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Kallionpää RA, etal. J Med Genet 2020;0:1–7. doi:10.1136/jmedgenet-2020-107062
ORIGINAL RESEARCH
Haploinsufficiency of the NF1 gene is associated with
protection againstdiabetes
Roope A Kallionpää,1 Sirkku Peltonen,2,3 Jussi Leppävirta,4,5 Minna Pöyhönen,4,5
Kari Auranen,6 Hannu Järveläinen,1,7 Juha Peltonen 1
Genotype- phenotype correlations
To cite: Kallionpää RA,
Peltonen S, Leppävirta J, etal.
J Med Genet Epub ahead of
print: [please include Day
Month Year]. doi:10.1136/
jmedgenet-2020-107062
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1Institute of Biomedicine,
University of Turku, Turku,
Finland
2Department of Dermatology
and Venereology, University of
Turku, Turku, Finland
3Department of Dermatology,
Turku University Hospital, Turku,
Finland
4Department of Clinical
Genetics, HUSLAB, Helsinki
University Hospital (HUS)
Diagnostic Center, Helsinki,
Finland
5Department of Medical and
Clinical Genetics, University of
Helsinki, Helsinki, Finland
6Department of Mathematics
and Statistics and Department
of Clinical Medicine, University
of Turku, Turku, Finland
7Department of Internal
Medicine, Satakunta Central
Hospital, Pori, Finland
Correspondence to
Professor Juha Peltonen,
Institute of Biomedicine,
University of Turku, Turku FI
20520, Finland; juhpel@ utu. fi
Received 1 April 2020
Revised 8 May 2020
Accepted 11 May 2020
© Author(s) (or their
employer(s)) 2020. Re- use
permitted under CC BY- NC. No
commercial re- use. See rights
and permissions. Published
by BMJ.
ABSTRACT
Background The hereditary predisposition to diabetes
is only partially explained by genes identified so far.
Neurofibromatosis type 1 (NF1) is a rare monogenic
dominant syndrome caused by aberrations of the NF1
gene. Here, we used a cohort of 1410 patients with NF1
to study the association of the NF1 gene with type 1
(T1D) and type 2 diabetes (T2D).
Methods A total of 1410 patients were confirmed to
fulfil the National Institutes of Health diagnostic criteria
for NF1 by individually reviewing their medical records.
The patients with NF1 were compared with 14 017
controls matched for age, sex and area of residence as
well as 1881 non- NF1 siblings of the patients with NF1.
Register- based information on purchases of antidiabetic
medication and hospital encounters related to diabetes
were retrieved. The Cox proportional hazards model was
used to calculate the relative risk for diabetes in NF1.
Results Patients with NF1 showed a lower rate of T2D
when compared with a 10- fold control cohort (HR 0.27,
95% CI 0.17 to 0.43) or with their siblings without NF1
(HR 0.28, 95% CI 0.16 to 0.47). The estimates remained
practically unchanged after adjusting the analyses for
history of obesity and dyslipidaemias. The rate of T1D
in NF1 was decreased although statistically non-
significantly (HR 0.58, 95% CI 0.27 to 1.25).
Conclusion Haploinsufficiency of the NF1 gene may
protect against T2D and probably T1D. Since NF1
negatively regulates the Ras signalling pathway, the
results suggest that the Ras pathway may be involved in
the pathogenesis of diabetes.
INTRODUCTION
Diabetes is characterised by impaired insulin produc-
tion or action, leading to chronically increased
blood glucose concentrations. Type 2 diabetes
(T2D) is the most common form of diabetes.1 It
typically manifests in adulthood and is strongly
linked to lifestyle factors such as obesity and lack
of exercise.1 2 The development of T2D involves
decreased insulin sensitivity and commonly leads
to impaired insulin production.1 3 Type 1 diabetes
(T1D) is an autoimmune disorder characterised
by destruction of the insulin- producing β-cells in
the pancreas.4 T1D is usually diagnosed already in
childhood. While T2D can be treated with a variety
of medications and lifestyle changes, patients with
T1D are fully dependent on insulin treatment.
