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• Genomic platform specific polygenic risk scores impact breast cancer risk stratification

  Background: At present, there is no consensus on which genotyping platform should serve as the standard for clinical polygenic risk score (PRS) implementation. Previous studies have compared the overall performance and concordance of different genotyping and sequencing technologies; however, these analyses have generally averaged the results over the whole genome. We evaluated differences in a 313-variant breast cancer PRS (PRS313) across genomic platforms and their impact on risk stratification. Methods: We compare PRS313 derived from genotyping arrays (Global Screening Array [GSA], OncoArray-500K [OncoArray], Global Diversity Array [GDA], custom Axiom_PrecipV1 array [ThermoFisher]) and low-coverage genome sequencing (lc-WGS) in 2 cell lines and 92 individuals. Probes are designed for all variants on ThermoFisher (success rate: 259/313). Sanger sequencing profiles indels. Concordance of high-risk classification (PRS313scoresum > 0.6) across platforms is assessed using Kappa statistics. Results: In saliva samples, indel concordance with Sanger sequencing varies widely (Kappa: 0.007-1.000). PRS313-ThermoFisher is predictable from other platforms using linear models, despite systematic differences. Greater agreement is observed between arrays with high imputation overlap (e.g., GDA ~ GSA slope=0.986). Agreement in high-risk classification before mean correction is moderate (Fleiss's Kappa=0.552) and improves after mean correction (Kappa=0.650). Arrays with similar designs show higher agreement before mean correction (Kappa=0.745). Mean correction narrows high-risk proportions from 4-45% to 15-21%. Overall, 26 of 92 samples are classified as high risk on at least one platform, but only 7 are high risk across all. When restricting to identical variants across all platforms for PRS313 calculation, the corresponding number of high-risk individuals are 24 and 11. Conclusion: Our findings demonstrate that platform-specific variability can influence PRS313 estimates to potentially reclassify individuals around clinically relevant thresholds.

  Study EGAS00001008439

• Genetic analysis of HLA and immune escape genes in Diffuse Large B-cell Lymphoma

  Fifty percent of diffuse large B-cell lymphoma (DLBCL) cases lack cell-surface expression of the class-I major histocompatibility complex (MHC-I), thereby escaping immune recognition by cytotoxic T cells. In order to comprehensively identify the mechanisms involved in MHC-I loss, we first performed immunophenotypic analysis of both MHC class-I and -II in 657 cases across the spectrum of B-NHL, revealing that loss of MHC-I, but not MHC-II, is preferentially restricted to DLBCL. We then used whole exome and targeted deep-sequencing to examine genes involved in MHC-I expression in 74 DLBCL samples representative of MHC-I positive and negative cases. We show here that somatic biallelic or monoallelic inactivation of B2M and/or HLA-I is present in 80.9% (34/42) of MHC-I negative tumors. Furthermore, 68.8% (22/32) of MHC-I positive DLBCLs also harbored monoallelic HLA-I genetic alterations (MHC-I positivemono) that lead to allelic imbalance, suggesting allele-specific inactivation. Both MHC-I negative and MHC-I positivemono cases showed a significantly higher mutational burden as well as a higher number of inferred neo-antigens, suggesting co-selection of HLA-I loss and sustained neo-antigen production. Interestingly, the analysis of > 500.000 individuals in two databases revealed homozygosity of germline HLA-I genes in 26-38% of DLBCL patients, a frequency significantly higher than that observed in any other cancer type. In mice, germinal-center B cells lacking HLA-I expression did not progress to lymphoma and were counterselected in the context of oncogene-driven lymphomagenesis, suggesting that additional events are needed to license immune evasion. These results suggest a multi-step process of HLA-I loss including both germ-line and somatic events in DLBCL development, and have direct implications for the pathogenesis and immunotherapeutic targeting of this disease.

