Connection

Co-Authors

This is a "connection" page, showing publications co-authored by ERIC BOERWINKLE and MELISSA RICHARD.
Connection Strength

0.954
  1. DNA Methylation Analysis Identifies Loci for Blood Pressure Regulation. Am J Hum Genet. 2017 Dec 07; 101(6):888-902.
    View in: PubMed
    Score: 0.153
  2. Gene-educational attainment interactions in a multi-population genome-wide meta-analysis identify novel lipid loci. Front Genet. 2023; 14:1235337.
    View in: PubMed
    Score: 0.058
  3. Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure. Mol Psychiatry. 2021 11; 26(11):6293-6304.
    View in: PubMed
    Score: 0.048
  4. Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals. Nat Genet. 2020 12; 52(12):1314-1332.
    View in: PubMed
    Score: 0.047
  5. Multi-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits. HGG Adv. 2021 Jan 14; 2(1).
    View in: PubMed
    Score: 0.047
  6. Role of Rare and Low-Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels. Circ Genom Precis Med. 2020 08; 13(4):e002772.
    View in: PubMed
    Score: 0.046
  7. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci. Mol Psychiatry. 2021 Jun; 26(6):2111-2125.
    View in: PubMed
    Score: 0.045
  8. Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration. Nat Commun. 2019 Nov 12; 10(1):5121.
    View in: PubMed
    Score: 0.044
  9. A multi-ancestry genome-wide study incorporating gene-smoking interactions identifies multiple new loci for pulse pressure and mean arterial pressure. Hum Mol Genet. 2019 Aug 01; 28(15):2615-2633.
    View in: PubMed
    Score: 0.043
  10. Genetic analyses of diverse populations improves discovery for complex traits. Nature. 2019 06; 570(7762):514-518.
    View in: PubMed
    Score: 0.043
  11. Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions. Am J Epidemiol. 2019 Jun 01; 188(6):1033-1054.
    View in: PubMed
    Score: 0.042
  12. Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids. Nat Genet. 2019 Apr; 51(4):636-648.
    View in: PubMed
    Score: 0.042
  13. Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity. Nat Commun. 2019 Jan 22; 10(1):376.
    View in: PubMed
    Score: 0.041
  14. Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries. PLoS One. 2018; 13(6):e0198166.
    View in: PubMed
    Score: 0.040
  15. A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure. Am J Hum Genet. 2018 Mar 01; 102(3):375-400.
    View in: PubMed
    Score: 0.039
  16. New Blood Pressure-Associated Loci Identified in Meta-Analyses of 475?000 Individuals. Circ Cardiovasc Genet. 2017 Oct; 10(5).
    View in: PubMed
    Score: 0.038
  17. Exome Genotyping Identifies Pleiotropic Variants Associated with Red Blood Cell Traits. Am J Hum Genet. 2016 Jul 07; 99(1):8-21.
    View in: PubMed
    Score: 0.035
  18. Platelet-Related Variants Identified by Exomechip Meta-analysis in 157,293 Individuals. Am J Hum Genet. 2016 Jul 07; 99(1):40-55.
    View in: PubMed
    Score: 0.035
  19. Large-Scale Exome-wide Association Analysis Identifies Loci for White Blood Cell Traits and Pleiotropy with Immune-Mediated Diseases. Am J Hum Genet. 2016 Jul 07; 99(1):22-39.
    View in: PubMed
    Score: 0.035
  20. An Empirical Comparison of Joint and Stratified Frameworks for Studying G ? E Interactions: Systolic Blood Pressure and Smoking in the CHARGE Gene-Lifestyle Interactions Working Group. Genet Epidemiol. 2016 07; 40(5):404-15.
    View in: PubMed
    Score: 0.034
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.