Down syndrome in diverse populations

Paul Kruszka, Antonio R. Porras, Andrew K. Sobering, Felicia A. Ikolo, Samantha La Qua, Vorasuk Shotelersuk, Brian H.Y. Chung, Gary T.K. Mok, Annette Uwineza, Leon Mutesa, Angélica Moresco, María Gabriela Obregon, Ogochukwu Jidechukwu Sokunbi, Nnenna Kalu, Daniel Akinsanya Joseph, Desmond Ikebudu, Christopher Emeka Ugwu, Christy A.N. Okoromah, Yonit A. Addissie, Katherine L. PardoJ. Joseph Brough, Ni Chung Lee, Katta M. Girisha, Siddaramappa Jagdish Patil, Ivy S.L. Ng, Breana Cham Wen Min, Saumya S. Jamuar, Shailja Tibrewal, Batriti Wallang, Suma Ganesh, Nirmala D. Sirisena, Vajira H.W. Dissanayake, C. Sampath Paththinige, L. B.Lahiru Prabodha, Antonio Richieri-Costa, Premala Muthukumarasamy, Meow Keong Thong, Kelly L. Jones, Omar A. Abdul-Rahman, Ekanem Nsikak Ekure, Adebowale A. Adeyemo, Marshall Summar, Marius George Linguraru, Maximilian Muenke

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

Down 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.

Original languageEnglish
Pages (from-to)42-53
Number of pages12
JournalAmerican Journal of Medical Genetics, Part A
Volume173
Issue number1
DOIs
Publication statusPublished - 01-01-2017

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Down Syndrome
Population
Technology
Craniosynostoses
Lacrimal Apparatus
Asian Americans
Nose
Signs and Symptoms
Ear
Neck
Newborn Infant
Sensitivity and Specificity
Skin

All Science Journal Classification (ASJC) codes

  • Genetics
  • Genetics(clinical)

Cite this

Kruszka, P., Porras, A. R., Sobering, A. K., Ikolo, F. A., La Qua, S., Shotelersuk, V., ... Muenke, M. (2017). Down syndrome in diverse populations. American Journal of Medical Genetics, Part A, 173(1), 42-53. https://doi.org/10.1002/ajmg.a.38043
Kruszka, Paul ; Porras, Antonio R. ; Sobering, Andrew K. ; Ikolo, Felicia A. ; La Qua, Samantha ; Shotelersuk, Vorasuk ; Chung, Brian H.Y. ; Mok, Gary T.K. ; Uwineza, Annette ; Mutesa, Leon ; Moresco, Angélica ; Obregon, María Gabriela ; Sokunbi, Ogochukwu Jidechukwu ; Kalu, Nnenna ; Joseph, Daniel Akinsanya ; Ikebudu, Desmond ; Ugwu, Christopher Emeka ; Okoromah, Christy A.N. ; Addissie, Yonit A. ; Pardo, Katherine L. ; Brough, J. Joseph ; Lee, Ni Chung ; Girisha, Katta M. ; Patil, Siddaramappa Jagdish ; Ng, Ivy S.L. ; Min, Breana Cham Wen ; Jamuar, Saumya S. ; Tibrewal, Shailja ; Wallang, Batriti ; Ganesh, Suma ; Sirisena, Nirmala D. ; Dissanayake, Vajira H.W. ; Paththinige, C. Sampath ; Prabodha, L. B.Lahiru ; Richieri-Costa, Antonio ; Muthukumarasamy, Premala ; Thong, Meow Keong ; Jones, Kelly L. ; Abdul-Rahman, Omar A. ; Ekure, Ekanem Nsikak ; Adeyemo, Adebowale A. ; Summar, Marshall ; Linguraru, Marius George ; Muenke, Maximilian. / Down syndrome in diverse populations. In: American Journal of Medical Genetics, Part A. 2017 ; Vol. 173, No. 1. pp. 42-53.
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Kruszka, P, Porras, AR, Sobering, AK, Ikolo, FA, La Qua, S, Shotelersuk, V, Chung, BHY, Mok, GTK, Uwineza, A, Mutesa, L, Moresco, A, Obregon, MG, Sokunbi, OJ, Kalu, N, Joseph, DA, Ikebudu, D, Ugwu, CE, Okoromah, CAN, Addissie, YA, Pardo, KL, Brough, JJ, Lee, NC, Girisha, KM, Patil, SJ, Ng, ISL, Min, BCW, Jamuar, SS, Tibrewal, S, Wallang, B, Ganesh, S, Sirisena, ND, Dissanayake, VHW, Paththinige, CS, Prabodha, LBL, Richieri-Costa, A, Muthukumarasamy, P, Thong, MK, Jones, KL, Abdul-Rahman, OA, Ekure, EN, Adeyemo, AA, Summar, M, Linguraru, MG & Muenke, M 2017, 'Down syndrome in diverse populations', American Journal of Medical Genetics, Part A, vol. 173, no. 1, pp. 42-53. https://doi.org/10.1002/ajmg.a.38043

