Characterisation of retinoblastomas without RB1 mutations: genomic, gene expression, and clinical studies

SummaryBackgroundRetinoblastoma is the childhood retinal cancer that defined tumour-suppressor genes. Previous work shows that mutation of both alleles of the RB1 retinoblastoma suppressor gene initiates disease. We aimed to characterise non-familial retinoblastoma tumours with no detectable RB1 mutations.MethodsOf 1068 unilateral non-familial retinoblastoma tumours, we compared those with no evidence of RB1 mutations (RB1+/+) with tumours carrying a mutation in both alleles (RB1−/−). We analysed genomic copy number, RB1 gene expression and protein function, retinal gene expression, histological features, and clinical data.FindingsNo RB1 mutations (RB1+/+) were reported in 29 (2·7%) of 1068 unilateral retinoblastoma tumours. 15 of the 29 RB1+/+ tumours had high-level MYCN oncogene amplification (28–121 copies; RB1+/+MYCNA), whereas none of 93 RB1−/− primary tumours tested showed MYCN amplification (p<0·0001). RB1+/+MYCNA tumours expressed functional RB1 protein, had fewer overall genomic copy-number changes in genes characteristic of retinoblastoma than did RB1−/− tumours, and showed distinct aggressive histological features. MYCN amplification was the sole copy-number change in one RB1+/+MYCNA retinoblastoma. One additional MYCNA tumour was discovered after the initial frequencies were determined, and this is included in further analyses. Median age at diagnosis of the 17 children with RB1+/+MYCNA tumours was 4·5 months (IQR 3·5–10), compared with 24 months (15–37) for 79 children with non-familial unilateral RB1−/− retinoblastoma.InterpretationAmplification of the MYCN oncogene might initiate retinoblastoma in the presence of non-mutated RB1 genes. These unilateral RB1+/+MYCNA retinoblastomas are characterised by distinct histological features, only a few of the genomic copy-number changes that are characteristic of retinoblastoma, and very early age of diagnosis.FundingNational Cancer Institute–National Institutes of Health, Canadian Institutes of Health Research, German Research Foundation, Canadian Retinoblastoma Society, Hyland Foundation, Toronto Netralaya and Doctors Lions Clubs, Ontario Ministry of Health and Long Term Care, UK-Essen, and Foundations Avanti-STR and KiKa

Rare and low-frequency coding variants alter human adult height

Height is a highly heritable, classic polygenic trait with ~700 common associated variants identified so far through genome - wide association studies . Here , we report 83 height - associated coding variants with lower minor allele frequenc ies ( range of 0.1 - 4.8% ) and effects of up to 2 16 cm /allele ( e.g. in IHH , STC2 , AR and CRISPLD2 ) , >10 times the average effect of common variants . In functional follow - up studies, rare height - increasing alleles of STC2 (+1 - 2 cm/allele) compromise d proteolytic inhibition of PAPP - A and increased cleavage of IGFBP - 4 in vitro , resulting in higher bioavailability of insulin - like growth factors . The se 83 height - associated variants overlap genes mutated in monogenic growth disorders and highlight new biological candidates ( e.g. ADAMTS3, IL11RA, NOX4 ) and pathways ( e.g . proteoglycan/ glycosaminoglycan synthesis ) involved in growth . Our results demonstrate that sufficiently large sample sizes can uncover rare and low - frequency variants of moderate to large effect associated with polygenic human phenotypes , and that these variants implicate relevant genes and pathways

Neural network-based model for supporting the expert driven project estimation process in mold manufacturing

One of the crucial activities for running a successful mold manufacturing business is project estimation. The estimation process is an early project activity which is usually handled by highly skilled, in-house experts. One of the most important parameters affecting the estimation process is the volume of manufacturing hours (VMH) to produce the mold. This article suggests how to address the problem of estimating the volume of manufacturing hours by using the support of an artificial neural network (ANN) model, and its inclusion into the expert driven project estimation process. Based on the histogram of ANN estimations the percentage of unwanted underestimations of the VMH can be estimated as well and decreased by an introduced safety factor. The developed model-based estimation enables an expert to improve project estimation by using easily obtainable input data

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

In the HTML version of this article initially published, the author groups ‘CHD Exome+ Consortium’, ‘EPIC-CVD Consortium’, ‘ExomeBP Consortium’, ‘Global Lipids Genetic Consortium’, ‘GoT2D Genes Consortium’, ‘EPIC InterAct Consortium’, ‘INTERVAL Study’, ‘ReproGen Consortium’, ‘T2D-Genes Consortium’, ‘The MAGIC Investigators’ and ‘Understanding Society Scientific Group’ appeared at the end of the author list but should have appeared earlier in the list, after author Krina T. Zondervan. The errors have been corrected in the HTML version of the article

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure underpinning obesity

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, non-coding variants from which pinpointing causal genes remains challenging. Here, we combined data from 718,734 individuals to discover rare and low-frequency (MAF<5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which eight in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2, ZNF169) newly implicated in human obesity, two (MC4R, KSR2) previously observed in extreme obesity, and two variants in GIPR. Effect sizes of rare variants are ~10 times larger than of common variants, with the largest effect observed in carriers of an MC4R stop-codon (p.Tyr35Ter, MAF=0.01%), weighing ~7kg more than non-carriers. Pathway analyses confirmed enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically-supported therapeutic targets to treat obesity

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity