Oral vascular network pattern abnormalities in the
unaffected parents of children with achondroplasia
CLAUDIO DE FELICE1* , GIORGIO BIANCIARDI3*, STEFANO PARRINI4, PETER SHERIDAN DODDS7,
KENNETH SHIRRIFF8, GIOVANNI DI MAGGIO2, RICARDO N. LAURINI9, AND GIUSEPPE LATINI5,6
……………………………………………………………………………………………
1
Neonatal Intensive Care Unit, Section of Preventive Paediatrics and Neonatology
and 2Section of Paediatric Surgery,
Department of Paediatrics, Obstetrics and Reproductive Medicine, Siena, Italy
3
Institute of Pathological Anatomy and Histology, Siena, Italy
4
Department of Odontostomatological Sciences, Siena, Italy
5
Division of Paediatrics, Perrino Hospital, Azienda Ospedaliera A. Di Summa, Brindisi, Italy
6
Clinical Physiology Institute (IFC-CNR), National Research Council of Italy, Lecce Section, Italy
7
Department of Earth Sciences, Columbia University, New York, USA
8
(……….)Berkeley (?), California, USA
9
Department of Obstetrics and Gynaecology, University Hospital San Joao, Porto, Portugal
* These authors contributed equally to the work
Correspondence should be addressed to C.D.F.; email: defelice.claudio@libero.it
2
ABSTRACT
Achondroplasia (ACH) (OMIM 100800), the most frequent form of skeletal dysplasia in
humans1, is usually associated with a missense mutation resulting in a Gly 380Arg (G380R)
amino acid change in the transmembrane domain of the fibroblast growth factor receptor-3
(FGFR3) gene2, and is transmitted as an autosomal dominant disorder. However,
approximately 90% of the ACH cases are sporadic as the result of a de novo mutation3, and no
phenotypical markers for the unaffected ACH parents are known. An abnormal
vascularization in ACH patients4 and ACH animal models5,6 has been previously reported.
The 2-D vascular network geometry of the venous plexus of the oral mucosa was analysed in a
reproducible manner in the unaffected parents of ACH children. The ACH parents showed
significantly higher network density, fractal dimension, and minimum-path dimension and
significantly lower vessel-free area size compared to controls. Density and vessel-free area size
were highly accurate in identifying subjects with an ACH offspring (97.1 to 100% sensitivity,
100% specificity). The findings indicate the presence of a previously unrecognised, vascular
network abnormality of the oral mucosa in the unaffected parents of children with ACH, and
provide a useful clinical marker for identifying couples potentially at risk for ACH offspring.
3
RESULTS
The oral vascular network patterns of the unaffected ACH parents appeared to be
significantly more complex than those of control parents (Fig. 1), in the absence of other
macroscopical differences. The ACH children and the unaffected ACH parents showed
significantly higher vascular density, D(1-46),D (1-15)and Dmin, together with a lower vessel-free
area size than age- and sex-matched controls (Table 1). In particular, vascular density in the ACH
parents was 1.81  0.14 times higher and vessel-free area size was 3.33  0.069 times lower than
that of control parents. No statistically significant differences in the examined vascular pattern
characteristics between the vascular networks of the unaffected ACH parents and those of the ACH
children were found (P 0.29). Oral vascular network of the unaffected ACH fathers exhibited a
significantly higher complexity than those of the unaffected ACH mothers, with higher vascular
density (P=0.0004), D(1-46) (P=0.0002), D (1-15)(P=0.012)and Dmin (P<0.00001), as well as a
lower vessel-free area size value (P<0.00001).
A vascular network density >10.65% and a median vessel-free area size  56,832 m2 were
found to accurately discriminate the unaffected ACH parents from the control parents (Table
2),with adequate model calibration (2  0.02, df = 1, p  0.90). No statistically significant
difference between these two AUCs was observed (AUC difference: 0.0025  0.016 [95% CI: 0.004, 0.08]; p=0.10). Conversely, fractal dimensions [ (D(1-46), D (1-15) ] showed lower accuracy
as compared to the other network parameters (AUC difference range 0.025  0.016 to 0.038 
0.021; p≤ 0.073).
