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In 1948, Claude Shannon published a mathematical system describing the probabilistic relationships between the letters of a natural language and their subsequent order or syntax structure. By counting unique, reoccurring sequences of letters called N-grams, this language model was used to generate recognizable English sentences from N-gram frequency probability tables. More recently, N-gram analysis methodologies have been successfully applied to address many complex problems in a variety of domains, from language processing to genomics. One such example is the common use of N-gram frequency patterns and supervised classification models to determine authorship and plagiarism. In this paradigm, DNA is a language model where nucleotides are analogous to the letters of a word and nucleotide N-grams are analogous to the words of a sentence. Because DNA contains highly conserved and identifiable nucleotide sequence frequency patterns, this approach can be applied to a variety of classification and data reduction problems, such as identifying species based on unknown DNA segments. Other useful applications of this methodology include the identification of functional gene elements, microorganisms, sequence contamination, and sequencing artifacts. To this end, I present DNAnamer, a generalized and extensible methodological framework and analysis toolkit for the supervised classification of DNA sequences based on their N-gram frequency patterns., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: John Stephen Malamon reports administrative support was provided by 10.13039/100014450University of Colorado Anschutz Medical Campus School of Medicine. John Stephen Malamon reports a relationship with University of Colorado Anschutz Medical Campus School of Medicine that includes: employment. John Stephen Malamon has patent pending to N/A. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author. Published by Elsevier Ltd.)

Detecting structural variants (SVs) in whole-genome sequencing poses significant challenges. We present a protocol for variant calling, merging, genotyping, sensitivity analysis, and laboratory validation for generating a high-quality SV call set in whole-genome sequencing from the Alzheimer's Disease Sequencing Project comprising 578 individuals from 111 families. Employing two complementary pipelines, Scalpel and Parliament, for SV/indel calling, we assessed sensitivity through sample replicates (N = 9) with in silico variant spike-ins. We developed a novel metric, D-score, to evaluate caller specificity for deletions. The accuracy of deletions was evaluated by Sanger sequencing. We generated a high-quality call set of 152,301 deletions of diverse sizes. Sanger sequencing validated 114 of 146 detected deletions (78.1%). Scalpel excelled in accuracy for deletions ≤100 bp, whereas Parliament was optimal for deletions >900 bp. Overall, 83.0% and 72.5% of calls by Scalpel and Parliament were validated, respectively, including all 11 deletions called by both Parliament and Scalpel between 101 and 900 bp. Our flexible protocol successfully generated a high-quality deletion call set and a truth set of Sanger sequencing-validated deletions with precise breakpoints spanning 1-17,000 bp., (© 2024 Malamon et al.)

Background: The cytomegalovirus (CMV) mismatch rate in deceased donor kidney transplant (DDKT) recipients in the US remains above 40%. Since CMV mismatching is common in DDKT recipients, the cumulative effects may be significant in the context of overall patient and graft survival. Our primary objective was to describe the short- and long-term risks associated with high-risk CMV donor positive/recipient negative (D+/R-) mismatching among DDKT recipients with the explicit goal of deriving a mathematical mismatching penalty., Methods: We conducted a retrospective, secondary analysis of the Scientific Registry of Transplant Recipients (SRTR) database using donor-matched DDKT recipient pairs (N=105,608) transplanted between 2011-2022. All-cause mortality and graft failure hazard ratios were calculated from one year to ten years post-DDKT. All-cause graft failure included death events. Survival curves were calculated using the Kaplan-Meier estimation at 10 years post-DDKT and extrapolated to 20 years to provide the average graft days lost (aGDL) and average patient days lost (aPDL) due to CMV D+/R- serostatus mismatching. We also performed an age-based stratification analysis to compare the relative risk of CMV D+ mismatching by age., Results: Among 31,518 CMV D+/R- recipients, at 1 year post-DDKT, the relative risk of death increased by 29% (p<0.001), and graft failure increased by 17% (p<0.001) as compared to matched CMV D+/R+ group (N=31,518). Age stratification demonstrated a significant increase in the risk associated with CMV mismatching in patients 40 years of age and greater. The aGDL per patient due to mismatching was 125 days and the aPDL per patient was 100 days., Conclusion: The risks of CMV D+/R- mismatching are seen both at 1 year post-DDKT period and accumulated throughout the lifespan of the patient, with the average CMV D+/R- recipient losing more than three months of post-DDKT survival time. CMV D+/R- mismatching poses a more significant risk and a greater health burden than previously reported, thus obviating the need for better preventive strategies including CMV serodirected organ allocation to prolong lifespans and graft survival in high-risk patients., Competing Interests: MA was employed by Merck Corporation. KE was employed by Gilead Sciences, Merck Corporation, and ViiV HealthCare Limited. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Abidi, Schold, Kaplan, Weinberg, Erlandson and Malamon.)

