Fanconi anemia (FA) is caused by pathogenic variants in the FA/BRCA DNA repair pathway genes, and is characterized by congenital abnormalities, bone marrow failure (BMF) and increased cancer risk. We conducted a genotype-phenotype and outcomes study of 203 patients with FA in our cohort. We compared across the genes, FA/BRCA DNA repair pathways (upstream, ID complex and downstream), and type of pathogenic variants (hypomorphic or null). We explored differences between the patients evaluated in our clinic (clinic cohort) and those who provided data remotely (field cohort). Patients with variants in upstream complex pathway had less severe phenotype [lacked VACTERL-H (Vertebral, Anal, Cardiac, Trachea-esophageal fistula, Esophageal/duodenal atresia, Renal, Limb, Hydrocephalus) association and/or PHENOS (Pigmentation, small-Head, small-Eyes, Neurologic, Otologic, Short stature) features]. ID complex was associated with VACTERL-H. The clinic cohort had more PHENOS features than the field cohort. PHENOS was associated with increased risk of BMF, and VACTERL-H with hypothyroidism. The cumulative incidence of severe BMF was 70%, solid tumors (ST) 20% and leukemia 6.5% as the first event. Head and neck and gynecological cancers were the most common ST, with further increased risk after hematopoietic cell transplantation. Among patients with FANCA, variants in exons 27-30 were associated with higher frequency of ST. Overall median survival was 37 years; patients with leukemia or FANCD1/BRCA2 variants had poorest survival. Patients with variants in the upstream complex had better survival than ID or downstream complex (p=0.001 and 0.016, respectively). FA is phenotypically and genotypically heterogeneous; detailed characterization provides new insights towards understanding this complex syndrome and guiding clinical management.
Fanconi anemia (FA), a predominantly autosomal recessive genomic instability disorder, is the most common inherited bone marrow failure (BMF) syndrome. FA is characterized by hypersensitivity to DNA cross-linking agents, specific congenital abnormalities, progressive BMF and predisposition to cancer, particularly head and neck squamous cell carcinomas and acute myeloid leukemia (AML).1,2 Pathogenic variants in at least 22 genes have been identified in the FA/BRCA DNA repair pathway which functions to remove DNA interstrand crosslinks. The involved genes are grouped according to their function in the pathway as upstream (FANC-A, B, C, E, F, G, L, M and T), ID (FANC-I and D2) and downstream complexes (FANC-D1, J, N, O, P, Q, R, S, U, V and W).3-5
Guido Fanconi reported the first cases of FA in 1927 in three brothers with microcephaly, short stature, skin hyperpigmentation, microorchidism and macrocytic anemia.6 Many other abnormalities affecting multiple organ systems have since been defined. Approximately 40% of FA cases have no physical abnormalities.7 Congenital anomalies commonly seen in FA are included in the VACTERL-H association (Vertebral abnormalities, Anal atresia, Cardiac abnormalities, Tracheo-esophageal fistula, Esophageal or duodenal atresia, Renal abnormalities, upper Limb abnormalities and Hydrocephalus).8 We recently grouped six other common FA features into the acronym PHENOS (skin Pigmentation abnormalities, small Head, small Eyes, structural central Nervous system abnormalities, Otologic abnormalities and Short stature), and found that patients with three or more of the eight VACTERL-H features frequently had four or more PHENOS features.9 BMF in FA usually develops during the first decade of life and varies from mild to severe cytopenias requiring hematopoietic cell transplantation (HCT), or progression to myelodysplastic syndrome (MDS) or AML.10 Endocrine, metabolic and reproductive abnormalities have been reported in approximately 80% of patients11 and may be due to the syndrome and/or the treatment.
Cohort studies investigating genotype-phenotype associations in FA have mostly been limited by patient numbers, and the findings across studies were not always consistent due to the rarity of the syndrome and population differences.12-16 Specific early cancers were reported in patients with pathogenic variants in FANCD1/BRCA2 and FANCN/PALB2.17-19
Our group previously reviewed the genotype-phenotype associations in FA from literature cases.7 We now explore genotype-phenotype and outcome associations in patients with FA enrolled in the National Cancer Institute (NCI) inherited BMF syndrome cohort according to the FA genes, mutation pathways and the type of pathogenic variants. We also investigate differences between the patients followed in the field versus those seen in our clinic. We hypothesized that there would be differences in phenotypes, hematologic, oncological, and endocrine outcomes between patients enrolled in the field cohort and those seen in our clinic.
Patients with FA were enrolled in the NCI Institutional Review Board-approved inherited BMF syndrome cohort study (clinicaltrials.gov identifier: NCT00027274) from January 2002 through November 2020. Participants and/or their proxies signed written consent and medical record release forms. All individuals were initially enrolled in the “Field Cohort” (FC) and completed individual information questionnaires. A subset of patients was then evaluated at the National Institutes of Health Clinical Center and formed the “Clinic Cohort” (CC) (Figure 1A).2 Data on all participants (FC and CC) were abstracted from the individual information questionnaires, biennial follow-up forms, medical records, and National Institutes of Health evaluations (for CC participants).
FA was diagnosed by an abnormal chromosomal breakage test and confirmed by genetic testing when possible. Physical abnormalities were grouped as VACTERL-H, PHENOS and Other. The VACTERL-H association was defined by the presence of three or more of the eight features, and PHENOS as four or more of the six features. Other physical findings are described in Online Supplementary Table S1. Phenotypes not stated as present were considered absent.
