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\begin{document}

\title{The \emph{PIG-A} gene mutation assay in human biomonitoring and disease}



\author[1]{Rachel Lawrence}%
\author[2]{Kathryn Munn}%
\author[2]{Hamsa Naser}%
\author[2]{Laura Thomas}%
\author[3]{Hasan Haboubi}%
\author[4]{Lisa Williams}%
\author[2]{Shareen Doak}%
\author[2]{Gareth Jenkins}%
\affil[1]{Queen Mary University of London - Charterhouse Square Campus}%
\affil[2]{Swansea University Faculty of Medicine Health and Life Science}%
\affil[3]{Cardiff and Vale University Health Board}%
\affil[4]{Swansea Bay University Health Board}%


\vspace{-1em}



  
  \date{June 09, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
The blood cell phosphatidylinositol glycan class A (\emph{PIG-A}) gene
mutation assay has been extensively researched in rodents for \emph{in
vivo} mutagenicity testing and is now being investigated in humans. The
\emph{PIG-A} gene is involved in glycosyl phosphatidylinositol
(GPI)-anchor biosynthesis. A single mutation in this X-linked gene leads
to loss of membrane bound GPI-anchors, which can be enumerated using
flow cytometry. With many studies published to date measuring this
mutation in erythrocytes, there is remarkable consistency across
research groups. Moreover, with the low background level of mutant
erythrocytes in healthy subjects (2.9 - 5.56 x 10-6 mutants), induction
of mutation post genotoxic exposure can be detected. Cigarette smoking,
radiotherapy and occupational exposures including lead, have been shown
to increase mutant levels. Identification of harmful agents can allow us
to recommend new exposure limits, minimising individual risk.
Conversely, protective agents such as aspirin and healthy diets could
mitigate these effects, reducing baseline somatic mutation levels and
such behaviours can be encouraged. This mutational monitoring approach
may also provide information on individuals at higher risk of cancer
development. Patients with inflammatory bowel disease, oesophageal
adenocarcinoma and pancreatic cancer have elevated numbers of
\emph{PIG-A} mutant erythrocytes compared to age-matched controls. With
further technological progress including protocol standardisation and
the development of cryopreservation methods to improve GPI-anchor
stability, this assay can be widely employed in rural and low-income
countries. Here we review the current literature on \emph{PIG-A}
mutation in human subjects and discuss the potential role of this assay
in human biomonitoring and disease.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Measuring somatic mutations in humans provides an invaluable tool for
identifying exogenous mutagenic sources, allowing us to make better
informed public health choices to avoid harmful exposures and to
introduce regulatory approaches to reduce these adverse exposures. As
cancer is driven by DNA mutations, an accumulation of somatic mutations
is known to increase an individual's cancer risk (Hanahan \& Weinberg,
2011). Hence monitoring individuals for the number and types of somatic
DNA mutations will allow the identification of those who may be at
increased risk of cancer development which may allow for early
intervention and perhaps even cancer prevention. Environmental exposures
that can induce mutation include dietary, lifestyle, accidental and
occupational exposures. Developing tools that allow us to measure such
mutations will aid in the identification of new mutagenic and/or
carcinogenic exposures (Loomis, Guha, Hall, \& Straif, 2018). Knowledge
of the lifestyle factors associated with increased mutation levels could
be used to tailor advice to members of the public in relation to
avoiding risky behaviours (e.g., smoking) through public health
measures. Everyday exposures may conversely reduce our mutational risk,
e.g., diets containing anti-mutagenic compounds. Chemo-preventative, or
anti-genotoxicity lifestyle factors could be specifically identified
through large-scale human biomonitoring studies (e.g., dietary compounds
and medications) using high-throughput approaches needed to unpick the
multi-faceted exposures we face daily.

In addition, genetic polymorphisms may modulate an individual's risk of
mutation (and hence cancer), either by increasing or decreasing the
likelihood of mutational events. For example, if a certain exposure to a
genotoxin induces DNA damage which cannot be efficiently repaired due to
polymorphisms in genes such as \emph{OGG1} (Jensen et al., 2012)
or\emph{XRCC1} (Monteiro, Vilas Boas, Gigliotti, \& Salvadori, 2014)
(involved in base excision repair), this may increase an individual's
sensitivity to DNA damage. In addition, germline mutations in DNA
polymerases increases somatic mutational burden in normal tissues
(Robinson et al., 2022), and somatic mutation rates are increased in the
normal tissues of patients with MUTYH-associated polyposis (MAP)
(Robinson et al., 2021). Therefore, a personalised approach to precision
exposure monitoring may be most beneficial with the inclusion of these
biomarkers of susceptibility.

There are a handful of cytogenetic techniques that can detect DNA
abnormalities in human cells. Currently available genotoxicity tests
suitable for measuring DNA damage and mutation include the lymphocyte
cytokinesis-block micronucleus test (CBMN) (Fenech et al., 2011), the
lymphocyte COMET assay (Fenech et al., 2011) and the
hypoxanthine-guanine phosphoribosyl transferase (\emph{hprt} ) test
(Townsend, Robison, \& O'Neill, 2018) as well as approaches measuring
sister chromatid exchanges (Sunada, Haskins, \& Kato, 2019) and
chromosomal abnormalities (Sunada et al., 2019). Recently, increased
accessibility to DNA sequencing technologies able to overcome
difficulties associated with background mutation rates, have identified
DNA mutational signatures (Alexandrov et al., 2020; Alexandrov et al.,
2013), particularly those that correlate with certain human exposures
including Aflatoxin B1 and ultraviolet irradiation (Phillips, 2018).
Whilst whole genome/exome sequencing allows us to measure mutations
across the whole genome, and not just those produced in reporter genes
such as \emph{hprt} or phosphatidylinositol glycan class A\emph{(PIG-A)}
, the technology is still relatively expensive and not therefore
suitable for wide-scale roll out in population-based biomonitoring
studies. Moreover, not all exposures have known mutational profiles or
signatures at this stage and therefore it is not informative to measure
\emph{de novo} mutational signatures if we do not know the cause.

