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1. Harmonizing Outcomes for Genomic Medicine: Comparison of eMERGE Outcomes to ClinGen Outcome/Intervention Pairs

Author

Janet L. Williams, Wendy K. Chung, Alex Fedotov, Krzysztof Kiryluk, Chunhua Weng, John J. Connolly, Margaret Harr, Hakon Hakonarson, Kathleen A. Leppig, Eric B. Larson, Gail P. Jarvik, David L. Veenstra, Christin Hoell, Maureen E. Smith, Ingrid A. Holm, Josh F. Peterson, and Marc S. Williams

Subjects
genomics, genomic medicine, health outcomes, evidence, standards, eMERGE, ClinGen, precision public health, Medicine
Abstract

Genomic medicine is moving from research to the clinic. There is a lack of evidence about the impact of genomic medicine interventions on health outcomes. This is due in part to a lack of standardized outcome measures that can be used across different programs to evaluate the impact of interventions targeted to specific genetic conditions. The eMERGE Outcomes working group (OWG) developed measures to collect information on outcomes following the return of genomic results to participants for several genetic disorders. These outcomes were compared to outcome intervention pairs for genetic disorders developed independently by the ClinGen Actionability working group (AWG). In general, there was concordance between the defined outcomes between the two groups. The ClinGen outcomes tended to be from a higher level and the AWG scored outcomes represented a subset of outcomes referenced in the accompanying AWG evidence review. eMERGE OWG outcomes were more detailed and discrete, facilitating a collection of relevant information from the health records. This paper demonstrates that common outcomes for genomic medicine interventions can be identified. Further work is needed to standardize outcomes across genomic medicine implementation projects and to make these publicly available to enhance dissemination and assist in making precision public health a reality.

Published
2018
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2. Neptune: an environment for the delivery of genomic medicine

