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. Author manuscript; available in PMC: 2024 Dec 1.
Published in final edited form as: Br J Haematol. 2023 Jun 24;203(5):820–828. doi: 10.1111/bjh.18945

The distribution and accumulation of the shortest telomeres in telomere biology disorders

Hannah A Raj 1, Tsung-Po Lai 2, Marena R Niewisch 1,3, Neelam Giri 1, Youjin Wang 1, Stephen R Spellman 4, Abraham Aviv 2, Shahinaz M Gadalla 1, Sharon A Savage 1
PMCID: PMC10748793  NIHMSID: NIHMS1914523  PMID: 37354000

Abstract

Individuals with telomere biology disorders (TBDs) have very short telomeres, high risk of bone marrow failure (BMF), and reduced survival. Using data from TBD patients, a mean leukocyte Southern blot telomere length (TL) of 5 kilobases (kb) was estimated as the ‘telomere brink’ at which human survival is markedly reduced. However, the shortest telomere, not the mean TL, signals replicative senescence. We used the Telomere Shortest Length Assay (TeSLA) to tally TL of all 46 chromosomes in blood-derived DNA and examined its relationship with TBDs. Patients (n=18) had much shorter mean TL (TeSmTL) (2.54±0.41 kb vs 4.48±0.52 kb, p<0.0001) and more telomeres <3 kb than controls (n=22) (70.43±8.76% vs 33.05±6.93%, p<0.0001). The proportion of ultrashort telomeres (<1.6 kb) was also higher in patients than controls (39.29±10.69% vs 10.40±4.09%, p<0.0001). TeS<1.6kb was associated with severe (n=11) compared with non-severe (n=7) BMF (p=0.027). Patients with multi-organ manifestations (n=10) had more telomeres <1.6 kb than those with one affected organ system (n=8) (p=0.029). Findings suggest that TBD clinical manifestations are associated with a disproportionately higher number of hematopoietic cell telomeres reaching a telomere brink, whose length at the single telomere level is yet to be determined.

Keywords: bone marrow failure, dyskeratosis congenita, telomere biology disorder, TeSLA, telomere length, telomere

Graphical Abstract

graphic file with name nihms-1914523-f0005.jpg

INTRODUCTION

Telomeres comprise TTAGGG tandem repeats and specialized proteins that protect chromosome ends and prevent genomic instability (Harley, et al 1990). They shorten with each cell division due to the inability of the DNA replication machinery to fully replicate DNA ends (Brenner and Nandakumar 2022, Lai, et al 2023, Levy, et al 1992). The biological signal defining telomere-mediated replicative senescence comes from the shortest telomeres in a cell (Hemann, et al 2001, Zou, et al 2004). In the general population, short mean telomere length (TL) in leukocytes has been associated with lower risk of many cancers, higher risk of atherosclerotic cardiovascular disease and diminished longevity (Arbeev, et al 2020, Codd, et al 2021, Savage 2018, Shay and Wright 2019). The correlation between longevity and leukocyte TL suggest the existence of a leukocyte TL threshold below which the chances of human survival are reduced, i.e., a ‘telomere brink’ (Steenstrup, et al 2017). A human telomere brink of approximately 5 kilobases (kb) has been estimated based on 1) the mean leukocyte TL (LTL) of 4.99±0.79 kb (median 4.66 kb, range 3.83-6.55 kb), measured by Southern blotting (SB) in 23 patients with dyskeratosis congenita (DC), a telomere biology disorder (TBD), and 2) statistical modeling of age-related telomere shortening and life expectancy in 12,320 individuals from the general population (Steenstrup, et al 2017). This estimate was recently redefined using TeSLA (telomere shortest length assay) which measures the complete distribution of telomeres across all chromosome ends(Lai, et al 2017). Using a 3 kb cut-off of TL measured by TeSLA recent data suggest healthy individuals are unlikely to reach a hematopoietic TL limit during their lifespan but that patients with TBDs do reach this telomere brink (Lai, et al 2023).