The \emph{PIG-A} assay measures \emph{de novo} somatic mutations in
the\emph{PIG-A} gene. The test measures the steady state accumulation of
mutations in blood cells, to provide a snapshot of mutant cell levels at
any given point in time relative to the lifespan of erythrocytes
(approximately 115-120 days) (Franco, 2012; Thiagarajan, Parker, \&
Prchal, 2021). The \emph{PIG-A} gene is located at Xp22.2 in humans. The
protein product of the gene is responsible for the production of a
catalytic subunit of N-acetylglucosamine transferase, an enzyme involved
in one of the early steps of glycosyl phosphatidylinositol (GPI)-anchor
biosynthesis (Takeda et al., 1993). Although there are over 20 genes
involved in GPI-anchor production, only one mutation in the
\emph{PIG-A}gene is required to inactivate the gene and result in a GPI
deficient phenotype (Miyata et al., 1993). As shown in Figure 1,
\emph{PIG-A}wild-type cells present many GPI-anchors and their
corresponding GPI-anchored proteins (GPI-AP) on the cell surface which
can subsequently be detected using fluorescently labelled antibodies
targeting the GPI-AP of choice through flow cytometry.
\emph{PIG-A}mutant cells lack these GPI anchors and crucially lack the
GPI-APs and therefore GPI-AP targeted antibodies are unable to bind to
the extracellular surface.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1.} Flow cytometric analysis of red blood cell
phosphatidylinositol glycan class A (\emph{PIG-A} ) gene status.
Anti-CD235A antibodies can be used to isolate erythrocytes in a whole
blood sample and anti-CD55/CD59 antibodies are used to detect the
presence of the glycosylphosphatidylinositol (GPI)-linked proteins CD55
and CD59. \emph{PIG-A} wild-type cells present functional (GPI) anchors
and corresponding GPI-linked proteins at the extracellular surface (top
panel) whilst \emph{PIG-A} mutant cells do not fluoresce as they lack
GPI-anchors and corresponding anchored proteins (made using
biorender.com).

Blood cell \emph{PIG-A} mutations were first described in patients with
paroxysmal nocturnal haemoglobinuria (PNH). A \emph{de novoPIG-A}
mutation in haematopoietic stem cells results in clonal expansion of the
mutant and subsequent GPI (and GPI-AP) deficiency (measured using
antibodies targeting CD55/CD59). Clinical symptoms of PNH include
intravascular haemolysis and thrombosis (Endo, Ware, Vreeke, Howard, \&
Parker, 1996). Whilst there are around 150 GPI-APs, many GPI-APs are
immune effectors. This includes CD55 and CD59 which regulate the
complement immune system. In PNH, therefore, their widespread deficiency
results in complement mediated erythrolysis (Boccuni, Del Vecchio, Di
Noto, \& Rotoli, 2000). Clinical presentation of symptoms similar to
that of PNH have also been observed in patients with germline mutations
resulting in systemic loss of the GPI-AP CD59 (Yamashina et al., 1990).

This mutation test has been widely researched in rodents to test novel
products for mutagenic effects as part of regulatory safety assessment
(Dobrovolsky, Cao, Bhalli, \& Heflich, 2020; Olsen et al., 2017). It is
also highly suitable for human application as the same biochemical
pathway is conserved across mammals (Kawagoe, Takeda, Endo, \&
Kinoshita, 1994). Typical analysis time is 3-4 hours, not requiring
further culturing or sub-cloning of mutant cells and costing as little
as \selectlanguage{ngerman}£50 per sample. The suitability of the \emph{PIG-A} mutation assay as
a tool for human biomonitoring and cancer detection has been examined
and reported in the literature and is discussed in detail in this
review.

\textbf{Background mutant frequency in healthy populations}

Somatic \emph{PIG-A} mutations can occur at low frequency through
spontaneous mutational processes during normal haematopoiesis without
inducing PNH-like clinical symptoms. This is perhaps because these
mutated, GPI-negative blood cells occur at a lower frequency than is
required to activate mass complement mediated lysis (Araten, Nafa,
Pakdeesuwan, \& Luzzatto, 1999; Hu et al., 2005). These
\emph{PIG-A}mutated erythrocytes are present in healthy individuals at
low numbers (Cao et al., 2016; Dertinger, Avlasevich, Bemis, Chen, \&
MacGregor, 2015; Dobrovolsky, Elespuru, Bigger, Robison, \& Heflich,
2011; Lawrence, Haboubi, Williams, Doak, \& Jenkins, 2020), allowing for
easy observation of any increase in mutant cell levels and association
with individual mutagenic exposures. At low levels, such mutant
mammalian cells are growth neutral, viable and are easily detectable
using flow cytometry (David et al., 2018) (Figure 1).

\emph{PIG-A} mutations can be measured in all blood cell types and have
been reported for erythrocytes, reticulocytes, granulocytes, and
lymphocytes, with the majority of the reports using human erythrocytes.
A number of publications have measured \emph{PIG-A} mutant erythrocyte
levels in healthy populations with values ranging from 2.9 - 5.56 x
10\textsuperscript{-6} mutants per million erythrocytes (Figure 2).
These 7 studies all measured \emph{PIG-A} status through flow cytometric
analysis, using antibodies that target the GPI-linked protein CD59 (Cao,
Wang, Xi, et al., 2020; Cao et al., 2021; Cao et al., 2016; Dobrovolsky
et al., 2011), or CD55 and CD59 in combination (Dertinger et al., 2015;
Haboubi et al., 2019; Lawrence et al., 2020). Using both CD55 and CD59
in combination may reduce the number of falsely classified mutant cells
by eliminating any effect of reduced CD59 expression (Peruzzi, Araten,
Notaro, \& Luzzatto, 2010). However, as seen in Figure 2, there is no
significant difference in mutant cell levels between studies that
applied either CD55 alone (blue bars) or in combination with CD59 (red
bars) (p=0.057). The green bar on the graph represents the weighted
average from these 7 publications which is 4.58 \(\pm\) 4.2 x
10\textsuperscript{-6} mutants per million erythrocytes. The consistency
across studies is remarkable, considering that mutant frequency can be
easily inflated by any slight technological variation. The number of
mutant cells is subject to technical variation and can be artificially
altered in a number of ways. This includes antibody batch to batch
variation and supplier differences, sample preparation resulting in
shearing of anchored proteins, flow cytometer choice, flow rate, laser
strength and gating procedure. Test reproducibility is essential for
successful biomarker implementation. It is particularly important if
such a test were to be used in the assessment of human genotoxic
exposures where a subtle change in mutant frequency, may be indicative
of a positive genotoxic response.

