Publications by authors named "Ron Do"

79 Publications

Whole-Genome Sequencing Association Analyses of Stroke and Its Subtypes in Ancestrally Diverse Populations From Trans-Omics for Precision Medicine Project.

Stroke 2021 Nov 3:STROKEAHA120031792. Epub 2021 Nov 3.

Department of Medicine, Stanford University, CA (T.L.A.).

Background And Purpose: Stroke is the leading cause of death and long-term disability worldwide. Previous genome-wide association studies identified 51 loci associated with stroke (mostly ischemic) and its subtypes among predominantly European populations. Using whole-genome sequencing in ancestrally diverse populations from the Trans-Omics for Precision Medicine (TOPMed) Program, we aimed to identify novel variants, especially low-frequency or ancestry-specific variants, associated with all stroke, ischemic stroke and its subtypes (large artery, cardioembolic, and small vessel), and hemorrhagic stroke and its subtypes (intracerebral and subarachnoid).

Methods: Whole-genome sequencing data were available for 6833 stroke cases and 27 116 controls, including 22 315 European, 7877 Black, 2616 Hispanic/Latino, 850 Asian, 54 Native American, and 237 other ancestry participants. In TOPMed, we performed single variant association analysis examining 40 million common variants and aggregated association analysis focusing on rare variants. We also combined TOPMed European populations with over 28 000 additional European participants from the UK BioBank genome-wide array data through meta-analysis.

Results: In the single variant association analysis in TOPMed, we identified one novel locus for large artery at whole-genome-wide significance (<5.00×10) and 4 novel loci at genome-wide significance (<5.00×10), all of which need confirmation in independent studies. Lead variants in all 5 loci are low-frequency but are more common in non-European populations. An aggregation of synonymous rare variants within the gene demonstrated suggestive evidence of association for hemorrhagic stroke (<3.11×10). By meta-analyzing European ancestry samples in TOPMed and UK BioBank, we replicated several previously reported stroke loci including , , , and .

Conclusions: We represent the first association analysis for stroke and its subtypes using whole-genome sequencing data from ancestrally diverse populations. While our findings suggest the potential benefits of combining whole-genome sequencing data with populations of diverse genetic backgrounds to identify possible low-frequency or ancestry-specific variants, they also highlight the need to increase genome coverage and sample sizes.
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http://dx.doi.org/10.1161/STROKEAHA.120.031792DOI Listing
November 2021

Derivation and Validation of Genome-Wide Polygenic Score for Ischemic Heart Failure.

J Am Heart Assoc 2021 Nov 29;10(22):e021916. Epub 2021 Oct 29.

The Charles Bronfman Institute for Personalized MedicineIcahn School of Medicine at Mount Sinai New York NY.

Background Despite advances in cardiovascular disease and risk factor management, mortality from ischemic heart failure (HF) in patients with coronary artery disease (CAD) remains high. Given the partial role of genetics in HF and lack of reliable risk stratification tools, we developed and validated a polygenic risk score for HF in patients with CAD, which we term HF-PRS. Methods and Results Using summary statistics from a recent genome-wide association study for HF, we developed candidate PRSs in the Mount Sinai Bio CAD patient cohort (N=6274) by using the pruning and thresholding method and LDPred. We validated the best score in the Penn Medicine BioBank (N=7250) and performed a subgroup analysis in a high-risk cohort who had undergone coronary catheterization. We observed a significant association between HF-PRS score and ischemic HF even after adjusting for evidence of obstructive CAD in patients of European ancestry in both Bio (odds ratio [OR], 1.14 per SD; 95% CI, 1.05-1.24; =0.003) and Penn Medicine BioBank (OR, 1.07 per SD; 95% CI, 1.01-1.13; =0.016). In European patients with CAD in Penn Medicine BioBank who had undergone coronary catheterization, individuals in the top 10th percentile of PRS had a 2-fold increased odds of ischemic HF (OR, 2.0; 95% CI, 1.1-3.7; =0.02) compared with the bottom 10th percentile. Conclusions A PRS for HF enables risk stratification in patients with CAD. Future prospective studies aimed at demonstrating clinical utility are warranted for adoption in the patient setting.
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http://dx.doi.org/10.1161/JAHA.121.021916DOI Listing
November 2021

Non-invasive ventilation versus mechanical ventilation in hypoxemic patients with COVID-19.

Infection 2021 Oct 5;49(5):989-997. Epub 2021 Jun 5.

The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, Annenberg Building, Floor 18 Room 80A, 1468 Madison Ave, New York, NY, 10029, USA.

Purpose: Limited mechanical ventilators (MV) during the Coronavirus disease (COVID-19) pandemic have led to the use of non-invasive ventilation (NIV) in hypoxemic patients, which has not been studied well. We aimed to assess the association of NIV versus MV with mortality and morbidity during respiratory intervention among hypoxemic patients admitted with COVID-19.

Methods: We performed a retrospective multi-center cohort study across 5 hospitals during March-April 2020. Outcomes included mortality, severe COVID-19-related symptoms, time to discharge, and final oxygen saturation (SpO2) at the conclusion of the respiratory intervention. Multivariable regression of outcomes was conducted in all hypoxemic participants, 4 subgroups, and propensity-matched analysis.

Results: Of 2381 participants with laboratory-confirmed SARS-CoV-2, 688 were included in the study who were hypoxemic upon initiation of respiratory intervention. During the study period, 299 participants died (43%), 163 were admitted to the ICU (24%), and 121 experienced severe COVID-19-related symptoms (18%). Participants on MV had increased mortality than those on NIV (128/154 [83%] versus 171/534 [32%], OR = 30, 95% CI 16-60) with a mean survival of 6 versus 15 days, respectively. The MV group experienced more severe COVID-19-related symptoms [55/154 (36%) versus 66/534 (12%), OR = 4.3, 95% CI 2.7-6.8], longer time to discharge (mean 17 versus 7.1 days), and lower final SpO2 (92 versus 94%). Across all subgroups and propensity-matched analysis, MV was associated with a greater OR of death than NIV.