Both types of diabetes are associated with increased
mortality.1 4
Familial aggregation and twin studies clearly
indicate a genetic component in diabetes risk.2 4–6
However, the genetic risk for especially T2D is highly
complex with relatively limited contributions from
individual genes. Genome- wide association studies
(GWAS) and sequencing have identified numerous
variants associated with T2D.7–11 These are mostly
common variants with small or modest effects or
low frequency variants with larger effects.9 12 Vari-
ants protective against T2D have been described
in, for example, CCND2,8 9 SLC30A8,11 13 TCF2,14
MC4R15 and PPARG,16 some of which can also
harbour risk- increasing variants.8 15 Regarding
T1D, up to 50% of its heredity can be explained
by human leucocyte antigen (HLA) genes, espe-
cially with HLA- DR3- DQ2 and HLA- DR4- DQ8
conferring increased risk as well as certain HLA
haplotypes providing protection against T1D.5 17 18
Other major T1D- associated genes include INS,
PTPN22 and IL2RA while most of the known non-
HLA risk genes only confer minor increases in T1D
susceptibility.18 The genes contributing to the initial
development of autoimmunity may differ from
those involved in the progression from islet autoan-
tibodies to clinical T1D, which further complicates
the genetics of T1D.19 Since family history of T1D
associates with higher risk for T2D and vice versa,
these diseases are thought to have also shared risk
genes but only a few (eg, MTNR1B and HNF1A)
have been identified.20–22 The identification of the
genetic underpinnings of diabetes elucidates the
disease pathogenesis, and knowledge of the protec-
tive variants may also suggest novel therapeutic
approaches.12
Neurofibromatosis type 1 (NF1; MIM 162200)
is a dominantly inherited monogenic multiorgan
syndrome caused by aberrations of the NF1 gene
in chromosome 17q11.2. NF1 has a prevalence
of 1/3000–1/2000 (0.03%–0.05%).23 The diag-
nosis is based on the National Institutes of Health
(NIH) diagnostic criteria,24 which include café-
au- lait macules of the skin, cutaneous and plexi-
form neurofibromas, skinfold freckling, Lisch
nodules of the eye, optic glioma, distinct osseous
lesions and NF1 in a family member. The NF1
gene encodes a tumour suppressor protein neuro-
fibromin that downregulates Ras activity.25 Thus,
NF1 is a Rasopathy. The disease- causing variants
are spread throughout the gene, and only few
mutational hotspots have been identified.26 NF1
is associated with increased mortality and a variety
of comorbidities including predisposition to many
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Genotype- phenotype correlations
types of cancers and cardiovascular complications.27–32 Lower
fasting blood glucose concentrations have been reported in NF1
compared with control persons.33–35 A reduced rate of gestational
diabetes was observed in one cohort of patients with NF136 but
not in another.37 An analysis of insurance claims reported OR of
0.4 for diabetes among patients with NF1 in the USA.38 In addi-
tion, two previous studies based on death certificates have noted
a lower than expected number of diabetes- related deaths among
patients with NF1.39 40 However, these studies have not excluded
premature mortality associated with NF1 as the cause for the
lower rate of diabetes among patients with NF1. Interestingly, a
recent Danish cohort study reported a significantly reduced rate
of T1D- related hospitalisations and non- significantly reduced
rate of T2D- related hospitalisations among patients with NF1.32
Here, we aimed at further dissecting the risk for diabetes in NF1.
METHODS
Research permissions
Research permissions were obtained from the Finnish Insti-
tute for Health and Welfare, The Social Insurance Institution
of Finland, Finnish Population Register Centre and all partici-
pating hospitals. The study was register- based and exempt from
obtaining informed consent from participants.
Patients
The collection of the NF1 cohort has previously been
described.29 In brief, the cohort was collected by searching for
neurofibromatosis- related hospital visits in the 5 University
Hospitals and 15 Central Hospitals of mainland Finland in
1987–2011. The medical records of the patients identified in this
initial search were individually reviewed to confirm NF1 by the
NIH diagnostic criteria.24 Thus, the cohort is fully ascertained
and based on the complete population of mainland Finland.
The procedure yielded a total of 1410 patients with confirmed
NF1 and availability of valid minimum necessary information.
All Finnish residents have a unique personal identity code that
can be used as a key for retrieving information from national
registers.
