Don Lindberg and the creation of the National Center for Biotechnology Information.

The highest priority new initiative resulting from the 1985-86 National Library of Medicine Long Range Planning exercise initiated by NLM Director Dr. Donald A.B. Lindberg was the creation of new information resources and services related to molecular biology and genetics, termed "biotechnology information". Beginning with existing NLM resources and research projects associated with molecular data, and with Lindberg's enthusiastic support, the institution launched a Congressionally-mandated Center that has become an essential part of 21st century biomedical science.

Don Lindberg, High performance computing and communications, and telemedicine.

From 1992 to 1995 Donald A.B. Lindberg M.D. served concurrently as the founding director of the National Coordination Office (NCO) for High Performance Computing and Communications (HPCC) and NLM director. The NCO and its successors coordinate the Presidential-level multi-agency HPCC research and development (R&D) program called for in the High-Performance Computing Act of 1991. All large Federal science and technology R&D and applications agencies, including those involved in medical research and health care, participate in the now-30-year-old program. Lindberg's HPCC efforts built on his pioneering work in developing and applying advances in computing and networking to meet the needs of the medical research and health care communities. As part of NLM's participation in HPCC, Lindberg promoted R&D and demonstrations in telemedicine, including testbeds, medical data privacy, medical decision-making, and health education. That telemedicine technologies were ready to meet demand during the COVID-19 pandemic is testament to Lindberg's visionary leadership.

Genome- and phenome-wide analyses of cardiac conduction identifies markers of arrhythmia risk.

BACKGROUND: ECG QRS duration, a measure of cardiac intraventricular conduction, varies ≈2-fold in individuals without cardiac disease. Slow conduction may promote re-entrant arrhythmias. METHODS AND RESULTS: We performed a genome-wide association study to identify genomic markers of QRS duration in 5272 individuals without cardiac disease selected from electronic medical record algorithms at 5 sites in the Electronic Medical Records and Genomics (eMERGE) network. The most significant loci were evaluated within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium QRS genome-wide association study meta-analysis. Twenty-three single-nucleotide polymorphisms in 5 loci, previously described by CHARGE, were replicated in the eMERGE samples; 18 single-nucleotide polymorphisms were in the chromosome 3 SCN5A and SCN10A loci, where the most significant single-nucleotide polymorphisms were rs1805126 in SCN5A with P=1.2×10(-8) (eMERGE) and P=2.5×10(-20) (CHARGE) and rs6795970 in SCN10A with P=6×10(-6) (eMERGE) and P=5×10(-27) (CHARGE). The other loci were in NFIA, near CDKN1A, and near C6orf204. We then performed phenome-wide association studies on variants in these 5 loci in 13859 European Americans to search for diagnoses associated with these markers. Phenome-wide association study identified atrial fibrillation and cardiac arrhythmias as the most common associated diagnoses with SCN10A and SCN5A variants. SCN10A variants were also associated with subsequent development of atrial fibrillation and arrhythmia in the original 5272 "heart-healthy" study population. CONCLUSIONS: We conclude that DNA biobanks coupled to electronic medical records not only provide a platform for genome-wide association study but also may allow broad interrogation of the longitudinal incidence of disease associated with genetic variants. The phenome-wide association study approach implicated sodium channel variants modulating QRS duration in subjects without cardiac disease as predictors of subsequent arrhythmias.

A genome- and phenome-wide association study to identify genetic variants influencing platelet count and volume and their pleiotropic effects.

Platelets are enucleated cell fragments derived from megakaryocytes that play key roles in hemostasis and in the pathogenesis of atherothrombosis and cancer. Platelet traits are highly heritable and identification of genetic variants associated with platelet traits and assessing their pleiotropic effects may help to understand the role of underlying biological pathways. We conducted an electronic medical record (EMR)-based study to identify common variants that influence inter-individual variation in the number of circulating platelets (PLT) and mean platelet volume (MPV), by performing a genome-wide association study (GWAS). We characterized genetic variants associated with MPV and PLT using functional, pathway and disease enrichment analyses; we assessed pleiotropic effects of such variants by performing a phenome-wide association study (PheWAS) with a wide range of EMR-derived phenotypes. A total of 13,582 participants in the electronic MEdical Records and GEnomic network had data for PLT and 6,291 participants had data for MPV. We identified five chromosomal regions associated with PLT and eight associated with MPV at genome-wide significance (P < 5E-8). In addition, we replicated 20 SNPs [out of 56 SNPs (α: 0.05/56 = 9E-4)] influencing PLT and 22 SNPs [out of 29 SNPs (α: 0.05/29 = 2E-3)] influencing MPV in a published meta-analysis of GWAS of PLT and MPV. While our GWAS did not find any new associations, our functional analyses revealed that genes in these regions influence thrombopoiesis and encode kinases, membrane proteins, proteins involved in cellular trafficking, transcription factors, proteasome complex subunits, proteins of signal transduction pathways, proteins involved in megakaryocyte development, and platelet production and hemostasis. PheWAS using a single-SNP Bonferroni correction for 1,368 diagnoses (0.05/1368 = 3.6E-5) revealed that several variants in these genes have pleiotropic associations with myocardial infarction, autoimmune, and hematologic disorders. We conclude that multiple genetic loci influence interindividual variation in platelet traits and also have significant pleiotropic effects; the related genes are in multiple functional pathways including those relevant to thrombopoiesis.

