Noémi B. A. Roy

Cardiac iron overload in transfusion-dependent patients with myelodysplastic syndromes

Transfusion‐dependent myelodysplastic (MDS) patients are prone to iron overload. We evaluated 43 transfused MDS patients with T2* magnetic resonance imaging scans. 81% had liver and 16·8% cardiac iron overload. Liver R2* (1000/T2*), but not cardiac R2*, was correlated with number of units transfused (r = 0·72, P < 0·0001) and ferritin (r = 0·53, P < 0·0001). The area under the curve of a time‐ferritin plot was found to be much greater in patients with cardiac iron loading (median 53·7 × 105 Megaunits vs. 12·2 × 105 Megaunits, P = 0·002). HFE, HFE2, HAMP or SLC40A1 genotypes were not predictors of iron overload in these patients.

A novel 33-Gene targeted resequencing panel provides accurate, clinical-grade diagnosis and improves patient management for rare inherited anaemias.

Accurate diagnosis of rare inherited anaemias is challenging, requiring a series of complex and expensive laboratory tests. Targeted next‐generation‐sequencing (NGS) has been used to investigate these disorders, but the selection of genes on individual panels has been narrow and the validation strategies used have fallen short of the standards required for clinical use. Clinical‐grade validation of negative results requires the test to distinguish between lack of adequate sequencing reads at the locations of known mutations and a real absence of mutations. To achieve a clinically‐reliable diagnostic test and minimize false‐negative results we developed an open‐source tool (CoverMi) to accurately determine base‐coverage and the ‘discoverability’ of known mutations for every sample. We validated our 33‐gene panel using Sanger sequencing and microarray. Our panel demonstrated 100% specificity and 99·7% sensitivity. We then analysed 57 clinical samples: molecular diagnoses were made in 22/57 (38·6%), corresponding to 32 mutations of which 16 were new. In all cases, accurate molecular diagnosis had a positive impact on clinical management. Using a validated NGS‐based platform for routine molecular diagnosis of previously undiagnosed congenital anaemias is feasible in a clinical diagnostic setting, improves precise diagnosis and enhances management and counselling of the patient and their family.

The role of X-inactivation in the gender bias of patients with acquired α-thalassaemia and myelodysplastic syndrome (ATMDS)

Αlpha thalassaemia myelodysplastic syndrome (ATMDS) is an unusual complication of chronic myeloid malignancy that is associated with a striking red cell phenotype. It represents an acquired form of α‐thalassaemia that most commonly arises in the context of myelodysplasia. It has recently been shown that this condition occurs in association with somatic mutations of a known X‐encoded trans‐acting regulator of α globin gene (HBA) expression, ATRX. There is an unexplained, strong male preponderance of individuals with the ATMDS phenotype with a >5:1 male–female ratio and furthermore, all the somatic ATRX mutations described to date have been in males. Here we report the identification, in a single centre, of two females with ATMDS and mutations in the ATRX gene, proving that ATMDS associated with such mutations may occur, albeit rarely, in females. It seemed possible that females might be less likely to develop ATMDS if the inactivated copy of the ATRX gene (ATRX) became progressively re‐activated throughout life. This study ruled out this hypothesis by investigating the pattern of ATRX inactivation in a cross‐sectional analysis of normal females at ages ranging from newborn to 90 years.

Serum hepcidin potentially identifies iron deficiency in survivors of critical illness at the time of hospital discharge