\textbf{Hosted file}

\verb`image2.emf`  available at \url{https://authorea.com/users/656289/articles/661744-the-pig-a-gene-mutation-assay-in-human-biomonitoring-and-disease}

\textbf{Figure 2.} Background levels of phosphatidylinositol glycan
class A (\emph{PIG-A} ) mutant erythrocytes in healthy populations from
published research. Blue bars represent publications that have used
antibodies targeting CD55 only and red bars represent publications that
have used antibodies targeting CD55 and CD59 in combination. The green
bar shows the weighted mean. The bars represent mean values and the
error bars represent standard deviation.

We have assessed repeated measurements of individuals over time to
provide further evidence relating to the reproducibility of the assay
and the stability of the erythrocyte \emph{PIG-A} mutant phenotype.
Figure 3A shows repeat measurements from the same 4 individuals (2
females and 2 males) over a period of 17 weeks (see (Lawrence, 2020 \#4)
for methods). Although intra-individual variation exists,
erythrocyte\emph{PIG-A} mutant frequency remains relatively stable. For
example, the mutant frequency of Participant 2 remains relatively high
between 7 and 14 x 10\textsuperscript{-6} mutants (average 10.53
\(\pm\) 2.16 x 10\textsuperscript{-6} mutants) whilst the
mutant frequency of Participant 4 is consistently below 5 x
10\textsuperscript{-6} mutants (average 3.56 \(\pm\) 1.22 x
10\textsuperscript{-6} mutants). This is similar to what has been
previously published where Cao and colleagues repeatedly measured the
RBC \emph{PIG-A} mutant frequency of 3 individuals and discovered that
whilst 2 subjects had MF's consistently below 5 x 10\textsuperscript{-6}
mutants, one subject's MF always remained around 15 x
10\textsuperscript{-6} mutants (Cao et al., 2016). The average
coefficient of variation (CV) (indicator of intra-individual variation)
of the 4 individuals presented here was 35.2\%. This is lower than the
intra-individual variation observed in granulocytes by Rondelli\emph{et
al} where 32 healthy subjects were tested for \emph{PIG-A}status on 3
separate occasions which produced a CV of 44.3\% (Rondelli et al.,
2013). Figure 3B further shows the erythrocyte \emph{PIG-A}mutant
frequency for 9 healthy volunteers at 2 different time points. The
duration between each time point ranged from 92 to 516 days with an
average duration of 270 days. Participant HV112 had consistently high
mutation frequency of 9.61 -- 10.75 x 10\textsuperscript{-6} mutant
erythrocytes and HV038 mutant frequency remained low between 2.14 and
2.43 x 10\textsuperscript{-6} mutants over this period. This data
further demonstrates the general stability of \emph{PIG-A} mutant
phenotype over a longer period in self-reported healthy volunteers.

\textbf{Hosted file}

\verb`image3.emf`  available at \url{https://authorea.com/users/656289/articles/661744-the-pig-a-gene-mutation-assay-in-human-biomonitoring-and-disease}

\textbf{Figure 3:} (A) Repeat erythrocyte phosphatidylinositol glycan
class A (\emph{PIG-A} ) mutant frequency measurements for 4 participants
over a 17-week period. (B) Measurement of \emph{PIG-A} mutant frequency
for 9 healthy volunteers on two separate occasions. The time between
each blood sample acquisition ranged from 92 to 516 days with an average
time of 270 days. Methods published previously (Lawrence, 2020 \#23).

\textbf{Factors that influence \emph{PIG-A} mutant frequency}

Several human \emph{PIG-A} studies have also looked to identify
individual factors that may result in mutant frequency variation. The
fact that humans have higher \emph{PIG-A} mutant frequencies compared to
laboratory rodents (Olsen et al., 2017) could be due the fact that
humans are long-lived and are exposed to a wider range of lifestyle
genotoxins compared to laboratory confined rodents. Some of the human
studies mentioned above explored whether mutant frequency differs
between sexes, producing contrasting results (Figure 4). Dobrovolsky and
colleagues found that females had significantly higher erythrocyte
mutant frequencies compared to males (p=0.025), although only 26 females
were included in this cohort (Dobrovolsky et al., 2011). Conversely, Cao
and colleagues measured higher mutant erythrocytes in males compared to
females (p\textless{}0.0001) (Cao et al., 2016). The other publications
presented in Figure 2 (Cao, Wang, Xi, et al., 2020; Cao et al., 2021;
Haboubi et al., 2019; Lawrence et al., 2020) as well as the study by
Dertinger and colleagues (Dertinger et al., 2015) (not shown in Figure
4) revealed no significant differences in erythrocyte \emph{PIG-A}mutant
frequencies between sexes. A study measuring reticulocyte\emph{PIG-A}
identified a higher level of mutant reticulocytes in males compared to
females (Torous et al., 2020). Even though the reason behind these sex
differences is unclear it may be due to the different ethnicities
studied in these particular two groups with one research group measuring
\emph{PIG-A} mutation status in an ethnic Chinese population (Cao et
al., 2016) and the other in a mainly Caucasian/Hispanic population
(Dobrovolsky et al., 2011).This suggested difference in gender may also
be due to limited sample sizes and lack of integration of alternative
factors (known or unknown) that can confound mutation status at the
\emph{PIG-A} locus.

\textbf{Hosted file}

\verb`image4.emf`  available at \url{https://authorea.com/users/656289/articles/661744-the-pig-a-gene-mutation-assay-in-human-biomonitoring-and-disease}

\textbf{Figure 4:} Sex differences in erythrocyte phosphatidylinositol
glycan class A (\emph{PIG-A} ) mutant frequency for 5 publications.
Solid bars represent the mean mutant frequency and error bars show
standard deviation. The white numbers on each bar represent the number
of healthy participants in each category.