  Study EGAS00001005054

• Target sequencing of 27 cancer-predisposing genes and 13 renal cell carcinoma-related genes in Japanese renal cell carcinoma patients

  Identifying causative genes via genetic testing is useful for the screening, prevention, and treatment of cancer. Several hereditary syndromes are known to occur in renal cell carcinoma (RCC). However, these evidences came from the European population; it remains unclear how the RCC-related genes and other cancer-predisposing genes contribute to the development RCC in the Japanese population. A case-control study of 14 RCC-related genes and 26 cancer-predisposing genes was performed using 1,563 Japanese patients with RCC and 6,016 controls. Patients were divided into two major histological subtypes of clear cell RCC (ccRCC) or non-clear cell RCC (nccRCC). Gene-based analysis of germline pathogenic variants in patients with each subtype and cancer-free subjects was performed. Following quality control, 1,532 patients with RCC and 5,996 controls were further analyzed. For ccRCC, 52 of 1,283 (4.05%) patients carried pathogenic variants mainly in the cancer-predisposing genes such as TP53 (P = 1.73 �� 10-4; OR, 5.8; 95% CI, 2.2���15.7). Approximately 80% of patients with pathogenic variants in TP53 had p.Ala189Val that was specific in East Asian population. For nccRCC, 14 of 249 (5.62%) patients carried pathogenic variants mainly in the RCC-related genes such as BAP1 (P = 6.27 �� 10-5; OR, Inf; 95% CI, 10.0���Inf), and FH (P = 6.27 �� 10-5; OR, Inf; 95% CI, 10.0���Inf). Our study showed different and population-specific contributions of risk genes between ccRCC and nccRCC in Japanese for better-personalized medicine.

  Study JGAS000414

• A Phase I/II Trial of Sirolimus (Rapamune®) and Cyclosporine in Patients with Refractory Aplastic Anemia

  The most successful treatment for aplastic anemia is bone marrow transplantation. However, few patients are eligible for this procedure. For others, treatment usually consists of immunosuppressive agents, such as antithymocyte globulin (ATG) and cyclosporine. Unfortunately, even with immunosuppressive therapy, relapse is common. New combinations of medications may offer alternative and more effective treatment options. Sirolimus and cyclosporine are two drugs routinely used to suppress the immune system and prevent rejection in patients who have received organ transplants. While cyclosporine has been proven effective for treating aplastic anemia, sirolimus has not been tested for this disease. This study will evaluate the safety and efficacy of sirolimus in combination with cyclosporine for treating individuals with aplastic anemia that have not responded to other treatments. This study will last at least 6 months. Participants will first be screened to verify diagnosis of aplastic anemia. The screening will include a physical examination, blood test, bone marrow biopsy from the pelvic bone, and review of medications and medical history. Individuals who are eligible will then start the first treatment period. Participants will receive two medications: cyclosporine will be taken twice a day and sirolimus will be taken once a day. Depending on side effects, the dose of either drug may be temporarily stopped or lowered. On Day 1, blood will be drawn and females will undergo a pregnancy test. Subsequent study visits will occur weekly for the first month, every 2 weeks for 2 months, and then once a month for the remainder of the study. Each visit will include a physical examination, vital sign assessment, and review of side effects and medications. Blood tests will be performed weekly for the first 3 weeks, and then every 2 weeks. After 6 months of treatment, if a participant has shown improvements in disease status without major side effects, the treatment will continue. Over time the doses may be lowered. If a participant has not improved while on the study medication, treatment will stop at 6 months. Whenever treatment is discontinued, the participant will again undergo a physical examination, blood tests, and bone marrow biopsy.

  Study phs000695

• Clonal selection after gene therapy in sickle cell disease

  While gene therapy (GT) provides a potentially curative treatment option for patients with sickle cell disease (SCD), the occurrence of myeloid malignancies in clinical trials has prompted concern. To interrogate potential mechanisms underlying increased cancer risk, we used hematopoietic stem cell (HSC) clonal tracking by whole genome sequencing (WGS) to map the somatic mutation and clonal landscape of 2,592 gene modified as well as unmodified single stem and progenitor cells from six SCD patients undergoing gene therapy (7-26 years old, average 12.7× depth). Pre-GT phylogenetic trees in SCD were highly polyclonal and mutation burdens per cell were elevated in some, but not all, patients. Post-GT, no clonal expansions were identified. However, an increased frequency of driver mutations associated with myeloid neoplasms or clonal hematopoiesis (DNMT3A- and EZH2-mutated clones in particular) were seen in both genetically modified and unmodified cells suggested positive selection of mutant clones during gene therapy. This work sheds light on the mutation landscape and HSC clonal dynamics in gene therapy for SCD and highlights enhanced fitness of some HSCs harboring pre-existing driver mutations following gene therapy. Future studies should define the long-term fate of mutant clones including any contribution to expansions associated with myeloid neoplasms.