TBDs are caused by pathogenic/likely pathogenic (P/LP) germline variants in genes engaged in telomere maintenance. These P/LP variants cause very short telomeres, leading to early mortality with median survival of 52.6 years (95% confidence interval 45.5-57.6) (Niewisch, et al 2022). The diagnosis of TBDs is often complicated by their heterogeneous clinical presentations and a broad phenotypic spectrum including the classic mucocutaneous findings of dyskeratosis congenita, bone marrow failure (BMF), and other clinical outcomes. While genetic testing for the currently known 18 TBD-related genes can aid in the diagnosis of individuals, pathogenic/likely pathogenic (P/LP) variants are not identified in approximately 20% of patients with TBDs (Niewisch, et al 2022, Tummala, et al 2022).

Lymphocyte mean TL <1st percentile-for age measured by flow cytometry with fluorescent in situ hybridization (flow FISH) is highly sensitive and specific for diagnosing TBDs but limited by the need for fresh blood samples (Alder, et al 2018, Alter, et al 2012). Flow FISH can quantify TL in different leukocyte populations, including granulocytes, total lymphocytes, and lymphocyte subsets (CD45+, CD45−, CD57+, and CD45RA−) and has been associated with TBD genotypes and phenotypes (Alder, et al 2018, Alter, et al 2012, Niewisch, et al 2022). However, such associations are of limited predictive value beyond disease diagnosis perhaps because the shortest telomere in a cell, not the mean TL, triggers TL-mediated replicative senescence (Hemann, et al 2001, Zou, et al 2004).

High-throughput Single Telomere Length Analysis (HT-STELA) has recently been proposed as a method for differentiating patients with TBDs from controls (Norris, et al 2021). HT-STELA typically determines the distributions of only the Xp and Yp telomeres, including telomeres < 3 kilobases (kb) (Baird, et al 2003), which are not typically captured by SB or flow FISH. TeSLA, in contrast, measures the lengths and tallies the proportions of the 92 single telomeres on all 23 pairs of all human chromosomes (Benetos, et al 2021, Lai, et al 2021, Lai, et al 2023, Lai, et al 2017, Mender, et al 2018). We used TeSLA to examine intra- and inter-individual TL variation across all chromosomes in patients with TBDs and healthy controls.

METHODS

Study Participants

Patients with TBDs were enrolled in the National Cancer Institute’s (NCI) Institutional Review Board approved Inherited Bone Marrow Failure syndrome (IBMFS) study (clinicaltrials.gov Identifier NCT00027274, https://marrowfailure.cancer.gov). Participants or their legal guardians provided written informed consent. Detailed questionnaires were completed by participants and medical records were reviewed. A subset of study participants was also clinically evaluated by the IBMFS team at the National Institutes of Health Clinical Center, as described (Niewisch, et al 2022). Patients with a clinical diagnosis of DC but unknown genetic etiology were excluded.

For this study, participants were designated as having a TBD if they had clinical manifestations and a P/LP germline variant in a known TBD-associated gene meeting the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) variant curation guidelines (Niewisch, et al 2022, Richards, et al 2008). Severe BMF was defined as absolute neutrophil count (ANC) < 500/mm3, platelet count <20,000/mm3, and/or hemoglobin (Hb) <8.0 g/dl, or when patients required treatment for cytopenia, e.g., transfusions, oral androgens, or hematopoietic cell transplant. Non-severe BMF was defined by an ANC of 500 to <1500/mm3, platelet count of 20,000 to <150,000/mm3, and/or Hb ≥8g/dl to less than normal for age. Other TBD-associated phenotypes we examined included hematological malignancies, pulmonary fibrosis, pulmonary arteriovenous malformations, gastrointestinal telangiectasias, avascular osteonecrosis, esophageal strictures, severe liver disease, and solid tumors. Clinical features were grouped by organ system as previously described (Supplementary Table 1). For this analysis, hematologic system involvement was defined by the presence of severe BMF, myelodysplastic syndrome, or leukemia.