Author

Venner Eric, Victoria Yi, David Murdock, Sara E. Kalla, Tsung-Jung Wu, Aniko Sabo, Shoudong Li, Qingchang Meng, Xia Tian, Mullai Murugan, Michelle Cohen, Christie Kovar, Wei-Qi Wei, Wendy K. Chung, Chunhua Weng, Georgia L. Wiesner, Gail P. Jarvik, Donna Muzny, Richard A. Gibbs, Debra Abrams, Samuel E. Adunyah, Ladia Albertson-Junkans, Berta Almoguera, Darren C. Ames, Paul Appelbaum, Samuel Aronson, Sharon Aufox, Lawrence J. Babb, Adithya Balasubramanian, Hana Bangash, Melissa Basford, Lisa Bastarache, Samantha Baxter, Meckenzie Behr, Barbara Benoit, Elizabeth Bhoj, Suzette J. Bielinski, Sarah T. Bland, Carrie Blout, Kenneth Borthwick, Erwin P. Bottinger, Mark Bowser, Harrison Brand, Murray Brilliant, Wendy Brodeur, Pedro Caraballo, David Carrell, Andrew Carroll, Lisa Castillo, Victor Castro, Gauthami Chandanavelli, Theodore Chiang, Rex L. Chisholm, Kurt D. Christensen, Wendy Chung, Christopher G. Chute, Brittany City, Beth L. Cobb, John J. Connolly, Paul Crane, Katherine Crew, David R. Crosslin, Jyoti Dayal, Mariza De Andrade, Jessica De la Cruz, Josh C. Denny, Shawn Denson, Tim DeSmet, Ozan Dikilitas, Michael J. Dinsmore, Sheila Dodge, Phil Dunlea, Todd L. Edwards, Christine M. Eng, David Fasel, Alex Fedotov, Qiping Feng, Mark Fleharty, Andrea Foster, Robert Freimuth, Christopher Friedrich, Stephanie M. Fullerton, Birgit Funke, Stacey Gabriel, Vivian Gainer, Ali Gharavi, Andrew M. Glazer, Joseph T. Glessner, Jessica Goehringer, Adam S. Gordon, Chet Graham, Robert C. Green, Justin H. Gundelach, Heather S. Hain, Hakon Hakonarson, Maegan V. Harden, John Harley, Margaret Harr, Andrea Hartzler, M. Geoffrey Hayes, Scott Hebbring, Nora Henrikson, Andrew Hershey, Christin Hoell, Ingrid Holm, Kayla M. Howell, George Hripcsak, Jianhong Hu, Elizabeth Duffy Hynes, Joy C. Jayaseelan, Yunyun Jiang, Yoonjung Yoonie Joo, Sheethal Jose, Navya Shilpa Josyula, Anne E. Justice, Divya Kalra, Elizabeth W. Karlson, Brendan J. Keating, Melissa A. Kelly, Eimear E. Kenny, Dustin Key, Krzysztof Kiryluk, Terrie Kitchner, Barbara Klanderman, Eric Klee, David C. Kochan, Viktoriya Korchina, Leah Kottyan, Emily Kudalkar, Alanna Kulchak Rahm, Iftikhar J. Kullo, Philip Lammers, Eric B. Larson, Matthew S. Lebo, Magalie Leduc, Ming Ta (Michael) Lee, Niall J. Lennon, Kathleen A. Leppig, Nancy D. Leslie, Rongling Li, Wayne H. Liang, Chiao-Feng Lin, Jodell E. Linder, Noralane M. Lindor, Todd Lingren, James G. Linneman, Cong Liu, Wen Liu, Xiuping Liu, John Lynch, Hayley Lyon, Alyssa Macbeth, Harshad Mahadeshwar, Lisa Mahanta, Bradley Malin, Teri Manolio, Maddalena Marasa, Keith Marsolo, Michelle L. McGowan, Elizabeth McNally, Jim Meldrim, Frank Mentch, Hila Milo Rasouly, Jonathan Mosley, Shubhabrata Mukherjee, Thomas E. Mullen, Jesse Muniz, David R. Murdock, Shawn Murphy, Melanie F. Myers, Bahram Namjou, Yizhao Ni, Robert C. Onofrio, Aniwaa Owusu Obeng, Thomas N. Person, Josh F. Peterson, Lynn Petukhova, Cassandra J. Pisieczko, Siddharth Pratap, Cynthia A. Prows, Megan J. Puckelwartz, Ritika Raj, James D. Ralston, Arvind Ramaprasan, Andrea Ramirez, Luke Rasmussen, Laura Rasmussen-Torvik, Soumya Raychaudhuri, Heidi L. Rehm, Marylyn D. Ritchie, Catherine Rives, Beenish Riza, Dan M. Roden, Elisabeth A. Rosenthal, Avni Santani, Schaid Dan, Steven Scherer, Stuart Scott, Aaron Scrol, Soumitra Sengupta, Ning Shang, Himanshu Sharma, Richard R. Sharp, Rajbir Singh, Patrick M.A. Sleiman, Kara Slowik, Joshua C. Smith, Maureen E. Smith, Duane T. Smoot, Jordan W. Smoller, Sunghwan Sohn, Ian B. Stanaway, Justin Starren, Mary Stroud, Jessica Su, Casey Overby Taylor, Kasia Tolwinski, Sara L. Van Driest, Sean M. Vargas, Matthew Varugheese, David Veenstra, Eric Venner, Miguel Verbitsky, Gina Vicente, Michael Wagner, Kimberly Walker, Theresa Walunas, Liwen Wang, Qiaoyan Wang, Scott T. Weiss, Quinn S. Wells, Peter S. White, Ken L. Wiley, Janet L. Williams, Marc S. Williams, Michael W. Wilson, Leora Witkowski, Laura Allison Woods, Betty Woolf, Julia Wynn, Yaping Yang, Ge Zhang, Lan Zhang, and Hana Zouk

Subjects
Computer science, business.industry, Process (engineering), MEDLINE, High-Throughput Nucleotide Sequencing, Genomics, Data science, Article, Personalization, Variety (cybernetics), Workflow, Neptune, Pharmacogenomics, Health care, Electronic Health Records, Humans, business, Software, Genetics (clinical)
Abstract

Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune .

