Malinowski, Jennifer
https://orcid.org/0000-0001-7500-2199
Mayo Clinic
Write InScite LLC , Pound Ridge, NY 10576,
Citations 2
PhenoFit: a framework for determining computable phenotyping algorithm fitness for purpose and reuse
Wiley, Laura K. , Rasmussen, Luke V. , Levinson, Rebecca T. , Malinowski, Jennifer , Manemann, Sheila M., Wilson, Melissa P. , Chapman, Martin , Pacheco, Jennifer A. , Walunas, Theresa L. , Starren, Justin , Richesson, Rachel , Malinowski, Jennnifer , Starren, Justin B , Bielinski, Suzette , Richesson, Rachel L , Rasmussen, Luke V , Pacheco, Jennifer A , Wiley, Laura K , Walunas, Theresa L , Bielinski, Suzette J.
Journal of the American Medical Informatics Association | November 12, 2025 | Volume: 33 | Issue: 2 | Pages: 536-542
Abstract Background Computational phenotyping from electronic health records (EHRs) is essential for clinical research, decision support, and quality/population health assessment, but the proliferation of algorithms for the same conditions makes it difficult to identify which algorithm is most appropriate for reuse. Objective To develop a framework for assessing phenotyping algorithm fitness for purpose and reuse. Fitness for Purpose Phenotyping algorithms are fit for purpose when they identify the intended population with performance characteristics appropriate for the intended application. Fitness for Reuse Phenotyping algorithms are fit for reuse when the algorithm is implementable and generalizable—that is, it identifies the same intended population with similar performance characteristics when applied to a new setting. Conclusions The PhenoFit framework provides a structured approach to evaluate and adapt phenotyping algorithms for new contexts increasing efficiency and consistency of identifying patient populations from EHRs.
Shared Genetic Risk Factors of Intracranial, Abdominal, and Thoracic Aneurysms
Hof, Femke N. G. van ’t, Ruigrok, Ynte M. , Lee, Cue Hyunkyu , Ripke, Stephan , Anderson, Graig, Baas, Annette F., Blankensteijn, Jan D. , Böttinger, Erwin P. , Bown, Matthew J. , Broderick, Joseph P., Bijlenga, Philippe , Crosslin, David R. , Ebeling, Christian , Eriksson, Johan G. , Fornage, Myriam , Foroud, Tatiana, Fraunberg, Mikael von und zu , Friedrich, Christoph M. , Gaál, Emília Ilona, Gottesman, Omri, Guo, Dongchuan , Harrison, Seamus C. , Hernesniemi, Juha , Hofman, Albert , Inoue, Ituro , Jääskeläinen, Juha E. , Kiemeney, Lambertus A. , Kivisaari, Riku , Ko, Nerissa , Koskinen, Seppo, Kubo, Michiaki , Kuivaniemi, Helena , Laakso, Aki , Lehto, Hanna, LeMaire, Scott A. , Malinowski, Jennifer , McCarty, Catherine A. , Mosley, Thomas H., Nakaoka, Hirofumi , Peissig, Peggy , Pera, Joanna , Rasmussen‐Torvik, Laura J. , Ritchie, Marylyn D. , Rivadeneira, Fernando , Rij, André M. van , Santos‐Cortez, Regie Lyn P., Saratzis, Athanasios , Słowik, Agnieszka , Tromp, Gerard , Uitterlinden, André G. , Vermeulen, Sita H. , Wang, Gao T., Han, Buhm , Bakker, Paul I. W. de , Verissimo, Ana Raquel, Wright, Benjamin J., Bumpstead, Suzannah, Grétarsdóttir, Sólveig , Badger, Stephen A., Child, Anne H. , Cockerill, Gillian, Hafez, Hany , Futers, Simon , Sohrabi, Soroush, Smith, Alberto, Thompson, Matthew M., Bockxmeer, Frank M. van, Matthíasson, Stefán E., Þorsteinsdóttir, Unnur , Graaf, Jacqueline de , Palmen, Jutta, Lindholt, Jes S. , Bradley, Declan , Waltham, Matthew, Gwilliam, Rhian, Golledge, Jonathan , Eriksson, Per , Stefánsson, Kāri , Thompson, John R., Humphries, Steve E. , Sayers, Robert D., Deloukas, Panos , Samani, Nilesh J. , Phillip, L. Victoria, Hill, Geraldine B., Williams, Michael , Thomson, Ian , Krysa, Jo, Wilkins, Gerard , Vasudevan, Thodor M., Lewis, David R. , Blair, Ross D., Hill, Andrew A., de Andrade, Mariza, Ripke, Stephan , Andrade, Mariza de , Broderick, Joseph, Carrell, David , Crawford, Dana C. , Jones, Gregory T. , Kullo, Iftikhar J. , Kurki, Mitja , Lai, Dongbing , Leal, Suzanne M. , Low, Siew‐Kee , Milewicz, Dianna M. , Nakamura, Yusuke , Niemela, Mika R. , Pacheco, Jennifer A. , Takahashi, Atsushi , Verma, Shefali S. , Rinkel, Gabriël J.E. , Clough, Rachel E. , Scott, D. Julian A., Þorleifsson, Guðmar , Teijink, Joep A.W. , Wijmenga, Cisca , Smith, Andrew J P , Edkins, Sarah , Hunt, Sarah E , Potter, Simon , Norman, Paul E , Powell, Janet T. , Merriman, Tony Raymond , Kiemeney, Lambertus A , Bijlenga, Philippe , Lindholt, Jes Sanddal , Malinowski, Jennnifer , Rasmussen-Torvik, Laura J , Eriksson, Per
Journal of the American Heart Association | July 15, 2016 | Volume: 5 | Issue: 7 | Pages: No page available
Background Intracranial aneurysms ( IAs ), abdominal aortic aneurysms ( AAAs ), and thoracic aortic aneurysms ( TAAs ) all have a familial predisposition. Given that aneurysm types are known to co‐occur, we hypothesized that there may be shared genetic risk factors for IAs , AAAs, and TAAs . Methods and Results We performed a mega‐analysis of 1000 Genomes Project‐imputed genome‐wide association study ( GWAS ) data of 4 previously published aneurysm cohorts: 2 IA cohorts (in total 1516 cases, 4305 controls), 1 AAA cohort (818 cases, 3004 controls), and 1 TAA cohort (760 cases, 2212 controls), and observed associations of 4 known IA , AAA , and/or TAA risk loci (9p21, 18q11, 15q21, and 2q33) with consistent effect directions in all 4 cohorts. We calculated polygenic scores based on IA ‐, AAA ‐, and TAA ‐associated SNP s and tested these scores for association to case‐control status in the other aneurysm cohorts; this revealed no shared polygenic effects. Similarly, linkage disequilibrium–score regression analyses did not show significant correlations between any pair of aneurysm subtypes. Last, we evaluated the evidence for 14 previously published aneurysm risk single‐nucleotide polymorphisms through collaboration in extended aneurysm cohorts, with a total of 6548 cases and 16 843 controls ( IA ) and 4391 cases and 37 904 controls ( AAA ), and found nominally significant associations for IA risk locus 18q11 near RBBP 8 to AAA (odds ratio [ OR ]=1.11; P =4.1×10 −5 ) and for TAA risk locus 15q21 near FBN 1 to AAA ( OR =1.07; P =1.1×10 −3 ). Conclusions Although there was no evidence for polygenic overlap between IAs , AAAs , and TAAs , we found nominally significant effects of two established risk loci for IAs and TAAs in AAAs . These two loci will require further replication.