BMF was defined by the presence of cytopenia for age20 and categorized as non-severe or severe (Table 1). Diagnoses of MDS, AML and solid tumors were based on the review of medical records, personal or proxy reports. Endocrine, metabolic, and gonadal problems including hormone deficiencies, low bone mineral density, diabetes mellitus, insulin resistance, dyslipidemia, abnormal body mass index, and infertility, were recorded.
The genetic variants were annotated using ANNOVAR,21 BayesDel22 and Human Splicing Finder.23 Variants were classified according to the 2015 American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines24 with the modifications specified in the legend of Online Supplementary Table S2.
Frameshift, nonsense, start loss or deletion of four or more nucleotides and splice site variants that were predicted to cause mis-splicing were classified as null. Missense, in-frame insertion/deletion and splice site variants causing a protein change were classified as hypomorphic. Patients with bi-allelic null variants were grouped as having a “null” genotype, and those with one or both hypomorphic variants as having a “hypomorphic” genotype.
Since FANCA was the most frequently affected gene, we investigated phenotype and outcome associations in patients with FANCA variants, focusing on the location of variants on the FANCA protein (Figure 1B). FANCA variants were plotted using ProteinPaint.25 Patients with one or both variants in (i) the BRCA1 interaction region, (ii) the FAAP20-binding domain, and (iii) exons 27-30 (where we observed a clustering of variants), were compared with patients without variants in these regions.
Analyses were performed using Stata 16 (StataCorp. TX, USA) and RStudio (RStudio, Boston, MA, USA). A two-sided Fisher exact test was used for frequency comparisons, the Mann-Whitney U test was used for continuous variables; P-values less than 0.05 were considered statistically significant. The Bonferroni correction was applied for multiple comparisons. Cox regression models were used to estimate relative risks of clinical outcomes; weighted Cox models were used when the proportional hazards assumption was violated, and average hazard ratios (AHR) are reported. A competing risk analysis for cumulative incidences of first adverse events (BMF leading to HCT or death, leukemia or solid tumors) was performed as described previously.26 Survival probabilities were calculated by the Kaplan-Meier method in the absence of competing risks with censoring at last follow-up; the log-rank test was used for comparisons.
The FA cohort included 203 patients, 146 in the FC and 57 in the CC (Figure 1A). Phenotype information was not available for seven FC participants. The genotype was known for 54 patients in the CC and 110 patients in the FC; for 19 patients in the FC, only the complementation groups were known, but no gene variants were reported. Demographics and clinical characteristics are summarized in Table 1. The sex distribution was similar in the FC and CC (P=0.4) with more females than males in each cohort. The median age at diagnosis of FA was 5.4 years and the median age at study enrollment was 11.2 years with no significant difference between the cohorts. The FC was younger than the CC at last follow-up with median ages of 15.7 and 25.2 years, respectively (P<0.001). Most patients self-reported as white in both cohorts.
FANCA was the most frequently affected gene, observed in 98 patients. Fifty-three patients with FANCA had one or bi-allelic variants within or involving the BRCA1 interaction region of the FANCA protein, 21 had variants involving the FAAP20-binding domain and 45 had variants involving the region of exons 27-30 (Figure 1B). Patients with variants in FANCA accounted for 45% of the FC and 56% of the CC, followed by those with variants in FANCC, who accounted for 12% and 16%, respectively (Figure 2A). More than 80% of the variants were in the upstream complex in both cohorts (Figure 2B). Genotypes were similarly distributed as hypomorphic or null in both the FC and CC among the 142 patients with available molecular diagnoses (Figure 2C). The hypomorphic genotype was more common in FANCA (P=0.006) and the null genotype was more common in FANCC (P<0.001) (Online Supplementary Figure S1).
Physical abnormalities were identified in 133 of 139 (95.7%) FC and all CC patients (Figure 1). The VACTERL-H association (≥3/8 features) was present in 23% of the FC and 35% of the CC (P=0.1). Vertebral abnormalities were more often recognized in CC patients (P<0.001). Other VACTERLH features were identified at similar frequencies in both cohorts (Figure 3). The most common abnormalities were upper limb (60%) and renal (35-37%) and the least common (<10%) were tracheo-esophageal fistula, hydrocephalus, and anal atresia (Figure 3).
PHENOS features (≥4/6) were present in 56% of the CC and 33% of the FC (P=0.004). The most common findings were skin pigmentation abnormalities (68% in the FC, 82% in the CC; P=0.04), followed by small eyes (52% in the FC, 82% in the CC; P<0.001). Structural central nervous system abnormalities were detected more often in the CC than in the FC (P<0.001). Other physical findings not part of VACTERL-H or PHENOS were also more common in the CC (Figure 3). VACTERL-H plus PHENOS was more frequent in the CC (31.6% vs. 16.7%, P=0.02) and neither VACTERL-H nor PHENOS was more frequent in the FC (60.1% vs. 40.4%, P=0.03) (Figure 3).
Physical abnormalities according to the gene, mutation pathway, and type of pathogenic variant
Phenotype comparison across FA genes after Bonferroni correction revealed significant associations. All gene-spe-cific associations were isolated to either the FC or the CC, as the number of patients in each cohort varied (Table 2A). Patients with variants in the upstream complex pathway were least likely to have neurodevelopmental abnormalities, VACTERL-H association, or the presence of at least one of VACTERL-H or PHENOS in both the FC and the CC (P=0.01, P<0.001 and P<0.001, respectively). Variants in the ID complex were associated with VACTERL-H and most physical abnormalities in FC patients (Table 2B). The hypomorphic genotype was associated with upper limb abnormalities in the FC (Table 2C).
