The association of neurodevelopmental abnormalities, congenital heart and renal defects in a tuberous sclerosis complex patient cohort

Abstract

Background
Tuberous sclerosis complex (TSC) is a rare multi-system genetic disorder characterised by the presence of benign tumours throughout multiple organs including the brain, kidneys, heart, liver, eyes, lungs and skin, in addition to neurological and neuropsychiatric complications. Intracardiac tumour (rhabdomyoma), neurodevelopmental disorders (NDDs) and kidney disorders (KD) are common manifestations of TSC and have been linked with TSC1 and TSC2 loss-of-function mutations independently, but the dynamic relationship between these organ manifestations remains unexplored. Therefore, this study aims to characterise the nature of the relationship specifically between these three organs’ manifestations in TSC1 and TSC2 mutation patients.

Methods
Clinical data gathered from TSC patients across South Wales registered with Cardiff and Vale University Health Board (CAV UHB) between 1990 and 2020 were analysed retrospectively to evaluate abnormalities in the heart, brain and kidney development. TSC-related abnormalities such as tumour prevalence, location and size were analysed for each organ in addition to neuropsychiatric involvement and were compared between TSC1 and TSC2 mutant genotypes. Lastly, statistical co-occurrence between organ manifestations co-morbidity was quantified, and trajectories of disease progression throughout organs were modelled.

Results
This study found a significantly greater mutational frequency at the TSC2 locus in the cohort in comparison to TSC1. An equal proportion of male and female patients were observed in this group and by meta-analysis of previous studies. No significant difference in characterisation of heart involvement was observed between TSC1 and TSC2 patients. Brain involvement was seen with increased severity in TSC2 patients, characterised by a greater prevalence of cortical tubers and communication disorders. Renal pathology was further enhanced in TSC2 patients, marked by increased bilateral angiomyolipoma prevalence. Furthermore, co-occurrence of NDDs and KDs was the most positively correlated out of investigated manifestations, regardless of genotype. Analysis of disease trajectories revealed a more diverse clinical outcome for TSC2 patients: however, a chronological association of rhabdomyoma, NDD and KD was most frequently observed for TSC1 patients.

Conclusions
This study marks the first empirical investigation of the co-morbidity between congenital heart defects (CHD), NDDs, and KDs in TSC1 and TSC2 patients. This remains a unique first step towards the characterisation of the dynamic role between genetics, heart function, brain function and kidney function during the early development in the context of TSC.

Full text

Robinsonetal. BMC Medicine (2022) 20:123
https://doi.org/10.1186/s12916-022-02325-0
RESEARCH ARTICLE
The association ofneurodevelopmental
abnormalities, congenital heart andrenal
defects inatuberous sclerosis complex patient
cohort
Jessica Robinson1,2, Orhan Uzun3*, Ne Ron Loh3,4, Isabelle Rose Harris1,2, Thomas E. Woolley5,
Adrian J. Harwood1,2, Jennifer Frances Gardner3 and Yasir Ahmed Syed1,2*
Abstract
Background: Tuberous sclerosis complex (TSC) is a rare multi-system genetic disorder characterised by the presence
of benign tumours throughout multiple organs including the brain, kidneys, heart, liver, eyes, lungs and skin, in addi-
tion to neurological and neuropsychiatric complications. Intracardiac tumour (rhabdomyoma), neurodevelopmental
disorders (NDDs) and kidney disorders (KD) are common manifestations of TSC and have been linked with TSC1 and
TSC2 loss-of-function mutations independently, but the dynamic relationship between these organ manifestations
remains unexplored. Therefore, this study aims to characterise the nature of the relationship specifically between
these three organs’ manifestations in TSC1 and TSC2 mutation patients.
Methods: Clinical data gathered from TSC patients across South Wales registered with Cardiff and Vale University
Health Board (CAV UHB) between 1990 and 2020 were analysed retrospectively to evaluate abnormalities in the heart,
brain and kidney development. TSC-related abnormalities such as tumour prevalence, location and size were analysed
for each organ in addition to neuropsychiatric involvement and were compared between TSC1 and TSC2 mutant
genotypes. Lastly, statistical co-occurrence between organ manifestations co-morbidity was quantified, and trajecto-
ries of disease progression throughout organs were modelled.
Results: This study found a significantly greater mutational frequency at the TSC2 locus in the cohort in comparison
to TSC1. An equal proportion of male and female patients were observed in this group and by meta-analysis of previ-
ous studies. No significant difference in characterisation of heart involvement was observed between TSC1 and TSC2
patients. Brain involvement was seen with increased severity in TSC2 patients, characterised by a greater prevalence
of cortical tubers and communication disorders. Renal pathology was further enhanced in TSC2 patients, marked by
increased bilateral angiomyolipoma prevalence. Furthermore, co-occurrence of NDDs and KDs was the most posi-
tively correlated out of investigated manifestations, regardless of genotype. Analysis of disease trajectories revealed a
more diverse clinical outcome for TSC2 patients: however, a chronological association of rhabdomyoma, NDD and KD
was most frequently observed for TSC1 patients.
© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
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Open Access
*Correspondence: Uzun@cardiff.ac.uk; syedy@cardiff.ac.uk
2 School of Bioscience, The Sir Martin Evans Building, Museum Ave,
Cardiff CF10 3AX, UK
3 University Hospital of Wales, Heath Park, Cardiff CF10 3AX, UK
Full list of author information is available at the end of the article
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Robinsonetal. BMC Medicine (2022) 20:123
Background
Tuberous sclerosis complex (also known as tuberous
sclerosis or TSC) is a multi-system autosomal dominant
neurocutaneous genetic disorder prevalent in 1 in 6000
to 1 in 12,000 live births [1]. e disease results from a
variety of loss-of-function mutations in the tumour sup-
pressor genes TSC1 and TSC2, with more than 200 TSC1
and nearly 700 TSC2 unique allelic variants having been
identified in TSC patients thus far [2, 3]. e condition
is classified as tuberous sclerosis complex 1 or 2 depend-
ing on whether their mutation falls within the respective
TSC1 or TSC2 genetic loci. However, genetic testing has
revealed TSC2 mutations account for an overwhelm-
ing 70–90% of cases, which are often correlated with
a more severe clinical outcome [2, 4–7]. TSC presents
diverse clinical manifestations throughout multiple organ
systems, most notably hamartomas (a type of benign
tumour) in the brain, heart, kidneys, skin and lungs
[8]. Additionally, 90% of TSC patients also suffer from
TSC-associated neuropsychiatric disorders (TAND), an
umbrella term describing the range of neurodevelopmen-
tal (NDD), psychiatric, psychosocial and behavioural dis-
orders which vary from patient to patient [9, 10]. TSC is a
highly complex and variable disease; however, it has been
reported that fewer than half of individuals with TSC
receive adequate centralised coordinated care in adher-
ence to TSC patient management guidelines [11]. In
light of this, it is imperative that all TSC patients receive
coordinated care and that this care is supported by man-
agement guidelines that reflect up to date research and
accounts for the co-morbidity of TSC manifestations,
rather than reviewing each on an independent basis.
Cardiac rhabdomyoma (CR) accounts for 45% of pri-
mary cardiac tumours in children, making it the most
common form of childhood cardiac tumour [12, 13].
