J Dent Res 82(7): 523-527, 2003
© 2003 International and American Associations for Dental Research
RESEARCH REPORT
Clinical
Segregation Analysis of Mandibular
Prognathism in Libya
A.A. El-Gheriani1,2, B.S. Maher2, A.S. El-Gheriani3, J.J. Sciote4, F.A. Abushahba5, R. Al-Azemi4,7, and M.L. Marazita1,2,6,*
1
Department of Human Genetics, Graduate School of Public Health, 500 Cellomics Bldg., University
of Pittsburgh, 100 Technology Dr., Pittsburgh, PA 15219;
2
Center for Craniofacial and Dental Genetics, Division of Oral Biology, School of Dental Medicine,
University of Pittsburgh, PA;
3
Department of Prosthodontics, Faculty of Dentistry, Benghazi, Libya (currently Department of
Restorative Dentistry, Ajman University of Science and Technology, Ajman, UAE);
4
Department of Orthodontics, School of Dental Medicine, University of Pittsburgh, PA
7
(currently Department of Orthodontics, Ministry of Health, Kuwait);
5
Department of Orthodontics, Faculty of Dentistry, Benghazi, Libya; and
6
Department of Oral and Maxillofacial Surgery, School of Dental Medicine, University of Pittsburgh,
PA;
*corresponding author, marazita@sdmgenetics.pitt.edu
ABSTRACT
The etiology of mandibular prognathism has been attributed to various genetic
inheritance patterns and some environmental factors. The variation in inheritance
patterns can be partly due to the use of different statistical approaches in the
respective studies. The objective of this study was to investigate the role of genetic
influences in the etiology of this trait. We performed segregation analysis on 37
families of patients currently being treated for mandibular prognathism. Mandibular
prognathism was treated as a qualitative trait, with cephalometric radiographs, dental
models, and photographs used to verify diagnosis. Segregation analysis of a
prognathic mandible in the entire dataset supported a transmissible Mendelian major
effect, with a dominant mode of inheritance determined to be the most parsimonious.
KEY WORDS:
mandible • mandibular prognathism • Class III malocclusion • genetics
INTRODUCTION
Mandibular prognathism is a common finding, with prevalence varying by race
(Singh, 1999)—in particular, with higher prevalence in East Asians (Allwright and
Bundred, 1964), Africans (Garner and Butt, 1985), and Caucasians (Emrich et al.,
1965), respectively—and also varying by age, ranging from an approximate
prevalence of 0.5% in children 6-14 yrs old (Newman, 1956) to a range of 2-4% in
adults (Jorgenson, 1990).
Despite many years of investigation, the relative contributions of genetic and
environmental components in the etiology of non-syndromic mandibular prognathism
are unclear. Mossey (1999) states that this is due to a lack of research dedicated to this
problem, relatively imprecise measuring tools and limited knowledge about the
genetic mechanisms involved, and the precise nature and effects of environmental
influences. It should also be added that little is known about the interaction between
genetic and environmental factors in the causation of mandibular prognathism.
Mandibular prognathism cases have been associated with various environmental
etiologies, such as: enlarged tonsils (Angle, 1907); endocrine imbalances (Downs,
1928); posture, trauma, and disease (Gold, 1949); hormonal disturbance (Pascoe et al.,
1960); congenital anatomic defects (Monteleone and Duvigneaud, 1963); and
instrument deliveries (Schoenwetter, 1974). Familial aggregation of mandibular
prognathism has also been described and ascribed to a variety of genetic models,
including autosomal-recessive (Downs, 1928; Iwagaki, 1938), autosomal-dominant
(Stiles and Luke, 1953; Wolff et al., 1993), and a polygenic model of transmission
(Litton et al., 1970). However, Kraus et al.(1959) maintained that "the role of heredity
could not be discerned". Although the genetic models differ, there is a consensus that
there is a role for genetics in determining the occurrence of mandibular prognathism.