Introduction: Currently in the United States, deceased donor liver transplant (DDLT) allocation priority is based on the model for end-stage liver disease including sodium (MELD-Na) score. The United Network for organ sharing's 'Share-15' policy states that candidates with MELD-Na scores of 15 or greater have priority to receive local organ offers compared to candidates with lower MELD-Na scores. Since the inception of this policy, major changes in the primary etiologies of end-stage liver disease have occurred and previous assumptions need to be recalibrated., Methods: The authors retrospectively analyzed the Scientific Registry of Transplant Recipients database between 2012 and 2021 to determine life years saved by DDLT at each interval of MELD-Na score and the time-to-equal risk and time-to-equal survival versus remaining on the waitlist. The authors stratified our analysis by MELD exception points, primary disease etiology, and MELD score., Results: On aggregate, compared to remaining on the waitlist, a significant 1-year survival advantage of DDLT at MELD-Na scores as low as 12 was found. The median life years saved at this score after a liver transplant was estimated to be greater than 9 years. While the total life years saved were comparable across all MELD-Na scores, the time-to-equal risk and time-to-equal survival decreased exponentially as MELD-Na scores increased., Conclusion: Herein, the authors challenge the perception as to the timing of DDLT and when that benefit occurs. The national liver allocation policy is transitioning to a continuous distribution framework and these data will be instrumental to defining the attributes of the continuos allocation score., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)

On July 14, 2022, the Organ Procurement and Transplantation Network's (OPTN) Membership and Professional Standards Committee (MPSC) approved bylaws including two new post-transplant performance evaluation metrics, the 90-day (90D) and 1-year conditional on the 90-day (1YC90D) graft survival hazard ratio (HR). These metrics have replaced the previous 1-year (1Y) unconditional, post-transplant graft survival HR and are used to nationally rank and identify programs for MPSC review. The MPSC's policies have major implications for all transplant programs, providers, and patients across the United States. Herein we show two significant limitations with the new evaluation criteria, arbitrary censoring periods and interdependence in the new performance metrics. We have demonstrated a strong and consistent inverse correlation between the new evaluation metrics, thus proving a lack of independence. Moreover, these two evaluation criteria are interdependent even at nominal HRs. Thus, the 90D cohort can be used to accurately predict whether the 1YC90D is above or below a given HR threshold. This could alter practice behaviors and the timing of patient event reporting, which may result in many unintended consequences related to clinical practice. Here we provide the first evidence that this new evaluation system will lead to a significant increase in the number of programs flagged for MPSC review. When this occurs, the cost of operating a transplant program will increase without a clear demonstration of an increased accuracy in identifying problematic programs., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Malamon, Ho, Jackson, Saben, Schold, Pomposelli, Pomfret and Kaplan.)