Approximately 70–90% of children with CRs will also
be diagnosed with TSC and conversely 90% of children
with TSC under 2 years old will either have single or
multiple CRs [12, 14]. CRs are a variety of benign mes-
enchymal tumour composed of cardiac myocytes, cat-
egorised within a group of late-onset congenital heart
diseases [15]. Rhabdomyoma can appear as a singu-
lar or multiple tumours and are able to develop in all
myocardial areas, although are most frequently located
within the septal or ventricular walls wherein they can
range in size from only a few millimetres to several
centimetres [12, 16]. Although benign in histology, a
minority of patients with CRs may experience symp-
toms before and shortly after birth which could include
arrhythmias and/or obstruction of inflow or outflow
by tumours which may lead to ventricular dysfunction
and ultimately heart failure [12, 15]. Multiple congeni-
tal CRs are a well-established early marker for TSC and
are often one of the first warning signs that lead to a
diagnosis, appearing prenatally at around 20–30 weeks’
gestation and detectable by foetal echocardiography,
which is now the primary diagnostic tool for paediat-
ric cardiac tumour evaluation [17, 18]. Typically, spon-
taneous regression of CRs occurs within the first year
of life for the majority of TSC patients, with preva-
lence decreasing to approximately 20% once the patient
reaches 2 years old [8, 12].
TSC manifests in the brain as anatomical abnor-
malities and other neurological complications such
as seizures, cognitive impairment and behavioural
concerns. Around 90% of TSC patients exhibit some
form of classic TSC brain pathology including: corti-
cal tubers, subependymal nodules (SEN), subependy-
mal giant cell astrocytoma (SEGA) and white matter
migration tracts [19].
Previous studies have observed these brain lesions
as early as 20 weeks of gestation in the developing
foetal brain [20]. e most common brain manifesta-
tions observed in TSC are cortical tubers (glioneuronal
hamartomas), small regions of cerebral cortical dys-
plasia that appear during early brain development and
display impaired or absent cortical lamination as well
as the presence of dysmorphic neurons, and can range
from only a few millimetres to several centimetres in
size [21, 22]. Unlike cortical tubers, SEN and SEGA are
benign tumours composed of glial neuroastrocytes and
tend to form deeper within the brain, particularly along
the ependymal lining of the ventricles [23].
Approximately, 80% of TSC patients develop SEN,
which are most commonly located near the caudate
nucleus behind the foramen of Monro, where they
usually appear in their multiples, with singular lesions
ranging from 2 to 10mm in diameter and remaining
stable in size in most cases [24, 25]. Whilst the major-
ity of SEN cases are asymptomatic, 5–10% of cases
Conclusions: This study marks the first empirical investigation of the co-morbidity between congenital heart defects
(CHD), NDDs, and KDs in TSC1 and TSC2 patients. This remains a unique first step towards the characterisation of the
dynamic role between genetics, heart function, brain function and kidney function during the early development in
the context of TSC.
Keywords: TSC1, TSC2, Rhabdomyoma, Neurodevelopmental disorders, TAND, Kidney lesions
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Robinsonetal. BMC Medicine (2022) 20:123
degenerate into SEGA which can grow large enough to
obstruct the foramen of Monro resulting in intracranial
hypertension, blindness or death if untreated [26].
In addition to anatomical abnormalities in neurology,
epilepsy is a further major cause of mortality and mor-
bidity in TSC patients, with prevalence reported to range
from 63 to 93% [27]. Epilepsy and infantile spasm associ-
ated with TSC first become apparent usually within the
first year of life and has a strong association with both
neurodevelopmental and cognitive problems [28]. TSC is
also associated with a diverse range of cognitive, behav-
ioural and psychiatric manifestations which are referred
to as TSC-associated neuropsychiatric disorders (TAND)
by specialists.
TAND can be investigated at six levels: behavioural,
psychiatric, intellectual, academic, neuropsychological
and psychosocial [10]. In total, it is estimated that around
90% of TSC individuals will experience some features
consistent with TAND over their lifetime [29]. Many dis-
orders under the TAND umbrella also overlap with the
Diagnostic and Statistical Manual of Mental Disorders,
5th Edition (DSM-5) classification of neurodevelopmen-
tal disorders. Such disorders within this category include
intellectual disabilities (both intellectual disability (ID)
and global/developmental delay (GDD), communication
disorders, autism spectrum disorder (ASD), attention-
deficit/hyperactivity disorder (ADHD) and motor dis-
orders [30]. e most frequent NDDs burdening TSC
patients are ID and ASD, which affect 50% of individuals
and share common risk factors including the presence of
TSC2 mutation, structural brain abnormalities and epi-
lepsy [31].
Renal manifestations of TSC are the second most
observed symptom of the disease after brain manifes-
tations, with renal angiomyolipoma (AMLs) and renal
cystic disease present in 80% and 30% of individuals,
respectively [32, 33]. Renal AMLs are the most com-
mon type of benign renal tumour and have a prevalence
of 0.2–0.6% in the general population, with 20% of these
cases being associated with TSC [34]. ese tumours are
classified as a heterogenous group of neoplasms and are
composed of three elements in variable amounts; blood
vessels (angio-), smooth muscle (myo-) and adipose tis-
sue (lipo-) [35]. Renal AMLs are present in approxi-
mately 75% of TSC patients and whilst the majority of
cases remain asymptomatic when tumours are small,
larger tumours may result in loin pain, catastrophic
haematuria and hypertension [34, 36]. Renal cysts are
a secondary manifestation of TSC in the kidneys, how-
ever are observed with less frequency than AMLs [32].
Cysts exhibit two modes of presentation: the most com-
mon being single or multiple lesions that are rarely
symptomatic and histologically uniform, and the other
presentation involving large, symptomatic cysts as a
result of polycystic kidney disease (PKD), which is linked
to deletions of TSC2 with contiguous deletion of adjacent
PKD1 [37].
is study seeks to systematically evaluate abnor-
malities in the heart, brain and kidney development in
patients with TSC1 and TSC2 mutations and establish
an association between the three as no other study has
done before (Fig.1A). ese three organ complications
were selected initially as they are the most commonly
investigated manifestation. Correlation between TSC
gene mutations and incidence of CR, kidney disorders
and poorer neurodevelopmental outcomes in children
have long since been investigated independently of one
another, but few studies have attempted to establish a
direct link between two of these variables, let alone three.
To achieve this, a retrospective clinical study was con-
ducted using data from TSC patient databases at Cardiff
and Vale University Health Board (CAV UHB). is TSC
lifespan centre is the only referral clinic for South Wales
and the only hospital performing TSC genetic testing for
the 30-year study period. Using this cohort, a breakdown
of comorbidity between CR, NDDs and KDs in both
TSC1 and TSC2 patients will be presented which will
provide a clear genotype-phenotype profile of these three
organ manifestations of TSC. e outcomes of this study
may inform future clinical recommendations for TSC
patient management for comorbidity between CR, NDDs
and RDs and direct future clinical strategy which consid-
ers comorbidity of these three manifestations as a direct
link of one another instead of being treated as independ-
ent disorders.
Methods
Data collection
is investigation is a retrospective cohort study of
clinical data from TSC patients that has been collected
by Cardiff and Vale University Health Board (CAV
UHB) over a 30-year period. e clinical patient data-
base used includes 160 anonymous patients situated all
across South Wales who were referred to the hospital
and fulfilled the current TSC clinical diagnostic criteria
either prenatally, at birth, or at follow-up appointments
between 1990 and up until the end of 2020 [38]. is
database of registered patients with TSC uses multiple
sources of patient data ascertainment which includes
patient diagnostic data from multiple hospital depart-
ments such as the Institute of Clinical Genetics, Paedi-
atric Cardiology, Neurology, Renal Unit, Dermatology,
Ophthalmology and Respiratory medicine. Genetic data
was logged in accordance with standard nomenclature
recommendations by the Human Genome Variation
Society (HGVS) as used in practice by the Institute of
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Robinsonetal. BMC Medicine (2022) 20:123
Fig. 1 Graphical abstract and flow chart of the study depicting exclusion criteria for data analysis during this investigation. A The aim of the
study was to look at association of comorbidities of the tuberous sclerosis complex (TSC1/2) on clinical organ manifestations of the heart, brain
and kidney using the TSC patient cohort of 30 years referred to Cardiff and Vale University Health Board (CAV UHB). B Raw data from 160 patients
with TSC provided by CAV UHB was filtered according to outlined exclusion criteria to improve cohort suitability for data analysis. Patients were
separated into either TSC1 group or TSC2 group depending on results from genetic testing, and respective sample sizes are summarised. TSC,
tuberous sclerosis complex; CAV UHB, Cardiff and Vale University Health Board
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Robinsonetal. BMC Medicine (2022) 20:123
Medical Genetics in Cardiff. NDD data was also recorded
and standardised in line with the Diagnostic and Statis-
tical Manual of Mental Disorders, 5th Edition (DSM-
5) classifications of NDDs; however, this is likely to be
incomplete due to a frequently observed treatment and
assessment gap of TAND in the UK [29]. Lastly, cardiac,
renal and neurological data were collected in a more gen-
eralised standard format, with a general descriptor such
as ‘rhabdomyoma’ for cardiac information, ‘AML’ or ‘cyst’
for renal information and ‘cortical tuber’, ‘SEN’, ‘SEGA’ or
‘epilepsy’ for neurological information.
