Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

    Jonathan Mosley

    Heparin-induced thrombocytopenia (HIT) is an unpredictable, potentially catastrophic adverse effect of heparin treatment resulting from an immune response to platelet factor 4 (PF4)/heparin complexes. No genome-wide evaluations have been... more
    Heparin-induced thrombocytopenia (HIT) is an unpredictable, potentially catastrophic adverse effect of heparin treatment resulting from an immune response to platelet factor 4 (PF4)/heparin complexes. No genome-wide evaluations have been performed to identify potential genetic influences on HIT. Here, we performed a genome-wide association study (GWAS) and candidate gene study using HIT cases and controls identified using electronic medical records (EMRs) coupled to a DNA biobank and attempted to replicate GWAS associations in an independent cohort. We subsequently investigated influences of GWAS-associated single nucleotide polymorphisms (SNPs) on PF4/heparin antibodies in non-heparin treated individuals. In a recessive model, we observed significant SNP associations (odds ratio [OR] 18.52; 95% confidence interval [CI] 6.33-54.23; p=3.18×10⁻⁹) with HIT near the T-Cell Death-Associated Gene 8 (TDAG8). These SNPs are in linkage disequilibrium with a missense TDAG8 SNP. TDAG8 SNPs trended toward an association with HIT in replication analysis (OR 5.71; 0.47-69.22; p=0.17), and the missense SNP was associated with PF4/heparin antibody levels and positive PF4/heparin antibodies in non-heparin treated patients (OR 3.09; 1.14-8.13; p=0.02). In the candidate gene study, SNPs at HLA-DRA were nominally associated with HIT (OR 0.25; 0.15-0.44; p=2.06×10⁻⁶). Further study of TDAG8 and HLA-DRA SNPs is warranted to assess their influence on the risk of developing HIT.
    New drugs are routinely screened for IKr blocking properties thought to predict QT prolonging and arrhythmogenic liability. However, recent data suggest that chronic (hours) drug exposure to phosphoinositide 3-kinase inhibitors used in... more
    New drugs are routinely screened for IKr blocking properties thought to predict QT prolonging and arrhythmogenic liability. However, recent data suggest that chronic (hours) drug exposure to phosphoinositide 3-kinase inhibitors used in cancer can prolong QT by inhibiting potassium currents and increasing late sodium current (INa-L) in cardiomyocytes. We tested the extent to which IKr blockers with known QT liability generate arrhythmias through this pathway. Acute exposure to dofetilide, an IKr blocker without other recognized electropharmacologic actions, produced no change in ion currents or action potentials in adult mouse cardiomyocytes, which lack IKr. By contrast, 2 to 48 hours of exposure to the drug generated arrhythmogenic afterdepolarizations and ≥15-fold increases in INa-L. Including phosphatidylinositol 3,4,5-trisphosphate, a downstream effector for the phosphoinositide 3-kinase pathway, in the pipette inhibited these effects. INa-L was also increased, and inhibitable by...
    One-third of type 2 diabetes patients do not respond to metformin. Genetic variants in metformin transporters have been extensively studied as a likely contributor to this high failure rate. Here, we investigate, for the first time, the... more
    One-third of type 2 diabetes patients do not respond to metformin. Genetic variants in metformin transporters have been extensively studied as a likely contributor to this high failure rate. Here, we investigate, for the first time, the effect of genetic variants in transcription factors on metformin pharmacokinetics (PK) and response. Overall, 546 patients and healthy volunteers contributed their genome-wide, pharmacokinetic (235 subjects), and HbA1c data (440 patients) for this analysis. Five variants in specificity protein 1 (SP1), a transcription factor that modulates the expression of metformin transporters, were associated with changes in treatment HbA1c (P < 0.01) and metformin secretory clearance (P < 0.05). Population pharmacokinetic modeling further confirmed a 24% reduction in apparent clearance in homozygous carriers of one such variant, rs784888. Genetic variants in other transcription factors, peroxisome proliferator-activated receptor-α and hepatocyte nuclear factor 4-α, were significantly associated with HbA1c change only. Overall, our study highlights the importance of genetic variants in transcription factors as modulators of metformin PK and response.
    Research Interests:
    Many genetic variants have been shown to affect drug response through changes in drug efficacy and likelihood of adverse effects. Much of pharmacogenomic science has focused on discovering and clinically implementing single gene variants... more
    Many genetic variants have been shown to affect drug response through changes in drug efficacy and likelihood of adverse effects. Much of pharmacogenomic science has focused on discovering and clinically implementing single gene variants with large effect sizes. Given the increasing complexities of drug responses and their variability, a systems approach may be enabling for discovery of new biology in this area. Further, systems approaches may be useful in addressing challenges in moving these data to clinical implementation, including creation of predictive models of drug response phenotypes, improved clinical decision-making through complex biological models, improving strategies for integrating genomics into clinical practice, and evaluating the impact of implementation programs on public health.
