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Aref Smiley,* Te-Yi Tsai,* Ihor Havrylchuk,* Wanting Cui,* Irena Parvanova,* Elena Zakashansky,* Taulant Xhakli,* Hu Cui,* Joseph Finkelstein* Center for Biomedical and Population Health Informatics, Icahn School of Medicine at Mount Sinai, New York, NY, USA*These authors contributed equally to this workCorrespondence: Aref Smiley, Center for Biomedical and Population Health Informatics, Icahn School of Medicine at Mount Sinai, 1770 Madison Avenue, New York, NY, 10035, USA, Tel +1 212-659-9596, Email Aref.smiley@gmail.comPurpose: This paper focuses on developing and testing three versions of interactive bike (iBikE) interfaces for remote monitoring and control of cycling exercise sessions to promote upper and lower limb rehabilitation.Methods: Two versions of the system, which consisted of a portable bike and a tablet PC, were designed to communicate through either Bluetooth low energy (BLE) or Wi-Fi interfaces for real-time monitoring of exercise progress by both the users and their clinical team. The third version of the iBikE system consisted of a motorized bike and a tablet PC. It utilized conventional Bluetooth to implement remote control of the motorized bike’s speed during an exercise session as well as to provide real-time visualization of the exercise progress. We developed three customized tablet PC apps with similar user interfaces but different communication protocols for all the platforms to provide a graphical representation of exercise progress. The same microcontroller unit (MCU), ESP-32, was used in all the systems.Results: Each system was tested in 1-minute exercise sessions at various speeds. To evaluate the accuracy of the measured data, in addition to reading speed values from the iBikE app, the cycling speed of the bikes was measured continuously using a tachometer. The mean differences of averaged RPMs for both data sets were calculated. The calculated values were 0.38 ± 0.03, 0.25 ± 0.27, and 6.7 ± 3.3 for the BLE system, the Wi-Fi system, and the conventional Bluetooth system, respectively.Conclusion: All interfaces provided sufficient accuracy for use in telerehabilitation.Keywords: telerehabilitation, cycling exercise, wireless interface, accuracy

Joseph Finkelstein, 1 Irena Parvanova, 1 Frederick Zhang 2 1Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA; 2Center for Bioinformatics and Data Analytics, Columbia University, New York, NY, USACorrespondence: Joseph FinkelsteinDepartment of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, Icahn L2-36, New York, NY 10029, USATel +1 212-659-9596Email Joseph.Finkelstein@mssm.eduAbstract: As biomedical data integration and analytics play an increasing role in the field of stem cell research, it becomes important to develop ways to standardize, aggregate, and share data among researchers. For this reason, many databases have been developed in recent years in an attempt to systematically warehouse data from different stem cell projects and experiments at the same time. However, these databases vary widely in their implementation and structure. The aim of this scoping review is to characterize the main features of available stem cell databases in order to identify specifications useful for implementation in future stem cell databases. We conducted a scoping review of peer-reviewed literature and online resources to identify and review available stem cell databases. To identify the relevant databases, we performed a PubMed search using relevant MeSH terms followed by a web search for databases which may not have an associated journal article. In total, we identified 16 databases to include in this review. The data elements reported in these databases represented a broad spectrum of parameters from basic socio-demographic variables to various cells characteristics, cell surface markers expression, and clinical trial results. Three broad sets of functional features that provide utility for future stem cell research and facilitate bioinformatics workflows were identified. These features consisted of the following: common data elements, data visualization and analysis tools, and biomedical ontologies for data integration. Stem cell bioinformatics is a quickly evolving field that generates a growing number of heterogeneous data sets. Further progress in the stem cell research may be greatly facilitated by development of applications for intelligent stem cell data aggregation, sharing and collaboration process.Keywords: stem cells, data integration, databases

Frederick Zhang,1 Joseph Finkelstein21Center for Bioinformatics and Data Analytics, Columbia University Irving Medical Center, New York, NY, USA; 2Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USAIntroduction: Racial and ethnic categories are frequently used in pharmacogenetics literature to stratify patients; however, these categories can be inconsistent across different studies. To address the ongoing debate on the applicability of traditional concepts of race and ethnicity in the context of precision medicine, we aimed to review the application of current racial and ethnic categories in pharmacogenetics and its potential impact on clinical care.Methods: One hundred and three total pharmacogenetics papers involving the CYP2C9, CYP2C19, and CYP2D6 genes were analyzed for their country of origin, racial, and ethnic categories used, and allele frequency data. Correspondence between the major continental racial categories promulgated by National Institutes of Health (NIH) and those reported by the pharmacogenetics papers was evaluated.Results: The racial and ethnic categories used in the papers we analyzed were highly heterogeneous. In total, we found 66 different racial and ethnic categories used which fall under the NIH race category “White”, 47 different racial and ethnic categories for “Asian”, and 62 different categories for “Black”. The number of categories used varied widely based on country of origin: Japan used the highest number of different categories for “White” with 17, Malaysia used the highest number for “Asian” with 24, and the US used the highest number for “Black” with 28. Significant variation in allele frequency between different ethnic subgroups was identified within 3 major continental racial categories.Conclusion: Our analysis showed that racial and ethnic classification is highly inconsistent across different papers as well as between different countries. Evidence-based consensus is necessary for optimal use of self-identified race as well as geographical ancestry in pharmacogenetics. Common taxonomy of geographical ancestry which reflects specifics of particular countries and is accepted by the entire scientific community can facilitate reproducible pharmacogenetic research and clinical implementation of its results.Keywords: pharmacogenetics, single nucleotide polymorphism, ethnic differences, drug responsiveness