The patients with NF1 were compared with two cohorts that
were formed using data from the Finnish Population Register
Centre: (1) For each patient with NF1, 10 controls matched for
date of birth, sex and place of residence were retrieved. First-
degree relatives of patients with NF1 were excluded. Due to the
small size of some municipalities, a total of 14 017 controls were
obtained. (2) Siblings of patients with NF1, defined by at least
one shared parent, were retrieved and persons with known or
suspected NF1 diagnosis were excluded. A total of 1881 non-
NF1 siblings of patients with NF1 were available.
Data sources
Dates of death and emigration were retrieved from the Finnish
Population Register Centre, yielding complete follow- up.
The Finnish Institute for Health and Welfare maintains the
Care Register for Health Care. The register was founded in 1969
as Hospital Discharge Register covering inpatient care. Since
1998, specialised public outpatient care has also been included.
The hospital visits and stays have been recorded using Interna-
tional Classification of Diseases, 9th revision (ICD-9) diagnosis
codes in 1987–1995 and ICD-10 diagnosis codes since 1996.
Each hospital visit and stay can be associated with up to six
diagnoses, all of which were taken into account in the present
study. These diagnoses do not necessarily reflect the primary
reason for the hospital encounter but may also be used to record
pre- existing chronic diseases. Hospital visits and stays associ-
ated with diabetes in overall were identified using ICD-10 codes
E10–E14. In order to identify T1D, ICD-10 code E10 was used.
For T2D, ICD-10 code E11 was used in 1996–2014 and ICD-9
code 250xA, where x can be any digit, was used pre-1996. The
ICD-10 code E66 was used to retrieve diagnoses of obesity, E78
for disorders of lipoprotein metabolism and other lipidaemias,
and I10 for primary hypertension.
The Social Insurance Institution of Finland is a govern-
ment agency that reimburses part of medication costs for most
prescription drugs bought by Finnish residents. The reimburse-
ments are paid directly to pharmacies when the drug is dispensed,
and the patient only pays the remaining part of the price. Since
the reimbursement does not require application by the patient,
the system encompasses the vast majority of all prescription
drug purchases in Finland. Reimbursed medication purchases
have been recorded since 1995 using Anatomical Therapeutic
Chemical (ATC) coding. Insulins and analogues are included in
class A10A and blood glucose lowering drugs other than insulins
in class A10B. Patients may also receive a higher special reim-
bursement of drugs prescribed for certain conditions, including
insulin- dependent diabetes, where an application by the physi-
cian is required.
Statistical methods
The primary study period was from 1 January 1998 to 31
December 2014 since all data types were available starting from
1998. The follow- up of patients with NF1 started at the age of
their first neurofibromatosis- related hospital visit or at their age
at the beginning of the study period, whichever was later. The
follow- up of controls started at the latter of the age at the first
neurofibromatosis- related hospital visit of the respective patient
with NF1 or the age at the beginning of the study period. The
follow- up of the siblings without NF1 started at birth, age at
the first neurofibromatosis- related hospital visit of their NF1
sibling(s) or the age at the beginning of the study period, which-
ever occurred last. For all study subjects, the follow- up ended at
the age of the first occurrence of a diagnosis of interest, death,
emigration or end of study period, whichever came first.
When all types of diabetes or T2D only were analysed, the
first occurrence of diabetes was defined by the first hospital
visit or stay with a relevant diagnosis code or the first purchase
of drugs classified as ATC A10A or A10B. In the T2D analysis
adjusted by the features of metabolic syndrome, the history
of having had a diagnosis of obesity or dyslipidaemias at any
time during the follow- up was included as a covariate. In the
T1D analysis, only the hospital visits and stays were considered
when defining the follow- up, but since T1D always progresses
to insulin- dependency, having purchased insulin or its analogue
(ATC A10A) at any time was also required to exclude any coding
errors. Patients with T1D were excluded from the analyses of
T2D. As a sensitivity analysis, the rate of T2D was also assessed
in the years 1987–2014 but medication purchases were not
included due to the availability of this information only since
1995. Another sensitivity analysis restricted the age range of
follow- up to 0–50 years.
