publication . Article . Other literature type . 2016

Replicating Cardiovascular Condition-Birth Month Associations

Riccardo Miotto;
Open Access
  • Published: 14 Sep 2016
Abstract
Independent replication is vital for study findings drawn from Electronic Health Records (EHR). This replication study evaluates the relationship between seasonal effects at birth and lifetime cardiovascular condition risk. We performed a Season-wide Association Study on 1,169,599 patients from Mount Sinai Hospital (MSH) to compute phenome-wide associations between birth month and CVD. We then evaluated if seasonal patterns found at MSH matched those reported at Columbia University Medical Center. Coronary arteriosclerosis, essential hypertension, angina, and pre-infarction syndrome passed phenome-wide significance and their seasonal patterns matched those previ...
Subjects
free text keywords: Article, Cardiovascular system--Diseases--Risk factors, Epidemiology, Medical informatics, Environmental health, Multidisciplinary
Funded by
NIH| Drug Effect Discovery Through Data Mining and Integrative Chemical Biology
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01GM107145-03
  • Funding stream: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
,
NIH| Mount Sinai's Knowledge Management Center for Illuminating the Druggable Genome
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1U54CA189201-01
  • Funding stream: NATIONAL CANCER INSTITUTE
,
NIH| Methods for Evolutionary Informed Network Analysis to Discover Disease Variation
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01DK098242-03
  • Funding stream: NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES
25 references, page 1 of 2

Ioannidis J. P.. Increasing value and reducing waste in research design, conduct, and analysis. Lancet 383, 166–175, doi: 10.1016/S0140-6736(13)62227-8 (2014).24411645 [OpenAIRE] [PubMed] [DOI]

Ioannidis J. P., Ntzani E. E., Trikalinos T. A. & Contopoulos-Ioannidis D. G. Replication validity of genetic association studies. Nature genetics 29, 306–309, doi: 10.1038/ng749 (2001).11600885 [OpenAIRE] [PubMed] [DOI]

Denny J. C.. PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations. Bioinformatics 26, 1205–1210, doi: 10.1093/bioinformatics/btq126 (2010).20335276 [OpenAIRE] [PubMed] [DOI]

Gottesman O.. The Electronic Medical Records and Genomics (eMERGE) Network: past, present, and future. Genetics in medicine: official journal of the American College of Medical Genetics 15, 761–771, doi: 10.1038/gim.2013.72 (2013).23743551 [OpenAIRE] [PubMed] [DOI]

Crawford D. C.. eMERGEing progress in genomics-the first seven years. Frontiers in genetics 5, 184, doi: 10.3389/fgene.2014.00184 (2014).24987407 [OpenAIRE] [PubMed] [DOI]

Carroll R. J.. Portability of an algorithm to identify rheumatoid arthritis in electronic health records. Journal of the American Medical Informatics Association 19, e162–e169 (2012).22374935 [OpenAIRE] [PubMed]

Boland M. R., Hripcsak G., Shen Y., Chung W. K. & Weng C. Defining a comprehensive verotype using electronic health records for personalized medicine. Journal of the American Medical Informatics Association: JAMIA 20, e232–e238, doi: 10.1136/amiajnl-2013-001932 (2013).24001516 [OpenAIRE] [PubMed] [DOI]

Weiskopf N. G. & Weng C. Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research. Journal of the American Medical Informatics Association: JAMIA 20, 144–151, doi: 10.1136/amiajnl-2011-000681 (2013).22733976 [OpenAIRE] [PubMed] [DOI]

Boland M. R., Shahn Z., Madigan D., Hripcsak G. & Tatonetti N. P. Birth month affects lifetime disease risk: a phenome-wide method. Journal of the American Medical Informatics Association: JAMIA 22, 1042–1053, doi: 10.1093/jamia/ocv046 (2015).26041386 [OpenAIRE] [PubMed] [DOI]

Korsgaard J. & Dahl R. Sensitivity to house dust mite and grass pollen in adults. Influence of the month of birth. Clinical allergy 13, 529–535 (1983).6640888 [PubMed]

Halldner L.. Relative immaturity and ADHD: findings from nationwide registers, parent- and self-reports. Journal of child psychology and psychiatry, and allied disciplines 55, 897–904, doi: 10.1111/jcpp.12229 (2014). [OpenAIRE] [DOI]

Huber S., Fieder M., Wallner B., Moser G. & Arnold W. Brief communication: birth month influences reproductive performance in contemporary women. Human reproduction 19, 1081–1082, doi: 10.1093/humrep/deh247 (2004).15121731 [OpenAIRE] [PubMed] [DOI]

Boland M. R., Hripcsak G., Ryan P. & Tatonetti N. P. A Climate-Wide Journey to Explore Mechanisms Underlying Birth Month-Disease Risk Associations: A Call for Collaboration.

Overhage J. M., Ryan P. B., Reich C. G., Hartzema A. G. & Stang P. E. Validation of a common data model for active safety surveillance research. Journal of the American Medical Informatics Association: JAMIA 19, 54–60, doi: 10.1136/amiajnl-2011-000376 (2012).22037893 [OpenAIRE] [PubMed] [DOI]

Polubriaginof F., Boland M. R., Perotte A. & Vawdrey D. Quality of Race and Ethnicity Data in Electronic Health Records. AMIA Translational Informatics Joint Summits. In Press (2016).

