Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2014 Feb 1.
Published in final edited form as: Br J Haematol. 2012 Dec 17;160(4):547–554. doi: 10.1111/bjh.12167

Erythrocyte Adenosine Deaminase: Diagnostic Value for Diamond-Blackfan Anaemia

John H Fargo 1,2, Christian P Kratz 1, Neelam Giri 1, Sharon A Savage 1, Carolyn Wong 3, Karen Backer 3, Blanche P Alter 1, Bertil Glader 3
PMCID: PMC3609920  NIHMSID: NIHMS422704  PMID: 23252420

Summary

Diamond-Blackfan anaemia (DBA) is an inherited bone marrow failure syndrome (IBMFS) characterized by red cell aplasia. Mutations in ribosomal genes are found in more than 50% of cases. Elevated erythrocyte adenosine deaminase (eADA) was first noted in DBA in 1983. In this study we determined the value of eADA for the diagnosis of DBA compared with other IBMFS; the association of eADA in DBA with age, gender or other haematological parameters; and the association with known DBA-related gene mutations. For the diagnosis of DBA compared with non-DBA patients with other bone marrow failure syndromes, eADA had a sensitivity of 84%, specificity 95%, and positive and negative predictive values of 91%. In patients with DBA there was no association between eADA and gender, age, or other haematological parameters. Erythrocyte ADA segregated with, as well as independent of, known DBA gene mutations. While eADA was an excellent confirmatory test for DBA, 16% of patients with classical clinical DBA had a normal eADA.

Keywords: Diamond-Blackfan anaemia, erythrocyte adenosine deaminase, ribosomopathy, bone marrow failure

Introduction

Diamond-Blackfan anaemia (DBA; Mendelian Inheritance in Man #105650) is a rare inherited bone marrow failure syndrome (IBMFS), with red cell aplasia (Diamond & Blackfan, 1938) and cancer predisposition (Shimamura & Alter, 2010, Vlachos et al, 2012). It is categorized as a ribosomopathy, because more than half of the patients have haploinsufficiency of either a small or large subunit-associated ribosomal protein (Vlachos et al, 2008). Nine mutated ribosomal genes have been identified: RPS19, RPL5, RPS26, RPL11, RPL35A, RPS10, RPS24, RPS7, and RPS17 (Boria et al, 2010). DBA is an autosomal dominant disorder with a high degree of clinical and genetic heterogeneity. The classical form of DBA has specific clinical and laboratory findings: presentation at age less than 1 year, macrocytic anaemia with no other significant cytopenias, reticulocytopenia, and normal bone marrow cellularity with a paucity of erythroid precursors (Diamond et al, 1976). Supporting criteria include: gene mutation described in “classical” DBA, positive family history, elevated erythrocyte adenosine deaminase (eADA), congenital anomalies involving the head, upper limbs, heart, and genitourinary system, and elevated haemoglobin F (Hb F) (Vlachos et al, 2008). However, clinical heterogeneity remains. About 15% are diagnosed at age >1 year, about 75% do not have a congenital anomaly (Shimamura & Alter, 2010), about 45% do not have a genetic mutation (Vlachos & Muir, 2010, Farrar et al, 2011), and elevated Hb F and macrocytosis are nonspecific and seen in other IBMFS (Shimamura & Alter, 2010).

Adenosine deaminase is an enzyme involved in purine salvage, which catalyses the irreversible deamination of adenosine to inosine and 2′ deoxyadenosine to 2′ deoxyinosine (Whitehouse et al, 1986). It was first noted to be significantly elevated in erythrocytes of patients with DBA in 1983 (Glader et al, 1983) and other studies thereafter (Whitehouse et al, 1984, Glader & Backer, 1988). The gene for ADA is located on chromosome 20q13.12. Despite this long history, the role of ADA in the pathophysiology of DBA remains unclear.

In this study, we investigated the diagnostic value of eADA in patients with Diamond-Blackfan anaemia compared with their relatives and with other (non-DBA) IBMFS patients and relatives. We also explored the association of eADA with gender, age, and other haematological parameters in patients with DBA, and examined the segregation of eADA with specific DBA-related gene mutations.

Methods

Participants were enrolled in the National Cancer Institute (NCI) Clinical Genetics Branch Inherited Bone Marrow Failure Syndromes protocol, NCI 02-C-0052 [NCT00027274] (www.marrowfailure.cancer.gov). The NCI IBMFS cohort is an open retrospective/prospective cohort, established in January 2002, with approval from the NCI Institutional Review Board. Data reported here include individuals enrolled prior to December, 2011. All participants or their guardians provided written informed consent in accordance with the Declaration of Helsinki.