Understanding the specific genetic factors contributing to variation in the risk for
mandibular prognathism would be a major advance in dentofacial orthopedics and oral
and maxillofacial surgery.
The goal of the current study was to apply modern methods of segregation analysis to
examine specific genetic models of the familial transmission of mandibular
prognathism in a series of large Libyan families.
MATERIALS & METHODS
Subjects
The authors identified 37 probands with mandibular prognathism from the patient
base of several dental clinics in Benghazi, Libya. Complete family histories for each
proband and the affection status of other individuals in each family were confirmed by
cephalometric, photographic, and/or dental models. The study sample of 37 families,
comprised of 1013 individuals (285 first-degree relatives, 658 extended relatives, and
33 individuals related to the proband through marriage), is summarized in Table 1 .
Consenting probands (or their parent/guardian) were asked to discuss this study with
other family members prior to participation in the study. The study protocol was
approved by the University of Pittsburgh Institutional Review Board, and informed
consent was obtained from all subjects.
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Table 1. Numbers of Individuals by Phenotype and Sex in 37
Families Ascertained through Probands with Mandibular
Prognathism
Procedure
Assessment
We determined mandibular prognathism by assessing one or more of the following
orthodontic records: a lateral cephalogram, orthodontic study models, and/or lateral
profile facial photographs (Fig. ). This assessment was done by Drs. A.S. El-Gheriani
and F.A. Abu-shahba. The highest level of evidence was considered to be the
radiographic records; if radiographic records were not available, then dental models
were used. If no dental models were available, photographs were utilized. Cases for
which affection status consensus could not be reached were classified as unknown.
Figure. Shown in three different subjects are the
diagnostic criteria for inclusion, either (a) a
cephalogram, (b) a study model, or (c) a lateral
photograph.
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All 37 probands had a lateral cephalometric radiograph as part of their treatment
record, and a confirmed negative ANB angle was a prerequisite for enrollment in the
study; however, we were able to obtain lateral cephalometric radiographs on 11
subjects for further evaluation at the University of Pittsburgh School of Dental
Medicine. These cephalograms were measured and compared with selected linear and
angular values found in the Bolton Growth Study (Broadbent et al., 1975) (Table 2 ).
Since the data are stratified by age and sex, we chose pooled sex measurements at age
12 as the mean value for each measurement for comparative purposes. Although interand intra-rater reliability measurements were not assessed, we used the 11
cephalographs as confirmation of the clinical diagnosis made on all subjects, since the
cephalometric values confirmed a skeletal class III diagnosis in all cases.
View this table: Table 2. Cephalometric Analysis Results
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This criterion establishes the forward relationship of the mandible to the maxilla.
Affection status of relatives (on whom radiographic records were not available) was
determined by the presence of an edge-to-edge incisor relationship or an anterior
crossbite in dental casts articulated in centric jaw relation. The final diagnostic tool
was the utilization of lateral photographs on individuals for whom radiographic and
dental cast records were unavailable. The subject was determined to have a prognathic
appearance (concave facial profile) when viewed in a lateral photograph. Individuals
for whom these records were not available were classified as unknown.
Statistical methods
We investigated the role of genetics and other influences in the skeletal malocclusion
family patterns by fitting class A regressive models (Bonney, 1984) as implemented
by the REGD routine (for dichotomous traits) in S.A.G.E. release 3.1 [SAGE, 1994].
These models assume that variation in a trait among individuals results from a major
gene effect and residual variation which may reflect both familial correlations and
individual variation. The class A models assumed that the similarity between siblings
is due only to common parentage. We tested hypotheses by fitting a more complete
model and comparing the resulting likelihood with those of reduced nested models.
The analysis model allowed for statistical detection of major transmissible effects in a
dichotomous trait, but did not allow for explicit tests of multigenic/multifactorial
contributions to the trait. Such tests are not readily available for analysis of a
dichotomous trait in extended kindreds. The hypothesis of most interest was whether
there was a major effect that would then allow the application of the powerful genemapping methods to identify specific gene(s) involved in mandibular prognathism.