Rates were estimated using the Poisson distribution. The esti-
mation of HRs was based on the Cox proportional hazard models
with delayed entry. In these analyses, the proportional hazards
assumption was fulfilled as assessed using scaled Schoenfeld
residuals. To allow heterogeneity between subgroups formed by
each patient with NF1 and the respective controls, a subgroup-
specific frailty term was included in the models. Similarly, in the
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Kallionpää RA, etal. J Med Genet 2020;0:1–7. doi:10.1136/jmedgenet-2020-107062
Genotype- phenotype correlations
Table 1 Characteristics of the study cohorts in the primary study period 1998–2014 and in the sensitivity analysis study period 1987–2014
Follow- up 1998–2014 Follow- up 1987–2014
Patients with NF1 Controls Siblings without NF1 Patients with NF1 Controls Siblings without NF1
n 1349 13 870 1871 1410 14 017 1881
Sex
Females, n (%) 694 (51.4) 7189 (51.8) 893 (47.7) 732 (51.9) 7256 (51.8) 895 (47.6)
Males, n (%) 655 (48.6) 6681 (48.2) 978 (52.3) 678 (48.1) 6761 (48.2) 986 (52.4)
Year of birth, mean (SD) 1975.2 (21.6) 1974.4 (22.0) 1976.5 (18.5) 1974.0 (22.4) 1974.0 (22.4) 1976.4 (18.5)
Start of follow- up (cohort entry)
Age, mean (SD) 25.7 (20.7) 26.3 (21.0) 24.4 (17.4) 23.6 (20.7) 23.6 (20.7) 21.5 (16.7)
Year, mean (SD) 2001.1 (4.2) 2001.0 (4.1) 2001.1 (4.1) 1997.6 (7.3) 1997.6 (7.3) 1997.9 (7.2)
End of follow- up
Age, mean (SD) 38.3 (20.8) 39.7 (21.5) 37.8 (18.4) 38.6 (21.0) 40.0 (21.6) 37.7 (18.4)
Year, mean (SD) 2013.1 (2.8) 2013.7 (1.8) 2013.7 (1.5) 2012.2 (4.9) 2013.5 (2.7) 2013.6 (2.1)
Follow- up time, mean
(SD)
12.7 (4.9) 13.4 (4.5) 13.4 (4.4) 15.0 (7.5) 16.3 (7.4) 16.2 (7.2)
NF1, neurofibromatosis type 1.
analyses comparing patients with NF1 and their siblings without
NF1, each family was included as a frailty term. Results are
reported as point estimates and 95% CIs. Statistical significance
is defined at the two- sided 5% level. The R software (V.3.6.1)
and package survival (V.3.1–8) were used in the analyses.
RESULTS
We explored the incidence of diabetes in NF1 using a cohort
of 1410 Finnish patients with NF1 (table 1). Patients with
NF1 were compared with 14 017 control subjects individually
matched for age, sex and place of residence. Another comparison
cohort consisted of 1881 non- NF1 siblings of the patients with
NF1. We used register- based information on hospital visits and
stays and purchases of antidiabetic medication in 1998–2014 to
identify those with diabetes. The overall rate of diabetes among
patients with NF1 was 1.7 cases per 1000 person- years (95%
CI 1.1 to 2.4) while the rate was 5.1 (95% CI 4.8 to 5.4) in the
control cohort and 4.3 (95% CI 3.5 to 5.2) among the non- NF1
siblings. Consequently, the relative rate of diabetes was markedly
lower among patients with NF1 when compared with controls
(HR 0.34, 95% CI 0.23 to 0.49) or the siblings without NF1
(HR 0.35, 95% CI 0.23 to 0.55).
Type 1 diabetes
We next analysed T1D and T2D separately. Seven persons with
T1D were observed in the NF1 cohort during the follow- up
1998–2014, while there were 129 persons with T1D in the
control cohort and 19 siblings with T1D (tables 2 and 3). The
HR for T1D in NF1 was 0.58 (95% CI 0.27 to 1.25) when
compared with controls and 0.55 (95% CI 0.23 to 1.33) when
compared with the siblings without NF1 but the associations
were not statistically significant (table 2). One patient with NF1
and eight control persons were observed to have both T1D
and coeliac disease, yet no cases of autoimmune thyroiditis or
Addison's disease were seen among the patients with T1D. No
complication of T1D was particularly common among patients
with NF1 (online supplementary table S1).