The diagnosis of DBA was made if the patient met the criteria of: macrocytic, pure red cell aplasia with normal to hypocellular bone marrow with paucity of erythroid precursors, no evidence of another IBMFS, and/or the presence of a pathogenic mutation in a known DBA-related gene (Vlachos et al, 2008). Non-DBA patients were categorized according to criteria for a specific IBMFS. Fanconi anaemia (FA) was diagnosed by abnormal chromosome breakage in peripheral blood lymphocytes, using both diepoxybutane and mitomycin C (Cervenka et al, 1981, Auerbach et al, 1989). Skin fibroblasts were analysed when lymphocytes were normal but FA remained highly suspect (seeking evidence for haematopoietic mosaicism) (Alter et al, 2005). FA complementation group analyses were performed using retroviral correction (Chandra et al, 2005). The clinical diagnosis of dyskeratosis congenita (DC) was made in individuals with components of the diagnostic triad (nail dystrophy, reticular pigmentation, and oral leucoplakia), or those with at least one other typical physical finding (Vulliamy et al, 2006, Savage & Alter, 2009), in association with marrow failure. We expanded the criteria for DC to include patients with or without marrow failure, any of the above physical parameters, and blood leucocyte subset telomere lengths below the first percentile of normal-for-age (Alter et al, 2007, Alter et al, 2012). We also classified as “DC” those probands and healthy family members who had pathogenic mutations in known DC genes, such as DKC1, TERC, TERT, and TINF2, including those with none of the typical physical findings (Savage & Alter, 2009). Patients with Shwachman-Diamond syndrome (SDS) had neutropenia and exocrine pancreatic insufficiency, confirmed by detection of sub-normal levels of serum pancreatic trypsinogen and isoamylase (Ip et al, 2002, Rothbaum et al, 2002), and/or biallelic mutations in SBDS (Boocock et al, 2003). Individuals who could not be classified as having a specific IBMFS were designated as “Others.” Categories of “DC-like,” “FA-like,” and “SDS-like” were used for individuals whose features initially suggested DC, FA, or SDS but who failed to meet diagnostic criteria. DBA and non-DBA relatives were parents, siblings, and children who did not fit any of the criteria described above.

Bone marrow failure was defined according to clinical guidelines for the management of FA: severe, haemoglobin less than 80 g/l, absolute neutrophil count < 0.5 ×109/l, platelet count < 30 ×109/l, or on treatment; moderate, below normal for age but above the criteria for severe; or none, normal values for age. For single cytopenias, severe, on treatment; or moderate, below diagnostic values for the relevant lineage (Hb less than 2 standard deviations (SD) below the mean for age for anaemia, absolute neutrophil count < 1.5 ×109/l for neutropenia, platelet count < 140 ×109/l for thrombocytopenia) Eller et al, 2005). No subjects included in the study had a red blood cell transfusion within 6 months of the blood draw. Subjects were excluded if they had a haematopoietic stem cell transplant.

EADA was measured according to previously described standard methods (Glader et al, 1983). Normal and abnormal controls were run each time testing was performed. Normal control samples were from laboratory personnel not affected with DBA, stored at −70°C and discarded after one year. Abnormal controls were from known patients with DBA, stored at −70°C and discarded after 6 months. Mutations in genes for DBA, DC, FA, and SDS were identified by bidirectional sequencing of polymerase chain reaction-amplified fragments (GeneDX, Gaithersberg, MD, USA or Ambry Genetics, Viejo, CA, USA). Haematological parameter data included: haemoglobin (Hb), mean corpuscular volume (MCV), erythropoietin (Epo), and fetal haemoglobin (Hb F). Hb F was converted to absolute Hb F by multiplying the Hb F % by total Hb and expressed as g/l. Normal reference ranges for the individual haematological parameters are based on standards for age (Brugnara et al, 2009).

Analyses were performed using Microsoft Office Excel (2007 release) and StataSE11 (StataCorp Release 11, College Station, TX). Data are reported as odds ratio (OR) in favour of diagnosis of DBA, 95% confidence intervals (CI), sensitivity and specificity, and positive and negative predictive values (PPV and NPV) based on an elevated eADA greater than or equal to 1 international unit (iu)/g of Hb. This value was 3 SD above the mean of a historical, healthy control population established by Stanford University Medical Center (Glader et al, 1983). Statistical significance was determined by Fisher’s exact test for “Age”, binomial analysis for “Gender”, and Student t-test for “eADA” and “Haematological parameters.” P values are 2-sided; P < 0.05 was considered significant.

Results

There were a total of 198 subjects of whom 11 were excluded: 4 with DBA, 6 with DC, and 1 with FA-like. The remaining 187 subjects consisted of: 37 patients with DBA, 73 of their first-degree relatives; 21 with DC, 5 of their first-degree relatives; 20 with FA; 10 with SDS; 13 designated as “Other”, and 8 of their first-degree relatives (Table I). Those subjects designated as “Other” included: 2 with thrombocytopenia absent radii (TAR), 1 with severe congenital neutropenia, and 11 with unclassified but possibly inherited conditions designated by “like” [8 with DC-like, 2 with FA-like, and 1 with SDS-like]. These subjects were then classified into the 4 main study groups: DBA patients (n = 37), DBA relatives (n = 73), non-DBA patients [DC, FA, SDS, and Other] (n = 64), and non-DBA relatives (n = 13). Twelve DBA probands were studied with their families, while in 7 cases there were no family data available. In the non-DBA groups 23 probands were studied with their families, while 42 probands did not have any family data.

