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• Risk Factors for Asymptomatic Diverticulosis

  Data for this analysis came from a prospective study of colonic diverticulosis at the University of North Carolina Hospital in Chapel Hill, North Carolina (NIH R01DK094738). This is a case-control genetic and transcriptomic study to identify the genetic and cellular determinants underlying colonic diverticulosis and the relationship with other gastrointestinal disorders. The study inclusion and exclusion are described below. DNA and RNA sequencing were performed on colonic tissue from 404 patients with (N=172) and without (N=232) diverticulosis. We assessed variation in the transcriptome associated with diverticulosis and integrated this variation with human intestine single-cell RNA-seq data. We integrated our expression quantitative trait loci with GWAS using Mendelian Randomization. A polygenic risk score analysis examined associations between severity of diverticulosis and other gastrointestinal disorders. We identified 38 genes with differential expression and 17 genes with varied transcript usage linked to diverticulosis. Our results suggest tissue remodeling as a primary mechanism for diverticula formation. The presence of diverticulosis was linked to stromal and epithelial cells in the colon including endothelial cells, myofibroblasts, fibroblasts, goblet, tuft, enterocytes, neurons, and glia. MR highlighted five genes including CCN3, CRISPLD2, ENTPD7, PHGR1, and TNFSF13. In diverticulosis cases, ENTPD7 upregulation was confirmed. A greater burden of diverticula was positively correlated with genetic predisposition to diverticulitis. The data related to the study including total RNA-Seq, SNP array and imputed genotypes will be available through dbGaP.

  Study phs003556

• Progress in Diabetes Genetics in Youth (ProDIGY) Exome Sequencing Study: SEARCH for Diabetes in Youth

  The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the SEARCH for Diabetes in Youth cohort was part of the ProDIGY (Progress in Diabetes Genetics in Youth) consortium, which is a NIDDK-funded research consortium that investigated genetic variants for childhood type 2 diabetes (T2D). This consortium involved sequencing multiethnic samples from childhood T2D cases located across the United States. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies table, th, td { border: 1px solid black; border-collapse: collapse; } Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 500 526 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 530 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow up study BioMe Biobank Program (BioMe) US 1297 1256 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1& Follow up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow up study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow up study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmo-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow up study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow up study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 & SIGMAv2 Starr County, Texas US 1762 1738 Hispanic SIGMAv1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMAv1 & v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMAv1 & v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMAv1 & v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multi ethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multi ethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 551 538 South Asian T2D-GENES Project 1 & Follow up study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow up study Pakistan Risk of Myocardial Infarction Study (PROMIS) Pakistan 914 932 The SEARCH study contributed 553 cases and 0 controls to 52k T2D exome sequencing study.

  Study phs001511

• Slim Initiative in Genomic Medicine for the Americas (SIGMA): Diabetes in Mexico Study (DMS)

  The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas: Type 2 Diabetes (SIGMA T2D) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the SIGMA Diabetes in Mexico Study (DMS) was part of the Slim Initiative in Genomic Medicine for the Americas: Type 2 Diabetes (SIGMA T2D), which is an international research consortium funded by the Carlos Slim Foundation that seeks to identify the genetic risk factors for type 2 diabetes (T2D) in Mexico and Latin America and translate those findings into improved treatment and prevention of diabetes. The SIGMA T2D project has sequenced and genotyped more than 13,000 samples from Mexican and Mexican Americans. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGaP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGaP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 500 526 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 530 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow up study BioMe Biobank Program (BioMe) US 1297 1256 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1& Follow up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow up study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow up study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmo-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow up study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow up study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 & SIGMAv2 Starr County, Texas US 1762 1738 Hispanic SIGMAv1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMAv1 & v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMAv1 & v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMAv1 & v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multi ethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multi ethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 & Follow up study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow up study Pakistan Genomic Resource (PGR) Pakistan 914 932 The Diabetes in Mexico Study (DMS) study contributed 1,522 cases and 1,546 controls to the 52k T2D exome sequencing study.