    The coupling of electronic medical records (EMR) with genetic data has created the potential for implementing reverse genetic approaches in humans, whereby the function of a gene is inferred from the shared pattern of morbidity among... more
    The coupling of electronic medical records (EMR) with genetic data has created the potential for implementing reverse genetic approaches in humans, whereby the function of a gene is inferred from the shared pattern of morbidity among homozygotes of a genetic variant. We explored the feasibility of this approach to identify phenotypes associated with low frequency variants using Vanderbilt's EMR-based BioVU resource. We analyzed 1,658 low frequency non-synonymous SNPs (nsSNPs) with a minor allele frequency (MAF)<10% collected on 8,546 subjects. For each nsSNP, we identified diagnoses shared by at least 2 minor allele homozygotes and with an association p<0.05. The diagnoses were reviewed by a clinician to ascertain whether they may share a common mechanistic basis. While a number of biologically compelling clinical patterns of association were observed, the frequency of these associations was identical to that observed using genotype-permuted data sets, indicating that the associations were likely due to chance. To refine our analysis associations, we then restricted the analysis to 711 nsSNPs in genes with phenotypes in the On-line Mendelian Inheritance in Man (OMIM) or knock-out mouse phenotype databases. An initial comparison of the EMR diagnoses to the known in vivo functions of the gene identified 25 candidate nsSNPs, 19 of which had significant genotype-phenotype associations when tested using matched controls. Twleve of the 19 nsSNPs associations were confirmed by a detailed record review. Four of 12 nsSNP-phenotype associations were successfully replicated in an independent data set: thrombosis (F5,rs6031), seizures/convulsions (GPR98,rs13157270), macular degeneration (CNGB3,rs3735972), and GI bleeding (HGFAC,rs16844401). These analyses demonstrate the feasibility and challenges of using reverse genetics approaches to identify novel gene-phenotype associations in human subjects using low frequency variants. As increasing amounts of rare variant data are generated from modern genotyping and sequence platforms, model organism data may be an important tool to enable discovery.
    The use of electronic medical record data linked to biological specimens in health care settings is expected to enable cost-effective and rapid genomic analyses. Here, we present a model that highlights potential advantages for genomic... more
    The use of electronic medical record data linked to biological specimens in health care settings is expected to enable cost-effective and rapid genomic analyses. Here, we present a model that highlights potential advantages for genomic discovery and describe the operational infrastructure that facilitated multiple simultaneous discovery efforts.
    A single mutation can alter cellular and global homeostatic mechanisms and give rise to multiple clinical diseases. We hypothesized that these disease mechanisms could be identified using low minor allele frequency... more
    A single mutation can alter cellular and global homeostatic mechanisms and give rise to multiple clinical diseases. We hypothesized that these disease mechanisms could be identified using low minor allele frequency (MAF<0.1) non-synonymous SNPs (nsSNPs) associated with "mechanistic phenotypes", comprised of collections of related diagnoses. We studied two mechanistic phenotypes: (1) thrombosis, evaluated in a population of 1,655 African Americans; and (2) four groupings of cancer diagnoses, evaluated in 3,009 white European Americans. We tested associations between nsSNPs represented on GWAS platforms and mechanistic phenotypes ascertained from electronic medical records (EMRs), and sought enrichment in functional ontologies across the top-ranked associations. We used a two-step analytic approach whereby nsSNPs were first sorted by the strength of their association with a phenotype. We tested associations using two reverse genetic models and standard additive and recessive models. In the second step, we employed a hypothesis-free ontological enrichment analysis using the sorted nsSNPs to identify functional mechanisms underlying the diagnoses comprising the mechanistic phenotypes. The thrombosis phenotype was solely associated with ontologies related to blood coagulation (Fisher's p = 0.0001, FDR p = 0.03), driven by the F5, P2RY12 and F2RL2 genes. For the cancer phenotypes, the reverse genetics models were enriched in DNA repair functions (p = 2×10-5, FDR p = 0.03) (POLG/FANCI, SLX4/FANCP, XRCC1, BRCA1, FANCA, CHD1L) while the additive model showed enrichment related to chromatid segregation (p = 4×10-6, FDR p = 0.005) (KIF25, PINX1). We were able to replicate nsSNP associations for POLG/FANCI, BRCA1, FANCA and CHD1L in independent data sets. Mechanism-oriented phenotyping using collections of EMR-derived diagnoses can elucidate fundamental disease mechanisms.
