Ligase IV syndrome is a rare differential diagnosis for Nijmegen breakage syndrome owing to a shared predisposition to lympho-reticular malignancies, significant microcephaly, and radiation hypersensitivity. Only 16 cases with mutations in LIG4 have been described to date with phenotypes varying from malignancy in developmentally normal individuals, to severe combined immunodeficiency and early mortality. Here, we report the identification of biallelic truncating LIG4 mutations in 11 patients with microcephalic primordial dwarfism presenting with restricted prenatal growth and extreme postnatal global growth failure (average OFC -10.1 s.d., height -5.1 s.d.). Subsequently, most patients developed thrombocytopenia and leucopenia later in childhood and many were found to have previously unrecognized immunodeficiency following molecular diagnosis. None have yet developed malignancy, though all patients tested had cellular radiosensitivity. A genotype-phenotype correlation was also noted with position of truncating mutations corresponding to disease severity. This work extends the phenotypic spectrum associated with LIG4 mutations, establishing that extreme growth retardation with microcephaly is a common presentation of bilallelic truncating mutations. Such growth failure is therefore sufficient to consider a diagnosis of LIG4 deficiency and early recognition of such cases is important as bone marrow failure, immunodeficiency, and sometimes malignancy are long term sequelae of this disorder.
Knowledge of genes influencing longitudinal patterns may offer information about predicting disease progression. We developed a systematic procedure for testing association between SNP genotypes and longitudinal phenotypes. We evaluated false positive rates and statistical power to localize genes for disease progression. We used genome-wide SNP data from the Framingham Heart Study. With longitudinal data from two real studies unrelated to Framingham, we estimated three trajectory curves from each study. We performed simulations by randomly selecting 500 individuals. In each simulation replicate, we assigned each individual to one of the three trajectory groups based on the underlying hypothesis (null or alternative), and generated corresponding longitudinal data. Individual Bayesian posterior probabilities (BPPs) for belonging to a specific trajectory curve were estimated. These BPPs were treated as a quantitative trait and tested (using the Wald test) for genome-wide association. Empirical false positive rates and power were calculated. Our method maintained the expected false positive rate for all simulation models. Also, our method achieved high empirical power for most simulations. Our work presents a method for disease progression gene mapping. This method is potentially clinically significant as it may allow doctors to predict disease progression based on genotype and determine treatment accordingly.
Adolescent idiopathic scoliosis (AIS) is an unexplained and common spinal deformity seen in otherwise healthy children. Its pathophysiology is poorly understood despite intensive investigation. Although genetic underpinnings are clear, replicated susceptibility loci that could provide insight into etiology have not been forthcoming. To address these issues, we performed genome-wide association studies (GWAS) of ?327 000 single nucleotide polymorphisms (SNPs) in 419 AIS families. We found strongest evidence of association with chromosome 3p26.3 SNPs in the proximity of the CHL1 gene (P < 8 × 10(-8) for rs1400180). We genotyped additional chromosome 3p26.3 SNPs and tested replication in two follow-up case-control cohorts, obtaining strongest results when all three cohorts were combined (rs10510181 odds ratio = 1.49, 95% confidence interval = 1.29-1.73, P = 2.58 × 10(-8)), but these were not confirmed in a separate GWAS. CHL1 is of interest, as it encodes an axon guidance protein related to Robo3. Mutations in the Robo3 protein cause horizontal gaze palsy with progressive scoliosis (HGPPS), a rare disease marked by severe scoliosis. Other top associations in our GWAS were with SNPs in the DSCAM gene encoding an axon guidance protein in the same structural class with Chl1 and Robo3. We additionally found AIS associations with loci in CNTNAP2, supporting a previous study linking this gene with AIS. Cntnap2 is also of functional interest, as it interacts directly with L1 and Robo class proteins and participates in axon pathfinding. Our results suggest the relevance of axon guidance pathways in AIS susceptibility, although these findings require further study, particularly given the apparent genetic heterogeneity in this disease.
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