Down syndrome in diverse populations. / Kruszka, Paul; Porras, Antonio R.; Sobering, Andrew K.; Ikolo, Felicia A.; La Qua, Samantha; Shotelersuk, Vorasuk; Chung, Brian H.Y.; Mok, Gary T.K.; Uwineza, Annette; Mutesa, Leon; Moresco, Angélica; Obregon, María Gabriela; Sokunbi, Ogochukwu Jidechukwu; Kalu, Nnenna; Joseph, Daniel Akinsanya; Ikebudu, Desmond; Ugwu, Christopher Emeka; Okoromah, Christy A.N.; Addissie, Yonit A.; Pardo, Katherine L.; Brough, J. Joseph; Lee, Ni Chung; Girisha, Katta M.; Patil, Siddaramappa Jagdish; Ng, Ivy S.L.; Min, Breana Cham Wen; Jamuar, Saumya S.; Tibrewal, Shailja; Wallang, Batriti; Ganesh, Suma; Sirisena, Nirmala D.; Dissanayake, Vajira H.W.; Paththinige, C. Sampath; Prabodha, L. B.Lahiru; Richieri-Costa, Antonio; Muthukumarasamy, Premala; Thong, Meow Keong; Jones, Kelly L.; Abdul-Rahman, Omar A.; Ekure, Ekanem Nsikak; Adeyemo, Adebowale A.; Summar, Marshall; Linguraru, Marius George; Muenke, Maximilian.

In: American Journal of Medical Genetics, Part A, Vol. 173, No. 1, 01.01.2017, p. 42-53.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Down syndrome in diverse populations

AU - Kruszka, Paul

AU - Porras, Antonio R.

AU - Sobering, Andrew K.

AU - Ikolo, Felicia A.

AU - La Qua, Samantha

AU - Shotelersuk, Vorasuk

AU - Chung, Brian H.Y.

AU - Mok, Gary T.K.

AU - Uwineza, Annette

AU - Mutesa, Leon

AU - Moresco, Angélica

AU - Obregon, María Gabriela

AU - Sokunbi, Ogochukwu Jidechukwu

AU - Kalu, Nnenna

AU - Joseph, Daniel Akinsanya

AU - Ikebudu, Desmond

AU - Ugwu, Christopher Emeka

AU - Okoromah, Christy A.N.

AU - Addissie, Yonit A.

AU - Pardo, Katherine L.

AU - Brough, J. Joseph

AU - Lee, Ni Chung

AU - Girisha, Katta M.

AU - Patil, Siddaramappa Jagdish

AU - Ng, Ivy S.L.

AU - Min, Breana Cham Wen

AU - Jamuar, Saumya S.

AU - Tibrewal, Shailja

AU - Wallang, Batriti

AU - Ganesh, Suma

AU - Sirisena, Nirmala D.

AU - Dissanayake, Vajira H.W.

AU - Paththinige, C. Sampath

AU - Prabodha, L. B.Lahiru

AU - Richieri-Costa, Antonio

AU - Muthukumarasamy, Premala

AU - Thong, Meow Keong

AU - Jones, Kelly L.

AU - Abdul-Rahman, Omar A.

AU - Ekure, Ekanem Nsikak

AU - Adeyemo, Adebowale A.

AU - Summar, Marshall

AU - Linguraru, Marius George

AU - Muenke, Maximilian

PY - 2017/1/1

Y1 - 2017/1/1

N2 - Down 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.

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Kruszka P, Porras AR, Sobering AK, Ikolo FA, La Qua S, Shotelersuk V et al. Down syndrome in diverse populations. American Journal of Medical Genetics, Part A. 2017 Jan 1;173(1):42-53. https://doi.org/10.1002/ajmg.a.38043