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Background: Postoperative nausea and vomiting (PONV) is a key driver of unplanned admission and patient satisfaction after surgery. Because traditional risk factors do not completely explain variability in risk, this study hypothesized that genetics may contribute to the overall risk for this complication. The objective of this research is to perform a genome-wide association study of PONV, derive a polygenic risk score for PONV, assess associations between the risk score and PONV in a validation cohort, and compare any genetic contributions to known clinical risks for PONV., Methods: Surgeries with integrated genetic and perioperative data performed under general anesthesia at Michigan Medicine (Ann Arbor, Michigan) and Vanderbilt University Medical Center (Nashville, Tennessee) were studied. PONV was defined as nausea or emesis occurring and documented in the postanesthesia care unit. In the discovery phase, genome-wide association studies were performed on each genetic cohort, and the results were meta-analyzed. Next, the polygenic phase assessed whether a polygenic score, derived from genome-wide association study in a derivation cohort from Vanderbilt University Medical Center, improved prediction within a validation cohort from Michigan Medicine, as quantified by discrimination (c-statistic) and net reclassification index., Results: Of 64,523 total patients, 5,703 developed PONV (8.8%). The study identified 46 genetic variants exceeding the threshold of P < 1 × 10-5, occurring with minor allele frequency greater than 1%, and demonstrating concordant effects in both cohorts. Standardized polygenic score was associated with PONV in a basic model, controlling for age and sex (adjusted odds ratio, 1.027 per SD increase in overall genetic risk; 95% CI, 1.001 to 1.053; P = 0.044), a model based on known clinical risks (adjusted odds ratio, 1.029; 95% CI, 1.003 to 1.055; P = 0.030), and a full clinical regression, controlling for 21 demographic, surgical, and anesthetic factors, (adjusted odds ratio, 1.029; 95% CI, 1.002 to 1.056; P = 0.033). The addition of polygenic score improved overall discrimination in models based on known clinical risk factors (c-statistic, 0.616 compared to 0.613; P = 0.028) and improved net reclassification of 4.6% of cases., Conclusions: Standardized polygenic risk was associated with PONV in all three of the study's models, but the genetic influence was smaller than exerted by clinical risk factors. Specifically, a patient with a polygenic risk score greater than 1 SD above the mean has 2 to 3% greater odds of developing PONV when compared to the baseline population, which is at least an order of magnitude smaller than the increase associated with having prior PONV or motion sickness (55%), having a history of migraines (17%), or being female (83%) and is not clinically significant. Furthermore, the use of a polygenic risk score does not meaningfully improve discrimination compared to clinical risk factors and is not clinically useful., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc., on behalf of the American Society of Anesthesiologists.)

Patients with inflammatory bowel disease (IBD) are at increased risk of Clostridioides difficile infection (CDI). Herein, we aimed to determine if genetic risk contributes to this observed association. We carried out a genome-wide association study (GWAS) analysis in the Michigan Genomics Initiative and the United Kingdom Biobank for CDI based on ICD codes and meta-analyzed these results with similar publicly accessible GWAS summary statistics from Finngen. Conditional and joint multi-SNP analyses were used to identify independent associations. Imputation of the human leukocyte antigen (HLA) region with fine mapping was used to try to identify causal HLA allele groups. Two-sample bidirectional Mendelian randomization (MR) was implemented to determine causal relationships between IBD and CDI. A total of 3,500 cases of CDI and 674,323 controls were meta-analyzed, revealing one genome-wide significant variant for CDI, HLA-C;LINC02571 -rs3134745-C ( P = 4.27E-08), which annotated to the major histocompatibility complex on chromosome 6. While fine mapping did not identify a statistically significant HLA allele group, there was a suggestive signal for HLA-B *35:01 ( P = 4.74e-04). Using two-sample MR, genetically predicted IBD was associated with increased risk of CDI (MR Egger [odds ratio {OR} 1.16, 95% confidence interval {CI} 1.02-1.31]). Subset analysis revealed that risk was primarily driven by genetically predicted ulcerative colitis (MR Egger [OR 1.22, 95% CI 1.05-1.41]). These results highlight the importance of the host immune response in CDI pathogenesis, help explain the observed relationship between IBD and CDI, and open new avenues for targeted treatment of CDI in IBD.IMPORTANCEData from this paper (i) provide reproducible evidence that susceptibility CDI is genetically mediated, (ii) highlight genetic risk as a mechanism for the increased risk of CDI in patients with inflammatory bowel disease, and (iii) point toward anti-interleukin-23 therapy as a common therapeutic strategy., Competing Interests: K.C.C.-D. reports access to data and committee disclosure for the Crohn's and Colitis Foundation, as well as committee disclosure for the American College of Gastroenterology. K.R. is supported in part by an investigator-initiated grant from Merck & Co, Inc.; he has consulted for Seres Therapeutics, Inc., Rebiotix, Inc., and Summit Therapeutics, Inc. P.H. reports personal fees from Abbvie, Eli Lilly, and Pfizer outside of the submitted work. All other authors report no conflict of interest.