Background: The estimated long-term survival (EPTS) score is used for kidney allocation. A comparable prognostic tool to accurately quantify EPTS benefit in deceased donor liver transplant (DDLT) candidates is nonexistent., Methods: Using the Scientific Registry of Transplant Recipients (SRTR) database, we developed, calibrated, and validated a nonlinear regression equation to calculate liver-EPTS (L-EPTS) for 5- and 10-year outcomes in adult DDLT recipients. The population was randomly split (70:30) into two discovery (N = 26,372 and N = 46,329) and validation cohorts (N = 11,288 and N = 19,859) for 5- and 10-year post-transplant outcomes, respectively. Discovery cohorts were used for variable selection, Cox proportional hazard regression modeling, and nonlinear curve fitting. Eight clinical variables were selected to construct the L-EPTS formula, and a five-tiered ranking system was created., Findings: Tier thresholds were defined and the L-EPTS model was calibrated (R 2  = 0.96 [5-year] and 0.99 [10-year]). Patients' median survival probabilities in the discovery cohorts for 5- and 10-year outcomes ranged from 27.94% to 89.22% and 16.27% to 87.97%, respectively. The L-EPTS model was validated via calculation of receiver operating characteristic (ROC) curves using validation cohorts. Area under the ROC curve was 82.4% (5-year) and 86.5% (10-year)., Interpretation: L-EPTS has high applicability and clinical utility because it uses easily obtained pre-transplant patients characteristics to accurately discriminate between those who are likely to receive a prolonged survival benefit and those who are not. It is important to evaluate medical urgency alongside survival benefit and placement efficiency when considering the allocation of a scarce resource., Funding: There are no funding sources related to this project., Competing Interests: Declaration of interests No funding was used to support this work. The authors of this manuscript have no conflicts of interest to disclose as described by eBioMedicine., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Importance: Despite the acceptance of living-donor liver transplant (LDLT) as a lifesaving procedure for end-stage liver disease, it remains underused in the United States. Quantification of lifetime survival benefit and the Model for End-stage Liver Disease incorporating sodium levels (MELD-Na) score range at which benefit outweighs risk in LDLT is necessary to demonstrate its safety and effectiveness., Objective: To assess the survival benefit, life-years saved, and the MELD-Na score at which that survival benefit was obtained for individuals who received an LDLT compared with that for individuals who remained on the wait list., Design, Setting, and Participants: This case-control study was a retrospective, secondary analysis of the Scientific Registry of Transplant Recipients database of 119 275 US liver transplant candidates and recipients from January 1, 2012, to September 2, 2021. Liver transplant candidates aged 18 years or older who were assigned to the wait list (N = 116 455) or received LDLT (N = 2820) were included. Patients listed for retransplant or multiorgan transplant and those with prior kidney or liver transplants were excluded., Exposures: Living-donor liver transplant vs remaining on the wait list., Main Outcomes and Measures: The primary outcome of this study was life-years saved from receiving an LDLT. Secondary outcomes included 1-year relative mortality and risk, time to equal risk, time to equal survival, and the MELD-Na score at which that survival benefit was obtained for individuals who received an LDLT compared with that for individuals who remained on the wait list. MELD-Na score ranges from 6 to 40 and is well correlated with short-term survival. Higher MELD-Na scores (>20) are associated with an increased risk of death., Results: The mean (SD) age of the 119 275 study participants was 55.1 (11.2) years, 63% were male, 0.9% were American Indian or Alaska Native, 4.3% were Asian, 8.2% were Black or African American, 15.8% were Hispanic or Latino, 0.2% were Native Hawaiian or Other Pacific Islander, and 70.2% were White. Mortality risk and survival models confirmed a significant survival benefit for patients receiving an LDLT who had a MELD-Na score of 11 or higher (adjusted hazard ratio, 0.64 [95% CI, 0.47-0.88]; P = .006). Living-donor liver transplant recipients gained an additional 13 to 17 life-years compared with patients who never received an LDLT., Conclusions and Relevance: An LDLT is associated with a substantial survival benefit to patients with end-stage liver disease even at MELD-Na scores as low as 11. The findings of this study suggest that the life-years gained are comparable to or greater than those conferred by any other lifesaving procedure or by a deceased-donor liver transplant. This study's findings challenge current perceptions regarding when LDLT survival benefit occurs.

We have applied a novel and integrative analysis framework for next-generation sequencing (NGS) data to 503 human subjects provided by the Religious Orders Study and Memory and Aging Project (ROSMAP) to examine changes in transcriptomic organization and common variants in association with late-onset Alzheimer's disease (LOAD). Our framework identified seven reproducible, co-regulated modules after quality control (QC), clinical segregation, preservation filtering, and functional ontology analysis. These modules were specifically enriched in several innate and adaptive immune system processes, the synaptic vesicle cycle, and Hippo signaling. Topological and functional erosion of these modules due to shedding of genes and loss of in-module connectivity was diagnostic of disease progression. Perturbation analysis revealed that only 1% of eQTLs overlapped genes participating in these co-regulated modules. Common variants nevertheless identified components of the immune systems like human leukocyte antigen (HLA) complex and microtubule-associated protein tau (MAPT) regions in association with LOAD. Our results implicate microglial function, adaptive immune response, and the structural degeneration of neurons as contributors to the transcriptional deregulation observed along with common genetic variants in the progression of LOAD., (Copyright © 2020 Malamon and Kriete.)

Late-onset Alzheimer's disease (LOAD) and age are significantly correlated such that one-third of Americans beyond 85 years of age are afflicted. We have designed and implemented a pilot study that combines systems biology approaches with traditional next-generation sequencing (NGS) analysis techniques to identify relevant regulatory pathways, infer functional relationships and confirm the dysregulation of these biological pathways in LOAD. Our study design is a most comprehensive systems approach combining co-expression network modeling derived from RNA-seq data, rigorous quality control (QC) standards, functional ontology, and expression quantitative trait loci (eQTL) derived from whole exome (WES) single nucleotide variant (SNV) genotype data. Our initial results reveal several statistically significant, biologically relevant genes involved in sphingolipid metabolism. To validate these findings, we performed a gene set enrichment analysis (GSEA). The GSEA revealed the sphingolipid metabolism pathway and regulation of autophagy in association with LOAD cases. In the execution of this study, we have successfully tested an integrative approach to identify both novel and known LOAD drivers in order to develop a broader and more detailed picture of the highly complex transcriptional and regulatory landscape of age-related dementia., Competing Interests: The authors declare no conflict of interest.