Cluster analyzes of facial models of autistic patients aim to clarify whether it is possible to diagnose autism on the basis of facial features and further to stratify the autism spectrum disorder. We performed a cluster analysis of sets of 3D scans of ASD patients (116) and controls (157) using Euclidean and geodesic distances in order to recapitulate the published results on the Czech population. In the presented work, we show that the major factor determining the clustering structure and consequently also the correlation of resulting clusters with autism severity degree is body mass index corrected for age (BMIFA). After removing the BMIFA effect from the data in two independent ways, both the cluster structure and autism severity correlations disappeared. Despite the fact that the influence of body mass index (BMI) on facial dimensions was studied many times, this is the first time to our knowledge when BMI was incorporated into the faces clustering study and it thereby casts doubt on previous results. We also performed correlation analysis which showed that the only correction used in the existing clustering studies-dividing the facial distance by the average value within the face-is not eliminating correlation between facial distances and BMIFA within the facial cohort.

Department of Anthropology and Human Genetics Faculty of Science Charles University Prague Czech Republic

Department of Biology and Medical Genetics 2nd Faculty of Medicine Charles University Prague and Motol University Hospital Prague Czech Republic

Faculty of Science and Engineering Curtin University Perth Australia

PRENET Laboratoře Lékařské Genetiky s r o Pardubice Czech Republic

Zobrazit více v PubMed

Handbook of Autism and Pervasive Developmental Disorders. 2 (Wiley, 1997).

Hrdlička, M. & Komárek, V. Dětský Autismus: Přehled Současných Poznatků. 2 (Portál, 2014).

Vorstman JAS, Parr JR, Moreno-De-Luca D, Anney RJL, Nurnberger JI, Hallmayer JF. Autism genetics: Opportunities and challenges for clinical translation. Nat. Rev. Genet. 2017;18:362–376. doi: 10.1038/nrg.2017.4. PubMed DOI

Lai M-C, Lombardo MV, Baron-Cohen S. Autism. Lancet. 2014;383:896–910. doi: 10.1016/S0140-6736(13)61539-1. PubMed DOI

Wing L, Gould J. Severe impairments of social interaction and associated abnormalities in children: Epidemiology and classification. J. Autism Dev. Disord. 1979;9:11–29. doi: 10.1007/BF01531288. PubMed DOI

Hua R, Wei M, Zhang C. The complex genetics in autism spectrum disorders. Sci. China Life Sci. 2015;58:933–945. doi: 10.1007/s11427-015-4893-5. PubMed DOI

Guo H, Wang T, Huidan W, Long M, Coe BP, Li H, et al. Inherited and multiple de novo mutations in autism/developmental delay risk genes suggest a multifactorial model. Mol. Autism. 2018 doi: 10.1186/s13229-018-0247-z. PubMed DOI PMC

Bensaid M, Loe-Mie Y, Lepagnol-Bestel A-M, Han W, Santpere G, Klarić T, et al. Multi-hit autism genomic architecture evidenced from consanguineous families with involvement of FEZF2 and mutations in high-risk genes. Neuroscience. 2018 doi: 10.1101/759480. DOI

Centanni TM, Green JR, Iuzzini-Seigel J, Bartlett CW, Hogan TP. Evidence for the multiple hits genetic theory for inherited language impairment: A case study. Front. Genet. 2015;6:272. doi: 10.3389/fgene.2015.00272. PubMed DOI PMC

Miller LE, Dai YG, Fein DA, Robins DL. Characteristics of toddlers with early versus later diagnosis of autism spectrum disorder. Autism. 2021;25:416–428. doi: 10.1177/1362361320959507. PubMed DOI PMC

Borden MC, Ollendick TH. An examination of the validity of social subtypes in autism. J. Autism Dev. Disord. 1994;24:23–37. doi: 10.1007/BF02172210. PubMed DOI

Castelloe P, Dawson G. Subclassification of children with autism and pervasive developmental disorder: A questionnaire based on Wing’s subgrouping scheme. J. Autism Dev. Disord. 1993;23:229–241. doi: 10.1007/BF01046217. PubMed DOI

Eaves LC, Ho HH, Eaves DM. Subtypes of autism by cluster analysis. J. Autism Dev. Disord. 1994;24:3–22. doi: 10.1007/BF02172209. PubMed DOI

O’Brien SK. The validity and reliability of the Wing Subgroups Questionnaire. J. Autism Dev. Disord. 1996;26:321–335. doi: 10.1007/BF02172477. PubMed DOI

Volkmar FR, Cohen DJ, Bregman JD, Hooks MY, Stevenson JM. An examination of social typologies in autism. J. Am. Acad. Child Adolesc. Psychiatry. 1989;28:82–86. doi: 10.1097/00004583-198901000-00015. PubMed DOI

Duffy FH, Als H. Autism, spectrum or clusters? An EEG coherence study. BMC Neurol. 2019;19:27. doi: 10.1186/s12883-019-1254-1. PubMed DOI PMC