Ethical approval of this retrospective review study was
not necessary as the data was retrieved anonymously
from the previously collected clinical information in vari-
ous databases. Nevertheless, this study was approved as
an audit project by the Cardiff and Vale University Health
Board and registered on the Clinical Audit Database, ref-
erence no: 9618.
Identication ofgenetic abnormalities
Genetic data of specific TSC mutations was kindly pro-
vided by the Institute of Medical Genetics in Cardiff.
Data was obtained either via previous research testing
or attendance of patients at the resident TSC clinic, and
records and results of these tests are held on the Medi-
cal Genetics departmental system, Shire. Historically, the
Institute of Medical Genetics employed Sanger sequenc-
ing (SS) methods to identify mutations during genetic
testing; however, this has since evolved in favour of the
next-generation sequencing (NGS) technology. Iden-
tification of TSC1/2 mutations is a vital step towards
establishing a clear clinical diagnosis of TSC, with the
recommendation of the 2012 and updated 2021 Inter-
national TSC Consensus Conference suggesting that
identification of a pathogenic TSC1 or TSC2 mutation
should be sufficient for the diagnosis or prediction of
TSC regardless of clinical findings [38]. With this recom-
mendation in mind, an exclusion criterion was proposed
where in order for a patient to be included in data analy-
sis they must have been genetically tested and identified
with a TSC1 or TSC2 mutation in addition to known sex
to improve the quality of data records and improve the
suitability of the cohort for data analysis (Fig.1B).
All genetic alterations were annotated and reported in
accordance with recommendations of the HUGO Gene
Nomenclature Committee (https:// www. genen ames. org/;
http:// www. hgvs. org/). Single-nucleotide variants (SNVs)
and insertion-deletion mutations (indels) were reported
using standard mutation nomenclature based on coding
DNA reference sequences or protein-level amino acid
sequences which require the prefixes of ‘c.’ or ‘p.’, respec-
tively [39]. Exonic sequences are numbered according to
their sequential position from the initiation codon to the
stop codon and intronic sequences are also numbered
in relation to the exonic coding sequence. Each record
was then grouped into one of several mutation type
descriptions; nonsense, missense, intronic (missense),
frameshift, large deletion or ‘unknown’ when there were
no further details of genetic mutation besides simply
‘TSC1 mutation’ or ‘TSC2 mutation’.
Mathematical modelling
In order to evaluate the association between organ sys-
tems in the context of TSC and provide probabilities of
possible disease trajectories throughout life, mathemati-
cal modelling techniques were explored in collabora-
tion with Cardiff University School of Mathematics and
employed in this study. Comorbidity data was provided
for each patient in addition to the age at which each
organ system manifestations of TSC was first detected
in the patient. e terminology was specified where
three outcomes were defined; CHD, where a patient pre-
sents rhabdomyoma; NDD, where a patient has one or
more neurodevelopmental disorders; and KD, where a
patient presents with kidney lesions. Co-occurrence was
denoted in Boolean operator terms as the ‘cap’ notation
visually represented by ‘∩’, so for example where CHD
denotes the presence of a CHD, NDD denotes NDD and
KD denotes renal involvement and CHD ∩ NDD would
represent a scenario where a patient has both a CHD
and an NDD. Using temporal data, supposing we know
where organ manifestations start originally, the aim is to
predict where they will appear next for TSC1 and TSC2
patients separately. To do this, all the possible trajectories
and their probabilities were enumerated from the data.
Namely, where were manifestations of TSC first detected
(i.e. heart, CHD; brain, NDD; or kidneys, KD) and where
will they transition next? Probabilities of all possible dis-
ease trajectories for this cohort are defined in Tables S1
and S2.
Statistical analysis
All statistical analysis of the data was performed in
GraphPad Prism version 9.1 (GraphPad Software, San
Diego, California, USA, www. graph pad. com) and Micro-
soft Excel. Two-sided p values of p < 0.05 were consid-
ered statistically significant. Where applicable, data was
assessed for Gaussian distribution with Shapiro-Wilk test
and generated QQ plots of predicted vs actual data are
found in Supplementary information (Additional file1:
Figs. S1, S6, S7 and S10). Due to the nature of data col-
lection for this project, it is important to note that no
control group information (i.e. a group with no TSC1/2
mutation) is included within this data set. When compar-
ing TSC1 vs TSC2 patient group prevalence within one
categorical variable (i.e. mutation type, rhabdomyoma
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Robinsonetal. BMC Medicine (2022) 20:123
prevalence), Fisher’s exact test was used to assess sta-
tistical significance when the overall sample size was
30 patients or fewer, and alternatively for larger sample
sizes, a Z-score test for two population proportions was
used.
Cochrane’s Q test for heterogeneity was employed to
assess heterogeneity between male to female ratio (M:F)
during meta-analysis of previous studies assuming a null
hypothesis that the true effect is the same across all stud-
ies and variations are due to statistical chance alone. A
more powerful quantity I2 is derived from the Q-statistic
by dividing the resulting statistic and its degrees of free-
dom by the Q value and was also used to provide an esti-
mate of the percentage in variability across studies due
to factors other than chance. Logarithmic trendlines for
graphs of the rate of rhabdomyoma regression, rate of
brain involvement detection and rate of kidney involve-
ment detection were generated in Microsoft Excel along
with the R2 coefficient of determination to assess the
goodness of fit of the trendline to the fitted values and
observed values. Residual plots of fitted values vs residu-
als are included in Supplementary information (Addi-
tional file1: Figs. S2-S5, S8 and S9). Two-tailed Wilcoxon
matched-pairs signed-rank tests were also performed
between TSC1 and TSC2 groups to assess whether their
population mean ranks differ. Significant effectiveness of
pairings was assessed with Spearman’s rank, rs.
Results
Burden andcharacteristic features ofTSC1 andTSC2
inacohort
In order to fulfil the aims of this study, the characteri-
sation of the patient cohort was first conducted. To do
this, examination of several key variables was necessary
which included the prevalence and type of each specific
TSC mutation, ratio of males to females, and diagnostic
data of the brain, kidney, and heart to further delve into
the very essence of TSC as a multisystem heterogenous
genetic disorder.
TSC1 and TSC2 mutations in the patient cohort were
identified using NGS and SS methods. TSC2 variants
represented the majority of the cohort, constituting
approximately 72% (N = 68) of all 95 genetically tested
TSC patients (Fig.2A). In contrast, only 25% of tested
patients had TSC1 mutations (N = 24), and no mutation
was identified (NMI) in the remainder (N = 3) (Fig.2A).
is means that the ratio of TSC1 to TSC2 patients for
this cohort is approximately 1:2.8. A further breakdown
of the mutation variant types of the 92 patients with an
identified mutation is summarised in Fig.2B, where 63%
of all changes corresponded to small variants (SV) such
as small deletions or insertions, duplications, or point
mutations. ere was also a further group of 13 patients,
where no mutation data was available on hospital data-
bases beyond unspecified ‘TSC1 mutation’ or ‘TSC2
mutation’, who were therefore classed into an ‘unknown’
category. e data presented in Fig. 3B was then fur-
ther explored in Fig.2C where the proportion of each
type of variant in TSC1 vs TSC2 was compared and sta-
tistically evaluated. ere was no significant difference
between TSC1 and TSC2 groups in the case of nonsense
mutations (p = 0.059), missense mutations (p = 0.051),
intronic mutations (p = 0.105) and large deletions (p =
1.00). However, a significant difference in the propor-
tion of frameshift mutations was identified (p = 0.0018)
comprising 33% and 6% of the TSC1 vs TSC2 groups,
respectively.