Published
2021

3. Genome-wide polygenic score to predict chronic kidney disease across ancestries

Author

Atlas Khan, Michael C. Turchin, Amit Patki, Vinodh Srinivasasainagendra, Ning Shang, Rajiv Nadukuru, Alana C. Jones, Edyta Malolepsza, Ozan Dikilitas, Iftikhar J. Kullo, Daniel J. Schaid, Elizabeth Karlson, Tian Ge, James B. Meigs, Jordan W. Smoller, Christoph Lange, David R. Crosslin, Gail P. Jarvik, Pavan K. Bhatraju, Jacklyn N. Hellwege, Paulette Chandler, Laura Rasmussen Torvik, Alex Fedotov, Cong Liu, Christopher Kachulis, Niall Lennon, Noura S. Abul-Husn, Judy H. Cho, Iuliana Ionita-Laza, Ali G. Gharavi, Wendy K. Chung, George Hripcsak, Chunhua Weng, Girish Nadkarni, Marguerite R. Irvin, Hemant K. Tiwari, Eimear E. Kenny, Nita A. Limdi, and Krzysztof Kiryluk

Subjects
Multifactorial Inheritance, Genotype, General Medicine, Apolipoprotein L1, Polymorphism, Single Nucleotide, Article, General Biochemistry, Genetics and Molecular Biology, Gene Frequency, Risk Factors, Humans, Genetic Predisposition to Disease, Renal Insufficiency, Chronic, Alleles, Genome-Wide Association Study
Abstract

Chronic kidney disease (CKD) is a common complex condition associated with high morbidity and mortality. Polygenic prediction could enhance CKD screening and prevention; however, this approach has not been optimized for ancestrally diverse populations. By combining APOL1 risk genotypes with genome-wide association studies (GWAS) of kidney function, we designed, optimized and validated a genome-wide polygenic score (GPS) for CKD. The new GPS was tested in 15 independent cohorts, including 3 cohorts of European ancestry (n = 97,050), 6 cohorts of African ancestry (n = 14,544), 4 cohorts of Asian ancestry (n = 8,625) and 2 admixed Latinx cohorts (n = 3,625). We demonstrated score transferability with reproducible performance across all tested cohorts. The top 2% of the GPS was associated with nearly threefold increased risk of CKD across ancestries. In African ancestry cohorts, the APOL1 risk genotype and polygenic component of the GPS had additive effects on the risk of CKD.