BMF developed in 170/198 patients (86%) at a median age of 6.6 years in the combined FC and CC (Table 1). Twenty-eight percent of patients were dependent on transfusions and 24% received androgen therapy in either cohort. None of the four patients with FANCD1/BRCA2 had cytopenia. Cytogenetic abnormalities were reported in 40.4% of the CC and 18.3% of the FC patients (P=0.03). MDS was reported in 27 patients at a median age of 15 years (range, 9.9-24.2) and AML in eight patients at a median age of 19 years (range, 12-60). A total of 103 (51%) patients received HCT with the frequency being similar in the FC and CC; 75.3% for severe BMF, 22.7% for cytogenetic abnormalities or MDS and 2% for AML.
A weighted multiple Cox regression model for BMF included 133 patients with available data and excluded the four patients with FANCD1/BRCA2 due to lack of BMF. The analysis identified a higher risk of BMF in males than in females (AHR=1.65, 95% confidence interval [95% CI]: 1.1-2.6). The presence of PHENOS predicted a higher risk of BMF than absence (AHR=2.9, 95% CI: 1.7-4.95). Compared with patients with FANCA, patients with FANCC, G, I and J had a higher risk of BMF by the same age (Online Supplementary Table S3A). A weighted Cox regression model for MDS that included 138 patients with available data showed that patients with FANCC (AHR=4.7, 95% CI: 1.55-14.4) and FANCD1/BRCA2 gene variants (AHR=61, 95% CI: 4.4-848.9) were at higher risk of MDS than patients with FANCA (Online Supplementary Table S3B). The increased risk of MDS in FANCD1/BRCA2 was based on one out of the four patients with FANCD1/BRCA2 who received HCT for a diagnosis of hypocellular MDS associated with cytogenetic changes without antecedent pancytopenia.
Endocrine, metabolic, and reproductive outcomes
Approximately 30% of the FC and 42% of the CC developed hypothyroidism at a median age of 7.2 and 13.9 years (P=0.005), respectively. Hypothyroidism predated HCT in 64% of cases. A weighted multiple Cox regression model for 139 patients with available data showed an increased risk of hypothyroidism in patients with prior HCT (AHR=11.1, 95% CI: 4.3-28.4), VACTERL-H association (AHR=4.7, 95% CI: 1.92-11.2), and variants in FANCD1, D2, G, I and J (Online Supplementary Table S4A).
Osteoporosis was more often reported in the CC than in the FC (P=0.049); median age was 23 years in both cohorts. Growth hormone deficiency was reported in 28.6% of the CC and 18% of the FC patients and it was associated with HCT in 10% of cases. Diabetes mellitus developed in 17% of the FC and 10.5% of the CC; 11/23 of these patients had treatment-induced diabetes, 5/23 had type 1 diabetes and 7/23 had type 2 diabetes. Overall, 57% of patients with available data had insulin resistance, 38.7% had abnormal body mass index (19.6% were underweight, 11.7% overweight and 7.4% obese), and 14% had metabolic syndrome.
We previously described obstetric outcomes in seven women with FA.27 We now report 26 pregnancies in 14 women resulting in 20 live births (Online Supplementary Table S5). The median age at first pregnancy was 25 years (range, 19-32 years). Ten patients were FANCA cases; notably, four of these patients had hypomorphic c.3624C>T (p.Ser1208=) synonymous variants and five had a null genotype. The FA gene was unknown for four patients. A Cox regression analysis showed that patients with milder phenotype (no VACTERL-H or PHENOS) were more likely to become pregnant (HR=7.3, 95% CI: 1.003-52.9); prior HCT and the presence or severity of BMF were not significant predictors (Online Supplementary Table S4B).
Forty-eight of 196 patients (24.4%) developed at least one malignancy; eight had leukemia, 36 had solid tumors and 11 had skin cancers. Head and neck squamous cell carcinoma was the most common solid tumor and developed at a median age of 34.4 years. The second most common was vulvar cancer, which developed at a median age of 29.3 years (Table 3).
Competing risk analyses of first adverse events showed a similar cumulative incidence of severe BMF leading to HCT or death in the FC (72%) and CC (67%) by the age of 60 years. Solid tumors developed in 18% of the FC and 24% of the CC by age 60 (P=0.7). The cumulative incidence of leukemia was 6% in the FC and 2.5% in the CC by age 30; one patient in the FC developed AML in his 60s (Online Supplementary Figure S2). By the age of 70, the cumulative incidences of severe BMF, solid tumors and leukemia were 70.4%, 19.8% and 6.5%, respectively, in the combined cohort (Figure 4A). Patients who underwent HCT had an increased risk of solid tumors with a hazard ratio of 4.6 (95% CI: 2.2-9.8) for transplanted versus non-transplanted patients (Figure 4B).
Solid tumors were seen in patients with FANCA, FANCC and FANCD1 variants. Brain tumors were exclusive to FANCD1/BRCA2 and developed at a median age of 3.1 years. Head and neck squamous cell carcinomas and vulvar/cervical cancers in patients with FANCA and FANCC variants were seen with both hypomorphic and null genotypes. All four patients with esophageal cancer had FANCA null genotype. FA genes for four of the eight leukemia patients were unknown; one had FANCA and three had FANCC (Online Supplementary Figure S3).