Table I.

Population characteristics

Patients Relatives
Diagnosis DBA FA DC SDS Other* Non-DBA DBA Non-DBA P1 P2 P3
 No. of patients 37 20 21 10 13 64 73 13
 Male: Female 19:18 5:15§ 17:4^§ 5:5 6:7 33:31 32:41 2:11§ 1 0.6 0.05
Age (years)
 median (range) 13 (2–58) 23.5 (4–56) 19 (3–46) 11.5 (5–42) 15 (3–37) 16 (3–56) 31 (1–62) 30 (3–64) 0.4 0.1 0.03
eADA level (iu/g of Hb)
 mean ± SD 1.58 ± 0.81 0.57 ± 0.27 0.56 ± 0.18 0.65 ± 0.25 0.59 ± 0.14 0.58 ± 0.21 0.61 ± 0.2 0.57 ± 0.15 <0.001 <0.001 <0.001
 median (range) 1.33 (0.65–4.62) 0.53 (0.17–1.41) 0.52 (0.36–1.07) 0.64 (0.37–1.23) 0.63 (0.38–0.85) 0.54 (0.17–1.41) 0.58 (0.26–1.49) 0.55 (0.37–0.93)
 No. of patients with eADA ≥ 1 iu/g of Hb (%) 31 (84) 1 (5) 1 (5) 1 (10) 0 (0) 3 (5) 5 (7) 0 (0) <0.001 <0.001 <0.001
Open in a new tab

DBA, Diamond-Blackfan anaemia; FA, Fanconi anaemia; DC, dyskeratosis congenita; SDS, Shwachman-Diamond syndrome; eADA, erythrocyte adenosine deaminase; Hb, haemoglobin.

*

Includes: FA-like, DC-like, SDS-like, thrombocytopenia absent radii, and severe congenital neutropenia.

P1: DBA vs. Non-DBA patients. P2: DBA vs. DBA relatives, P3: DBA vs. Non-DBA relatives.

^

When analysed on individual basis this is statistically different from DBA patients.

§

There is a statistically significant difference between number of males and females in this population

The male to female ratio of DBA patients was 1.1:1, non-DBA patients 1.1:1, DBA relatives 1.3:1, and non-DBA relatives 1:5.5 (Table I). The DBA patients were significantly younger than non-DBA relatives, but similar in age to non-DBA patients and DBA relatives.

The mean ± SD value for eADA for DBA patients, 1.58 ± 0.81 iu/g of Hb, was significantly elevated compared with all non-DBA patients (0.58 ± 0.21; P < 0.001), DBA relatives (0.61 ± 0.2; P < 0.001), and non-DBA relatives (0.57 ± 0.15; P < 0.001) (Table I). Thirty-one out of 37 (84%) DBA patients had an elevated eADA compared with 3 of 64 (5%) non-DBA patients, 5 of 73 (7%) DBA relatives, and 0 of 13 (0%) non-DBA relatives (Fig 1). Each of the 3 non-DBA patients with an elevated eADA had a different IBMFS diagnosis; 1 DC (1.07 iu/g of Hb), 1 FA (1.14 iu/g of Hb), and 1 SDS (1.23 IU/g of Hb). The patient with FA had mutations in FANCA and met criteria for myelodysplastic syndrome (MDS). The DC patient did not have a known DC gene mutation and the patient with SDS did not have mutations in SBDS. The patient with DC met criteria based on the presence of the clinical triad for DC. He had a severe variant, Hoyerall-Hreidarsson, which includes cerebellar hypoplasia, microcephaly, immunodeficiency, and intrauterine growth retardation. The patient with SDS met criteria with exocrine pancreatic insufficiency and intermittent neutropenia. None of the “Other” patients had an elevated eADA. The 5 DBA relatives who had an elevated eADA (from 3 separate families) did not have haematological findings or congenital anomalies consistent with the diagnosis of DBA. These DBA relatives did not have the DBA-related gene mutations present in the respective proband, removing non-penetrance as a confounding factor. None of the non-DBA relatives had an elevated eADA.

Figure 1. Comparison of eADA in the study population.

Figure 1

Open in a new tab

Symbols represent individual subjects within the patient groups. Bold horizontal axis line is the eADA upper limit of normal of 0.99 iu/g of Hb. “Total Non-DBA Patients” is the entire group, followed by individual classifications “DC”, “FA”, “SDS”, and “Other”. DBA, Diamond-Blackfan anaemia; eADA, erythrocyte adenosine deaminase; Hb, haemoglobin; DC, dyskeratosis congenita; FA, Fanconi anaemia; SDS, Shwachman-Diamond syndrome. Note that 1 each of DC, FA, and SDS, and 5 DBA relatives have an eADA above 1 iu/g of Hb.

We assessed the performance characteristics of eADA for diagnosing DBA in suspected patients (Table II). In the comparison of DBA patients with non-DBA patients, eADA was 84% sensitive, 95% specific, and both PPV and NPV were 91% (OR 105; 95% CI 21–632). In the comparison of DBA patients with DBA relatives, specificity was 93% and PPV 86% (OR 70; 95% CI 17–304). In contrast, comparison of DBA patients with the combination of non-DBA patients and relatives led to a specificity of 96% and NPV of 93% (OR 132; 95% CI 27–793).