Published
2021

4. Harmonizing Clinical Sequencing and Interpretation for the eMERGE III Network

Author

Ian B. Stanaway, Dan M. Roden, Divya Kalra, Dustin Key, Debra J. Abrams, David Fasel, Victor Castro, Brad Malin, Berta Almoguera, Beenish Riza, Meckenzie A. Behr, Eric Venner, Christine M. Eng, Joy Jayaseelan, Scott J. Hebbring, Michelle L. McGowan, Steven E. Scherer, Theresa L. Walunas, Mark Bowser, James D. Ralston, Wei-Qi Wei, Liwen Wang, David R. Murdock, Wayne H. Liang, Julia Wynn, Nancy D. Leslie, Laura J. Rasmussen-Torvik, Ming Ta (Michael) Lee, Frank D. Mentch, Lan Zhang, Alanna Kulchak Rahm, Josh F. Peterson, Jodell E. Linder, Joshua C. Smith, Soumitra Sengupta, Brendan J. Keating, Gina Vicente, Andrew Carroll, Nora B. Henrikson, Anne E. Justice, Heather S. Hain, Wen Liu, Andrea H. Ramirez, Matthew S. Lebo, Hana Zouk, Georgia L. Wiesner, Andrea L. Hartzler, Cassandra J. Pisieczko, Catherine M. Rives, Jessica Goehringer, Maegan V. Harden, John Lynch, Chiao-Feng Lin, Peter White, Phil Dunlea, Shawn N. Murphy, Mullai Murugan, Harshad Mahadeshwar, Mark Fleharty, Andrea Foster, Arvind Ramaprasan, Christopher A. Friedrich, Justin H. Gundelach, Hayley Lyon, Niall J. Lennon, Eric W. Klee, David R. Crosslin, Ge Zhang, Rongling Li, Ozan Dikilitas, Xiuping Liu, Christin Hoell, Aniwaa Owusu Obeng, Katherine D. Crew, Lisa M. Castillo, Justin Starren, Jonathan D. Mosley, Carrie L. Blout, Himanshu Sharma, Elizabeth M. McNally, Sarah T. Bland, Megan J. Puckelwartz, Matthew Varugheese, Keith Marsolo, Betty Woolf, Sharon Aufox, Janet L. Williams, Kimberly Walker, Murray H. Brilliant, Birgit Funke, Laura Allison Woods, Marylyn D. Ritchie, Brittany City, Todd Lingren, Hila Milo Rasouly, Lawrence J. Babb, Alex Fedotov, Robert C. Onofrio, Margaret Harr, Suzette J. Bielinski, Michael W. Wilson, Shubhabrata Mukherjee, Robert R. Freimuth, Chet Graham, Todd L. Edwards, Quinn S. Wells, Marc S. Williams, Jordan W. Smoller, Wendy K. Chung, Avni Santani, Paul K. Crane, George Hripcsak, QiPing Feng, Ali G. Gharavi, Yizhao Ni, Iftikhar J. Kullo, Michael Wagner, Philip E. Lammers, Michael J. Dinsmore, Thomas N. Person, Victoria Yi, Samuel E. Adunyah, Tim DeSmet, Eric B. Larson, Elizabeth Hynes, David C. Kochan, Eimear E. Kenny, Magalie S. Leduc, Lisa Mahanta, David Carrell, Paul S. Appelbaum, Viktoriya Korchina, Beth L. Cobb, Lynn Petukhova, Jessica De la Cruz, Patrick M. A. Sleiman, Stuart A. Scott, Tsung-Jung Wu, Gail P. Jarvik, Erwin P. Bottinger, Ken Wiley, Josh C. Denny, Melissa A. Basford, Samuel J. Aronson, David L. Veenstra, Yaping Yang, Kayla Marie Howell, John J. Connolly, Jessica Su, Yoonjung Yoonie Joo, Miguel Verbitsky, Sean M. Vargas, Cong Liu, Barbara Benoit, Andrew Hershey, Richard A. Gibbs, Cynthia A. Prows, Hana Bangash, Wendy Brodeur, Gauthami Chandanavelli, Sara L. Van Driest, Kurt D. Christensen, Elizabeth J. Bhoj, Vivian S. Gainer, Adam S. Gordon, Robert C. Green, Hakon Hakonarson, Krzysztof Kiryluk, Elisabeth A. Rosenthal, Rajbir Singh, James G. Linneman, Harrison Brand, Theodore Chiang, Sheila Dodge, Ingrid A. Holm, M. Geoffrey Hayes, Yunyun Jiang, Ning Shang, Samantha Baxter, Noralane M. Lindor, Kathleen A. Leppig, Teri A. Manolio, Sara E. Kalla, Pedro J. Caraballo, Ritika Raj, Aaron Scrol, Jyoti G. Dayal, Richard R. Sharp, Christie Kovar, Soumya Raychaudhuri, Sunghwan Sohn, Emily Kudalkar, Maddalena Marasa, Stacey Gabriel, Dan Schaid, Ladia Albertson-Junkans, Rex L. Chisholm, Maureen E. Smith, Donna M. Muzny, Casey Overby Taylor, Jianhong Hu, Elizabeth W. Karlson, Lisa Bastarache, Darren C. Ames, Joseph T. Glessner, Leora Witkowski, Siddharth Pratap, Qiaoyan Wang, Melissa A. Kelly, Adithya Balasubramanian, Kara Slowik, Terrie Kitchner, Barbara J. Klanderman, Shawn Denson, Mary Stroud, Alyssa Macbeth, Melanie F. Myers, Jesse Muniz, Kasia Tolwinski, Scott T. Weiss, Chunhua Weng, Stephanie M. Fullerton, John B. Harley, Christopher G. Chute, Heidi L. Rehm, Sheethal Jose, Andrew M. Glazer, Navya Shilpa Josyula, Kenneth M. Borthwick, Thomas E. Mullen, Mariza de Andrade, Leah C. Kottyan, Luke V. Rasmussen, James Meldrim, and Bahram Namjou