Further analysis of data from 86 patients with FANCA pathogenic variants showed a significant association of solid tumors with variants within/involving exons 27-30. Fifteen of 45 patients (33.3%) with one or both single nucleotide variants/small insertion-deletions within exons 27-30 or multi-exon deletions covering this region developed solid tumors compared to three of 41 patients (7.3%) without a variant in this region (P=0.003). A Cox model adjusting for HCT status showed that patients with any pathogenic variant within/involving exons 27-30 appeared to have a higher risk of solid tumors (HR=6.2, 95% CI: 1.36-28.2) than patients without variants in this region, with a cumulative incidence of 60% versus 25% by age 40 (Figure 4C). Phenotypes, BMF, endocrine outcomes and age at first cancer were not different. Cancer outcomes were similar among patients with either a single variant or both variants within exons 27-30. Individual variants are shown in Figure 4D.
Overall survival data were available for 200 patients. The median survival age was 37 years (95% CI: 34.7-43.1); 81% of patients were older than 18 years at last follow-up (Figure 5A). Patients with leukemia had a poorer survival (median age 17.7 years; range, 12.1-27.3) than patients with no leukemia (after exclusion of the patient who developed AML in his 60s) (Figure 5B).
The median survival of patients with FANCA variants was 43.4 years (95% CI: 36.5-49.5) and that of patients with FANCC variants was 32.6 years (95% CI: 24.4-not available). Patients with FANCD1/BRCA2 variants had the poorest survival (median 4.3 years) (Figure 5C). Patients with variants in upstream complex genes had a better survival (median survival age 39 years) than patients with variants in ID or downstream complex genes (P=0.001 and P=0.016, respectively) (Figure 5D). Survival among patients with hypomorphic or null genotype was similar (Figure 5E).
This study of a large cohort of patients with FA provides a detailed assessment of physical abnormalities and clinical outcomes in relation to FA genes, mutation pathways and type of pathogenic variants.
(A) Overall survival. The median survival age was 37 years, shown by the red line. (B) Survival according to the presence or absence of adverse events. The adverse event groups compared were: no hematopoietic cell transplantation (HCT) or cancer (orange), HCT only (khaki), leukemia (green), solid tumor only (blue), and both HCT and solid tumor (purple). (C) Survival according to the gene involved. Genes involved in fewer than ten patients were grouped as other genes, except for FANCD1/BRCA2 (blue) with four patients. (D) Survival according to FA/BRCA DNA repair pathway: upstream (orange), ID (green), and downstream (blue). (E) Survival according to the type of pathogenic variant: null group (red) and hypomorphic group (blue). Survival curves were estimated using the Kaplan-Meier method. Comparisons between groups were made by the logrank test, P-values were adjusted using the Benjamini-Hochberg method for multiple comparisons.
Almost all patients in our cohort (96.9%) had at least one physical abnormality; this is a higher percentage than in previous reports (60-90%).7,28,29 We corroborated our earlier findings of a higher frequency of VACTERL-H association in FA than that described in the literature cases.7, 9 VACTERL-H features that cause functional compromise (cardiac anomaly, tracheo-esophageal fistula, esophageal, duodenal or anal atresia) or those that are generally recognized in early life (upper limb and renal abnormalities) were present at similar rates in the CC and FC participants. Vertebral anomalies and structural central nervous system abnormalities whose detection requires imaging procedures were more frequently identified in the CC because baseline skeletal survey and brain magnetic resonance imaging are part of the systematic evaluations of CC participants. Other PHENOS features such as skin pigmentary changes and small eyes, which may escape recognition if not specifically looked for, were more often identified in the CC. Likewise, PHENOS (≥4/6 features) and PHENOS plus VACTERL-H (≥3/8 features) were more common in the CC and proportions in both cohorts were higher than in cases reported in the literature.7 This underscores the need for all patients with FA to have a full dysmorphology evaluation upon diagnosis.
Our findings of milder phenotype in patients with upstream complex pathway variants, with less likelihood of VACTERL-H or PHENOS, is mainly a reflection of inclusion of patients with FANCA and FANCC variants who had fewer physical abnormalities than patients with variants in other gene groups. Consistent with the review of the literature cases, variants in the ID complex pathway were associated with a more severe phenotype (VACTERL-H) in both cohorts and the presence of at least one of VACTERL-H or PHENOS in the FC.7 However, unlike the literature cases, we found no significant association of VACTERL-H and severe phenotype with null genotype.7 The results from the FC were more comparable with the literature cases, but data from the CC provided a more complete picture of the FA phenotype. The discrepancies between the literature cases and the NCI cohort are likely due to lack of variant details and phenotypes in patients within these groups and may be overcome by the development of a standardized approach for systematic evaluation of all individuals with FA. This will facilitate international and trans-institutional comparisons, risk stratification, and genotypephenotype and outcome assessment of patients with this rare syndrome.