Variants near FOXE1 are associated with hypothyroidism and other thyroid conditions: using electronic medical records for genome- and phenome-wide studies.

We repurposed existing genotypes in DNA biobanks across the Electronic Medical Records and Genomics network to perform a genome-wide association study for primary hypothyroidism, the most common thyroid disease. Electronic selection algorithms incorporating billing codes, laboratory values, text queries, and medication records identified 1317 cases and 5053 controls of European ancestry within five electronic medical records (EMRs); the algorithms' positive predictive values were 92.4% and 98.5% for cases and controls, respectively. Four single-nucleotide polymorphisms (SNPs) in linkage disequilibrium at 9q22 near FOXE1 were associated with hypothyroidism at genome-wide significance, the strongest being rs7850258 (odds ratio [OR] 0.74, p = 3.96 × 10(-9)). This association was replicated in a set of 263 cases and 1616 controls (OR = 0.60, p = 5.7 × 10(-6)). A phenome-wide association study (PheWAS) that was performed on this locus with 13,617 individuals and more than 200,000 patient-years of billing data identified associations with additional phenotypes: thyroiditis (OR = 0.58, p = 1.4 × 10(-5)), nodular (OR = 0.76, p = 3.1 × 10(-5)) and multinodular (OR = 0.69, p = 3.9 × 10(-5)) goiters, and thyrotoxicosis (OR = 0.76, p = 1.5 × 10(-3)), but not Graves disease (OR = 1.03, p = 0.82). Thyroid cancer, previously associated with this locus, was not significantly associated in the PheWAS (OR = 1.29, p = 0.09). The strongest association in the PheWAS was hypothyroidism (OR = 0.76, p = 2.7 × 10(-13)), which had an odds ratio that was nearly identical to that of the curated case-control population in the primary analysis, providing further validation of the PheWAS method. Our findings indicate that EMR-linked genomic data could allow discovery of genes associated with many diseases without additional genotyping cost.

Robust replication of genotype-phenotype associations across multiple diseases in an electronic medical record.

Large-scale DNA databanks linked to electronic medical record (EMR) systems have been proposed as an approach for rapidly generating large, diverse cohorts for discovery and replication of genotype-phenotype associations. However, the extent to which such resources are capable of delivering on this promise is unknown. We studied whether an EMR-linked DNA biorepository can be used to detect known genotype-phenotype associations for five diseases. Twenty-one SNPs previously implicated as common variants predisposing to atrial fibrillation, Crohn disease, multiple sclerosis, rheumatoid arthritis, or type 2 diabetes were successfully genotyped in 9483 samples accrued over 4 mo into BioVU, the Vanderbilt University Medical Center DNA biobank. Previously reported odds ratios (OR(PR)) ranged from 1.14 to 2.36. For each phenotype, natural language processing techniques and billing-code queries were used to identify cases (n = 70-698) and controls (n = 808-3818) from deidentified health records. Each of the 21 tests of association yielded point estimates in the expected direction. Previous genotype-phenotype associations were replicated (p < 0.05) in 8/14 cases when the OR(PR) was > 1.25, and in 0/7 with lower OR(PR). Statistically significant associations were detected in all analyses that were adequately powered. In each of the five diseases studied, at least one previously reported association was replicated. These data demonstrate that phenotypes representing clinical diagnoses can be extracted from EMR systems, and they support the use of DNA resources coupled to EMR systems as tools for rapid generation of large data sets required for replication of associations found in research cohorts and for discovery in genome science.

Technical desiderata for the integration of genomic data into Electronic Health Records.

