Genotyping of the rs1800440 Polymorphism in CYP1B1 Gene and the rs9258883 Polymorphism in HLA-B Gene in a Spanish Cohort of 223 Patients with Frontal Fibrosing Alopecia.

The pathogenesis of frontal fibrosing alopecia has been linked to specific genetic variants. CYP1B1 codes for a component of the cytochrome p450 machinery that is involved in the metabolism of xenobiotic oestrogens. The study of the prevalence of polymorphisms in this gene may help to understand their role in the development of frontal fibrosing alopecia. The aim of this study is to describe the frequency of genetic variations in the alleles HLA-B*07:02 and CYP1B1 in patients with frontal fibrosing alopecia. A cross-sectional study was designed to evaluate blood samples from patients with frontal fibrosing alopecia who attended the Dermatology Department at University Hospital Ramón y Cajal (Madrid, Spain), in search of the polymorphisms rs9258883 and rs1800440 in the alleles HLA-B*07:02 and CYP1B1, respectively. A total of 223 patients were included in the study. Among the 83.8% of patients who carried the rs9258883 polymorphism in HLA-B*07:02, 58.7% were heterozygous for this variant and it was not present in 14.8% of the cases. The majority of patients with frontal fibrosing alopecia lacked the protective rs1800440 polymorphism in CYP1B1 (75.2%). This suggests a relevant role of this variant in development of frontal fibrosing alopecia. The genetic approach to this condition might influence patient prognosis and therapy options.

Development and validation of a sequential two-step algorithm for the screening of individuals with potential polycythaemia vera.

In 2016, the WHO included haemoglobin values within normal ranges as a diagnostic criterion for Polycythaemia Vera (PV). Since then, concerns have arisen that a large number of patients are undergoing unnecessary screening for PV. To address this issue, we estimated the prevalence of JAK2 p.V617F in individuals with elevated haemoglobin or haematocrit and developed and validated a screening algorithm for PV. A total of 15,366 blood counts performed in seven non-consecutive days were reviewed, of which 1001 were selected for subsequent JAK2 p.V617F mutation screening. Eight (0.8%) new JAK2 p.V617F-mutated cases were detected. From ROC curves, a two-step algorithm was developed based on the optimal cut-off for the detection of the JAK2 p.V617F mutation. The algorithm was prospectively validated in an independent cohort of 15,298 blood counts. A total of 1595 (10.4%) cases met the criterion for haemoglobin or haematocrit, of whom 581 passed to step 2 (3.8% of the total). The JAK2 p.V617F mutation was detected in 7 of the 501 patients tested, which accounts for 0.04% of the total cohort and 0.4% of patients with erythrocytosis. In conclusion, this data show that our two-step algorithm improves the selection of candidates for JAK2 p.V617F testing.