Conclusions: NIV was associated with lower respiratory intervention mortality and morbidity than MV. However, findings may be liable to unmeasured confounding and further study from randomized controlled trials is needed to definitively determine the role of NIV in hypoxemic patients with COVID-19.
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http://dx.doi.org/10.1007/s15010-021-01633-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8179090PMC
October 2021

Genetic pleiotropy of ERCC6 loss-of-function and deleterious missense variants links retinal dystrophy, arrhythmia, and immunodeficiency in diverse ancestries.

Hum Mutat 2021 Aug 31;42(8):969-977. Epub 2021 May 31.

Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

Biobanks with exomes linked to electronic health records (EHRs) enable the study of genetic pleiotropy between rare variants and seemingly disparate diseases. We performed robust clinical phenotyping of rare, putatively deleterious variants (loss-of-function [LoF] and deleterious missense variants) in ERCC6, a gene implicated in inherited retinal disease. We analyzed 213,084 exomes, along with a targeted set of retinal, cardiac, and immune phenotypes from two large-scale EHR-linked biobanks. In the primary analysis, a burden of deleterious variants in ERCC6 was strongly associated with (1) retinal disorders; (2) cardiac and electrocardiogram perturbations; and (3) immunodeficiency and decreased immunoglobulin levels. Meta-analysis of results from the BioMe Biobank and UK Biobank showed a significant association of deleterious ERCC6 burden with retinal dystrophy (odds ratio [OR] = 2.6, 95% confidence interval [CI]: 1.5-4.6; p = 8.7 × 10 ), atypical atrial flutter (OR = 3.5, 95% CI: 1.9-6.5; p = 6.2 × 10 ), arrhythmia (OR = 1.5, 95% CI: 1.2-2.0; p = 2.7 × 10 ), and lymphocyte immunodeficiency (OR = 3.8, 95% CI: 2.1-6.8; p = 5.0 × 10 ). Carriers of ERCC6 LoF variants who lacked a diagnosis of these conditions exhibited increased symptoms, indicating underdiagnosis. These results reveal a unique genetic link among retinal, cardiac, and immune disorders and underscore the value of EHR-linked biobanks in assessing the full clinical profile of carriers of rare variants.
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http://dx.doi.org/10.1002/humu.24220DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295228PMC
August 2021

Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices.

Nat Commun 2021 04 12;12(1):2182. Epub 2021 Apr 12.

Division of Cardiology, George Washington University School of Medicine and Healthcare Sciences, Washington, DC, USA.

Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.
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http://dx.doi.org/10.1038/s41467-021-22339-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8042019PMC
April 2021

Genome-wide polygenic risk score for retinopathy of type 2 diabetes.

Hum Mol Genet 2021 May;30(10):952-960

The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Diabetic retinopathy (DR) is a common consequence in type 2 diabetes (T2D) and a leading cause of blindness in working-age adults. Yet, its genetic predisposition is largely unknown. Here, we examined the polygenic architecture underlying DR by deriving and assessing a genome-wide polygenic risk score (PRS) for DR. We evaluated the PRS in 6079 individuals with T2D of European, Hispanic, African and other ancestries from a large-scale multi-ethnic biobank. Main outcomes were PRS association with DR diagnosis, symptoms and complications, and time to diagnosis, and transferability to non-European ancestries. We observed that PRS was significantly associated with DR. A standard deviation increase in PRS was accompanied by an adjusted odds ratio (OR) of 1.12 [95% confidence interval (CI) 1.04-1.20; P = 0.001] for DR diagnosis. When stratified by ancestry, PRS was associated with the highest OR in European ancestry (OR = 1.22, 95% CI 1.02-1.41; P = 0.049), followed by African (OR = 1.15, 95% CI 1.03-1.28; P = 0.028) and Hispanic ancestries (OR = 1.10, 95% CI 1.00-1.10; P = 0.050). Individuals in the top PRS decile had a 1.8-fold elevated risk for DR versus the bottom decile (P = 0.002). Among individuals without DR diagnosis, the top PRS decile had more DR symptoms than the bottom decile (P = 0.008). The PRS was associated with retinal hemorrhage (OR = 1.44, 95% CI 1.03-2.02; P = 0.03) and earlier DR presentation (10% probability of DR by 4 years in the top PRS decile versus 8 years in the bottom decile). These results establish the significant polygenic underpinnings of DR and indicate the need for more diverse ancestries in biobanks to develop multi-ancestral PRS.
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http://dx.doi.org/10.1093/hmg/ddab067DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8165647PMC
May 2021

Exploiting the GTEx resources to decipher the mechanisms at GWAS loci.

Genome Biol 2021 01 26;22(1):49. Epub 2021 Jan 26.

Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA.

The resources generated by the GTEx consortium offer unprecedented opportunities to advance our understanding of the biology of human diseases. Here, we present an in-depth examination of the phenotypic consequences of transcriptome regulation and a blueprint for the functional interpretation of genome-wide association study-discovered loci. Across a broad set of complex traits and diseases, we demonstrate widespread dose-dependent effects of RNA expression and splicing. We develop a data-driven framework to benchmark methods that prioritize causal genes and find no single approach outperforms the combination of multiple approaches. Using colocalization and association approaches that take into account the observed allelic heterogeneity of gene expression, we propose potential target genes for 47% (2519 out of 5385) of the GWAS loci examined.
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http://dx.doi.org/10.1186/s13059-020-02252-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836161PMC
January 2021

Probing the aggregated effects of purifying selection per individual on 1,380 medical phenotypes in the UK Biobank.

