia A phenotype in seven females.

Summary.  Background: Hemophilia A (HA) in females is a rare observation. Here we describe various genetic mechanisms that result in phenotypic expression of HA in seven females. Methods: The F8 gene was examined in all patients and relatives by direct sequencing. Multiplex ligation‐dependent probe amplification (MLPA) was performed for large deletion screening. X chromosome inactivation was studied by PCR analysis of a polymorphic CAG repeat in the first exon of the human androgen receptor (HUMARA) gene. Results: In two females sequencing of the F8 gene revealed homozygous missense mutations (Arg593Cys and Tyr1680Phe) as a consequence of consanguineous marriage. The third case was due to compound heterozygosity comprising the missense mutation Leu412Phe inherited from the carrier mother, together with a de novo large deletion spanning exon 9–22, probably originating from the germ cells of the healthy father. Three further cases shared a common mechanism representing heterozygous mutations in the F8 gene (Arg1781His, Arg327His, small deletion in exon 10) combined with non‐random inactivation of the X chromosome. The final case describes a coincidental inheritance of HA and Coffin–Lowry syndrome in the same family. The HA phenotype results from a heterozygous small deletion affecting the F8 gene (c.6872 del CT leading to Thr2272fs) and a complete inactivation of the maternal X chromosome, which segregates with Coffin–Lowry syndrome in the two brothers of the proposita. Conclusions: In conclusion, molecular genetic analysis represents an essentially valuable tool in elucidating the nature of the molecular mechanisms underlying the HA phenotype in females.

F8 haplotype and inhibitor risk: results from the Hemophilia Inhibitor Genetics Study (HIGS) Combined Cohort.

Ancestral background, specifically African descent, confers higher risk for development of inhibitory antibodies to factor VIII (FVIII) in haemophilia A. It has been suggested that differences in the distribution of FVIII gene (F8) haplotypes, and mismatch between endogenous F8 haplotypes and those comprising products used for treatment could contribute to risk. Data from the Hemophilia Inhibitor Genetics Study (HIGS) Combined Cohort were used to determine the association between F8 haplotype 3 (H3) vs. haplotypes 1 and 2 (H1 + H2) and inhibitor risk among individuals of genetically determined African descent. Other variables known to affect inhibitor risk including type of F8 mutation and human leucocyte antigen (HLA) were included in the analysis. A second research question regarding risk related to mismatch in endogenous F8 haplotype and recombinant FVIII products used for treatment was addressed. Haplotype 3 was associated with higher inhibitor risk among those genetically identified (N = 49) as of African ancestry, but the association did not remain significant after adjustment for F8 mutation type and the HLA variables. Among subjects of all racial ancestries enrolled in HIGS who reported early use of recombinant products (N = 223), mismatch in endogenous haplotype and the FVIII proteins constituting the products used did not confer greater risk for inhibitor development. Haplotype 3 was not an independent predictor of inhibitor risk. Furthermore, our findings did not support a higher risk of inhibitors in the presence of a haplotype mismatch between the FVIII molecule infused and that of the individual.

Defining severity of hemophilia: more than factor levels.

Patients with severe hemophilia generally exhibit a severe bleeding phenotype with bleeding into joints or muscles at an early age. Although the severity and frequency of bleeding symptoms correlate with the residual factor VIII/IX (FVIII/IX) activity in the plasma, a considerable variability in bleeding pattern, FVIII/IX concentrate utilization, and joint damage has been observed. A subset of 10 to 15% of patients with severe hemophilia A shows a milder disease phenotype with significantly reduced frequencies of spontaneous bleeding and lower requirements for factor concentrate. This mitigated clinical phenotype is determined by the underlying mutations in the F8/F9 genes, genetic alterations and polymorphisms in other genes of the hemostasis system, differences in inflammatory and immune response genes, limitations in laboratory diagnostics, as well as environmental factors. Identification of disease-modifying factors in hemophilia may influence treatment decisions, such as starting and tailoring prophylaxis according to the specific clinical phenotype, rather than just the laboratory-defined degree of severity. This review focuses on the current information of factors mitigating the clinical presentation of hemophilia and contributing to its high phenotypic heterogeneity.

Increased frequency of the CTLA-4 49 A/G polymorphism in patients with acquired haemophilia A compared to healthy controls.

Summary.  Acquired haemophilia (AH) is an autoimmune disorder characterized by autoantibodies against endogenous factor VIII (FVIII). Half of the patients present with an underlying disease known to cause the FVIII autoantibodies whereas in the other half the disease is of idiopathic nature. Recently, it has been shown that variants of the polymorphic cytotoxic T lymphocyte antigen‐4 (CTLA‐4) gene are associated with autoimmune diseases and also represent a risk factor for inhibitor formation in inherited haemophilia A. In the present study, we investigated whether CTLA‐4 variants also play a role in the pathogenesis of AH. Therefore, we analyzed three single nucleotide polymorphisms (SNPs) of the CTLA‐4 gene (‐318 C/T, +49 A/G and CT60 A/G) in 57 AH patients and 98 controls. The CTLA‐4 + 49 G allele occurred with a significantly higher frequency in patients with AH compared with controls [odds ratio (OR) = 2.17, 95% confidence interval (CI): 1.36–3.48, P = 0.001]. This effect was mainly caused by a higher frequency of the 49 G allele in female patients (OR = 5.1, 95% CI: 1.76–15.02, P = 0.002), whereas in males the frequencies were not significantly different (OR = 1.4, P = 0.5). A higher frequency of the G allele was also observed in the subcohort with AH and underlying autoimmune disease (OR = 3.1, P = 0.04). Our observations of a higher frequency of the CTLA‐4 + 49 A/G SNP in AH patients are in concordance with findings in other autoimmune disorders. In conclusion, on the background of the CTLA‐4 gene polymorphism, further genetic and/or environmental factors might contribute to and finally trigger the clinical manifestation of AH.

Mutation distribution in the von Willebrand factor gene related to the different von Willebrand disease (VWD) types in a cohort of VWD patients

Von Willebrand disease (VWD) is the most common inherited bleeding disorder caused by quantitative or qualitative defects of the von Willebrand factor (VWF). VWD is classified into three types--type 1 (partial quantitative deficiencies), type 2 (qualitative defects) and type 3 (complete deficiency of VWF). In this study we explored genotype and phenotype characteristics of patients with VWD with the aim of dissecting the distribution of mutations in different types of VWD. One hundred fourteen patients belonging to 78 families diagnosed to have VWD were studied. Mutation analysis was performed by direct sequencing of the VWF . Large deletions were investigated by multiplex ligation-dependent probe amplification (MLPA) analysis. The impact of novel candidate missense mutations and potential splice site mutations was predicted by in silico assessments. We identified mutations in 66 index patients (IPs) (84.6%). Mutation detection rate was 68%, 94% and 94% for VWD type 1, 2 and 3, respectively. In total, 68 different putative mutations were detected comprising 37 missense mutations (54.4%), 10 small deletions (14.7%), two small insertions (2.9%), seven nonsense mutations (10.3%), five splice-site mutations (7.4%), six large deletions (8.8%) and one silent mutation (1.5%). Twenty-six of these mutations were novel. Furthermore, in type 1 and type 2 VWD, the majority of identified mutations (74% vs. 88.1%) were missense substitutions while mutations in type 3 VWD mostly caused null alleles (82%). Genotyping in VWD is a helpful tool to further elucidate the pathogenesis of VWD and to establish the relationship between genotype and phenotype.