We identified a higher risk of BMF in patients with PHENOS (≥4/6) whereas VACTERL-H (≥3/8) was not a significant predictor of BMF. We previously noted abnormal radii as the strongest predictor of early BMF and developed a congenital abnormality score (CABS; between 0-5 based on the number of abnormalities in five categories: developmental delay, heart or lung, kidney, hearing and small head) to distinguish prognostic groups in patients with normal radii.30 The data from the German FA registry31 and the Israeli FA cohort29 indicated that CABS was a strong risk factor for BMF. Notably, two of the features of PHENOS (hearing and small head) are included in CABS. Studies incorporating PHENOS (≥4/6) or individual PHENOS features in prediction models may help in estimating BMF risk stratification and pre-emptive transplant decisions in FA.32
The risk of MDS was increased in our patients with FANCC and FANCD1/BRCA2 compared with FANCA (Online Supplementary Table S3). The increased risk of MDS in FANCD1/BRCA2 should be interpreted with caution as it was based on a single patient with hypocellular MDS. The cumulative incidence of AML as the first event as well as the median age at AML were similar to prior estimates.1,2,14 Clonal cytogenetic abnormalities and MDS were previously reported in FANCA, C, D1/BRCA2 and G groups.33,34 Frequent bone marrow evaluations in these groups may detect clonal changes and dysplasia earlier. Chromosomal aberrations and other somatic events in the genome may have prognostic importance and be clues to clonal hematopoiesis.33,35,36 Longitudinal studies characterizing somatic variants are needed to understand how variants drive clonal hematopoiesis in FA and their association with leukemogenesis, as identified in Shwachman Diamond syndrome.37
The frequencies of endocrine, metabolic and reproductive abnormalities were similar to those in earlier reports.11,27,38,39 We confirmed endocrine and metabolic disturbances as long-term complications following HCT in FA patients, as previously described.40,41 The relationship between VACTERL-H, FA genes and hypothyroidism needs further study to be fully elucidated. Recently, dysregulated tryptophan metabolism and hyperserotonemia were proposed as mechanisms of metabolic disturbances in FA.42 Larger studies with broader representation of various FA gene groups may provide mechanistic insights and identify gene-specific associations in metabolism. We noted that four of the ten women with FANCA variants who became pregnant had the c.3624C>T synonymous variant which causes aberrant splicing.43 It is possible that some residual protein function may be present with this variant and is sufficient for patients to conceive. Functional analysis of this variant will be important to understand its in vivo effect on FANCA protein.
Here we updated cumulative incidence estimates of cancer.2 The cumulative incidence of solid tumors as the first event was similar to our earlier estimates, and confirmed the increased risk of solid tumors in transplanted patients.2,26 The most common solid tumors were head and neck squamous cell carcinomas and gynecological cancers followed by esophageal cancers (all esophageal cancers were in patients with null FANCA variants) (Online Supplementary Figure S3). Brain tumors remained exclusive to the FANCD1/BRCA2 group. Despite the severe phenotype observed in the FANCD2 group, these patients were not at an increased risk of BMF compared with those in the FANCA group and did not develop cytogenetic abnormalities, MDS or cancer. In our cohort, among five patients with the c.2444G>A FANCD2 variant, two had early BMF and four had VACTERL-H plus PHENOS, in contrast with the report by Kalb et al.44 in which mild phenotype and adult-onset BMF were described with this variant. This may be due to differences in the second allele affecting outcomes. Further study of patients with this recurrent variant may uncover a unique phenotype in this group.
An interesting and novel finding from our study was the high frequency of solid tumors in patients with one or both FANCA variants within/involving the region of exons 27-30 when compared with that in patients who had no FANCA variant within/involving this region. The exon 27-30 region is within the C-terminal domain of the protein. FANCA forms a homodimer interacting through the C-terminal domain to function and the C-terminal domain is crucial for nuclear localization of FANCA.45,46 After our data were locked in November 2020, we became aware of an additional patient in our cohort who has developed a head and neck squamous cell carcinoma; this patient has a FANCA variant within the exon 27-30 region. Collaborative studies with more patients are needed to further investigate the relevance of this finding. Functional analysis of variants in this region and other variants in trans would also provide insights into carcinogenesis in FA and may have implications for personalized cancer screening. We observed a significant variant heterogeneity in FANCA, whereas many variants were recurrent in FANCC and FANCD2. This could explain the complexity of establishing genotype-phenotype correlations in FA but may not be the only reason. Phenotypes and outcomes varied greatly even between affected siblings. With regard to this, we observed three FA patients with bi-allelic variants in one FA gene and a third variant in another FA gene. Investigating how additional variants contribute to disease may explain differences between patients with the same disease-causing FA variants. Tomaszowski et al. hypothesized that FA is a polygenic disease demonstrating a FA phenotype with different affected FA genes.47 Studies on the combined effect of variants in FA and/or non-FA genes, as well as epigenetic regulations are needed.
Most patients reached adulthood, with the median survival being 37 years, similar to that in our prior report.2 Patients with FANCA and FANCC variants had better survival than those with variants in other genes. Variants in the upstream complex pathway were associated with better survival. Patients with leukemia had the poorest survival. The outcomes of FA patients with AML has improved with improvements in HCT regimens and clinical care, although the overall survival remains around 40-50% and treatment toxicities and relapse rates are high.48,49
In summary, we have reported detailed phenotypes and outcomes in a large, prospectively followed FA cohort, consisting of both children and adults. We found significant differences between the FC and the CC. We were limited by patient and family reports on some outcomes and genotype data. Medical records for the FC were not as complete as those for the CC. There may be recent complications of which we were not aware, especially for FC patients as some had old records and may be less engaged with the study. Variant classification was based on the existing literature and in silico predictions. More data and functional studies of variants may reveal further information.