Iron is an essential mineral that supports numerous biological functions. Studies have reported associations between iron dysregulation and certain cardiovascular and neurodegenerative diseases, but the direction of influence is not clear. Our goal was to use computational approaches to better understand the role of genetically predicted iron levels on disease risk. We meta-analyzed genome-wide association study summary statistics for serum iron levels from two cohorts and two previous meta-analyses. We then obtained summary statistics from 11 neurodegenerative, cerebrovascular, cardiovascular or lipid traits to assess global and regional genetic correlation between iron levels and these traits. We used two-sample Mendelian randomization (MR) to estimate causal effects. Sex-stratified analyses were also carried out to identify effects potentially differing by sex. Overall, we identified three significant global correlations between iron levels and (i) coronary heart disease, (ii) triglycerides, and (iii) high-density lipoprotein (HDL) cholesterol levels. A total of 194 genomic regions had significant (after correction for multiple testing) local correlations between iron levels and the 11 tested traits. MR analysis revealed two potential causal relationships, between genetically predicted iron levels and (i) total cholesterol or (ii) non-HDL cholesterol. Sex-stratified analyses suggested a potential protective effect of iron levels on Parkinson's disease risk in females, but not in males. Our results will contribute to a better understanding of the genetic basis underlying iron in cardiovascular and neurological health in aging, and to the eventual identification of new preventive interventions or therapeutic avenues for diseases which affect women and men worldwide., (© 2024. The Author(s).)

Polygenic variation unrelated to disease contributes to interindividual variation in baseline white blood cell (WBC) counts, but its clinical significance is uncharacterized. We investigated the clinical consequences of a genetic predisposition toward lower WBC counts among 89,559 biobank participants from tertiary care centers using a polygenic score for WBC count (PGS WBC ) comprising single nucleotide polymorphisms not associated with disease. A predisposition to lower WBC counts was associated with a decreased risk of identifying pathology on a bone marrow biopsy performed for a low WBC count (odds-ratio = 0.55 per standard deviation increase in PGS WBC [95%CI, 0.30-0.94], p = 0.04), an increased risk of leukopenia (a low WBC count) when treated with a chemotherapeutic (n = 1724, hazard ratio [HR] = 0.78 [0.69-0.88], p = 4.0 × 10 -5 ) or immunosuppressant (n = 354, HR = 0.61 [0.38-0.99], p = 0.04). A predisposition to benign lower WBC counts was associated with an increased risk of discontinuing azathioprine treatment (n = 1,466, HR = 0.62 [0.44-0.87], p = 0.006). Collectively, these findings suggest that there are genetically predisposed individuals who are susceptible to escalations or alterations in clinical care that may be harmful or of little benefit., (© 2024. The Author(s).)

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes 1,2 and molecular mechanisms that are often specific to cell type 3,4 . Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10 -8 ) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores 5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care., (© 2024. The Author(s).)

Using pharmacogenetics (PGx) to inform clinical decision making can benefit patients but clinical use of PGx testing has been limited. Existing genetics data obtained in the course of research could be used to identify patients who are suspected, but have not yet been confirmed, to carry clinically actionable genotypes, in whom confirmatory genetic testing could be conducted for highly efficient PGx implementation. Herein, we demonstrate that it is regulatorily and technically feasible to implement PGx by identifying suspected carriers of actionable genotypes within an institutional genetics data repository and conduct confirmatory PGx testing immediately prior to that patient receiving the PGx-relevant drug, using a case study of DPYD testing prior to fluoropyrimidine chemotherapy. In 2 years since launching this program, ~ 3,000 suspected DPYD carriers have been passively monitored and one confirmed DPYD carrier was prevented from receiving unacceptably toxic fluoropyrimidine treatment, for minimal cost and effort. Now that we have demonstrated the feasibility of this strategy, we plan to transition to PGx panel testing and expand implementation to other genes and drugs for which the evidence of clinical benefit of PGx-informed treatment is high but PGx testing is not generally conducted. This highly efficient implementation process will maximize the clinical benefits of testing and could be explored at other institutions that have research-only genetic data repositories to expand the number of patients who benefit from PGx-informed treatment while we continue to work toward wide-scale adoption of PGx testing and implementation., (© 2023 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Biobanks of linked clinical patient histories and biological samples are an efficient strategy to generate large cohorts for modern genetics research. Biobank recruitment varies by factors such as geographic catchment and sampling strategy, which affect biobank demographics and research utility. Here, we describe the Michigan Genomics Initiative (MGI), a single-health-system biobank currently consisting of >91,000 participants recruited primarily during surgical encounters at Michigan Medicine. The surgical enrollment results in a biobank enriched for many diseases and ideally suited for a disease genetics cohort. Compared with the much larger population-based UK Biobank, MGI has higher prevalence for nearly all diagnosis-code-based phenotypes and larger absolute case counts for many phenotypes. Genome-wide association study (GWAS) results replicate known findings, thereby validating the genetic and clinical data. Our results illustrate that opportunistic biobank sampling within single health systems provides a unique and complementary resource for exploring the genetics of complex diseases., Competing Interests: G.R.A. and A.P. work for Regeneron Pharmaceuticals. C.J.W. took a position at Regeneron Pharmaceuticals after the initial submission of this manuscript., (© 2023 The Authors.)