Next, a meta-analysis was conducted of the male to
female ratio (M:F) for this study in addition to ten other
previous studies of TSC patient cohorts (Fig.2D). Within
the CAV UHB cohort, there were 50 male patients and
42 females, resulting in a M:F ratio of 1.19:1 (Fig.3D).
e 95% confidence interval (CI) intersects with the line
of no effect (x = 1), and thus, at the given level of confi-
dence, the M:F ratio does not differ from equal ratio and
is therefore statistically insignificant (Fig.3D). Explicitly,
TSC burdens male and female patients equally in this
particular cohort. Out of the other ten studies inspected,
a further eight were also synonymous with this result and
also showed equal burden of TSC in male and female
patients. e total M:F ratio across all studies was cal-
culated at 1.04:1 with a slim confidence interval of 0.97
to 1.10 and therefore did not differ from an equal ratio.
Cochrane’s Q test revealed no significant heterogeneity
between studies (Q = 8.14, df = 11, p = 0.61), which was
further confirmed with a more powerful quantity I2 that
established 0% of total variation across studies was due
to heterogeneity instead of chance. erefore, male and
(See figure on next page.)
Fig. 2 Genetic characterisation and mutational spectra of pathogenic TSC mutations and male to female ratio. A Number and proportion of cases
with TSC1 or TSC2 mutation or no mutation identified (NMI); B Number and prevalence of mutation types of 92 patients with an identified genetic
mutation; C Proportions of each mutation type in TSC1 vs TSC2 compared with Fisher’s exact test (p < 0.05 significance); D Forest plot indicating the
male to female ratio calculated from each study involving a TSC patient cohort (red circle), and the overall mean male to female ratio is represented
by the green circle, confidence whiskers represent a 95% confidence interval (CI) for each study and the mean, male to female ratio (M:F) and upper
and lower confidence intervals are listed in right hand columns where a M:F of 1 (x = 1) signifies equal number of males and females in each cohort
as graphically indicated by the dotted line, x<1 represents more females than males and x>1 represents more males than females, Cochran’s Q test
for heterogeneity: Q=8.14, df=11 (p=0.61); I2=0%; CI, confidence interval; TSC, tuberous sclerosis complex; ** p < 0.01. ; n.s., non-significant
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Robinsonetal. BMC Medicine (2022) 20:123
Fig. 2 (See legend on previous page.)
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Page 8 of 19
Robinsonetal. BMC Medicine (2022) 20:123
female patients are burdened by TSC at equal rates and
any variance of the M:F ratio is due to statistical chance
alone.
Patient ages in the whole cohort (as of October 2020)
ranges between < 0 (prenatal) and 75 years of age, with
median ages of 17 and 20 years old between TSC1 and
TSC2 groups, respectively. e age distribution between
TSC1 and TSC2 groups is very similar, with median ages
of first symptom detection in both groups being at < 1
year of age with interquartile ranges of 2.25 and 2 years
respectively. e standard deviation of age at first inclu-
sion was 1.91 in the TSC1 group, and 8.01 in the TSC2
group indicating a greater variety of detection age in the
latter (Additional file1: TableS1).
Prevalence ofCHD
e overall aim of this investigation is to characterise
the nature of the relationship between CHDs, NDDs and
KDs in TSC1 and TSC2 patients. To establish the asso-
ciation between the three conditions, it is important to
first investigate each manifestation at its individual organ
level. Firstly, CHD prevalence in TSC1 and TSC2 patients
in this cohort were determined, with 57% and 75% of
patients respectively receiving a diagnosis of either sin-
gle or multiple CR at some point during their lifetime,
with no significant difference in rhabdomyoma preva-
lence between the two populations found (z = −1.56, p =
0.119) (Fig.3A).
e location of rhabdomyoma within the heart was
also compared between TSC1 and TSC2 patients to
evaluate whether their genotype impacted the prefer-
ential location CR development within different heart
structures. e position of CRs within the heart was
categorised into five primary locations; interventricu-
lar septum (IVS), left ventricle (LV), right ventricle
(RV), left atrium (LA) and right atrium (RA) (Fig.3B).
Cumulatively, it was found that 98% of all TSC patients
with CR had at least one tumour located in either ven-
tricle or the IVS (Fig.3B). Despite a marked difference
between the prevalence of CR in the ventricles versus
the atria in all patients, no significant difference of CR
prevalence in each structure was found when compar-
ing TSC1 vs TSC2 hearts (Fig. 3B), implying that the
tumours appear at the same rate in each heart structure
no matter the genotype (IVS, z = −0.162, p = 0.873;
LV, z = 0.695, p = 0.490; RV, z = 0.969, p = 0.332; LA, z
= −1.02, p = 0.308; RA, z = 0.681, p = 0.497).
In addition to the structural location of CR, the num-
ber of individual tumours is also a considerable factor
in the overall cardiovascular health of TSC patients.
e proportion of individuals with multiple CRs as
opposed to an isolated tumour stands at 86% of TSC1
patients and 89% of TSC2 patients with cardiac mani-
festations (Fig.3C).
Overall, most patients with multiple CR had either
two or three tumours, representing 43% and 65% of
the patients in TSC1 and TSC2 cohorts, respectively
(Fig.3C). ere was no significant difference between
number of tumours observed between TSC1 and TSC2
patients; therefore, we hypothesise that the number of
tumours follow the same distribution, no matter the
genotype (1 tumour, z = 0.268, p = 0.787; 2–3 tumours,
z = –1.10, p = 0.271; 4+ tumours, z = 1.01, p = 0.313).
e diameter of the largest cardiac rhabdomyoma
in TSC1 and TSC2 patients was also investigated and
ranged from 5 mm up to 34 mm, with the majority
(22%) ranging from 10 to 15mm (Fig. 3D). Both fre-
quency distributions followed a normal Gaussian distri-
bution as confirmed by a non-significant Shapiro-Wilk
test result (TSC1, W = 0.84, df = 6, p = 0.099; TSC2,
W = 0.94, df = 6, p = 0.61). e two distributions
returned a z-test statistic of 1.59, and a p value of 0.11
indicating there was no significant difference between
the largest CR diameter of TSC1 and TSC2 patients.
Whilst CRs are thought to be present as early as
20–30 weeks of gestation [17], in this cohort, only 43%
of rhabdomyoma patients were diagnosed in utero
(Fig.3E). After birth and onset of tumour regression,
once a CR has completely shrunk or remains stable in
size, it is said to be ‘resolved’. An exponential graph of
resolution of tumours over time (Fig.3F) revealed an
average CR resolution age of 6.8 years old, with an aver-
age resolution age of 6.7 years old in TSC1 patients,
and 7.2 years old in TSC2 patients. However, no fur-
ther tumour regression was observed in either TSC1 or
TSC2 patients beyond 15.5 years of age, meaning that
for approximately 16% of patients, CR persisted into
adulthood.
