Mutations in the RNA exosome component gene EXOSC3 cause pontocerebellar hypoplasia and spinal motor neuron degeneration

RNA exosomes are multi-subunit complexes conserved throughout evolution and are emerging as the major cellular machinery for processing, surveillance and turnover of a diverse spectrum of coding and noncoding RNA substrates essential for viability. By exome sequencing, we discovered recessive mutations in EXOSC3 (encoding exosome component 3) in four siblings with infantile spinal motor neuron disease, cerebellar atrophy, progressive microcephaly and profound global developmental delay, consistent with pontocerebellar hypoplasia type 1 (PCH1; MIM 607596). We identified mutations in EXOSC3 in an additional 8 of 12 families with PCH1. Morpholino knockdown of exosc3 in zebrafish embryos caused embryonic maldevelopment, resulting in small brain size and poor motility, reminiscent of human clinical features, and these defects were largely rescued by co-injection with wild-type but not mutant exosc3 mRNA. These findings represent the first example of an RNA exosome core component gene that is responsible for a human disease and further implicate dysregulation of RNA processing in cerebellar and spinal motor neuron maldevelopment and degeneration.     

Mutations in ISPD cause Walker-Warburg syndrome and defective glycosylation of α-dystroglycan

Walker-Warburg syndrome (WWS) is an autosomal recessive multisystem disorder characterized by complex eye and brain abnormalities with congenital muscular dystrophy (CMD) and aberrant a-dystroglycan glycosylation. Here we report mutations in the ISPD gene (encoding isoprenoid synthase domain containing) as the second most common cause of WWS. Bacterial IspD is a nucleotidyl transferase belonging to a large glycosyltransferase family, but the role of the orthologous protein in chordates is obscure to date, as this phylum does not have the corresponding non-mevalonate isoprenoid biosynthesis pathway. Knockdown of ispd in zebrafish recapitulates the human WWS phenotype with hydrocephalus, reduced eye size, muscle degeneration and hypoglycosylated a-dystroglycan. These results implicate ISPD in a-dystroglycan glycosylation in maintaining sarcolemma integrity in vertebrates.     

Common variants at 12q14 and 12q24 are associated with hippocampal volume

Aging is associated with reductions in hippocampal volume that are accelerated by Alzheimer's disease and vascular risk factors. Our genome-wide association study (GWAS) of dementia-free persons (n = 9,232) identified 46 SNPs at four loci with P values of <4.0 × 10(-7). In two additional samples (n = 2,318), associations were replicated at 12q14 within MSRB3-WIF1 (discovery and replication; rs17178006; P = 5.3 × 10(-11)) and at 12q24 near HRK-FBXW8 (rs7294919; P = 2.9 × 10(-11)). Remaining associations included one SNP at 2q24 within DPP4 (rs6741949; P = 2.9 × 10(-7)) and nine SNPs at 9p33 within ASTN2 (rs7852872; P = 1.0 × 10(-7)); along with the chromosome 12 associations, these loci were also associated with hippocampal volume (P < 0.05) in a third younger, more heterogeneous sample (n = 7,794). The SNP in ASTN2 also showed suggestive association with decline in cognition in a largely independent sample (n = 1,563). These associations implicate genes related to apoptosis (HRK), development (WIF1), oxidative stress (MSR3B), ubiquitination (FBXW8) and neuronal migration (ASTN2), as well as enzymes targeted by new diabetes medications (DPP4), indicating new genetic influences on hippocampal size and possibly the risk of cognitive decline and dementia.     

A mixed-model approach for genome-wide association studies of correlated traits in structured populations

Genome-wide association studies (GWAS) are a standard approach for studying the genetics of natural variation. A major concern in GWAS is the need to account for the complicated dependence structure of the data, both between loci as well as between individuals. Mixed models have emerged as a general and flexible approach for correcting for population structure in GWAS. Here, we extend this linear mixed-model approach to carry out GWAS of correlated phenotypes, deriving a fully parameterized multi-trait mixed model (MTMM) that considers both the within-trait and between-trait variance components simultaneously for multiple traits. We apply this to data from a human cohort for correlated blood lipid traits from the Northern Finland Birth Cohort 1966 and show greatly increased power to detect pleiotropic loci that affect more than one blood lipid trait. We also apply this approach to an Arabidopsis thaliana data set for flowering measurements in two different locations, identifying loci whose effect depends on the environment.     

Loss-of-function mutations in TGFB2 cause a syndromic presentation of thoracic aortic aneurysm

Loeys-Dietz syndrome (LDS) associates with a tissue signature for high transforming growth factor (TGF)-β signaling but is often caused by heterozygous mutations in genes encoding positive effectors of TGF-β signaling, including either subunit of the TGF-β receptor or SMAD3, thereby engendering controversy regarding the mechanism of disease. Here, we report heterozygous mutations or deletions in the gene encoding the TGF-β2 ligand for a phenotype within the LDS spectrum and show upregulation of TGF-β signaling in aortic tissue from affected individuals. Furthermore, haploinsufficient Tgfb2(+/-) mice have aortic root aneurysm and biochemical evidence of increased canonical and noncanonical TGF-β signaling. Mice that harbor both a mutant Marfan syndrome (MFS) allele (Fbn1(C1039G/+)) and Tgfb2 haploinsufficiency show increased TGF-β signaling and phenotypic worsening in association with normalization of TGF-β2 expression and high expression of TGF-β1. Taken together, these data support the hypothesis that compensatory autocrine and/or paracrine events contribute to the pathogenesis of TGF-β-mediated vasculopathies.     

Activation of the AXL kinase causes resistance to EGFR-targeted therapy in lung cancer

Human non-small cell lung cancers (NSCLCs) with activating mutations in EGFR frequently respond to treatment with EGFR-targeted tyrosine kinase inhibitors (TKIs), such as erlotinib, but responses are not durable, as tumors acquire resistance. Secondary mutations in EGFR (such as T790M) or upregulation of the MET kinase are found in over 50% of resistant tumors. Here, we report increased activation of AXL and evidence for epithelial-to-mesenchymal transition (EMT) in multiple in vitro and in vivo EGFR-mutant lung cancer models with acquired resistance to erlotinib in the absence of the EGFR p.Thr790Met alteration or MET activation. Genetic or pharmacological inhibition of AXL restored sensitivity to erlotinib in these tumor models. Increased expression of AXL and, in some cases, of its ligand GAS6 was found in EGFR-mutant lung cancers obtained from individuals with acquired resistance to TKIs. These data identify AXL as a promising therapeutic target whose inhibition could prevent or overcome acquired resistance to EGFR TKIs in individuals with EGFR-mutant lung cancer.     

An efficient multi-locus mixed-model approach for genome-wide association studies in structured populations

Population structure causes genome-wide linkage disequilibrium between unlinked loci, leading to statistical confounding in genome-wide association studies. Mixed models have been shown to handle the confounding effects of a diffuse background of large numbers of loci of small effect well, but they do not always account for loci of larger effect. Here we propose a multi-locus mixed model as a general method for mapping complex traits in structured populations. Simulations suggest that our method outperforms existing methods in terms of power as well as false discovery rate. We apply our method to human and Arabidopsis thaliana data, identifying new associations and evidence for allelic heterogeneity. We also show how a priori knowledge from an A. thaliana linkage mapping study can be integrated into our method using a Bayesian approach. Our implementation is computationally efficient, making the analysis of large data sets (n > 10,000) practicable.