  Dataset EGAD00001010914

• National Sleep Research Resource (NSRR): Cleveland Family Study (CFS)

  The Cleveland Family Study (CFS) is a family-based study of sleep apnea, consisting of 2,284 individuals (46% African American) from 361 families studied on up to 4 occasions over a period of 16 years. The study began in 1990 with the initial aims of quantifying the familial aggregation of sleep apnea. National Institutes of Health (NIH) renewals provided expansion of the original cohort, including increased minority recruitment, and longitudinal follow-up, with the last exam occurring in February 2006. The CFS was designed to provide fundamental epidemiological data on risk factors for sleep disordered breathing (SDB). The sample was selected by identifying affected probands who had laboratory diagnosed obstructive sleep apnea. All first-degree relatives, spouses and available second-degree relatives of affected probands were studied. In addition, during the first 5 study years, neighborhood control families were identified through a neighborhood proband, and his/her spouses and first-degree relatives. Each exam, occurring at approximately 4-year intervals, included new enrollment as well as follow up exams for previously enrolled subjects. For the first three visits, data, including an overnight sleep study, were collected in participants' homes while the last visit occurred in a general clinical research center (GCRC). Phenotypic characterization of the entire cohort included overnight sleep apnea studies, blood pressure, spirometry, anthropometry and questionnaires. Currently, data of 710 individuals are available for use through BioData Catalyst (with genotype data available through dbGaP).The National Sleep Research Resource (NSRR) is a NIH-supported sleep data repository that offers free access to large collections of de-identified physiological signals and related clinical data from a large range of cohort studies, clinical trials and other data sources from children and adults, including healthy individuals from the community and individuals with known sleep or other health disorders. The goals of NSRR are to facilitate rigorous research that requires access to large or more diverse data sets, including raw physiological signals, to promote a better understanding of risk factors for sleep and circadian disorders and/or the impact of sleep disturbances on health-related outcomes. Data from over 15 data sources and more than 40,000 individual sleep studies, many linked to dozens if not hundreds of clinical data elements, are available (as of Feb. 2022). Query tools are available to identify variables of interest, and their meta-data and provenance.

  Study phs002715

• NHLBI TOPMed: San Antonio Family Heart Study (SAFHS)

  The San Antonio Family Heart Study (SAFHS) is a complex pedigree-based mixed longitudinal study designed to identify low frequency or rare variants influencing susceptibility to cardiovascular disease, using whole genome sequence (WGS) information from 2,590 individuals in large Mexican American pedigrees from San Antonio, Texas. The major objectives of this study are to identify low frequency or rare variants in and around known common variant signals for CVD, as well as to find novel low frequency or rare variants influencing susceptibility to CVD. WGS of the SAFHS cohort has been obtained through three efforts. Approximately 540 WGS were performed commercially at 50X by Complete Genomics, Inc (CGI) as part of the large T2D-GENES Project. The phenotype and genotype data for this group is available at dbGaP under accession number phs000462. An additional ~900 WGS at 30X were obtained through Illumina as part of the R01HL113322 "Whole Genome Sequencing to Identify Causal Genetic Variants Influencing CVD Risk" project. Finally, ~1,150 WGS at 30X WGS were obtained through Illumina funded by a supplement as part of the NHLBI's TOPMed program. Extensive phenotype data are provided for sequenced individuals primarily obtained from the P01HL45522 "Genetics of Atherosclerosis in Mexican Americans" for adults and R01HD049051 for children in these same families. Phenotype information was collected between 1991 and 2016. For this dataset, the SAFHS appellation represents an amalgamation of the original SAFHS participants and an expansion that reexamined families previously recruited for the San Antonio Family Diabetes Study (R01DK042273) and the San Antonio Family Gall Bladder Study (R01DK053889). Due to this substantial examination history, participants may have information from up to five visits. The clinical variables reported are coordinated with TOPMed and include major adverse cardiac events (MACE), T2D status and age at diagnosis, glycemic traits (fasting glucose and insulin), blood pressure, blood lipids (total cholesterol, HDL cholesterol, calculated LDL cholesterol and triglycerides). Additional phenotype data include the medication status at each visit, classified in four categories as any current use of diabetes, hypertension or lipid-lowering medications, and, for females, current use of female hormones. Anthropometric measurements include age, sex, height, weight, hip circumference, waist circumference and derived ratios. PBMC derived gene expression assays for a subset of ~1,060 individuals obtained using the Illumina Sentrix-6 chip is also available from the baseline examination. The WGS data have been jointly called and are available in the current TOPMed accession (phs001215).

