The VA Hypertension Primary Care Longitudinal Cohort: Electronic medical records in the post-genomic era

Factors influencing the development of primary care data collection projects from electronic health records: a systematic review of the literature

BACKGROUND

Primary care data gathered from Electronic Health Records are of the utmost interest considering the essential role of general practitioners (GPs) as coordinators of patient care. These data represent the synthesis of the patient history and also give a comprehensive picture of the population health status. Nevertheless, discrepancies between countries exist concerning routine data collection projects. Therefore, we wanted to identify elements that influence the development and durability of such projects.

METHODS

A systematic review was conducted using the PubMed database to identify worldwide current primary care data collection projects. The gray literature was also searched via official project websites and their contact person was emailed to obtain information on the project managers. Data were retrieved from the included studies using a standardized form, screening four aspects: projects features, technological infrastructure, GPs' roles, data collection network organization.

RESULTS

The literature search allowed identifying 36 routine data collection networks, mostly in English-speaking countries: CPRD and THIN in the United Kingdom, the Veterans Health Administration project in the United States, EMRALD and CPCSSN in Canada. These projects had in common the use of technical facilities that range from extraction tools to comprehensive computing platforms. Moreover, GPs initiated the extraction process and benefited from incentives for their participation. Finally, analysis of the literature data highlighted that governmental services, academic institutions, including departments of general practice, and software companies, are pivotal for the promotion and durability of primary care data collection projects.

CONCLUSION

Solid technical facilities and strong academic and governmental support are required for promoting and supporting long-term and wide-range primary care data collection projects.

Applying deep neural networks to unstructured text notes in electronic medical records for phenotyping youth depression

Background

We report a study of machine learning applied to the phenotyping of psychiatric diagnosis for research recruitment in youth depression, conducted with 861 labelled electronic medical records (EMRs) documents. A model was built that could accurately identify individuals who were suitable candidates for a study on youth depression.

Objective

Our objective was a model to identify individuals who meet inclusion criteria as well as unsuitable patients who would require exclusion.

Methods

Our methods included applying a system that coded the EMR documents by removing personally identifying information, using two psychiatrists who labelled a set of EMR documents (from which the 861 came), using a brute force search and training a deep neural network for this task.

Findings

According to a cross-validation evaluation, we describe a model that had a specificity of 97% and a sensitivity of 45% and a second model with a specificity of 53% and a sensitivity of 89%. We combined these two models into a third one (sensitivity 93.5%; specificity 68%; positive predictive value (precision) 77%) to generate a list of most suitable candidates in support of research recruitment.

Conclusion

Our efforts are meant to demonstrate the potential for this type of approach for patient recruitment purposes but it should be noted that a larger sample size is required to build a truly reliable recommendation system.

Clinical implications

Future efforts will employ alternate neural network algorithms available and other machine learning methods.

Interactions between intersubunit transmembrane domains regulate the chaperone-dependent degradation of an oligomeric membrane protein

In the kidney, the epithelial sodium channel (ENaC) regulates blood pressure through control of sodium and volume homeostasis, and in the lung, ENaC regulates the volume of airway and alveolar fluids. ENaC is a heterotrimer of homologous α-, β- and γ-subunits, and assembles in the endoplasmic reticulum (ER) before it traffics to and functions at the plasma membrane. Improperly folded or orphaned ENaC subunits are subject to ER quality control and targeted for ER-associated degradation (ERAD). We previously established that a conserved, ER lumenal, molecular chaperone, Lhs1/GRP170, selects αENaC, but not β- or γ-ENaC, for degradation when the ENaC subunits were individually expressed. We now find that when all three subunits are co-expressed, Lhs1-facilitated ERAD was blocked. To determine which domain-domain interactions between the ENaC subunits are critical for chaperone-dependent quality control, we employed a yeast model and expressed chimeric α/βENaC constructs in the context of the ENaC heterotrimer. We discovered that the βENaC transmembrane domain was sufficient to prevent the Lhs1-dependent degradation of the α-subunit in the context of the ENaC heterotrimer. Our work also found that Lhs1 delivers αENaC for proteasome-mediated degradation after the protein has become polyubiquitinated. These data indicate that the Lhs1 chaperone selectively recognizes an immature form of αENaC, one which has failed to correctly assemble with the other channel subunits via its transmembrane domain.

Paraoxonase 1 (PON1) C/T-108 association with longitudinal mean arterial blood pressure

BACKGROUND

Blood pressure is a complex quantitative trait with a strong genetic component. In this study, we leveraged the Veterans Affairs electronic medical record system to explore the relationship between Paraoxonase 1 (PON1)-108 C/T (rs705379) and mean arterial blood pressure (MAP).

METHODS

Outpatient blood pressure data over an approximate 8-year period was collected from the Veterans Affairs Hypertensive Cohort (N = 1,302). Association between genotype and longitudinal MAP was further explored using a random effects model controlling for age, ancestry, renal function, and other determinants of blood pressure. To control for population stratification, principal component groupings based on ancestry informative markers in this dataset were included as covariates (in addition to self-identified ancestry). Data from the African American Study of Kidney Disease and Hypertension (AASK, N = 857) was used to confirm significant findings in an independent cohort.

