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• Comparison of the diagnostic yield of aCGH and NGS across different neurodevelopmental disorders

  Current recommendations for the genetic diagnosis of neurodevelopmental disorders (NDDs) do not include the use of next generation sequencing (NGS) and are still based on chromosomal microarrays, such as comparative genomic hybridization array (aCGH). The present study compares the diagnostic yield obtained by aCGH and clinical exome sequencing in NDD globally and its spectrum of disorders. To that end, 1412 patients clinically diagnosed with NDDs and studied with aCGH were classified into phenotype categories: Global developmental delay/intellectual disability (GDD/ID); autism spectrum disorder (ASD); and Other NDDs. These categories were further subclassified into subcategories, based on the most frequent accompanying signs and symptoms: isolated forms, forms with epilepsy; forms with micro or macrocephaly and syndromic forms. A subset of 245 patients of the 1412 were subjected to clinical exome sequencing. Diagnostic yield of aCGH and clinical exome sequencing, expressed as the number of solved cases, was compared for each phenotype category and subcategory. Clinical exome sequencing was superior than aCGH for all cases except for isolated ASD, with no cases solved by NGS. Globally, clinical exome sequencing solved 20% of cases (versus 5.7% by aCGH) and the diagnostic yield was highest for all forms of GDD/ID and lowest for Other NDDs (7.1% versus 1.4% by aCGH) and ASD (6.1% versus 3% by aCGH). In the majority of cases, diagnostic yield was higher in the phenotype subcategories than in the mother category. These results support the use of NGS as the first-tier test in the diagnostic algorithm of all NDDs followed by aCGH when necessary.

  Study EGAS00001004949

• Prediction of pigmentation phenotypes by SNP typing in a Northern German population

  Human pigmentation traits are of great interest to many research areas, from ancient DNA analysis to forensic science. We aimed to develop a gene-based predictive model for pigmentation phenotypes in a realistic target population for forensic case work from Northern Germany. Our aim was to determine whether better prediction accuracy can be achieved, or fewer genetic markers may suffice, than in previously studied, genetically more heterogeneous populations. We investigated the association between eye, hair and skin colour, and 12 candidate single nucleotide polymorphisms (SNPs) from six genes. Our study comprised two samples of 300 and 100 individuals from Northern Germany who were carefully characterized with regard to pigmentation phenotypes. The first sample was used to select trait-associated SNPs whereas the second sample served to estimate odds ratios (ORs) and to quantify the predictive capability of the respective SNP genotypes. SNP rs12913832 in HERC2 was found to be strongly associated with blue eye colour (OR=15.6, p<1.2•10-4) and to yield reasonable predictive power (90% sensitivity, 63% specificity). SNP associations with hair and skin colour were weaker and genotypes less predictive. A comparison to two recently published sets of markers to predict eye and hair colour revealed that the consideration of additional SNPs with weak to moderate effect increases the predictive power in Northern Germans for eye colour, but not for hair colour. In addition, fine phenotyping and differentiation of hair colour (light / dark and red tint / no red tint) were found to increase the number of significant genotype-phenotype associations.

  Study EGAS00001001174

• Associations between APOE status and cognitive ability across the lifecourse

  The association between APOE genotype and cognitive function suggests a positive role for the e2 allele and a negative role for the e4 allele. Both alleles have relatively low frequencies in the general population, hence meta-analyses have been based on many small, heterogeneous studies. Here we report the APOE-cognition associations in the largest single analysis to date. APOE status and cognitive ability were measured in 18,337 participants from the Generation Scotland study between 2006 and 2011. The age range was 18-94 years with a mean of 47 (SD 15). Four cognitive domains were assessed: verbal declarative memory (paragraph recall), processing speed (digit symbol substitution), verbal fluency (phonemic verbal fluency), and vocabulary (Mill Hill synonyms). Linear regression was used to assess the associations between APOE genetic status and cognition. Possession of the e4 allele was associated with lower scores on the measures of memory and processing speed in subjects aged >60. Across all age ranges, the e4 allele was linked to better verbal fluency scores. In younger subjects (≤60 years) the e4 allele was linked to higher vocabulary scores. There were no associations between the e2 allele and cognitive ability. As seen in previous meta-analyses, the APOE e4 allele is linked to poorer cognitive performance in the domains of memory and processing speed. By contrast, positive associations were seen between the e4 allele and measures of verbal fluency and vocabulary. All associations were relatively small and, in many cases, nominally significant despite the very large sample size.

