Search Results - EGA European Genome-Phenome Archive

Methotrexate Clearance GWAS in Acute Lymphoblastic Leukemia (ALL) Patients

We estimated the plasma clearance of methotrexate from 1279 acute lymphoblastic leukemia (ALL) patients treated on the Children Oncology Group 9904 and 9905 trials (http://clinicaltrials.gov/show/NCT00005585 and http://clinicaltrials.gov/show/NCT00005596). Patients received either a 24-hour infusion of a 1 g/m2 dose or 4-hour infusion of a 2 g/m2 dose). Methotrexate clearance was lower in older children (p=7 x 10-7), females (p=2.7 x 10-4), and patients who received a delayed intensification phase (p=0.0022). In a genome-wide analysis, methotrexate clearance was associated with polymorphisms in the SLCO1B1 gene (p=2.1 x 10-11), which encodes for an organic anion transporter. This replicates findings using different schedules of high-dose methotrexate in ALL patients treated on St. Jude protocols. A combined meta-analysis yields a p-value of 5.7 x 10-19 for the association of methotrexate clearance with SLCO1B1 SNP rs4149056 (Trevino et al, PMID 19901119 and Ramsey et al, PMID 23233662). This data set includes the dependent variable of methotrexate clearance and all of the SNP data available from arrays.

Study phs000637

HuBMAP: Single-Cell Multiplex Chromatin and RNA Interactions in Aging Human Brain

The study employs the Multi-Nucleic Acid Interaction Mapping in Single Cell (MUSIC) technique to concurrently profile multiplex chromatin interactions, gene expression, and RNA-chromatin associations within individual nuclei, revealing dynamically organized chromatin complexes in human frontal cortex samples from elderly donors. The MUSIC technique allows for the exploration of chromatin architecture and transcription at cellular resolution in complex tissues. The study includes 14 human cortex tissues and employs MUSIC to delineate diverse cortical cell types and states, revealing that nuclei with fewer short-range chromatin interactions correlate with an "older" transcriptomic signature and Alzheimer's pathology. Additionally, the study elucidates that specific cell types, characterized by chromatin contacts between cis expression quantitative trait loci (cis eQTLs) and a promoter, are particularly susceptible to the regulatory impact of these cis eQTLs on target gene expression. Furthermore, the female cortical cells exhibit highly heterogeneous interactions between the X-inactive specific transcript (XIST) non-coding RNA and Chromosome X, along with diverse spatial organizations of the X chromosomes. MUSIC presents a potent tool for exploring chromatin architecture and transcription at cellular resolution in complex tissues.

Study phs003568

Cryptic Relatedness in the Singapore Living Biobank Project

The Singapore Living Biobank is a collection of healthy population-based Chinese and Malay individuals, for the purpose of phenotype recall study of high-impact variant carriers. These individuals are sampled from two studies: Multi-Ethnic Cohort (MEC), and the Singapore Health 2012 (SH2012). The MEC is a population-based cohort initiated in 2007 to investigate the genetic and lifestyle factors that affect the risk of developing chronic diseases such as diabetes and cardiovascular outcomes in the three ethnic groups (Chinese, Malays, and Indians). The SH2012 study is a population-based cross-sectional survey conducted in Singapore between 2012 and 2013, with over-sampling of Malays and Indians. Participants in MEC and SH2012 completed a similar set of questionnaire components, health examination, and biochemisty panels. Description of the MEC and SH2012 studies can be found at http://blog.nus.edu.sg/sphs/. We generated whole-exome sequencing data and Illumina OmniExpress array genotyping data for 1,299 Chinese and 1,229 Malays from the Singapore Living Biobank. This study includes a subset of 762 individuals that were found to be closely related (≤3rd degree), including 263 Chinese and 499 Malays.