PLoS Genet 2021 01 25;17(1):e1009337. Epub 2021 Jan 25.

The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.

Understanding the relationship between natural selection and phenotypic variation has been a long-standing challenge in human population genetics. With the emergence of biobank-scale datasets, along with new statistical metrics to approximate strength of purifying selection at the variant level, it is now possible to correlate a proxy of individual relative fitness with a range of medical phenotypes. We calculated a per-individual deleterious load score by summing the total number of derived alleles per individual after incorporating a weight that approximates strength of purifying selection. We assessed four methods for the weight, including GERP, phyloP, CADD, and fitcons. By quantitatively tracking each of these scores with the site frequency spectrum, we identified phyloP as the most appropriate weight. The phyloP-weighted load score was then calculated across 15,129,142 variants in 335,161 individuals from the UK Biobank and tested for association on 1,380 medical phenotypes. After accounting for multiple test correction, we observed a strong association of the load score amongst coding sites only on 27 traits including body mass, adiposity and metabolic rate. We further observed that the association signals were driven by common variants (derived allele frequency > 5%) with high phyloP score (phyloP > 2). Finally, through permutation analyses, we showed that the load score amongst coding sites had an excess of nominally significant associations on many medical phenotypes. These results suggest a broad impact of deleterious load on medical phenotypes and highlight the deleterious load score as a tool to disentangle the complex relationship between natural selection and medical phenotypes.
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http://dx.doi.org/10.1371/journal.pgen.1009337DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7861521PMC
January 2021

An integrative multiomic network model links lipid metabolism to glucose regulation in coronary artery disease.

Nat Commun 2021 01 22;12(1):547. Epub 2021 Jan 22.

Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.

Elevated plasma cholesterol and type 2 diabetes (T2D) are associated with coronary artery disease (CAD). Individuals treated with cholesterol-lowering statins have increased T2D risk, while individuals with hypercholesterolemia have reduced T2D risk. We explore the relationship between lipid and glucose control by constructing network models from the STARNET study with sequencing data from seven cardiometabolic tissues obtained from CAD patients during coronary artery by-pass grafting surgery. By integrating gene expression, genotype, metabolomic, and clinical data, we identify a glucose and lipid determining (GLD) regulatory network showing inverse relationships with lipid and glucose traits. Master regulators of the GLD network also impact lipid and glucose levels in inverse directions. Experimental inhibition of one of the GLD network master regulators, lanosterol synthase (LSS), in mice confirms the inverse relationships to glucose and lipid levels as predicted by our model and provides mechanistic insights.
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http://dx.doi.org/10.1038/s41467-020-20750-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7822923PMC
January 2021

Exome-wide evaluation of rare coding variants using electronic health records identifies new gene-phenotype associations.

Nat Med 2021 01 11;27(1):66-72. Epub 2021 Jan 11.

Division of Cardiothoracic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX, USA.

The clinical impact of rare loss-of-function variants has yet to be determined for most genes. Integration of DNA sequencing data with electronic health records (EHRs) could enhance our understanding of the contribution of rare genetic variation to human disease. By leveraging 10,900 whole-exome sequences linked to EHR data in the Penn Medicine Biobank, we addressed the association of the cumulative effects of rare predicted loss-of-function variants for each individual gene on human disease on an exome-wide scale, as assessed using a set of diverse EHR phenotypes. After discovering 97 genes with exome-by-phenome-wide significant phenotype associations (P < 10), we replicated 26 of these in the Penn Medicine Biobank, as well as in three other medical biobanks and the population-based UK Biobank. Of these 26 genes, five had associations that have been previously reported and represented positive controls, whereas 21 had phenotype associations not previously reported, among which were genes implicated in glaucoma, aortic ectasia, diabetes mellitus, muscular dystrophy and hearing loss. These findings show the value of aggregating rare predicted loss-of-function variants into 'gene burdens' for identifying new gene-disease associations using EHR phenotypes in a medical biobank. We suggest that application of this approach to even larger numbers of individuals will provide the statistical power required to uncover unexplored relationships between rare genetic variation and disease phenotypes.
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http://dx.doi.org/10.1038/s41591-020-1133-8DOI Listing
January 2021

Intraocular Pressure, Glaucoma, and Dietary Caffeine Consumption: A Gene-Diet Interaction Study from the UK Biobank.

Ophthalmology 2021 06 14;128(6):866-876. Epub 2020 Dec 14.

Department of Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York.

Purpose: We examined the association of habitual caffeine intake with intraocular pressure (IOP) and glaucoma and whether genetic predisposition to higher IOP modified these associations. We also assessed whether genetic predisposition to higher coffee consumption was related to IOP.

Design: Cross-sectional study in the UK Biobank.

Participants: We included 121 374 participants (baseline ages, 39-73 years) with data on coffee and tea intake (collected 2006-2010) and corneal-compensated IOP measurements in 2009. In a subset of 77 906 participants with up to 5 web-based 24-hour-recall food frequency questionnaires (2009-2012), we evaluated total caffeine intake. We also assessed the same relationships with glaucoma (9286 cases and 189 763 controls).

Methods: We evaluated multivariable-adjusted associations with IOP using linear regression and with glaucoma using logistic regression. For both outcomes, we examined gene-diet interactions using a polygenic risk score (PRS) that combined the effects of 111 genetic variants associated with IOP. We also performed Mendelian randomization using 8 genetic variants associated with coffee intake to assess potential causal effects of coffee consumption on IOP.

