Abstract
BACKGROUND: Obesity is a global and severe health problem. Due to genetic heterogeneity, the identification of genetic defects in patients with obesity can be time consuming and costly. Therefore, we developed a custom diagnostic targeted next-generation sequencing (NGS)-based analysis to simultaneously identify mutations in 52 obesity-related genes. The aim of this study was to assess the diagnostic yield of this approach in patients with suspected genetic obesity.
METHODS: DNA of 1230 patients with obesity (median BMI adults 43.6 kg/m2; median body mass index-SD children +3.4 SD) was analysed in the genome diagnostics section of the Department of Genetics of the UMC Utrecht (The Netherlands) by targeted analysis of 52 obesity-related genes.
RESULTS: In 48 patients pathogenic mutations confirming the clinical diagnosis were detected. The majority of these were observed in the MC4R gene (18/48). In an additional 67 patients a probable pathogenic mutation was identified, necessitating further analysis to confirm the clinical relevance.
CONCLUSIONS: NGS-based gene panel analysis in patients with obesity led to a definitive diagnosis of a genetic obesity disorder in 3.9% of obese probands, and a possible diagnosis in an additional 5.4% of obese probands. The highest yield was achieved in a selected paediatric subgroup, establishing a definitive diagnosis in 12 out of 164 children with severe early onset obesity (7.3%). These findings give a realistic insight in the diagnostic yield of genetic testing for patients with obesity and could help these patients to receive (future) personalised treatment.
| Original language | English |
|---|---|
| Pages (from-to) | 578-586 |
| Number of pages | 9 |
| Journal | Journal of Medical Genetics |
| Volume | 55 |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - Sep 2018 |
Cite this
}
Genetic obesity : next-generation sequencing results of 1230 patients with obesity. / Kleinendorst, Lotte; Massink, Maarten P G; Cooiman, Mellody I; Savas, Mesut; van der Baan-Slootweg, Olga H; Roelants, Roosje J; Janssen, Ignace C M; Meijers-Heijboer, Hanne J; Knoers, Nine V A M; Ploos van Amstel, Hans Kristian; van Rossum, Elisabeth F C; van den Akker, Erica L T; van Haaften, Gijs; van der Zwaag, Bert; van Haelst, Mieke M.
In: Journal of Medical Genetics, Vol. 55, No. 9, 09.2018, p. 578-586.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - Genetic obesity
T2 - next-generation sequencing results of 1230 patients with obesity
AU - Kleinendorst, Lotte
AU - Massink, Maarten P G
AU - Cooiman, Mellody I
AU - Savas, Mesut
AU - van der Baan-Slootweg, Olga H
AU - Roelants, Roosje J
AU - Janssen, Ignace C M
AU - Meijers-Heijboer, Hanne J
AU - Knoers, Nine V A M
AU - Ploos van Amstel, Hans Kristian
AU - van Rossum, Elisabeth F C
AU - van den Akker, Erica L T
AU - van Haaften, Gijs
AU - van der Zwaag, Bert
AU - van Haelst, Mieke M
N1 - © Author(s) (or their employer(s)) 2018. No commercial re-use. See rights and permissions. Published by BMJ.
PY - 2018/9
Y1 - 2018/9
N2 - BACKGROUND: Obesity is a global and severe health problem. Due to genetic heterogeneity, the identification of genetic defects in patients with obesity can be time consuming and costly. Therefore, we developed a custom diagnostic targeted next-generation sequencing (NGS)-based analysis to simultaneously identify mutations in 52 obesity-related genes. The aim of this study was to assess the diagnostic yield of this approach in patients with suspected genetic obesity.METHODS: DNA of 1230 patients with obesity (median BMI adults 43.6 kg/m2; median body mass index-SD children +3.4 SD) was analysed in the genome diagnostics section of the Department of Genetics of the UMC Utrecht (The Netherlands) by targeted analysis of 52 obesity-related genes.RESULTS: In 48 patients pathogenic mutations confirming the clinical diagnosis were detected. The majority of these were observed in the MC4R gene (18/48). In an additional 67 patients a probable pathogenic mutation was identified, necessitating further analysis to confirm the clinical relevance.CONCLUSIONS: NGS-based gene panel analysis in patients with obesity led to a definitive diagnosis of a genetic obesity disorder in 3.9% of obese probands, and a possible diagnosis in an additional 5.4% of obese probands. The highest yield was achieved in a selected paediatric subgroup, establishing a definitive diagnosis in 12 out of 164 children with severe early onset obesity (7.3%). These findings give a realistic insight in the diagnostic yield of genetic testing for patients with obesity and could help these patients to receive (future) personalised treatment.
AB - BACKGROUND: Obesity is a global and severe health problem. Due to genetic heterogeneity, the identification of genetic defects in patients with obesity can be time consuming and costly. Therefore, we developed a custom diagnostic targeted next-generation sequencing (NGS)-based analysis to simultaneously identify mutations in 52 obesity-related genes. The aim of this study was to assess the diagnostic yield of this approach in patients with suspected genetic obesity.METHODS: DNA of 1230 patients with obesity (median BMI adults 43.6 kg/m2; median body mass index-SD children +3.4 SD) was analysed in the genome diagnostics section of the Department of Genetics of the UMC Utrecht (The Netherlands) by targeted analysis of 52 obesity-related genes.RESULTS: In 48 patients pathogenic mutations confirming the clinical diagnosis were detected. The majority of these were observed in the MC4R gene (18/48). In an additional 67 patients a probable pathogenic mutation was identified, necessitating further analysis to confirm the clinical relevance.CONCLUSIONS: NGS-based gene panel analysis in patients with obesity led to a definitive diagnosis of a genetic obesity disorder in 3.9% of obese probands, and a possible diagnosis in an additional 5.4% of obese probands. The highest yield was achieved in a selected paediatric subgroup, establishing a definitive diagnosis in 12 out of 164 children with severe early onset obesity (7.3%). These findings give a realistic insight in the diagnostic yield of genetic testing for patients with obesity and could help these patients to receive (future) personalised treatment.
U2 - 10.1136/jmedgenet-2018-105315
DO - 10.1136/jmedgenet-2018-105315
M3 - Article
VL - 55
SP - 578
EP - 586
JO - Journal of Medical Genetics
JF - Journal of Medical Genetics
SN - 0022-2593
IS - 9
ER -