DISCUSSION
The main findings of this study indicate the presence of a previously unrecognised venous
vascular pattern abnormality in the oral mucosa of the unaffected parents of children with FGFR3G380R mutation-associated ACH. This observation can be used as a clinical marker to identify
couples potentially at risk for ACH offspring.
An aberrant vascularization is a known feature of diagnostic significance in the growth plate
of ACH patients4, and FGFR-3G380R transgenic ACH mouse model5. In addition, evidence of
markedly dilated retinal veins6 for the cn mice model7 of ACH has been described. Angiogenesis is
of crucial importance for the normal development of endochondral bone formation and a delicate
balance between the rate of formation of calcified cartilage and its vascularization must be
maintained in order for bone development to proceed normally8. On the other hand, little is known
about the control of angiogenesis at the growth plate9. Our findings of an abnormal vascularization
in ACH patients in anatomical sites different from the growth plate cartilage suggest the presence of
ACH-associated mesenchymal changes more generalized than previously thought.
A marked paternal age effect is a well-known feature of ACH10 and the predominat paternal
origin of new mutations has been documented11. Our observation of a more significant vascular
network abnormality in the unaffected ACH fathers compared to the unaffected ACH mothers
appears to confirm the importance of a paternal effect in the disease.
In the present study, fractal geometry was applied as a tool to assess the oral vascular
networks’ complexity. It has been previously shown that fractal dimension (D), and other fractal
characteristics can be used to identify abnormal vascular patterns, including corneal12, retinal13, and
tumor-associated neovascular growth14,15. The D(1-46) and Dmin results for the vascular networks
of the ACH parents and patients dysplay intermediate characteristics from the diffusion-limited
aggregation-like16 behaviour of control networks to the percolation-like scaling17 of tumorassociated vascular growth14.
4
A more generally relevant question concerning the forces controlling the spatial arrangement
of vascular networks is to be addressed. The supracellular structures of a multicellular organism are
essentially the product of a stochastic process under incomplete mechanical restriction, where the
constituent units are piled up in an arrangement required from the second law of thermodynamics to
minimise the potential energy of the system. This leads to equilibrium space division (ESD), as a
general principle of supracellular structures18. As blood vessels are localised predominantly on the
edges of ESD, vascular geometry largely depends on ESD, where a uniform centripetal force is
generated mostly by the tension of the connective tissue18. Therefore, we speculate that the aberrant
oral vascularization observed in the unaffected ACH parents might be related to a hitherto
unrecognised, systemic mesenchymal abnormality. The mechanism underlying the observed
association between the mesenchymal changes in the parents and the occurrence of ACH in the
offspring is currently unknown.
The findings of the present study (i) indicate that a previously unrecognised, vascular
network pattern abnormality of the oral mucosa is present in the unaffected parents of children with
ACH and can provide a useful clinical marker for identifying potential couples potentially at risk
for ACH offspring; and (ii) generate the testable hypothesis that geometrical pattern abnormalities
of either oral or extra-oral vascular networks may occur in mesenchymal pathology-associated
diseases other than ACH.
5
METHODS
Subjects
Nonconsanguineous, unaffected parents (n=30; M:15, age: 34.6 ± 6.5 years; F:15, age: 31.5 ± 6.3 years) of ACH
children with typical phenotype and G-to-A transition at nucleotide 1138 of the FGFR3 gene, a total of 15 unrelated
children with sporadic ACH and FGFR3 G380R mutation (M: 9, F: 6; age 6.5 ± 2.2 years ; mean height-SD 0.36 ±
1.01, according to ACH growth charts19) together with a population of 45, genetically unrelated sex- and age-matched
control subjects (fathers, age: 34.1 ± 5.6 years, n=15; mothers, age: 30.8 ± 5.5 years, n=15; children, M:9; F:6; age 6.4
± 2.0 years, n=15) participated to the study. Informed consent was obtained from all the subjects or their parents. The
study was approved by the Italian National Association for the study of ACH (A.I.S.ac.). The clinical, biological and
demographic data for each subject were obtained by two operators who were unaware of the oral vascular findings.
