Congenital hypopituitarism in two brothers with a duplication of the ‘acrogigantism gene’ GPR101: clinical findings and review of the literature

Purpose: Congenital hypopituitarism (CH) can cause significant morbidity or even mortality. In the majority of patients, the etiology of CH is unknown. Understanding the etiology of CH is important for anticipation of clinical problems and for genetic counselling. Our previous studies showed that only a small proportion of cases have mutations in the known ‘CH genes’. In the current project, we present the results of SNP array based copy number variant analysis in a family with unexplained congenital hypopituitarism. Methods: DNA samples of two affected brothers with idiopathic CH and their mother were simultaneously analyzed by SNP arrays for copy number variant analysis and Whole Exome Sequencing (WES) for mutation screening. DNA of the father was not available. Results: We found a 6 Mb duplication including GPR101 and SOX3 on the X-chromosome (Xq26.2-q27.1) in the two siblings and their mother, leading to 2 copies of this region in the affected boys and 3 copies in the mother. Duplications of GPR101 are associated with X-linked acrogigantism (the phenotypic ‘opposite’ of the affected brothers), whereas alterations in SOX3 are associated with X-linked hypopituitarism. Conclusion: In our patients with hypopituitarism we found a 6 Mb duplication which includes GPR101, a gene associated with X- linked gigantism, and SOX3, a gene involved in early pituitary organogenesis that is associated with variable degrees of hypopituitarism. Our findings show that in duplications containing both GPR101 and SOX3, the growth hormone deficiency phenotype is dominant. This suggests that, if GPR101 is duplicated, it might not be expressed phenotypically when early patterning of the embryonic pituitary is affected due to SOX3 duplication. These results, together with the review of the literature, shed a new light on the role of GPR101 and SOX3 in pituitary function

Whole Exome Sequencing in Two Southeast Asian Families With Atypical Femur Fractures

Atypical femur fractures (AFFs) are rare complications of anti-resorptive therapy. Devastating to the affected individual, they pose a public health concern because of reduced uptake of an effective treatment for osteoporosis due to patient concern. The risk of AFF is increased sixfold to sevenfold in patients of Asian ethnicity compared with Europeans. Genetic factors may underlie the AFF phenotype. Given the rarity of AFFs, studying familial AFF cases is valuable in providing insights into any genetic predisposition. We present two Singaporean families, one comprising a mother (1-a) and a daughter (1-b), and the other comprising two sisters (2-a and 2-b). All four cases presented with bisphosphonate-associated AFF. Whole-exome sequencing (WES) was performed on 1-b, 2-a, and 2-b. DNA for 1-a was not available. Variants were examined using a candidate gene approach comprising a list of genes previously associated with AFF in the literature, as well as using unbiased filtering based on dominant and/or recessive inheritance patterns. Using a candidate gene approach, rare variants shared between all three cases were not identified. A rare variant in TMEM25, shared by the two sisters (2-a and 2-b), was identified. A rare heterozygous PLOD2 variant was present in the daughter case with AFF (1-b), but not in the sisters. A list of potential genetic variants for AFF was identified after variant filtering and annotation analysis of the two sisters (2-a and 2-b), including a Gly35Arg variant in TRAF4, a gene required for normal skeletal development. Although the findings from this genetic analysis are inconclusive, a familial aggregation of AFFs is suggestive of a genetic component in AFF pathogenesis. We provide a comprehensive list of rare variants identified in these AFF familial cases to aid future genetic studies

A comparison of genotyping arrays

Array technology to genotype single-nucleotide variants (SNVs) is widely used in genome-wide association studies (GWAS), clinical diagnostics, and linkage studies. Arrays have undergone a tremendous growth in both number and content over recent years making a comprehensive comparison all the more important. We have compared 28 genotyping arrays on their overall content, genome-wide coverage, imputation quality, presence of known GWAS loci, mtDNA variants and clinically relevant genes (i.e., American College of Medical Genetics (ACMG) actionable genes, pharmacogenetic genes, human leukocyte antigen (HLA) genes and SNV density). Our comparison shows that genome-wide coverage is highly correlated with the number of SNVs on the array but does not correlate with imputation quality, which is the main determinant of GWAS usability. Average imputation quality for all tested arrays was similar for European and African populations, indicating that this is not a good criterion for choosing a genotyping array. Rather, the additional content on the array, such as pharmacogenetics or HLA variants, should be the deciding factor. As the research question of a study will in large part determine which class of genes are of interest, there is not just one perfect array for all different research questions. This study can thus help as a guideline to determine which array best suits a study’s requirements

Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences

Humans vary substantially in their willingness to take risks. In a combined sample of over 1 million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. Across all GWAS, we identified hundreds of associated loci, including 99 loci associated with general risk tolerance. We report evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is genetically correlated (∣r̂ g∣ ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near SNPs associated with general risk tolerance are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We found no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.</p