Key words newborn screening - sickle cell disease - two-tiered testing - qPCR - benchmarking
- high-throughput screening
Schlüsselwörter Neugeborenenscreening - Sichelzellkrankheit - zweistufige Diagnostik - qPCR - Laborvergleich
- Hochdurchsatz-Screening
Introduction
Sickle cell disease (SCD) is a serious disease leading to circulatory disorders,
organ damage, severe pain and early death [1 ].
According to current figures, about 400,000 are born with SCD every year [2 ]. The term SCD comprises a group of hemoglobin (Hb)
disorders, which are autosomal recessively inherited and characterized by the
presence of hemoglobin S (HbS) resulting from a point mutation in the 6th
codon of the β-globin encoding HBB gene (HBB CD 6
GAG>GTG [Glu>Val]). The underlying genotype of the disorder can be
homozygous or compound-heterozygous in case a certain second pathogenic HBB
mutation is present. In the deoxygenated form, HbS tends to polymerize, resulting
in
the eponymous sickle shape of affected erythrocytes, which are prone to aggregation
and hemolysis [3 ]
[4 ]. In
newborns, fetal hemoglobin (HbF, α2 γ2 )
represents the largest Hb share in the child’s blood with HbA accounting for
approx. 1/4 at term. During the first months of life, the HbA concentration
continues to increase. After reaching a critical level, which typically occurs
between the third and fourth month, symptoms begin to manifest in SCD-affected
individuals, commonly within the first year of life [5 ]. The clinical presentations of such persons include acute pain,
vaso-occlusions, and chronic organ complications with the severity of symptoms
differing among SCD variants. [3 ]
[4 ]. Individuals with sickle cell trait (HbS/A),
have only one mutated HBB allele and do not develop symptoms. Early detection
of SCD patients has proven to be beneficial for disease management, for treatment
outcome, and substantially reduces morbidity and mortality [5 ]
[6 ]. Thus, SCD has been included as
target disease in newborn screening (NBS) programs in several countries; in Europe,
these are Belgium, France, Malta, the Netherlands, the United Kingdom, Spain, and,
since October 2021, Germany [7 ]
[8 ].
Due to the Hb variants relevant to SCD, screening methods used for its detection
usually rely on the analysis of corresponding proteins or peptides and include
high-performance liquid chromatography (HPLC), capillary electrophoresis (CE),
isoelectric focusing, MALDI-TOF or tandem mass spectrometry (MS/MS) [7 ]
[9 ]. For NBS
laboratories, inclusion of new target diseases in existing screening programs can
be
challenging in many aspects, e. g., considering sample logistics, spatial,
personnel, and analytical capacities, particularly if they operate in
high-throughput conditions (e. g.,>1,000 samples per day). Hence,
methods are required that do not noticeably affect the throughput rate, are
cost-efficient and meet analytical specifications, such as sufficient sensitivity
[8 ]. Apart from investing in new instruments,
strategies such as multiplexing or the implementation of multi stage analytical
processes are applied to address such challenges; in the first case, new targets are
integrated into existing methods, platforms or workflows, in the latter case, a
1st -tier method performs the mass-screening and one or more
subsequent methods with comparably higher specificity than the first one are used
for confirmation and differentiation [10 ]
[11 ].
Of the mentioned techniques applied to SCD screening, only MS/MS has been
commonly used in German NBS laboratories. However, the required sample preparation
is incompatible with existing NBS methods (i. e., analysis of acylcarnitines
and amino acids) and cannot be integrated in existing workflows [12 ]. Since the inclusion of severe combined
immunodeficiencies (SCID) as target disease in 2019 and spinal muscular atrophy
(SMA) in 2021, concurrent with SCD screening, qPCR is present in German NBS
laboratories. This analytical platform is capable of multiplexing [13 ], and specific PCR-based methods to detect HbS
alleles have been published [14 ]. As SCD arises from a
nucleotide change present in all its forms, qPCR is a predestined method to perform
the primary screening in a two-tiered analytical approach and preselect
HbS-containing specimens. A subsequent 2nd -tier method is then needed to
distinguish HbS/A cases from specimens with Hb variants indicative of SCD.