  Study phs001388

• Slim Initiative in Genomic Medicine for the Americas (SIGMA): Mexico City Diabetes Study (MCDS)

  The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas: Type 2 Diabetes (SIGMA T2D) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the SIGMA Mexico City Diabetes Study was part of the Slim Initiative in Genomic Medicine for the Americas: Type 2 Diabetes (SIGMA T2D), which is an international research consortium funded by the Carlos Slim Foundation that seeks to identify the genetic risk factors for type 2 diabetes (T2D) in Mexico and Latin America and translate those findings into improved treatment and prevention of diabetes. The SIGMA T2D project has sequenced and genotyped more than 13,000 samples from Mexican and Mexican Americans. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGaP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGaP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 500 526 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 530 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow up study BioMe Biobank Program (BioMe) US 1297 1256 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1& Follow up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow up study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow up study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmo-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow up study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow up study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 & SIGMAv2 Starr County, Texas US 1762 1738 Hispanic SIGMAv1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMAv1 & v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMAv1 & v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMAv1 & v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multi ethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multi ethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 & Follow up study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow up study Pakistan Genomic Resource (PGR) Pakistan 914 932

  Study phs001375

• Whole-genome methylation profiling of menstrual stem cells identifies novel biomarkers for endometriosis

  Endometriosis, despite its high prevalence, is underdiagnosed and poorly managed due to lack of clinically validated biomarkers and pathophysiological insight. Menstrual bloodderived stem cells (MenSCs) have been implicated in disease pathogenesis, but their diagnostic potential remains unexplored. We conducted a clinical study (n=42; 19 endometriosis, 23 controls) to assess whether DNA methylation profiles of freshly isolated MenSCs can identify disease-specific biomarkers. Whole-genome methylation sequencing revealed differentially methylated regions (DMRs) enriched in genes linked to hallmarks of endometriosis (e.g., inflammation, tissue remodelling, development). These DMRs robustly distinguished cases from controls, independent of technical and clinical variables. Machine learning models trained and validated on these DMRs achieved high diagnostic performance (specificity 83%, sensitivity 79%). Integration with an independent single-cell RNA sequencing dataset showed that the DMRs may modulate gene expression, further supporting their biological relevance. These findings position MenSC DNA methylation profiling as a promising, non-invasive approach for early endometriosis diagnosis and personalised care.

  Dataset EGAD50000002353

• DRIP-seq data for Molecular Characterization of ETMRs

  This dataset contains DRIP-seq data from 2 patients. DNA–RNA hybrids were extracted from tissue derived from ETMR patient-derived xenograft (PDX) models (BT183) that were treated using topotecan or saline as described previously27. Tumours were subsequently frozen and pelleted using ultracentrifugation. DNA–RNA hybrids were extracted as described previously using the same protocol that is applied for cultured cells21. DNA was extracted using proteinase K followed by phenol–chloroform extraction and ethanol precipitation. Subsequently the DNA was fragmented using the restriction enzymes HindIII, EcoRI, BsrGI, XbaI and SspI (New England Biolabs). Digested DNA was subsequently incubated with the anti-DNA–RNA hybrid anti- body S9.6 (Merck, MABE1095) and immunoprecipitated using agarose beads. Bound DNA–RNA hybrids were eluted and incubated with pro- teinase K and cleaned with an additional phenol–chloroform–ethanol extraction. The DNA was subsequently sonicated and sequenced using a Hiseq 2000 machine with a 50-bp single-read protocol. Each treat- ment condition was performed in duplicate and both RNase H and the input was included as negative controls resulting in 10 Fastq files.

