Robert L. Hanson
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Research Interests
Robert L. Hanson has a total of 105 co-authors. Here are the top co-authors by number of shared publications:
- Adan Valladares-Salgado
Unidad de Investigación Médica en Bioquímica, Hospital de Especialidades, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social
1 shared publication - Adnan Custovic
National Heart and Lung Institute, Imperial College London London UK
1 shared publication - Akram Alyass
Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
1 shared publication - Alessandra Chesi
Center for Spatial and Functional Genomics, Children’s Hospital of Pennsylvania, Philadelphia, USA
1 shared publication - Amélie Bonnefond
Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, Lille University Hospital, Lille, France
1 shared publication André G Uitterlinden
Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
1 shared publication
Latest Publications
- 18 May 2020
- Published by Springer Nature in Diabetologia
- Vol. 63 (9) , 1753-1763
Weight tracking in childhood and adolescence and type 2 diabetes risk
Aims/hypothesis The aim of this work was to examine the associations of average weight and weight velocity in three growth periods from birth through adolescence with type 2 diabetes incidence. Methods Child participants were selected from a 43 year longitudinal study of American Indians to represent three growth periods: pre-adolescence (birth to ~8 years); early adolescence (~8 to ~13 years); and late adolescence (~13 to ~18 years). Age-, sex- and height-standardised weight z score mean and weight z score velocity (change/year) were computed for each period. Participants were followed for up to 25 years from the end of each growth period until they developed diabetes. Associations of weight z score mean or weight z score velocity with diabetes incidence were determined with sex-, birth date- and maternal diabetes-adjusted Poisson regression models. Results Among 2100 participants representing the pre-adolescence growth period, 1558 representing the early adolescence period and 1418 representing the late adolescence period, there were 290, 315 and 380 incident diabetes cases, respectively. During the first 10 years of follow-up, the diabetes incidence rate ratio (95% CI) was 1.72 (1.40, 2.11)/SD of log10 weight z score mean in pre-adolescence, 2.09 (1.68, 2.60)/SD of log10 weight z score mean in early adolescence and 1.85 (1.58, 2.17)/SD of log10 weight z score mean in late adolescence. The diabetes incidence rate ratio (95% CI) was 1.79 (1.49, 2.17)/SD of log10 weight z score velocity in pre-adolescence, 1.13 (0.91, 1.41)/SD of log10 weight z score velocity in early adolescence and 1.29 (1.09, 1.51)/SD of log10 weight z score velocity in late adolescence. There were strong correlations in the weight z score means and weak correlations in the weight z score velocities between successive periods. Conclusions/interpretation Higher weight and accelerated weight gain in all growth periods associate with increased type 2 diabetes risk. Importantly, higher weight and greater weight velocity during pre-adolescence jointly associate with the highest type 2 diabetes risk. Graphical abstract
- 18 May 2020
- Published by Springer Nature in Diabetologia
- Vol. 63 (9) , 1753-1763
Weight tracking in childhood and adolescence and type 2 diabetes risk
Aims/hypothesis The aim of this work was to examine the associations of average weight and weight velocity in three growth periods from birth through adolescence with type 2 diabetes incidence. Methods Child participants were selected from a 43 year longitudinal study of American Indians to represent three growth periods: pre-adolescence (birth to ~8 years); early adolescence (~8 to ~13 years); and late adolescence (~13 to ~18 years). Age-, sex- and height-standardised weight z score mean and weight z score velocity (change/year) were computed for each period. Participants were followed for up to 25 years from the end of each growth period until they developed diabetes. Associations of weight z score mean or weight z score velocity with diabetes incidence were determined with sex-, birth date- and maternal diabetes-adjusted Poisson regression models. Results Among 2100 participants representing the pre-adolescence growth period, 1558 representing the early adolescence period and 1418 representing the late adolescence period, there were 290, 315 and 380 incident diabetes cases, respectively. During the first 10 years of follow-up, the diabetes incidence rate ratio (95% CI) was 1.72 (1.40, 2.11)/SD of log10 weight z score mean in pre-adolescence, 2.09 (1.68, 2.60)/SD of log10 weight z score mean in early adolescence and 1.85 (1.58, 2.17)/SD of log10 weight z score mean in late adolescence. The diabetes incidence rate ratio (95% CI) was 1.79 (1.49, 2.17)/SD of log10 weight z score velocity in pre-adolescence, 1.13 (0.91, 1.41)/SD of log10 weight z score velocity in early adolescence and 1.29 (1.09, 1.51)/SD of log10 weight z score velocity in late adolescence. There were strong correlations in the weight z score means and weak correlations in the weight z score velocities between successive periods. Conclusions/interpretation Higher weight and accelerated weight gain in all growth periods associate with increased type 2 diabetes risk. Importantly, higher weight and greater weight velocity during pre-adolescence jointly associate with the highest type 2 diabetes risk. Graphical abstract
- Open Access
- 7 June 2019
- Published by Oxford University Press (OUP) in Human Molecular Genetics
- Vol. 28 (19) , 3327-3338
A trans-ancestral meta-analysis of genome-wide association studies reveals loci associated with childhood obesity
Although hundreds of genome-wide association studies-implicated loci have been reported for adult obesity-related traits, less is known about the genetics specific for early-onset obesity and with only a few studies conducted in non-European populations to date. Searching for additional genetic variants associated with childhood obesity, we performed a trans-ancestral meta-analysis of 30 studies consisting of up to 13 005 cases (≥95th percentile of body mass index (BMI) achieved 2–18 years old) and 15 599 controls (consistently METTL15). The variant was nominally associated with only the European subgroup analysis but had a consistent direction of effect in other ethnicities. We then utilized trans-ancestral Bayesian analysis to narrow down the location of the probable causal variant at each genome-wide significant signal. Of all the fine-mapped loci, we were able to narrow down the causative variant at four known loci to fewer than 10 single nucleotide polymorphisms (SNPs) (FAIM2, GNPDA2, MC4R and SEC16B loci). In conclusion, an ethnically diverse setting has enabled us to both identify an additional pediatric obesity locus and further fine-map existing loci.
- 7 June 2019
- Published by Oxford University Press (OUP) in Human Molecular Genetics
- Vol. 28 (19) , 3327-3338
Open AccessA trans-ancestral meta-analysis of genome-wide association studies reveals loci associated with childhood obesity
Although hundreds of genome-wide association studies-implicated loci have been reported for adult obesity-related traits, less is known about the genetics specific for early-onset obesity and with only a few studies conducted in non-European populations to date. Searching for additional genetic variants associated with childhood obesity, we performed a trans-ancestral meta-analysis of 30 studies consisting of up to 13 005 cases (≥95th percentile of body mass index (BMI) achieved 2–18 years old) and 15 599 controls (consistently METTL15). The variant was nominally associated with only the European subgroup analysis but had a consistent direction of effect in other ethnicities. We then utilized trans-ancestral Bayesian analysis to narrow down the location of the probable causal variant at each genome-wide significant signal. Of all the fine-mapped loci, we were able to narrow down the causative variant at four known loci to fewer than 10 single nucleotide polymorphisms (SNPs) (FAIM2, GNPDA2, MC4R and SEC16B loci). In conclusion, an ethnically diverse setting has enabled us to both identify an additional pediatric obesity locus and further fine-map existing loci.