Anaemia is common in patients admitted to and discharged from intensive care (ICU) and is associated with poor quality of life in ICU survivors (Walsh et al, 2010; Lasocki et al, 2014). The majority of ICU patients will have an anaemia of inflammation (AI) as a collective result of functional iron deficiency, leading to iron restricted erythropoiesis, increased cytokine production, suppressed bone marrow activity and reduced red blood cell life span (Lasocki et al, 2010). Identifying iron deficiency in this context is challenging because commonly used tests, such as ferritin and transferrin saturation, are significantly confounded by inflammation. Hepcidin is a circulating polypeptide, which, via its inhibitory action on the key iron exporter ferroportin, acts as a key regulator in iron homeostasis (Girelli et al, 2016). Inhibition of ferroportin results in retention of iron within enterocytes, macrophages and hepatocytes with a consequent decrease in serum iron levels, thereby restricting its availability for erythropoiesis. Hepcidin expression is increased by inflammation and iron overload but reduced in iron deficiency, hypoxia and enhanced erythropoietic drive. Elevated hepcidin levels restricting the use of iron, along with suppressed bone marrow function, may partly explain why trials of iron supplementation in the acute phase of critical illness have not shown any benefit (Litton et al, 2016; Shah et al, 2016). Hepcidin may be a better marker of iron deficiency (or requirement for iron) than the routine biochemical assays in current use, allowing more precise identification of anaemic patients likely to respond to iron therapy (Girelli et al, 2016). In order to identify a potential cohort of patients who would probably respond [i.e. increase haemoglobin (Hb) concentration] to iron supplementation, we investigated the utility of serum hepcidin concentrations of ICU survivors at hospital discharge. Patients recruited to the RECOVER (Evaluation of a Rehabilitation Complex Intervention for Patients Following Intensive Care Discharge) trial and who consented to a biomarker sub-study were eligible (Walsh et al, 2015). RECOVER was a randomized controlled trial examining the effect of a complex rehabilitation package on physical outcome in ICU survivors. Laboratory tests recorded included Hb concentration, serum creatinine, albumin and C-reactive protein (CRP). Serum hepcidin was measured by enzyme-linked immunosorbent assay (ELISA) (hepcidin-25 high sensitivity ELISA, DRG Instruments, Marburg, Germany). Other markers of iron status and erythropoiesis, such as ferritin, serum iron, transferrin saturation (Tsat), soluble transferrin receptor (sTfR), erythropoietin, vitamin B12 and folate, were also analysed. Anaemia was defined according to World Health Organization (WHO) guidelines: males Hb <130 g/l and females Hb <120 g/l. A ferritin cut-off of <15 lg/l was used to diagnose iron deficiency anaemia (WHO, 2001). In the presence of inflammation (defined as CRP >8 mg/l), a ferritin cut-off of 150 lg/l was used to differentiate between combined anaemia of iron deficiency and inflammation (IDI) (ferritin <150 lg/l) and AI (ferritin >150 lg/l) as previous reported (Lee et al, 2002). Baseline characteristics are shown in Table 1. Median (interquartile range, IQR) CRP for the entire cohort was 36 (15–72) mg/l, reflecting ongoing inflammation even at hospital discharge. 110/117 (94%) patients were anaemic with a CRP of >8 mg/l prior to hospital discharge. Of these, 89/110 (81%) had AI and 11/110 (10%) had IDI (Table 2). 10 patients developed anaemia that appeared unrelated to iron, B12, and/or folate deficiency or inflammation. Laboratory results are shown in Table 2. Median (IQR) serum hepcidin concentration was significantly lower in the IDI group and there was no statistical difference in CRP concentrations between both groups, indicating the difference in hepcidin values may not reflect a higher level of inflammation in the AI group. Levels of the sTfR-ferritin index, another potential marker of iron deficiency in inflammation, were higher in the IDI group and linear regression of (log) sTfR-ferritin index with (log) hepcidin showed a strong association (co-efficient 0 8, P < 0 001). There were no significant differences in age, illness severity, Hb and renal function between both groups. The maximal Youden index was achieved at a hepcidin cut-off of <19 ng/ml, with a sensitivity of 73% and specificity of 74%. Using current definitions of iron deficiency, 11/110 patients would be considered eligible for oral iron replacement. Applying a hepcidin cut-off <19 ng/ml, a further 24 patients would be included, raising this to 32% of the anaemic cohort. This study has confirmed a high prevalence of anaemia at time of hospital discharge in ICU survivors (Walsh et al, 2010). While inflammatory processes are still active in this patient group, as evidenced by the raised median CRP in the correspondence

Unexpected haemophilia despite pre-natal testing - a combined haemophilia A and haemophilia B family

Prenatal diagnosis for at-risk male fetuses of haemophilia carriers is useful to families for planning of delivery. However, high sensitivity and specificity detection techniques cannot account for all eventualities. Here, individual I.1 with haemophilia A had two daughters, both obligate carriers for his mutation in F8 c.5557G>A, (amino acid change p.Ala1853Thr). Daughter II.4 had a son (III.2), confirmed with severe haemophilia A [factor VIII (FVIII) levels < 0 01 iu/ml] and hemizygosity for p.Ala1853Thr. Upon her second pregnancy, pre-natal diagnostic testing by chorionic villus sampling confirmed an unaffected male fetus (wild type F8). However, at birth, this boy (III.3) had a prolonged activated partial thromboplastin time and a factor IX (FIX) level of <0 01 iu/ml. Genetic analysis revealed a mutation in F9 c.1331A>C (amino acid change p.Tyr444Ser). I.2 and II.4 were then confirmed carriers for this mutation, with FVIII and FIX levels consistent with heterozygosity for each of the mutations in II.4. This chance association of independent genetic changes in both F8 and F9 highlights the need to consider alternative causes of bleeding disorders in families with one known genetic alteration if this cannot explain the phenotype of all affected individuals. Interestingly, the mutation p.Ala1853Thr has been reported as causing mild, moderate and severe haemophilia A on the European Association for Haemophilia and Allied Disorders database (http:// www.factorviii-db.org/).

Using serum hepcidin to identify iron deficiency in previously critically ill patients at time of hospital discharge

Introduction: Over the last 25 years there has been significant work carried out in producing risk prediction models for patients admitted to critical care units. The most recent of these models is the Intensive Care National Audit and Research Centre (ICNARC) model developed in 2007 (1) which uses data from 231,930 admissions to 163 critical care units to develop and validate a UK based model outperforming other approaches (with an average c index of 0.863). Aims: This research aims to present an artificial neural network based model for critical care admissions that improves over the ICNARC model in terms of the discrimination across the data set used in this study. Results: Figure 1 shows a comparison between the receiver operator characteristics (ROC) curve for our artificial neural network (ANN) model and the ICNARC model presented in (1). This figure shows the ROC curve and point-wise confidence intervals for the true positive values of both our model (in blue) and the ICNARC model (in red). In comparison, our artificial neural network classification model produces an average c value of 0.8983 in 10 fold cross validation of our data compared to a c value of 0.8306 for the ICNARC model using the same data set (consisting of 642 patients admitted to North Middlesex Hospital critical care unit over a 28 month period. Data excludes 432 patients where data was incomplete). Conclusion: Our classification model provides a percentage risk score that outperforms the ICNARC model. This classification model does suffer from some of same issues surrounding the ICNARC model – for instance, the influence of some of the parameters within both models can be unclear to clinicians trying to predict the survival of individual patients. However, further work is ongoing to improve the transparency of this model