Comprehensive investigations of physical phenotypes and clinical outcomes in centers experienced with FA will enhance our knowledge of FA, and increase the possibility of using phenotypes and genotypes to stratify risks of outcomes. Follow-up studies investigating finer molecular associations will provide opportunities for tailored risk estimates, surveillance strategies and treatment plans.
- Received September 13, 2021
- Accepted February 23, 2022
No conflicts of interest to disclose.
BA, NG, LJM and BPA designed the study, and established and curated the dataset; BA, NG, LJM, AB and BPA contributed to the methodology; NG, LJM and BPA provided supervision; BA, NG and BPA analyzed and interpreted the data and drafted the manuscript; all authors contributed to revising the manuscript and approved the submitted version.
De-identified clinical and genetic data are available, upon reasonable request, from Neelam Giri
This research was supported in part by the intramural research program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, and by contract HHSN261201700004C with Westat, Inc.
The authors are grateful to Dr. Jung Kim for her input on variant evaluation, Drs. Philip Rosenberg and Marena Niewisch for their suggestions regarding cumulative incidence analyses, Dr. Maryam Rafati for her input on patients with unknown genotype and the research team at Westat Inc. for their help with medical records review and logistics. The authors would like to acknowledge the DCEG Cancer Genomics Research Laboratory Sequencing Group for providing whole exome sequencing data. We thank all participating patients and families who made this study possible, as well as referring clinicians for their contributions.
- Shimamura A, Alter BP. Pathophysiology and management of inherited bone marrow failure syndromes. Blood Rev. 2010; 24(3):101-122. https://doi.org/10.1016/j.blre.2010.03.002PubMedPubMed CentralGoogle Scholar
- Alter BP, Giri N, Savage SA, Rosenberg PS. Cancer in the National Cancer Institute inherited bone marrow failure syndrome cohort after fifteen years of follow-up. Haematologica. 2018; 103(1):30-39. https://doi.org/10.3324/haematol.2017.178111PubMedPubMed CentralGoogle Scholar
- Kottemann MC, Smogorzewska A.. Fanconi anaemia and the repair of Watson and Crick DNA crosslinks. Nature. 2013; 493(7432):356-363. https://doi.org/10.1038/nature11863PubMedPubMed CentralGoogle Scholar
- Taylor AMR, Rothblum-Oviatt C, Ellis NA. Chromosome instability syndromes. Nat Rev Dis Primers. 2019; 5(1):64. https://doi.org/10.1038/s41572-019-0113-0PubMedGoogle Scholar
- Datta A, Brosh RM Jr. Holding all the cards -how Fanconi anemia proteins deal with replication stress and preserve genomic stability. Genes (Basel). 2019; 10(2):170. https://doi.org/10.3390/genes10020170PubMedPubMed CentralGoogle Scholar
- Fanconi G. Familiäre infantile perniziosaartige Anämie (perniziöses Blutbild und Konstitution). Jahrbuch Kinder. 1927; 117:257-280. Google Scholar
- Fiesco-Roa MO, Giri N, McReynolds LJ, Best AF, Alter BP. Genotype-phenotype associations in Fanconi anemia: a literature review. Blood Rev. 2019; 37:100589. https://doi.org/10.1016/j.blre.2019.100589PubMedPubMed CentralGoogle Scholar
- Solomon BD, Baker LA, Bear KA. An approach to the identification of anomalies and etiologies in neonates with identified or suspected VACTERL (vertebral defects, anal atresia, tracheo-esophageal fistula with esophageal atresia, cardiac anomalies, renal anomalies, and limb anomalies) association. J Pediatr. 2014; 164(3):451-457. https://doi.org/10.1016/j.jpeds.2013.10.086PubMedPubMed CentralGoogle Scholar
- Alter BP, Giri N.. Thinking of VACTERL-H? Rule out Fanconi anemia according to PHENOS. Am J Med Genet A. 2016; 170(6):1520-1524. https://doi.org/10.1002/ajmg.a.37637PubMedGoogle Scholar
- Alter BP. Fanconi anemia and the development of leukemia. Best Pract Res Clin Haematol. 2014; 27(3-4):214-221. https://doi.org/10.1016/j.beha.2014.10.002PubMedPubMed CentralGoogle Scholar
- Rose SR, Myers KC, Rutter MM. Endocrine phenotype of children and adults with Fanconi anemia. Pediatr Blood Cancer. 2012; 59(4):690-696. https://doi.org/10.1002/pbc.24095PubMedGoogle Scholar
- Gillio AP, Verlander PC, Batish SD, Giampietro PF, Auerbach AD. Phenotypic consequences of mutations in the Fanconi anemia FAC gene: an International Fanconi Anemia Registry study. Blood. 1997; 90(1):105-110. https://doi.org/10.1182/blood.V90.1.105Google Scholar