Frederick Zhang,1 Joseph Finkelstein2 1College of Dental Medicine, Columbia University, New York, NY, USA; 2Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USAObjectives: The purpose of this review was to evaluate the relationship between genetic polymorphisms and dental implant loss. Materials and methods: All case-control studies examining single nucleotide polymorphisms (SNPs) and dental implant failure were considered. A Boolean search was conducted on PubMed and Scopus to find eligible studies. Results: The initial search produced 78 results. Twenty-one studies were considered for inclusion after review and 16 were included in the final review. Twenty-two different polymorphisms were analyzed and statistically significant correlation was found for IL-4, IL-1A, IL-1B, MMP-8, and MMP-1 polymorphisms for dental implant failure.Discussion: A limited number of comprehensive studies have been done in this field. Additional studies with larger sample sizes and different ethnic backgrounds need to be done to see if the results can be reproduced. Of the polymorphisms studied, the IL-4 (+33), MMP-8 (−799), MMP-1 (−519), and MMP-1 (−1607) polymorphisms show the greatest association with dental implant loss.Keywords: dental implants, single nucleotide polymorphisms, genetic risk factors, scoping review

Joseph Finkelstein,1 Carol Friedman,1 George Hripcsak,1 Manuel Cabrera,2 1Department of Biomedical Informatics, 2Department of Medicine, Columbia University College of Physicians and Surgeons, New York, NY, USA Abstract: Pharmacogenetic testing identifies genetic biomarkers that are predictive of individual sensitivity to particular drugs. A significant proportion of medications that are widely prescribed for older adults are metabolized by enzymes that are encoded by highly polymorphic genes. Pharmacogenetic testing is increasingly used to optimize the medication regimen; however, its potential in older adults with polypharmacy has not been systematically explored. Following the initial case–series study, this study hypothesized that frequently hospitalized older adults with polypharmacy have higher frequency of pharmacogenetic polymorphism as compared to older adults with polypharmacy who are rarely admitted to a hospital. To test this hypothesis, a nested case–control study was conducted with pharmacogenetic polymorphism as an exposure and hospitalization rate as an outcome. In this study, frequently hospitalized older adults (≥65 years of age) with polypharmacy were matched with rarely hospitalized older adults with polypharmacy by age, gender, race, ethnicity, and chronic disease score. Average age and number of prescription drugs did not differ in cases and controls (77.2±5.0 and 78.3±5.1 years, 14.3±5.3 and 14.0±2.9 medications, respectively). No statistically significant difference in sociodemographic, clinical, and behavioral characteristics that are known to affect hospitalization risk was found between the cases and controls. Major pharmacogenetic polymorphism defined as presence of at least one allelic combination resulting in poor or rapid metabolizer status was identified in all the cases. No major pharmacogenetic polymorphisms were detected in controls. Based on the exact McNemar’s test, the difference in major pharmacogenetic polymorphism frequency between cases and controls was statistically significant (p

Joseph Finkelstein,1 Carol Friedman,1 George Hripcsak,1 Manuel Cabrera2 1Department of Biomedical Informatics, 2Department of Medicine, Columbia University, New York, NY, USA Abstract: Pharmacogenomic (PGx) testing has been increasingly used to optimize drug regimens; however, its potential in older adults with polypharmacy has not been systematically studied. In this hypothesis-generating study, we employed a case series design to explore potential utility of PGx testing in older adults with polypharmacy and to highlight barriers in implementing this methodology in routine clinical practice. Three patients with concurrent chronic heart and lung disease aged 74, 78, and 83 years and whose medication regimen comprised 26, 17, and 18 drugs, correspondingly, served as cases for this study. PGx testing identified major genetic polymorphisms in the first two cases. The first case was identified as “CYP3A4/CYP3A5 poor metabolizer”, which affected metabolism of eleven prescribed drugs. The second case had “CYP2D6 rapid metabolizer” status affecting three prescribed medications, two of which were key drugs for managing this patient's chronic conditions. Both these patients also had VKORC1 allele *A, resulting in higher sensitivity to warfarin. All cases demonstrated a significant number of potential drug–drug interactions. Both patients with significant drug–gene interactions had a history of frequent hospitalizations (six and 23, respectively), whereas the person without impaired cytochrome P450 enzyme activity had only two acute episodes in the last 5 years, although he was older and had multiple comorbidities. Since all patients received guideline-concordant therapy from the same providers and were adherent to their drug regimen, we hypothesized that genetic polymorphism may represent an additional risk factor for higher hospitalization rates in older adults with polypharmacy. However, evidence to support or reject this hypothesis is yet to be established. Studies evaluating clinical impact of PGx testing in older adults with polypharmacy are warranted. For practical implementation of pharmacogenomics in routine clinical care, besides providing convincing evidence of its clinical effectiveness, multiple barriers must be addressed. Introduction of intelligent clinical decision support in electronic medical record systems is required to address complexities of simultaneous drug–gene and drug–drug interactions in older adults with polypharmacy. Physician training, clear clinical pathways, evidence-based guidelines, and patient education materials are necessary for unlocking full potential of pharmacogenomics into routine clinical care of older adults. Keywords: precision medicine, pharmacogenomics, polypharmacy, elderly, case series