Subjects
0301 basic medicine, Standardization, Test data generation, business.industry, Computer science, Sequence Analysis, DNA, 030105 genetics & heredity, Precision medicine, Data science, Clinical decision support system, Biobank, Article, 3. Good health, Data sharing, 03 medical and health sciences, 030104 developmental biology, Genetics, Humans, Genetic Testing, Prospective Studies, Sample collection, Personalized medicine, Precision Medicine, business, Genetics (clinical)
Abstract

The advancement of precision medicine requires new methods to coordinate and deliver genetic data from heterogeneous sources to physicians and patients. The eMERGE III Network enrolled >25,000 participants from biobank and prospective cohorts of predominantly healthy individuals for clinical genetic testing to determine clinically actionable findings. The network developed protocols linking together the 11 participant collection sites and 2 clinical genetic testing laboratories. DNA capture panels targeting 109 genes were used for testing of DNA and sample collection, data generation, interpretation, reporting, delivery, and storage were each harmonized. A compliant and secure network enabled ongoing review and reconciliation of clinical interpretations, while maintaining communication and data sharing between clinicians and investigators. A total of 202 individuals had positive diagnostic findings relevant to the indication for testing and 1,294 had additional/secondary findings of medical significance deemed to be returnable, establishing data return rates for other testing endeavors. This study accomplished integration of structured genomic results into multiple electronic health record (EHR) systems, setting the stage for clinical decision support to enable genomic medicine. Further, the established processes enable different sequencing sites to harmonize technical and interpretive aspects of sequencing tests, a critical achievement toward global standardization of genomic testing. The eMERGE protocols and tools are available for widespread dissemination.

Published
2019

5. Penetrance of breast cancer genes from the eMERGE III Network

Author

Christin Hoell, Ian B. Stanaway, Marc S. Williams, Maureen E. Smith, Adam S. Gordon, Xiao Fan, Scott J. Hebbring, Nora B. Henrikson, Elisabeth A. Rosenthal, Eric B. Larson, Katherine D. Crew, Wendy K. Chung, Rongling Li, Janet L. Williams, Adam H. Buchanan, Yufeng Shen, Chunhua Weng, Alex Fedotov, Georgia L. Wiesner, Kathleen A. Leppig, Cong Liu, Miranda L.G. Hallquist, Laura J. Rasmussen-Torvik, Ning S, Josh F. Peterson, Gail P. Jarvik, Julia Wynn, Murad A, and David R. Crosslin

Subjects
Oncology, medicine.medical_specialty, education.field_of_study, biology, medicine.diagnostic_test, business.industry, PALB2, Population, medicine.disease, Penetrance, Breast cancer, Internal medicine, medicine, biology.protein, PTEN, Family history, skin and connective tissue diseases, business, education, CHEK2, Genetic testing
Abstract

We studied the penetrance and clinical outcomes of seven breast cancer susceptibility genes (BRCA1, BRCA2, TP53, CHEK2, ATM, PALB2 and PTEN) in almost 25,000 participants unselected for personal or family history of breast cancer. We identified 420 participants with pathogenic or likely pathogenic variants, and 147 were women who did not previously know their genetic results. Out of these 147 women, 32 women were diagnosed with breast cancer at an average age of 52.8 years. Estimated penetrance by age 60 years ranged from 18-44%, depending on the gene. Within the first twelve months after genetic results disclosure, 42% of women had taken actions related to their genetic results and two new breast cancer cases were identified. Our study provides population-based penetrance estimates for the understudied genes, CHEK2, ATM, and PALB2, and highlights the importance of using unselected populations for penetrance studies. It also demonstrates the potential clinical impact of genetic testing to improve healthcare through early diagnosis and preventative screening.