Such screening approaches have been developed and applied in three high-throughput
NBS laboratories, which together account for over 60% of the German NBS
capacity [15 ]. In a joint effort, an extensive sample
exchange was set up pursuing two goals: i) As a quality assurance task for the
screening processes and ii) to demonstrate that a two-step analytical approach with
a qPCR-based primary screening is suitable to reliably detect SCD cases. Here, the
results of these benchmarking tests are presented together with a summarized outcome
of the first nine months of regular SCD screening in these laboratories.
Materials and Methods
Samples
Most patient samples for benchmarking were taken from Guthrie-cards sent to the
laboratories for regular NBS and for which written informed consent was given.
In addition to the NBS specimens, several previously donated and anonymized,
pathologic samples were included for which written consent was given. Each of
the three laboratories compiled three identical sets of 150 dried blood spot
(DBS) samples, that were anonymized and double blinded. The aim was to detect
and specify a small proportion of SCD-relevant samples and a larger proportion
of heterozygous (S/A) among predominantly wild-type samples, without
considering a distribution of phenotypes representative for the German
population in the compilation. One set each was sent to the other
laboratories.
To compare the results of the individual analytical platforms, the benchmarking
sample sets were entirely analyzed, i. e., using all analytical methods
that are part of the laboratories’ SCD screening. In the regular NBS,
however, the methods were applied in the conceptualized, two-tiered analytical
procedures, so that the methods for differentiation were used only on samples
that had been preselected by qPCR.
Analytical methods
Each of the three laboratories’ screening approaches is based on two-tier
testing procedures using a multiplex qPCR method for mass screening that allows
detection of SCID and SMA in parallel with HbS alleles. Subsequent
2nd -tier methods are used to differentiate the pre-selected
subset of samples.
In Lab 1 and Lab 2, the qPCR analyses are performed using Lightmix kits (TIB
Molbiol, Berlin, Germany) and a Lightcycler 480 System (Roche Diagnostics
International, Rotkreuz, Switzerland) with high-resolution melting curve
analysis to detect HBB variants. In Lab 3, an in-house developed qPCR
method using specific fluorescent TaqMan probes (synthesized by Integrated DNA
Technologies, Coralville, USA) is performed using a Quantstudio 7 Flex System
(Applied Biosystems, Massachusetts USA).
For differentiation of the preselected specimens, automated HPLC systems were
used in Lab 1 (Variant nbs, Bio-Rad, Feldkirchen, Germany) and Lab 2 (HLC-723G8,
TOSOH, Stuttgart, Germany), which were operated according to the
manufacturers’ instructions. Lab 3 used Newborn haemoglobinopathy
screening kits (SpotOn Clinical Diagnostics Ltd., London, Great Britain) with a
modified protocol in combination with a flow injection analysis MS/MS
system (Acquity UPLC and Xevo TQD, Waters, Eschborn, Germany) for this task. At
the time of the benchmarking tests, a CE system (Capillarys 3 DBS, Sebia,
Lisses, France) was evaluated in Lab 1 for differentiation, so that results for
these samples could also be generated with this system, even if it was not
subsequently applied as part of the lab’s two-tiered approach.
More detailed descriptions about the methods, including measures for quality
control, are provided in the supplemental file (section “Method
descriptions”) and elsewhere [13 ]
[16 ].
Results
Benchmarking
Three equal sets of 150 DBS samples were provided by each of the three
laboratories and distributed among them to be analyzed. The composition of
genotypes in these 450 benchmarking samples is shown in [Fig. 1 ]. In total, 36 samples of these represented
physiological conditions considered positive in an SCD screening setting: 29
homozygous HbS/S, four compound-heterozygous HbS/C, and three
HbS/β thalassemia (HbS/βThal, no further
characterization available). Forty-seven specimens were of sickle cell trait,
and the 367 specimens designated as "non-HbS" were of Hb types
that did not contain HbS (mostly wildtype, four HbC/A samples and one
HbC/C).