    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... more
    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.
    The aim of this study was to test the hypothesis that rare variants are associated with drug-induced long QT interval syndrome (diLQTS) and torsades de pointes. diLQTS is associated with the potentially fatal arrhythmia torsades de... more
    The aim of this study was to test the hypothesis that rare variants are associated with drug-induced long QT interval syndrome (diLQTS) and torsades de pointes. diLQTS is associated with the potentially fatal arrhythmia torsades de pointes. The contribution of rare genetic variants to the underlying genetic framework predisposing to diLQTS has not been systematically examined. We performed whole-exome sequencing on 65 diLQTS patients and 148 drug-exposed control subjects of European descent. We used rare variant analyses (variable threshold and sequence kernel association test) and gene-set analyses to identify genes enriched with rare amino acid coding (AAC) variants associated with diLQTS. Significant associations were reanalyzed by comparing diLQTS patients with 515 ethnically matched control subjects from the National Heart, Lung, and Blood Grand Opportunity Exome Sequencing Project. Rare variants in 7 genes were enriched in the diLQTS patients according to the sequence kernel association test or variable threshold compared with drug-exposed controls (p < 0.001). Of these, we replicated the diLQTS associations for KCNE1 and ACN9 using 515 Exome Sequencing Project control subjects (p < 0.05). A total of 37% of the diLQTS patients also had 1 or more rare AAC variants compared with 21% of control subjects (p = 0.009), in a pre-defined set of 7 congenital long QT interval syndrome (cLQTS) genes encoding potassium channels or channel modulators (KCNE1, KCNE2, KCNH2, KCNJ2, KCNJ5, KCNQ1, AKAP9). By combining whole-exome sequencing with aggregated rare variant analyses, we implicate rare variants in KCNE1 and ACN9 as risk factors for diLQTS. Moreover, diLQTS patients were more burdened by rare AAC variants in cLQTS genes encoding potassium channel modulators, supporting the idea that multiple rare variants, notably across cLQTS genes, predispose to diLQTS.
    Positional cloning and candidate gene approaches have shown that atrial fibrillation (AF) is a complex disease with familial aggregation. Here, we employed whole-exome sequencing (WES) in AF kindreds to identify variants associated with... more
    Positional cloning and candidate gene approaches have shown that atrial fibrillation (AF) is a complex disease with familial aggregation. Here, we employed whole-exome sequencing (WES) in AF kindreds to identify variants associated with familial AF. WES was performed on 18 individuals in six modestly sized familial AF kindreds. After filtering very rare variants by multiple metrics, we identified 39 very rare and potentially pathogenic variants [minor allele frequency (MAF) ≤0.04%] in genes not previously associated with AF. Despite stringent filtering >1 very rare variants in the 5/6 of the kindreds were identified, whereas no plausible variants contributing to familial AF were found in 1/6 of the kindreds. Two candidate AF variants in the calcium channel subunit genes (CACNB2 and CACNA2D4) were identified in two separate families using expression data and predicted function. By coupling family data with exome sequencing, we identified multiple very rare potentially pathogenic variants in five of six families, suggestive of a complex disease mechanism, whereas none were identified in the remaining AF pedigree. This study highlights some important limitations and challenges associated with performing WES in AF including the importance of having large well-curated multi-generational pedigrees, the issue of potential AF misclassification, and limitations of WES technology when applied to a complex disease.
    A prolonged QT interval is associated with increased risk of Torsades de pointes (TdP) and may be fatal. We sought to investigate the extent to which clinical covariates affect the change in QT interval among... more
    A prolonged QT interval is associated with increased risk of Torsades de pointes (TdP) and may be fatal. We sought to investigate the extent to which clinical covariates affect the change in QT interval among 'real-world' patients treated with sotalol and followed in an electronic medical record (EMR) system. We used clinical alerts in our EMR system to identify all patients in whom a new prescription for sotalol was written (2001-11). Rate-corrected QT (QTc) was calculated by Bazett's formula. Correlates of sotalol-induced change in the QTc interval and sotalol discontinuation were examined using linear and logistic regression, respectively. Overall, 541 sotalol-exposed patients were identified (n = 200 women, 37%). The mean first sotalol dose was 86 ± 39 mg, age 64 ± 13 years, and BMI 30 ± 7 kg/m(2). Atrial fibrillation/flutter was the predominant indication (92.2%). After initial exposure, the change in the QTc interval from baseline was highly variable: ΔQTc after 2 h = 3 ± 42 ms (P = 0.17) and 11 ± 37 ms after ≥48 h (P < 0.001). Multivariable linear regression analysis identified female gender and age, reduced left ventricular ejection fraction, high sotalol dose, hypertrophic cardiomyopathy, and loop diuretic co-administration as correlates of increased ΔQTc at ≥48 h (P < 0.05 for all). Within 3 days of initiation, 12% discontinued sotalol of which 31% were because of exaggerated QTc prolongation. One percent developed TdP. In this EMR-based cohort, the increase in QTc with sotalol initiation was highly variable, and multiple clinical factors contributed. These data represent an important step in ongoing work to identify real-world patients likely to tolerate long-term therapy and reinforces the utility of EMR-based cohorts as research tools.