Background: Inflammatory bowel disease is associated with an increased risk of skin cancer. The aims of this study were to determine whether IBD susceptibility variants are also associated with skin cancer susceptibility and if such risk is augmented by use of immune-suppressive therapy., Methods: The discovery cohort included participants in the UK Biobank. The validation cohort included participants in the Michigan Genomics Initiative. The primary outcome of interest was skin cancer, subgrouped into nonmelanoma skin cancers (NMSC) and melanoma skin cancers (MSC). Multivariable logistic regression with matched controls (3 controls:1 case) was performed to identify genomic predictors of skin malignancy in the discovery cohort. Variants with P < .05 were tested for replication in the validation cohort. Validated Single nucleotide polymorphisms were then evaluated for effect modification by immune-suppressive medications., Results: The discovery cohort included 10,247 cases of NMSC and 1883 cases of MSC. The validation cohort included 7334 cases of NMSC and 3304 cases of MSC. Twenty-nine variants were associated with risk of NMSC in the discovery cohort, of which 5 replicated in the validation cohort (increased risk, rs7773324-A [DUSP22; IRF4], rs2476601-G [PTPN22], rs1847472-C [BACH2], rs72810983-A [CPEB4]; decreased risk, rs6088765-G [PROCR; MMP24]). Twelve variants were associated with risk of MSC in the discovery cohort, of which 4 were replicated in the validation cohort (increased risk, rs61839660-T [IL2RA]; decreased risk, rs17391694-C [GIPC2; MGC27382], rs6088765-G [PROCR; MMP24], and rs1728785-C [ZFP90]). No effect modification was observed., Conclusions: The results of this study highlight shared genetic susceptibility across IBD and skin cancer, with increased risk of NMSC in those who carry risk variants in IRF4, PTPN22, CPEB4, and BACH2 and increased risk of MSC in those who carry a risk variant in IL2RA., (© The Author(s) 2022. Published by Oxford University Press on behalf of Crohn’s & Colitis Foundation. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)-a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits., Competing Interests: M.J.D. is a founder of Maze Therapeutics. B.M.N. is a member of the scientific advisory board at Deep Genomics and a consultant for Camp4 Therapeutics, Takeda Pharmaceutical, and Biogen. The spouse of C.J.W. works at Regeneron Pharmaceuticals. C.-Y.C. is employed by Biogen. C.R.G. owns stock in 23andMe, Inc. T.R.G. has received research funding from various pharmaceutical companies to support the application of Mendelian randomization to drug target prioritization. E.E.K. has received speaker fees from Regeneron, Illumina, and 23andMe and is a member of the advisory board for Galateo Bio. R.E.M. has received speaker fees from Illumina and is a scientific advisor to the Epigenetic Clock Development Foundation. G.D.S. has received research funding from various pharmaceutical companies to support the application of Mendelian randomization to drug target prioritization. K.S. and U.T. are employed by deCODE Genetics/Amgen, Inc. J.Z. has received research funding from various pharmaceutical companies to support the application of Mendelian randomization to drug target prioritization. S.M. is a co-founder of and holds stock in Seonix Bio., (© 2022.)