Fig.1 Distribution of genotypes in the total benchmarking sample
set. The term ‘non-HbS’ here refers to variants devoid
of HbS, i. e., mainly wildtype; the figure was created with R
(4.1.2) and ggplot2 (3.3.5).
All benchmarking samples were analyzed by means of both methods used for SCD
screening in the labs, i. e., three qPCR, two HPLC methods, and one
MS/MS method. In addition, Lab 1 provided results obtained with CE for these
samples although this platform has not been applied in its regular SCD
screening. The results are summarized in [Tab.
1 ]. A detailed list of the individual results is given in the
supplemental file (Tab. S 1) . Among the 450 samples, 36 belong to
genotypes relevant for SCD disease, and 414 are considered negative (367 non-HbS
and 47 HbS/A) in an NBS scenario. However, in a two-step screening
process with an integrated preselection of HbS-containing samples in the
1st tier (i. e., based on qPCR targeting HbS alleles), it
is equally necessary to recognize the 47 HbS/A samples.
Tab. 1 Numbers (n ) of specimens per type included
in the benchmarking samples and returned results by applying the
respective laboratories’ individual
1st –tier PCR– and their
2nd –tier differentiation methods and CE. The full
set of samples has been analyzed by each method. For
PCR–based methods, a further differentiation of HbS
containing samples is not pursued. *CE results were provided
by Lab 1 although this platform is not part of the
two–tiered analytical setups.
**HbS/βThal: compound heterozygous
HbS/β thalassemia.
Lab 1
Lab 2
Lab 3
Type
n
PCR
HPLC
PCR
HPLC
PCR
MS/MS
CE*
non–HbS
367
362
367
362
367
367
367
367
HbS–containing
83
88
83
88
83
83
83
83
HbS/A
47
–
47
–
47
–
47
47
HbS/S
29
–
32
–
31
–
31
30
HbS/C
4
–
4
–
4
–
4
4
HbS/βThal**
3
–
0
–
1
–
1
2
In the sample exchange, the 83 samples containing HbS were found by all methods
applied. However, in the qPCR tests, Lab 1 and Lab 2 categorized five additional
samples as “HbS-containing” (Σ=88) which turned
out to be of those genotypes containing HbC after unblinding. In the form used
to submit the test results, these five samples were annotated in the
1st -tier method stating that “HbC could not be
excluded”. As expected, application of the respective methods intended
for differentiation not only allowed to distinguish between
“non-HbS” and the “HbS-containing” sample
groups, but also to further elucidate the latter: All 47 specimens of
HbS/A were correctly recognized and SCD-variant specimens categorized.
However, while homozygous HbS/S and compound-heterozygous HbS/C
type samples were identified, one or more of the HbS/βThal
samples were labelled HbS/S using either of the three methods, CE, HPLC,
or MS/MS.
Regular screening
As of October 1st , 2021, SCD was included in the German NBS panel as
new target disease. Hence, the two-tiered screening strategies described here
were applied in routine NBS from then on. The number of screened specimens in
nine months between October 1st, 2021 and June 30th, 2022 and the results of the
SCD screening are summarized in [Tab. 2 ].
Tab. 2 Individual numbers of screened samples, suspect and
reported SCD findings of the individual labs and the respective
sums. Other SCD variants in scope of the screening, such as
HbS/D, HbS/E, or HbS/O were not
detected.