  Study phs001215

• Alzheimer's Disease Sequencing Project (ADSP)

  NOTICE OF CHANGE IN LOCATION FOR ALZHEIMER'S DISEASE SEQUENCING PROJECT (ADSP) GENETIC AND PHENOTYPIC DATA: ADSP whole exome and whole genome sequence data that are shared through dbGaP were mapped to the Genome Reference Consortium human genome GRCh37 (build 37). These data are from the Discovery Phase of the project (described below) and will continue to be available at this site. Please see the ADSP Design page for the complete study description. All data that are mapped to GRCh38 (hg38) are being shared through the NIA Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) Data Sharing Service (DSS). For instructions on how access the ADSP Build 38 data that are shared through NIAGADS DSS, visit the Application Instructions page. STUDY DESCRIPTION FOR dbGaP BUILD 37 ADSP DATA: The overarching goals of the Alzheimer's Disease Sequencing Project (ADSP) are to: (1) identify new genomic variants contributing to increased risk of developing Alzheimer's Disease (AD), (2) identify new genomic variants contributing to protection against developing AD, and (3) provide insight as to why individuals with known risk factor variants escape from developing AD. These factors will be studied in multi-ethnic populations in order to identify new pathways for disease prevention. Such a study of human genomic variation and its relationship to health and disease requires examination of a large number of study participants and needs to capture information about common and rare variants (both single nucleotide and copy number) in well phenotyped individuals. Using existing samples from NIH funded and other studies, three NHGRI funded Large Scale Sequencing and Analysis Centers (LSAC) - Broad, Baylor, and Washington University - produced the DNA sequence data. Variant call data are being made available to the scientific community through NIH-approved data repositories. Statistical analysis of the sequence data is anticipated to identify new genetic risk and protective factors. The ADSP will conduct and facilitate analysis of sequence data to extend previous discoveries that may ultimately result in new directions for AD therapeutics. Analysis of ADSP data will be done in two phases. The Discovery Phase analysis (2014-2018) is funded under PAR-12-183. The entire Discovery dataset contains whole-genome sequencing data on 584 subjects from 113 families, and pedigree data for > 4000 subjects; whole exome sequencing data on 5096 cases 4965 controls; and whole exome sequence data on an additional 853 (682 Cases [510 Non-Hispanic, 172 Hispanic]), and 171 Hispanic Control subjects from families that are multiply affected with AD. The Replication Phase (2016-2021) analysis will be funded under RFA-AG-16-001 and RFA-AG-16-002 and is expected to include a combination of genotyping and sequencing approaches on at least 30,000 subjects. Targeted sequencing will be done by the LSACs. GRCh37 Data Releases The first ADSP data release occurred on November 25, 2013. It included the whole-genome sequencing data in BAM file format on 410 individuals. The second ADSP data release occurred on March 31, 2014, and included the whole-genome sequencing data in BAM file format for an additional 168 individuals. The third ADSP data release occurred on November 03, 2014 and included whole-exome sequencing data in BAM file format for 10,939 individuals. The fourth ADSP data release occurred on February 13, 2015 and included revised ethnic data for subjects with whole-exome sequencing data. The fifth ADSP data release occurred on July 13, 2015 and included whole-genome genotypes and updated phenotypes as well as changes to pedigree structures and sample IDs. The sixth ADSP data release occurred on December 8, 2015, and included whole-exome genotypes and updated phenotypes as well as changes to subject IDs. This seventh ADSP data release on April 12, 2016 includes: (1) WES and WGS SNV VCF files (2) WES and WGS Indel PLINK files ADSP Data Available through dbGaP: ADSP - Whole Genome Sequencing ADSP - Whole Exome Sequencing Comments DNA-Seq (BAM) n=578 n=10913 Sequence data available (plus n=38 replications w/out genotype data) Concordant SNV Genotypes (PLINK format) N/A n=10913 QC'ed genotypes that are concordant between the Atlas (Baylor's) and GATK (Broad's) calling pipelines (a subset of the consensus genotype set) Consensus Genotypes (PLINK and VCF format) n=578 n=10913 QC'ed genotypes that are concordant between Atlas and GATK pipelines as well as those that that were called uniquely by Atlas or GATK Concordant Indel Genotypes (PLINK format) n=578 n=10913 QC'ed genotypes that are concordant between the Atlas and GATK calling pipelines Phenotype Data n=4735 n=10913 Data of n=53 phenotype variables available (plus administrative data), including APOE genotype. WGS phenotypes include data of connecting family members. Please use the release notes provided by dbGaP to obtain detailed information about study release updates. The ADSP data portal provides a customized interface for users to quickly identify and retrieve files by covariates, phenotypes, and data properties such as sequencing facility or coverage. For more information about the ADSP study and the data portal, please visit https://www.niagads.org/adsp/.