Hrdlicka M, Dudova I, Beranova I, Lisy J, Belsan T, Neuwirth J, et al. Subtypes of autism by cluster analysis based on structural MRI data. EuropChild Adolescent Psych. 2005;14:138–144. doi: 10.1007/s00787-005-0453-z. PubMed DOI

Tan DW, Maybery MT, Gilani SZ, Alvares GA, Mian A, Suter D, et al. A broad autism phenotype expressed in facial morphology. Transl. Psychiatry. 2020;10:1–9. doi: 10.1038/s41398-020-0695-z. PubMed DOI PMC

Aldridge K, George ID, Cole KK, Austin JR, Takahashi TN, Duan Y, et al. Facial phenotypes in subgroups of prepubertal boys with autism spectrum disorders are correlated with clinical phenotypes. Mol. Autism. 2011;2:15. doi: 10.1186/2040-2392-2-15. PubMed DOI PMC

Obafemi-Ajayi T, Miles JH, Takahashi TN, Qi W, Aldridge K, Zhang M, et al. Facial structure analysis separates autism spectrum disorders into meaningful clinical subgroups. J. Autism Dev. Disord. 2015;45:1302–1317. doi: 10.1007/s10803-014-2290-8. PubMed DOI

American Psychiatric Association . Diagnostic and Statistical Manual of Mental Disorders. 5. UK: American Psychiatric Association; 2013.

Palmer RL, Helmholz P, Baynam G. Cliniface: Phenotypic visualisation and analysis using non-rigid registration of 3D facial images. Int. Arch. Photogram. Remote Sens. Spat. Inf. Sci. 2020;XLIII-B2-2020:301–308. doi: 10.5194/isprs-archives-XLIII-B2-2020-301-2020. DOI

3D Systems. Geomagic Wrap 2017. (2017). Available from: https://www.3dsystems.com/

Farkas LG. Anthropometry of the Head and Face. Raven Press; 1994.

R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, Vienna, 2021). Available from: https://www.R-project.org/

The MathWorks, Inc. Matlab version R2022b. (Natick, 2022). Available from: www.mathworks.com

Peyre, G. Toolbox Fast Marching. MATLAB Central File Exchange; (2023). Available from: https://www.mathworks.com/matlabcentral/fileexchange/6110-toolbox-fast-marching

Spearman C. The proof and measurement of association between two things. Am. J. Psychol. 1987;100:441–471. doi: 10.2307/1422689. PubMed DOI

Caliński T, Harabasz J. A dendrite method for cluster analysis. Commun. Stat. 1974;3:1–27.

Rosner B. Percentage points for a generalized ESD many-outlier procedure. Technometrics. 1983;25:165–172. doi: 10.1080/00401706.1983.10487848. DOI

Bonferroni CE. Teoria statistica delle classi e calcolo delle probabilita. Pubblicazioni del R Istituto Superiore di Scienze Economiche e Commericiali di Firenze. 1936;8:3–62.

Kruskal WH, Wallis WA. Use of ranks in one-criterion variance analysis. J. Am. Stat. Assoc. 1952;47:583–621. doi: 10.1080/01621459.1952.10483441. DOI

Student. The probable error of a mean. Biometrika. 1–25 (1908).

Wilcoxon F. Individual comparisons by ranking methods. Biometr. Bull. 1945;1:80–83. doi: 10.2307/3001968. DOI

Armitage, P., Berry, G. & Matthews, J. N. S. Statistical Methods in Medical Research. 4th edn 760–783 (2008).

Levy SE, Pinto-Martin JA, Bradley CB, Chittams J, Johnson SL, Pandey J, et al. Relationship of weight outcomes, co-occurring conditions, and severity of autism spectrum disorder in the study to explore early development. J. Pediatr. 2019;205:202–209. doi: 10.1016/j.jpeds.2018.09.003. PubMed DOI PMC

Curtin C, Anderson SE, Must A, Bandini L. The prevalence of obesity in children with autism: A secondary data analysis using nationally representative data from the National Survey of Children’s Health. BMC Pediatr. 2010;10:11. doi: 10.1186/1471-2431-10-11. PubMed DOI PMC

Curtin C, Jojic M, Bandini LG. Obesity in children with autism spectrum disorders. Harvard Rev. Psychiatry. 2014;22:93. doi: 10.1097/HRP.0000000000000031. PubMed DOI PMC

Baraskewich J, von Ranson KM, McCrimmon A, McMorris CA. Feeding and eating problems in children and adolescents with autism: A scoping review. Autism. 2021;25:1505–1519. doi: 10.1177/1362361321995631. PubMed DOI PMC

Tan DW, Gilani SZ, Maybery MT, Mian A, Hunt A, Walters M, et al. Hypermasculinised facial morphology in boys and girls with Autism Spectrum Disorder and its association with symptomatology. Sci. Rep. 2017;7:9348. doi: 10.1038/s41598-017-09939-y. PubMed DOI PMC

The relationship between facial directional asymmetry, handedness, chewing side preference, and eyedness