  Study EGAS00001001235

• Search for new loci and low-frequency variants influencing glioma risk by exome-array analysis

  To identify protein altering variants (PAVs) for glioma we analysed Illumina HumanExome BeadChip exome array data on 1,882 glioma cases and 8,079 controls from three independent European populations. In addition to single variant tests we incorporated information on the predicted functional consequences of PAVs and analysed sets of genes with a higher likelihood of having a role in glioma on the basis of the profile of somatic mutations documented by large-scale sequencing initiatives. Globally tThere was a strong relationship between effect size and SNPs predicted to be damaging (P=2.29x10-49); however, these variants which are most likely to impact on risk, are rare (MAF<5%). While no single variant showed an association which was statistically significant at the genomewide threshold a number of represented promising Notable associations - were seen with the BRCA2:c.9976A>T, p.(Lys3326Ter)BRCA2 p.Lys332X variant, which has been shown documented to influence breast and lung cancer risks (OR=2.3, P=4.00x10-4 for glioblastoma [GBM]) and IDH2:c.782G>A, p.(Arg261His)IDH2 p.Arg261His (OR=3.21, P=7.67x10-3, for non-GBM). Additionally, gene burden tests revealed a statistically significant association for HARS2 and risk of GBM (P=2.20x10-6). Genome scans of low frequency PAVs represent a complementary strategy to identify disease-causing variants compared with scans based on tagSNPs. Strategies to lessen the multiple testing burden by restricting analysis to PAVs with higher priors affords an opportunity to maximise study power.

  Study EGAS00001001258

• Exome sequencing

  Human telomere biology disorders (TBD), a heterogeneous group of disorders characterized by telomere attrition and premature aging phenotypes, are caused by inherited loss-of-function mutations in telomere-associated genes. Here, we identify three germline heterozygous missense variants in RPA1 gene in four unrelated probands presenting with short telomeres and varying clinical features of TBD including bone marrow failure, myelodysplastic syndrome, T- and B-cell lymphopenia, pulmonary fibrosis, and skin manifestations. All variants cluster to DNA binding domain A of RPA1 protein. RPA1 is an essential single-strand DNA-binding protein essential for DNA replication and repair. RPA1 has been implicated in telomere maintenance but the mechanism remains elusive. Thus far, no genetic disorder had been linked to RPA1. Using FRET assays, we showed that RPA1E240K and RPA1V227A exhibit increased binding to single-strand and telomeric DNA, implying a gain in DNA-binding function while RPA1T270A has binding properties similar to wild type. To study the mutational effect, RPA1E240K, with the highest binding capacity, was knocked-in iPSCs using CRISPR/Cas9, which showed severe telomere shortening and impaired hematopoietic differentiation. Furthermore, in the RPA1E240K patient, stable blood counts over two decades due coincided with clonal rescue hematopoiesis with an RNA-degrading truncating RPA1 mutation and a uniparental isodisomy 17p with loss of RPA1E240K allele. Using single cell DNA sequencing, the two somatic genetic rescue events were proven to be independently acquired in hematopoietic stem cells. In summary, we describe the first human disease caused by germline RPA1 variants in individuals with TBD.