Study EGAS00001002619

Small variants in mtDNA Canary Islands - WES Illumina (ITER)

The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

Study EGAS00001005678

Small variants in mtDNA Canary Islands - WGS Illumina (ITER)

The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

Study EGAS00001005679

Small variants in mtDNA Canary Islands - WGS Oxford Nanopore Technologies (ITER)

The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

Study EGAS00001005677

Childhood Cancer Data Initiative (CCDI): Identification and Targeting of Treatment Resistant Progenitor Populations in T-cell Acute Lymphoblastic Leukemia

Our goal with this study was to identify the mechanisms of treatment resistance in T-cell acute lymphoblastic leukemia (ALL) using single-cell genomics. We profiled 40 T-ALL cases from the Children's Oncology Group AALL0434 clinical trial using CITE-seq/snATAC-seq, capturing a breadth of immunophenotypes, including early T-cell precursor (ETP) and near-ETP/non-ETP subtypes. By integrating analyses of T-ALL cells with the normal T-cell developmental trajectory, the study identified a specific subgroup of leukemia cells resembling bone marrow progenitors (BMP-like cells). These BMP-like cells were associated with treatment failure and poor overall survival in T-ALL patients. Overall, this study reveals comprehensive multiomic signatures for rapidly assessing risk and tailoring targeted treatment for high-risk T-ALL patients.

Study phs003432

Long-read sequencing of saliva collected and stablized at room temperature in Oragene devices on the PacBio Revio

Saliva collected in Oragene™ devices and extracted with Nanobind kits yields high‑molecular‑weight DNA suitable for PacBio HiFi whole‑genome sequencing, offering a convenient alternative to blood collection (“High-quality HMW DNA was obtained from all samples…”). Sequencing of paired saliva and blood samples on the Revio system produced comparable HiFi read lengths, yields, and 30–39× genome coverage. Methylation profiles were also highly similar, with minor differences attributable to small amounts of non‑human DNA present in saliva (“DNA extracted from saliva is typically ~75–95% human…”). Variant calling using PacBio WGS pipelines showed high concordance between saliva and blood from the same donor for both SNVs and structural variants. These results demonstrate that saliva enables reliable, high‑throughput HiFi sequencing workflows with performance equivalent to blood.

Study EGAS50000001666

Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Autism - Simons Simplex Collection (SSC)

In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

Study phs001676

Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Victorian Collaborative AuTism Study (CATS): Family and Community Study of the Genetics of Autism Spectrum Disorder

In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

Study phs002044

Human genomic and phenotypic synthetic data for the study of rare diseases

The purpose of this dataset is to facilitate development of technical implementations for rare disease data integration, analysis, discovery, and federated access. This synthetic dataset includes clinical and genomic data from 6 rare disease cases. It consists of 18 whole genomes (6 index cases with their parents) which have genetic background based on public human data sequenced in the context of the Illumina Platinum initiative (Eberle, MA et al. (2017)) and made available by the HapMap project (https://www.genome.gov/10001688/international-hapmap-project). In each of the cases, real causative variants correlating with the phenotypic data provided were spiked-in. The cases included in this synthetic dataset correspond to the following type of disorders: CASE 1- Congenital myasthenic syndrome (Autosomal Dominant -de novo variant) CASE 2- Macular dystrophy (Autosomal Dominant) CASE 3- Muscular dystrophy (Autosomal Recessive-compound heterozygous variants) CASE 4- Mitochondrial disorder (Autosomal Recessive-consanguineous case - homozygous variant) CASE 5- Breast cancer (Autosomal Dominant) CASE 6- Similar as case 1 for patient matchmaking tests: Congenital myasthenic syndrome (Autosomal Dominant-de novo variant) For each case you will be able to download the following data: clinical information (phenopackets per individual and pedigree per family), raw genomic data (FASTQ and BAMs) and processed genomic data (vcfs). When using the data, the following should be acknowledged: the RD-Connect GPAP (https://platform.rd-connect.eu/), EC H2020 project EJP-RD (grant # 825575), EC H2020 project B1MG (grant # 951724) and Generalitat de Catalunya VEIS project (grant # 001-P-001647).

Study EGAS00001005702

The data access committee for Evolution of neoantigen landscape during immune checkpoint blockade in non-small cell lung cancer.