Type 2 diabetes
During the follow- up 1998–2014, T2D was significantly less
common among patients with NF1 than among controls (HR
0.27, 95% CI 0.17 to 0.43) or siblings without NF1 (HR 0.28,
95% CI 0.16 to 0.47) and the HRs for T2D in NF1 were even
lower than for T1D (table 2). Although statistically significant
in both sexes, the reduction in the rate was more pronounced
among males (HR 0.14, 95% CI 0.06 to 0.35 in comparison NF1
versus controls) than among females (HR 0.40, 95% CI 0.23 to
0.68). Approximately 90%–98% of the persons had purchased
antidiabetic medication while only 33%–40% had a T2D- related
hospital encounter, indicating that the treatment was primarily
carried out in primary care setting (table 4). Moreover, 5/7
patients with NF1 and T2D- related hospital encounters had at
least one hospital encounter due to T2D without complications
(online supplementary table S2).
To assess whether the lower rate of T2D among patients
with NF1 was affected by premature mortality, the analysis was
restricted to ages<50 years. The decreased rate of T2D in NF1
persisted at ages<50 years with HR 0.35 (95% CI 0.16 to 0.79)
in comparison with controls and HR 0.30 (95% CI 0.13 to 0.71)
in comparison with the siblings without NF1. In this analysis,
T2D was observed in six patients with NF1, 184 control subjects
and 36 siblings without NF1. We had to restrict the time range of
the primary analysis to 1998–2014 because outpatient hospital
visits were only available since 1998 and medication purchases
since 1995. However, the relative risk estimates remained stable
when the study period was extended to 1987–2014 and only
hospital visits and stays were considered (NF1 versus controls:
7 and 338 persons with T2D, respectively; HR 0.26, 95% CI
0.12 to 0.54; NF1 versus siblings: 7 and 28 persons with T2D,
respectively; HR 0.20, 95% CI 0.07 to 0.53).
We next explored whether the reduced rate of T2D in NF1
was related to metabolic syndrome and overweight. The HR for
a diagnosis of obesity in NF1 was 0.94 (95% CI 0.59 to 1.48)
compared with the matched controls and 1.44 (95% CI 0.76 to
2.72) compared with the siblings without NF1. When the rate of
any of the features of metabolic syndrome other than hypergly-
caemia were considered, that is, obesity, primary hypertension
and disorders of lipoprotein metabolism and other lipidaemias,
their HR in NF1 was 1.37 (95% CI 1.14 to 1.66) compared with
controls and 1.66 (95% CI 1.25 to 2.21) compared with the
siblings without NF1. After exclusion of hypertension, which is
known to be more prevalent among patients with NF1, the HRs
were 1.04 (95% CI 0.76 to 1.43) and 1.20 (95% CI 0.77 to 1.87),
respectively. Thus, the other components of metabolic syndrome
do not seem to be less frequent among patients with NF1 despite
the decreased rate of T2D. Consequently, after adjusting the
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Genotype- phenotype correlations
Table 2 Observed follow- up times, diabetes cases during the follow- up and the resulting HRs in NF1 as compared with controls without NF1 or siblings without NF1 in 1998–2014
Patients with NF1 vs controls Patients with NF1 vs siblings without NF1
All Females Males All Females Males
Type 1 diabetes HR (95% CI) 0.58 (0.27 to 1.25) 0.95 (0.38 to 2.36) 0.29 (0.07 to 1.2) 0.55 (0.23 to 1.33) 1.11 (0.35 to 3.52) 0.26 (0.06 to 1.16)
NF1 Number of diabetes cases 7 5 2 7 5 2
Follow- up (person- years) 17 005.9 8814.0 8191.9 17 005.9 8814.0 8191.9
Rate (n/1000 person- years) (95% CI) 0.41 (0.17 to 0.85) 0.57 (0.18 to 1.32) 0.24 (0.03 to 0.88) 0.41 (0.17 to 0.85) 0.57 (0.18 to 1.32) 0.24 (0.03 to 0.88)
Reference Number of diabetes cases 129 57 72 19 7 12
Follow- up (person- years) 184 594.4 97 064.6 87 529.8 24 928.7 12 138.2 12 790.5