Main Outcome Measures: Intraocular pressure and glaucoma.

Results: Mendelian randomization analysis did not support a causal effect of coffee drinking on IOP (P > 0.1). Greater caffeine intake was associated weakly with lower IOP: the highest (≥232 mg/day) versus lowest (<87 mg/day) caffeine consumption was associated with a 0.10-mmHg lower IOP (P = 0.01). However, the IOP PRS modified this association: among those in the highest IOP PRS quartile, consuming > 480 mg/day versus < 80 mg/day was associated with a 0.35-mmHg higher IOP (P = 0.01). The relationship between caffeine intake and glaucoma was null (P ≥ 0.1). However, the IOP PRS also modified this relationship: compared with those in the lowest IOP PRS quartile consuming no caffeine, those in the highest IOP PRS quartile consuming ≥ 321 mg/day showed a 3.90-fold higher glaucoma prevalence (P = 0.0003).

Conclusions: Habitual caffeine consumption was associated weakly with lower IOP, and the association between caffeine consumption and glaucoma was null. However, among participants with the strongest genetic predisposition to elevated IOP, greater caffeine consumption was associated with higher IOP and higher glaucoma prevalence.
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http://dx.doi.org/10.1016/j.ophtha.2020.12.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8154631PMC
June 2021

Prediction of Incident Heart Failure in TTR Val122Ile Carriers One Year Ahead of Diagnosis in a Multiethnic Biobank.

Am J Cardiol 2021 03 18;142:151-153. Epub 2020 Dec 18.

The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA; BioMe Phenomics Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA. Electronic address:

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http://dx.doi.org/10.1016/j.amjcard.2020.12.015DOI Listing
March 2021

A genotype-first approach to exploring Mendelian cardiovascular traits with clear external manifestations.

Genet Med 2021 01 29;23(1):94-102. Epub 2020 Sep 29.

Mindich Child Health and Development Institute, Icahn School of Medicine, New York, NY, USA.

Purpose: The purpose of this study is to use a genotype-first approach to explore highly penetrant, autosomal dominant cardiovascular diseases with external features, the RASopathies and Marfan syndrome (MFS), using biobank data.

Methods: This study uses exome sequencing and corresponding phenotypic data from Mount Sinai's BioMe (n = 32,344) and the United Kingdom Biobank (UKBB; n = 49,960). Variant curation identified pathogenic/likely pathogenic (P/LP) variants in RASopathy genes and FBN1.

Results: Twenty-one subjects harbored P/LP RASopathy variants; three (14%) were diagnosed, and another 46% had ≥1 classic Noonan syndrome (NS) feature. Major NS features (short stature [9.5% p = 7e-5] and heart anomalies [19%, p < 1e-5]) were less frequent than expected. Prevalence of hypothyroidism/autoimmune disorders was enriched compared with biobank populations (p = 0.007). For subjects with FBN1 P/LP variants, 14/41 (34%) had a MFS diagnosis or highly suggestive features. Five of 15 participants (33%) with echocardiographic data had aortic dilation, fewer than expected (p = 8e-6). Ectopia lentis affected only 15% (p < 1e-5).

Conclusions: Substantial fractions of individuals harboring P/LP variants with partial or full phenotypic matches to a RASopathy or MFS remain undiagnosed, some not meeting diagnostic criteria. Routine population genotyping would enable multidisciplinary care and avoid life-threatening events.
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http://dx.doi.org/10.1038/s41436-020-00973-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7796917PMC
January 2021

Tissue-specific genetic features inform prediction of drug side effects in clinical trials.

Sci Adv 2020 Sep 10;6(37). Epub 2020 Sep 10.

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Adverse side effects often account for the failure of drug clinical trials. We evaluated whether a phenome-wide association study (PheWAS) of 1167 phenotypes in >360,000 U.K. Biobank individuals, in combination with gene expression and expression quantitative trait loci (eQTL) in 48 tissues, can inform prediction of drug side effects in clinical trials. We determined that drug target genes with five genetic features-tissue specificity of gene expression, Mendelian associations, phenotype- and tissue-level effects of genome-wide association (GWA) loci driven by eQTL, and genetic constraint-confer a 2.6-fold greater risk of side effects, compared to genes without such features. The presence of eQTL in multiple tissues resulted in more unique phenotypes driven by GWA loci, suggesting that drugs delivered to multiple tissues can induce several side effects. We demonstrate the utility of PheWAS and eQTL data from multiple tissues for informing drug side effect prediction and highlight the need for tissue-specific drug delivery.
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http://dx.doi.org/10.1126/sciadv.abb6242DOI Listing
September 2020

Derivation and validation of genome-wide polygenic score for urinary tract stone diagnosis.

Kidney Int 2020 11 12;98(5):1323-1330. Epub 2020 Jun 12.