Fig. 3 Characterisation of cardiac rhabdomyoma in TSC1 and TSC2 patients by echocardiography. A The prevalence of cardiac rhabdomyoma in
TSC1 vs TSC2 patients (TSC1, N = 11; TSC2, N = 44); B The location of cardiac rhabdomyoma within heart chambers of TSC1 vs TSC2 rhabdomyoma
patients (TSC1, N = 9; TSC2, N = 38); C The number of rhabdomyoma in hearts of TSC1 vs TSC2 rhabdomyoma patients (TSC1, N = 7; TSC2, N =
37); D The size of the largest rhabdomyoma in TSC1 vs TSC2 patients (TSC1, N = 8; TSC2, N = 29); E The proportion of patients diagnosed with
rhabdomyoma as a foetus (F) vs proportion of postnatally (PN) diagnosed patients (N = 49); F The rate of the rhabdomyoma prevalence as tumours
resolve in TSC1 vs TSC2 rhabdomyoma patients (TSC1, N = 7; TSC2, N = 33) as age increases (mean ± SEM); TSC1 vs TSC2 statistically compared
with Z-score for 2 population proportions (p < 0.05 significance); IVS, interventricular septum; LV, left ventricle; RV, right ventricle; LA, left atrium; RA,
right atrium; n.s., non-significant; SEM, standard error of mean; *p < 0.05
(See figure on next page.)
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Robinsonetal. BMC Medicine (2022) 20:123
Fig. 3 (See legend on previous page.)
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Page 10 of 19
Robinsonetal. BMC Medicine (2022) 20:123
Prevalence ofNDD
In addition to structural abnormalities within the brain,
often seizures and delayed developmental milestones
will become apparent during infancy and childhood,
potentially leading to a diagnosis of some form of the
neurodevelopmental disorder (NDD) which lie under
the umbrella term of TSC-associated neuropsychiatric
disorders (TAND). e areas of cerebral cortical dyspla-
sia in the form of cortical tubers (CT) were prevalent in
42% and 80% of TSC1 and TSC2 patients, respectively
(Fig.4A). By employing a Z-score test for two popula-
tion proportions, this marked difference between the two
groups was deemed statistically significant (Z = −3.0, df
= 1, p = 0.0026). Subependymal nodules (SEN) appear
deeper within the brain, affecting 68% and 78% of TSC1
and 2 patients in their respective groups, and subepend-
ymal giant cell astrocytoma (SEGA) were detected with
even smaller prevalence at 32% and 26%, respectively
(Fig.4A). Neither of these lesion types differed signifi-
cantly between TSC1 and TSC2 (TSC1, Z = 0.85, df = 1,
p = 0.40; TSC2, Z = 0.49, df = 1, p = 0.62).
e presence of NDDs in the cohort was evaluated
from results of regular TAND screening, and the comor-
bidity of epilepsy was also quantified. 75% of TSC1
patients and 81% of TSC2 patients experienced epilepsy
in the form of a range of seizure types (Fig.4B). Statistical
analysis revealed that epilepsy occurs with equal preva-
lence between TSC1 and TSC2 groups (Z = −0.53, df =
1, p = 0.60). Most of the other TAND assessed such as
motor disorders, anxiety, depression and global develop-
mental delay (GDD) also showed no significant difference
in prevalence between TSC1 and TSC2 patient groups.
Autism spectrum disorder (ASD) and intellectual dis-
ability (ID) are thought to affect around half of all TSC
patients; however, within this cohort, the ASD preva-
lence ranged from 14 to 25% and ID prevalence from 25
to 36% (Fig.4B), possibly a direct result of an observed
assessment gap for TAND in the UK [40]. Furthermore,
a significant difference was found between the presenta-
tion of communication disorders in TSC1 and TSC2 at
a prevalence of 6% and 50%, respectively (Fig.4B) (Z =
−3.17, df = 1, p = 0.0015).
e comorbidity between different structural brain
abnormalities and NDDs was explored in this cohort.
Individual instances of each type of NDD were counted
for each comorbidity with either CT, SEN, or SEGA and
expressed as a percentage of all NDD diagnoses for each
brain lesion type (Fig.4C). Differences in proportions of
separate NDDs were unremarkable when comparing by
both lesion type or genotype, and appeared in almost
equal proportions as the findings from Fig. 4B, most
likely a result of the technicality that often brain malfor-
mations appear together, and thus, it is difficult to quan-
tify TAND prevalence as a comorbidity of each type of
lesion separately.
Finally, the age at which patients received a brain
magnetic resonance imaging (MRI) screening which
returned consistent with TSC-associated brain abnor-
malities was graphed for both TSC1 and TSC2 patient
groups (Fig.4D). Both graphs of brain lesion prevalence
within the cohort follow a logarithmic curve, with a pla-
teau indicating the final prevalence, settling at 79% prev-
alence in the TSC1 patient group and 92% in the TSC2
patient group. e mean age of brain lesion detection
varied slightly between the groups, with TSC1 patients
on average receiving a diagnosis at 2.5 months old, which
was extended to 6.4 months old for TSC2 patients. Both
models were assessed for normal Gaussian distribution
with Shapiro-Wilk test, both of which demonstrated
non-normal distribution (TSC1, W = 0.62, df = 30, p
< 0.0001; TSC2, W = 0.86, df = 30, p = 0.0008. A two-
tailed Wilcoxon matched-pairs signed-rank test was
performed and the outcome revealed no significant dif-
ference between the brain abnormality detection pattern
observed between TSC1 and TSC2 groups (W = 24, df =
30, p = 0.82).
Prevalence ofKD
Unlike CRs and brain malformations, detection of kidney
lesions is very rare at initial presentation [14]. A stark dif-
ference was observed between the prevalence of AMLs
between TSC1 and TSC2 groups at 32% and 68%, respec-
tively (Fig.5A). Statistical quantification of this difference
with the Z-score test for two population proportions
confirmed statistical significance between these groups
(Z = −2.9, df = 1, p = 0.0035). In contrast, this same dif-
ference is not observed in the case of renal cysts, where
prevalence amongst TSC1 and TSC2 patients is almost
equal at 27% and 29%, respectively (Fig.6A), an insignifi-
cant difference at p < 0.05 (Z = −0.18, df = 1, p = 0.86).
(See figure on next page.)
Fig. 4 Characterisation of brain involvement in TSC1 and TSC2 patients by brain MRI and TAND assessment. A The prevalence of cortical tubers,
subependymal nodules (SEN) and subependymal giant cell astrocytoma (SEGA) in the brains TSC1 vs TSC2 patients (TSC1, N = 19; TSC2, N = 46); B
The prevalence of TSC-associated neuropsychiatric disorders (TAND) and epilepsy in TSC1 vs TSC2 patients; C TAND prevalence by brain lesion type
for TSC1 vs TSC2; D The prevalence of brain lesions as patients age TSC1 vs TSC2 (mean ± SEM); TSC1 vs TSC2 statistically compared with Z-score
for 2 population proportions (p < 0.05 significance); MRI, magnetic resonance imaging; motor dis., motor disorders; A/D, anxiety/depression; ID,
intellectual disability; ASD, autism spectrum disorder; GDD, global developmental delay; comm. dis., communication disorder; ** p < 0.01; n.s.,
non-significant
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Robinsonetal. BMC Medicine (2022) 20:123
Fig. 4 (See legend on previous page.)
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Page 12 of 19
Robinsonetal. BMC Medicine (2022) 20:123
The diameter of the largest AML in each patient
was extracted from renal imaging data and catego-
rised into small groups at 5mm increments to evaluate
the distribution of tumour sizes amongst the cohort
(Fig. 5B). Across all patients, an individuals’ largest
observed AML measured 10 mm or smaller in 44%
of cases, with an even split between tumours ≤5mm
and 5–10mm in diameter. All four TSC1 patients
with recorded AML sizes also fell within the 5–10mm
category. The median largest AML size across patients
was determined as 15 mm with an interquartile range
of 25 mm.
Renal lesion localisation across both kidneys was inves-
tigated. TSC2 patients demonstrated a pronounced local-
isation within both kidneys concurrently (78%), where
in contrast only a quarter of investigated TSC1 patients
had lesions within both kidneys at any one time (Fig.5C).