Table II.

Performance characteristics of eADA in DBA patients vs. DBA relatives and Non-DBA patients and relatives

Increased eADA† Performance Characteristics
DBA patients DBA relatives Non-DBA patients Non-DBA patients and relatives OR 95% CI Sensitivity (%) Specificity (%) NPV (%) PPV (%)
31/37 5*/68 70 17–304 84 93 92 86
31/37 3/64 105 21–632 84 95 91 91
31/37 3/77 132 27–793 84 96 93 91
Open in a new tab

OR indicates odds ratio in favour of being a DBA patient; CI, confidence interval; NPV, negative predictive value; PPV, positive predictive value; DBA, Diamond-Blackfan anaemia; eADA, erythrocyte adenosine deaminase.

†

Data and number of patients of individuals with increased ADA/number analysed.

*

These individuals did not meet the diagnostic criteria of DBA as described in the methods section.

DBA patients with elevated eADA (n = 27) had Hb from 69 to 155 g/l, those with normal eADA (n = 6) had Hb from 85 to 14 g/l (Table III). After accounting for age, 10 (37%) of the DBA patients with elevated eADA were anaemic compared with 3 (50%) of those with a normal eADA. The extent and frequency of anaemia were not different (P = 0.66, Table III) and did not correlate with eADA). The MCV in DBA patients with elevated eADA (n = 27) ranged from 70 to 123 fl with a median of 97 fl, and in those with normal eADA (n = 6) from 89 to 106 fl with a median of 97 fl (Table III). Thirteen (48%) of those with elevated eADA were macrocytic compared with 3 (50%) of those with normal eADA; these were not different (P = 1, Table III) and did not correlate with eADA). Epo in patients with elevated eADA (n = 16) ranged from 8.6 to 559 mu/ml, and was 10–124 mu/ml in those with normal eADA (n = 4) (Table III). Nine (56%) with an elevated eADA had an Epo level > 25 mu/ml compared with 2 (66%) with a normal eADA; these were not different (P = 1, Table III) and did not correlate with eADA). The absolute Hb F in patients with elevated eADA (n = 24) ranged from 0 to 10 g/l and in those with normal eADA (n = 4) was 0 to 5.0 g/l (Table III). Twelve (50%) with an elevated eADA had a Hb F of > 1% compared with 1 (25%) with normal eADA; these were not different (P = 0.6, Table III) and the absolute Hb F did not correlate with eADA. In patients with DBA, there was no significant association between eADA and gender, age, or mutation status (data not shown).

Table III.

Haematological parameters of DBA patients with elevated vs. normal eADA*

Parameter eADA ≥ 1 iu/g of Hb eADA <1 iu/g of Hb P
Hb (g/l)
 No. of patients 27 6
 median (range) 123 (69–155) 118 (85–140) 0.44
 No. of patients anaemic (%)† 10 (37) 3 (50) 0.66
 Correlation coefficient 0.31
MCV (fl)
 No. of patients 27 6
 median (range) 97 (70–123) 97 (89–106) 0.95
 No. of patients macrocytic (%)† 13 (48) 3 (50) 1
 Correlation coefficient 0.32
Epo (mu/ml)
 No. of patients 16 4
 median (range) 28 (8.6–559) 33 (10–124) 0.56
 No. of patients with Epo >25 (%)† 9 (56) 2 (66) 1
 Correlation coefficient 0.5
Hb F
 No. of patients 24 4
 median (range) % 1.5 (0–12.5) 0.9 (0–4.1) 0.4
 median (range) g/l 2.0 (0–10) 1.0 (0–5.0) 0.4
 No. of patients with Hb F >1 % (%)† 12 (50) 1 (25) 0.6
 Correlation coefficient 0.34
Open in a new tab

DBA, Diamond-Blackfan anaemia; eADA, erythrocyte adenosine deaminase; Hb, haemoglobin; MCV, mean corpuscular volume; Epo, erythropoietin; Hb F, fetal haemoglobin.

*

Not every patient in the cohort had concurrent blood test results for haematological parameters.

†

Based on standards for age (Brugnara et al, 2009).

Twenty-two of 23 DBA patients with a mutation in a known DBA gene had elevated eADA (Fig 2); one patient with a known mutation in RPS19 had normal eADA (0.95 iu/g of Hb). “Unknown” patients (n = 14) are those with classical DBA in whom no DBA gene mutations have been identified. Among these 14 “Unknown” patients there were 4 probands without eADA data from family members: 2 of these patients had elevated eADA and 2 had normal eADA. There were 5 families with 1 clinically affected proband each; 3 of these probands had normal eADA. There was 1 family with 5 clinically affected individuals, all of whom had an elevated eADA (Fig 2). One of the 5 “Unknown” patients with a normal eADA was anaemic (Hb 109 g/l) and had elevated Epo (124.5 mu/ml) and HbF (4.1%); two were anaemic (Hb 89 and 85 g/l) and macrocytic (MCV 106 and 98.6 fl); the fourth was macrocytic (105 fl) and had elevated Epo (32.9 mu/ml) with steroid responsive anaemia; while the fifth patient had normal haematological parameters. The latter was diagnosed with DBA because of her position in the pedigree; she had an affected son and nephew. Compared with the “Unknown” patients, a significantly higher proportion of subjects with a known gene mutation had elevated eADA (P = 0.002).