Published
2021

6. Harmonizing Outcomes for Genomic Medicine: Comparison of eMERGE Outcomes to ClinGen Outcome/Intervention Pairs

Author

Margaret Harr, Eric B. Larson, Krzysztof Kiryluk, Hakon Hakonarson, Ingrid A. Holm, Janet L. Williams, Josh F. Peterson, Wendy K. Chung, Marc S. Williams, Gail P. Jarvik, Chunhua Weng, David L. Veenstra, John J. Connolly, Alex Fedotov, Maureen E. Smith, Kathleen A. Leppig, and Christin Hoell

Subjects
ClinGen, 0301 basic medicine, medicine.medical_specialty, Leadership and Management, Concordance, Psychological intervention, lcsh:Medicine, Health Informatics, 030105 genetics & heredity, Health outcomes, Outcome (game theory), Article, general_medical_research, 03 medical and health sciences, eMERGE, Health Information Management, Intervention (counseling), genomics, medicine, health outcomes, Genomic medicine, 030304 developmental biology, 0303 health sciences, evidence, business.industry, Health Policy, Public health, lcsh:R, 030305 genetics & heredity, 3. Good health, precision public health, genomic medicine, Family medicine, standards, business, Relevant information
Abstract

Genomic medicine is moving from research to the clinic. There is a lack of evidence about the impact of genomic medicine interventions on health outcomes. This is due in part to a lack of standardized outcome measures that can be used across different programs to evaluate the impact of interventions targeted to specific genetic conditions. The eMERGE Outcomes working group (OWG) developed measures to collect information on outcomes following the return of genomic results to participants for several genetic disorders. These outcomes were compared to outcome intervention pairs for genetic disorders developed independently by the ClinGen Actionability working group (AWG). In general, there was concordance between the defined outcomes between the two groups. The ClinGen outcomes tended to be from a higher level and the AWG scored outcomes represented a subset of outcomes referenced in the accompanying AWG evidence review. eMERGE OWG outcomes were more detailed and discrete, facilitating a collection of relevant information from the health records. This paper demonstrates that common outcomes for genomic medicine interventions can be identified. Further work is needed to standardize outcomes across genomic medicine implementation projects and to make these publicly available to enhance dissemination and assist in making precision public health a reality.

Published
2020

7. Predictive Utility of Polygenic Risk Scores for Coronary Heart Disease in Three Major Racial and Ethnic Groups

Author

Patrick M. A. Sleiman, Matthew L. Kosel, Ozan Dikilitas, Joshua A. Denny, Christopher G. Chute, Alex Fedotov, Ming Ta Michael Lee, Robb Rowley, Wei-Qi Wei, Amy C. Sturm, Teri A. Manolio, Marc S. Williams, Yanfei Zhang, Gail P. Jarvik, Robert J. Carroll, C. Michael Stein, Iftikhar J. Kullo, Jennifer A. Pacheco, Daniel J. Schaid, QiPing Feng, Hakon Hakonarson, and Georgia L. Wiesner

Subjects
0301 basic medicine, Male, Multifactorial Inheritance, Ethnic group, Coronary Disease, 030204 cardiovascular system & hematology, White People, Article, Coronary artery disease, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Genetics, Odds Ratio, Medicine, Humans, Genetic Predisposition to Disease, Genetics (clinical), business.industry, Hazard ratio, Mean age, Odds ratio, Hispanic or Latino, Middle Aged, medicine.disease, Coronary heart disease, Black or African American, 030104 developmental biology, Cohort, Polygenic risk score, Female, business, Demography
Abstract

Because polygenic risk scores (PRSs) for coronary heart disease (CHD) are derived from mainly European ancestry (EA) cohorts, their validity in African ancestry (AA) and Hispanic ethnicity (HE) individuals is unclear. We investigated associations of “restricted” and genome-wide PRSs with CHD in three major racial and ethnic groups in the U.S. The eMERGE cohort (mean age 48 ± 14 years, 58% female) included 45,645 EA, 7,597 AA, and 2,493 HE individuals. We assessed two restricted PRSs (PRS(Tikkanen) and PRS(Tada); 28 and 50 variants, respectively) and two genome-wide PRSs (PRS(metaGRS) and PRS(LDPred); 1.7 M and 6.6 M variants, respectively) derived from EA cohorts. Over a median follow-up of 11.1 years, 2,652 incident CHD events occurred. Hazard and odds ratios for the association of PRSs with CHD were similar in EA and HE cohorts but lower in AA cohorts. Genome-wide PRSs were more strongly associated with CHD than restricted PRSs were. PRS(metaGRS), the best performing PRS, was associated with CHD in all three cohorts; hazard ratios (95% CI) per 1 SD increase were 1.53 (1.46–1.60), 1.53 (1.23–1.90), and 1.27 (1.13–1.43) for incident CHD in EA, HE, and AA individuals, respectively. The hazard ratios were comparable in the EA and HE cohorts (p(interaction) = 0.77) but were significantly attenuated in AA individuals (p(interaction)= 2.9 × 10(−3)). These results highlight the potential clinical utility of PRSs for CHD as well as the need to assemble diverse cohorts to generate ancestry- and ethnicity PRSs.