Lab 1
Lab 2
Lab 3
Sum
total samples screened
129,194
120,009
104,016
353,219
samples flagged for 2nd tier
613
591
430
1,634
SCD positive
31
23
24
78
HbS/S
13
19
16
48
HbS/C
3
2
5
10
HbS/β0 -Thal
1
1
2
4
HbS/β+ -Thal
14
1
0
15
HbS/HPFH
–
–
1
1
In the individual labs, 104,016, 120,009, and 129,194 samples have been analyzed
during this period accounting for 353,219 samples in total, which went through
qPCR-based primary screening. Of these, 1,634 samples (0.46%) were
flagged for subsequent differentiation, thus, the qPCR-based screening reduced
the number of samples requiring differentiation by more than 99.5%. As
expected, the lion’s share of the specimens preselected by qPCR were of
heterozygous HbS/A or non-SCD variants and, as such, classified as
screen negative after 2nd -tier analyses. However, during the nine
months of routine screening, 78 SCD patients were revealed, reported, and
referred for follow-up: In total, 48 homozygous HbS/S cases, ten
HbS/C, four HbS/β0 thalassemia, 15
HbS/β+ thalassemia cases, and one child
having HbS combined with hereditary persistence of fetal hemoglobin (HPFH). To
date, as far as feedback could be obtained through tracking, 59 of the reported
cases have been confirmed. Feedback on eight HbS/S, two HbS/C
and four HbS/β+ thalassemia findings is still
pending. Five of the reported
HbS/β+ thalassemia findings have turned out to
be heterozygous HbS/A.
Discussion
Benchmarking
In a sample exchange, identical anonymized and double-blinded sets of 450 DBS
samples were analyzed at three different sites using one individual qPCR method
per lab and different analytical platforms (intended for differentiation) with
commercial kits designed for hemoglobinopathy analyses: CE, 2×HPLC, and
MS/MS. After unblinding and comparing the reported results to target
conditions, it was found that the “non-HbS”
(n =367) and “HbS-containing”
(n =83) sample groups were distinctly separated applying CE, HPLC,
MS/MS, and TaqMan-based qPCR. Application of two qPCR methods that
employed melting curve analysis concordantly resulted in 362 samples categorized
as non-HbS (“screen negative”), so that five additional
specimens (four HbC/A and one HbC/C) would have been flagged and
forwarded to 2nd -tier analysis for differentiation. Both
β-globin encoding gene variants (HBB c.20 A>T,
p.Glu6Val for HbS and HBB c.19 G>A, p.Glu6Lys for HbC)
are situated on the same codon in the HBB gene [3 ]. In qPCR with melting curve analysis, the signals for both alleles
appear at similar Tm values
(∆Tm =1°C). However, the aim of the applied
algorithm in 1st -tier screening is variant detection, thus all
non-wildtype samples are flagged at this stage, independent of the underlying
variant. Moreover, the logical consequence for any equivocal results in
analytical tests is further clarification, e. g., by repetition with an
extended experimental design or by applying an independent method. The latter is
the core of two-stage analytical processes, and it is therefore consistent to
flag such samples for later verification (or rebuttal) [11 ]. Here, this is done by HPLC-based differentiation as described in
the ‘Materials and Methods’ section (and the supplemental file).
In all cases, the set goal for qPCR, to preselect all specimens containing HbS
(i. e., no false-negatives) in the sample exchange, was fully
achieved.
The distinction of genotypes in the benchmarking analyses was performed with two
independent HPLC methods, one MS/MS, and one CE method. All of these
correctly categorized HbS/A, HbS/S, and HbS/C variants.
Sickle cell carriers are typically asymptomatic and must not be reported after
screening. Even if such samples are preselected in the qPCR 1st tier,
it could be demonstrated that the 2nd -tier method clearly recognizes
HbS/A specimens (and other non-SCD variants forwarded to
differentiation) as screen negatives. For the three compound-heterozygous
HbS/β Thal in the benchmarking samples, with each
differentiation method, at least one of the specimens was classified as
HbS/S. Homozygous HbS/S, HbS/β0
thalassemia, and HbS/HPFH share the same Hb patterns (F and S) and can
thus not be distinguished by means of the mentioned methods. In case of
HbS/β+ thalassemia, HbA additionally
appears in the pattern, and depending on the residual expression of
ß-globin from the thalassemic HBB allele, indicative ratios of
calculated variant to wildtype signals can overlap with the ranges of
HbS/A [17 ]
[18 ]. The main objective of NBS programs, however, is to improve
outcomes for individuals at risk for a disease through early detection and thus
early treatment and care [5 ]. Moreover, screening
results are considered presumptive and are to be confirmed by independent
analytical methods in follow-up. Considering the benchmarking results, in a
two-stage screening setup of qPCR and one of the applied differentiation
methods, neither false positives (non-SCD) nor false negatives would have been
reported. The goal of identifying specimens representing affected patients would
hence also be fulfilled.