Figure 2. Association of DBA gene mutation and eADA.

Figure 2

Open in a new tab

“Unknown”, those in whom no DBA gene mutations have been identified. Note that 1 patient with an RPS19 mutation and 5 patients with an unknown mutation have normal eADA.

Among the 23 DBA patients with a mutation in a known DBA gene there were 3 probands without gene mutation data from family members; 1 family with 9 patients with a mutation; 1 family with 3 patients; 2 families with 2 patients each; and 4 families with 1 patient each with a mutated gene. There were two distinct patterns of gene mutation and eADA. Elevated eADA segregated with DBA-related mutations in 5 families: RPL5, RPS7, RPS19 (2 families), and RPS24. Elevated eADA segregated independent of mutations in 3 families: RPL5, RPL11, and RPS24. In the example in Fig 3A, Family 168 had three affected members with RPS7 mutations; all had eADA ≥ 1 iu/g of Hb. The two unaffected, mutation-negative family members had normal eADA levels. In Fig 3B, Family 117 had one affected family member with an RPL11 mutation and elevated eADA; his mother and two of his siblings were unaffected, mutation-negative, and also had elevated eADA. The other two unaffected, mutation-negative family members had normal eADA levels.

Figure 3. eADA segregating with and independent of DBA gene mutation.

Figure 3

Figure 3

Open in a new tab

(A) In Family 168 eADA segregates with gene mutation and (B) in Family 117 eADA is independent of gene mutation. Shaded, subjects diagnosed with DBA. Arrow, eADA ≥ 1 iu/g of Hb. The measured eADA level and DBA gene mutation status are displayed below each subject. Wild type, targeted sequencing for the 9 known ribosomal gene mutations in DBA showed no abnormalities.

Discussion

In disorders with clinical and genetic heterogeneity, such as DBA, it is important to have criteria with significant diagnostic value. Erythrocyte adenosine deaminase has always been considered a supporting diagnostic criterion for DBA (Vlachos et al, 2008). The greatest value of eADA has been in its specificity in distinguishing DBA from other disorders, such as transient erythroblastopenia of childhood, acquired aplastic anaemia, acute lymphoblastic leukaemia, acute nonlymphoblastic leukaemia, and hereditary haemolytic anaemia (Glader et al, 1983, Glader & Backer, 1988).

We have now shown for the first time that eADA is specific for DBA in the context of a possible diagnosis of another IBMFS. The mean value of eADA was significantly higher than in any of the other marrow failure syndromes. With a cutoff of ≥ 1 iu/g of Hb, eADA was 95% specific for DBA compared with these other syndromes. A limited number of studies have shown other disorders to also be associated with elevated eADA, such as cartilage-hair hypoplasia (Sanchez-Corona et al, 1990), myelodysplastic syndromes (di Marco et al, 1992), paroxysmal nocturnal haemoglobinuria (di Marco et al, 1992), and acquired immunodeficiency syndrome (Cowan et al, 1986). As with the non-DBA IBMFS, each of these disorders has clinical features that distinguish them from the possible diagnosis of DBA. Our study did find elevated eADA in one individual each with FA, DC and SDS; the patients with DC and SDS did not have mutations in the known genes associated with the respective syndrome. Although this may raise the possibility of misclassification, both patients met other major diagnostic criteria and the subject with FA was confirmed as FANCA. The FA subject also had MDS, raising this as a possible aetiology for an elevated eADA. There were no MDS features in the DC or SDS subjects. The diagnostic value of eADA for DBA is strengthened by our finding that there was no correlation between eADA and age; eADA in young patients with DBA was similar to the oldest patients with DBA. Therefore, it remains important to utilize eADA when considering the diagnosis of DBA regardless of the age of the individual.

The sensitivity of eADA in distinguishing patients with DBA from non-DBA individuals suggests that eADA should remain a minor criterion in diagnosing DBA. A similar percentage, ranging from 82% to 96%, has been reported in European studies (Willig et al, 1998, Ramenghi et al, 1999, Orfali et al, 2004). Clearly, there is a cluster of individuals with DBA that have an unexplained normal eADA. We found 5 DBA patients with normal eADA and without a known DBA gene mutation. This was not related to gender or haematological parameters because DBA patients with an elevated eADA and those with a normal eADA had the same Hb, MCVs, Epo, and Hb F. We need a better understanding of why eADA is elevated in DBA in order to determine the reason why some DBA patients have an elevated eADA, while others are normal. We speculate that this difference might be due to genetic or epigenetic mechanisms involving genes for DBA or for ADA itself. One example is the discovery of X-linked GATA1 mutations resulting in DBA using exome sequencing (Sankaran et al, 2012). Two siblings described by Sankaran et al had normal eADA levels. The 5 DBA patients in our study with normal eADA consisted of 2 females and 3 males. One of the males was deceased and we did not have additional samples to test for a GATA1 mutation. One male does not fit an X-linked pattern of inheritance for his DBA. The third male is currently undergoing GATA1 mutation analysis.