  Study EGAS00001005761

• Benchmarking for alignment and variant calling

  Background: Lung cancer is a heterogeneous disease and the primary cause of cancer-related mortality worldwide. Somatic mutations, including large structural variants, are important biomarkers in lung cancer for selecting targeted therapy. Genomic studies in lung cancer have been conducted using short-read sequencing. Emerging long-read sequencing technologies are a promising alternative to study somatic structural variants, however there is no current consensus on how to process data and call somatic events. In this study, we preformed whole genome sequencing of lung cancer and matched non-tumour samples using long and short read sequencing to comprehensively benchmark three sequence aligners and six structural variant callers comprised of four generic callers (Sniffles2, cuteSV, SVIM and DELLY in generic mode) and two somatic callers (nanomonsv and DELLY in somatic modes). Results: Different combinations of aligners and variant callers influenced somatic structural variant detection. The choice of caller had a significant influence on somatic structural variant detection in terms of variant type, size, sensitivity, and accuracy. The performance of each variant caller was assessed by comparing to somatic structural variants identified by short read sequencing. When compared to somatic structural variants detected with short read sequencing, more events were detected with long read sequencing. The mean recall of somatic variant events identified by short read sequencing was higher for the somatic callers (64%) than generic callers (52%), with nanomonsv (69%) showing the best performance. Conclusion: Long read sequencing can identify somatic structural variants. The longer reads have the potential to improve our understanding of cancer development and inform personalized cancer treatment.

  Study EGAS00001007819

• Analysis of the Elements Involved in the Enrichment of a Panel of Genomic Regions by Nanopore Sequencing Using Adaptive Sampling

  DNA sequencing using nanopore technologies with the affordable MinION device is useful for the identification and characterization of structural variants, long haplotypes, sequencing of repetitive regions and identification of epigenetic modifications. The main limitation of this approach is the low coverage obtained, which might be avoided by adaptive sampling, a computationally controlled method of enrichment for targeted genomic regions. This study dissects the factors involved in the enrichment by adaptive sampling of a panel of 18 human genome regions containing 20 genes implicated in breast cancer sequenced in 16 patients with familial breast cancer negative for NGS screening. An average coverage of 2.0x was obtained for the whole genome and 5.1x for selected regions. Sequencing time was the main factor improving coverage. The selection of long reads (>1 Kb) did not improve the enrichment. The length of the selected region, which in our study ranged from 126 to 565 Kb, did not play a significant role in enrichment. However, the region containing PMS2 showed significantly lower coverage, which could be explained by the high number of PMS2 pseudogenes (N = 14), which were also enriched. Our study shows new evidence of enrichment obtained by adaptive sampling in a panel of genomic regions and shows parameters, the relevance of sequencing time and the role of pseudogenes, that improve the enrichment yield with no library reloading or GPU use, data useful for a more efficient application of this procedure in future studies.

  Study EGAS00001007375

• Efficacy of nivolumab in pediatric cancers with high mutation burden and mismatch-repair deficiency

  Purpose: Checkpoint-inhibitors have limited efficacy for children with unselected solid and brain tumors. We report the first prospective pediatric trial (NCT02992964) using nivolumab exclusively for refractory non-hematological cancers harboring tumor mutation burden (TMB) ≥5 mutations/megabase (mut/Mb) and/or mismatch-repair deficiency (MMRD). Patients and methods: Twenty patients were screened, and ten ultimately included in the response cohort of whom nine had TMB >10mut/Mb (three initially eligible based on MMRD) and one patient had TMB between 5-10 mut/Mb. Results: Delayed immune responses contributed to best overall response of 50%, improving on initial objective responses (20%) and leading to 2-year overall survival (OS) of 50% (95% CI; 27, 93). Four children, including three with refractory malignant gliomas are in complete remission at a median follow-up of 37-months (range: 32.4-60), culminating in 2-year OS of 43% (95% CI; 18.2, 100). Biomarker analyses confirmed benefit in children with germline MMRD, microsatellite instability, higher activated and lower regulatory circulating T-cells. Stochastic mutation accumulation driven by underlying germline MMRD impacted the tumor microenvironment, contributing to delayed responses. No benefit was observed in the single patient with a MMR-proficient tumour and TMB 7.4 mut/Mb. Conclusions: Nivolumab resulted in durable responses and prolonged survival for the first time in a pediatric trial of refractory hypermutated cancers including malignant gliomas. Novel biomarkers identified here need to be translated rapidly to clinical care to identify children who can benefit from checkpoint-inhibitors, including for upfront management of their cancers.