Regular screening
SCD was included as target disease in the German NBS program on October
1st , 2021, so the different combinations of two-tiered approaches
and strategies described above were employed in routine screening since then.
More specifically, the qPCR-based primary screen was realized within multiplexed
methods that enabled the simultaneous detection of SCID, SMA as well as HbS
specimens in a high-throughput environment (e. g.,>1,000 samples
on peak days). In the nine months ending June 30th , 2022, a total of
353,219 patient samples had passed through the three NBS centers, and 1,634
samples of these were investigated with 2nd -tier analyses. Compared
to a setting in which the full number of received samples would have been
screened for SCD by HPLC, CE, or MS/MS, the antecedent qPCR step
efficiently reduced the number of specimens to be reanalyzed by more than
99.5%. Of the specimens characterized as non-wildtype or HbS-containing,
the majority (1,556 or 95.2%) was recognized as non-SCD (i. e.,
HbS/A or a variant not relevant for SCD) during differentiation by means
of 2nd -tier HPLC or MS/MS, ensuring these samples were
reported as screen negative. In contrast, 78 patients were detected with
genotypes consistent with SCD (48 HbS/S, 15
HbS/β+ thalassemia, ten HbS/C,
four HbS/β0 thalassemia, and one HbS/HPFH).
In follow-up, all cases reported as HbS/S, HbS/C,
HbS/β0 thalassemia, or HbS/HPFH and for
which feedback could be obtained during tracking were confirmed. However, no
results from confirmation diagnostics have been communicated for 14 patients to
date. Five of the cases that were reported as
HbS/β+ thalassemia have been found to be
HbS carriers without β thalassemia. Due to the overlapping ranges of
S/A ratios, the differentiation of
HbS/β+ thalassemia and HbS/A is a
known difficulty [17 ]. Here, the analytical
evaluation was designed to avoid false-negatives, which in turn means that some
false-positive findings for HbS/β+ thalassemia
may occur.
Assuming that pending confirmation results prove positive, these results
correspond to an overall incidence of 1:4,773, which is in good agreement with a
statistical evaluation of health insurance data (1:5,102) [19 ], a previous study in Germany that included
urban and rural areas near Berlin (1:4,154) [12 ],
and comprehensibly lower than in two studies representing mainly urban areas
(Hamburg: 1:2,385 and Berlin: 1:2,433) [20 ]
[21 ]
[22 ]. Furthermore,
after nine months of regular screening (and until the preparation of this
manuscript), no false-negative results have been brought to our attention.
Further aspects of qPCR-based two-tiered SCD screening
In routine NBS, two often discussed drawbacks are prematurity of babies and
transfusions. In premature children, the share of HbF in the blood highly
exceeds the proportion of adult HbA (e. g., probably detectable from 30
weeks gestation and 5–10% by 34–36 weeks gestation)
[5 ]. Blood transfusions, however, lead to a
dilution of the patient’s blood and may produce misleading analytical
results in case of an SCD patient, e. g., wrong diagnostic ratios
indicating sickle cell trait or even a wildtype condition. In contrast to
biochemical methods, qPCR targets nucleic acid sequences rather than peptides
and is thus intrinsically unaffected by such drawbacks. Hence, even in cases of
low concentrations of natively synthesized β-globin molecules, this
technique reliably detects HbS alleles, which represents one more advantage in
an NBS environment.
As stated above,<0.5% of the samples entering the laboratories
had to be investigated by 2nd -tier analyses after the qPCR primary
screening. Such a drastic reduction in analytical workload is also associated
with substantial savings in chemicals, consumables, energy, and working time of
specialized personnel, thus enabling economical and more sustainable operation.