Willig (Willig et al, 1998) first described eADA segregating with the RPS19 mutation. They found that in 6 families where DBA was associated with elevated eADA, 14 of 15 individuals had an RPS19 mutation. Thus, eADA segregated with the known DBA gene mutation. They concluded that an isolated elevation of eADA in an asymptomatic individual represented a silent carrier. Our study found a similar result in other DBA genotypes. We had 5 families where DBA was associated with a known DBA-related gene mutation, in which 16 of 17 individuals with a mutation had an elevated eADA. However, we had 3 families where DBA was associated with elevated eADA and the proband represented a de novo mutation. In these families, there were a total of 5 unaffected family members who had elevated eADA and were DBA gene wild type; eADA segregated independent of the gene mutation. It is unclear why their unaffected, wild type gene family members had an elevated eADA. It doesn’t appear to be associated with genotype because RPL5 and RPS24 mutations were present in families where eADA segregated with and independent of the gene mutations. Elevated eADA doesn’t appear to be related to alterations in haematological parameters because one subject had iron deficiency anaemia (98 g/l) with microcytosis (76 fL), RDW 17.9 %, ferritin 4 μg/l, and mildly elevated Epo (34.9 mu/ml); the remaining 4 had normal haematological parameters.

This is the first study looking at the diagnostic value of eADA in DBA compared with another IBMFS. All of the major IBMFS are represented in this study. A strength of the study is the confidence in IBMFS classification. After the patients and families are enrolled on the study, continuous updates on disease status and care are obtained. This longitudinal data gathering allows for adjustments in classification as additional information is supplied to the study. For example, a subject thought to have DBA who later is found to have transient erythroblastopenia of childhood would not be included in the analyses. Studying the IBMFS is difficult due to the rarity of their diagnoses; therefore another strength of this study is the large sample size for each individual syndrome. Additionally, there was a large sample of healthy, unaffected relatives of each disorder to serve as a comparative control population.

Although it may be a large sample size for rare syndromes, one of the limitations of this study is the small overall sample size. This is most evident in the analysis comparing the haematological parameter differences between DBA patients with an elevated versus normal eADA. Our use of individual families in studying the segregation patterns of eADA added a great deal of new information, but the small number of families available is also a limitation. Another limitation is the lack of a clear diagnosis for our non-DBA patients designated “Other.” Finally, the study lacks a concurrent healthy control population.

In conclusion, when considering DBA as a possible diagnosis, an elevated eADA strongly indicates DBA and, typically, associates with a DBA-related gene mutation; while a normal eADA does not exclude DBA. However, eADA occasionally segregates independent of a DBA-related gene mutation. In addition, in patients with DBA there is no statistically significant association between age, gender, and other haematological parameters.

Acknowledgments

We are grateful to all the patients who participate in the National Cancer Institute inherited bone marrow failure syndromes (IBMFS) cohort, to the physicians who referred the patients, and to our colleagues in the Clinical Genetics Branch of the NCI and the subspecialty clinics at the National Institutes of Health for their evaluations of the patients. We thank Lisa Leathwood, RN; Ann Carr, MS, CGC; Maureen Risch, RN and the other members of the IBMFS team at Westat, Inc. for their extensive efforts. This work was supported in part by the Intramural Program of the National Institutes of Health and the National Cancer Institute and by contracts N02-CP-11019, N02-CP-65504, and N02-CP-65501.

Footnotes

Authorship

Contributions: B.P.A., C.P.K, and B.G. developed the research idea. B.P.A, C.P.K and J.H.F analysed the data. B.G., C.W., and K.B. performed eADA assays. N.G. and S.A.S. personally examined and classified many of the participants. J.H.F. wrote the paper; all authors revised and checked the final version of the paper.

Conflict-of-interest: All authors declare no competing financial interests.