The era of "Personalized Medicine," guided by individual molecular variation in DNA, RNA, expressed proteins and other forms of high volume molecular data brings new requirements and challenges to the design and implementation of Electronic Health Records (EHRs). In this article we describe the characteristics of biomolecular data that differentiate it from other classes of data commonly found in EHRs, enumerate a set of technical desiderata for its management in healthcare settings, and offer a candidate technical approach to its compact and efficient representation in operational systems.

Don Lindberg, High Performance Computing and Communications, and Telemedicine.

From 1992 to 1995 Donald A.B. Lindberg M.D. served concurrently as the founding director of the National Coordination Office (NCO) for High Performance Computing and Communications (HPCC) and NLM director. The NCO and its successors coordinate the Presidential-level multi-agency HPCC research and development (R&D) program called for in the High-Performance Computing Act of 1991. All large Federal science and technology R&D and applications agencies, including those involved in medical research and health care, participate in the now-30-year-old program. Lindberg's HPCC efforts built on his pioneering work in developing and applying advances in computing and networking to meet the needs of the medical research and health care communities. As part of NLM's participation in HPCC, Lindberg promoted R&D and demonstrations in telemedicine, including testbeds, medical data privacy, medical decision-making, and health education. That telemedicine technologies were ready to meet demand during the COVID-19 pandemic is testament to Lindberg's visionary leadership.

Don Lindberg and the Creation of the National Center for Biotechnology Information.

The highest priority new initiative resulting from the 1985-86 National Library of Medicine Long Range Planning exercise initiated by NLM Director Dr. Donald A.B. Lindberg was the creation of new information resources and services related to molecular biology and genetics, termed "biotechnology information". Beginning with existing NLM resources and research projects associated with molecular data, and with Lindberg's enthusiastic support, the institution launched a Congressionally-mandated Center that has become an essential part of 21st century biomedical science.

Identification of genomic predictors of atrioventricular conduction: using electronic medical records as a tool for genome science.

BACKGROUND: Recent genome-wide association studies in which selected community populations are used have identified genomic signals in SCN10A influencing PR duration. The extent to which this can be demonstrated in cohorts derived from electronic medical records is unknown. METHODS AND RESULTS: We performed a genome-wide association study on 2334 European American patients with normal ECGs without evidence of prior heart disease from the Vanderbilt DNA databank, BioVU, which accrues subjects from routine patient care. Subjects were identified by combinations of natural language processing, laboratory queries, and billing code queries of deidentified medical record data. Subjects were 58% female, of mean (± SD) age 54 ± 15 years, and had mean PR intervals of 158 ± 18 ms. Genotyping was performed with the use of the Illumina Human660W-Quad platform. Our results identify 4 single nucleotide polymorphisms (rs6800541, rs6795970, rs6798015, rs7430477) linked to SCN10A associated with PR interval (P=5.73 × 10(-7) to 1.78 × 10(-6)). CONCLUSIONS: This genome-wide association study confirms a gene heretofore not implicated in cardiac pathophysiology as a modulator of PR interval in humans. This study is one of the first replication genome-wide association studies performed with the use of an electronic medical records-derived cohort, supporting their further use for genotype-phenotype analyses.

StarBRITE: the Vanderbilt University Biomedical Research Integration, Translation and Education portal.

StarBRITE is a one-stop, web-based research portal designed to meet the day-to-day needs of the Vanderbilt University and Meharry Medical College research community during the planning and conduct of research studies. StarBRITE serves as the main online location for research support addressing issues such as identification and location of resources, identification of experts, guidance for regulatory applications and approvals, regulatory assistance, funding requests, research data planning and collection, and serves as a central repository for educational offerings. To date, there have been more than 590,038 StarBRITE hits by more than 6582 cumulative users. We present here StarBRITE design objectives, details about technical infrastructure and system components, status report and activity metrics for the first 2.75-years of operation, and a report of lessons learned during organizing, launching and refining the portal.

An analytical approach to characterize morbidity profile dissimilarity between distinct cohorts using electronic medical records.

We describe a two-stage analytical approach for characterizing morbidity profile dissimilarity among patient cohorts using electronic medical records. We capture morbidities using the International Statistical Classification of Diseases and Related Health Problems (ICD-9) codes. In the first stage of the approach separate logistic regression analyses for ICD-9 sections (e.g., "hypertensive disease" or "appendicitis") are conducted, and the odds ratios that describe adjusted differences in prevalence between two cohorts are displayed graphically. In the second stage, the results from ICD-9 section analyses are combined into a general morbidity dissimilarity index (MDI). For illustration, we examine nine cohorts of patients representing six phenotypes (or controls) derived from five institutions, each a participant in the electronic MEdical REcords and GEnomics (eMERGE) network. The phenotypes studied include type II diabetes and type II diabetes controls, peripheral arterial disease and peripheral arterial disease controls, normal cardiac conduction as measured by electrocardiography, and senile cataracts.