Dac EGAC00001000757

UK10K COHORT ALSPAC

The UK10K project proposes a series of complementary genetic approaches to find new low-frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome-wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein-coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will directly analyse quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The Avon Longitudinal Study of Parents and Children (ALSPAC) is a two-generation prospective study. Pregnant women living in one of three health districts in the former county of Avon with an expected delivery date between April 1991 and December 1992 were eligible to be enrolled in the study, and this formed the initial point of contact for the development of a large, family based resource. Information has been collected on the children and the mothers through retrieval of biological materials (e.g. antenatal blood samples, placentas), biological sampling (e.g. collection of cord blood, umbilical cord, milk teeth, hair, toenails, blood and urine), self-administered questionnaires, data extraction from medical notes, linkage to routine information systems and at repeat research clinics.

Study EGAS00001000090

Molecular features of adenomas predicting metachronous colorectal cancer: a nested-case control study

"Background & Aims: Current morphological features defining advanced adenomas (size ≥10 mm, high grade dysplasia or >25% villous component) cannot optimally distinguish individuals at high-risk or low-risk of metachronous colorectal cancer (me-CRC), which may result in suboptimal surveillance. Certain DNA copy number alterations are associated with adenoma-to-carcinoma progression (cancer-associated events; CAEs). We aimed to evaluate whether CAEs can better predict an individual’s risk of me-CRC than the morphological advanced adenoma features. Methods: In this nested case-control study, 529 individuals with a single adenoma at their first colonoscopy were selected from a Norwegian adenoma cohort. DNA copy number profiles were determined, by means of low-coverage whole genome sequencing. We assessed the prevalence of CAEs in advanced and non-advanced adenomas and its association with me-CRC. For the latter, cases (with CRC) were matched to controls (without CRC), with the same follow-up period as cases, as well as age and sex. Subsequently, odds ratios (OR) for the association of the presence of an advanced adenoma or a molecularly-defined high-risk adenoma with me-CRC were calculated. Results: Molecular high-risk features were observed in 85/267 (32%) of advanced adenomas and in 27/262 (10%) of non-advanced adenomas. Me-CRC was more strongly associated with advanced adenomas (OR 3.58; 95% CI 2.27-5.72) than with molecular high-risk adenomas (OR 1.90; 95% CI 1.14–3.16). After adjusting for other variables, only advanced adenoma remained significantly associated with me-CRC (OR 3.39; 95% CI 2.10–5.55). Conclusion: Molecularly-defined high-risk adenomas were associated with me-CRC, but the association of advanced adenoma with me-CRC was stronger. " Project goal: Evaluate the value of DNA copy numbers alterations detected in a baseline adenoma, in the prediction of risk of metachronous CRC

Study EGAS00001007039

Center for Common Disease Genomics (CCDG) - Cardiovascular: Harvard Gene-Diet Interaction in a Costa Rican Cohort

The National Human Genome Research Institute (NHGRI) has funded the Centers for Common Disease Genomics (CCDG), a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes and to better understand the general principles of genomic architecture underlying common, complex inherited diseases. This study contains whole genome sequence data and associated variant calls of more than 4200 participants in a cohort collected by the Harvard School of Public Health. The cohort includes subjects from thirty-four countries in the Central Valley of Costa Rica covering a full range of socioeconomic levels, as well as urban, peri-urban and rural lifestyle