The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The BioMe Phenomics Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Renal Program, James J Peters Veterans Affairs Medical Center at Bronx, New York, New York, USA. Electronic address:

Urinary tract stones have high heritability indicating a strong genetic component. However, genome-wide association studies (GWAS) have uncovered only a few genome wide significant single nucleotide polymorphisms (SNPs). Polygenic risk scores (PRS) sum cumulative effect of many SNPs and shed light on underlying genetic architecture. Using GWAS summary statistics from 361,141 participants in the United Kingdom Biobank, we generated a PRS and determined association with stone diagnosis in 28,877 participants in the Mount Sinai BioMe Biobank. In BioMe (1,071 cases and 27,806 controls), for every standard deviation increase, we observed a significant increment in adjusted odds ratio of a factor of 1.2 (95% confidence interval 1.13-1.26). In comparison, a risk score comprised of GWAS significant SNPs was not significantly associated with diagnosis. After stratifying individuals into low and high-risk categories on clinical risk factors, there was a significant increment in adjusted odds ratio of 1.3 (1.12-1.6) in the low- and 1.2 (1.1-1.2) in the high-risk group for every standard deviation increment in PRS. In a 14,348-participant validation cohort (Penn Medicine Biobank), every standard deviation increment was associated with a significant adjusted odds ratio of 1.1 (1.03 - 1.2). Thus, a genome-wide PRS is associated with urinary tract stones overall and in the absence of known clinical risk factors and illustrates their complex polygenic architecture.
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http://dx.doi.org/10.1016/j.kint.2020.04.055DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7606592PMC
November 2020

Acute Kidney Injury in Hospitalized Patients with COVID-19.

medRxiv 2020 May 8. Epub 2020 May 8.

Importance: Preliminary reports indicate that acute kidney injury (AKI) is common in coronavirus disease (COVID)-19 patients and is associated with worse outcomes. AKI in hospitalized COVID-19 patients in the United States is not well-described.

Objective: To provide information about frequency, outcomes and recovery associated with AKI and dialysis in hospitalized COVID-19 patients.

Design: Observational, retrospective study.

Setting: Admitted to hospital between February 27 and April 15, 2020.

Participants: Patients aged ≥18 years with laboratory confirmed COVID-19 Exposures: AKI (peak serum creatinine increase of 0.3 mg/dL or 50% above baseline). Main Outcomes and Measures: Frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aOR) with mortality. We also trained and tested a machine learning model for predicting dialysis requirement with independent validation.

Results: A total of 3,235 hospitalized patients were diagnosed with COVID-19. AKI occurred in 1406 (46%) patients overall and 280 (20%) with AKI required renal replacement therapy. The incidence of AKI (admission plus new cases) in patients admitted to the intensive care unit was 68% (553 of 815). In the entire cohort, the proportion with stages 1, 2, and 3 AKI were 35%, 20%, 45%, respectively. In those needing intensive care, the respective proportions were 20%, 17%, 63%, and 34% received acute renal replacement therapy. Independent predictors of severe AKI were chronic kidney disease, systolic blood pressure, and potassium at baseline. In-hospital mortality in patients with AKI was 41% overall and 52% in intensive care. The aOR for mortality associated with AKI was 9.6 (95% CI 7.4-12.3) overall and 20.9 (95% CI 11.7-37.3) in patients receiving intensive care. 56% of patients with AKI who were discharged alive recovered kidney function back to baseline. The area under the curve (AUC) for the machine learned predictive model using baseline features for dialysis requirement was 0.79 in a validation test.

Conclusions And Relevance: AKI is common in patients hospitalized with COVID-19, associated with worse mortality, and the majority of patients that survive do not recover kidney function. A machine-learned model using admission features had good performance for dialysis prediction and could be used for resource allocation.
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http://dx.doi.org/10.1101/2020.05.04.20090944DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7274245PMC
May 2020

Limitations of Contemporary Guidelines for Managing Patients at High Genetic Risk of Coronary Artery Disease.

J Am Coll Cardiol 2020 06;75(22):2769-2780

Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts; Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts. Electronic address:

Background: Polygenic risk scores (PRS) for coronary artery disease (CAD) identify high-risk individuals more likely to benefit from primary prevention statin therapy. Whether polygenic CAD risk is captured by conventional paradigms for assessing clinical cardiovascular risk remains unclear.

Objectives: This study sought to intersect polygenic risk with guideline-based recommendations and management patterns for CAD primary prevention.

Methods: A genome-wide CAD PRS was applied to 47,108 individuals across 3 U.S. health care systems. The authors then assessed whether primary prevention patients at high polygenic risk might be distinguished on the basis of greater guideline-recommended statin eligibility and higher rates of statin therapy.

Results: Of 47,108 study participants, the mean age was 60 years, and 11,020 (23.4%) had CAD. The CAD PRS strongly associated with prevalent CAD (odds ratio: 1.4 per SD increase in PRS; p < 0.0001). High polygenic risk (top 20% of PRS) conferred 1.9-fold odds of developing CAD (p < 0.0001). However, among primary prevention patients (n = 33,251), high polygenic risk did not correspond with increased recommendations for statin therapy per the American College of Cardiology/American Heart Association (46.2% for those with high PRS vs. 46.8% for all others, p = 0.54) or U.S. Preventive Services Task Force (43.7% vs. 43.7%, p = 0.99) or higher rates of statin prescriptions (25.0% vs. 23.8%, p = 0.04). An additional 4.1% of primary prevention patients may be recommended for statin therapy if high CAD PRS were considered a guideline-based risk-enhancing factor.

Conclusions: Current paradigms for primary cardiovascular prevention incompletely capture a polygenic susceptibility to CAD. An opportunity may exist to improve CAD prevention efforts by integrating both genetic and clinical risk.
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http://dx.doi.org/10.1016/j.jacc.2020.04.027DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7346975PMC
June 2020

Minority-centric meta-analyses of blood lipid levels identify novel loci in the Population Architecture using Genomics and Epidemiology (PAGE) study.

PLoS Genet 2020 03 30;16(3):e1008684. Epub 2020 Mar 30.

Department of Medicine, University of Washington Medical Center, Seattle, Washington, United States of America.