An XML model of an enhanced data dictionary to facilitate the exchange of pre-existing clinical research data in international studies.

Pre-existing clinical research data sets exchanged in international epidemiology research often lack the elements needed to assess their suitability for use in multi-region meta-analyses or other clinical studies. While the missing information is generally known to local investigators, it is not contained in the files exchanged between sites. Instead, such content must be solicited by the study coordinating center though a series of lengthy phone and electronic communications: an informal process whose reproducibility and accuracy decays over time. This report describes a set of supplemental information needed to assess whether clinical research data from diverse research sites are truly comparable, and what metadata ("data about the data") should be preserved when a data set is archived for future use. We propose a structured Extensible Markup Language (XML) model that captures this information. The authors hope this model will be a first step towards preserving the metadata associated with clinical research data sets, thereby improving the quality of international data exchange, data archiving, and merged-data research using data collected in many different countries, languages and care settings.

Effects of current and future information technologies on the health care workforce.

Information technologies have the potential to affect the types and distribution of jobs in the health care workforce. Against a background of an explosively growing body of knowledge in the health sciences, current models of clinical decision making by autonomous practitioners, relying upon their memory and personal experience, will be inadequate for effective twenty-first-century health care delivery. The growth of consumerism and the proliferation of Internet-accessible sources of health-related information will modify the traditional roles of provider and patient and will provide opportunities for new kinds of employment in health-related professions.

New Directions in Bioinformatics.

Two decades have passed since the first large scale, public access computer-based information systems were developed to store and disseminate the knowledge of medicine and biology. These first systems were bibliographic, and though the searching of computer files of citations remains the most common use of biological databases, there are dramatic forces at work in basic biology which are driving a transition from the printed page to the factual database. Unlike bibliographic systems, which contain only a pointer to information located elsewhere, factual data-bases contain the information sought. Development of automated methods to sequence DNA, RNA, proteins, and other macromolecules have yielded oceans of cryptic symbols, for which there is an absolute dependence upon computerized factual databases to acquire, store, retrieve, and analyze data. The Human Genome Project has focussed attention on the information science aspects of nucleic acid data, yet for the practicing scientist nucleic acids and other sequence data are just one piece of an increasingly complex biological puzzle whose solution will be expressed in terms of structure and function. Access to and integration of information across multiple related biological data-bases is a major challenge facing information system builders, a challenge which holds the promise of creating knowledge synergy from what are today disconnected, stand-alone information sources.

Genetic variants associated with serum thyroid stimulating hormone (TSH) levels in European Americans and African Americans from the eMERGE Network.

Thyroid stimulating hormone (TSH) hormone levels are normally tightly regulated within an individual; thus, relatively small variations may indicate thyroid disease. Genome-wide association studies (GWAS) have identified variants in PDE8B and FOXE1 that are associated with TSH levels. However, prior studies lacked racial/ethnic diversity, limiting the generalization of these findings to individuals of non-European ethnicities. The Electronic Medical Records and Genomics (eMERGE) Network is a collaboration across institutions with biobanks linked to electronic medical records (EMRs). The eMERGE Network uses EMR-derived phenotypes to perform GWAS in diverse populations for a variety of phenotypes. In this report, we identified serum TSH levels from 4,501 European American and 351 African American euthyroid individuals in the eMERGE Network with existing GWAS data. Tests of association were performed using linear regression and adjusted for age, sex, body mass index (BMI), and principal components, assuming an additive genetic model. Our results replicate the known association of PDE8B with serum TSH levels in European Americans (rs2046045 p = 1.85×10-17, ß = 0.09). FOXE1 variants, associated with hypothyroidism, were not genome-wide significant (rs10759944: p = 1.08×10-6, ß = -0.05). No SNPs reached genome-wide significance in African Americans. However, multiple known associations with TSH levels in European ancestry were nominally significant in African Americans, including PDE8B (rs2046045 p = 0.03, ß = -0.09), VEGFA (rs11755845 p = 0.01, ß = -0.13), and NFIA (rs334699 p = 1.50×10-3, ß = -0.17). We found little evidence that SNPs previously associated with other thyroid-related disorders were associated with serum TSH levels in this study. These results support the previously reported association between PDE8B and serum TSH levels in European Americans and emphasize the need for additional genetic studies in more diverse populations.

Genetic variants that confer resistance to malaria are associated with red blood cell traits in African-Americans: an electronic medical record-based genome-wide association study.