As DNA damage and subsequent mutations can accumulate with age due to
age-related reductions in DNA repair capacity and the lifelong
accumulation of such DNA damage, the potential impact of age has been
investigated by several research groups. A significant association
between older age and increased mutant frequencies was found in three
cohorts interrogating erythrocytes (Dertinger et al., 2015; Haboubi et
al., 2019; Lawrence et al., 2020) and one interrogating reticulocytes
(Torous et al., 2020), whilst other research groups either found minimal
or no correlation with age. However, when Cao and colleagues measured
the utility of this assay to identify mutagenicity in a cohort
occupationally exposed to polycyclic aromatic hydrocarbons, the
statistical analysis performed accounted for the impact of age on mutant
frequency, suggesting there may be an age effect in this ethnic Chinese
population (Cao et al., 2021). We may expect a correlation between
mutation accumulation and age, with previous publications demonstrating
an increased in single-base substitution mutational burden with age
(Robinson et al., 2021). However, the studies published to date do not
include a sufficient number of participants at either end of the age
spectrum to fully inform us whether an effect exists on an
epidemiological scale.

\emph{PIG-A} \textbf{mutation test in human biomonitoring}

Other factors that may influence mutation levels in participants include
smoking, diet and medication usage. A summary of studies assessing
different exposures on erythrocyte \emph{PIG-A} mutant levels is shown
in Table I. Although a significant increase in \emph{PIG-A} mutant cells
was observed in smokers of one study (Haboubi et al., 2019), and an
association between the number of \emph{PIG-A} mutant cells and
cigarette-pack-years was seen in another study (Cao et al., 2016), other
research groups failed to identify an association between cigarette
smoking and mutant cell levels. Whilst the genotoxic nature of cigarette
smoking has been extensively studied (Alsaad et al., 2019; Mohammed,
Hussen, Rashad, \& Hasheesh, 2020), the lack of association
with\emph{PIG-A} mutant frequency may be due to the limited number of
smokers recruited in some studies, the lack of information on
cigarette-pack-years or the influence of confounding factors including
gender, age, diet, inflammation and DNA repair, on mutant cell number.

The effect of diet and lifestyle has been studied in a single, large
cohort with results indicating that high dietary intake of vegetables
and exercising for more than one hour per week, may reduce mutant cell
levels (Lawrence et al., 2020). In addition, aspirin intake may be
protective against an increase in \emph{PIG-A} mutation levels. Whilst
the anti-cancer effects of aspirin have been well documented (Jiang,
Swacha, Aung, \& Gekara, 2023), the specific interaction of dietary
intake and erythrocyte mutant levels remains unclear. Cancer treatment
i.e., chemo or radiotherapy, may also change mutation levels. One study
measured granulocyte \emph{PIG-A} mutant levels in breast cancer
patients undergoing radiotherapy but found no change in mutant cell
number. However, the authors state that as the irradiation administered
concerned only a part of the sternum and ribs, the probability of a
granulocyte precursor gaining a mutation could have been too low to
significantly impact blood cell \emph{PIG-A} mutation levels (Bonetto et
al., 2021). Another study measuring erythrocyte mutant cell levels in a
cohort of patients undergoing chemotherapy +/- radiotherapy could not
evaluate the effect of treatment as no pre-treatment blood samples were
obtained. Furthermore, these patients had various types of malignancy
and were undergoing different treatment regimens (Horibata, Ukai,
Ishikawa, Sugano, \& Honma, 2016). Another study identified only 1/10
patients undergoing chemotherapy had a notable (3-fold) increase in
erythrocyte \emph{PIG-A} mutant cell levels (Dobrovolsky et al., 2011).
Reticulocyte \emph{PIG-A} mutant cell levels have been shown to increase
in testicular cancer patients (n=3) after cisplatin-based treatment, but
it took longer to observe \emph{PIG-A} mutant reticulocytes compared to
micronucleated reticulocytes (Torous et al., 2023). Although we would
expect systemic genotoxic agents such as chemotherapy to induce mutant
levels, the time between treatment and mutant manifestation is critical.
One of the downfalls in the literature to date in measuring
\emph{PIG-A}mutation in patients undergoing treatment, is the lack of
pre-treatment samples to allow for meaningful comparisons. In addition,
lack of associations between chemotherapy and mutant cell levels may be
due to the long-term nature of \emph{PIG-A} mutant manifestation, where
the genotoxic effect is not detectable within the study timeframe
(Dobrovolsky et al., 2011). By maximising study durations and obtaining
samples at the optimum time point (considering cell life span and/or
maturation time from haematopoietic stem cell), this assay could
potentially inform us as to which patients are more sensitive to
treatment and may therefore respond better to therapy. A test battery
would also be most beneficial in measuring chemotherapy sensitivity, as
effects may be observed sooner with the micronucleus assay than
the\emph{PIG-A} test, which in turn may be more informative on the
accumulation of genotoxic exposure and long-term effects (Torous et al.,
2020).

Work carried out by Cao and colleagues has assessed the DNA damage
potential of multiple exposures including azathioprine treatment in a
cohort of inflammatory bowel disease (IBD) patients (Cao, Wang, Liu, et
al., 2020) and occupational exposure to lead (Cao, Wang, Xi, et al.,
2020), polycyclic aromatic hydrocarbons (PAHs) (Cao et al., 2021; Xi et
al., 2023) and benzene (Cao et al., 2023). Whilst IBD patients had
higher mutant cell levels than healthy controls, azathioprine treatment
did not affect erythrocyte \emph{PIG-A} mutant frequency (Cao, Wang,
Liu, et al., 2020). Interestingly, \emph{PIG-A} mutant frequency was
higher in workers occupationally exposed to lead (Cao, Wang, Xi, et al.,
2020), PAHs (Cao et al., 2021) and benzene (Cao et al., 2023) (compared
to controls). The important work carried out in workers exposed to
benzene demonstrated that even below the occupational exposure limit
(OEL) of 1ppm, workers had elevated levels of erythrocyte
\emph{PIG-A}mutant cells and lymphocyte micronuclei compared to
controls, with the authors proposing a new OEL of 0.07ppm (Cao et al.,
2023). This study highlights the limitations of current DNA damage tests
particularly in the occupational exposure setting. In addition,
measuring urinary or airborne levels of genotoxins in this manner should
be widely implemented in studies where the exposure is known, with these
biomarkers of exposure complementing the \emph{PIG-A} biomarker of
effect. In order to avoid exposing workers to such health hazards,
the\emph{PIG-A} test should be included in a battery of genotoxicity
assays as well as quantifying genotoxin levels to re-define OELs and
ensure safe work environments. Whilst these tests will be useful as
biomarkers of exposure, the potential long-term carcinogenic effects can
be elucidated through longitudinal epidemiological studies.