Rate (n/1000 person- years) (95% CI) 0.7 (0.58 to 0.83) 0.59 (0.44 to 0.76) 0.82 (0.64 to 1.04) 0.76 (0.46 to 1.19) 0.58 (0.23 to 1.19) 0.94 (0.48 to 1.64)
Type 2 diabetes HR (95% CI) 0.27 (0.17 to 0.43) 0.40 (0.23 to 0.68) 0.14 (0.06 to 0.35) 0.28 (0.16 to 0.47) 0.37 (0.19 to 0.71) 0.15 (0.06 to 0.41)
NF1 Number of diabetes cases 19 14 5 19 14 5
Follow- up (person- years) 16 877.2 8714.6 8162.6 16 877.2 8714.6 8162.6
Rate (n/1000 person- years) (95% CI) 1.13 (0.68 to 1.76) 1.61 (0.88 to 2.70) 0.61 (0.20 to 1.43) 1.13 (0.68 to 1.76) 1.61 (0.88 to 2.70) 0.61 (0.20 to 1.43)
Reference Number of diabetes cases 779 402 377 83 42 41
Follow- up (person- years) 179 213.0 94 286.5 84 926.6 24 337.8 11 890.2 12 447.6
Rate (n/1000 person- years) (95% CI) 4.35 (4.05 to 4.66) 4.26 (3.86 to 4.70) 4.44 (4.00 to 4.91) 3.41 (2.72 to 4.23) 3.53 (2.55 to 4.77) 3.29 (2.36 to 4.47)
NF1, neurofibromatosis type 1.
T2D analyses for both history of obesity and dyslipidaemias, the
relative rate for T2D among patients with NF1 remained low
with HRs of 0.28 (95% CI 0.18 to 0.44) in comparison to the
control cohort and 0.27 (95% CI 0.16 to 0.46) in comparison to
the siblings without NF1.
DISCUSSION
Here, we have shown that NF1 is associated with a reduced rate
of T2D and a statistically non- significant reduction in the rate of
T1D. Since NF1 is caused by pathogenic variants of the NF1 gene
with full penetrance, the results suggest that germline aberrations
of the NF1 gene and the resulting deficiency of neurofibromin
protein confer protection against diabetes. NF1 syndrome is
rare with the prevalence <0.05%,23 and any individual patho-
genic variant of the NF1 gene is even rarer. Rare variants are
generally hard to detect in GWAS,12 and the case of NF1 is even
more difficult as the variants are spread throughout the gene.
Variants of NF1 are also associated with reduced fitness, further
decreasing their prevalence in older age groups.23 It is thus not
surprising that the association between the NF1 gene and T1D
or T2D has not been recognised in the previous studies looking
for genes associated with diabetes. Our approach of studying
a curated clinical cohort of patients who share aberrations of
the NF1 gene overcomes some of these limitations. The clinical
features of NF1 allow combining a variety of different variants
with similar functional consequences. Assuming a prevalence of
1/2000–3000 for NF1, observing as many persons with NF1
haploinsufficiency and diabetes as in our cohort would require
an unselected population of 2.8–4.2 million persons, which is
much more than in the largest diabetes- GWAS published so far.9
Only few genes affecting the risk of both T1D and T2D have
been identified despite their overlapping heritability patterns.20 21
Although the ages of onset and risk factors of T1D and T2D are
largely different, the two types of diabetes share pathological
processes. Both types may involve inflammatory loss of pancre-
atic β-cell mass, which is due to autoimmunity in T1D and toxic
metabolites in T2D.3 4 20 21 Moreover, T1D may present with
insulin resistance.20 21 The association between NF1 and T1D
reported here was not statistically significant, yet a reduced rate
of T1D- related hospitalisations among persons with NF1 was
also observed in a recent cohort study.32 Together, these results
suggest that NF1 aberrations may be a mechanism affecting both
types of diabetes. Unfortunately, our register- based data do not
allow dissecting whether the observed low HRs for T1D and
T2D in NF1 are related to, for example, inflammation or meta-
bolic activity. Previous data show NF1- associated alterations in
the immune system,41 and gene expression data from Schwann
cells suggest association of NF1 gene dosage with HLA class II
expression (NCBI GEO database, accession GSE32029), which
may speak in favour of an inflammation- mediated mechanism.