References

  1. Alter BP, Joenje H, Oostra AB, Pals G. Fanconi anemia: Adult head and neck cancer and hematopoietic mosaicism. Archives of Otolaryngology--Head & Neck Surgery. 2005;131:635–639. doi: 10.1001/archotol.131.7.635. [DOI] [PubMed] [Google Scholar]
  2. Alter BP, Baerlocher GM, Savage SA, Chanock SJ, Weksler BB, Willner JP, Peters JA, Giri N, Lansdorp PM. Very short telomere length by flow fluorescence in situ hybridization identifies patients with dyskeratosis congenita. Blood. 2007;110:1439–1447. doi: 10.1182/blood-2007-02-075598. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Alter BP, Rosenberg PS, Giri N, Baerlocher GM, Lansdorp PM, Savage SA. Telomere length is associated with disease severity and declines with age in dyskeratosis congenita. Haematologica. 2012;97:353–359. doi: 10.3324/haematol.2011.055269. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Auerbach AD, Ghosh R, Pollio PC, Min Z. Diepoxybutane (DEB) test for prenatal and postnatal diagnosis of Fanconi anemia. In: Schroeder TM, Auerbach AD, Obe G, editors. Fanconi Anemia Clinical Cytogenetic and Experimental Aspects. Springer-Verlag; Heidelberg: 1989. pp. 71–82. [Google Scholar]
  5. Boocock GR, Morrison JA, Popovic M, Richards N, Ellis L, Durie PR, Rommens JM. Mutations in SBDS are associated with Shwachman-Diamond syndrome. Nature Genetics. 2003;33:97–101. doi: 10.1038/ng1062. [DOI] [PubMed] [Google Scholar]
  6. Boria I, Garelli E, Gazda HT, Aspesi A, Quarello P, Pavesi E, Ferrante D, Meerpohl JJ, Kartal M, Da Costa L, Proust A, Leblanc T, Simansour M, Dahl N, Frojmark AS, Pospisilova D, Cmejla R, Beggs AH, Sheen MR, Landowski M, Buros CM, Clinton CM, Dobson LJ, Vlachos A, Atsidaftos E, Lipton JM, Ellis SR, Ramenghi U, Dianzani I. The ribosomal basis of Diamond-Blackfan anemia: Mutation and database update. Human Mutation. 2010;31:1269–1279. doi: 10.1002/humu.21383. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Brugnara C, Oski FA, Nathan DG. Disorders of erythrocyte production. In: Orkin SH, Nathan DG, Ginsburg D, Look AT, Fisher DE, Lux SE IV, editors. Nathan and Oski’s Hematology of Infancy and Childhood. 7. WB Saunders; Philadelphia, PA: 2009. p. 1774. [Google Scholar]
  8. Cervenka J, Arthur D, Yasis C. Mitomycin C test for diagnostic differentiation of idiopathic aplastic anemia and Fanconi anemia. Pediatrics. 1981;67:119–127. [PubMed] [Google Scholar]
  9. Chandra S, Levran O, Jurickova I, Maas C, Kapur R, Schindler D, Henry R, Milton K, Batish SD, Cancelas JA, Hanenberg H, Auerbach AD, Williams DA. A rapid method for retrovirus-mediated identification of complementation groups in Fanconi anemia patients. Molecular Therapy: The Journal of the American Society of Gene Therapy. 2005;12:976–984. doi: 10.1016/j.ymthe.2005.04.021. [DOI] [PubMed] [Google Scholar]
  10. Cowan MJ, Brady RO, Widder KJ. Elevated erythrocyte adenosine deaminase activity in patients with acquired immunodeficiency syndrome. Proceedings of the National Academy of Sciences of the United States of America. 1986;83:1089–1091. doi: 10.1073/pnas.83.4.1089. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. di Marco P, Tinnirello D, Tambone-Reyes M, Tedesco L, Luna S, Citarella P. Biologic relevance of elevated red cell adenosine deaminase activity in myelodysplastic syndromes and paroxysmal nocturnal hemoglobinuria. Tumori. 1992;78:370–373. doi: 10.1177/030089169207800604. [DOI] [PubMed] [Google Scholar]
  12. Diamond LK, Blackfan KD. Hypoplastic anemia. American Journal of Diseases of Children. 1938;56:464–466. [Google Scholar]
  13. Diamond LK, Wang WC, Alter BP. Congenital hypoplastic anemia. Advances in Pediatrics. 1976;22:349–378. [PubMed] [Google Scholar]
  14. Eiler M, Frohnmayer D, Frohnmayer L, Larsen K, Owen J. Fanconi anemia: Standards for clinical care. Fanconi Anemia Research Fund, Inc; Eugene, OR: 2005. [Google Scholar]
  15. Farrar JE, Vlachos A, Atsidaftos E, Carlson-Donohoe H, Markello TC, Arceci RJ, Ellis SR, Lipton JM, Bodine DM. Ribosomal protein gene deletions in Diamond-Blackfan anemia. Blood. 2011;118:6943–6951. doi: 10.1182/blood-2011-08-375170. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Glader BE, Backer K. Elevated red cell adenosine deaminase activity: A marker of disordered erythropoiesis in Diamond-Blackfan anaemia and other haematologic diseases. British Journal of Haematology. 1988;68:165–168. doi: 10.1111/j.1365-2141.1988.tb06184.x. [DOI] [PubMed] [Google Scholar]