- Faivre L, Guardiola P, Lewis C. Association of complementation group and mutation type with clinical outcome in Fanconi anemia. European Fanconi Anemia Research Group. Blood. 2000; 96(13):4064-4070. Google Scholar
- Kutler DI, Singh B, Satagopan J. A 20-year perspective on the International Fanconi Anemia Registry (IFAR). Blood. 2003; 101(4):1249-1256. https://doi.org/10.1182/blood-2002-07-2170PubMedGoogle Scholar
- Castella M, Pujol R, Callen E. Origin, functional role, and clinical impact of Fanconi anemia FANCA mutations. Blood. 2011; 117(14):3759-3769. https://doi.org/10.1182/blood-2010-08-299917PubMedPubMed CentralGoogle Scholar
- Bottega R, Nicchia E, Cappelli E. Hypomorphic FANCA mutations correlate with mild mitochondrial and clinical phenotype in Fanconi anemia. Haematologica. 2018; 103(3):417-426. https://doi.org/10.3324/haematol.2017.176131PubMedPubMed CentralGoogle Scholar
- Wagner JE, Tolar J, Levran O. Germline mutations in BRCA2: shared genetic susceptibility to breast cancer, early onset leukemia, and Fanconi anemia. Blood. 2004; 103(8):3226-3229. https://doi.org/10.1182/blood-2003-09-3138PubMedGoogle Scholar
- Alter BP, Rosenberg PS, Brody LC. Clinical and molecular features associated with biallelic mutations in FANCD1/BRCA2. J Med Genet. 2007; 44(1):1-9. https://doi.org/10.1136/jmg.2006.043257PubMedPubMed CentralGoogle Scholar
- Reid S, Schindler D, Hanenberg H. Biallelic mutations in PALB2 cause Fanconi anemia subtype FA-N and predispose to childhood cancer. Nat Genet. 2007; 39(2):162-164. https://doi.org/10.1038/ng1947PubMedGoogle Scholar
- Orkin SH, Nathan DG, Ginsburg D, Look AT, Fisher DE, Lux S.. Nathan and Oski's Hematology of Infancy and Childhood E-book: Elsevier Health Sciences. 2008. Google Scholar
- Wang K, Li M, Hakonarson H.. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010; 38(16):e164. https://doi.org/10.1093/nar/gkq603PubMedPubMed CentralGoogle Scholar
- Feng BJ. PERCH: a unified framework for disease gene prioritization. Hum Mutat. 2017; 38(3):243-251. https://doi.org/10.1002/humu.23158PubMedPubMed CentralGoogle Scholar
- Desmet FO, Hamroun D, Lalande M, Collod-Beroud G, Claustres M, Beroud C.. Human Splicing Finder: an online bioinformatics tool to predict splicing signals. Nucleic Acids Res. 2009; 37(9):e67. https://doi.org/10.1093/nar/gkp215PubMedPubMed CentralGoogle Scholar
- Richards S, Aziz N, Bale S. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015; 17(5):405-424. https://doi.org/10.1038/gim.2015.30PubMedPubMed CentralGoogle Scholar
- Zhou X, Edmonson MN, Wilkinson MR. Exploring genomic alteration in pediatric cancer using ProteinPaint. Nat Genet. 2016; 48(1):4-6. https://doi.org/10.1038/ng.3466PubMedPubMed CentralGoogle Scholar
- Rosenberg PS, Greene MH, Alter BP. Cancer incidence in persons with Fanconi anemia. Blood. 2003; 101(3):822-826. https://doi.org/10.1182/blood-2002-05-1498PubMedGoogle Scholar
- Giri N, Stratton P, Savage SA, Alter BP. Pregnancies in patients with inherited bone marrow failure syndromes in the NCI cohort. Blood. 2017; 130(14):1674-1676. https://doi.org/10.1182/blood-2017-08-802991PubMedPubMed CentralGoogle Scholar
- Risitano AM, Marotta S, Calzone R, Grimaldi F, Zatterale A, RIAF Contributors. Twenty years of the Italian Fanconi Anemia Registry: where we stand and what remains to be learned. Haematologica. 2016; 101(3):319-327. https://doi.org/10.3324/haematol.2015.133520PubMedPubMed CentralGoogle Scholar
- Steinberg-Shemer O, Goldberg TA, Yacobovich J. Characterization and genotype-phenotype correlation of patients with Fanconi anemia in a multi-ethnic population. Haematologica. 2020; 105(7):1825-1834. https://doi.org/10.3324/haematol.2019.222877PubMedPubMed CentralGoogle Scholar
- Rosenberg PS, Huang Y, Alter BP. Individualized risks of first adverse events in patients with Fanconi anemia. Blood. 2004; 104(2):350-355. https://doi.org/10.1182/blood-2004-01-0083PubMedGoogle Scholar
- Rosenberg PS, Alter BP, Ebell W.. Cancer risks in Fanconi anemia: findings from the German Fanconi Anemia Registry. Haematologica. 2008; 93(4):511-517. https://doi.org/10.3324/haematol.12234PubMedGoogle Scholar
- Khan NE, Rosenberg PS, Alter BP. Preemptive bone marrow transplantation and event-free survival in Fanconi anemia. Biol Blood Marrow Transplant. 2016; 22(10):1888-1892. https://doi.org/10.1016/j.bbmt.2016.06.018PubMedPubMed CentralGoogle Scholar
- Tonnies H, Huber S, Kuhl JS, Gerlach A, Ebell W, Neitzel H.. Clonal chromosomal aberrations in bone marrow cells of Fanconi anemia patients: gains of the chromosomal segment 3q26q29 as an adverse risk factor. Blood. 2003; 101(10):3872-3874. https://doi.org/10.1182/blood-2002-10-3243PubMedGoogle Scholar