  Study phs000572

• Low mutation burden and frequent loss of CDKN2A/B and SMARCA2, but not PRC2, define pre-malignant neurofibromatosis type 1-associated atypical neurofibromas

  Neurofibromatosis type 1 (NF1) is a tumor-predisposition disorder caused by germline mutations in NF1. NF1 patients have an 8-16% lifetime risk of developing a malignant peripheral nerve sheath tumor (MPNST), a highly aggressive soft-tissue sarcoma, often arising from pre-existing benign plexiform neurofibromas (PN) and atypical neurofibromas (ANF). ANF are distinct from both PN and MPNST, representing an intermediate step in malignant transformation. In the first comprehensive genomic analysis of ANF, we performed tumor/normal exome sequencing (ES) of 16 ANFs. In addition, we conducted ES of three MPNSTs, copy-number meta-analysis of 26 ANF and 28 MPNST, and whole transcriptome RNA-seq analysis of five ANF and five MPNST. We identified low mutation burden (median 1, range 0-5) in the exomes of ANF (only NF1 somatic mutations were recurrent), and frequent deletions of CDKN2A/CDKN2B (69%) and SMARCA2(42%) loci. We determined that polycomb repressor complex 2 (PRC2) genes EED or SUZ12 were frequently mutated, deleted or downregulated in MPNST but not in ANF. Our gene expression study revealed upregulated NRAS, MDM2, CCND1/CCND2/CCND3 and CDK4/CDK6 in both ANF and MPNST, and overexpression of EZH2 in MPNST only. We conclude that the PN-ANF transition is primarily driven by the deletion of CDKN2A/CDKN2B in addition to already present inactivated NF1. Further progression from ANF to MPNST likely involves broad chromosomal rearrangements and frequent inactivation of the PRC2 genes, loss of the DNA repair genes, and copy-number increase of signal transduction, cell cycle and pluripotency self-renewal genes.

  Study phs001993

• Recurrent somatic DICER1 mutations in non-epithelial ovarian tumors

  Background: Germline truncating mutations in DICER1, an RNase III-type endoribonuclease essential for processing of microRNAs, are seen in families with the pleuropulmonary blastoma-family tumor and dysplasia syndrome; these individuals have a propensity to develop non-epithelial ovarian tumors (i.e. sex-cord stromal and germ cell tumors). Methods: We sequenced the whole transcriptomes or exomes of 14 non-epithelial ovarian tumors and noted closely clustered mutations in the RNase IIIb domain of DICER1 in four cases. Using Sanger sequencing, we then analyzed additional ovarian tumors for mutations in this region. The impact of the mutations on the enzymatic activity of Dicer1 was determined using in vitro RNA cleavage assays. Results: RNase IIIb domain DICER1 mutations were found in 30/102 non-epithelial ovarian tumors (29%), predominantly Sertoli-Leydig cell tumors (26/43, 60%), including 4/4 from individuals with germline DICER1 mutations. The mutations were restricted to metal binding sites within the RNase IIIb catalytic centres critical for miRNA interaction and cleavage, and were somatic in all 14 cases where germline DNA was available for testing. Of 266 epithelial ovarian and endometrial cancers tested, one case, an ovarian carcinosarcoma, had a hotspot mutation. In vitro, the mutant DICER proteins showed reduced RNase IIIb activity but retained RNase IIIa activity. Conclusions: Somatic missense mutations of the RNase IIIb domain of DICER1 are common in non-epithelial ovarian tumors. Genetic, pathologic, and functional evidence suggest that these mutations do not obliterate DICER1 function, rather, they alter it in specific cell types, a novel mechanism through which perturbed microRNA expression is oncogenic.

  Study EGAS00001000135