Vascular Network Imaging and Analysis
A ~704 mm2–size area (~32 x 22 mm) of the lower vestibular and free gingival oral region was photographed for each
subject (1:1 ratio; orthogonal projection) 20,21. This particular anatomical area was selected due to the high-visibility of
the vasculature pattern and easy accessibility to photographic documentation. All photographs were taken by a single
operator with the use of a Yashica Dental Eye model photocamera equipped with an automated annular flash and a 55
mm, f 1:4 Yashica lens (Yashica-Kyocera Co., Kyoto, Japan). Kodak Elite Chrome 100 ISO/21 DIN films (KodakEastman Kodak Co., Rochester, New York, USA) were used and the positives developed according to the standard E-6
procedure. Direct prints from 35 mm slides were obtained according to the standard Ilfochrome procedure
(Ilfochrome-Chugai Photo Chemical Co, Tokyo, Japan). Images were digitised using a HP Scanjet 4C (color resolution:
300 d.p.i.) scanner (Hewlett-Packard, Palo Alto, California, USA), with a Windows ’98 operating system (Microsoft
Co., Redmond, Washington, USA). Manual outline of the vascular networks’ trajectories was performed using Adobe
Photoshop ver. 5.0 (Adobe Systems Inc., San Jose, California, USA) on a Sony 19” Trinitron Multiscan G420 screen
(Sony Co., Tokyo, Japan) (resolution: 16-m/pixel) by two independent operators who were unaware of the subjects
clinical findings. Non-readable areas were always <5% of the total digitised image area and were excluded from
analysis. The obtained two-dimensional vascular networks were analysed using the Image Pro-Plus ver. 1.3 image
analysis software (Image Pro-Plus-Media Cybernetics, Inc., Silver Spring, Maryland, USA). Images were processed to
threshold the vessel network without background interference and the networks were subsequently converted into an
outline of single pixels. Density of the vessel network and vessel-free area (inter-vessel “islands”) size were determined
automatically using the software histogram and counting functions, respectively. A total of 14,169 areas were evaluated
(unaffected ACH parents, n=8,105; ACH children, n=2,830; control parents, n= 1,756; and control children, n=1,478).
The fractal dimension of the skeletonized images was measured using the box-counting algorithm22 using a software
program written by one of the authors. As the natural fractals show upper and lower limits, the local fractal dimension
(D) was determined for two regions: box lengths <740 m (pixels 1-46, D(1-46) and <140 m pixels 1-15, D (115). The measuring procedure was calibrated against shapes of known fractal dimension (square, circle and quadric
Koch island) with accuracy ± 2 %. The fractal dimension of the minimum path, Dmin, was computed for each vascular
cluster from the power law lc = r Dmin, where Dmin is the exponent that governs the dependence of the minimum path
length between two points (lc) on the Pythagorean distance (r) between them17.The lc value was determined using the
algorithm by Herrmann & Stanley23. The whole procedure was found to be reproducible with mean intra- and interobserver coefficients of variation (CV%) < 5% and <10%, respectively [vascular network density, intra-observer
CV%: 4.64 ± 0.85, inter-observer CV% : 9.63 ± 6.16; D (1-46), intra-observer CV%: 0.74 ± 0.51, inter-observer
CV% : 1.14 ± 0.70; D(1-15), intra-observer CV%: 2.81 ± 1.39, inter-observer CV% : 3.76 ± 2.32; Dmin, intra-observer
CV%: 2.64 ± 1.99 ; inter-observer CV%: 7.52 ± 3.22); and vessel-free area size (A), intra-observer CV%: 3.22 ± 2.51;
inter-observer CV%: 5.69 ± 1.41) ( n=6 replicate observations)].
Statistical Analysis
Data were expressed as mean ± s.d. for continuous normally distributed data and median with interquartile range [25th
and 75th percentiles] for non normal distributions. The t-test or Wilcoxon’s test were used to compare continuous
normally distributed data and nonparametric continuous data, respectively. Discrimination (the ability of the model to
identify unaffected ACH parents and control parents) was tested using receiver characteristic (ROC) curves and an area
under the curve (AUC) value >0.80 was accepted to indicate good discrimination 24. Comparison of the AUCs were
evaluated by the DeLong method25. Model calibration was evaluated using 2 to compare the observed frequency with
the expected frequency of the unaffected ACH parents according to the examined oral vascular network characteristics.