Study phs002282

Genome-Wide Association Study of Patients with Coccidioidomycosis

BackgroundValley Fever is typically an infection of the lungs caused by the fungi Coccidioides immitis and Coccidioides posadasii. The incidence of Coccidioidomycosis (CM), or infection with Coccidioides, has dramatically increased over the last 20 years. This is particularly true in the Southwest of the United States, where people often breathe fungal spores that arise from the soil. Reasons for increased infection rates are thought to include population growth and construction in these endemic regions, an increase in the number of people whose immune systems are compromised due to infection or treatment with drugs required for organ transplants, climate change, as well as improved testing practices and greater physician awareness. Mild CM most commonly presents itself with flu-like symptoms and rashes, which can last weeks to months. Individuals with compromised immune systems, specifically-- substantial suppression of the immune cells known as T cells, can develop severe pulmonary and disseminated disease. Infection that remains localized to the lungs is referred to as pulmonary disease, but when the infection spreads out of the lungs into other parts of the body it represents a more serious condition referred to as a disseminated disease, or disseminated CM. In nature, Coccidioides spp. exists as mold and lives in dust and soil. When the contaminated soil or dust is disturbed by human activity, animals, or weather, the Coccidiodies spores are released into the air. Airborne spores are taken up by breathing and settle in the lungs. Once in the moist and warm environment of the lung, spores transform into spherules, which divide and become filled with smaller spores, called endospores. When the spherules get large enough, they rupture and release these endospores, which can spread and disseminate to surrounding tissue. The cycle then repeats itself as these endospores develop into new spherules3. Different ethnic groups have been described to vary in their susceptibility to developing disseminated CM after initial infection with Coccidioides. For example, evidence suggests that African-American and Filipino patients suffer the disseminated disease at a greater rate than other ethnicities. The suggestion that race plays a role in the clinical expression of the disease is still a source of debate amongst the scientific community and any genetic mechanisms responsible for these differences have yet to be fully elucidated. If our genetic makeup influences our ability to limit the spread of infection, finding which DNA differences cause these variances could provide clues to how the body successfully fights infection, and provide opportunities to boost the body’s ability to do this. Further, if we are able to identify the specific genetic risk factors that correlate with the development of disseminated infection, physicians could perform genetic screenings to identify high-risk patients and provide them with preemptive antifungal therapy prior to developing disseminated disease.The genome, made up of DNA, contains all of the information needed for humans to develop and grow. Genome-wide association studies (GWAS) allow us to look for inherited differences that are more common between people who share a particular trait, for example, height or susceptibility to certain diseases, compared to those who do not share the trait. Although some traits and diseases are controlled by a single gene, the majority are influenced by contribution from several, or even many, different genes. To find evidence of genes that contribute to specific traits, GWAS typically compares genome information from large numbers of people who have a particular disease (referred to as “cases”) looking for DNA sequences that are common among these samples, and are different from DNA sequences seen in large numbers of people who lack the trait, but are as much like the cases as possible (referred to as “controls”). The DNA sequence data from each group, cases versus controls, are analyzed to see if there are specific genomic differences that tend to be associated with the disease. MethodsTwo separate GWAS approaches were taken to look for genetic differences that could be responsible for the observed differences between the different patient populations we are studying. The first method, known as genotyping, scans for differences at a set of positions across the genome, which includes both the genes that encode our proteins and the larger amount of DNA that does not. The second method, known as exome sequencing, allows us to compare the entire sequence of the portion of the genome that codes for proteins.  For this study, DNA from patients with either pulmonary or disseminated CM were genotyped and exome sequenced to look for DNA differences that are associated with one condition or the other. All patients were at least 18 years old, had no evidence of immunosuppression, and had proven or probable pulmonary coccidioidomycosis according to established diagnostic criteria. Of these patients, a subset demonstrated disseminated disease, i.e., they showed evidence of coccidioidal infection outside of the thorax by biopsy/aspiration, had radiographic imaging, and show positive coccidioidal serology. Our criteria for including patients with the pulmonary disease were that they must not require ongoing antifungal treatment or show evidence of active CM (in skin test positive patients), show no evidence of extrapulmonary dissemination, and have no evidence of ongoing pulmonary infection (pulmonary nodules are accepted) beyond six months from diagnosis.Patient DNA was purified from blood or from sputum samples by the labs of our collaborators, Drs. George Thompson (UC Davis School of Medicine) and John Galgiani (University of Arizona Health Sciences). Genome-wide association (GWAS) analysis was carried out to look for candidate loci associated with pulmonary versus disseminated disease, taking into account the population structure of the samples. Single nucleotide or insertion/deletion variants were identified from whole-exome sequences (WES) using the Picard/BWA/GATK pipeline. ResultsTable 1. Pulmonary versus Disseminated Cases of Coccidiomycosis for GWAS, Sorted by EthnicityEthnicityPulmonary CasesDisseminated CasesAsian85Black/African American1664Caucasian/White4015Filipino03Hispanic/Latino3414Indian21Mexican American1039Pacific Islander01Samoan03Vietnamese10Unknown16917More than one race02Total373134Table 1 shows the number of samples analyzed from patients with pulmonary versus disseminated disease, and patient ethnicity, where known. In all, we worked with 507 samples, including 134 samples from patients with disseminated disease and 373 samples from patients with pulmonary disease. Of these, 505 samples were genotyped using the Multi-Ethnic Global Array from Illumina Inc. In addition, we were able to generate whole-exome sequence from 498 patient samples. No significant associations were detected that differed between samples from patients with pulmonary versus disseminated disease; that is, no particular DNA sequences were found to be significantly enriched in patients with disseminated disease compared to patients with pulmonary disease. The ability to detect genetic association between specific sequences and genetically determined traits is influenced by several factors, including how many patient samples are available to compare, how many different genes contribute to the trait and how strong their contributions are. When the number of genes is small and the contribution of each gene is great, smaller numbers of patient samples are needed to detect an association. When more genes are involved, or the contribution from each gene is more modest, larger numbers of patient samples must be examined. While we were not able to detect any associated within this study, it does not mean that subsequent studies would not find this connection. Our study suggests significantly more samples should be analyzed in further studies.Whole-exome sequences were generated from 498 samples and were aligned to reference sequences to identify positions where the sequences differed from the reference. These data are being analyzed to determine if any variants are associated with pulmonary, versus disseminated, disease. 