Lipid levels are important markers for the development of cardio-metabolic diseases. Although hundreds of associated loci have been identified through genetic association studies, the contribution of genetic factors to variation in lipids is not fully understood, particularly in U.S. minority groups. We performed genome-wide association analyses for four lipid traits in over 45,000 ancestrally diverse participants from the Population Architecture using Genomics and Epidemiology (PAGE) Study, followed by a meta-analysis with several European ancestry studies. We identified nine novel lipid loci, five of which showed evidence of replication in independent studies. Furthermore, we discovered one novel gene in a PrediXcan analysis, minority-specific independent signals at eight previously reported loci, and potential functional variants at two known loci through fine-mapping. Systematic examination of known lipid loci revealed smaller effect estimates in African American and Hispanic ancestry populations than those in Europeans, and better performance of polygenic risk scores based on minority-specific effect estimates. Our findings provide new insight into the genetic architecture of lipid traits and highlight the importance of conducting genetic studies in diverse populations in the era of precision medicine.
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http://dx.doi.org/10.1371/journal.pgen.1008684DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145272PMC
March 2020

Association of the V122I Hereditary Transthyretin Amyloidosis Genetic Variant With Heart Failure Among Individuals of African or Hispanic/Latino Ancestry.

JAMA 2019 12;322(22):2191-2202

The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York.

Importance: Hereditary transthyretin (TTR) amyloid cardiomyopathy (hATTR-CM) due to the TTR V122I variant is an autosomal-dominant disorder that causes heart failure in elderly individuals of African ancestry. The clinical associations of carrying the variant, its effect in other African ancestry populations including Hispanic/Latino individuals, and the rates of achieving a clinical diagnosis in carriers are unknown.

Objective: To assess the association between the TTR V122I variant and heart failure and identify rates of hATTR-CM diagnosis among carriers with heart failure.

Design, Setting, And Participants: Cross-sectional analysis of carriers and noncarriers of TTR V122I of African ancestry aged 50 years or older enrolled in the Penn Medicine Biobank between 2008 and 2017 using electronic health record data from 1996 to 2017. Case-control study in participants of African and Hispanic/Latino ancestry with and without heart failure in the Mount Sinai BioMe Biobank enrolled between 2007 and 2015 using electronic health record data from 2007 to 2018.

Exposures: TTR V122I carrier status.

Main Outcomes And Measures: The primary outcome was prevalent heart failure. The rate of diagnosis with hATTR-CM among TTR V122I carriers with heart failure was measured.

Results: The cross-sectional cohort included 3724 individuals of African ancestry with a median age of 64 years (interquartile range, 57-71); 1755 (47%) were male, 2896 (78%) had a diagnosis of hypertension, and 753 (20%) had a history of myocardial infarction or coronary revascularization. There were 116 TTR V122I carriers (3.1%); 1121 participants (30%) had heart failure. The case-control study consisted of 2307 individuals of African ancestry and 3663 Hispanic/Latino individuals; the median age was 73 years (interquartile range, 68-80), 2271 (38%) were male, 4709 (79%) had a diagnosis of hypertension, and 1008 (17%) had a history of myocardial infarction or coronary revascularization. There were 1376 cases of heart failure. TTR V122I was associated with higher rates of heart failure (cross-sectional cohort: n = 51/116 TTR V122I carriers [44%], n = 1070/3608 noncarriers [30%], adjusted odds ratio, 1.7 [95% CI, 1.2-2.4], P = .006; case-control study: n = 36/1376 heart failure cases [2.6%], n = 82/4594 controls [1.8%], adjusted odds ratio, 1.8 [95% CI, 1.2-2.7], P = .008). Ten of 92 TTR V122I carriers with heart failure (11%) were diagnosed as having hATTR-CM; the median time from onset of symptoms to clinical diagnosis was 3 years.

Conclusions And Relevance: Among individuals of African or Hispanic/Latino ancestry enrolled in 2 academic medical center-based biobanks, the TTR V122I genetic variant was significantly associated with heart failure.
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http://dx.doi.org/10.1001/jama.2019.17935DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081752PMC
December 2019

HOPS: a quantitative score reveals pervasive horizontal pleiotropy in human genetic variation is driven by extreme polygenicity of human traits and diseases.

Genome Biol 2019 10 25;20(1):222. Epub 2019 Oct 25.

The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY, USA.

Horizontal pleiotropy, where one variant has independent effects on multiple traits, is important for our understanding of the genetic architecture of human phenotypes. We develop a method to quantify horizontal pleiotropy using genome-wide association summary statistics and apply it to 372 heritable phenotypes measured in 361,194 UK Biobank individuals. Horizontal pleiotropy is pervasive throughout the human genome, prominent among highly polygenic phenotypes, and enriched in active regulatory regions. Our results highlight the central role horizontal pleiotropy plays in the genetic architecture of human phenotypes. The HOrizontal Pleiotropy Score (HOPS) method is available on Github at https://github.com/rondolab/HOPS .
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http://dx.doi.org/10.1186/s13059-019-1844-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6815001PMC
October 2019

Augmented intelligence with natural language processing applied to electronic health records for identifying patients with non-alcoholic fatty liver disease at risk for disease progression.

Int J Med Inform 2019 09 6;129:334-341. Epub 2019 Jul 6.

The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, USA; Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, USA. Electronic address:

Objective: Electronic health record (EHR) systems contain structured data (such as diagnostic codes) and unstructured data (clinical documentation). Clinical insights can be derived from analyzing both. The use of natural language processing (NLP) algorithms to effectively analyze unstructured data has been well demonstrated. Here we examine the utility of NLP for the identification of patients with non-alcoholic fatty liver disease, assess patterns of disease progression, and identify gaps in care related to breakdown in communication among providers.