The importance of studying large cohorts is paramount when developing a
biomonitoring tool. Disparate or non-reproducible results in some
publications could be due to the small number of individuals studied.
Whereas studies examining \emph{PIG-A} MF in hundreds of patients may be
more informative, population scale studies including multi-ethnicities,
wide age ranges and different exposures (diet, cigarette smoking,
medication and occupational genotoxins) are required. These studies will
require an international, collaborative effort, but are crucial to the
understanding of what drives mutant cell levels, and a necessity for
biomarker implementation.

\textbf{Table I:} The effect of different exposures on
phosphatidylinositol glycan class A (\emph{PIG-A} ) mutant frequency.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\begin{minipage}[b]{0.17\columnwidth}\raggedright\strut
\textbf{Exposure}\strut
\end{minipage} & \begin{minipage}[b]{0.17\columnwidth}\raggedright\strut
\textbf{Cell type}\strut
\end{minipage} & \begin{minipage}[b]{0.17\columnwidth}\raggedright\strut
\textbf{Test groups}\strut
\end{minipage} & \begin{minipage}[b]{0.17\columnwidth}\raggedright\strut
\textbf{Effect of exposure}\strut
\end{minipage} & \begin{minipage}[b]{0.17\columnwidth}\raggedright\strut
\textbf{Reference}\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Cigarette smoking\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Erythrocytes\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Non-cancer control cohort non-smokers (n=274) and smokers (n=26)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
No difference in \emph{PIG-A} mutant cell levels (p=0.186)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Lawrence et al., 2020)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Erythrocytes\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Male healthy volunteers (n=129)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
No difference between smoker and non-smoker (p=0.8594). No association
between \emph{PIG-A} and smoking duration (p=0.0541). Association
between PIG-A mutant frequency and cigarette pack/years
(p\textless{}0.0001).\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Cao et al., 2016)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Erythrocytes\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Non-cancer control cohort non-smokers (n=247) and smokers (n=29)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Smokers had \emph{PIG-A} mutant frequencies of over double that of
non-smokers (p=0.011) with mutant frequencies of 5.82 (95\% CI
2.79--9.52) and 2.8 (95\% CI 2.49--3.57) respectively.\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Haboubi et al., 2019)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Depleted Uranium\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
T-Lymphocytes\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Gulf war I veterans (n=35) Low-uU (n=22) Vs High-uU (n=13)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
No significant difference Low-uU mean mutant frequency
=18.13\(\pm\)4.85 High-uU mean mutant frequency = 9.45
\(\pm\) 0.81 P = 0.08\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
(McDiarmid et al., 2011)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Chemotherapy\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Erythrocytes\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Patients with different cancer types (n=10)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Pre-treatment \emph{PIG-A} mutant frequency was the same as healthy
controls. Minimal changes in mutant frequency during and post therapy
except for one patient undergoing Cisplatin and Etoposide therapy who
had 3x increase in \emph{PIG-A} mutant levels.\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Dobrovolsky et al., 2011)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Chemotherapy +/- Radiotherapy\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Erythrocytes\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Healthy volunteers (n=10) and cancer patients undergoing chemotherapy
+/- radiotherapy (n=27)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Healthy volunteer \emph{PIG-A} mutant frequency range =
0.00--5.00~\selectlanguage{ngerman}×~10\selectlanguage{english}\textsuperscript{-6} and cancer patients =
0.00--49.67~x~10\selectlanguage{english}\textsuperscript{-6}. No pre-treatment blood samples
taken so difficult to determine effect of therapy on mutant
levels.\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Horibata et al., 2016)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Radiotherapy\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Granulocyte\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Patients undergoing therapy for breast cancer (n=30). Five patients had
previously received chemotherapy.\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Lower mutant frequency during (p=0.0035) and after radiotherapy
treatment (p=0.006) compared to pre-treatment.\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Bonetto et al., 2021)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Azathioprine (AZA)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Erythrocyte\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
AZA treated inflammatory bowel disease (IBD) patients (n=36) and healthy
controls (n=36).\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
IBD patients exhibited a higher MF (6.10 \(\pm\) 4.44 \selectlanguage{ngerman}×
10\textsuperscript{-6}) than healthy volunteers (4.97 \(\pm\)
2.74 × 10\textsuperscript{-6}) (P = 0.0489). No association between AZA
treatment and MF.\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Cao, Wang, Liu, et al., 2020)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Lead\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Erythrocyte\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Workers occupationally exposed to lead (n=267) and healthy volunteers
from previous study (n=217).\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\emph{PIG-A} MFs were significantly higher in lead-exposed workers
(10.90 \selectlanguage{ngerman}± 10.7 × 10\selectlanguage{english}-6) than in a general population studied previously
(5.25 +- 3.6 x 10\selectlanguage{english}-6) (p \textless{}0.0001).\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Cao, Wang, Xi, et al., 2020)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Polycyclic Aromatic Hydrocarbons (PAH)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Erythrocyte\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
PAH exposed BBQ restaurant workers (n=70) and healthy controls (n=56).
Urinary PAH metabolites measured to determine individual exposure.\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
PAH exposed group had higher \emph{PIG-A} MFs than healthy controls
(p\textless{}0.001). A higher \emph{PIG-A} MF was associated with higher
PAH exposure determined by urinary metabolites (p=0.006).\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Cao et al., 2021)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Erythrocyte\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
PAH exposed coke oven workers (n=364), newly employed non-exposed
controls (n=34) and control group from non-industrially polluted area
(n=273).\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Coke oven workers had higher \emph{PIG-A} MF's of 21.01 \selectlanguage{ngerman}± 25.1 x
10\textsuperscript{-6} compared to 4.3 ± 3.02 x 10\textsuperscript{-6}
for newly employed non-exposed group and 5.45 ± 4.56 x
10\textsuperscript{-6} for the larger control group from non-industrial
city.\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Xi et al., 2023)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Benzene\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Erythrocyte\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Benzene exposed chemical plant workers (n=104) and controls (n=273) from
previous publication (Cao et al., 2016 and Cao et al., 2021).\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Benzene exposed workers had higher \emph{PIG-A} MF's of
15.96~\selectlanguage{ngerman}±~14.41~×~10\selectlanguage{english}\textsuperscript{-6} compared to controls who had an
average MF of 5.46~+-~4.56~x~10\selectlanguage{english}\textsuperscript{-6} (p\textless{}0.001).
Observed a significant association between \emph{PIG-A} MF and airborne
benzene exposure levels (r=0.501, p\textless{}0.001) measured by gas
chromatography.\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
(Cao et al., 2023)\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\textbf{The \emph{PIG-A} mutation test in disease}