Study phs002170

National Eye Institute (NEI) Exfoliation Genotyping Study

The overall goal of our research is to elucidate the pathogenesis of exfoliation syndrome and the associated glaucoma, making it possible to implement effective screening and prevention strategies and to develop novel therapies. Cases genotyped for this project are from the Nurses Health Study (NHS), the Health Professionals Follow-up Study (HPFS), the Women's Genome Health Study (WGHS), the Massachusetts Eye and Ear Infirmary (MEEI), Mayo Clinic, the University of Iowa, the University of Miami and Duke University Medical Center. Exfoliation syndrome (XFS) is a common condition that is a major risk factor for high-tension open-angle glaucoma, pre-mature cataract formation, and increased risk of complications during cataract surgery. Previous studies suggest that exfoliation syndrome and the related glaucoma (XFG) are genetically complex, and one gene, LOXL1, has been identified as a major genetic risk factor. LOXL1 variants are found in up to 98% of affected patients; however, these same variants are also present in up to 80% of unaffected individuals, indicating that additional genetic and/or environmental factors are necessary for disease development. Samples genotyped for this study are a case set (1,096 samples) and 24 pedigrees (98 samples). Controls for association analyses are selected from the NEIGHBORHOOD study.

Study phs001053

Botswana 15 autosomal unlinked microsatellites

Population structure was investigated in 990 Botswana individuals according to ethno-linguistics, Bantu and Khoisan, and geography (the nine administrative districts) using the AmpFLSTR Identifiler autosomal microsatellite markers. Genetic diversity and forensic parameters were calculated for the overall population, and according to ethno-linguistics and geography. The overall combined power of exclusion (CPE) was 0.9999965412 and the combined match probability 6,28 x 10-19. CPE was highest for the Khoisan Tuu ethnolinguistic group and the Northeast District at 0.9999582029 and 0.9999922652 respectively. CMP ranged from 6.28 x 10-19 (Khoisan Tuu) to 1,02 x 10-18 (Northwest district). Using pairwise genetic distances (FST), analysis of molecular variance (AMOVA), factorial correspondence analysis (FCA), and the unsupervised Bayesian clustering method found in STRUCTURE and landscape genetics software TESS, ethno-linguistics were found to have a greater influence on population structure than geography. FCA showed clustering between Bantu and Khoisan, and within the Bantu. This Bantu sub-structuring was not seen with STRUCTURE and TESS, which detected clustering only between Bantu and Khoisan. The patterns of population structure revealed highlight the need for regional reference databases that include ethno-linguistic and geographic location information. These markers have important potential for bio-anthropological studies as well as for forensic applications.