Statistical testing with a Z-score test for two population
Fig. 5 Characterisation of renal involvement in TSC1 and TSC2 patients by abdominal MRI and USS. A The prevalence of angiomyolipoma (AML)
and cysts in the kidneys of TSC1 vs TSC2 patients (TSC1, N=21; TSC2, N=65); B The size of AML (mm) as a proportion of total measured tumours
(TSC1, N=4; TSC2, N=68); C The prevalence of kidney lesions in either left kidney (L), right kidney (R) or both kidneys (L + R) in TSC1 vs TSC2; L and
R compared with Fisher’s exact test (p < 0.05 significance); D The prevalence of kidney lesions as patients age TSC1 vs TSC2 (mean ± SEM); TSC1 vs
TSC2 statistically compared with Z-score for 2 population proportions (p < 0.05 significance); MRI, magnetic resonance imaging; USS, ultrasound; * p
< 0.05; ** p < 0.01; n.s., non-significant
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Robinsonetal. BMC Medicine (2022) 20:123
proportions revealed that this difference was indeed
statistically significant (Z = −3.0, df = 1, p = 0.0030).
Furthermore, lesion presence had a significantly higher
degree of localisation to the left kidney in TSC1 patients
than TSC2 patients as confirmed with Fisher’s exact test
(p = 0.026); however, this was not the case within the
Fig. 6 The frequency and co-occurrence of TSC manifestations and lifetime trajectory of organ involvement between CHD, NDD and KD in TSC1
and TSC2 patients. A Lifetime prevalence and degree of co-morbidity between CHD, NDD and KD in all patients combined, TSC1 patients and TSC2
patients. The size of circles is the proportional to the prevalence of each organ manifestation labelled in brackets, and the width of connecting lines
is proportional to the degree of relative comorbidity between disorders; B The probability trajectory of lifetime organ involvement in TSC1 patients
from point of initial presentation. Initial presentation at the base of the tree occurs in either the heart, brain or kidney and branches to other organs
as indicated by transition probability on a branch; C The probability trajectory of lifetime organ involvement in TSC2 patients from point of initial
presentation. CHD, congenital heart disorder; NDD, neurodevelopmental disorder; RD, renal disease
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Page 14 of 19
Robinsonetal. BMC Medicine (2022) 20:123
right kidney where instead lesions had an equal preva-
lence across both groups (p = 0.33).
Finally, the age at which patients received a USS or MRI
screening which exhibited consistency with TSC-asso-
ciated renal abnormalities was graphed for both TSC1
and TSC2 patient groups (Fig.5D). e choice of imag-
ing technique reflected clinical practise and pragmatic
resource availability. Patients were frequently screened
with ultrasound (USS), and MRI would be requested
for confirmation of growing AML. Both time graphs of
kidney lesion prevalence within the cohort follow a loga-
rithmic curve, with a plateau indicating the final preva-
lence of all kidney lesions within each group, settling at
56% prevalence in the TSC1 patient group and 73% in
the TSC2 patient group. e mean age of kidney lesion
detection was identical between the groups, with both
TSC1 and TSC2 patients on average receiving a diagno-
sis of renal involvement at 4.7 years of age. Both mod-
els were then assessed for normal Gaussian distribution
using Shapiro-Wilk test, both of which demonstrated
non-normal distribution (TSC1, W = 0.87, df = 161, p
< 0.0001; TSC2, W = 0.87, df = 161, p < 0.0001). A two-
tailed Wilcoxon matched-pairs signed-rank test was per-
formed and the outcome revealed a significant difference
between the kidney lesion detection pattern observed
between TSC1 and TSC2 groups (W = 13019, df = 161,
p < 0.0001). A median difference of 12.2% prevalence
was observed between TSC1 and TSC2 groups at any
one point in time, with the prevalence of kidney lesions
within the TSC1 group consistently trailing behind those
in their counterpart genotype throughout life.
Co‑occurrence ofCHD, NDD andKD
With organ system involvement of TSC having been
characterised for this cohort on a separate basis, it is now
crucial to consider the quintessence of TSC as a multi-
system disorder where disease manifests simultaneously
in parallel systems throughout the whole body. Firstly,
the prevalence and co-occurrence of organ manifesta-
tions of TSC were calculated for CHD, NDD and KD and
results were separated into either a combined association
for both TSC1 and TSC2 patients cumulatively, as well
as separate genotypes (Fig. 6A). With TSC1 and TSC2
patients combined, the prevalence of organ involvement
stood at 70% of patients with a CHD, 88% with an NDD
and 63% with renal disorders. Separately, only 57% of
TSC1 patients exhibited some form of cardiac involve-
ment, as opposed to 75% of TSC2 patients, and a fur-
ther TSC1/2 variation of 42% and 71%, respectively, was
observed in the case of renal involvement. e preva-
lence of NDDs remained consistent between both groups
at 83% and 90%, respectively.
Relative co-occurrence of different organ system mani-
festations was determined for the group. A consistent
pattern is clear across both TSC1 and TSC2 patients
where the order of co-occurrences from least probable
to most probable in Boolean operator terms is P(CHD
∩ KD), P(CHD ∩ NDD) and P(KD ∩ NDD) (Additional
file1: Tables S2 and S3). erefore, the most frequently
observed co-morbidity throughout the whole dataset is
the presence of one or more NDD and co-occurring renal
involvement.
However, static data only holds a limited degree of
predictive power. A temporal variable was added to the
comorbidity data which enabled ‘tracking’ of a patients’
disease trajectory throughout their lifetime. Probability
trees of disease trajectory throughout organ systems were
generated for both TSC1 patients (Fig. 6B) and TSC2
patients (Fig.6C). Initial organ presentation is character-
ised at the base of each tree. From an initial presentation
at the ‘starter organ’, disease trajectory branches out to
different organs with variable transitional probabilities.
e most probable disease trajectory out of all possible
disease outcome scenarios calculated for TSC2 patients
was CHD → NDD at 0.85, with a further 0.74 probability
of renal involvement detected afterward (Fig.6C). Within
the TSC1 patient group, the most probable trajectory was
CHD → NDD at a probability of 0.70, with no further
organ involvement likely at 0.86 probability (Fig. 6C).
Altogether, this figure provides disease trajectories and
probability for 18 different possible disease outcomes
across both TSC1 and TSC2 patient groups.
Discussion
is project marks the first empirical investigation of the
statistical association between the aberrant heart, brain
and kidney development in a regional cohort of tuber-
ous sclerosis complex patients. Furthermore, this study
is one of the first to provide comprehensive genotype-
phenotype profiling of all three of the discussed organ
presentations of TSC1 and TSC2 patients separately as
opposed to a combined population where the genetic
profile is negated. Additionally, establishing genotype-
phenotype relationships and co-morbidity data for this
study have made it possible to predict probable disease
trajectories of TSC throughout a patient’s lifetime, which
lays the groundwork of a powerful diagnostic tool for cli-
nicians involved with the management of TSC patients.
Other important findings of this study include signifi-
cantly greater frequency of TSC2 mutations, particu-
larly frameshift variants; equal disease burden amongst
male and female patients; delayed rhabdomyoma reso-
lution in TSC1 patients; the significantly greater preva-
lence of cortical tubers, communication disorders and
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Robinsonetal. BMC Medicine (2022) 20:123
angiomyolipoma in TSC2 patients; most frequent co-
occurrence of organ involvement between brain and kid-
neys; a diverse disease trajectory in TSC2 patients; and
most probable disease association trajectory of CHD →
NDD → KD in TSC2 individuals.
Impact ofgenetic andsex dierences onTSC
pre‑disposition
Past evidence has long postulated a significantly greater
TSC2 mutation yield in TSC patient cohorts as opposed
to TSC1, with TSC2 mutations accounting for approxi-
mately 70–90% of mutations within the analysed cohorts
[2, 4–7]. e findings from this study also corrobo-
rate with these previous studies, indicating a significant
majority of TSC patients with a mutation at the TSC2
genetic locus, with a TSC1:TSC2 mutation ratio of 2.8
TSC2 patients for every TSC1 patient, or TSC1 and
TSC2 mutation rates amongst the cohort at 25% and
72%, respectively. Furthermore, the detection rate of TSC
mutations was determined as 97%, superseding previous
studies where the detection rate ranged from 82 to 94%
[41–44].