NF1 is known to affect especially the cells of the neural crest
during development. Interestingly, neural crest cells have been
observed to regulate the size of the β-cell population in a murine
model during embryonic development.42
Previous publications have suggested lower fasting blood
glucose levels, increased insulin sensitivity and higher resting
energy expenditure in NF1.34 35 43 Hypothetically, the volumi-
nous benign neurofibroma tumour mass could be one mecha-
nism increasing the energy consumption of patients with NF1.
The increased energy expenditure in NF1 is in concordance with
results from other Rasopathies, as high resting energy expendi-
ture has also been reported in patients with Costello syndrome,44
and a murine model of Noonan syndrome with multiple
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Kallionpää RA, etal. J Med Genet 2020;0:1–7. doi:10.1136/jmedgenet-2020-107062
Genotype- phenotype correlations
Table 3 Descriptive characteristics of patients with T1D during follow- up 1998–2014
Patients with NF1 Controls Siblings without NF1
n 7 129 19
Sex
Female, n (%) 5 (71.4) 57 (44.2) 7 (36.8)
Male, n (%) 2 (28.6) 72 (55.8) 12 (63.2)
Age at first T1D- related encounter during follow- up, mean (SD) 31.05 (19.15) 30.17 (20.42) 33.16 (20.99)
Number of T1D- related encounters/patient, median (range) 25 (2 to 72) 21 (1 to 1195) 22 (1 to 62)
Number of insulin purchases (ATC A10A)/patient, median (range) 50 (2 to 115) 66 (1 to 152) 62 (15 to 118)
Special drug reimbursement for insulin, n (%) 7 (100) 129 (100) 19 (100)
ATC, Anatomical Therapeutic Chemical classification; NF1, neurofibromatosis type 1; T1D, type 1 diabetes.
Table 4 Descriptive characteristics of patients with T2D during
follow- up 1998–2014
Patients with
NF1 Controls
Siblings
without NF1
n 19 779 83
Sex
Female, n (%) 14 (73.7) 402 (51.6) 42 (50.6)
Male, n (%) 5 (26.3) 377 (48.4) 41 (49.4)
Age at first T2D- related
encounter or drug purchase
during follow- up, mean (SD)
56.49 (17.45) 58.64 (14.18) 49.48 (12.63)
T2D- related encounters
Patients, n (%) 7 (36.8) 312 (40.1) 27 (32.5)
Number/patient among
those with at least
one encounter, median
(range)
2 (1 to 8) 2 (1 to 190) 2 (1 to 504)
Purchases of insulins and
analogues (ATC A10A)
Patients, n (%) 6 (31.6) 201 (25.8) 17 (20.5)
Number/patient among
those with at least one
purchase, median (range)
15 (2 to 22) 17 (1 to 99) 10 (1 to 85)
Purchases of other
antidiabetic medication
(ATC A10B)
Patients, n (%) 17 (89.5) 723 (92.8) 76 (91.6)
Number/patient among
those with at least one
purchase, median (range)
10 (1 to 81) 18 (1 to 128) 15 (1 to 104)
Special drug reimbursement
for insulin, n (%)
10 (52.6) 554 (71.1) 56 (67.5)
ATC, Anatomical Therapeutic Chemical classification; NF1, neurofibromatosis type 1;
T2D, type 2 diabetes.
lentigines showed increased energy expenditure.45 Costello
and Noonan syndromes and Noonan syndrome with multiple
lentigines have been reported to associate with lower weight
and a decreased rate of obesity.44–46 These findings suggest that
the present observation of reduced risk of T2D in NF1 may be
related to Ras signalling pathway activity. Interestingly, NF1 of
the child has been found to increase birth weight,37 while low
birth weight is known to be associated with increased risk for
T2D.47 Therefore, the increased birth weight of children with
NF1 may be an underlying factor of the lower risk for T2D in
NF1, or both these observations may reflect the same biological
process. Our present analysis of obesity and other components
of metabolic syndrome do not suggest lower incidence of these
risk factors among patients with NF1, nor did we previously find
altered rates of gestational diabetes in NF1.37
In light of the previous studies,48 the association between the
NF1 gene and T2D highlights the role of the Ras pathway in the
pathogenesis of T2D. The increased phosphorylation of Erk1/2
has previously been linked to protection against T2D by gain-
of- function variants of MC4R,15 and the protection conferred
by AKNRD55 is linked to MAP3K1 (MEK kinase).7 The lean
phenotype observed in a mouse model of the Noonan syndrome
with multiple lentigines was observed to revert on MEK inhi-
bition.45 Moreover, a study using mouse embryonic fibroblasts
reported altered mitochondrial function attributed to ERK1/2
activity induced by NF1 loss.49 While the pharmacological inhi-
bition of the tumour suppressor protein neurofibromin is not a
feasible therapeutic approach, downstream components of the
Ras pathway may provide targets for interfering with the patho-
genesis of T2D.