  Dataset EGAD00001006219

• Selection of somatic escape variants in SERPINA1 in liver tissue of patients with alpha-1 anti-trypsin deficiency - WGS

  Somatic variants accumulate in non-malignant tissues with age. Functional variants leading to clonal advantage of hepatocytes accumulate in the liver from patients with acquired chronic liver disease (CLD). Whether somatic variants are common to CLD from differing aetiologies is unknown. We analysed liver somatic variants in patients with genetic CLD from alpha-1 anti-trypsin (A1AT) deficiency or haemochromatosis. We show that somatic variants in SERPINA1, the gene encoding A1AT, are strongly selected for in A1AT deficiency, with evidence of convergent evolution. Acquired SERPINA1 variants are clustered leading to truncation or coding change at the C-terminus of A1AT. In vitro and in vivo, C-terminal truncation variants reduce disease-associated Z-A1AT polymer accumulation and disruption of the endoplasmic reticulum, supporting the C-terminal domain swap mechanism. Therefore, somatic escape variants from a deleterious germline variant are selected for in A1AT deficiency, suggesting functional somatic variants are disease-specific in CLD and point to disease-associated mechanisms.

  Dataset EGAD00001015430

• A practical guide for mutational signature analysis in hematological malignancies

  Analysis of mutational signatures is becoming routine in cancer genomics, with implications for pathogenesis, classification, prognosis, and even treatment decisions. However, the field lacks a consensus on analysis and result interpretation. Using whole-genome sequencing of multiple myeloma (MM), chronic lymphocytic leukemia (CLL) and acute myeloid leukemia, we compare the performance of public signature analysis tools. We describe caveats and pitfalls of de novo signature extraction and fitting approaches, reporting on common inaccuracies: erroneous signature assignment, identification of localized hyper-mutational processes, overcalling of signatures. We provide reproducible solutions to solve these issues and use orthogonal approaches to validate our results. We show how a comprehensive mutational signature analysis may provide relevant biological insights, reporting evidence of c-AID activity among unmutated CLL cases or the absence of BRCA1/BRCA2-mediated homologous recombination deficiency in a MM cohort. Finally, we propose a general analysis framework to ensure production of accurate and reproducible mutational signature data.

  Dataset EGAD00001005028

• Selection of somatic escape variants in SERPINA1 in liver tissue of patients with alpha-1 anti-trypsin deficiency - Exome

  Somatic variants accumulate in non-malignant tissues with age. Functional variants leading to clonal advantage of hepatocytes accumulate in the liver from patients with acquired chronic liver disease (CLD). Whether somatic variants are common to CLD from differing aetiologies is unknown. We analysed liver somatic variants in patients with genetic CLD from alpha-1 anti-trypsin (A1AT) deficiency or haemochromatosis. We show that somatic variants in SERPINA1, the gene encoding A1AT, are strongly selected for in A1AT deficiency, with evidence of convergent evolution. Acquired SERPINA1 variants are clustered leading to truncation or coding change at the C-terminus of A1AT. In vitro and in vivo, C-terminal truncation variants reduce disease-associated Z-A1AT polymer accumulation and disruption of the endoplasmic reticulum, supporting the C-terminal domain swap mechanism. Therefore, somatic escape variants from a deleterious germline variant are selected for in A1AT deficiency, suggesting functional somatic variants are disease-specific in CLD and point to disease-associated mechanisms.

  Dataset EGAD00001015431

• Genetic Studies in the Hutterites

  We conducted genetic studies of disease-associated quantitative phenotypes, including microbiome and gene expression studies, and common diseases, such as asthma and Alzheimer's disease, by genotyping and/or sequencing in the Hutterites, a founder population of European descent. The Hutterites who have participated in our studies live on communal farms in South Dakota and are related to each other through multiple lines of descent in a 3,657-person, 13-generation pedigree with 64 founders. The small number of founding genomes reduces genetic heterogeneity whereas their communal lifestyle ensures that non-genetic factors are remarkably uniform between individuals. Our sample includes >1,600 subjects who have participated in our studies of fertility (since 1982), asthma, cardiovascular disease and other complex phenotypes (since 1993), microbiome studies (since 2011), and/or immune response (since 2012). The variable 'Total number of consented subjects' reflects the count of subjects with individual level phenotype and genotype data in dbGaP.

  Study phs000185