Patients with clinical TBD features were further categorized by the P/LP variant mode of inheritance: autosomal dominant (AD), autosomal recessive (AR), or X-linked recessive (XLR). Participants with a monoallelic RTEL1 P/LP variant and no clinical features were analyzed separately. These individuals were parents or siblings of patients with clinical disease due to biallelic (n=6) or monoallelic (n=1) P/LP RTEL1 variants.

Controls were healthy donors (n=22) for recipients of hematopoietic cell transplant with TeSLA measurements as part of another study and in collaboration between the NCI, the Center for International Blood and Marrow Transplant Research (CIBMTR), and the Aviv lab at Rutgers University (Lai, et al 2022).

Telomere Length Measurement

Genomic DNA was extracted from whole blood using standard methods. The detailed TeSLA method has been described previously (Lai, et al 2017). Briefly, DNA was ligated with TeSLA-Ts at the telomeric overhangs, which contain seven nucleotides of telomeric C-rich repeats at the 3′ end. After digestion with a panel of four restriction enzymes (BfaI/CviAII/MseI/NdeI), double strand adaptors were ligated, and telomeric regions were PCR amplified. Custom software was used for lane and band detection, leading to band size annotation and statistical quantification. The TL parameters used in these analyses were as described(Lai, et al 2022) 1) TeSLA mean TL(TeSmTL), 2) shortest 20% of telomeres in kb (TeS20%), 3) the percent of telomeres shorter than 3 kb (TeS<3kb), and 4) the percent of telomeres shorter than 1.6 kb (TeS<1.6kb). Precision of TeSLA measurements, as indicated by the intraclass correlation coefficient, is 0.90 (Lai, et al 2022).

Flow FISH mean lymphocyte TL was measured under CLIA conditions at Repeat Diagnostics, Inc. (Vancouver, BC) as described (Alter, et al 2012, Baerlocher, et al 2002). The correlations between flow FISH mean lymphocyte TL and TeSLA parameters were r=0.53 (p=0.03), r=0.48 (p=0.05), r=−0.55 (p=0.02), and r=−0.46 (p=0.06) for TeSmTL, TeS20%, TeS<3kb, and TeS<1.6kb, respectively (Supplementary Figure 1).

Statistical Analyses

TeSLA TL parameters between patients with TBDs and controls were compared using Student’s t-test. Correlations of TeSLA parameters with age and flow FISH TL were calculated using Pearson’s correlation coefficient. Given the small sample sizes, we did not adjust for age in analyses although it may lead to a more conservative estimates given the older age of controls and healthy monoallelic RTEL1 relatives and expected their shorter TL. A p-value of <0.05 was considered statistically significant; all analyses were two sided. SPSS Statistics version 28.0.0.0, SAS version 9.4, and Prism version 9.2.0 were used for all analyses and visualizations.

RESULTS

Participant characteristics

The study included 18 patients with clinical TBD and a proven germline genetic etiology (3 TERC, 2 TERT, 3 TINF2, 3 DKC1, and 7 RTEL1, designated hereafter as “patients”), eight healthy relatives of patients with one RTEL1 P/LP variant (RTEL1 relatives), and 22 healthy controls (Table 1 and Supplementary Table 2). Patients were younger than the controls (mean age 21.5 vs. 29.7 years; p=0.05), but no sex difference was noted (p=0.25). One clinically affected patient had a monoallelic RTEL1 variant, while the other six patients had biallelic RTEL1 variants.

Table 1:

Demographics and TeSLA Parameters of study participants.

