Down syndrome in diverse populations

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dc.contributor.authorKruszka, P.
dc.contributor.authorPorras, A.R.
dc.contributor.authorSobering, A.K.
dc.contributor.authorIkolo, F.A.
dc.contributor.authorLa Qua, S.
dc.contributor.authorShotelersuk, V.
dc.contributor.authorChung, B.H.
dc.contributor.authorMok, G.T.
dc.contributor.authorUwineza, A.
dc.contributor.authorMutesa, L.
dc.contributor.authorMoresco, A.
dc.contributor.authorObregon, M.G.
dc.contributor.authorSokunbi, O.J.
dc.contributor.authorKalu, N.
dc.contributor.authorJoseph, D.A.
dc.contributor.authorIkebudu, D.
dc.contributor.authorUgwu, C.E.
dc.contributor.authorOkoromah, C.A.
dc.contributor.authorAddissie, Y.A.
dc.contributor.authorPardo, K.L.
dc.contributor.authorBrough, J.J.
dc.contributor.authorLee, N.C.
dc.contributor.authorGirisha, K.M.
dc.contributor.authorPatil, S.J.
dc.contributor.authorNg, I.S.
dc.contributor.authorMin, B.C.
dc.contributor.authorJamuar, S.S.
dc.contributor.authorTibrewal, S.
dc.contributor.authorWallang, B.
dc.contributor.authorGanesh, S.
dc.contributor.authorSirisena, N.D.
dc.contributor.authorDissanayake, V.H.
dc.contributor.authorPaththinige, C.S.
dc.contributor.authorPrabodha, L.B.
dc.contributor.authorRichieri-Costa, A.
dc.contributor.authorMuthukumarasamy, P.
dc.contributor.authorThong, M.K.
dc.contributor.authorJones, K.L.
dc.contributor.authorAbdul-Rahman, O.A.
dc.contributor.authorEkure, E.N.
dc.contributor.authorAdeyemo, A.A.
dc.contributor.authorSummar, M.
dc.contributor.authorLinguraru, M.G.
dc.contributor.authorMuenke, M.
dc.date.accessioned2019-11-12T11:24:09Z
dc.date.available2019-11-12T11:24:09Z
dc.date.issued2017-01
dc.descriptionStaff publicationsen_US
dc.description.abstractDown syndrome is the most common cause of cognitive impairment and presents clinically with universally recognizable signs and symptoms. In this study, we focus on exam findings and digital facial analysis technology in individuals with Down syndrome in diverse populations. Photos and clinical information were collected on 65 individuals from 13 countries, 56.9% were male and the average age was 6.6 years (range 1 month to 26 years; SD = 6.6 years). Subjective findings showed that clinical features were different across ethnicities (Africans, Asians, and Latin Americans), including brachycephaly, ear anomalies, clinodactyly, sandal gap, and abundant neck skin, which were all significantly less frequent in Africans (P < 0.001, P < 0.001, P < 0.001, P < 0.05, and P < 0.05, respectively). Evaluation using a digital facial analysis technology of a larger diverse cohort of newborns to adults (n = 129 cases; n = 132 controls) was able to diagnose Down syndrome with a sensitivity of 0.961, specificity of 0.924, and accuracy of 0.943. Only the angles at medial canthus and ala of the nose were common significant findings amongst different ethnicities (Caucasians, Africans, and Asians) when compared to ethnically matched controls. The Asian group had the least number of significant digital facial biometrics at 4, compared to Caucasians at 8 and Africans at 7. In conclusion, this study displays the wide variety of findings across different geographic populations in Down syndrome and demonstrates the accuracy and promise of digital facial analysis technology in the diagnosis of Down syndrome internationally.en_US
dc.description.sponsorshipDivision of Intramural Research at the National Human Genome Research Institute,NIH; Grant sponsor: Government of Abu Dhabi to the Children’s National Health System, Washington DC.en_US
dc.identifier.citationKruszka P, Porras AR, Sobering AK, Ikolo FA, La Qua S, Shotelersuk V, Chung BH, Mok GT, Uwineza A, Mutesa L, Moresco A, Obregon MG, Sokunbi OJ, Kalu N, Joseph DA, Ikebudu D, Ugwu CE, Okoromah CA, Addissie YA, Pardo KL, Brough JJ, Lee NC, Girisha KM, Patil SJ, Ng IS, Min BC, Jamuar SS, Tibrewal S, Wallang B, Ganesh S, Sirisena ND, Dissanayake VH, Paththinige CS, Prabodha LB, Richieri-Costa A, Muthukumarasamy P, Thong MK, Jones KL, Abdul-Rahman OA, Ekure EN, Adeyemo AA, Summar M, Linguraru MG, Muenke M. Down syndrome in diverse populations. Am J Med Genet A. 2017 Jan;173(1):42-53.en_US
dc.identifier.otherdoi: 10.1002/ajmg.a.38043
dc.identifier.urihttps://ir.unilag.edu.ng/handle/123456789/6819
dc.language.isoenen_US
dc.publisherWiley Periodicals, Inc.en_US
dc.subjectdiverse populationsen_US
dc.subjectdown syndromeen_US
dc.subjectfacial analysis technologyen_US
dc.subjecttrisomy 21en_US
dc.subjectResearch Subject Categories::MEDICINEen_US
dc.titleDown syndrome in diverse populationsen_US
dc.typeArticleen_US
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