Materials And Methods: All clinical notes available on the 38,575 patients enrolled in the Mount Sinai BioMe cohort were loaded into the NLP system. We compared analysis of structured and unstructured EHR data using NLP, free-text search, and diagnostic codes with validation against expert adjudication. We then used the NLP findings to measure physician impression of progression from early-stage NAFLD to NASH or cirrhosis. Similarly, we used the same NLP findings to identify mentions of NAFLD in radiology reports that did not persist into clinical notes.

Results: Out of 38,575 patients, we identified 2,281 patients with NAFLD. From the remainder, 10,653 patients with similar data density were selected as a control group. NLP outperformed ICD and text search in both sensitivity (NLP: 0.93, ICD: 0.28, text search: 0.81) and F2 score (NLP: 0.92, ICD: 0.34, text search: 0.81). Of 2281 NAFLD patients, 673 (29.5%) were believed to have progressed to NASH or cirrhosis. Among 176 where NAFLD was noted prior to NASH, the average progression time was 410 days. 619 (27.1%) NAFLD patients had it documented only in radiology notes and not acknowledged in other forms of clinical documentation. Of these, 170 (28.4%) were later identified as having likely developed NASH or cirrhosis after a median 1057.3 days.

Discussion: NLP-based approaches were more accurate at identifying NAFLD within the EHR than ICD/text search-based approaches. Suspected NAFLD on imaging is often not acknowledged in subsequent clinical documentation. Many such patients are later found to have more advanced liver disease. Analysis of information flows demonstrated loss of key information that could have been used to help prevent the progression of early NAFLD (NAFL) to NASH or cirrhosis.

Conclusion: For identification of NAFLD, NLP performed better than alternative selection modalities. It then facilitated analysis of knowledge flow between physician and enabled the identification of breakdowns where key information was lost that could have slowed or prevented later disease progression.
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http://dx.doi.org/10.1016/j.ijmedinf.2019.06.028DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6717556PMC
September 2019

Genetic analyses of diverse populations improves discovery for complex traits.

Nature 2019 06 19;570(7762):514-518. Epub 2019 Jun 19.

Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions-the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.
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http://dx.doi.org/10.1038/s41586-019-1310-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6785182PMC
June 2019

Estimation of metabolic syndrome heritability in three large populations including full pedigree and genomic information.

Hum Genet 2019 Jul 1;138(7):739-748. Epub 2019 Jun 1.

Medical and Genomic Statistics Unit, Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy.

Metabolic syndrome is a complex human disorder characterized by a cluster of conditions (increased blood pressure, hyperglycemia, excessive body fat around the waist, and abnormal cholesterol or triglyceride levels). Any of these conditions increases the risk of serious disorders such as diabetes or cardiovascular disease. Currently, the degree of genetic regulation of this syndrome is under debate and partially unknown. The principal aim of this study was to estimate the genetic component and the common environmental effects in different populations using full pedigree and genomic information. We used three large populations (Gubbio, ARIC, and Ogliastra cohorts) to estimate the heritability of metabolic syndrome. Due to both pedigree and genotyped data, different approaches were applied to summarize relatedness conditions. Linear mixed models (LLM) using average information restricted maximum likelihood (AIREML) algorithm were applied to partition the variances and estimate heritability (h) and common sib-household effect (c). Globally, results obtained from pedigree information showed a significant heritability (h: 0.286 and 0.271 in Gubbio and Ogliastra, respectively), whereas a lower, but still significant heritability was found using SNPs data ([Formula: see text]: 0.167 and 0.254 in ARIC and Ogliastra). The remaining heritability between h and [Formula: see text] ranged between 0.031 and 0.237. Finally, the common environmental c in Gubbio and Ogliastra were also significant accounting for about 11% of the phenotypic variance. Availability of different kinds of populations and data helped us to better understand what happened when heritability of metabolic syndrome is estimated and account for different possible confounding. Furthermore, the opportunity of comparing different results provided more precise and less biased estimation of heritability.
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http://dx.doi.org/10.1007/s00439-019-02024-6DOI Listing
July 2019

No causal effects of serum urate levels on the risk of chronic kidney disease: A Mendelian randomization study.

PLoS Med 2019 01 15;16(1):e1002725. Epub 2019 Jan 15.

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.

Background: Studies have shown strong positive associations between serum urate (SU) levels and chronic kidney disease (CKD) risk; however, whether the relation is causal remains uncertain. We evaluate whether genetic data are consistent with a causal impact of SU level on the risk of CKD and estimated glomerular filtration rate (eGFR).

Methods And Findings: We used Mendelian randomization (MR) methods to evaluate the presence of a causal effect. We used aggregated genome-wide association data (N = 110,347 for SU, N = 69,374 for gout, N = 133,413 for eGFR, N = 117,165 for CKD), electronic-medical-record-linked UK Biobank data (N = 335,212), and population-based cohorts (N = 13,425), all in individuals of European ancestry, for SU levels and CKD. Our MR analysis showed that SU has a causal effect on neither eGFR level nor CKD risk across all MR analyses (all P > 0.05). These null associations contrasted with our epidemiological association findings from the 4 population-based cohorts (change in eGFR level per 1-mg/dl [59.48 μmol/l] increase in SU: -1.99 ml/min/1.73 m2; 95% CI -2.86 to -1.11; P = 8.08 × 10(-6); odds ratio [OR] for CKD: 1.48; 95% CI 1.32 to 1.65; P = 1.52 × 10(-11)). In contrast, the same MR approaches showed that SU has a causal effect on the risk of gout (OR estimates ranging from 3.41 to 6.04 per 1-mg/dl increase in SU, all P < 10-3), which served as a positive control of our approach. Overall, our MR analysis had >99% power to detect a causal effect of SU level on the risk of CKD of the same magnitude as the observed epidemiological association between SU and CKD. Limitations of this study include the lifelong effect of a genetic perturbation not being the same as an acute perturbation, the inability to study non-European populations, and some sample overlap between the datasets used in the study.