    Whole exome sequencing is a powerful technique for Mendelian disease gene discovery. However, variant prioritization remains a challenge. We applied whole exome sequencing to identify the causal variant in a large family with familial... more
    Whole exome sequencing is a powerful technique for Mendelian disease gene discovery. However, variant prioritization remains a challenge. We applied whole exome sequencing to identify the causal variant in a large family with familial dilated cardiomyopathy of unknown pathogenesis. A large family with autosomal dominant, familial dilated cardiomyopathy was identified. Exome capture and sequencing were performed in 3 remotely related, affected subjects predicted to share <0.1% of their genomes by descent. Shared variants were filtered for rarity, evolutionary conservation, and predicted functional significance, and remaining variants were filtered against 71 locally generated exomes. Variants were also prioritized using the Variant Annotation Analysis and Search Tool. Final candidates were validated by Sanger sequencing and tested for segregation. There were 664 shared heterozygous nonsense, missense, or splice site variants, of which 26 were rare (minor allele frequency ≤0.001 or not reported) in 2 public databases. Filtering against internal exomes reduced the number of candidates to 2, and of these, a single variant (c.1907 G>A) in RBM20, segregated with disease status and was absent in unaffected internal reference exomes. Bioinformatic prioritization with Variant Annotation Analysis and Search Tool supported this result. Whole exome sequencing of remotely related dilated cardiomyopathy subjects from a large, multiplex family, followed by systematic filtering, identified a causal RBM20 mutation without the need for linkage analysis.
    ECG QRS duration, a measure of cardiac intraventricular conduction, varies ≈2-fold in individuals without cardiac disease. Slow conduction may promote re-entrant arrhythmias. We performed a genome-wide association study to identify... more
    ECG QRS duration, a measure of cardiac intraventricular conduction, varies ≈2-fold in individuals without cardiac disease. Slow conduction may promote re-entrant arrhythmias. 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. 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.
    Phenome-wide association studies (PheWAS) have demonstrated utility in validating genetic associations derived from traditional genetic studies as well as identifying novel genetic associations. Here we used an electronic health record... more
    Phenome-wide association studies (PheWAS) have demonstrated utility in validating genetic associations derived from traditional genetic studies as well as identifying novel genetic associations. Here we used an electronic health record (EHR)-based PheWAS to explore pleiotropy of genetic variants in the fat mass and obesity associated gene (FTO), some of which have been previously associated with obesity and type 2 diabetes (T2D). We used a population of 10,487 individuals of European ancestry with genome-wide genotyping from the Electronic Medical Records and Genomics (eMERGE) Network and another population of 13,711 individuals of European ancestry from the BioVU DNA biobank at Vanderbilt genotyped using Illumina HumanExome BeadChip. A meta-analysis of the two study populations replicated the well-described associations between FTO variants and obesity (odds ratio [OR] = 1.25, 95% Confidence Interval = 1.11-1.24, p = 2.10 × 10(-9)) and FTO variants and T2D (OR = 1.14, 95% CI = 1.08-1.21, p = 2.34 × 10(-6)). The meta-analysis also demonstrated that FTO variant rs8050136 was significantly associated with sleep apnea (OR = 1.14, 95% CI = 1.07-1.22, p = 3.33 × 10(-5)); however, the association was attenuated after adjustment for body mass index (BMI). Novel phenotype associations with obesity-associated FTO variants included fibrocystic breast disease (rs9941349, OR = 0.81, 95% CI = 0.74-0.91, p = 5.41 × 10(-5)) and trends toward associations with non-alcoholic liver disease and gram-positive bacterial infections. FTO variants not associated with obesity demonstrated other potential disease associations including non-inflammatory disorders of the cervix and chronic periodontitis. These results suggest that genetic variants in FTO may have pleiotropic associations, some of which are not mediated by obesity.