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LoFTK: a framework for fully automated calculation of predicted Loss-of-Function variants and genes
Alasiri, Abdulrahman; Karczewski, Konrad J; Cole, Brian; Loza, Bao-Li; Moore, Jason H; van der Laan, Sander W; Asselbergs, Folkert W; Keating, Brendan J; van Setten, Jessica
BACKGROUND:Loss-of-Function (LoF) variants in human genes are important due to their impact on clinical phenotypes and frequent occurrence in the genomes of healthy individuals. The association of LoF variants with complex diseases and traits may lead to the discovery and validation of novel therapeutic targets. Current approaches predict high-confidence LoF variants without identifying the specific genes or the number of copies they affect. Moreover, there is a lack of methods for detecting knockout genes caused by compound heterozygous (CH) LoF variants. RESULTS:We have developed the Loss-of-Function ToolKit (LoFTK), which allows efficient and automated prediction of LoF variants from genotyped, imputed and sequenced genomes. LoFTK enables the identification of genes that are inactive in one or two copies and provides summary statistics for downstream analyses. LoFTK can identify CH LoF variants, which result in LoF genes with two copies lost. Using data from parents and offspring we show that 96% of CH LoF genes predicted by LoFTK in the offspring have the respective alleles donated by each parent. CONCLUSIONS:LoFTK is a command-line based tool that provides a reliable computational workflow for predicting LoF variants from genotyped and sequenced genomes, identifying genes that are inactive in 1 or 2 copies. LoFTK is an open software and is freely available to non-commercial users at https://github.com/CirculatoryHealth/LoFTK .
PMCID:9893534
PMID: 36732776
ISSN: 1756-0381
CID: 5478962
Genome-wide copy number variant screening of Saudi schizophrenia patients reveals larger deletions in cases versus controls
Abumadini, Mahdi S; Al Ghamdi, Kholoud S; Alqahtani, Abdullah H; Almedallah, Dana K; Callans, Lauren; Jarad, Jumanah A; Cyrus, Cyril; Koeleman, Bobby P C; Keating, Brendan J; Pankratz, Nathan; Al-Ali, Amein K
INTRODUCTION/UNASSIGNED:Genome-wide association studies have discovered common polymorphisms in regions associated with schizophrenia. No genome-wide analyses have been performed in Saudi schizophrenia subjects. METHODS/UNASSIGNED:Genome-wide genotyping data from 136 Saudi schizophrenia cases and 97 Saudi controls in addition to 4,625 American were examined for copy number variants (CNVs). A hidden Markov model approach was used to call CNVs. RESULTS/UNASSIGNED: = 0.04). The analyses focused on extremely large >250 kilobases CNVs or homozygous deletions of any size. One extremely large deletion was noted in a single case (16.5 megabases on chromosome 10). Two cases had an 814 kb duplication of chromosome 7 spanning a cluster of genes, including circadian-related loci, and two other cases had 277 kb deletions of chromosome 9 encompassing an olfactory receptors gene family. CNVs were also seen in loci previously associated with schizophrenia, namely a 16p11 proximal duplication and two 22q11.2 deletions. DISCUSSION/UNASSIGNED:Runs of homozygosity (ROHs) were analyzed across the genome to investigate correlation with schizophrenia risk. While rates and sizes of these ROHs were similar in cases and controls, we identified 10 regions where multiple cases had ROHs and controls did not.
PMCID:9950097
PMID: 36846569
ISSN: 1662-5099
CID: 5478972
GENOME-WIDE ASSOCIATION META-ANALYSIS IDENTIFIES NOVEL LOCI FOR KIDNEY FAILURE [Meeting Abstract]
van der Most, Peter; Wang, Siqi; Guan, Weihua; Schladt, David; Loza, Bao-Li; Stapleton, Caragh; Heinzel, Andreas; Israni, Ajay; Jacobson, Pamala; Keating, Brendan; Conlon, Peter; Oberbauer, Rainer; Snieder, Harold; De Borst, Martin
ISI:000813350704092
ISSN: 0931-0509
CID: 5479232
Donor and recipient polygenic risk scores influence the risk of post-transplant diabetes
Shaked, Abraham; Loza, Bao-Li; Van Loon, Elisabet; Olthoff, Kim M; Guan, Weihua; Jacobson, Pamala A; Zhu, Andrew; Fishman, Claire E; Gao, Hui; Oetting, William S; Israni, Ajay K; Testa, Giuliano; Trotter, James; Klintmalm, Goran; Naesens, Maarten; Asrani, Sumeet K; Keating, Brendan J
Post-transplant diabetes mellitus (PTDM) reduces allograft and recipient life span. Polygenic risk scores (PRSs) show robust association with greater risk of developing type 2 diabetes (T2D). We examined the association of PTDM with T2D PRS in liver recipients (n = 1,581) and their donors (n = 1,555), and kidney recipients (n = 2,062) and their donors (n = 533). Recipient T2D PRS was associated with pre-transplant T2D and the development of PTDM. T2D PRS in liver donors, but not in kidney donors, was an independent risk factor for PTDM development. The inclusion of a combined liver donor and recipient T2D PRS significantly improved PTDM prediction compared with a model that included only clinical characteristics: the area under the curve (AUC) was 67.6% (95% confidence interval (CI) 64.1-71.1%) for the combined T2D PRS versus 62.3% (95% CI 58.8-65.8%) for the clinical characteristics model (P = 0.0001). Liver recipients in the highest quintile of combined donor and recipient T2D PRS had the greatest risk of PTDM, with an odds ratio of 3.22 (95% CI 2.07-5.00) (P = 1.92 × 10-7) compared with those in the lowest quintile. In conclusion, T2D PRS identifies transplant candidates with high risk of PTDM for which pre-emptive diabetes management and donor selection may be warranted.