n Age in years, mean +/− SD M:F Flow FISH mean lymphocyte TL (kb) TeSmTL (kb) P TeS20% (kb) P % TeS<3kb P % TeS<1.6kb P
Controls 22 29.8 +/− 9.2 12:10 NA 4.48 +/− 0.52 <0.0001 2.28 +/− 0.33 <0.0001 33.05 +/− 6.93 <0.0001 10.40 +/− 4.09 <0.0001
TBD clinically affected 18 22.5 +/− 16.6 12:6 3.95 +/− 0.93 2.54 +/− 0.41 1.11 +/− 0.21 70.43 +/− 8.76 39.29 +/− 10.69
Gene TERC 3 34.9 +/− 19.9 1:2 4.3 +/− 1.14 2.72 +/− 0.31 - 1.14 +/− 0.14 - 70.18 +/− 9.44 - 38.1 +/− 6.0 -
TERT 2 37.8 +/− 17.0 1:1 3.9 +/− 0.14 2.76 +/− 0.007 - 1.32 +/− 0.11 - 67.59 +/− 2.80 - 29.2 +/− 1.70 -
TINF2 3 17.5 +/− 12.1 3:0 3.76 +/− 1.26 2.54 +/− 0.80 - 1.15 +/− 0.39 - 69.35 +/− 18.32 - 36.2 +/− 21.1 -
DKC1 3 36.3 +/− 8.69 3:0 3.37 +/− 0.45 2.65 +/− 0.42 - 1.16 +/− 0.19 - 70.20 +/− 8.73 - 40.2 +/− 9.48 -
Biallelic RTEL1 6 9.88 +/− 7.51 3:3 3.88+/− 0.96 2.30 +/− 0.28 <0.0001a 0.94 +/− 0.106 <0.0001a 73.51 +/− 5.51 a 45.0 +/− 8.41 <0.0001a
Monoallelic RTEL1 1 3.20 1:0 5.60 2.78 - 1.26 - 62.31 - 35.38 -
Healthy TBD relatives with monoallelic RTEL1 8 32.25 +/− 14.17 4:4 5.51 +/− 0.93 3.41 +/− 0.88 0.0003a 1.65 +/− 0.56 0.010b 51.50 +/− 17.09 0.0002a 23.7 +/− 16.6 0.0013a
0.012b 0.0007a 0.011b 0.014b
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Abbreviations: n, number; SD, standard deviation; M, male; F, female; kb, kilobases; TL, telomere length; TBD, telomere biology disorder; TeSmTL, TeSLA mean TL; TeS20%; TeSLA mean shortest 20% of telomeres; TeS<3kb, % of TeSLA TL <3 kb; TeS<1.6kb, % of TeSLA TL <1.6 kb

a

Comparison of healthy TBD relatives with monoallelic RTEL1 with Controls

b

Comparison of healthy TBD relatives with monoallelic RTEL1 with biallelic RTEL1

All patients had flow FISH TL less than the 1st percentile for age except for one patient with a c.847C>T (p.P283S) variant in TINF2 whose TL was between the slightly above the 1st percentile (Supplementary Figure 2). Patients with TBDs had significantly shorter TeSmTL than controls (mean 2.54 ±0.41 kb vs 4.48± 0.52 kb, p<0.0001).

Individuals with TBDs have high proportions of short and ultrashort telomeres

The distribution of telomere band size (kb) versus the percentage of bands in patients was significantly different than that of the RTEL1 relatives and the controls (Figure 1). There were notably more short telomeres (defined as <3 kb) in patients with TBDs than in controls. Specifically, the mean of TeS20% was 1.11±0.21 kb in TBD patients and 2.28±0.33 kb in controls (p<0.0001, Table 1 and Figure 2). The proportion of telomeres <3 kb was 70.43±8.76% in patients with TBDs compared with 33.05±6.93%in controls (p<0.0001). Similarly, ultrashort telomeres (defined as TeS<1.6kb) were present in 39.29±10.69%in patients with TBDs and 10.40±4.09% in controls (p<0.0001).

Figure 1.

Figure 1.

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Distribution of TeSLA telomere length band size in blood-derived DNA of patients with with telomere biology disorders (TBDs; blue), healthy RTEL1 monoallelic relatives (red), and controls (green).

Figure 2: Telomere Shortest Length Assay (TeSLA) parameters in patients with telomere biology disorders and controls.

Figure 2:

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A) Distribution of TeSLA band size versus the percentage of bands in patients with TBDs, healthy RTEL1 monoallelic relatives, and controls; B) TeSLA mean telomere length in kilobases (TeSmTL); C) the shortest 20% of telomeres (TeS20%) in kb; D) the percent of telomeres <3.0 kb (TeS<3kb); E) the percent of telomeres <1.6 kb (TeS<1.6kb).