To identify novel genetic loci influencing interindividual variation in red blood cell (RBC) traits in African-Americans, we conducted a genome-wide association study (GWAS) in 2315 individuals, divided into discovery (n = 1904) and replication (n = 411) cohorts. The traits included hemoglobin concentration (HGB), hematocrit (HCT), RBC count, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC). Patients were participants in the electronic MEdical Records and GEnomics (eMERGE) network and underwent genotyping of ~1.2 million single-nucleotide polymorphisms on the Illumina Human1M-Duo array. Association analyses were performed adjusting for age, sex, site, and population stratification. Three loci previously associated with resistance to malaria-HBB (11p15.4), HBA1/HBA2 (16p13.3), and G6PD (Xq28)-were associated (P ≤ 1 × 10(-6)) with RBC traits in the discovery cohort. The loci replicated in the replication cohort (P ≤ 0.02), and were significant at a genome-wide significance level (P < 5 × 10(-8)) in the combined cohort. The proportions of variance in RBC traits explained by significant variants at these loci were as follows: rs7120391 (near HBB) 1.3% of MCHC, rs9924561 (near HBA1/A2) 5.5% of MCV, 6.9% of MCH and 2.9% of MCHC, and rs1050828 (in G6PD) 2.4% of RBC count, 2.9% of MCV, and 1.4% of MCH, respectively. We were not able to replicate loci identified by a previous GWAS of RBC traits in a European ancestry cohort of similar sample size, suggesting that the genetic architecture of RBC traits differs by race. In conclusion, genetic variants that confer resistance to malaria are associated with RBC traits in African-Americans.

Duration of anti-tuberculosis therapy and timing of antiretroviral therapy initiation: association with mortality in HIV-related tuberculosis.

BACKGROUND: Antiretroviral therapy (ART) decreases mortality risk in HIV-infected tuberculosis patients, but the effect of the duration of anti-tuberculosis therapy and timing of anti-tuberculosis therapy initiation in relation to ART initiation on mortality, is unclear. METHODS: We conducted a retrospective observational multi-center cohort study among HIV-infected persons concomitantly treated with Rifamycin-based anti-tuberculosis therapy and ART in Latin America. The study population included persons for whom 6 months of anti-tuberculosis therapy is recommended. RESULTS: Of 253 patients who met inclusion criteria, median CD4+ lymphocyte count at ART initiation was 64 cells/mm(3), 171 (68%) received >180 days of anti-tuberculosis therapy, 168 (66%) initiated anti-tuberculosis therapy before ART, and 43 (17%) died. In a multivariate Cox proportional hazards model that adjusted for CD4+ lymphocytes and HIV-1 RNA, tuberculosis diagnosed after ART initiation was associated with an increased risk of death compared to tuberculosis diagnosis before ART initiation (HR 2.40; 95% CI 1.15, 5.02; P = 0.02). In a separate model among patients surviving >6 months after tuberculosis diagnosis, after adjusting for CD4+ lymphocytes, HIV-1 RNA, and timing of ART initiation relative to tuberculosis diagnosis, receipt of >6 months of anti-tuberculosis therapy was associated with a decreased risk of death (HR 0.23; 95% CI 0.08, 0.66; P=0.007). CONCLUSIONS: The increased risk of death among persons diagnosed with tuberculosis after ART initiation highlights the importance of screening for tuberculosis before ART initiation. The decreased risk of death among persons receiving > 6 months of anti-tuberculosis therapy suggests that current anti-tuberculosis treatment duration guidelines should be re-evaluated.

Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data.

Candidate gene and genome-wide association studies (GWAS) have identified genetic variants that modulate risk for human disease; many of these associations require further study to replicate the results. Here we report the first large-scale application of the phenome-wide association study (PheWAS) paradigm within electronic medical records (EMRs), an unbiased approach to replication and discovery that interrogates relationships between targeted genotypes and multiple phenotypes. We scanned for associations between 3,144 single-nucleotide polymorphisms (previously implicated by GWAS as mediators of human traits) and 1,358 EMR-derived phenotypes in 13,835 individuals of European ancestry. This PheWAS replicated 66% (51/77) of sufficiently powered prior GWAS associations and revealed 63 potentially pleiotropic associations with P < 4.6 × 10⁻6 (false discovery rate < 0.1); the strongest of these novel associations were replicated in an independent cohort (n = 7,406). These findings validate PheWAS as a tool to allow unbiased interrogation across multiple phenotypes in EMR-based cohorts and to enhance analysis of the genomic basis of human disease.