- Mitchell R, Wagner JE, Hirsch B, DeFor TE, Zierhut H, MacMillan ML. Haematopoietic cell transplantation for acute leukaemia and advanced myelodysplastic syndrome in Fanconi anaemia. Br J Haematol. 2014; 164(3):384-395. https://doi.org/10.1111/bjh.12634PubMedPubMed CentralGoogle Scholar
- Rochowski A, Olson SB, Alonzo TA, Gerbing RB, Lange BJ, Alter BP. Patients with Fanconi anemia and AML have different cytogenetic clones than de novo cases of AML. Pediatr Blood Cancer. 2012; 59(5):922-924. https://doi.org/10.1002/pbc.24168PubMedPubMed CentralGoogle Scholar
- Chao MM, Thomay K, Goehring G. Mutational spectrum of Fanconi anemia associated myeloid neoplasms. Klin Padiatr. 2017; 229(6):329-334. https://doi.org/10.1055/s-0043-117046PubMedGoogle Scholar
- Kennedy AL, Myers KC, Bowman J. Distinct genetic pathways define pre-malignant versus compensatory clonal hematopoiesis in Shwachman-Diamond syndrome. Nat Commun. 2021; 12(1):1334. https://doi.org/10.1038/s41467-021-21588-4PubMedPubMed CentralGoogle Scholar
- Giri N, Batista DL, Alter BP, Stratakis CA. Endocrine abnormalities in patients with Fanconi anemia. J Clin Endocrinol Metab. 2007; 92(7):2624-2631. https://doi.org/10.1210/jc.2007-0135PubMedGoogle Scholar
- Elder DA, D'Alessio DA, Eyal O. Abnormalities in glucose tolerance are common in children with Fanconi anemia and associated with impaired insulin secretion. Pediatr Blood Cancer. 2008; 51(2):256-260. https://doi.org/10.1002/pbc.21589PubMedGoogle Scholar
- Barnum JL, Petryk A, Zhang L. Endocrinopathies, bone health, and insulin resistance in patients with Fanconi anemia after hematopoietic cell transplantation. Biol Blood Marrow Transplant. 2016; 22(8):1487-1492. https://doi.org/10.1016/j.bbmt.2016.05.004PubMedPubMed CentralGoogle Scholar
- Petryk A, Kanakatti Shankar R, Giri N. Endocrine disorders in Fanconi anemia: recommendations for screening and treatment. J Clin Endocrinol Metab. 2015; 100(3):803-811. https://doi.org/10.1210/jc.2014-4357PubMedPubMed CentralGoogle Scholar
- Bartlett AL, Romick-Rosendale L, Nelson A. Tryptophan metabolism is dysregulated in individuals with Fanconi anemia. Blood Adv. 2021; 5(1):250-261. https://doi.org/10.1182/bloodadvances.2020002794PubMedPubMed CentralGoogle Scholar
- Ameziane N, Errami A, Leveille F. Genetic subtyping of Fanconi anemia by comprehensive mutation screening. Hum Mutat. 2008; 29(1):159-166. https://doi.org/10.1002/humu.20625PubMedGoogle Scholar
- Kalb R, Neveling K, Hoehn H. Hypomorphic mutations in the gene encoding a key Fanconi anemia protein, FANCD2, sustain a significant group of FA-D2 patients with severe phenotype. Am J Hum Genet. 2007; 80(5):895-910. https://doi.org/10.1086/517616PubMedPubMed CentralGoogle Scholar
- Benitez A, Liu W, Palovcak A. FANCA promotes DNA doublestrand break repair by catalyzing single-strand annealing and strand exchange. Mol Cell. 2018; 71(4):621-628e624. https://doi.org/10.1016/j.molcel.2018.06.030PubMedPubMed CentralGoogle Scholar
- Wang S, Wang R, Peralta C, Yaseen A, Pavletich NP. Structure of the FA core ubiquitin ligase closing the ID clamp on DNA. Nat Struct Mol Biol. 2021; 28(3):300-309. https://doi.org/10.1038/s41594-021-00568-8PubMedPubMed CentralGoogle Scholar
- Tomaszowski K-H, Roy S, Keshvani C. Polygenic mutations model the pleiotropic disease of Fanconi anemia. bioRxiv. 2020. https://doi.org/10.1101/2020.09.01.277038Google Scholar
- Ebens CL, MacMillan ML, Wagner JE. Hematopoietic cell transplantation in Fanconi anemia: current evidence, challenges and recommendations. Expert Rev Hematol. 2017; 10(1):81-97. https://doi.org/10.1080/17474086.2016.1268048PubMedPubMed CentralGoogle Scholar
- Giardino S, de Latour RP, Aljurf M. Outcome of patients with Fanconi anemia developing myelodysplasia and acute leukemia who received allogeneic hematopoietic stem cell transplantation: a retrospective analysis on behalf of EBMT group. Am J Hematol. 2020; 95(7):809-816. https://doi.org/10.1002/ajh.25810PubMedGoogle Scholar
- Folias A, Matkovic M, Bruun D. BRCA1 interacts directly with the Fanconi anemia protein FANCA. Hum Mol Genet. 2002; 11(21):2591-2597. https://doi.org/10.1093/hmg/11.21.2591PubMedGoogle Scholar
- Ali AM, Pradhan A, Singh TR. FAAP20: a novel ubiquitin-binding FA nuclear core-complex protein required for functional integrity of the FA-BRCA DNA repair pathway. Blood. 2012; 119(14):3285-3294. https://doi.org/10.1182/blood-2011-10-385963PubMedPubMed CentralGoogle Scholar
Figures & Tables
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.