Accumulation of short telomeres is associated with BMF and other TBD phenotypes

We next evaluated whether TeSLA telomere parameters were associated with BMF severity (Figure 3). TeSmTL, TeS20%, and TeS<1.6kb were significantly associated with severe BMF (n=11) compared with non-severe BMF (n=7) (p=0.046, p=0.011, p=0.027, respectively). However, the TeS<3kb was not associated with BMF severity.

Figure 3: Telomere Shortest Length Assay (TeSLA) parameters vary by clinical manifestations in patients with telomere biology disorders.

Figure 3:

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A-D) TeSLA parameter comparisons by severity of bone marrow failure (BMF): A) TeSLA mean telomere length (TeSmTL); B) shortest 20% of telomeres (TeS20%) in kilobases (kb); C) the percent of telomeres <3.0 kb (TeS<3kb); D) the percent of telomeres <1.6 kb (TeS<1.6). E-H) TeSLA parameters comparisons according to organ system involvement as defined in the Methods: E) TeSmTL; F) TeS20%; G) TeS<3kb; H) TeS<1.6.

Ten patients with TBDs had clinical presentations spanning multiple organ systems, including seven with severe BMF plus involvement of at least one additional organ system, and three with two or more major manifestations in other organ systems. Those with multi-organ manifestations had shorter TeSmTL (p=0.025) than those with just one affected organ system (Figure 3). This was also reflected by the greater accumulation of TeS<3kb and TeS<1.6kb in patients with multi-organ manifestations (p=0.006 and p=0.029, respectively, Figure 3).

Genotype affects proportions of short telomeres

The mean length of the TeS20% was 1.01±0.17 kb in those with AR/XLR TBDs (n=9) compared with 1.22±0.14 kb in those with AD-non-TINF2 disease (n=6) (p=0.026). TeS<1.6kb was slightly higher in AR/XLR TBDs than AD-non-TINF2 (43.38±8.52% vs 34.71±5.84%, p=0.05) (Supplementary Figure 3).

Two male patients with TINF2 P/LP variants ages 8.8 years (NCI-156-1, c.845G>A, p.R282H) and 12.5 (NCI-102-1, c.847C>T, p.P283S) had striking differences in the frequency of short telomeres. Sixty percent of NCI-156-1’s telomeres were <1.6 kb compared with 27.7% in NCI-102-1with p.R283S (Supplementary Figure 3D). Both individuals had all three mucocutaneous triad features and severe BMF. However, the patient with p.R282 had additional complications including pulmonary arteriovenous malformations, severe liver disease, and pulmonary fibrosis and died at 16.5 years of age. In contrast, the patient with p.R283S is currently 27 years of age and has not developed additional TBD-related complications.

We next focused on the three families with TBDs due to P/LP RTEL1 variants, including six patients with TBDs due to biallelic RTEL1 variants and eight healthy heterozygous family members (Table 1, Figure 4). TeSmTL was 2.30±0.276 kb in those with biallelic RTEL1 variants compared with 3.41±0.88 kb in those with one RTEL1 variant, and 4.48±0.52 kb in controls (biallelic vs. controls p<0.0001, monoallelic vs. controls p=0.0003, biallelic vs. monoallelic p=0.01). Distinct differences were noted in the distribution and proportion of the short telomeres in individuals with biallelic RTEL1 variants compared with monoallelic RTEL1 variants (Figure 4). The mean TeS20% were the shortest in patients with biallelic RTEL1 variants (0.94±0.11 kb) followed by those with a single variant (1.65±0.56 kb) compared with controls at 2.28±0.33 kb (p<0.0001, p=0.0007, p=0.010, respectively). Similarly, TeS<3kb was 73.51±5.51% for patients with biallelic RTEL1 variants, 51.50±17.09% for monoallelic relatives, and 33.05±6.93% for controls (p<0.0001, p=0.0002, p=0.011, respectively). TeS<1.6kb was 44.99±8.41% for patients with biallelic RTEL1 variants, 23.70±16.60% for those with a single variant, and 10.40±4.08% for controls (p<0.0001, p=0.0013, p=0.014, respectively).

