Personalized Medicine and the Power of Electronic Health Records

Abul‐Husn, Noura S.; Kenny, Eimear E.

doi:10.1016/j.cell.2019.02.039

Cited by 239 publications

(175 citation statements)

References 120 publications

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“…Achieving this goal will necessitate greater precision in our health systems so that the right intervention can be applied in the right population at the right time. Recent advances in genomic technology have resulted in a rapid increase in the amount of human genomic data in health systems 6 . Here we demonstrate how this data may be used for fine-scale population health monitoring.…”

Section: Discussionmentioning

confidence: 99%

“…With the advent of large, population-based DNA biobanks in health systems, new opportunities are available to characterize the links between demography and a broad range of health outcomes [3][4][5][6][7] . Knowledge about genetic variation shared across human populations can aid in understanding the demographic events that might impact disease burden across populations.…”

Section: Introductionmentioning

confidence: 99%

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Towards a fine-scale population health monitoring system

Belbin

Wenric

Cullina

et al. 2019

Preprint

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Understanding population health disparities is an essential component of equitable precision health efforts. Epidemiology research often relies on definitions of race and ethnicity, but these population labels may not adequately capture disease burdens specific to sub-populations. Here we propose a framework for repurposing data from Electronic Health Records (EHRs) in concert with genomic data to explore enrichment of disease within sub-populations. Using data from a diverse biobank in New York City, we genetically identified 17 sub-populations, and noted the presence of genetic founder effects in 7. By then linking community membership to the EHR, we were able to identify over 600 health outcomes that were statistically enriched within a specific population, with many representing known associations, and many others being novel. This work reinforces the utility of linking genomic data to EHRs, and provides a framework towards fine-scale monitoring of population health.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Towards a fine-scale population health monitoring system

Belbin

Wenric

Cullina

et al. 2019

Preprint

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“…Additionally, some percentage of variants of uncertain significance may in fact be pathogenic, and likely will be classified as such in the future. We were also constrained by the use of EHR-extracted clinical information, which may not reflect complete medical and family history (49), and may downwardly bias the true penetrance of HBOC in our cohort.…”

Section: Discussionmentioning

confidence: 99%

Exome Sequencing Reveals a High Prevalence ofBRCA1andBRCA2Founder Variants in a Diverse Population-Based Biobank

Abul‐Husn

Soper

Odgis

et al. 2019

Preprint

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Word Count: 340 Manuscript Word Count: 4214Abstract Pathogenic variants in BRCA1 and BRCA2 (BRCA1/2) lead to increased risk of breast, ovarian, and other cancers, but most variant positive individuals in the general population are unaware of their risk, and little is known about the prevalence of pathogenic BRCA1/2 variants in non-European populations.We investigated BRCA1/2 prevalence and impact using exome sequencing and electronic health record (EHR) data from 30,223 adult participants of the BioMe Biobank in New York City. There were 218 (0.7%) individuals harboring expected pathogenic variants, resulting in an overall prevalence of 1 in 139. In subpopulations defined by genetic ancestry, the highest prevalence was in individuals of Ashkenazi Jewish (AJ; 1 in 49), Filipino and Southeast Asian (1 in 81), and Non-AJ European (1 in 103) descent. Among 218 variant positive individuals, 112 (51.4%) harbored known founder variants: 80 had AJ founder variants (BRCA1 c.5266dupC and c.68_69delAG, and BRCA2 c.5946delT), 7 had a Puerto Rican founder variant (BRCA2 c.3922G>T), and 25 had one of 19 other founder variants. Non-European populations were more likely to harbor BRCA1/2 variants that were not classified in ClinVar, or that had uncertain or conflicting evidence for pathogenicity. Within mixed ancestry populations, such as Hispanic/Latinos with genetic ancestry from Africa, Europe, and the Americas, there was a strong correlation between the proportion African genetic ancestry and the likelihood of harboring a BRCA1/2 variant with uncertain or conflicting evidence for pathogenicity. Based on EHR and participant questionnaire data, ~28% of variant positive individuals had a personal history, and ~45% a personal or family history of BRCA1/2-associated cancers.Approximately 27% of variant positive individuals had evidence of prior clinical genetic testing for BRCA1/2. However, individuals with AJ founder variants were twice as likely to have had a clinical test (38%) than those with other pathogenic variants (19%). These findings deepen our knowledge about BRCA1/2 variants and associated cancer risk in diverse populations, indicate a gap in knowledge about potential cancer-related variants in non-European populations, and suggest that genomic screening in diverse patient populations may be an effective tool to identify at-risk individuals.

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“…In other words, SIRE categories provide valuable information for stratifying PGx risk at the population level but not for predicting individual-level PGx variants. Having said that, and despite the promise of population scale genomic screening initiatives and biobanks 80 , such as the NIH All of Us project 81 , the day when all Americans will have ready access to their genetic profiles remains far in the future. Unfortunately, this is likely to be even more so for minority communities that are vastly underrepresented among clinical genetic cohorts 82; 83 .…”

Section: The Current and Future Utility Of Race And Ethnicity In Pharmentioning

confidence: 99%

Population structure and pharmacogenomic risk stratification in the United States

Nagar

Conley

Jordan

2020

Preprint

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Pharmacogenomic (PGx) variants mediate how individuals respond to medication, and response differences among racial/ethnic groups have been attributed to patterns of PGx diversity. We hypothesized that genetic ancestry (GA) would provide higher resolution for stratifying PGx risk, since it serves as a more reliable surrogate for genetic diversity than self-identified race/ethnicity (SIRE), which includes a substantial social component. We analyzed a cohort of 8,628 individuals from the United States (US), for whom we had both SIRE information and whole genome genotypes, with a focus on the three largest SIRE groups in the US: White, Black, and Hispanic. Whole genome genotypes were used to characterize individuals' continental ancestry fractions -European, African, and Native American -and individuals were grouped according to their GA profiles. SIRE and GA groups were found to be highly concordant. Continental ancestry predicts individuals' SIRE with >96% accuracy, and accordingly GA provides only a marginal increase in resolution for PGx risk stratification. PGx variants are highly diverged compared to the genomic background; 82 variants show significant frequency differences among SIRE groups, and genome-wide patterns of PGx variation are almost entirely concordant with SIRE. Nevertheless, 97% of PGx variation is found within rather than between groups. Examples of highly differentiated PGx variants illustrate how SIRE partitions PGx variation based on group-specific ancestry patterns and contains valuable information for risk stratification. Finally, we show that individuals who identify as Black or Hispanic benefit more when SIRE is considered for treatment decisions than individuals from the majority White population.

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Personalized Medicine and the Power of Electronic Health Records

Cited by 239 publications

References 120 publications

Towards a fine-scale population health monitoring system

Towards a fine-scale population health monitoring system

Exome Sequencing Reveals a High Prevalence ofBRCA1andBRCA2Founder Variants in a Diverse Population-Based Biobank

Population structure and pharmacogenomic risk stratification in the United States

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