Whilst the applicability of this mutation assay has mostly been
investigated in humans exposed to defined mutagenic agents, the
application of the \emph{PIG-A} test in disease detection has also been
explored. Reports by Nichols et al., showed that patients with
pancreatic cancer had elevated levels of \emph{PIG-A} mutant
erythrocytes (5.775 \selectlanguage{ngerman}× 10\textsuperscript{-6} (95\% CI 4.777-10) compared
to non-cancer controls (4.211 × 10\textsuperscript{-6} (95\% CI
1.39-5.16)) (Nichols et al., 2023). Although this difference was subtle,
it may indicate an underlying individual susceptibility to mutation and
hence risk of malignancy. In a larger cohort studied by Haboubi et al,
oesophageal adenocarcinoma patients had elevated levels of mutant
erythrocytes (9.75 x 10\textsuperscript{-6} (95\% CI 4.36-17.52))
compared to healthy volunteers (2.8 x 10\textsuperscript{-6} (95\% CI
2.21-3.57)), patients with gastro-oesophageal reflux disease (3.44 x
10\textsuperscript{-6} (95\% CI 1.56-5.43)) and patients with the
pre-malignant condition Barrett's oesophagus (4.35 x
10\textsuperscript{-6} (95\% CI 2.49-6.09)). Moreover, the number
of\emph{PIG-A} mutant cells was associated with tumour staging and
metastatic disease. Elevated \emph{PIG-A} mutant frequency was
identified as risk factor for oesophageal cancer independent of age and
gender using general linear model analyses (Haboubi et al., 2019). Two
publications have assessed \emph{PIG-A} mutant cells in IBD patients.
Firstly, Baig and colleagues found no significant increase in mutant
reticulocytes in paediatric IBD patients although 10 patients with
higher micronucleus frequencies all had established disease (Baig et
al., 2020). Secondly, Cao et al., found significantly elevated
erythrocyte mutant cell number in adult Chinese IBD patients, although
these were all undergoing azathioprine treatment (Cao, Wang, Liu, et
al., 2020). Whilst the mechanistic link between solid tumour development
and induction of circulating \emph{PIG-A} mutation levels remain
unclear, with inflammatory driven malignancies such as oesophageal
cancer and IBD, circulating blood cells (RETs or immature red blood
cells) may be exposed to inflammatory mediators and subsequently
accumulate DNA damage which results in a \emph{PIG-A} mutant phenotype
in erythrocytes.

\textbf{Technical differences}

When measuring such scarce cells as \emph{PIG-A} mutant erythrocytes, it
is important to note that slight methodological variations can
significantly alter results. For example, using antibodies that target
the GPI-AP's CD55 and CD59 in combination may reduce the number of false
positive mutant cells compared to targeting only one GPI-AP (see Figure
2). Alternatively, GPI anchor status can be measured using a fluorophore
conjugated variant of proaerolysin. Proaerolysin is an inactive form of
the bacterial toxin aerolysin which binds to GPI anchors, permitting
direct assessment of \emph{PIG-A} status. Whilst a FITC-conjugated form
of proaerolysin is commercially available (Cedarlane, Canada), most
research groups have chosen to use antibodies that target GPI-AP's.

Furthermore, the type and/or performance of the flow cytometer used may
impact results. Previous work carried out in our lab revealed that
variations between cytometers exists. For example, the Facs Aria I (BD
Biosciences) on average scored a higher number of mutant cells than the
Navios flow cytometer (Beckman Coulter) although there was a strong
correlation between the two machines (Haboubi et al., 2019). Flow
cytometer performance characteristics that may impact mutant cell
scoring include laser strength and alignment, flow speed, stream
characteristics and cleanliness of inner tube networks. These factors
can be mitigated with routine maintenance and quality control. Whilst it
is difficult to account for slight variations that could significantly
influence classification of \emph{PIG-A} phenotype and hence falsely
classify a mutant cell, \emph{in vitro} cell lines with
known\emph{PIG-A} status can be used as a quality control. For example,
we have generated a \emph{PIG-A} mutant L5178Y mouse lymphoma cell line
by treating wild type cells with the methyl methanesulfonate and using
magnetic bead enrichment followed by fluorescence activated cell sorting
(FACS) to create a cell line consisting of
\textasciitilde{}96\%\emph{PIG-A} mutant cells which is routinely used
to check for flow cytometer variations (Haboubi et al., 2019).

The gating strategy applied to categorise mutant cells is also very
important to consider. Inflating the lower fluorescence limit for mutant
classification could falsely classify erythrocytes with lower (but not
absent) GPI-AP staining as \emph{PIG-A} mutant. These intermediate cells
may have less GPI anchors or GPI-AP's due to incomplete staining,
shearing off of GPI-AP's during sample processing or may pass through
the laser stream at an angle where fewer GPI-APs are exposed and so less
fluorophores are excited by the corresponding laser. This is
particularly important when measuring \emph{PIG-A} status of biconcave
erythrocytes. The gating strategy usually involves the gating of singlet
erythrocytes using anti-CD235a (erythrocyte specific marker) followed by
the gating of \emph{PIG-A} mutant erythrocytes using an unstained or
mutant mimic control (also known as an instrument calibration standard)
with this methodology being adopted by most research groups (Cao et al.,
2016; Dertinger et al., 2015; Dobrovolsky et al., 2011; Haboubi et al.,
2019; Lawrence et al., 2020). As this \emph{PIG-A} erythrocyte test only
requires a finger prick volume of whole blood, re-running samples from
individuals with known mutant frequency can also act as an additional
quality control.

Although this test is quick to perform, batching samples would be most
beneficial. Not only would this save time and money, but it would also
allow the transport of samples from regional/remote locations to a
central processing laboratory. However, the stability of
\emph{PIG-A}status post blood-draw has not been measured over a
prolonged period. Within our research group we have demonstrated that
erythrocyte\emph{PIG-A} mutant frequency is stable up to 72 hours post
venepuncture when collected in K\textsubscript{2} EDTA coated
vacutainers and stored at room temperature (unpublished, data not
shown). Dertinger and colleagues have demonstrated \emph{PIG-A} mutant
stability of over a week when the sample was kept at 4°C (Dertinger,
2015 \#21). After this time, the mutant frequency increases, potentially
due to loss of membrane integrity, GPI anchors and/or GPI-APs as cells
start to die. Cryopreservation medium for human samples similar to that
supplied by Litron Laboratories (New York, USA) for mouse and rat blood
could help to make sample batching of human blood a reality.