Study EGAS00001002380

SLCO1B1 Variants and Methotrexate Clearance

Methotrexate plasma concentration is related to its clinical effects. To identify the genetic basis of interindividual variability in methotrexate pharmacokinetics in children with newly diagnosed acute lymphoblastic leukemia (ALL), we performed a genome-wide analysis (GWAS) of 500,568 germline single-nucleotide polymorphisms (SNPs) in 434 children with ALL who received 3,014 courses of methotrexate at 2 to 5 g/m2. SNPs were validated in an independent cohort of 206 patients. Adjusting for age, race, sex, and methotrexate regimen, the most significant associations were with SNPs in the organic anion transporter polypeptide, SLCO1B1 (rs11045879 (P = 1.7 x 10-10) and rs4149081 (P = 1.7 x 10-9) (Trevino et al, PMID: 19901119). To test whether rare variants in SLCO1B1 could alter its function, we genotyped SLCO1B1 exons in a slightly larger group of 699 children with ALL who received methotrexate and identified 93 single nucleotide polymorphisms (SNPs). We found several common and rare non-synonymous (NS) SNPs associated with methotrexate clearance. NS SNPs predicted to be functionally damaging (common or rare) were more likely to be found among patients with the lowest adjusted methotrexate clearance (lowest 10%) than patients with high clearance (highest 10%). Four SLCO1B1 haplotypes were associated with reduced methotrexate clearance and we verified that these haplotypes have lower function with in vitro transport assays. We were able to quantitatively account for a third of the population variability in clearance of methotrexate with clinical and genetic covariates. This data set includes the dependent variable of methotrexate clearance and all of the SNP data available from arrays, sequencing, and genotyping.

Study phs000426

The genomic landscape of pediatric acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer and arises from B- or T-lineage lymphocyte precursors. ALL comprises dozens of subtypes, and genomic analyses have largely been performed within these subtypes. Here we analyze pediatric ALL genomes across all subtypes, including 768 whole genomes, 1,729 exomes, and 1,889 transcriptomes in 2,754 patients. Most ALL subtypes harbor 4 or more driver alterations per sample, similar to adult cancers, despite low mutation burdens. Hyperdiploid B-ALL copy gains are likely acquired early and synchronously, with copy gains occurring before ultraviolet-induced mutations. By contrast, ultraviolet-induced mutations precede copy gains in iAMP21 B-ALL. Overall, we identified 378 putative ALL driver genes. Most driver alterations vary in prevalence across ALL subtypes, with B-ALL enriched for Ras and B-lineage-related alterations, and T-ALL enriched for PI3K, JAK, and cell cycle alterations. Most B-ALL (54.3%) and T-ALL (51.2%) samples bear at least one rare driver gene alteration (present in less than 2% of samples), including 30 putative novel cancer driver genes associated with ubiquitination, SUMOylation, non-coding, and other functions. Known or novel alterations associated with poor outcomes in specific subtypes include TBL1XR1 alterations in ETV6-RUNX1 patients, CREBBP in Ph-like-CRLF2, SETD2 in hyperdiploid, and PTEN in TAL1 patients. Intriguingly, DUX4 and KMT2A subtypes separate into CEBPA/FLT3- or NFATC4-expressing subgroups with potential clinical implications. Together, these results deepen understanding of ALL etiology and outcomes, and facilitate ALL model development.

Study EGAS00001005250

Study on the consequences of prenatal famine exposure on DNA methylation.

The potential of the epigenome to undergo environmentally-induced changes during early development is central to its postulated role in human disease. Here, we report a genome-scale view of DNA methylation differences after early gestational malnutrition that was caused by the Dutch Hunger Winter, a severe famine at the end of World War II. We adopted an annotation guided analysis of reduced-representation bisulfite sequencing data generated in 24 middle-aged individuals who had been exposed to famine in utero and 24 unexposed sibling controls. We observed differential DNA methylation primarily at genomic regions with regulatory potential, including enhancers active during early development. In-depth annotation of 181 prenatally-induced differentially methylated regions (P-DMRs) showed that they were predominantly located in gene bodies and co-occurred with histone marks denoting an active state. In line with the early gestational timing of the exposure, the P-DMRs mapped to genes that were enriched for differential expression patterns during blastocyst development and early organogenesis. Validation and further explorative analyses of 6 P-DMRs mapping to SMAD7, CDH23, INSR, RFTN1, CPT1A and KLF13 highlighted the critical role of gestational timing, indicated that differential methylation extended along pathways involved in growth, development and metabolism, and suggested associations with birth weight and serum LDL cholesterol in adulthood and confirmed an enhancer function for the INSR and CPT1A P-DMRs. Our results point toward a link between prenatal malnutrition and epigenetic modulation of growth and lipid metabolism that may underlie the adverse metabolic phenotype of exposed individuals in later life.