Conclusions: Evidence from our series of causal inference approaches using genetics does not support a causal effect of SU level on eGFR level or CKD risk. Reducing SU levels is unlikely to reduce the risk of CKD development.
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http://dx.doi.org/10.1371/journal.pmed.1002725DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6333326PMC
January 2019

The Genetic Landscape of Diamond-Blackfan Anemia.

Am J Hum Genet 2018 12 29;103(6):930-947. Epub 2018 Nov 29.

Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.

Diamond-Blackfan anemia (DBA) is a rare bone marrow failure disorder that affects 7 out of 1,000,000 live births and has been associated with mutations in components of the ribosome. In order to characterize the genetic landscape of this heterogeneous disorder, we recruited a cohort of 472 individuals with a clinical diagnosis of DBA and performed whole-exome sequencing (WES). We identified relevant rare and predicted damaging mutations for 78% of individuals. The majority of mutations were singletons, absent from population databases, predicted to cause loss of function, and located in 1 of 19 previously reported ribosomal protein (RP)-encoding genes. Using exon coverage estimates, we identified and validated 31 deletions in RP genes. We also observed an enrichment for extended splice site mutations and validated their diverse effects using RNA sequencing in cell lines obtained from individuals with DBA. Leveraging the size of our cohort, we observed robust genotype-phenotype associations with congenital abnormalities and treatment outcomes. We further identified rare mutations in seven previously unreported RP genes that may cause DBA, as well as several distinct disorders that appear to phenocopy DBA, including nine individuals with biallelic CECR1 mutations that result in deficiency of ADA2. However, no new genes were identified at exome-wide significance, suggesting that there are no unidentified genes containing mutations readily identified by WES that explain >5% of DBA-affected case subjects. Overall, this report should inform not only clinical practice for DBA-affected individuals, but also the design and analysis of rare variant studies for heterogeneous Mendelian disorders.
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http://dx.doi.org/10.1016/j.ajhg.2018.10.027DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6288280PMC
December 2018

Publisher Correction: Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases.

Nat Genet 2018 08;50(8):1196

The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

In the version of this article initially published, the Supplementary Text and Figures file was missing Supplementary Tables 4, 6, 8 and 10-14. The correct file has now been provided online.
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http://dx.doi.org/10.1038/s41588-018-0164-2DOI Listing
August 2018

Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases.

Nat Genet 2018 05 23;50(5):693-698. Epub 2018 Apr 23.

The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Horizontal pleiotropy occurs when the variant has an effect on disease outside of its effect on the exposure in Mendelian randomization (MR). Violation of the 'no horizontal pleiotropy' assumption can cause severe bias in MR. We developed the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) test to identify horizontal pleiotropic outliers in multi-instrument summary-level MR testing. We showed using simulations that the MR-PRESSO test is best suited when horizontal pleiotropy occurs in <50% of instruments. Next we applied the MR-PRESSO test, along with several other MR tests, to complex traits and diseases and found that horizontal pleiotropy (i) was detectable in over 48% of significant causal relationships in MR; (ii) introduced distortions in the causal estimates in MR that ranged on average from -131% to 201%; (iii) induced false-positive causal relationships in up to 10% of relationships; and (iv) could be corrected in some but not all instances.
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http://dx.doi.org/10.1038/s41588-018-0099-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6083837PMC
May 2018

Plasma biomarkers are associated with renal outcomes in individuals with APOL1 risk variants.

Kidney Int 2018 06 25;93(6):1409-1416. Epub 2018 Apr 25.

Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA. Electronic address:

G1/G2 variants in the Apolipoprotein L1 (APOL1) gene are associated with end-stage renal disease (ESRD) in people with African ancestry. Plasma biomarkers may have utility for risk stratification in APOL1 high-risk individuals of African ancestry. To evaluate this, we measured tumor necrosis factor receptor 1/2 (TNFR1/2) and kidney injury molecule-1 (KIM1) in baseline plasma specimens from individuals of African ancestry with high-risk APOL1 genotype. Biomarker association with a composite renal outcome of ESRD or 40% sustained decline in estimated glomerular filtration rate (eGFR) was then determined and then assessed as improvement in area under curve. Among the 498 participants, the median age was 56 years, 67.7% were female, and the baseline eGFR was 83.3 ml/min/1.73 m with 80 reaching outcome over 5.9 years. TNFR1, TNFR2, and KIM1 at enrollment were independently associated with renal outcome continuously (adjusted hazard ratio 2.0 [95% confidence interval 1.3-3.1]; 1.5 [1.2-1.9]; and 1.6 [1.3-1.9] per doubling in levels, respectively) or by tertiles. The area under the curve significantly improved from 0.75 with the clinical model to 0.79 with the biomarker-enhanced model. The event rate was 40% with all 3 biomarkers elevated (adjusted odds ratio of 5.3 (2.3-12.0) vs. 17% (adjusted odds ratio 1.8 [0.9-3.6] with 1 or 2 elevated and 7% with no biomarkers elevated. Thus, plasma concentrations of TNFR1, TNFR2, and KIM1 are independently associated with renal outcome and improve discrimination or reclassification of African ancestry individuals with a high-risk APOL1 genotype and preserve renal function. Elevation of all markers had higher risk of outcome and can assist with better clinical prediction and improved clinical trial efficiency by enriching event rates.
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http://dx.doi.org/10.1016/j.kint.2018.01.026DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5918426PMC
June 2018
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