RESULTS

There was a significant interaction between PON1-108 C/T genotype and follow-up age group. At a younger age (<50 years), there was an estimated 2.53 mm Hg (95% confidence interval: 1.06, 4.00) increase in MAP with each additional C-allele. At the older age groups, there were no significant associations between PON1-108 C/T genotype and MAP. Using data from the AASK trial, the C-allele at PON1-108 C/T was significantly associated with a higher MAP (P = 0.005) but only among younger participants (<54 years).

CONCLUSIONS

The PON1-108 polymorphism may be associated with MAP in an age-dependent manner.

Looking to the future: incorporating genomic information into disparities research to reduce measurement error and selection bias

OBJECTIVE

To extend recent conceptual and methodological advances in disparities research to include the incorporation of genomic information in analyses of racial/ethnic disparities in health care and health outcomes.

DATA SOURCES

Published literature on human genetic variation, the role of genetics in disease and response to treatment, and methodological developments in disparities research.

STUDY DESIGN

We present a conceptual framework for incorporating genomic information into the Institute of Medicine definition of racial/ethnic disparities in health care, identify key concepts used in disparities research that can be informed by genomics research, and illustrate the incorporation of genomic information into current methods using the example of HER-2 mutations guiding care for breast cancer.

PRINCIPAL FINDINGS

Genomic information has not yet been incorporated into disparities research, though it has direct relevance to concepts of race/ethnicity, health status, appropriate care, and socioeconomic status. The HER-2 example demonstrates how available genetic information can be incorporated into current disparities methods to reduce selection bias and measurement error. Advances in health information infrastructure may soon make standardized genetic information more available to health services researchers.

CONCLUSION

Genomic information can refine measurement of racial/ethnic disparities in health care and health outcomes and should be included wherever possible in disparities research.

Methylenetetrahydrofolate reductase (MTHFR) polymorphism A1298C (Glu429Ala) predicts decline in renal function over time in the African-American Study of Kidney Disease and Hypertension (AASK) Trial and Veterans Affairs Hypertension Cohort (VAHC)

BACKGROUND

Hyperhomocysteinemia is associated with increased venous thrombosis and cardiovascular disease (CVD). Mutations in the human methylenetetrahydrofolate reductase (MTHFR) gene have been associated with increased homocysteine levels and risks of CVD in various populations including those with kidney disease. Here, we evaluated the influence of MTHFR variants on progressive loss of kidney function.

METHODS

We analyzed 821 subjects with hypertensive nephrosclerosis from the longitudinal National Institute of Diabetes and Digestive and Kidney Diseases African-American Study of Kidney Disease and Hypertension (AASK) Trial to determine whether decline in glomerular filtration rate (GFR) over ∼4.2 years was predicted by common genetic variation within MTHFR at non-synonymous positions C677T (Ala222Val) and A1298C (Glu429Ala) or by MTHFR haplotypes. The effect on GFR decline was then supported by a study of 1333 subjects from the San Diego Veterans Affairs Hypertension Cohort (VAHC), followed over ∼4.5 years. Linear effect models were utilized to determine both genotype [single-nucleotide polymorphism (SNP)] and genotype (SNP)-by-time interactions.

RESULTS

In AASK, the polymorphism at A1298C predicted the rate of GFR decline: A1298/A1298 major allele homozygosity resulted in a less pronounced decline of GFR, with a significant SNP-by-time interaction. An independent follow-up study in the San Diego VAHC subjects supports that A1298/A1298 homozygotes have the greatest estimated GFR throughout the study. Haplotype analysis with C677T yielded concurring results.

CONCLUSION

We conclude that the MTHFR-coding polymorphism at A1298C is associated with renal decline in African-Americans with hypertensive nephrosclerosis and is supported by a veteran cohort with a primary care diagnosis of hypertension. Further investigation is needed to confirm such findings and to determine what molecular mechanism may contribute to this association.

Adrenergic beta-1 receptor genetic variation predicts longitudinal rate of GFR decline in hypertensive nephrosclerosis

BACKGROUND

End-stage renal disease (ESRD) due to hypertension is common and displays familial aggregation in African Americans, suggesting genetic risk factors, including adrenergic activity alterations which are noted in both hypertension and ESRD.

METHODS

We analysed 554 hypertensive nephrosclerosis participants (without clinically significant proteinuria) from the longitudinal National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) African American Study of Kidney Disease and Hypertension (AASK) cohort to determine whether decline in glomerular filtration rate (GFR) over approximately 3.8 years was predicted by common genetic variation within the adrenergic beta-1 (ADRB1) receptor at non-synonymous positions Ser49Gly and Arg389Gly.

RESULTS

The polymorphism at Ser49Gly (though not Arg389Gly, in only partial linkage disequilibrium at r(2) = 0.18) predicted the chronic rate of GFR decline, with minimal decline in Gly(49)/Gly(49) (minor allele) homozygotes compared to Ser(49) carriers; concordant results were observed for haplotypes and diploid haplotype pairs at the locus. An independent replication study in 1244 subjects from the San Diego Veterans Affairs Hypertension Cohort confirmed that Gly(49)/Gly(49) homozygotes displayed the least rapid decline of eGFR over approximately 3.6 years.

CONCLUSION

We conclude that GFR decline rate in hypertensive renal disease is controlled in part by genetic variation within the adrenergic pathway, particularly at ADRB1. The results suggest novel strategies to approach the role of the adrenergic system in the risk and treatment of progressive renal disease.