Letter to the Editor: “A Genome-Wide Pharmacogenetic Study of Growth Hormone Responsiveness”

2020 ◽  
Vol 106 (1) ◽  
pp. e397-e398
Author(s):  
Pierre Bougnères
2020 ◽  
Vol 106 (1) ◽  
pp. e409-e410
Author(s):  
Joel N Hirschhorn ◽  
Andrew Dauber ◽  
Laura Audi ◽  
Sailaja Vedantam ◽  
Michael B Ranke ◽  
...  

Author(s):  
Dauber A ◽  
Meng Y ◽  
Audi L ◽  
Vedantam S ◽  
Weaver B ◽  
...  

2020 ◽  
Vol 105 (10) ◽  
pp. 3203-3214 ◽  
Author(s):  
Andrew Dauber ◽  
Yan Meng ◽  
Laura Audi ◽  
Sailaja Vedantam ◽  
Benjamin Weaver ◽  
...  

Abstract Context Individual patients vary in their response to growth hormone (GH). No large-scale genome-wide studies have looked for genetic predictors of GH responsiveness. Objective To identify genetic variants associated with GH responsiveness. Design Genome-wide association study (GWAS). Setting Cohorts from multiple academic centers and a clinical trial. Patients A total of 614 individuals from 5 short stature cohorts receiving GH: 297 with idiopathic short stature, 276 with isolated GH deficiency, and 65 born small for gestational age. Intervention Association of more than 2 million variants was tested. Main Outcome Measures Primary analysis: individual single nucleotide polymorphism (SNP) association with first-year change in height standard deviation scores. Secondary analyses: SNP associations in clinical subgroups adjusted for clinical variables; association of polygenic score calculated from 697 genome-wide significant height SNPs with GH responsiveness. Results No common variant associations reached genome-wide significance in the primary analysis. The strongest suggestive signals were found near the B4GALT4 and TBCE genes. After meta-analysis including replication data, signals at several loci reached or retained genome-wide significance in secondary analyses, including variants near ST3GAL6. There was no significant association with variants previously reported to be associated with GH response nor with a polygenic predicted height score. Conclusions We performed the largest GWAS of GH responsiveness to date. We identified 2 loci with a suggestive effect on GH responsiveness in our primary analysis and several genome-wide significant associations in secondary analyses that require further replication. Our results are consistent with a polygenic component to GH responsiveness, likely distinct from the genetic regulators of adult height.


2014 ◽  
Vol 226 (03) ◽  
Author(s):  
F Ponthan ◽  
D Pal ◽  
J Vormoor ◽  
O Heidenreich
Keyword(s):  

2007 ◽  
Vol 30 (4) ◽  
pp. 86
Author(s):  
M. Lanktree ◽  
J. Robinson ◽  
J. Creider ◽  
H. Cao ◽  
D. Carter ◽  
...  

Background: In Dunnigan-type familial partial lipodystrophy (FPLD) patients are born with normal fat distribution, but subcutaneous fat from extremities and gluteal regions are lost during puberty. The abnormal fat distribution leads to the development of metabolic syndrome (MetS), a cluster of phenotypes including hyperglycemia, dyslipidemia, hypertension, and visceral obesity. The study of FPLD as a monogenic model of MetS may uncover genetic risk factors of the common MetS which affects ~30% of adult North Americans. Two molecular forms of FPLD have been identified including FPLD2, resulting from heterozygous mutations in the LMNA gene, and FPLD3, resulting from both heterozygous dominant negative and haploinsufficiency mutations in the PPARG gene. However, many patients with clinically diagnosed FPLD have no mutation in either LMNA or PPARG, suggesting the involvement of additional genes in FPLD etiology. Methods: Here, we report the results of an Affymetrix 10K GeneChip microarray genome-wide linkage analysis study of a German kindred displaying the FPLD phenotype and no known lipodystrophy-causing mutations. Results: The investigation identified three chromosomal loci, namely 1q, 3p, and 9q, with non-parametric logarithm of odds (NPL) scores >2.7. While not meeting the criteria for genome-wide significance, it is interesting to note that the 1q and 3p peaks contain the LMNA and PPARG genes respectively. Conclusions: Three possible conclusions can be drawn from these results: 1) the peaks identified are spurious findings, 2) additional genes physically close to LMNA, PPARG, or within 9q, are involved in FPLD etiology, or 3) alternative disease causing mechanisms not identified by standard exon sequencing approaches, such as promoter mutations, alternative splicing, or epigenetics, are also responsible for FPLD.


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