A two-sided P value of <0.05 was considered to be statistically significant, and the Bonferroni corrected significance
levels were used for multiple t-tests.
Acknowledgements
6
We thank Laura De Felice (helpful discussion and inspiration); Gordon B. Avery, Emeritus Professor of
Paediatrics, Children’s Hospital, Washington (critical reading of a preliminary draft of the manuscript); the
Cartiera di Crusinallo SPA–Gruppo Favini (help in shape analysis); Alessandra Lombardi, MD and Laura
Valdambrini, MD (help in data collection); and all the ACH and control families who accepted to participate
in the study and Mrs. Donatella Valerio Sessa on behalf of the the Italian National Association for the study
of ACH (A.I.S.ac.). C.D.F. would like to dedicate this paper to his first clinical teacher, Bruna Marchi, MD.
7
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Fig. 1 Oral venous plexus vascular networks of the unaffected parents of ACH offspring show a significantly higher
complexity than those of control parents. a, Representative skeletonized oral vascular pattern of an unaffected ACH
father and b, a control father. Binary forms were generated after conversion from the original networks (photographs of
the lower oral vestibulum and free gingival oral region, orthogonal projection; 1:1 ratio).
.
Table 1 Unaffected ACH parents and ACH children display an abnormal oral vascular network pattern
Fathers
ACH (n=15)
Density (%)
D [1-46]
D [1-15]
Dmin
13.48 ± 0.72
1.84 ± 0.02
1.41 ± 0.05
1.31 ± 0.08
Vessel-free
size (m2)
area
30,720
[29,696-32,256]
Controls (n=15)
7.05 ± 2.39
1.59 ± 0.15
1.13 ± 0.11
1.07 ± 0.04
P<0.00001
P<0.00001
P<0.00001
P<0.00001
Mothers
ACH (n=15)
12.37 ± 0.80
1.78 ± 0.05
1.35 ± 0.07
1.16 ± 0.07
Controls(n=15)
7.25 ± 2.07
1.60 ± 0.12
1.14 ± 0.09
1.09 ± 0.03
100,864
[87,188-116,480]
P<0.00001
37,376
[29,696-35,462]
P<0.00001
P<0.00001
P<0.00001
P=0.0013
Children
ACH (n=15)
13.45 ± 1.07
1.82 ± 0.07
1.40 ± 0.08
1.33 ± 0.07
Controls (n=15)
11.35 ± 1.06
1.77 ± 0.02
1.28 ± 0.12
1.14 ± 0.11
P<0.00001
P=0.013
P=0.0032
P<0.00001
126,208
[113,920139,776]
P<0.00001
30,720
[29,184-32,256]
89,715
[84,454-94,973]
P<0.00001
Data are presented as mean ± s.d. with the exception of vessel-free area size in which median with interquartile range
are used. Statistical analysis was performed with a two-tailed, paired, Student’s t-test, with the exception of vessel-free
area size in which a two-tailed Wilcoxon test was used.
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Table 2 Low vessel-free area size and high vascular network density accurately discriminate between unaffected ACH
parents from control parents
Variable
Density (%)
D (1-46)
D (1-15)
Vessel-free area size
(m2)
Cut-off
AUC ± s.e.m.
Sensitivity (%)
Specificity (%)
Criterion
(95% C.I.)
(95% C.I. )
(95% C.I.)
> 10.85
0.998 ± 0.006
97.1
100
(0.936-1.0)
(85.0-99.5)
0.959 ± 0.025
85.7
92.6
(0.875-0.993)
(69.7-95.1)
(80.3-99.4)
0.973 ± 0.020
88.6
96.2
(0.894-0.996)
(73.2-96.7)
(80.3-99.4)
1.0
100
100
> 1.75
> 1.28
 56,832
Data are the result of a receiver-operating characteristic curve analysis
11
Corresponding Author: Claudio De Felice, MD, U.O. Terapia Intensiva Neonatale, Sezione di Pediatria
Preventiva e Neonatologia, Dipartimento di Pediatria Ostetricia e Medicina della Riproduzione, Azienda
Ospedaliera Senese, Viale M. Bracci 16, I-53100 Siena, Italy. Phone: +39 0577 586542; Fax:+39 0577
586155; e-mail: defelice.claudio@libero.it
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