\textbf{Cell types investigated for \emph{PIG-A} status}

There are multiple different reports evaluating which human cell type is
most suitable for the \emph{PIG-A} assay, including the use of
erythrocytes, reticulocytes (RETs), granulocytes, and peripheral blood
mononuclear cells (PBMCs) (Table II). The most frequently used cell type
for measuring \emph{PIG-A} mutations is erythrocytes as only a finger
prick volume of whole blood (3-10\(\mu\)l) is required to
measure the\emph{PIG-A} status of over a million cells. This is crucial
to identify such rare events as \emph{PIG-A} mutant cells, where
millions of cells need to be interrogated. Furthermore, with the
addition of the anti-CD235a antibody, blood pre-processing is minimised,
and the high throughput technology of flow cytometry is exploited.
Alongside RBC\emph{PIG-A} analysis, some groups have also measured the
percentage of reticulocytes (\%RET) to account for abnormalities in
haematopoietic function (Cao et al., 2016; Dertinger et al., 2015).
However, no compromise in \%RET has been observed to date (Dertinger et
al., 2015; Xi et al., 2023).

Some groups favour the use of alternative blood cells to
measure\emph{PIG-A} mutation as mature erythrocytes that lack the
complement inhibitors CD55 and CD59 may undergo complement mediated
lysis (Ruiz-Arguelles \& Llorente, 2007). Although we believe this
effect to be minimal, evidence suggests mutant erythrocytes may be
subject to modest selective pressure (Dertinger et al., 2015). Despite
this disadvantage to using erythrocytes over RETs, the population of
reticulocytes found in human peripheral blood is low in comparison, and
therefore the use of erythrocytes is much more rapid, and simple to
carry out. Furthermore, Dertinger and colleagues have noted that
inter-individual variation of RET \emph{PIG-A} mutant frequency may be
as high as 30-fold (Dertinger et al., 2015). However, RETs may be the
most desirable cell type for analysis when measuring mutant induction
post exposure as such an effect may be observed sooner than with RBCs
which need to enucleate and mature to yield a mutant phenotype post
exposure. Importantly, \emph{in vitro Pig-A} analysis in the L5178Y cell
line has shown a phenotypic expression period of 8 days post treatment
(David et al., 2018).

The utility of granulocytes in measuring \emph{PIG-A} mutation status
has also been explored. As with RETs, mutation induction post exposure
may be observed sooner than with RBCs. However, the short life span of
granulocytes (1-2 days) provides only a short window in which mutant
cell levels can be accurately measured following a mutagenic event.
Although granulocyte mutant cell levels are present at approximately the
same frequency as erythrocyte mutant cells in healthy volunteers
(Rondelli et al., 2013), using granulocytes to measure
\emph{PIG-A}mutation requires blood pre-processing and a more complex
flow cytometry gating strategy (Bonetto et al., 2021; Peruzzi et al.,
2010; Rondelli et al., 2013). Peripheral blood mononuclear cells (PBMCs)
have also been interrogated for \emph{PIG-A} mutation status. Like
granulocytes, this process requires cell isolation from whole blood
prior to flow cytometry. Two studies carried out by McDiarmid et al.,
and Ware et al., detected higher background mutant frequencies in PBMCs
(compared to healthy volunteer erythrocytes published elsewhere) of
18.13 x 10\textsuperscript{-6} (McDiarmid et al., 2011) and 18 x
10\textsuperscript{-6} mutants (Ware, Pickens, DeCastro, \& Howard,
2001) respectively. This technique also required the subculture of PBMCs
under Aerolysin selection. Although there are advantages and
disadvantages to using each cell type (Table II), the decision of which
type to use should be based on the type and requirements of the study.

\textbf{Table II:} Advantages and disadvantages of exploiting different
blood cell types for the phosphatidylinositol glycan class A
(\emph{PIG-A} ) mutation assay.\selectlanguage{english}
\begin{longtable}[]{@{}lll@{}}
\toprule
\begin{minipage}[b]{0.30\columnwidth}\raggedright\strut
\textbf{Cell type}\strut
\end{minipage} & \begin{minipage}[b]{0.30\columnwidth}\raggedright\strut
\textbf{Advantages}\strut
\end{minipage} & \begin{minipage}[b]{0.30\columnwidth}\raggedright\strut
\textbf{Disadvantages}\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
Erythrocytes\strut
\end{minipage} & \begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
Small volume of blood (3-10\(\mu\)l) required so suitable for
finger prick test and multiple sampling. Doesn't require any blood
pre-processing so less hands on time. Reticulocyte percentage (\%RET) in
whole blood can be analysed simultaneously as a measure of
haematopoietic function. Can detect an accumulation of DNA damage from
repeat dosing over a prolonged period; long term effect.\strut
\end{minipage} & \begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
Cannot confirm mutant phenotype by DNA sequencing. Unsuitable for
cryopreservation and batching samples from remote locations.
\emph{PIG-A} mutant erythrocytes may be subject to complement mediated
lysis.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
Reticulocytes\strut
\end{minipage} & \begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
May be able to observe mutant induction sooner post exposure than
erythrocytes. Reticulocyte percentage (\%RET) in whole blood can be
analysed simultaneously as a measure of haematopoietic function.
\emph{PIG-A} mutant reticulocytes would not be sensitive to complement
mediated lysis.\strut
\end{minipage} & \begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
Proportion of reticulocytes is low in whole blood compared to
erythrocytes so would require larger blood volume.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
Granulocytes\strut
\end{minipage} & \begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
May be able to observe mutant induction sooner post exposure than
erythrocytes. Allows for mutation confirmation using DNA
sequencing.\strut
\end{minipage} & \begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
Requires blood pre-processing and a more complex flow cytometry gating
strategy. Short life span of 1-2 days provides a small window of
opportunity to capture mutant cells.\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
Peripheral blood mononuclear cells\strut
\end{minipage} & \begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
Allows for mutation confirmation using DNA sequencing.\strut
\end{minipage} & \begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
Published methodology includes subculture of PBMCs under Aerolysin
selection. Requires larger volume of blood. Current studies show higher
background level of mutant cells compared to erythrocytes.\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\textbf{Future directions}