PMID: 35393535
ISSN: 1546-170x
CID: 5478912
Whole transcriptome profiling of prospective endomyocardial biopsies reveals prognostic and diagnostic signatures of cardiac allograft rejection
Piening, Brian D; Dowdell, Alexa K; Zhang, Mengqi; Loza, Bao-Li; Walls, David; Gao, Hui; Mohebnasab, Maede; Li, Yun Rose; Elftmann, Eric; Wei, Eric; Gandla, Divya; Lad, Hetal; Chaib, Hassan; Sweitzer, Nancy K; Deng, Mario; Pereira, Alexandre C; Cadeiras, Martin; Shaked, Abraham; Snyder, Michael P; Keating, Brendan J
BACKGROUND:Heart transplantation provides a significant improvement in survival and quality of life for patients with end-stage heart disease, however many recipients experience different levels of graft rejection that can be associated with significant morbidities and mortality. Current clinical standard-of-care for the evaluation of heart transplant acute rejection (AR) consists of routine endomyocardial biopsy (EMB) followed by visual assessment by histopathology for immune infiltration and cardiomyocyte damage. We assessed whether the sensitivity and/or specificity of this process could be improved upon by adding RNA sequencing (RNA-seq) of EMBs coupled with histopathological interpretation. METHODS:Up to 6 standard-of-care, or for-cause EMBs, were collected from 26 heart transplant recipients from the prospective observational Clinical Trials of Transplantation (CTOT)-03 study, during the first 12-months post-transplant and subjected to RNA-seq (n = 125 EMBs total). Differential expression and random-forest-based machine learning were applied to develop signatures for classification and prognostication. RESULTS:Leveraging the unique longitudinal nature of this study, we show that transcriptional hallmarks for significant rejection events occur months before the actual event and are not visible using traditional histopathology. Using this information, we identified a prognostic signature for 0R/1R biopsies that with 90% accuracy can predict whether the next biopsy will be 2R/3R. CONCLUSIONS:RNA-seq-based molecular characterization of EMBs shows significant promise for the early detection of cardiac allograft rejection.
PMCID:9133065
PMID: 35317953
ISSN: 1557-3117
CID: 5478902
LoFTK: a framework for efficient and automated prediction of loss-of-function variants [Meeting Abstract]
Alasiri, Abdulrahman; Karczewsk, Konrad J.; Cole, Brian; Loza, Bao-Li; van der Laan, Sander W.; Asselbergs, Folkert W.; Keating, Brendan James; van Setten, Jessica
ISI:000779367702281
ISSN: 1018-4813
CID: 5479222
Cytokine Analysis of First Gal-KO Renal Xenotransplantation From a Pig-To-Human Recipient [Meeting Abstract]
Stern, Jeffrey; Lonze, Bonnie E.; Stewart, Zoe A.; Mangiola, Massimo; Tatapudi, Vasishta; Zhang, Weimin; Camellato, Brendan; Xia, Bo; Boeke, Jef; Pass, Harvey; Weldon, Elaina; Lawson, Nikki; Griesemer, Adam; Keating, Brendan; Montgomery, Robert A.
ISI:000889117001034
ISSN: 0041-1337
CID: 5479262
GERMLINE SUSCEPTIBILITY TO HEPATOCELLULAR CARCINOMA AMONG PATIENTS WITH CIRRHOSIS: A GENOME-WIDE ASSOCIATION STUDY [Meeting Abstract]
Kaplan, David E.; Vujkovic, Marijana; Dochtermann, Daniel; Chang, Bao-Li; Hoteit, Maarouf A.; Wangensteen, Kirk; Keating, Brendan; Shaked, Abraham; Olthoff, Kim M.; Asrani, Sumeet K.; Testa, Giuliano; Trotter, James F.; Klintmalm, Goran B.; Devineni, Poornima; Schwantes-An, Tae-Hwi; Sendamarai, Anoop; Karnam, Purushotham; Sileo, Emily; Anglin, Tori; Norden-Krichmar, Trina; Lewis, Adam; Bastarache, Lisa; Schneider, Carolin Victoria; Tsao, Philip; Morgan, Timothy R.; Pyarajan, Saiju; Lynch, Julie A.; Voight, Benjamin F.; Chang, Kyong-Mi
ISI:000870796600208
ISSN: 0270-9139
CID: 5479252
Testing the application of polygenic risk scores in the transplant setting - Relevance for precision medicine [Comment]
Shaked, Abraham; Loza, Bao-Li; Olthoff, Kim; Keating, Brendan
PMID: 35968930
ISSN: 2001-1326
CID: 5478922
Impact of CYP3A5 Status on the Clinical and Financial Outcomes Among African American Kidney Transplant Recipients
Obayemi, Joy; Keating, Brendan; Callans, Lauren; Lentine, Krista L; Schnitzler, Mark A; Caliskan, Yasar; Xiao, Huiling; Dharnidharka, Vikas R; Mannon, Roslyn B; Axelrod, David A
UNLABELLED:genotype on clinical outcomes and financial expenditure. METHODS/UNASSIGNED:). Individuals were categorized as rapid metabolism phenotype without LoF alleles' intermediate phenotype for 1 LoF allele' and slow phenotype for 2 LoF alleles. KTx outcomes (patient/kidney survival and Medicare spending) were determined using linked transplant registry and claims data. RESULTS/UNASSIGNED: = 0.003). CONCLUSIONS/UNASSIGNED:functional variants appear to be associated with differential outcome and spending after transplant.
PMCID:9529042
PMID: 36204191
ISSN: 2373-8731
CID: 5478932