  Study EGAS00001007393

• Peripheral blood DNA methylome in adalimumab-treated patients with rheumatoid arthritis

  Background and aims Rheumatoid arthritis (RA) patients are currently treated with biological agents mostly aimed at cytokine blockade such as anti-TNFα therapy. Currently, there are no biomarkers to predict therapy response to these agents. Here, we aimed to predict response to adalimumab (ADA) treatment in RA patients using DNA methylation in peripheral blood Methods DNA methylation profiling on whole peripheral blood from 92 RA patients before the start of adalimumab (ADA) was determined using Illumina HumanMethylationEPIC BeadChip Array. After 6 months, treatment response was assessed according to the Alliance of Associations for Rheumatology (EULAR) criteria for disease response. Patients were classified as responders (DAS28<3.2 or decrease of 1.2 points) or as non-responders (DAS28>5.1 or decrease of less than 0.6 points). Machine learning models were built with gradient boosting and stability selection models to predict response prior to ADA treatment with predictor DNA methylation markers. Results We demonstrated a 27-feature panel of DNA methylation markers or CpG classifiers that predict response in RA patients treated with ADA. Forty-nine patients were assigned as responder and 43 patients assigned as non-responders. We differentiate responders from non-responders with a high sensitivity (AUC 0.76). The predictor CpGs annotated to genes involved in immunological- and pathophysiological pathways related to RA such as T-cell signaling, B-cell pathology and angiogenesis. Conclusion Our findings indicate that DNA methylation signatures discriminate responders and non-responders to ADA treatment and can serve as a tool for therapy prediction.

  Study EGAS00001007578

• NHLBI TOPMed: The Genetic Epidemiology of Asthma in Costa Rica

  This administrative supplement to the project, "The Genetic Epidemiology of Asthma in Costa Rica" (R37 HL066289) is in response to NOT-HL-14-029 to perform whole genome sequencing (WGS) on existing NHLBI populations. We focus on asthma because of its public health significance. Asthma affects 26 million U.S. children and adults, remains a major cause of morbidity (one-half million hospitalizations a year) and is the most common cause of school and work days lost. Asthma-related costs are estimated to be over $12.7 billion annually. The Asthma Probands for both the extended pedigrees and the trios utilized in this study were selected on the basis of a physician diagnosis of asthma; a history of recurrent asthma attacks or at least 2 respiratory symptoms; and either airway hyperresponsiveness to methacholine or significant response to bronchodilator (Albuterol) administration. These criteria are identical to the criteria used in the Childhood Asthma Management Program (CAMP). The three primary goals of this project are to: (1) identify common and rare genetic variants that determine asthma and its associated phenotypes (height, weight, IgE level, lung function, bronchodilator response, steroid treatment response) through whole genome sequencing (WGS); (2) perform novel family based association analysis of our WGS data to identify novel genes for asthma; and (3) integrate epigenomic and transcriptomic data with our WGS data and determine the epistatic interactions present using systems genomics approaches. Identification of the molecular determinants of asthma remains an important priority in translational science. Genome-wide association studies (GWAS) have been successful in this regard, identifying at least 10 novel susceptibility genes for asthma. However, as with most complex traits, the variants identified by GWAS explain only a fraction of the estimated heritability of this disorder. Herein, we propose a novel family-based study design and state-of-the-art genome sequencing techniques to map a set of sequence variants for asthma and its associated phenotypes and assess the interrelationships of the identified genes and variants using systems genomics methods. We have assembled a team of investigators highly-skilled and expert in whole genome sequencing (Drs. Michael Cho and Benjamin Raby), genetic association analysis (Drs. Scott T. Weiss, Jessica Lasky-Su and Christoph Lange), integrative genomics (Drs. Raby, Kelan Tantisira, Augusto Litonjua and Dawn DeMeo), and systems genomics (Drs. Weiss, Amitabh Sharma, Lange and Raby) to address this important problem with both a novel study design and data set.

  Study phs000988