More research is required to assess the effectiveness of detecting
genotoxic exposures in humans using the \emph{PIG-A} assay, especially
in different blood cell types (Bonetto et al., 2021). International
collaborative projects are required and are anticipated to provide
further evidence of the application of the human \emph{PIG-A} assay.
Studies are necessary to understand the role of this reporter gene in
detecting genotoxin exposure in order to interpret future research
findings. We also need to assess the long term follow up of patients
following baseline \emph{PIG-A} measurement to link the level of mutant
frequency to development of later cancers and other chronic disease.
This has proved to be fascinating in the lymphocyte MN field (Bonassi et
al., 2007) and can be carried out using long-term epidemiological
studies.

Moreover, it is not only crucial to determine the individual
consequences of high levels of \emph{PIG-A} mutant cells but also to
confirm the degree to which GPI anchor deficiency is comparable
to\emph{PIG-A} mutation. Confirmation of \emph{PIG-A} mutation has been
carried out in GPI-deficient human T-lymphocytes (Ware et al., 2001) and
granulocytes (Araten et al., 1999). Base-pair substitutions, small
frameshift insertions and large deletions were identified in
GPI-deficient T-lymphocytes isolated using aerolysin selection (Ware et
al., 2001). \emph{PIG-A} mutations including base-pair changes leading
to single amino acid replacements were identified in granulocytes
isolated by flow sorting from healthy volunteers. All mutations were
found to either interfere with protein function or lead to protein
truncation (Araten et al., 1999). Although confirmatory mutant
sequencing is impossible in anucleate erythrocytes, periodic assessment
in alternative blood cell types may provide information regarding the
nature of mutation and also the type of genotoxic exposure.

Although there is still some uncertainty about whether erythrocytes are
a suitable cell population for a human \emph{PIG-A} assay, the
proof-of-concept studies in the current literature indicates that the
assay could be helpful for monitoring populations exposed to potential
genotoxins. Possible clinical applications of the assay may include the
diagnosis of DNA repair-deficient cancer-prone 'mutator' phenotypes or
monitoring chemotherapy patients for drug-induced mutation as a
predictor of susceptibility to the formation of secondary tumours.

Another area for refinement for this test is the need for standard
protocols for not only sample preparation but also data analysis. When
measuring such rare cells, any subtle changes in the staining protocol
or data acquisition, for example defining mutant gates on the flow
cytometer can have an impact on results. Whilst the
published\emph{PIG-A} mutant data in healthy controls is remarkably
consistent, a standard protocol would potentially minimise
inter-laboratory variation and allow for comparison of results between
research groups. Furthermore, the true potential of the \emph{PIG-A}
assay will be observed when we can overcome the issue of sample batching
and are able to provide this test in low-income countries where
mutagenic hazards and exposure-related diseases are often more common.

Combining this assay with others focussed on different mutational
endpoints, such as the MN test or Comet assay, can enhance its
effectiveness (Cao et al., 2023). Mutagenic exposures that act through
different mechanisms and may give contrasting results in tests that
measure a particular endpoint. A combination of tests including CBMN
(Fenech et al., 2011), Comet (Milic et al., 2021) hypoxanthine-guanine
phosphoribosyltransferase (HPRT) (Townsend et al., 2018)
and\(\gamma\)H2AX assay (Kopp, Khoury, \& Audebert, 2019) may
improve test sensitivity and inform us about the nature of exposures.
Research in our group indicates that the correlation between individual
\emph{PIG-A}mutant frequency and lymphocyte MN levels is not good with
individuals often having high levels of \emph{PIG-A} mutation or MN, but
not vice versa (Figure 5). This suggests that using only one test is not
sufficient to detect elevated levels of DNA damage in all individuals.
Furthermore, when more than one DNA damage endpoint (\emph{PIG-A} ,
micronuclei or COMET) has been measured in humans in response to a
genotoxic exposure, positive associations have not been found with all
endpoints. This could be due to the test used; for example, the
RBC\emph{PIG-A} assay may represent an accumulation of exposure over a
prolonged period given the time taken for immature RBCs or
haematopoietic stem cells to mature into \emph{PIG-A} mutant RBCs. Given
that the DNA damage evaluated in the COMET assay can be repaired, it is
perhaps not surprising that not all genotoxins (i.e., lead) produce a
positive response (Cao, Wang, Xi, et al., 2020). Aneugenic or
clastogenic type DNA damage that can be observed in the lymphocyte
micronucleus assay is essentially a snapshot of damage detected at the
time of blood sampling which may otherwise be repaired \emph{in vivo} so
represents a shorter time window between exposure and measurable blood
cell effects. This short time frame of opportunity may also be the case
for the COMET assay. Together with the mechanistic differences of these
endpoints and the differences in fate of the mutated cells, proves the
need for the combination of complementary assays to comprehensively
recognise genotoxic exposures (Torous et al., 2023).

\textbf{Hosted file}

\verb`image5.emf`  available at \url{https://authorea.com/users/656289/articles/661744-the-pig-a-gene-mutation-assay-in-human-biomonitoring-and-disease}

\textbf{Figure 5:} Erythrocyte phosphatidylinositol glycan class A
(\emph{PIG-A} ) mutant frequency and lymphocyte micronucleus levels for
141 individuals (R=0.2124, p=0.0114).

\textbf{Conclusion}

As evidenced by the current literature, the \emph{PIG-A} mutation test
is a promising tool for human biomonitoring and disease. With further
technological development, test battery development and international
collaboration, we expect this simple, high-throughput assay to advise us
on both harmful and beneficial exposures to genotoxins and
chemo-preventative agents. This will ultimately lead to improved
lifestyle choices, reduced occupational hazards and even earlier
diagnosis of high-risk cancer patients and other cancer associated
inflammatory diseases such as IBD.

\textbf{Conflicts of interest}

The authors declare no conflicts of interest

\textbf{Author contributions}

RL, KM and HN carried out and wrote the manuscript under supervision by
GJ. HH, LT, SD and LW contributed ideas and edited the manuscript.

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