Biology subjects

Bottinger, E. P.

Publications and source records attributed to Bottinger, E. P..

5 recordsLinked to original sources

bioRxiv2019

Towards a Fine-scale Population Health Monitoring System

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.

genomics↗

bioRxiv2019

Rapid response to the Alpha-1 Adrenergic Agent Phenylephrine in the Perioperative Period is Impacted by Genomics and Ancestry

BackgroundThe emergence of genomic data in biobanks and health systems offers new ways to derive medically important phenotypes, including acute phenotypes that occur during in-patient clinical care. We hypothesized that there is a genetic underpinning to the magnitude of the response to phenylephrine, an 1-adrenergic receptor agonist commonly used to treat hypotension during anesthesia and surgery.\n\nMethodsWe quantified the response to phenylephrine by determining the delta between the minimum blood pressure (BP) within five minutes before and the maximum BP within five minutes after bolus administration. We then performed a genome-wide association study (GWAS) adjusted for genetic ancestry, demographics, and relevant clinical covariates to investigate genetic factors underlying individual differences systolic BP response to phenylephrine ({Delta}SBP), as well as mean arterial pressure ({Delta}MAP) and diastolic BP ({Delta}DBP), for both the entire study cohort as well as for each of 3 ancestry sub-cohorts; European American(EA), African American(AA), and Hispanic American(HA).\n\nResults4,317 patients met inclusion criteria, of which 3,699 were genotyped. Average {Delta}BP values over the entire cohort were {Delta}SBP=17(+-25) mmHg, {Delta}MAP=14(+-18) mmHg, {Delta}DBP=11(+-14) mmHg. The largest difference between populations was observed for {Delta}SBP ({Delta}SBPEA=20(+-24) mmHg; {Delta}SBPHA=16(+-25) mmHg; {Delta}SBPAA=15(+-25) mmHg). The differences remained after adjusting for clinical covariates and ancestry (EA vs. HA: {Delta}SBP, p<0.032;{Delta}MAP, p<0.021;{Delta}DBP,p<0.008);(EA vs. AA:{Delta}SBP,p<5.13x10-5;{Delta}MAP,p<2.1x10-4;{Delta}DBP,p<3.3x10-4). GWAS revealed significant associations between loci and BP response in 5 different genome regions (p<5x10-8) in the entire cohort, and suggestive associations in 2 different regions in EAs (p<6x10-8,p<7x10-8). We observed non-random enrichment in association with SBP drug response in 165 loci previously reported to be associated with systolic blood pressure. Finally, we discovered rare variants, rs188427942 and rs147664194 present at [~]1% in EAs and rs146535276 present at [~]1% in AAs respectively, where patients carrying one copy of these variants show no response to phenylephrine.\n\nConclusionsIt is possible to derive a quantitative phenotype suited for comparative statistics and genome-wide association studies from routinely collected perioperative data. There are population differences in rapid response to phenylephrine, large effect alleles and novel genes affecting pharmaceutical response, and phenylephrine non-responders, with implications for personalized treatment during surgery.

genomics↗

bioRxiv2018

Trans-ethnic genome-wide association study provides insight into effector genes and molecular mechanisms for kidney function and highlights a causal effect on kidney-specific disease aetiologies

Chronic kidney disease (CKD) affects [~]10% of the global population, with considerable ethnic differences in prevalence and aetiology. We assembled genome-wide association studies (GWAS)1-3 of estimated glomerular filtration rate (eGFR), a measure of kidney function that defines CKD, in 312,468 individuals from four ancestry groups. We identified 93 loci (20 novel), which were delineated to 127 distinct association signals. These signals were homogenous across ancestries, and were enriched for protein-coding exons, kidney-specific histone modifications, and transcription factor binding sites for HDAC2 and EZH2. Fine-mapping revealed 40 high-confidence variants driving eGFR associations and highlighted potential causal genes with cell-type specific expression in glomerulus, and proximal and distal nephron. Mendelian randomisation (MR) supported causal effects of eGFR on overall and cause-specific CKD, kidney stone formation, diastolic blood pressure (DBP) and hypertension. These results define novel molecular mechanisms and effector genes for eGFR, offering insight into clinical outcomes and routes to CKD treatment development.

genetics↗

bioRxiv2018

Fine-mapping of an expanded set of type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps

We aggregated genome-wide genotyping data from 32 European-descent GWAS (74,124 T2D cases, 824,006 controls) imputed to high-density reference panels of >30,000 sequenced haplotypes. Analysis of {small tilde}27M variants ({small tilde}21M with minor allele frequency [MAF]<5%), identified 243 genome-wide significant loci (p<5x10-8; MAF 0.02%-50%; odds ratio [OR] 1.04-8.05), 135 not previously-implicated in T2D-predisposition. Conditional analyses revealed 160 additional distinct association signals (p<10-5) within the identified loci. The combined set of 403 T2D-risk signals includes 56 low-frequency (0.5%[≤]MAF<5%) and 24 rare (MAF<0.5%) index SNPs at 60 loci, including 14 with estimated allelic OR>2. Forty-one of the signals displayed effect-size heterogeneity between BMI-unadjusted and adjusted analyses. Increased sample size and improved imputation led to substantially more precise localisation of causal variants than previously attained: at 51 signals, the lead variant after fine-mapping accounted for >80% posterior probability of association (PPA) and at 18 of these, PPA exceeded 99%. Integration with islet regulatory annotations enriched for T2D association further reduced median credible set size (from 42 variants to 32) and extended the number of index variants with PPA>80% to 73. Although most signals mapped to regulatory sequence, we identified 18 genes as human validated therapeutic targets through coding variants that are causal for disease. Genome wide chip heritability accounted for 18% of T2D-risk, and individuals in the 2.5% extremes of a polygenic risk score generated from the GWAS data differed >9-fold in risk. Our observations highlight how increases in sample size and variant diversity deliver enhanced discovery and single-variant resolution of causal T2D-risk alleles, and the consequent impact on mechanistic insights and clinical translation.

genomics↗

bioRxiv2017

Genetic Identification Of A Common Collagen Disease In Puerto Ricans Via Identity-By-Descent Mapping In A Health System

Achieving confidence in the causality of a disease locus is a complex task that often requires supporting data from both statistical genetics and clinical genomics. Here we describe a combined approach to identify and characterize a genetic disorder that leverages distantly related patients in a health system and population-scale mapping. We utilize genomic data to uncover components of distant pedigrees, in the absence of recorded pedigree information, in the multi-ethnic BioMe biobank in New York City. By linking to medical records, we discover a locus associated with genetic relatedness that also underlies extreme short stature. We link the gene, COL27A1, with a little-known genetic disease, previously thought to be rare and recessive. We demonstrate that disease manifests in both heterozygotes and homozygotes, indicating a common collagen disorder impacting up to 2% of individuals of Puerto Rican ancestry, leading to a better understanding of the continuum of complex and Mendelian disease.

genomics↗