Clinical characteristics and outcomes of systemic loxoscelism.

<p>Clinical characteristics and outcomes of systemic loxoscelism.</p

Significant findings for PheWAS of loxoscelism (adjusted significance level, <i>p</i> < 1.2 x 10⁻⁴).

<p>Significant findings for PheWAS of loxoscelism (adjusted significance level, <i>p</i> < 1.2 x 10⁻⁴).</p

Phenotypes and PheWAS of Individuals with Moderate-Severe Loxoscelism.

<p>(A) Manhattan plot representing the number of individuals with moderate to severe loxoscelism with each phenotype. The most frequent phenotypes validated the loxoscelism definition and included the toxic effect of venom, acquired hemolytic anemia, fever of unknown origin, and rash/skin eruption. (B) PheWAS for moderate-severe loxoscelism. The blue line represents significance level without correction (<i>p</i> = 0.05). The red line is representative of the adjusted significance threshold using the Bonferroni correction for multiple comparisons (<i>p =</i> 1.2 x 10⁻⁴). 29 phenotypes showed a significant correlation (p < 1.2 x 10⁻⁴) with the loxoscelism phenotype when compared to controls.</p

Integrating EMR-Linked and <i>In Vivo</i> Functional Genetic Data to Identify New Genotype-Phenotype Associations

<div><p>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 <i>in vivo</i> 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 (<i>F5</i>,rs6031), seizures/convulsions (<i>GPR98</i>,rs13157270), macular degeneration (<i>CNGB3</i>,rs3735972), and GI bleeding (<i>HGFAC</i>,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.</p></div

Association statistics for the 12 candidate nsSNPs.

<p>For each nsSNP, clinical phenotypes were constructed using diagnosis codes that closely approximated the phenotype descriptions in the OMIM and KO mouse databases. Shown are the subject counts and results of exact logistic regression analyses comparing minor allele homozygotes to matched common allele homozygotes. The common allele homozygotes were matched for age, race, gender and data set.</p

Characteristics of the selected nsSNPs.

<p>OMIM/KO mouse phenotypes are associated at the gene level, not the specific nsSNP. Minor allele frequencies (MAF) are based on the frequencies observed in this study population. Chromosome and position are from Human Annotation Release 104.</p

Replication analyses.

<p>Replication analyses for nsSNP-phenotype associations using an additive logistic regression model adjusting for age, gender and principal components. A (—) indicates that less than 50 cases (i.e., individuals with the given phenotype) were available for analyses.</p

Overview of the nsSNP selection process.

<p>There was no difference in number of diagnoses significantly associated with the 1,658 nsSNPs when compared to genotype-permuted data. Hence, a nsSNP selection strategy that compared to diagnoses to those reported in either OMIM or the KO Mouse data was used. A multi-step selection and review process identified 12 candidate nsSNPs.</p

Population characteristics.

<p>Population characteristics.</p

DataSheet1_Genetic predisposition may not improve prediction of cardiac surgery-associated acute kidney injury.pdf

Background: The recent integration of genomic data with electronic health records has enabled large scale genomic studies on a variety of perioperative complications, yet genome-wide association studies on acute kidney injury have been limited in size or confounded by composite outcomes. Genome-wide association studies can be leveraged to create a polygenic risk score which can then be integrated with traditional clinical risk factors to better predict postoperative complications, like acute kidney injury.Methods: Using integrated genetic data from two academic biorepositories, we conduct a genome-wide association study on cardiac surgery-associated acute kidney injury. Next, we develop a polygenic risk score and test the predictive utility within regressions controlling for age, gender, principal components, preoperative serum creatinine, and a range of patient, clinical, and procedural risk factors. Finally, we estimate additive variant heritability using genetic mixed models.Results: Among 1,014 qualifying procedures at Vanderbilt University Medical Center and 478 at Michigan Medicine, 348 (34.3%) and 121 (25.3%) developed AKI, respectively. No variants exceeded genome-wide significance (p −8) threshold, however, six previously unreported variants exceeded the suggestive threshold (p −6). Notable variants detected include: 1) rs74637005, located in the exonic region of NFU1 and 2) rs17438465, located between EVX1 and HIBADH. We failed to replicate variants from prior unbiased studies of post-surgical acute kidney injury. Polygenic risk was not significantly associated with post-surgical acute kidney injury in any of the models, however, case duration (aOR = 1.002, 95% CI 1.000–1.003, p = 0.013), diabetes mellitus (aOR = 2.025, 95% CI 1.320–3.103, p = 0.001), and valvular disease (aOR = 0.558, 95% CI 0.372–0.835, p = 0.005) were significant in the full model.Conclusion: Polygenic risk score was not significantly associated with cardiac surgery-associated acute kidney injury and acute kidney injury may have a low heritability in this population. These results suggest that susceptibility is only minimally influenced by baseline genetic predisposition and that clinical risk factors, some of which are modifiable, may play a more influential role in predicting this complication. The overall impact of genetics in overall risk for cardiac surgery-associated acute kidney injury may be small compared to clinical risk factors.</p