To highlight this aspect in more detail, exemplary comparisons of consumables
and solvents for the described methods applied in different settings are
provided in the supplemental file (Tab. S 2) . If SCD screening was based
solely on MS/MS in Lab 3, 2,100 more microplates, 107,000 additional
pipette tips, and 43 L more MeOH would have been spent during the
nine-month study period.
According to 2019 data from the Global Burden of Disease project, SCD is
responsible for 0.6 deaths, 44.8 years of life lost and 48.7 years lived with
disability, each per 100,000 individuals [23 ]. SCD
is widespread in sub-Saharan Africa and central India. In low- and middle-income
countries such as these, it is difficult to raise the necessary funds for
expensive ready-to-use newborn screening tests [24 ], so SCD is often not diagnosed until life-threatening situations
occur or severe pain requires a hospitalization of children. In a recent
retrospective observational study, the mortality rate for infants under five
years of age in sub-Saharan Africa was estimated to be about 36.4%.
[25 ]. Besides cost, the availability of a
detection method is an important factor. During the SARS-CoV 2 pandemic, qPCR
has experienced a boost in dissemination, and in light of multiplex testing, it
can be a cost-effective and readily available analytical platform for many
purposes. While the approved NBS tests for SCD applying HPLC, MS, or CE account
for a large part of (routine) Hb variant analyses, tests based on,
e. g., enzyme-linked immunoassays, chip microarrays, or other techniques
have also been developed and may provide cost-effective alternatives [26 ]. In order to achieve a pre-selection within a
cohort and thus to focus the use of such methods on relevant samples, a
combination with qPCR may in turn be reasonable.
Conclusions
In benchmarking tests, it could be demonstrated that qPCR is well suited to detect
samples carrying the HbS point mutation and thus to reliably perform a preselection
in two-tiered analytical setups for SCD screening. As expected, established
analytical platforms were subsequently successful in distinguishing the carrier
state from SCD cases and differentiating SCD variants based on the detected Hb
patterns. During nine months of regular screening, 353,219 patient samples were
analyzed in three high-throughput NBS centers applying two-tiered analytical
procedures for SCD screening that incorporated a qPCR-based 1st -tier
within multiplexed methods. This preselection step efficiently reduced the sample
numbers for the 2nd -tier methods by more than 99.5% spotlighting
specimens relevant for further testing, i. e., non-wildtype or
HbS-containing samples, while not being affected by confounding factors such as
prematurity or transfusions. Further investigations by HPLC or MS/MS used as
2nd -tier methods ensured that individuals with carrier state or
non-target variants were categorized SCD negative, while 78 patients with
SCD-variants were revealed: 48 HbS/S, 15
HbS/β+ thalassemia, ten HbS/C, four
HbS/β0 thalassemia, and one HbS/HPFH. As far
as feedback has been received, all of them but four cases of
HbS/β+ thalassemia were confirmed in
follow-up, and concurrently, no false-negatives have emerged. Compared to a scenario
in which all samples would have been screened with HPLC or MS/MS only, the
massive reduction of sample numbers by 1st -tier qPCR testing also
resulted in a more cost-effective and sustainable workflow. Combining qPCR with less
costly methods for differentiation as the established ones may provide an option for
SCD screening to middle- or low-income countries.
Contributor’s Statement
Writing – Original Draft: J. Janda, S. Hegert, J. Bzdok, J. Durner; Writing
– Review & Editing: R. Tesorero, U. Holtkamp, F. Hörster, G.
F. Hoffmann, N. Janzen, J. G. Okun, M. Becker; Data Curation: J. Janda, S. Hegert,
J. Bzdok, R. Tesorero, U. Holtkamp, E. Schuhmann; Formal analysis: J. Janda, S.
Hegert, J. Bzdok, R. Tesorero, U. Holtkamp, S. Burggraf, E. Schuhmann; Validation:
S. Burggraf, E. Schuhmann, F. Hörster; Conceptualization: N. Janzen, J. G.
Okun, J. Durner; Funding acquisition: G. F. Hoffmann, N. Janzen, M. Becker