Figure 4. Variable telomere lengths distributions in participants with monoallelic versus biallelic pathogenic/likely pathogenic RTEL1 variants.

Figure 4.

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A) TeSLA mean telomere length (TL); B) shortest 20% of telomeres; C) the percent of telomeres <3.0 kb; D) the percent of telomeres <1.6 kb; E-H) TeSLA telomere length distributions in E) family NCI-180, F) family NCI-297, G) family NCI-345, and H) unaffected control samples. M, male, F, female, numbers on the X axis indicate age in years.

Family NCI-297 was notable for differences in TL distribution by genotype (Figure 4). The three family members with monoallelic RTEL1 variants (c.1338+3 A>G IVS15+3 A>G in the sibling and father, c.3361delG p.A1121LfsX6 in the mother) had flow FISH mean lymphocyte TL between the 1st and 10th percentiles for age. The proband’s father had a greater proportion of TeS<1.6kb than the proband’s sibling or mother (60.0% vs. 16.67% and 20.66%, respectively) (Figure 4). Among the eight individuals from three families with monoallelic RTEL1 variants in this study, the father in family NCI-297 was the only individual to subsequently develop the TBD-related clinical manifestation of BMF, over eight years of follow-up.

DISCUSSION

In this study, we identified distinct differences in the distribution of TL in patients with TBDs compared with controls or monoallelic RTEL1 healthy relatives. Notably, there were high proportions of short telomeres (< 3 kb) and ultrashort telomeres (< 1.6 kb) in patients with TBDs. Proportions of ultrashort telomeres were associated with BMF and disease severity. We also found that proportions of short telomeres were associated with mode of disease inheritance, which often determines BMF and severity of TBDs. To date, research on the relationships between telomere biology and human disease has predominately focused on the mean TL (Savage 2018, Shay and Wright 2019, Wang, et al 2018). This led to the introduction of flow FISH TL measurements to the clinic, a tool that has markedly improved the diagnosis of TBDs and led to the discovery of their diverse genetic underpinnings (Alder, et al 2018, Alter, et al 2012, Revy, et al 2022, Savage, et al 2008). Flow FISH mean TL is highly correlated with TL measured by SB (R2=0.68 to 0.73) in the same laboratory that performed TeSLA in the present study (Khincha, et al 2017b). However, the flow FISH TL correlations with TL parameters measured by TeSLA are modest, ranging from a Pearson’s correlation coefficient (r) of −0.46 to 0.55 (R2 =0.21 to 0.30), suggesting that flow FISH may have limited ability to measure short/ultrashort telomeres. It is also important to recognize that the mean TL determined by STELA, HT-STELA, and TeSLA is correlated with but much lower than flow FISH and Southern blot TL because they can measure the full array of short telomeres.

The shortest telomere, not the mean TL, triggers cellular senescence. The high proportion of ultrashort telomeres in TBD patients with severe BMF suggests that TL-mediated senescence of hematopoietic cells is the direct cause of the cytopenias. This may also be the mechanism driving the other phenotypes, including pulmonary fibrosis, liver disease, cancer, and vascular telangiectasias/arteriovenous malformations, but these are complex phenotypes in need of further investigation (Higgs, et al 2019, Himes, et al 2021, Khincha, et al 2017a, Niewisch, et al 2022, Tummala, et al 2022).

Gaining further knowledge about the relation between short and ultrashort telomeres and the clinical manifestations of TBDs is an important step towards introducing single TL measurements into patient management. STELA, which principally measures telomeres on Xp and Yp, has led to important insights into the dynamics of single telomeres in cultured cells undergoing senescence (Baird, et al 2003). The high-throughput version of STELA, HT-STELA, has been recently used to show the accumulation of telomeres <3 kb in patients with TBDs but it is limited in the number of telomeres measured (Norris, et al 2021). In contrast, TeSLA is highly sensitive and specific in detecting a wide range of TL across all chromosomes in a given DNA preparation (Lai, et al 2017). In principle, telomeres on any of the 92 human chromosome arms may reach the critical length that signals replicative senescence.

