Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
17 authors.
Satoshi KoyamaProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0002-9286-0360
Ying WangProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Kaavya ParuchuriProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0003-1228-1674
Md Mesbah UddinProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0003-1846-0411
So Mi J ChoProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0003-2460-3335
Sarah M UrbutProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0002-1135-9647
Sara HaidermotaProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0002-8588-3388
Whitney E HornsbyProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0002-0672-0338
Robert C GreenDepartment of Medicine, Harvard Medical School, Boston, MA, USA.ORCID 0000-0001-8472-0424
Mark J DalyAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0002-0949-8752
Benjamin M NealeProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0003-1513-6077
Patrick T EllinorProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0002-2067-0533
Jordan W SmollerDepartment of Medicine, Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-0381-6334
Matthew S LeboDepartment of Medicine, Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-9733-5207
Elizabeth W KarlsonDepartment of Medicine, Harvard Medical School, Boston, MA, USA.ORCID 0000-0001-5455-7443
Alicia R MartinProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0003-0241-3522
Pradeep NatarajanProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0001-8402-7435
Funding
The Broad-LMM-Color Genome Center for All of UsOT2OD002750 · OD · BROAD INSTITUTE, INC. · PI GABRIEL, STACEY, REHM, HEIDI L · 2018 to 2023
$264.7M
Interactive Data Portals and Robust Analytic Tools to Wrap PASC Cohorts (iDRAW) OTA-21-015AOT2HL161841 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI FOULKES, ANDREA S, KARLSON, ELIZABETH W · 2021 to 2024
$182.2M
The New England Precision Medicine Consortium of the All of Us Research ProgramOT2OD026553 · OD · MASSACHUSETTS GENERAL HOSPITAL · PI CLARK, CHERYL RENEE, KARLSON, ELIZABETH W · 2018 to 2023
$58.8M
ClinGen AI Data Delivery SupplementU24HG006834 · NHGRI · BROAD INSTITUTE, INC. · PI Marina DiStefano, CHRISTA LESE MARTIN · 2021 to 2026
$26.7M
IDENTIFICATION OF COMMON GENETIC VARIANTS FOR ATRIAL FIBRILLATION AND PR INTERVALR01HL092577 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI BENJAMIN, EMELIA J., ELLINOR, PATRICK THOMAS · 2009 to 2025
$20.6M
Finding Genomic Profiles of COVID-19 Phenotypes from the EHRU01HG008685 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI ELIZABETH W KARLSON, Matthew S Lebo · 2015 to 2026
$13.6M
Joint Biology Consortium Resource-based CenterP30AR070253 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI Peter A Nigrovic, Jeffrey Andrew Sparks · 2016 to 2026
$9.4M
Using genetic variation to study biology of blood lipids & coronary heart diseaseR01HL127564 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Pradeep Natarajan, Gina Marie Peloso · 2015 to 2026
$7.3M
Return of Genomic Results and Estimating Penetrance in Population-Based CohortsR01HL143295 · NHLBI · BROAD INSTITUTE, INC. · PI CARSON, APRIL P, GREEN, ROBERT C. · 2019 to 2022
$7.2M
Statistical methods to localize disease heritability and identify biological mechanismsR37MH107649 · NIMH · BROAD INSTITUTE, INC. · PI Benjamin Michael Neale · 2019 to 2026
$7.0M
Enabling improved applicability and transferability of polygenic scores across populationsU01HG011719 · NHGRI · MASSACHUSETTS GENERAL HOSPITAL · PI Alicia Martin · 2021 to 2026
$5.5M
Implementation of Whole Genome Sequencing as Screening in a Diverse Cohort of Healthy InfantsU01TR003201 · NCATS · BRIGHAM AND WOMEN'S HOSPITAL · PI GREEN, ROBERT C., HOLM, INGRID ADELE · 2021 to 2024
Mass General Brigham, an integrated healthcare system based in the Greater Boston area of Massachusetts, annually serves 1.5 million patients. We established the Mass General Brigham Biobank (MGBB), encompassing 142,238 participants, to unravel the intricate relationships among genomic profiles, environmental context, and disease manifestations within clinical practice. In this study, we highlight the impact of ancestral diversity in the MGBB by employing population genetics, geospatial assessment, and association analyses of rare and common genetic variants. The population structures captured by the genetics mirror the sequential immigration to the Greater Boston area throughout American history, highlighting communities tied to shared genetic and environmental factors. Our investigation underscores the potency of unbiased, large-scale analyses in a healthcare-affiliated biobank, elucidating the dynamic interplay across genetics, immigration, structural geospatial factors, and health outcomes in one of the earliest American sites of European colonization.
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Decoding Genetics, Ancestry, and Geospatial Context for Precision Health. · full record | OpenQuestion