Such gene-mapping methods will also allow for assessment of multigene
contributions to the trait, and also gene x environmental interactions.
The overall model that was used allows for two alleles (A and B) at a single locus,
resulting in three genotypes or "types" (AA, AB, BB). For our analyses, we assumed
the distribution of the three types in the population to be in Hardy-Weinberg
equilibrium. In the "no transmission" test, there is only one type.
The parameters of the models include the regression coefficients for each "type" (ßAA,
ßAB, ßBB), and the frequency of allele A (denoted qA). Individuals of types AA, AB,
and BB were assumed to transmit the A allele to their offspring with probabilities AA,
AB,
and BB. These transmission probabilities were used to calculate the probabilities
of all three types for individuals whose parents are in the pedigree.
The segregation analyses consisted of fitting a series of models ranging from simple
no-transmission models to the most general transmission model. The general model
was fitted and compared with various more restricted submodels. To guard against the
presence of multiple local maxima, we used several initial estimates of the parameters.
Models that were tested for skeletal malocclusion will include no-transmission
models, A-dominant, A-recessive (B-dominant), additive and co-dominant major gene
models, and a general model. The no-transmission model assumed one type with all
individuals being independent of one another. The A-dominant model restricted ßAA =
ßAB, while a B-dominant model restricted ßAB = ßBB. The additive model assumed ßAB
to be the average of ßAA and ßBB. The co-dominant major gene model put no
restrictions on the types. Under these genetic models, the transmission parameters
were restricted to the Mendelian expected values of AA = 1, AB = 0.5 and BB = 0.
For us to utilize the general model in these analyses, there were no restrictions on the
regression coefficients of the types or on tAB, allowing for tests of Mendelian
transmission.
Segregation analysis is sensitive to the method of identifying families, i.e., the
ascertainment scheme used. In these studies, families were ascertained through
probands. The analysis was therefore adjusted for the ascertaining scheme by
conditioning on the probands when the likelihood calculations were performed.
Hypotheses were tested according to the Likelihood Ratio Criterion, which is the ratio
of the maximum value of the likelihood under the most general model to the
likelihood under a restricted model. Each null hypothesis corresponds to one or more
restrictions being placed on the most general model to the likelihood under a restricted
model. The models were evaluated with a test statistic defined as minus the log of the
likelihood ratio criterion. The distribution of this statistic was approximated by a 2
distribution with the number of degrees of freedom equal to the difference in the
numbers of parameters between the model under the null hypothesis and the more
general model. The null hypothesis was rejected if this statistic is greater than the 2
value corresponding to the desired significance level ( = 0.05). Additionally, equally
likely models were assessed based on Akaike’s information criteria (AIC; Akaike,
1974). For any given model, the AIC = -2ln(L) + 2 number of parameters estimated.
The model with the lowest AIC was considered to be the most parsimonious among
equally likely models.
RESULTS
The segregation analysis results are summarized in Table 3 . Compared with the
general model, the no-transmission model (p = 0.01) and co-dominant major gene
model (p < 0.001) were both rejected. Autosomal-dominant, -recessive, and additive
major locus models could not be rejected by the likelihood ratio test (all p-values >
0.14). Of the models that were not rejected, the autosomal-dominant major locus
model was determined to be the most parsimonious (AIC = 531.65).
View this table: Table 3. Results of Segregation Analysis
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DISCUSSION
Our results support the previous findings that there is a hereditary component to the
expression of this phenotype. We were able to rule out the "no transmission" and codominant models. By utilizing the AIC, we were able to conclude that, among the
autosomal-dominant, -recessive, and additive models, the autosomal-dominant model
was the most parsimonious. Our conclusion of autosomal-dominant inheritance was in
agreement with Wolff et al.(1993), who utilized pictures or authentic descriptions to
determine affection status, but disagreed with the polygenic conclusion of Litton et
al.(1970). Note that Litton et al.(1970) relied on articulated dental casts, while we
used cephalograms as a means of determining affection status.