We acknowledge several limitations: First, the sample size of the study is small. Second, control matching was not perfect with the control mean age of 29.8 years (+/− 9.2) and TBD case mean age 22.5 years (+/− 16.6), resulting in an age over correction for TBD cases less than 20 years of age (n=9) and under correction in cases more than 40 years of age (n=4). Third, TeSLA does not identify the specific chromosomal origins of the telomeres it tallies and measures and defining short telomeres based on a length < 3 kb and ultrashort telomeres based on a length < 1.6 kb is somewhat arbitrary but based robust studies of TL dynamics (Lai, et al 2022, Steenstrup, et al 2017). Leveraging the entire distributions of TL parameters generated by TeSLA, future studies based on larger sample sizes might better define thresholds for TL parameters that can be used in clinical setting for patient management and prognosis. At this time, we are also unable to address whether hematopoietic somatic genetic rescue and/or clonal hematopoiesis could contribute to the TL distributions or TBD clinical manifestations.

In summary, this study shows that information about short and ultrashort telomeres generates new knowledge of TL factors that define the outcomes of TBDs. The high frequency of telomeres <1.6 kb in TBDs suggests their BMF etiology stems from loss of replicative capacity of hematopoietic cells due to a disproportionate number of cells with chromosome arms that have reached a telomere length limit. Additional studies are warranted to develop predictive models of phenotype progression based on accumulation of very short telomeres approaching the telomere brink in humans.

Supplementary Material

Table S1-S2

Supplementary Table 1. Organ system groups used in analyses. Based on Niewisch et al, Blood 2022.

Supplementary Table 2. Affected gene and germline variant of study participants.

Supinfo

Supplementary Figure 1. Correlation between Telomere Shortest Length Assay (TeSLA) parameters and flow cytometry with fluorescent in situ hybridization (flow FISH) telomere lengths (TL) in individuals with telomere biology disorders (TBDs). Thirteen participants had flow FISH and TeSLA TL measured at the same age. Flow FISH and TeSLA were measured at different ages for five patients: 43 and 45, 11 and 12, 3 and 8.8, 11 and 13, and 16 and 18 years, respectively.

A) Correlation between TeSLA mean TL and flow FISH; B) Correlation between TeSLA shortest 20% TL and flow FISH; C) Correlation between TeSLA percent telomeres <3 kb and flow FISH; D) Correlation between TeSLA percent telomeres <1.6 kb and flow FISH.

Supplementary Figure 2. Telomere lengths of study participants. Flow cytometry with fluorescent in situ hybridization (flow FISH) lymphocyte telomere lengths of study participants.

Supplementary Figure 3. Comparisons of Telomere Shortest Length Assay (TeSLA) parameters by mode of inheritance, gene function, and specific genes. A-C) Analyses by mode of inheritance: A) TeSLA mean telomere length (TeSmTL); B) shortest 20% of telomeres (TeS20%) in kilobases (kb); C) the percent of telomeres <1.6 kb (TeS<1.6); D) Variable TeSLA telomere length (TL) in two patients with pathogenic TINF2 variants. Individual (NCI-156-1, TINF2 p.R282H) was 8.8 years of age at measurement with 60.2% of telomeres <1.6 kb. He had severe nail dysplasia, abnormal skin pigmentation, oral leukoplakia, severe bone marrow failure (BMF) requiring hematopoietic cell transplantation (HCT) and developed severe liver disease and pulmonary fibrosis which led to death at 16.5 years. In contrast NCI-102-1 (TINF2 p.P283S), 12.5 years of age at measurement, had 27.7% of telomeres <1.6 kb, and severe nail dysplasia, abnormal skin pigmentation, oral leukoplakia, and severe BMF. E-G) TeSLA parameter comparisons by gene E) TeSmTL; F) TeS20%; G) TeS<1.6kb.

ACKNOWLEDGEMENTS

The authors are grateful to all study participants and their families for their invaluable contributions to this research. Lisa Leathwood, RN, Maureen Risch, RN, and Ann Carr, CGC of Westat, Inc. provided valuable study management under contract HHSN261201700004C with the National Cancer Institute.