  17. Glader BE, Backer K, Diamond LK. Elevated erythrocyte adenosine deaminase activity in congenital hypoplastic anemia. New England Journal of Medicine. 1983;309:1486–1490. doi: 10.1056/NEJM198312153092404. [DOI] [PubMed] [Google Scholar]
  18. Ip WF, Dupuis A, Ellis L, Beharry S, Morrison J, Stormon MO, Corey M, Rommens JM, Durie PR. Serum pancreatic enzymes define the pancreatic phenotype in patients with Shwachman-Diamond syndrome. The Journal of Pediatrics. 2002;141:259–265. doi: 10.1067/mpd.2002.125849. [DOI] [PubMed] [Google Scholar]
  19. Orfali KA, Ohene-Abuakwa Y, Ball SE. Diamond-Blackfan anaemia in the UK: Clinical and genetic heterogeneity. British Journal of Haematology. 2004;125:243–252. doi: 10.1111/j.1365-2141.2004.04890.x. [DOI] [PubMed] [Google Scholar]
  20. Ramenghi U, Garelli E, Valtolina S, Campagnoli MF, Timeus F, Crescenzio N, Mair M, Varotto S, D’Avanzo M, Nobili B, Massolo F, Mori PG, Locatelli F, Gustavsson P, Dahl N, Dianzani I. Diamond-Blackfan anaemia in the Italian population. British Journal of Haematology. 1999;104:841–848. doi: 10.1046/j.1365-2141.1999.01267.x. [DOI] [PubMed] [Google Scholar]
  21. Rothbaum R, Perrault J, Vlachos A, Cipolli M, Alter BP, Burroughs S, Durie P, Elghetany MT, Grand R, Hubbard V, Rommens J, Rossi T. Shwachman-Diamond syndrome: Report from an international conference. The Journal of Pediatrics. 2002;141:266–270. doi: 10.1067/mpd.2002.125850. [DOI] [PubMed] [Google Scholar]
  22. Sanchez-Corona J, Garcia-Cruz D, Medina C, Cantu JM, Ramos-Zepeda R, Rivas F. Increased adenosine deaminase activity in a patient with cartilage-hair hypoplasia. Annales De Genetique. 1990;33:99–102. [PubMed] [Google Scholar]
  23. Sankaran VG, Ghazvinian R, Do R, Thiru P, Vergilio JA, Beggs AH, Sieff CA, Orkin SH, Nathan DG, Lander ES, Gazda HT. Exome sequencing identifies GATA1 mutations resulting in Diamond-Blackfan anemia. The Journal of Clinical Investigation. 2012;122:2439–2443. doi: 10.1172/JCI63597. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Savage SA, Alter BP. Dyskeratosis congenita. Hematology/Oncology Clinics of North America. 2009;23:215–231. doi: 10.1016/j.hoc.2009.01.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Shimamura A, Alter BP. Pathophysiology and management of inherited bone marrow failure syndromes. Blood Reviews. 2010;24:101–122. doi: 10.1016/j.blre.2010.03.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Vlachos A, Muir E. How I treat Diamond-Blackfan anemia. Blood. 2010;116:3715–3723. doi: 10.1182/blood-2010-02-251090. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Vlachos A, Ball S, Dahl N, Alter BP, Sheth S, Ramenghi U, Meerpohl J, Karlsson S, Liu JM, Leblanc T, Paley C, Kang EM, Leder EJ, Atsidaftos E, Shimamura A, Bessler M, Glader B, Lipton JM Participants of Sixth Annual Daniella Maria Arturi International Consensus Conference. Diagnosing and treating Diamond-Blackfan anaemia: Results of an international clinical consensus conference. British Journal of Haematology. 2008;142:859–876. doi: 10.1111/j.1365-2141.2008.07269.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Vlachos A, Rosenberg PS, Atsidaftos E, Alter BP, Lipton JM. Incidence of neoplasia in Diamond-Blackfan anemia: A report from the Diamond-Blackfan anemia registry. Blood. 2012;119:3815–3819. doi: 10.1182/blood-2011-08-375972. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Vulliamy TJ, Marrone A, Knight SW, Walne A, Mason PJ, Dokal I. Mutations in dyskeratosis congenita: Their impact on telomere length and the diversity of clinical presentation. Blood. 2006;107:2680–2685. doi: 10.1182/blood-2005-07-2622. [DOI] [PubMed] [Google Scholar]
  30. Whitehouse DB, Hopkinson DA, Evans DI. Adenosine deaminase activity in Diamond-Blackfan syndrome. Lancet. 1984;2:1398–1399. doi: 10.1016/s0140-6736(84)92092-0. [DOI] [PubMed] [Google Scholar]
  31. Whitehouse DB, Hopkinson DA, Pilz AJ, Arredondo FX. Adenosine deaminase activity in a series of 19 patients with the Diamond-Blackfan syndrome. Advances in Experimental Medicine and Biology. 1986;195(Pt A):85–92. doi: 10.1007/978-1-4684-5104-7_14. [DOI] [PubMed] [Google Scholar]
  32. Willig TN, Perignon JL, Gustavsson P, Gane P, Draptchinskaya N, Testard H, Girot R, Debre M, Stephan JL, Chenel C, Cartron JP, Dahl N, Tchernia G. High adenosine deaminase level among healthy probands of Diamond-Blackfan anemia (DBA) cosegregates with the DBA gene region on chromosome 19q13. The DBA working group of societe d’immunologie pediatrique (SHIP) Blood. 1998;92:4422–4427. [PubMed] [Google Scholar]

RESOURCES