Study EGAS00001000668

Novel optineurin frameshift insertion causing familial frontotemporal dementia and parkinsonism without amyotrophic lateral sclerosis

Frontotemporal Dementia (FTD) is a common cause of Young Onset Dementia and has diverse clinical manifestations involving behaviour, executive function, language and motor function, including parkinsonism. Up to 50% of FTD patients report a positive family history, supporting a strong genetic basis, particularly in cases with both FTD and amyotrophic lateral sclerosis (FTD-ALS). Mutations in three genes are associated with the majority of familial FTD (fFTD) cases - microtubule associated protein tau gene (MAPT), progranulin gene (PGRN), and hexanucleotide repeat expansions in chromosome 9 open reading frame 72 (C9orf72), whilst mutations in other genes such as optineurin (OPTN) have rarely been reported. Mutations in OPTN have been reported mostly in familial and sporadic cases of ALS, or in rare cases of FTD-ALS, but not in association with pure or predominant FTD and/or parkinsonian phenotype. Here, we report for the first time, a family from the Philippines with 4 affected members harbouring the same OPTN frameshift insertion, presenting with FTD-related phenotypes, including one sibling with predominant parkinsonism resembling corticobasal syndrome. Notably, none of the affected members showed any evidence of motor neuron disease or ALS at the time of writing, both clinically and on electrophysiological testing, expanding the phenotypic spectrum of OPTN mutations. Close follow-up of mutation carriers for the development of new clinical features and wider investigation of additional family members with further genetic analyses will be conducted to investigate the possibility of other genetic modifiers in this family which could explain phenotypic heterogeneity.

Study EGAS00001005220

NHLBI TOPMed: Childhood Asthma Management Program (CAMP)

The Childhood Asthma Management Program (CAMP) was designed to evaluate whether continuous, long-term treatment (over a period of four to six years) with either an inhaled corticosteroid (budesonide) or an inhaled noncorticosteroid drug (nedocromil) safely produces an improvement in lung growth as compared with treatment for symptoms only (with albuterol and, if necessary, prednisone, administered as needed). The primary outcome in the study was lung growth, as assessed by the change in forced expiratory volume in one second (FEV1, expressed as a percentage of the predicted value) after the administration of a bronchodilator. Secondary outcomes included the degree of airway responsiveness, morbidity, physical growth, and psychological development.

Study phs001726

scRNAseq analysis of CD8 T cells infiltrating the bladder and tumor of 4 non-muscle-invasive bladder cancer patients, before and after BCG treatment.

We performed scRNAseq analysis of CD8 T cells infiltrating the bladder and tumor of 4 non-muscle-invasive bladder cancer patients, before and after BCG treatment. In order to identify tumor-specific T cells, we selected CD8 T cells that were enriched in the tumor of the patient. We also selected CD8 T cells appearing in the bladder after BCG treatment, with the hypothesis that BCG treatment stimulates tumor-specific CD8 T cells. Next, we cloned the TCR of these T cells in a Jurkat cell line and tested these TCR for recognition of tumor-specific antigens.

Study EGAS50000001384

Extracellular vesicles from TGF-β-activated cancer-associated fibroblasts remodel the tumor microenvironment through EV surface-associated proteins.

In this study, we explored the function of extracellular vesicles (EVs) derived from non-activated cancer-associated fibroblasts (CAFs) and TGF-β-activated CAFs. We tested these two types of EVs on other cell types in the tumor environment, including cancer cells, CD8+ T cells, and CAFs. We further explored the protein cargo in EVs altered by TGF-β treatment using quantitative proteomics, and selected several highly upregulated proteins for further analysis. We found that the majority of these proteins were presented on the EV surface, and they regulated the target cells in an EV-cell contact dependent manner.

Study EGAS50000000922

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