The present findings are corroborated by previous studies,
which suggested a lower rate of diabetes in NF1.32 38–40 Our
total population- based approach reduces biases inherent in
hospital- based patient ascertainment and the individual curation
of NF1 diagnoses ensures reliability. Since we assessed the rates
of diabetes using patient- specific person times conditionally on
survival, the premature mortality associated with NF1 cannot
explain the findings. This conclusion is further supported by
the robustness of the decreased rate of T2D in NF1 also among
persons aged <50 years. Moreover, we were able to analyse T1D
and T2D separately to show that especially the rate of T2D is
reduced among patients with NF1. A limitation of the present
study is the lack of biospecimens that would allow elucidating
the reasons of the decreased rate of diabetes, and T2D in partic-
ular, seen in NF1. The use of register- based data also leaves some
uncertainty in the diabetes diagnoses as a large proportion of
T2D is known to be undiagnosed in the population. However,
patients with NF1 are not expected to have a higher rate of
missing diagnoses than persons without NF1, since NF1 and
its comorbidities are likely to increase the number of healthcare
contacts. Furthermore, the comprehensive data on medication
purchases should allow identification of all patients undergoing
treatment.
All the patients with NF1 included in the present study fulfilled
the diagnostic criteria of NF1 and thus carried a pathogenic
variant of the NF1 gene. Comparing patients with NF1 with both
the matched controls and siblings allows ruling out confounding
related to, for example, calendar time, age, parental education
or hereditary factors other than NF1. Thus, we conclude that the
lower rate of at least T2D and probably T1D in NF1 is indeed
associated with the NF1 gene.
Acknowledgements Turku University Hospital is a member of ERN GENTURIS.
Contributors Data acquisition: RAK, SP, JL, MP, JP. Data analysis: RAK, JL, KA.
Drafting the manuscript: RAK. All authors have made contributions to the conception
on June 22, 2020 by guest. Protected by copyright.http://jmg.bmj.com/J Med Genet: first published as 10.1136/jmedgenet-2020-107062 on 22 June 2020. Downloaded from
6Kallionpää RA, etal. J Med Genet 2020;0:1–7. doi:10.1136/jmedgenet-2020-107062
Genotype- phenotype correlations
and design of the study, taken part in data interpretation, revised the manuscript
and approved the submitted version.
Funding The study was funded with grants from the Finnish Cancer Foundation,
Turku University Hospital, University of Turku, Turku University Foundation, Orion
Research Foundation and Ida Montin Foundation.
Competing interests JP, consultant to AstraZeneca.
Patient consent for publication Not required.
Ethics approval The study was approved by the Ethics Committee of the Hospital
District of Southwest Finland and adhered to the principles of the Declaration of
Helsinki.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data may be obtained from a third party and are
not publicly available. Data are available for researchers with appropriate research
permissions from Finnish Institute for Health and Welfare, The Social Insurance
Institution of Finland and Finnish Population Register Centre.
Open access This is an open access article distributed in accordance with the
Creative Commons Attribution Non Commercial (CC BY- NC 4.0) license, which
permits others to distribute, remix, adapt, build upon this work non- commercially,
and license their derivative works on different terms, provided the original work is
properly cited, appropriate credit is given, any changes made indicated, and the use
is non- commercial. See:http:// creativecommons. org/ licenses/ by- nc/ 4. 0/.
ORCID iD
JuhaPeltonen http:// orcid. org/ 0000- 0002- 5732- 4167
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