Published
2019

8. Shock-wave measurements with fiber Bragg gratings

Author

Garry Berkovic, Avi Ravid, Alex Fedotov-Gefen, Ehud Shafir, Shlomi Zilberman, and Yonatan Schweitzer

Subjects
Shock wave, Materials science, business.industry, Physics::Optics, 02 engineering and technology, 021001 nanoscience & nanotechnology, Diagnostic tools, 01 natural sciences, law.invention, 010309 optics, Wavelength, Optics, Fiber Bragg grating, law, Wavelength-division multiplexing, 0103 physical sciences, Light-gas gun, 0210 nano-technology, business, Shock front, Pressure gradient
Abstract

Fiber Bragg Gratings may serve as diagnostic tools for shock waves, their response following the extreme and rapid pressure gradients. In accordance with basic theory, the relative orientation between the FBG and the shock front has a dramatic effect on the FBG response, even changing from a reduction to an increase of Bragg wavelengths. In order to match the shock-wave dimensions, short (∼1mm) FBGs are used.

Published
2017

9. Correction: Evaluation of the cost and effectiveness of diverse recruitment methods for a genetic screening study

Author

Hila Milo Rasouly, Julia Wynn, Maddalena Marasa, Rachel Reingold, Debanjana Chatterjee, Sheena Kapoor, Stacy Piva, Byum Hee Kil, Xueru Mu, Maria Alvarez, Jordan Nestor, Karla Mehl, Anya Revah-Politi, Natalie Lippa, Michelle E. Ernst, Louise Bier, Aileen Espinal, Bianca Haser, Anoushka Sinha, Ian Halim, David Fasel, Nicole Cuneo, Jacqueline J. Thompson, Miguel Verbitsky, Elizabeth G. Cohn, Jill Goldman, Karen Marder, Robert L. Klitzman, Manuela A. Orjuela, Yat S. So, Alex Fedotov, Katherine D. Crew, Krzysztof Kiryluk, Paul S. Appelbaum, Chunhua Weng, Karolynn Siegel, Ali G. Gharavi, and Wendy K. Chung

Subjects
Adult, Male, Clinical Trials as Topic, Patient Selection, Genomics, Middle Aged, Article, Research Design, Costs and Cost Analysis, Ethnicity, Humans, Mass Screening, Female, Genetic Testing, Genetics (clinical), Retrospective Studies
Abstract

Recruitment of participants from diverse backgrounds is crucial to the generalizability of genetic research, but has proven challenging. We retrospectively evaluated recruitment methods used for a study on return of genetic results.The costs of study design, development, and participant enrollment were calculated, and the characteristics of the participants enrolled through the seven recruitment methods were examined.A total of 1118 participants provided consent, a blood sample, and questionnaire data. The estimated cost across recruitment methods ranged from $579 to $1666 per participant and required a large recruitment team. Recruitment methods using flyers and staff networks were the most cost-efficient and resulted in the highest completion rate. Targeted sampling that emphasized the importance of Latino/a participation, utilization of translated materials, and in-person recruitments contributed to enrolling a demographically diverse sample.Although all methods were deployed in the same hospital or neighborhood and shared the same staff, each recruitment method was different in terms of cost and characteristics of the enrolled participants, suggesting the importance of carefully choosing the recruitment methods based on the desired composition of the final study sample. This analysis provides information about the effectiveness and cost of different methods to recruit adults for genetic research.

Published
2019

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