Heterogeneous Forecast Adjustment

There is ample empirical evidence that expert‐adjusted model forecasts can be improved. One way to potential improvement concerns providing various forms of feedback to the sales forecasters. It is also often recognized that the experts (forecasters) might not constitute a homogeneous group. This paper provides a data‐based methodology to discern latent clusters of forecasters, and applies it to a fully new large database with data on expert‐adjusted forecasts, model forecasts and realizations. For the data at hand, two clusters can clearly be identified. Next, the consequences of having clusters are discussed. Copyright © 2016 John Wiley & Sons, Ltd.     

Nesprin interchain associations control nuclear size

Nesprins-1/-2/-3/-4 are nuclear envelope proteins, which connect nuclei to the cytoskeleton. The largest nesprin-1/-2 isoforms (termed giant) tether F-actin through their N-terminal actin binding domain (ABD). Nesprin-3, however, lacks an ABD and associates instead to plectin, which binds intermediate filaments. Nesprins are integrated into the outer nuclear membrane via their C-terminal KASH-domain. Here, we show that nesprin-1/-2 ABDs physically and functionally interact with nesprin-3. Thus, both ends of nesprin-1/-2 giant are integrated at the nuclear surface: via the C-terminal KASH-domain and the N-terminal ABD-nesprin-3 association. Interestingly, nesprin-2 ABD or KASH-domain overexpression leads to increased nuclear areas. Conversely, nesprin-2 mini (contains the ABD and KASH-domain but lacks the massive nesprin-2 giant rod segment) expression yields smaller nuclei. Nuclear shrinkage is further enhanced upon nesprin-3 co-expression or microfilament depolymerization. Our findings suggest that multivariate intermolecular nesprin interactions with the cytoskeleton form a lattice-like filamentous network covering the outer nuclear membrane, which determines nuclear size.     

Extremely low-coverage sequencing and imputation increases power for genome-wide association studies

Genome-wide association studies (GWAS) have proven to be a powerful method to identify common genetic variants contributing to susceptibility to common diseases. Here, we show that extremely low-coverage sequencing (0.1-0.5×) captures almost as much of the common (>5%) and low-frequency (1-5%) variation across the genome as SNP arrays. As an empirical demonstration, we show that genome-wide SNP genotypes can be inferred at a mean r(2) of 0.71 using off-target data (0.24× average coverage) in a whole-exome study of 909 samples. Using both simulated and real exome-sequencing data sets, we show that association statistics obtained using extremely low-coverage sequencing data attain similar P values at known associated variants as data from genotyping arrays, without an excess of false positives. Within the context of reductions in sample preparation and sequencing costs, funds invested in extremely low-coverage sequencing can yield several times the effective sample size of GWAS based on SNP array data and a commensurate increase in statistical power.     

Dominant missense mutations in ABCC9 cause Cantú syndrome

Cantú syndrome is characterized by congenital hypertrichosis, distinctive facial features, osteochondrodysplasia and cardiac defects. By using family-based exome sequencing, we identified a de novo mutation in ABCC9. Subsequently, we discovered novel dominant missense mutations in ABCC9 in 14 of the 16 individuals with Cantú syndrome examined. The ABCC9 protein is part of an ATP-dependent potassium (K(ATP)) channel that couples the metabolic state of a cell with its electrical activity. All mutations altered amino acids in or close to the transmembrane domains of ABCC9. Using electrophysiological measurements, we show that mutations in ABCC9 reduce the ATP-mediated potassium channel inhibition, resulting in channel opening. Moreover, similarities between the phenotype of individuals with Cantú syndrome and side effects from the K(ATP) channel agonist minoxidil indicate that the mutations in ABCC9 result in channel opening. Given the availability of ABCC9 antagonists, our findings may have direct implications for the treatment of individuals with Cantú syndrome.     

Mutations in CTC1, encoding conserved telomere maintenance component 1, cause Coats plus

Coats plus is a highly pleiotropic disorder particularly affecting the eye, brain, bone and gastrointestinal tract. Here, we show that Coats plus results from mutations in CTC1, encoding conserved telomere maintenance component 1, a member of the mammalian homolog of the yeast heterotrimeric CST telomeric capping complex. Consistent with the observation of shortened telomeres in an Arabidopsis CTC1 mutant and the phenotypic overlap of Coats plus with the telomeric maintenance disorders comprising dyskeratosis congenita, we observed shortened telomeres in three individuals with Coats plus and an increase in spontaneous γH2AX-positive cells in cell lines derived from two affected individuals. CTC1 is also a subunit of the α-accessory factor (AAF) complex, stimulating the activity of DNA polymerase-α primase, the only enzyme known to initiate DNA replication in eukaryotic cells. Thus, CTC1 may have a function in DNA metabolism that is necessary for but not specific to telomeric integrity.     

Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits

We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium.     

Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease

Using variants from the 1000 Genomes Project pilot European CEU dataset and data from additional resequencing studies, we densely genotyped 183 non-HLA risk loci previously associated with immune-mediated diseases in 12,041 individuals with celiac disease (cases) and 12,228 controls. We identified 13 new celiac disease risk loci reaching genome-wide significance, bringing the number of known loci (including the HLA locus) to 40. We found multiple independent association signals at over one-third of these loci, a finding that is attributable to a combination of common, low-frequency and rare genetic variants. Compared to previously available data such as those from HapMap3, our dense genotyping in a large sample collection provided a higher resolution of the pattern of linkage disequilibrium and suggested localization of many signals to finer scale regions. In particular, 29 of the 54 fine-mapped signals seemed to be localized to single genes and, in some instances, to gene regulatory elements. Altogether, we define the complex genetic architecture of the risk regions of and refine the risk signals for celiac disease, providing the next step toward uncovering the causal mechanisms of the disease.