25 references, page 1 of 2
Related research
Abstract
Independent replication is vital for study findings drawn from Electronic Health Records (EHR). This replication study evaluates the relationship between seasonal effects at birth and lifetime cardiovascular condition risk. We performed a Season-wide Association Study on 1,169,599 patients from Mount Sinai Hospital (MSH) to compute phenome-wide associations between birth month and CVD. We then evaluated if seasonal patterns found at MSH matched those reported at Columbia University Medical Center. Coronary arteriosclerosis, essential hypertension, angina, and pre-infarction syndrome passed phenome-wide significance and their seasonal patterns matched those previ...
Subjects
free text keywords: Article, Cardiovascular system--Diseases--Risk factors, Epidemiology, Medical informatics, Environmental health, Multidisciplinary
Funded by
NIH| Drug Effect Discovery Through Data Mining and Integrative Chemical Biology
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01GM107145-03
  • Funding stream: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
,
NIH| Mount Sinai's Knowledge Management Center for Illuminating the Druggable Genome
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1U54CA189201-01
  • Funding stream: NATIONAL CANCER INSTITUTE
,
NIH| Methods for Evolutionary Informed Network Analysis to Discover Disease Variation
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01DK098242-03
  • Funding stream: NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES
25 references, page 1 of 2

Ioannidis J. P.. Increasing value and reducing waste in research design, conduct, and analysis. Lancet 383, 166–175, doi: 10.1016/S0140-6736(13)62227-8 (2014).24411645 [OpenAIRE] [PubMed] [DOI]

Ioannidis J. P., Ntzani E. E., Trikalinos T. A. & Contopoulos-Ioannidis D. G. Replication validity of genetic association studies. Nature genetics 29, 306–309, doi: 10.1038/ng749 (2001).11600885 [OpenAIRE] [PubMed] [DOI]

Denny J. C.. PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations. Bioinformatics 26, 1205–1210, doi: 10.1093/bioinformatics/btq126 (2010).20335276 [OpenAIRE] [PubMed] [DOI]

Gottesman O.. The Electronic Medical Records and Genomics (eMERGE) Network: past, present, and future. Genetics in medicine: official journal of the American College of Medical Genetics 15, 761–771, doi: 10.1038/gim.2013.72 (2013).23743551 [OpenAIRE] [PubMed] [DOI]

Crawford D. C.. eMERGEing progress in genomics-the first seven years. Frontiers in genetics 5, 184, doi: 10.3389/fgene.2014.00184 (2014).24987407 [OpenAIRE] [PubMed] [DOI]

Carroll R. J.. Portability of an algorithm to identify rheumatoid arthritis in electronic health records. Journal of the American Medical Informatics Association 19, e162–e169 (2012).22374935 [OpenAIRE] [PubMed]

Boland M. R., Hripcsak G., Shen Y., Chung W. K. & Weng C. Defining a comprehensive verotype using electronic health records for personalized medicine. Journal of the American Medical Informatics Association: JAMIA 20, e232–e238, doi: 10.1136/amiajnl-2013-001932 (2013).24001516 [OpenAIRE] [PubMed] [DOI]

Weiskopf N. G. & Weng C. Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research. Journal of the American Medical Informatics Association: JAMIA 20, 144–151, doi: 10.1136/amiajnl-2011-000681 (2013).22733976 [OpenAIRE] [PubMed] [DOI]

Boland M. R., Shahn Z., Madigan D., Hripcsak G. & Tatonetti N. P. Birth month affects lifetime disease risk: a phenome-wide method. Journal of the American Medical Informatics Association: JAMIA 22, 1042–1053, doi: 10.1093/jamia/ocv046 (2015).26041386 [OpenAIRE] [PubMed] [DOI]

Korsgaard J. & Dahl R. Sensitivity to house dust mite and grass pollen in adults. Influence of the month of birth. Clinical allergy 13, 529–535 (1983).6640888 [PubMed]

Halldner L.. Relative immaturity and ADHD: findings from nationwide registers, parent- and self-reports. Journal of child psychology and psychiatry, and allied disciplines 55, 897–904, doi: 10.1111/jcpp.12229 (2014). [OpenAIRE] [DOI]

Huber S., Fieder M., Wallner B., Moser G. & Arnold W. Brief communication: birth month influences reproductive performance in contemporary women. Human reproduction 19, 1081–1082, doi: 10.1093/humrep/deh247 (2004).15121731 [OpenAIRE] [PubMed] [DOI]

Boland M. R., Hripcsak G., Ryan P. & Tatonetti N. P. A Climate-Wide Journey to Explore Mechanisms Underlying Birth Month-Disease Risk Associations: A Call for Collaboration.

Overhage J. M., Ryan P. B., Reich C. G., Hartzema A. G. & Stang P. E. Validation of a common data model for active safety surveillance research. Journal of the American Medical Informatics Association: JAMIA 19, 54–60, doi: 10.1136/amiajnl-2011-000376 (2012).22037893 [OpenAIRE] [PubMed] [DOI]

Polubriaginof F., Boland M. R., Perotte A. & Vawdrey D. Quality of Race and Ethnicity Data in Electronic Health Records. AMIA Translational Informatics Joint Summits. In Press (2016).

25 references, page 1 of 2
Related research
Powered by OpenAIRE Research Graph
Any information missing or wrong?Report an Issue