Although the genetic profile of TSC1/2 regions was
determined to be a fundamental basis for TSC pre-
disposition, the effect of patient sex was negligible. e
male to female ratio (M:F) for this cohort was 1.19 male
patients for every female patient, although statistically
male and female patients were determined to be in equal
proportions. Previous studies were compiled into a meta-
analysis where the overall M:F range varied from 0.73 to
1.79 male patients for every female patient; however, ulti-
mately a pooled M:F score of 1.04 was achieved across all
studies. Hence, this study accords with previous observa-
tions that incidence of TSC is not linked with patient sex.
Enhanced clinical phenotype severity inpatients withTSC2
mutations
Considering such a pronounced disproportion between
TSC1 and TSC2 mutational frequency, this is further
mirrored by a frequently observed more severe disease
phenotype in TSC2 patients, which has largely been
hypothesised to be a result of ascertainment bias [3–5,
41]. e results from this study were no different, with
a more severe disease presentation observed in both the
brain and kidneys; however, the heart was seemingly
unaffected by genotype differences in this study.
Firstly, a significantly greater proportion of TSC2
patients presented cortical tubers, almost double that
observed in TSC1. Previous studies have highlighted the
ambiguity of the role of TSC1/2 in cortical tuber forma-
tion; however, experimentation with TSC1/2 mutant
mice have highlighted the critical role of both these genes
for normal neuronal function as well as a high expression
of these genes within the cortical plate and maturing
neurons [45, 46]. Furthermore, the presence of cortical
tubers has previously been associated with epilepsy and
poorer neurodevelopmental outcome [47, 48]; however,
no significant difference in epilepsy prevalence between
TSC1 and TSC2 patients was found in this study. None-
theless, a stark difference was observed in the preva-
lence of communication disorders between the groups,
with TSC2 patients once again demonstrating a poorer
outcome. Interestingly, the prevalence of two NDDs
remained markedly lower from the previously published
literature on TSC. Autism spectrum disorder (ASD) and
intellectual disability (ID) are thought to normally affect
around half of all TSC patients [31]; however, within this
cohort ASD prevalence ranged from 14 to 25% and ID
prevalence from 25 to 36%. As discussed previously, this
may be a direct consequence of a large assessment gap
of TAND in the UK as published by the tuberous sclero-
sis registry to increase disease awareness (TOSCA) [40].
Patients with NDD are also less likely to have genetic test-
ing due to a lack of personal need for reproduction. is
group would have been excluded from this study. Fur-
thermore, one would expect to see a considerably greater
comorbidity between epilepsy and CTs alone based on
previous studies [48]; however, the prevalence of epi-
lepsy remains consistent between all three brain tumour
types. is is most likely because often brain malforma-
tions appear together, and thus, it is difficult to quantify
the TAND prevalence as a comorbidity of each type of
lesion separately as they simply do not appear in isolation
the majority of the time considering the extremely high
prevalence of CTs and SEN amongst the TSC population.
Overall, the kidney presentation also varied between
TSC1 and TSC2 patient cases. A greater prevalence of
patients with AMLs was observed in the TSC2 popula-
tion, which has been well-documented in the past and
postulated to be a result of Knudson’s two-hit events
occurring less frequently in TSC1 than TSC2 [37, 41]. No
difference in renal cyst prevalence between the two geno-
types in this study was found however, despite a previ-
ously observed trend of higher prevalence in TSC2 likely
due to mutations also impacting the polycystic kidney
disease (PDK1) gene adjacent to TSC2 [41, 49]. Further-
more, AMLs were typically located bilaterally in both
kidneys in TSC2 patients, as opposed to TSC1 where
lesions were localised in just one kidney 3/4 of the time.
Prediction oforgan manifestation co‑occurrence
anddisease trajectory asadiagnostic tool
Arguably, the most important and novel outcome
of this study is the statistical evaluation of the asso-
ciation between CHDs, NDDs and RDs. is suggests
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Robinsonetal. BMC Medicine (2022) 20:123
manifestations of TSC are perceived as dynamically
interwoven with one another as opposed to simply being
diagnosed and managed at their individual organ system
level.
Previous research of non-TSC populations has identi-
fied associations between aberrant development in all
three organs; however, the most well-documented link
lies between co-occurrence of CHDs and NDDs. e
heart and brain development is intimately related, and
children with CHDs are well-known to be at increased
risk of NDD likely due to altered perfusion and substrate
delivery to the developing brain during early gestation
[50, 51]. Furthermore, significant altered brain metabo-
lism and microstructure as well as white matter immatu-
rity and delay in cortical folding has been noted in CHD
individuals shortly after birth [52, 53]. Contrary to this,
the association between CHD and KD is not as well-
established. Both mice and human studies have shown
a significant overlap in genetic aetiology of CHD and
kidney abnormalities which has been postulated to the
conservation of developmental pathways and signalling
mechanisms that regulate the heart and renal develop-
ment; however, there is not a large volume of studies to
support this hypothesis [54]. Moreover, abnormal neu-
rodevelopment has been identified as a co-morbidity in
patients with kidney disorders, most notably amongst
paediatric chronic kidney disease (CKD) patients where
common dysfunctions have been identified as ASD, ID,
academic difficulties, attention problems and poor execu-
tive functioning [55–57].
Interestingly, in this study, the most frequent co-occur-
rence was witnessed between NDDs and KDs in both
TSC1 and TSC2 patient groups, with NDD and CHD
correlation as a close second. As this is a novel finding,
there is little previous research to suggest why this may
be the case in the context of TSC specifically; however,
there is sufficient evidence from general population stud-
ies discussed previously to outline the possible aetiology
behind this. However, as is the nature of TSC as a multi-
system disease, different organ manifestations do not
appear simultaneously and instead first become apparent
at variable developmental stages. e progressive disease
trajectory throughout the heart, brain and kidneys has
remained elusive until now.
is study has developed a probability tree of all the
possible disease outcome scenarios of TSC1 and TSC2
patients in this cohort using mathematical modelling of
comorbidity and time-scale data to propose likely dis-
ease trajectories. e trajectories of TSC2 were far more
diverse than TSC1; however, co-occurrence of all three
organ manifestations together was rare, occurring in only
7% of patients. Co-occurrence of two organ manifesta-
tions was most frequently observed, with CHD → NDD
most probable amongst the group. A common disease
trajectory of CHD → NDD and further devolvement
to KD was observed in the TSC2 patient group most
frequently.
is study provides a foundation for disease outcome
prediction, which is crucial for effective patient man-
agement strategy throughout the hospital system, espe-
cially when spanning different clinical departments. For
these predictions to be improved, especially in the case
of TSC1 patients with a smaller a sample size, more TSC
patient cohorts need to be analysed for disease trajecto-
ries to reflect a more accurate prediction.
Strengths ofthis study
e TSC patient database from CAV UHB incorpo-
rates clinical data from a spectrum of patients from the
South of Wales gathered over a 30-year period. is
database integrates information from a multitude of hos-
pital departments that provide a detailed account of a
patient’s experience living with TSC which is invaluable
for studies such as these that explore genotype-pheno-
type relationships as well as the trajectory of the disease.
Furthermore, the duration of gathered data contributes
to a timeline of TSC manifestations across patients’ life-
times which is instrumental for tracking the trajectory of
disease for future clinical applications. erefore, these
strengths have allowed the exploration of research ave-
nues that have not yet been investigated before in TSC
cohorts.