This study was funded in part by the intramural research program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute. The CIBMTR is supported primarily by Public Health Service U24CA076518 from the National Cancer Institute (NCI), the National Heart, Lung and Blood Institute (NHLBI) and the National Institute of Allergy and Infectious Diseases (NIAID); HHSH250201700006C from the Health Resources and Services Administration (HRSA); and N00014-21-1-2954 and N00014-23-1-2057. from the Office of Naval Research; Support is also provided by Be the Match Foundation, the Medical College of Wisconsin, the National Marrow Donor Program. M.R.N. was supported by the Mildred-Scheel-Postdoctoral Fellowship Program of German Cancer Aid. The work of A.A. was supported by NIH grant U01AG066529.

Footnotes

DECLARATION OF INTERESTS

The authors declare no competing interests.

DATA AVAILABILITY

There are restrictions to the availability of data herein due to the importance of maintaining participant confidentiality. De-identified data from this study may be requested from the corresponding author, Dr. Sharon A. Savage, and will be made available to qualified scientists after completion of appropriate data transfer agreements and NIH Institutional Review Board approval.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1-S2

Supplementary Table 1. Organ system groups used in analyses. Based on Niewisch et al, Blood 2022.

Supplementary Table 2. Affected gene and germline variant of study participants.

NIHMS1914523-supplement-Table_S1-S2.docx (21.8KB, docx)
Supinfo

Supplementary Figure 1. Correlation between Telomere Shortest Length Assay (TeSLA) parameters and flow cytometry with fluorescent in situ hybridization (flow FISH) telomere lengths (TL) in individuals with telomere biology disorders (TBDs). Thirteen participants had flow FISH and TeSLA TL measured at the same age. Flow FISH and TeSLA were measured at different ages for five patients: 43 and 45, 11 and 12, 3 and 8.8, 11 and 13, and 16 and 18 years, respectively.

A) Correlation between TeSLA mean TL and flow FISH; B) Correlation between TeSLA shortest 20% TL and flow FISH; C) Correlation between TeSLA percent telomeres <3 kb and flow FISH; D) Correlation between TeSLA percent telomeres <1.6 kb and flow FISH.

Supplementary Figure 2. Telomere lengths of study participants. Flow cytometry with fluorescent in situ hybridization (flow FISH) lymphocyte telomere lengths of study participants.

Supplementary Figure 3. Comparisons of Telomere Shortest Length Assay (TeSLA) parameters by mode of inheritance, gene function, and specific genes. A-C) Analyses by mode of inheritance: A) TeSLA mean telomere length (TeSmTL); B) shortest 20% of telomeres (TeS20%) in kilobases (kb); C) the percent of telomeres <1.6 kb (TeS<1.6); D) Variable TeSLA telomere length (TL) in two patients with pathogenic TINF2 variants. Individual (NCI-156-1, TINF2 p.R282H) was 8.8 years of age at measurement with 60.2% of telomeres <1.6 kb. He had severe nail dysplasia, abnormal skin pigmentation, oral leukoplakia, severe bone marrow failure (BMF) requiring hematopoietic cell transplantation (HCT) and developed severe liver disease and pulmonary fibrosis which led to death at 16.5 years. In contrast NCI-102-1 (TINF2 p.P283S), 12.5 years of age at measurement, had 27.7% of telomeres <1.6 kb, and severe nail dysplasia, abnormal skin pigmentation, oral leukoplakia, and severe BMF. E-G) TeSLA parameter comparisons by gene E) TeSmTL; F) TeS20%; G) TeS<1.6kb.

NIHMS1914523-supplement-Supinfo.pptx (234.1KB, pptx)

Data Availability Statement

There are restrictions to the availability of data herein due to the importance of maintaining participant confidentiality. De-identified data from this study may be requested from the corresponding author, Dr. Sharon A. Savage, and will be made available to qualified scientists after completion of appropriate data transfer agreements and NIH Institutional Review Board approval.

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