Purpose: Cyclophosphamide is a commonly used cancer agent that is metabolically activated by polymorphic enzymes. This study aims to investigate the association between predicted activity of candidate pharmacogenes with severe toxicity during cyclophosphamide treatment., Methods: Genome-wide genetic data was collected from an institutional genetic data repository for CYP2B6, CYP3A4, CYP2C9, CYP2C19, GSTA1, GSTP1, ALDH1A1, ALDH3A1, ABCC1, ABCB1, and ERCC1. Treatment and toxicity data were retrospectively collected from the patient's medical record. The a priori selected primary hypothesis was that patients who have CYP2B6 reduced metabolizer activity (poor or intermediate (PM/IM) vs. normal (NM) metabolizer) have lower risk of severe toxicity or cyclophosphamide treatment modification due to toxicity., Results: In the primary analysis of 510 cyclophosphamide-treated patients with available genetic data, there was no difference in the odds of severe toxicity or treatment modification due to toxicity in CYP2B6 PM/IM vs. NM (odds ratio = 0.97, 95% Confidence Interval: 0.62-1.50, p = 0.88). In an exploratory, statistically uncorrected secondary analysis, carriers of the ALDH1A1 rs8187996 variant had a lower risk of the primary toxicity endpoint compared with wild-type homozygous patients (odds ratio = 0.31, 95% Confidence Interval: 0.09-0.78, p = 0.028). None of the other tested phenotypes or genotypes was associated with the primary or secondary endpoints in unadjusted analysis (all p > 0.05)., Conclusion: The finding that patients who carry ALDH1A1 rs8187996 may have a lower risk of cyclophosphamide toxicity than wild-type patients contradicts a prior finding for this variant and should be viewed with skepticism. We found weak evidence that any of these candidate pharmacogenetic predictors of cyclophosphamide toxicity may be useful to personalize cyclophosphamide dosing to optimize therapeutic outcomes in patients with cancer., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Objective: Haemorrhoidal disease (HEM) affects a large and silently suffering fraction of the population but its aetiology, including suspected genetic predisposition, is poorly understood. We report the first genome-wide association study (GWAS) meta-analysis to identify genetic risk factors for HEM to date., Design: We conducted a GWAS meta-analysis of 218 920 patients with HEM and 725 213 controls of European ancestry. Using GWAS summary statistics, we performed multiple genetic correlation analyses between HEM and other traits as well as calculated HEM polygenic risk scores (PRS) and evaluated their translational potential in independent datasets. Using functional annotation of GWAS results, we identified HEM candidate genes, which differential expression and coexpression in HEM tissues were evaluated employing RNA-seq analyses. The localisation of expressed proteins at selected loci was investigated by immunohistochemistry., Results: We demonstrate modest heritability and genetic correlation of HEM with several other diseases from the GI, neuroaffective and cardiovascular domains. HEM PRS validated in 180 435 individuals from independent datasets allowed the identification of those at risk and correlated with younger age of onset and recurrent surgery. We identified 102 independent HEM risk loci harbouring genes whose expression is enriched in blood vessels and GI tissues, and in pathways associated with smooth muscles, epithelial and endothelial development and morphogenesis. Network transcriptomic analyses highlighted HEM gene coexpression modules that are relevant to the development and integrity of the musculoskeletal and epidermal systems, and the organisation of the extracellular matrix., Conclusion: HEM has a genetic component that predisposes to smooth muscle, epithelial and connective tissue dysfunction., Competing Interests: Competing interests: Vladimir Vacic and Olga V. Sazonova are/were employed by and hold stock or stock options in 23andMe, Inc. All other authors have nothing to declare., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Genotype imputation is an indispensable step in human genetic studies. Large reference panels with deeply sequenced genomes now allow interrogating variants with minor allele frequency < 1% without sequencing. Although it is critical to consider limits of this approach, imputation methods for rare variants have only done so empirically; the theoretical basis of their imputation accuracy has not been explored. To provide theoretical consideration of imputation accuracy under the current imputation framework, we develop a coalescent model of imputing rare variants, leveraging the joint genealogy of the sample to be imputed and reference individuals. We show that broadly used imputation algorithms include model misspecifications about this joint genealogy that limit the ability to correctly impute rare variants. We develop closed-form solutions for the probability distribution of this joint genealogy and quantify the inevitable error rate resulting from the model misspecification across a range of allele frequencies and reference sample sizes. We show that the probability of a falsely imputed minor allele decreases with reference sample size, but the proportion of falsely imputed minor alleles mostly depends on the allele count in the reference sample. We summarize the impact of this error on genotype imputation on association tests by calculating the r2 between imputed and true genotype and show that even when modeling other sources of error, the impact of the model misspecification has a significant impact on the r2 of rare variants. To evaluate these predictions in practice, we compare the imputation of the same dataset across imputation panels of different sizes. Although this empirical imputation accuracy is substantially lower than our theoretical prediction, modeling misspecification seems to further decrease imputation accuracy for variants with low allele counts in the reference. These results provide a framework for developing new imputation algorithms and for interpreting rare variant association analyses., (© The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America. All rights reserved. For permissions, please email: journals.permissions@oup.com.)