Limitations ofthis study
Despite the strengths of this study, there are still a num-
ber of limitations. Firstly, the nature of TSC as a rela-
tively rare disease with a prevalence of 1 in 6000 to 1 in
12,000 unfortunately renders the sample size relatively
small at only 160 patients in South Wales from 1990 to
2020. Patients with mild manifestations may not present
to medical professionals. More significantly, 43.5% of the
original cohort size were excluded from analysis as out-
lined in Fig.2 due to incomplete patient data records or
lack of genetic testing. In addition, the size of the TSC1
group was particularly small at only 24 patients; there-
fore, an accurate result may not be justified for this
specific group. In future, analysis of larger cohorts or
meta-analyses of multiple cohorts should be performed
to increase the overall sample size and compare with the
findings from this study.
Furthermore, the hypothesised association between
CHDs, NDDs and KDs in this study is purely correla-
tional. Further larger studies should be aimed at estab-
lishing a causal relationship between these and with
other organ manifestations of TSC, directing particular
interest at the implications of each manifestation during
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 17 of 19
Robinsonetal. BMC Medicine (2022) 20:123
development. e liver, eye, lung and skin clinical mani-
festations of TSC were not the subjects of this study,
hence their interaction with the studied systems could
not be evaluated. e exclusion of other clinical mani-
festations potentially can influence the association across
these three organs.
Lastly, the data collected in this study has not been
compared with other patient cohorts, except for the male
to female ratio. Such sources of ascertainment could
include the Clinical Practice Research Datalink (CPRD)
which includes 6 million active patients, of which over
300 patients with a TSC diagnosis were identified as of
2016 [58]. A further meta-analysis of TSC patients across
multiple cohorts is crucial to confirm the observed trends
in this study, as well as evaluate the overall statistical sig-
nificance of findings.
As mentioned previously, the findings from this study
have several implications for future clinical practice,
particularly concerning the long-term care plan of TSC
patients. To evaluate the practical applications of this,
personalised medicine and targeted therapy avenues of
disease management need to be explored. A likely can-
didate for such methods would be the use of human-
induced pluripotent stem cells (iPSCs) to model the
abnormal development of organs in vitro and further
elucidate the pathophysiology behind this process. iPSCs
can be derived from TSC patient somatic cells and dif-
ferentiated into tissue-specific derivatives to model the
development of different organs impacted by TSC and
trial therapeutic agents e.g. mTOR inhibitors as a pre-
ventative measure that may alter disease progression [59,
60].
Conclusion
is study offers an insightful initiative towards charac-
terisation of the relationship between CHDs, NDDs and
KDs in TSC1 and TSC2 patients. Specifically, analysis of
disease trajectories throughout TSC patients’ lifetimes
lays the groundwork for future prediction of disease out-
comes from initial presentation, and future long-term
studies of larger TSC cohorts should aim to improve
the accuracy of these predictions. Investigation of the
pathophysiological aetiology behind the correlations
identified here and any future studies is also essential,
and the enterprising field of iPSC technology is a likely
candidate for disease modelling and a starting point for
novel therapeutic agents. Many patients with multiorgan
disease experience fragmented care, and we have high-
lighted previously the need for adequate centralised care
of TSC patients that adheres to published guidelines to
alleviate the high burden of illness on patients and their
support network. Such research as outlined here is a
unique first step towards the development of updated
patient management guidelines and novel treatments, in
addition to opening avenues for further understanding of
the dynamic role between genetics, heart function, brain
function and kidney function during early development.
Abbreviations
ADHD: Attention-deficit/hyperactivity disorder; AML: Angiomyolipoma; ASD:
Autism spectrum disorder; CAV UHB: Cardiff and Vale University Health Board;
CHD: Congenital heart defect; CKD: Chronic kidney disease; CPRD: Clinical
Practice Research Datalink; CR: Cardiac rhabdomyoma; CT: Cortical tubers;
DSM-5: Diagnostic and Statistical Manual of Mental Disorders, 5th Edition;
GDD: Global developmental delay; iPSCs: Induced pluripotent stem cells;
ID: Intellectual disability; INDEL: Insertion-deletion mutation; IVS: Interven-
tricular septum; KD: Kidney disorders; LA: Left atrium; LV: Left ventricle; MRI:
Magnetic resonance imaging; NDD: Neurodevelopmental disorders; NGS:
Next-generation sequencing; PKD: Polycystic kidney disease; RA: Right atrium;
RV: Right ventricle; SEN: Subependymal nodules; SEGA: Subependymal giant
cell astrocytoma; SNV: Single-nucleotide variants; SS: Sanger sequencing; SV:
Small variants; TAND: TSC-associated neuropsychiatric disorders; TSC: Tuberous
sclerosis complex; USS: Ultrasound.
Supplementary Information
The online version contains supplementary material available at https:// doi.
org/ 10. 1186/ s12916- 022- 02325-0.
Additional le1: TableS1. Age distribution of TSC patients in the cohort.
TableS2. Disease trajectory outcome probability in TSC1 patients where
initial presenting organ or ‘start point’ is known or unknown (N = 24).
TableS3. Disease trajectory outcome probability in TSC2 patients where
initial presenting organ or ‘start point’ is known or unknown (N = 68).
Figure S1. QQ plot of Shapiro-Wilk test for normality of rhabdomyoma
size distribution TSC1 vs TSC2. Figure S2. Residual plot of the difference
between observed value and predicted value of remaining rhabdomyoma
prevalence from regression trendline in TSC1 rhabdomyoma group (N =
6). Figure S3. Residual plot of the difference between observed value and
predicted value of remaining rhabdomyoma prevalence from regression
trendline in TSC2 rhabdomyoma group (N = 28). Figure S4. Residual plot
of the difference between observed value and predicted value of brain
lesion prevalence from logarithmic trendline in TSC1 brain lesion group (N
= 19). Figure S5. Residual plot of the difference between observed value
and predicted value of brain lesion prevalence from logarithmic trendline
in TSC2 brain lesion group (N = 59). Figure S6. QQ plot of Shapiro-Wilk
test for normality of brain lesion prevalence TSC1 vs TSC2. Figure S7. QQ
plot of Shapiro-Wilk test for normality of AML size distribution TSC1 vs
TSC2. Figure S8. Residual plot of the difference between observed value
and predicted value of AML prevalence from logarithmic trendline in
TSC1 group (N = 18). Figure S9. Residual plot of the difference between
observed value and predicted value of AML prevalence from logarithmic
trendline in TSC2 group (N = 45). Figure S10. QQ plot of Shapiro-Wilk test
for normality of AML prevalence TSC1 vs TSC2.
Acknowledgements
The authors thank the patients, study coordinators and investigators who
participated in this trial.
Authors’ contributions
OU and YAS designed the research. OU and JFG contributed to the data acqui-
sition. JR, TEW and YAS conducted the research. JR and TEW performed the
statistical analysis. AJH, NRL and OU provided the critical revision. JR, IRH and
YAS wrote the first draft of the manuscript. The authors revised and approved
the final version of the manuscript. The authors read and approved the final
manuscript.
Funding
YAS is funded by a CMU fellowship and a project grant from the Hodge
Foundation.
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 18 of 19
Robinsonetal. BMC Medicine (2022) 20:123
Availability of data and materials
The data that supports the findings are available upon request from cor-
responding authors.
Declarations
Ethics approval and consent to participate
Ethical approval of this retrospective review study was not necessary as the
data was retrieved anonymously from the previously collected clinical infor-
mation in various databases.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1 Neuroscience and Mental Health Research Institute, Hadyn Ellis Building,
Cardiff CF24 4HQ, UK. 2 School of Bioscience, The Sir Martin Evans Building,
Museum Ave, Cardiff CF10 3AX, UK. 3 University Hospital of Wales, Heath Park,
Cardiff CF10 3AX, UK. 4 Royal United Hospitals Bath NHS Foundation Trust,
Bath BA1 3NG, UK. 5 School of Mathematics, Cardiff University, Cardiff CF24
4AG, UK.
Received: 8 December 2021 Accepted: 7 March 2022
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