Now that we have statistical genetic evidence for major locus involvement in
mandibular prognathism, gene-mapping studies will be feasible. Gene-mapping
studies would have the potential to identify the gene or genes involved in the trait,
providing powerful confirmation for a genetic basis for mandibular prognathism. Such
studies will also allow for tests of multiple genes to detect any etiological
heterogeneity in the trait.
Careful clinical characterization of mandibular prognathism will be key to additional
progress in our understanding of the genetics of this common disorder. The Steiner
analysis is readily known and easy to perform, and, as Saunders et al.(1980) reported,
there is a positive correlation between the ANB angle among family members. Note,
however, that the important points are the relative position of the mandible to the
cranial base/maxilla, and also which aspects of the skeletal morphology seem to be
associated with the relative mandibular prognathism.
The drawback to basing this study on cephalometric records was the ethical
implication of unnecessary radiation exposure. Therefore, the probands who were
required to have radiographs taken as part of their routine treatment were confirmed
radiographically; however, the affection status of other relatives could not be verified
unless they were also under orthodontic treatment. The use of dental models, as
proposed by Ngan et al.(1997), to diagnose Class III malocclusion overcomes the
radiation exposure issue; however, the contributions of each growth site and anatomic
area cannot be determined in the overall phenotypic expression when diagnosis is
based on dental models.
The cephalometric analysis (Table 2 ) highlights the difficulty in the study of this
trait. The ages ranged from 10 to 38 yrs, and the ANB angles ranged from -0.9° to 9.1°. Even though all 11 subjects have a negative ANB, there were noticeable
differences in their cephalometric measures that warrant the notion that there may be
multiple factors or multiple types of mandibular prognathism (Jacobson et al., 1974).
The Bolton standards were compared with our measured values because there are no
definitive cephalometric norms for the Libyan population, and Libyan schoolchildren
have been shown to have a cephalic index similar to that of European schoolchildren
(Gardiner, 1982).
Other than the fact that the phenotype is difficult to define correctly, craniofacial
growth, and particularly the growth of the mandible, is highly variable and is reported
to continue into the late teens and well beyond the third decade of life (Behrents,
1985), although Tollaro et al.(1994) reported that a distinctive Class III pattern could
be detected in children with complete deciduous dentitions (age 4-6 yrs). It is not
reasonable for clinicians to delay treatment for those individuals exhibiting
mandibular prognathism in an attempt to see the final phenotype, and conversely,
could one compare the untreated cases of mandibular prognathism (individuals in their
late 20s and beyond) with those of pre-pubescent children who are still growing?
Litton et al.(1970) used a cut-off point of 15 years of age, such that all unaffected
children below the age of 15 were classified as unknown, since there is potential for
them to develop this condition at a later time. We did not incorporate such a condition
into our study and will be looking at the incidence of mandibular prognathism with
increasing age for future studies.
The emphasis now should be placed on devising a safe and acceptable method of not
only diagnosing mandibular prognathism, but also investigating the inheritance
patterns of each skeletal morphologic characteristic that may contribute to it. Once a
definitive method of phenotype classification is developed, this study will be
expanded to other population groups in the US, Europe, Africa, and the Middle East.
Finally, given this statistical evidence of a major transmissible effect in mandibular
prognathism, we will begin linkage studies to identify the specific gene(s) involved in
the trait.
ACKNOWLEDGMENTS
This study was supported by NIH grant T35-DE07336. The results of this paper were
obtained by use of the program package S.A.G.E., which is supported by a US Public
Health Service Resource Grant (1 P41 RR03655) from the National Center for
Research Resources. We also thank Drs. M.K. Nair, F. Hamad, A. Sultan, R.E.
Ferrell, M. Rahouma, H. Ben Khayal, Mr. F Reybod, and the study subjects for their
contributions to this research.
Received September 5, 2002; Last revision January 13, 2003; Accepted April 15,
2003
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